Dynamic Motion Research Articles

Combining optimization and dynamic movement primitives for planning energy optimal forestry crane motions

Forestry cranes are an important tool for safe and efficient timber harvesting with forestry machines. However, their complex manual control often led to inefficiencies and excessive energy usage, due to the many joysticks and buttons that must be used in a precise sequence to perform efficient movements. To address this, the industry is increasingly turning to partial automation, making manual control more intuitive for the operator and, consequently, achieving improvements in energy efficiency. This article introduces a novel approach to energy-optimal motion planning that can be used along with a feedback control system to automate crane motions, taking over portions of the operator’s work. Our method combines dynamic movement primitives (DMPs) and an energy-optimization algorithm. DMPs is a machine learning technique for motion planning based on human demonstrations, while the optimization algorithm exploits the crane’s redundancy to find energy-optimal trajectories. Simulation results show that DMPs can replicate human-like controlled motions with a 25% reduction in energy consumption. However, our energy optimization algorithm shows improvements of over 40%, providing substantial energy savings and a promising pathway towards environmentally friendly partially automated machines.

Utilising dynamic motor control index to identify age-related differences in neuromuscular control

PurposeConsidering the relationship between aging and neuromuscular control decline, early detection of age-related changes can ensure that timely interventions are implemented to attenuate or restore neuromuscular deficits. The dynamic motor control index (DMCI), a measure based on variance accounted for (VAF) by one muscle synergy (MS), is a metric used to assess age-related changes in neuromuscular control. The aim of the study was to investigate the use of one-synergy VAF, and consecutively DMCI, in assessing age-related changes in neuromuscular control over a range of exercises with varying difficulty. MethodsThirty-one subjects walked on a flat and inclined treadmill, as well as performed forward and lateral stepping up tasks. Motion and muscular activity were recorded, and muscle synergy analysis was conducted using one-synergy VAF, DMCI, and number of synergies. ResultsDifference between older and younger group was observed for one-synergy VAF, DMCI for forward stepping up task (one-synergy VAF difference of 2.45 (0.22, 4.68) and DMCI of 9.21 (0.81, 17.61), p = 0.033), but not for lateral stepping up or walking. ConclusionThe use of VAF based metrics and specifically DMCI, rather than number of MS, in combination with stepping forward exercise can provide a low-cost and easy to implement approach for assessing neuromuscular control in clinical settings.

Understanding compound extreme precipitations preconditioned by heatwaves over China under climate change

Abstract Compared with individual heatwaves or storm events, the compound extreme precipitations preconditioned by heatwaves (CHEPs) usually amplify their adverse repercussions on both ecosystems and society. However, little is known about the physical mechanisms of generations, especially considering precipitation types triggered by various factors and synoptic patterns. By classifying extreme precipitations based on duration, we conduct an event-based analysis and comprehensively assess CHEPs using the machine learning-constrained framework and binning scaling methods over China. We find the fraction of CHEPs to total extreme short-duration/long-duration precipitations (ESDPs/ELDPs) has substantially increased by 18% /15% from 1979 to 2021, when using dry-bulb temperature to identify heatwaves. More notably, the hotspots of CHEPs are generally consistent with those of ESDPs. The ESDPs play a dominant role in shaping CHEPs episodes, which are governed by enhancing atmospheric instability due to preconditioned heatwaves. The horizontal moisture advection and transient vertical dynamic motion of moisture, which are paramount to long-duration precipitations, is not significantly enhanced by the overheating atmosphere, leading to a small fraction of long-duration precipitations to CHEPs. In addition, the intensity of ESDPs tends to increase with air temperature at higher rates than that of ELDPs. As short-duration storms may trigger severe flash floods, ample attention should be paid to the escalating risks of CHEPs under climate change.

Dynamic movement of the Golgi unit and its glycosylation enzyme zones.

