Anomalous diffusion evidenced by particle tracking at high frame rates.

Diffusion is a common phenomenon in nature and generally is associated with a system trying to reach a local or a global equilibrium state, as a result of highly irregular individual particle motion. Therefore it is of fundamental importance in physics, chemistry and biology. Particle tracking in complex fluids can reveal important characteristics of its properties. In living cells, we coat the microbead with a peptide (RGD) that binds to integrin receptors at the plasma membrane, which connects to the CSK. This procedure is based on the hypothesis that the microsphere can move only if the structure where it is attached move as well. Then, the observed trajectory of microbeads is a probe of the cytoskeleton (CSK), which is governed by several factors, including thermal diffusion, pressure gradients, and molecular motors. The possibility of separating the trajectories into passive and active diffusion may give information about the viscoelasticity of the cell structure and molecular motors activity. And also we could analyze the motion via generalized Stokes-Einstein relation, avoiding the use of any active techniques. Usually a 12 to 16 Frames Per Second (FPS) system is used to track the microbeads in cell for about 5 minutes. Several factors make this FPS limitation: camera computer communication, light, computer speed for online analysis among others. Here we used a high quality camera and our own software, developed in C++ and Linux, to reach high FPS. Measurements were conducted with samples for 10£ and 20£ objectives. We performed sequentially images with different intervals, all with 2 ¹s exposure. The sequences of intervals are in milliseconds: 4 5 ms (maximum speed) 14, 25, 50 and 100 FPS. Our preliminary results highlight the difference between passive and active diffusion, since the passive diffusion is represented by a Gaussian in the distribution of displacements of the center of mass of individual beads between consecutive frames. However, the active process, or anomalous diffusion, shows as long tails in the distribution of displacements.

A marker-and-cell approach to free surface 2-D multiphase flows

This work describes a methodology to simulate free surface incompressible multiphase flows. This novel methodology allows the simulation of multiphase flows with an arbitrary number of phases, each of them having different densities and viscosities. Surface and interfacial tension effects are also included. The numerical technique is based on the GENSMAC front-tracking method. The velocity field is computed using a finite-difference discretization of a modification of the NavierStokes equations. These equations together with the continuity equation are solved for the two-dimensional multiphase flows, with different densities and viscosities in the different phases. The governing equations are solved on a regular Eulerian grid, and a Lagrangian mesh is employed to track free surfaces and interfaces. The method is validated by comparing numerical with analytic results for a number of simple problems; it was also employed to simulate complex problems for which no analytic solutions are available. The method presented in this paper has been shown to be robust and computationally efficient. Copyright (c) 2012 John Wiley & Sons, Ltd.

Model for the Dynamics of the Cytoskeleton.

Particle tracking of microbeads attached to the cytoskeleton (CSK) reveals an intermittent dynamic. The mean squared displacement (MSD) is subdiffusive for small Δt and superdiffusive for large Δt, which are associated with periods of traps and periods of jumps respectively. The analysis of the displacements has shown a non-Gaussian behavior, what is indicative of an active motion, classifying the cells as a far from equilibrium material. Using Langevin dynamics, we reconstruct the dynamic of the CSK. The model is based on the bundles of actin filaments that link themself with the bead RGD coating, trapping it in an harmonic potential. We consider a one- dimensional motion of a particle, neglecting inertial effects (over-damped Langevin dynamics). The resultant force is decomposed in friction force, elastic force and random force, which is used as white noise representing the effect due to molecular agitation. These description until now shows a static situation where the bead performed a random walk in an elastic potential. In order to modeling the active remodeling of the CSK, we vary the equilibrium position of the potential. Inserting a motion in the well center, we change the equilibrium position linearly with time with constant velocity. The result found exhibits a MSD versus time ’tau’ with three regimes. The first regime is when ‘tau’ < ‘tau IND 0’, where ‘tau IND 0’ is the relaxation time, representing the thermal motion. At this regime the particle can diffuse freely. The second regime is a plateau, ‘tau IND 0’ < ‘tau’ < ‘tau IND 1’, representing the particle caged in the potential. Here, ‘tau IND 1’ is a characteristic time that limit the confinement period. And the third regime, ‘tau’ > ‘tau IND 1’, is when the particles are in the superdiffusive behavior. This is where most of the experiments are performed, under 20 frames per second (FPS), thus there is no experimental evidence that support the first regime. We are currently performing experiments with high frequency, up to 100 FPS, attempting to visualize this diffusive behavior. Beside the first regime, our simple model can reproduce MSD curves similar to what has been found experimentally, which can be helpful to understanding CSK structure and properties.

