Direction Of Motion Research Articles

IMPACT OF SEISMIC ZONES ON THE STRUCTURAL DESIGN OF HIGHRISE BUILDINGS FOR RECTANGULAR AND C-SECTION

Earthquakes induce vibrations in structures, causing motion in horizontal and vertical directions, with horizontal shaking being predominant. Proper consideration of lateral loads due to earthquakes is essential for designing earthquake-resistant reinforced concrete (RC) structures, especially high-rise buildings. This study analysesthe behaviour of a G+15 multi-storied RC building with a consistent story height of 3 meters, subjected to earthquake loads, using response spectrum analysis as per IS 1893 (Part-1): 2016. The seismic performance is evaluated for four seismic zones (II, III, IV, and V) using the ETABS software. Key parameters analysed include bending moment, shear force, lateral displacement, story shear, and story drift. Comparative results highlight the effects of varying seismic zone factors. The findings contribute to understanding structural behaviour under seismic conditions and optimizing designs for enhanced safety and performance in earthquake-prone regions. Keywords: Earthquake-resistant design, Seismic analysis, Response spectrum analysis, Reinforced concrete (RC) buildings, Seismic zones, ETABS, IS 1893 (Part-1): 2016.

Decoding covert visual attention to motion direction using graph theory features of EEG signals and quadratic discriminant analysis

Visual attention is a type of selective attention that plays an important role in prioritizing and processing the information received from the visual scenes around us. The brain is an intricate network composed of numerous regions, each with distinct functions. As different tasks are performed, brain regions regularly synchronize and correlate with each other through intricate networks of connections. The aim of this study is to decode two states of attention by examining the interactions and connections between different brain regions using graph theory. This is demonstrated by EEG recordings from 15 participants who performed visual attention task. Pearson's correlation coefficient and coherence have been used to measure the functional connections between brain regions. In fact, each of these two criteria is regarded as an individual feature, and we perform decoding using each criterion separately. With an optimal selection of 40 connectivity features, the QDA classifier attained accuracies of 79.83% and 83.28% using correlation and coherence features, respectively. The results of attention decoding using the coherence criterion are more promising, indicating the superior effectiveness of coherence-based methods. Therefore, this study employed graph theory to analyse a neural network derived from coherence measurements. The study focused on three graph-theoretical metrics: degree centrality, efficiency, and betweenness centrality. The QDA classifier, using an optimal set of 40 features that includes degree, betweenness, and channel efficiency, achieved an accuracy of 86.46%. In comparison, the QDA classifier with 40 features based solely on degree centrality reached an accuracy of 89.96%. Finally, the results of this research indicate that analysing brain connections and brain network graphs can effectively decode different covert visual attention states.

EFFECT OF EARTHQUAKE DIRECTIONALITY ON THE SEISMIC RESPONSE OF RC WALL BUILDINGS

Reinforced concrete (RC) wall buildings are widely used for their proven seismic resilience, as evidenced in past earthquakes. To understand their behavior, extensive research has been conducted using both experimental and numerical methods. Despite these efforts, the impact of earthquake directionality on these structures deserves further exploration. Addressing this gap, this paper examines the effects of earthquake directionality on three RC wall buildings. Eleven ground motion records from the far-field suite of the FEMA P695 were selected, rotated, and used to perform incremental dynamic analyses of the three buildings in OpenSeesPy. The buildings seismic performance was evaluated in terms of the roof drift ratio, axial load ratio, and bending moments. Additionally, a novel performance metric, namely the MaxRotEDPpp is introduced to assess the building’s response. The results show that the direction of ground motions has a significant impact on engineering demand parameters and in the probability of exceedance for different thresholds, which can double compared to non-rotated ground motions.