Knowledge on the distribution and dynamics of glycosylation enzymes in the Golgi is essential for better understanding this modification. Here, using a combination of CRISPR/Cas9 knockin technology and super-resolution microscopy, we show that the Golgi complex is assembled by a number of small 'Golgi units' that have 1-3 μm in diameter. Each Golgi unit contains small domains of glycosylation enzymes which we call 'zones'. The zones of N- and O-glycosylation enzymes are colocalised. However, they are less colocalised with the zones of a glycosaminoglycan synthesizing enzyme. Golgi units change shapes dynamically and the zones of glycosylation enzymes rapidly move near the rim of the unit. Photobleaching analysis indicates that a glycosaminoglycan synthesizing enzyme moves between units. Depletion of giantin dissociates units and prevents the movement of glycosaminoglycan synthesizing enzymes, which leads to insufficient glycosaminoglycan synthesis. Thus, we show the structure-function relationship of the Golgi and its implications in human pathogenesis.

Electric Motor by using Machine Learning.

This research paper addresses the crucial issue of early bearing failure within electric motors, a common problem impacting industrial operations. It begins with a thorough problem identification and historical study of asset failures to pinpoint strategic sensor placement on the motor casing, specifically targeting the bearing area. Time series data acquisition captures the dynamic motor behavior, with LabVIEW software facilitating visualization through frequency plots and spectral graphs. Subsequent preprocessing involves modifying data structure and computing vibration metrics like RRMS and IRRMS to quantify vibration levels. The processing stage consists of condition monitoring using structured supervised datasets transformed into the frequency domain in MATLAB. Interpretation of results enables bearing health assessment and identification of dominant frequency components. Additionally, the remaining useful life of the bearing is estimated using the Support Vector Classifier algorithm, supplemented by RRMS and IRRMS to enhance prediction accuracy. A machine learning model, developed in Python and trained on bearing datasets, predicts the remaining useful life based on sensor-collected data. This comprehensive methodology aims to provide insights into bearing health, facilitating proactive maintenance and optimizing industrial operations

Impact of professional dance training on characteristics of postural sway

The stability of human upright posture determines the range and dynamics of movements performed. Consequently, the repertoire and quality of the movements performed by a dancer are mainly determined by the efficiency of postural control. This is of particular importance in professional dance training that should focus on shaping optimal movement‑posture interaction. To get a deeper insight into this problem, the impact of the training on postural sway characteristics during quiet stance was analyzed in 16 female students in the seventh grade of a ballet school and compared with the size‑ and age‑matched group of secondary school students. Center of pressure trajectories were recorded for 25.6 s while standing quiet with eyes open (EO) and then with eyes closed (EC). The assessment of postural control was based on novel normalized sway parameters including sway vector (SV), sway anteroposterior (AP) and mediolateral (ML) directional indices (DIAP and DIML), and sway ratios (SRAP and SRML). The results document a significant contribution of vision to postural stability control in ballet students, which seems to compensate for training‑related changes in joint mobility and altered activity ranges of the legs’ muscles. In the control group standing with EC, SV amplitude increased only by 18% whereas in the ballet students tested in the same conditions, the increase exceeded 72%. Under full control of standing posture (EO test), the training‑related increase of leg muscle forces allows dancers to maintain balance with lesser effort as documented here by 21% reduced SRAP. Additionally, the dancers while tested with their EC exhibited a 12% increase in the anteroposterior sway with a concomitant reduction of the mediolateral sway. The resulting changes in the postural control asymmetry were documented by both DIAP/DIML and SV azimuth. In conclusion, our novel analysis of postural sway seems a useful tool in monitoring the effects of trainingas well as the proper course of postural control development in children and adolescents.

Numerical calibration of the mooring system for a semi-submersible floating wind turbine model

Abstract Numerical modelling of the floating offshore wind turbine (FOWT) dynamics plays a critical role at the design stage of a floating wind project. Still, there exist challenges for verification of efficient engineering models against experimental results. Recently, an experimental campaign was carried out for a 1:96 downscaled model of the OC4-DeepCWind semi-submersible platform with mooring lines made of fibre ropes and chains. Leveraging the results of this campaign, this paper focuses on development and calibration of a numerical model for the semi-submersible platform with a focus on the dynamic responses under bichromatic waves. In the numerical model, the hydrodynamic loads are modelled based on the potential flow theory with Morison drag. The lumped mass method is applied to model the mooring system. Both free decay tests and bichromatic wave conditions are considered in the model calibration process, and key uncertain parameters (e.g., mooring line length) that affect the response have been identified and discussed. Using the proposed calibration procedure, we establish a reasonably good numerical model for prediction of the platform motion and mooring dynamics. The low-frequency responses of the platform under bichromatic waves are well-captured. These outcomes contribute to the development of efficient numerical FOWT models under experimental uncertainty.

