Irrigation Requirement Estimation Using Vegetation Indices and Inverse Biophysical Modeling
Bounoua, Lahouari; Imhoff, Marc L.; Franks, Shannon
2010-01-01
We explore an inverse biophysical modeling process forced by satellite and climatological data to quantify irrigation requirements in semi-arid agricultural areas. We constrain the carbon and water cycles modeled under both equilibrium, balance between vegetation and climate, and non-equilibrium, water added through irrigation. We postulate that the degree to which irrigated dry lands vary from equilibrium climate conditions is related to the amount of irrigation. The amount of water required over and above precipitation is considered as an irrigation requirement. For July, results show that spray irrigation resulted in an additional amount of water of 1.3 mm per occurrence with a frequency of 24.6 hours. In contrast, the drip irrigation required only 0.6 mm every 45.6 hours or 46% of that simulated by the spray irrigation. The modeled estimates account for 87% of the total reported irrigation water use, when soil salinity is not important and 66% in saline lands.
Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah
2007-01-01
An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.
Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah
2007-01-01
An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.
Verrelst, J.; Rivera, J. P.; Leonenko, G.; Alonso, L.; Moreno, J.
2012-04-01
Radiative transfer (RT) modeling plays a key role for earth observation (EO) because it is needed to design EO instruments and to develop and test inversion algorithms. The inversion of a RT model is considered as a successful approach for the retrieval of biophysical parameters because of being physically-based and generally applicable. However, to the broader community this approach is considered as laborious because of its many processing steps and expert knowledge is required to realize precise model parameterization. We have recently developed a radiative transfer toolbox ARTMO (Automated Radiative Transfer Models Operator) with the purpose of providing in a graphical user interface (GUI) essential models and tools required for terrestrial EO applications such as model inversion. In short, the toolbox allows the user: i) to choose between various plant leaf and canopy RT models (e.g. models from the PROSPECT and SAIL family, FLIGHT), ii) to choose between spectral band settings of various air- and space-borne sensors or defining own sensor settings, iii) to simulate a massive amount of spectra based on a look up table (LUT) approach and storing it in a relational database, iv) to plot spectra of multiple models and compare them with measured spectra, and finally, v) to run model inversion against optical imagery given several cost options and accuracy estimates. In this work ARTMO was used to tackle some well-known problems related to model inversion. According to Hadamard conditions, mathematical models of physical phenomena are mathematically invertible if the solution of the inverse problem to be solved exists, is unique and depends continuously on data. This assumption is not always met because of the large number of unknowns and different strategies have been proposed to overcome this problem. Several of these strategies have been implemented in ARTMO and were here analyzed to optimize the inversion performance. Data came from the SPARC-2003 dataset
Bounoua, L.; Imhoff, M.L.; Franks, S.
2008-01-01
Human demand for food influences the water cycle through diversion and extraction of fresh water needed to support agriculture. Future population growth and economic development alone will substantially increase water demand and much of it for agricultural uses. For many semi-arid lands, socio-economic shifts are likely to exacerbate changes in climate as a driver of future water supply and demand. For these areas in particular, where the balance between water supply and demand is fragile, variations in regional climate can have potentially predictable effect on agricultural production. Satellite data and biophysically-based models provide a powerful method to quantify the interactions between local climate, plant growth and water resource requirements. In irrigated agricultural lands, satellite observations indicate high vegetation density while the precipitation amount indicates otherwise. This inconsistency between the observed precipitation and the observed canopy leaf density triggers the possibility that the observed high leaf density is due to an alternate source of water, irrigation. We explore an inverse process approach using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), climatological data, and the NASA's Simple Biosphere model, SiB2, to quantitatively assess water demand in a semi-arid agricultural land by constraining the carbon and water cycles modeled under both equilibrium (balance between vegetation and prevailing local climate) and nonequilibrium (water added through irrigation) conditions. We postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. We added water using two distribution methods: The first method adds water on top of the canopy and is a proxy for the traditional spray irrigation. The second method allows water to be applied directly into the soil layer and serves as proxy for drip irrigation. Our approach indicates that over
Stochastic biophysical modeling of irradiated cells
Fornalski, Krzysztof Wojciech
2014-01-01
The paper presents a computational stochastic model of virtual cells irradiation, based on Quasi-Markov Chain Monte Carlo method and using biophysical input. The model is based on a stochastic tree of probabilities for each cell of the entire colony. Biophysics of the cells is described by probabilities and probability distributions provided as the input. The adaptation of nucleation and catastrophe theories, well known in physics, yields sigmoidal relationships for carcinogenic risk as a function of the irradiation. Adaptive response and bystander effect, incorporated into the model, improves its application. The results show that behavior of virtual cells can be successfully modeled, e.g. cancer transformation, creation of mutations, radioadaptation or radiotherapy. The used methodology makes the model universal and practical for simulations of general processes. Potential biophysical curves and relationships are also widely discussed in the paper. However, the presented theoretical model does not describe ...
Global energy modeling - A biophysical approach
Energy Technology Data Exchange (ETDEWEB)
Dale, Michael
2010-09-15
This paper contrasts the standard economic approach to energy modelling with energy models using a biophysical approach. Neither of these approaches includes changing energy-returns-on-investment (EROI) due to declining resource quality or the capital intensive nature of renewable energy sources. Both of these factors will become increasingly important in the future. An extension to the biophysical approach is outlined which encompasses a dynamic EROI function that explicitly incorporates technological learning. The model is used to explore several scenarios of long-term future energy supply especially concerning the global transition to renewable energy sources in the quest for a sustainable energy system.
Glaser, Roland
1999-01-01
The message of this book is that biophysics is the science of physical principles underlying the "phenomenon life" on all levels of organization. Rather than teaching "physics for biologists" or "physical methods applied to biology", it regards its subject as a defined discipline with its own network of ideas and approaches. The book starts by explaining molecular structures of biological systems, various kinds of atomic, molecular and ionic interactions, movements, energy transfer, self organization of supramolecular structures and dynamic properties of biological membranes. It then goes on to introduce the biological organism as a non-equilibrium system, before treating thermodynamic concepts of osmotic and electrolyte equilibria as well as currents and potential profiles. It continues with topics of environmental biophysics and such medical aspects as the influence of electromagnetic fields or radiation on living systems and the biophysics of hearing and noice protection. The book concludes with a discussi...
DEFF Research Database (Denmark)
Houborg, Rasmus Møller; Søgaard, Henrik; Bøgh, Eva
2007-01-01
change. The present study explores the benefits of combining vegetation index and physically based approaches for the spatial and temporal mapping of green leaf area index (LAI), total chlorophyll content (TCab), and total vegetation water content (VWC). A numerical optimization method was employed...... and computationally efficient VI approach makes the combined retrieval scheme for LAI, TCab, and VWC suitable for large-scale mapping operations. In order to facilitate application of the canopy reflectance model to heterogeneous forested areas, a simple correction scheme was elaborated, which was found to improve...... constituents without utilizing calibration measurements. Preliminary LAI validation results for the Island of Zealand, Denmark (57°N, 12°E) provided confidence in the approach with root mean square (RMS) deviations between estimates and in-situ measurements of 0.62, 0.46, and 0.63 for barley, wheat...
Biophysically realistic minimal model of dopamine neuron
Oprisan, Sorinel
2008-03-01
We proposed and studied a new biophysically relevant computational model of dopaminergic neurons. Midbrain dopamine neurons are involved in motivation and the control of movement, and have been implicated in various pathologies such as Parkinson's disease, schizophrenia, and drug abuse. The model we developed is a single-compartment Hodgkin-Huxley (HH)-type parallel conductance membrane model. The model captures the essential mechanisms underlying the slow oscillatory potentials and plateau potential oscillations. The main currents involved are: 1) a voltage-dependent fast calcium current, 2) a small conductance potassium current that is modulated by the cytosolic concentration of calcium, and 3) a slow voltage-activated potassium current. We developed multidimensional bifurcation diagrams and extracted the effective domains of sustained oscillations. The model includes a calcium balance due to the fundamental importance of calcium influx as proved by simultaneous electrophysiological and calcium imaging procedure. Although there are significant evidences to suggest a partially electrogenic calcium pump, all previous models considered only elecrtogenic pumps. We investigated the effect of the electrogenic calcium pump on the bifurcation diagram of the model and compared our findings against the experimental results.
Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series
Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik
2016-06-01
Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model
Bio-Physical Ocean Modeling in the Gulf of Mexico
2009-01-01
SS11/G (Rev. 12- efl ] (o) Bio-Physical Ocean Modeling in the Gulf of Mexico Sergio deRada, Robert A. Arnone, Stephanie Anderson Naval Research...for viewing the model results interactively and dynamically in real-time. Initial assessment of the model prediction skill is presented along with...comprehensive picture of the ocean environment. In mutual benefit, the numerical solution gains skill from the assimilation of observational data which are
Multiscale Modelling and Inverse Problems
Nolen, J; Stuart, A M
2010-01-01
The need to blend observational data and mathematical models arises in many applications and leads naturally to inverse problems. Parameters appearing in the model, such as constitutive tensors, initial conditions, boundary conditions, and forcing can be estimated on the basis of observed data. The resulting inverse problems are often ill-posed and some form of regularization is required. These notes discuss parameter estimation in situations where the unknown parameters vary across multiple scales. We illustrate the main ideas using a simple model for groundwater flow. We will highlight various approaches to regularization for inverse problems, including Tikhonov and Bayesian methods. We illustrate three ideas that arise when considering inverse problems in the multiscale context. The first idea is that the choice of space or set in which to seek the solution to the inverse problem is intimately related to whether a homogenized or full multiscale solution is required. This is a choice of regularization. The ...
Modelling benthic biophysical drivers of ecosystem structure and biogeochemical response
Stephens, Nicholas; Bruggeman, Jorn; Lessin, Gennadi; Allen, Icarus
2016-04-01
The fate of carbon deposited at the sea floor is ultimately decided by biophysical drivers that control the efficiency of remineralisation and timescale of carbon burial in sediments. Specifically, these drivers include bioturbation through ingestion and movement, burrow-flushing and sediment reworking, which enhance vertical particulate transport and solute diffusion. Unfortunately, these processes are rarely satisfactorily resolved in models. To address this, a benthic model that explicitly describes the vertical position of biology (e.g., habitats) and biogeochemical processes is presented that includes biological functionality and biogeochemical response capturing changes in ecosystem structure, benthic-pelagic fluxes and biodiversity on inter-annual timescales. This is demonstrated by the model's ability to reproduce temporal variability in benthic infauna, vertical pore water nutrients and pelagic-benthic solute fluxes compared to in-situ data. A key advance is the replacement of bulk parameterisation of bioturbation by explicit description of the bio-physical processes responsible. This permits direct comparison with observations and determination of key parameters in experiments. Crucially, the model resolves the two-way interaction between sediment biogeochemistry and ecology, allowing exploration of the benthic response to changing environmental conditions, the importance of infaunal functional traits in shaping benthic ecological structure and the feedback the resulting bio-physical processes exert on pore water nutrient profiles. The model is actively being used to understand shelf sea carbon cycling, the response of the benthos to climatic change, food provision and other societal benefits.
Biophysical models of transcription in cells
Choubey, Sandeep
Cells constantly face environmental challenges and deal with them by changing their gene expression patterns. They make decisions regarding which genes to express and which genes not to express based on intra-cellular and environmental cues. These decisions are often made by regulating the process of transcription. While the identities of the different molecules that take part in regulating transcription have been determined for a number of different genes, their dynamics inside the cell are still poorly understood. One key feature of these regulatory dynamics is that the numbers of the bio-molecules involved is typically small, resulting in large temporal fluctuations in transcriptional outputs (mRNA and protein). In this thesis I show that measurements of the cell-to-cell variability of the distribution of transcribing RNA polymerases along a gene provide a previously unexplored method for deciphering the mechanism of its transcription in vivo. First, I propose a simple kinetic model of transcription initiation and elongation from which I calculate transcribing RNA polymerase copy-number fluctuations. I test my theory against published data obtained for yeast genes and propose a novel mechanism of transcription. Rather than transcription being initiated through a single rate-limiting step, as was previously proposed, my single-cell analysis reveals the presence of at least two rate limiting steps. Second, I compute the distribution of inter-polymerase distance distribution along a gene and propose a method for analyzing inter-polymerase distance distributions acquired in experiments. By applying this method to images of polymerases transcribing ribosomal genes in E.coli I show that one model of regulation of these genes is consistent with inter-polymerase distance data while a number of other models are not. The analytical framework described in this thesis can be used to extract quantitative information about the dynamics of transcription from single
Mathematical and computational modelling of skin biophysics: a review
Limbert, Georges
2017-07-01
The objective of this paper is to provide a review on some aspects of the mathematical and computational modelling of skin biophysics, with special focus on constitutive theories based on nonlinear continuum mechanics from elasticity, through anelasticity, including growth, to thermoelasticity. Microstructural and phenomenological approaches combining imaging techniques are also discussed. Finally, recent research applications on skin wrinkles will be presented to highlight the potential of physics-based modelling of skin in tackling global challenges such as ageing of the population and the associated skin degradation, diseases and traumas.
Electrophysiological Data and the Biophysical Modelling of Local Cortical Circuits
Directory of Open Access Journals (Sweden)
Dimitris Pinotsis
2014-03-01
Full Text Available This paper shows how recordings of gamma oscillations – under different experimental conditions or from different subjects – can be combined with a class of population models called neural fields and dynamic causal modeling (DCM to distinguish among alternative hypotheses regarding cortical structure and function. This approach exploits inter-subject variability and trial-specific effects associated with modulations in the peak frequency of gamma oscillations. It draws on the computational power of Bayesian model inversion, when applied to neural field models of cortical dynamics. Bayesian model comparison allows one to adjudicate among different mechanistic hypotheses about cortical excitability, synaptic kinetics and the cardinal topographic features of local cortical circuits. It also provides optimal parameter estimates that quantify neuromodulation and the spatial dispersion of axonal connections or summation of receptive fields in the visual cortex. This paper provides an overview of a family of neural field models that have been recently implemented using the DCM toolbox of the academic freeware Statistical Parametric Mapping (SPM. The SPM software is a popular platform for analyzing neuroimaging data, used by several neuroscience communities worldwide. DCM allows for a formal (Bayesian statistical analysis of cortical network connectivity, based upon realistic biophysical models of brain responses. It is this particular feature of DCM – the unique combination of generative models with optimization techniques based upon (variational Bayesian principles – that furnishes a novel way to characterize functional brain architectures. In particular, it provides answers to questions about how the brain is wired and how it responds to different experimental manipulations. For a review of the general role of neural fields in SPM the reader can consult e.g. see [1]. Neural fields have a long and illustrious history in mathematical
Biophysical Modeling of Alpha Rhythms During Halothane-Induced Unconsciousness.
Vijayan, Sujith; Ching, ShiNung; Purdon, Patrick L; Brown, Emery N; Kopell, Nancy J
2013-01-01
During the induction of general anesthesia there is a shift in power from the posterior regions of the brain to the frontal cortices; this shift in power is called anteriorization. For many anesthetics, a prominent feature of anteriorization is a shift specifically in the alpha band (8-13 Hz) from posterior to frontal cortices. Here we present a biophysical computational model that describes thalamocortical circuit-level dynamics underlying anteriorization of the alpha rhythm in the case of halothane. Halothane potentiates GABAA and increases potassium leak conductances. According to our model, an increase in potassium leak conductances hyperpolarizes and silences the high-threshold thalamocortical (HTC) cells, a specialized subset of thalamocortical cells that fire at the alpha frequency at relatively depolarized membrane potentials (>-60 mV) and are thought to be the generators of quiet awake occipital alpha. At the same time the potentiation of GABAA imposes an alpha time scale on both the cortical and the thalamic component of the frontal portion of our model. The alpha activity in the frontal component is further strengthened by reciprocal thalamocortical feedback. Thus, we argue that the dual molecular targets of halothane induce the anteriorization of the alpha rhythm by increasing potassium leak conductances, which abolishes occipital alpha, and by potentiating GABAA, which induces frontal alpha. These results provide a computational modeling formulation for studying highly detailed biophysical mechanisms of anesthetic action in silico.
A biochemical/biophysical 3D FE intervertebral disc model.
Schroeder, Y; Huyghe, J M; van Donkelaar, C C; Ito, K
2010-10-01
Present research focuses on different strategies to preserve the degenerated disc. To assure long-term success of novel approaches, favorable mechanical conditions in the disc tissue are essential. To evaluate these, a model is required that can determine internal mechanical conditions which cannot be directly measured as a function of assessable biophysical characteristics. Therefore, the objective is to evaluate if constitutive and material laws acquired on isolated samples of nucleus and annulus tissue can be used directly in a whole-organ 3D FE model to describe intervertebral disc behavior. The 3D osmo-poro-visco-hyper-elastic disc (OVED) model describes disc behavior as a function of annulus and nucleus tissue biochemical composition, organization and specific constituent properties. The description of the 3D collagen network was enhanced to account for smaller fibril structures. Tissue mechanical behavior tests on isolated nucleus and annulus samples were simulated with models incorporating tissue composition to calculate the constituent parameter values. The obtained constitutive laws were incorporated into the whole-organ model. The overall behavior and disc properties of the model were corroborated against in vitro creep experiments of human L4/L5 discs. The OVED model simulated isolated tissue experiments on confined compression and uniaxial tensile test and whole-organ disc behavior. This was possible, provided that secondary fiber structures were accounted for. The fair agreement (radial bulge, axial creep deformation and intradiscal pressure) between model and experiment was obtained using constitutive properties that are the same for annulus and nucleus. Both tissue models differed in the 3D OVED model only by composition. The composition-based modeling presents the advantage of reducing the numbers of material parameters to a minimum and to use tissue composition directly as input. Hence, this approach provides the possibility to describe internal
Phenomenological vs. biophysical models of thermal stress in aquatic eggs.
Martin, Benjamin T; Pike, Andrew; John, Sara N; Hamda, Natnael; Roberts, Jason; Lindley, Steven T; Danner, Eric M
2017-01-01
Predicting species responses to climate change is a central challenge in ecology. These predictions are often based on lab-derived phenomenological relationships between temperature and fitness metrics. We tested one of these relationships using the embryonic stage of a Chinook salmon population. We parameterised the model with laboratory data, applied it to predict survival in the field, and found that it significantly underestimated field-derived estimates of thermal mortality. We used a biophysical model based on mass transfer theory to show that the discrepancy was due to the differences in water flow velocities between the lab and the field. This mechanistic approach provides testable predictions for how the thermal tolerance of embryos depends on egg size and flow velocity of the surrounding water. We found support for these predictions across more than 180 fish species, suggesting that flow and temperature mediated oxygen limitation is a general mechanism underlying the thermal tolerance of embryos.
Biophysical Modeling of Cross-Shore Plankton Transport
Fujimura, A.; Reniers, A.; Paris, C. B.; Shanks, A.; MacMahan, J.; Morgan, S.
2016-02-01
Coastal ecosystems are influenced by cross-shore flows. Processes that create coastal plankton distributions are not well understood, even though possible mechanisms of plankton transport in the surf zone have been investigated. Our data from a rip-channeled beach show that concentrations of zooplankton and phytoplankton are higher in the surf zone than offshore. To examine how plankton are transported toward the shore, we used a coupled biophysical model, comprised of Delft3D wave/flow simulations and an individual-based model for tracking plankton. Model results indicate that onshore delivery of zooplankton is enhanced by Stokes drift, wave-driven bottom boundary streaming, alongshore topographic variability, and turbulence-dependent sinking behavior of zooplankton. Phytoplankton sinking may also be accelerated by turbulence, but the mechanism differs from that which affects zooplankton. Turbulence has the potential to increase phytoplankton growth rates. Therefore, the phytoplankton transport model includes turbulence-induced sinking velocity and growth rate, although the latter appears to have little influence on phytoplankton distributions. Modeled phytoplankton concentrations in the surf zone are much lower than expected, although the zooplankton transport model qualitatively reproduced our observations. Thus, there must be other possible factors influencing phytoplankton transport, some of which will be discussed.
A Biophysical Model for the Staircase Geometry of Stereocilia.
Directory of Open Access Journals (Sweden)
Gilad Orly
Full Text Available Cochlear hair cell bundles, made up of 10s to 100s of individual stereocilia, are essential for hearing, and even relatively minor structural changes, due to mutations or injuries, can result in total deafness. Consistent with its specialized role, the staircase geometry (SCG of hair cell bundles presents one of the most striking, intricate, and precise organizations of actin-based cellular shapes. Composed of rows of actin-filled stereocilia with increasing lengths, the hair cell's staircase-shaped bundle is formed from a progenitor field of smaller, thinner, and uniformly spaced microvilli with relatively invariant lengths. While recent genetic studies have provided a significant increase in information on the multitude of stereocilia protein components, there is currently no model that integrates the basic physical forces and biochemical processes necessary to explain the emergence of the SCG. We propose such a model derived from the biophysical and biochemical characteristics of actin-based protrusions. We demonstrate that polarization of the cell's apical surface, due to the lateral polarization of the entire epithelial layer, plays a key role in promoting SCG formation. Furthermore, our model explains many distinct features of the manifestations of SCG in different species and in the presence of various deafness-associated mutations.
MODEL SELECTION FOR SPECTROPOLARIMETRIC INVERSIONS
Energy Technology Data Exchange (ETDEWEB)
Asensio Ramos, A.; Manso Sainz, R.; Martinez Gonzalez, M. J.; Socas-Navarro, H. [Instituto de Astrofisica de Canarias, E-38205, La Laguna, Tenerife (Spain); Viticchie, B. [ESA/ESTEC RSSD, Keplerlaan 1, 2200 AG Noordwijk (Netherlands); Orozco Suarez, D., E-mail: aasensio@iac.es [National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588 (Japan)
2012-04-01
Inferring magnetic and thermodynamic information from spectropolarimetric observations relies on the assumption of a parameterized model atmosphere whose parameters are tuned by comparison with observations. Often, the choice of the underlying atmospheric model is based on subjective reasons. In other cases, complex models are chosen based on objective reasons (for instance, the necessity to explain asymmetries in the Stokes profiles) but it is not clear what degree of complexity is needed. The lack of an objective way of comparing models has, sometimes, led to opposing views of the solar magnetism because the inferred physical scenarios are essentially different. We present the first quantitative model comparison based on the computation of the Bayesian evidence ratios for spectropolarimetric observations. Our results show that there is not a single model appropriate for all profiles simultaneously. Data with moderate signal-to-noise ratios (S/Ns) favor models without gradients along the line of sight. If the observations show clear circular and linear polarization signals above the noise level, models with gradients along the line are preferred. As a general rule, observations with large S/Ns favor more complex models. We demonstrate that the evidence ratios correlate well with simple proxies. Therefore, we propose to calculate these proxies when carrying out standard least-squares inversions to allow for model comparison in the future.
Biophysical model of prokaryotic diversity in geothermal hot springs.
Klales, Anna; Duncan, James; Nett, Elizabeth Janus; Kane, Suzanne Amador
2012-02-01
Recent studies of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than a single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. We present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms.
Mechanisms of Soil Aggregation: a biophysical modeling framework
Ghezzehei, T. A.; Or, D.
2016-12-01
Soil aggregation is one of the main crosscutting concepts in all sub-disciplines and applications of soil science from agriculture to climate regulation. The concept generally refers to adhesion of primary soil particles into distinct units that remain stable when subjected to disruptive forces. It is one of the most sensitive soil qualities that readily respond to disturbances such as cultivation, fire, drought, flooding, and changes in vegetation. These changes are commonly quantified and incorporated in soil models indirectly as alterations in carbon content and type, bulk density, aeration, permeability, as well as water retention characteristics. Soil aggregation that is primarily controlled by organic matter generally exhibits hierarchical organization of soil constituents into stable units that range in size from a few microns to centimeters. However, this conceptual model of soil aggregation as the key unifying mechanism remains poorly quantified and is rarely included in predictive soil models. Here we provide a biophysical framework for quantitative and predictive modeling of soil aggregation and its attendant soil characteristics. The framework treats aggregates as hotspots of biological, chemical and physical processes centered around roots and root residue. We keep track of the life cycle of an individual aggregate from it genesis in the rhizosphere, fueled by rhizodeposition and mediated by vigorous microbial activity, until its disappearance when the root-derived resources are depleted. The framework synthesizes current understanding of microbial life in porous media; water holding and soil binding capacity of biopolymers; and environmental controls on soil organic matter dynamics. The framework paves a way for integration of processes that are presently modeled as disparate or poorly coupled processes, including storage and protection of carbon, microbial activity, greenhouse gas fluxes, movement and storage of water, resistance of soils against
Microbial Life in Soil - Linking Biophysical Models with Observations
Or, Dani; Tecon, Robin; Ebrahimi, Ali; Kleyer, Hannah; Ilie, Olga; Wang, Gang
2015-04-01
Microbial life in soil occurs within fragmented aquatic habitats formed in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools
Wake Vortex Inverse Model User's Guide
Lai, David; Delisi, Donald
2008-01-01
NorthWest Research Associates (NWRA) has developed an inverse model for inverting landing aircraft vortex data. The data used for the inversion are the time evolution of the lateral transport position and vertical position of both the port and starboard vortices. The inverse model performs iterative forward model runs using various estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Forward model predictions of lateral transport and altitude are then compared with the observed data. Differences between the data and model predictions guide the choice of vortex parameter values, crosswind profile and circulation evolution in the next iteration. Iterations are performed until a user-defined criterion is satisfied. Currently, the inverse model is set to stop when the improvement in the rms deviation between the data and model predictions is less than 1 percent for two consecutive iterations. The forward model used in this inverse model is a modified version of the Shear-APA model. A detailed description of this forward model, the inverse model, and its validation are presented in a different report (Lai, Mellman, Robins, and Delisi, 2007). This document is a User's Guide for the Wake Vortex Inverse Model. Section 2 presents an overview of the inverse model program. Execution of the inverse model is described in Section 3. When executing the inverse model, a user is requested to provide the name of an input file which contains the inverse model parameters, the various datasets, and directories needed for the inversion. A detailed description of the list of parameters in the inversion input file is presented in Section 4. A user has an option to save the inversion results of each lidar track in a mat-file (a condensed data file in Matlab format). These saved mat-files can be used for post-inversion analysis. A description of the contents of the saved files is given in Section 5. An example of an inversion input
Forward modeling. Route to electromagnetic inversion
Energy Technology Data Exchange (ETDEWEB)
Groom, R.; Walker, P. [PetRos EiKon Incorporated, Ontario (Canada)
1996-05-01
Inversion of electromagnetic data is a topical subject in the literature, and much time has been devoted to understanding the convergence properties of various inverse methods. The relative lack of success of electromagnetic inversion techniques is partly attributable to the difficulties in the kernel forward modeling software. These difficulties come in two broad classes: (1) Completeness and robustness, and (2) convergence, execution time and model simplicity. If such problems exist in the forward modeling kernel, it was demonstrated that inversion can fail to generate reasonable results. It was suggested that classical inversion techniques, which are based on minimizing a norm of the error between data and the simulated data, will only be successful when these difficulties in forward modeling kernels are properly dealt with. 4 refs., 5 figs.
Relative risk regression models with inverse polynomials.
Ning, Yang; Woodward, Mark
2013-08-30
The proportional hazards model assumes that the log hazard ratio is a linear function of parameters. In the current paper, we model the log relative risk as an inverse polynomial, which is particularly suitable for modeling bounded and asymmetric functions. The parameters estimated by maximizing the partial likelihood are consistent and asymptotically normal. The advantages of the inverse polynomial model over the ordinary polynomial model and the fractional polynomial model for fitting various asymmetric log relative risk functions are shown by simulation. The utility of the method is further supported by analyzing two real data sets, addressing the specific question of the location of the minimum risk threshold.
Multiscattering inversion for low-model wavenumbers
Alkhalifah, Tariq Ali
2016-09-21
A successful full-waveform inversion implementation updates the low-wavenumber model components first for a proper description of the wavefield propagation and slowly adds the high wavenumber potentially scattering parts of the model. The low-wavenumber components can be extracted from the transmission parts of the recorded wavefield emanating directly from the source or the transmission parts from the single- or double-scattered wavefield computed from a predicted scatter field acting as secondary sources.We use a combined inversion of data modeled from the source and those corresponding to single and double scattering to update the velocity model and the component of the velocity (perturbation) responsible for the single and double scattering. The combined inversion helps us access most of the potential model wavenumber information that may be embedded in the data. A scattering-angle filter is used to divide the gradient of the combined inversion, so initially the high-wavenumber (low-scattering-angle) components of the gradient are directed to the perturbation model and the low-wavenumber (highscattering- angle) components are directed to the velocity model. As our background velocity matures, the scatteringangle divide is slowly lowered to allow for more of the higher wavenumbers to contribute the velocity model. Synthetic examples including the Marmousi model are used to demonstrate the additional illumination and improved velocity inversion obtained when including multiscattered energy. © 2016 Society of Exploration Geophysicists.
Directory of Open Access Journals (Sweden)
Jessica Melbourne-Thomas
2011-09-01
Full Text Available Transdisciplinary approaches that consider both socioeconomic and biophysical processes are central to understanding and managing rapid change in coral reef systems worldwide. To date, there have been limited attempts to couple the two sets of processes in dynamic models for coral reefs, and these attempts are confined to reef systems in developed countries. We present an approach to coupling existing biophysical and socioeconomic models for coral reef systems in the Mexican state of Quintana Roo. The biophysical model is multiscale, using dynamic equations to capture local-scale ecological processes on individual reefs, with reefs connected at regional scales by the ocean transport of larval propagules. The agent-based socioeconomic model simulates changes in tourism, fisheries, and urbanization in the Quintana Roo region. Despite differences in the formulation and currencies of the two models, we were able to successfully modify and integrate them to synchronize and define information flows and feedbacks between them. A preliminary evaluation of the coupled model system indicates that the model gives reasonable predictions for fisheries and ecological variables and can be used to examine scenarios for future social-ecological change in Quintana Roo. We provide recommendations for where efforts might usefully be focused in future attempts to integrate models of biophysical and socioeconomic processes, based on the limitations of our coupled system.
Error handling strategies in multiphase inverse modeling
Energy Technology Data Exchange (ETDEWEB)
Finsterle, S.; Zhang, Y.
2010-12-01
Parameter estimation by inverse modeling involves the repeated evaluation of a function of residuals. These residuals represent both errors in the model and errors in the data. In practical applications of inverse modeling of multiphase flow and transport, the error structure of the final residuals often significantly deviates from the statistical assumptions that underlie standard maximum likelihood estimation using the least-squares method. Large random or systematic errors are likely to lead to convergence problems, biased parameter estimates, misleading uncertainty measures, or poor predictive capabilities of the calibrated model. The multiphase inverse modeling code iTOUGH2 supports strategies that identify and mitigate the impact of systematic or non-normal error structures. We discuss these approaches and provide an overview of the error handling features implemented in iTOUGH2.
Rubin, Andrew
2014-01-01
This book presents concise descriptions and analysis of the classical and modern models used in mathematical biophysics. The authors ask the question "what new information can be provided by the models that cannot be obtained directly from experimental data?" Actively developing fields such as regulatory mechanisms in cells and subcellular systems and electron transport and energy transport in membranes are addressed together with more classical topics such as metabolic processes, nerve conduction and heart activity, chemical kinetics, population dynamics, and photosynthesis. The main approach is to describe biological processes using different mathematical approaches necessary to reveal characteristic features and properties of simulated systems. With the emergence of powerful mathematics software packages such as MAPLE, Mathematica, Mathcad, and MatLab, these methodologies are now accessible to a wide audience. Provides succinct but authoritative coverage of a broad array of biophysical topics and models Wr...
Inverse problems in spin models
Sessak, Vitor
2010-01-01
Several recent experiments in biology study systems composed of several interacting elements, for example neuron networks. Normally, measurements describe only the collective behavior of the system, even if in most cases we would like to characterize how its different parts interact. The goal of this thesis is to extract information about the microscopic interactions as a function of their collective behavior for two different cases. First, we will study a system described by a generalized Ising model. We find explicit formulas for the couplings as a function of the correlations and magnetizations. In the following, we will study a system described by a Hopfield model. In this case, we find not only explicit formula for inferring the patterns, but also an analytical result that allows one to estimate how much data is necessary for a good inference.
Auditory model inversion and its application
Institute of Scientific and Technical Information of China (English)
ZHAO Heming; WANG Yongqi; CHEN Xueqin
2005-01-01
Auditory model has been applied to several aspects of speech signal processing field, and appears to be effective in performance. This paper presents the inverse transform of each stage of one widely used auditory model. First of all it is necessary to invert correlogram and reconstruct phase information by repetitious iterations in order to get auditory-nerve firing rate. The next step is to obtain the negative parts of the signal via the reverse process of the HWR (Half Wave Rectification). Finally the functions of inner hair cell/synapse model and Gammatone filters have to be inverted. Thus the whole auditory model inversion has been achieved. An application of noisy speech enhancement based on auditory model inversion algorithm is proposed. Many experiments show that this method is effective in reducing noise.Especially when SNR of noisy speech is low it is more effective than other methods. Thus this auditory model inversion method given in this paper is applicable to speech enhancement field.
Inverse modeling for Large-Eddy simulation
Geurts, Bernardus J.
1998-01-01
Approximate higher order polynomial inversion of the top-hat filter is developed with which the turbulent stress tensor in Large-Eddy Simulation can be consistently represented using the filtered field. Generalized (mixed) similarity models are proposed which improved the agreement with the kinetic
A biophysical model for identifying splicing regulatory elements and their interactions.
Directory of Open Access Journals (Sweden)
Ji Wen
Full Text Available Alternative splicing (AS of precursor mRNA (pre-mRNA is a crucial step in the expression of most eukaryotic genes. Splicing factors (SFs play an important role in AS regulation by binding to the cis-regulatory elements on the pre-mRNA. Although many splicing factors (SFs and their binding sites have been identified, their combinatorial regulatory effects remain to be elucidated. In this paper, we derive a biophysical model for AS regulation that integrates combinatorial signals of cis-acting splicing regulatory elements (SREs and their interactions. We also develop a systematic framework for model inference. Applying the biophysical model to a human RNA-Seq data set, we demonstrate that our model can explain 49.1%-66.5% variance of the data, which is comparable to the best result achieved by biophysical models for transcription. In total, we identified 119 SRE pairs between different regions of cassette exons that may regulate exon or intron definition in splicing, and 77 SRE pairs from the same region that may arise from a long motif or two different SREs bound by different SFs. Particularly, putative binding sites of polypyrimidine tract-binding protein (PTB, heterogeneous nuclear ribonucleoprotein (hnRNP F/H and E/K are identified as interacting SRE pairs, and have been shown to be consistent with the interaction models proposed in previous experimental results. These results show that our biophysical model and inference method provide a means of quantitative modeling of splicing regulation and is a useful tool for identifying SREs and their interactions. The software package for model inference is available under an open source license.
Energy Technology Data Exchange (ETDEWEB)
Souza, Fabio Marques Simoes de [Cell and Developmental Biology, University of Colorado at Denver and Health Science Center, Campus Box 6511, PO Box 6511, 12801 East 17th Avenue, Aurora, CO 80045 (United States); Antunes, Gabriela [Psychobiology Sector and Department of Chemistry, Faculdade de Filosofia Ciencias e Letras de Ribeirao Preto, Universidade de Sao Paulo, Av. Bandeirantes, 3900, 14040-901, Ribeirao Preto, SP (Brazil)
2007-03-15
The majority of the biophysical models of olfaction have been focused on the electrical properties of the system, which is justified by the relative facility of recording the electrical activity of the olfactory cells. However, depending on the level of detail utilized, a biophysical model can explore molecular, cellular and network phenomena. This review presents the state of the art of the biophysical approach to understanding olfaction. The reader is introduced to the principal problems involving the study of olfaction and guided gradually to comprehend why it is important to develop biophysical models to investigate olfaction. A large number of representative biophysical efforts in olfaction, their main contributions, the trends for the next generations of biophysical models and the improvements that may be explored by future biophysicists of olfaction have been reviewed.
Directory of Open Access Journals (Sweden)
Rachel eLees-Green
2011-07-01
Full Text Available Gastrointestinal motility research is progressing rapidly, leading to significant advances in the last 15 years in understanding the cellular mechanisms underlying motility, following the discovery of the central role played by the interstitial cells of Cajal (ICC. As experimental knowledge of ICC physiology has expanded, biophysically-based modelling has become a valuable tool for integrating experimental data, for testing hypotheses on ICC pacemaker mechanisms, and for applications in in silico studies including in multiscale models. This review is focused on the cellular electrophysiology of ICC. Recent evidence from both experimental and modelling domains have called aspects of the existing pacemaker theories into question. Therefore, current experimental knowledge of ICC pacemaker mechanisms is examined in depth, and current theories of ICC pacemaking are evaluated and further developed. Existing biophysically-based ICC models and their physiological foundations are then critiqued in light of the recent advances in experimental knowledge, and opportunities to improve these models are identified. The review concludes by examining several potential clinical applications of biophysically-based ICC modelling from the subcellular through to the organ level, including ion channelopathies and ICC network degradation.
A selective view of stochastic inference and modeling problems in nanoscale biophysics
Institute of Scientific and Technical Information of China (English)
KOU S. C.
2009-01-01
Advances in nanotechnology enable scientists for the first time to study biological processes on a nanoscale molecule-by-molecule basis. They also raise challenges and opportunities for statisticians and applied probabilists. To exemplify the stochastic inference and modeling problems in the field, this paper discusses a few selected cases, ranging from likelihood inference, Bayesian data augmentation, and semi- and non-parametric inference of nanometric biochemical systems to the utilization of stochastic integro-differential equations and stochastic networks to model single-molecule biophysical processes. We discuss the statistical and probabilistic issues as well as the biophysical motivation and physical meaning behind the problems, emphasizing the analysis and modeling of real experimental data.
A selective view of stochastic inference and mod-eling problems in nanoscale biophysics
Institute of Scientific and Technical Information of China (English)
KOU; S.C.
2009-01-01
Advances in nanotechnology enable scientists for the first time to study biological pro-cesses on a nanoscale molecule-by-molecule basis.They also raise challenges and opportunities for statisticians and applied probabilists.To exemplify the stochastic inference and modeling problems in the field,this paper discusses a few selected cases,ranging from likelihood inference,Bayesian data augmentation,and semi-and non-parametric inference of nanometric biochemical systems to the uti-lization of stochastic integro-differential equations and stochastic networks to model single-molecule biophysical processes.We discuss the statistical and probabilistic issues as well as the biophysical motivation and physical meaning behind the problems,emphasizing the analysis and modeling of real experimental data.
Investigating complex networks with inverse models
Wens, Vincent
2014-01-01
Recent advances in neuroscience have motivated the study of network organization in spatially distributed dynamical systems from indirect measurements. However, the associated connectivity estimation, when combined with inverse modeling, is strongly affected by spatial leakage. We formulate this problem in a general framework and develop a new approach to model spatial leakage and limit its effects. It is analytically compared to existing regression-based methods used in electrophysiology, which are shown to yield biased estimates of amplitude and phase couplings.
Inversion identities for inhomogeneous face models
Frahm, Holger; Karaiskos, Nikos
2014-10-01
We derive exact inversion identities satisfied by the transfer matrix of inhomogeneous interaction-round-a-face (IRF) models with arbitrary boundary conditions using the underlying integrable structure and crossing properties of the local Boltzmann weights. For the critical restricted solid-on-solid (RSOS) models these identities together with some information on the analytical properties of the transfer matrix determine the spectrum completely and allow to derive the Bethe equations for both periodic and general open boundary conditions.
Inversion identities for inhomogeneous face models
Directory of Open Access Journals (Sweden)
Holger Frahm
2014-10-01
Full Text Available We derive exact inversion identities satisfied by the transfer matrix of inhomogeneous interaction-round-a-face (IRF models with arbitrary boundary conditions using the underlying integrable structure and crossing properties of the local Boltzmann weights. For the critical restricted solid-on-solid (RSOS models these identities together with some information on the analytical properties of the transfer matrix determine the spectrum completely and allow to derive the Bethe equations for both periodic and general open boundary conditions.
Inversion identities for inhomogeneous face models
Energy Technology Data Exchange (ETDEWEB)
Frahm, Holger; Karaiskos, Nikos
2014-10-15
We derive exact inversion identities satisfied by the transfer matrix of inhomogeneous interaction-round-a-face (IRF) models with arbitrary boundary conditions using the underlying integrable structure and crossing properties of the local Boltzmann weights. For the critical restricted solid-on-solid (RSOS) models these identities together with some information on the analytical properties of the transfer matrix determine the spectrum completely and allow to derive the Bethe equations for both periodic and general open boundary conditions.
Incorporating Plant Phenology Dynamics in a Biophysical Canopy Model
Barata, Raquel A.; Drewry, Darren
2012-01-01
The Multi-Layer Canopy Model (MLCan) is a vegetation model created to capture plant responses to environmental change. Themodel vertically resolves carbon uptake, water vapor and energy exchange at each canopy level by coupling photosynthesis, stomatal conductance and leaf energy balance. The model is forced by incoming shortwave and longwave radiation, as well as near-surface meteorological conditions. The original formulation of MLCan utilized canopy structural traits derived from observations. This project aims to incorporate a plant phenology scheme within MLCan allowing these structural traits to vary dynamically. In the plant phenology scheme implemented here, plant growth is dependent on environmental conditions such as air temperature and soil moisture. The scheme includes functionality that models plant germination, growth, and senescence. These growth stages dictate the variation in six different vegetative carbon pools: storage, leaves, stem, coarse roots, fine roots, and reproductive. The magnitudes of these carbon pools determine land surface parameters such as leaf area index, canopy height, rooting depth and root water uptake capacity. Coupling this phenology scheme with MLCan allows for a more flexible representation of the structure and function of vegetation as it responds to changing environmental conditions.
Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara
2015-04-01
Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.
Integrating Economic Models with Biophysical Models in the Willamette Water 2100 Project
Jaeger, W. K.; Plantinga, A.
2013-12-01
This paper highlights the human system modeling components for Willamette Water 2100, a comprehensive, highly integrated study of hydrological, ecological, and human factors affecting water scarcity in the Willamette River Basin (WRB). The project is developing a spatiotemporal simulation model to predict future trajectories of water scarcity, and to evaluate mitigation policies. Economic models of land use and water use are the main human system models in WW2100. Water scarcity depends on both supply and demand for water, and varies greatly across time and space (Jaeger et al., 2013). Thus, the locations of human water use can have enormous influence on where and when water is used, and hence where water scarcity may arise. Modeling the locations of human uses of water (e.g., urban versus agricultural) as well as human values and choices, are the principal quantitative ways that social science can contribute to research of this kind. Our models are empirically-based models of human resource allocation. Each model reflects private behavior (choices by households, farms, firms), institutions (property rights, laws, markets, regulations), public infrastructure (dams, canals, highways), and also 'external drivers' that influence the local economy (migration, population growth, national markets and policies). This paper describes the main model components, emphasizing similarities between human and biophysical components of the overall project, and the model's linkages and feedbacks relevant to our predictions of changes in water scarcity between now and 2100. Results presented include new insights from individual model components as well as available results from the integrated system model. Issues include water scarcity and water quality (temperature) for out-of-stream and instream uses, the impact of urban expansion on water use and potential flood damage. Changes in timing and variability of spring discharge with climate change, as well as changes in human uses of
Voltammetry: mathematical modelling and Inverse Problem
Koshev, N A; Kuzina, V V
2016-01-01
We propose the fast semi-analytical method of modelling the polarization curves in the voltammetric experiment. The method is based on usage of the special func- tions and shows a big calculation speed and a high accuracy and stability. Low computational needs of the proposed algorithm allow us to state the set of Inverse Problems of voltammetry for the reconstruction of metal ions concentrations or the other parameters of the electrolyte under investigation.
Biophysical studies of cholesterol in unsaturated phospholipid model membranes
Williams, Justin Adam
Cellular membranes contain a staggering diversity of lipids. The lipids are heterogeneously distributed to create regions, or domains, whose physical properties differ from the bulk membrane and play an essential role in modulating the function of resident proteins. Many basic questions pertaining to the formation of these lateral assemblies remain. This research employs model membranes of well-defined composition to focus on the potential role of polyunsaturated fatty acids (PUFAs) and their interaction with cholesterol (chol) in restructuring the membrane environment. Omega-3 (n-3) PUFAs are the main bioactive components of fish oil, whose consumption alleviates a variety of health problems by a molecular mechanism that is unclear. We hypothesize that the incorporation of PUFAs into membrane lipids and the effect they have on molecular organization may be, in part, responsible. Chol is a major constituent in the plasma membrane of mammals. It determines the arrangement and collective properties of neighboring lipids, driving the formation of domains via differential affinity for different lipids. The molecular organization of 1-[2H31]palmitoyl-2-eicosapentaenoylphosphatidylcholine (PEPC-d31) and 1-[2H31]palmitoyl-2-docosahexaenoylphosphatidylcholine (PDPC-d31) in membranes with sphingomyelin (SM) and chol (1:1:1 mol) was compared by solid-state 2H NMR spectroscopy. Eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids are the two major n-3 PUFAs found in fish oil, while PEPC-d31 and PDPC-d31 are phospholipids containing the respective PUFAs at the sn-2 position and a perdeuterated palmitic acid at the sn-1 position. Analysis of spectra recorded as a function of temperature indicates that in both cases, formation of PUFA-rich (less ordered) and SM-rich (more ordered) domains occurred. A surprisingly substantial proportion of PUFA was found to infiltrate the more ordered domain. There was almost twice as much DHA (65%) as EPA (30%). The implication is that n-3
Mesoscale simulations of two model systems in biophysics: from red blood cells to DNAs
Peng, Zhangli; Chen, Yeng-Long; Lu, Huijie; Pan, Zehao; Chang, Hsueh-Chia
2015-12-01
Computational modeling has become increasingly important in biophysics, but the great challenge in numerical simulations due to the multiscale feature of biological systems limits the capability of modeling in making discoveries in biology. Innovative multiscale modeling approaches are desired to bridge different scales from nucleic acids and proteins to cells and tissues. Although all-atom molecular dynamics has been successfully applied in many microscale biological processes such as protein folding, it is still prohibitively expensive for studying macroscale problems such as biophysics of cells and tissues. On the other hand, continuum-based modeling has become a mature procedure for analysis and design in many engineering fields, but new insights for biological systems in the microscale are limited when molecular details are missing in continuum-based modeling. In this context, mesoscale modeling approaches such as Langevin dynamics, lattice Boltzmann method, and dissipative particle dynamics have become popular by simultaneously incorporating molecular interactions and long-range hydrodynamic interactions, providing insights to properties on longer time and length scales than molecular dynamics. In this review, we summarized several mesoscale simulation approaches for studying two model systems in biophysics: red blood cells (RBCs) and deoxyribonucleic acids (DNAs). The RBC is a model system for cell mechanics and biological membranes, while the DNA represents a model system for biopolymers. We introduced the motivations of studying these problems and presented the key features of different mesoscale methods. Furthermore, we described the latest progresses in these methods and highlighted the major findings for modeling RBCs and DNAs. Finally, we also discussed the challenges and potential issues of different approaches.
Madhuprakash, Jogi; Bobbili, Kishore Babu; Moerschbacher, Bruno M.; Singh, Tej Pal; Swamy, Musti J.; Podile, Appa Rao
2015-01-01
Serratia proteamaculans chitinase-D (SpChiD) has a unique combination of hydrolytic and transglycosylation (TG) activities. The TG activity of SpChiD can be used for large-scale production of chito-oligosaccharides (CHOS). The multiple activities (hydrolytic and/or chitobiase activities and TG) of SpChiD appear to be strongly influenced by the substrate-binding cleft. Here, we report the unique property of SpChiD substrate-binding cleft, wherein, the residues Tyr28, Val35 and Thr36 control chitobiase activity and the residues Trp160 and Trp290 are crucial for TG activity. Mutants with reduced (V35G and T36G/F) or no (SpChiDΔ30–42 and Y28A) chitobiase activity produced higher amounts of the quantifiable even-chain TG product with degree of polymerization (DP)-6, indicating that the chitobiase and TG activities are inversely related. In addition to its unprecedented catalytic properties, unlike other chitinases, the single modular SpChiD showed dual unfolding transitions. Ligand-induced thermal stability studies with the catalytically inactive mutant of SpChiD (E153A) showed that the transition temperature increased upon binding of CHOS with DP2–6. Isothermal titration calorimetry experiments revealed the exceptionally high binding affinities for E153A to CHOS with DP2–6. These observations strongly support that the architecture of SpChiD substrate-binding cleft adopted to control chitobiase and TG activities, in addition to usual chitinase-mediated hydrolysis. PMID:26493546
Wu, H.; Furusawa, Y.; George, K.; Kawata, T.; Cucinotta, F.
Biophysical models addressing the formation of radiation-induced chromosome aberrations are usually based on the assumption that chromosome aberrations are formed by DNA double strand break (DSB) misrejoining, via either the homologous or the non-homologous repair pathway. However, comparing chromosome aberration data with model predictions is not always straightforward. In this paper we discuss some of the aspects that must be considered to make these comparisons meaningful. Firstly, biophysical models are usually applied to DSB rejoining and misrejoining in the G0/G1 phase of the cell cycle, while most chromosome aberration data reported in the literature are analyzed in metaphase. Since cells must progress through the cell cycle check points in order to reach mitosis, model predictions that differ from the metaphase chromosome analysis may actually agree with the aberration data in chromosomes collected in interphase. Secondly, high- LET radiation generally produces more complex aberrations involving exchanges between three or more DSB. While some models have successfully provided quantitative predictions of high-LET radiation induced complex aberrations in human lymphocytes, applying such models to other cell types requires special considerations due to the lack of geometric symmetry of the nucleus. Chromosome aberration data for non-spherical human fibroblast cells bombarded from various directions by high-LET charged particles will be presented, and their implication on physical modeling will be discussed.
Mellem, Daniel; Fischer, Frank; Jaspers, Sören; Wenck, Horst; Rübhausen, Michael
2016-01-01
Mitochondria are essential for the energy production of eukaryotic cells. During aging mitochondria run through various processes which change their quality in terms of activity, health and metabolic supply. In recent years, many of these processes such as fission and fusion of mitochondria, mitophagy, mitochondrial biogenesis and energy consumption have been subject of research. Based on numerous experimental insights, it was possible to qualify mitochondrial behaviour in computational simulations. Here, we present a new biophysical model based on the approach of Figge et al. in 2012. We introduce exponential decay and growth laws for each mitochondrial process to derive its time-dependent probability during the aging of cells. All mitochondrial processes of the original model are mathematically and biophysically redefined and additional processes are implemented: Mitochondrial fission and fusion is separated into a metabolic outer-membrane part and a protein-related inner-membrane part, a quality-dependent threshold for mitophagy and mitochondrial biogenesis is introduced and processes for activity-dependent internal oxidative stress as well as mitochondrial repair mechanisms are newly included. Our findings reveal a decrease of mitochondrial quality and a fragmentation of the mitochondrial network during aging. Additionally, the model discloses a quality increasing mechanism due to the interplay of the mitophagy and biogenesis cycle and the fission and fusion cycle of mitochondria. It is revealed that decreased mitochondrial repair can be a quality saving process in aged cells. Furthermore, the model finds strategies to sustain the quality of the mitochondrial network in cells with high production rates of reactive oxygen species due to large energy demands. Hence, the model adds new insights to biophysical mechanisms of mitochondrial aging and provides novel understandings of the interdependency of mitochondrial processes.
Mellem, Daniel; Fischer, Frank; Jaspers, Sören; Wenck, Horst; Rübhausen, Michael
2016-01-01
Mitochondria are essential for the energy production of eukaryotic cells. During aging mitochondria run through various processes which change their quality in terms of activity, health and metabolic supply. In recent years, many of these processes such as fission and fusion of mitochondria, mitophagy, mitochondrial biogenesis and energy consumption have been subject of research. Based on numerous experimental insights, it was possible to qualify mitochondrial behaviour in computational simulations. Here, we present a new biophysical model based on the approach of Figge et al. in 2012. We introduce exponential decay and growth laws for each mitochondrial process to derive its time-dependent probability during the aging of cells. All mitochondrial processes of the original model are mathematically and biophysically redefined and additional processes are implemented: Mitochondrial fission and fusion is separated into a metabolic outer-membrane part and a protein-related inner-membrane part, a quality-dependent threshold for mitophagy and mitochondrial biogenesis is introduced and processes for activity-dependent internal oxidative stress as well as mitochondrial repair mechanisms are newly included. Our findings reveal a decrease of mitochondrial quality and a fragmentation of the mitochondrial network during aging. Additionally, the model discloses a quality increasing mechanism due to the interplay of the mitophagy and biogenesis cycle and the fission and fusion cycle of mitochondria. It is revealed that decreased mitochondrial repair can be a quality saving process in aged cells. Furthermore, the model finds strategies to sustain the quality of the mitochondrial network in cells with high production rates of reactive oxygen species due to large energy demands. Hence, the model adds new insights to biophysical mechanisms of mitochondrial aging and provides novel understandings of the interdependency of mitochondrial processes. PMID:26771181
Bio-physical modeling of time-resolved forward scattering by Listeria colonies
Bae, Euiwon; Banada, Padmapriya P.; Bhunia, Arun K.; Hirleman, E. Daniel
2006-10-01
We have developed a detection system and associated protocol based on optical forward scattering where the bacterial colonies of various species and strains growing on solid nutrient surfaces produced unique scatter signatures. The aim of the present investigation was to develop a bio-physical model for the relevant phenomena. In particular, we considered time-varying macroscopic morphological properties of the growing colonies and modeled the scattering using scalar diffraction theory. For the present work we performed detailed studies with three species of Listeria; L. innocua, L. monocytogenes, and L. ivanovii. The baseline experiments involved cultures grown on brain heart infusion (BHI) agar and the scatter images were captured every six hours for an incubation period of 42 hours. The morphologies of the colonies were studied by phase contrast microscopy, including measurement of the diameter of the colony. Growth curves, represented by colony diameter as a function of time, were compared with the time-evolution of scattering signatures. Similar studies were carried out with L. monocytogenes grown on different substrates. Non-dimensionalizing incubation time in terms of the time to reach stationary phase was effective in reducing the dimensionality of the model. Bio-physical properties of the colony such as diameter, bacteria density variation, surface curvature/profile, and transmission coefficient are important parameters in predicting the features of the forward scattering signatures. These parameters are included in a baseline model that treats the colony as a concentric structure with radial variations in phase modulation. In some cases azimuthal variations and random phase inclusions were included as well. The end result is a protocol (growth media, incubation time and conditions) that produces reproducible and distinguishable scatter patterns for a variety of harmful food borne pathogens in a short period of time. Further, the bio-physical model we
Directory of Open Access Journals (Sweden)
Daniel Mellem
Full Text Available Mitochondria are essential for the energy production of eukaryotic cells. During aging mitochondria run through various processes which change their quality in terms of activity, health and metabolic supply. In recent years, many of these processes such as fission and fusion of mitochondria, mitophagy, mitochondrial biogenesis and energy consumption have been subject of research. Based on numerous experimental insights, it was possible to qualify mitochondrial behaviour in computational simulations. Here, we present a new biophysical model based on the approach of Figge et al. in 2012. We introduce exponential decay and growth laws for each mitochondrial process to derive its time-dependent probability during the aging of cells. All mitochondrial processes of the original model are mathematically and biophysically redefined and additional processes are implemented: Mitochondrial fission and fusion is separated into a metabolic outer-membrane part and a protein-related inner-membrane part, a quality-dependent threshold for mitophagy and mitochondrial biogenesis is introduced and processes for activity-dependent internal oxidative stress as well as mitochondrial repair mechanisms are newly included. Our findings reveal a decrease of mitochondrial quality and a fragmentation of the mitochondrial network during aging. Additionally, the model discloses a quality increasing mechanism due to the interplay of the mitophagy and biogenesis cycle and the fission and fusion cycle of mitochondria. It is revealed that decreased mitochondrial repair can be a quality saving process in aged cells. Furthermore, the model finds strategies to sustain the quality of the mitochondrial network in cells with high production rates of reactive oxygen species due to large energy demands. Hence, the model adds new insights to biophysical mechanisms of mitochondrial aging and provides novel understandings of the interdependency of mitochondrial processes.
Bagstad, Kenneth J.; Reed, James; Semmens, Darius J.; Sherrouse, Ben C.; Troy, Austin
2016-01-01
Through extensive research, ecosystem services have been mapped using both survey-based and biophysical approaches, but comparative mapping of public values and those quantified using models has been lacking. In this paper, we mapped hot and cold spots for perceived and modeled ecosystem services by synthesizing results from a social-values mapping study of residents living near the Pike–San Isabel National Forest (PSI), located in the Southern Rocky Mountains, with corresponding biophysically modeled ecosystem services. Social-value maps for the PSI were developed using the Social Values for Ecosystem Services tool, providing statistically modeled continuous value surfaces for 12 value types, including aesthetic, biodiversity, and life-sustaining values. Biophysically modeled maps of carbon sequestration and storage, scenic viewsheds, sediment regulation, and water yield were generated using the Artificial Intelligence for Ecosystem Services tool. Hotspots for both perceived and modeled services were disproportionately located within the PSI’s wilderness areas. Additionally, we used regression analysis to evaluate spatial relationships between perceived biodiversity and cultural ecosystem services and corresponding biophysical model outputs. Our goal was to determine whether publicly valued locations for aesthetic, biodiversity, and life-sustaining values relate meaningfully to results from corresponding biophysical ecosystem service models. We found weak relationships between perceived and biophysically modeled services, indicating that public perception of ecosystem service provisioning regions is limited. We believe that biophysical and social approaches to ecosystem service mapping can serve as methodological complements that can advance ecosystem services-based resource management, benefitting resource managers by showing potential locations of synergy or conflict between areas supplying ecosystem services and those valued by the public.
Mechanism and Modeling for Polymerization of Acrylamide in Inverse Microemulsions
Institute of Scientific and Technical Information of China (English)
LiXiao; ZhangWeiying; YuanHuigen
2004-01-01
After discussion on the mechanism of polymer particle nucleation and growth in inverse microemulsion polymerization, a schematic physical model for polymerization of acrylamide in inverse microemulsions was presented. Furthermore, several key problems in mathematically modeling of inverse microemulsion polymerization were pointed out.
Stochastic inverse problems: Models and metrics
Energy Technology Data Exchange (ETDEWEB)
Sabbagh, Elias H.; Sabbagh, Harold A.; Murphy, R. Kim [Victor Technologies, LLC, Bloomington, IN 47407-7706 (United States); Aldrin, John C. [Computational Tools, Gurnee, IL 60031 (United States); Annis, Charles [Statistical Engineering, Palm Beach Gardens, FL 33418 (United States); Knopp, Jeremy S. [Air Force Research Laboratory (AFRL/RXCA), Wright Patterson AFB, OH 45433-7817 (United States)
2015-03-31
In past work, we introduced model-based inverse methods, and applied them to problems in which the anomaly could be reasonably modeled by simple canonical shapes, such as rectangular solids. In these cases the parameters to be inverted would be length, width and height, as well as the occasional probe lift-off or rotation. We are now developing a formulation that allows more flexibility in modeling complex flaws. The idea consists of expanding the flaw in a sequence of basis functions, and then solving for the expansion coefficients of this sequence, which are modeled as independent random variables, uniformly distributed over their range of values. There are a number of applications of such modeling: 1. Connected cracks and multiple half-moons, which we have noted in a POD set. Ideally we would like to distinguish connected cracks from one long shallow crack. 2. Cracks of irregular profile and shape which have appeared in cold work holes during bolt-hole eddy-current inspection. One side of such cracks is much deeper than other. 3. L or C shaped crack profiles at the surface, examples of which have been seen in bolt-hole cracks. By formulating problems in a stochastic sense, we are able to leverage the stochastic global optimization algorithms in NLSE, which is resident in VIC-3D®, to answer questions of global minimization and to compute confidence bounds using the sensitivity coefficient that we get from NLSE. We will also address the issue of surrogate functions which are used during the inversion process, and how they contribute to the quality of the estimation of the bounds.
