On the Co-orbitation of Satellite Galaxies along the Great Plane of Andromeda: NGC 147, NGC 185, and Expectations from Cosmological Simulations

Half of the satellite galaxies of Andromeda form a narrow plane termed the Great Plane of Andromeda (GPoA), and their line-of-sight velocities display a correlation reminiscent of a rotating structure. Recently reported first proper-motion measurements for the on-plane satellites NGC 147 and NGC 185 indicate that they indeed co-orbit along the GPoA. This provides a novel opportunity to compare the M31 satellite system to ΛCDM expectations. We perform the first detailed comparison of the orbital alignment of two satellite galaxies beyond the Milky Way with several hydrodynamical and dark-matter-only cosmological simulations (Illustris TNG50, TNG100, ELVIS, and PhatELVIS) in the context of the Planes of Satellite Galaxies Problem. In line with previous works, we find that the spatial flattening and line-of-sight velocity correlation are already in substantial tension with ΛCDM, with none of the simulated analogs simultaneously reproducing both parameters. Almost none (3%–4%) of the simulated systems contain two satellites with orbital poles as well aligned with their satellite plane as indicated by the most likely proper motions of NGC 147 and NGC 185. However, within current measurement uncertainties, it is common (≈70%) that the two best-aligned satellites of simulated systems are consistent with the orbital alignment. Yet, the chance that any two simulated on-plane satellites have as well-aligned orbital poles as observed is low (≈4%). We conclude that confirmation of the tight orbital alignment for these two objects via improved measurements, or the discovery of similar alignments for additional GPoA members, holds the potential to further raise the tension with ΛCDM expectations.

Phase-Space Correlations among Systems of Satellite Galaxies

Driven by the increasingly complete observational knowledge of systems of satellite galaxies, mutual spatial alignments and relations in velocities among satellites belonging to a common host have become a productive field of research. Numerous studies have investigated different types of such phase-space correlations and were met with varying degrees of attention by the community. The Planes of Satellite Galaxies issue is maybe the best-known example, with a rich field of research literature and an ongoing, controversial debate on how much of a challenge it poses to the ΛCDM model of cosmology. Another type of correlation, the apparent excess of close pairs of dwarf galaxies, has received considerably less attention despite its reported tension with ΛCDM expectations. With the fast expansion of proper motion measurements in recent years, largely driven by the Gaia mission, other peculiar phase-space correlations have been uncovered among the satellites of the Milky Way. Examples are the apparent tangential velocity excess of satellites compared to cosmological expectations, and the unexpected preference of satellites to be close to their pericenters. At the same time, other kinds of correlations have been found to be more in line with cosmological expectations—specifically, lopsided satellite galaxy systems and the accretion of groups of satellite galaxies. The latter has mostly been studied in cosmological simulations thus far, but it offers the potential to address some of the other issues by providing a way to produce correlations among the orbits of a group’s satellite galaxy members. This review is the first to provide an introduction to the highly active field of phase-space correlations among satellite galaxy systems. The emphasis is on summarizing existing, recent research and highlighting interdependencies between the different, currently almost exclusively individually considered types of correlations. Future prospects in light of upcoming observational facilities and our ever-expanding knowledge of satellite galaxy systems beyond the Local Group are also briefly discussed.

SwingNet

Sports analytics in the wild (i.e., ubiquitously) is a thriving industry. Swing tracking is a key feature in sports analytics. Therefore, a centimeter-level tracking resolution solution is required. Recent research has explored deep neural networks for sensor fusion to produce consistent swing-tracking performance. This is achieved by combining the advantages of two sensor modalities (IMUs and depth sensors) for golf swing tracking. Here, the IMUs are not affected by occlusion and can support high sampling rates. Meanwhile, depth sensors produce significantly more accurate motion measurements than those produced by IMUs. Nevertheless, this method can be further improved in terms of accuracy and lacking information for different domains (e.g., subjects, sports, and devices). Unfortunately, designing a deep neural network with good performance is time consuming and labor intensive, which is challenging when a network model is deployed to be used in new settings. To this end, we propose a network based on Neural Architecture Search (NAS), called SwingNet, which is a regression-based automatic generated deep neural network via stochastic neural network search. The proposed network aims to learn the swing tracking feature for better prediction automatically. Furthermore, SwingNet features a domain discriminator by using unsupervised learning and adversarial learning to ensure that it can be adaptive to unobserved domains. We implemented SwingNet prototypes with a smart wristband (IMU) and smartphone (depth sensor), which are ubiquitously available. They enable accurate sports analytics (e.g., coaching, tracking, analysis and assessment) in the wild. Our comprehensive experiment shows that SwingNet achieves less than 10 cm errors of swing tracking with a subject-independent model covering multiple sports (e.g., golf and tennis) and depth sensor hardware, which outperforms state-of-the-art approaches.