Reactive Gait Composition With Stability: Dynamic Walking Amidst Static and Moving Obstacles

Abstract This paper presents a modular approach to motion planning with provable stability guarantees for robots that move through changing environments via periodic locomotion behaviors. We focus on dynamic walkers as a paradigm for such systems, although the tools developed in this paper can be used to support general compositional approaches to robot motion planning with dynamic movement primitives (DMPs). By formulating the planning process as a switching system with multiple equilibria (SSME), we prove that the system's evolution remains within explicitly characterized trapping regions in the state space under suitable constraints on the frequency of switching among the DMPs. These conditions encapsulate the low-level stability limitations in a form that can be easily communicated to the planner. Furthermore, we show how the available primitives can be safely composed online in a receding horizon manner to enable the robot to react to moving obstacles. The proposed framework can be applied in a wide class of 3D bipedal walking models, and offers a modular approach for integrating readily available low-level locomotion control and high-level planning methods.

Функциональные резервы адаптации двигательной системы спортсменов с позиций физиолого-биомеханического подхода

Human adaptation to physical activity is manifested through mobilization of functional reserves. The purpose of this study was to provide a scientific and experimental substantiation of the adaptation of functional reserves of the motor system in athletes to specific sports activities from the standpoint of the physiological and biomechanical approach. Materials and methods. The study involved 704 elite athletes doing various sports. Reaction time was determined using the hardware and software package “Sports Psychophysiologist”. Stabilometric parameters were analysed using stabilometric platforms with the Smart BTS Motion System (BTS Bioengineering, Italy); the static analysis test protocol was applied. Electromyographic and biomechanical (kinematic and dynamic) movement control was performed using the Smart BTS Motion System as well. Functional reserves of the motor system were studied in line with the existing ideas about the components of the human body’s physiological reserves activated when doing sports. The following were evaluated: sensory systems (sensorimotor reactions, vestibular stability), movement control (stabilography, kinematics, dynamics), regulation of homeostasis, and implementation of activity (neuromuscular system). Results. We found that both single (in respect of urgent adaptation: an increase in voltage, optimization of kinematics and dynamics during a weightlifting snatch) and systematic (as regards long-term adaptation: improvement in reaction time and vestibular stability in athletes of various sports) training sessions involving maximum strength, power and speed contribute to the activation of the relevant sensory systems, central nervous system and muscular system, which form the basis of the motor system and increase its functionality as a whole.

Synthesis and Conformational Dynamics of Selenanthrene (Oxides): Establishing an Energetic Flexibility Index for Scaffolds.

The use of new dynamic scaffolds for constructing inorganic and organometallic complexes with enhanced reactivities is an important new research direction. Toward this fundamental aim, an improved synthesis of the dynamic scaffold selenanthrene, along with its monoxide, trans-dioxide and the previously unknown trioxide, is reported. A discussion of the potential reaction mechanism for selenanthrene is provided, and all products were characterized using 1H, 13C, and 77Se nuclear magnetic resonance (NMR) spectroscopy and single-crystal X-ray crystallography. The dynamic ring inversion processes (i.e., "butterfly motion") for selenanthrene and its oxides were investigated using variable-temperature 1H NMR and density functional theory calculations. The findings suggest that selenanthrene possesses a roughly equal barrier to inversion as its sulfur analogue, thianthrene. However, selenanthrene oxides evidently possess larger inversion barriers as compared to their sulfur analogues due to the enhanced electrostatic intramolecular interactions inherent between the highly polar selenium-oxygen bond and adjacent C-H moieties. Finally, we propose a quantitative "flexibility index" in deg/(kcal/mol) for various tricyclic scaffolds to provide researchers with a comparative scale of dynamic motion across many different systems.

