Verification of an algorithm for actin tail detection of subviral particles by comparison with expert validated data

The locomotion of subviral particles of Marburg virus has been shown to be primarily actin based. For this work, a virologist selected 14 subviral particles that show actin tails in fluorescence image sequences. Using the tracked coordinates, examination areas around these subviral particles are defined. The brightness of within the examination area behind the subviral particle is analysed. In addition, the speed of the particle in each frame is calculated to investigate potential correlations between actin activity and particle speed. The results show that actin tracks can be automatically detected and analysed. First hints of a correlation between subviral particle movement and actin activity could be gathered with the presented actin tail quantifier.

Uncertainty-induced instantaneous speed and acceleration of a levitated particle

Levitating nanoparticles trapped in optical potentials at low pressure open the experimental investigation of nonlinear ballistic phenomena. With engineered non-linear potentials and fast optical detection, the observation of autonomous transient mechanical effects, such as instantaneous speed and acceleration stimulated purely by initial position uncertainty, are now achievable. By using parameters of current low pressure experiments, we simulate and analyse such uncertainty-induced particle ballistics in a cubic optical potential demonstrating their evolution, faster than their standard deviations, justifying the feasibility of the experimental verification. We predict, the maxima of instantaneous speed and acceleration distributions shift alongside the potential force, while the maximum of position distribution moves opposite to it. We report that cryogenic cooling is not necessary in order to observe the transient effects, while a low uncertainty in initial particle speed is required, via cooling or post-selection, to not mask the effects. These results stimulate the discussion for both attractive stochastic thermodynamics, and extension of recently explored quantum regime.

The Dual Character of MAX Phase Nano-Layered Structure Highlighted by Supersonic Particles Deposition

MAX phase compounds offer an attractive mixture of ceramic–metallic properties due to their covalent ionic–metallic nature. Since their discovery, a great interest was attributed to their synthesis and potential applications, but the processing of pure compounds as coatings for industrial large-scale application is still considered a challenge. To date, a limited number of papers have evaluated the build-up of MAX phase coating by cold spray (CS), a novel cost-effective and productive spray technology used in both areas of research and industry. Employing CS, the hot gas-propelled material particles have ballistic impingement on a substrate where they undergo plastic deformation. Because of the brittleness, internal delamination, and limited deformability, the deposition of the pure MAX phase is rather challenging. This paper presents the building-up ability of dense MAX-phase coatings by CS with retained structures and compositions, in close relation with the substrate characteristics and phase composition that influences the dual character ceramic–metallic behaviour. Besides recent literature, the originality of this research consists of pioneering deposition of Ti3AlC2 that emphasizes the ceramic–metallic character influenced by the particle speed and the mechanical properties of both substrate and compound.

Dust Telescopes for Dust Astronomy

<p>Dust Astronomy investigates the nature and the origin of dust particles in space. The particle size distribution ranges from nanodust to approximately 100 micrometer. The study of the elemental and/or chemical composition of the particles together with the knowledge about their origin provides insights into many disciplines. Dust Astronomy is an interdisciplinary working field, which includes Solar System Science, Interstellar Medium studies and Astrobiology. A basic tool for these studies are Dust Telescopes.</p> <p>Dust Telescopes are in-situ instruments to characterize individual dust particles by their velocity vector, size and composition. They are based on impact ionization used for time-of-flight compositional analysis and on charge induction for particle speed and size measurements.<span class="Apple-converted-space"> </span></p> <p>In this sense, already the Cassini Cosmic Dust Analyzer (CDA) was a simple Dust Telescope, which successfully characterized the dust environment at Saturn. Now, future missions go even further. In the next years the missions DESTINY+, EUROPA and IMAP will launch. In this talk, a summary is given about the capabilities of Dust Telescopes with a focus on the DESTINY+ Dust Analyser (DDA). DDA is a medium size instrument with a target diameter of 26 cm. A two-axis articulation allows to track dust RAM directions. Larger Telescopes like the record breaking LAMA instrument, developed especially for the measurement of low interstellar dust fluxes, and the instruments for the probes IMAP and EUROPA are compared with DDA.</p> <p>The paper will address questions about the detection of nanodust or, what is a good instrument approach for a Dust Observatory? What are the instrumental challenges for an Interstellar Probe?</p>

Computer Simulation of Low Frequency Vibration in Electrochemical Machining

This research studies how particles transport between low frequency vibrating electrodes during electrochemical machining (ECM). The ANSYS Fluent software was used to study the particle speed while the Star CCM+ software was utilized to study particle interactions during vibration-assisted ECM process. A series of simulations were conducted to calculate the particle average flushing speed. Collided particles either gained momentum or deflected their trajectories to accelerate in the flow of electrolyte. Simulation results showed that the highest average flushing speed of 0.4 m/s was obtained at 40 Hz vibration frequency and 10 µm vibration amplitude. Such higher flushing speed of particles improved machining depth (material removal rate) and produced a sharper machined profile. Experiment results confirmed that the maximum machining depth and minimum taper angle were obtained when vibrating the anodic workpiece at 40 Hz and 10 µm amplitude. Machining depth and ECM material removal rate had a positive correlation with the average flushing speed. A sharper ECM’ed profile was achieved since the taper angle was favorably reduced at high average flushing speed.

