In search of climate effects on Atlantic Croaker (Micropogonias undulatus) stock off the U.S. Atlantic coast with Bayesian state-space biomass dynamic models

Atlantic Croaker (Micropogonias undulatus) production dynamics along the U.S. Atlantic coast are regulated by fishing and winter water temperature. Stakeholders for this resource have recommended investigating the effects of climate covariates in assessment models. This study used state-space biomass dynamic models without (model 1) and with (model 2) the minimum winter estuarine temperature (MWET) to examine MWET effects on Atlantic Croaker population dynamics during 1972–2008. In model 2, MWET was introduced into the intrinsic rate of population increase (r). For both models, a prior probability distribution (prior) was constructed for r or a scaling parameter (r0); imputs were the fishery removals, and fall biomass indices developed by using data from the Multispecies Bottom Trawl Survey of the Northeast Fisheries Science Center, National Marine Fisheries Service, and the Coastal Trawl Survey of the Southeast Area Monitoring and Assessment Program. Model sensitivity runs incorporated a uniform (0.01,1.5) prior for r or r0 and bycatch data from the shrimp-trawl fishery. All model variants produced similar results and therefore supported the conclusion of low risk of overfishing for the Atlantic Croaker stock in the 2000s. However, the data statistically supported only model 1 and its configuration that included the shrimp-trawl fishery bycatch. The process errors of these models showed slightly positive and significant correlations with MWET, indicating that warmer winters would enhance Atlantic Croaker biomass production. Inconclusive, somewhat conflicting results indicate that biomass dynamic models should not integrate MWET, pending, perhaps, accumulation of longer time series of the variables controlling the production dynamics of Atlantic Croaker, preferably including winter-induced estimates of Atlantic Croaker kills.

Composition and decomposition in bimanual dynamic learning.

Our ability to skillfully manipulate an object often involves the motor system learning to compensate for the dynamics of the object. When the two arms learn to manipulate a single object they can act cooperatively, whereas when they manipulate separate objects they control each object independently. We examined how learning transfers between these two bimanual contexts by applying force fields to the arms. In a coupled context, a single dynamic is shared between the arms, and in an uncoupled context separate dynamics are experienced independently by each arm. In a composition experiment, we found that when subjects had learned uncoupled force fields they were able to transfer to a coupled field that was the sum of the two fields. However, the contribution of each arm repartitioned over time so that, when they returned to the uncoupled fields, the error initially increased but rapidly reverted to the previous level. In a decomposition experiment, after subjects learned a coupled field, their error increased when exposed to uncoupled fields that were orthogonal components of the coupled field. However, when the coupled field was reintroduced, subjects rapidly readapted. These results suggest that the representations of dynamics for uncoupled and coupled contexts are partially independent. We found additional support for this hypothesis by showing significant learning of opposing curl fields when the context, coupled versus uncoupled, was alternated with the curl field direction. These results suggest that the motor system is able to use partially separate representations for dynamics of the two arms acting on a single object and two arms acting on separate objects.

Asymptotic Recovery for Discrete-Time Systems

An asymptotic recovery design procedure is proposed for square, discrete-time, linear, time-invariant multivariable systems, which allows a state-feedback design to be approximately recovered by a dynamic output feedback scheme. Both the case of negligible processing time (compared to the sampling interval) and of significant processing time are discussed. In the former case, it is possible to obtain perfect. © 1985 IEEE.

THEORETICAL ROAD DAMAGE DUE TO DYNAMIC TYRE FORCES OF HEAVY VEHICLES. PART 2: SIMULATED DAMAGE CAUSED BY A TANDEM-AXLE VEHICLE.

The literature relating to road surface failure and design is briefly reviewed and the conventional methods for assessing the road damaging effects of dynamic tire forces are examined. A new time domain technique for analyzing dynamic tire forces and four associated road damage criteria are presented. The force criteria are used to examine the road damaging characteristics of a simple tandem-axle vehicle model for a range of speed and road roughness conditions. It is concluded that for the proposed criteria, the theoretical service life of road surfaces that are prone to fatigue failure may be reduced significantly by the dynamic component of wheel forces. The damage done to approximately five per cent of the road surface area during the passage of a theoretical model vehicle at typical highway speeds may be increased by as much as four times.

Applications of the dynamic mode decomposition

The decomposition of experimental data into dynamic modes using a data-based algorithm is applied to Schlieren snapshots of a helium jet and to time-resolved PIV-measurements of an unforced and harmonically forced jet. The algorithm relies on the reconstruction of a low-dimensional inter-snapshot map from the available flow field data. The spectral decomposition of this map results in an eigenvalue and eigenvector representation (referred to as dynamic modes) of the underlying fluid behavior contained in the processed flow fields. This dynamic mode decomposition allows the breakdown of a fluid process into dynamically revelant and coherent structures and thus aids in the characterization and quantification of physical mechanisms in fluid flow. © 2010 Springer-Verlag.