Simulation of Tillage Systems Impact on Soil Biophysical Properties Using the SALUS Model
Directory of Open Access Journals (Sweden)
Luigi Sartori
2011-02-01
Full Text Available A sustainable land management has been defined as the management system that allows for production, while minimizing risk, maintaining quality of soil and water. Tillage systems can significantly decrease soil carbon storage and influence the soil environment of a crop. Crop growth models can be useful tools in evaluating the impact of different tillage systems on soil biophysical properties and on the growth and final yield of the crops. The objectives of this paper were i to illustrate the SALUS model and its tillage component; ii to evaluate the effects of different tillage systems on water infiltration and time to ponding, iii to simulate the effect of tillage systems on some soil biophysical properties. The SALUS (System Approach to Land Use Sustainability model is designed to simulate continuous crop, soil, water and nutrient conditions under different tillage and crop residues management strategies for multiple years. Predictions of changes in surface residue, bulk density, runoff, drainage and evaporation were consistent with expected behaviours of these parameters as described in the literature. The experiment to estimate the time to ponding curve under different tillage system confirmed the theory and showed the beneficial effects of the residue on soil surface with respect to water infiltration. It also showed that the no-tillage system is a more appropriate system to adopt in areas characterized by high intensity rainfall.
Directory of Open Access Journals (Sweden)
Lahouari Bounoua
2015-01-01
Full Text Available In terms of the space cities occupy, urbanization appears as a minor land transformation. However, it permanently modifies land’s ecological functions, altering its carbon, energy, and water fluxes. It is therefore necessary to develop a land cover characterization at fine spatial and temporal scales to capture urbanization’s effects on surface fluxes. We develop a series of biophysical vegetation parameters such as the fraction of photosynthetically active radiation, leaf area index, vegetation greenness fraction, and roughness length over the continental US using MODIS and Landsat products for 2001. A 13-class land cover map was developed at a climate modeling grid (CMG merging the 500 m MODIS land cover and the 30 m impervious surface area from the National Land Cover Database. The landscape subgrid heterogeneity was preserved using fractions of each class from the 500 m and 30 m into the CMG. Biophysical parameters were computed using the 8-day composite Normalized Difference Vegetation Index produced by the North American Carbon Program. In addition to urban impact assessments, this dataset is useful for the computation of surface fluxes in land, vegetation, and urban models and is expected to be widely used in different land cover and land use change applications.
New organelles by gene duplication in a biophysical model of eukaryote endomembrane evolution.
Ramadas, Rohini; Thattai, Mukund
2013-06-04
Extant eukaryotic cells have a dynamic traffic network that consists of diverse membrane-bound organelles exchanging matter via vesicles. This endomembrane system arose and diversified during a period characterized by massive expansions of gene families involved in trafficking after the acquisition of a mitochondrial endosymbiont by a prokaryotic host cell >1.8 billion years ago. Here we investigate the mechanistic link between gene duplication and the emergence of new nonendosymbiotic organelles, using a minimal biophysical model of traffic. Our model incorporates membrane-bound compartments, coat proteins and adaptors that drive vesicles to bud and segregate cargo from source compartments, and SNARE proteins and associated factors that cause vesicles to fuse into specific destination compartments. In simulations, arbitrary numbers of compartments with heterogeneous initial compositions segregate into a few compositionally distinct subsets that we term organelles. The global structure of the traffic system (i.e., the number, composition, and connectivity of organelles) is determined completely by local molecular interactions. On evolutionary timescales, duplication of the budding and fusion machinery followed by loss of cross-interactions leads to the emergence of new organelles, with increased molecular specificity being necessary to maintain larger organellar repertoires. These results clarify potential modes of early eukaryotic evolution as well as more recent eukaryotic diversification. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Benchmarking sensitivity of biophysical processes to leaf area changes in land surface models
Forzieri, Giovanni; Duveiller, Gregory; Georgievski, Goran; Li, Wei; Robestson, Eddy; Kautz, Markus; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro
2017-04-01
Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates
Harrison, R R; Koch, C
1999-10-01
Flies are capable of rapid, coordinated flight through unstructured environments. This flight is guided by visual motion information that is extracted from photoreceptors in a robust manner. One feature of the fly's visual processing that adds to this robustness is the saturation of wide-field motion-sensitive neuron responses with increasing pattern size. This makes the cell's responses less dependent on the sparseness of the optical flow field while retaining motion information. By implementing a compartmental neuronal model in silicon, we add this "gain control" to an existing analog VLSI model of fly vision. This results in enhanced performance in a compact, low-power CMOS motion sensor. Our silicon system also demonstrates that modern, biophysically-detailed models of neural sensory processing systems can be instantiated in VLSI hardware.
Rahmati, Vahid; Kirmse, Knut; Marković, Dimitrije; Holthoff, Knut; Kiebel, Stefan J
2016-02-01
Calcium imaging has been used as a promising technique to monitor the dynamic activity of neuronal populations. However, the calcium trace is temporally smeared which restricts the extraction of quantities of interest such as spike trains of individual neurons. To address this issue, spike reconstruction algorithms have been introduced. One limitation of such reconstructions is that the underlying models are not informed about the biophysics of spike and burst generations. Such existing prior knowledge might be useful for constraining the possible solutions of spikes. Here we describe, in a novel Bayesian approach, how principled knowledge about neuronal dynamics can be employed to infer biophysical variables and parameters from fluorescence traces. By using both synthetic and in vitro recorded fluorescence traces, we demonstrate that the new approach is able to reconstruct different repetitive spiking and/or bursting patterns with accurate single spike resolution. Furthermore, we show that the high inference precision of the new approach is preserved even if the fluorescence trace is rather noisy or if the fluorescence transients show slow rise kinetics lasting several hundred milliseconds, and inhomogeneous rise and decay times. In addition, we discuss the use of the new approach for inferring parameter changes, e.g. due to a pharmacological intervention, as well as for inferring complex characteristics of immature neuronal circuits.
Updated Results for the Wake Vortex Inverse Model
Robins, Robert E.; Lai, David Y.; Delisi, Donald P.; Mellman, George R.
2008-01-01
NorthWest Research Associates (NWRA) has developed an Inverse Model for inverting aircraft wake vortex data. The objective of the inverse modeling is to obtain estimates of the vortex circulation decay and crosswind vertical profiles, using time history measurements of the lateral and vertical position of aircraft vortices. The Inverse Model performs iterative forward model runs using estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Iterations are performed until a user-defined criterion is satisfied. Outputs from an Inverse Model run are the best estimates of the time history of the vortex circulation derived from the observed data, the vertical crosswind profile, and several vortex parameters. The forward model, named SHRAPA, used in this inverse modeling is a modified version of the Shear-APA model, and it is described in Section 2 of this document. Details of the Inverse Model are presented in Section 3. The Inverse Model was applied to lidar-observed vortex data at three airports: FAA acquired data from San Francisco International Airport (SFO) and Denver International Airport (DEN), and NASA acquired data from Memphis International Airport (MEM). The results are compared with observed data. This Inverse Model validation is documented in Section 4. A summary is given in Section 5. A user's guide for the inverse wake vortex model is presented in a separate NorthWest Research Associates technical report (Lai and Delisi, 2007a).
The inverse gravimetric problem in gravity modelling
Sanso, F.; Tscherning, C. C.
1989-01-01
One of the main purposes of geodesy is to determine the gravity field of the Earth in the space outside its physical surface. This purpose can be pursued without any particular knowledge of the internal density even if the exact shape of the physical surface of the Earth is not known, though this seems to entangle the two domains, as it was in the old Stoke's theory before the appearance of Molodensky's approach. Nevertheless, even when large, dense and homogeneous data sets are available, it was always recognized that subtracting from the gravity field the effect of the outer layer of the masses (topographic effect) yields a much smoother field. This is obviously more important when a sparse data set is bad so that any smoothing of the gravity field helps in interpolating between the data without raising the modeling error, this approach is generally followed because it has become very cheap in terms of computing time since the appearance of spectral techniques. The mathematical description of the Inverse Gravimetric Problem (IGP) is dominated mainly by two principles, which in loose terms can be formulated as follows: the knowledge of the external gravity field determines mainly the lateral variations of the density; and the deeper the density anomaly giving rise to a gravity anomaly, the more improperly posed is the problem of recovering the former from the latter. The statistical relation between rho and n (and its inverse) is also investigated in its general form, proving that degree cross-covariances have to be introduced to describe the behavior of rho. The problem of the simultaneous estimate of a spherical anomalous potential and of the external, topographic masses is addressed criticizing the choice of the mixed collection approach.
Synchrony suppression in complex stimulus responses of a biophysical model of the cochlea.
Shamma, S A; Morrish, K A
1987-05-01
A minimal biophysical model of the cochlea is used to investigate the validity of the hypothesis that a single compressive nonlinearity at the hair cell level can explain some of the suppression phenomena in cochlear responses to complex stimuli. The dependencies of the model responses on the amplitudes and frequencies of two-tone stimuli resemble in many respects the behavior of the experimental data, and can be traced to explicit biophysical parameters in the model. Most discrepancies between theory and experiment stem from simplifications in parameters of the minimal model that play no direct role in the hypothesis. The analysis and simulations predict further results which, pending experimental verification, may provide a more direct test of the influence of the compressive nonlinearity on the relative amplitudes of the synchronous response components, and hence of its role in synchrony suppression. For instance, regardless of the overall absolute levels of a two-tone stimulus applied to this type of model, the ratio of the amplitudes at the input and the ratio of the corresponding responses at the output remain approximately constant and equal (the output ratio changes by at most 6 dB in favor of the stronger tone). Other nonlinear responses to multitonal stimuli can also be reproduced, such as "spectral edge enhancement" [Horst et al., Peripheral Auditory Mechanisms (Springer, Berlin, 1985)] and some aspects of three-tone suppression [Javel et al., Mechanisms of Hearing (Monash U.P., Australia, 1983)]. In contrast to the complex behavior of suppression with increasing sound intensity and the drastic influence of the compressive nonlinearity on the absolute response measures on the auditory nerve (e.g., average rate and synchrony profiles), the percepts of complex sounds are relatively stable. This suggests that the invariant relative response measures are more likely used in the encoding and CNS extraction of the spectrum of complex stimuli such as speech.
Voxel inversion of airborne electromagnetic data for improved model integration
Fiandaca, Gianluca; Auken, Esben; Kirkegaard, Casper; Vest Christiansen, Anders
2014-05-01
Inversion of electromagnetic data has migrated from single site interpretations to inversions including entire surveys using spatial constraints to obtain geologically reasonable results. Though, the model space is usually linked to the actual observation points. For airborne electromagnetic (AEM) surveys the spatial discretization of the model space reflects the flight lines. On the contrary, geological and groundwater models most often refer to a regular voxel grid, not correlated to the geophysical model space, and the geophysical information has to be relocated for integration in (hydro)geological models. We have developed a new geophysical inversion algorithm working directly in a voxel grid disconnected from the actual measuring points, which then allows for informing directly geological/hydrogeological models. The new voxel model space defines the soil properties (like resistivity) on a set of nodes, and the distribution of the soil properties is computed everywhere by means of an interpolation function (e.g. inverse distance or kriging). Given this definition of the voxel model space, the 1D forward responses of the AEM data are computed as follows: 1) a 1D model subdivision, in terms of model thicknesses, is defined for each 1D data set, creating "virtual" layers. 2) the "virtual" 1D models at the sounding positions are finalized by interpolating the soil properties (the resistivity) in the center of the "virtual" layers. 3) the forward response is computed in 1D for each "virtual" model. We tested the new inversion scheme on an AEM survey carried out with the SkyTEM system close to Odder, in Denmark. The survey comprises 106054 dual mode AEM soundings, and covers an area of approximately 13 km X 16 km. The voxel inversion was carried out on a structured grid of 260 X 325 X 29 xyz nodes (50 m xy spacing), for a total of 2450500 inversion parameters. A classical spatially constrained inversion (SCI) was carried out on the same data set, using 106054
Häussinger, Daniel; Pfohl, Thomas
2010-01-01
Biophysical chemistry at the Department of Chemistry, University of Basel, covers the NMR analysis of protein-protein interaction using paramagnetic tags and sophisticated microscopy techniques investigating the dynamics of biological matter.
Directory of Open Access Journals (Sweden)
N. Ghilain
2012-08-01
Full Text Available Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I, showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI and Fractional Vegetation Cover (FVC products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land
Neural-Based Pattern Matching for Selection of Biophysical Model Meteorological Forcings
Coleman, A. M.; Wigmosta, M. S.; Li, H.; Venteris, E. R.; Skaggs, R. J.
2011-12-01
The current interest and demand for developing renewable and sustainable bio-based energies has brought microalgae and other terrestrial feedstocks into the active research domain where different components and strategies of the lifecycle are evaluated for economic and resource efficiency. To understand the potential energy returns and resource requirements of large-scale open- and closed-pond microalgae cultivation facilities and terrestrial feedstock growth on marginal lands, a spatial modeling and biophysical modeling suite, referred to as the Biomass Assessment Tool (BAT), has been developed. BAT is in part comprised of (1) a high spatial resolution multi-criteria land suitability model; (2) a coupled, high-temporal resolution, full mass and energy balance hydrodynamic pond temperature and microalgae growth model; (3) a terrestrial water demand and biomass growth model; and (4) an spatially-based energy, land, and water use optimization routine. Depending on the criteria used, our national spatial land suitability model yields tens of thousands of potential large-scale bioenergy sites for modeling and evaluation of production and resource demand. The fundamental driver of water use and bioenergy production rates in pond-based cultivation systems and traditional terrestrial crop growth is the meteorology; however, a major obstacle in the use of high spatiotemporal resolution biophysical models is the lack of sufficient and readily available meteorological data at the appropriate scale. To address this issue, firstly, the daily meteorology data from 2,522 USDA CLIGEN stations within the conterminous United States were disaggregated to an hourly time-step using the physics-based approach of Waichler and Wigmosta (2003), yielding a high-temporal resolution 30-year meteorological record. Secondly, in order to best describe the meteorological model forcings for a given site and significantly increase modeling efficiency, we developed a novel multi-scale pattern
Linearized Functional Minimization for Inverse Modeling
Energy Technology Data Exchange (ETDEWEB)
Wohlberg, Brendt [Los Alamos National Laboratory; Tartakovsky, Daniel M. [University of California, San Diego; Dentz, Marco [Institute of Environmental Assessment and Water Research, Barcelona, Spain
2012-06-21
Heterogeneous aquifers typically consist of multiple lithofacies, whose spatial arrangement significantly affects flow and transport. The estimation of these lithofacies is complicated by the scarcity of data and by the lack of a clear correlation between identifiable geologic indicators and attributes. We introduce a new inverse-modeling approach to estimate both the spatial extent of hydrofacies and their properties from sparse measurements of hydraulic conductivity and hydraulic head. Our approach is to minimize a functional defined on the vectors of values of hydraulic conductivity and hydraulic head fields defined on regular grids at a user-determined resolution. This functional is constructed to (i) enforce the relationship between conductivity and heads provided by the groundwater flow equation, (ii) penalize deviations of the reconstructed fields from measurements where they are available, and (iii) penalize reconstructed fields that are not piece-wise smooth. We develop an iterative solver for this functional that exploits a local linearization of the mapping from conductivity to head. This approach provides a computationally efficient algorithm that rapidly converges to a solution. A series of numerical experiments demonstrates the robustness of our approach.
Soft leptogenesis in the inverse seesaw model
Garayoa, J; Rius, N
2007-01-01
We consider leptogenesis induced by soft supersymmetry breaking terms ("soft leptogenesis"), in the context of the inverse seesaw mechanism. In this model there are lepton number (L) conserving and L-violating soft supersymmetry-breaking B-terms involving the singlet sneutrinos which, together with the -- generically small-- L-violating parameter responsible of the neutrino mass, give a small mass splitting between the four singlet sneutrino states of a single generation. In combination with the trilinear soft supersymmetry breaking terms they also provide new CP violating phases needed to generate a lepton asymmetry in the singlet sneutrino decays. We obtain that in this scenario the lepton asymmetry is proportional to the L-conserving soft supersymmetry-breaking B-term, and it is not suppressed by the L-violating parameters. Consequently we find that, as in the standard see-saw case, this mechanism can lead to sucessful leptogenesis only for relatively small value of the relevant soft bilinear coupling. The...
CICAAR - Convolutive ICA with an Auto-Regressive Inverse Model
DEFF Research Database (Denmark)
Dyrholm, Mads; Hansen, Lars Kai
2004-01-01
We invoke an auto-regressive IIR inverse model for convolutive ICA and derive expressions for the likelihood and its gradient. We argue that optimization will give a stable inverse. When there are more sensors than sources the mixing model parameters are estimated in a second step by least squares...
Inverse Modelling Problems in Linear Algebra Undergraduate Courses
Martinez-Luaces, Victor E.
2013-01-01
This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
Inverse Modelling Problems in Linear Algebra Undergraduate Courses
Martinez-Luaces, Victor E.
2013-01-01
This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
Investigating Irregularly Patterned Deep Brain Stimulation Signal Design Using Biophysical Models
Directory of Open Access Journals (Sweden)
Samantha Rose Summerson
2015-06-01
Full Text Available Parkinson’s disease (PD is a neurodegenerative disorder which follows from cell loss of dopaminergic neurons in the substantia nigra pars compacta (SNc, a nucleus in the basal ganglia (BG. Deep brain stimulation (DBS is an electrical therapy that modulates the pathological activity to treat the motor symptoms of PD. Although this therapy is currently used in clinical practice, the sufficient conditions for therapeutic efficacy are unknown. In this work we develop a model of critical motor circuit structures in the brain using biophysical cell models as the base components and then evaluate performance of different DBS signals in this model to perform comparative studies of their efficacy. Biological models are an important tool for gaining insights into neural function and, in this case, serve as effective tools for investigating innovative new DBS paradigms. Experiments were performed using the hemi-parkinsonian rodent model to test the same set of signals, verifying the obedience of the model to physiological trends. We show that antidromic spiking from DBS of the subthalamic nucleus (STN has a significant impact on cortical neural activity, which is frequency dependent and additionally modulated by the regularity of the stimulus pulse train used. Irregular spacing between stimulus pulses, where the amount of variability added is bounded, is shown to increase diversification of response of basal ganglia neurons and reduce entropic noise in cortical neurons, which may be fundamentally important to restoration of information flow in the motor circuit.
Thermal Manikins & Clothing Biophysics Laboratories
Federal Laboratory Consortium — Five biophysical evaluation chambers containing fully sensored, articulated, moveable copper manikins, and other metallic models of feet and hands are available for...
Thermal Manikins & Clothing Biophysics Laboratories
Federal Laboratory Consortium — Five biophysical evaluation chambers containing fully sensored, articulated, moveable copper manikins, and other metallic models of feet and hands are available for...
Hati, Sanchita; Bhattacharyya, Sudeep
2016-01-01
A project-based biophysical chemistry laboratory course, which is offered to the biochemistry and molecular biology majors in their senior year, is described. In this course, the classroom study of the structure-function of biomolecules is integrated with the discovery-guided laboratory study of these molecules using computer modeling and…
A Biophysically Based Mathematical Model for the Kinetics of Mitochondrial Na+-Ca2+ Antiporter
Pradhan, Ranjan K.; Beard, Daniel A.; Dash, Ranjan K.
2010-01-01
Sodium-calcium antiporter is the primary efflux pathway for Ca2+ in respiring mitochondria, and hence plays an important role in mitochondrial Ca2+ homeostasis. Although experimental data on the kinetics of Na+-Ca2+ antiporter are available, the structure and composition of its functional unit and kinetic mechanisms associated with the Na+-Ca2+ exchange (including the stoichiometry) remains unclear. To gain a quantitative understanding of mitochondrial Ca2+ homeostasis, a biophysical model of Na+-Ca2+ antiporter is introduced that is thermodynamically balanced and satisfactorily describes a number of independent data sets under a variety of experimental conditions. The model is based on a multistate catalytic binding mechanism for carrier-mediated facilitated transport and Eyring's free energy barrier theory for interconversion and electrodiffusion. The model predicts the activating effect of membrane potential on the antiporter function for a 3Na+:1Ca2+ electrogenic exchange as well as the inhibitory effects of both high and low pH seen experimentally. The model is useful for further development of mechanistic integrated models of mitochondrial Ca2+ handling and bioenergetics to understand the mechanisms by which Ca2+ plays a role in mitochondrial signaling pathways and energy metabolism. PMID:20338843
A biophysical model of S. aurita early life history in the northern Gulf of Guinea
Koné, Vamara; Lett, Christophe; Penven, Pierrick; Bourlès, Bernard; Djakouré, Sandrine
2017-02-01
S. aurita is the most abundant small pelagic fish in the northern Gulf of Guinea. Its reproduction and recruitment depend crucially on environmental conditions. We developed a biophysical model of S. aurita early life history by coupling offline an individual-based model with the regional oceanic modeling system (ROMS). We used this model to investigate the main factors driving variability in eggs and larval dispersal and survival in the northern Gulf of Guinea. Precisely, individuals were released from different spawning areas along the coast and tracked for a period of 28 days corresponding to their planktonic phase. Individuals that remained in the coastal recruitment areas at an age more than 7 days, at which they can supposedly actively retain themselves in a favorable area, were considered as recruited. Simulation results show the importance of the spawning areas around Cape Palmas and Cape Three Points where cyclonic eddies trap eggs and larvae along the coast, preventing their advection offshore by the Guinea Current. The spawning period also plays a key role in the recruitment success, with highest coastal retention obtained during the major upwelling period (July-September). We find that a second retention peak can occur during the minor upwelling period (February-March) when larval mortality due to temperature is included in the model. These results are in general agreement with knowledge of S. aurita reproduction in the northern Gulf of Guinea.
Devaraju, N; Bala, G; Nemani, R
2015-09-01
Land-use changes since the start of the industrial era account for nearly one-third of the cumulative anthropogenic CO2 emissions. In addition to the greenhouse effect of CO2 emissions, changes in land use also affect climate via changes in surface physical properties such as albedo, evapotranspiration and roughness length. Recent modelling studies suggest that these biophysical components may be comparable with biochemical effects. In regard to climate change, the effects of these two distinct processes may counterbalance one another both regionally and, possibly, globally. In this article, through hypothetical large-scale deforestation simulations using a global climate model, we contrast the implications of afforestation on ameliorating or enhancing anthropogenic contributions from previously converted (agricultural) land surfaces. Based on our review of past studies on this subject, we conclude that the sum of both biophysical and biochemical effects should be assessed when large-scale afforestation is used for countering global warming, and the net effect on global mean temperature change depends on the location of deforestation/afforestation. Further, although biochemical effects trigger global climate change, biophysical effects often cause strong local and regional climate change. The implication of the biophysical effects for adaptation and mitigation of climate change in agriculture and agroforestry sectors is discussed.
Hartwigsen, Gesa; Bergmann, Til Ole; Herz, Damian Marc; Angstmann, Steffen; Karabanov, Anke; Raffin, Estelle; Thielscher, Axel; Siebner, Hartwig Roman
2015-01-01
Noninvasive transcranial brain stimulation (NTBS) is widely used to elucidate the contribution of different brain regions to various cognitive functions. Here we present three modeling approaches that are informed by functional or structural brain mapping or behavior profiling and discuss how these approaches advance the scientific potential of NTBS as an interventional tool in cognitive neuroscience. (i) Leveraging the anatomical information provided by structural imaging, the electric field distribution in the brain can be modeled and simulated. Biophysical modeling approaches generate testable predictions regarding the impact of interindividual variations in cortical anatomy on the injected electric fields or the influence of the orientation of current flow on the physiological stimulation effects. (ii) Functional brain mapping of the spatiotemporal neural dynamics during cognitive tasks can be used to construct causal network models. These models can identify spatiotemporal changes in effective connectivity during distinct cognitive states and allow for examining how effective connectivity is shaped by NTBS. (iii) Modeling the NTBS effects based on neuroimaging can be complemented by behavior-based cognitive models that exploit variations in task performance. For instance, NTBS-induced changes in response speed and accuracy can be explicitly modeled in a cognitive framework accounting for the speed-accuracy trade-off. This enables to dissociate between behavioral NTBS effects that emerge in the context of rapid automatic responses or in the context of slow deliberate responses. We argue that these complementary modeling approaches facilitate the use of NTBS as a means of dissecting the causal architecture of cognitive systems of the human brain.
Cervera, Javier; Alcaraz, Antonio; Mafe, Salvador
2016-02-04
Bioelectrical signals and ion channels are central to spatial patterns in cell ensembles, a problem of fundamental interest in positional information and cancer processes. We propose a model for electrically connected cells based on simple biological concepts: i) the membrane potential of a single cell characterizes its electrical state; ii) the long-range electrical coupling of the multicellular ensemble is realized by a network of gap junction channels between neighboring cells; and iii) the spatial distribution of an external biochemical agent can modify the conductances of the ion channels in a cell membrane and the multicellular electrical state. We focus on electrical effects in small multicellular ensembles, ignoring slow diffusional processes. The spatio-temporal patterns obtained for the local map of cell electric potentials illustrate the normalization of regions with abnormal cell electrical states. The effects of intercellular coupling and blocking of specific channels on the electrical patterns are described. These patterns can regulate the electrically-induced redistribution of charged nanoparticles over small regions of a model tissue. The inclusion of bioelectrical signals provides new insights for the modeling of cancer biophysics because collective multicellular states show electrical coupling mechanisms that are not readily deduced from biochemical descriptions at the individual cell level.
An estimate of the dispersion of repolarization times based on a biophysical model of the ECG.
Sassi, Roberto; Mainardi, Luca T
2011-12-01
Temporal heterogeneity of ventricular repolarization is a key quantity for the development of ventricular reentrant arrhythmia. In this paper, we introduce the V-index, a novel ECG-based estimator of the standard deviation of ventricular myocytes' repolarization times s(ϑ). Differently from other ECG metrics of repolarization heterogeneity, the V-index was derived from the analysis of a biophysical model of the ECG, where repolarization is described by the dominant T-wave (DTW) paradigm. The model explains the shape of T-waves in each lead as a projection of a main waveform (the DTW) and its derivatives weighted by scalars, the lead factors. A mathematical formula is derived to link the heterogeneity of ventricular repolarization s(ϑ) and the V-index. The formula was verified using synthetic 12-lead ECGs generated with a direct electrophysiological model for increasing values of s(ϑ) (in the range 20-70 ms). A linear relationship between the V-index and s(ϑ) was observed, V ≈ 0.675 s(ϑ) + 1.8 ms (R(2) = 0.9992). Finally, 68 ECGs from the E-OTH-12-0068-010 database of the Telemetric and Holter ECG Warehouse were analyzed. The V-index coherently increased after sotalol administration, a drug known to have QT-prolonging potential (p < 0.001).
Chromosome aberrations and cell death by ionizing radiation: Evolution of a biophysical model
Ballarini, Francesca; Carante, Mario P.
2016-11-01
The manuscript summarizes and discusses the various versions of a radiation damage biophysical model, implemented as a Monte Carlo simulation code, originally developed for chromosome aberrations and subsequently extended to cell death. This extended version has been called BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations). According to the basic assumptions, complex double-strand breaks (called ;Cluster Lesions;, or CLs) produce independent chromosome free-ends, mis-rejoining within a threshold distance d (or un-rejoining) leads to chromosome aberrations, and ;lethal aberrations; (i.e., dicentrics plus rings plus large deletions) lead to clonogenic cell death. The mean number of CLs per Gy and per cell is an adjustable parameter. While in BIANCA the threshold distance d was the second parameter, in a subsequent version, called BIANCA II, d has been fixed as the mean distance between two adjacent interphase chromosome territories, and a new parameter, f, has been introduced to represent the chromosome free-end un-rejoining probability. Simulated dose-response curves for chromosome aberrations and cell survival obtained by the various model versions were compared with literature experimental data. Such comparisons provided indications on some open questions, including the role of energy deposition clustering at the nm and the μm level, the probability for a chromosome free-end to remain un-rejoined, and the relationship between chromosome aberrations and cell death. Although both BIANCA and BIANCA II provided cell survival curves in general agreement with human and hamster fibroblast survival data, BIANCA II allowed for a better reproduction of dicentrics, rings and deletions considered separately. Furthermore, the approach adopted in BIANCA II for d is more consistent with estimates reported in the literature. After testing against aberration and survival data, BIANCA II was applied to investigate the depth-dependence of the radiation
Biophysical modelling of early and delayed radiation damage at chromosome level
Andreev, S.; Eidelman, Y.
Exposure by ionising radiation increases cancer risk in human population Cancer is thought to originate from an altered expression of certain number of specific genes It is now widely recognised that chromosome aberrations CA are involved in stable change in expression of genes by gain or loss of their functions Thus CA can contribute to initiation or progression of cancer Therefore understanding mechanisms of CA formation in the course of cancer development might be valuable tool for quantification and prognosis of different stages of radiation carcinogenesis Early CA are defined as aberrations induced in first post-irradiation mitotic cycle The present work describes the original biophysical technique for early CA modelling It includes the following simulation steps the ionising particle track structure the structural organisation of all chromosomes in G 0 G 1 cell nucleus spatial distribution of radiation induced DNA double-strand breaks dsb within chromosomes dsb rejoining and misrejoining modelling cell cycle taking into account mitotic delay which results in complex time dependence of aberrant cells in first mitosis The results on prediction of dose-response curves for simple and complex CA measured in cells undergoing first division cycle are presented in comparison with recent experimental data There is increasing evidence that CA are also observed in descendents of irradiated cells many generations after direct DNA damage These delayed CA or chromosome instability CI are thought to be a manifestation of genome
Dawson, Michael N; Sen Gupta, Alex; England, Matthew H
2005-08-23
The anthropogenic introduction of exotic species is one of the greatest modern threats to marine biodiversity. Yet exotic species introductions remain difficult to predict and are easily misunderstood because knowledge of natural dispersal patterns, species diversity, and biogeography is often insufficient to distinguish between a broadly dispersed natural population and an exotic one. Here we compare a global molecular phylogeny of a representative marine meroplanktonic taxon, the moon-jellyfish Aurelia, with natural dispersion patterns predicted by a global biophysical ocean model. Despite assumed high dispersal ability, the phylogeny reveals many cryptic species and predominantly regional structure with one notable exception: the globally distributed Aurelia sp.1, which, molecular data suggest, may occasionally traverse the Pacific unaided. This possibility is refuted by the ocean model, which shows much more limited dispersion and patterns of distribution broadly consistent with modern biogeographic zones, thus identifying multiple introductions worldwide of this cryptogenic species. This approach also supports existing evidence that (i) the occurrence in Hawaii of Aurelia sp. 4 and other native Indo-West Pacific species with similar life histories is most likely due to anthropogenic translocation, and (ii) there may be a route for rare natural colonization of northeast North America by the European marine snail Littorina littorea, whose status as endemic or exotic is unclear.
A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition.
Directory of Open Access Journals (Sweden)
Margarita Zachariou
Full Text Available Memories are believed to be represented in the synaptic pathways of vastly interconnected networks of neurons. The plasticity of synapses, that is, their strengthening and weakening depending on neuronal activity, is believed to be the basis of learning and establishing memories. An increasing number of studies indicate that endocannabinoids have a widespread action on brain function through modulation of synaptic transmission and plasticity. Recent experimental studies have characterised the role of endocannabinoids in mediating both short- and long-term synaptic plasticity in various brain regions including the hippocampus, a brain region strongly associated with cognitive functions, such as learning and memory. Here, we present a biophysically plausible model of cannabinoid retrograde signalling at the synaptic level and investigate how this signalling mediates depolarisation induced suppression of inhibition (DSI, a prominent form of short-term synaptic depression in inhibitory transmission in hippocampus. The model successfully captures many of the key characteristics of DSI in the hippocampus, as observed experimentally, with a minimal yet sufficient mathematical description of the major signalling molecules and cascades involved. More specifically, this model serves as a framework to test hypotheses on the factors determining the variability of DSI and investigate under which conditions it can be evoked. The model reveals the frequency and duration bands in which the post-synaptic cell can be sufficiently stimulated to elicit DSI. Moreover, the model provides key insights on how the state of the inhibitory cell modulates DSI according to its firing rate and relative timing to the post-synaptic activation. Thus, it provides concrete suggestions to further investigate experimentally how DSI modulates and is modulated by neuronal activity in the brain. Importantly, this model serves as a stepping stone for future deciphering of the role of
Mathematical model of MMR inversion for geophysical data
Directory of Open Access Journals (Sweden)
Suabsagun Yooyuanyong
2007-09-01
Full Text Available In this paper, we present an analysis of the solution to a number of geophysical inverse problems which are generally non-unique. The mathematical inverse problem that arises is commonly ill-posed in the sense that small changes in the data lead to large changes in the solution. We conduct the inversion algorithm to explore the conductivity for the ground structure. The algorithm uses the data in the form of magnetic field measurements for magnetometric resistivity (MMR. The inversion example is performed to investigate the conductivity ground profile that best fits the observed data. The result is compared with the true model and discussed to show the efficiency of the method. The model for the inversion example with the apparent conductivity and the true conductivity are plotted to show the convergence of the algorithm.
A simple biophysically plausible model for long time constants in single neurons.
Tiganj, Zoran; Hasselmo, Michael E; Howard, Marc W
2015-01-01
Recent work in computational neuroscience and cognitive psychology suggests that a set of cells that decay exponentially could be used to support memory for the time at which events took place. Analytically and through simulations on a biophysical model of an individual neuron, we demonstrate that exponentially decaying firing with a range of time constants up to minutes could be implemented using a simple combination of well-known neural mechanisms. In particular, we consider firing supported by calcium-controlled cation current. When the amount of calcium leaving the cell during an interspike interval is larger than the calcium influx during a spike, the overall decay in calcium concentration can be exponential, resulting in exponential decay of the firing rate. The time constant of the decay can be several orders of magnitude larger than the time constant of calcium clearance, and it could be controlled externally via a variety of biologically plausible ways. The ability to flexibly and rapidly control time constants could enable working memory of temporal history to be generalized to other variables in computing spatial and ordinal representations.
Forward and inverse modelling of post-seismic deformation
Crawford, Ophelia; Al-Attar, David; Tromp, Jeroen; Mitrovica, Jerry X.
2016-11-01
We consider a new approach to both the forward and inverse problems in post-seismic deformation. We present a method for forward modelling post-seismic deformation in a self-gravitating, heterogeneous and compressible earth with a variety of linear and non-linear rheologies. We further demonstrate how the adjoint method can be applied to the inverse problem both to invert for rheological structure and to calculate the sensitivity of a given surface measurement to changes in rheology or time-dependence of the source. Both the forward and inverse aspects are illustrated with several numerical examples implemented in a spherically symmetric earth model.
Forward and inverse modelling of post-seismic deformation
Crawford, Ophelia; Al-Attar, David; Tromp, Jeroen; Mitrovica, Jerry X.
2017-02-01
We consider a new approach to both the forward and inverse problems in post-seismic deformation. We present a method for forward modelling post-seismic deformation in a self-gravitating, heterogeneous and compressible earth with a variety of linear and nonlinear rheologies. We further demonstrate how the adjoint method can be applied to the inverse problem both to invert for rheological structure and to calculate the sensitivity of a given surface measurement to changes in rheology or time-dependence of the source. Both the forward and inverse aspects are illustrated with several numerical examples implemented in a spherically symmetric earth model.
Modeling and inverse problems in the presence of uncertainty
Banks, H T; Thompson, W Clayton
2014-01-01
Modeling and Inverse Problems in the Presence of Uncertainty collects recent research-including the authors' own substantial projects-on uncertainty propagation and quantification. It covers two sources of uncertainty: where uncertainty is present primarily due to measurement errors and where uncertainty is present due to the modeling formulation itself. After a useful review of relevant probability and statistical concepts, the book summarizes mathematical and statistical aspects of inverse problem methodology, including ordinary, weighted, and generalized least-squares formulations. It then
Baby, André R.; Lacerda, Áurea C. L.; Prestes, Paula S.; Velasco, María Valéria R.; Kawano, Yoshio; Kaneko,Telma Mary
2011-01-01
The influence of the nonionic surfactant lauryl alcohol ethoxylate with 12 moles ethylene oxide (LAE-12OE) was evaluated on the Stratum corneum model biomembrane (SCMM) of shed snake skin (Bothrops jararaca and Spilotes pullatus) through the biophysical techniques Fourier transform Raman spectroscopy (FT-Raman) and Fourier transform infrared photoacoustic spectroscopy (PAS-FTIR). The surfactant was used in aqueous solutions above and below the critical micelle concentration (cmc), 50.0 and 0....
Roemer, R B; Booth, D; Bhavsar, A A; Walter, G H; Terry, L I
2012-12-21
A mathematical model based on conservation of energy has been developed and used to simulate the temperature responses of cones of the Australian cycads Macrozamia lucida and Macrozamia. macleayi during their daily thermogenic cycle. These cones generate diel midday thermogenic temperature increases as large as 12 °C above ambient during their approximately two week pollination period. The cone temperature response model is shown to accurately predict the cones' temperatures over multiple days as based on simulations of experimental results from 28 thermogenic events from 3 different cones, each simulated for either 9 or 10 sequential days. The verified model is then used as the foundation of a new, parameter estimation based technique (termed inverse calorimetry) that estimates the cones' daily metabolic heating rates from temperature measurements alone. The inverse calorimetry technique's predictions of the major features of the cones' thermogenic metabolism compare favorably with the estimates from conventional respirometry (indirect calorimetry). Because the new technique uses only temperature measurements, and does not require measurements of oxygen consumption, it provides a simple, inexpensive and portable complement to conventional respirometry for estimating metabolic heating rates. It thus provides an additional tool to facilitate field and laboratory investigations of the bio-physics of thermogenic plants. Copyright © 2012 Elsevier Ltd. All rights reserved.
Modeling temperature inversion in southeastern Yellow Sea during winter 2016
Pang, Ig-Chan; Moon, Jae-Hong; Lee, Joon-Ho; Hong, Ji-Seok; Pang, Sung-Jun
2017-05-01
A significant temperature inversion with temperature differences larger than 3°C was observed in the southeastern Yellow Sea (YS) during February 2016. By analyzing in situ hydrographic profiles and results from a regional ocean model for the YS, this study examines the spatiotemporal evolution of the temperature inversion and its connection with wind-induced currents in winter. Observations reveal that in winter, when the northwesterly wind prevails over the YS, the temperature inversion occurs largely at the frontal zone southwest of Korea where warm/saline water of a Kuroshio origin meets cold/fresh coastal water. Our model successfully captures the temperature inversion observed in the winter of 2016 and suggests a close relation between northwesterly wind bursts and the occurrence of the large inversion. In this respect, the strong northwesterly wind drove cold coastal water southward in the upper layer via Ekman transport, which pushed the water mass southward and increased the sea level slope in the frontal zone in southeastern YS. The intensified sea level slope propagated northward away from the frontal zone as a shelf wave, causing a northward upwind flow response along the YS trough in the lower layer, thereby resulting in the large temperature inversion. Diagnostic analysis of the momentum balance shows that the westward pressure gradient, which developed with shelf wave propagation along the YS trough, was balanced with the Coriolis force in accordance with the northward upwind current in and around the inversion area.
A model realizing inverse seesaw and resonant leptogenesis
Aoki, Mayumi; Takahashi, Ryo
2015-01-01
We construct a model realizing the inverse seesaw mechanism. The model has two types of gauge singlet fermions in addition to right-handed neutrinos. A required Majorana mass scale (keV scale) for generating the light active neutrino mass in the conventional inverse seesaw can be naturally explained by a "seesaw" mechanism between the two singlet fermions in our model. We find that our model can decrease the magnitude of hierarchy among mass parameters by $\\mathcal{O}(10^4)$ from that in the conventional inverse seesaw model. We also show that a successful resonant leptogenesis occurs for generating the baryon asymmetry of the universe in our model. The desired mass degeneracy for the resonant leptogenesis can also be achieved by the "seesaw" between the two singlet fermions.
The Impact of Forest Density on Forest Height Inversion Modeling from Polarimetric InSAR Data
Directory of Open Access Journals (Sweden)
Changcheng Wang
2016-03-01
Full Text Available Forest height is of great significance in analyzing the carbon cycle on a global or a local scale and in reconstructing the accurate forest underlying terrain. Major algorithms for estimating forest height, such as the three-stage inversion process, are depending on the random-volume-over-ground (RVoG model. However, the RVoG model is characterized by a lot of parameters, which influence its applicability in forest height retrieval. Forest density, as an important biophysical parameter, is one of those main influencing factors. However, its influence to the RVoG model has been ignored in relating researches. For this paper, we study the applicability of the RVoG model in forest height retrieval with different forest densities, using the simulated and real Polarimetric Interferometric SAR data. P-band ESAR datasets of the European Space Agency (ESA BioSAR 2008 campaign were selected for experiments. The test site was located in Krycklan River catchment in Northern Sweden. The experimental results show that the forest density clearly affects the inversion accuracy of forest height and ground phase. For the four selected forest stands, with the density increasing from 633 to 1827 stems/Ha, the RMSEs of inversion decrease from 4.6 m to 3.1 m. The RVoG model is not quite applicable for forest height retrieval especially in sparsely vegetated areas. We conclude that the forest stand density is positively related to the estimation accuracy of the ground phase, but negatively correlates to the ground-to-volume scattering ratio.
Underground water quality model inversion of genetic algorithm
Institute of Scientific and Technical Information of China (English)
MA Ruijie; LI Xin
2009-01-01
The underground water quality model with non-linear inversion problem is ill-posed, and boils down to solving the minimum of nonlinear function. Genetic algorithms are adopted in a number of individuals of groups by iterative search to find the optimal solution of the problem, the encoding strings as its operational objective, and achieving the iterative calculations by the genetic operators. It is an effective method of inverse problems of groundwater, with incomparable advantages and practical significances.
Inverse Kinematic Analysis of Human Hand Thumb Model
Toth-Tascau, Mirela; Pater, Flavius; Stoia, Dan Ioan; Menyhardt, Karoly; Rosu, Serban; Rusu, Lucian; Vigaru, Cosmina
2011-09-01
This paper deals with a kinematic model of the thumb of the human hand. The proposed model has 3 degrees of freedom being able to model the movements of the thumb tip with respect to the wrist joint centre. The kinematic equations are derived based on Denavit-Hartenberg Convention and solved in both direct and inverse way. Inverse kinematic analysis of human hand thumb model reveals multiple and connected solutions which are characteristic to nonlinear systems when the number of equations is greater than number of unknowns and correspond to natural movements of the finger.
Nonlinear inversion for arbitrarily-oriented anisotropic models II: Inversion techniques
Bremner, P. M.; Panning, M. P.
2011-12-01
We present output models from inversion of a synthetic surface wave dataset. We implement new 3-D finite-frequency kernels, based on the Born approximation, to invert for upper mantle structure beneath western North America. The kernels are formulated based on a hexagonal symmetry with an arbitrary orientation. Numerical tests were performed to achieve a robust inversion scheme. Four synthetic input models were created, to include: isotropic, constant strength anisotropic, variable strength anisotropic, and both anisotropic and isotropic together. The reference model was a simplified version of PREM (dubbed PREM LIGHT) in which the crust and 220 km discontinuity have been removed. Output models from inversions of calculated synthetic data are compared against these input models to test for accurate reproduction of input model features, and the resolution of those features. The object of this phase of the study was to determine appropriate nonlinear inversion schemes that adequately recover the input models. The synthetic dataset consists of collected seismic waveforms of 126 earthquake mechanisms, of magnitude 6-7 from Dec 2006 to Feb 2009, from the IRIS database. Events were selected to correlate with USArray deployments, and to have as complete an azimuthal coverage as possible. The events occurred within a circular region of radius 150o centered about 44o lat, -110o lon (an arbitrary location within USArray coverage). Synthetic data were calculated utilizing a spectral element code (SEM) coupled to a normal mode solution. The mesh consists of a 3-D heterogeneous outer shell, representing the upper mantle above 450 km depth, coupled to a spherically symmetric inner sphere. From the synthetic dataset, multi-taper fundamental mode surface wave phase delay measurements are taken. The orthogonal 2.5π -prolate spheroidal wave function eigentapers (Slepian tapers) reduce noise biasing, and can provide error estimates in phase delay measurements. This study is a
Duveiller, Gregory; Forzieri, Giovanni; Robertson, Eddy; Georgievski, Goran; Li, Wei; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro
2017-04-01
Changes in vegetation cover can affect the climate by altering the carbon, water and energy cycles. The main tools to characterize such land-climate interactions for both the past and future are land surface models (LSMs) that can be embedded in larger Earth System models (ESMs). While such models have long been used to characterize the biogeochemical effects of vegetation cover change, their capacity to model biophysical effects accurately across the globe remains unclear due to the complexity of the phenomena. The result of competing biophysical processes on the surface energy balance varies spatially and seasonally, and can lead to warming or cooling depending on the specific vegetation change and on the background climate (e.g. presence of snow or soil moisture). Here we present a global scale benchmarking exercise of four of the most commonly used LSMs (JULES, ORCHIDEE, JSBACH and CLM) against a dedicated dataset of satellite observations. To facilitate the understanding of the causes that lead to discrepancies between simulated and observed data, we focus on pure transitions amongst major plant functional types (PFTs): from different tree types (evergreen broadleaf trees, deciduous broadleaf trees and needleleaf trees) to either grasslands or crops. From the modelling perspective, this entails generating a separate simulation for each PFT in which all 1° by 1° grid cells are uniformly covered with that PFT, and then analysing the differences amongst them in terms of resulting biophysical variables (e.g net radiation, latent and sensible heat). From the satellite perspective, the effect of pure transitions is obtained by unmixing the signal of different 0.05° spatial resolution MODIS products (albedo, latent heat, upwelling longwave radiation) over a local moving window using PFT maps derived from the ESA Climate Change Initiative land cover map. After aggregating to a common spatial support, the observation and model-driven datasets are confronted and
Duarte, Jorge; Januário, Cristina; Martins, Nuno
2009-06-01
Bursting activity is an interesting feature of the temporal organization in many cell firing patterns. This complex behavior is characterized by clusters of spikes (action potentials) interspersed with phases of quiescence. As shown in experimental recordings, concerning the electrical activity of real neurons, the analysis of bursting models reveals not only patterned periodic activity but also irregular behavior 1,2]. The interpretation of experimental results, particularly the study of the influence of coupling on chaotic bursting oscillations, is of great interest from physiological and physical perspectives. The inability to predict the behavior of dynamical systems in presence of chaos suggests the application of chaos control methods, when we are more interested in obtaining regular behavior. In the present article, we focus our attention on a specific class of biophysically motivated maps, proposed in the literature to describe the chaotic activity of spiking-bursting cells [Cazelles B, Courbage M, Rabinovich M. Anti-phase regularization of coupled chaotic maps modelling bursting neurons. Europhys Lett 2001;56:504-9]. More precisely, we study a map that reproduces the behavior of a single cell and a map used to examine the role of reciprocal inhibitory coupling, specially on two symmetrically coupled bursting neurons. Firstly, using results of symbolic dynamics, we characterize the topological entropy associated to the maps, which allows us to quantify and to distinguish different chaotic regimes. In particular, we exhibit numerical results about the effect of the coupling strength on the variation of the topological entropy. Finally, we show that complicated behavior arising from the chaotic coupled maps can be controlled, without changing of its original properties, and turned into a desired attracting time periodic motion (a regular cycle). The control is illustrated by an application of a feedback control technique developed by Romeiras et al. [Romeiras
Research of inverse mathematical model to high-speed trains
Institute of Scientific and Technical Information of China (English)
朱涛; 肖守讷; 马卫华; 阳光武
2014-01-01
Operation safety and stability of the train mainly depend on the interaction between the wheel and rail. Knowledge of wheel/rail contact force is important for vehicle control systems that aim to enhance vehicle stability and passenger safety. Since wheel/rail contact forces of high-speed train are very difficult to measure directly, a new estimation process for wheel/rail contact forces was introduced in this work. Based on the state space equation, dynamic programming methods and the Bellman principle of optimality, the main theoretical derivation of the inversion mathematical model was given. The new method overcomes the weakness of large fluctuations which exist in current inverse techniques. High-speed vehicle was chosen as the research object, accelerations of axle box as input conditions, 10 degrees of freedom vertical vibration model and 17 degrees of freedom lateral vibration model were established, respectively. Under 250 km/h, the vertical and lateral wheel/rail forces were identified. From the time domain and frequency domain, the comparison of the results between inverse and SIMPACK models were given. The results show that the inverse mathematical model has high precision for inversing the wheel/rail contact forces of an operation high-speed vehicle.
Parameterization of geophysical inversion model using particle clustering
Yang, Dikun
2015-01-01
This paper presents a new method of constructing physical models in a geophysical inverse problem, when there are only a few possible physical property values in the model and they are reasonably known but the geometry of the target is sought. The model consists of a fixed background and many small "particles" as building blocks that float around in the background to resemble the target by clustering. This approach contrasts the conventional geometric inversions requiring the target to be regularly shaped bodies, since here the geometry of the target can be arbitrary and does not need to be known beforehand. Because of the lack of resolution in the data, the particles may not necessarily cluster when recovering compact targets. A model norm, called distribution norm, is introduced to quantify the spread of particles and incorporated into the objective function to encourage further clustering of the particles. As proof of concept, 1D magnetotelluric inversion is used as example. My experiments reveal that the ...
Henderson, Laura S.; Subbarao, Kamesh
2016-12-01
This work presents a case wherein the selection of models when producing synthetic light curves affects the estimation of the size of unresolved space objects. Through this case, "inverse crime" (using the same model for the generation of synthetic data and data inversion), is illustrated. This is done by using two models to produce the synthetic light curve and later invert it. It is shown here that the choice of model indeed affects the estimation of the shape/size parameters. When a higher fidelity model (henceforth the one that results in the smallest error residuals after the crime is committed) is used to both create, and invert the light curve model the estimates of the shape/size parameters are significantly better than those obtained when a lower fidelity model (in comparison) is implemented for the estimation. It is therefore of utmost importance to consider the choice of models when producing synthetic data, which later will be inverted, as the results might be misleadingly optimistic.
Why operational risk modelling creates inverse incentives
Doff, R.
2015-01-01
Operational risk modelling has become commonplace in large international banks and is gaining popularity in the insurance industry as well. This is partly due to financial regulation (Basel II, Solvency II). This article argues that operational risk modelling is fundamentally flawed, despite efforts
Multi-scattering inversion for low model wavenumbers
Alkhalifah, Tariq Ali
2015-08-19
A successful full wavenumber inversion (FWI) implementation updates the low wavenumber model components first for proper wavefield propagation description, and slowly adds the high-wavenumber potentially scattering parts of the model. The low-wavenumber components can be extracted from the transmission parts of the recorded data given by direct arrivals or the transmission parts of the single and double-scattering wave-fields developed from a predicted scatter field. We develop a combined inversion of data modeled from the source and those corresponding to single and double scattering to update both the velocity model and the component of the velocity (perturbation) responsible for the single and double scattering. The combined inversion helps us access most of the potential model wavenumber information that may be embedded in the data. A scattering angle filter is used to divide the gradient of the combined inversion so initially the high wavenumber (low scattering angle) components of the gradient is directed to the perturbation model and the low wavenumber (high scattering angle) components to the velocity model. As our background velocity matures, the scattering angle divide is slowly lowered to allow for more of the higher wavenumbers to contribute the velocity model.
Inverse modeling of European CH4 emissions 2001–2006
Bergamaschi, P.; Krol, M.C.; Meirink, J.F.; Dentener, F.; Segers, A.; Aardenne, van J.A.; Monni, S.; Vermeulen, A.T.
2010-01-01
European CH4 emissions are estimated for the period 2001–2006 using a fourdimensional variational (4DVAR) inverse modeling system, based on the atmospheric zoom model TM5. Continuous observations are used from various European monitoring stations, complemented by European and global flask samples fr
Data-Driven Model Order Reduction for Bayesian Inverse Problems
Cui, Tiangang
2014-01-06
One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce the computational cost of numerical PDE evaluations in this context.
Fundamental Concepts in Biophysics Volume 1
Jue, Thomas
2009-01-01
HANDBOOK OF MODERN BIOPHYSICS Series Editor Thomas Jue, PhD Handbook of Modern Biophysics brings current biophysics topics into focus, so that biology, medical, engineering, mathematics, and physical-science students or researchers can learn fundamental concepts and the application of new techniques in addressing biomedical challenges. Chapters explicate the conceptual framework of the physics formalism and illustrate the biomedical applications. With the addition of problem sets, guides to further study, and references, the interested reader can continue to explore independently the ideas presented. Volume I: Fundamental Concepts in Biophysics Editor Thomas Jue, PhD In Fundamental Concepts in Biophysics, prominent professors have established a foundation for the study of biophysics related to the following topics: Mathematical Methods in Biophysics Quantum Mechanics Basic to Biophysical Methods Computational Modeling of Receptor–Ligand Binding and Cellular Signaling Processes Fluorescence Spectroscopy Elec...
Inverse kinematics model of parallel macro-micro manipulator system
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
An improved design, which employs the integration of optic, mechanical and electronic technologies for the next generation large radio telescope, is presented in this note. The authors propose the concept of parallel macro-micro manipulator system from the feed support structure with a rough tuning subsystem based on a cable structure and a fine tuning subsystem based on the Stewart platform. According to the requirement of astronomical observation, the inverse kinematics model of this parallel macro-micro manipulator system is deduced. This inverse kinematics model is necessary for the computer-controlled motion of feed.
Inverse distributed hydrological modelling of alpine catchments
Directory of Open Access Journals (Sweden)
H. Kunstmann
2005-12-01
Full Text Available Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions.
WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km^{2} in a 100×100 m^{2} horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m. Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex
Material model calibration through indentation test and stochastic inverse analysis
Buljak, Vladimir
2015-01-01
Indentation test is used with growing popularity for the characterization of various materials on different scales. Developed methods are combining the test with computer simulation and inverse analyses to assess material parameters entering into constitutive models. The outputs of such procedures are expressed as evaluation of sought parameters in deterministic sense, while for engineering practice it is desirable to assess also the uncertainty which affects the final estimates resulting from various sources of errors within the identification procedure. In this paper an experimental-numerical method is presented centered on inverse analysis build upon data collected from the indentation test in the form of force-penetration relationship (so-called indentation curve). Recursive simulations are made computationally economical by an a priori model reduction procedure. Resulting inverse problem is solved in a stochastic context using Monte Carlo simulations and non-sequential Extended Kalman filter. Obtained re...
THE INVERSE PROBLEM OF A REPRODUCTION MODEL OF NATIONAL INCOME
Directory of Open Access Journals (Sweden)
Laipanova Z. M.
2016-02-01
Full Text Available In practice, there were developed and tested some mathematical models of balance relationships (balance model, economic growth, expanding economy, labour market, theories of consumption, production, competitive equilibrium models of the economy in conditions of imperfect competition and others. The basis of these models were based on linear algebra, mathematical analysis, mathematical programming, differential equations, optimization methods, optimal control theory, probability theory, stochastic processes, operations research, game theory, statistical analysis. The inverse problem in various models of mathematical Economics was considered quite rare. These tasks were sufficiently investigated in the study of physical processes. As shown by the analysis of the theoretical and applied studies of economic processes, they represent considerable interest for practice. Therefore, the considered in the study inverse problems of the mathematical model, as it is shown by the already introduced results of other mathematical models, are of considerable interest in applied and theoretical research. In this article, the authors have formulated and investigated an inverse problem for a model of economic growth. For its solution the authors propose to build a system of algebraic equations, using a reproduction model of national income; then, using methods of quadratic programming, to find the best average quadratic estimates of the model parameter
Improved neural network modeling of inverse lens distortion
CSIR Research Space (South Africa)
De Villiers, JP
2011-04-01
Full Text Available Inverse lens distortion modelling allows one to find the pixel in a distorted image which corresponds to a known point in object space, such as may be produced by a RADAR. This paper extends recent work using neural networks as a compromise between...
Inverse neutrino mass hierarchy in a flavour GUT model
Energy Technology Data Exchange (ETDEWEB)
Antusch, Stefan, E-mail: stefan.antusch@unibas.ch [Department of Physics, University of Basel, Klingelbergstr. 82, CH-4056 Basel (Switzerland); Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), Föhringer Ring 6, D-80805 München (Germany); Gross, Christian, E-mail: christian.gross@unibas.ch [Department of Physics, University of Basel, Klingelbergstr. 82, CH-4056 Basel (Switzerland); Maurer, Vinzenz, E-mail: vinzenz.maurer@unibas.ch [Department of Physics, University of Basel, Klingelbergstr. 82, CH-4056 Basel (Switzerland); Sluka, Constantin, E-mail: constantin.sluka@unibas.ch [Department of Physics, University of Basel, Klingelbergstr. 82, CH-4056 Basel (Switzerland)
2014-02-15
We construct a supersymmetric SU(5)×A{sub 4} flavour GUT model in which an inverse neutrino mass hierarchy is realised without fine-tuning of parameters. The model shares some properties with the normal hierarchy model which we presented in (arXiv:1305.6612) – in particular the relation θ{sub 13}{sup PMNS}≃θ{sub C}/√(2). Besides these shared features, there are also important differences, mainly due to the different neutrino sector. These differences not only change the predictions in the lepton sector, but also in the quark sector, and will allow to discriminate between the two models using the results of present and future experiments. From a Markov Chain Monte Carlo fit we find that the inverse hierarchy model is in excellent agreement with the present experimental data.
Inverse neutrino mass hierarchy in a flavour GUT model
Antusch, Stefan; Maurer, Vinzenz; Sluka, Constantin
2014-01-01
We construct a supersymmetric SU(5) x A_4 flavour GUT model in which an inverse neutrino mass hierarchy is realised without fine-tuning of parameters. The model shares some properties with the normal hierarchy model which we presented in arXiv:1305.6612 - in particular the relation theta_13^PMNS = theta_C / sqrt(2). Besides these shared features, there are also important differences, mainly due to the different neutrino sector. These differences not only change the predictions in the lepton sector, but also in the quark sector, and will allow to discriminate between the two models using the results of present and future experiments. From a Markov Chain Monte Carlo fit we find that the inverse hierarchy model is in excellent agreement with the present experimental data.
An evolution equation modeling inversion of tulip flames
Energy Technology Data Exchange (ETDEWEB)
Dold, J.W. [Univ. of Bristol (United Kingdom). School of Mathematics; Joulin, G. [E.N.S.M.A., Poitiers (France). Lab. d`Energetique et de Detonique
1995-02-01
The authors attempt to reduce the number of physical ingredients needed to model the phenomenon of tulip-flame inversion to a bare minimum. This is achieved by synthesizing the nonlinear, first-order Michelson-Sivashinsky (MS) equation with the second order linear dispersion relation of Landau and Darrieus, which adds only one extra term to the MS equation without changing any of its stationary behavior and without changing its dynamics in the limit of small density change when the MS equation is asymptotically valid. However, as demonstrated by spectral numerical solutions, the resulting second-order nonlinear evolution equation is found to describe the inversion of tulip flames in good qualitative agreement with classical experiments on the phenomenon. This shows that the combined influences of front curvature, geometric nonlinearity and hydrodynamic instability (including its second-order, or inertial effects, which are an essential result of vorticity production at the flame front) are sufficient to reproduce the inversion process.