Passivity-Based Control with Disturbance Observer of Electromagnetic Formation Flight Spacecraft in the Port-Hamiltonian Framework

Satellite formation flying technology currently represents a focal point in space mission research. Traditional spacecraft payload performance and lifespan are often constrained by propellant limitations. Electromagnetic Formation Flying (EMFF), a propellant-free formation flying technique, has garnered widespread attention. Its inherent strong nonlinearity and coupling present challenges for high-precision control within EMFF. This paper presents the relative motion dynamics of a two-satellite EMFF in the port-Hamiltonian framework and constructs an accurate nonlinear model of the dynamics. Utilizing the concept of Interconnection and Damping Assignment and nonlinear disturbance observer, a composite disturbance-rejection passivity-based controller is designed, offering a method for controlling the magnetic dipole strength of formation satellites. Finally, numerical simulations are conducted to demonstrate the viability of the proposed dynamics model and control strategy.

Numerical modeling of inkjet cell output under the interplay of cell-laden bioink consumption and sedimentation

Inkjet printing utilizes the bioink involving biological materials and living cells to generate cell-laden droplets for precise construction of 3D tissue/organ models in a layer-by-layer manner. While printing, the suspended cells in bioink sediment due to predominant gravitational force, and form cell aggregates. It is increasingly difficult to transfer aggregates to the nozzle dispenser, resulting in gradual decay of the cell output, which becomes a critical challenge significantly affecting printing reliability and quality. This study has proposed a computational model coupling the cell flow field due to cell sedimentation and the bioink flow field due to bioink consumption. The modeled cell output has been validated by the experimental results showing a good agreement. Precise prediction of cell output enables optimization of the bioprinting process with less trial-and-error cost and promotes fabrication of more consistent and reproducible bioconstructs. The study finds that (1) the measured cell sedimentation velocity at bioink reservoir bottom increases due to the greater cell aggregates formed while printing; (2) the cell movement dynamics revealed by the model exhibit reduced movement from the sides towards the center of the bioink reservoir due to an increased sedimentation effect over printing; (3) the cell output decreases by 75 % within 60-minute printing at 400 Hz frequency. Applying greater inkjet frequency from 200 to 1000 Hz enables greater cell output efficiency from 0.48 to 0.93; (4) under 75 % preset efficiency criterion, applying frequency > 97 Hz for 60-minute printing is recommended to secure positive cell output considering the minimal threshold to counter sedimentation.

Comparison of the Effects of Pilates and Yoga Exercise on the Dynamic Balancing Ability and Functional Movement of Fencers.

This study was conducted to compare and analyze whether Pilates exercise and yoga exercise help improve the performance of female fencers and prevent injury, and the dynamic balance test (LQ-YBT) and functional movement screening (FMS) test score of the elite adult female fencers were compared and analyzed as evaluation indicators. Participants were randomly classified into Pilates (n = 10) and yoga groups (n = 10), members of which took part in 50 min of exercise (5 min of warm-up, 40 min of main exercise, and 5 min of cool-down) twice weekly for eight weeks. The results obtained from this study were analyzed via independent t-test and 2-way ANOVA. The results were as follows: LQ-YBT measures (reaching distance) increased significantly for both groups, as did FMS scores (deep squat, hurdle step, inline lunge, shoulder mobility, active straight-leg raise, trunk-stability push-up, and rotary stability). These results suggest that Pilates exercise and yoga exercise might be likely effective in improving the performance of adult female fencers and injury prevention by increasing their dynamic balance ability and functional movement.

Profiling the acceleration and deceleration components in elite futsal players

ABSTRACT This retrospective observational study explores the acceleration and deceleration demands of elite male futsal players (age: 28.8 ± 2.4 years, weight: 73.7 ± 6.2 kg, height: 175.9 ± 5.9 cm) in official matches. Utilising a local positioning system, tracking data from twelve matches involving two elite teams with nineteen players was analysed. Physical demands were assessed at various thresholds, considering standing and rolling efforts based on initial and final velocities. The most prevalent efforts were rolling accelerations (32.4%) and decelerations (31.3%), along with standing accelerations (18.7%) and decelerations (17.6%). A majority of efforts occurred within small distances (less than 10 metres), representing 27.9% to 71.1% of cases. Intensity comparisons revealed that larger distances consistently had significantly higher velocities (d = 0.67 to d = 5.91). High-intensity efforts over large distances were notably shorter than their low-intensity counterparts, both in standing (d = 1.75 to d = 1.98) and rolling (d = 0.64 to d = 0.82) effort types. In essence, elite futsal players predominantly engage in rolling accelerations and decelerations within short distances, exhibiting average speeds below 3 m·s−2. This insight into the nuanced dynamics of player movements provides valuable information for optimising training regimens and enhancing performance in elite futsal competitions.