Effect of Forearm Position on Glenohumeral External Rotation Measurements in Baseball Players

Background: Alterations in glenohumeral internal rotation (GIR), glenohumeral external rotation (GER), and the total arc of motion (TAM) have been linked with increased injury risk in the shoulder and elbow. These motions have been routinely measured with the forearm in neutral rotation (GIRN, GERN, TAMN). GER capacity appears to be especially important. The throwing motion, however, requires forearm pronation as GER occurs to achieve optimal cocking (GERP). No previous studies have evaluated GERP to determine GER capacity or pronated TAM (TAMP) values. Hypothesis: There would be significant differences between GERN and TAMN and between GERP and TAMP. Study Design: Cross-sectional. Level of Evidence: Level 3. Methods: Sixty asymptomatic male Minor League Baseball players (32 pitchers, 28 position players) participated in the study and were tested on the first day of spring training. Passive range of motion measurements were recorded using a long-arm bubble goniometer for GIRN, GERN, and GERP on both arms. TAM was calculated separately as the sum of internal and external rotational measurements under neutral and pronated conditions. Results: Within pitchers and position players, all measurements were statistically reduced for the throwing arm ( P ≤ 0.03) except for GERN of the pitchers. GERP measures were significantly less than GERN for both arms of each group ( P < 0.01): pitchers throwing arm +11.8°/nonthrowing arm +4.8°, position players throwing arm = +8.6°/nonthrowing arm +4.0°. Conclusion: The forearm position of pronation, which appears to be mediated by tightness of the biceps, decreases GER capacity and TAM. GER and TAM should be calculated in neutral and pronated positions, considering that 80% of the players have a demonstrated difference between 8° and 12°. Clinical Relevance: Measurement of GERP more accurately reflects the GER required in throwing, allows better quantification of the motion capacity necessary to withstand the loads in throwing, and may suggest interventions for at risk athletes.

Does Dry Needling Treatment Make an Extra Contribution to Conventional Treatment in Hemiplegic Shoulder Pain? A Randomized Controlled Study

Aim: To evaluate the effect of adding dry needling treatment to conventional rehabilitation on pain, range of motion, and functionality on hemiplegic shoulder pain. Methods: A total of 38 patients with hemiplegic shoulder pain were divided into two groups. A multimodal rehabilitation protocol including physical therapy methods and exercise treatments was applied to both groups (5 sessions per week for a total of 15 sessions). In addition to the rehabilitation, three sessions of dry needling treatment were applied for dry needling group. Pain with visual analog scale, range of motion with a goniometer, functionality was evaluated by quick disability of the arm, shoulder, and hand and fugl meyer assessment upper extremity. Evaluations were made before treatment, after treatment, and at the third month of treatment. Results: Patients aged from 30-60 years (mean±SD=53.1± 5.3). The average duration of HSP was 6.7±1 months. While a significant improvement was observed in both groups in all parameters after the treatment, a statistical superiority was found in the dry needling group (p<0.05). At the 3rd month follow-up, there was no difference in pain and functionality parameters between the groups, while flexion and abduction measurements were higher in the dry needling group (p <0.05). Conclusion: Adding dry needling treatment to conventional rehabilitation did not show any difference except for some joint range of motion measurements in the subacute period.

Removing residual airborne sensor motion for measuring seismic signals from a drone

Acquiring seismic data using drones requires excellent knowledge of the drone’s motion since positional measurements made from an airborne sensor represent a combination of sensor and ground motion. Recent advancements in laser Doppler vibrometry and repeat lidar surveys show that the frequency and resolution of non-contact motion measurements is increasing to the point necessary for measuring seismic signals. We explore the conditions under which separation of sensor motion from ground motion can be accomplished in practice. We assume (i) that the translation and rotation of a stabilized airborne sensor follows an analytic form in time that is either known or can be estimated from the sensor’s measurements, (ii) that the seismic signal we observe has compact support contained within the measurement window, and (iii) that the ground motion can be described by a rigid translation. We analyze the effectiveness of our signal separation problem as a function of peak signal, sensor noise level, sensor rotation angle, and sensor point sampling density by defining a boundary where SNR = 0 dB for various combinations of these parameters. We find that under the set of assumptions, lower rotation angles, lower sensor noise, and denser point samplings on the ground provide better signal separation using our method.

An inertial sensor-based protocol for spinal range of motion measurements

To develop a protocol for assessing spinal range of motion using an inertial sensor device. The baseline error of an inertial sensor was assessed using a bicycle wheel. Nineteen healthy subjects (12 females and 7 males, average age 18.2 ± 0.6 years) were then prospectively enrolled in a study to assess the reliability of an inertial sensor-based method for assessing spinal motion. Three raters each took three measurements of subjects’ flexion/extension, right and left bending, and right and left rotation. Afterwards, one trial from each set of measurements was excluded. Correlations and the ICC (3,1) were used to assess intra-rater reliability, and ICC (3,2) was used to assess inter-rater reliability of the protocol. The baseline error of the sensor was 1.45°. Correlation and ICC (3,1) values for the protocol all exceeded 0.888, indicating high intra-rater reliability. ICC (3,2) values for the protocol exceed 0.87, indicating high inter-rater reliability. Our study presents both a paradigm for assessing the baseline error of inertial sensors and a protocol for assessing motion of the spine using an inertial sensing device.