The unconventional secretion of stress-inducible protein 1 by a heterogeneous population of extracellular vesicles

The co-chaperone stress-inducible protein 1 (STI1) is released by astrocytes, and has important neurotrophic properties upon binding to prion protein (PrPC). However, STI1 lacks a signal peptide and pharmacological approaches pointed that it does not follow a classical secretion mechanism. Ultracentrifugation, size exclusion chromatography, electron microscopy, vesicle labeling, and particle tracking analysis were used to identify three major types of extracellular vesicles (EVs) released from astrocytes with sizes ranging from 20–50, 100–200, and 300–400 nm. These EVs carry STI1 and present many exosomal markers, even though only a subpopulation had the typical exosomal morphology. The only protein, from those evaluated here, present exclusively in vesicles that have exosomal morphology was PrPC. STI1 partially co-localized with Rab5 and Rab7 in endosomal compartments, and a dominant-negative for vacuolar protein sorting 4A (VPS4A), required for formation of multivesicular bodies (MVBs), impaired EV and STI1 release. Flow cytometry and PK digestion demonstrated that STI1 localized to the outer leaflet of EVs, and its association with EVs greatly increased STI1 activity upon PrPC-dependent neuronal signaling. These results indicate that astrocytes secrete a diverse population of EVs derived from MVBs that contain STI1 and suggest that the interaction between EVs and neuronal surface components enhances STI1–PrPC signaling

Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization

At each outer iteration of standard Augmented Lagrangian methods one tries to solve a box-constrained optimization problem with some prescribed tolerance. In the continuous world, using exact arithmetic, this subproblem is always solvable. Therefore, the possibility of finishing the subproblem resolution without satisfying the theoretical stopping conditions is not contemplated in usual convergence theories. However, in practice, one might not be able to solve the subproblem up to the required precision. This may be due to different reasons. One of them is that the presence of an excessively large penalty parameter could impair the performance of the box-constraint optimization solver. In this paper a practical strategy for decreasing the penalty parameter in situations like the one mentioned above is proposed. More generally, the different decisions that may be taken when, in practice, one is not able to solve the Augmented Lagrangian subproblem will be discussed. As a result, an improved Augmented Lagrangian method is presented, which takes into account numerical difficulties in a satisfactory way, preserving suitable convergence theory. Numerical experiments are presented involving all the CUTEr collection test problems.

The boundedness of penalty parameters in an augmented Lagrangian method with constrained subproblems

Augmented Lagrangian methods are effective tools for solving large-scale nonlinear programming problems. At each outer iteration, a minimization subproblem with simple constraints, whose objective function depends on updated Lagrange multipliers and penalty parameters, is approximately solved. When the penalty parameter becomes very large, solving the subproblem becomes difficult; therefore, the effectiveness of this approach is associated with the boundedness of the penalty parameters. In this paper, it is proved that under more natural assumptions than the ones employed until now, penalty parameters are bounded. For proving the new boundedness result, the original algorithm has been slightly modified. Numerical consequences of the modifications are discussed and computational experiments are presented.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

Optimal reactive power flow via the modified barrier Lagrangian function approach

A new approach called the Modified Barrier Lagrangian Function (MBLF) to solve the Optimal Reactive Power Flow problem is presented. In this approach, the inequality constraints are treated by the Modified Barrier Function (MBF) method, which has a finite convergence property: i.e. the optimal solution in the MBF method can actually be in the bound of the feasible set. Hence, the inequality constraints can be precisely equal to zero. Another property of the MBF method is that the barrier parameter does not need to be driven to zero to attain the solution. Therefore, the conditioning of the involved Hessian matrix is greatly enhanced. In order to show this, a comparative analysis of the numeric conditioning of the Hessian matrix of the MBLF approach, by the decomposition in singular values, is carried out. The feasibility of the proposed approach is also demonstrated with comparative tests to Interior Point Method (IPM) using various IEEE test systems and two networks derived from Brazilian generation/transmission system. The results show that the MBLF method is computationally more attractive than the IPM in terms of speed, number of iterations and numerical conditioning. (C) 2011 Elsevier B.V. All rights reserved.