An inverse model for magnetorheological dampers based on a restructured phenomenological model
Qian, Li-Jun; Liu, Bo; Chen, Peng; Bai, Xian-Xu
2016-04-01
Magnetorheological dampers (MRDs), a semi-active actuator based on MR effect, have great potential in vibration/shock control systems. However, it is difficult to establish its inverse model due to its intrinsic strong nonlinear hysteresis behaviors, and sequentially the precise, fast and effective control could not be realized effectively. This paper presents an inverse model for MRDs based on a restructured phenomenological model with incorporation of the "normalization" concept. The proposed inverse model of MRDs is validated by the simulation of the force tracking. The research results indicate that the inverse model could be applied for the damping force control with consideration of the strong nonlinear hysteresis behaviors of the MRDs.
knowledge base model for evaluation of bio-physical tendency of dryland
Institute of Scientific and Technical Information of China (English)
RJANA; MVKHIRE
2004-01-01
The present study aims the evaluation of bio-physical characteristics towards soil-water-vegetation stress and a rule is envisaged to assess the degree of temporal changes. The digital rule for assessment is initialized through the index of land Instability (ILI) where the variance indicates the temporal instability of the pixel i.e., smallest land unit. It is assumed that the biophysical characteristic of land is in command of land-dynamics where there is no change in Land Use/Land Cover (LU&LC). The intensity map on tendency of albedo (IALB) assesses the intensity of soil erosion and water stress whereas intensity map on tendency of NDVI (INDVI) appraises the stress on vegetation. The carry-out study covers a part of semiarid Western India. Primarily remote sensing technique, which carries the digital information of land temporally and spatially, is adopted in this paper. A part of the study area is represented using two sets of IRS IA/1B LISS-I data of March with a decadal time domain 0989-1998) as a test area. It is assumed that the soil-water-vegetation stress is maximum during summer(March-April-May) in any tropical belt and decadal data will stretch the possibilitv of climate as well as man-made activity over the land.
Directory of Open Access Journals (Sweden)
Wolfgang Wagner
2009-11-01
Full Text Available Automated, image based methods for the retrieval of vegetation biophysical and biochemical variables are often hampered by the lack of a priori knowledge about land cover and phenology, which makes the retrieval a highly underdetermined problem. This study addresses this problem by presenting a novel approach, called CRASh, for the concurrent retrieval of leaf area index, leaf chlorophyll content, leaf water content and leaf dry matter content from high resolution solar reflective earth observation data. CRASh, which is based on the inversion of the combined PROSPECT+SAILh radiative transfer model (RTM, explores the benefits of combining semi-empirical and physically based approaches. The approach exploits novel ways to address the underdetermined problem in the context of an automated retrieval from mono-temporal high resolution data. To regularize the inverse problem in the variable domain, RTM inversion is coupled with an automated land cover classification. Model inversion is based on a two step lookup table (LUT approach: First, a range of possible solutions is selected from a previously calculated LUT based on the analogy between measured and simulated reflectance. The final solution is determined from this subset by minimizing the difference between the variables used to simulate the spectra contained in the reduced LUT and a first guess of the solution. This first guess of the variables is derived from predictive semi-empirical relationships between classical vegetation indices and the single variables. Additional spectral regularization is obtained by the use of hyperspectral data. Results show that estimates obtained with CRASh are significantly more accurate than those obtained with a tested conventional RTM inversion and semi-empirical approach. Accuracies obtained in this study are comparable to the results obtained by various authors for better constrained inversions that assume more a priori information. The completely automated
Energy Technology Data Exchange (ETDEWEB)
Flentje, M.; Hensley, F.; Gademann, G.; Wannenmacher, M. (Univ. of Heidelberg (Germany)); Menke, M. (German Cancer Research Center, Heidelberg (Germany))
1993-09-01
A patient series was analyzed retrospectively as an example of whole organ kidney irradiation with an inhomogenous dose distribution to test the validity of biophysical models predicting normal tissue tolerance to radiotherapy. From 1969 to 1984, 142 patients with seminoma were irradiated to the paraaortic region using predominantly rotational techniques which led to variable but partly substantial exposure of the kidneys. Median follow up was 8.2 (2.1-21) years and actuarial 10-year survival (Kaplan-Meier estimate) 82.8%. For all patients 3-dimensional dose distributions were reconstructed and normal tissue complication probabilities for the kidneys were generated from the individual dose volume histograms. To this respect different published biophysical algorithms were introduced in a 3-dimensional-treatment planning system. In seven patients clinically manifest renal impairment was observed (interval 10-84 months). An excellent agreement between predicted and observed effects was seen for two volume-oriented models, whereas complications were overestimated by an algorithm based on critical element assumptions. Should these observations be confirmed and extended to different types of organs corresponding algorithms could easily be integrated into 3-dimensional-treatment planning programs and be used for comparing and judging different plans on a more biologically oriented basis.
Dynamic inverse models in human-cyber-physical systems
Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar
2016-05-01
Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.
Energy Technology Data Exchange (ETDEWEB)
Dobranszky, G.
2005-12-15
Stratigraphic modeling aims at rebuilding the history of the sedimentary basins by simulating the processes of erosion, transport and deposit of sediments using physical models. The objective is to determine the location of the bed-rocks likely to contain the organic matter, the location of the porous rocks that could trap the hydrocarbons during their migration and the location of the impermeable rocks likely to seal the reservoir. The model considered within this thesis is based on a multi-lithological diffusive transport model and applies to large scales of time and space. Due to the complexity of the phenomena and scales considered, none of the model parameters is directly measurable. Therefore it is essential to inverse them. The standard approach, which consists in inverting all the parameters by minimizing a cost function using a gradient method, proved very sensitive to the choice of the parameterization, to the weights given to the various terms of the cost function (hearing on data of very diverse nature) and to the numerical noise. These observations led us to give up this method and to carry out the in-version step by step by decoupling the parameters. This decoupling is not obtained by fixing the parameters but by making several assumptions on the model resulting in a range of reduced but relevant models. In this thesis, we show how these models enable us to inverse all the parameters in a robust and interactive way. (author)
Theoretical Molecular Biophysics
Scherer, Philipp
2010-01-01
"Theoretical Molecular Biophysics" is an advanced study book for students, shortly before or after completing undergraduate studies, in physics, chemistry or biology. It provides the tools for an understanding of elementary processes in biology, such as photosynthesis on a molecular level. A basic knowledge in mechanics, electrostatics, quantum theory and statistical physics is desirable. The reader will be exposed to basic concepts in modern biophysics such as entropic forces, phase separation, potentials of mean force, proton and electron transfer, heterogeneous reactions coherent and incoherent energy transfer as well as molecular motors. Basic concepts such as phase transitions of biopolymers, electrostatics, protonation equilibria, ion transport, radiationless transitions as well as energy- and electron transfer are discussed within the frame of simple models.
Biophysics of protein evolution and evolutionary protein biophysics
Sikosek, Tobias; Chan, Hue Sun
2014-01-01
The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution. PMID:25165599
Two radiative inverse seesaw models, dark matter, and baryogenesis
Baldes, Iason; Petraki, Kalliopi; Volkas, Raymond R
2013-01-01
The inverse seesaw mechanism allows the neutrino masses to be generated by new physics at an experimentally accessible scale, even with O(1) Yukawa couplings. In the inverse seesaw scenario, the smallness of neutrino masses is linked to the smallness of a lepton number violating parameter. This parameter may arise radiatively. In this paper, we study the cosmological implications of two contrasting radiative inverse seesaw models, one due to Ma and the other to Law and McDonald. The former features spontaneous, the latter explicit lepton number violation. First, we examine the effect of the lepton-number violating interactions introduced in these models on the baryon asymmetry of the universe. We investigate under what conditions a pre-existing baryon asymmetry does not get washed out. While both models allow a baryon asymmetry to survive only once the temperature has dropped below the mass of their heaviest fields, the Ma model can create the baryon asymmetry through resonant leptogenesis. Then we investigat...
Inverse thermal history modelling as a hydrocarbon exploration tool
Energy Technology Data Exchange (ETDEWEB)
Gallagher, K. [Imperial College of Science, Technology and Medicine, London (United Kingdom). TH Huxley School of Environment, Earth Science and Engineering
1998-12-31
Thermal history modelling is a significant part of hydrocarbon exploration and resource assessment. Its primary use is to predict the volume and timing of hydrocarbon generation as a sedimentary basin evolves on timescales of 10{sup 7}-10{sup 8} years. Forward modelling is commonly used to constrain the thermal history in sedimentary basins. Alternatively, inversion schemes may be used which have many advantages over the conventional forward modelling approach. An example of an inversion approach is presented here, wherein the preferred philosophy is to find the least complex model that fits the data. In this case, we estimate a heat flow function (of time) which provides an adequate fit to the available thermal indicator calibration data. The function is also constrained to be smooth, in either a first or second derivative sense. Extra complexity or structure is introduced into the function only where required to fit the data and the regularization stabilizes the inversion. The general formulation is presented and a real data example from the North Slope, Alaska is discussed. (author)
Anatomy of Higgs mass in supersymmetric inverse seesaw models
Energy Technology Data Exchange (ETDEWEB)
Chun, Eung Jin, E-mail: ejchun@kias.re.kr [Korea Institute for Advanced Study, Seoul 130-722 (Korea, Republic of); Mummidi, V. Suryanarayana, E-mail: soori9@cts.iisc.ernet.in [Centre for High Energy Physics, Indian Institute of Science, Bangalore 560012 (India); Vempati, Sudhir K., E-mail: vempati@cts.iisc.ernet.in [Centre for High Energy Physics, Indian Institute of Science, Bangalore 560012 (India)
2014-09-07
We compute the one loop corrections to the CP-even Higgs mass matrix in the supersymmetric inverse seesaw model to single out the different cases where the radiative corrections from the neutrino sector could become important. It is found that there could be a significant enhancement in the Higgs mass even for Dirac neutrino masses of O(30) GeV if the left-handed sneutrino soft mass is comparable or larger than the right-handed neutrino mass. In the case where right-handed neutrino masses are significantly larger than the supersymmetry breaking scale, the corrections can utmost account to an upward shift of 3 GeV. For very heavy multi TeV sneutrinos, the corrections replicate the stop corrections at 1-loop. We further show that general gauge mediation with inverse seesaw model naturally accommodates a 125 GeV Higgs with TeV scale stops.
OpenMP Programming for a Global Inverse Model
Directory of Open Access Journals (Sweden)
Ping Wang
2002-01-01
Full Text Available The objective of our investigation is to establish robust inverse algorithms to convert GRACE gravity and ICESat altimetry mission data into global current and past surface mass variations. To assess separation of global sources of change and to evaluate spatio-temporal resolution and accuracy statistically from full posterior covariance matrices, a high performance version of a global simultaneous grid inverse algorithm is essential. One means to accomplish this is to implement a general, well-optimized, parallel global model on massively parallel supercomputers. In our present work, an efficient parallel version of a global inverse program has been implemented on the Origin 2000 using the OpenMP programming model. In this paper, porting a sequential global code to a shared-memory computing system is discussed; several efficient strategies to optimize the code are reported; well-optimized scientific libraries are used; detailed parallel implementation of the global model is reported; performance data of the code are analyzed. Scaling performance on a shared-memory system is also discussed. The parallel version software gives good speedup and dramatically reduces total data processing time.
Adiabatic approximation for the Rabi model with broken inversion symmetry
Shen, Li-Tuo; Yang, Zhen-Biao; Wu, Huai-Zhi
2017-01-01
We study the properties and behavior of the Rabi model with broken inversion symmetry. Using an adiabatic approximation approach, we explore the high-frequency qubit and oscillator regimes, and obtain analytical solutions for the qubit-oscillator system. We demonstrate that, due to broken inversion symmetry, the positions of two potentials and zero-point energies in the oscillators become asymmetric and have a quadratic dependence on the mean dipole moments within the high-frequency oscillator regime. Furthermore, we find that there is a critical point above which the qubit-oscillator system becomes unstable, and the position of this critical point has a quadratic dependence on the mean dipole moments within the high-frequency qubit regime. Finally, we verify this critical point based on the method of semiclassical approximation.
GARCH modelling of covariance in dynamical estimation of inverse solutions
Energy Technology Data Exchange (ETDEWEB)
Galka, Andreas [Institute of Experimental and Applied Physics, University of Kiel, 24098 Kiel (Germany) and Institute of Statistical Mathematics (ISM), Minami-Azabu 4-6-7, Tokyo 106-8569 (Japan)]. E-mail: galka@physik.uni-kiel.de; Yamashita, Okito [ATR Computational Neuroscience Laboratories, Hikaridai 2-2-2, Kyoto 619-0288 (Japan); Ozaki, Tohru [Institute of Statistical Mathematics (ISM), Minami-Azabu 4-6-7, Tokyo 106-8569 (Japan)
2004-12-06
The problem of estimating unobserved states of spatially extended dynamical systems poses an inverse problem, which can be solved approximately by a recently developed variant of Kalman filtering; in order to provide the model of the dynamics with more flexibility with respect to space and time, we suggest to combine the concept of GARCH modelling of covariance, well known in econometrics, with Kalman filtering. We formulate this algorithm for spatiotemporal systems governed by stochastic diffusion equations and demonstrate its feasibility by presenting a numerical simulation designed to imitate the situation of the generation of electroencephalographic recordings by the human cortex.
Aircraft automatic flight control system with model inversion
Smith, G. A.; Meyer, George
1990-01-01
A simulator study was conducted to verify the advantages of a Newton-Raphson model-inversion technique as a design basis for an automatic trajectory control system in an aircraft with highly nonlinear characteristics. The simulation employed a detailed mathematical model of the aerodynamic and propulsion system performance characteristics of a vertical-attitude takeoff and landing tactical aircraft. The results obtained confirm satisfactory control system performance over a large portion of the flight envelope. System response to wind gusts was satisfactory for various plausible combinations of wind magnitude and direction.
Aircraft automatic flight control system with model inversion
Smith, G. A.; Meyer, George
1990-01-01
A simulator study was conducted to verify the advantages of a Newton-Raphson model-inversion technique as a design basis for an automatic trajectory control system in an aircraft with highly nonlinear characteristics. The simulation employed a detailed mathematical model of the aerodynamic and propulsion system performance characteristics of a vertical-attitude takeoff and landing tactical aircraft. The results obtained confirm satisfactory control system performance over a large portion of the flight envelope. System response to wind gusts was satisfactory for various plausible combinations of wind magnitude and direction.
Quantum inverse scattering and the lambda deformed principal chiral model
Appadu, Calan; Hollowood, Timothy J.; Price, Dafydd
2017-07-01
The lambda model is a one parameter deformation of the principal chiral model that arises when regularizing the non-compactness of a non-abelian T dual in string theory. It is a current-current deformation of a WZW model that is known to be integrable at the classical and quantum level. The standard techniques of the quantum inverse scattering method cannot be applied because the Poisson bracket is non ultra-local. Inspired by an approach of Faddeev and Reshetikhin, we show that in this class of models, there is a way to deform the symplectic structure of the theory leading to a much simpler theory that is ultra-local and can be quantized on the lattice whilst preserving integrability. This lattice theory takes the form of a generalized spin chain that can be solved by standard algebraic Bethe Ansatz techniques. We then argue that the IR limit of the lattice theory lies in the universality class of the lambda model implying that the spin chain provides a way to apply the quantum inverse scattering method to this non ultra-local theory. This points to a way of applying the same ideas to other lambda models and potentially the string world-sheet theory in the gauge-gravity correspondence.
Li, Guoshi; Linster, Christiane; Cleland, Thomas A
2015-12-01
Olfactory bulb granule cells are modulated by both acetylcholine (ACh) and norepinephrine (NE), but the effects of these neuromodulators have not been clearly distinguished. We used detailed biophysical simulations of granule cells, both alone and embedded in a microcircuit with mitral cells, to measure and distinguish the effects of ACh and NE on cellular and microcircuit function. Cholinergic and noradrenergic modulatory effects on granule cells were based on data obtained from slice experiments; specifically, ACh reduced the conductance densities of the potassium M current and the calcium-dependent potassium current, whereas NE nonmonotonically regulated the conductance density of an ohmic potassium current. We report that the effects of ACh and NE on granule cell physiology are distinct and functionally complementary to one another. ACh strongly regulates granule cell firing rates and afterpotentials, whereas NE bidirectionally regulates subthreshold membrane potentials. When combined, NE can regulate the ACh-induced expression of afterdepolarizing potentials and persistent firing. In a microcircuit simulation developed to investigate the effects of granule cell neuromodulation on mitral cell firing properties, ACh increased spike synchronization among mitral cells, whereas NE modulated the signal-to-noise ratio. Coapplication of ACh and NE both functionally improved the signal-to-noise ratio and enhanced spike synchronization among mitral cells. In summary, our computational results support distinct and complementary roles for ACh and NE in modulating olfactory bulb circuitry and suggest that NE may play a role in the regulation of cholinergic function.
Linster, Christiane
2015-01-01
Olfactory bulb granule cells are modulated by both acetylcholine (ACh) and norepinephrine (NE), but the effects of these neuromodulators have not been clearly distinguished. We used detailed biophysical simulations of granule cells, both alone and embedded in a microcircuit with mitral cells, to measure and distinguish the effects of ACh and NE on cellular and microcircuit function. Cholinergic and noradrenergic modulatory effects on granule cells were based on data obtained from slice experiments; specifically, ACh reduced the conductance densities of the potassium M current and the calcium-dependent potassium current, whereas NE nonmonotonically regulated the conductance density of an ohmic potassium current. We report that the effects of ACh and NE on granule cell physiology are distinct and functionally complementary to one another. ACh strongly regulates granule cell firing rates and afterpotentials, whereas NE bidirectionally regulates subthreshold membrane potentials. When combined, NE can regulate the ACh-induced expression of afterdepolarizing potentials and persistent firing. In a microcircuit simulation developed to investigate the effects of granule cell neuromodulation on mitral cell firing properties, ACh increased spike synchronization among mitral cells, whereas NE modulated the signal-to-noise ratio. Coapplication of ACh and NE both functionally improved the signal-to-noise ratio and enhanced spike synchronization among mitral cells. In summary, our computational results support distinct and complementary roles for ACh and NE in modulating olfactory bulb circuitry and suggest that NE may play a role in the regulation of cholinergic function. PMID:26334007
A Model for TSUnami FLow INversion from Deposits (TSUFLIND)
Tang, Hui
2015-01-01
Modern tsunami deposits are employed to estimate the overland flow characteristics of tsunamis. With the help of the overland-flow characteristics, the characteristics of the causative tsunami wave can be estimated. The understanding of tsunami deposits has tremendously improved over the last decades. There are three prominent inversion models: Moore advection model, Soulsby's model and TsuSedMod model. TSUFLIND incorporates all three models and adds new modules to better simulate tsunami deposit formation and calculate flow condition. TSUFLIND takes grain-size distribution, thickness, water depth and topography information as inputs. TSUFLIND computes sediment concentration, grain-size distribution of sediment source and initial flow condition to match the sediment thickness and grain size distribution from field observation. Furthermore, TSUFLIND estimates the flow speed, Froude number and representative wave amplitude. The model is tested by using field data collected at Ranganathapuram, India after the 20...
Directory of Open Access Journals (Sweden)
Ojcius David M
2009-08-01
Full Text Available Abstract Background Promoter identification is a first step in the quest to explain gene regulation in bacteria. It has been demonstrated that the initiation of bacterial transcription depends upon the stability and topology of DNA in the promoter region as well as the binding affinity between the RNA polymerase σ-factor and promoter. However, promoter prediction algorithms to date have not explicitly used an ensemble of these factors as predictors. In addition, most promoter models have been trained on data from Escherichia coli. Although it has been shown that transcriptional mechanisms are similar among various bacteria, it is quite possible that the differences between Escherichia coli and Chlamydia trachomatis are large enough to recommend an organism-specific modeling effort. Results Here we present an iterative stochastic model building procedure that combines such biophysical metrics as DNA stability, curvature, twist and stress-induced DNA duplex destabilization along with duration hidden Markov model parameters to model Chlamydia trachomatis σ66 promoters from 29 experimentally verified sequences. Initially, iterative duration hidden Markov modeling of the training set sequences provides a scoring algorithm for Chlamydia trachomatis RNA polymerase σ66/DNA binding. Subsequently, an iterative application of Stepwise Binary Logistic Regression selects multiple promoter predictors and deletes/replaces training set sequences to determine an optimal training set. The resulting model predicts the final training set with a high degree of accuracy and provides insights into the structure of the promoter region. Model based genome-wide predictions are provided so that optimal promoter candidates can be experimentally evaluated, and refined models developed. Co-predictions with three other algorithms are also supplied to enhance reliability. Conclusion This strategy and resulting model support the conjecture that DNA biophysical properties
Joint Inversion Modelling of Geophysical Data From Lough Neagh Basin
Vozar, J.; Moorkamp, M.; Jones, A. G.; Rath, V.; Muller, M. R.
2015-12-01
Multi-dimensional modelling of geophysical data collected in the Lough Neagh Basin is presented in the frame of the IRETHERM project. The Permo-Triassic Lough Neagh Basin, situated in the southeastern part of Northern Ireland, exhibits elevated geothermal gradient (~30 °C/km) in the exploratory drilled boreholes. This is taken to indicate good geothermal exploitation potential in the Sherwood Sandstone aquifer for heating, and possibly even electricity production, purposes. We have used a 3-D joint inversion framework for modelling the magnetotelluric (MT) and gravity data collected to the north of the Lough Neagh to derive robust subsurface geological models. Comprehensive supporting geophysical and geological data (e.g. borehole logs and reflection seismic images) have been used in order to analyze and model the MT and gravity data. The geophysical data sets were provided by the Geological Survey of Northern Ireland (GSNI). Considering correct objective function weighting in favor of noise-free MT response functions is particularly important in joint inversion. There is no simple way how to correct distortion effects the 3-D responses as can be done in 1-D or 2-D case. We have used the Tellus Project airborne EM data to constrain magnetotelluric data and correct them for near surface effects. The shallow models from airborne data are used to constrain the uppermost part of 3-D inversion model. Preliminary 3-D joint inversion modeling reveals that the Sherwood Sandstone Group and the Permian Sandstone Formation are imaged as a conductive zone at the depth range of 500 m to 2000 m with laterally varying thickness, depth, and conductance. The conductive target sediments become shallower and thinner to the north and they are laterally continuous. To obtain better characterization of thermal transport properties of investigated area we used porosity and resistivity data from the Annaghmore and Ballymacilroy boreholes to estimate the relations between porosity
Constraining canopy biophysical simulations with MODIS reflectance data
Drewry, D. T.; Duveiller, G.
2013-05-01
Modern vegetation models incorporate ecophysiological details that allow for accurate estimates of carbon dioxide uptake, water use and energy exchange, but require knowledge of dynamic structural and biochemical traits. Variations in these traits are controlled by genetic factors as well as growth stage and nutrient and moisture availability, making them difficult to predict and prone to significant error. Here we explore the use of MODIS optical reflectance data for constraining key canopy- and leaf-level traits required by forward biophysical models. A multi-objective optimization algorithm is used to invert the PROSAIL canopy radiation transfer model, which accounts for the effects of leaf-level optical properties, foliage distribution and orientation on canopy reflectance across the optical range. Inversions are conducted for several growing seasons for both soybean and maize at several sites in the Central US agro-ecosystem. These inversions provide estimates of seasonal variations, and associated uncertainty, of variables such as leaf area index (LAI) that are then used as inputs into the MLCan biophysical model to conduct forward simulations. MLCan characterizes the ecophysiological functioning of a plant canopy at a half-hourly timestep, and has been rigorously validated for both C3 and C4 crops against observations of canopy CO2 uptake, evapotranspiration and sensible heat exchange across a wide range of meteorological conditions. The inversion-derived canopy properties are used to examine the ability of MODIS data to characterize seasonal variations in canopy properties in the context of a detailed forward canopy biophysical model, and the uncertainty induced in forward model estimates as a function of the uncertainty in the inverted parameters. Special care is made to ensure that the satellite observations match adequately, in both time and space, with the coupled model simulations. To do so, daily MODIS observations are used and a validated model of
Bronson, Jonathan E; Fei, Jingyi; Hofman, Jake M; Gonzalez, Ruben L; Wiggins, Chris H
2009-12-16
Time series data provided by single-molecule Förster resonance energy transfer (smFRET) experiments offer the opportunity to infer not only model parameters describing molecular complexes, e.g., rate constants, but also information about the model itself, e.g., the number of conformational states. Resolving whether such states exist or how many of them exist requires a careful approach to the problem of model selection, here meaning discrimination among models with differing numbers of states. The most straightforward approach to model selection generalizes the common idea of maximum likelihood--selecting the most likely parameter values--to maximum evidence: selecting the most likely model. In either case, such an inference presents a tremendous computational challenge, which we here address by exploiting an approximation technique termed variational Bayesian expectation maximization. We demonstrate how this technique can be applied to temporal data such as smFRET time series; show superior statistical consistency relative to the maximum likelihood approach; compare its performance on smFRET data generated from experiments on the ribosome; and illustrate how model selection in such probabilistic or generative modeling can facilitate analysis of closely related temporal data currently prevalent in biophysics. Source code used in this analysis, including a graphical user interface, is available open source via http://vbFRET.sourceforge.net.
Humanoid Walking Robot: Modeling, Inverse Dynamics, and Gain Scheduling Control
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Elvedin Kljuno
2010-01-01
Full Text Available This article presents reference-model-based control design for a 10 degree-of-freedom bipedal walking robot, using nonlinear gain scheduling. The main goal is to show concentrated mass models can be used for prediction of the required joint torques for a bipedal walking robot. Relatively complicated architecture, high DOF, and balancing requirements make the control task of these robots difficult. Although linear control techniques can be used to control bipedal robots, nonlinear control is necessary for better performance. The emphasis of this work is to show that the reference model can be a bipedal walking model with concentrated mass at the center of gravity, which removes the problems related to design of a pseudo-inverse system. Another significance of this approach is the reduced calculation requirements due to the simplified procedure of nominal joint torques calculation. Kinematic and dynamic analysis is discussed including results for joint torques and ground force necessary to implement a prescribed walking motion. This analysis is accompanied by a comparison with experimental data. An inverse plant and a tracking error linearization-based controller design approach is described. We propose a novel combination of a nonlinear gain scheduling with a concentrated mass model for the MIMO bipedal robot system.
A nonlinear inversion for the velocity background and perturbation models
Wu, Zedong
2015-08-19
Reflected waveform inversion (RWI) provides a method to reduce the nonlinearity of the standard full waveform inversion (FWI) by inverting for the single scattered wavefield obtained using an image. However, current RWI methods usually neglect diving waves, which is an important source of information for extracting the long wavelength components of the velocity model. Thus, we propose a new optimization problem through breaking the velocity model into the background and the perturbation in the wave equation directly. In this case, the perturbed model is no longer the single scattering model, but includes all scattering. We optimize both components simultaneously, and thus, the objective function is nonlinear with respect to both the background and perturbation. The new introduced w can absorb the non-smooth update of background naturally. Application to the Marmousi model with frequencies that start at 5 Hz shows that this method can converge to the accurate velocity starting from a linearly increasing initial velocity. Application to the SEG2014 demonstrates the versatility of the approach.
The Quantum Inverse Scattering Method for Hubbard-like Models
Martins, M J
1997-01-01
This work is concerned with various aspects of the formulation of the quantum inverse scattering method for the one-dimensional Hubbard model. We first establish the essential tools to solve the eigenvalue problem for the transfer matrix of the classical ``covering'' Hubbard model within the algebraic Bethe Ansatz framework. The fundamental commutation rules exhibit a hidden 6-vertex symmetry which plays a crucial role in the whole algebraic construction. Next we apply this formalism to study the SU(2) highest weights properties of the eigenvectors and the solution of a related coupled spin model with twisted boundary conditions. The machinery developed in this paper is applicable to many other models, and as an example we present the algebraic solution of the Bariev XY coupled model.
Inverse modeling approach to allogenic karst system characterization.
Dörfliger, N; Fleury, P; Ladouche, B
2009-01-01
Allogenic karst systems function in a particular way that is influenced by the type of water infiltrating through river water losses, by karstification processes, and by water quality. Management of this system requires a good knowledge of its structure and functioning, for which a new methodology based on an inverse modeling approach appears to be well suited. This approach requires both spring and river inflow discharge measurements and a continuous record of chemical parameters in the river and at the spring. The inverse model calculates unit hydrographs and the impulse responses of fluxes from rainfall hydraulic head at the spring or rainfall flux data, the purpose of which is hydrograph separation. Hydrograph reconstruction is done using rainfall and river inflow data as model input and enables definition at each time step of the ratio of each component. Using chemical data, representing event and pre-event water, as input, it is possible to determine the origin of spring water (either fast flow through the epikarstic zone or slow flow through the saturated zone). This study made it possible to improve a conceptual model of allogenic karst system functioning. The methodology is used to study the Bas-Agly and the Cent Font karst systems, two allogenic karst systems in Southern France.
Bayat, Bagher; Van der Tol, Christiaan; Verhoef, Wouter
2016-08-01
Plant-available soil moisture is a key element which affects plant properties in their ecosystems. This study shows Poa pratensis -a species of grass- responses to soil moisture deficit during an artificial drought episode in a greenhouse experiment. We used radiative transfer model inversion to monitor the gradual manifestation of soil moisture deficit effects on vegetation in a laboratory setting. Plots of 21 cm x 14.5 cm surface area with Poa pratensis plants that formed a closed canopy were subjected to water stress for 40 days. In a regular weekly schedule, canopy reflectance was measured. The 1-D bidirectional canopy reflectance model SAIL, coupled with the leaf optical properties model PROSPECT, was inverted using hyperspectral measurements by means of an iterative optimization method to retrieve vegetation biophysical and biochemical parameters (mainly; LAI, Cab, Cw, Cdm and Cs). The relationships between these retrieved parameters with soil moisture content were established in two separated groups; stress and non-stressed. All parameters retrieved by model inversion using canopy spectral data showed good correlation with soil moisture content in the drought episode. These parameters co- varied with soil moisture content under the stress condition (Chl: R2= 0.91, Cw: R2= 0.97, Cs: R2= 0.88 and LAI: R2=0.48) at the canopy level.
Directory of Open Access Journals (Sweden)
R. Locatelli
2013-04-01
Full Text Available A modelling experiment has been conceived to assess the impact of transport model errors on the methane emissions estimated by an atmospheric inversion system. Synthetic methane observations, given by 10 different model outputs from the international TransCom-CH4 model exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the PYVAR-LMDZ-SACS inverse system to produce 10 different methane emission estimates at the global scale for the year 2005. The same set-up has been used to produce the synthetic observations and to compute flux estimates by inverse modelling, which means that only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg CH4 per year at the global scale, representing 5% of the total methane emissions. At continental and yearly scales, transport model errors have bigger impacts depending on the region, ranging from 36 Tg CH4 in north America to 7 Tg CH4 in Boreal Eurasian (from 23% to 48%. At the model gridbox scale, the spread of inverse estimates can even reach 150% of the prior flux. Thus, transport model errors contribute to significant uncertainties on the methane estimates by inverse modelling, especially when small spatial scales are invoked. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher resolution models. The analysis of methane estimated fluxes in these different configurations questions the consistency of transport model errors in current inverse systems. For future methane inversions, an improvement in the modelling of the atmospheric transport would make the estimations more accurate. Likewise, errors of the observation covariance matrix should be more consistently prescribed in future inversions in order to limit the impact of transport model errors on estimated methane
Neural Network method for Inverse Modeling of Material Deformation
Energy Technology Data Exchange (ETDEWEB)
Allen, J.D., Jr.; Ivezic, N.D.; Zacharia, T.
1999-07-10
A method is described for inverse modeling of material deformation in applications of importance to the sheet metal forming industry. The method was developed in order to assess the feasibility of utilizing empirical data in the early stages of the design process as an alternative to conventional prototyping methods. Because properly prepared and employed artificial neural networks (ANN) were known to be capable of codifying and generalizing large bodies of empirical data, they were the natural choice for the application. The product of the work described here is a desktop ANN system that can produce in one pass an accurate die design for a user-specified part shape.
Stochastic reduced order models for inverse problems under uncertainty.
Warner, James E; Aquino, Wilkins; Grigoriu, Mircea D
2015-03-01
This work presents a novel methodology for solving inverse problems under uncertainty using stochastic reduced order models (SROMs). Given statistical information about an observed state variable in a system, unknown parameters are estimated probabilistically through the solution of a model-constrained, stochastic optimization problem. The point of departure and crux of the proposed framework is the representation of a random quantity using a SROM - a low dimensional, discrete approximation to a continuous random element that permits e cient and non-intrusive stochastic computations. Characterizing the uncertainties with SROMs transforms the stochastic optimization problem into a deterministic one. The non-intrusive nature of SROMs facilitates e cient gradient computations for random vector unknowns and relies entirely on calls to existing deterministic solvers. Furthermore, the method is naturally extended to handle multiple sources of uncertainty in cases where state variable data, system parameters, and boundary conditions are all considered random. The new and widely-applicable SROM framework is formulated for a general stochastic optimization problem in terms of an abstract objective function and constraining model. For demonstration purposes, however, we study its performance in the specific case of inverse identification of random material parameters in elastodynamics. We demonstrate the ability to efficiently recover random shear moduli given material displacement statistics as input data. We also show that the approach remains effective for the case where the loading in the problem is random as well.
Optimised spectral merge of the background model in seismic inversion
White, Roy; Zabihi Naeini, Ehsan
2017-01-01
The inversion of seismic reflection data to absolute impedance generates low-frequency deviations around the true impedance if the frequency content of the background impedance model does not merge seamlessly into the spectrum of the inverted seismic data. We present a systematic method of selecting a background model that minimises the mismatch between the background model and the relative impedance obtained by inverting the seismic data at wells. At each well a set of well-log relative impedances is formed by passing the impedance log through a set of zero-phase high-pass filters. The corresponding background models are constructed by passing the impedance log through the complementary zero-phase low-pass filters and a set of seismic relative impedances is computed by inverting the seismic data using these background models. If the inverted seismic data is to merge perfectly with the background model, it should correspond at the well to the well-log relative impedance. This correspondence is the basis of a procedure for finding the optimum combination of background model and inverted seismic data. It is difficult to predict the low-frequency content of inverted seismic data. These low frequencies are affected by the uncertainties in (1) measuring the low-frequency response of the seismic wavelet and (2) knowing how inversion protects the signal-to-noise ratio at low frequencies. Uncertainty (1) becomes acute for broadband seismic data; the low-frequency phase is especially difficult to estimate. Moreover we show that a mismatch of low-frequency phase is a serious source of inversion artefacts. We also show that relative impedance can estimate the low-frequency phase where a well tie cannot. Consequently we include a low-frequency phase shift, applied to the seismic relative impedances, in the search for the best spectral merge. The background models are specified by a low-cut corner frequency and the phase shifts by a phase intercept at zero frequency. A scan of
The Mechanics and Biophysics of Hearing
Geisler, C; Matthews, John; Ruggero, Mario; Steele, Charles
1990-01-01
Proceedings of a workshop on the physics and biophysics of hearing that brought together experimenters and modelers working on all aspects of audition. Topics covered include: cochlear mechanical measurements, cochlear models, mechanicals and biophysics of hair cells, efferent control, and ultrastructure.
Forecasting wind-driven wildfires using an inverse modelling approach
Directory of Open Access Journals (Sweden)
O. Rios
2013-12-01
Full Text Available A technology able to rapidly forecast wildlfire dynamics would lead to a paradigm shift in the response to emergencies, providing the Fire Service with essential information about the on-going fire. The article at hand presents and explores a novel methodology to forecast wildfire dynamics in wind-driven conditions, using real time data assimilation and inverse modelling. The forecasting algorithm combines Rothermel's rate of spread theory with a perimeter expansion model based on Huygens principle and solves the optimisation problem with a tangent linear approach and a forward automatic differentiation. Its potential is investigated using synthetic data and evaluated in different wildfire scenarios. The results show the high capacity of the method to quickly predict the location of the fire front with a positive lead time (ahead of the event. This work opens the door to further advances framework and more sophisticated models while keeping the computational time suitable for operativeness.
Directory of Open Access Journals (Sweden)
Iman Farasat
2016-01-01
Full Text Available The ability to precisely modify genomes and regulate specific genes will greatly accelerate several medical and engineering applications. The CRISPR/Cas9 (Type II system binds and cuts DNA using guide RNAs, though the variables that control its on-target and off-target activity remain poorly characterized. Here, we develop and parameterize a system-wide biophysical model of Cas9-based genome editing and gene regulation to predict how changing guide RNA sequences, DNA superhelical densities, Cas9 and crRNA expression levels, organisms and growth conditions, and experimental conditions collectively control the dynamics of dCas9-based binding and Cas9-based cleavage at all DNA sites with both canonical and non-canonical PAMs. We combine statistical thermodynamics and kinetics to model Cas9:crRNA complex formation, diffusion, site selection, reversible R-loop formation, and cleavage, using large amounts of structural, biochemical, expression, and next-generation sequencing data to determine kinetic parameters and develop free energy models. Our results identify DNA supercoiling as a novel mechanism controlling Cas9 binding. Using the model, we predict Cas9 off-target binding frequencies across the lambdaphage and human genomes, and explain why Cas9's off-target activity can be so high. With this improved understanding, we propose several rules for designing experiments for minimizing off-target activity. We also discuss the implications for engineering dCas9-based genetic circuits.
Farasat, Iman; Salis, Howard M.
2016-01-01
The ability to precisely modify genomes and regulate specific genes will greatly accelerate several medical and engineering applications. The CRISPR/Cas9 (Type II) system binds and cuts DNA using guide RNAs, though the variables that control its on-target and off-target activity remain poorly characterized. Here, we develop and parameterize a system-wide biophysical model of Cas9-based genome editing and gene regulation to predict how changing guide RNA sequences, DNA superhelical densities, Cas9 and crRNA expression levels, organisms and growth conditions, and experimental conditions collectively control the dynamics of dCas9-based binding and Cas9-based cleavage at all DNA sites with both canonical and non-canonical PAMs. We combine statistical thermodynamics and kinetics to model Cas9:crRNA complex formation, diffusion, site selection, reversible R-loop formation, and cleavage, using large amounts of structural, biochemical, expression, and next-generation sequencing data to determine kinetic parameters and develop free energy models. Our results identify DNA supercoiling as a novel mechanism controlling Cas9 binding. Using the model, we predict Cas9 off-target binding frequencies across the lambdaphage and human genomes, and explain why Cas9’s off-target activity can be so high. With this improved understanding, we propose several rules for designing experiments for minimizing off-target activity. We also discuss the implications for engineering dCas9-based genetic circuits. PMID:26824432
An inverse problem for a mathematical model of aquaponic agriculture
Bobak, Carly; Kunze, Herb
2017-01-01
Aquaponic agriculture is a sustainable ecosystem that relies on a symbiotic relationship between fish and macrophytes. While the practice has been growing in popularity, relatively little mathematical models exist which aim to study the system processes. In this paper, we present a system of ODEs which aims to mathematically model the population and concetrations dynamics present in an aquaponic environment. Values of the parameters in the system are estimated from the literature so that simulated results can be presented to illustrate the nature of the solutions to the system. As well, a brief sensitivity analysis is performed in order to identify redundant parameters and highlight those which may need more reliable estimates. Specifically, an inverse problem with manufactured data for fish and plants is presented to demonstrate the ability of the collage theorem to recover parameter estimates.
Ellipsoidal head model for fetal magnetoencephalography: forward and inverse solutions
Energy Technology Data Exchange (ETDEWEB)
Gutierrez, David [Department of Bioengineering, University of Illinois at Chicago, 851 S. Morgan St (M/C 063), Chicago, IL 60607-7053 (United States); Nehorai, Arye [Department of Bioengineering, University of Illinois at Chicago, 851 S. Morgan St (M/C 063), Chicago, IL 60607-7053 (United States); Department of Electrical and Computer Engineering, University of Illinois at Chicago, 851 S. Morgan St, 1120 SEO (M/C 154), Chicago, IL 60607-7053 (United States); Preissl, Hubert [Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, AR 72205 (United States); MEG-Center, University of Tuebingen, Tuebingen, 72206 (Germany)
2005-05-07
Fetal magnetoencephalography (fMEG) is a non-invasive technique where measurements of the magnetic field outside the maternal abdomen are used to infer the source location and signals of the fetus' neural activity. There are a number of aspects related to fMEG modelling that must be addressed, such as the conductor volume, fetal position and orientation, gestation period, etc. We propose a solution to the forward problem of fMEG based on an ellipsoidal head geometry. This model has the advantage of highlighting special characteristics of the field that are inherent to the anisotropy of the human head, such as the spread and orientation of the field in relationship with the localization and position of the fetal head. Our forward solution is presented in the form of a kernel matrix that facilitates the solution of the inverse problem through decoupling of the dipole localization parameters from the source signals. Then, we use this model and the maximum likelihood technique to solve the inverse problem assuming the availability of measurements from multiple trials. The applicability and performance of our methods are illustrated through numerical examples based on a real 151-channel SQUID fMEG measurement system (SARA). SARA is an MEG system especially designed for fetal assessment and is currently used for heart and brain studies. Finally, since our model requires knowledge of the best-fitting ellipsoid's centre location and semiaxes lengths, we propose a method for estimating these parameters through a least-squares fit on anatomical information obtained from three-dimensional ultrasound images.
Uncertainty Visualization in Forward and Inverse Cardiac Models.
Burton, Brett M; Erem, Burak; Potter, Kristin; Rosen, Paul; Johnson, Chris R; Brooks, Dana H; Macleod, Rob S
2013-01-01
Quantification and visualization of uncertainty in cardiac forward and inverse problems with complex geometries is subject to various challenges. Specific to visualization is the observation that occlusion and clutter obscure important regions of interest, making visual assessment difficult. In order to overcome these limitations in uncertainty visualization, we have developed and implemented a collection of novel approaches. To highlight the utility of these techniques, we evaluated the uncertainty associated with two examples of modeling myocardial activity. In one case we studied cardiac potentials during the repolarization phase as a function of variability in tissue conductivities of the ischemic heart (forward case). In a second case, we evaluated uncertainty in reconstructed activation times on the epicardium resulting from variation in the control parameter of Tikhonov regularization (inverse case). To overcome difficulties associated with uncertainty visualization, we implemented linked-view windows and interactive animation to the two respective cases. Through dimensionality reduction and superimposed mean and standard deviation measures over time, we were able to display key features in large ensembles of data and highlight regions of interest where larger uncertainties exist.
Institute of Scientific and Technical Information of China (English)
YANG Xiao-Hua; WANG Fu-Min; HUANG Jing-Feng; WANG Jian-Wen; WANG Ren-Chao; SHEN Zhang-Quan; WANG Xiu-Zhen
2009-01-01
The radial basis function (RBF) emerged as a variant of artificial neural network.Generalized regression neural network (GRNN) is one type of RBF,and its principal advantages are that it can quickly learn and rapidly converge to the optimal regression surface with large number of data sets.Hyperspectral reflectance (350 to 2 500 nm) data were recorded at two different rice sites in two experiment fields with two cultivars,three nitrogen treatments and one plant density (45 plants m-2).Stepwise multivariable regression model (SMR) and RBF were used to compare their predictability for the leaf area index (LAI) and green leaf chlorophyll density (GLCD) of rice based on reflectance (R) and its three different transformations,the first derivative reflectance (D1),the second derivative reflectance (D2) and the log-transformed reflectance (LOG).GRNN based on D1 was the best model for the prediction of rice LAI and GLCD.The relationships between different transformations of reflectance and rice parameters could be further improved when RBF was employed.Owing to its strong capacity for nonlinear mapping and good robustness,GRNN could maximize the sensitivity to chlorophyll content using D1.It is concluded that RBF may provide a useful exploratory and predictive tool for the estimation of rice biophysical parameters.
Natural vs. artificial groundwater recharge, quantification through inverse modeling
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H. Hashemi
2013-02-01
Full Text Available Estimating the change in groundwater recharge from an introduced artificial recharge system is important in order to evaluate future water availability. This paper presents an inverse modeling approach to quantify the recharge contribution from both an ephemeral river channel and an introduced artificial recharge system based on floodwater spreading in arid Iran. The study used the MODFLOW-2000 to estimate recharge for both steady- and unsteady-state conditions. The model was calibrated and verified based on the observed hydraulic head in observation wells and model precision, uncertainty, and model sensitivity were analyzed in all modeling steps. The results showed that in a normal year without extreme events, the floodwater spreading system is the main contributor to recharge with 80% and the ephemeral river channel with 20% of total recharge in the studied area. Uncertainty analysis revealed that the river channel recharge estimation represents relatively more uncertainty in comparison to the artificial recharge zones. The model is also less sensitive to the river channel. The results show that by expanding the artificial recharge system, the recharge volume can be increased even for small flood events, while the recharge through the river channel increases only for major flood events.
Anthropomorphic Coding of Speech and Audio: A Model Inversion Approach
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W. Bastiaan Kleijn
2005-06-01
Full Text Available Auditory modeling is a well-established methodology that provides insight into human perception and that facilitates the extraction of signal features that are most relevant to the listener. The aim of this paper is to provide a tutorial on perceptual speech and audio coding using an invertible auditory model. In this approach, the audio signal is converted into an auditory representation using an invertible auditory model. The auditory representation is quantized and coded. Upon decoding, it is then transformed back into the acoustic domain. This transformation converts a complex distortion criterion into a simple one, thus facilitating quantization with low complexity. We briefly review past work on auditory models and describe in more detail the components of our invertible model and its inversion procedure, that is, the method to reconstruct the signal from the output of the auditory model. We summarize attempts to use the auditory representation for low-bit-rate coding. Our approach also allows the exploitation of the inherent redundancy of the human auditory system for the purpose of multiple description (joint source-channel coding.
Analysis for Cellinoid shape model in inverse process from lightcurves
Lu, Xiao-Ping; Ip, Wing-Huen; Huang, Xiang-Jie; Zhao, Hai-Bin
2017-01-01
Based on the special shape first introduced by Alberto Cellino, which consists of eight ellipsoidal octants with the constraint that adjacent octants must have two identical semi-axes, an efficient algorithm to derive the physical parameters, such as the rotational period, pole orientation, and overall shape from either lightcurves or sparse photometric data of asteroids, is developed by Lu et al. and named as 'Cellinoid' shape model. For thoroughly investigating the relationship between the morphology of the synthetic lightcurves generated by the Cellinoid shape and its six semi-axes as well as rotational period and pole, the numerical tests are implemented to compare the synthetic lightcurves generated by three Cellinoid models with different parameters in this article. Furthermore, from the synthetic lightcurves generated by two convex shape models of (6) Hebe and (4179) Toutatis, the inverse process based on Cellinoid shape model is applied to search the best-fit parameters. Especially, for better simulating the real observations, the synthetic lightcurves are generated under the orbit limit of the two asteroids. By comparing the results derived from synthetic lightcurves observed in one apparition and multiple apparitions, the performance of Cellinoid shape model is confirmed and the suggestions for observations are presented. Finally, the whole process is also applied to real observed lightcurves of (433) Eros and the derived results are consistent with the known results.
Locatelli, R.; Bousquet, P.; Chevallier, F.; Fortems-Cheney, A.; Szopa, S.; Saunois, M.; Agusti-Panareda, A.; Bergmann, D.; Bian, H.; Cameron-Smith, P.; Chipperfield, M.P.; Gloor, E.; Houweling, S.; Kawa, S.R.; Krol, M.C.; Patra, P.K.; Prinn, R.G.; Rigby, M.; Saito, R.; Wilson, C.
2013-01-01
A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, ar
Unified dark energy-dark matter model with inverse quintessence
Energy Technology Data Exchange (ETDEWEB)
Ansoldi, Stefano [ICRA — International Center for Relativistic Astrophysics, INFN — Istituto Nazionale di Fisica Nucleare, and Dipartimento di Matematica e Informatica, Università degli Studi di Udine, via delle Scienze 206, I-33100 Udine (UD) (Italy); Guendelman, Eduardo I., E-mail: ansoldi@fulbrightmail.org, E-mail: guendel@bgu.ac.il [Department of Physics, Ben-Gurion University of the Negeev, Beer-Sheva 84105 (Israel)
2013-05-01
We consider a model where both dark energy and dark matter originate from the coupling of a scalar field with a non-canonical kinetic term to, both, a metric measure and a non-metric measure. An interacting dark energy/dark matter scenario can be obtained by introducing an additional scalar that can produce non constant vacuum energy and associated variations in dark matter. The phenomenology is most interesting when the kinetic term of the additional scalar field is ghost-type, since in this case the dark energy vanishes in the early universe and then grows with time. This constitutes an ''inverse quintessence scenario'', where the universe starts from a zero vacuum energy density state, instead of approaching it in the future.
Electron electric dipole moment in Inverse Seesaw models
Abada, Asmaa
2016-01-01
We consider the contribution of sterile neutrinos to the electric dipole moment of charged leptons in the most minimal realisation of the Inverse Seesaw mechanism, in which the Standard Model is extended by two right-handed neutrinos and two sterile fermion states. Our study shows that the two pairs of (heavy) pseudo-Dirac mass eigenstates can give significant contributions to the electron electric dipole moment, lying close to future experimental sensitivity if their masses are above the electroweak scale. The major contribution comes from two-loop diagrams with pseudo-Dirac neutrino states running in the loops. In our analysis we further discuss the possibility of having a successful leptogenesis in this framework, compatible with a large electron electric dipole moment.
Nölting, Bengt
2006-01-01
Incorporating recent dramatic advances, this textbook presents a fresh and timely introduction to modern biophysical methods. An array of new, faster and higher-power biophysical methods now enables scientists to examine the mysteries of life at a molecular level. This innovative text surveys and explains the ten key biophysical methods, including those related to biophysical nanotechnology, scanning probe microscopy, X-ray crystallography, ion mobility spectrometry, mass spectrometry, proteomics, and protein folding and structure. Incorporating much information previously unavailable in tutorial form, Nölting employs worked examples and 267 illustrations to fully detail the techniques and their underlying mechanisms. Methods in Modern Biophysics is written for advanced undergraduate and graduate students, postdocs, researchers, lecturers and professors in biophysics, biochemistry and related fields. Special features in the 2nd edition: • Illustrates the high-resolution methods for ultrashort-living protei...
Nölting, Bengt
2010-01-01
Incorporating recent dramatic advances, this textbook presents a fresh and timely introduction to modern biophysical methods. An array of new, faster and higher-power biophysical methods now enables scientists to examine the mysteries of life at a molecular level. This innovative text surveys and explains the ten key biophysical methods, including those related to biophysical nanotechnology, scanning probe microscopy, X-ray crystallography, ion mobility spectrometry, mass spectrometry, proteomics, and protein folding and structure. Incorporating much information previously unavailable in tutorial form, Nölting employs worked examples and about 270 illustrations to fully detail the techniques and their underlying mechanisms. Methods in Modern Biophysics is written for advanced undergraduate and graduate students, postdocs, researchers, lecturers, and professors in biophysics, biochemistry and related fields. Special features in the 3rd edition: Introduces rapid partial protein ladder sequencing - an important...
Directory of Open Access Journals (Sweden)
R. Locatelli
2013-10-01
Full Text Available A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr−1 at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr−1 in North America to 7 Tg yr−1 in Boreal Eurasia (from 23 to 48%, respectively. At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly
Adjoint inversion modeling of Asian dust emission using lidar observations
Directory of Open Access Journals (Sweden)
K. Yumimoto
2008-06-01
Full Text Available A four-dimensional variational (4D-Var data assimilation system for a regional dust model (RAMS/CFORS-4DVAR; RC4 is applied to an adjoint inversion of a heavy dust event over eastern Asia during 20 March–4 April 2007. The vertical profiles of the dust extinction coefficients derived from NIES Lidar network are directly assimilated, with validation using observation data. Two experiments assess impacts of observation site selection: Experiment A uses five Japanese observation sites located downwind of dust source regions; Experiment B uses these and two other sites near source regions. Assimilation improves the modeled dust extinction coefficients. Experiment A and Experiment B assimilation results are mutually consistent, indicating that observations of Experiment A distributed over Japan can provide comprehensive information related to dust emission inversion. Time series data of dust AOT calculated using modeled and Lidar dust extinction coefficients improve the model results. At Seoul, Matsue, and Toyama, assimilation reduces the root mean square differences of dust AOT by 35–40%. However, at Beijing and Tsukuba, the RMS differences degrade because of fewer observations during the heavy dust event. Vertical profiles of the dust layer observed by CALIPSO are compared with assimilation results. The dense dust layer was trapped at potential temperatures (θ of 280–300 K and was higher toward the north; the model reproduces those characteristics well. Latitudinal distributions of modeled dust AOT along the CALIPSO orbit paths agree well with those of CALIPSO dust AOT, OMI AI, and MODIS coarse-mode AOT, capturing the latitude at which AOTs and AI have high values. Assimilation results show increased dust emissions over the Gobi Desert and Mongolia; especially for 29–30 March, emission flux is about 10 times greater. Strong dust uplift fluxes over the Gobi Desert and Mongolia cause the heavy dust event. Total optimized dust emissions are 57
Booth, E.; Chen, X.; Motew, M.; Qiu, J.; Zipper, S. C.; Carpenter, S. R.; Kucharik, C. J.; Steven, L. I.
2015-12-01
Scenario analysis is a powerful tool for envisioning future social-ecological change and its consequences on human well-being. Scenarios that integrate qualitative storylines and quantitative biophysical models can create a vivid picture of these potential futures but the integration process is not straightforward. We present - using the Yahara Watershed in southern Wisconsin (USA) as a case study - a method for developing quantitative inputs (climate, land use/cover, and land management) to drive a biophysical modeling suite based on four provocative and contrasting narrative scenarios that describe plausible futures of the watershed to 2070. The modeling suite consists of an agroecosystem model (AgroIBIS-VSF), hydrologic routing model (THMB), and empirical lake water quality model and estimates several biophysical indicators to evaluate the watershed system under each scenario. These indicators include water supply, lake flooding, agricultural production, and lake water quality. Climate (daily precipitation and air temperature) for each scenario was determined using statistics from 210 different downscaled future climate projections for two 20-year time periods (2046-2065 and 2081-2100) and modified using a stochastic weather generator to allow flexibility for matching specific climate events within the scenario narratives. Land use/cover for each scenario was determined first by quantifying changes in areal extent every decade for 15 categories at the watershed scale to be consistent with the storyline events and theme. Next, these changes were spatially distributed using a rule-based framework based on land suitability metrics that determine transition probabilities. Finally, agricultural inputs including manure and fertilizer application rates were determined for each scenario based on the prevalence of livestock, water quality regulations, and technological innovations. Each scenario is compared using model inputs (maps and time-series of land use/cover and
Koutsou, Achilleas; Bugmann, Guido; Christodoulou, Chris
2015-10-01
Biological systems are able to recognise temporal sequences of stimuli or compute in the temporal domain. In this paper we are exploring whether a biophysical model of a pyramidal neuron can detect and learn systematic time delays between the spikes from different input neurons. In particular, we investigate whether it is possible to reinforce pairs of synapses separated by a dendritic propagation time delay corresponding to the arrival time difference of two spikes from two different input neurons. We examine two subthreshold learning approaches where the first relies on the backpropagation of EPSPs (excitatory postsynaptic potentials) and the second on the backpropagation of a somatic action potential, whose production is supported by a learning-enabling background current. The first approach does not provide a learning signal that sufficiently differentiates between synapses at different locations, while in the second approach, somatic spikes do not provide a reliable signal distinguishing arrival time differences of the order of the dendritic propagation time. It appears that the firing of pyramidal neurons shows little sensitivity to heterosynaptic spike arrival time differences of several milliseconds. This neuron is therefore unlikely to be able to learn to detect such differences.
Vologodskii, Alexander
2015-01-01
Surveying the last sixty years of research, this book describes the physical properties of DNA in the context of its biological functioning. It is designed to enable both students and researchers of molecular biology, biochemistry and physics to better understand the biophysics of DNA, addressing key questions and facilitating further research. The chapters integrate theoretical and experimental approaches, emphasising throughout the importance of a quantitative knowledge of physical properties in building and analysing models of DNA functioning. For example, the book shows how the relationship between DNA mechanical properties and the sequence specificity of DNA-protein binding can be analyzed quantitatively by using our current knowledge of the physical and structural properties of DNA. Theoretical models and experimental methods in the field are critically considered to enable the reader to engage effectively with the current scientific literature on the physical properties of DNA.
An inverse problem approach to modelling coastal effluent plumes
Lam, D. C. L.; Murthy, C. R.; Miners, K. C.
Formulated as an inverse problem, the diffusion parameters associated with length-scale dependent eddy diffusivities can be viewed as the unknowns in the mass conservation equation for coastal zone transport problems. The values of the diffusion parameters can be optimized according to an error function incorporated with observed concentration data. Examples are given for the Fickian, shear diffusion and inertial subrange diffusion models. Based on a new set of dyeplume data collected in the coastal zone off Bronte, Lake Ontario, it is shown that the predictions of turbulence closure models can be evaluated for different flow conditions. The choice of computational schemes for this diagnostic approach is based on tests with analytic solutions and observed data. It is found that the optimized shear diffusion model produced a better agreement with observations for both high and low advective flows than, e.g., the unoptimized semi-empirical model, Ky=0.075 σy1.2, described by Murthy and Kenney.
A biophysical model of the mitochondrial respiratory system and oxidative phosphorylation.
Directory of Open Access Journals (Sweden)
Daniel A Beard
2005-09-01
Full Text Available A computational model for the mitochondrial respiratory chain that appropriately balances mass, charge, and free energy transduction is introduced and analyzed based on a previously published set of data measured on isolated cardiac mitochondria. The basic components included in the model are the reactions at complexes I, III, and IV of the electron transport system, ATP synthesis at F1F0 ATPase, substrate transporters including adenine nucleotide translocase and the phosphate-hydrogen co-transporter, and cation fluxes across the inner membrane including fluxes through the K+/H+ antiporter and passive H+ and K+ permeation. Estimation of 16 adjustable parameter values is based on fitting model simulations to nine independent data curves. The identified model is further validated by comparison to additional datasets measured from mitochondria isolated from rat heart and liver and observed at low oxygen concentration. To obtain reasonable fits to the available data, it is necessary to incorporate inorganic-phosphate-dependent activation of the dehydrogenase activity and the electron transport system. Specifically, it is shown that a model incorporating phosphate-dependent activation of complex III is able to reasonably reproduce the observed data. The resulting validated and verified model provides a foundation for building larger and more complex systems models and investigating complex physiological and pathophysiological interactions in cardiac energetics.
A Biophysical Model of the Mitochondrial Respiratory System and Oxidative Phosphorylation.
Directory of Open Access Journals (Sweden)
2005-09-01
Full Text Available A computational model for the mitochondrial respiratory chain that appropriately balances mass, charge, and free energy transduction is introduced and analyzed based on a previously published set of data measured on isolated cardiac mitochondria. The basic components included in the model are the reactions at complexes I, III, and IV of the electron transport system, ATP synthesis at F(1F(0 ATPase, substrate transporters including adenine nucleotide translocase and the phosphate-hydrogen co-transporter, and cation fluxes across the inner membrane including fluxes through the K/H antiporter and passive H and K permeation. Estimation of 16 adjustable parameter values is based on fitting model simulations to nine independent data curves. The identified model is further validated by comparison to additional datasets measured from mitochondria isolated from rat heart and liver and observed at low oxygen concentration. To obtain reasonable fits to the available data, it is necessary to incorporate inorganic-phosphate-dependent activation of the dehydrogenase activity and the electron transport system. Specifically, it is shown that a model incorporating phosphate-dependent activation of complex III is able to reasonably reproduce the observed data. The resulting validated and verified model provides a foundation for building larger and more complex systems models and investigating complex physiological and pathophysiological interactions in cardiac energetics.
