Regularizing velocity differences in time-lapse FWI using gradient mismatch information

We present a method for recovering time-lapse velocity changes using full waveform inversion (FWI). In a preprocessing step we invert for a single intermediate model by simultaneously minimizing the data misfit in the baseline and the monitor surveys. We record the individual FWI gradients corresponding to the baseline and the monitor datasets at each iteration of the inversion. Regions where these gradients consistently have opposing sign are likely to correspond to locations of time-lapse change. This insight is used to generate a spatially varying confidence map for time-lapse change. In a subsequent joint inversion we invert for baseline and monitor models while regularizing the difference between the models with this spatially varying confidence map. Unlike double difference full waveform inversion (DDFWI) we do not require identical source and receiver positions in the baseline and monitor surveys

Iterative estimation of reflectivity and image texture: Least-squares migration with an empirical Bayes approach

In many geophysical inverse problems, smoothness assumptions on the underlying geology are used to mitigate the effects of nonuniqueness, poor data coverage, and noise in the data and to improve the quality of the inferred model parameters. Within a Bayesian inference framework, a priori assumptions about the probabilistic structure of the model parameters can impose such a smoothness constraint, analogous to regularization in a deterministic inverse problem. We have considered an empirical Bayes generalization of the Kirchhoff-based least-squares migration (LSM) problem. We have developed a novel methodology for estimation of the reflectivity model and regularization parameters, using a Bayesian statistical framework that treats both of these as random variables to be inferred from the data. Hence, rather than fixing the regularization parameters prior to inverting for the image, we allow the data to dictate where to regularize. Estimating these regularization parameters gives us information about the degree of conditional correlation (or lack thereof) between neighboring image parameters, and, subsequently, incorporating this information in the final model produces more clearly visible discontinuities in the estimated image. The inference framework is verified on 2D synthetic data sets, in which the empirical Bayes imaging results significantly outperform standard LSM images. We note that although we evaluated this method within the context of seismic imaging, it is in fact a general methodology that can be applied to any linear inverse problem in which there are spatially varying correlations in the model parameter space.MIT Energy Initiative (Shell International Exploration and Production B.V.)ERL Founding Member Consortiu

Spin and magnetization effects in plasmas

We give a short review of a number of different models for treating magnetization effects in plasmas. In particular, the transition between kinetic models and fluid models is discussed. We also give examples of applications of such theories. Some future aspects are discussed.Comment: 18 pages, 1 figure. To appear in Plasma Physics and Controlled Fusion, Special Issue for the 37th ICPP, Santiago, Chil

From extended phase space dynamics to fluid theory

We derive a fluid theory for spin-1/2 particles starting from an extended kinetic model based on a spin-projected density matrix formalism. The evolution equation for the spin density is found to contain a pressure-like term. We give an example where this term is important by looking at a linear mode previously found in a spin kinetic model.Comment: 4 page

Spin kinetic theory - quantum kinetic theory in extended phase space

The concept of phase space distribution functions and their evolution is used in the case of en enlarged phase space. In particular, we include the intrinsic spin of particles and present a quantum kinetic evolution equation for a scalar quasi-distribution function. In contrast to the proper Wigner transformation technique, for which we expect the corresponding quasi-distribution function to be a complex matrix, we introduce a spin projection operator for the density matrix in order to obtain the aforementioned scalar quasi-distribution function. There is a close correspondence between this projection operator and the Husimi (or Q) function used extensively in quantum optics. Such a function is based on a Gaussian smearing of a Wigner function, giving a positive definite distribution function. Thus, our approach gives a Wigner-Husimi quasi-distribution function in extended phase space, for which the reduced distribution function on the Bloch sphere is strictly positive. We also discuss the gauge issue and the fluid moment hierarchy based on such a quantum kinetic theory.Comment: 10 pages, to appear in Transport Theory and Statistical Physics, proceedings of Vlasovia III, 200

Ferroplasmas: Magnetic Dust Dynamics in a Conducting Fluid

We consider a dusty plasma, in which the dust particles have a magnetic dipole moment. A Hall-MHD type of model, generalized to account for the intrinsic magnetization, is derived. The model is shown to be energy conserving, and the energy density and flux is derived. The general dispersion relation is then derived, and we show that kinetic Alfv\'en waves exhibit an instability for a low temperature and high density plasma. We discuss the implication of our results.Comment: 6 pages, 1 figur

Keeping thinning-derived deadwood logs on forest floor improves soil organic carbon, microbial biomass, and enzyme activity in a temperate spruce forest