Dynamic analysis of the brushless doubly-fed induction generator during symmetrical three-phase voltage dips

The Brushless Doubly-Fed Induction Generator (BDFIG) shows commercial promise as replacement for doublyfed slip-ring generators for wind power applications by offering reduced capital and operational costs due to its brushless operation. In order to facilitate its commercial deployment, the capabilities of the BDFIG system to comply with grid code requirements have to be assessed. This paper, for the first time, studies the performance of the BDFIG under grid fault ride-through and presents the dynamic behaviour of the machine during three-phase symmetrical voltage dips. Both full and partial voltage dips are studied using a vector model. Simulation and experimental results are provided for a 180 frame BDFIG.

Characterize dynamic conformational space of human CCR5 extracellular domain by molecular modeling and molecular dynamics simulation

The chemokine receptor CCR5 is the receptor for several chemokines and major coreceptor for R5 human immunodeficiency virus type-1 strains entry into cell. Three-dimensional models of CCR5 were built by using homology modeling approach and 1 ns molecular dynamics (MD) simulation, because studies of site-directed mutagenesis and chimeric receptors have indicated that the N-terminus (Nt) and extracellular loops (ECLs) of CCR5 are important for ligands binding and viral fusion and entry, special attention was focused on disulfide bond function, conformational flexibility, hydrogen bonding, electrostatic interactions, and solvent-accessible surface area of Nt and ECLs of this protein part. We found that the extracellular segments of CCR5 formed a well-packet globular domain with complex interactions occurred between them in a majority of time of MID simulation, but Nt region could protrude from this domain sometimes. The disulfide bond Cys20-Cys269 is essential in controlling specific orientation of Nt region and maintaining conformational integrity of extracellular domain. RMS comparison analysis between conformers revealed the ECL1 of CCR5 stays relative rigid, whereas the ECL2 and Nt are rather flexible. Solvent-accessible surface area calculations indicated that the charged residues within Nt and ECL2 are often exposed to solvent. Integrating these results with available experimental data, a two-step gp120-CCR5 binding mechanism was proposed. The dynamic interaction of CCR5 extracellular domain with gp120 was emphasized. (C) 2004 Elsevier B.V. All rights reserved.

Bayesian interpolation in a dynamic sinusoidal model with application to packet-loss concealment

In this paper, we consider Bayesian interpolation and parameter estimation in a dynamic sinusoidal model. This model is more flexible than the static sinusoidal model since it enables the amplitudes and phases of the sinusoids to be time-varying. For the dynamic sinusoidal model, we derive a Bayesian inference scheme for the missing observations, hidden states and model parameters of the dynamic model. The inference scheme is based on a Markov chain Monte Carlo method known as Gibbs sampler. We illustrate the performance of the inference scheme to the application of packet-loss concealment of lost audio and speech packets. © EURASIP, 2010.

The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking

We present a novel filtering algorithm for tracking multiple clusters of coordinated objects. Based on a Markov chain Monte Carlo (MCMC) mechanism, the new algorithm propagates a discrete approximation of the underlying filtering density. A dynamic Gaussian mixture model is utilized for representing the time-varying clustering structure. This involves point process formulations of typical behavioral moves such as birth and death of clusters as well as merging and splitting. For handling complex, possibly large scale scenarios, the sampling efficiency of the basic MCMC scheme is enhanced via the use of a Metropolis within Gibbs particle refinement step. As the proposed methodology essentially involves random set representations, a new type of estimator, termed the probability hypothesis density surface (PHDS), is derived for computing point estimates. It is further proved that this estimator is optimal in the sense of the mean relative entropy. Finally, the algorithm's performance is assessed and demonstrated in both synthetic and realistic tracking scenarios. © 2012 Elsevier Ltd. All rights reserved.

Differential Dynamic Microscopy: a High-Throughput Method for Characterizing the Motility of Microorganism

We present a fast, high-throughput method for characterizing the motility of microorganisms in 3D based on standard imaging microscopy. Instead of tracking individual cells, we analyse the spatio-temporal fluctuations of the intensity in the sample from time-lapse images and obtain the intermediate scattering function (ISF) of the system. We demonstrate our method on two different types of microorganisms: bacteria, both smooth swimming (run only) and wild type (run and tumble) Escherichia coli, and the bi-flagellate alga Chlamydomonas reinhardtii. We validate the methodology using computer simulations and particle tracking. From the ISF, we are able to extract (i) for E. coli: the swimming speed distribution, the fraction of motile cells and the diffusivity, and (ii) for C. reinhardtii: the swimming speed distribution, the amplitude and frequency of the oscillatory dynamics. In both cases, the motility parameters are averaged over \approx 10^4 cells and obtained in a few minutes.

