Global Motion Research Articles

Engineering attributes of ground motions from February 2023 Türkiye earthquake sequence

The 2023 Türkiye earthquake sequence includes the 6 February M7.81 mainshock followed approximately 9 h later by an M7.74 event, and many smaller aftershocks including M6.81 and M6.37 events on 6 and 20 February, respectively. These events occurred in a region near the plate boundary of the East Anatolian Fault, in the proximity of which numerous ground motion recording stations had been installed north of the Türkiye–Syria border. As a result, the events were well recorded both near the fault and at rupture distances up to 582 km. We describe the available recordings and component-specific data processing performed with the aim of optimizing usable bandwidth. The resulting database includes 337, 365, 284, and 229 usable three-component recordings from the M7.81, M7.74, M6.81, and M6.37 events, respectively. We also present source, path, and site metadata that were compiled according to uniform protocols. Comparisons to a global ground motion model (GMM) for active tectonic regions and a local, Türkiye-specific model demonstrate the existence of complex path effects that result in relatively poor fits between the GMMs and observed data at large distances (generally R JB > 200 km). Under-predictions at some stations may be influenced by directivity and/or basin effects that affect the ground motions but that are not accounted for directly in the GMMs. We present analysis of spatial variability of several intensity measures. The residual maps produced from these analyses demonstrate that the global GMM overpredicts on the Anatolian block and underpredicts on the Arabian block, which is suggestive of distinct crustal attenuation features.

DMOT-SLAM: visual SLAM in dynamic environments with moving object tracking

Visual simultaneous localization and mapping (SLAM) in dynamic environments has received significant attention in recent years, and accurate segmentation of real dynamic objects is the key to enhancing the accuracy of pose estimation in such environments. In this study, we propose a visual SLAM approach based on ORB-SLAM3, namely dynamic multiple object tracking SLAM (DMOT-SLAM), which can accurately estimate the camera’s pose in dynamic environments while tracking the trajectories of moving objects. We introduce a spatial point correlation constraint and combine it with instance segmentation and epipolar constraint to identify dynamic objects. We integrate the proposed motion check method into DeepSort, an object tracking algorithm, to facilitate inter-frame tracking of dynamic objects. This integration not only enhances the stability of dynamic features detection but also enables the estimation of global motion trajectories for dynamic objects and the construction of object-level semi-dense semantic maps. We evaluate our approach on the public TUM, Bonn, and KITTI dataset, and the results show that our approach has a significant improvement over ORB-SLAM3 in dynamic scenes and performs better compared to other state-of-the-art SLAM approaches. Moreover, experiments in real-world scenarios further substantiate the effectiveness of our approach.

Anterior cervical hybrid constructs reduce superior adjacent segment burden compared to multilevel anterior cervical discectomy and fusion.

Traditional surgical treatment for symptomatic cervical degenerative disc disease is anterior cervical discectomy and fusion (ACDF), yet the increased risk of adjacent segment degeneration (ASD) requiring additional surgery exists and may result in limiting long-term surgical success when it occurs. Disc arthroplasty can preserve or restore physiologic range of motion (ROM), decreasing adjacent level stress and subsequent surgery. For patients with multilevel pathology requiring at least a 1-level fusion, interest is growing in anterior cervical hybrid (ACH) surgery as a partial motion-preserving procedure to decrease the adjacent level burden. This radiographic study compares postoperative superior adjacent segment motion between ACH and ACDF. Secondarily, total global motion, construct motion, inferior adjacent segment motion, and sagittal alignment parameters were compared. This is a single-center, multi-surgeon, retrospective cohort study of 2- and 3-level ACH and ACDF cases between 2013 and 2021. Degrees of motion were analyzed on flexion/extension views using Cobb angles to measure global (C2-C7) construct and adjacent segment lordosis. Neutral lateral X-rays were analyzed for alignment parameters, including global lordosis, cervical sagittal vertical axis (cSVA), and T1 slope (T1S). Differences were determined by independent t-test and Fisher's exact test. Of 100 patients, 38% were 2-level cases (47% ACH, 53% ACDF) and 62% were 3-level cases: (52% ACH, 48% ACDF). Postoperatively, superior adjacent segment motion increased with ACDF and decreased with ACH (-1.3°±5.3° ACH, 1.6°±4.6° ACDF, P=0.005). Postoperatively, the ACH group had greater ROM across the construct (16.3°±8.7° ACH, 4.7°±3.3° ACDF, P<0.001) and total global ROM (38.0°±12.8° ACH, 28.0°±11.1° ACDF, P<0.001). ACH resulted in a significant reduction of motion loss across the construct (-10.0°±11.7° ACH, -18.1°±10.8° ACDF, P<0.001). Postoperative alignment restoration was similar between both cohorts (-2.61°±8.36° ACH, 0.04°±12.24° ACDF, P=0.21). Compared to ACDF, hybrid constructs partially preserved motion across operative levels and had greater postoperative global ROM without increasing superior adjacent segment mobility or sacrificing alignment restoration. This supports the consideration of ACH in patients with multilevel degenerative cervical pathology requiring at least a 1-level fusion and suggests a propensity for long-term success by reducing the superior adjacent segment burden.

