Mass conservative three-dimensional water tracer distribution from Markov chain Monte Carlo inversion of time-lapse ground-penetrating radar data

Time-lapse geophysical measurements are widely used to monitor the movement of water and solutes through the subsurface. Yet commonly used deterministic least squares inversions typically suffer from relatively poor mass recovery, spread overestimation, and limited ability to appropriately estimate nonlinear model uncertainty. We describe herein a novel inversion methodology designed to reconstruct the three-dimensional distribution of a tracer anomaly from geophysical data and provide consistent uncertainty estimates using Markov chain Monte Carlo simulation. Posterior sampling is made tractable by using a lower-dimensional model space related both to the Legendre moments of the plume and to predefined morphological constraints. Benchmark results using cross-hole ground-penetrating radar travel times measurements during two synthetic water tracer application experiments involving increasingly complex plume geometries show that the proposed method not only conserves mass but also provides better estimates of plume morphology and posterior model uncertainty than deterministic inversion results.

MAR elements regulate the probability of epigenetic switching between active and inactive gene expression.

Gene expression often cycles between active and inactive states in eukaryotes, yielding variable or noisy gene expression in the short-term, while slow epigenetic changes may lead to silencing or variegated expression. Understanding how cells control these effects will be of paramount importance to construct biological systems with predictable behaviours. Here we find that a human matrix attachment region (MAR) genetic element controls the stability and heritability of gene expression in cell populations. Mathematical modeling indicated that the MAR controls the probability of long-term transitions between active and inactive expression, thus reducing silencing effects and increasing the reactivation of silent genes. Single-cell short-terms assays revealed persistent expression and reduced expression noise in MAR-driven genes, while stochastic burst of expression occurred without this genetic element. The MAR thus confers a more deterministic behavior to an otherwise stochastic process, providing a means towards more reliable expression of engineered genetic systems.

T helper 1 (Th1) and Th2 characteristics start to develop during T cell priming and are associated with an immediate ability to induce immunoglobulin class switching.

The respective production of specific immunoglobulin (Ig)G2a or IgG1 within 5 d of primary immunization with Swiss type mouse mammary tumor virus [MMTV(SW)] or haptenated protein provides a model for the development of T helper 1 (Th1) and Th2 responses. The antibody-producing cells arise from cognate T cell B cell interaction, revealed by the respective induction of Cgamma2a and Cgamma1 switch transcript production, on the third day after immunization. T cell proliferation and upregulation of mRNA for interferon gamma in response to MMTV(SW) and interleukin 4 in response to haptenated protein also starts during this day. It follows that there is minimal delay in these responses between T cell priming and the onset of cognate interaction between T and B cells leading to class switching and exponential growth. The Th1 or Th2 profile is at least partially established at the time of the first cognate T cell interaction with B cells in the T zone. The addition of killed Bordetella pertussis to the hapten-protein induces nonhapten-specific IgG2a and IgG1 plasma cells, whereas the anti-hapten response continues to be IgG1 dominated. This indicates that a Th2 response to hapten-protein can proceed in a node where there is substantial Th1 activity.

Stochastic processes induced by dichotomous markov noise: Some exact dynamical results

Stochastic processes defined by a general Langevin equation of motion where the noise is the non-Gaussian dichotomous Markov noise are studied. A non-FokkerPlanck master differential equation is deduced for the probability density of these processes. Two different models are exactly solved. In the second one, a nonequilibrium bimodal distribution induced by the noise is observed for a critical value of its correlation time. Critical slowing down does not appear in this point but in another one.

Job switching in ants: role of a kinase

Reproductive division of labour is a defining characteristic of eusociality in insect societies. The task of reproduction is performed by the fertile males and queens of the colony, while the non-fertile female worker caste performs all other tasks related to colony upkeep, foraging and nest defence. Division of labour, or polyethism, within the worker caste is organized such that specific tasks are performed by discrete groups of individuals. Ordinarily, workers of one group will not participate in the tasks of other groups making the groups of workers behaviourally distinct. In some eusocial species, this has led to the evolution of a remarkable diversity of subcaste morphologies within the worker caste, and a division of labour amongst the subcastes. This caste polyethism is best represented in many species of ants where a smaller-bodied minor subcaste typically performs foraging duties while larger individuals of the major subcaste are tasked with nest defence. Recent work suggests that polyethism in the worker caste is influenced by an evolutionarily conserved, yet diversely regulated, gene called foraging (for), which encodes a cGMP-dependent protein kinase (PKG). Additionally, flexibility in the activity of this enzyme allows for workers from one task group to assist the workers of other task groups in times of need during the colony's life.

Native Grassland Conversion: the Roles of Risk Intervention and Switching Costs

We develop a real option model of the irreversible native grassland conversion decision. Upon plowing, native grassland can be followed by either a permanent cropping system or a system in which land is put under cropping (respectively, grazing) whenever crop prices are high (respectively, low). Switching costs are incurred upon alternating between cropping and grazing. The effects of risk intervention in the form of crop insurance subsidies are studied, as are the effects of cropping innovations that reduce switching costs. We calibrate the model by using cropping return data for South Central North Dakota from 1989 to 2012. Simulations show that a risk intervention that offsets 20% of a cropping return shortfall increases the sod-busting cost threshold, below which native sod will be busted, by 41% (or $43.7/acre). Omitting cropping return risk across time underestimates this sod-busting cost threshold by 23% (or $24.35/acre), and hence underestimates the native sod conversion caused by crop production.