Biomechanical evaluation of the porcine carpus as a potential preclinical animal model for the human carpus

Advancing successful treatments for carpal instabilities of the wrist are hindered due, in part, to limited preclinical animal models. The purpose of this study was to evaluate the forelimb of the Yucatan minipig (YP) as a preclinical animal model for the human wrist by quantifying carpal biomechanics in vitro in the intact and after two ligament transection conditions. Porcine wrist biomechanics (n = 12, 5 M, 7F) were determined in 28 range of motion (ROM) directions, in pronation-supination, and in volar-dorsal translation using a six-axis robotic musculoskeletal simulator. Testing was implemented in three conditions – intact, and after sequential transection of radial intermediate ligament (RIL) and dorsal intercarpal ligament (DIC). Mixed models were employed to examine differences in direction and conditions among male and female specimens. The intact ROM envelope was elliptical in shape and oriented toward ulnar flexion with the largest ROM about 15° from the flexion–extension axis. Transection of RIL and DIC did not alter the ROM envelope orientation, however, subtle increases in ROM were observed in extension and radial deviation following transection of both RIL and DIC. Pronation in neutral was greater than supination in all three test conditions. Volar translation increased subtly in the RIL + DIC condition. This novel study investigated the multidirectional biomechanics of the YP forelimb. ROM in the general directions of extension, radial and ulnar deviation were less than in humans, while flexion was substantially larger. These specific ligament transections had minor effects on the biomechanics of the YP forelimb.

The Influence of a Sudden Impact Loading on the Creep, Damage, and Fracture of Beams Made From Functionally Graded Materials

ABSTRACTAn approach to the analysis of the influence of impact loading on creep, accumulation of hidden damage and fracture of structural elements made of functionally graded materials (FGM) is proposed. The approach is based on the analysis of additional damage caused by the impact loading and the stress redistribution caused by it. For the numerical modeling, finite element analysis was applied using algorithms for determining the size and direction of motion of macroscopic defects by means of the analysis of the time‐varying damage field. The fracture after an impact on a beam made from FGM is considered. The nature of fracture of a beam made of two‐layer metal‐ceramic material was studied. The advantages of using FGM to ensure a better long‐term response of a structural element to a non‐destructive impact loading are shown. An approach to determine the time until the complete fracture of the FGM beam by the simultaneous description of the motion of two cracks is proposed.

Artificial Visual Network with Fully Modeled Retinal Direction-Selective Neural Pathway for Motion Direction Detection in Grayscale Scenes

The complexity and functional evolution of mammalian visual systems have always been a focal point in neuroscience and biological science research. The primary neurons that output motion direction signals have been a focal point of research in visual neuroscience for nearly 130 years. These neurons are widely present in the cortex and retina of mammals. Although the relevant pathways have been discovered and studied for almost 60 years due to experimental accessibility, research still remains at the cellular level. The specific functions and overall operational mechanisms of the component neurons in the motion direction-selective pathways are yet to be clearly elucidated. In this study, we modeled existing relevant neuroscience conclusions based on the symmetry and asymmetry of whole cells in the retina-to-cortex pathway and proposed a quantitative mechanism for motion direction selectivity pathways, called the Artificial Visual System (AVS). By tests based on 1 million instances of 2D, eight-direction grayscale moving objects, including 10 randomly shaped objects of various sizes, we confirm AVS’s high effectiveness on motion direction detecting. Furthermore, by comparing the AVS with two well-known convolutional neural networks, namely LeNet-5 and EfficientNetB0, we verify its efficiency, generalization, and noise resistance. Moreover, the analysis indicates that the AVS exhibits evident biomimetic characteristics and application advantages concerning hardware implementation, biological plausibility, interpretability, parameter count, and learning difficulty.

