Direction Of Motion Research Articles

Optimization in Visual Motion Estimation.

Sighted animals use visual signals to discern directional motion in their environment. Motion is not directly detected by visual neurons, and it must instead be computed from light signals that vary over space and time. This makes visual motion estimation a near universal neural computation, and decades of research have revealed much about the algorithms and mechanisms that generate directional signals. The idea that sensory systems are optimized for performance in natural environments has deeply impacted this research. In this article, we review the many ways that optimization has been used to quantitatively model visual motion estimation and reveal its underlying principles. We emphasize that no single optimization theory has dominated the literature. Instead, researchers have adeptly incorporated different computational demands and biological constraints that are pertinent to the specific brain system and animal model under study. The successes and failures of the resulting optimization models have thereby provided insights into how computational demands and biological constraints together shape neural computation.

Revisiting the 1934 Mw 8.2 Bihar–Nepal earthquake—Simulation of broadband ground motions

SUMMARY The 1934 Mw 8.2 Bihar–Nepal earthquake was one of the devastating earthquakes, which made seismologists realize the importance of proper seismic hazard analysis and design aspects in India. The event occurred way before proper seismic networks were implemented and hence there are no recorded ground motions available for this event. This study, thus aims to generate possible ground motions for the 1934 Mw 8.2 Bihar–Nepal event. The complex geographical features, ambiguous source information and lack of ground motion data make the simulation and validation of ground motions very difficult. In this regard, the broad-band (BB) ground motions are simulated and validated for the most recent well-documented Himalayan event, that is, the 2015 Mw 7.9 Nepal earthquake in order to calibrate the model and simulation methodology. For this purpose, the computational model is presented for a region of 1000 km × 670 km (longitude 80–89 °E and latitude 23–30 °N) in the Indo-Gangetic Basin to simulate the low-frequency (LF) ground motions using spectral element method. These deterministically simulated LF ground motions are combined with stochastically simulated high-frequency (HF) ground motions based on an improved seismological model . The seismic moment and dimensions of the rupture plane are used to generate ten samples for the finite fault source model having different slip distribution along the rupture plane as a random field. The BB ground motions (0.01–25 Hz) are obtained by merging LF and HF ground motions in the time domain by matching them at a frequency of ∼0.3 Hz. Such BB results are simulated at a grid of stations and at locations where modified Mercalli intensity (MMI) values are available. The estimated MMI values and the observed MMI values are compared to emphasize the efficacy of the model. The maximum PGA estimated from the simulated ground motions in horizontal and vertical directions are observed to be 0.48 g and 0.4 g. Further, 5 per cent damped response spectra and spectral amplification are analysed concerning the sediment depth of the Indo-Gangetic Basin. The results from the study can serve as inputs for dynamic analysis and the design of earthquake-resistant structures across different locations in the Indo-Gangetic Basin.

Kinematic analysis and experimental validation of a tripod parallel continuum manipulator

A tripod is a classical lower mobility parallel manipulator with three degrees of freedom. The usual geometrical constraints enforce a type of motion with two rotations on a horizontal plane and a translational motion in a vertical direction. These devices are applicable where a task requires a precise orientational motion. Nevertheless, some parasitic motions occur on the constrained degrees of freedom. Parallel Continuum Manipulators are devices where some elements have been replaced by slender rods whose deformation is source of mobility, allowing the elimination of some of the kinematic joints. This type of closed-loop compliant mechanisms have some features that can be useful in certain applications, e.g., the deformed state introduces a certain preload that avoids backslash, they have an inherent compliance that can be useful in some delicate tasks, and a certain control on wrench applied can be obtained. In this article, the comprehensive kinetostatic analysis of a tripod-type parallel continuum manipulator, 3 P ¯ FS , is explained and compared with that of its rigid counterpart 3 P ¯ RS . Workspace and singularity locus is obtained, positioning accuracy and wrench generation are evaluated experimentally.