Deadwood is a key component of forest ecosystems, but there is limited information on how it influences forest soils. Moreover, studies on the effect of thinning-derived deadwood logs on forest soil properties are lacking. This study aimed to investigate the impact of thinning-derived deadwood logs on the soil chemical and microbial properties of a managed spruce forest on a loamy sand Podzol in Bavaria, Germany, after about 15 years. Deadwood increased the soil organic carbon contents by 59% and 56% at 0–4 cm and 8–12 cm depths, respectively. Under deadwood, the soil dissolved organic carbon and carbon to nitrogen ratio increased by 66% and 15% at 0–4 cm depth and by 55% and 28% at 8–12 cm depth, respectively. Deadwood also induced 71% and 92% higher microbial biomass carbon, 106% and 125% higher microbial biomass nitrogen, and 136% and 44% higher β-glucosidase activity in the soil at 0–4 cm and 8–12 cm depths, respectively. Many of the measured variables significantly correlated with soil organic carbon suggesting that deadwood modified the soil biochemical processes by altering soil carbon storage. Our results indicate the potential of thinned spruce deadwood logs to sequester carbon and improve the fertility of Podzol soils. This could be associated with the slow decay rate of spruce deadwood logs and low biological activity of Podzols that promote the accumulation of soil carbon. We propose that leaving thinning-derived deadwood on the forest floor can support soil and forest sustainability as well as carbon sequestration

Scalar quantum kinetic theory for spin-1/2 particles: mean field theory

Starting from the Pauli Hamiltonian operator, we derive a scalar quantum kinetic equations for spin-1/2 systems. Here the regular Wigner two-state matrix is replaced by a scalar distribution function in extended phase space. Apart from being a formulation of principal interest, such scalar quantum kinetic equation makes the comparison to classical kinetic theory straightforward, and lends itself naturally to currently available numerical Vlasov and Boltzmann schemes. Moreover, while the quasi-distribution is a Wigner function in regular phase space, it is given by a Q-function in spin space. As such, nonlinear and dynamical quantum plasma problems are readily handled. Moreover, the issue of gauge invariance is treated. Applications (e.g. ultra-dense laser compressed targets and their diagnostics), possible extensions, and future improvements of the presented quantum statistical model are discussed.Comment: 21 pages, 2 figure

Severe pulmonary arterial hypertension is characterized by increased neutrophil elastase and relative elafin deficiency

BACKGROUND: Preclinical evidence implicates neutrophil elastase (NE) in PAH pathogenesis, and the NE inhibitor elafin is under early therapeutic investigation. RESEARCH QUESTION: Are circulating NE and elafin levels abnormal in PAH and associated with clinical severity? STUDY DESIGN/METHODS: . In an observational Stanford University PAH cohort (N=249), plasma NE and elafin were measured in comparison to healthy controls (N=106) then related to clinical features and relevant ancillary biomarkers. Cox regression models were fitted with cubic spline functions to associate NE and elafin with survival. To validate prognostic relationships, we analyzed two United Kingdom cohorts (N=75, N=357). Mixed effects models evaluated NE and elafin changes during disease progression. Finally, we studied effects of NE/elafin balance on pulmonary artery endothelial cells (PAECs) from PAH patients. RESULTS: Relative to controls, patients had increased NE (205.1 [123.6-387.3] vs. 97.6 [74.4-126.6] ng/mL, P168.5 ng/mL portended increased mortality risk after adjustment for known clinical predictors (HR 2.52, CI 1.36-4.65, P=0.003) or prognostic cytokines (HR 2.63, CI 1.42-4.87, P=0.001), and NE added incremental value to established PAH risk scores. Similar prognostic thresholds were identified in validation cohorts. Longitudinal NE changes tracked with clinical trends and outcomes. PAH-PAECs exhibited increased apoptosis and attenuated angiogenesis when exposed to NE at the level observed in patients' blood. Elafin rescued PAEC homeostasis, yet the required dose exceeded levels found in patients. INTERPRETATION: NE is increased and elafin deficient across PAH subtypes. NE associates with disease severity and outcomes, and this target-specific biomarker could facilitate therapeutic development of elafin

Role of the electro-thermo-mechanical multiple coupling on the operation of RF microswitch

A phenomenological approach is proposed to identify some effects occurring within the structure of the microswitch conceived for radio frequency application. This microsystem is operated via a nonlinear electromechanical action imposed by the applied voltage. Unfortunately, it can be affected by residual stress, due to the microfabrication process, therefore axial and flexural behaviors are strongly coupled. This coupling increases the actuation voltage required to achieve the so-called ‘‘pull-in'' condition. Moreover, temperature may strongly affect strain and stress distributions, respectively. Environmental temperature, internal dissipation of material, thermo-elastic and Joule effects play different roles on the microswitch flexural isplacement. Sometimes buckling phenomenon evenly occurs. Literature show that all those issues make difficult an effective computation of ‘‘pull-in'' and ‘‘pull-out'' voltages for evenly distinguishing the origin of some failures detected in operation. Analysis, numerical methods and experiments are applied to an industrial test case to investigate step by step the RF-microswitch operation. Multiple electro-hermomechanical coupling is first modeled to have a preliminary and comprehensive description of the microswitch behavior and of its reliability. ‘‘Pull-in'' and ‘‘pull-out'' tests are then performed to validate the proposed models and to find suitable criteria to design the RF-MEM