A biophysically based mathematical model for the catalytic mechanism of glutathione reductase.
Pannala, Venkat R; Bazil, Jason N; Camara, Amadou K S; Dash, Ranjan K
2013-12-01
Glutathione reductase (GR) catalyzes the reduction of oxidized glutathione (GSSG) to reduced glutathione (GSH) using NADPH as the reducing cofactor, and thereby maintains a constant GSH level in the system. GSH scavenges superoxide (O2(*-)) and hydroxyl radicals (OH) nonenzymatically or by serving as an electron donor to several enzymes involved in reactive oxygen species (ROS) detoxification. In either case, GSH oxidizes to GSSG and is subsequently regenerated by the catalytic action of GR. Although the GR kinetic mechanism has been extensively studied under various experimental conditions with variable substrates and products, the catalytic mechanism has not been studied in terms of a mechanistic model that accounts for the effects of the substrates and products on the reaction kinetics. The aim of this study is therefore to develop a comprehensive mathematical model for the catalytic mechanism of GR. We use available experimental data on GR kinetics from various species/sources to develop the mathematical model and estimate the associated model parameters. The model simulations are consistent with the experimental observation that GR operates via both ping-pong and sequential branching mechanisms based on relevant concentrations of its reaction substrate GSSG. Furthermore, we show the observed pH-dependent substrate inhibition of GR activity by GSSG and bimodal behavior of GR activity with pH. The model presents a unique opportunity to understand the effects of products on the kinetics of GR. The model simulations show that under physiological conditions, where both substrates and products are present, the flux distribution depends on the concentrations of both GSSG and NADP(+), with ping-pong flux operating at low levels and sequential flux dominating at higher levels. The kinetic model of GR may serve as a key module for the development of integrated models for ROS-scavenging systems to understand protection of cells under normal and oxidative stress
Exploring the Red Sea seasonal ecosystem functioning using a three-dimensional biophysical model
Triantafyllou, G.
2014-03-01
The Red Sea exhibits complex hydrodynamic and biogeochemical dynamics, which vary both in time and space. These dynamics have been explored through the development and application of a 3-D ecosystem model. The simulation system comprises two off-line coupled submodels: the MIT General Circulation Model (MITgcm) and the European Regional Seas Ecosystem Model (ERSEM), both adapted for the Red Sea. The results from an annual simulation under climatological forcing are presented. Simulation results are in good agreement with satellite and in situ data illustrating the role of the physical processes in determining the evolution and variability of the Red Sea ecosystem. The model was able to reproduce the main features of the Red Sea ecosystem functioning, including the exchange with the Gulf of Aden, which is a major driving mechanism for the whole Red Sea ecosystem and the winter overturning taking place in the north. Some model limitations, mainly related to the dynamics of the extended reef system located in the southern part of the Red Sea, which is not currently represented in the model, still need to be addressed.
Biophysical Interactions in Porous Media: an Integrated Experimental and Modelling Approach
Otten, W.; Baveye, P.; Falconer, R.
2012-12-01
A critical feature of porous media is that the geometry provides habitats of a complexity that is not seen above ground, offering shelter, food water and gasses to microorganisms, who's spatial and temporal dynamics are shaped by this microscopic heterogeneity. The microbial dynamics, including fungal and bacterial growth, in turn affect the geometry and the hydrological properties, shaping the pore architecture at short and long time scales, altering surface tension, and (partially) blocking pores, thereby affecting the flow paths of water through a structure. Crucially, the majority of these processes occur at microscopic scales with impact on larger scale ecological processes and ecosystem services. The complexity of these interacting processes and feed-back mechanisms at first may seem overwhelming. However, we show in this paper how with recent progress in experimental techniques, integrated with a modelling approach we can begin to understand the importance of microscopic heterogeneity on microbial dynamics. We will demonstrate this integrated approach for fungal dynamics in porous media such as soil through a combination of novel experimental tools and mathematical modelling. Using benchtop X-ray CT systems we present the finer detail of pore structure at scales relevant for microbial processes, and present our recent advances in the use of theoretical tools to rigorously characterise, and quantitatively describe this environment, and present the state-of-the art with respect to visualization of water in porous media. Severe challenges remain with studying the spatial distribution of microorganisms. We present how biological thin sectioning techniques offer a way forward to study the spatial distribution of fungi and bacteria within pore geometries. Through a series of detailed experiments we show how pathways, resulting from connected pore volumes and distribution of water within them, are preferentially explored during fungal invasion. We complement the
Abdellah, Marwan
2017-02-15
Background We present a visualization pipeline capable of accurate rendering of highly scattering fluorescent neocortical neuronal models. The pipeline is mainly developed to serve the computational neurobiology community. It allows the scientists to visualize the results of their virtual experiments that are performed in computer simulations, or in silico. The impact of the presented pipeline opens novel avenues for assisting the neuroscientists to build biologically accurate models of the brain. These models result from computer simulations of physical experiments that use fluorescence imaging to understand the structural and functional aspects of the brain. Due to the limited capabilities of the current visualization workflows to handle fluorescent volumetric datasets, we propose a physically-based optical model that can accurately simulate light interaction with fluorescent-tagged scattering media based on the basic principles of geometric optics and Monte Carlo path tracing. We also develop an automated and efficient framework for generating dense fluorescent tissue blocks from a neocortical column model that is composed of approximately 31000 neurons. Results Our pipeline is used to visualize a virtual fluorescent tissue block of 50 μm3 that is reconstructed from the somatosensory cortex of juvenile rat. The fluorescence optical model is qualitatively analyzed and validated against experimental emission spectra of different fluorescent dyes from the Alexa Fluor family. Conclusion We discussed a scientific visualization pipeline for creating images of synthetic neocortical neuronal models that are tagged virtually with fluorescent labels on a physically-plausible basis. The pipeline is applied to analyze and validate simulation data generated from neuroscientific in silico experiments.
Thomas, Yoann; Dumas, Franck; Andréfouët, Serge
2016-12-01
The black-lip pearl oyster (Pinctada margaritifera) is cultured extensively to produce black pearls, especially in French Polynesia atoll lagoons. This aquaculture relies on spat collection, a process that experiences spatial and temporal variability and needs to be optimized by understanding which factors influence recruitment. Here, we investigate the sensitivity of P. margaritifera larval dispersal to both physical and biological factors in the lagoon of Ahe atoll. Coupling a validated 3D larval dispersal model, a bioenergetics larval growth model following the Dynamic Energy Budget (DEB) theory, and a population dynamics model, the variability of lagoon-scale connectivity patterns and recruitment potential is investigated. The relative contribution of reared and wild broodstock to the lagoon-scale recruitment potential is also investigated. Sensitivity analyses pointed out the major effect of the broodstock population structure as well as the sensitivity to larval mortality rate and inter-individual growth variability to larval supply and to the subsequent settlement potential. The application of the growth model clarifies how trophic conditions determine the larval supply and connectivity patterns. These results provide new cues to understand the dynamics of bottom-dwelling populations in atoll lagoons, their recruitment, and discuss how to take advantage of these findings and numerical models for pearl oyster management.
A MODEL FOR PREDICTING PHASE INVERSION IN OIL-WATER TWO-PHASE PIPE FLOW
Institute of Scientific and Technical Information of China (English)
GONG Jing; LI Qing-ping; YAO Hai-yuan; YU Da
2006-01-01
Experiments of phase inversion characteristics for horizontal oil-water two-phase flow in a stainless steel pipe loop (25.7 mm inner diameter,52 m long) are conducted. A new viewpoint is brought forward about the process of phase inversion in oil-water two-phase pipe flow. Using the relations between the total free energies of the pre-inversion and post-inversion dispersions, a model for predicting phase inversion in oil-water two-phase pipe flow has been developed that considers the characteristics of pipe flow. This model is compared against other models with relevant data of phase inversion in oil-water two-phase pipe flow. Results indicate that this model is better than other models in terms of calculation precision and applicability. The model is useful for guiding the design for optimal performance and safety in the operation of oil-water two-phase pipe flow in oil fields.
A MATLAB based 3D modeling and inversion code for MT data
Singh, Arun; Dehiya, Rahul; Gupta, Pravin K.; Israil, M.
2017-07-01
The development of a MATLAB based computer code, AP3DMT, for modeling and inversion of 3D Magnetotelluric (MT) data is presented. The code comprises two independent components: grid generator code and modeling/inversion code. The grid generator code performs model discretization and acts as an interface by generating various I/O files. The inversion code performs core computations in modular form - forward modeling, data functionals, sensitivity computations and regularization. These modules can be readily extended to other similar inverse problems like Controlled-Source EM (CSEM). The modular structure of the code provides a framework useful for implementation of new applications and inversion algorithms. The use of MATLAB and its libraries makes it more compact and user friendly. The code has been validated on several published models. To demonstrate its versatility and capabilities the results of inversion for two complex models are presented.
Inverse modelling of national and European CH4 emissions using the atmospheric zoom model TM5
Bergamaschi, P.; Krol, M.C.; Dentener, F.; Vermeulen, A.; Meinhardt, F.; Graul, R.; Ramonet, M.; Peters, W.; Dlugokencky, E.J.
2005-01-01
A synthesis inversion based on the atmospheric zoom model TM5 is used to derive top-down estimates of CH4 emissions from individual European countries for the year 2001. We employ a model zoom over Europe with 1° × 1° resolution that is two-way nested into the global model domain (with resolution of
A biophysical model of cell adhesion mediated by immunoadhesin drugs and antibodies.
Directory of Open Access Journals (Sweden)
Ryan N Gutenkunst
Full Text Available A promising direction in drug development is to exploit the ability of natural killer cells to kill antibody-labeled target cells. Monoclonal antibodies and drugs designed to elicit this effect typically bind cell-surface epitopes that are overexpressed on target cells but also present on other cells. Thus it is important to understand adhesion of cells by antibodies and similar molecules. We present an equilibrium model of such adhesion, incorporating heterogeneity in target cell epitope density, nonspecific adhesion forces, and epitope immobility. We compare with experiments on the adhesion of Jurkat T cells to bilayers containing the relevant natural killer cell receptor, with adhesion mediated by the drug alefacept. We show that a model in which all target cell epitopes are mobile and available is inconsistent with the data, suggesting that more complex mechanisms are at work. We hypothesize that the immobile epitope fraction may change with cell adhesion, and we find that such a model is more consistent with the data, although discrepancies remain. We also quantitatively describe the parameter space in which binding occurs. Our model elaborates substantially on previous work, and our results offer guidance for the refinement of therapeutic immunoadhesins. Furthermore, our comparison with data from Jurkat T cells also points toward mechanisms relating epitope immobility to cell adhesion.
Directory of Open Access Journals (Sweden)
Steven Niederer
Full Text Available The myocardial ischemic border zone is associated with the initiation and sustenance of arrhythmias. The profile of ionic concentrations across the border zone play a significant role in determining cellular electrophysiology and conductivity, yet their spatial-temporal evolution and regulation are not well understood. To investigate the changes in ion concentrations that regulate cellular electrophysiology, a mathematical model of ion movement in the intra and extracellular space in the presence of ionic, potential and material property heterogeneities was developed. The model simulates the spatial and temporal evolution of concentrations of potassium, sodium, chloride, calcium, hydrogen and bicarbonate ions and carbon dioxide across an ischemic border zone. Ischemia was simulated by sodium-potassium pump inhibition, potassium channel activation and respiratory and metabolic acidosis. The model predicted significant disparities in the width of the border zone for each ionic species, with intracellular sodium and extracellular potassium having discordant gradients, facilitating multiple gradients in cellular properties across the border zone. Extracellular potassium was found to have the largest border zone and this was attributed to the voltage dependence of the potassium channels. The model also predicted the efflux of [Formula: see text] from the ischemic region due to electrogenic drift and diffusion within the intra and extracellular space, respectively, which contributed to [Formula: see text] depletion in the ischemic region.
Analytical Charge Voltage Model in MOS Inversion Layer Based on Space Charge Capacitance
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The concept of Space Charge Capacitance (SCC) is proposed and used to make a novel analytical charge model of quantized inversion layer in MOS structures. Based on SCC,continuous expressions of surface potential and inversion layer carrier density are derived.Quantum mechanical effects on both inversion layer carrier density and surface potential are extensively included. The accuracy of the model is verified by the numerical solution to Schrodinger and Poisson equation and the model is demonstrated,too.
Glacial Amazonia at the canopy-scale: Using a biophysical model to understand forest robustness
Sato, Hiromitsu; Cowling, Sharon Anne
2017-09-01
A canopy-scale model (CANOAK) was used to simulate lowland Amazonia during the Last Glacial Maximum. Modeled values of Net Ecosystem Exchange driven by glacial environmental conditions were roughly half the magnitude of modern fluxes. Factorial experiments reveal lowered [CO2] to be the primary cause of reduced carbon fluxes while lowered air temperatures enhance net carbon uptake. LGM temperatures are suggested to be closer to optimal for carbon uptake than modern temperatures, explained through the canopy energy balance. Further analysis of the canopy energy balance and resultant leaf temperature regime provide viable mechanisms to explain enhanced carbon-water relations at lowered temperatures and forest robustness over glaciations. An ecophysiological phenomena known as the 'cross-over' point, wherein leaf temperatures sink below air temperature, was reproduced and found to demarcate critical changes in energy balance partitioning.
DEFF Research Database (Denmark)
Hartwigsen, Gesa; Bergmann, Til Ole; Herz, Damian Marc
2015-01-01
Noninvasive transcranial brain stimulation (NTBS) is widely used to elucidate the contribution of different brain regions to various cognitive functions. Here we present three modeling approaches that are informed by functional or structural brain mapping or behavior profiling and discuss how...... predictions regarding the impact of interindividual variations in cortical anatomy on the injected electric fields or the influence of the orientation of current flow on the physiological stimulation effects. (ii) Functional brain mapping of the spatiotemporal neural dynamics during cognitive tasks can...
A Biophysical Model of the Mitochondrial ATP-Mg/Pi Carrier
2012-01-01
Mitochondrial adenine nucleotide (AdN) content is regulated through the Ca2+-activated, electroneutral ATP-Mg/Pi carrier (APC). The APC is a protein in the mitochondrial carrier super family that localizes to the inner mitochondrial membrane (IMM). It is known to modulate a number of processes that depend on mitochondrial AdN content, such as gluconeogenesis, protein synthesis, and citrulline synthesis. Despite this critical role, a kinetic model of the underlying mechanism has not been devel...
Biophysical model of the role of actin remodeling on dendritic spine morphology
Miermans, C. A.; Kusters, R. P. T.; Hoogenraad, C. C.; Storm, C.
2017-01-01
Dendritic spines are small membranous structures that protrude from the neuronal dendrite. Each spine contains a synaptic contact site that may connect its parent dendrite to the axons of neighboring neurons. Dendritic spines are markedly distinct in shape and size, and certain types of stimulation prompt spines to evolve, in fairly predictable fashion, from thin nascent morphologies to the mushroom-like shapes associated with mature spines. It is well established that the remodeling of spines is strongly dependent upon the actin cytoskeleton inside the spine. A general framework that details the precise role of actin in directing the transitions between the various spine shapes is lacking. We address this issue, and present a quantitative, model-based scenario for spine plasticity validated using realistic and physiologically relevant parameters. Our model points to a crucial role for the actin cytoskeleton. In the early stages of spine formation, the interplay between the elastic properties of the spine membrane and the protrusive forces generated in the actin cytoskeleton propels the incipient spine. In the maturation stage, actin remodeling in the form of the combined dynamics of branched and bundled actin is required to form mature, mushroom-like spines. Importantly, our model shows that constricting the spine-neck aids in the stabilization of mature spines, thus pointing to a role in stabilization and maintenance for additional factors such as ring-like F-actin structures. Taken together, our model provides unique insights into the fundamental role of actin remodeling and polymerization forces during spine formation and maturation. PMID:28158194
Kapur, M. R.
2016-02-01
Simulative models of reef ecosystems have been used to evaluate ecological responses to a myriad of disturbance events, including fishing pressure, coral bleaching, invasion by alien species, and nutrient loading. The Coral Reef Scenario Evaluation Tool (CORSET), has been developed and instantiated for both the Meso-American Reef (MAR) and South China Sea (SCS) regions. This model is novel in that it accounts for the many scales at which reef ecosystem processes take place; is comprised of a "bottom-up" structure wherein complex behaviors are not pre-programmed, but emergent and highly portable to new systems. Local-scale dynamics are coupled across regions through larval connectivity matrices, derived sophisticated particle transport simulations that include key elements of larval behavior. By this approach, we are able to directly evaluate some of the potential consequences of larval connectivity patterns across a range of spatial scales and under multiple climate scenarios. This work develops and applies the CORSET (Coral Reef Scenario Evaluation Tool) to the Main Hawaiian Islands under a suite of climate and ecological scenarios. We introduce an adaptation constant into reef-building coral dynamics to simulate observed resiliencies to bleaching events. This presentation will share results from the model's instantiation under two Resource Concentration Pathway climate scenarios, with emphasis upon larval connectivity dynamics, emergent coral tolerance to increasing thermal anomalies, and patterns of spatial fishing closures. Results suggest that under a business-as-usual scenario, thermal tolerance and herbivore removal will have synergistic effects on reef resilience.
T-wave alternans: lessons learned from a biophysical ECG model.
Sassi, Roberto; Mainardi, Luca T
2012-01-01
T-wave alternans (TWA) is an alteration of the ECG T-wave which repeats every other beat. An alternating pattern has been also observed at myocytes level, involving both action potential duration and morphology (mainly in phases 2 and 3). While this might happen in a specific region (i.e., myocardial ischemia), it can also involve the entire myocardium. It is still unclear how alternations at the myocytes level are reflected on surface ECG modification of T-waves, especially when in vivo human hearts are considered. We have recently proposed a simple stochastic model of ventricular repolarization (IEEE Trans. Biomed. Eng., 2011), which takes into account both repolarization heterogeneity across the myocardium as well as random beat-to-beat variations in cells' activity. In this work, we generalized that model incorporating a term which describes myocytes alternans related to T-wave variability. Starting from the model and using the electrophysiological formulation developed by van Oosterom, we derived an analytical formula relating surface ECG to variations at the myocytes' level. Several theoretical results were then obtained. First, temporal small random variations in repolarization heterogeneity affect the precision of TWA estimates in a significant way. Second, TWA theoretically differs across leads, but multilead configuration can be used to reduce the effect of noise. Finally, the dependency between TWA and T-wave amplitude was analyzed.
Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban Centers
Directory of Open Access Journals (Sweden)
Mohammad Z. Al-Hamdan
2016-11-01
Full Text Available In this paper, we assessed and compared land surface temperature (LST in urban centers using data from Landsat, MODIS, and the Simple Biosphere model (SiB2. We also evaluated the sensitivity of the model’s LST to different land cover types, fractions (percentages, and emissivities compared to reference points derived from Landsat thermal data. This was demonstrated in three climatologically- and morphologically-different cities of Atlanta, GA, New York, NY, and Washington, DC. Our results showed that in these cities SiB2 was sensitive to both the emissivity and the land cover type and fraction, but much more sensitive to the latter. The practical implications of these results are rather significant since they imply that the SiB2 model can be used to run different scenarios for evaluating urban heat island (UHI mitigation strategies. This study also showed that using detailed emissivities per land cover type and fractions from Landsat-derived data caused a convergence of the model results towards the Landsat-derived LST for most of the studied cases. This study also showed that SiB2 LSTs are closer in magnitude to Landsat-derived LSTs than MODIS-derived LSTs. It is important, however, to emphasize that both Landsat and MODIS LSTs are not direct observations and, as such, do not represent a ground truth. More studies will be needed to compare these results to in situ LST data and provide further validation.
Sathar, Shameer; Trew, Mark L.; Du, Peng; O’ Grady, Greg; Cheng, Leo K.
2014-01-01
Gastrointestinal motility is coordinated by slow waves (SWs) generated by the interstitial cells of Cajal (ICC). Experimental studies have shown that SWs spontaneously activate at different intrinsic frequencies in isolated tissue, whereas in intact tissues they are entrained to a single frequency. Gastric pacing has been used in an attempt to improve motility in disorders such as gastroparesis by modulating entrainment, but the optimal methods of pacing are currently unknown. Computational models can aid in the interpretation of complex in-vivo recordings and help to determine optical pacing strategies. However, previous computational models of SW entrainment are limited to the intrinsic pacing frequency as the primary determinant of the conduction velocity, and are not able to accurately represent the effects of external stimuli and electrical anisotropies. In this paper, we present a novel computationally efficient method for modelling SW propagation through the ICC network while accounting for conductivity parameters and fiber orientations. The method successfully reproduced experimental recordings of entrainment following gastric transection and the effects of gastric pacing on SW activity. It provides a reliable new tool for investigating gastric electrophysiology in normal and diseased states, and to guide and focus future experimental studies. PMID:24276722
Study of TEC fluctuation via stochastic models and Bayesian inversion
Bires, A.; Roininen, L.; Damtie, B.; Nigussie, M.; Vanhamäki, H.
2016-11-01
We propose stochastic processes to be used to model the total electron content (TEC) observation. Based on this, we model the rate of change of TEC (ROT) variation during ionospheric quiet conditions with stationary processes. During ionospheric disturbed conditions, for example, when irregularity in ionospheric electron density distribution occurs, stationarity assumption over long time periods is no longer valid. In these cases, we make the parameter estimation for short time scales, during which we can assume stationarity. We show the relationship between the new method and commonly used TEC characterization parameters ROT and the ROT Index (ROTI). We construct our parametric model within the framework of Bayesian statistical inverse problems and hence give the solution as an a posteriori probability distribution. Bayesian framework allows us to model measurement errors systematically. Similarly, we mitigate variation of TEC due to factors which are not of ionospheric origin, like due to the motion of satellites relative to the receiver, by incorporating a priori knowledge in the Bayesian model. In practical computations, we draw the so-called maximum a posteriori estimates, which are our ROT and ROTI estimates, from the posterior distribution. Because the algorithm allows to estimate ROTI at each observation time, the estimator does not depend on the period of time for ROTI computation. We verify the method by analyzing TEC data recorded by GPS receiver located in Ethiopia (11.6°N, 37.4°E). The results indicate that the TEC fluctuations caused by the ionospheric irregularity can be effectively detected and quantified from the estimated ROT and ROTI values.
Inverse limits and statistical properties for chaotic implicitly defined economic models
Mihailescu, Eugen
2011-01-01
In this paper we study the dynamics and ergodic theory of certain economic models which are implicitly defined. We consider 1-dimensional and 2-dimensional overlapping generations models, a cash-in-advance model, heterogeneous markets and a cobweb model with adaptive adjustment. We consider the inverse limit spaces of certain chaotic invariant fractal sets and their metric, ergodic and stability properties. The inverse limits give the set of intertemporal perfect foresight equilibria for the economic problem considered. First we show that the inverse limits of these models are stable under perturbations. We prove that the inverse limits are expansive and have specification property. We then employ utility functions on inverse limits in our case. We give two ways to rank such utility functions. First, when perturbing certain dynamical systems, we rank utility functions in terms of their \\textit{average values} with respect to invariant probability measures on inverse limits, especially with respect to measures...
Inverse modeling for heat conduction problem in human abdominal phantom.
Huang, Ming; Chen, Wenxi
2011-01-01
Noninvasive methods for deep body temperature measurement are based on the principle of heat equilibrium between the thermal sensor and the target location theoretically. However, the measurement position is not able to be definitely determined. In this study, a 2-dimensional mathematical model was built based upon some assumptions for the physiological condition of the human abdomen phantom. We evaluated the feasibility in estimating the internal organs temperature distribution from the readings of the temperature sensors arranged on the skin surface. It is a typical inverse heat conduction problem (IHCP), and is usually mathematically ill-posed. In this study, by integrating some physical and physiological a-priori information, we invoked the quasi-linear (QL) method to reconstruct the internal temperature distribution. The solutions of this method were improved by increasing the accuracy of the sensors and adjusting their arrangement on the outer surface, and eventually reached the state of converging at the best state accurately. This study suggests that QL method is able to reconstruct the internal temperature distribution in this phantom and might be worthy of a further study in an anatomical based model.
Forecasting wind-driven wildfires using an inverse modelling approach
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O. Rios
2014-06-01
Full Text Available A technology able to rapidly forecast wildfire dynamics would lead to a paradigm shift in the response to emergencies, providing the Fire Service with essential information about the ongoing fire. This paper presents and explores a novel methodology to forecast wildfire dynamics in wind-driven conditions, using real-time data assimilation and inverse modelling. The forecasting algorithm combines Rothermel's rate of spread theory with a perimeter expansion model based on Huygens principle and solves the optimisation problem with a tangent linear approach and forward automatic differentiation. Its potential is investigated using synthetic data and evaluated in different wildfire scenarios. The results show the capacity of the method to quickly predict the location of the fire front with a positive lead time (ahead of the event in the order of 10 min for a spatial scale of 100 m. The greatest strengths of our method are lightness, speed and flexibility. We specifically tailor the forecast to be efficient and computationally cheap so it can be used in mobile systems for field deployment and operativeness. Thus, we put emphasis on producing a positive lead time and the means to maximise it.
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Tetsuya Uetake
2014-08-01
Full Text Available Promoting environmentally friendly farming products is crucial to meeting consumer demand. Although governments implement policy measures to improve the environmental performance of the agriculture sector, theirimpacts are difficult to assess. This study analyses the performance of agri‐environmental policies in Japan, by using the OECD’s policy impact model and reference level framework. In particular, it identifies the environmental impacts of three simulated agri‐environmental policies based on farms’ characteristics. The results suggest that a policy mix of regulation and an incentive payment would reduce environmental impacts, suggesting that targeted approaches could improve the cost‐effectiveness of agri‐environmental policies.
Fedosov, Dmitry
2011-03-01
Computational biophysics is a large and rapidly growing area of computational physics. In this talk, we will focus on a number of biophysical problems related to blood cells and blood flow in health and disease. Blood flow plays a fundamental role in a wide range of physiological processes and pathologies in the organism. To understand and, if necessary, manipulate the course of these processes it is essential to investigate blood flow under realistic conditions including deformability of blood cells, their interactions, and behavior in the complex microvascular network. Using a multiscale cell model we are able to accurately capture red blood cell mechanics, rheology, and dynamics in agreement with a number of single cell experiments. Further, this validated model yields accurate predictions of the blood rheological properties, cell migration, cell-free layer, and hemodynamic resistance in microvessels. In addition, we investigate blood related changes in malaria, which include a considerable stiffening of red blood cells and their cytoadherence to endothelium. For these biophysical problems computational modeling is able to provide new physical insights and capabilities for quantitative predictions of blood flow in health and disease.
Školová, Barbora; Kováčik, Andrej; Tesař, Ondřej; Opálka, Lukáš; Vávrová, Kateřina
2017-05-01
Ceramides based on phytosphingosine, sphingosine and dihydrosphingosine are essential constituents of the skin lipid barrier that protects the body from excessive water loss. The roles of the individual ceramide subclasses in regulating skin permeability and the reasons for C4-hydroxylation of these sphingolipids are not completely understood. We investigated the chain length-dependent effects of dihydroceramides, sphingosine ceramides (with C4-unsaturation) and phytoceramides (with C4-hydroxyl) on the permeability, lipid organization and thermotropic behavior of model stratum corneum lipid membranes composed of ceramide/lignoceric acid/cholesterol/cholesteryl sulfate. Phytoceramides with very long C24 acyl chains increased the permeability of the model lipid membranes compared to dihydroceramides or sphingosine ceramides with the same chain lengths. Either unsaturation or C4-hydroxylation of dihydroceramides induced chain length-dependent increases in membrane permeability. Infrared spectroscopy showed that C4-hydroxylation of the sphingoid base decreased the relative ratio of orthorhombic chain packing in the membrane and lowered the miscibility of C24 phytoceramide with lignoceric acid. The phase separation in phytoceramide membranes was confirmed by X-ray diffraction. In contrast, phytoceramides formed strong hydrogen bonds and highly thermostable domains. Thus, the large heterogeneity in ceramide structures and in their aggregation mechanisms may confer resistance towards the heterogeneous external stressors that are constantly faced by the skin barrier. Copyright © 2017 Elsevier B.V. All rights reserved.
An integrated Biophysical CGE model to provide Sustainable Development Goal insights
Sanchez, Marko; Cicowiez, Martin; Howells, Mark; Zepeda, Eduardo
2016-04-01
Future projected changes in the energy system will inevitably result in changes to the level of appropriation of environmental resources, particularly land and water, and this will have wider implications for environmental sustainability, and may affect other sectors of the economy. An integrated climate, land, energy and water (CLEW) system will provide useful insights, particularly with regard to the environmental sustainability. However, it will require adequate integration with other tools to detect economic impacts and broaden the scope for policy analysis. A computable general equilibrium (CGE) model is a well suited tool to channel impacts, as detected in a CLEW analysis, onto all sectors of the economy, and evaluate trade-offs and synergies, including those of possible policy responses. This paper will show an application of such integration in a single-country CGE model with the following key characteristics. Climate is partly exogenous (as proxied by temperature and rainfall) and partly endogenous (as proxied by emissions generated by different sectors) and has an impact on endogenous variables such as land productivity and labor productivity. Land is a factor of production used in agricultural and forestry activities which can be of various types if land use alternatives (e.g., deforestation) are to be considered. Energy is an input to the production process of all economic sectors and a consumption good for households. Because it is possible to allow for substitution among different energy sources (e.g. renewable vs non-renewable) in the generation of electricity, the production process of energy products can consider the use of natural resources such as oil and water. Water, data permitting, can be considered as an input into the production process of agricultural sectors, which is particularly relevant in case of irrigation. It can also be considered as a determinant of total factor productivity in hydro-power generation. The integration of a CLEW
Forward- vs. Inverse Problems in Modeling Seismic Attenuation
Morozov, I. B.
2015-12-01
Seismic attenuation is an important property of wave propagation used in numerous applications. However, the attenuation is also a complex phenomenon, and it is important to differentiate between its two typical uses: 1) in forward problems, to model the amplitudes and spectral contents of waves required for hazard assessment and geotechnical engineering, and 2) in inverse problems, to determine the physical properties of the subsurface. In the forward-problem sense, the attenuation is successfully characterized in terms of empirical parameters of geometric spreading, radiation patterns, scattering amplitudes, t-star, alpha, kappa, or Q. Arguably, the predicted energy losses can be correct even if the underlying attenuation model is phenomenological and not sufficiently based on physics. An example of such phenomenological model is the viscoelasticity based on the correspondence principle and the Q-factor assigned to the material. By contrast, when used to invert for in situ material properties, models addressing the specific physics are required. In many studies (including in this session), a Q-factor is interpreted as a property of a point within the subsurface; however this property is only phenomenological and may be physically insufficient or inconsistent. For example, the bulk or shear Q at the same point can be different when evaluated from different wave modes. The cases of frequency-dependent Q are particularly prone of ambiguities such as trade-off with the assumed background geometric spreading. To rigorously characterize the in situ material properties responsible for seismic-wave attenuation, it is insufficient to only focus on the seismic energy loss. Mechanical models of the material need to be considered. Such models can be constructed by using Lagrangian mechanics. These models should likely contain no Q but will be based on parameters of microstructure such as heterogeneity, fractures, or fluids. I illustrate several such models based on viscosity
Modeling the biophysical impacts of global change in mountain biosphere reserves
Bugmann, H.K.M.; Bjornsen, F. Ewert; Haeberli, W.; Guisan, A.; Fagre, Daniel B.; Kaab, A.
2007-01-01
Mountains and mountain societies provide a wide range of goods and services to humanity, but they are particularly sensitive to the effects of global environmental change. Thus, the definition of appropriate management regimes that maintain the multiple functions of mountain regions in a time of greatly changing climatic, economic, and societal drivers constitutes a significant challenge. Management decisions must be based on a sound understanding of the future dynamics of these systems. The present article reviews the elements required for an integrated effort to project the impacts of global change on mountain regions, and recommends tools that can be used at 3 scientific levels (essential, improved, and optimum). The proposed strategy is evaluated with respect to UNESCO's network of Mountain Biosphere Reserves (MBRs), with the intention of implementing it in other mountain regions as well. First, methods for generating scenarios of key drivers of global change are reviewed, including land use/land cover and climate change. This is followed by a brief review of the models available for projecting the impacts of these scenarios on (1) cryospheric systems, (2) ecosystem structure and diversity, and (3) ecosystem functions such as carbon and water relations. Finally, the cross-cutting role of remote sensing techniques is evaluated with respect to both monitoring and modeling efforts. We conclude that a broad range of techniques is available for both scenario generation and impact assessments, many of which can be implemented without much capacity building across many or even most MBRs. However, to foster implementation of the proposed strategy, further efforts are required to establish partnerships between scientists and resource managers in mountain areas.
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Anshuman Dixit
Full Text Available Deciphering functional mechanisms of the Hsp90 chaperone machinery is an important objective in cancer biology aiming to facilitate discovery of targeted anti-cancer therapies. Despite significant advances in understanding structure and function of molecular chaperones, organizing molecular principles that control the relationship between conformational diversity and functional mechanisms of the Hsp90 activity lack a sufficient quantitative characterization. We combined molecular dynamics simulations, principal component analysis, the energy landscape model and structure-functional analysis of Hsp90 regulatory interactions to systematically investigate functional dynamics of the molecular chaperone. This approach has identified a network of conserved regions common to the Hsp90 chaperones that could play a universal role in coordinating functional dynamics, principal collective motions and allosteric signaling of Hsp90. We have found that these functional motifs may be utilized by the molecular chaperone machinery to act collectively as central regulators of Hsp90 dynamics and activity, including the inter-domain communications, control of ATP hydrolysis, and protein client binding. These findings have provided support to a long-standing assertion that allosteric regulation and catalysis may have emerged via common evolutionary routes. The interaction networks regulating functional motions of Hsp90 may be determined by the inherent structural architecture of the molecular chaperone. At the same time, the thermodynamics-based "conformational selection" of functional states is likely to be activated based on the nature of the binding partner. This mechanistic model of Hsp90 dynamics and function is consistent with the notion that allosteric networks orchestrating cooperative protein motions can be formed by evolutionary conserved and sparsely connected residue clusters. Hence, allosteric signaling through a small network of distantly connected
Glaser, Roland
2012-01-01
Biophysics is the science of physical principles underlying all processes of life, including the dynamics and kinetics of biological systems. This fully revised 2nd English edition is an introductory text that spans all steps of biological organization, from the molecular, to the organism level, as well as influences of environmental factors. In response to the enormous progress recently made, especially in theoretical and molecular biophysics, the author has updated the text, integrating new results and developments concerning protein folding and dynamics, molecular aspects of membrane assembly and transport, noise-enhanced processes, and photo-biophysics. The advances made in theoretical biology in the last decade call for a fully new conception of the corresponding sections. Thus, the book provides the background needed for fundamental training in biophysics and, in addition, offers a great deal of advanced biophysical knowledge.
Modelling and genetic algorithm based optimisation of inverse supply chain
Bányai, T.
2009-04-01
(Recycling of household appliances with emphasis on reuse options). The purpose of this paper is the presentation of a possible method for avoiding the unnecessary environmental risk and landscape use through unprovoked large supply chain of collection systems of recycling processes. In the first part of the paper the author presents the mathematical model of recycling related collection systems (applied especially for wastes of electric and electronic products) and in the second part of the work a genetic algorithm based optimisation method will be demonstrated, by the aid of which it is possible to determine the optimal structure of the inverse supply chain from the point of view economical, ecological and logistic objective functions. The model of the inverse supply chain is based on a multi-level, hierarchical collection system. In case of this static model it is assumed that technical conditions are permanent. The total costs consist of three parts: total infrastructure costs, total material handling costs and environmental risk costs. The infrastructure-related costs are dependent only on the specific fixed costs and the specific unit costs of the operation points (collection, pre-treatment, treatment, recycling and reuse plants). The costs of warehousing and transportation are represented by the material handling related costs. The most important factors determining the level of environmental risk cost are the number of out of time recycled (treated or reused) products, the number of supply chain objects and the length of transportation routes. The objective function is the minimization of the total cost taking into consideration the constraints. However a lot of research work discussed the design of supply chain [8], but most of them concentrate on linear cost functions. In the case of this model non-linear cost functions were used. The non-linear cost functions and the possible high number of objects of the inverse supply chain leaded to the problem of choosing a
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Nicholas P. Schafer
2016-03-01
Full Text Available The human homolog of Drosophila ecdysoneless protein (ECD is a p53 binding protein that stabilizes and enhances p53 functions. Homozygous deletion of mouse Ecd is early embryonic lethal and Ecd deletion delays G1-S cell cycle progression. Importantly, ECD directly interacts with the Rb tumor suppressor and competes with the E2F transcription factor for binding to Rb. Further studies demonstrated ECD is overexpressed in breast and pancreatic cancers and its overexpression correlates with poor patient survival. ECD overexpression together with Ras induces cellular transformation through upregulation of autophagy. Recently we demonstrated that CK2 mediated phosphorylation of ECD and interaction with R2TP complex are important for its cell cycle regulatory function. Considering that ECD is a component of multiprotein complexes and its crystal structure is unknown, we characterized ECD structure by circular dichroism measurements and sequence analysis software. These analyses suggest that the majority of ECD is composed of α-helices. Furthermore, small angle X-ray scattering (SAXS analysis showed that deletion fragments, ECD(1–432 and ECD(1–534, are both well-folded and reveals that the first 400 residues are globular and the next 100 residues are in an extended cylindrical structure. Taking all these results together, we speculate that ECD acts like a structural hub or scaffolding protein in its association with its protein partners. In the future, the hypothetical model presented here for ECD will need to be tested experimentally.
Modeling the Biophysical Effects in a Carbon Beam Delivery Line using Monte Carlo Simulation
Cho, Ilsung; Cho, Sungho; Kim, Eun Ho; Song, Yongkeun; Shin, Jae-ik; Jung, Won-Gyun
2016-01-01
Relative biological effectiveness (RBE) plays an important role in designing a uniform dose response for ion beam therapy. In this study the biological effectiveness of a carbon ion beam delivery system was investigated using Monte Carlo simulation. A carbon ion beam delivery line was designed for the Korea Heavy Ion Medical Accelerator (KHIMA) project. The GEANT4 simulation tool kit was used to simulate carbon beam transporting into media. An incident energy carbon ion beam in the range between 220 MeV/u and 290 MeV/u was chosen to generate secondary particles. The microdosimetric-kinetic (MK) model is applied to describe the RBE of 10% survival in human salivary gland (HSG) cells. The RBE weighted dose was estimated as a function of the penetrating depth of the water phantom along the incident beam direction. A biologically photon-equivalent Spread Out Bragg Peak (SOBP) was designed using the RBE weighted absorbed dose. Finally, the RBE of mixed beams was predicted as a function of the water phantom depth.
Modeling the biophysical effects in a carbon beam delivery line by using Monte Carlo simulations
Cho, Ilsung; Yoo, SeungHoon; Cho, Sungho; Kim, Eun Ho; Song, Yongkeun; Shin, Jae-ik; Jung, Won-Gyun
2016-09-01
The Relative biological effectiveness (RBE) plays an important role in designing a uniform dose response for ion-beam therapy. In this study, the biological effectiveness of a carbon-ion beam delivery system was investigated using Monte Carlo simulations. A carbon-ion beam delivery line was designed for the Korea Heavy Ion Medical Accelerator (KHIMA) project. The GEANT4 simulation tool kit was used to simulate carbon-ion beam transport into media. An incident energy carbon-ion beam with energy in the range between 220 MeV/u and 290 MeV/u was chosen to generate secondary particles. The microdosimetric-kinetic (MK) model was applied to describe the RBE of 10% survival in human salivary-gland (HSG) cells. The RBE weighted dose was estimated as a function of the penetration depth in the water phantom along the incident beam's direction. A biologically photon-equivalent Spread Out Bragg Peak (SOBP) was designed using the RBE-weighted absorbed dose. Finally, the RBE of mixed beams was predicted as a function of the depth in the water phantom.
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Bao-Tian Huang
2017-01-01
Full Text Available Purpose. The consistency for predicting local control (LC data using biophysical models for stereotactic body radiotherapy (SBRT treatment of lung cancer is unclear. This study aims to compare the results calculated from different models using the treatment planning data. Materials and Methods. Treatment plans were designed for 17 patients diagnosed with primary non-small cell lung cancer (NSCLC using 5 different fraction schemes. The Martel model, Ohri model, and the Tai model were used to predict the 2-year LC value. The Gucken model, Santiago model, and the Tai model were employed to estimate the 3-year LC data. Results. We found that the employed models resulted in completely different LC prediction except for the Gucken and the Santiago models which exhibited quite similar 3-year LC data. The predicted 2-year and 3-year LC values in different models were not only associated with the dose normalization but also associated with the employed fraction schemes. The greatest difference predicted by different models was up to 15.0%. Conclusions. Our results show that different biophysical models influence the LC prediction and the difference is not only correlated to the dose normalization but also correlated to the employed fraction schemes.
Maye, Kelly M.
2012-01-01
Cognitive and biophysical factors have been considered contributors linked to identifiable markers of obsessive compulsive and anxiety disorders. Research demonstrates multiple causes and mixed results for the short-term success of educational programs designed to ameliorate problems that children with obsessive compulsive and anxiety disorders…
Pollution models and inverse distance weighting: Some critical remarks
de Mesnard, Louis
2013-03-01
When evaluating the impact of pollution, measurements from remote stations are often weighted by the inverse of distance raised to some nonnegative power (IDW). This is derived from Shepard's method of spatial interpolation (1968). The paper discusses the arbitrary character of the exponent of distance and the problem of monitoring stations that are close to the reference point. From elementary laws of physics, it is determined which exponent of distance should be chosen (or its upper bound) depending on the form of pollution encountered, such as radiant pollution (including radioactivity and sound), air pollution (plumes, puffs, and motionless clouds by using the classical Gaussian model), and polluted rivers. The case where a station is confused with the reference point (or zero distance) is also discussed: in real cases this station imposes its measurement on the whole area regardless of the measurements made by other stations. This is a serious flaw when evaluating the mean pollution of an area. However, it is shown that this is not so in the case of a continuum of monitoring stations, and the measurement at the reference point and for the whole area may differ, which is satisfactory.
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F. Souty
2012-10-01
Full Text Available Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii a spatially explicit distribution of potential (maximal crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL. The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.
Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.
2012-10-01
Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.
Bayes Estimation for Inverse Rayleigh Model under Different Loss Functions
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Guobing Fan
2015-04-01
Full Text Available The inverse Rayleigh distribution plays an important role in life test and reliability domain. The aim of this article is study the Bayes estimation of parameter of inverse Rayleigh distribution. Bayes estimators are obtained under squared error loss, LINEX loss and entropy loss functions on the basis of quasi-prior distribution. Comparisons in terms of risks with the estimators of parameter under three loss functions are also studied. Finally, a numerical example is used to illustrate the results.
Inverse hydrological modelling of spatio-temporal rainfall patterns
Grundmann, Jens; Hörning, Sebastian; Bárdossy, András
2016-04-01
Distributed hydrological models are commonly used for simulating the non-linear response of a watershed to rainfall events for addressing different hydrological properties of the landscape. Such models are driven by spatial rainfall patterns for consecutive time steps, which are normally generated from point measurements using spatial interpolation methods. However, such methods fail in reproducing the true spatio-temporal rainfall patterns especially in data scarce regions with poorly gauged catchments or for highly dynamic, small scaled rainstorms which are not well recorded by existing monitoring networks. Consequently, uncertainties are associated with poorly identified spatio-temporal rainfall distribution in distributed rainfall-runoff-modelling since the amount of rainfall received by a catchment as well as the dynamics of the runoff generation of flood waves are underestimated. For addressing these challenges a novel methodology for inverse hydrological modelling is proposed using a Markov-Chain-Monte-Carlo framework. Thereby, potential candidates of spatio-temporal rainfall patterns are generated and selected according their ability to reproduce the observed surface runoff at the catchment outlet for a given transfer function in a best way. The Methodology combines the concept of random mixing of random spatial fields with a grid-based spatial distributed rainfall runoff model. The conditional target rainfall field is obtained as a linear combination of unconditional spatial random fields. The corresponding weights of the linear combination are selected such that the spatial variability of the rainfall amounts as well as the actual observed rainfall values are reproduced. The functionality of the methodology is demonstrated on a synthetic example. Thereby, the known spatio-temporal distribution of rainfall is reproduced for a given number of point observations of rainfall and the integral catchment response at the catchment outlet for a synthetic catchment
Drewry, D. T.; Duveiller, G.
2012-12-01
Agricultural modeling and yield forecasting are complicated by seasonal variability in traits controlled by factors such as growth stage, nutrient availability and moisture status. While a new generation of vegetation models incorporate ecophysiological details that allow for accurate estimates of carbon uptake, water use and energy exchange, these increases in process-level detail have resulted in the requirement to estimate a broader set of model parameters. Constraining uncertainties in model estimates of productivity and water use requires periodic updates as the structural and physiological status of the vegetation varies over the growing season. Here we explore the utilization of remote sensing reflectance observations in the optical domain collected from the MODIS sensors onboard the Terra and Aqua satellites for constraining key canopy states and reducing the uncertainty in modeled CO2, water and energy exchange with the atmosphere. At the core of this approach is a vertically discretized model (MLCan) that characterizes the ecophysiological functioning of a plant canopy and its biophysical coupling to the ambient environment at a half-hourly timestep. Above-ground vegetation is partially controlled by a root system model that simulates moisture uptake in a multi-layer soil system. MLCan has been rigorously validated for both C3 and C4 crops against field- and leaf-scale observations of canopy CO2 uptake, evapotranspiration and sensible heat exchange across a wide range of meteorological conditions in both ambient and elevated CO2 environments. A widely utilized radiation transfer model (PROSAIL) that accounts for the effects of leaf-level optical properties and foliage distribution and orientation on canopy reflectance is coupled to MLCan. This coupling provides the capability of expanding the spectral resolution of the model to nm-scale over the optical range. The coupled model will provide a system for testing the links between plant canopy biochemical
Risk evaluation of uranium mining: A geochemical inverse modelling approach
Rillard, J.; Zuddas, P.; Scislewski, A.
2011-12-01
It is well known that uranium extraction operations can increase risks linked to radiation exposure. The toxicity of uranium and associated heavy metals is the main environmental concern regarding exploitation and processing of U-ore. In areas where U mining is planned, a careful assessment of toxic and radioactive element concentrations is recommended before the start of mining activities. A background evaluation of harmful elements is important in order to prevent and/or quantify future water contamination resulting from possible migration of toxic metals coming from ore and waste water interaction. Controlled leaching experiments were carried out to investigate processes of ore and waste (leached ore) degradation, using samples from the uranium exploitation site located in Caetité-Bahia, Brazil. In experiments in which the reaction of waste with water was tested, we found that the water had low pH and high levels of sulphates and aluminium. On the other hand, in experiments in which ore was tested, the water had a chemical composition comparable to natural water found in the region of Caetité. On the basis of our experiments, we suggest that waste resulting from sulphuric acid treatment can induce acidification and salinization of surface and ground water. For this reason proper storage of waste is imperative. As a tool to evaluate the risks, a geochemical inverse modelling approach was developed to estimate the water-mineral interaction involving the presence of toxic elements. We used a method earlier described by Scislewski and Zuddas 2010 (Geochim. Cosmochim. Acta 74, 6996-7007) in which the reactive surface area of mineral dissolution can be estimated. We found that the reactive surface area of rock parent minerals is not constant during time but varies according to several orders of magnitude in only two months of interaction. We propose that parent mineral heterogeneity and particularly, neogenic phase formation may explain the observed variation of the
A Direct inverse model to determine permeability fields from pressure and flow rate measurements
Brouwer, G.K.; Fokker, P.A.; Wilschut, F.; Zijl, W.
2008-01-01
The determination of the permeability field from pressure and flow rate measurements in wells is a key problem in reservoir engineering. This paper presents a Double Constraint method for inverse modeling that is an example of direct inverse modeling. The method is used with a standard block-centere
Dorigo, W.A.; Richter, R.; Schneider, T.; Schaepman, M.E.; Müller, A.; Wagner, W.
2009-01-01
The success of radiative transfer model (RTM) inversion strongly depends on various factors, including the choice of a suited radiative transfer model, the followed inversion strategy, and the band configuration of the remote sensing system. Current study aims at addressing the latter, by
Losada, David E.; Barreiro, Alvaro
2003-01-01
Proposes an approach to incorporate term similarity and inverse document frequency into a logical model of information retrieval. Highlights include document representation and matching; incorporating term similarity into the measure of distance; new algorithms for implementation; inverse document frequency; and logical versus classical models of…
Advanced Techniques in Biophysics
Arrondo, José Luis R
2006-01-01
Technical advancements are basic elements in our life. In biophysical studies, new applications and improvements in well-established techniques are being implemented every day. This book deals with advancements produced not only from a technical point of view, but also from new approaches that are being taken in the study of biophysical samples, such as nanotechniques or single-cell measurements. This book constitutes a privileged observatory for reviewing novel applications of biophysical techniques that can help the reader enter an area where the technology is progressing quickly and where a comprehensive explanation is not always to be found.
DEFF Research Database (Denmark)
Hansen, Thomas Mejer; Cordua, Knud Skou; Holm Jacobsen, Bo
2014-01-01
forward models, can be more than an order of magnitude larger than the measurement uncertainty. We also found that the modeling error is strongly linked to the spatial variability of the assumed velocity field, i.e., the a priori velocity model.We discovered some general tools by which the modeling error...... synthetic ground-penetrating radar crosshole tomographic inverse problems. Ignoring the modeling error can lead to severe artifacts, which erroneously appear to be well resolved in the solution of the inverse problem. Accounting for the modeling error leads to a solution of the inverse problem consistent...
Mass balance inverse modelling of methane in the 1990s using a Chemistry Transport Model
T. M. Butler; Simmonds, I.; Rayner, P. J.
2004-01-01
International audience; A mass balance inverse modelling procedure is applied with a time-dependent methane concentration boundary condition and a chemical transport model to relate observed changes in the surface distribution of methane mixing ratios during the 1990s to changes in its surface sources. The model reproduces essential features of the global methane cycle, such as the latitudinal distribution and seasonal cycle of fluxes, without using a priori knowledge of methane fluxes. A det...
2013-01-01
The Encyclopedia of Biophysics is envisioned both as an easily accessible source of information and as an introductory guide to the scientific literature. It includes entries describing both Techniques and Systems. In the Techniques entries, each of the wide range of methods which fall under the heading of Biophysics are explained in detail, together with the value and the limitations of the information each provides. Techniques covered range from diffraction (X-ray, electron and neutron) through a wide range of spectroscopic methods (X-ray, optical, EPR, NMR) to imaging (from electron microscopy to live cell imaging and MRI), as well as computational and simulation approaches. In the Systems entries, biophysical approaches to specific biological systems or problems – from protein and nucleic acid structure to membranes, ion channels and receptors – are described. These sections, which place emphasis on the integration of the different techniques, therefore provide an inroad into Biophysics from a biolo...
Rosas-Carbajal, M.; Linde, N.; Kalscheuer, T.; Vrugt, J.A.
2014-01-01
Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space
A trade-off solution between model resolution and covariance in surface-wave inversion
Xia, J.; Xu, Y.; Miller, R.D.; Zeng, C.
2010-01-01
Regularization is necessary for inversion of ill-posed geophysical problems. Appraisal of inverse models is essential for meaningful interpretation of these models. Because uncertainties are associated with regularization parameters, extra conditions are usually required to determine proper parameters for assessing inverse models. Commonly used techniques for assessment of a geophysical inverse model derived (generally iteratively) from a linear system are based on calculating the model resolution and the model covariance matrices. Because the model resolution and the model covariance matrices of the regularized solutions are controlled by the regularization parameter, direct assessment of inverse models using only the covariance matrix may provide incorrect results. To assess an inverted model, we use the concept of a trade-off between model resolution and covariance to find a proper regularization parameter with singular values calculated in the last iteration. We plot the singular values from large to small to form a singular value plot. A proper regularization parameter is normally the first singular value that approaches zero in the plot. With this regularization parameter, we obtain a trade-off solution between model resolution and model covariance in the vicinity of a regularized solution. The unit covariance matrix can then be used to calculate error bars of the inverse model at a resolution level determined by the regularization parameter. We demonstrate this approach with both synthetic and real surface-wave data. ?? 2010 Birkh??user / Springer Basel AG.
Directory of Open Access Journals (Sweden)
Y. Sun
2013-04-01
Full Text Available This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4. Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent – as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty
Ding, Deng
Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form
Houborg, Rasmus
2015-01-19
Leaf area index (LAI) and leaf chlorophyll content (Chll) represent key biophysical and biochemical controls on water, energy and carbon exchange processes in the terrestrial biosphere. In combination, LAI and Chll provide critical information on vegetation density, vitality and photosynthetic potentials. However, simultaneous retrieval of LAI and Chll from space observations is extremely challenging. Regularization strategies are required to increase the robustness and accuracy of retrieved properties and enable more reliable separation of soil, leaf and canopy parameters. To address these challenges, the REGularized canopy reFLECtance model (REGFLEC) inversion system was refined to incorporate enhanced techniques for exploiting ancillary LAI and temporal information derived from multiple satellite scenes. In this current analysis, REGFLEC is applied to a time-series of Landsat data.A novel aspect of the REGFLEC approach is the fact that no site-specific data are required to calibrate the model, which may be run in a largely automated fashion using information extracted entirely from image-based and other widely available datasets. Validation results, based upon in-situ LAI and Chll observations collected over maize and soybean fields in central Nebraska for the period 2001-2005, demonstrate Chll retrieval with a relative root-mean-square-deviation (RMSD) on the order of 19% (RMSD=8.42μgcm-2). While Chll retrievals were clearly influenced by the version of the leaf optical properties model used (PROSPECT), the application of spatio-temporal regularization constraints was shown to be critical for estimating Chll with sufficient accuracy. REGFLEC also reproduced the dynamics of in-situ measured LAI well (r2 =0.85), but estimates were biased low, particularly over maize (LAI was underestimated by ~36 %). This disparity may be attributed to differences between effective and true LAI caused by significant foliage clumping not being properly accounted for in the canopy
Seismology on a Comet: Calibration Measurements, Modeling and Inversion
Faber, C.; Hoppe, J.; Knapmeyer, M.; Fischer, H.; Seidensticker, K. J.
2011-12-01
The Mission Rosetta was launched to comet 67P/Churyumov-Gerasimenko in 2004. It will finally reach the comet and will deliver the Lander Philae at the surface of the nucleus in November 2014. The Lander carries ten experiments, one of which is the Surface Electric Sounding and Acoustic Monitoring Experiment (SESAME). Part of this experiment is the Comet Acoustic Surface Sounding Experiment (CASSE) housed in the three feet of the lander. The primary goal of CASSE is to determine the elastic parameters of the surface material, like the Young's modulus and the Poisson ratio. Additional goals are the determination of shallow structure, quantification of porosity, and the location of activity spots and thermally and impact caused cometary activity. We conduct calibration measurements with accelerometers identical to the flight model. The goal of these measurements is to develop inversion procedures for travel times and to estimate the expected accuracy that CASSE can achieve in terms of elastic wave velocity, elastic parameters, and source location. The experiments are conducted mainly on sandy soil, in dry, wet or frozen conditions, and apart from buildings with their reflecting walls and artificial noise sources. We expect that natural sources, like thermal cracking at sunrise and sunset, can be located to an accuracy of about 10 degrees in direction and a few decimeters (1σ) in distance if occurring within the sensor triangle and from first arrivals alone. The accuracy of the direction is essentially independent of the distance, whereas distance determination depends critically on the identification of later arrivals. Determination of elastic wave velocities on the comet will be conducted with controlled sources at known positions and are likely to achieve an accuracy of σ=15% for the velocity of the first arriving wave. Limitations are due to the fixed source-receiver geometry and the wavelength emitted by the CASSE piezo-ceramic sources. In addition to the
Huisman, J.A.; Rings, J.; Vrugt, J.A.; Sorg, J.; Vereecken, H.
2010-01-01
Coupled hydrogeophysical inversion aims to improve the use of geophysical data for hydrological model parameterization. Several numerical studies have illustrated the feasibility and advantages of a coupled approach. However, there is still a lack of studies that apply the coupled inversion approach
2009-09-30
Nevertheless, it is well known that traditional state-of-the-art inversion techniques suffer from poor resolution and nonuniqueness , especially when a...and to provide adequate starting models for 3D waveform inversion approaches. ACKNOWLEDGEMENTS We thank the scientists, engineers , and technicians
DEFF Research Database (Denmark)
Yoon, Daeung; Zhdanov, Michael; Cai, Hongzhu
2015-01-01
should be powerful and fast enough to be suitable for repeated use in hundreds of iterations of the inversion and for multiple transmitter/receiver positions. To this end, we have developed a novel 3D modeling and inversion approach, which combines the advantages of the finite difference (FD...
Huisman, J.A.; Rings, J.; Vrugt, J.A.; Sorg, J.; Vereecken, H.
2010-01-01
Coupled hydrogeophysical inversion aims to improve the use of geophysical data for hydrological model parameterization. Several numerical studies have illustrated the feasibility and advantages of a coupled approach. However, there is still a lack of studies that apply the coupled inversion approach
Directory of Open Access Journals (Sweden)
Lingen Chen
2012-01-01
Full Text Available A thermodynamic model of an open combined regenerative Brayton and inverse Brayton cycles with regeneration before the inverse cycle is established in this paper by using thermodynamic optimization theory. The flow processes of the working fluid with the pressure drops and the size constraint of the real power plant are modeled. There are 13 flow resistances encountered by the working fluid stream for the cycle model. Four of these, the friction through the blades and vanes of the compressors and the turbines, are related to the isentropic efficiencies. The remaining nine flow resistances are always present because of the changes in flow cross-section at the compressor inlet of the top cycle, regenerator inlet and outlet, combustion chamber inlet and outlet, turbine outlet of the top cycle, turbine outlet of the bottom cycle, heat exchanger inlet, and compressor inlet of the bottom cycle. These resistances associated with the flow through various cross-sectional areas are derived as functions of the compressor inlet relative pressure drop of the top cycle, and control the air flow rate, the net power output and the thermal efficiency. The analytical formulae about the power output, efficiency and other coefficients are derived with 13 pressure drop losses. It is found that the combined cycle with regenerator can reach higher thermal efficiency but smaller power output than those of the base combined cycle at small compressor inlet relative pressure drop of the top cycle.
Gu, Guo-Ying; Yang, Mei-Ju; Zhu, Li-Min
2012-06-01
This paper presents a novel real-time inverse hysteresis compensation method for piezoelectric actuators exhibiting asymmetric hysteresis effect. The proposed method directly utilizes a modified Prandtl-Ishlinskii hysteresis model to characterize the inverse hysteresis effect of piezoelectric actuators. The hysteresis model is then cascaded in the feedforward path for hysteresis cancellation. It avoids the complex and difficult mathematical procedure for constructing an inversion of the hysteresis model. For the purpose of validation, an experimental platform is established. To identify the model parameters, an adaptive particle swarm optimization algorithm is adopted. Based on the identified model parameters, a real-time feedforward controller is implemented for fast hysteresis compensation. Finally, tests are conducted with various kinds of trajectories. The experimental results show that the tracking errors caused by the hysteresis effect are reduced by about 90%, which clearly demonstrates the effectiveness of the proposed inverse compensation method with the modified Prandtl-Ishlinskii model.