A calibration method for telecentric line-scan cameras with an enhanced dynamic imaging model and initial estimates derived from direct linear transformation

This study presents a calibration method for telecentric line-scan cameras, incorporating a dynamic imaging model and initial estimates derived from direct linear transformation. The enhanced dynamic imaging model includes an inclination parameter instead of velocities in three orthogonal spatial directions. It is applicable to any direction of motion, considers lens distortion, and accommodates the line sensor at an arbitrary position relative to the optical axis. Employing the enhanced camera model, the initial values of telecentric line-scan camera parameters are determined derived from direct linear transformation. Sensitivity of our method with respect to the noise level of image points and the number of pattern planes are assessed through numerical simulations, while effectiveness and robustness are validated through experiments using real-world data, achieving a reprojection error of 0.6386 pixels and a standard deviation of 0.0160 pixels. The versatility of the proposed method can be extended to measurement applications utilizing flatbed scanners.

Micro magnetic field sensor based on bifunctional diodes

Multiple-quantum well (MQW) diodes can be used as bifunctional diodes due to the emission-detection spectral overlap. When integrated with magnetic fluids (MFs) that have tunable refractive index, they can be designed as micro magnetic field sensors. The sapphire substrate of the MQW diode chip that consists of an MQW transmitter and receiver that is directly exposed to the MF, and the external magnetic field strength is used to change the refractive index at the boundary between the sapphire and the MF, thus modulating the reflected light and realizing external magnetic field sensing. Verified by experimental measurements, the micromagnetic field sensor has a detection range of 0.001-0.05 T, a sensitivity of 127.3 µA/T, and a resolution of 4.5×10−5 T, with excellent stability and repeatability. Additionally, the sensor demonstrates good velocity resolution under dynamic magnetic fields and can detect the direction of magnetic field motion, providing significant application value.

Discriminating Clockwise and Counterclockwise Photoisomerization Paths in Achiral Photoswitches by Excited-State Electronic Circular Dichroism.

Despite the numerous investigations of photoisomerization reactions from both the computational and experimental points of view, even in complex environments, to date there is no direct demonstration of the direction of rotation of the retinal chromophore, initiating the vision process in several organisms, occurring upon light irradiation. In the literature, many proposals have been formulated to shed light on the details of this process, most of which are extracted from semiclassical simulations. Although high hopes are held in the development of time-resolved X-ray spectroscopy, I argue in this work that simpler but less known techniques can be used to unravel the details of this fascinating photochemical process. In fact, chiroptical spectroscopy would unambiguously prove the direction of the rotatory motion of the chromophore during the photoisomerization process by probing excited state chirality, a piece of information that, so far, has been exclusively extracted from atomistic simulations. I demonstrate this statement by computing the expected chiroptical response along photoisomerization pathways for several models of the retinal chromophores that are found in nature bound to rhodopsins, including nuclear ensemble spectra from semiclassical dynamics simulations, that can be compared with time-resolved experiments.

Surface Passivation of Norland Optical Adhesive Improves the Guiding Efficiency of Gliding Microtubules in Microfluidic Devices.

The microtubule-kinesin biomolecular motor system, which is vital for cellular function, holds significant promise for nanotechnological applications. In vitro gliding assays have demonstrated the ability to transport microcargo by propelling microtubules across kinesin-coated surfaces. However, the uncontrolled directional motion of microtubules has posed significant challenges, limiting the system's application for precise cargo delivery. Microfluidic devices provide a means to direct microtubule movement through their geometric features. Norland Optical Adhesive (NOA) is valued for its mold-free application in microfluidic device fabrication; however, microtubules often climb up channel walls, limiting controlled movement. In this study, a surface passivation method for NOA is introduced, using polyethylene glycol via a thiol-ene click reaction. This technique significantly improved the directional control and concentration of microtubules within NOA microchannels. This approach presents new possibilities for the precise application of biomolecular motors in nanotechnology, enabling advancements in the design of microfluidic systems for complex biomolecular manipulations.

Confined antiskyrmion motion driven by electric current excitations

Current-driven dynamics of topological spin textures, such as skyrmions and antiskyrmions, have garnered considerable attention in condensed matter physics and spintronics. As compared with skyrmions, the current-driven dynamics of their antiparticles – antiskyrmions − remain less explored due to the increased complexity of antiskyrmions. Here, we design and employ fabricated microdevices of a prototypical antiskyrmion host, (Fe0.63Ni0.3Pd0.07)3P, to allow in situ current application with Lorentz transmission electron microscopy observations. The experimental results and related micromagnetic simulations demonstrate current-driven antiskyrmion dynamics confined within stripe domains. Under nanosecond-long current pulses, antiskyrmions exhibit directional motion along the stripe regardless of the current direction, while the antiskyrmion velocity is linearly proportional to the current density. Significantly, the antiskyrmion mobility could be enhanced when the current flow is perpendicular to the stripe direction. Our findings provide novel and reliable insights on dynamical antiskyrmions and their potential implications on spintronics.