Full-range displacement sensor with dual FBGs combined cantilever beam based on magnetic grating

We propose a full-range displacement sensor system based on double fiber Bragg gratings (FBGs) with a cantilever beam. This sensor adopts a magnetic scale as a unique transmission mechanism. By combining a simple and low-cost cantilever beam structure makes the sensing probe very easy to realize. The optimal magnetic gap was explored through multiple sets of numerical simulations. The experiment proved the sine relationship between the center wavelength shifts of FBGs and the linear displacement, proving the feasibility of this method. Results indicate that the amplitude of the tensile compression load of FBGs are 169.76 με and 296.12 με. The fitting linearity based on sinusoidal function at an air gap of 3.5 mm is 0.9663 and 0.9566. The direction of motion can be determined by the phase difference between two FBGs. Moreover, the difference of double FBGs can realize the effect of temperature compensation. Thus, this sensor can achieve non-contact, temperature-independent, and full-range measurements. It can also be exploited to measure other parameters such as angular velocity, acceleration, and magnetic field strength.

Estimations of biological motion walking direction are affected by observer and walker genders

A facing-towards bias is commonly reported when observers are asked to judge the motion directions of others. However, it remains unclear just how accurately observers are able to estimate the motion direction of others and whether the gender of the observer and the walker affects the direction estimation. Here, we asked male and female participants to estimate the direction of a point-light walker (PLW) in three experiments. The gender of PLWs was neutral (Experiment 1, 96 participants), clearly male or female (Experiment 2, 72 participants), or more subtlety male or female (Experiment 3, 98 participants). We found that female PLWs showed a stronger reference repulsion bias (RRB) than male PLWs. That is, for female PLWs, the estimates of facing directions were biased away from the boundaries of facing-towards, facing-away, and lateral (left/right)-motion directions. Interestingly, RRBs differed depending on whether the observer was male or female. When the PLW gender difference was clear, the RRB was stronger for female participants than male participants; when the PLW gender difference was reduced, the trend disappeared or was reversed. Finally, the perceived PLW direction was biased towards the previously seen PLW direction, showing serial dependence that was not affected by the PLW and observer genders. In conclusion, the current study shows that observers can accurately estimate PLW directions, but that judgments are curiously affected by both the observers’ and PLWs’ genders.

ETTrack: enhanced temporal motion predictor for multi-object tracking

Many Multi-Object Tracking (MOT) approaches exploit motion information to associate all the detected objects across frames. However, traditional tracking-by-detection (TBD) methods, relying on the Kalman Filter, often work well in linear motion scenarios but struggle to accurately predict the locations of objects undergoing complex and non-linear movements. To overcome these limitations, we propose ETTrack, a novel motion prediction method with an enhanced temporal motion predictor. Specifically, the motion predictor integrates a transformer model and a Temporal Convolutional Network (TCN) to capture both long-term and short-term motion patterns, and it predicts the future motion of individual objects based on the historical motion information. Additionally, we propose a novel Momentum Correction Loss function that provides additional information regarding the motion direction of objects during training. This allows the motion predictor to rapidly adapt to sudden motion variations and more accurately predict future motion. Our experimental results demonstrate that ETTrack achieves a competitive performance compared with state-of-the-art trackers on DanceTrack and SportsMOT, scoring 56.4%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} and 74.4%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} in HOTA metrics, respectively. Our work provides a robust solution for MOT in complex dynamic environments, which enhances the non-linear motion prediction capabilities of tracking algorithms.

Divergent Visuomotor Strategies in Teleosts: Neural Circuit Mechanisms in Zebrafish and Danionella cerebrum.

Larval DC exhibit faster swimming than ZF , matching the direction of visual motion. DC execute OMR in smooth, curved swimming patterns, interspersed with sharp directional turns. ZF and DC share similar visuomotor neural architecture, recruiting pretectal and hindbrain regions. ZF and DC demonstrate lateralized encoding of turns, particularly in medial hindbrain neurons. Larval Danionella cerebrum respond to global visual motion cues in smooth, low-angle swimming patterns, interspersed with sharp directional turns, swimming consistently faster than zebrafish. Fouke et al. use behavioral tracking of freely moving and head fixed fish to reveal an evolutionarily conserved visuomotor neural architecture transforming visual motion cues into species-specific locomotor behaviors.