Adaptive sequential Monte Carlo approach for real-time applications

This paper presents an adaptive Sequential Monte Carlo approach for real-time applications. Sequential Monte Carlo method is employed to estimate the states of dynamic systems using weighted particles. The proposed approach reduces the run-time computation complexity by adapting the size of the particle set. Multiple processing elements on FPGAs are dynamically allocated for improved energy efficiency without violating real-time constraints. A robot localisation application is developed based on the proposed approach. Compared to a non-adaptive implementation, the dynamic energy consumption is reduced by up to 70% without affecting the quality of solutions. © 2012 IEEE.

Static and dynamic errors in particle tracking microrheology.

Particle tracking techniques are often used to assess the local mechanical properties of cells and biological fluids. The extracted trajectories are exploited to compute the mean-squared displacement that characterizes the dynamics of the probe particles. Limited spatial resolution and statistical uncertainty are the limiting factors that alter the accuracy of the mean-squared displacement estimation. We precisely quantified the effect of localization errors in the determination of the mean-squared displacement by separating the sources of these errors into two separate contributions. A "static error" arises in the position measurements of immobilized particles. A "dynamic error" comes from the particle motion during the finite exposure time that is required for visualization. We calculated the propagation of these errors on the mean-squared displacement. We examined the impact of our error analysis on theoretical model fluids used in biorheology. These theoretical predictions were verified for purely viscous fluids using simulations and a multiple-particle tracking technique performed with video microscopy. We showed that the static contribution can be confidently corrected in dynamics studies by using static experiments performed at a similar noise-to-signal ratio. This groundwork allowed us to achieve higher resolution in the mean-squared displacement, and thus to increase the accuracy of microrheology studies.

Minimum maneuver time calculation using convex optimization

The problem of calculating the minimum lap or maneuver time of a nonlinear vehicle, which is linearized at each time step, is formulated as a convex optimization problem. The formulation provides an alternative to previously used quasi-steady-state analysis or nonlinear optimization. Key steps are: the use of model predictive control; expressing the minimum time problem as one of maximizing distance traveled along the track centerline; and linearizing the track and vehicle trajectories by expressing them as small displacements from a fixed reference. A consequence of linearizing the vehicle dynamics is that nonoptimal steering control action can be generated, but attention to the constraints and the cost function minimizes the effect. Optimal control actions and vehicle responses for a 90 deg bend are presented and compared to the nonconvex nonlinear programming solution. Copyright © 2013 by ASME.

Frequency locked micro disk resonator for real time and precise monitoring of refractive index.

We experimentally demonstrate a frequency modulation locked servo loop, locked to a resonance line of an on-chip microdisk resonator in a silicon nitride platform. By using this approach, we demonstrate real-time monitoring of refractive index variations with a precision approaching 10(-7) RIU, using a moderate Q factor of 10(4). The approach can be applied for intensity independent, dynamic and precise index of refraction monitoring for biosensing applications.

Differential expression and dynamic changes of SOX3 during gametogenesis and sex reversal in protogynous hermaphroditic fish

SOX3 has been suggested to play significant roles in gametogenesis and gonad differentiation of vertebrates, but the exact cellular localization evidence is insufficient and controversial. In this study, a protogynous hermaphrodite fish Epinephelus coioides is selected to analyze EcSox3 differential expression and the expression pattern in both processes of oogenesis and spermatogenesis by utilizing the advantages that gonad development undergoes transition from ovary to intersexual gonad and then to testis, and primordial germ cells and different stage cells during oogenesis and spermatogenesis are synchronously observed in the transitional gonads. The detailed and clear immunofluoresence localization indicates that significantly differential expression and dynamic changes of Sox3 occur in the progresses of gametogenesis and sex reversal, and EcSOX3 protein exists in the differentiating primordial germ cells, oogonia, and different stage oocytes of ovaries, and also in the differentiating primordial germ cells and the Sertoli cells of testis. One important finding is that the EcSox3 expression is a significant time point for enterable gametogenesis of primordial germ cells because EcSOX3 is obviously expressed and localized in primordial germ cells. As EcSox3 continues to express, the EcSOX3-positive primordial germ cells develop toward oogonia and then oocytes, whereas when EcSox3 expression is ceased, the EcSOX3-positive primordial germ cells develop toward spermatogonia. Therefore, the current finding of EcSOX3 in the differentiating primordial germ cells again confirms the potential regulatory role in oogenesis and germ cell differentiation. The data further suggest that SOX3, as a transcription factor, might have more important roles in oogenesis than in spermatogenesis.