Clutaxis: an information-driven source search method balancing exploration and exploitation in turbulent environments

Locating unknown emission sources in turbulent environments is a challenging yet crucial task, particularly in emergency response scenarios. Existing studies have developed information-theoretic approaches to fuse intermittent information collected by mobile sensors regarding the sources. This fused information is then used to support source-term estimation (STE) in various search algorithms. Among these, the cognitive strategy—a promising information-driven search algorithm—leverages a reward-based action selection mechanism to balance exploration and exploitation during each search step. However, this mechanism is hampered by a high computational load and rigid search trajectories, limiting its application in real-world systems. To address these issues, this paper proposes a novel information-driven search method called Clutaxis, based on a global exploration and exploitation tradeoff principle. Specifically, a particle filter is leveraged to maintain the STE. After projecting the particle filter samples onto a 2D search scene, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to extract the density information of the samples, which is then used to construct a belief source area (BSA). By leveraging the uncertainty of the BSA, Clutaxis adopts explorative or exploitative actions with no restrictions on motion direction. Through dedicated simulations, the experimental results demonstrate the robustness of Clutaxis to key parameters and its advantages in computational complexity and search performance compared to two state-of-the-art algorithms (Infotaxis and Entrotaxis) and two Clutaxis variants (Clutaxis_ER and Clutaxis_EI).

Numerical investigation of wingtip aerodynamic interference of two flapping wings on opposite sides

Aerodynamic interference occurs at the wingtips when flying organisms fly in a V formation. In this paper, the wingtip aerodynamic interference of two flapping wings on opposite sides at low Reynolds numbers (Re) is numerically investigated. The effects of streamwise spacing (L1), spanwise spacing (L2), and phase angle (γ) on aerodynamic performance are considered. The results show that, compared to a single wing, a favorable combination of L1 and L2 can improve the overall thrust by 24% while keeping the overall lift essentially unchanged. In an unfavorable case, overall lift and thrust decrease by 18% and 20%, respectively. The overall aerodynamic forces are dominated by the rear wing. Analyzing the essential flow characteristics reveals the double-edged role of downwash and upwash in force generation. Moreover, it is found that the rear wing can realize the upwash/downwash exploitation by flap phasing, turning an unfavorable situation into a favorable one. The key flow physics behind this transformation lies in the relationship between the direction of wing motion and the direction of fluid velocity induced by vortices. These findings provide valuable insights into the understanding of biological phenomena and the design of new flapping wing vehicles.

Anomalous droplet transfer by surface acoustic waves through a microgap under a thin barrier

The transfer of droplets through a microgap under a thin barrier in the direction opposite to the motion of the surface acoustic waves (SAWs) acting on them has been discovered. Initially, the droplets are in contact with the barrier on the side opposite the SAW source. Under the SAW action, the transfer of a significant portion of the droplet volume through the microgap to the opposite side of the barrier is observed. This is in contrast to the behavior of droplets not in contact with the barrier. These droplets move in the direction of SAW motion. Experiments were performed to determine the effects of droplet size, SAW source power, and barrier wettability on the intensity of anomalous transfer. In addition, a computer simulation of a system simpler than the original was performed to identify the processes responsible for droplet growth on the side of the barrier facing the SAW source. Based on the analysis of the experimental and computational results, a model is proposed to explain the discovered phenomenon. The model assumes that the initial stage of anomalous transfer is due to atomization–coalescence, and the subsequent, more intense stage is due to the specificity of the streams circulating in the growing droplets. The article also shows that in a system of two parallel barriers, anomalous transfer allows either droplet division or droplet division and mixing.

Neutrino halo profiles: HR-DEMNUni simulation analysis

Using the high-resolution HR-DEMNUni simulations, we computed neutrino profiles within virialized dark matter haloes. These new high-resolution simulations allowed us to revisit fitting formulas proposed in the literature and provided updated fitting parameters that extend to less massive haloes and lower neutrino masses than previously in the literature, in accordance with new cosmological limits. The trend we observe for low neutrino masses is that, for dark matter halo masses below ∼ 4 × 1014 h -1 M ⊙, the presence of the core becomes weaker and the profile over the whole radius is closer to a simple power law. We also characterised the neutrino density profile dependence on the solid angle within clustered structures: a forward-backward asymmetry larger than 10% was found when comparing the density profiles from neutrinos along the direction of motion of cold dark matter particles within the same halo. In addition, we looked for neutrino wakes around halo centres produced by the peculiar motion of the halo itself. Our results suggest that the wakes effect is present in haloes with masses greater than 3 × 1014 h -1 M ⊙ where a mean displacement of 0.06h -1Mpc was found.