Consistent Individual Differences Drive Collective Movements in a Tibetan Macaque Group

Collective movement has emerged as a key area of interest in animal behavior. While individual differences are often viewed as a potential threat to group cohesion, growing evidence suggests that these differences can actually influence an animal’s behavior as an initiator or follower during collective movements, thereby driving the group‘s movement and decision-making processes. To resolve the divergence, we asked how personality can affect the dynamics of collective movements in one group of free-ranging Tibetan macaques (Macaca thibetana) in Huangshan, China. We assessed individual personality using principal component analysis and applied the generalized linear mixed model and linear mixed model to examine the influence of personality on decision making during collective movements. Our findings reveled three distinct personality types among Tibetan macaques: sociability, boldness, and anxiousness. Individuals with higher sociability scores and rank, or those with lower anxiousness scores, were more likely to initiate successful collective movements. Older individuals were less successful in initiating movements compared to young adults. Leaders with lower anxiousness scores or higher rank attracted more followers, with females attracting larger groups than males. As for followers, individuals with higher rank tended to join the collective movement earlier. Additionally, individuals with higher sociability or boldness scores had shorter joining latency in collective movement. Finally, there was a longer joining latency for middle-aged adults compared to young adults. These results suggest that individual differences are a potential driver of collective movements. We provide some insights into the relationships between personality and decision making in Tibetan macaques.

Modulation of reaching by spatial attention

Attention is needed to perform goal-directed vision-guided movements. We investigated whether the direction of covert attention modulates movement outcomes and dynamics. Right-handed and left-handed volunteers attended to a spatial location while planning a reach toward the same hemifield, the opposite one, or planned a reach without constraining attention. We measured behavioral variables as outcomes of ipsilateral and contralateral reaching and the tangling of behavioral trajectories obtained through principal component analysis as a measure of the dynamics of motor control. We found that the direction of covert attention had significant effects on the dynamics of motor control, specifically during contralateral reaching. Data suggest that motor control was more feedback-driven when attention was directed leftward than when attention was directed rightward or when it was not constrained, irrespectively of handedness. These results may help to better understand the neural bases of asymmetrical neurological diseases like hemispatial neglect.

Next-Generation Cardiac Interfacing Technologies Using Nanomaterial-Based Soft Bioelectronics.

Cardiac interfacing devices are essential components for the management of cardiovascular diseases, particularly in terms of electrophysiological monitoring and implementation of therapies. However, conventional cardiac devices are typically composed of rigid and bulky materials and thus pose significant challenges for effective long-term interfacing with the curvilinear surface of a dynamically beating heart. In this regard, the recent development of intrinsically soft bioelectronic devices using nanocomposites, which are fabricated by blending conductive nanofillers in polymeric and elastomeric matrices, has shown great promise. The intrinsically soft bioelectronics not only endure the dynamic beating motion of the heart and maintain stable performance but also enable conformal, reliable, and large-area interfacing with the target cardiac tissue, allowing for high-quality electrophysiological mapping, feedback electrical stimulations, and even mechanical assistance. Here, we explore next-generation cardiac interfacing strategies based on soft bioelectronic devices that utilize elastic conductive nanocomposites. We first discuss the conventional cardiac devices used to manage cardiovascular diseases and explain their undesired limitations. Then, we introduce intrinsically soft polymeric materials and mechanical restraint devices utilizing soft polymeric materials. After the discussion of the fabrication and functionalization of conductive nanomaterials, the introduction of intrinsically soft bioelectronics using nanocomposites and their application to cardiac monitoring and feedback therapy follow. Finally, comments on the future prospects of soft bioelectronics for cardiac interfacing technologies are discussed.