EDIG-CHANGES. II. Project Design and Initial Results on NGC 3556

The extraplanar diffuse ionized gas (eDIG) represents ionized gases traced by optical/UV lines beyond the stellar extent of galaxies. We herein introduce a novel multislit narrow-band spectroscopy method to conduct spatially resolved spectroscopy of the eDIG around a sample of nearby edge-on disk galaxies (eDIG-CHANGES). In this paper, we introduce the project design and major scientific goals, as well as a pilot study of NGC 3556 (M108). The eDIG is detected to a vertical extent of a few kiloparsecs above the disk, comparable to the X-ray and radio images. We do not see significant vertical variation of the [N ii]/Hα line ratio. A rough examination of the pressure balance between different circumgalactic medium phases indicates the magnetic field is in a rough pressure balance with the X-ray emitting hot gas and may play an important role in the global motion of both the eDIG and the hot gas in the lower halo. At the location of an Hubble Space Telescope/Cosmic Origins Spectrograph observed UV bright background active galactic nucleus ∼29 kpc from the center of NGC 3556, the magnetic pressure is much lower than that of the hot gas and the ionized gas traced by UV absorption lines, although the extrapolation of the pressure profiles may cause some biases in this comparison. By comparing the position–velocity diagrams of the optical and CO lines, we also find the dynamics of the two gas phases are consistent with each other, with no evidence of a global inflow/outflow and a maximum rotation velocity of ∼150 km s−1.

DIAGNOSTIC CRITERIA FOR NON–DILATED LEFT VENTRICULAR CARDIOMYOPATHY WITH PROGNOSTIC SIGNIFICANCE

Abstract Background Non–dilated left ventricular cardiomyopathy (NDLVC) is a novel diagnostic entity defined as non–ischemic LV scarring or fatty replacement regardless of the presence of global or regional wall motion abnormalities, or isolated global LV hypokinesia without scarring. While the absence of LV dilation and systolic dysfunction are implicit, no cut–offs were proposed. Methods All patients undergoing cardiac magnetic resonance (CMR) examination at a tertiary referral center from 2012 to 2022 and meeting the definition of NDLVC were evaluated. The primary endpoint was a composite of cardiac death, sustained ventricular tachycardia (VT) or ventricular fibrillation, appropriate defibrillator intervention; the secondary endpoint included also non–sustained VT. Results The cohort included 262 patients, with 176 men (67%) and a median age of 55 years (interquartile range 44–64 years). Patients without moderate (n=243, 93%) or severe LV dilation (n=249, 95%) had a longer survival free from both endpoints. The 50% LVEF threshold identified patients with different outcomes, whereas the 55% and 60% cut–offs did not. LVEF ≥50% and no severe LV dilation predicted a better outcome independent of percent LGE in the LV, the number of LV segments with LGE, LV fibro–fatty replacement, or right ventricular involvement. LVEF ≥50% and no severe LV dilation retained an independent prognostic value even in patients with LV LGE (80% of the whole cohort). Conclusions Excluding severe LV dilation (LVEDVi &amp;gt;129 mL/m2 in men and &amp;gt;116 mL/m2 in women) and LV dysfunction (LVEF &amp;lt;50%) could enhance the prognostic utility of the NDLVC definition.