Alkhalifah, Tariq Ali
2012-09-25
Traveltime inversion focuses on the geometrical features of the waveform (traveltimes), which is generally smooth, and thus, tends to provide averaged (smoothed) information of the model. On other hand, general waveform inversion uses additional elements of the wavefield including amplitudes to extract higher resolution information, but this comes at the cost of introducing non-linearity to the inversion operator, complicating the convergence process. We use unwrapped phase-based objective functions in waveform inversion as a link between the two general types of inversions in a domain in which such contributions to the inversion process can be easily identified and controlled. The instantaneous traveltime is a measure of the average traveltime of the energy in a trace as a function of frequency. It unwraps the phase of wavefields yielding far less non-linearity in the objective function than that experienced with conventional wavefields, yet it still holds most of the critical wavefield information in its frequency dependency. However, it suffers from non-linearity introduced by the model (or reflectivity), as reflections from independent events in our model interact with each other. Unwrapping the phase of such a model can mitigate this non-linearity as well. Specifically, a simple modification to the inverted domain (or model), can reduce the effect of the model-induced non-linearity and, thus, make the inversion more convergent. Simple numerical examples demonstrate these assertions.
Inverse and forward dynamics: models of multi-body systems.
Otten, E
2003-01-01
Connected multi-body systems exhibit notoriously complex behaviour when driven by external and internal forces and torques. The problem of reconstructing the internal forces and/or torques from the movements and known external forces is called the 'inverse dynamics problem', whereas calculating motion from known internal forces and/or torques and resulting reaction forces is called the 'forward dynamics problem'. When stepping forward to cross the street, people use muscle forces that generate angular accelerations of their body segments and, by virtue of reaction forces from the street, a forward acceleration of the centre of mass of their body. Inverse dynamics calculations applied to a set of motion data from such an event can teach us how temporal patterns of joint torques were responsible for the observed motion. In forward dynamics calculations we may attempt to create motion from such temporal patterns, which is extremely difficult, because of the complex mechanical linkage along the chains forming the multi-body system. To understand, predict and sometimes control multi-body systems, we may want to have mathematical expressions for them. The Newton-Euler, Lagrangian and Featherstone approaches have their advantages and disadvantages. The simulation of collisions and the inclusion of muscle forces or other internal forces are discussed. Also, the possibility to perform a mixed inverse and forward dynamics calculation are dealt with. The use and limitations of these approaches form the conclusion. PMID:14561340
Inverse modeling methods for indoor airborne pollutant tracking: literature review and fundamentals.
Liu, X; Zhai, Z
2007-12-01
Reduction in indoor environment quality calls for effective control and improvement measures. Accurate and prompt identification of contaminant sources ensures that they can be quickly removed and contaminated spaces isolated and cleaned. This paper discusses the use of inverse modeling to identify potential indoor pollutant sources with limited pollutant sensor data. The study reviews various inverse modeling methods for advection-dispersion problems and summarizes the methods into three major categories: forward, backward, and probability inverse modeling methods. The adjoint probability inverse modeling method is indicated as an appropriate model for indoor air pollutant tracking because it can quickly find source location, strength and release time without prior information. The paper introduces the principles of the adjoint probability method and establishes the corresponding adjoint equations for both multi-zone airflow models and computational fluid dynamics (CFD) models. The study proposes a two-stage inverse modeling approach integrating both multi-zone and CFD models, which can provide a rapid estimate of indoor pollution status and history for a whole building. Preliminary case study results indicate that the adjoint probability method is feasible for indoor pollutant inverse modeling. The proposed method can help identify contaminant source characteristics (location and release time) with limited sensor outputs. This will ensure an effective and prompt execution of building management strategies and thus achieve a healthy and safe indoor environment. The method can also help design optimal sensor networks.
Guma Biro Turk, Khalid
2016-07-01
Crop production under modern irrigation systems require unique management at field level and hence better utilization of agricultural inputs and water resources. This study aims to make use of remote sensing (RS) data and the surface energy balance algorithm for land (SEBAL) to improve the on-farm management. The study area is located in the Eastern part of the Blue Nile River about 60 km south of Khartoum, Sudan. Landsat-8 data were used to estimate a number of bio-physical indicators during the growing season of the year 2014/2015. Accordingly, in-situ weather data and SEBAL model were applied to calculate: the reference (ET0), actual (ETa) and potential (ETp) evapotranspiration, soil moisture (SM), crop factor (kc), nitrogen (N), biomass production (BP) and crop water productivity (CWP). Results revealed that ET0 showed steady variation throughout the year, varying from 5 to 7 mm/day. However, ETa and ETp showed clear temporal variation attributed to frequent cutting of the alfalfa, almost monthly. The BP of the alfalfa was observed to be high when there is no cutting activates were made before the image acquisition date. Nevertheless the CWP trends are following the biomass production ones, low when there is no biomass and high when the biomass is high. The application of SEBAL model within the study area using the Landsat-8 imagery indicates that it's possible to produce field-based bio-physical indicators, which can be useful in monitoring and managing the field during the growing season. However, a cross-calibration with the in-situ data should be considered in order to maintain the spatial variability within the field. Keywords: Bio-physical Indicators; Remote Sensing; SEBAL; Landsat-8; Eastern Nile Basin
Nikjoo, H.; Taleei, R.; Liamsuwan, T.; Liljequist, D.; Emfietzoglou, D.
2016-11-01
In radiation targeted therapy and genetic risk estimation of low dose radiation protection there is a crucial need for full description of DNA damage response and repair (DDR) leading to cell death and cell mutation. We propose such a description can be arrived through realistic track-structure simulations together with mechanistic mathematical formulation of DDR and the availability of experimental data for testing the proof of principle. In this paper we review briefly first the state of the art in DNA damage and repair, and then the recent advances in the physics of track structure which represents an essential tool in radiation biophysics.
From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution
Directory of Open Access Journals (Sweden)
M. Herrnegger
2014-12-01
Full Text Available This paper presents a novel technique to calculate mean areal rainfall in a high temporal resolution of 60 min on the basis of an inverse conceptual rainfall–runoff model and runoff observations. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. The most reliable hydrological information available refers to runoff, which in the presented work is used as input for a rainfall–runoff model. Thereby a conceptual, HBV-type model is embedded in an iteration algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value that corresponds to the observation. To verify the existence, uniqueness and stability of the inverse rainfall, numerical experiments with synthetic hydrographs as inputs into the inverse model are carried out successfully. The application of the inverse model with runoff observations as driving input is performed for the Krems catchment (38.4 km2, situated in the northern Austrian Alpine foothills. Compared to station observations in the proximity of the catchment, the inverse rainfall sums and time series have a similar goodness of fit, as the independent INCA rainfall analysis of Austrian Central Institute for Meteorology and Geodynamics (ZAMG. Compared to observations, the inverse rainfall estimates show larger rainfall intensities. Numerical experiments show, that cold state conditions in the inverse model do not influence the inverse rainfall estimates, when considering an adequate spin-up time. The application of the inverse model is a feasible approach to obtain improved estimates of mean areal rainfall. These can be used to enhance interpolated rainfall fields, e.g. for the estimation of rainfall correction factors, the parameterisation of
Constraint on Parameters of Inverse Compton Scattering Model for PSR B2319+60
Indian Academy of Sciences (India)
H. G. Wang; M. Lv
2011-03-01
Using the multifrequency radio profiles of pulsar PSR B2319+60, two parameters of inverse Compton scattering model, the initial Lorentz factor and the factor of energy loss of relativistic particles are constrained.
CSIR Research Space (South Africa)
Evers-King, H
2014-05-01
Full Text Available phytoplankton functional type descriptors within known confidence limits from remotely sensed data has become a major objective to extend the use of ocean colour data beyond chlorophyll a retrievals. Here, a new forward and inverse modelling structure...
Joint Hydrogeophysical Inversion: State Estimation for Seawater Intrusion Models in 3D
Steklova, K
2016-01-01
Seawater intrusion (SWI) is a complex process, where 3D modeling is often necessary in order to monitor and manage the affected aquifers. Here, we present a synthetic study to test a joint hydrogeophysical inversion approach aimed at solving the inverse problem of estimating initial and current saltwater distribution. First, we use a 3D groundwater model for variable density flow based on discretized flow and solute mass balance equations. In addition to the groundwater model, a 3D geophysical model was developed for direct current resistivity imaging and inversion. The objective function of the coupled problem consists of data misfit and regularization terms as well as a coupling term that relates groundwater and geophysical states. We present a novel approach to solve the inverse problem using an Alternating Direction Method of Multipliers (ADMM) to minimize this coupled objective function. The sensitivities are derived analytically for the discretized system of equations, which allows us to efficiently com...
MEG inversion using spherical head model combined with brain-shaped head model
Institute of Scientific and Technical Information of China (English)
LI Jun
2001-01-01
The spherical head model has been widely used in magnetoen cephalography (MEG) as a simple forward model for calculating the external mag netic field producing by neural currents in a human brain. But this model may lead to an inaccurate result, even if the computation speed is fast. For more precise computation, realistic brain-shaped head model is used with the boundary element method (BME), but at greatly increased computational cost. When solving MEG inverse problem by using optimization methods, the forward problem must often be solved for thousands of possible source configurations. So if the brain-shaped head model is used in all iterative steps of optimization, it may be computationally infeasible for practical application. In this paper, we present a method about using compound head model in MEG inverse solution. In this method, first spherical head model is used for a rough estimation, then brain-shaped head model is adopted for more precise solution. Numerical simulation indicates that under the condition of same accuracy, the computation speed for the present method is about three times faster than a method using the brain-shaped head model at all iterations.
CSIR Research Space (South Africa)
Robertson Lain, L
2014-07-01
Full Text Available (PFT) analysis. To these ends, an initial validation of a new model of Equivalent Algal Populations (EAP) is presented here. This paper makes a first order comparison of two prominent phytoplankton Inherent Optical Property (IOP) models with the EAP...
Kurz, H; Sandau, K; Christ, B
1997-02-01
Wilhelm Roux's doctoral thesis described the relationship between the angle and diameter of bifurcating blood vessels. We have re-read this work in the light of biophysics and developmental biology and found two remarkable aspects hidden among a multitude of observations, rules and exceptions to these rules. First, the author identified the major determinants involved in vascular development; genetics, cybernetics, and mechanics; moreover, he knew that he could not deal with the genetic and regulatory aspects, and could hardly treat the mechanical part adequately. Second, he was deeply convinced that the laws of physics determine the design of organisms, and that a necessity for optimality was inherent in development. We combined the analysis of diameter relationships with the requirement for optimality in a stochastic biophysical model, and concluded that a constant wall-stress condition could define a minimum wall-tissue optimum during arterial development. Hence, almost 120 years after Wilhelm Roux's pioneering work, our model indicates one possible way in which physical laws have determined the evolution of regulatory and structural properties in vessel wall development.
Illman, Walter A.; Berg, Steven J.; Zhao, Zhanfeng
2015-05-01
The robust performance of hydraulic tomography (HT) based on geostatistics has been demonstrated through numerous synthetic, laboratory, and field studies. While geostatistical inverse methods offer many advantages, one key disadvantage is its highly parameterized nature, which renders it computationally intensive for large-scale problems. Another issue is that geostatistics-based HT may produce overly smooth images of subsurface heterogeneity when there are few monitoring interval data. Therefore, some may question the utility of the geostatistical inversion approach in certain situations and seek alternative approaches. To investigate these issues, we simultaneously calibrated different groundwater models with varying subsurface conceptualizations and parameter resolutions using a laboratory sandbox aquifer. The compared models included: (1) isotropic and anisotropic effective parameter models; (2) a heterogeneous model that faithfully represents the geological features; and (3) a heterogeneous model based on geostatistical inverse modeling. The performance of these models was assessed by quantitatively examining the results from model calibration and validation. Calibration data consisted of steady state drawdown data from eight pumping tests and validation data consisted of data from 16 separate pumping tests not used in the calibration effort. Results revealed that the geostatistical inversion approach performed the best among the approaches compared, although the geological model that faithfully represented stratigraphy came a close second. In addition, when the number of pumping tests available for inverse modeling was small, the geological modeling approach yielded more robust validation results. This suggests that better knowledge of stratigraphy obtained via geophysics or other means may contribute to improved results for HT.
Energy Technology Data Exchange (ETDEWEB)
Privette, J.L.
1994-12-31
The angular distribution of radiation scattered by the earth surface contains information on the structural and optical properties of the surface. Potentially, this information may be retrieved through the inversion of surface bidirectional reflectance distribution function (BRDF) models. This report details the limitations and efficient application of BRDF model inversions using data from ground- and satellite-based sensors. A turbid medium BRDF model, based on the discrete ordinates solution to the transport equation, was used to quantify the sensitivity of top-of-canopy reflectance to vegetation and soil parameters. Results were used to define parameter sets for inversions. Using synthetic reflectance values, the invertibility of the model was investigated for different optimization algorithms, surface and sampling conditions. Inversions were also conducted with field data from a ground-based radiometer. First, a soil BRDF model was inverted for different soil and sampling conditions. A condition-invariant solution was determined and used as the lower boundary condition in canopy model inversions. Finally, a scheme was developed to improve the speed and accuracy of inversions.
Directory of Open Access Journals (Sweden)
F. Souty
2012-02-01
Full Text Available Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii a spatially explicit distribution of potential (maximal crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL. The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. The land-use modelling approach described in this paper entails several advantages. Firstly, it makes it possible to explore interactions among different types of biomass demand for food and animal feed, in a consistent approach, including indirect effects on land-use change resulting from international trade. Secondly, yield variations induced by the possible expansion of croplands on less suitable marginal lands are modelled by using regional land area distributions of potential yields, and a calculated boundary between intensive and extensive production. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or
Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.
2016-09-01
Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace such that the dimensionality of the problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2-D and a random hydraulic conductivity field in 3-D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ˜101 to ˜102 in a multicore computational environment. Therefore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate to large-scale problems.
Biophysics of molecular gastronomy.
Brenner, Michael P; Sörensen, Pia M
2015-03-26
Chefs and scientists exploring biophysical processes have given rise to molecular gastronomy. In this Commentary, we describe how a scientific understanding of recipes and techniques facilitates the development of new textures and expands the flavor palette. The new dishes that result engage our senses in unexpected ways. PAPERCLIP.
Hatzis, Christos
2013-07-01
Annual Review of Biophysics Rees D. Dill K., Williamson J., Annual Reviews Palo Alto, CA, 2010. 581 pp. (hardcover), ISBN: 978-0-8243-1839-0, © 2013 Doody's Review Service. Doody's Review Service. © 2013 American Association of Physicists in Medicine.
Houborg, Rasmus; McCabe, Matthew F.
2015-10-01
Accurate retrieval of canopy biophysical and leaf biochemical constituents from space observations is critical to diagnosing the functioning and condition of vegetation canopies across spatio-temporal scales. Retrieved vegetation characteristics may serve as important inputs to precision farming applications and as constraints in spatially and temporally distributed model simulations of water and carbon exchange processes. However significant challenges remain in the translation of composite remote sensing signals into useful biochemical, physiological or structural quantities and treatment of confounding factors in spectrum-trait relations. Bands in the red-edge spectrum have particular potential for improving the robustness of retrieved vegetation properties. The development of observationally based vegetation retrieval capacities, effectively constrained by the enhanced information content afforded by bands in the red-edge, is a needed investment towards optimizing the benefit of current and future satellite sensor systems. In this study, a REGularized canopy reFLECtance model (REGFLEC) for joint leaf chlorophyll (Chll) and leaf area index (LAI) retrieval is extended to sensor systems with a band in the red-edge region for the first time. Application to time-series of 5 m resolution multi-spectral RapidEye data is demonstrated over an irrigated agricultural region in central Saudi Arabia, showcasing the value of satellite-derived crop information at this fine scale for precision management. Validation against in-situ measurements in fields of alfalfa, Rhodes grass, carrot and maize indicate improved accuracy of retrieved vegetation properties when exploiting red-edge information in the model inversion process.
Houborg, Rasmus
2015-10-14
Accurate retrieval of canopy biophysical and leaf biochemical constituents from space observations is critical to diagnosing the functioning and condition of vegetation canopies across spatio-temporal scales. Retrieved vegetation characteristics may serve as important inputs to precision farming applications and as constraints in spatially and temporally distributed model simulations of water and carbon exchange processes. However significant challenges remain in the translation of composite remote sensing signals into useful biochemical, physiological or structural quantities and treatment of confounding factors in spectrum-trait relations. Bands in the red-edge spectrum have particular potential for improving the robustness of retrieved vegetation properties. The development of observationally based vegetation retrieval capacities, effectively constrained by the enhanced information content afforded by bands in the red-edge, is a needed investment towards optimizing the benefit of current and future satellite sensor systems. In this study, a REGularized canopy reFLECtance model (REGFLEC) for joint leaf chlorophyll (Chll) and leaf area index (LAI) retrieval is extended to sensor systems with a band in the red-edge region for the first time. Application to time-series of 5 m resolution multi-spectral RapidEye data is demonstrated over an irrigated agricultural region in central Saudi Arabia, showcasing the value of satellite-derived crop information at this fine scale for precision management. Validation against in-situ measurements in fields of alfalfa, Rhodes grass, carrot and maize indicate improved accuracy of retrieved vegetation properties when exploiting red-edge information in the model inversion process. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
Fetal Biophysical Profile Scoring
Directory of Open Access Journals (Sweden)
H.R. HaghighatKhah
2009-01-01
Full Text Available "nFetal biophysical profile scoring is a sonographic-based method of fetal assessment first described by Manning and Platt in 1980. "nThe biophysical profile score was developed as a method to integrate real-time observations of the fetus and his/her intrauterine environment in order to more comprehensively assess the fetal condition. These findings must be evaluated in the context of maternal/fetal history (i.e., chronic hypertension, post-dates, intrauterine growth restriction, etc, fetal structural integrity (presence or absence of congenital anomalies, and the functionality of fetal support structures (placental and umbilical cord. For example, acute asphyxia due to placental abruption may result in an absence of the acute variables of the biophysical profile score (fetal breathing movements, fetal movement, fetal tone, and fetal heart rate reactivity with a normal amniotic fluid volume. With post maturity the asphyxial event may be intermittent and chronic resulting in a decrease in amniotic fluid volume, but with the acute variables remaining normal. "nWhile the 5 components of the biophysical profile score have remained unchanged since 1980 (Manning, 1980, the definitions of a normal and abnormal parameter have evolved with increasing experience. "nIn 1984 the definition of oligohydramnios was increased from < 1cm pocket of fluid to < 2.0 x 1.0 cm pocket. Oligohydramnios is now defined as a pocket of amniotic fluid < 2.0 x 2.0 cm (Manning, 1995a "nIf the four ultrasound variables are normal, the accuracy of the biophysical profile score was not found to be significantly improved by adding the non-stress test. As a result, in 1987 the profile score was modified to incorporate the non-stress test only when one of the ultrasound variables was abnormal (Manning 1987. Table 1 outlines the current definitions for quantifying a variable as present or absent. "nEach of the 5 components of the biophysical profile score does not have equal
Relating biophysical properties across scales.
Flenner, Elijah; Marga, Francoise; Neagu, Adrian; Kosztin, Ioan; Forgacs, Gabor
2008-01-01
A distinguishing feature of a multicellular living system is that it operates at various scales, from the intracellular to organismal. Genes and molecules set up the conditions for the physical processes to act, in particular to shape the embryo. As development continues the changes brought about by the physical processes lead to changes in gene expression. It is this coordinated interplay between genetic and generic (i.e., physical and chemical) processes that constitutes the modern understanding of early morphogenesis. It is natural to assume that in this multiscale process the smaller defines the larger. In case of biophysical properties, in particular, those at the subcellular level are expected to give rise to those at the tissue level and beyond. Indeed, the physical properties of tissues vary greatly from the liquid to solid. Very little is known at present on how tissue level properties are related to cell and subcellular properties. Modern measurement techniques provide quantitative results at both the intracellular and tissue level, but not on the connection between these. In the present work we outline a framework to address this connection. We specifically concentrate on the morphogenetic process of tissue fusion, by following the coalescence of two contiguous multicellular aggregates. The time evolution of this process can accurately be described by the theory of viscous liquids. We also study fusion by Monte Carlo simulations and a novel Cellular Particle Dynamics (CPD) model, which is similar to the earlier introduced Subcellular Element Model (SEM; Newman, 2005). Using the combination of experiments, theory and modeling we are able to relate the measured tissue level biophysical quantities to subcellular parameters. Our approach has validity beyond the particular morphogenetic process considered here and provides a general way to relate biophysical properties across scales.
Weiland, Cédric
2012-01-01
We study the impact of the inverse seesaw mechanism on several leptonic and hadronic low-energy flavour-violating observables in the context of the Minimal Supersymmetric Standard Model. Indeed, the contributions of the light right-handed sneutrinos from the inverse seesaw significantly enhance the Higgs-mediated penguin diagrams. We find that this can increase the different branching ratios by as much as two orders of magnitude.
Directory of Open Access Journals (Sweden)
Abel Palafox
2014-01-01
Full Text Available We address a prototype inverse scattering problem in the interface of applied mathematics, statistics, and scientific computing. We pose the acoustic inverse scattering problem in a Bayesian inference perspective and simulate from the posterior distribution using MCMC. The PDE forward map is implemented using high performance computing methods. We implement a standard Bayesian model selection method to estimate an effective number of Fourier coefficients that may be retrieved from noisy data within a standard formulation.
Global Monthly CO2 Flux Inversion Based on Results of Terrestrial Ecosystem Modeling
Deng, F.; Chen, J.; Peters, W.; Krol, M.
2008-12-01
Most of our understanding of the sources and sinks of atmospheric CO2 has come from inverse studies of atmospheric CO2 concentration measurements. However, the number of currently available observation stations and our ability to simulate the diurnal planetary boundary layer evolution over continental regions essentially limit the number of regions that can be reliably inverted globally, especially over continental areas. In order to overcome these restrictions, a nested inverse modeling system was developed based on the Bayesian principle for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Inverse modeling was conducted in monthly steps using CO2 concentration measurements of 5 years (2000 - 2005) with the following two models: (a) An atmospheric transport model (TM5) is used to generate the transport matrix where the diurnal variation n of atmospheric CO2 concentration is considered to enhance the use of the afternoon-hour average CO2 concentration measurements over the continental sites. (b) A process-based terrestrial ecosystem model (BEPS) is used to produce hourly step carbon fluxes, which could minimize the limitation due to our inability to solve the inverse problem in a high resolution, as the background of our inversion. We will present our recent results achieved through a combination of the bottom-up modeling with BEPS and the top-down modeling based on TM5 driven by offline meteorological fields generated by the European Centre for Medium Range Weather Forecast (ECMFW).
Inverse modelling of national and European CH4 emissions using the atmospheric zoom model TM5
Directory of Open Access Journals (Sweden)
P. Bergamaschi
2005-01-01
Full Text Available A synthesis inversion based on the atmospheric zoom model TM5 is used to derive top-down estimates of CH4 emissions from individual European countries for the year 2001. We employ a model zoom over Europe with 1° × 1° resolution that is two-way nested into the global model domain (with resolution of 6° × 4°. This approach ensures consistent boundary conditions for the zoom domain and thus European top-down estimates consistent with global CH4 observations. The TM5 model, driven by ECMWF analyses, simulates synoptic scale events at most European and global sites fairly well, and the use of high-frequency observations allows exploiting the information content of individual synoptic events. A detailed source attribution is presented for a comprehensive set of 56 monitoring sites, assigning the atmospheric signal to the emissions of individual European countries and larger global regions. The available observational data put significant constraints on emissions from different regions. Within Europe, in particular several Western European countries are well constrained. The inversion results suggest up to 50-90% higher anthropogenic CH4 emissions in 2001 for Germany, France and UK compared to reported UNFCCC values (EEA, 2003. A recent revision of the German inventory, however, resulted in an increase of reported CH4 emissions by 68.5% (EEA, 2004, being now in very good agreement with our top-down estimate. The top-down estimate for Finland is distinctly smaller than the a priori estimate, suggesting much smaller CH4 emissions from Finnish wetlands than derived from the bottom-up inventory. The EU-15 totals are relatively close to UNFCCC values (within 4-30% and appear very robust for different inversion scenarios.
Prinn, Ronald G.
2001-01-01
For interpreting observational data, and in particular for use in inverse methods, accurate and realistic chemical transport models are essential. Toward this end we have, in recent years, helped develop and utilize a number of three-dimensional models including the Model for Atmospheric Transport and Chemistry (MATCH).
Inverse modeling and animation of growing single-stemmed trees at interactive rates
S. Rudnick; L. Linsen; E.G. McPherson
2007-01-01
For city planning purposes, animations of growing trees of several species can be used to deduce which species may best fit a particular environment. The models used for the animation must conform to real measured data. We present an approach for inverse modeling to fit global growth parameters. The model comprises local production rules, which are iteratively and...
Inverse modeling of a multistep outflow experiment for determining hysteretic hydraulic properties
DEFF Research Database (Denmark)
Finsterle, Stefan; Sonnenborg, Torben Obel; Faybishenko, B.
1998-01-01
A new, closed form hysteretic model of the capillary pressure-saturation and relative permeability-saturation relationship has been implemented into ITOUGH2. The hysteresis model was used in combination with inverse modeling techniques to examine the potential of a simple drainage-imbibition expe...
Gutmann, Ethan D.; Small, Eric E.
2007-01-01
Soil hydraulic properties (SHPs) regulate the movement of water in the soil. This in turn plays an important role in the water and energy cycles at the land surface. At present, SHPS are commonly defined by a simple pedotransfer function from soil texture class, but SHPs vary more within a texture class than between classes. To examine the impact of using soil texture class to predict SHPS, we run the Noah land surface model for a wide variety of measured SHPs. We find that across a range of vegetation cover (5 - 80% cover) and climates (250 - 900 mm mean annual precipitation), soil texture class only explains 5% of the variance expected from the real distribution of SHPs. We then show that modifying SHPs can drastically improve model performance. We compare two methods of estimating SHPs: (1) inverse method, and (2) soil texture class. Compared to texture class, inverse modeling reduces errors between measured and modeled latent heat flux from 88 to 28 w/m(exp 2). Additionally we find that with increasing vegetation cover the importance of SHPs decreases and that the van Genuchten m parameter becomes less important, while the saturated conductivity becomes more important.
Directory of Open Access Journals (Sweden)
C. Mukherjee
2011-01-01
Full Text Available Inverse modeling applications in atmospheric chemistry are increasingly addressing the challenging statistical issues of data synthesis by adopting refined statistical analysis methods. This paper advances this line of research by addressing several central questions in inverse modeling, focusing specifically on Bayesian statistical computation. Motivated by problems of refining bottom-up estimates of source/sink fluxes of trace gas and aerosols based on increasingly high-resolution satellite retrievals of atmospheric chemical concentrations, we address head-on the need for integrating formal spatial statistical methods of residual error structure in global scale inversion models. We do this using analytically and computationally tractable spatial statistical models, know as conditional autoregressive spatial models, as components of a global inversion framework. We develop Markov chain Monte Carlo methods to explore and fit these spatial structures in an overall statistical framework that simultaneously estimates source fluxes. Additional aspects of the study extend the statistical framework to utilize priors in a more physically realistic manner, and to formally address and deal with missing data in satellite retrievals. We demonstrate the analysis in the context of inferring carbon monoxide (CO sources constrained by satellite retrievals of column CO from the Measurement of Pollution in the Troposphere (MOPITT instrument on the TERRA satellite, paying special attention to evaluating performance of the inverse approach using various statistical diagnostic metrics. This is developed using synthetic data generated to resemble MOPITT data to define a~proof-of-concept and model assessment, and then in analysis of real MOPITT data.
Heeding the waveform inversion nonlinearity by unwrapping the model and data
Alkhalifah, Tariq Ali
2012-01-01
Unlike traveltime inversion, waveform inversion provides relatively higher-resolution inverted models. This feature, however, comes at the cost of introducing complex nonlinearity to the inversion operator complicating the convergence process. We use unwrapped-phase-based objective functions to reduce such nonlinearity in a domain in which the high-frequency component is given by the traveltime inversion. Such information is packaged in a frequency-dependent attribute (or traveltime) that can be easily manipulated at different frequencies. It unwraps the phase of the wavefield yielding far less nonlinearity in the objective function than those experienced with the conventional misfit objective function, and yet it still holds most of the critical waveform information in its frequency dependency. However, it suffers from nonlinearity introduced by the model (or reflectivity), as events interact with each other (something like cross talk). This stems from the sinusoidal nature of the band-limited reflectivity model. Unwrapping the phase for such a model can mitigate this nonlinearity as well. Specifically, a simple modification to the inverted domain (or model), can reduce the effect of the model-induced nonlinearity and, thus, make the inversion more convergent. Simple examples are used to highlight such features.
Inverse modeling of the terrestrial carbon flux in China with flux covariance among inverted regions
Wang, H.; Jiang, F.; Chen, J. M.; Ju, W.; Wang, H.
2011-12-01
Quantitative understanding of the role of ocean and terrestrial biosphere in the global carbon cycle, their response and feedback to climate change is required for the future projection of the global climate. China has the largest amount of anthropogenic CO2 emission, diverse terrestrial ecosystems and an unprecedented rate of urbanization. Thus information on spatial and temporal distributions of the terrestrial carbon flux in China is of great importance in understanding the global carbon cycle. We developed a nested inversion with focus in China. Based on Transcom 22 regions for the globe, we divide China and its neighboring countries into 17 regions, making 39 regions in total for the globe. A Bayesian synthesis inversion is made to estimate the terrestrial carbon flux based on GlobalView CO2 data. In the inversion, GEOS-Chem is used as the transport model to develop the transport matrix. A terrestrial ecosystem model named BEPS is used to produce the prior surface flux to constrain the inversion. However, the sparseness of available observation stations in Asia poses a challenge to the inversion for the 17 small regions. To obtain additional constraint on the inversion, a prior flux covariance matrix is constructed using the BEPS model through analyzing the correlation in the net carbon flux among regions under variable climate conditions. The use of the covariance among different regions in the inversion effectively extends the information content of CO2 observations to more regions. The carbon flux over the 39 land and ocean regions are inverted for the period from 2004 to 2009. In order to investigate the impact of introducing the covariance matrix with non-zero off-diagonal values to the inversion, the inverted terrestrial carbon flux over China is evaluated against ChinaFlux eddy-covariance observations after applying an upscaling methodology.
Forward modeling and inversion of responses for borehole normal and lateral electrode arrangements
Energy Technology Data Exchange (ETDEWEB)
Kim, J.H.
1986-01-01
The finite difference method is used to solve the forward problems which simulate the borehole normal and lateral electrode arrangements for the combined boundary (2-D) earth model which has both horizontal and cylindrical boundaries. The ridge regression estimator is then applied to solve the inverse problems which determine the earth parameters such as bed boundaries, extent of invaded zones, and vertical and horizontal resistivity profiles from the borehole normal and lateral resistivity logs. The apparent resistivity values in the presence of borehole mud, invaded zone, and horizontal bed boundaries can be obtained from an earth geometry provided that the model is symmetric around the borehole axis. The quick and accurate forward calculations are achieved by using a gradually expanding grid system and a terminal resistance type boundary condition, and by using a two-dimensional average resistivity scheme in a grid block. The finite difference solutions are verified against analytical solutions for limiting cases, and excellent agreement in obtained. The finite difference forward modeling also can be used for investigation into the effects of the earth parameter variations on the apparent resistivities. Inverse modeling is tested on synthetic and field data. The field data are inverted to a horizontally layered (1-D) model, and the theoretical data are inverted to a 2-D model. The test results indicate that the thickness and the resistivity of each layer can be determined simultaneously. For the practical inversion of field data, the 1-D model inversion results can be used as a first try model of the 2-d inversion. Interactive inverse modeling can be used for an automatic interpretation of the resistivity logs, with models constrained by logging and geologic information.
Puglisi, Joseph D
2007-01-01
This volume is a collection of articles from the proceedings of the ISSBMR 7th Course: Structure and Biophysics - New Technologies for Current Challenges in Biology and Beyond. This NATO Advanced Institute (ASI) was held in Erice at the Ettore Majorana Foundation and Centre for Scientific Culture on 22 June through 3 July 2005. The ASI brought together a diverse group of experts in the fields of Structural Biology, Biophysics and Physics. Prominent lecturers, from seven different countries, and students from around the world participated in the NATO ASI organized by Professors Joseph Puglisi (Stanford University, USA) and Alexander Arseniev (Moscow, RU). Advances in nuclear magnetic resonance spectroscopy (NMR) and x-ray crystallography have allowed the three-dimensional structures of many biological macromolecules and their complexes, including the ribosome and RNA polymerase to be solved. Fundamental principles of NMR spectroscopy and dynamics, x-ray crystallography, computation and experimental dynamics we...
Cotteril, Rodney
2002-01-01
Biophysics: An Introduction, is a concise balanced introduction to this subject. Written in an accessible and readable style, the book takes a fresh, modern approach with the author successfully combining key concepts and theory with relevant applications and examples drawn from the field as a whole. Beginning with a brief introduction to the origins of biophysics, the book takes the reader through successive levels of complexity, from atoms to molecules, structures, systems and ultimately to the behaviour of organisms. The book also includes extensive coverage of biopolymers, biomembranes, biological energy, and nervous systems. The text not only explores basic ideas, but also discusses recent developments, such as protein folding, DNA/RNA conformations, molecular motors, optical tweezers and the biological origins of consciousness and intelligence.
Research on Inversion Models for Forest Height Estimation Using Polarimetric SAR Interferometry
Zhang, L.; Duan, B.; Zou, B.
2017-09-01
The forest height is an important forest resource information parameter and usually used in biomass estimation. Forest height extraction with PolInSAR is a hot research field of imaging SAR remote sensing. SAR interferometry is a well-established SAR technique to estimate the vertical location of the effective scattering center in each resolution cell through the phase difference in images acquired from spatially separated antennas. The manipulation of PolInSAR has applications ranging from climate monitoring to disaster detection especially when used in forest area, is of particular interest because it is quite sensitive to the location and vertical distribution of vegetation structure components. However, some of the existing methods can't estimate forest height accurately. Here we introduce several available inversion models and compare the precision of some classical inversion approaches using simulated data. By comparing the advantages and disadvantages of these inversion methods, researchers can find better solutions conveniently based on these inversion methods.
Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models
Plant, Nathaniel G.; Holland, K. Todd
2011-01-01
A Bayesian network model has been developed to simulate a relatively simple problem of wave propagation in the surf zone (detailed in Part I). Here, we demonstrate that this Bayesian model can provide both inverse modeling and data-assimilation solutions for predicting offshore wave heights and depth estimates given limited wave-height and depth information from an onshore location. The inverse method is extended to allow data assimilation using observational inputs that are not compatible with deterministic solutions of the problem. These inputs include sand bar positions (instead of bathymetry) and estimates of the intensity of wave breaking (instead of wave-height observations). Our results indicate that wave breaking information is essential to reduce prediction errors. In many practical situations, this information could be provided from a shore-based observer or from remote-sensing systems. We show that various combinations of the assimilated inputs significantly reduce the uncertainty in the estimates of water depths and wave heights in the model domain. Application of the Bayesian network model to new field data demonstrated significant predictive skill (R2 = 0.7) for the inverse estimate of a month-long time series of offshore wave heights. The Bayesian inverse results include uncertainty estimates that were shown to be most accurate when given uncertainty in the inputs (e.g., depth and tuning parameters). Furthermore, the inverse modeling was extended to directly estimate tuning parameters associated with the underlying wave-process model. The inverse estimates of the model parameters not only showed an offshore wave height dependence consistent with results of previous studies but the uncertainty estimates of the tuning parameters also explain previously reported variations in the model parameters.
Three-dimensional electromagnetic modeling and inversion on massively parallel computers
Energy Technology Data Exchange (ETDEWEB)
Newman, G.A.; Alumbaugh, D.L. [Sandia National Labs., Albuquerque, NM (United States). Geophysics Dept.
1996-03-01
This report has demonstrated techniques that can be used to construct solutions to the 3-D electromagnetic inverse problem using full wave equation modeling. To this point great progress has been made in developing an inverse solution using the method of conjugate gradients which employs a 3-D finite difference solver to construct model sensitivities and predicted data. The forward modeling code has been developed to incorporate absorbing boundary conditions for high frequency solutions (radar), as well as complex electrical properties, including electrical conductivity, dielectric permittivity and magnetic permeability. In addition both forward and inverse codes have been ported to a massively parallel computer architecture which allows for more realistic solutions that can be achieved with serial machines. While the inversion code has been demonstrated on field data collected at the Richmond field site, techniques for appraising the quality of the reconstructions still need to be developed. Here it is suggested that rather than employing direct matrix inversion to construct the model covariance matrix which would be impossible because of the size of the problem, one can linearize about the 3-D model achieved in the inverse and use Monte-Carlo simulations to construct it. Using these appraisal and construction tools, it is now necessary to demonstrate 3-D inversion for a variety of EM data sets that span the frequency range from induction sounding to radar: below 100 kHz to 100 MHz. Appraised 3-D images of the earth`s electrical properties can provide researchers opportunities to infer the flow paths, flow rates and perhaps the chemistry of fluids in geologic mediums. It also offers a means to study the frequency dependence behavior of the properties in situ. This is of significant relevance to the Department of Energy, paramount to characterizing and monitoring of environmental waste sites and oil and gas exploration.
Probing the Heavy Neutrinos of Inverse Seesaw Model at the LHeC
Mondal, Subhadeep
2016-01-01
We consider the production of a heavy neutrino and its possible signals at the Large Hadron-electron Collider (LHeC) in the context of an inverse-seesaw model for neutrino mass generation. The inverse seesaw model extends the Standard Model (SM) particle content by adding two neutral singlet fermions for each lepton generation. It is a well motivated model in the context of generating non-zero neutrino masses and mixings. The proposed future LHeC machine presents us with a particularly interesting possibility to probe such extensions of the SM with new leptons due to the presence of an electron beam in the initial state. We show that the LHeC will be able to probe an inverse scenario with much better efficacy compared to the LHC with very nominal integrated luminosities as well as exploit the advantage of having the electron beam polarized to enhance the heavy neutrino production rates.
2.5D complex resistivity modeling and inversion using unstructured grids
Xu, Kaijun; Sun, Jie
2016-04-01
The characteristic of complex resistivity on rock and ore has been recognized by people for a long time. Generally we have used the Cole-Cole Model(CCM) to describe complex resistivity. It has been proved that the electrical anomaly of geologic body can be quantitative estimated by CCM parameters such as direct resistivity(ρ0), chargeability(m), time constant(τ) and frequency dependence(c). Thus it is very important to obtain the complex parameters of geologic body. It is difficult to approximate complex structures and terrain using traditional rectangular grid. In order to enhance the numerical accuracy and rationality of modeling and inversion, we use an adaptive finite-element algorithm for forward modeling of the frequency-domain 2.5D complex resistivity and implement the conjugate gradient algorithm in the inversion of 2.5D complex resistivity. An adaptive finite element method is applied for solving the 2.5D complex resistivity forward modeling of horizontal electric dipole source. First of all, the CCM is introduced into the Maxwell's equations to calculate the complex resistivity electromagnetic fields. Next, the pseudo delta function is used to distribute electric dipole source. Then the electromagnetic fields can be expressed in terms of the primary fields caused by layered structure and the secondary fields caused by inhomogeneities anomalous conductivity. At last, we calculated the electromagnetic fields response of complex geoelectric structures such as anticline, syncline, fault. The modeling results show that adaptive finite-element methods can automatically improve mesh generation and simulate complex geoelectric models using unstructured grids. The 2.5D complex resistivity invertion is implemented based the conjugate gradient algorithm.The conjugate gradient algorithm doesn't need to compute the sensitivity matrix but directly computes the sensitivity matrix or its transpose multiplying vector. In addition, the inversion target zones are
Institute of Scientific and Technical Information of China (English)
LANG Li-hui; LI Tao; ZHOU Xian-bin; B. E. KRISTENSEN; J. DANCKERT; K. B. NIELSEN
2006-01-01
By using aluminum alloys, the properties of the material in sheet hydroforming were obtained based on the identification of parameters for constitutive models by inverse modeling in which the friction coefficients were also considered in 2D and 3D simulations. With consideration of identified simulation parameters by inverse modeling, some key process parameters including tool dimensions and pre-bulging on the forming processes in sheet hydroforming were investigated and optimized. Based on the optimized parameters, the sheet hydroforming process can be analyzed more accurately to improve the robust design. It proves that the results from simulation based on the identified parameters are in good agreement with those from experiments.
Reservoir Modeling Combining Geostatistics with Markov Chain Monte Carlo Inversion
DEFF Research Database (Denmark)
Zunino, Andrea; Lange, Katrine; Melnikova, Yulia;
2014-01-01
, multi-step forward model (rock physics and seismology) and to provide realistic estimates of uncertainties. To generate realistic models which represent samples of the prior distribution, and to overcome the high computational demand, we reduce the search space utilizing an algorithm drawn from...
Modeling the isotope effect in Walden inversion reactions
Schechter, Israel
1991-05-01
A simple model to explain the isotope effect in the Walden exchange reaction is suggested. It is developed in the spirit of the line-of-centers models, and considers a hard-sphere collision that transfers energy from the relative translation to the desired vibrational mode, as well as geometrical properties and steric requirements. This model reproduces the recently measured cross sections for the reactions of hydrogen with isotopic silanes and older measurements of the substitution reactions of tritium atoms with isotopic methanes. Unlike previously given explanations, this model explains the effect of the attacking atom as well as of the other participating atoms. The model provides also qualitative explanation of the measured relative yields and thresholds of CH 3T and CH 2TF from the reaction T + CH 3F. Predictions for isotope effects and cross sections of some unmeasured reactions are given.
Institute of Scientific and Technical Information of China (English)
Yan Hanjie; Yan Hong; Li Yunping; Zhang Xiaofeng
2003-01-01
As gravity field, magnetic field, electric field and reismic wave field are all physical fields, their object function, reverse function and compound function are certainly infinite continuously differentiable functions which can be expanded into Taylor (Fourier) series within domain of definition and be further reduced into solving stochastic distribution function of series and statistic inference of optimal approximation. This is thebasis of combined gravity-magnetic-electric-seismic inversion of stochastic modeling. It is an uncertainty modeling technology of combining gravity-magnetic-electric-seismic inversion built on the basis of separation of field and source gravity-magnetic difference-value (D-value) trend surface, taking distribution-independent fault system as its unit, depths of seismic and electric interfaces of interests as its corresponding bivariate compound reverse function of gravity-magnetic anomalies and using high order polynomial (high order trigonometric function) approximating to its series distribution. The difference from current dominant inversion techniques is that, first, it does not respectively create gravity-seismic, magnetic-seismic deterministic inversion model from theoretical model, but combines gravity-magnetic-electric-seismic stochastic inversion model from stochastic model; second, after the concept of equivalent geological body being introduced, using feature of independent variable of gravity-magnetic field functions, taking density and susceptibility related to gravity-magnetic function as default parameters of model, the deterministic model is established owing to better solution to the contradiction of difficulty in identifying strata and less test analytical data for density and susceptibility in newly explored area; third, under assumption of independent parent distribution, a real modeling by strata, the problem of difficult plane closure arising in profile modeling is avoided. This technology has richer and more
Large-scale 3-D modeling by integration of resistivity models and borehole data through inversion
DEFF Research Database (Denmark)
Foged, N.; Marker, Pernille Aabye; Christiansen, A. V.;
2014-01-01
resistivity and the clay fraction. Through inversion we use the lithological data and the resistivity data to determine the optimum spatially distributed translator function. Applying the translator function we get a 3-D clay fraction model, which holds information from the resistivity data set....... The parameter of interest is the clay fraction, expressed as the relative length of clay units in a depth interval. The clay fraction is obtained from lithological logs and the clay fraction from the resistivity is obtained by establishing a simple petrophysical relationship, a translator function, between...... and the borehole data set in one variable. Finally, we use k-means clustering to generate a 3-D model of the subsurface structures. We apply the procedure to the Norsminde survey in Denmark, integrating approximately 700 boreholes and more than 100 000 resistivity models from an airborne survey...
Efficient inversion of three-dimensional finite element models of volcano deformation
Charco, M.; Galán del Sastre, P.
2014-03-01
Numerical techniques, as such as finite element method, allow for the inclusion of features, such as topography and/or mechanical heterogeneities, for the interpretation of volcanic deformation. However, models based on these numerical techniques usually are not suitable to be included in non-linear estimations of source parameters based on explorative optimization schemes because they require a calculation of the numerical approach for every evaluation of the misfit function. We present a procedure for finite element (FE) models that can be combined with explorative inversion schemes. The methodology is based on including a body force term representing an infinitesimal source in the model formulation that is responsible for pressure (volume) changes in the medium. This provides significant savings in both the time required for mesh generation and actual computational time of the numerical approach. Furthermore, we develop an inversion algorithm to estimate those parameters that characterize the changes in location and pressure (volume) of deformation sources. Both provide FE inversions in a single step, avoiding remeshing and assembly of the linear system of algebraic equations that define the numerical approach and/or the automatic mesh generation. After providing the theoretical basis for the model, the numerical approach and the algorithm for the inversions, we test the methodology using a synthetic example in a stratovolcano. Our results suggest that the FE inversion methodology can be considered suitable for efficiently save time in quantitative interpretations of volcano deformation.
Directory of Open Access Journals (Sweden)
ZHOU Hao
2015-08-01
Full Text Available In order to solve the intensive computing tasks and high memory demand problem in satellite gravity field model inversion on the basis of huge amounts of satellite gravity observations, the parallel algorithm for high truncated order and degree satellite gravity field model inversion with least square method on the basis of MPI was introduced. After analyzing the time and space complexity of each step in the solving flow, the parallel I/O, block-organized storage and block-organized computation algorithm on the basis of MPI are introduced to design the parallel algorithm for building design matrix, establishing and solving normal equation, and the simulation results indicate that the parallel efficiency of building design matrix, establishing and solving normal equation can reach to 95%, 68%and 63% respectively. In addition, on the basis of GOCE simulated orbits and radial disturbance gravity gradient data(518 400 epochs in total, two earth gravity models truncated to degree and order 120, 240 are inversed, and the relative computation time and memory demand are only about 40 minutes and 7 hours, 290 MB and 1.57 GB respectively. Eventually, a simulation numerical calculation for earth gravity field model inversion with the simulation data, which has the equivalent noise level with GRACE and GOCE mission, is conducted. The accuracy of inversion model has a good consistent with current released model, and the combined mode can complement the spectral information of each individual mission, which indicates that the parallel algorithm in this paper can be applied to inverse the high truncated degree and order earth gravity model efficiently and stably.
Directory of Open Access Journals (Sweden)
Benjamin L. Turner
2016-10-01
Full Text Available Agriculture-based irrigation communities of northern New Mexico have survived for centuries despite the arid environment in which they reside. These irrigation communities are threatened by regional population growth, urbanization, a changing demographic profile, economic development, climate change, and other factors. Within this context, we investigated the extent to which community resource management practices centering on shared resources (e.g., water for agricultural in the floodplains and grazing resources in the uplands and mutualism (i.e., shared responsibility of local residents to maintaining traditional irrigation policies and upholding cultural and spiritual observances embedded within the community structure influence acequia function. We used a system dynamics modeling approach as an interdisciplinary platform to integrate these systems, specifically the relationship between community structure and resource management. In this paper we describe the background and context of acequia communities in northern New Mexico and the challenges they face. We formulate a Dynamic Hypothesis capturing the endogenous feedbacks driving acequia community vitality. Development of the model centered on major stock-and-flow components, including linkages for hydrology, ecology, community, and economics. Calibration metrics were used for model evaluation, including statistical correlation of observed and predicted values and Theil inequality statistics. Results indicated that the model reproduced trends exhibited by the observed system. Sensitivity analyses of socio-cultural processes identified absentee decisions, cumulative income effect on time in agriculture, and land use preference due to time allocation, community demographic effect, effect of employment on participation, and farm size effect as key determinants of system behavior and response. Sensitivity analyses of biophysical parameters revealed that several key parameters (e.g., acres per
Geurts, Bernard J.; Meyers, Johan
2006-01-01
We propose the successive inverse polynomial interpolation method to optimize model parameters in subgrid parameterization for large-eddy simulation. This approach is illustrated for the Smagorinsky eddy-viscosity model used in homogeneous decaying turbulence. The optimal Smagorinsky parameter is re
MOLIERE-5: Forward and inversion model for sub-mm wavelengths
Urban, J.; Baron, P.; Lautie, N.
2012-12-01
MOLIERE-5 (Microwave Observation LIne Estimation and REtrieval) is a versatile forward and inversion model for the millimeter and submillimeter wavelengths range and includes an inversion model. The MOLIERE-5 forward model includes modules for the calculation of absorption coefficients, radiative transfer, and instrumental characteristics. The radiative transfer model is supplemented by a sensitivity module for estimating the contribution to the spectrum of each catalog line at its center frequency enabling the model to effectively filter for small spectral lines. The instrument model consists of several independent modules, including the calculation of the convolution of spectra and weighting functions with the spectrometer response functions. The instrument module also provides several options for modeling of frequency-switched observations. The MOLIERE-5 inversion model calculates linear Optimal Estimation, a least-squares retrieval method which uses statistical apriori knowledge on the retrieved parameters for the regularization of ill-posed inversion problems and computes diagnostics such as the measurement and smoothing error covariance matrices along with contribution and averaging kernel functions.
Geurts, Bernardus J.; Meyers, Johan
We propose the successive inverse polynomial interpolation method to optimize model parameters in subgrid parameterization for large-eddy simulation. This approach is illustrated for the Smagorinsky eddy-viscosity model used in homogeneous decaying turbulence. The optimal Smagorinsky parameter is
Inverse modelling of European N2O emissions: assimilating observations from different networks
Corazza, M.; Bergamaschi, P.; Vermeulen, A.T.; Krol, M.C.
2011-01-01
We describe the setup and first results of an inverse modelling system for atmospheric N2O, based on a four-dimensional variational (4DVAR) technique and the atmospheric transport zoom model TM5. We focus in this study on the European domain, utilizing a comprehensive set of quasi-continuous
Inverse modelling of European N2O emissions : Assimilating observations from different networks
Corazza, M.; Bergamaschi, P.; Vermeulen, A. T.; Aalto, T.; Haszpra, L.; Meinhardt, F.; O'Doherty, S.; Thompson, R.; Moncrieff, J.; Popa, Maria Elena; Steinbacher, M.; Jordan, A.; Dlugokencky, E.; Brühl, C.; Krol, M.; Dentener, F.
2011-01-01
We describe the setup and first results of an inverse modelling system for atmospheric N2O, based on a four-dimensional variational (4DVAR) technique and the atmospheric transport zoom model TM5. We focus in this study on the European domain, utilizing a comprehensive set of quasi-continuous
American Option Pricing using GARCH models and the Normal Inverse Gaussian distribution
DEFF Research Database (Denmark)
Stentoft, Lars Peter
In this paper we propose a feasible way to price American options in a model with time varying volatility and conditional skewness and leptokurtosis using GARCH processes and the Normal Inverse Gaussian distribution. We show how the risk neutral dynamics can be obtained in this model, we interpre....... In particular, improvements are found when considering the smile in implied standard deviations....
Humanoid Walking Robot: Modeling, Inverse Dynamics, and Gain Scheduling Control
Elvedin Kljuno; Williams, Robert L.
2010-01-01
This article presents reference-model-based control design for a 10 degree-of-freedom bipedal walking robot, using nonlinear gain scheduling. The main goal is to show concentrated mass models can be used for prediction of the required joint torques for a bipedal walking robot. Relatively complicated architecture, high DOF, and balancing requirements make the control task of these robots difficult. Although linear control techniques can be used to control bipedal robots, nonlinear control is n...
Estimation linear model using block generalized inverse of a matrix
Jasińska, Elżbieta; Preweda, Edward
2013-01-01
The work shows the principle of generalized linear model, point estimation, which can be used as a basis for determining the status of movements and deformations of engineering objects. The structural model can be put on any boundary conditions, for example, to ensure the continuity of the deformations. Estimation by the method of least squares was carried out taking into account the terms and conditions of the Gauss- Markov for quadratic forms stored using Lagrange function. The original sol...
DEFF Research Database (Denmark)
Ren, Tao; Modest, Michael F.; Fateev, Alexander
2015-01-01
In this study, we present an inverse calculation model based on the Levenberg-Marquardt optimization method to reconstruct temperature and species concentration from measured line-of-sight spectral transmissivity data for homogeneous gaseous media. The high temperature gas property database HITEMP...... 2010 (Rothman et al. (2010) [1]), which contains line-by-line (LBL) information for several combustion gas species, such as CO2 and H2O, was used to predict gas spectral transmissivities. The model was validated by retrieving temperatures and species concentrations from experimental CO2 and H2O...... transmissivity measurements. Optimal wavenumber ranges for CO2 and H2O transmissivity measured across a wide range of temperatures and concentrations were determined according to the performance of inverse calculations. Results indicate that the inverse radiation model shows good feasibility for measurements...
Institute of Scientific and Technical Information of China (English)
王锦地; 李小文; 孙晓敏; 刘强
2000-01-01
When the remote sensing pixel is composed of multiple components and a non-isothermal surface, its directional signature of thermal-infrared radiation is mainly determined by the 3D structure of the pixel. In this paper, we present our simple directional thermal radiation model to describe the relation between the pixel thermal emission and the pixel’s component parameters, and invert the model to get the component temperatures. For the inversion algorithm, we focus on how to use the information of given observations in a more effective way. The information content in data space and parameter space is defined, and the transferring of information content in inversion procedure is studied. Our forward model and inversion method are validated using indoor directional measurement data.
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
When the remote sensing pixel is composed of multiple components and a non-isothermal surface,its directional signature of thermal-infrared radiation is mainly determined by the 3D structure of the pixel.In this paper,we present our simple directional thermal radiation model to describe the relation between the pixel thermal emission and the pixel's component parameters,and invert the model to get the component temperatures.For the inversion algorithm,we focus on how to use the information of given observations in a more effective way.The information content in data space and parameter space is defined,and the transferring of information content in inversion procedure is studied.Our forward model and inversion method are validated using indoor directional measurement data.
Nonlinear inverse modeling of sensor based on back-propagation fuzzy logical system
Institute of Scientific and Technical Information of China (English)
Li Jun; Liu Junhua
2007-01-01
Objective To correct the nonlinear error of sensor output, a new approach to sensor inverse modeling based on Back-Propagation Fuzzy Logical System (BP FS) is presented. Methods The BP FS is a computationally efficient nonlinear universal approximator, which is capable of implementing complex nonlinear mapping from its input pattern space to the output with fast convergence speed. Results The neuro-fuzzy hybrid system, i.e. BP FS, is then applied to construct nonlinear inverse model of pressure sensor. The experimental results show that the proposed inverse modeling method automatically compensates the associated nonlinear error in pressure estimation, and thus the performance of pressure sensor is significantly improved. Conclusion The proposed method can be widely used in nonlinearity correction of various kinds of sensors to compensate the effects of nonlinearity and temperature on sensor output.
Implications of an inverse branching aftershock sequence model.
Turcotte, D L; Abaimov, S G; Dobson, I; Rundle, J B
2009-01-01
The branching aftershock sequence (BASS) model is a self-similar statistical model for earthquake aftershock sequences. A prescribed parent earthquake generates a first generation of daughter aftershocks. The magnitudes and times of occurrence of the daughters are obtained from statistical distributions. The first generation daughter aftershocks then become parent earthquakes that generate second generation aftershocks. The process is then extended to higher generations. The key parameter in the BASS model is the magnitude difference Deltam* between the parent earthquake and the largest expected daughter earthquake. In the application of the BASS model to aftershocks Deltam* is positive, the largest expected daughter event is smaller than the parent, and the sequence of events (aftershocks) usually dies out, but an exponential growth in the number of events with time is also possible. In this paper we explore this behavior of the BASS model as Deltam* varies, including when Deltam* is negative and the largest expected daughter event is larger than the parent. The applications of this self-similar branching process to biology and other fields are discussed.
Advanced model of eddy-current NDE inverse problem with sparse grid algorithm
Zhou, Liming; Sabbagh, Harold A.; Sabbagh, Elias H.; Murphy, R. Kim; Bernacchi, William
2017-02-01
In model-based inverse problem, some unknown parameters need to be estimated. These parameters are used not only to characterize the physical properties of cracks, but also to describe the position of the probes (such as lift off and angles) in the calibration. After considering the effect of the position of the probes in the inverse problem, the accuracy of the inverse result will be improved. With increasing the number of the parameters in the inverse problems, the burden of calculations will increase exponentially in the traditional full grid method. The sparse grid algorithm, which was introduced by Sergey A. Smolyak, was used in our work. With this algorithm, we obtain a powerful interpolation method that requires significantly fewer support nodes than conventional interpolation on a full grid. In this work, we combined sparse grid toolbox TASMANIAN, which is produced by Oak Ridge National Laboratory, and professional eddy-current NDE software, VIC-3D R◯, to solve a specific inverse problem. An advanced model based on our previous one is used to estimate length and depth of the crack, lift off and two angles of the position of probes. Considering the calibration process, pseudorandom noise is considered in the model and statistical behavior is discussed.
Inverse problems in geographical economics: parameter identification in the spatial Solow model.
Engbers, Ralf; Burger, Martin; Capasso, Vincenzo
2014-11-13
The identification of production functions from data is an important task in the modelling of economic growth. In this paper, we consider a non-parametric approach to this identification problem in the context of the spatial Solow model which allows for rather general production functions, in particular convex-concave ones that have recently been proposed as reasonable shapes. We formulate the inverse problem and apply Tikhonov regularization. The inverse problem is discretized by finite elements and solved iteratively via a preconditioned gradient descent approach. Numerical results for the reconstruction of the production function are given and analysed at the end of this paper.
Directory of Open Access Journals (Sweden)
A.A. Fahmy
2013-12-01
Full Text Available This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learning technique is applied to generate the required inverse modeling rules from input/output data recorded in the off-line structure learning phase. Second, a fully differentiable fuzzy neural network is developed to construct the inverse dynamics part of the controller for the online parameter learning phase. Finally, a fuzzy-PID-like incremental controller was employed as Feedback servo controller. The proposed control system was tested using dynamic model of a six-axis industrial robot. The control system showed good results compared to the conventional PID individual joint controller.
Relating Biophysical Properties Across Scales
Flenner, Elijah; Neagu, Adrian; Kosztin, Ioan; Forgacs, Gabor
2007-01-01
A distinguishing feature of a multicellular living system is that it operates at various scales, from the intracellular to organismal. Very little is known at present on how tissue level properties are related to cell and subcellular properties. Modern measurement techniques provide quantitative results at both the intracellular and tissue level, but not on the connection between these. In the present work we outline a framework to address this connection. We specifically concentrate on the morphogenetic process of tissue fusion, by following the coalescence of two contiguous multicellular aggregates. The time evolution of this process can accurately be described by the theory of viscous liquids. We also study fusion by Monte Carlo simulations and a novel Cellular Particle Dynamics (CPD) model, which is similar to the earlier introduced Subcellular Element Model (Newman, 2005). Using the combination of experiments, theory and modeling we are able to relate the measured tissue level biophysical quantities to s...