Directional DIC method with automatic feature selection

Using displacement identification via high-speed cameras is a non-contact, full-field technique for characterizing the dynamic properties of engineered structures. Achieving reliable measurements of structural deformation through conventional Digital Image Correlation (DIC) requires a well-defined spatial gradient in two orthogonal directions within an image subset of pixels. However, DIC is susceptible to the aperture problem, which leads to an ill-conditioned optimization problem. An example of such a case is cable systems on which no speckle patterns can be applied. This study proposes Directional DIC (D-DIC) as an alternative technique to overcome the limitations posed by the aperture problem in conventional DIC methods. Directional DIC assumes the local direction of motion, which is often a valid assumption in structural vibration tests, as individual vibration shapes are often unidirectional at localized parts of the structure. This alleviates some restrictions on trackable image subsets, enabling more trackable locations. A parameter for quantifying expected tracking performance for D-DIC is introduced. The parameter enables automatic feature selection for D-DIC, making optical methods more accessible for displacement identification on structures where no speckle patterns can be applied. Experimental modal tests are conducted using a flexible spider web-like structure to validate the D-DIC method and compare it to conventional DIC. The experimental findings show that the Directional DIC method allows for measuring displacements at significantly more locations than conventional DIC. Additionally, D-DIC provided less noisy frequency response functions, more retrieved stable poles, and more fitted vibrational modes. Lastly, the findings show that D-DIC is especially superior to DIC when using small subsets since D-DIC is less inhibited by the aperture problem.

Grain-scale microtribological behavior of VCoNi medium-entropy alloy

The tribological behavior of equiatomic face-centered cubic (FCC) VCoNi medium-entropy alloy (MEA) remains underexplored despite of the alloy’s notable tensile strength and ductility. In this study, the tribological performance of VCoNi MEA is investigated using microscratching techniques, with emphasis on the effects of grain orientation, normal force, and scratch velocity. The study has demonstrated that the grain orientation in VCoNi MEA determines the activation of slip systems during the scratching processes, which significantly affects the morphology of wear tracks, slip steps and pile-up, as well as changes in microtribological behavior. As the normal force increases, the degree of wear intensifies, which is attributed to the significant material pile-up and more intense plastic flow. The plastic deformation of VCoNi MEA is found to be independent of scratch velocity within the 0.1–2 µm/s range. Ploughing and micro-shearing are identified as the primary wear mechanisms under various friction conditions. Furthermore, during the ploughing process, the deformation mechanism of the alloy is still dominated by dislocations. The direction of dislocation motion aligns with the direction of pile-up resulted from plastic deformation. The present study offers critical insights into the tribological behavior of medium-entropy alloys and broadens the potential for their applications in friction-intensive environments.

Motion in the depth direction appears faster when the target is closer to the observer

The target velocity at the retina and the initial phase of target motion are known to affect the perceived velocity of a target in planar motion. For depth motion, however, the role of this information in velocity perception remains unclear. Therefore, the purpose of this study was to reveal the role of the angular velocity derived from the vergence angle and the initial phase of target motion on the perceived velocity for depth motion. We devised two experimental tasks with five stimuli and used a two-alternative forced-choice paradigm to investigate velocity perception. In the tasks, a target moving toward or away from the observer was used. The five stimuli in each task moved between 40 and 240 cm (standard stimulus), 20 and 240 cm, 20 and 220 cm, 40 and 260 cm, and 60 and 260 cm from the participants. In the comparison of the standard stimulus with other stimuli, the stimuli approaching or receding from a distance of 20 cm were perceived as faster than the standard stimulus approaching or receding from a distance of 40 cm. We also showed that the stimuli that receded starting from a distance of 60 cm were perceived as moving slower than the standard stimulus. Our results suggest that larger changes in angular velocity affect velocity perception for depth motion; thus, observers perceive the target velocity as faster when the target is closer to the observer.