On the generalized canonical equations of Hamilton for a time-dependent mass particle

Fundamental principles of mechanics were primarily conceived for constant mass systems. Since the pioneering works of Meshcherskii (see historical review in Mikhailov (Mech. Solids 10(5):32-40, 1975), efforts have been made in order to elaborate an adequate mathematical formalism for variable mass systems. This is a current research field in theoretical mechanics. In this paper, attention is focused on the derivation of the so-called 'generalized canonical equations of Hamilton' for a variable mass particle. The applied technique consists in the consideration of the mass variation process as a dissipative phenomenon. Kozlov's (Stek. Inst. Math 223:178-184, 1998) method, originally devoted to the derivation of the generalized canonical equations of Hamilton for dissipative systems, is accordingly extended to the scenario of variable mass systems. This is done by conveniently writing the flux of kinetic energy from or into the variable mass particle as a 'Rayleigh-like dissipation function'. Cayley (Proc. R Soc. Lond. 8:506-511, 1857) was the first scholar to propose such an analogy. A deeper discussion on this particular subject will be left for a future paper.

Controlling chaos in wave-particle interactions

We analyze the behavior of a relativistic particle moving under the influence of a uniform magnetic field and a stationary electrostatic wave. We work with a set of pulsed waves that allows us to obtain an exact map for the system. We also use a method of control for near-integrable Hamiltonians that consists of the addition of a small and simple control term to the system. This control term creates invariant tori in phase space that prevent chaos from spreading to large regions, making the controlled dynamics more regular. We show numerically that the control term just slightly modifies the system but is able to drastically reduce chaos with a low additional cost of energy. Moreover, we discuss how the control of chaos and the consequent recovery of regular trajectories in phase space are useful to improve regular particle acceleration.

Myocardial Deformation by Speckle Tracking in Severe Dilated Cardiomyopathy

Background: The high and increasing prevalence of Dilated Cardiomyopathy (DCM) represents a serious public health issue. Novel technologies have been used aiming to improve diagnosis and the therapeutic approach. In this context, speckle tracking echocardiography (STE) uses natural myocardial markers to analyze the systolic deformation of the left ventricle (LV). Objective: Measure the longitudinal transmural global strain (GS) of the LV through STE in patients with severe DCM, comparing the results with normal individuals and with echocardiographic parameters established for the analysis of LV systolic function, in order to validate the method in this population. Methods: Seventy-one patients with severe DCM (53 +/- 12 years, 72% men) and 20 controls (30 +/- 8 years, 45% men) were studied. The following variables were studied: LV volumes and ejection fraction calculated by two and three-dimensional echocardiography, Doppler parameters, Tissue Doppler Imaging systolic and diastolic LV velocities and GS obtained by STE. Results: Compared with controls, LV volumes were higher in the DCM group; however, LVEF and peak E-wave velocity were lower in the latter. The myocardial performance index was higher in the patient group. Tissue Doppler myocardial velocities (S', e', a') were significantly lower and E/e' ratio was higher in the DCM group. GS was decreased in the DCM group (-5.5% +/- 2.3%) when compared with controls (-14.0% +/- 1.8%). Conclusion: In this study, GS was significantly lower in patients with severe DCM, bringing new perspectives for therapeutic approaches in this specific population. (Arq Bras Cardiol 2012;99(3):834-842)

Measurement of event background fluctuations for charged particle jet reconstruction in Pb-Pb collisions at root s(NN)=2.76 TeV