Forward and Inverse Modeling of Brown Dwarf Atmospheres
Fortney, Jonathan
Ultracool dwarfs (UCDs), here defined as the L, T, and Y spectral classes, consist of the lowest mass stars and the substellar brown dwarfs. Over 1200 are currently known, from effective temperatures of 2400 K down to "room temperature" objects of 300 K. Observations of UCDs show tremendous diversity in their spectral characteristics. However, factors such as metallicity, non-solar C/O ratios, surface gravity, vertical mixing efficiency, cloud levels, and cloud thickness remain largely unexplored within atmosphere models. This leads to a very limited understanding of the physical and chemical causes of brown dwarf diversity. One of the main motivations of this proposal is to greatly expand the kinds of modeling efforts that we envision for UCD science to obtain fundamentally new insights from the spectra of several hundred objects. First, we will expand our self-consistent grids of combined atmosphere and evolution models. With this traditional approach we can test the sensitivity of synthetic spectra of changes in parameters like surface gravity, cloud thickness, partial cloudiness, cloud particle size, and vertical mixing efficiency. Second, we will use powerful retrieval techniques to invert the model-to-data comparison problem. These Bayesian techniques allow the inference of P-T profile structure and molecular abundances, directly from the data. The first target populations are benchmark brown dwarfs, which have a well-studied main sequence companion, and where metallicity, age, and even mass can be independently constrained. The second is the 500+ UCDs across all spectral types that have NIR spectra already in hand in the SpeX spectral library. The third population is brown dwarfs that are variable in emission. This work is directly relevant to the NASA Astrophysics Theory (ATP) program. The proposed falls within the ATP scope of "Stellar Astrophysics and Exoplanets," which specifically includes brown dwarfs. The current proposal both facilitates "the
Castro, Luísa; Aguiar, Paulo
2012-08-01
Phase precession is one of the most well known examples within the temporal coding hypothesis. Here we present a biophysical spiking model for phase precession in hippocampal CA1 which focuses on the interaction between place cells and local inhibitory interneurons. The model's functional block is composed of a place cell (PC) connected with a local inhibitory cell (IC) which is modulated by the population theta rhythm. Both cells receive excitatory inputs from the entorhinal cortex (EC). These inputs are both theta modulated and space modulated. The dynamics of the two neuron types are described by integrate-and-fire models with conductance synapses, and the EC inputs are described using non-homogeneous Poisson processes. Phase precession in our model is caused by increased drive to specific PC/IC pairs when the animal is in their place field. The excitation increases the IC's firing rate, and this modulates the PC's firing rate such that both cells precess relative to theta. Our model implies that phase coding in place cells may not be independent from rate coding. The absence of restrictive connectivity constraints in this model predicts the generation of phase precession in any network with similar architecture and subject to a clocking rhythm, independently of the involvement in spatial tasks.
Simutė, S.; Fichtner, A.
2015-12-01
We present a feasibility study for seismic source inversions using a 3-D velocity model for the Japanese Islands. The approach involves numerically calculating 3-D Green's tensors, which is made efficient by exploiting Green's reciprocity. The rationale for 3-D seismic source inversion has several aspects. For structurally complex regions, such as the Japan area, it is necessary to account for 3-D Earth heterogeneities to prevent unknown structure polluting source solutions. In addition, earthquake source characterisation can serve as a means to delineate existing faults. Source parameters obtained for more realistic Earth models can then facilitate improvements in seismic tomography and early warning systems, which are particularly important for seismically active areas, such as Japan. We have created a database of numerically computed 3-D Green's reciprocals for a 40°× 40°× 600 km size area around the Japanese Archipelago for >150 broadband stations. For this we used a regional 3-D velocity model, recently obtained from full waveform inversion. The model includes attenuation and radial anisotropy and explains seismic waveform data for periods between 10 - 80 s generally well. The aim is to perform source inversions using the database of 3-D Green's tensors. As preliminary steps, we present initial concepts to address issues that are at the basis of our approach. We first investigate to which extent Green's reciprocity works in a discrete domain. Considering substantial amounts of computed Green's tensors we address storage requirements and file formatting. We discuss the importance of the initial source model, as an intelligent choice can substantially reduce the search volume. Possibilities to perform a Bayesian inversion and ways to move to finite source inversion are also explored.
Dynamic inversion method based on the time-staggered stereo-modeling scheme and its acceleration
Jing, Hao; Yang, Dinghui; Wu, Hao
2016-12-01
A set of second-order differential equations describing the space-time behaviour of derivatives of displacement with respect to model parameters (i.e. waveform sensitivities) is obtained via taking the derivative of the original wave equations. The dynamic inversion method obtains sensitivities of the seismic displacement field with respect to earth properties directly by solving differential equations for them instead of constructing sensitivities from the displacement field itself. In this study, we have taken a new perspective on the dynamic inversion method and used acceleration approaches to reduce the computational time and memory usage to improve its ability of performing high-resolution imaging. The dynamic inversion method, which can simultaneously use different waves and multicomponent observation data, is appropriate for directly inverting elastic parameters, medium density or wave velocities. Full wavefield information is utilized as much as possible at the expense of a larger amount of calculations. To mitigate the computational burden, two ways are proposed to accelerate the method from a computer-implementation point of view. One is source encoding which uses a linear combination of all shots, and the other is to reduce the amount of calculations on forward modeling. We applied a new finite-difference (FD) method to the dynamic inversion to improve the computational accuracy and speed up the performance. Numerical experiments indicated that the new FD method can effectively suppress the numerical dispersion caused by the discretization of wave equations, resulting in enhanced computational efficiency with less memory cost for seismic modeling and inversion based on the full wave equations. We present some inversion results to demonstrate the validity of this method through both checkerboard and Marmousi models. It shows that this method is also convergent even with big deviations for the initial model. Besides, parallel calculations can be easily
Locatelli, Robin; Bousquet, Philippe; Chevallier, Frédéric
2013-04-01
Since the nineties, inverse modelling by assimilating atmospheric measurements into a chemical transport model (CTM) has been used to derive sources and sinks of atmospheric trace gases. More recently, the high global warming potential of methane (CH4) and unexplained variations of its atmospheric mixing ratio caught the attention of several research groups. Indeed, the diversity and the variability of methane sources induce high uncertainty on the present and the future evolution of CH4 budget. With the increase of available measurement data to constrain inversions (satellite data, high frequency surface and tall tower observations, FTIR spectrometry,...), the main limiting factor is about to become the representation of atmospheric transport in CTMs. Indeed, errors in transport modelling directly converts into flux changes when assuming perfect transport in atmospheric inversions. Hence, we propose an inter-model comparison in order to quantify the impact of transport and modelling errors on the CH4 fluxes estimated into a variational inversion framework. Several inversion experiments are conducted using the same set-up (prior emissions, measurement and prior errors, OH field, initial conditions) of the variational system PYVAR, developed at LSCE (Laboratoire des Sciences du Climat et de l'Environnement, France). Nine different models (ACTM, IFS, IMPACT, IMPACT1x1, MOZART, PCTM, TM5, TM51x1 and TOMCAT) used in TRANSCOM-CH4 experiment (Patra el al, 2011) provide synthetic measurements data at up to 280 surface sites to constrain the inversions performed using the PYVAR system. Only the CTM (and the meteorological drivers which drive them) used to create the pseudo-observations vary among inversions. Consequently, the comparisons of the nine inverted methane fluxes obtained for 2005 give a good order of magnitude of the impact of transport and modelling errors on the estimated fluxes with current and future networks. It is shown that transport and modelling errors
Frystacky, H.; Osorio-Murillo, C. A.; Over, M. W.; Kalbacher, T.; Gunnell, D.; Kolditz, O.; Ames, D.; Rubin, Y.
2013-12-01
The Method of Anchored Distributions (MAD) is a Bayesian technique for characterizing the uncertainty in geostatistical model parameters. Open-source software has been developed in a modular framework such that this technique can be applied to any forward model software via a driver. This presentation is about the driver that has been developed for OpenGeoSys (OGS), open-source software that can simulate many hydrogeological processes, including couple processes. MAD allows the use of multiple data types for conditioning the spatially random fields and assessing model parameter likelihood. For example, if simulating flow and mass transport, the inversion target variable could be hydraulic conductivity and the inversion data types could be head, concentration, or both. The driver detects from the OGS files which processes and variables are being used in a given project and allows MAD to prompt the user to choose those that are to be modeled or to be treated deterministically. In this way, any combination of processes allowed by OGS can have MAD applied. As for the software, there are two versions, each with its own OGS driver. A Windows desktop version is available as a graphical user interface and is ideal for the learning and teaching environment. High-throughput computing can even be achieved with this version via HTCondor if large projects want to be pursued in a computer lab. In addition to this desktop application, a Linux version is available equipped with MPI such that it can be run in parallel on a computer cluster. All releases can be downloaded from the MAD Codeplex site given below.
Modeling and inversion Matlab algorithms for resistivity, induced polarization and seismic data
Karaoulis, M.; Revil, A.; Minsley, B. J.; Werkema, D. D.
2011-12-01
M. Karaoulis (1), D.D. Werkema (3), A. Revil (1,2), A., B. Minsley (4), (1) Colorado School of Mines, Dept. of Geophysics, Golden, CO, USA. (2) ISTerre, CNRS, UMR 5559, Université de Savoie, Equipe Volcan, Le Bourget du Lac, France. (3) U.S. EPA, ORD, NERL, ESD, CMB, Las Vegas, Nevada, USA . (4) USGS, Federal Center, Lakewood, 10, 80225-0046, CO. Abstract We propose 2D and 3D forward modeling and inversion package for DC resistivity, time domain induced polarization (IP), frequency-domain IP, and seismic refraction data. For the resistivity and IP case, discretization is based on rectangular cells, where each cell has as unknown resistivity in the case of DC modelling, resistivity and chargeability in the time domain IP modelling, and complex resistivity in the spectral IP modelling. The governing partial-differential equations are solved with the finite element method, which can be applied to both real and complex variables that are solved for. For the seismic case, forward modeling is based on solving the eikonal equation using a second-order fast marching method. The wavepaths are materialized by Fresnel volumes rather than by conventional rays. This approach accounts for complicated velocity models and is advantageous because it considers frequency effects on the velocity resolution. The inversion can accommodate data at a single time step, or as a time-lapse dataset if the geophysical data are gathered for monitoring purposes. The aim of time-lapse inversion is to find the change in the velocities or resistivities of each model cell as a function of time. Different time-lapse algorithms can be applied such as independent inversion, difference inversion, 4D inversion, and 4D active time constraint inversion. The forward algorithms are benchmarked against analytical solutions and inversion results are compared with existing ones. The algorithms are packaged as Matlab codes with a simple Graphical User Interface. Although the code is parallelized for multi
Directory of Open Access Journals (Sweden)
N. Evangeliou
2017-07-01
Full Text Available This paper describes the results of an inverse modeling study for the determination of the source term of the radionuclides 134Cs, 137Cs and 131I released after the Chernobyl accident. The accident occurred on 26 April 1986 in the Former Soviet Union and released about 1019 Bq of radioactive materials that were transported as far away as the USA and Japan. Thereafter, several attempts to assess the magnitude of the emissions were made that were based on the knowledge of the core inventory and the levels of the spent fuel. More recently, when modeling tools were further developed, inverse modeling techniques were applied to the Chernobyl case for source term quantification. However, because radioactivity is a sensitive topic for the public and attracts a lot of attention, high-quality measurements, which are essential for inverse modeling, were not made available except for a few sparse activity concentration measurements far from the source and far from the main direction of the radioactive fallout. For the first time, we apply Bayesian inversion of the Chernobyl source term using not only activity concentrations but also deposition measurements from the most recent public data set. These observations refer to a data rescue attempt that started more than 10 years ago, with a final goal to provide available measurements to anyone interested. In regards to our inverse modeling results, emissions of 134Cs were estimated to be 80 PBq or 30–50 % higher than what was previously published. From the released amount of 134Cs, about 70 PBq were deposited all over Europe. Similar to 134Cs, emissions of 137Cs were estimated as 86 PBq, on the same order as previously reported results. Finally, 131I emissions of 1365 PBq were found, which are about 10 % less than the prior total releases. The inversion pushes the injection heights of the three radionuclides to higher altitudes (up to about 3 km than previously assumed (≈ 2.2 km in order
Effects of geometric head model perturbations on the EEG forward and inverse problems.
von Ellenrieder, Nicolás; Muravchik, Carlos H; Nehorai, Arye
2006-03-01
We study the effect of geometric head model perturbations on the electroencephalography (EEG) forward and inverse problems. Small magnitude perturbations of the shape of the head could represent uncertainties in the head model due to errors on images or techniques used to construct the model. They could also represent small scale details of the shape of the surfaces not described in a deterministic model, such as the sulci and fissures of the cortical layer. We perform a first-order perturbation analysis, using a meshless method for computing the sensitivity of the solution of the forward problem to the geometry of the head model. The effect on the forward problem solution is treated as noise in the EEG measurements and the Cramér-Rao bound is computed to quantify the effect on the inverse problem performance. Our results show that, for a dipolar source, the effect of the perturbations on the inverse problem performance is under the level of the uncertainties due to the spontaneous brain activity. Thus, the results suggest that an extremely detailed model of the head may be unnecessary when solving the EEG inverse problem.
Model study of the compact gravity reconstruction; Juryoku inversion `CGR` no model kento
Energy Technology Data Exchange (ETDEWEB)
Ishii, Y.; Muraoka, A. [Sogo Geophysical Exploration Co. Ltd., Tokyo (Japan)
1996-05-01
An examination was made on gravity inversion using a compact gravity reconstruction (CGR) method in gravity tomography analysis. In a model analysis, an analytical region of 100m{times}50m was divided into cells of 10m{times}10m, on the assumption that two density anomalous bodies with a density difference of 1.0g/cm{sup 3} existed with one shallow and the other deep density distribution. The result of the analysis revealed that, in a linear analysis by a general inverse matrix, blurs and blotting were plenty with a tendency of making gravity anomaly attributable to an anomalous distribution of shallow density; that CGR provided a large effect in making a clear contrast of an anomalous part; that, where structures of shallow and deep density anomalies existed, the analysis by CGR was inferior in the restoration of a deep structure with errors enlarged; that, if a gravity traverse was taken long compared with the distribution depth of density anomalies, the analytical precision of a deep part was improved; that an analytical convergence was better with the restriction of density difference given on the large side than on the small side; and so on. 3 refs., 10 figs.
Sabbagh, Harold A; Sabbagh, Elias H; Aldrin, John C; Knopp, Jeremy S
2013-01-01
Computational Electromagnetics and Model-Based Inversion: A Modern Paradigm for Eddy Current Nondestructive Evaluation describes the natural marriage of the computer to eddy-current NDE. Three distinct topics are emphasized in the book: (a) fundamental mathematical principles of volume-integral equations as a subset of computational electromagnetics, (b) mathematical algorithms applied to signal-processing and inverse scattering problems, and (c) applications of these two topics to problems in which real and model data are used. By showing how mathematics and the computer can solve problems more effectively than current analog practices, this book defines the modern technology of eddy-current NDE. This book will be useful to advanced students and practitioners in the fields of computational electromagnetics, electromagnetic inverse-scattering theory, nondestructive evaluation, materials evaluation and biomedical imaging. Users of eddy-current NDE technology in industries as varied as nuclear power, aerospace,...
Baptista, Isaurinda; Irvine, Brian; Fleskens, Luuk; Geissen, Violette; Ritsema, Coen
2015-04-01
Rainfall variability, the occurrence of extreme drought and historic land management practice have been recognised as contributing to serious environmental impact in Cabo Verde. Investment in conservation measures has become visible throughout the landscape. Despite this the biophysical and socioeconomic impacts of the conservation measures have been poorly assessed and documented. As such a concerted approach based on the DESIRE project continues to consult stackholders and carry out field trials for selected conservation technologies. Recent field trials have demonstrated the potential of conservation technologies but have also demonstrated that yield variability between sites and between years is significant. This variability appears to be driven by soil and rainfall characteristics However, where detailed field studies have only run for a limited period they have not as yet encountered the full range of climatic variability; thus a modelling approach is considered to capture a greater range of climatic conditions. The PESERA-DESMICE model is adopted which considers the biophysical and social economic benefits of the conservation technologies against a local baseline condition. PESERA is adopted as climate is implicitly considered in the model and, where appropriate, in-situ conservation measures are considered as an annual input to the soil. The DESMICE component of the model considers the suitability of the conservation measures and their costs and benefits in terms of environmental conditions and market access. Historic rainfall statistics are calculated from field measurements in the Ribeira Seca catchment. These statistics are used to generate a series of 50 year rainfall realisations to capture a fuller range of the climatic conditions. Each realisation provides a unique time-series of rainfall and through modelling can provide a simulated time-series of crop yield. Additional realisations and model simulations add to an envelope of the potential crop
Influence of head models on neuromagnetic fields and inverse source localizations
Directory of Open Access Journals (Sweden)
Schimpf Paul H
2006-10-01
Full Text Available Abstract Background The magnetoencephalograms (MEGs are mainly due to the source currents. However, there is a significant contribution to MEGs from the volume currents. The structure of the anatomical surfaces, e.g., gray and white matter, could severely influence the flow of volume currents in a head model. This, in turn, will also influence the MEGs and the inverse source localizations. This was examined in detail with three different human head models. Methods Three finite element head models constructed from segmented MR images of an adult male subject were used for this study. These models were: (1 Model 1: full model with eleven tissues that included detailed structure of the scalp, hard and soft skull bone, CSF, gray and white matter and other prominent tissues, (2 the Model 2 was derived from the Model 1 in which the conductivity of gray matter was set equal to the white matter, i.e., a ten tissuetype model, (3 the Model 3 consisted of scalp, hard skull bone, CSF, gray and white matter, i.e., a five tissue-type model. The lead fields and MEGs due to dipolar sources in the motor cortex were computed for all three models. The dipolar sources were oriented normal to the cortical surface and had a dipole moment of 100 μA meter. The inverse source localizations were performed with an exhaustive search pattern in the motor cortex area. A set of 100 trial inverse runs was made covering the 3 cm cube motor cortex area in a random fashion. The Model 1 was used as a reference model. Results The reference model (Model 1, as expected, performed best in localizing the sources in the motor cortex area. The Model 3 performed the worst. The mean source localization errors (MLEs of the Model 3 were larger than the Model 1 or 2. The contour plots of the magnetic fields on top of the head were also different for all three models. The magnetic fields due to source currents were larger in magnitude as compared to the magnetic fields of volume currents
Model-based optoacoustic inversion with arbitrary-shape detectors.
Rosenthal, Amir; Ntziachristos, Vasilis; Razansky, Daniel
2011-07-01
Optoacoustic imaging enables mapping the optical absorption of biological tissue using optical excitation and acoustic detection. Although most image-reconstruction algorithms are based on the assumption of a detector with an isotropic sensitivity, the geometry of the detector often leads to a response with spatially dependent magnitude and bandwidth. This effect may lead to attenuation or distortion in the recorded signal and, consequently, in the reconstructed image. Herein, an accurate numerical method for simulating the spatially dependent response of an arbitrary-shape acoustic transducer is presented. The method is based on an analytical solution obtained for a two-dimensional line detector. The calculated response is incorporated in the forward model matrix of an optoacoustic imaging setup using temporal convolution, and image reconstruction is performed by inverting the matrix relation. The method was numerically and experimentally demonstrated in two dimensions for both flat and focused transducers and compared to the spatial-convolution method. In forward simulations, the developed method did not suffer from the numerical errors exhibited by the spatial-convolution method. In reconstruction simulations and experiments, the use of both temporal-convolution and spatial-convolution methods lead to an enhancement in resolution compared to a reconstruction with a point detector model. However, because of its higher modeling accuracy, the temporal-convolution method achieved a noise figure approximated three times lower than the spatial-convolution method. The demonstrated performance of the spatial-convolution method shows it is a powerful tool for reducing reconstruction artifacts originating from the detector finite size and improving the quality of optoacoustic reconstructions. Furthermore, the method may be used for assessing new system designs. Specifically, detectors with nonstandard shapes may be investigated.
2.5-D forward and inverse modelling of full-waveform elastic seismic survey
Xiong, J. L.; Lin, Y.; Abubakar, A.; Habashy, T. M.
2013-05-01
We present a two-and-half-dimensional (2.5-D) forward and inversion algorithm for the interpretation of surface seismic elastic full-waveform data. The 2-D modelling approach for elastic waves might not be sufficiently accurate because of its line-source assumption. On the other hand, a full 3-D modelling of elastic waves is still computationally very expensive for seismic exploration applications. By employing the 2.5-D modelling approach, we assume that the elastic medium is 2-D while the source is a 3-D point source. We solve the 2.5-D problem by first transforming the elastic wave equation in the spatial domain into the wavenumber domain. Then, for each wavenumber we solve a 2-D problem using the finite difference method with staggered grids. After that an inverse wavenumber transform is performed to compute the 3-D field distribution. To handle the inverse transform, we develop an efficient numerical integration scheme by subdividing the integration domain and applying different integration rules to each subinterval. We show that this approach works well for surface seismic applications. The 2.5-D approach offers a more realistic modelling of the elastic wave data, hence it produces more accurate inversion results than the 2-D inversion approach. Finally, we validate this approach by using a numerical test. In this test we used our 2.5-D full-waveform inversion algorithm to invert the synthetic data generated by a 3-D finite-difference time-domain simulation.
Asteroid spin and shape modelling using two lightcurve inversion methods
Marciniak, Anna; Bartczak, Przemyslaw; Konstanciak, Izabella; Dudzinski, Grzegorz; Mueller, Thomas G.; Duffard, Rene
2016-10-01
We are conducting an observing campaign to counteract strong selection effects in photometric studies of asteroids. Our targets are long-period (P>12 hours) and low-amplitude (a_maxACM conf. 29B) provide a high level of agreement.Another way of validation is the shape model comparison with the asteroid shape contours obtained using different techniques (like the stellar occultation timings or adaptive optics imaging) or against data in thermal infrared range gathered by ground and space-bound observatories. The thermal data could provide assignment of size and albedo, but also can help to resolve spin-pole ambiguities. In special cases, the thermal data from Spitzer and Wise/NEOWise might even help in testing specific shape features via thermal infrared lightcurves.
Sekulić, Vladislav; Lawrence, J Josh; Skinner, Frances K
2014-01-01
Multi-compartmental models of neurons provide insight into the complex, integrative properties of dendrites. Because it is not feasible to experimentally determine the exact density and kinetics of each channel type in every neuronal compartment, an essential goal in developing models is to help characterize these properties. To address biological variability inherent in a given neuronal type, there has been a shift away from using hand-tuned models towards using ensembles or populations of models. In collectively capturing a neuron's output, ensemble modeling approaches uncover important conductance balances that control neuronal dynamics. However, conductances are never entirely known for a given neuron class in terms of its types, densities, kinetics and distributions. Thus, any multi-compartment model will always be incomplete. In this work, our main goal is to use ensemble modeling as an investigative tool of a neuron's biophysical balances, where the cycling between experiment and model is a design criterion from the start. We consider oriens-lacunosum/moleculare (O-LM) interneurons, a prominent interneuron subtype that plays an essential gating role of information flow in hippocampus. O-LM cells express the hyperpolarization-activated current (Ih). Although dendritic Ih could have a major influence on the integrative properties of O-LM cells, the compartmental distribution of Ih on O-LM dendrites is not known. Using a high-performance computing cluster, we generated a database of models that included those with or without dendritic Ih. A range of conductance values for nine different conductance types were used, and different morphologies explored. Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties. Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih. These findings inform future experiments that differentiate between
Directory of Open Access Journals (Sweden)
Vladislav Sekulić
Full Text Available Multi-compartmental models of neurons provide insight into the complex, integrative properties of dendrites. Because it is not feasible to experimentally determine the exact density and kinetics of each channel type in every neuronal compartment, an essential goal in developing models is to help characterize these properties. To address biological variability inherent in a given neuronal type, there has been a shift away from using hand-tuned models towards using ensembles or populations of models. In collectively capturing a neuron's output, ensemble modeling approaches uncover important conductance balances that control neuronal dynamics. However, conductances are never entirely known for a given neuron class in terms of its types, densities, kinetics and distributions. Thus, any multi-compartment model will always be incomplete. In this work, our main goal is to use ensemble modeling as an investigative tool of a neuron's biophysical balances, where the cycling between experiment and model is a design criterion from the start. We consider oriens-lacunosum/moleculare (O-LM interneurons, a prominent interneuron subtype that plays an essential gating role of information flow in hippocampus. O-LM cells express the hyperpolarization-activated current (Ih. Although dendritic Ih could have a major influence on the integrative properties of O-LM cells, the compartmental distribution of Ih on O-LM dendrites is not known. Using a high-performance computing cluster, we generated a database of models that included those with or without dendritic Ih. A range of conductance values for nine different conductance types were used, and different morphologies explored. Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties. Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih. These findings inform future experiments that
Vazquez-Anderson, Jorge; Mihailovic, Mia K.; Baldridge, Kevin C.; Reyes, Kristofer G.; Haning, Katie; Cho, Seung Hee; Amador, Paul; Powell, Warren B.
2017-01-01
Abstract Current approaches to design efficient antisense RNAs (asRNAs) rely primarily on a thermodynamic understanding of RNA–RNA interactions. However, these approaches depend on structure predictions and have limited accuracy, arguably due to overlooking important cellular environment factors. In this work, we develop a biophysical model to describe asRNA–RNA hybridization that incorporates in vivo factors using large-scale experimental hybridization data for three model RNAs: a group I intron, CsrB and a tRNA. A unique element of our model is the estimation of the availability of the target region to interact with a given asRNA using a differential entropic consideration of suboptimal structures. We showcase the utility of this model by evaluating its prediction capabilities in four additional RNAs: a group II intron, Spinach II, 2-MS2 binding domain and glgC 5΄ UTR. Additionally, we demonstrate the applicability of this approach to other bacterial species by predicting sRNA–mRNA binding regions in two newly discovered, though uncharacterized, regulatory RNAs. PMID:28334800
Wang, Dan; Jaiswal, Deepak; LeBauer, David S; Wertin, Timothy M; Bollero, Germán A; Leakey, Andrew D B; Long, Stephen P
2015-09-01
High-performance computing has facilitated development of biomass production models that capture the key mechanisms underlying production at high spatial and temporal resolution. Direct responses to increasing [CO2 ] and temperature are important to long-lived emerging woody bioenergy crops. Fast-growing willow (Salix spp.) within short rotation coppice (SRC) has considerable potential as a renewable biomass source, but performance over wider environmental conditions and under climate change is uncertain. We extended the bioenergy crop modeling platform, BioCro, to SRC willow by adding coppicing and C3 photosynthesis subroutines, and modifying subroutines for perennation, allocation, morphology, phenology and development. Parameterization with measurements of leaf photosynthesis, allocation and phenology gave agreement of modeled with measured yield across 23 sites in Europe and North America. Predictions for the continental USA suggest yields of ≥17 Mg ha(-1) year(-1) in a 4 year rotation. Rising temperature decreased predicted yields, an effect partially ameliorated by rising [CO2 ]. This model, based on over 100 equations describing the physiological and biophysical mechanisms underlying production, provides a new framework for utilizing mechanism of plant responses to the environment, including future climates. As an open-source tool, it is made available here as a community resource for further application, improvement and adaptation.
Directory of Open Access Journals (Sweden)
Yuri V. Konovalov
2012-09-01
Full Text Available We present results of basal friction coefficient inversion. The inversion was performed by a 2D flow line model for one of the four fast flowing ice streams on the southern side of the Academy of Sciences Ice Cap in the Komsomolets Island, Severnaya Zemlya archipelago. The input data for the performance of both the forward and the inverse problems included synthetic aperture radar interferometry ice surface velocities, ice surface elevations and ice thicknesses obtained by airborne measurements (all were taken from Dowdeswell et al., 2002. Numerical experiments with: i different sea level shifts; and ii randomly perturbed friction coefficient have been carried out in the forward problem. The impact of sea level changes on vertical distribution of horizontal velocity and on shear stress distribution near the ice front has been investigated in experiments with different sea level shifts. The experiments with randomly perturbed friction coefficient have revealed that the modeled surface velocity is weakly sensitive to the perturbations and, therefore, the inverse problem should be considered ill posed. To mitigate ill posedness of the inverse problem, Tikhonov’s regularization was applied. The regularization parameter was determined from the relation of the discrepancy between observed and modeled velocities to the regularization parameter. The inversion was performed for both linear and non-linear sliding laws. The inverted spatial distributions of the basal friction coefficient are similar for both sliding laws. The similarity between these inverted distributions suggests that the changes in the friction coefficient are accompanied by appropriate water content variations at the glacier base.
An Exactly Soluble Hierarchical Clustering Model Inverse Cascades, Self-Similarity, and Scaling
Gabrielov, A; Turcotte, D L
1999-01-01
We show how clustering as a general hierarchical dynamical process proceeds via a sequence of inverse cascades to produce self-similar scaling, as an intermediate asymptotic, which then truncates at the largest spatial scales. We show how this model can provide a general explanation for the behavior of several models that has been described as ``self-organized critical,'' including forest-fire, sandpile, and slider-block models.
Drewry, D.; Duveiller, G.
2013-12-01
Modern vegetation models incorporate ecophysiological details that allow for accurate estimates of carbon dioxide uptake, water use and energy exchange, but require knowledge of dynamic structural and biochemical traits. Variations in these traits are controlled by genetic factors as well as growth stage and nutrient and moisture availability, making them difficult to predict and prone to significant error. Here we explore the use of daily MODIS optical reflectance data for constraining key canopy- and leaf-level traits required by forward biophysical models. A multi-objective optimization algorithm is used to invert the PROSAIL canopy radiation transfer model against MODIS optical reflectance observations. PROSAIL accounts for the effects of leaf-level optical properties, foliage distribution and orientation on canopy reflectance across the optical range. Inversions are conducted for several growing seasons for both soybean and maize at multiple sites across the Central US agro-ecosystem. These inversions provide estimates of seasonal variations, and associated uncertainty, of variables such as leaf area index (LAI). The inversion-derived canopy properties are used to examine the ability of MODIS data to characterize seasonal variations in these states relative to field observations. The canopy properties are then used as inputs into the MLCan biophysical model to conduct forward simulations. MLCan characterizes the ecophysiological functioning of a plant canopy at a half-hourly timestep, and has been rigorously validated for both C3 and C4 crops against observations of canopy CO2 uptake, evapotranspiration and sensible heat exchange. By utilizing the inverted canopy states to drive MLCan over several growing seasons, we are able to assess the impact of uncertainty in the MODIS inversion procedure on uncertainties in forward model flux estimates. This work requires the use of instant (non-composited) observations obtained at a daily frequency from both Terra and
Ivanov, J.; Miller, R.D.; Xia, J.; Steeples, D.
2005-01-01
This paper is the second of a set of two papers in which we study the inverse refraction problem. The first paper, "Types of Geophysical Nonuniqueness through Minimization," studies and classifies the types of nonuniqueness that exist when solving inverse problems depending on the participation of a priori information required to obtain reliable solutions of inverse geophysical problems. In view of the classification developed, in this paper we study the type of nonuniqueness associated with the inverse refraction problem. An approach for obtaining a realistic solution to the inverse refraction problem is offered in a third paper that is in preparation. The nonuniqueness of the inverse refraction problem is examined by using a simple three-layer model. Like many other inverse geophysical problems, the inverse refraction problem does not have a unique solution. Conventionally, nonuniqueness is considered to be a result of insufficient data and/or error in the data, for any fixed number of model parameters. This study illustrates that even for overdetermined and error free data, nonlinear inverse refraction problems exhibit exact-data nonuniqueness, which further complicates the problem of nonuniqueness. By evaluating the nonuniqueness of the inverse refraction problem, this paper targets the improvement of refraction inversion algorithms, and as a result, the achievement of more realistic solutions. The nonuniqueness of the inverse refraction problem is examined initially by using a simple three-layer model. The observations and conclusions of the three-layer model nonuniqueness study are used to evaluate the nonuniqueness of more complicated n-layer models and multi-parameter cell models such as in refraction tomography. For any fixed number of model parameters, the inverse refraction problem exhibits continuous ranges of exact-data nonuniqueness. Such an unfavorable type of nonuniqueness can be uniquely solved only by providing abundant a priori information
Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N
2013-05-01
A whole-farm, stochastic and dynamic simulation model was developed to predict biophysical and economic performance of grazing dairy systems. Several whole-farm models simulate grazing dairy systems, but most of them work at a herd level. This model, named e-Dairy, differs from the few models that work at an animal level, because it allows stochastic behaviour of the genetic merit of individual cows for several traits, namely, yields of milk, fat and protein, live weight (LW) and body condition score (BCS) within a whole-farm model. This model accounts for genetic differences between cows, is sensitive to genotype × environment interactions at an animal level and allows pasture growth, milk and supplements price to behave stochastically. The model includes an energy-based animal module that predicts intake at grazing, mammary gland functioning and body lipid change. This whole-farm model simulates a 365-day period for individual cows within a herd, with cow parameters randomly generated on the basis of the mean parameter values, defined as input and variance and co-variances from experimental data sets. The main inputs of e-Dairy are farm area, use of land, type of pasture, type of crops, monthly pasture growth rate, supplements offered, nutritional quality of feeds, herd description including herd size, age structure, calving pattern, BCS and LW at calving, probabilities of pregnancy, average genetic merit and economic values for items of income and costs. The model allows to set management policies to define: dry-off cows (ceasing of lactation), target pre- and post-grazing herbage mass and feed supplementation. The main outputs are herbage dry matter intake, annual pasture utilisation, milk yield, changes in BCS and LW, economic farm profit and return on assets. The model showed satisfactory accuracy of prediction when validated against two data sets from farmlet system experiments. Relative prediction errors were profit and the associated risk.
Justiniano, A.; Jaya, Y.; Diephuis, G.; Veenhof, R.; Pringle, T.
2015-01-01
The objective of the study is to characterise the Triassic massive stacked sandstone deposits of the Main Buntsandstein Subgroup at Block Q16 located in the West Netherlands Basin. The characterisation was carried out through combining rock-physics modelling and seismic inversion techniques. The app
Inverse Magnetic Catalysis in hot quark matter within (P)NJL models
Ferreira, M; Providência, C; Lourenço, O; Frederico, T
2015-01-01
Apart from Magnetic Catalysis at low temperatures, recent LQCD studies have shown the opposite effect at temperatures near the transition region: instead of enhancing, the magnetic field suppresses the quark condensates (Inverse Magnetic Catalysis). In this paper, two approaches are discussed within NJL-type models with Polyakov Loop that reproduce both effects.
Modelling and Control of Inverse Dynamics for a 5-DOF Parallel Kinematic Polishing Machine
Directory of Open Access Journals (Sweden)
Weiyang Lin
2013-08-01
/ control method is presented and investigated 2∞ in order to track the error control of the inverse dynamic model; the simulation results from different conditions show that the mixed / control method could 2∞ achieve an optimal and robust control performance. This work shows that the presented PKPM has a higher dynamic performance than conventional machine tools.
The LXR inverse agonist SR9238 suppresses fibrosis in a model of non-alcoholic steatohepatitis
Directory of Open Access Journals (Sweden)
Kristine Griffett
2015-04-01
Conclusions: Here, we demonstrate that an LXR inverse agonist, SR9238, is effective in reduction of hepatic steatosis, inflammation and fibrosis in an animal model of NASH. These results have important implications for the development of therapeutics for treatment NASH in humans.
Inverse modeling of cloud-aerosol interactions -- Part 1: Detailed response surface analysis
Partridge, D.G.; Vrugt, J.A.; Tunved, P.; Ekman, A.M.L.; Gorea, D.; Sooroshian, A.
2011-01-01
New methodologies are required to probe the sensitivity of parameters describing cloud droplet activation. This paper presents an inverse modeling-based method for exploring cloud-aerosol interactions via response surfaces. The objective function, containing the difference between the measured and
Surface reaction network of CO oxidation on CeO2/Au(110) inverse model catalysts.
Ding, Liangbing; Xiong, Feng; Jin, Yuekang; Wang, Zhengming; Sun, Guanghui; Huang, Weixin
2016-11-30
CeO2/Au(110) inverse model catalysts were prepared and their activity toward the adsorption and co-adsorption of O2, CO, CO2 and water was studied by means of X-ray photoelectron spectroscopy, low energy electron diffraction, thermal desorption spectra and temperature-programmed reaction spectra. The Au surface of CeO2/Au(110) inverse model catalysts molecularly adsorbs CO, CO2 and water, and the polycrystalline CeO2 surface of CeO2/Au(110) inverse model catalysts molecularly adsorbs O2, and molecularly and reactively adsorbs CO, CO2 and water. By controllably preparing co-adsorbed surface species on CeO2/Au(110) inverse model catalysts, we successfully identified various surface reaction pathways of CO oxidation to produce CO2 with different barriers both on the CeO2 surface and at the Au-CeO2 interface, including CO oxidation by various oxygen species, and water/hydroxyl group-involved CO oxidation. These results establish a surface reaction network of CO oxidation catalyzed by Au/CeO2 catalysts, greatly advancing the fundamental understandings of catalytic CO oxidation reactions.
Justiniano, A.; Jaya, Y.; Diephuis, G.; Veenhof, R.; Pringle, T.
2015-01-01
The objective of the study is to characterise the Triassic massive stacked sandstone deposits of the Main Buntsandstein Subgroup at Block Q16 located in the West Netherlands Basin. The characterisation was carried out through combining rock-physics modelling and seismic inversion techniques. The app
Justiniano, A.; Jaya, M.; Diephuis, G.
2015-01-01
The objective of this study is to characterise the Jurassic Posidonia Shale Formation at Block Q16 located in the West Netherlands Basin. The characterisation was carried out through combining rock-physics modelling and seismic inversion techniques. The results show that the Posidonia Shale Formatio
Computer programs for forward and inverse modeling of acoustic and electromagnetic data
Ellefsen, Karl J.
2011-01-01
A suite of computer programs was developed by U.S. Geological Survey personnel for forward and inverse modeling of acoustic and electromagnetic data. This report describes the computer resources that are needed to execute the programs, the installation of the programs, the program designs, some tests of their accuracy, and some suggested improvements.
A Systematic and Numerically Efficient Procedure for Stable Dynamic Model Inversion of LTI Systems
George, K.; Verhaegen, M.; Scherpen, J.M.A.
1999-01-01
Output tracking via the novel Stable Dynamic model Inversion (SDI) technique, applicable to non-minimum phase systems, and which naturally takes into account the presence of noise in target time histories, is considered here. We are motivated by the typical need to replicate time signals in the auto
Comparison of inverse dynamics calculated by two- and three-dimensional models during walking
DEFF Research Database (Denmark)
Alkjaer, T; Simonsen, E B; Dyhre-Poulsen, P
2001-01-01
The purpose of the study was to compare joint moments calculated by a two- (2D) and a three-dimensional (3D) inverse dynamics model to examine how the different approaches influenced the joint moment profiles. Fifteen healthy male subjects participated in the study. A five-camera video system rec...
Bayesian Uncertainty Quantification for Subsurface Inversion Using a Multiscale Hierarchical Model
Mondal, Anirban
2014-07-03
We consider a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a random field (spatial or temporal). The Bayesian approach contains a natural mechanism for regularization in the form of prior information, can incorporate information from heterogeneous sources and provide a quantitative assessment of uncertainty in the inverse solution. The Bayesian setting casts the inverse solution as a posterior probability distribution over the model parameters. The Karhunen-Loeve expansion is used for dimension reduction of the random field. Furthermore, we use a hierarchical Bayes model to inject multiscale data in the modeling framework. In this Bayesian framework, we show that this inverse problem is well-posed by proving that the posterior measure is Lipschitz continuous with respect to the data in total variation norm. Computational challenges in this construction arise from the need for repeated evaluations of the forward model (e.g., in the context of MCMC) and are compounded by high dimensionality of the posterior. We develop two-stage reversible jump MCMC that has the ability to screen the bad proposals in the first inexpensive stage. Numerical results are presented by analyzing simulated as well as real data from hydrocarbon reservoir. This article has supplementary material available online. © 2014 American Statistical Association and the American Society for Quality.
A covariance-adaptive approach for regularized inversion in linear models
Kotsakis, Christopher
2007-11-01
The optimal inversion of a linear model under the presence of additive random noise in the input data is a typical problem in many geodetic and geophysical applications. Various methods have been developed and applied for the solution of this problem, ranging from the classic principle of least-squares (LS) estimation to other more complex inversion techniques such as the Tikhonov-Philips regularization, truncated singular value decomposition, generalized ridge regression, numerical iterative methods (Landweber, conjugate gradient) and others. In this paper, a new type of optimal parameter estimator for the inversion of a linear model is presented. The proposed methodology is based on a linear transformation of the classic LS estimator and it satisfies two basic criteria. First, it provides a solution for the model parameters that is optimally fitted (in an average quadratic sense) to the classic LS parameter solution. Second, it complies with an external user-dependent constraint that specifies a priori the error covariance (CV) matrix of the estimated model parameters. The formulation of this constrained estimator offers a unified framework for the description of many regularization techniques that are systematically used in geodetic inverse problems, particularly for those methods that correspond to an eigenvalue filtering of the ill-conditioned normal matrix in the underlying linear model. Our study lies on the fact that it adds an alternative perspective on the statistical properties and the regularization mechanism of many inversion techniques commonly used in geodesy and geophysics, by interpreting them as a family of `CV-adaptive' parameter estimators that obey a common optimal criterion and differ only on the pre-selected form of their error CV matrix under a fixed model design.
Inverse problem theory methods for data fitting and model parameter estimation
Tarantola, A
2002-01-01
Inverse Problem Theory is written for physicists, geophysicists and all scientists facing the problem of quantitative interpretation of experimental data. Although it contains a lot of mathematics, it is not intended as a mathematical book, but rather tries to explain how a method of acquisition of information can be applied to the actual world.The book provides a comprehensive, up-to-date description of the methods to be used for fitting experimental data, or to estimate model parameters, and to unify these methods into the Inverse Problem Theory. The first part of the book deals wi
Zhu, Lin; Gong, Huili; Gable, Carl; Teatini, Pietro
2015-01-01
Understanding the heterogeneity arising from the complex architecture of sedimentary sequences in alluvial fans is challenging. This paper develops a statistical inverse framework in a multi-zone transition probability approach for characterizing the heterogeneity in alluvial fans. An analytical solution of the transition probability matrix is used to define the statistical relationships among different hydrofacies and their mean lengths, integral scales, and volumetric proportions. A statistical inversion is conducted to identify the multi-zone transition probability models and estimate the optimal statistical parameters using the modified Gauss-Newton-Levenberg-Marquardt method. The Jacobian matrix is computed by the sensitivity equation method, which results in an accurate inverse solution with quantification of parameter uncertainty. We use the Chaobai River alluvial fan in the Beijing Plain, China, as an example for elucidating the methodology of alluvial fan characterization. The alluvial fan is divided...
New strategy of modeling inversion layer characteristics in MOS structure for ULSI applications
Institute of Scientific and Technical Information of China (English)
马玉涛; 李志坚; 刘理天
2001-01-01
With the development of ULSI silicon technology, metal oxide semiconductor field effect transistor (MOSFET) devices are scaling down to nanometer regime. Energy of carriers in inversion layer in MOS structure is quantized and consequently, the physics and then the transport characteristics of inversion layer carriers are different from those in semi-classical theory. One essential matter is that the widely used concept of conduction band (valence band as well) effective density-of-states is no longer valid in quantized inversion layer. In this paper, an alternative concept, called surface layer effective density-of-states, is used to model the characteristics of MOS structure including threshold voltage, carrier sheet density, surface potential as well as capacitance.
Tadmor, Arbel
2009-03-01
In this work a biophysical model of Escherichia coli is presented that predicts growth rate and an effective cellular composition from an effective, coarse-grained representation of its genome. We assume that E. coli is in a state of balanced exponential steady-state growth, growing in a temporally and spatially constant environment, rich in resources. We apply this model to a series of past measurements, where the growth rate and rRNA-to-protein ratio have been measured for seven E. coli strains with an rRNA operon copy number ranging from one to seven (the wild-type copy number). These experiments show that growth rate markedly decreases for strains with fewer than six copies. Using the model, we were able to reproduce these measurements. We show that the model that best fits these data suggests that the volume fraction of macromolecules inside E. coli is not fixed when the rRNA operon copy number is varied. Moreover, the model predicts that increasing the copy number beyond seven results in a cytoplasm densely packed with ribosomes and proteins. Assuming that under such overcrowded conditions prolonged diffusion times tend to weaken binding affinities, the model predicts that growth rate will not increase substantially beyond the wild-type growth rate, as indicated by other experiments. Our model therefore suggests that changing the rRNA operon copy number of wild-type E. coli cells growing in a constant rich environment does not substantially increase their growth rate. Other observations regarding strains with an altered rRNA operon copy number, such as nucleoid compaction and the rRNA operon feedback response, appear to be qualitatively consistent with this model. In addition, we discuss possible design principles suggested by the model and propose further experiments to test its validity.
Dettmer, Jan; Dosso, Stan E
2012-10-01
This paper develops a trans-dimensional approach to matched-field geoacoustic inversion, including interacting Markov chains to improve efficiency and an autoregressive model to account for correlated errors. The trans-dimensional approach and hierarchical seabed model allows inversion without assuming any particular parametrization by relaxing model specification to a range of plausible seabed models (e.g., in this case, the number of sediment layers is an unknown parameter). Data errors are addressed by sampling statistical error-distribution parameters, including correlated errors (covariance), by applying a hierarchical autoregressive error model. The well-known difficulty of low acceptance rates for trans-dimensional jumps is addressed with interacting Markov chains, resulting in a substantial increase in efficiency. The trans-dimensional seabed model and the hierarchical error model relax the degree of prior assumptions required in the inversion, resulting in substantially improved (more realistic) uncertainty estimates and a more automated algorithm. In particular, the approach gives seabed parameter uncertainty estimates that account for uncertainty due to prior model choice (layering and data error statistics). The approach is applied to data measured on a vertical array in the Mediterranean Sea.
Manning, A. J.; O'Doherty, S.; Jones, A. R.; Simmonds, P. G.; Derwent, R. G.
2011-01-01
Methane (CH4) and nitrous oxide (N2O) have strong radiative properties in the Earth's atmosphere and both are regulated through the United Nations Framework Convention on Climate Change. Through this convention the United Kingdom is obliged to report an inventory of annual emission estimates from 1990. This paper describes a methodology that estimates emissions of CH4 and N2O completely independent of the inventory values. Emissions have been estimated for each year 1990-2007 for the United Kingdom and for NW Europe. The methodology combines high-frequency observations from Mace Head, a monitoring site on the west coast of Ireland, with an atmospheric dispersion model and an inversion system. The sensitivities of the inversion method to the modeling assumptions are reported. The 20 year Northern Hemisphere midlatitude baseline mixing ratios, growth rates, and seasonal cycles of both gases are also presented. The results indicate reasonable agreement between the inventory and inversion results for the United Kingdom for N2O over the entire period. For CH4 the agreement is poor in the 1990s but good in the 2000s. The UK CH4 inventory reported reduction from 1990-1992 to 2005-2007 (over 50%) is dominated by changes to landfill and coal mine emissions and is more than double the corresponding drop in the inversion estimated emissions (24%). The inversion results suggest that the United Kingdom has met its Kyoto commitment (-12.5%) but by a smaller margin (-14.3%) than reported (-17.3%). The results for NW Europe with the United Kingdom removed show reasonable agreement in trend, on average the inversion results for N2O are 25% lower and for CH4 21% higher.
Approaches to highly parameterized inversion-A guide to using PEST for groundwater-model calibration
Doherty, John E.; Hunt, Randall J.
2010-01-01
Highly parameterized groundwater models can create calibration difficulties. Regularized inversion-the combined use of large numbers of parameters with mathematical approaches for stable parameter estimation-is becoming a common approach to address these difficulties and enhance the transfer of information contained in field measurements to parameters used to model that system. Though commonly used in other industries, regularized inversion is somewhat imperfectly understood in the groundwater field. There is concern that this unfamiliarity can lead to underuse, and misuse, of the methodology. This document is constructed to facilitate the appropriate use of regularized inversion for calibrating highly parameterized groundwater models. The presentation is directed at an intermediate- to advanced-level modeler, and it focuses on the PEST software suite-a frequently used tool for highly parameterized model calibration and one that is widely supported by commercial graphical user interfaces. A brief overview of the regularized inversion approach is provided, and techniques for mathematical regularization offered by PEST are outlined, including Tikhonov, subspace, and hybrid schemes. Guidelines for applying regularized inversion techniques are presented after a logical progression of steps for building suitable PEST input. The discussion starts with use of pilot points as a parameterization device and processing/grouping observations to form multicomponent objective functions. A description of potential parameter solution methodologies and resources available through the PEST software and its supporting utility programs follows. Directing the parameter-estimation process through PEST control variables is then discussed, including guidance for monitoring and optimizing the performance of PEST. Comprehensive listings of PEST control variables, and of the roles performed by PEST utility support programs, are presented in the appendixes.
Heng, Y.; Hoffmann, L.; Griessbach, S.; Rößler, T.; Stein, O.
2015-10-01
An inverse transport modeling approach based on the concepts of sequential importance resampling and parallel computing is presented to reconstruct altitude-resolved time series of volcanic emissions, which often can not be obtained directly with current measurement techniques. A new inverse modeling and simulation system, which implements the inversion approach with the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) is developed to provide reliable transport simulations of volcanic sulfur dioxide (SO2). In the inverse modeling system MPTRAC is used to perform two types of simulations, i. e., large-scale ensemble simulations for the reconstruction of volcanic emissions and final transport simulations. The transport simulations are based on wind fields of the ERA-Interim meteorological reanalysis of the European Centre for Medium Range Weather Forecasts. The reconstruction of altitude-dependent SO2 emission time series is also based on Atmospheric Infrared Sounder (AIRS) satellite observations. A case study for the eruption of the Nabro volcano, Eritrea, in June 2011, with complex emission patterns, is considered for method validation. Meteosat Visible and InfraRed Imager (MVIRI) near-real-time imagery data are used to validate the temporal development of the reconstructed emissions. Furthermore, the altitude distributions of the emission time series are compared with top and bottom altitude measurements of aerosol layers obtained by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite instruments. The final transport simulations provide detailed spatial and temporal information on the SO2 distributions of the Nabro eruption. The SO2 column densities from the simulations are in good qualitative agreement with the AIRS observations. Our new inverse modeling and simulation system is expected to become a useful tool to also study other volcanic
Directory of Open Access Journals (Sweden)
Y. Heng
2015-10-01
Full Text Available An inverse transport modeling approach based on the concepts of sequential importance resampling and parallel computing is presented to reconstruct altitude-resolved time series of volcanic emissions, which often can not be obtained directly with current measurement techniques. A new inverse modeling and simulation system, which implements the inversion approach with the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC is developed to provide reliable transport simulations of volcanic sulfur dioxide (SO2. In the inverse modeling system MPTRAC is used to perform two types of simulations, i. e., large-scale ensemble simulations for the reconstruction of volcanic emissions and final transport simulations. The transport simulations are based on wind fields of the ERA-Interim meteorological reanalysis of the European Centre for Medium Range Weather Forecasts. The reconstruction of altitude-dependent SO2 emission time series is also based on Atmospheric Infrared Sounder (AIRS satellite observations. A case study for the eruption of the Nabro volcano, Eritrea, in June 2011, with complex emission patterns, is considered for method validation. Meteosat Visible and InfraRed Imager (MVIRI near-real-time imagery data are used to validate the temporal development of the reconstructed emissions. Furthermore, the altitude distributions of the emission time series are compared with top and bottom altitude measurements of aerosol layers obtained by the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS satellite instruments. The final transport simulations provide detailed spatial and temporal information on the SO2 distributions of the Nabro eruption. The SO2 column densities from the simulations are in good qualitative agreement with the AIRS observations. Our new inverse modeling and simulation system is expected to become a useful tool to also study
Martelli, Fabrizio; Del Bianco, Samuele; Zaccanti, Giovanni
2011-02-01
We propose the use of a retrieval operator for biomedical applications in near-infrared spectroscopy. The proposed retrieval operator is based on the "Optimal Estimation" method. The main characteristic of this method relates to the possibility to include prior information both on target and on forward model parameters of the inversion procedure. The possibility of the retrieval operator to elaborate a-priori information can in principle be a benefit for the whole retrieval procedure. This means that a larger number of target parameters can be retrieved, or that a better accuracy can be achieved in retrieving the target parameters. The final goal of this inversion procedure is to have an improved estimate of the target parameters. The procedure has been tested on time-resolved simulated experiments obtained with a Monte Carlo code. The results obtained show that an improved performance of the inversion procedure is achieved when prior information on target and forward model parameters is available. With the use of a priori information on target parameters we have in average a lower difference between the retrieved values of the parameters and their true values, and the error bars determined by the inversion procedure on the retrieved parameters are significantly lower. At the same time a good estimate of the errors on the forward model parameters can significantly improve the retrieval of the target parameters.
Pseudo waveform inversion and model driven AVO(Amplitude Versus with Offset) analysis
Energy Technology Data Exchange (ETDEWEB)
Shin, Chang Soo; Park, Keun Pil [Korea Inst. of Geology Mining and Materials, Taejon (Korea, Republic of); Suh, Jung Hee; Hyun, Byung Koo; Shin, Sung Ryul [Seoul National University, Seoul (Korea, Republic of)
1995-12-01
The seismic reflection exploration technique which is one of the geophysical methods for oil exploration became effectively to image the subsurface structure with rapid development of computer. However, the imagining of subsurface based on the conventional data processing is almost impossible to obtain the information on physical properties of the subsurface such as velocity and density. Since seismic data are implicitly function of velocities of subsurface, it is necessary to develop the inversion method that can delineate the velocity structure using seismic topography and waveform inversion. As a tool to perform seismic inversion, seismic forward modeling program using ray tracing should be developed. This report consists of two articles. (1) Pseudo waveform inversion: In this study, we have developed the algorithm that calculate the travel time of the complex geologic structure using shooting ray tracing by subdividing the geologic model into blocky structure having the constant velocity. With the travel time calculation, the partial derivatives of travel time can be calculated efficiently without difficulties. (2) Hessian matrices and multiples: In this article we review the three possible approaches (gradient, Gauss-Newton and full Newton methods). By specifying from the outset implicit, frequency domain, modeling using finite difference or finite element methods, we are able to introduce a new discrete, matrix formalism that considerably simplifies the analysis. (author). 57 refs., 44 figs., 2 tabs.
Estimating leaf area index by inversion of reflectance model for semiarid natural grasslands
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
The study developed an integrated reflectance model combining radiative transfer and geometric optical properties in order to inverse leaf area index(LAI) of semiarid natural grasslands.In order to better link remote sensing information with land plants,and facilitate regional and global climate change studies,the model introduced a simple but important geometrical similarity parameter related to plant crown shapes.The model revealed the influences of different plant crown shapes(such as spherical,cylindrical/cuboidal and conic crowns) on leaf/branch angle distribution frequencies,shadow ground coverage,shadowed or sunlit background fractions,canopy reflectance,and scene reflectance.The modeled reflectance data agreed with the measured ones in the three Leymus chinensis steppes with different degradation degrees,which validated the reflectance model.The lower the degradation degree was,the better the modeled data agreed with the measured data.After this reflectance model was coupled with the optimization inversion method,LAI over the entire study region was estimated once every eight days using the eight-day products of surface reflectance obtained by multi-spectral Moderate-Resolution Imaging Spectroradiometer(MODIS) during the growing seasons in 2002.The temporal and spatial patterns of inversed LAI for the steppes with different cover degrees,swamps,flood plains,and croplands agreed with the general laws and measurements very well.But for unused land cover types(sands,saline,and barren lands) and forestlands,totally accounting for about 10% of the study region,the reasonable LAI values were not derived by inversing,requiring further revising of the model or the development of a new model for them.
Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling
Henne, Stephan; Brunner, Dominik; Oney, Brian; Leuenberger, Markus; Eugster, Werner; Bamberger, Ines; Meinhardt, Frank; Steinbacher, Martin; Emmenegger, Lukas
2016-03-01
Atmospheric inverse modelling has the potential to provide observation-based estimates of greenhouse gas emissions at the country scale, thereby allowing for an independent validation of national emission inventories. Here, we present a regional-scale inverse modelling study to quantify the emissions of methane (CH4) from Switzerland, making use of the newly established CarboCount-CH measurement network and a high-resolution Lagrangian transport model. In our reference inversion, prior emissions were taken from the "bottom-up" Swiss Greenhouse Gas Inventory (SGHGI) as published by the Swiss Federal Office for the Environment in 2014 for the year 2012. Overall we estimate national CH4 emissions to be 196 ± 18 Gg yr-1 for the year 2013 (1σ uncertainty). This result is in close agreement with the recently revised SGHGI estimate of 206 ± 33 Gg yr-1 as reported in 2015 for the year 2012. Results from sensitivity inversions using alternative prior emissions, uncertainty covariance settings, large-scale background mole fractions, two different inverse algorithms (Bayesian and extended Kalman filter), and two different transport models confirm the robustness and independent character of our estimate. According to the latest SGHGI estimate the main CH4 source categories in Switzerland are agriculture (78 %), waste handling (15 %) and natural gas distribution and combustion (6 %). The spatial distribution and seasonal variability of our posterior emissions suggest an overestimation of agricultural CH4 emissions by 10 to 20 % in the most recent SGHGI, which is likely due to an overestimation of emissions from manure handling. Urban areas do not appear as emission hotspots in our posterior results, suggesting that leakages from natural gas distribution are only a minor source of CH4 in Switzerland. This is consistent with rather low emissions of 8.4 Gg yr-1 reported by the SGHGI but inconsistent with the much higher value of 32 Gg yr-1 implied by the EDGARv4.2 inventory for
Directory of Open Access Journals (Sweden)
Alalade Muyiwa E.
2016-01-01
Full Text Available In order to assess the probability of foundation failure resulting from cyclic action on structures and to minimize the prediction error, various existing constitutive models considering cyclic loaded dry soils were extended to unsaturated soil conditions by the authors, thus requiring further calibration during application on existing slightly variable soil condition as well as the soil heterogeneities. The efficiency and effectiveness of these models is majorly influenced by the cyclic constitutive parameters and the soil suction. Little or no details exist in literature about the model based identification and the calibration of the constitutive parameters under cyclic loaded soils. This could be attributed to the difficulties and complexities of the inverse modeling of such complex phenomena. A wide variety of optimization strategies for the solution of the sum of least-squares problems as usually done in the field of model calibration exists, however the inverse analysis of the unsaturated soil response under oscillatory load functions has not been solved up to now. This paper gives insight into the model calibration challenges and also puts forward advanced optimization methods for the inverse modeling of cyclic loaded foundation response on unsaturated soils.
Park, Kiwan
2015-01-01
The inverse cascade of magnetic energy occurs when helicity or rotational instability exists in the magnetohydrodynamic (MHD) system. This well known phenomenon provides a basis for the large scale magnetic field in space. However even the decaying nonhelical magnetic energy can evolve to expand its scale. This phenomenon, inverse transfer of decaying nonhelical magnetic field may hold some vital clues to the origin of large scale magnetic field in the astrophysical system without helicity nor any significant driving source. Zeldovich's rope model has been considered as the basic principle with regard to the amplification of magnetic field. However, since the rope model assuming a driving force is not appropriate to the decaying system, we suggest a supplementary dynamo model based on the magnetic induction equation. The model explicitly shows the basic principle of migration and amplification of magnetic field. The expansion of scale and intensity of magnetic field is basically the consequent result of the r...