Tracing the Propagation of Shocks in the Equatorial Ring of SN 1987A over Decades with the Hubble Space Telescope

The nearby SN 1987A offers a unique opportunity to investigate the complex shock interaction between the ejecta and circumstellar medium. We track the evolution of the optical hot spots within the equatorial ring (ER) by analyzing 33 Hubble Space Telescope imaging observations between 1994 and 2022. By fitting the ER with an elliptical model, we determine its inclination to be 42.°85 ± 0.°50 with its major axis oriented −6.°24 ± 0.°31 from the west. We identify 26 distinct hot spots across the ER, with additional ones emerging over time, particularly on the western side. The hot spots initially show high velocities ranging from 390 to 1660 km s−1, followed by a deceleration phase around day ∼ 8000. Subsequent velocities vary from 40 to 660 km s−1. The light curves of the hot spots reach maxima between 7000 and 9000 days, suggesting a connection with the deceleration. Many spots are spatially resolved and show elongation perpendicular to the direction of motion, indicative of a short cooling time. To explain these results, we propose that each hot spot comprises dense substructures embedded in less dense gas. The initial velocities are then phase velocities, where the break occurs when the blast wave leaves the ER, while the late velocities reflect the propagation of radiative shocks in the dense substructures. We estimate that the dense substructures have a volumetric filling factor of ∼0.3ne/106cm−3−2% and a total mass of ∼0.24ne/106cm−3−1×10−2M⊙ .

Quantifying and Visualizing Severe Thunderstorm Motion Uncertainty for Improved Decision Support

Abstract Forecasts and observations of thunderstorm motion are key components of severe thunderstorm communication and decision support for preparedness and protective behaviors, as all National Weather Service (NWS) Storm Prediction Center (SPC) convective watches and NWS warnings contain information about storm translational speed and direction of motion. The goal of this research was to quantify uncertainty in thunderstorm motion using the information contained in NWS watch and warning products. Analyzing severe thunderstorm and tornado watches and warnings from 2008 to 2020, we matched and compared forecasted storm motions given in NWS warnings with those given in SPC watches. Translational speed deviations between watches and warnings exhibited symmetry, with about one-third of warning speeds falling within ±2.5 m s−1 of forecasts. Directional deviations were also symmetrical, with one-third of warning directions within ±9° of forecasts. However, when stratified to account for translational speed, the comparisons revealed greater directional uncertainty for slower-moving storms. Temporal analysis revealed faster and rightward translations in warnings during the latter half of watch durations. Using the distributions of speed and directional deviations, we developed new visualizations to represent both mean storm motion vectors and associated uncertainty sectors, aiding interpretation of motion uncertainties. Quantifiable storm motion uncertainty also can inform estimated ranges of storm arrival times, potentially enhancing NWS communication and decision support with key partners and a range of publics for safer outcomes during severe weather events.

Evaluating Visual Perception of Object Motion in Dynamic Environments

Precisely understanding how objects move in 3D is essential for broad scenarios such as video editing, gaming, driving, and athletics. With screen-displayed computer graphics content, users only perceive limited cues to judge the object motion from the on-screen optical flow. Conventionally, visual perception is studied with stationary settings and singular objects. However, in practical applications, we---the observer---also move within complex scenes. Therefore, we must extract object motion from a combined optical flow displayed on screen, which can often lead to mis-estimations due to perceptual ambiguities. We measure and model observers' perceptual accuracy of object motions in dynamic 3D environments, a universal but under-investigated scenario in computer graphics applications. We design and employ a crowdsourcing-based psychophysical study, quantifying the relationships among patterns of scene dynamics and content, and the resulting perceptual judgments of object motion direction. The acquired psychophysical data underpins a model for generalized conditions. We then demonstrate the model's guidance ability to significantly enhance users' understanding of task object motion in gaming and animation design. With applications in measuring and compensating for object motion errors in video and rendering, we hope the research establishes a new frontier for understanding and mitigating perceptual errors caused by the gap between screen-displayed graphics and the physical world.

Structuring in thin films during meniscus-guided deposition.

