Front-back Asymmetry Research Articles

Gas Dynamical Friction on Accreting Objects

The drag force experienced by astronomical objects moving through gaseous media (gas dynamical friction) plays a crucial role in their orbital evolution. Ostriker derived a formula for gas dynamical friction by linear analysis, and its validity has been confirmed through subsequent numerical simulations. However, the effect of gas accretion onto the objects on the dynamical friction is yet to be understood. In this study, we investigate the Mach number dependence of dynamical friction considering gas accretion through three-dimensional nested-grid simulations. We find that the net frictional force, determined by the sum of the gravitational force exerted by surrounding gas and momentum flux transferred by accreting gas, is independent of the resolution of simulations. Only the gas outside the Bondi–Hoyle–Lyttleton radius contributes to dynamical friction, because the gas inside this radius is eventually absorbed by the central object and returns the momentum obtained through the gravitational interaction with it. In the subsonic case, the front–back asymmetry induced by gas accretion leads to larger dynamical friction than predicted by the linear theory. Conversely, in the slightly supersonic case with a Mach number between 1 and 1.5, the nonlinear effect leads to a modification of the density distribution in a way that reduces the dynamical friction, compared with the linear theory. At a higher Mach number, the modification becomes insignificant and the dynamical friction can be estimated with the linear theory. We also provide a fitting formula for dynamical friction based on our simulations, which can be used in a variety of applications.

Molecular mechanism of core planar cell polarity complex function elucidated with single-molecule methods.

The planar cell polarity (PCP) signaling pathway polarizes epithelial cells along an axis parallel to the epithelial sheet in order to generate front-back asymmetry at the tissue level. Failures in PCP signaling underlie developmental defects and diseases such as neural tube and heart defects, deafness and contribute to cancer. Six core PCP proteins assemble into large, asymmetric complexes at cell-cell junctions, with Vang and Prickle recruited to one side of the cell-cell junction while Frizzled and Dishevelled are recruited to the other. How this asymmetric assembly process occurs is not known. Genetic evidence suggests that the process of symmetry breaking at PCP clusters is coupled to cluster formation. To test how this occurs, we developed a method to count the number of each of the six core proteins in individual PCP complexes. Specifically, by analyzing bleaching traces obtained with a high frame rate in live Drosophila wing cells imaged using total internal reflection microscopy, we quantify the intensity of single fluorophores in each complex and thereby calculate the molecular number in the corresponding PCP complex. Using this approach, we find that the molecular size distribution of PCP complexes follows an exponential function, indicating a single underlying growth mechanism. We report that specifically, the number of Vang molecules in PCP complexes increases from 15 hours after puparium formation until reaching a steady state around 28 hours. Besides, we measure the asymmetry as a function of cluster size and test the dependence of the observed relationship by introducing gain and loss of function mutations that perturb cluster assembly. In conclusion, our findings provide a detailed understanding of how the PCP mechanism generates stable polarization during embryonic development.

A Novel Deep Learning Model for Sea State Classification Using Visual-Range Sea Images

Wind-waves exhibit variations both in shape and steepness, and their asymmetrical nature is a well-known feature. One of the important characteristics of the sea surface is the front-back asymmetry of wind-wave crests. The wind-wave conditions on the surface of the sea constitute a sea state, which is listed as an essential climate variable by the Global Climate Observing System and is considered a critical factor for structural safety and optimal operations of offshore oil and gas platforms. Methods such as statistical representations of sensor-based wave parameters observations and numerical modeling are used to classify sea states. However, for offshore structures such as oil and gas platforms, these methods induce high capital expenditures (CAPEX) and operating expenses (OPEX), along with extensive computational power and time requirements. To address this issue, in this paper, we propose a novel, low-cost deep learning-based sea state classification model using visual-range sea images. Firstly, a novel visual-range sea state image dataset was designed and developed for this purpose. The dataset consists of 100,800 images covering four sea states. The dataset was then benchmarked on state-of-the-art deep learning image classification models. The highest classification accuracy of 81.8% was yielded by NASNet-Mobile. Secondly, a novel sea state classification model was proposed. The model took design inspiration from GoogLeNet, which was identified as the optimal reference model for sea state classification. Systematic changes in GoogLeNet’s inception block were proposed, which resulted in an 8.5% overall classification accuracy improvement in comparison with NASNet-Mobile and a 7% improvement from the reference model (i.e., GoogLeNet). Additionally, the proposed model took 26% less training time, and its per-image classification time remains competitive.

Fabrication of Microparticles with Front-Back Asymmetric Shapes Using Anisotropic Gelation.