Chatterjee, Shre Kumar; Das, Saptarshi; Manzella, Veronica; Vitaletti, Andrea; Masi, Elisa; Santopolo, Luisa; Mancuso, Stefano; Maharatna, Koushik
2014-01-01
In this paper, system identification approach has been adopted to develop a novel dynamical model for describing the relationship between light as an environmental stimulus and the electrical response as the measured output for a bay leaf (Laurus nobilis) plant. More specifically, the target is to predict the characteristics of the input light stimulus (in terms of on-off timing, duration and intensity) from the measured electrical response - leading to an inverse problem. We explored two major classes of system estimators to develop dynamical models - linear and nonlinear - and their several variants for establishing a forward and also an inverse relationship between the light stimulus and plant electrical response. The best class of models are given by the Nonlinear Hammerstein-Wiener (NLHW) estimator showing good data fitting results over other linear and nonlinear estimators in a statistical sense. Consequently, a few set of models using different functional variants of NLHW has been developed and their a...
On (no) inverse magnetic catalysis in the QCD hard and soft wall models
Dudal, D; Mertens, T G
2015-01-01
In this paper, we study the influence of an external magnetic field in holographic QCD models where the backreaction is modeled in via an appropriate choice of the background metric. We add a phenomenological soft wall dilaton to incorporate better IR behavior (confinement). Elaborating on previous studies conducted by [JHEP 1505 (2015) 121], we first discuss the Hawking-Page transition, the dual of the deconfinement transition, as a function of the magnetic field. We confirm that the critical deconfinement temperature can drop with the magnetic field. Secondly, we study the quark condensate holographically as a function of the applied magnetic field and demonstrate that this model does not exhibit inverse magnetic catalysis at the level of the chiral transition. The quest for a holographic QCD model that qualitatively describes the inverse magnetic catalysis at finite temperature is thus still open. Throughout this work, we pay special attention to the different holographic parameters and we attempt to fix t...
Ash plume properties retrieved from infrared images: a forward and inverse modeling approach
Cerminara, Matteo; Valade, Sébastien; Harris, Andrew J L
2014-01-01
We present a coupled fluid-dynamic and electromagnetic model for volcanic ash plumes. In a forward approach, the model is able to simulate the plume dynamics from prescribed input flow conditions and generate the corresponding synthetic thermal infrared (TIR) image, allowing a comparison with field-based observations. An inversion procedure is then developed to retrieve ash plume properties from TIR images. The adopted fluid-dynamic model is based on a one-dimensional, stationary description of a self-similar (top-hat) turbulent plume, for which an asymptotic analytical solution is obtained. The electromagnetic emission/absorption model is based on the Schwarzschild's equation and on Mie's theory for disperse particles, assuming that particles are coarser than the radiation wavelength and neglecting scattering. [...] Application of the inversion procedure to an ash plume at Santiaguito volcano (Guatemala) has allowed us to retrieve the main plume input parameters, namely the initial radius $b_0$, velocity $U_...
Hinsen, Konrad; Vaitinadapoule, Aurore; Ostuni, Mariano A; Etchebest, Catherine; Lacapere, Jean-Jacques
2015-02-01
The 18 kDa protein TSPO is a highly conserved transmembrane protein found in bacteria, yeast, animals and plants. TSPO is involved in a wide range of physiological functions, among which the transport of several molecules. The atomic structure of monomeric ligand-bound mouse TSPO in detergent has been published recently. A previously published low-resolution structure of Rhodobacter sphaeroides TSPO, obtained from tubular crystals with lipids and observed in cryo-electron microscopy, revealed an oligomeric structure without any ligand. We analyze this electron microscopy density in view of available biochemical and biophysical data, building a matching atomic model for the monomer and then the entire crystal. We compare its intra- and inter-molecular contacts with those predicted by amino acid covariation in TSPO proteins from evolutionary sequence analysis. The arrangement of the five transmembrane helices in a monomer of our model is different from that observed for the mouse TSPO. We analyze possible ligand binding sites for protoporphyrin, for the high-affinity ligand PK 11195, and for cholesterol in TSPO monomers and/or oligomers, and we discuss possible functional implications.
Higgs Boson Mass and Complex Snuetrino Dark Matter in the Supersymmetric Inverse Seesaw Models
Guo, Jun; Li, Tianjun; Liu, Yandong
2014-01-01
The discovery of a relatively heavy Standard Model (SM) -like Higgs boson challenges naturalness of the minimal supersymmetric standard model (MSSM) from both Higgs and dark matter (DM) sectors. We study these two aspects in the MSSM extended by the low-scale inverse seesaw mechanism. Firstly, it admits a sizable radiative correction on the Higgs boson mass m_h, up to \\sim 4 GeV in the case of an IR-fixed point of the coupling Y_\
Tsai, M.; Lee, C.; Yu, H.
2013-12-01
In the last 20 years, the Yunlin offshore industrial park has significantly contributed to the economic development of Taiwan. Its annual production value has reached almost 12 % of Taiwan's GDP in 2012. The offshore industrial park also balanced development of urban and rural in areas. However, the offshore industrial park is considered the major source of air pollution to nearby counties, especially, the emission of Volatile Organic Compounds(VOCs). Studies have found that exposures to high level of some VOCs have caused adverse health effects on both human and ecosystem. Since both health and ecological effects of air pollution have been the subject of numerous studies in recent years, it is a critical issue in estimating VOCs emissions. Nowadays emission estimation techniques are usually used emissions factors in calculation. Because the methodology considered totality of equipment activities based on statistical assumptions, it would encounter great uncertainty between these coefficients. This study attempts to estimate VOCs emission of the Yunlin Offshore Industrial Park using an inverse atmospheric dispersion model. The inverse modeling approach will be applied to the combination of dispersion modeling result which input a given one-unit concentration and observations at air quality stations in Yunlin. The American Meteorological Society-Environmental Protection Agency Regulatory Model (AERMOD) is chosen as the tool for dispersion modeling in the study. Observed concentrations of VOCs are collected by the Taiwanese Environmental Protection Administration (TW EPA). In addition, the study also analyzes meteorological data including wind speed, wind direction, pressure and temperature etc. VOCs emission estimations from the inverse atmospheric dispersion model will be compared to the official statistics released by Yunlin Offshore Industrial Park. Comparison of estimated concentration from inverse dispersion modeling and official statistical concentrations will
Modelling Inverse Gaussian Data with Censored Response Values: EM versus MCMC
Directory of Open Access Journals (Sweden)
R. S. Sparks
2011-01-01
Full Text Available Low detection limits are common in measure environmental variables. Building models using data containing low or high detection limits without adjusting for the censoring produces biased models. This paper offers approaches to estimate an inverse Gaussian distribution when some of the data used are censored because of low or high detection limits. Adjustments for the censoring can be made if there is between 2% and 20% censoring using either the EM algorithm or MCMC. This paper compares these approaches.
A musculoskeletal shoulder model based on pseudo-inverse and null-space optimization
Terrier, Alexandre; Aeberhard, Martin; Michellod, Yvan; Müllhaupt, Philippe; Gillet, Denis; Farron, Alain; Pioletti, Dominique P.
2010-01-01
The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulohumeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head a...
DERIVED DEMAND ELASTICITIES: MARKETING MARGIN METHODS VERSUS AN INVERSE DEMAND MODEL FOR CHOICE BEEF
Marsh, John M.
1991-01-01
Three methods of calculating the derived elasticity of demand for Choice slaughter beef are used: (a) a traditional marketing margin approach, (b) a modified marketing margin approach, and (c) an econometric, inverse demand model approach. The first method is more restrictive than the second but both tend to overestimate beef price flexibility and revenue changes. The econometric model, though an incomplete demand system, yields demand elasticities that are more consistent with marketing flex...
Three-dimensional modeling of Mount Vesuvius with sequential integrated inversion
Tondi, Rosaria; de Franco, Roberto
2003-05-01
A new image of Mount Vesuvius and the surrounding area is recovered from the tomographic inversion of 693 first P wave arrivals recorded by 314 receivers deployed along five profiles which intersect the crater, and gravity data collected in 17,598 stations on land and offshore. The final three-dimensional (3-D) velocity model presented here is determined by interpolation of five 2-D velocity sections obtained from sequential integrated inversion (SII) of seismic and gravity data. The inversion procedure adopts the "maximum likelihood" scheme in order to jointly optimize seismic velocities and densities. In this way we recover velocity and density models both consistent with seismic and gravity data information. The model parameterization of these 2-D models is chosen in order to keep the diagonal elements of the seismic resolution matrix in the order of 0.2-0.8. The highest values of resolution are detected under the volcano edifice. The imaged 6-km-thick crustal volume underlies a 25 × 45 km2 area. The interpolation is performed by choosing the right grid for a smoothing algorithm which prepares optimum models for asymptotic ray theory methods. Hence this model can be used as a reference model for a 3-D tomographic inversion of seismic data. The 3-D gravity modeling is straightforward. The results of this study clearly image the continuous structure of the Mesozoic carbonate basement top and the connection of the volcano conduit structure to two shallow depressions, which in terms of hazard prevention are the regions through which magma may more easily flow toward the surface and cause possible eruptions.
Nicolini, Claudio
1986-01-01
Since the early times of the Greek philosophers Leucippus and Democritus, and later of the Roman philosopher Lucretius, a simple, fundamental idea emerged that brought the life sciences into the realm of the physical sciences. Atoms, after various interactions, were assumed to acquire stable configurations that corresponded either to the living or to the inanimate world. This simple and unitary theory, which has evolved in successive steps to our present time, remarkably maintained its validity despite several centuries of alternative vicissitudes, and is the foundation of modern biophysics. Some of the recent developments of this ancient idea are the discovery of the direct relationship between spatial structures and chemical activity of such molecules as methane and benzene, and the later discovery of the three-dimensional structure of double-helical DNA, and of its relationship with biological activity. The relationship between the structure of various macromolecules and the function of living cells was on...
American Option Pricing using GARCH models and the Normal Inverse Gaussian distribution
DEFF Research Database (Denmark)
Stentoft, Lars Peter
In this paper we propose a feasible way to price American options in a model with time varying volatility and conditional skewness and leptokurtosis using GARCH processes and the Normal Inverse Gaussian distribution. We show how the risk neutral dynamics can be obtained in this model, we interpret...... the effect of the riskneutralization, and we derive approximation procedures which allow for a computationally efficient implementation of the model. When the model is estimated on financial returns data the results indicate that compared to the Gaussian case the extension is important. A study of the model...
Analogue modelling and mechanism of tectonic inversion of the Xihu Sag, East China Sea Shelf Basin
Wang, Qian; Li, Sanzhong; Guo, Lingli; Suo, Yanhui; Dai, Liming
2017-05-01
The East China Sea Shelf Basin lies between the Pacific Subduction and Indian-Eurasian Collision tectonic domains and records Cenozoic tectonic inversion, especially in the Xihu Sag. To improve the understanding of the evolution and mechanism of tectonic inversion, this paper employs analogue modelling to reproduce the evolutionary process. Combined with the structural analysis of seismic profile, this paper determines the pattern of basement-involved faults. Simulation results show that under the transtension, two subsidence centers developed and a number of normal faults assembled in two flower structures. When the stress field turned into transpression, the geometry and deformation of inversion basin inherited the previous transtensional basin and pre-existing faults, respectively. The geometry and fault patterns in models are well consistent with those observed in the Xihu Sag, which indicates the plausibility of similar deformation controls. The formation of the tectonic inversion is related to the variation in stress field caused by the changes in the rates and directions of the subduction of the Pacific Plate and the collision of the Indian Plate with Eurasian Plate.
Efficient non-negative constrained model-based inversion in optoacoustic tomography
Ding, Lu; Luís Deán-Ben, X.; Lutzweiler, Christian; Razansky, Daniel; Ntziachristos, Vasilis
2015-09-01
The inversion accuracy in optoacoustic tomography depends on a number of parameters, including the number of detectors employed, discrete sampling issues or imperfectness of the forward model. These parameters result in ambiguities on the reconstructed image. A common ambiguity is the appearance of negative values, which have no physical meaning since optical absorption can only be higher or equal than zero. We investigate herein algorithms that impose non-negative constraints in model-based optoacoustic inversion. Several state-of-the-art non-negative constrained algorithms are analyzed. Furthermore, an algorithm based on the conjugate gradient method is introduced in this work. We are particularly interested in investigating whether positive restrictions lead to accurate solutions or drive the appearance of errors and artifacts. It is shown that the computational performance of non-negative constrained inversion is higher for the introduced algorithm than for the other algorithms, while yielding equivalent results. The experimental performance of this inversion procedure is then tested in phantoms and small animals, showing an improvement in image quality and quantitativeness with respect to the unconstrained approach. The study performed validates the use of non-negative constraints for improving image accuracy compared to unconstrained methods, while maintaining computational efficiency.
Directory of Open Access Journals (Sweden)
Warsa
2014-07-01
Full Text Available Groundwater is an important economic source of water supply for drinking water and irrigation water for agriculture. Surface nuclear magnetic resonance (SNMR sounding is a relatively new geophysical method that can be used to determine the presence of culturally and economically important substances, such as subsurface water or hydrocarbon distribution. SNMR sounding allows the determination of water content and pore size distribution directly from the surface. The SNMR method is performed by stimulating an alternating current pulse through an antenna at the surface in order to confirm the existence of water in the subsurface. This paper reports the development of a 3-D forward modeling code for SNMR amplitudes and decay times, after which an improved 2-D and 3-D inversion algorithm is investigated, consisting of schemes for regularizing model parameterization. After briefly reviewing inversion schemes generally used in geophysics, the special properties of SNMR or magnetic resonance sounding (MRS inversion are evaluated. We present an extension of MRS to magnetic resonance tomography (MRT, i.e. an extension for 2-D and 3-D investigation, and the appropriate inversions.
Three dimensional modeling and inversion of Borehole-surface Electrical Resistivity Data
Zhang, Y.; Liu, D.; Liu, Y.; Qin, M.
2013-12-01
After a long time of exploration, many oil fields have stepped into the high water-cut period. It is sorely needed to determining the oil-water distribution and water flooding front. Borehole-surface electrical resistivity tomography (BSERT) system is a low-cost measurement with wide measuring scope and small influence on the reservoir. So it is gaining more and more application in detecting water flooding areas and evaluating residual oil distribution in oil fields. In BSERT system, current is connected with the steel casing of the observation well. The current flows along the long casing and transmits to the surface through inhomogeneous layers. Then received electric potential difference data on the surface can be used to inverse the deep subsurface resistivity distribution. This study presents the 3D modeling and inversion method of electrical resistivity data. In an extensive literature, the steel casing is treated as a transmission line current source with infinite small radius and constant current density. However, in practical multi-layered formations with different resistivity, the current density along the casing is not constant. In this study, the steel casing is modeled by a 2.5e-7 ohm-m physical volume that the casing occupies in the finite element mesh. Radius of the casing can be set to a little bigger than the true radius, and this helps reduce the element number and computation time. The current supply point is set on the center of the top surface of the physical volume. The homogeneous formation modeling result shows the same precision as the transmission line current source model. The multi-layered formation modeling result shows that the current density along the casing is high in the low-resistivity layer, and low in the high-resistivity layer. These results are more reasonable. Moreover, the deviated and horizontal well can be simulated as simple as the vertical well using this modeling method. Based on this forward modeling method, the
Full-model wavenumber inversion: An emphasis on the appropriate wavenumber continuation
Alkhalifah, Tariq Ali
2016-04-06
A model of the earth can be described using a Fourier basis represented by its wavenumber content. In full-waveform inversion (FWI), the wavenumber description of the model is natural because our Born-approximation-based velocity updates are made up of wavefields. Our objective in FWI is to access all the model wavenumbers available in our limited aperture and bandwidth recorded data that are not yet accurately present in the initial velocity model. To invert for those model wavenumbers, we need to locate their imprint in the data. Thus, I review the relation between the model wavenumber buildup and the inversion process. Specifically, I emphasize a focus on the model wavenumber components and identified their individual influence on the data. Missing the energy for a single vertical low-model wavenumber from the residual between the true Marmousi model and some initial linearly increasing velocity model produced a worse least-squares fit to the data than the initial model itself, in which all the residual model wavenumbers were missing. This stern realization validated the importance of wavenumber continuation, specifically starting from the low-model wavenumbers, to higher (resolution) wavenumbers, especially those attained in an order dictated by the scattering angle filter. A numerical Marmousi example determined the important role that the scattering angle filter played in managing the wavenumber continuation from low to high. An application on the SEG2014 blind test data set with frequencies lower than 7 Hz muted out further validated the versatility of the scattering angle filtering.
NUMERICAL MODELING FOR POSITIVE AND INVERSE PROBLEMS OF 3-D SEEPAGE IN DOUBLE FRACTURED MEDIA
Institute of Scientific and Technical Information of China (English)
ZHOU Zhi-fang; GUO Geng-xin
2005-01-01
Three-dimensional seepage in double fractured media was modeled in this paper.The determination of hydraulic conductivity tensor of rock mass is a vital problem for the sea water intrusion or sea water encroachment and seepage of fissured medium.According to the geological and hydrogeological conditions for the 2nd-stage construction of the Three Gorges Project (TGP), the physical and mathematical models for the groundwater movement through the 3D double fractured media of rock mass during construction were established in this paper.Based on discontinuity-control inverse theory, some related parameters of double fractured media were inversed with flux being the known quantity and calibration of water table the objective function.Synchronously, the seepage field of the construction region was systematically analyzed and simulated, the results of which exhibit that the double fractured media model of fracture water can comprehensively and correctly describe the geological and hydrogeological conditions in the construction region.
Inverse hydrograph routing optimization model based on the kinematic wave approach
Saghafian, B.; Jannaty, M. H.; Ezami, N.
2015-08-01
This article presents and validates the inverse flood hydrograph routing optimization model under kinematic wave (KW) approximation in order to produce the upstream (inflow) hydrograph, given the downstream (outflow) hydrograph of a river reach. The cost function involves minimization of the error between the observed outflow hydrograph and the corresponding directly routed outflow hydrograph. Decision variables are the inflow hydrograph ordinates. The KW and genetic algorithm (GA) are coupled, representing the selected methods of direct routing and optimization, respectively. A local search technique is also enforced to achieve better agreement of the routed outflow hydrograph with the observed hydrograph. Computer programs handling the direct flood routing, cost function and local search are linked with the optimization model. The results show that the case study inflow hydrographs obtained by the GA were reconstructed with accuracy. It was also concluded that the coupled KW-GA model framework can perform inverse hydrograph routing with numerical stability.
A nonlinear model reference adaptive inverse control algorithm with pre-compensator
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
In this paper, the reduced-order modeling (ROM)technology and its corresponding linear theory are expanded from the linear dynamic system to the nonlinear one, and H∞ control theory is employed in the frequency domain to design some nonlinear system' s pre-compensator in some special way. The adaptive model inverse control (AMIC)theory coping with nonlinear system is improved as well. Such is the model reference adaptive inverse control with pre-compensator (PCMRAIC). The aim of that algorithm is to construct a strategy of control as a whole. As a practical example of the application, the numerical simulation has been given on matlab software packages. The numerical result is given. The proposed strategy realizes the linearization control of nonlinear dynamic system. And it carries out a good performance to deal with the nonlinear system.
Numerical modeling of axi-symmetrical cold forging process by ``Pseudo Inverse Approach''
Halouani, A.; Li, Y. M.; Abbes, B.; Guo, Y. Q.
2011-05-01
The incremental approach is widely used for the forging process modeling, it gives good strain and stress estimation, but it is time consuming. A fast Inverse Approach (IA) has been developed for the axi-symmetric cold forging modeling [1-2]. This approach exploits maximum the knowledge of the final part's shape and the assumptions of proportional loading and simplified tool actions make the IA simulation very fast. The IA is proved very useful for the tool design and optimization because of its rapidity and good strain estimation. However, the assumptions mentioned above cannot provide good stress estimation because of neglecting the loading history. A new approach called "Pseudo Inverse Approach" (PIA) was proposed by Batoz, Guo et al.. [3] for the sheet forming modeling, which keeps the IA's advantages but gives good stress estimation by taking into consideration the loading history. Our aim is to adapt the PIA for the cold forging modeling in this paper. The main developments in PIA are resumed as follows: A few intermediate configurations are generated for the given tools' positions to consider the deformation history; the strain increment is calculated by the inverse method between the previous and actual configurations. An incremental algorithm of the plastic integration is used in PIA instead of the total constitutive law used in the IA. An example is used to show the effectiveness and limitations of the PIA for the cold forging process modeling.
Particle Swarm Optimization (PSO) for Magnetotelluric (MT) 1D Inversion Modeling
Grandis, Hendra; Maulana, Yahya
2017-04-01
Particle Swarm Optimization (PSO) is one of nature-inspired optimization algorithms that adopts swarm (insects, school of fish, flock of birds etc.) behaviour in search for food or common target in a collaborative manner. The particles (or agents) in the swarm learn from their neighbours as well as themselves regarding the promising area in the search space. The information is then used to update their position in order to reach the target. The search algorithm of a particle is dictated by the best position of that particle during the process (individual learning term) and the best particle in its surroundings (social learning term) at a particular iteration. In terms of optimization, the particles are models defined by their parameters, while the promising area in the model space is characterized by a low misfit associated with optimum models. Being a global search approach, PSO is suitable for nonlinear inverse problem resolution. The algorithm was applied to a simple minimization problem for illustration purpose. The application of PSO in geophysical inverse problem is demonstrated by inversion of synthetic magnetotelluric (MT) data associated with simple 1D models with satisfactory results in terms of model recovery as well as data misfit.
Inverse Optimization: A New Perspective on the Black-Litterman Model.
Bertsimas, Dimitris; Gupta, Vishal; Paschalidis, Ioannis Ch
2012-12-11
The Black-Litterman (BL) model is a widely used asset allocation model in the financial industry. In this paper, we provide a new perspective. The key insight is to replace the statistical framework in the original approach with ideas from inverse optimization. This insight allows us to significantly expand the scope and applicability of the BL model. We provide a richer formulation that, unlike the original model, is flexible enough to incorporate investor information on volatility and market dynamics. Equally importantly, our approach allows us to move beyond the traditional mean-variance paradigm of the original model and construct "BL"-type estimators for more general notions of risk such as coherent risk measures. Computationally, we introduce and study two new "BL"-type estimators and their corresponding portfolios: a Mean Variance Inverse Optimization (MV-IO) portfolio and a Robust Mean Variance Inverse Optimization (RMV-IO) portfolio. These two approaches are motivated by ideas from arbitrage pricing theory and volatility uncertainty. Using numerical simulation and historical backtesting, we show that both methods often demonstrate a better risk-reward tradeoff than their BL counterparts and are more robust to incorrect investor views.
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Hugo Jacquin
2016-05-01
Full Text Available Inverse statistical approaches to determine protein structure and function from Multiple Sequence Alignments (MSA are emerging as powerful tools in computational biology. However the underlying assumptions of the relationship between the inferred effective Potts Hamiltonian and real protein structure and energetics remain untested so far. Here we use lattice protein model (LP to benchmark those inverse statistical approaches. We build MSA of highly stable sequences in target LP structures, and infer the effective pairwise Potts Hamiltonians from those MSA. We find that inferred Potts Hamiltonians reproduce many important aspects of 'true' LP structures and energetics. Careful analysis reveals that effective pairwise couplings in inferred Potts Hamiltonians depend not only on the energetics of the native structure but also on competing folds; in particular, the coupling values reflect both positive design (stabilization of native conformation and negative design (destabilization of competing folds. In addition to providing detailed structural information, the inferred Potts models used as protein Hamiltonian for design of new sequences are able to generate with high probability completely new sequences with the desired folds, which is not possible using independent-site models. Those are remarkable results as the effective LP Hamiltonians used to generate MSA are not simple pairwise models due to the competition between the folds. Our findings elucidate the reasons for the success of inverse approaches to the modelling of proteins from sequence data, and their limitations.
A Network Inversion Filter combining GNSS and InSAR for tectonic slip modeling
Bekaert, D. P.; Segall, P.; Wright, T. J.; Hooper, A. J.
2016-12-01
Time-dependent slip modeling can be a powerful tool to improve our understanding of the interaction of earthquake cycle processes such as interseismic, coseismic, postseismic, and aseismic slip. Interferometric Synthetic Aperture Radar (InSAR) observations allow us to model slip at depth with a higher spatial resolution than when using GNSS alone. Typically the temporal resolution of InSAR has been limited. However, the recent generation of SAR satellites including Sentinel-1, COSMO-SkyMED, and RADARSAT-2 permits the use of InSAR for time-dependent slip modeling, at intervals of a few days when combined. The increasing amount of SAR data makes a simultaneous data inversion of all epochs challenging. Here, we expanded the original Network Inversion Filter (Segall and Matthews, 1997) to include InSAR observations of surface displacements in addition to GNSS. In the NIF framework, geodetic observations are limited to those of a given epoch, where a physical model describes the slip evolution over time. The combination of the Kalman forward filtering and backward smoothing allows all geodetic observations to constrain the complete observation period. Combining GNSS and InSAR allows us to model time-dependent slip at an unprecedented spatial resolution. We validate the approach with a simulation of the 2006 Guerrero slow slip event. In our study, we emphasize the importance of including the InSAR covariance information, and demonstrate that InSAR provides an additional constraint on the spatial extent of the slow slip. References: Segall, P., and M. Matthews (1997), Time dependent inversion of geodetic data, J. Geophys. Res., 102 (B10), 22,391 - 22,409, doi:10.1029/97JB01795. Bekaert, D., P. Segall, T.J. Wright, and A. Hooper (2016), A Network Inversion Filter combining GNSS and InSAR for tectonic slip modeling, JGR, doi:10.1002/2015JB012638 (open access).
Double inverse stochastic resonance with dynamic synapses
Uzuntarla, Muhammet; Torres, Joaquin J.; So, Paul; Ozer, Mahmut; Barreto, Ernest
2017-01-01
We investigate the behavior of a model neuron that receives a biophysically realistic noisy postsynaptic current based on uncorrelated spiking activity from a large number of afferents. We show that, with static synapses, such noise can give rise to inverse stochastic resonance (ISR) as a function of the presynaptic firing rate. We compare this to the case with dynamic synapses that feature short-term synaptic plasticity and show that the interval of presynaptic firing rate over which ISR exists can be extended or diminished. We consider both short-term depression and facilitation. Interestingly, we find that a double inverse stochastic resonance (DISR), with two distinct wells centered at different presynaptic firing rates, can appear.
Huisman, J. A.; Rings, J.; Vrugt, J. A.; Sorg, J.; Vereecken, H.
2010-01-01
SummaryCoupled hydrogeophysical inversion aims to improve the use of geophysical data for hydrological model parameterization. Several numerical studies have illustrated the feasibility and advantages of a coupled approach. However, there is still a lack of studies that apply the coupled inversion approach to actual field data. In this paper, we test the feasibility of coupled hydrogeophysical inversion for determining the hydraulic properties of a model dike using measurements of electrical resistance tomography (ERT). Our analysis uses a two-dimensional (2D) finite element hydrological model (HYDRUS-2D) coupled to a 2.5D finite element electrical resistivity code (CRMOD), and includes explicit recognition of parameter uncertainty by using a Bayesian and multiple criteria framework with the DREAM and AMALGAM population based search algorithms. To benchmark our inversion results, soil hydraulic properties determined from ERT data are compared with those separately obtained from detailed in situ soil water content measurements using Time Domain Reflectometry (TDR). Our most important results are as follows. (1) TDR and ERT data theoretically contain sufficient information to resolve most of the soil hydraulic properties, (2) the DREAM-derived posterior distributions of the hydraulic parameters are quite similar when estimated separately using TDR and ERT measurements for model calibration, (3) among all parameters, the saturated hydraulic conductivity of the dike material is best constrained, (4) the saturation exponent of the petrophysical model is well defined, and matches independently measured values, (5) measured ERT data sufficiently constrain model predictions of water table dynamics within the model dike. This finding demonstrates an innate ability of ERT data to provide accurate hydrogeophysical parameterizations for flooding events, which is of particular relevance to dike management, and (6) the AMALGAM-derived Pareto front demonstrates trade-off in the
3D forward modeling and inversion of large scale CSEM method
Fu, C.; Di, Q.; Xu, C.
2012-12-01
MT and CSAMT methods have been widely applied in many areas such as coal, mineral, geothermal and engineering exploration, are very useful exploration methods, but they still have some problems. So an electromagnetic (EM) method using a fixed large power source, such as a long bipole current source, is beginning to take shape. In this method, the distance between receiver and source may reach thousands of kilometers, so the effect of ionosphere on the EM fields should be considered when we doing the modeling or inversion. The integral equation (IE) method is a reliable way to do the 3D forward modeling and inversion for 3D models. We have deduced a 3D IE method that can effectively modeling the large scale CSEM method which including ionosphere's effect. In order to find the characteristics of EM fields and the exploration ability for this large scale CSEM method, we build a typical 3D mineral model, and then make the forward modeling and inversion by using of 3D IE method. There are mainly two stratums in the forwarding modeling model, the upper layer is limestone, the resistivity is 2000 ohm.m, the lower layer is granite, the resistivity is 5000 ohm.m, and there are some granite in the upper layer as intrusive rock. Two ore bodies are at contact zone of the two rocks, the resistivity are 100 ohm.m and 200 ohm.m, respectively. The forward modeling results showed that, because the effect of ionosphere, the EM field is not very weak although the distance is very large between receiver and source. We can see some obscure low resistivity zone in the pseudo section map. After the inversion, the two ore bodies are clearly being showed, and we also can find the intrusive mass which corresponds to the original model. The results showed that our 3D IE forward and inversion code is reliable, and the large scale CSEM method has good resolution, it can be applied in the area of geophysical exploration.
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Myron A. Peck
2009-10-01
Full Text Available We employed 3-D biophysical modeling and dispersion kernel analysis to explore inter-annual and inter-specific differences in the drift trajectories of eggs and yolksac larvae of plaice (Pleuronectes platessa, Atlantic cod (Gadus morhua, sprat (Sprattus sprattus and horse mackerel (Trachurus trachurus in the North Sea. In this region, these four species exhibit peak spawning during the boreal winter, late winter/early spring, late spring/early summer, and mid-summer respectively, but utilize the same spawning locations (our simulations included Dogger Bank, Southern Bight and the German Bight. Inter-annual differences in the temperature history, and an increase in the area of dispersion and final distribution at the end of the yolksac phase were more pronounced (and related to the North Atlantic Oscillation for winter- and early spring-spawners compared to late spring/summer spawners. The progeny of the latter experienced the largest (up to 10-fold inter-annual differences in drift distances, although absolute drift distances were modest (~2 to 30 km when compared to those of the former (~ 20 to 130 km. Our results highlight the complex interplay that exists between the specific life history strategies of the different species and the impacts of the variability in (climate-driven physical factors during the earliest life stages of marine fish.
A numerical study of the inverse problem of breast infrared thermography modeling
Jiang, Li; Zhan, Wang; Loew, Murray H.
2010-03-01
Infrared thermography has been shown to be a useful adjunctive tool for breast cancer detection. Previous thermography modeling techniques generally dealt with the "forward problem", i.e., to estimate the breast thermogram from known properties of breast tissues. The present study aims to deal with the so-called "inverse problem", namely to estimate the thermal properties of the breast tissues from the observed surface temperature distribution. By comparison, the inverse problem is a more direct way of interpreting a breast thermogram for specific physiological and/or pathological information. In tumor detection, for example, it is particularly important to estimate the tumor-induced thermal contrast, even though the corresponding non-tumor thermal background usually is unknown due to the difficulty of measuring the individual thermal properties. Inverse problem solving is technically challenging due to its ill-posed nature, which is evident primarily by its sensitivity to imaging noise. Taking advantage of our previously developed forward-problemsolving techniques with comprehensive thermal-elastic modeling, we examine here the feasibility of solving the inverse problem of the breast thermography. The approach is based on a presumed spatial constraint applied to three major thermal properties, i.e., thermal conductivity, blood perfusion, and metabolic heat generation, for each breast tissue type. Our results indicate that the proposed inverse-problem-solving scheme can be numerically stable under imaging noise of SNR ranging 32 ~ 40 dB, and that the proposed techniques can be effectively used to improve the estimation to the tumor-induced thermal contrast, especially for smaller and deeper tumors.
Research Note: Full-waveform inversion of the unwrapped phase of a model
Alkhalifah, Tariq Ali
2013-12-06
Reflections in seismic data induce serious non-linearity in the objective function of full- waveform inversion. Thus, without a good initial velocity model that can produce reflections within a half cycle of the frequency used in the inversion, convergence to a solution becomes difficult. As a result, we tend to invert for refracted events and damp reflections in data. Reflection induced non-linearity stems from cycle skipping between the imprint of the true model in observed data and the predicted model in synthesized data. Inverting for the phase of the model allows us to address this problem by avoiding the source of non-linearity, the phase wrapping phenomena. Most of the information related to the location (or depths) of interfaces is embedded in the phase component of a model, mainly influenced by the background model, while the velocity-contrast information (responsible for the reflection energy) is mainly embedded in the amplitude component. In combination with unwrapping the phase of data, which mitigates the non-linearity introduced by the source function, I develop a framework to invert for the unwrapped phase of a model, represented by the instantaneous depth, using the unwrapped phase of the data. The resulting gradient function provides a mechanism to non-linearly update the velocity model by applying mainly phase shifts to the model. In using the instantaneous depth as a model parameter, we keep track of the model properties unfazed by the wrapping phenomena. © 2013 European Association of Geoscientists & Engineers.
Inverse transport modeling of volcanic sulfur dioxide emissions using large-scale simulations
Heng, Yi; Hoffmann, Lars; Griessbach, Sabine; Rößler, Thomas; Stein, Olaf
2016-05-01
An inverse transport modeling approach based on the concepts of sequential importance resampling and parallel computing is presented to reconstruct altitude-resolved time series of volcanic emissions, which often cannot be obtained directly with current measurement techniques. A new inverse modeling and simulation system, which implements the inversion approach with the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) is developed to provide reliable transport simulations of volcanic sulfur dioxide (SO2). In the inverse modeling system MPTRAC is used to perform two types of simulations, i.e., unit simulations for the reconstruction of volcanic emissions and final forward simulations. Both types of transport simulations are based on wind fields of the ERA-Interim meteorological reanalysis of the European Centre for Medium Range Weather Forecasts. The reconstruction of altitude-dependent SO2 emission time series is also based on Atmospheric InfraRed Sounder (AIRS) satellite observations. A case study for the eruption of the Nabro volcano, Eritrea, in June 2011, with complex emission patterns, is considered for method validation. Meteosat Visible and InfraRed Imager (MVIRI) near-real-time imagery data are used to validate the temporal development of the reconstructed emissions. Furthermore, the altitude distributions of the emission time series are compared with top and bottom altitude measurements of aerosol layers obtained by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite instruments. The final forward simulations provide detailed spatial and temporal information on the SO2 distributions of the Nabro eruption. By using the critical success index (CSI), the simulation results are evaluated with the AIRS observations. Compared to the results with an assumption of a constant flux of SO2 emissions, our inversion approach leads to an improvement
Zhang, Z.; Xue, Y.; MacDonald, G. M.; Cox, P. M.; Collatz, G. J.
2014-12-01
This study applies a 2-D biophysical model/dynamic vegetation model (SSiB4/TRIFFID) to investigate the dominant factors affecting vegetation equilibrium conditions, to assess the model's ability to simulate seasonal to decadal variability for the past 60 years (from 1948 through 2008), to analyze vegetation spatiotemporal characteristics over North America (NA), and to identify the relationships between vegetation and climate. Satellite data are employed as constraints for this study. The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka-Volterra equation have major impact on the vegetation spatial distribution and reach to equilibrium status in SSiB4/TRIFFID. The phenomenon that vegetation competition coefficients affect equilibrium suggests the importance of including biotic effects in dynamical vegetation modeling. SSiB4/TRIFFID can reproduce the features of NA distributions of dominant vegetation types, the vegetation fraction, and LAI, including its seasonal, interannual, and decadal variability, well compared with satellite-derived products. The NA LAI shows an increasing trend after the 1970s in responding to warming. Meanwhile, both simulation and satellite observations reveal LAI increased in the southeastern U.S. starting from the 1980s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S.on vegetation are also evident from the simulated and satellite-derived LAIs.Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring through their effect on photosynthesis and phenological processes. During the summer, the areas with positive correlations retreat northward. Meanwhile, in southwestern dry lands, the negative correlations appear due to the heat stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which
Atmospheric inverse modeling with known physical bounds: an example from trace gas emissions
Directory of Open Access Journals (Sweden)
S. M. Miller
2013-09-01
Full Text Available Many inverse problems in the atmospheric sciences involve parameters with known physical constraints. Examples include non-negativity (e.g., emissions of some urban air pollutants or upward limits implied by reaction or solubility constants. However, probabilistic inverse modeling approaches based on Gaussian assumptions cannot incorporate such bounds and thus often produce unrealistic results. The atmospheric literature lacks consensus on the best means to overcome this problem, and existing atmospheric studies rely on a limited number of the possible methods with little examination of the relative merits of each. This paper investigates the applicability of several approaches to bounded inverse problems and is also the first application of Markov chain Monte Carlo (MCMC to estimation of atmospheric trace gas fluxes. The approaches discussed here are broadly applicable. A common method of data transformations is found to unrealistically skew estimates for the examined example application. The method of Lagrange multipliers and two MCMC methods yield more realistic and accurate results. In general, the examined MCMC approaches produce the most realistic result but can require substantial computational time. Lagrange multipliers offer an appealing alternative for large, computationally intensive problems when exact uncertainty bounds are less central to the analysis. A synthetic data inversion of US anthropogenic methane emissions illustrates the strengths and weaknesses of each approach.
RESEARCH ON INVERSION MODELS FOR FOREST HEIGHT ESTIMATION USING POLARIMETRIC SAR INTERFEROMETRY
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L. Zhang
2017-09-01
Full Text Available The forest height is an important forest resource information parameter and usually used in biomass estimation. Forest height extraction with PolInSAR is a hot research field of imaging SAR remote sensing. SAR interferometry is a well-established SAR technique to estimate the vertical location of the effective scattering center in each resolution cell through the phase difference in images acquired from spatially separated antennas. The manipulation of PolInSAR has applications ranging from climate monitoring to disaster detection especially when used in forest area, is of particular interest because it is quite sensitive to the location and vertical distribution of vegetation structure components. However, some of the existing methods can’t estimate forest height accurately. Here we introduce several available inversion models and compare the precision of some classical inversion approaches using simulated data. By comparing the advantages and disadvantages of these inversion methods, researchers can find better solutions conveniently based on these inversion methods.
Energy Technology Data Exchange (ETDEWEB)
Pison, I.; Blond, N. [Paris-7 Univ., Creteil (France). LISA, CNRS; Menut, L. [Ecole Polytechnique, Palaiseau (France). LMD/IPSL
2006-07-01
A new methodology for the inversion of anthropogenic emissions at a local scale is tested. The inversion constraints are provided by a kriging technique used in air quality forecast in the Paris area, which computes an analyzed concentration field from network measurements and the first-guess simulation of a CTM. The inverse developed here is based on the CHIMERE model and its adjoint to perform 4-D integration. The methodology is validated on synthetic cases inverting emission fluxes. It is shown that the information provided by the analyzed concentrations is sufficient to reach a mathematically acceptable solution to the optimization, even when little information is available in the measurements. As compared to the use of measurements alone or of measurements and a background matrix, the use of kriging leads to a more homogeneous distribution of the corrections, both in space and time. Moreover, it is then possible to double the accuracy of the inversion by performing two kriging-optimization cycles. Nevertheless, kriging analysis cannot compensate for a very important lack of information in the measurements. (orig.)
Directory of Open Access Journals (Sweden)
I. Pison
2006-07-01
Full Text Available A new methodology for the inversion of anthropogenic emissions at a local scale is tested. The inversion constraints are provided by a kriging technique used in air quality forecast in the Paris area, which computes an analyzed concentration field from network measurements and the first-guess simulation of a CTM. The inverse developed here is based on the CHIMERE model and its adjoint to perform 4-D integration. The methodology is validated on synthetic cases inverting emission fluxes. It is shown that the information provided by the analyzed concentrations is sufficient to reach a mathematically acceptable solution to the optimization, even when little information is available in the measurements. As compared to the use of measurements alone or of measurements and a background matrix, the use of kriging leads to a more homogeneous distribution of the corrections, both in space and time. Moreover, it is then possible to double the accuracy of the inversion by performing two kriging-optimization cycles. Nevertheless, kriging analysis cannot compensate for a very important lack of information in the measurements.
Extending the conditions of application of an inversion of the Hodgkin-Huxley gating model.
Raba, Ashley E; Cordeiro, Jonathan M; Antzelevitch, Charles; Beaumont, Jacques
2013-05-01
We present an inversion of the Hodgkin-Huxley formalism to estimate initial conditions and model parameters, including functions of voltage, from the solutions of the underlying ordinary differential equation (ODE) subjected to multiple voltage step stimulations. As such, the procedure constitutes a means to estimate the parameters including functions of voltage of an Hodgkin-Huxley formalism from experimental data.The basic idea was developed in a previous communication (SIAM J. Appl. Math. 64:1264-1274, 2009). The inversion in question applies to currents exhibiting activation and inactivation, but the version, as published previously, cannot estimate the unknowns for channels that rapidly inactivate just after a brief opening. In such cases, the amplitude of the current, in a given voltage range, is too small to be detectable by the instrumentation using previously applied experimental protocols. This is, for example, the case for the sodium channels in a number of excitable tissue for potential in the vicinity of the cell resting potential. The current communication extends the inversion procedure in a manner to overcome this limitation.Furthermore, within the inversion framework, we can determine whether the data at the basis of the estimation sufficiently constrains the estimation problem, i.e., whether it is complete. We exploit this element of our method to document a set of stimulation protocols that constitute a complete data set for the purpose of inverting the Hodgkin-Huxley formalism.
Discrete model of spacetime in terms of inverse spectra of the $T_0$ Alexandroff topological spaces
Efremov, V N; Efremov, Vladimir N.; Mitskievich, Nikolai V.
2003-01-01
The theory of inverse spectra of $T_0$ Alexandroff topological spaces is used to construct a model of $T_0$-discrete four-dimensional spacetime. The universe evolution is interpreted in terms of a sequence of topology changes in the set of $T_0$-discrete spaces realized as nerves of the canonical partitions of three-dimensional compact manifolds. The cosmological time arrow arises being connected with the refinement of the canonical partitions, and it is defined by the action of homomorphisms in the proper inverse spectrum of three-dimensional $T_0$-discrete spaces. A new causal order relation in this spectrum is postulated having the basic properties of the causal order in the pseudo-Riemannian spacetime however also bearing certain quasi-quantum features. An attempt is made to describe topological changes between compact manifolds in terms of bifurcations of proper inverse spectra; this led us to the concept of bispectrum. As a generalization of this concept, inverse multispectra and superspectrum are intro...
AVAZ inversion for fracture weakness parameters based on the rock physics model
Chen, Huaizhen; Yin, Xingyao; Qu, Shouli; Zhang, Guangzhi
2014-12-01
Subsurface fractures within many carbonates and unconventional resources play an important role in the storage and movement of fluid. The more reliably the detection of fractures could be performed, the more finely the reservoir description could be made. In this paper, we aim to propose a method which uses two important tools, a fractured anisotropic rock physics effective model and AVAZ (amplitude versus incident and azimuthal angle) inversion, to predict fractures from azimuthal seismic data. We assume that the rock, which contains one or more sets of vertical or sub-vertical fractures, shows transverse isotropy with a horizontal axis of symmetry (HTI). Firstly, we develop one improved fractured anisotropic rock physics effective model. Using this model, we estimate P-wave velocity, S-wave velocity and fracture weaknesses from well-logging data. Then the method is proposed to predict fractures from azimuthal seismic data based on AVAZ inversion, and well A is used to verify the reliability of the improved rock physics effective model. Results show that the estimated results are consistent with the real log value, and the variation of fracture weaknesses may detect the locations of fractures. The damped least squares method, which uses the estimated results as initial constraints during the inversion, is more stable. Tests on synthetic data show that fracture weaknesses parameters are still estimated reasonably with moderate noise. A test on real data shows that the estimated results are in good agreement with the drilling.
Peddle, Derek R.; Huemmrich, K. Fred; Hall, Forrest G.; Masek, Jeffrey G.; Soenen, Scott A.; Jackson, Chris D.
2011-01-01
Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.
Energy Technology Data Exchange (ETDEWEB)
Watanabe, T.; Sassa, K. [Kyoto University, Kyoto (Japan); Uesaka, S. [Kyoto University, Kyoto (Japan). Faculty of Engineering
1996-10-01
The effect of initial models on full-wave inversion (FWI) analysis based on acoustic wave-equation was studied for elastic wave tomography of underground structures. At present, travel time inversion using initial motion travel time is generally used, and inverse analysis is conducted using the concept `ray,` assuming very high wave frequency. Although this method can derive stable solutions relatively unaffected by initial model, it uses only the data of initial motion travel time. FWI calculates theoretical waveform at each receiver using all of observed waveforms as data by wave equation modeling where 2-D underground structure is calculated by difference calculus under the assumption that wave propagation is described by wave equation of P wave. Although it is a weak point that FWI is easily affected by noises in an initial model and data, it is featured by high resolution of solutions. This method offers very excellent convergence as a proper initial model is used, resulting in sufficient performance, however, it is strongly affected by initial model. 2 refs., 7 figs., 1 tab.
Ramakrishnan, N.; Tourdot, Richard W.; Eckmann, David M.; Ayyaswamy, Portonovo S.; Muzykantov, Vladimir R.; Radhakrishnan, Ravi
2016-06-01
In order to achieve selective targeting of affinity-ligand coated nanoparticles to the target tissue, it is essential to understand the key mechanisms that govern their capture by the target cell. Next-generation pharmacokinetic (PK) models that systematically account for proteomic and mechanical factors can accelerate the design, validation and translation of targeted nanocarriers (NCs) in the clinic. Towards this objective, we have developed a computational model to delineate the roles played by target protein expression and mechanical factors of the target cell membrane in determining the avidity of functionalized NCs to live cells. Model results show quantitative agreement with in vivo experiments when specific and non-specific contributions to NC binding are taken into account. The specific contributions are accounted for through extensive simulations of multivalent receptor-ligand interactions, membrane mechanics and entropic factors such as membrane undulations and receptor translation. The computed NC avidity is strongly dependent on ligand density, receptor expression, bending mechanics of the target cell membrane, as well as entropic factors associated with the membrane and the receptor motion. Our computational model can predict the in vivo targeting levels of the intracellular adhesion molecule-1 (ICAM1)-coated NCs targeted to the lung, heart, kidney, liver and spleen of mouse, when the contributions due to endothelial capture are accounted for. The effect of other cells (such as monocytes, etc.) do not improve the model predictions at steady state. We demonstrate the predictive utility of our model by predicting partitioning coefficients of functionalized NCs in mice and human tissues and report the statistical accuracy of our model predictions under different scenarios.
Le Goff, Clément; Lavaud, Romain; Cugier, Philippe; Jean, Fred; Flye-Sainte-Marie, Jonathan; Foucher, Eric; Desroy, Nicolas; Fifas, Spyros; Foveau, Aurélie
2017-03-01
In this paper we used a modelling approach integrating both physical and biological constraints to understand the biogeographical distribution of the great scallop Pecten maximus in the English Channel during its whole life cycle. A 3D bio-hydrodynamical model (ECO-MARS3D) providing environmental conditions was coupled to (i) a population dynamics model and (ii) an individual ecophysiological model (Dynamic Energy Budget model). We performed the coupling sequentially, which underlined the respective role of biological and physical factors in defining P. maximus distribution in the English Channel. Results show that larval dispersion by hydrodynamics explains most of the scallop distribution and enlighten the main known hotspots for the population, basically corresponding to the main fishing areas. The mechanistic description of individual bioenergetics shows that food availability and temperature control growth and reproduction and explain how populations may maintain themselves in particular locations. This last coupling leads to more realistic densities and distributions of adults in the English Channel. The results of this study improves our knowledge on the stock and distribution dynamics of P. maximus, and provides grounds for useful tools to support management strategies.
Inverse Magnetic Catalysis in Nambu--Jona-Lasinio Model beyond Mean Field
Mao, Shijun
2016-01-01
We study inverse magnetic catalysis in the Nambu--Jona-Lasinio model beyond mean field approximation. The feed-down from mesons to quarks is embedded in an effective coupling constant at finite temperature and magnetic field. While the magnetic catalysis is still the dominant effect at low temperature, the meson dressed quark mass drops down with increasing magnetic field at high temperature due to the dimension reduction of the Goldstone mode in the Pauli-Villars regularization scheme.
Gosselin, Jeremy M.; Dosso, Stan E.; Cassidy, John F.; Quijano, Jorge E.; Molnar, Sheri; Dettmer, Jan
2017-10-01
This paper develops and applies a Bernstein-polynomial parametrization to efficiently represent general, gradient-based profiles in nonlinear geophysical inversion, with application to ambient-noise Rayleigh-wave dispersion data. Bernstein polynomials provide a stable parametrization in that small perturbations to the model parameters (basis-function coefficients) result in only small perturbations to the geophysical parameter profile. A fully nonlinear Bayesian inversion methodology is applied to estimate shear wave velocity (VS) profiles and uncertainties from surface wave dispersion data extracted from ambient seismic noise. The Bayesian information criterion is used to determine the appropriate polynomial order consistent with the resolving power of the data. Data error correlations are accounted for in the inversion using a parametric autoregressive model. The inversion solution is defined in terms of marginal posterior probability profiles for VS as a function of depth, estimated using Metropolis-Hastings sampling with parallel tempering. This methodology is applied to synthetic dispersion data as well as data processed from passive array recordings collected on the Fraser River Delta in British Columbia, Canada. Results from this work are in good agreement with previous studies, as well as with co-located invasive measurements. The approach considered here is better suited than `layered' modelling approaches in applications where smooth gradients in geophysical parameters are expected, such as soil/sediment profiles. Further, the Bernstein polynomial representation is more general than smooth models based on a fixed choice of gradient type (e.g. power-law gradient) because the form of the gradient is determined objectively by the data, rather than by a subjective parametrization choice.
An Inverse Model of Three-Dimensional Flow and Transport in Heterogeneous Porous Media
Robinson, B. A.; Vrugt, J. A.; Yoon, H.; Zhang, C.; Werth, C. J.; Kitanidis, P. K.; Lichtner, P. C.; Lu, C.
2007-12-01
A three-dimensional flow and transport model was developed to simulate the results of a laboratory-scale experiment in which snapshots of concentration were obtained using magnetic resonance imaging (MRI) during the displacement of tracer through a 14 by 8 by 8 cm flow cell. The medium was deliberately constructed to be heterogeneous with a known spatial correlation structure using sand of five different grain-size distributions. The extremely well characterized flow cell and large, high-precision data set of concentrations during displacement make this a unique experiment for examining the validity of flow and transport models, and for exploring new methods for interpreting large data sets using advanced optimization algorithms. A transport model was constructed by solving the steady state flow equations using the Finite Element Heat and Mass (FEHM) code, using FEHM's particle tracking transport model for simulating tracer migration. The particle tracking model was selected so that precise estimates of the transport parameters could be obtained that are not corrupted by numerical dispersion; a large number of particles (typically one million) were required to provide accuracy. The inverse model included nine uncertain parameters, the five permeability values of the individual sand units, and four dispersion/diffusion parameters. The inverse problem was solved with AMALGAM and DREAM, two recently developed self-adaptive multimethod optimization algorithms. The computations were enabled by performing both the transport model and the optimization loop on a high-performance computing cluster. Computational results indicate that parameter estimates and increased understanding of the behavior of the system can be obtained, and significant improvements in the fit to the data over hand calibration can be achieved, using this inverse modeling approach. The study also illustrates that numerical methods that make effective use of high- performance computing resources and
Polarimetry data inversion in conditions of tokamak plasma: Model based tomography concept
Energy Technology Data Exchange (ETDEWEB)
Bieg, B. [Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin (Poland); Chrzanowski, J., E-mail: j.chrzanowski@am.szczecin.pl [Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin (Poland); Kravtsov, Yu. A. [Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin (Poland); Space Research Institute, Profsoyuznaya St. 82/34 Russian Academy of Science, Moscow 117997 (Russian Federation); Mazon, D. [CEA, IRFM, F-13108 Saint Paul-lez-Durance (France)
2015-10-15
Highlights: • Model based plasma tomography is presented. • Minimization procedure for the error function is suggested to be performed using the gradient method. • model based procedure of data inversion in the case of joint polarimetry–interferometry data. - Abstract: Model based plasma tomography is studied which fits a hypothetical multi-parameter plasma model to polarimetry and interferometry experimental data. Fitting procedure implies minimization of the error function, defined as a sum of squared differences between theoretical and empirical values. Minimization procedure for the function is suggested to be performed using the gradient method. Contrary to traditional tomography, which deals exclusively with observational data, model-based tomography (MBT) operates also with reasonable model of inhomogeneous plasma distribution and verifies which profile of a given class better fits experimental data. Model based tomography (MBT) restricts itself by definite class of models for instance power series, Fourier expansion etc. The basic equations of MBT are presented which generalize the equations of model based procedure of polarimetric data inversion in the case of joint polarimetry–interferometry data.
Directory of Open Access Journals (Sweden)
J. F. Meirink
2008-06-01
Full Text Available A four-dimensional variational (4D-var data assimilation system for inverse modelling of atmospheric methane emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of measurements, in particular satellite observations and quasi-continuous in-situ observations, and at the same time it enables the optimization of a large number of model parameters, specifically grid-scale emission rates. Furthermore, the variational method allows to estimate uncertainties in posterior emissions. Here, the system is applied to optimize monthly methane emissions over a 1-year time window on the basis of surface observations from the NOAA-ESRL network. The results are rigorously compared with an analogous inversion by Bergamaschi et al. (2007, which was based on the traditional synthesis approach. The posterior emissions as well as their uncertainties obtained in both inversions show a high degree of consistency. At the same time we illustrate the advantage of 4D-Var in reducing aggregation errors by optimizing emissions at the grid scale of the transport model. The full potential of the assimilation system is exploited in Meirink et al. (2008, who use satellite observations of column-averaged methane mixing ratios to optimize emissions at high spatial resolution, taking advantage of the zooming capability of the TM5 model.
Smith, G. A.; Meyer, G.; Nordstrom, M.
1986-01-01
A new automatic flight control system concept suitable for aircraft with highly nonlinear aerodynamic and propulsion characteristics and which must operate over a wide flight envelope was investigated. This exact model follower inverts a complete nonlinear model of the aircraft as part of the feed-forward path. The inversion is accomplished by a Newton-Raphson trim of the model at each digital computer cycle time of 0.05 seconds. The combination of the inverse model and the actual aircraft in the feed-forward path alloys the translational and rotational regulators in the feedback path to be easily designed by linear methods. An explanation of the model inversion procedure is presented. An extensive set of simulation data for essentially the full flight envelope for a vertical attitude takeoff and landing aircraft (VATOL) is presented. These data demonstrate the successful, smooth, and precise control that can be achieved with this concept. The trajectory includes conventional flight from 200 to 900 ft/sec with path accelerations and decelerations, altitude changes of over 6000 ft and 2g and 3g turns. Vertical attitude maneuvering as a tail sitter along all axes is demonstrated. A transition trajectory from 200 ft/sec in conventional flight to stationary hover in the vertical attitude includes satisfactory operation through lift-cure slope reversal as attitude goes from horizontal to vertical at constant altitude. A vertical attitude takeoff from stationary hover to conventional flight is also demonstrated.
Energy Technology Data Exchange (ETDEWEB)
Chen, Yu [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gao, Kai [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Huang, Lianjie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Sabin, Andrew [Geothermal Program Office, China Lake, CA (United States)
2016-03-31
Accurate imaging and characterization of fracture zones is crucial for geothermal energy exploration. Aligned fractures within fracture zones behave as anisotropic media for seismic-wave propagation. The anisotropic properties in fracture zones introduce extra difficulties for seismic imaging and waveform inversion. We have recently developed a new anisotropic elastic-waveform inversion method using a modified total-variation regularization scheme and a wave-energy-base preconditioning technique. Our new inversion method uses the parameterization of elasticity constants to describe anisotropic media, and hence it can properly handle arbitrary anisotropy. We apply our new inversion method to a seismic velocity model along a 2D-line seismic data acquired at Eleven-Mile Canyon located at the Southern Dixie Valley in Nevada for geothermal energy exploration. Our inversion results show that anisotropic elastic-waveform inversion has potential to reconstruct subsurface anisotropic elastic parameters for imaging and characterization of fracture zones.
Juhojuntti, N. G.; Kamm, J.
2010-12-01
We present a layered-model approach to joint inversion of shallow seismic refraction and resistivity (DC) data, which we believe is a seldom tested method of addressing the problem. This method has been developed as we believe that for shallow sedimentary environments (roughly fairly simple 2D geometries, mainly for checking the validity of the calculations. The inversion generally converges towards the correct solution, although there could be stability problems if the starting model is too erroneous. We have also applied the code to field data from seismic refraction and multi-electrode resistivity measurements at typical sand-gravel groundwater reservoirs. The tests are promising, as the calculated depths agree fairly well with information from drilling and the velocity and resistivity values appear reasonable. Current work includes better regularization of the inversion as well as defining individual weight factors for the different datasets, as the present algorithm tends to constrain the depths mainly by using the seismic data. More complex synthetic examples will also be tested, including models addressing the seismic hidden-layer problem.
Modeling and forecasting foreign exchange daily closing prices with normal inverse Gaussian
Teneng, Dean
2013-09-01
We fit the normal inverse Gaussian(NIG) distribution to foreign exchange closing prices using the open software package R and select best models by Käärik and Umbleja (2011) proposed strategy. We observe that daily closing prices (12/04/2008 - 07/08/2012) of CHF/JPY, AUD/JPY, GBP/JPY, NZD/USD, QAR/CHF, QAR/EUR, SAR/CHF, SAR/EUR, TND/CHF and TND/EUR are excellent fits while EGP/EUR and EUR/GBP are good fits with a Kolmogorov-Smirnov test p-value of 0.062 and 0.08 respectively. It was impossible to estimate normal inverse Gaussian parameters (by maximum likelihood; computational problem) for JPY/CHF but CHF/JPY was an excellent fit. Thus, while the stochastic properties of an exchange rate can be completely modeled with a probability distribution in one direction, it may be impossible the other way around. We also demonstrate that foreign exchange closing prices can be forecasted with the normal inverse Gaussian (NIG) Lévy process, both in cases where the daily closing prices can and cannot be modeled by NIG distribution.