Recognizing online video genres using ensemble deep convolutional learning for digital media service management

It's evident that streaming services increasingly seek to automate the generation of film genres, a factor profoundly shaping a film's structure and target audience. Integrating a hybrid convolutional network into service management emerges as a valuable technique for discerning various video formats. This innovative approach not only categorizes video content but also facilitates personalized recommendations, content filtering, and targeted advertising. Given the tendency of films to blend elements from multiple genres, there is a growing demand for a real-time video classification system integrated with social media networks. Leveraging deep learning, we introduce a novel architecture for identifying and categorizing video film genres. Our approach utilizes an ensemble gated recurrent unit (ensGRU) neural network, effectively analyzing motion, spatial information, and temporal relationships. Additionally,w we present a sophisticated deep neural network incorporating the recommended GRU for video genre classification. The adoption of a dual-model strategy allows the network to capture robust video representations, leading to exceptional performance in multi-class movie classification. Evaluations conducted on well-known datasets, such as the LMTD dataset, consistently demonstrate the high performance of the proposed GRU model. This integrated model effectively extracts and learns features related to motion, spatial location, and temporal dynamics. Furthermore, the effectiveness of the proposed technique is validated using an engine block assembly dataset. Following the implementation of the enhanced architecture, the movie genre categorization system exhibits substantial improvements on the LMTD dataset, outperforming advanced models while requiring less computing power. With an impressive F1 score of 0.9102 and an accuracy rate of 94.4%, the recommended model consistently delivers outstanding results. Comparative evaluations underscore the accuracy and effectiveness of our proposed model in accurately identifying and classifying video genres, effectively extracting contextual information from video descriptors. Additionally, by integrating edge processing capabilities, our system achieves optimal real-time video processing and analysis, further enhancing its performance and relevance in dynamic media environments.

Learning an Autonomous Dynamic System to Encode Periodic Human Motion Skills.

Learning an autonomous dynamic system (ADS) encoding human motion rules has been shown as an effective way for human motion skills transfer. However, most existing approaches focus on goal-directed motion skills transfer, and the study on periodic motion skills transfer is rare. One popular approach for periodic motion skills transfer is learning periodic dynamic movement primitive (DMP); however, periodic DMP is sensitive to spatial disturbances due to the introduction of the phase parameters. To solve this issue, this brief presents a novel approach to learn an ADS with a stable limit cycle without introducing phase parameters. First, a data-driven Lyapunov function (energy function) is learned, such that one of its level surfaces is consistent with periodic human demonstration trajectories. Then, an ADS is learned by sequentially solving energy function-related constrained optimization problems. With a proper design of constraint functions, we can ensure that the trajectory generated by the ADS will converge to an energy function-level surface, of which the shape is similar to periodic human demonstration trajectories. Experiments are conducted to show the effectiveness of the proposed approach (PA).

Ni migration on porous yttria-stabilized zirconia and yttria-micropatterned fuel electrodes in solid oxide fuel cells

This study investigates the mechanism of Ni migration and methods for preventing Ni migration by utilizing ceramic obstacles that can block or slow Ni movement during solid oxide fuel cell (SOFC) operation. A patterned thin-Ni model anode on mirror-polished yttria-stabilized zirconia (YSZ) substrate exhibited dynamic movement during operation, as reported previously. In this study, we attempt to elucidate the mechanism of Ni migration that occurs only on the surface of solid-state Ni by blocking or slowing this movement using porous patterns of different materials. Porous micropatterns of 100 % YSZ and 80 wt% yttria (Y2O3) + YSZ composites were fabricated on a YSZ electrolyte, and velocity changes and blocking of Ni were observed. The porous YSZ structure changed the velocity of the Ni. In contrast, no Ni migration occurred in the Y2O3/YSZ composite porous structure, despite migration occurring in the neighboring smooth YSZ area in the same cell. The Ni-migrated areas were separated by the Y2O3/YSZ porous area, indicating that Ni migration was not caused by microscale differences in temperature or supplied gas diffusion, and Ni moved only on the cell surface, not via Ni-containing gases because temperatures and gases cannot form micropatterns.