Stability-dependent behavioural and electro-cortical reorganizations during intentional switching between bimanual tapping modes

This study investigated behavioural and electro-cortical reorganizations accompanying intentional switching between two distinct bimanual coordination tapping modes (In-phase and Anti-phase) that differ in stability when produced at the same movement rate. We expected that switching to a less stable tapping mode (In-to-Anti switching) would lead to larger behavioural perturbations and require supplementary neural resources than switching to a more stable tapping mode (Anti-to-In switching). Behavioural results confirmed that the In-to-Anti switching lasted longer than the Anti-to-In switching. A general increase in attention-related neural activity was found at the moment of switching for both conditions. Additionally, two condition-dependent EEG reorganizations were observed. First, a specific increase in cortico-cortical coherence appeared exclusively during the In-to-Anti switching. This result may reflect a strengthening in inter-regional communication in order to engage in the subsequent, less stable, tapping mode. Second, a decrease in motor-related neural activity (increased beta spectral power) was found for the Anti-to-In switching only. The latter effect may reflect the interruption of the previous, less stable, tapping mode. Given that previous results on spontaneous Anti-to-In switching revealing an inverse pattern of EEG reorganization (decreased beta spectral power), present findings give new insight on the stability-dependent neural correlates of intentional motor switching. © 2010 Elsevier Ireland Ltd. All rights reserved

Análise da transição entre dias secos e chuvosos por meio da cadeia de Markov de terceira ordem

O objetivo deste trabalho foi verificar se as ocorrências de dias secos e chuvosos são condicionalmente dependentes da seqüência dos três dias secos e chuvosos anteriores, numa zona pluviometricamente homogênea, por meio da cadeia não-homogênea de Markov de terceira ordem. Os resultados mostraram que as probabilidades diárias de transição podem ser adequadamente estimadas, com base em dados agregados bimestralmente, seguidas de interpolação por meio de funções sinusoidais. Além disso, evidenciou-se que, naquela zona, as ocorrências diárias de chuva são condicionalmente dependentes da seqüência de dias secos e chuvosos nos três dias anteriores. A cadeia não-homogênea de Markov de terceira ordem é um importante instrumento para a análise da dependência entre as seqüências de dias secos e chuvosos em determinadas regiões.

Post-switching beta synchronization reveals concomitant sensory reafferences and active inhibition processes

It is known that post-movement beta synchronization (PMBS) is involved both in active inhibition and in sensory reafferences processes. The aim of this study was examine the temporal and spatial dynamics of the PMBS involved during multi-limb coordination task. We investigated post-switching beta synchronization (assigned PMBS) using time-frequency and source estimations analyzes. Participants (n = 17) initiated an auditory-paced bimanual tapping. After a 1500 ms preparatory period, an imperative stimulus required to either selectively stop the left while maintaining the right unimanual tapping (Switch condition: SWIT) or to continue the bimanual tapping (Continue condition: CONT). PMBS significantly increased in SWIT compared to CONT with maximal difference within right central region in broad-band 14âeuro"30 Hz and within left central region in restricted-band 22âeuro"26 Hz. Source estimations localized these effects within right pre-frontal cortex and left parietal cortex, respectively. A negative correlation showed that participants with a low percentage of errors in SWIT had a large PMBS amplitude within right parietal and frontal cortices. This study shows for the first time simultaneous PMBS with distinct functions in different brain regions and frequency ranges. The left parietal PMBS restricted to 22âeuro"26 Hz could reflect the sensory reafferences of the right hand tapping disrupted by the switching. In contrast, the right pre-frontal PMBS in a broad-band 14âeuro"30 Hz is likely reflecting the active inhibition of the left hand stopped. Finally, correlations between behavioral performance and the magnitude of the PMBS suggest that beta oscillations can be viewed as a marker of successful active inhibition.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Bayesian Markov-chain-Monte-Carlo inversion of time-lapse cross hole ground-penetrating radar data to characterize the vadose zone at the Arrenaes field site, Denmark

The ground-penetrating radar (GPR) geophysical method has the potential to provide valuable information on the hydraulic properties of the vadose zone because of its strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR traveltime data can allow for a significant reduction in uncertainty regarding subsurface van Genuchten-Mualem (VGM) parameters. Much of the previous work on the stochastic estimation of VGM parameters from crosshole GPR data has considered the case of steady-state infiltration conditions, which represent only a small fraction of practically relevant scenarios. We explored in detail the dynamic infiltration case, specifically examining to what extent time-lapse crosshole GPR traveltimes, measured during a forced infiltration experiment at the Arreneas field site in Denmark, could help to quantify VGM parameters and their uncertainties in a layered medium, as well as the corresponding soil hydraulic properties. We used a Bayesian Markov-chain-Monte-Carlo inversion approach. We first explored the advantages and limitations of this approach with regard to a realistic synthetic example before applying it to field measurements. In our analysis, we also considered different degrees of prior information. Our findings indicate that the stochastic inversion of the time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions compared with the corresponding priors, which in turn significantly improves knowledge of soil hydraulic properties. Overall, the results obtained clearly demonstrate the value of the information contained in time-lapse GPR data for characterizing vadose zone dynamics.

On the convergence of EM-like algorithms for image segmentation using Markov random fields.

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.