East European sedimentary basins long heated by a fading mantle upwelling

A strong negative anomaly of seismic wave velocities at the core-mantle boundary (the Perm Anomaly) beneath the East European platform is attributed to the remnant of a deep mantle upwelling. The interaction between the upwelling and the East European lithosphere in the geological past and its resulting surface manifestations are still poorly understood. Using mantle plume modelling and global plate motion reconstructions, we show here that the East European lithosphere is likely to have been situated over the weakening Perm Anomaly upwelling for about 150–200 million years. As the East European platform moved above the Perm Anomaly in post-Jurassic times, the vertical tectonic movements recorded in sedimentary hydrocarbon-rich basins show either hiatus/uplift or insignificant subsidence. Analytical modelling of heat conduction through the lithosphere demonstrates that the basins have been slowly heated for a long time by the Perm Anomaly upwelling, creating suitable conditions for hydrocarbon maturation. This suggests a profound relationship between mantle plume dynamics, basin evolution, and hydrocarbon generation.

Moving Object Detection in Freely Moving Camera via Global Motion Compensation and Local Spatial Information Fusion.

Motion object detection (MOD) with freely moving cameras is a challenging task in computer vision. To extract moving objects, most studies have focused on the difference in motion features between foreground and background, which works well for dynamic scenes with relatively regular movements and variations. However, abrupt illumination changes and occlusions often occur in real-world scenes, and the camera may also pan, tilt, rotate, and jitter, etc., resulting in local irregular variations and global discontinuities in motion features. Such complex and changing scenes bring great difficulty in detecting moving objects. To solve this problem, this paper proposes a new MOD method that effectively leverages local and global visual information for foreground/background segmentation. Specifically, on the global side, to support a wider range of camera motion, the relative inter-frame transformations are optimized to absolute transformations referenced to intermediate frames in a global form after enriching the inter-frame matching pairs. The global transformation is fine-tuned using the spatial transformer network (STN). On the local side, to address the problem of dynamic background scenes, foreground object detection is optimized by utilizing the pixel differences between the current frame and the local background model, as well as the consistency of local spatial variations. Then, the spatial information is combined using optical flow segmentation methods, enhancing the precision of the object information. The experimental results show that our method achieves a detection accuracy improvement of over 1.5% compared with the state-of-the-art methods on the datasets of CDNET2014, FBMS-59, and CBD. It demonstrates significant effectiveness in challenging scenarios such as shadows, abrupt changes in illumination, camera jitter, occlusion, and moving backgrounds.

Basketball Tactics Analysis Based on Improved Openpose Algorithm and Its Application

The use of information technology has currently resulted in a change in people's production and lifestyles as well as a catalyst for the sports industry's evolution. Currently, there is a growing use of digitization in the sports industry's basketball realm. Using 2D posture estimation, a novel lightweight deep learning architecture (LDLA) is built to accomplish the automatic analysis of basketball game footage. We offer a real-time method to identify numerous people's 2D poses in a video. Additionally, it examines how 2D pose estimation might be used to analyse basketball shooting videos. First, group and global motion features are extracted to represent semantic events. A full basketball game video is broken down into three stages: clip-based segmentation, classification of semantics occurrences utilizing audio and video, and temporal sequence characteristics employing GRU CNN. Video is first processed to create some basic video categorization and segmentation using the visual, movement, and auditory data. Further use of domain knowledge is made to find important events in the basketball video. Shot and image threshold recognition algorithms for videos have used both optical and kinematic prediction information; scene classification comes next. The placements of probable semantic events, such as "fouling" and "shooting at the basket," are then discovered by comparing the multidimensional data with supplementary domain expertise. Experimental results demonstrate the proposed LDLA method achieves 99.6% of accuracy, 93.2% of precision, 93.5% of recall and 89.5% of F1-score.