Droplet-based microfluidics is a powerful tool for producing monodispersed micrometer-sized droplets with controlled sizes and shapes; thus, it has been widely applied in diverse fields from fundamental science to industries. Toward a simpler method for fabricating microparticles with front–back asymmetry in their shapes, we studied anisotropic gelation of alginate droplets, which occurs inside a flow-focusing microfluidic device. In the proposed method, sodium alginate (NaAlg) aqueous phase fused with a calcium chloride () emulsion dispersed in the organic phase just before the aqueous phase breaks up into the droplets. The fused droplet with a front–back asymmetric shape was generated, and the asymmetric shape was kept after geometrical confinement by a narrow microchannel was removed. The shape of the fused droplet depended on the size of prefused NaAlg aqueous phase and a emulsion, and the front–back asymmetry appeared in the case of the smaller emulsion size. The analysis of the velocity field inside and around the droplet revealed that the stagnation point at the tip of the aqueous phase also played an important role. The proposed mechanism will be potentially applicable as a novel fabrication technique of microparticles with asymmetric shapes.

Front-back asymmetry controls the impact of viscoelasticity on helical swimming

We conduct experiments with force-free magnetically-driven rigid helical swimmers in Newtonian and viscoelastic (Boger) fluids. By varying the sizes of the swimmer body and its helical tail, we show that the impact of viscoelasticity strongly depends on the swimmer geometry: it can lead to a significant increase of the swimming speed (up to a factor of five), a similar decrease (also up to a factor of five) or it can have approximately no impact. Analysis of our data along with theoretical modeling shows that the influence of viscoelasticity on helical propulsion is controlled by a snowman-like effect, previously reported for dumbbell swimmers, wherein the front-back asymmetry of the swimmer leads to a non-Newtonian elastic force that can either favor or hinder locomotion.

A temporal phase-truncated double random phase encoding cryptosystem in the temporal skew Fourier transform domain

A temporal phase-truncated double random phase encoding cryptosystem is proposed to be improved by replacing the temporal Fourier transformers (TFTs) of the dispersion-time lens-dispersion structure with temporal skew Fourier transformers (TSFTs). A TSFT is similar to a TFT except for the time lens (TL) replaced by a skew time lens (STL). A STL is a temporal analog of a spatial cylindrical lens with the in-plane rotational asymmetry mapping to a front–back asymmetry. The front–back asymmetry is achieved by adding the chirp factor C of a TL by +ϵ⋅C and −ϵ⋅C respectively along the positive and negative half axis of the local time coordinate. The skew coefficients ϵ1 and ϵ2 of the two TSFTs involved in the encryption stage are dimensionless and ideally unbounded, serving as additional secret keys. By mathematical analysis, STLs are proven to have complex-value modulations on low frequency components of input signals of TSFTs, which cannot be removed by phase truncations (PTs) in the legal decryption stage. The plain/cipher-text-independent and non-removability features of STLs make phase retrieval attacks unable to exempt eavesdroppers from brute-force trials of STLs. A STL is implemented by an electrical arbitrary waveform generator (AWG) driven electro-optic phase modulator (EOPM). By numerical simulations, the using of STLs is proven to increase the difficulty of phase retrieval attacks in terms of the time consuming required for convergence. Even if phase retrieval attacks converge, the plaintext signal cannot be recovered without the knowledge of ϵ1,2 in the encryption stage. The total key space of ϵ1,2 is also evaluated as 217 at AWG bandwidth Bm=20 GHz, and as 237 at Bm=100 GHz. The fidelity robustness of our optical cryptosystem against possible noise and occlusion penalties on the communication channels and networks of optical cipher-text signals is also proven.

On the physical mechanism of front–back asymmetry of non-breaking gravity–capillary waves

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Wave asymmetry and particle orbits in irregular wave models

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On the distribution of helicity in the tropical cyclone boundary layer from dropsonde composites

This study analyzes GPS dropsonde data in multiple tropical cyclones from 1997 to 2017 to investigate the boundary layer structure with a focus on helicity distribution. A helicity-based method for boundary layer height is developed and evaluated by comparing it to other boundary layer height scales including the inflow layer depth, height of the maximum tangential wind speed and thermodynamic mixed layer depth. Our dropsonde composites confirmed the radial variations of these boundary layer heights seen in previous studies. The results show that the boundary layer height defined by the maximum vertical gradient of helicity is closest to the height of the maximum tangential wind speed or jet height and is located between the inflow layer depth and thermodynamic mixed layer height in all intensity groups. All three kinematic height scales generally decrease with storm intensity at a given radius. These kinematic height scales converge in the major hurricane group, while the inflow layer depth is much larger than the other two height scales in the tropical storm group. The maximum normalized helicity is located at 100–200 m altitude which is close to the height of the maximum inflow. Both front-back and downshear-upshear asymmetries are observed in the 0–1 km layer integrated helicity in the inner core region of a storm, and the helicity on the front and downshear sides is larger in all intensity groups. The results also show that the helicity magnitude is generally larger in the boundary layer of stronger storms. Application of helicity to quantify turbulent characteristics in the boundary layer is discussed.