Unilateral buckling of thin plates by complementarity eigenvalue analyses

In this work, the analysis by the finite element method of thin plates subjected to buckling in the presence of unilateral punctual obstacles, that is, supports that allow the plate to move in one direction but prevent the motion in the opposite direction, is addressed. An appropriate algorithm based on the solution of a semi-smooth system of equations, that results from the formulation of the unilateral buckling problem as a complementarity eigenvalue problem, is used. Rectangular and square plates are analysed under various membrane loadings, including compression and shear. The conformal Bogner–Fox–Schmit (BFS) finite element is employed to compute the bifurcation loads and the corresponding instability modes in scenarios with and without unilateral obstacles. For each plate and type of loading, the six lowest bifurcation loads and corresponding modes are computed for different levels of mesh refinement. The results confirm that the convergence of bifurcation loads obtained using the BFS element is monotonically decreasing as the mesh is refined. It is also confirmed that, when unilateral obstacles are present, the lowest bifurcation load, known as the critical load, can never be lower than the one of the homologous problem without unilateral obstacles.

Femtosecond trimer quench in the unconventional charge-density-wave material 1T′−TaTe2

Ultrafast optical switching of materials properties promises future technological applications, enabled by fundamental insights about microscopic couplings and nonequilibrium phenomena. Transition-metal dichalcogenides (TMDCs) combine photosensitivity with strong correlations, furthering rich phase diagrams and enhanced tunability. The compound 1T′−TaTe2 exhibits an electronically and structurally unique set of charge density waves (CDWs), featuring an unusual increase in conductivity and amplitude modes of low prominence. Compared to other charge-ordered TMDCs, only very few studies addressed the ultrafast response of this material to optical excitation. In particular, the question whether such unconventional properties translate to unusual quench dynamics remains largely unresolved. Here, we investigate the structural dynamics in 1T′−TaTe2 by means of ultrafast nanobeam electron diffraction at an unprecedented repetition rate of 2MHz. We reveal a strongly directional cooperative atomic motion during the one-dimensional quench of the low-temperature trimer lattice. These dynamics are completed within less than 500fs, substantially faster than reported previously. In striking contrast, the periodic lattice distortion of the room-temperature phase is unusually robust against high-density electronic excitation. In conjunction with the known sensitivity of 1T′−TaTe2 to chemical doping, we thus expect the material to serve as a versatile platform for tunable structural control by optical stimuli. Published by the American Physical Society 2024

A Learning Dendritic Neuron-Based Motion Direction Detective System and Its Application to Grayscale Images.

In recent research, dendritic neuron-based models have shown promise in effectively learning and recognizing object motion direction within binary images. Leveraging the dendritic neuron structure and On-Off Response mechanism within the primary cortex, this approach has notably reduced learning time and costs compared to traditional neural networks. This paper advances the existing model by integrating bio-inspired components into a learnable dendritic neuron-based artificial visual system (AVS), specifically incorporating mechanisms from horizontal and bipolar cells. This enhancement enables the model to proficiently identify object motion directions in grayscale images, aligning its threshold with human-like perception. The enhanced model demonstrates superior efficiency in motion direction recognition, requiring less data (90% less than other deep models) and less time for training. Experimental findings highlight the model's remarkable robustness, indicating significant potential for real-world applications. The integration of bio-inspired features not only enhances performance but also opens avenues for further exploration in neural network research. Notably, the application of this model to realistic object recognition yields convincing accuracy at nearly 100%, underscoring its practical utility.

Load motion on an ice cover in the presence of a liquid layer with velocity shear

The behavior of an ice cover on the surface of an ideal incompressible fluid of finite depth under the action of a pressure domain that moves rectilinearly at a constant velocity in the presence of a current with velocity shift in the upper layer is studied. It is assumed that the ice deflection is steady in the coordinate system moving with the load. The Fourier transform method is used within the framework of the linear wave theory. The critical velocities, the deflection of ice cover, and the wave forces are studied depending on the current velocity gradient, the shear layer thickness, the direction of motion, and the compression ratio.