Assessment of left and right ventricular systolic function in dogs with multicentric lymphoma

ObjectiveMyocardial dysfunction in cardio-oncology is generally thought to be related to the cardiotoxicity of chemotherapy treatment. However, it is known that some tumors have direct effects on myocardial function. These effects have already been studied in man, but there are no publications of these of the effects in dogs. Novel advanced echocardiographic techniques may allow early detection of myocardial dysfunction when compared to conventional echocardiographic techniques. This study aims to assess myocardial systolic function in dogs with multicentric lymphoma prior to initiation of chemotherapy. AnimalsFifteen dogs with multicentric lymphoma and nineteen healthy dogs. MethodsCase-control study. Dogs with multicentric lymphoma and healthy control dogs underwent physical examination, electrocardiography, systolic blood pressure measurement, standard and speckle tracking echocardiography to assess biventricular systolic function. ResultsThere were no differences between groups in terms of ejection fraction, fractional shortening, left ventricular systolic and diastolic diameter, tricuspid annular plane systolic excursion, mitral annular plane systolic excursion and fractional area change of the right ventricle (RV). However, there was a reduction in the values of global circumferential strain (p = 0.0003), RV strain (p = 0.01) and RV tissue motion annular displacement (p < 0.05) in the dogs with lymphoma when compared to the control group. ConclusionsSpeckle tracking techniques appear to demonstrate early systolic dysfunction, primarily affecting the RV, in dogs with lymphoma prior to chemotherapy treatment.

CEDFlow: Latent Contour Enhancement for Dark Optical Flow Estimation

Accurately computing optical flow in low-contrast and noisy dark images is challenging, especially when contour information is degraded or difficult to extract. This paper proposes CEDFlow, a latent space contour enhancement for estimating optical flow in dark environments. By leveraging spatial frequency feature decomposition, CEDFlow effectively encodes local and global motion features. Importantly, we introduce the 2nd-order Gaussian difference operation to select salient contour features in the latent space precisely. It is specifically designed for large-scale contour components essential in dark optical flow estimation. Experimental results on the FCDN and VBOF datasets demonstrate that CEDFlow outperforms state-of-the-art methods in terms of the EPE index and produces more accurate and robust flow estimation. Our code is available at: https://github.com/xautstuzfy.

A reliable unmanned aerial vehicle multi-target tracking system with global motion compensation for monitoring Procapra przewalskii

Procapra przewalskii, which inhabits plateau areas, faces the constant threat of poaching and unpredictable risks that impede its survival. The implementation of a comprehensive, real-time monitoring and tracking system for Procapra przewalskii using artificial intelligence and unmanned aerial vehicle (UAV) technology is crucial to safeguard its existence. Therefore, a UAV multi-object-tracking (MOT) system with global motion compensation (GMC) was proposed in this study. YOLOv7 and Deep SORT were employed for object detection and tracking, respectively. Furthermore, the Kalman filter (KF) in Deep SORT is optimized to enhance the accuracy of object-tracking. Moreover, a novel appearance feature-extraction network (FEN) is introduced to enable more effective multi-scale feature (MSF) extraction. In addition, a GMC module was proposed to align neighboring frames through feature matching. This facilitates the correction of the position of the target in the subsequent frame, mitigating the impact of UAV camera motion on tracking. The results demonstrated the remarkable tracking accuracy of the system. Compared with the Deep SORT model, the proposed system exhibited an increase of 6.4% in MOTA, 2.7% in MOTP, and 7.9% in IDF1. Through a comprehensive evaluation and analysis of real-world tracking scenarios, the system proposed in this study exhibits reliability in complex scenes and holds the potential to significantly enhance the protection of Procapra przewalskii from threats.

PDTE: Pyramidal deep Taylor expansion for optical flow estimation

Optical flow estimation is an important hot research in computer vision. Although existing methods had got a considerable progress in improving their performance, they still have drawbacks, such as heavily computational burden, inaccurate pixel-level offset estimation, and poor interpretability. To address these issues, this letter proposes a pyramidal deep Taylor expansion (PDTE) framework, including: First, we seriously interpreted the relationship between optical flow computation and Taylor expansion. Then, the proposed PDTE is constructed by employing global motion aggregation (GMA) to calculate each derivative part which contributes to the final estimated optical flow. Quantitative and qualitative results on the Sintel and KITTI datasets validate that the proposed PDTE scheme is effective and outperforms the state-of-the-art optical flow estimation methods. The results of extensive experiments in the ablation study demonstrate that PDTE performs well on shape preservation and the accuracy improvement of optical flow estimation, even pixel-level offset calculation.