Hurricane Boundary Layer Height Relative to Storm Motion from GPS Dropsonde Composites

This study investigates the asymmetric distribution of hurricane boundary layer height scales in a storm-motion-relative framework using global positioning system (GPS) dropsonde observations. Data from a total of 1916 dropsondes collected within four times the radius of maximum wind speed of 37 named hurricanes over the Atlantic basin from 1998 to 2015 are analyzed in the composite framework. Motion-relative quadrant mean composite analyses show that both the kinematic and thermodynamic boundary layer height scales tend to increase with increasing radius in all four motion-relative quadrants. It is also found that the thermodynamic mixed layer depth and height of maximum tangential wind speed are within the inflow layer in all motion-relative quadrants. The inflow layer depth and height of the maximum tangential wind are both found to be deeper in the two front quadrants, and they are largest in the right-front quadrant. The difference in the thermodynamic mixed layer depth between the front and back quadrants is smaller than that in the kinematic boundary layer height. The thermodynamic mixed layer is shallowest in the right-rear quadrant, which may be due to the cold wake phenomena. The boundary layer height derived using the critical Richardson number ( R i c ) method shows a similar front-back asymmetry as the kinematic boundary layer height.

Time‐change models for asymmetric processes

AbstractMany records in environmental sciences exhibit asymmetric trajectories. The physical mechanisms behind these records may lead for example to sample paths with different characteristics at high and low levels (up–down asymmetries) or in the ascending and descending phases leading to time irreversibility (front–back asymmetries). Such features are important for many applications, and there is a need for simple and tractable models that can reproduce them. In this paper, we explore original time‐change models where the clock is a stochastic process that depends on the observed trajectory. The ergodicity of the proposed model is established under general conditions, and this result is used to develop nonparametric estimation procedures based on the joint distribution of the process and its derivative. The methodology is illustrated on meteorological and oceanographic data sets. We show that, combined with a marginal transformation, the proposed methodology is able to reproduce important characteristics of the data set such as marginal distributions, up‐crossing intensity, and up–down and front–back asymmetries.

Diabatic Heating and Convective Asymmetries During Rapid Intensity Changes of Tropical Cyclones Over North Indian Ocean

ABSTRACT Rapid changes in Tropical Cyclone (TC) structure and intensity are the most difficult aspects of TC forecasting. The intensity and structural changes associated with rapid intensification (RI) and rapid weakening (RW) instances of TCs of North Indian Ocean (NIO) are analysed based on 5 cases each for RI and RW. The vertical profiles of heat (Q1) and moisture (Q2) based on heat and moisture budget equations are analysed to bring out the role of diabatic heating during the RI and RW processes. The associated structural changes are analysed based on the Fourier first order wave number-1 asymmetry in the precipitation patterns associated with RI and RW instances. During RI process, there are 2 predominant Q1 maxima associated with latent heat release near the TC centre, one in the upper troposphere and the other in the lower troposphere. During RW process, there is a single dominant Q1 and Q2 maxima in the mid-troposphere. Regarding the structural changes, there is a pronounced front-back asymmetry in both RI and RW cases. The asymmetry amplitude in the inner core is lower in the case of RI events but, is quite high for RW events. Thus, RW events are characterised by large convective asymmetry.

Comparison of a Lagrangian and a Gaussian model for power output predictions in a random sea

This paper concerns the prediction of the power output performances of an oscillating surge wave energy converter in irregular waves. The generated power has been calculated using a new methodology by incorporating a stochastic Lagrange wave model into a non-linear filter which takes also hydrodynamic forces into account. It is shown that the stochastic Lagrange wave model in this paper can be utilized to generate irregular waves with realistic crest-trough and front-back asymmetries, and when used in combination with the non-linear filter will produce more accurate power output predictions than the traditional Gaussian wave model can do. The research findings in this paper demonstrate that the stochastic Lagrange wave model together with a non-linear filter can be utilized as a robust tool for engineers in their design, analysis and optimization of wave energy converters.

