Local Motion Research Articles

Length Scale of Molecular Motions Governing Glass Equilibration in Hyperquenched and Slow-Cooled Polystyrene.

Polymer glasses attain thermodynamic equilibrium owing to structural relaxation at various length scales. Herein, calorimetry experiments were conducted to trace the macroscopic relaxation of slow-cooled (SC) and hyperquenched (HQ) polystyrene (PS) glasses and based on detailed comparisons with molecular dynamics probed by dye reorientation, we discussed the possible molecular process governing the equilibration of PS glasses near the glass transition temperatures (Tg). Both SC and HQ glasses equilibrate owing to the cooperative segment motion above a characteristic temperature (Tc) slightly lower than the Tg. In contrast, below the Tc, the localized backbone motion with an apparent activation energy of 290 ± 20 kJ/mol, involving approximately six repeating units, assists equilibrium recovery of PS glasses on the experimentally accessible time scales. The results possibly indicate the presence of an alternative mechanism other than the α-cooperative process controlling physical aging of materials in their deep glassy states.

Feature matching based on Gaussian kernel convolution and minimum relative motion

Feature matching is a necessary and important step for remote sensing image registration, intended to establish reliable point correspondences between two sets of features. In this paper, we propose a feature registration model based on local relative motion, which combines Gaussian kernel convolution with relative motion (GRM) vector to obtain better results by removing wrong matches and improving the inlier point accuracy. We first establish putative matching based on the similarity between local descriptors. Then, the preliminary hypothetical matching point set is filtered using consistency with nearest neighbors among the inlier points to obtain a more accurate motion vector, and to fit the real motion vector through the Gaussian convolution kernel. Finally, we find the displacement between the fitted motion vector and the matching generated motion vector. And combine the displacement with the optimization model to find the inlier point set. Experimental results show that our GRM method outperforms related work, achieving better matching results.

Laser manufacturing of spatial resolution approaching quantum limit

Atomic and close-to-atom scale manufacturing is a promising avenue toward single-photon emitters, single-electron transistors, single-atom memory, and quantum-bit devices for future communication, computation, and sensing applications. Laser manufacturing is outstanding to this end for ease of beam manipulation, batch production, and no requirement for photomasks. It is, however, suffering from optical diffraction limits. Herein, we report a spatial resolution improved to the quantum limit by exploiting a threshold tracing and lock-in method, whereby the two-order gap between atomic point defect complexes and optical diffraction limit is surpassed, and a feature size of <5 nm is realized. The underlying physics is that the uncertainty of local atom thermal motion dominates electron excitation, rather than the power density slope of the incident laser. We show that the colour centre yield in hexagonal boron nitride is transformed from stochastic to deterministic, and the emission from individual sites becomes polychromatic to monochromatic. As a result, single colour centres in the regular array are deterministically created with a unity yield and high positional accuracy, serving as a step forward for integrated quantum technological applications.

Switching molecular recognition selectivities by temperature in a diffusion-regulatory porous material

Over the long history of evolution, nature has developed a variety of biological systems with switchable recognition functions, such as the ion transmissibility of biological membranes, which can switch their ion selectivities in response to diverse stimuli. However, developing a method in an artificial host-guest system for switchable recognition of specific guests upon the change of external stimuli is a fundamental challenge in chemistry because the order in the host-guest affinity of a given system hardly varies along with environmental conditions. Herein, we report temperature-responsive recognition of two similar gaseous guests, CO2 and C2H2, with selectivities switched by temperature change by a diffusion-regulatory mechanism, which is realized by a dynamic porous crystal featuring ultrasmall pore apertures with flip-flop locally-motive organic moiety. The dynamic local motion regulates the diffusion process of CO2 and C2H2 and amplifies their rate differences, allowing the crystal to selectively adsorb CO2 at low temperatures and C2H2 at high temperatures with separation factors of 498 (CO2/C2H2) and 181 (C2H2/CO2), respectively.

Optimization of the Tracking Beam Sequence in Harmonic Motion Imaging.