Macroscopic Lattice Boltzmann Method

The lattice Boltzmann method (LBM) is a highly simplified model for fluid flows using a few limited fictitious particles. It has been developed into a very efficient and flexible alternative numerical method in computational physics, demonstrating its great power and potential for resolving more and more challenging physical problems in science and engineering covering a wide range of disciplines such as physics, chemistry, biology, material science and image analysis. The LBM is implemented through the two routine steps of streaming and collision using the three parameters of the lattice size, particle speed and collision operator. A fundamental question is if the two steps are integral to the method or if the three parameters can be reduced to one for a minimal lattice Boltzmann method. In this paper, it is shown that the collision step can be removed and the standard LBM can be reformulated into a simple macroscopic lattice Boltzmann method (MacLAB). This model relies on macroscopic physical variables only and is completely defined by one basic parameter of the lattice size δx, bringing the LBM into a precise “lattice” Boltzmann method. The viscous effect on flows is naturally embedded through the particle speed, making it an ideal automatic simulator for fluid flows. Three additional advantages compared to the existing LBMs are that: (i) physical variables can directly be retained as the boundary conditions; (ii) much less computational memory is required; and (iii) the model is unconditionally stable. The findings are demonstrated and confirmed with numerical tests including flows that are independent of and dependent on fluid viscosity, 2D and 3D cavity flows and an unsteady Taylor–Green vortex flow. This provides an efficient and powerful model for resolving physical problems in various disciplines of science and engineering.

Non-resonant acceleration of charged particles driven by the associated effects of the radiation reaction

In the present analysis, we study effects of the radiation reaction (RR) on the dynamics of charged particles submitted to the action of localized longitudinal high-frequency carriers travelling at the speed of light. As the wave's crests and troughs keep overtaking particles, dissipative RR forces tend to drag particles alongside the wave in an effort to reduce the relative wave–particle speed. Particles of course never reach the phase velocity of the wave, but are instead driven to an ever-growing velocity, towards the speed of light, while in the wave localization region. We developed a modified average Hamiltonian formalism capable of describing the intricacies of the corresponding dynamics. The modified formalism agrees with simulations and is of particular usefulness in the study of optimum values for the localization length and maximum wave amplitude.

Horizontal projectile motion: comparing free fall and drag resistance

The motion of a particle that is projected into a resistant medium and subjected to a uniform gravitational field is considered. The drag force that acts upon the particle within the medium is proportional to the particle’s speed, the density of the medium, and the cross-section area of the projectile. We review the problem of a horizontal motion with a drag force that is linear in speed. The problem is formulated in terms of particle speed, mass, height, time, and expelled gas velocity. The equations of motion are solved analytically, and a case study is discussed. As a result, we obtain the deviation of the projectile as a function of time because of the expelled gases with or without drag force.

An exact solution of cosmic ray modulation problem in a stationary composite heliosphere model

ABSTRACT A new theoretical approach to describe the physical processes of energy particle propagation is proposed. This approach is based on the analytically iterative method for solving closed cosmic ray (CR) modulation problems, which was proposed by Shakhov and Kolesnyk. First, we have applied the approach on a simple model of the heliosphere, wherein the diffusion coefficients κ for each region of CR modulation are constants. This approach produced a very good matching of the obtained solution and also provided a numerical solution and an analytical solution. Finally, a modern problem of CR modulation in a stationary composite model of the heliosphere was considered. This model includes an environment that contains adjacent spherically symmetric regions with different modes of propagation of the solar wind (SW) speed for each layer. The CR scattering is due to different factors for each layer of the environment, as characterized by relevant κ values that simultaneously have dependence on the momentum of the particle p and the particle speed $\upsilon$, i.e. $\kappa \propto p\upsilon$. The local interstellar spectra (LISs) are given by a power-law unmodulated spectrum with the slope of the initial spectrum α, i.e. LIS ∝ p−α. An exact solution of the problem of CR modulation for low-energy particles and high-energy particles was first derived and qualitatively compared against the Voyager 1 data.

MODEL FEED FORWARD NEURAL NETWORK (FFNN) DENGAN ALGORITMA PARTICLE SWARM SEBAGAI OPTIMASI BOBOT (Studi Kasus : Harga Daging Sapi dari Bank Dunia Periode Januari 2007 – Desember 2018)

Beef is one of the important food commodities to fulfill the nutritional adequacy of humans. The World Bank notes the beef prices that are exported worldwide every month. For this reason, those data becomes a predictable series for the next period. Feed Forward Neural Network is a non-parametric method that can be used to make predictions from time series data without having to be bound by classical assumptions. The initiated weight will be evaluated by an algorithm that can minimize errors. Particle Swarm Optimization (PSO) is an optimization algorithm based on particle speed to reach the destination. The FFNN model will be combined with PSO to get predictive results that are close to the target. The best architecture on FFNN is obtained with 2 units of input, 1 unit of bias, 3 hidden units, and 1 unit of output by producing MAPE training 11.7735% and MAPE testing 8.14%. According to Lewis (1982) in Moreno et. al (2013), the MAPE value below 10% is highly accurate forecasting. Keywords: Feed Forward Neural Network (FFNN), Particle Swarm Optimization (PSO), neurons, weights, predictions.