Comment on “Calculated Trajectories of Curling Stones Under Asymmetrical Friction: Validation of Published Models”

It has been suggested that front–back asymmetry cannot account for the full curl distance of a curling rock [1]. It has also been proposed that this implies that front–back asymmetry cannot explain why curling rocks curl and cannot account for any of the curl distance. It is shown here that these views are inappropriate. Reasons for their erroneous statements are given. A simple analytical calculation is carried out to show that the full curl distance can be due solely to front–back asymmetry. Several examples are presented in which the front–back-asymmetric, thin-liquid-film model makes predictions which are confirmed experimentally or observationally. Consequently, the choice to dismiss this front–back asymmetry mechanism, which is made by the authors of the paper in question [1], is inappropriate.

Moving forward by localized translation

Cell Migration Proper development and morphogenesis requires many cells to coordinate movements that are influenced by local forces, or from the migration of cells under their own power. In mesenchymal cell migration, actin filaments at the front push the cell forward while the back portion is retracted. By comparing mRNA localization and translation rate in the forwardlocated protrusions relative to trailing section, Mardakheh et al. identify the mechanism by which front-back cell asymmetry is maintained. Protein translation in the front of the cell is critical to stabilize the protrusion and produce the cell's polarized morphology. Analyses reveal specific cis-regulatory mRNA UTR motifs and RNA-binding proteins, such as the exosome core complex, as important for cell migration asymmetry. Dev. Cell. 35 , 344 (2015).

Horseshoe-like patterns in first-order 3D random Gauss-Lagrange waves with directional spreading

The Gauss–Lagrange model for ocean waves describes the vertical and horizontal movements of water particles as three correlated Gaussian fields. The model can produce irregular waves, asymmetric in both vertical and horizontal direction, and by judicious choice of a single skewness parameter the front–back asymmetry can be regulated to realistic values. In this paper, it is shown that this additive model for shallow waters can also produce horseshoe-like patterns around moderate to high wave crests. Such phenomena are usually analyzed and described as nonlinear interaction effects between different frequencies. The tool in the paper is a Slepian model for the three-dimensional movements conditioned on a wave crest

Emergence of upstream swimming via a hydrodynamic transition.

We demonstrate that upstream swimming of sperm emerges via an orientation disorder-order transition. The order parameter, the average orientation of the sperm head against the flow, follows a 0.5 power law with the deviation from the critical flow shear rate (γ-γ_{c}). This transition is successfully explained by a hydrodynamic bifurcation theory, which extends the sperm upstream swimming to a broad class of near surface microswimmers that possess front-back asymmetry and circular motion.

Asymmetric waves in wave energy systems analysed by the stochastic Gauss–Lagrange wave model

The Gauss-Lagrange stochastic wave model is known to produce irregular waves with realistic degrees of asymmetry. We present the basic structure of the model and illustrate three of its characteristic properties: front-back asymmetry, particle orbits, and average horseshoe pattern. We also study the effect of a linear filter in a wave energy converting (WEC) system on asymmetry and on average power of the system.

Study on Doppler spectra of two-dimensional skewed sea surfaces

This paper deals with the effects of horizontal skewness on Doppler spectra. A.K. Fung et al. pointed out that the crests of the sea waves are tilted towards the wind direction, which is referred to as horizontal skewness. Although the nonlinear sea surface is more realistic than the linear one, it cannot embody the statistical front-back asymmetry of real sea waves due to the influence of the wind. Thus, the impact of horizontal skewness must be considered. The first-order modified Lagrange model for asymmetric ocean waves is combined with Monte Carlo method to produce the two-dimensional (2-D) time-varying skewed sea surfaces which are nonlinear and skewed simultaneously. Moreover, the second-order small-slope approximation method is used to calculate the scattering field and study the Doppler spectral characteristics from skewed sea surfaces. Horizontal skewness makes Doppler spectra broader in upwind case, but narrower in downwind case. In addition, the impact of horizontal skewness on Doppler spectra is dependent on wind direction and incident elevation angle.

Modeling process asymmetries with Laplace moving average

Many records in environmental science exhibit asymmetries: for example in shallow water and with variable bathymetry, the sea wave time series shows front–back asymmetries and different shapes for crests and troughs. In such situation, numerical models are available but their computational cost and complexity are high. A stochastic process aimed at modeling such asymmetries has recently been proposed, the Laplace moving average process, which consists in applying a linear filter on a non-Gaussian noise built using the generalized Laplace distribution. The objective is to propose a new non-parametric estimator for the kernel involved in the definition of this process. Results based on a comprehensive numerical study will be shown in order to evaluate the performances of the proposed method.