Harmonic motion imaging (HMI) is an ultrasound elastography technique that estimates the viscoelastic properties of tissues by inducing localized oscillatory motion using focused ultrasound (FUS). The resulting displacement, assumed to be inversely proportional to the tissue local stiffness, is estimated using an imaging array based on RF speckle tracking. In conventional HMI, this is accomplished with plane-wave (PW) imaging, which inherently suffers from low lateral resolution. Coherent PW compounding (PWC) leverages spatial and temporal resolution using synthetic focusing in transmit. In this study, we introduced focused imaging with parallel tracking in HMI and compared parallel tracking of various transmit F-numbers (F/2.6, 3, 4, and 5) qualitatively and quantitatively with PW and PWC imaging at various compounded angle ranges (6°, 12°, and 18°). An in silico model of a 56-kPa spherical inclusion (diameter: 3.6 mm) embedded in a 5.3-kPa background and a 5.3-kPa elastic phantom with cylindrical inclusions (Young's moduli: 22-56 kPa, diameters: 2.0-8.6 mm) were imaged to assess different tracking beam sequences. Speckle biasing in displacement estimation associated with parallel tracking was also investigated and concluded to be negligible in HMI. Parallel tracking in receive (Rx) resulted in 2%-7% and 8%-12% increase compared to PW imaging ( ) in HMI contrast and contrast-to-noise ratio in silico and phantoms. Focused imaging with parallel tracking in Rx was concluded to be most robust among PW and PWC imaging for displacement estimation, and its preclinical feasibility was demonstrated in postsurgical human cancerous breast tissue specimens and in vivo murine models of breast cancer.

Multifractality approach of a generalized Shannon index in financial time series.

Multifractality is a concept that extends locally the usual ideas of fractality in a system. Nevertheless, the multifractal approaches used lack a multifractal dimension tied to an entropy index like the Shannon index. This paper introduces a generalized Shannon index (GSI) and demonstrates its application in understanding system fluctuations. To this end, traditional multifractality approaches are explained. Then, using the temporal Theil scaling and the diffusive trajectory algorithm, the GSI and its partition function are defined. Next, the multifractal exponent of the GSI is derived from the partition function, establishing a connection between the temporal Theil scaling exponent and the generalized Hurst exponent. Finally, this relationship is verified in a fractional Brownian motion and applied to financial time series. In fact, this leads us to proposing an approximation called local fractional Brownian motion approximation, where multifractal systems are viewed as a local superposition of distinct fractional Brownian motions with varying monofractal exponents. Also, we furnish an algorithm for identifying the optimal q-th moment of the probability distribution associated with an empirical time series to enhance the accuracy of generalized Hurst exponent estimation.

MarkerNet: A divide‐and‐conquer solution to motion capture solving from raw markers

AbstractMarker‐based optical motion capture (MoCap) aims to localize 3D human motions from a sequence of input raw markers. It is widely used to produce physical movements for virtual characters in various games such as the role‐playing game, the fighting game, and the action‐adventure game. However, the conventional MoCap cleaning and solving process is extremely labor‐intensive, time‐consuming, and usually the most costly part of game animation production. Thus, there is a high demand for automated algorithms to replace costly manual operations and achieve accurate MoCap cleaning and solving in the game industry. In this article, we design a divide‐and‐conquer‐based MoCap solving network, dubbed MarkerNet, to estimate human skeleton motions from sequential raw markers effectively. In a nutshell, our key idea is to decompose the task of direct solving of global motion from all markers into first modeling sub‐motions of local parts from the corresponding marker subsets and then aggregating sub‐motions into a global one. In this manner, our model can effectively capture local motion patterns w.r.t. different marker subsets, thus producing more accurate results compared to the existing methods. Extensive experiments on both real and synthetic data verify the effectiveness of the proposed method.

Conformational Dynamics in Proteins: Entangled Slow Fluctuations and Nonequilibrium Reaction Events.

Proteins exhibit conformational fluctuations and changes over various time scales, ranging from rapid picosecond-scale local atomic motions to slower microsecond-scale global conformational transformations. In the presence of these intricate fluctuations, chemical reactions occur and functions emerge. These conformational fluctuations of proteins are not merely stochastic random motions but possess distinct spatiotemporal characteristics. Moreover, chemical reactions do not always proceed along a single reaction coordinate in a quasi-equilibrium manner. Therefore, it is essential to understand spatiotemporal conformational fluctuations of proteins and the conformational change processes associated with reactions. In this Perspective, we shed light on the complex dynamics of proteins and their role in enzyme catalysis by presenting recent results regarding dynamic couplings and disorder in the conformational dynamics of proteins and rare but rapid enzymatic reaction events obtained from molecular dynamics simulations.