We theoretically study the evaporation-driven phase separation of a binary fluid mixture in a thin film deposited on a moving substrate, as occurs in meniscus-guided deposition for solution-processed materials. Our focus is on the limit of rapid substrate motion where phase separation takes place far away from the coating device. In this limit, demixing takes place under conditions mimicking those in a stationary film because substrate and film move at the same speed. We account for the hydrodynamic transport of the mixture within the lubrication approximation. In the early stages of demixing, diffusive and evaporative mass transport predominates, consistent with earlier studies on evaporation-driven spinodal decomposition. In the late-stage coarsening of the demixing process, the interplay of solvent evaporation, diffusive, and hydrodynamic mass transport results in several distinct coarsening mechanisms. The effective coarsening rate is dictated by the dominant mass transport mechanism and therefore depends on the material properties, evaporation rate, and time: slow solvent evaporation results in initially diffusive coarsening that for sufficiently strong hydrodynamic transport transitions to hydrodynamic coarsening, whereas rapid solvent evaporation can preempt and suppress hydrodynamic and diffusive coarsening. We identify a novel hydrodynamic coarsening regime for off-critical mixtures, arising from the interaction of the interfaces between solute-rich and solute-poor regions in the film with the solution-gas interface. This interaction induces a directional motion of solute-rich droplets along gradients in the film thickness, from regions where the film is relatively thick to where it is thinner. The solute-rich domains subsequently accumulate and coalesce in the thinner regions.

Dynamics of massive and massless particles in the spacetime of a wiggly cosmic dislocation

In this paper, we investigate the spacetime containing both small-scale structures (wiggles) and spatial dislocation, forming a wiggly cosmic dislocation. We study the combined effects of these features on the dynamics of massive and massless particles. Our results show that while wiggles alone lead to bound states and dislocation introduces angular momentum corrections, their coupling produces more complex effects, influencing both particle motion and wave propagation. Notably, this coupling significantly modifies radial solutions and eigenvalues, with the direction of motion or propagation becoming a critical factor in determining the outcomes. Numerical solutions reveal detailed aspects of particle dynamics as functions of dislocation and string parameters, including plots of trajectories, probability densities, and energy levels. These findings deepen our understanding of how a wiggly cosmic dislocation shapes particle dynamics, suggesting new directions for theoretical exploration in cosmological models.

Comparing conventional and action video game training in visual perceptual learning

Action video game (AVG) playing has been found to transfer to a variety of laboratory tasks in visual cognition. More recently, it has even been found to transfer to low-level visual "psychophysics tasks. This is unexpected since such low-level tasks have traditionally been found to be largely “immune” to transfer from another task, or even from the same task but a different stimulus attribute, e.g., motion direction. In this study, we set out to directly quantify transfer efficiency from AVG training to motion discrimination. Participants (n = 65) trained for 20 h on either a first-person active shooting video game, or a motion direction discrimination task with random dots. They were tested before, midway, and after training with the same motion task and an orientation discrimination task that had been shown to receive transfer from AVG training, but not from motion training. A subsequent control group (n = 18) was recruited to rule out any test–retest effect, by taking the same tests with the same time intervals, but without training. We found that improvement in motion discrimination performance was comparable between the AVG training and control groups, and less than the motion discrimination training group. We could not replicate the AVG transfer to orientation discrimination, but this was likely due to the fact that our participants were practically at chance for this task at all test points. Our study found no evidence, in either accuracy or reaction time, that AVG training transferred to motion discrimination. Overall, our results suggest that AVG training transferred little to lower-level visual skills, refining understanding of the mechanisms by which AVGs may affect vision.Protocol registration The accepted stage 1 protocol for this study can be found on the Open Science Framework at https://osf.io/zdv9c/?view_only=5b3b0c161dad448d9d1d8b14ce91ab11.The stage 1 protocol for this Registered Report was accepted in principle on 01/12/22. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/ZDV9C

Deictic motion verbs and anchoring the direction of motion in Estonian, Finnish and Czech

Deictic motion verbs and anchoring the direction of motion in Estonian, Finnish and Czech