Magnetically driven capsules with multimodal response and multifunctionality for biomedical applications

Untethered capsules hold clinical potential for the diagnosis and treatment of gastrointestinal diseases. Although considerable progress has been achieved recently in this field, the constraints imposed by the narrow spatial structure of the capsule and complex gastrointestinal tract environment cause many open-ended problems, such as poor active motion and limited medical functions. In this work, we describe the development of small-scale magnetically driven capsules with a distinct magnetic soft valve made of dual-layer ferromagnetic soft composite films. A core technological advancement achieved is the flexible opening and closing of the magnetic soft valve by using the competitive interactions between magnetic gradient force and magnetic torque, laying the foundation for the functional integration of both drug release and sampling. Meanwhile, we propose a magnetic actuation strategy based on multi-frequency response control and demonstrate that it can achieve effective decoupled regulation of the capsule’s global motion and local responses. Finally, through a comprehensive approach encompassing ideal models, animal ex vivo models, and in vivo assessment, we demonstrate the versatility of the developed magnetic capsules and their multiple potential applications in the biomedical field, such as targeted drug delivery and sampling, selective dual-drug release, and light/thermal-assisted therapy.

Dendritic mGluR2 and perisomatic Kv3 signaling regulate dendritic computation of mouse starburst amacrine cells

Dendritic mechanisms driving input-output transformation in starburst amacrine cells (SACs) are not fully understood. Here, we combine two-photon subcellular voltage and calcium imaging and electrophysiological recording to determine the computational architecture of mouse SAC dendrites. We found that the perisomatic region integrates motion signals over the entire dendritic field, providing a low-pass-filtered global depolarization to dendrites. Dendrites integrate local synaptic inputs with this global signal in a direction-selective manner. Coincidental local synaptic inputs and the global motion signal in the outward motion direction generate local suprathreshold calcium transients. Moreover, metabotropic glutamate receptor 2 (mGluR2) signaling in SACs modulates the initiation of calcium transients in dendrites but not at the soma. In contrast, voltage-gated potassium channel 3 (Kv3) dampens fast voltage transients at the soma. Together, complementary mGluR2 and Kv3 signaling in different subcellular regions leads to dendritic compartmentalization and direction selectivity, highlighting the importance of these mechanisms in dendritic computation.

Design and Dynamic Analysis of a Co-Existence Solution Between a Semi-Submersible Offshore Fish Cage and a Spar-Type Floating Offshore Wind Turbine

Abstract Clean energy captured by offshore wind turbines has been widely used for supporting onshore activities. In the near future, facilities such as offshore wind turbines can also play an important role in the energy transition of offshore activities. Offshore wind energy can be employed for electrifying operations in offshore fish farms, which are traditionally supplied by diesel-engine barges/generators. Based on this motivation, this study focuses on the design of a shared mooring system between a semi-submersible offshore fish cage and a spar-type floating wind turbine. A numerical model of the proposed shared mooring system is implemented in a global response analysis software sima for performing fully coupled time-domain simulations. The configuration of the shared mooring line is determined using an engineering approach, which comprises Irvine’s formulation, system eigenvalue analysis, and cost estimation. Moreover, relevant case studies by altering the environmental conditions are performed. Extreme operational conditions that may give large relative motions are investigated thoroughly. The dynamic performance of the integrated system is compared with that of individual structures. The global motion of the floating wind turbine and its mooring line’s tension behavior are obviously influenced by the existence of the shared line. In general, the present work investigates the feasibility of a shared mooring system for these types of offshore structures and further gives insights into the engineering design procedure.

Audio-visual saliency prediction with multisensory perception and integration

Audio-visual saliency prediction (AVSP) is a task that aims to model human attention patterns in the perception of auditory and visual scenes. Given the challenges associated with perceiving and combining multi-modal saliency features from videos, this paper presents a multi-sensory framework for AVSP. This framework is designed to extract audio, motion and image saliency features and integrate them effectively, which can then serve as a general architecture for the AVSP task. To obtain multi-sensory information, we develop a three-stream encoder that extracts audio, motion and image saliency features. In particular, we utilize a pre-trained encoder with knowledge related to image saliency to extract saliency features for each frame. The image saliency features are then incorporated with motion features using a spatial attention module. For motion features, 3D convolutional neural networks (CNNs) like S3D are commonly used in AVSP models. However, these networks are unable to effectively capture the global motion relationship in videos. To tackle this problem, we incorporate Transformer- and MLP-based motion encoders into the AVSP models. To learn joint audio-visual representations, an audio-visual fusion block is exploited to enhance the correlation between audio and visual motion features under the supervision of a cosine similarity loss in a self-supervised manner. Finally, a multi-stage decoder integrates audio, motion and image saliency features to generate the final saliency map. We evaluate our methods on six audio-visual eye-tracking datasets. Experimental results demonstrate that our method achieves compelling performance compared to the state-of-the-art methods. The source code is available at https://github.com/oraclefina/MSPI.