Local motion feature extraction and spatiotemporal attention mechanism for action recognition

Local motion feature extraction and spatiotemporal attention mechanism for action recognition

Incidental visual processing of spatiotemporal cues in communicative interactions: An fMRI investigation

Abstract The interpretation of social interactions between people is important in many daily situations. The coordination of the relative body movements between them may provide visual cues that observers use without attention to discriminate such social interactions from the actions of people acting independently of each other. Previous studies highlighted brain regions involved in the visual processing of interacting versus independently acting people, including posterior superior temporal sulcus, and areas of lateral occipitotemporal and parietal cortices. Unlike these previous studies, we focused on the incidental visual processing of social interactions; that is, the processing of the body movements outside the observers’ focus of attention. In the current study, we used functional imaging to measure brain activation while participants were presented with point-light dyads portraying communicative interactions or individual actions. However, their task was to discriminate the brightness of two crosses also on the screen. To investigate brain regions that may process the spatial and temporal relationships between the point-light displays, we either reversed the facing direction of one agent or spatially scrambled the local motion of the points. Incidental processing of communicative interactions elicited activation in right anterior STS only when the two agents were facing each other. Controlling for differences in local motion by subtracting brain activation to scrambled versions of the point-light displays revealed significant activation in parietal cortex for communicative interactions, as well as left amygdala and brain stem/cerebellum. Our results complement previous studies and suggest that additional brain regions may be recruited to incidentally process the spatial and temporal contingencies that distinguish people acting together from people acting individually.

Sea level rise and the drivers of daily water levels in the Sacramento-San Joaquin Delta

Water levels in deltas and estuaries vary on multiple timescales due to coastal, hydrologic, meteorologic, geologic, and anthropogenic factors. These diverse factors increase the uncertainty of, and may bias, relative sea level rise (RSLR) estimates. Here, we evaluate RSLR in San Francisco Bay and the Sacramento-San Joaquin Delta, USA by applying a physics-based, nonlinear regression to 50 tide gauges that determines the spatially varying controls on daily mean water level for water years 2004–2022. Results show that elevated river flow and pumping (99th percentile) raise water level up to 6 m and lower it up to 0.35 m, respectively, and coastal water level variations are attenuated by 30-60% within the Delta. Strong westerly winds raise water level up to 0.17 m, and tidal-fluvial interaction during spring tides and low discharge raises water level up to 0.15 m. Removal of these interfering factors greatly improves RSLR estimates, narrowing 95% confidence intervals by 89–99% and removing bias due to recent drought. Results show that RSLR is spatially heterogeneous, with rates ranging from − 2.8 to 12.9 mm y-1 (95% uncertainties < 1 mm y-1). RSLR also exceeds coastal SLR of 3.3 mm y-1 in San Francisco at 85% of stations. Thus, RSLR in the Delta is strongly influenced by local vertical land motion and will likely produce significantly different, location-dependent future flood risk trajectories.

Flexible and accurate total variation and cascaded denoisers-based image reconstruction algorithm for hyperspectrally compressed ultrafast photography

Hyperspectrally compressed ultrafast photography (HCUP) based on compressed sensing and time- and spectrum-to-space mappings can simultaneously realize the temporal and spectral imaging of non-repeatable or difficult-to-repeat transient events with a passive manner in single exposure. HCUP possesses an incredibly high frame rate of tens of trillions of frames per second and a sequence depth of several hundred, and therefore plays a revolutionary role in single-shot ultrafast optical imaging. However, due to ultra-high data compression ratios induced by the extremely large sequence depth, as well as limited fidelities of traditional algorithms over the image reconstruction process, HCUP suffers from a poor image reconstruction quality and fails to capture fine structures in complex transient scenes. To overcome these restrictions, we report a flexible image reconstruction algorithm based on a total variation (TV) and cascaded denoisers (CD) for HCUP, named the TV-CD algorithm. The TV-CD algorithm applies the TV denoising model cascaded with several advanced deep learning-based denoising models in the iterative plug-and-play alternating direction method of multipliers framework, which not only preserves the image smoothness with TV, but also obtains more priori with CD. Therefore, it solves the common sparsity representation problem in local similarity and motion compensation. Both the simulation and experimental results show that the proposed TV-CD algorithm can effectively improve the image reconstruction accuracy and quality of HCUP, and may further promote the practical applications of HCUP in capturing high-dimensional complex physical, chemical and biological ultrafast dynamic scenes.

Complex conjugate rupture of the 2014 Mw 6.2 Ludian (Yunnan, China) earthquake

The Mw 6.2 Ludian earthquake, struck Yunnan, China on August 3rd, 2014, leading to a complex aftershock distribution and enormous disaster. The Ludian earthquake is well recorded by the China Earthquake Network. The rupture process of the Ludian earthquake is constrained by the more local strong motion data including the LLT station with epicentral distance of ∼2 km and teleseismic body waves and surface waves in this study. The local strong motion data constrained the epicenter’s location and rupture process better. Waveform fit of key local strong-motion stations supported that the Ludian earthquake ruptured two conjugate faults with strike angles of 77° and 160°, respectively. The rupture simultaneously took place on two conjugate faults and lasted approximately 10 s. The peak slip, rise time, and average slip rate are 0.63 m, 0.69 s, and 2.12 m/s, respectively. The result shows that the main rupture zone was on the fault with a strike of 160°. The depth of the major slip patch was 0–4 km with a centroid depth of 2 km. It indicates that the shallow slip is the main reason for the enormous disaster from the earthquake source perspective.