The effect of event background fluctuations on charged particle jet reconstruction in Pb-Pb collisions at root s(NN) = 2.76 TeV has been measured with the ALICE experiment. The main sources of non-statistical fluctuations are characterized based purely on experimental data with an unbiased method, as well as by using single high p(t) particles and simulated jets embedded into real Pb-Pb events and reconstructed with the anti-k(t) jet finder. The influence of a low transverse momentum cut-off on particles used in the jet reconstruction is quantified by varying the minimum track p(t) between 0.15 GeV/c and 2 GeV/c. For embedded jets reconstructed from charged particles with p(t) &gt; 0.15 GeV/c, the uncertainty in the reconstructed jet transverse momentum due to the heavy-ion background is measured to be 11.3 GeV/c (standard deviation) for the 10% most central Pb-Pb collisions, slightly larger than the value of 11.0 GeV/c measured using the unbiased method. For a higher particle transverse momentum threshold of 2 GeV/c, which will generate a stronger bias towards hard fragmentation in the jet finding process, the standard deviation of the fluctuations in the reconstructed jet transverse momentum is reduced to 4.8-5.0 GeV/c for the 10% most central events. A non-Gaussian tail of the momentum uncertainty is observed and its impact on the reconstructed jet spectrum is evaluated for varying particle momentum thresholds, by folding the measured fluctuations with steeply falling spectra.

Impact of the Manaus urban plume on trace gas mixing ratios near the surface in the Amazon Basin: Implications for the NO-NO2-O-3 photostationary state and peroxy radical levels

We measured the mixing ratios of NO, NO2, O-3, and volatile organic carbon as well as the aerosol light-scattering coefficient on a boat platform cruising on rivers downwind of the city of Manaus (Amazonas State, Brazil) in July 2001 (Large-Scale Biosphere-Atmosphere Experiment in Amazonia-Cooperative LBA Airborne Regional Experiment-2001). The dispersion and impact of the Manaus plume was investigated by a combined analysis of ground-based (boat platform) and airborne trace gas and aerosol measurements as well as by meteorological measurements complemented by dispersion calculations (Hybrid Single-Particle Lagrangian Integrated Trajectory model). For the cases with the least anthropogenic influence (including a location in a so far unexplored region similar to 150 km west of Manaus on the Rio Manacapuru), the aerosol scattering coefficient, sigma(s), was below 11 Mm(-1), NOx mixing ratios remained below 0.6 ppb, daytime O-3 mixing ratios were mostly below 20 ppb and maximal isoprene mixing ratios were about 3 ppb in the afternoon. The photostationary state (PSS) was not established for these cases, as indicated by values of the Leighton ratio, Phi, well above unity. Due to the influence of river breeze systems and other thermally driven mesoscale circulations, a change of the synoptic wind direction from east-northeast to south-southeast in the afternoon often caused a substantial increase of ss and trace gas mixing ratios (about threefold for sigma(s), fivefold for NOx, and twofold for O-3), which was associated with the arrival of the Manaus pollution plume at the boat location. The ratio F reached unity within its uncertainty range at NOx mixing ratios of about 3 ppb, indicating "steady-state" conditions in cases when radiation variations, dry deposition, emissions, and reactions mostly involving peroxy radicals (XO2) played a minor role. The median midday/afternoon XO2 mixing ratios estimated using the PSS method range from 90 to 120 parts per trillion (ppt) for the remote cases (sigma(s) &lt; 11 Mm(-1) and NOx &lt; 0.6 ppb), while for the polluted cases our estimates are 15 to 60 ppt. These values are within the range of XO2 estimated by an atmospheric chemistry box model (Chemistry As A Box model Application-Module Efficiently Calculating the Chemistry of the Atmosphere (CAABA/MECCA)-3.0).

Exact correlation functions in particle-reaction models with immobile particles

Exact results on particle densities as well as correlators in two models of immobile particles, containing either a single species or else two distinct species, are derived. The models evolve following a descent dynamics through pair annihilation where each particle interacts once at most throughout its entire history. The resulting large number of stationary states leads to a non-vanishing configurational entropy. Our results are established for arbitrary initial conditions and are derived via a generating function method. The single-species model is the dual of the 1D zero-temperature kinetic Ising model with Kimball-Deker-Haake dynamics. In this way, both in finite and semi-infinite chains and also the Bethe lattice can be analysed. The relationship with the random sequential adsorption of dimers and weakly tapped granular materials is discussed.