Agreement between a markerless and a marker-based motion capture systems for balance related quantities

Balance studies usually focus on quantities describing the global body motion. Assessing such quantities using classical marker-based approach can be tedious and modify the participant’s behaviour. The recent development of markerless motion capture methods could bypass the issues related to the use of markers. This work compared dynamic balance related quantities obtained with markers and videos. Sixteen young healthy participants performed four different motor tasks: walking at self-selected speed, balance loss, walking on a narrow beam and countermovement jumps. Their movements were recorded simultaneously by marker-based and markerless motion capture systems. Videos were processed using a commercial markerless pose estimation software, Theia3D. The centre of mass position (CoM) was computed, and the associated extrapolated centre of mass position (XCoM) and whole-body angular momentum (WBAM) were derived. Bland-Altman analysis was performed and root mean square difference (RMSD) and coefficient of correlation were computed to compare the results obtained with marker-based and markerless methods. Bias remained of the magnitude of a few mm for CoM and XCoM positions, and RMSD of CoM and XCoM was around 1 cm. RMSD of the WBAM was less than 10 % of the total amplitude in any direction, and bias was less than 1 %. Results suggest that outcomes of balance studies will be similar whether marker-based or markerless motion capture system are used. Nevertheless, one should be careful when assessing dynamic movements such as jumping, as they displayed the biggest differences (both bias and RMSD), although it is unclear whether these differences are due to errors in markerless or marker-based motion capture system.

Are chimpanzees futurists? Effects of motion lines and motion blur on the judgments of global motion direction in chimpanzees (Pan troglodytes).

Based on the invention and development of photography and movie in the 19th century, schools of contemporary art, such as Futurism, have emerged that express the dynamism of motion in painting. Painting techniques such as multiple stroboscopic images, motion blur, and motion lines are culturally based, but the biological basis of their perception has also been intensively investigated recently. Then what are the evolutionary origins of such pictorial representations of motion? Do nonhuman animals also have sensitivity to such representations? To address this question, we examined the effects of motion blur and motion lines on the judgments of global motion directions in chimpanzees. The results showed that the motion lines biased the chimpanzees' judgments toward the direction of motion implied by them, whereas the effect of the motion blur was either absent or weak (Experiment 1). In Experiment 2, we manipulated the length and number of motion lines to examine the effect of "speed" and "distance" in addition to the motion direction implied by the motion lines. The results showed that the effect of motion lines became stronger as the length and the number of lines increased within a specific range. These results indicate that the motion lines also imply the direction of motion in chimpanzees and provide a clue to the evolutionary basis for the pictorial representations of motion. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

3-D Facial Priors Guided Local–Global Motion Collaboration Transforms for One-Shot Talking-Head Video Synthesis

3-D Facial Priors Guided Local–Global Motion Collaboration Transforms for One-Shot Talking-Head Video Synthesis

The possible positive effects of physical exercise on the global motion perception aging: the cognitive mechanism.

Sensitivity to global motion perception (GMP) decreases gradually with age, and the mechanism to effectively alleviate its aging process is still unclear. This study aimed to examine the impact and mechanism of exercise on GMP aging. This study adopted the global motion direction discrimination task and used motion coherence thresholds to assess GMP sensitivity. It adopted the perceptual template model (PTM) to fit the GMP processing efficiency. The threshold for the elderly group with no exercise was higher than that of the elderly group with exercise, while the threshold of the latter was higher than that of the youth group. The results of the model fitting showed that both models, Aa and Af, corresponding to the elderly group with exercise and the elderly group with no exercise, respectively, were the best-fitted models when compared with that of the youth group. Compared to the elderly group with no exercise, models Aa and Af, were the best-fitted models. These results showed that good exercise habits might have a certain degree of positive effect on GMP aging, by lower their internal additive noise (Aa), and improve the ability to eliminate external noise (Af).