A Shared Control Approach Based on First-Order Dynamical Systems and Closed-Loop Variable Stiffness Control

In this paper, we present a novel learning-based shared control framework. This framework deploys first-order Dynamical Systems (DS) as motion generators providing the desired reference motion, and a Variable Stiffness Dynamical Systems (VSDS) (Chen et al. 2021) for haptic guidance. We show how to shape several features of our controller in order to achieve authority allocation, local motion refinement, in addition to the inherent ability of the controller to automatically synchronize with the human state during joint task execution. We validate our approach in a teleoperated task scenario, where we also showcase the ability of our framework to deal with situations that require updating task knowledge due to possible changes in the task scenario, or changes in the environment. Finally, we conduct a user study to compare the performance of our VSDS controller for guidance generation to two state-of-the-art controllers in a target reaching task. The result shows that our VSDS controller has the highest successful rate of task execution among all conditions. Besides, our VSDS controller helps reduce the execution time and task load significantly, and was selected as the most favorable controller by participants.

Integration of motion information in illusory motion perceived in stationary patterns

Illusory motion is a phenomenon in which stationary images with repeating luminance gradient patterns appear to be moving. In this study, we conducted experiments focusing on illusory motion to verify the hypothetical rule that velocity information, extracted from local luminance patterns, is integrated by summation in visual information processing. This rule is based on the hypothesis of velocity integration, and could estimate perceived velocity of stimulus. The summation rule was evaluated by a psychophysical experiment. Our results showed that the summation rule unbiasedly predicted perceived velocity, suggesting that an algorithm for integrating velocity information in illusory motion is based on the summation rule. These results would contribute to understanding of the spatial integration of local motion signals in visual information processing.

Modular interneuron circuits control motion sensitivity in the mouse retina

Neural computations arise from highly precise connections between specific types of neurons. Retinal ganglion cells (RGCs) with similar stratification patterns are positioned to receive similar inputs but often display different response properties. In this study, we used intersectional mouse genetics to achieve single-cell type labeling and identified an object motion sensitive (OMS) AC type, COMS-AC(counter-OMS AC). Optogenetic stimulation revealed that COMS-AC makes glycinergic synapses with the OMS-insensitive HD2p-RGC, while chemogenetic inactivation showed that COMS-AC provides inhibitory control to HD2p-RGC during local motion. This local inhibition, combined with the inhibitory drive from TH2-AC during global motion, explains the OMS-insensitive feature of HD2p-RGC. In contrast, COMS-AC fails to make synapses with W3(UHD)-RGC, allowing it to exhibit OMS under the control of VGlut3-AC and TH2-AC. These findings reveal modular interneuron circuits that endow structurally similar RGC types with different responses and present a mechanism for redundancy-reduction in the retina to expand coding capacity.

Characteristics of boundary layer height and its influencing factors in global monsoon regions

Monsoon precipitation changes has led to substantial changes in the spatial pattern of land surface energy in most monsoon regions of the world, which subsequently affect the structure and development of the atmospheric boundary layer (ABL) over land. Based on the ERA-Interim reanalysis data (1979–2018), the present study analyzes the long-term variability characteristics of Boundary layer height (BLH) and its influencing factors in the global land monsoon region. The results show that the long-term annual mean BLH averaged over all the monsoon regions across the globe is approximately 653.2 m, but there exist great differences between various regions. The highest BLH occurs in the Australian (AUS) region, followed by that in South Africa (SAF), North Africa (NAF), North America (NAM) and South America (SAM) regions, and the lowest BLH occurs in the Asian (ASN) monsoon region. The differences in BLH between various regions reflect significant regional differences in surface energy distribution. A larger sensible heat flux SHF usually corresponds to a higher BLH, while NAM with the largest latent heat flux LHF corresponds to not the lowest BLH, which is related to its smaller cloud radiation cooling. In the past 40 years, the spatial variation of BLH in ASN region is the most special among all monsoon regions, which is mainly manifested in the increasing trend in the east (east of 100°E) and the decreasing trend in the west (west of 100°E), partly due to the distribution of more precipitation in the east and less precipitation in the west in recent decades. The differences in BLH distribution in different monsoonal regions are mainly caused by SHF. Wind shearSand vertical sensible heat advectionHmv, as the main driving sources of ABL development, play a non-negligible role in the variances of BLH structure in different monsoon areas, although their contributions are much smaller than that of SHF.The role of S in promoting or inhibiting the development of ABL is not only related to S size, but also closely related to the atmospheric turbulence environment. Additionally, each monsoon region's Hmv influence on BLH is the most complex, and changes in near-surface temperature and annual precipitation can only partially explain the observed occurrences. The complicated process must also take into account the significance of local vertical motion brought on by weather variations and surface irregularities in various monsoon regions.