Analysis of Sidewalk Traffic Lights Setting Modes Optimization

There are often some problems with the traditional setting mode of traffic lights, especially on some non-main roads. The unreasonable setting of pedestrian traffic lights can easily lead to empty spaces for people and vehicles, waste resources, and increase the risks of traffic congestion, Although the push-button traffic lights improves traffic efficiency, there is still a waste of waiting time for pedestrians and vehicles due to the fixed setting of the traffic time. This article mainly studies the use of machine learning to solve the recognition, motion direction, and time models of people and vehicles, and optimize pedestrian traffic light signals. By identifying pedestrians and vehicles and allocating release signal time reasonably, the waiting time of pedestrians and vehicles crossing the road can be reduced, and traffic accidents can be minimized. The optimized traffic system is applied to sidewalks on non-main roads, it can replace the push-button traffic lights, reduce manual intervention, save construction costs, and improve traffic efficiency.

Directional Adaptive Triboelectric Nanogenerator with Wind-Wave Synergy.

To enhance the adaptability and synergy of the triboelectric nanogenerator (TENG) in a wave environment, this paper introduces a directional adaptive triboelectric nanogenerator (DA-TENG) with wind-water synergistic action for wave energy collection. An innovative design combining a wind vane on the top and fan-shaped blade electrodes internally allows the DA-TENG to adjust its swinging direction adaptively to align with the direction of wave motion. The internal multiple power generation units work in coordination, effectively addressing the issues of low efficiency associated with spherical TENGs in capturing multidirectional wave energy. The DA-TENG demonstrates superior performance under various wind speed conditions, showcasing its practical application potential. Experimental results show that the DA-TENG, equipped with a single tail wind vane and a 700 g mass block, can achieve an output voltage, current, and charge of 374.97 V, 84.77 μA, and 622.69 nC under a mild wind environment. Its peak power density reaches 7.51 W m-3, enabling successful data transmission for a wireless temperature and humidity sensor and powering 248 light-emitting diodes (LEDs). This research expands the possibilities of omnidirectional wave energy collection and the collaborative operation of multiple power generation units, offering an effective method for powering low-power maritime devices.

The IGD-based prediction strategy for dynamic multi-objective optimization

In recent years, an increasing number of prediction-based strategies have shown promising results in handling dynamic multi-objective optimization problems (DMOPs), and prediction models are also considered to be very favorable. Nevertheless, some linear prediction models may not always be effective. In particular, when the motion direction trends of different individuals are not aligned, these models can yield inaccurate prediction results. Inverted generational distance (IGD) is a commonly used metric for evaluating the performance of algorithms. This paper proposes a prediction model based on the IGD metric. Specifically, we assume that the pareto optimal front (POF) of the population at the previous time step is the true POF, and the POF at the current time step is the approximate POF. We cluster the current population with reference to the euclidean distances from uniform points on the true POF to the current POF points, with slight overlap between adjacent clusters, enables a better tradeoff between convergence and diversity in the prediction process. We consider the movement directions of individuals within each cluster separately through different cluster distributions, while balancing the individual movement directions and the overall population movement direction by overlaying cluster coverage areas, thereby helping to avoid the clustered prediction population from getting trapped in local optima. Experimental results and comparisons with other algorithms demonstrate that this strategy exhibits strong competitiveness in handling DMOPs.

Inbound friend or foe: how motion bistability is resolved under threat

Anxiety prepares us to deal with unpredictable threats, such as the approaching of an unknown person. Studies have shown our innate tendency to see approaching motion in ambiguous walkers in what was termed facing-the-viewer (FTV) bias. Here we investigated if anxiety states further contributed to this bias, hypothesizing that such states would increase overall FTV biases. Throughout three Experiments, we asked participants to judge the motion direction of ambiguous point-light walkers and measured their respective FTV biases under safe and anxiety-related conditions induced via imagery (Experiment 1), screaming sounds (Experiment 2), and threat of shock (Experiment 3). Across all experiments, we showed that anxiety does not affect our tendency to perceive an approaching behavior in ambiguous walkers. Based on our findings, and the discrepancies found in the literature, we emphasize the need for future studies to paint a clearer picture on the nature and aspects capable of affecting this bias.