Fitz, Hartmut; Chang, Franklin
2017-09-01
Nativist theories have argued that language involves syntactic principles which are unlearnable from the input children receive. A paradigm case of these innate principles is the structure dependence of auxiliary inversion in complex polar questions (Chomsky, 1968, 1975, 1980). Computational approaches have focused on the properties of the input in explaining how children acquire these questions. In contrast, we argue that messages are structured in a way that supports structure dependence in syntax. We demonstrate this approach within a connectionist model of sentence production (Chang, 2009) which learned to generate a range of complex polar questions from a structured message without positive exemplars in the input. The model also generated different types of error in development that were similar in magnitude to those in children (e.g., auxiliary doubling, Ambridge, Rowland, & Pine, 2008; Crain & Nakayama, 1987). Through model comparisons we trace how meaning constraints and linguistic experience interact during the acquisition of auxiliary inversion. Our results suggest that auxiliary inversion rules in English can be acquired without innate syntactic principles, as long as it is assumed that speakers who ask complex questions express messages that are structured into multiple propositions. Copyright © 2017 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S. [Univ. of Lethbridge, Dept. of Geography, Lethbridge, Alberta (Canada)
2008-06-15
Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter {mu} {+-} 1{sigma}), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha{sup -1}{center_dot}year{sup -1}. This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat
Inversion of geothermal heat flux in a thermomechanically coupled nonlinear Stokes ice sheet model
Zhu, Hongyu; Petra, Noemi; Stadler, Georg; Isaac, Tobin; Hughes, Thomas J. R.; Ghattas, Omar
2016-07-01
We address the inverse problem of inferring the basal geothermal heat flux from surface velocity observations using a steady-state thermomechanically coupled nonlinear Stokes ice flow model. This is a challenging inverse problem since the map from basal heat flux to surface velocity observables is indirect: the heat flux is a boundary condition for the thermal advection-diffusion equation, which couples to the nonlinear Stokes ice flow equations; together they determine the surface ice flow velocity. This multiphysics inverse problem is formulated as a nonlinear least-squares optimization problem with a cost functional that includes the data misfit between surface velocity observations and model predictions. A Tikhonov regularization term is added to render the problem well posed. We derive adjoint-based gradient and Hessian expressions for the resulting partial differential equation (PDE)-constrained optimization problem and propose an inexact Newton method for its solution. As a consequence of the Petrov-Galerkin discretization of the energy equation, we show that discretization and differentiation do not commute; that is, the order in which we discretize the cost functional and differentiate it affects the correctness of the gradient. Using two- and three-dimensional model problems, we study the prospects for and limitations of the inference of the geothermal heat flux field from surface velocity observations. The results show that the reconstruction improves as the noise level in the observations decreases and that short-wavelength variations in the geothermal heat flux are difficult to recover. We analyze the ill-posedness of the inverse problem as a function of the number of observations by examining the spectrum of the Hessian of the cost functional. Motivated by the popularity of operator-split or staggered solvers for forward multiphysics problems - i.e., those that drop two-way coupling terms to yield a one-way coupled forward Jacobian - we study the
Magnetic catalysis and inverse magnetic catalysis in nonlocal chiral quark models
Pagura, V. P.; Gómez Dumm, D.; Noguera, S.; Scoccola, N. N.
2017-02-01
We study the behavior of strongly interacting matter under an external constant magnetic field in the context of nonlocal chiral quark models within the mean field approximation. We find that at zero temperature the behavior of the quark condensates shows the expected magnetic catalysis effect, our predictions being in good quantitative agreement with lattice QCD results. On the other hand, in contrast to what happens in the standard local Nambu-Jona-Lasinio model, when the analysis is extended to the case of finite temperature, our results show that nonlocal models naturally lead to the inverse magnetic catalysis effect.
Magnetic catalysis and inverse magnetic catalysis in nonlocal chiral quark models
Pagura, V P; Noguera, S; Scoccola, N N
2016-01-01
We study the behavior of strongly interacting matter under an external constant magnetic field in the context of nonlocal chiral quark models within the mean field approximation. We find that at zero temperature the behavior of the quark condensates shows the expected magnetic catalysis effect, our predictions being in good quantitative agreement with lattice QCD results. On the other hand, in contrast to what happens in the standard local Nambu-Jona-Lasinio model, when the analysis is extended to the case of finite temperature our results show that nonlocal models naturally lead to the Inverse Magnetic Catalysis effect.
Z_3 Polyakov Loop Models and Inverse Monte-Carlo Methods
Wozar, Christian; Uhlmann, Sebastian; Wipf, Andreas; Heinzl, Thomas
2007-01-01
We study effective Polyakov loop models for SU(3) Yang-Mills theory at finite temperature. A comprehensive mean field analysis of the phase diagram is carried out and compared to the results obtained from Monte-Carlo simulations. We find a rich phase structure including ferromagnetic and antiferromagnetic phases. Due to the presence of a tricritical point the mean field approximation agrees very well with the numerical data. Critical exponents associated with second-order transitions coincide with those of the Z_3 Potts model. Finally, we employ inverse Monte-Carlo methods to determine the effective couplings in order to match the effective models to Yang-Mills theory.
Flatness-based model inverse for feed-forward braking control
de Vries, Edwin; Fehn, Achim; Rixen, Daniel
2010-12-01
For modern cars an increasing number of driver assistance systems have been developed. Some of these systems interfere/assist with the braking of a car. Here, a brake actuation algorithm for each individual wheel that can respond to both driver inputs and artificial vehicle deceleration set points is developed. The algorithm consists of a feed-forward control that ensures, within the modelled system plant, the optimal behaviour of the vehicle. For the quarter-car model with LuGre-tyre behavioural model, an inverse model can be derived using v x as the 'flat output', that is, the input for the inverse model. A number of time derivatives of the flat output are required to calculate the model input, brake torque. Polynomial trajectory planning provides the needed time derivatives of the deceleration request. The transition time of the planning can be adjusted to meet actuator constraints. It is shown that the output of the trajectory planning would ripple and introduce a time delay when a gradual continuous increase of deceleration is requested by the driver. Derivative filters are then considered: the Bessel filter provides the best symmetry in its step response. A filter of same order and with negative real-poles is also used, exhibiting no overshoot nor ringing. For these reasons, the 'real-poles' filter would be preferred over the Bessel filter. The half-car model can be used to predict the change in normal load on the front and rear axle due to the pitching of the vehicle. The anticipated dynamic variation of the wheel load can be included in the inverse model, even though it is based on a quarter-car. Brake force distribution proportional to normal load is established. It provides more natural and simpler equations than a fixed force ratio strategy.
Chapelle, Dominique; Fragu, Marc; Mallet, Vivien; Moireau, Philippe
2013-01-01
International audience; We present the fundamental principles of data assimilation underlying the Verdandi library, and how they are articulated with the modular architecture of the library. This translates -- in particular -- into the definition of standardized interfaces through which the data assimilation library interoperates with the model simulation software and the so-called observation manager. We also survey various examples of data assimilation applied to the personalization of biop...
A linear model approach for ultrasonic inverse problems with attenuation and dispersion.
Carcreff, Ewen; Bourguignon, Sébastien; Idier, Jérôme; Simon, Laurent
2014-07-01
Ultrasonic inverse problems such as spike train deconvolution, synthetic aperture focusing, or tomography attempt to reconstruct spatial properties of an object (discontinuities, delaminations, flaws, etc.) from noisy and incomplete measurements. They require an accurate description of the data acquisition process. Dealing with frequency-dependent attenuation and dispersion is therefore crucial because both phenomena modify the wave shape as the travel distance increases. In an inversion context, this paper proposes to exploit a linear model of ultrasonic data taking into account attenuation and dispersion. The propagation distance is discretized to build a finite set of radiation impulse responses. Attenuation is modeled with a frequency power law and then dispersion is computed to yield physically consistent responses. Using experimental data acquired from attenuative materials, this model outperforms the standard attenuation-free model and other models of the literature. Because of model linearity, robust estimation methods can be implemented. When matched filtering is employed for single echo detection, the model that we propose yields precise estimation of the attenuation coefficient and of the sound velocity. A thickness estimation problem is also addressed through spike deconvolution, for which the proposed model also achieves accurate results.
2012-03-22
of-the-art inversion techniques suffer from poor resolution and nonuniqueness , especially when a single surface-wave mode is used (Huang et al...seismic analyses and to provide adequate starting models for 3D waveform inversion approaches. ACKNOWLEDGEMENTS We thank the scientists, engineers
Shifman, Aaron R; Longtin, André; Lewis, John E
2015-10-30
Identifying and understanding the current sources that give rise to bioelectric fields is a fundamental problem in the biological sciences. It is very difficult, for example, to attribute the time-varying features of an electroencephalogram recorded from the head surface to the neural activity of specific brain areas; model systems can provide important insight into such problems. Some species of fish actively generate an oscillating (c. 1000 Hz) quasi-dipole electric field to communicate and sense their environment in the dark. A specialized electric organ comprises neuron-like cells whose collective signal underlies this electric field. As a step towards understanding the detailed biophysics of signal generation in these fish, we use an anatomically-detailed finite-element modelling approach to reverse-engineer the electric organ signal over one oscillation cycle. We find that the spatiotemporal profile of current along the electric organ constitutes a travelling wave that is well-described by two spatial Fourier components varying in time. The conduction velocity of this wave is faster than action potential conduction in any known neuronal axon (>200 m/s), suggesting that the spatiotemporal features of high-frequency electric organ discharges are not constrained by the conduction velocities of spinal neuron pathways.
Directory of Open Access Journals (Sweden)
Susan L Campbell
2014-12-01
Full Text Available Cortical dysplasia is associated with intractable epilepsy and developmental delay in young children. Recent work with the rat freeze-induced focal cortical dysplasia (FCD model has demonstrated that hyperexcitability in the dysplastic cortex is due in part to higher levels of extracellular glutamate. Astrocyte glutamate transporters play a pivotal role in cortical maintaining extracellular glutamate concentrations. Here we examined the function of astrocytic glutamate transporters in a FCD model in rats. Neocortical freeze lesions were made in postnatal day (PN 1 rat pups and whole cell electrophysiological recordings and biochemical studies were performed at PN 21-28. Synaptically evoked glutamate transporter currents in astrocytes showed a near 10-fold reduction in amplitude compared to sham operated controls. Astrocyte glutamate transporter currents from lesioned animals were also significantly reduced when challenged exogenously applied glutamate. Reduced astrocytic glutamate transport clearance contributed to increased NMDA receptor-mediated current decay kinetics in lesioned animals. The electrophysiological profile of astrocytes in the lesion group was also markedly changed compared to sham operated animals. Control astrocytes demonstrate large-amplitude linear leak currents in response to voltage-steps whereas astrocytes in lesioned animals demonstrated significantly smaller voltage-activated inward and outward currents. Significant decreases in astrocyte resting membrane potential and increases in input resistance were observed in lesioned animals. However, Western blotting, immunohistochemistry and quantitative PCR demonstrated no differences in the expression of the astrocytic glutamate transporter GLT-1 in lesioned animals relative to controls. These data suggest that, in the absence of changes in protein or mRNA expression levels, functional changes in astrocytic glutamate transporters contribute to neuronal hyperexcitability in
Eguchi, Akihiro; Neymotin, Samuel A; Stringer, Simon M
2014-01-01
Although many computational models have been proposed to explain orientation maps in primary visual cortex (V1), it is not yet known how similar clusters of color-selective neurons in macaque V1/V2 are connected and develop. In this work, we address the problem of understanding the cortical processing of color information with a possible mechanism of the development of the patchy distribution of color selectivity via computational modeling. Each color input is decomposed into a red, green, and blue representation and transmitted to the visual cortex via a simulated optic nerve in a luminance channel and red-green and blue-yellow opponent color channels. Our model of the early visual system consists of multiple topographically-arranged layers of excitatory and inhibitory neurons, with sparse intra-layer connectivity and feed-forward connectivity between layers. Layers are arranged based on anatomy of early visual pathways, and include a retina, lateral geniculate nucleus, and layered neocortex. Each neuron in the V1 output layer makes synaptic connections to neighboring neurons and receives the three types of signals in the different channels from the corresponding photoreceptor position. Synaptic weights are randomized and learned using spike-timing-dependent plasticity (STDP). After training with natural images, the neurons display heightened sensitivity to specific colors. Information-theoretic analysis reveals mutual information between particular stimuli and responses, and that the information reaches a maximum with fewer neurons in the higher layers, indicating that estimations of the input colors can be done using the output of fewer cells in the later stages of cortical processing. In addition, cells with similar color receptive fields form clusters. Analysis of spiking activity reveals increased firing synchrony between neurons when particular color inputs are presented or removed (ON-cell/OFF-cell).
DEFF Research Database (Denmark)
Khan, Ahmad Raza; Chuhutin, Andrey; Wiborg, Ove
2016-01-01
Abstract Depression is one of the leading causes of disability worldwide. Immense heterogeneity in symptoms of depression causes difficulty in diagnosis, and to date, there are no established biomarkers or imaging methods to examine depression. Unpredictable chronic mild stress (CMS) induced...... anhedonia is considered to be a realistic model of depression in studies of animal subjects. Stereological and neuronal tracing techniques have demonstrated persistent remodeling of microstructure in hippocampus, prefrontal cortex and amygdala of CMS brains. Recent developments in diffusion MRI (d...... changes in CMS rat brains and these parameters might have value in clinical diagnosis of depression and for evaluation of treatment efficacy....
Directory of Open Access Journals (Sweden)
Bagher Bayat
2016-07-01
Full Text Available The aim of this study was to follow the response to drought stress in a Poa pratensis canopy exposed to various levels of soil moisture deficit. We tracked the changes in the canopy reflectance (450–2450 nm and retrieved vegetation properties (Leaf Area Index (LAI, leaf chlorophyll content (Cab, leaf water content (Cw, leaf dry matter content (Cdm and senescent material (Cs during a drought episode. Spectroscopic techniques and radiative transfer model (RTM inversion were employed to monitor the gradual manifestation of drought effects in a laboratory setting. Plots of 21 cm × 14.5 cm surface area with Poa pratensis plants that formed a closed canopy were divided into a well-watered control group and a group subjected to water stress for 36 days. In a regular weekly schedule, canopy reflectance and destructive measurements of LAI and Cab were taken. Spectral analysis indicated the first sign of stress after 4–5 days from the start of the experiment near the water absorption bands (at 1930 nm, 1440 nm and in the red (at 675 nm. Spectroscopic techniques revealed plant stress up to 6 days earlier than visual inspection. Of the water stress-related vegetation indices, the response of Normalized Difference Water Index (NDWI_1241 and Normalized Photochemical Reflectance Index (PRI_norm were significantly stronger in the stressed group than the control. To observe the effects of stress on grass properties during the drought episode, we used the RTMo (RTM of solar and sky radiation model inversion by means of an iterative optimization approach. The performance of the model inversion was assessed by calculating R2 and the Normalized Root Mean Square Error (RMSE between retrieved and measured LAI (R2 = 0.87, NRMSE = 0.18 and Cab (R2 = 0.74, NRMSE = 0.15. All parameters retrieved by model inversion co-varied with soil moisture deficit. However, the first strong sign of water stress on the retrieved grass properties was detected as a change of Cw
Improving atomic force microscopy imaging by a direct inverse asymmetric PI hysteresis model.
Wang, Dong; Yu, Peng; Wang, Feifei; Chan, Ho-Yin; Zhou, Lei; Dong, Zaili; Liu, Lianqing; Li, Wen Jung
2015-02-03
A modified Prandtl-Ishlinskii (PI) model, referred to as a direct inverse asymmetric PI (DIAPI) model in this paper, was implemented to reduce the displacement error between a predicted model and the actual trajectory of a piezoelectric actuator which is commonly found in AFM systems. Due to the nonlinearity of the piezoelectric actuator, the standard symmetric PI model cannot precisely describe the asymmetric motion of the actuator. In order to improve the accuracy of AFM scans, two series of slope parameters were introduced in the PI model to describe both the voltage-increase-loop (trace) and voltage-decrease-loop (retrace). A feedforward controller based on the DIAPI model was implemented to compensate hysteresis. Performance of the DIAPI model and the feedforward controller were validated by scanning micro-lenses and standard silicon grating using a custom-built AFM.
Improving Atomic Force Microscopy Imaging by a Direct Inverse Asymmetric PI Hysteresis Model
Directory of Open Access Journals (Sweden)
Dong Wang
2015-02-01
Full Text Available A modified Prandtl–Ishlinskii (PI model, referred to as a direct inverse asymmetric PI (DIAPI model in this paper, was implemented to reduce the displacement error between a predicted model and the actual trajectory of a piezoelectric actuator which is commonly found in AFM systems. Due to the nonlinearity of the piezoelectric actuator, the standard symmetric PI model cannot precisely describe the asymmetric motion of the actuator. In order to improve the accuracy of AFM scans, two series of slope parameters were introduced in the PI model to describe both the voltage-increase-loop (trace and voltage-decrease-loop (retrace. A feedforward controller based on the DIAPI model was implemented to compensate hysteresis. Performance of the DIAPI model and the feedforward controller were validated by scanning micro-lenses and standard silicon grating using a custom-built AFM.
Martin, Adriana A. T.; Tomasini, Michael; Kholodovych, Vladyslav; Gu, Li; Sommerfeld, Sven Daniel; Uhrich, Kathryn E.; Murthy, N. Sanjeeva; Welsh, William J.; Moghe, Prabhas V.
2015-01-01
The design and synthesis of enhanced membrane-intercalating biomaterials for drug delivery or vascular membrane targeting is currently challenged by the lack of screening and prediction tools. The present work demonstrates the generation of a Quantitative Structural Activity Relationship model (QSAR) to make a priori predictions. Amphiphilic macromolecules (AMs) “stealth lipids” built on aldaric and uronic acids frameworks attached to poly(ethylene glycol) (PEG) polymer tails were developed to form self-assembling micelles. In the present study, a defined set of novel AM structures were investigated in terms of their binding to lipid membrane bilayers using Quartz Crystal Microbalance with Dissipation (QCM-D) experiments coupled with computational coarse-grained molecular dynamics (CG MD) and all-atom MD (AA MD) simulations. The CG MD simulations capture the insertion dynamics of the AM lipophilic backbones into the lipid bilayer with the PEGylated tail directed into bulk water. QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface. Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo. More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials. PMID:25855953
Institute of Scientific and Technical Information of China (English)
ZHOU Tao; SHI PeiJun; HUI DaFeng; LUO YiQi
2009-01-01
Temperature sensitivity of soil respiration (Q_(10)) is an important parameter in modeling the effects of global warming on ecosystem carbon release. Experimental studies of soil respiration have ubiquitously indicated that Q_(10) has high spatial heterogeneity. However, most biogeochemical models still use a constant Q_(10) in projecting future climate change and no spatial pattern of Q_(10) values at large scales has been derived. In this study, we conducted an inverse modeling analysis to retrieve the spatial pattern of Q_(10) in China at 8 km spatial resolution by assimilating data of soil organic carbon into a process-based terrestrial carbon model (CASA model). The results indicate that the optimized Q_(10) values are spatially heterogeneous and consistent to the values derived from soil respiration observations. The mean Q_(10). values of different soil types range from 1.09 to 2.38, with the highest value in volcanic soil,and the lowest value in cold brown calcic soil. The spatial pattern of Q_(10) is related to environmental factors, especially precipitation and top soil organic carbon content. This study demonstrates that inverse modeling is a useful tool in deriving the spatial pattern of Q_(10) at large scales, with which being incorporated into biogeochemical models, uncertainty in the projection of future carbon dynamics could be potentially reduced.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Temperature sensitivity of soil respiration (Q10) is an important parameter in modeling the effects of global warming on ecosystem carbon release. Experimental studies of soil respiration have ubiquitously indicated that Q10 has high spatial heterogeneity. However, most biogeochemical models still use a constant Q10 in projecting future climate change and no spatial pattern of Q10 values at large scales has been derived. In this study, we conducted an inverse modeling analysis to retrieve the spatial pattern of Q10 in China at 8 km spatial resolution by assimilating data of soil organic carbon into a proc-ess-based terrestrial carbon model (CASA model). The results indicate that the optimized Q10 values are spatially heterogeneous and consistent to the values derived from soil respiration observations. The mean Q10 values of different soil types range from 1.09 to 2.38, with the highest value in volcanic soil, and the lowest value in cold brown calcic soil. The spatial pattern of Q10 is related to environmental factors, especially precipitation and top soil organic carbon content. This study demonstrates that inverse modeling is a useful tool in deriving the spatial pattern of Q10 at large scales, with which being incorporated into biogeochemical models, uncertainty in the projection of future carbon dynamics could be potentially reduced.
Quantum states for quantum processes: A toy model for ammonia inversion spectra
Energy Technology Data Exchange (ETDEWEB)
Arteca, Gustavo A. [Departement de Chimie et Biochimie and Biomolecular Sciences Programme, Laurentian University, Ramsey Lake Road, Sudbury, Ontario, Canada P3E 2C6 (Canada); Department of Physical Chemistry, Uppsala University, A ring ngstroemlaboratoriet, Box 259, S-751 05 Uppsala (Sweden); Tapia, O. [Department of Physical Chemistry, Uppsala University, A ring ngstroemlaboratoriet, Box 259, S-751 05 Uppsala (Sweden)
2011-07-15
Chemical transformations are viewed here as quantum processes modulated by external fields, that is, as shifts in reactant to product amplitudes within a quantum state represented by a linear (coherent) superposition of electronuclear basis functions; their electronic quantum numbers identify the ''chemical species.'' This basis set can be mapped from attractors built from a unique electronic configurational space that is invariant with respect to the nuclear geometry. In turn, the quantum numbers that label these basis functions and the semiclassical potentials for the electronic attractors may be used to derive reaction coordinates to monitor progress as a function of the applied field. A generalization of Feynman's three-state model for the ammonia inversion process illustrates the scheme; to enforce symmetry for the entire inversion process model and ensure invariance with respect to nuclear configurations, the three attractors and their basis functions are computed with a grid of fixed floating Gaussian functions. The external-field modulation of the effective inversion barrier is discussed within this conceptual approach. This analysis brings the descriptions of chemical processes near modern technologies that employ molecules to encode information by means of confinement and external fields.
Truong-Loi, My-Linh; Saatchi, Sassan; Jaruwatanadilok, Sermsak
2012-01-01
A semi-empirical algorithm for the retrieval of soil moisture, root mean square (RMS) height and biomass from polarimetric SAR data is explained and analyzed in this paper. The algorithm is a simplification of the distorted Born model. It takes into account the physical scattering phenomenon and has three major components: volume, double-bounce and surface. This simplified model uses the three backscattering coefficients ( sigma HH, sigma HV and sigma vv) at low-frequency (P-band). The inversion process uses the Levenberg-Marquardt non-linear least-squares method to estimate the structural parameters. The estimation process is entirely explained in this paper, from initialization of the unknowns to retrievals. A sensitivity analysis is also done where the initial values in the inversion process are varying randomly. The results show that the inversion process is not really sensitive to initial values and a major part of the retrievals has a root-mean-square error lower than 5% for soil moisture, 24 Mg/ha for biomass and 0.49 cm for roughness, considering a soil moisture of 40%, roughness equal to 3cm and biomass varying from 0 to 500 Mg/ha with a mean of 161 Mg/ha
Model-based elastography: a survey of approaches to the inverse elasticity problem
Doyley, M M
2012-01-01
Elastography is emerging as an imaging modality that can distinguish normal versus diseased tissues via their biomechanical properties. This article reviews current approaches to elastography in three areas — quasi-static, harmonic, and transient — and describes inversion schemes for each elastographic imaging approach. Approaches include: first-order approximation methods; direct and iterative inversion schemes for linear elastic; isotropic materials; and advanced reconstruction methods for recovering parameters that characterize complex mechanical behavior. The paper’s objective is to document efforts to develop elastography within the framework of solving an inverse problem, so that elastography may provide reliable estimates of shear modulus and other mechanical parameters. We discuss issues that must be addressed if model-based elastography is to become the prevailing approach to quasi-static, harmonic, and transient elastography: (1) developing practical techniques to transform the ill-posed problem with a well-posed one; (2) devising better forward models to capture the transient behavior of soft tissue; and (3) developing better test procedures to evaluate the performance of modulus elastograms. PMID:22222839
Quantum states for quantum processes: A toy model for ammonia inversion spectra
Arteca, Gustavo A.; Tapia, O.
2011-07-01
Chemical transformations are viewed here as quantum processes modulated by external fields, that is, as shifts in reactant to product amplitudes within a quantum state represented by a linear (coherent) superposition of electronuclear basis functions; their electronic quantum numbers identify the “chemical species.” This basis set can be mapped from attractors built from a unique electronic configurational space that is invariant with respect to the nuclear geometry. In turn, the quantum numbers that label these basis functions and the semiclassical potentials for the electronic attractors may be used to derive reaction coordinates to monitor progress as a function of the applied field. A generalization of Feynman's three-state model for the ammonia inversion process illustrates the scheme; to enforce symmetry for the entire inversion process model and ensure invariance with respect to nuclear configurations, the three attractors and their basis functions are computed with a grid of fixed floating Gaussian functions. The external-field modulation of the effective inversion barrier is discussed within this conceptual approach. This analysis brings the descriptions of chemical processes near modern technologies that employ molecules to encode information by means of confinement and external fields.
Jacquin, Hugo; Shakhnovich, Eugene; Cocco, Simona; Monasson, Rémi
2016-01-01
Inverse statistical approaches to determine protein structure and function from Multiple Sequence Alignments (MSA) are emerging as powerful tools in computational biology. However the underlying assumptions of the relationship between the inferred effective Potts Hamiltonian and real protein structure and energetics remain untested so far. Here we use lattice protein model (LP) to benchmark those inverse statistical approaches. We build MSA of highly stable sequences in target LP structures, and infer the effective pairwise Potts Hamiltonians from those MSA. We find that inferred Potts Hamiltonians reproduce many important aspects of 'true' LP structures and energetics. Careful analysis reveals that effective pairwise couplings in inferred Potts Hamiltonians depend not only on the energetics of the native structure but also on competing folds; in particular, the coupling values reflect both positive design (stabilization of native conformation) and negative design (destabilization of competing folds). In addi...
Realizing the supersymmetric inverse seesaw model in the framework of R-parity violation
Pires, C A de S; da Silva, P S Rodrigues
2016-01-01
If, on one hand, the inverse seesaw is the paradigm of TeV scale seesaw mechanism, on the other it is a challenge to find scenarios capable of realizing it. In this work we propose a scenario, based on the framework of R-parity violation, that realizes minimally the supersymmetric inverse seesaw mechanism. In it the energy scale parameters involved in the mechanism are recognized as the vacuum expectation values of the scalars that compose the superfields $\\hat N^C$ and $\\hat S$. We develop also the scalar sector of the model and show that the Higgs mass receives a new tree-level contribution that, when combined with the standard contribution plus loop correction, is capable of attaining $125$GeV without resort to heavy stops.
Realizing the supersymmetric inverse seesaw model in the framework of R-parity violation
de S. Pires, C. A.; Rodrigues, J. G.; Rodrigues da Silva, P. S.
2016-08-01
If, on one hand, the inverse seesaw is the paradigm of TeV scale seesaw mechanism, on the other it is a challenge to find scenarios capable of realizing it. In this work we propose a scenario, based on the framework of R-parity violation, that realizes minimally the supersymmetric inverse seesaw mechanism. In it the energy scale parameters involved in the mechanism are recognized as the vacuum expectation values of the scalars that compose the singlet superfields NˆC and S ˆ . We develop also the scalar sector of the model and show that the Higgs mass receives a new tree-level contribution that, when combined with the standard contribution plus loop correction, is capable of attaining 125 GeV without resort to heavy stops.
Inverse-model-based cuffless blood pressure estimation using a single photoplethysmography sensor.
Suzuki, Arata
2015-07-01
This paper proposes an inverse-model-based cuffless method for estimating blood pressure using a single photoplethysmography sensor. The proposed method, which is based on the relationship between blood pressure and the features of pulse waves, employs an inverse estimation and uses the blood pressure as the explanatory variable. Using this method, the blood pressure can be estimated with high accuracy even in situations where the pulse wave features are scattered, as the method uses the dynamic signal-to-noise ratio of the Taguchi method. In order to verify the effectiveness of the proposed method, we employed it to measure the systolic blood pressure. It could be confirmed that the estimation accuracy of the proposed method is higher than that of similar methods.
Learning the Inverse Model of the Dynamics of a Robot Leg by Auto-imitation
Kalveram, Karl Theodor; Seyfarth, Andre
Walking, running and hopping are based on self-stabilizing oscillatory activity. In contrast, aiming movements serve to direct a limb to a desired location and demand a quite different manner of control which also includes learning the physical parameters of that limb. The paper is concerned with the question how reaching a goal can be integrated into locomotion. A prerequisite of piecing together both types of control is the acquisition of a model of the limb’s inverse dynamics. To test whether auto-imitation, a biologically inspired learning algorithm, can solve this problem, we build a motor driven device with a two-segmented arm. A preliminary study revealed that at least the forearm — with the upper arm fixed — can be made controllable by this method we called “auto-imitatively adaptable inverse control”.
Forward and inverse effects of the complete electrode model in neonatal EEG.
Pursiainen, S; Lew, S; Wolters, C H
2017-03-01
This paper investigates finite element method-based modeling in the context of neonatal electroencephalography (EEG). In particular, the focus lies on electrode boundary conditions. We compare the complete electrode model (CEM) with the point electrode model (PEM), which is the current standard in EEG. In the CEM, the voltage experienced by an electrode is modeled more realistically as the integral average of the potential distribution over its contact surface, whereas the PEM relies on a point value. Consequently, the CEM takes into account the subelectrode shunting currents, which are absent in the PEM. In this study, we aim to find out how the electrode voltage predicted by these two models differ, if standard size electrodes are attached to a head of a neonate. Additionally, we study voltages and voltage variation on electrode surfaces with two source locations: 1) next to the C6 electrode and 2) directly under the Fz electrode and the frontal fontanel. A realistic model of a neonatal head, including a skull with fontanels and sutures, is used. Based on the results, the forward simulation differences between CEM and PEM are in general small, but significant outliers can occur in the vicinity of the electrodes. The CEM can be considered as an integral part of the outer head model. The outcome of this study helps understanding volume conduction of neonatal EEG, since it enlightens the role of advanced skull and electrode modeling in forward and inverse computations.NEW & NOTEWORTHY The effect of the complete electrode model on electroencephalography forward and inverse computations is explored. A realistic neonatal head model, including a skull structure with fontanels and sutures, is used. The electrode and skull modeling differences are analyzed and compared with each other. The results suggest that the complete electrode model can be considered as an integral part of the outer head model. To achieve optimal source localization results, accurate electrode
Khan, Ahmad Raza; Chuhutin, Andrey; Wiborg, Ove; Kroenke, Christopher D; Nyengaard, Jens R; Hansen, Brian; Jespersen, Sune Nørhøj
2016-11-15
Depression is one of the leading causes of disability worldwide. Immense heterogeneity in symptoms of depression causes difficulty in diagnosis, and to date, there are no established biomarkers or imaging methods to examine depression. Unpredictable chronic mild stress (CMS) induced anhedonia is considered to be a realistic model of depression in studies of animal subjects. Stereological and neuronal tracing techniques have demonstrated persistent remodeling of microstructure in hippocampus, prefrontal cortex and amygdala of CMS brains. Recent developments in diffusion MRI (d-MRI) analyses, such as neurite density and diffusion kurtosis imaging (DKI), are able to capture microstructural changes and are considered to be robust tools in preclinical and clinical imaging. The present study utilized d-MRI analyzed with a neurite density model and the DKI framework to investigate microstructure in the hippocampus, prefrontal cortex, caudate putamen and amygdala regions of CMS rat brains by comparison to brains from normal controls. To validate findings of CMS induced microstructural alteration, histology was performed to determine neurite, nuclear and astrocyte density. d-MRI based neurite density and tensor-based mean kurtosis (MKT) were significantly higher, while mean diffusivity (MD), extracellular diffusivity (Deff) and intra-neurite diffusivity(DL) were significantly lower in the amygdala of CMS rat brains. Deff was also significantly lower in the hippocampus and caudate putamen in stressed groups. Histological neurite density corroborated the d-MRI findings in the amygdala and reductions in nuclear and astrocyte density further buttressed the d-MRI results. The present study demonstrated that the d-MRI based neurite density and MKT can reveal specific microstructural changes in CMS rat brains and these parameters might have value in clinical diagnosis of depression and for evaluation of treatment efficacy.
The mathematical biophysics of Nicolas Rashevsky.
Cull, Paul
2007-04-01
N. Rashevsky (1899-1972) was one of the pioneers in the application of mathematics to biology. With the slogan: mathematical biophysics : biology :: mathematical physics ; physics, he proposed the creation of a quantitative theoretical biology. Here, we will give a brief biography, and consider Rashevsky's contributions to mathematical biology including neural nets and relational biology. We conclude that Rashevsky was an important figure in the introduction of quantitative models and methods into biology.
Dettmer, Jan; Molnar, Sheri; Steininger, Gavin; Dosso, Stan E.; Cassidy, John F.
2012-02-01
This paper applies a general trans-dimensional Bayesian inference methodology and hierarchical autoregressive data-error models to the inversion of microtremor array dispersion data for shear wave velocity (vs) structure. This approach accounts for the limited knowledge of the optimal earth model parametrization (e.g. the number of layers in the vs profile) and of the data-error statistics in the resulting vs parameter uncertainty estimates. The assumed earth model parametrization influences estimates of parameter values and uncertainties due to different parametrizations leading to different ranges of data predictions. The support of the data for a particular model is often non-unique and several parametrizations may be supported. A trans-dimensional formulation accounts for this non-uniqueness by including a model-indexing parameter as an unknown so that groups of models (identified by the indexing parameter) are considered in the results. The earth model is parametrized in terms of a partition model with interfaces given over a depth-range of interest. In this work, the number of interfaces (layers) in the partition model represents the trans-dimensional model indexing. In addition, serial data-error correlations are addressed by augmenting the geophysical forward model with a hierarchical autoregressive error model that can account for a wide range of error processes with a small number of parameters. Hence, the limited knowledge about the true statistical distribution of data errors is also accounted for in the earth model parameter estimates, resulting in more realistic uncertainties and parameter values. Hierarchical autoregressive error models do not rely on point estimates of the model vector to estimate data-error statistics, and have no requirement for computing the inverse or determinant of a data-error covariance matrix. This approach is particularly useful for trans-dimensional inverse problems, as point estimates may not be representative of the
Hanuschkin, A; Ganguli, S; Hahnloser, R H R
2013-01-01
Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli.
Directory of Open Access Journals (Sweden)
Alexander eHanuschkin
2013-06-01
Full Text Available Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: Random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, they allow for imitating arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions.Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird’s own song
Inverse modeling of dynamic nonequilibrium in water flow with an effective approach
Diamantopoulos, E.; Iden, S. C.; Durner, W.
2012-03-01
Observations of water flow in unsaturated soils often show "dynamic effects," indicated by nonequilibrium between water contents and water potential, a phenomenon that cannot be modeled with the Richards equation. The objective of this article is to formulate an effective process description of dynamic nonequilibrium flow in variably saturated soil which is both flexible enough to match experimental observations and as parsimonious as possible to allow unique parameter estimation by inverse modeling. In the conceptual model, water content is partitioned into two fractions. Water in one fraction is in equilibrium with the pressure head, whereas water in the second fraction is in nonequilibrium, described by the kinetic equilibration approach of Ross and Smettem (2000). Between the two fractions an instantaneous equilibration of the pressure head is assumed. The new model, termed the dual-fraction nonequilibrium model, requires only one additional parameter compared to the nonequilibrium approach of Ross and Smettem. We tested the model with experimental data from multistep outflow experiments conducted on two soils and compared it to the Richards equation, the nonequilibrium model of Ross and Smettem, and the dual-porosity model of Philip (1968). The experimental data were evaluated by inverse modeling using a robust Markov chain Monte Carlo sampler. The results show that the proposed model is superior to the Richards equation and the Ross and Smettem model in describing dynamic nonequilibrium effects occurring in multistep outflow experiments. The three popular model selection criteria (Akaike information criterion, Bayesian information criterion, and deviance information criterion) all favored the new model because of its smaller number of parameters.
Energy Technology Data Exchange (ETDEWEB)
Moskvin, A S [Ural State University, Ekaterinburg, 620083 (Russian Federation); Philipiev, M P [Ural State University, Ekaterinburg, 620083 (Russian Federation); Solovyova, O E [Ural State University, Ekaterinburg, 620083 (Russian Federation); Markhasin, V S [Institute of Immunology and Physiology, Ekaterinburg, 620219 (Russian Federation)
2005-01-01
Theory of photo-induced phase transitions has been adapted to describe the cooperative dynamics of the lattice of ryanodine receptors/channels (RyR) in cardiac muscle which regulate the release of the intracellular activator calcium from calcium stores in the sarcoplasmic reticulum (SR) by a process of Ca{sup 2+}-induced Ca{sup 2+} release (CICR). We introduce two main degrees of freedom for RyR channel, fast electronic and slow conformational ones. The RyR lattice response to the L-type channel triggering evolves due to a nucleation process with a step-by-step domino-like opening of RyR channels. Typical mode of RyR lattice functioning in a CICR process implies the fractional release with a robust termination due to the depletion of SR with a respective change in effective conformational strain. The SR overload leads to an unconventional auto-oscillation regime with a spontaneous calcium release. The model is believed to consistently describe the main features of CICR, that is its gradedness, coupled gating, irreversibility, inactivation/adaptation, and spark termination.
Constraining the rheology of the lithosphere and upper mantle with geodynamic inverse modelling
Kaus, Boris; Baumann, Tobias
2016-04-01
The rheology of the lithosphere is of key importance for the physics of the lithosphere. Yet, it is probably the most uncertain parameter in geodynamics as experimental rock rheologies have to be extrapolated to geological conditions and as existing geophysical methods such as EET estimations make simplifying assumptions about the structure of the lithosphere. In many geologically interesting regions, such as the Alps, Andes or Himalaya, we actually have a significant amount of data already and as a result the geometry of the lithosphere is quite well constrained. Yet, knowing the geometry is only one part of the story, as we also need to have an accurate knowledge on the rheology and temperature structure of the lithosphere. Here, we discuss a relatively new method that we developed over the last few years, which is called geodynamic inversion. The basic principle of the method is simple: we compile available geophysical data into a realistic geometric model of the lithosphere and incorporate that into a thermo-mechanical numerical model of lithospheric deformation. In order to do so, we have to know the temperature structure, the density and the (nonlinear) rheological parameters for various parts of the lithosphere (upper crust, upper mantle, etc.). Rather than fixing these parameters we assume that they are all uncertain. This is used as a priori information to formulate a Bayesian inverse problem that employs topography, gravity, horizontal and vertical surface velocities to invert for the unknown material parameters and temperature structure. In order to test the general methodology, we first perform a geodynamic inversion of a synthetic forward model of intra-oceanic subduction with known parameters. This requires solving an inverse problem with 14-16 parameters, depending on whether temperature is assumed to be known or not. With the help of a massively parallel direct-search combined with a Markov Chain Monte Carlo method, solving the inverse problem
Non-Abelian {SU}{(3)}_{k} anyons: inversion identities for higher rank face models
Frahm, Holger; Karaiskos, Nikos
2015-12-01
The spectral problem for an integrable system of particles satisfying the fusion rules of {SU}{(3)}k is expressed in terms of exact inversion identities satisfied by the commuting transfer matrices of the integrable fused {A}2(1) interaction round a face model of Jimbo, Miwa and Okado. The identities are proven using local properties of the Boltzmann weights, in particular the Yang-Baxter equation and unitarity. They are closely related to the consistency conditions for the construction of eigenvalues obtained in the separation of variables approach to integrable vertex models.
Rafique, Rashad; Fienen, Michael N.; Parkin, Timothy B.; Anex, Robert P.
2013-01-01
DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameterized through a traditional “trial and error” approach and has not been calibrated using statistical inverse modelling (i.e. algorithmic parameter estimation). The aim of this study is to establish and demonstrate a procedure for calibration of DayCent to improve estimation of GHG emissions. We coupled DayCent with the parameter estimation (PEST) software for inverse modelling. The PEST software can be used for calibration through regularized inversion as well as model sensitivity and uncertainty analysis. The DayCent model was analysed and calibrated using N2O flux data collected over 2 years at the Iowa State University Agronomy and Agricultural Engineering Research Farms, Boone, IA. Crop year 2003 data were used for model calibration and 2004 data were used for validation. The optimization of DayCent model parameters using PEST significantly reduced model residuals relative to the default DayCent parameter values. Parameter estimation improved the model performance by reducing the sum of weighted squared residual difference between measured and modelled outputs by up to 67 %. For the calibration period, simulation with the default model parameter values underestimated mean daily N2O flux by 98 %. After parameter estimation, the model underestimated the mean daily fluxes by 35 %. During the validation period, the calibrated model reduced sum of weighted squared residuals by 20 % relative to the default simulation. Sensitivity analysis performed provides important insights into the model structure providing guidance for model improvement.
Schuurman, N K; Grasman, R P P P; Hamaker, E L
2016-01-01
Multilevel autoregressive models are especially suited for modeling between-person differences in within-person processes. Fitting these models with Bayesian techniques requires the specification of prior distributions for all parameters. Often it is desirable to specify prior distributions that have negligible effects on the resulting parameter estimates. However, the conjugate prior distribution for covariance matrices-the Inverse-Wishart distribution-tends to be informative when variances are close to zero. This is problematic for multilevel autoregressive models, because autoregressive parameters are usually small for each individual, so that the variance of these parameters will be small. We performed a simulation study to compare the performance of three Inverse-Wishart prior specifications suggested in the literature, when one or more variances for the random effects in the multilevel autoregressive model are small. Our results show that the prior specification that uses plug-in ML estimates of the variances performs best. We advise to always include a sensitivity analysis for the prior specification for covariance matrices of random parameters, especially in autoregressive models, and to include a data-based prior specification in this analysis. We illustrate such an analysis by means of an empirical application on repeated measures data on worrying and positive affect.
A tensorial approach to the inversion of group-based phylogenetic models.
Sumner, Jeremy G; Jarvis, Peter D; Holland, Barbara R
2014-12-04
Hadamard conjugation is part of the standard mathematical armoury in the analysis of molecular phylogenetic methods. For group-based models, the approach provides a one-to-one correspondence between the so-called "edge length" and "sequence" spectrum on a phylogenetic tree. The Hadamard conjugation has been used in diverse phylogenetic applications not only for inference but also as an important conceptual tool for thinking about molecular data leading to generalizations beyond strictly tree-like evolutionary modelling. For general group-based models of phylogenetic branching processes, we reformulate the problem of constructing a one-one correspondence between pattern probabilities and edge parameters. This takes a classic result previously shown through use of Fourier analysis and presents it in the language of tensors and group representation theory. This derivation makes it clear why the inversion is possible, because, under their usual definition, group-based models are defined for abelian groups only. We provide an inversion of group-based phylogenetic models that can implemented using matrix multiplication between rectangular matrices indexed by ordered-partitions of varying sizes. Our approach provides additional context for the construction of phylogenetic probability distributions on network structures, and highlights the potential limitations of restricting to group-based models in this setting.
Hybrid modeling of spatial continuity for application to numerical inverse problems
Friedel, Michael J.; Iwashita, Fabio
2013-01-01
A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km2 Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km2 fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km2 transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.
Institute of Scientific and Technical Information of China (English)
Jianzhong Zhang; Han Liu; Zhihui Zou; Zhonglai Huang
2015-01-01
A velocity model is an important factor influencing microseismic event locations. We re-view the velocity modeling and inversion techniques for locating microseismic events in exploration for unconventional oil and gas reservoirs. We first describe the geological and geophysical characteristics of reservoir formations related to hydraulic fracturing in heterogeneity, anisotropy, and variability, then discuss the influences of velocity estimation, anisotropy model, and their time-lapse changes on the accuracy in determining microseismic event locations, and then survey some typical methods for build-ing velocity models in locating event locations. We conclude that the three tangled physical attributes of reservoirs make microseismic monitoring very challenging. The uncertainties in velocity model and ig-noring its anisotropies and its variations in hydraulic fracturing can cause systematic mislocations of microseismic events which are unacceptable in microseismic monitoring. So, we propose some potential ways for building accurate velocity models.
Pinker, Franziska; Schelcher, Cédric; Fernandez-Millan, Pablo; Gobert, Anthony; Birck, Catherine; Thureau, Aurélien; Roblin, Pierre; Giegé, Philippe; Sauter, Claude
2017-08-25
RNase P is a universal enzyme that removes 5' leader sequences from tRNA precursors. The enzyme is therefore essential for maturation of functional tRNAs and mRNA translation. RNase P represents a unique example of an enzyme that can occur either as ribonucleoprotein or as protein alone. The latter form of the enzyme, called protein-only RNase P (PRORP), is widespread in eukaryotes in which it can provide organellar or nuclear RNase P activities. Here, we have focused on Arabidopsis nuclear PRORP2 and its interaction with tRNA substrates. Affinity measurements helped assess the respective importance of individual pentatricopeptide repeat motifs in PRORP2 for RNA binding. We characterized the PRORP2 structure by X-ray crystallography and by small-angle X-ray scattering in solution as well as that of its complex with a tRNA precursor by small-angle X-ray scattering. Of note, our study reports the first structural data of a PRORP-tRNA complex. Combined with complementary biochemical and biophysical analyses, our structural data suggest that PRORP2 undergoes conformational changes to accommodate its substrate. In particular, the catalytic domain and the RNA-binding domain can move around a central hinge. Altogether, this work provides a refined model of the PRORP-tRNA complex that illustrates how protein-only RNase P enzymes specifically bind tRNA and highlights the contribution of protein dynamics to achieve this specific interaction. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
A Network Inversion Filter combining GNSS and InSAR for tectonic slip modeling
Bekaert, D. P. S.; Segall, P.; Wright, T. J.; Hooper, A. J.
2016-03-01
Studies of the earthquake cycle benefit from long-term time-dependent slip modeling, as it can be a powerful means to improve our understanding on the interaction of earthquake cycle processes such as interseismic, coseismic, post seismic, and aseismic slip. Observations from Interferometric Synthetic Aperture Radar (InSAR) allow us to model slip at depth with a higher spatial resolution than when using Global Navigation Satellite Systems (GNSS) alone. While the temporal resolution of InSAR has typically been limited, the recent fleet of SAR satellites including Sentinel-1, COSMO-SkyMED, and RADARSAT-2 permits the use of InSAR for time-dependent slip modeling at intervals of a few days when combined. With the vast amount of SAR data available, simultaneous data inversion of all epochs becomes challenging. Here we expanded the original network inversion filter to include InSAR observations of surface displacements in addition to GNSS. In the Network Inversion Filter (NIF) framework, geodetic observations are limited to those of a given epoch, with a stochastic model describing slip evolution over time. The combination of the Kalman forward filtering and backward smoothing allows all geodetic observations to constrain the complete observation period. Combining GNSS and InSAR allows modeling of time-dependent slip at unprecedented spatial resolution. We validate the approach with a simulation of the 2006 Guerrero slow slip event. We highlight the importance of including InSAR covariance information and demonstrate that InSAR provides an additional constraint on the spatial extent of the slow slip.
Energy Technology Data Exchange (ETDEWEB)
Xie, G.; Li, J.; Majer, E.; Zuo, D.
1998-07-01
This paper describes a new 3D parallel GILD electromagnetic (EM) modeling and nonlinear inversion algorithm. The algorithm consists of: (a) a new magnetic integral equation instead of the electric integral equation to solve the electromagnetic forward modeling and inverse problem; (b) a collocation finite element method for solving the magnetic integral and a Galerkin finite element method for the magnetic differential equations; (c) a nonlinear regularizing optimization method to make the inversion stable and of high resolution; and (d) a new parallel 3D modeling and inversion using a global integral and local differential domain decomposition technique (GILD). The new 3D nonlinear electromagnetic inversion has been tested with synthetic data and field data. The authors obtained very good imaging for the synthetic data and reasonable subsurface EM imaging for the field data. The parallel algorithm has high parallel efficiency over 90% and can be a parallel solver for elliptic, parabolic, and hyperbolic modeling and inversion. The parallel GILD algorithm can be extended to develop a high resolution and large scale seismic and hydrology modeling and inversion in the massively parallel computer.
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
This paper aims at constructing an emission source inversion model using a variational processing method and adaptive nudging scheme for the Community Multiscale Air Quality Model (CMAQ) based on satellite data to investigate the applicability of high resolution OMI (Ozone Monitoring Instrument) column concentration data for air quality forecasts over the North China. The results show a reasonable consistency and good correlation between the spatial distributions of NO2 from surface and OMI satellite measurements in both winter and summer. Such OMI products may be used to implement integrated variational analysis based on observation data on the ground. With linear and variational corrections made, the spatial distribution of OMI NO2 clearly revealed more localized distributing characteristics of NO2 concentration. With such information, emission sources in the southwest and southeast of North China are found to have greater impacts on air quality in Beijing. When the retrieved emission source inventory based on high-resolution OMI NO2 data was used, the coupled Weather Research Forecasting CMAQ model (WRF-CMAQ) performed significantly better in forecasting NO2 concentration level and its tendency as reflected by the more consistencies between the NO2 concentrations from surface observation and model result. In conclusion, satellite data are particularly important for simulating NO2 concentrations on urban and street-block scale. High-resolution OMI NO2 data are applicable for inversing NOx emission source inventory, assessing the regional pollution status and pollution control strategy, and improving the model forecasting results on urban scale.
A refinement of the emission data for Kola Peninsula based on inverse dispersion modelling
Prank, M.; Sofiev, M.; Denier van der Gon, H. A. C.; Kaasik, M.; Ruuskanen, T. M.; Kukkonen, J.
2010-06-01
The study reviews the emission estimates of sulphur oxides (SOx) and primary particulate matter (PM) from the major industrial sources of Kola Peninsula. Analysis of the disagreements between the existing emission inventories for the Kola region combined with forward and inverse ensemble dispersion modelling, analysis of observation time-series and model-measurement comparison showed that the emission of the Nikel non-ferrous metallurgy plant was missing from the EMEP inventory, as well as from some others, being in some cases misplaced or mis-attributed to other sources of the region. A more consistent inventory of the anthropogenic emissions of SOx and PM has been compiled for the peninsula, compared with the existing estimates and verified by means of dispersion modelling. In particular, the SILAM model simulations for 2003 and 2006 with the revised emission data showed much lower bias - up to 6 times for the most-affected sites - for SO2 with regard to the measured concentrations of 8 Finnish and Norwegian observational stations in the region. Temporal correlation improved moderately (10-20%) but homogeneously over Lapland. The study demonstrates the value of a combined usage of forward and inverse ensemble modelling for source apportionment in case of limited observational data.
A refinement of the emission data for Kola Peninsula based on inverse dispersion modelling
Directory of Open Access Journals (Sweden)
M. Prank
2010-06-01
Full Text Available The study reviews the emission estimates of sulphur oxides (SO_{x} and primary particulate matter (PM from the major industrial sources of Kola Peninsula. Analysis of the disagreements between the existing emission inventories for the Kola region combined with forward and inverse ensemble dispersion modelling, analysis of observation time-series and model-measurement comparison showed that the emission of the Nikel non-ferrous metallurgy plant was missing from the EMEP inventory, as well as from some others, being in some cases misplaced or mis-attributed to other sources of the region. A more consistent inventory of the anthropogenic emissions of SO_{x} and PM has been compiled for the peninsula, compared with the existing estimates and verified by means of dispersion modelling. In particular, the SILAM model simulations for 2003 and 2006 with the revised emission data showed much lower bias – up to 6 times for the most-affected sites – for SO_{2} with regard to the measured concentrations of 8 Finnish and Norwegian observational stations in the region. Temporal correlation improved moderately (10–20% but homogeneously over Lapland. The study demonstrates the value of a combined usage of forward and inverse ensemble modelling for source apportionment in case of limited observational data.
Multi-year Estimates of Methane Fluxes in Alaska from an Atmospheric Inverse Model
Miller, S. M.; Commane, R.; Chang, R. Y. W.; Miller, C. E.; Michalak, A. M.; Dinardo, S. J.; Dlugokencky, E. J.; Hartery, S.; Karion, A.; Lindaas, J.; Sweeney, C.; Wofsy, S. C.
2015-12-01
We estimate methane fluxes across Alaska over a multi-year period using observations from a three-year aircraft campaign, the Carbon Arctic Reservoirs Vulnerability Experiment (CARVE). Existing estimates of methane from Alaska and other Arctic regions disagree in both magnitude and distribution, and before the CARVE campaign, atmospheric observations in the region were sparse. We combine these observations with an atmospheric particle trajectory model and a geostatistical inversion to estimate surface fluxes at the model grid scale. We first use this framework to estimate the spatial distribution of methane fluxes across the state. We find the largest fluxes in the south-east and North Slope regions of Alaska. This distribution is consistent with several estimates of wetland extent but contrasts with the distribution in most existing flux models. These flux models concentrate methane in warmer or more southerly regions of Alaska compared to the estimate presented here. This result suggests a discrepancy in how existing bottom-up models translate wetland area into methane fluxes across the state. We next use the inversion framework to explore inter-annual variability in regional-scale methane fluxes for 2012-2014. We examine the extent to which this variability correlates with weather or other environmental conditions. These results indicate the possible sensitivity of wetland fluxes to near-term variability in climate.
A refinement of the emission data for Kola Peninsula based on inverse dispersion modelling
Directory of Open Access Journals (Sweden)
M. Prank
2010-11-01
Full Text Available The study reviews the emission estimates of sulphur oxides (SO_{x} and primary particulate matter (PM from the major industrial sources of Kola Peninsula. Analysis of the disagreements between the existing emission inventories for the Kola region combined with forward and inverse ensemble dispersion modelling, analysis of observation time-series and model-measurement comparison showed that the emission of the Nikel metallurgy plant was missing or strongly under-estimated in the major European emission inventories, such as EMEP, EDGAR, TNO-GEMS, and PAREST-MEGAPOLI. In some cases it was misplaced or mis-attributed to other sources of the region. A more consistent inventory of the anthropogenic emissions of SO_{x} and PM has been compiled for the Peninsula, compared with the existing estimates and verified by means of dispersion modelling. In particular, the SILAM model simulations for 2003 and 2006 with the revised emission data showed much smaller under-estimation of SO_{2} concentrations at 8 Finnish and Norwegian observational stations. For the nearest site to the plant the 10-fold underestimation turned to a 1.5-fold over-prediction. Temporal correlation improved more moderately (up to 45% for concentrations, up to 3 times for deposition. The study demonstrates the value of a combined usage of forward and inverse ensemble modelling for source apportionment in case of limited observational data.
Al-Ma'shumah, Fathimah; Permana, Dony; Sidarto, Kuntjoro Adji
2015-12-01
Customer Lifetime Value is an important and useful concept in marketing. One of its benefits is to help a company for budgeting marketing expenditure for customer acquisition and customer retention. Many mathematical models have been introduced to calculate CLV considering the customer retention/migration classification scheme. A fairly new class of these models which will be described in this paper uses Markov Chain Models (MCM). This class of models has the major advantage for its flexibility to be modified to several different cases/classification schemes. In this model, the probabilities of customer retention and acquisition play an important role. From Pfeifer and Carraway, 2000, the final formula of CLV obtained from MCM usually contains nonlinear form of the transition probability matrix. This nonlinearity makes the inverse problem of CLV difficult to solve. This paper aims to solve this inverse problem, yielding the approximate transition probabilities for the customers, by applying metaheuristic optimization algorithm developed by Yang, 2013, Flower Pollination Algorithm. The major interpretation of obtaining the transition probabilities are to set goals for marketing teams in keeping the relative frequencies of customer acquisition and customer retention.
Sensitivity of basal conditions in an inverse model: Vestfonna ice cap, Nordaustlandet/Svalbard
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M. Schäfer
2012-07-01
Full Text Available The dynamics of Vestfonna ice cap (Svalbard are dominated by fast-flowing outlet glaciers. Its mass balance is poorly known and affected dynamically by these fast-flowing outlet glaciers. Hence, it is a challenging target for ice flow modeling. Precise knowledge of the basal conditions and implementation of a good sliding law are crucial for the modeling of this ice cap. Here we use the full-Stokes finite element code Elmer/Ice to model the 3-D flow over the whole ice cap. We use a Robin inverse method to infer the basal friction from the surface velocities observed in 1995. Our results illustrate the importance of the basal friction parameter in reproducing observed velocity fields. We also show the importance of having variable basal friction as given by the inverse method to reproduce the velocity fields of each outlet glacier – a simple parametrization of basal friction cannot give realistic velocities in a forward model. We study the robustness and sensitivity of this method with respect to different parameters (mesh characteristics, ice temperature, errors in topographic and velocity data. The uncertainty in the observational parameters and input data proved to be sufficiently small as not to adversely affect the fidelity of the model.
Estimation of semolina dough rheological parameters by inversion of a finite elements model
Directory of Open Access Journals (Sweden)
Angelo Fabbri
2015-10-01
Full Text Available The description of the rheological properties of food material plays an important role in food engineering. Particularly for the optimisation of pasta manufacturing process (extrusion is needful to know the rheological properties of semolina dough. Unfortunately characterisation of non-Newtonian fluids, such as food doughs, requires a notable time effort, especially in terms of number of tests to be carried out. The present work proposes an alternative method, based on the combination of laboratory measurement, made with a simplified tool, with the inversion of a finite elements numerical model. To determine the rheological parameters, an objective function, defined as the distance between simulation and experimental data, was considered and the well-known Levenberg-Marqard optimisation algorithm was used. In order to verify the feasibility of the method, the rheological characterisation of the dough was carried also by a traditional procedure. Results shown that the difference between measurements of rheological parameters of the semolina dough made with traditional procedure and inverse methods are very small (maximum percentage error equal to 3.6%. This agreement supports the coherence of the inverse method that, in general, may be used to characterise many non-Newtonian materials.
Fast and accurate analytical model to solve inverse problem in SHM using Lamb wave propagation
Poddar, Banibrata; Giurgiutiu, Victor
2016-04-01
Lamb wave propagation is at the center of attention of researchers for structural health monitoring of thin walled structures. This is due to the fact that Lamb wave modes are natural modes of wave propagation in these structures with long travel distances and without much attenuation. This brings the prospect of monitoring large structure with few sensors/actuators. However the problem of damage detection and identification is an "inverse problem" where we do not have the luxury to know the exact mathematical model of the system. On top of that the problem is more challenging due to the confounding factors of statistical variation of the material and geometric properties. Typically this problem may also be ill posed. Due to all these complexities the direct solution of the problem of damage detection and identification in SHM is impossible. Therefore an indirect method using the solution of the "forward problem" is popular for solving the "inverse problem". This requires a fast forward problem solver. Due to the complexities involved with the forward problem of scattering of Lamb waves from damages researchers rely primarily on numerical techniques such as FEM, BEM, etc. But these methods are slow and practically impossible to be used in structural health monitoring. We have developed a fast and accurate analytical forward problem solver for this purpose. This solver, CMEP (complex modes expansion and vector projection), can simulate scattering of Lamb waves from all types of damages in thin walled structures fast and accurately to assist the inverse problem solver.
Finite-Source Inversion for the 2004 Parkfield Earthquake using 3D Velocity Model Green's Functions
Kim, A.; Dreger, D.; Larsen, S.
2008-12-01
We determine finite fault models of the 2004 Parkfield earthquake using 3D Green's functions. Because of the dense station coverage and detailed 3D velocity structure model in this region, this earthquake provides an excellent opportunity to examine how the 3D velocity structure affects the finite fault inverse solutions. Various studies (e.g. Michaels and Eberhart-Phillips, 1991; Thurber et al., 2006) indicate that there is a pronounced velocity contrast across the San Andreas Fault along the Parkfield segment. Also the fault zone at Parkfield is wide as evidenced by mapped surface faults and where surface slip and creep occurred in the 1966 and the 2004 Parkfield earthquakes. For high resolution images of the rupture process"Ait is necessary to include the accurate 3D velocity structure for the finite source inversion. Liu and Aurchuleta (2004) performed finite fault inversions using both 1D and 3D Green's functions for 1989 Loma Prieta earthquake using the same source paramerizati