The monthly evolution of precipitation and warm conveyor belts during the central southwest Asia wet season

Abstract. Understanding the nature of precipitation over central southwest Asia (CSWA), a data-sparse, semi-arid region, is important given its relation to agricultural productivity and the likelihood of hazards such as flooding. The present study considers how daily precipitation and local vertical motion – represented by warm conveyor belts (WCBs) – evolve from November to April over CSWA. First we compare several precipitation datasets, revealing that the seasonality of daily precipitation is consistent across estimates that incorporate satellite information, while total accumulation amounts differ substantially. A common feature across datasets is that the majority of precipitation occurs on the few days when area-averaged accumulation exceeds 4 mm, which are most frequent in February and March. The circulation pattern associated with heavy (&lt; 4 mm d−1) precipitation days evolves within the wet season from a southwest–northeast tilted couplet of circulation anomalies in January and February to a neutrally tilted monopole pattern in April. El Niño conditions are associated with more heavy precipitation days than La Niña conditions, with both enhanced WCB frequency and moisture transport observed during the former. An exception to this is found in January, when precipitation, WCB frequency, and moisture do not increase, despite a similar increase in surface cyclones to other months, suggesting that precipitation changes cannot always be inferred from cyclone frequency changes. Nonetheless, our results generally support prior connections made between the El Niño–Southern Oscillation (ENSO) and seasonal-to-interannual precipitation anomalies and extend this connection to one between the slowly evolving ENSO influence and transient and local vertical motion represented by WCBs.

Simulation of ground motion emissions from wind turbines in low mountain ranges: implications for amplitude decay prediction

The characterization and prediction of wind turbine (WT) emissions are important steps in reducing their impact on humans or sensitive technologies such as seismic stations or physics experiments. Here, WT ground motion emissions are studied along two measurement lines set up at two wind farms on the Eastern Swabian Alb, southwest Germany. The main purpose of the data analysis is to estimate amplitude decay rates from vertical component data and surface wave phase velocities excited by the permanent motion of the WT towers. Phase velocities as well as geological information serve as input to build realistic subsurface models for numerical wave field simulations. Amplitude A decay rates are characterized by b-values through Asim 1/r^b depending on distance r and are derived from peaks in power spectral density (PSD). We find an increase of b_text {PSD} with frequency from 0.5 to 3.2 for field data. For low frequencies (1.2 Hz and 3.6 Hz), b_text {PSD} ranges from 0.5 to 1.1, hence close to the geometrical spreading factor of surface waves (b_text {PSD}=1). Anelastic damping and scattering seem not to be significant at these frequencies which also shows in numerical simulations for quality factors Q=50-200. We also find that the emitted wavefields from several WTs interfere, especially in the near-field, and produce strong local ground motion amplitudes. The inclusion of a steep topography present in low mountain ranges adds more wave field distortions which can further increase the amplitudes. This needs to be considered when predicting WT induced ground motions.

Truly pattern: Nonlinear integration of motion signals is required to account for the responses of pattern cells in rat visual cortex.

A key feature of advanced motion processing in the primate dorsal stream is the existence of pattern cells-specialized cortical neurons that integrate local motion signals into pattern-invariant representations of global direction. Pattern cells have also been reported in rodent visual cortex, but it is unknown whether the tuning of these neurons results from truly integrative, nonlinear mechanisms or trivially arises from linear receptive fields (RFs) with a peculiar geometry. Here, we show that pattern cells in rat primary (V1) and lateromedial (LM) visual cortex process motion direction in a way that cannot be explained by the linear spatiotemporal structure of their RFs. Instead, their tuning properties are consistent with and well explained by those of units in a state-of-the-art neural network model of the dorsal stream. This suggests that similar cortical processes underlay motion representation in primates and rodents. The latter could thus serve as powerful model systems to unravel the underlying circuit-level mechanisms.