Divergent Component Research Articles

The effects of assessment instruction and test anxiety on divergent components of creative problem-solving tasks

IntroductionThis study looked at how an assessment instruction and test anxiety (TA) can influence divergent thinking (DT) components of creativity in a playful robotic problem-solving task.MethodsWe measured TA and creative performance (TD) under assessment and non-assessment conditions in 122 secondary students engaged in creative problem solving (CPS).ResultThe aspects of DT (fluidity and originality) showed a tendency to be impacted by assessment instruction. Thus, under non-assessment conditions, the learners show higher fluidity and better originality in the first occurrence of the CPS task. In the second occurrence, time spent on CPS decreases. Moreover, the originality turns to be impaired in the second trial and only student under assessment maintain their engagement in the activity. No correlation was found between TA and DT, and no gender or age differences were observed. The results suggest that TA does not influence the performance of the students involved in creative problem-solving processes.DiscussionWe discuss the findings in relation to game-based learning specificities. The assessment instruction in playful activities can be perceived as a positive challenge and even the students showing higher levels of test anxiety do not perceive it as a threat. Furthermore, if time constraints are minimized, the impact of assessment instruction on creative performance might be further reduced. The finding of this study opens promising perspectives to the research on innovative forms of school assessment and creative problem solving.

Balance and Walking Control for Biped Robot Based on Divergent Component of Motion and Contact Force Optimization

Balance and Walking Control for Biped Robot Based on Divergent Component of Motion and Contact Force Optimization

Generalized div-curl based regularization for physically constrained deformable image registration

Variational image registration methods commonly employ a similarity metric and a regularization term that renders the minimization problem well-posed. However, many frequently used regularizations such as smoothness or curvature do not necessarily reflect the underlying physics that apply to anatomical deformations. This, in turn, can make the accurate estimation of complex deformations particularly challenging. Here, we present a new highly flexible regularization inspired from the physics of fluid dynamics which allows applying independent penalties on the divergence and curl of the deformations and/or their nth order derivative. The complexity of the proposed generalized div-curl regularization renders the problem particularly challenging using conventional optimization techniques. To this end, we develop a transformation model and an optimization scheme that uses the divergence and curl components of the deformation as control parameters for the registration. We demonstrate that the original unconstrained minimization problem reduces to a constrained problem for which we propose the use of the augmented Lagrangian method. Doing this, the equations of motion greatly simplify and become managable. Our experiments indicate that the proposed framework can be applied on a variety of different registration problems and produce highly accurate deformations with the desired physical properties.

A hybrid TIM complex mediates protein import into hydrogenosomes of Trichomonas vaginalis

BackgroundHydrogenosomes are a specific type of mitochondria that have adapted for life under anaerobiosis. Limited availability of oxygen has resulted in the loss of the membrane-associated respiratory chain, and consequently in the generation of minimal inner membrane potential (Δψ), and inefficient ATP synthesis via substrate-level phosphorylation. The changes in energy metabolism are directly linked with the organelle biogenesis. In mitochondria, proteins are imported across the outer membrane via the Translocase of the Outer Membrane (TOM complex), while two Translocases of the Inner Membrane, TIM22, and TIM23, facilitate import to the inner membrane and matrix. TIM23-mediated steps are entirely dependent on Δψ and ATP hydrolysis, while TIM22 requires only Δψ. The character of the hydrogenosomal inner membrane translocase and the mechanism of translocation is currently unknown.ResultsWe report unprecedented modification of TIM in hydrogenosomes of the human parasite Trichomonas vaginalis (TvTIM). We show that the import of the presequence-containing protein into the hydrogenosomal matrix is mediated by the hybrid TIM22-TIM23 complex that includes three highly divergent core components, TvTim22, TvTim23, and TvTim17-like proteins. The hybrid character of the TvTIM is underlined by the presence of both TvTim22 and TvTim17/23, association with small Tim chaperones (Tim9-10), which in mitochondria are known to facilitate the transfer of substrates to the TIM22 complex, and the coupling with TIM23-specific ATP-dependent presequence translocase-associated motor (PAM). Interactome reconstruction based on co-immunoprecipitation (coIP) and mass spectrometry revealed that hybrid TvTIM is formed with the compositional variations of paralogs. Single-particle electron microscopy for the 132-kDa purified TvTIM revealed the presence of a single ring of small Tims complex, while mitochondrial TIM22 complex bears twin small Tims hexamer. TvTIM is currently the only TIM visualized outside of Opisthokonta, which raised the question of which form is prevailing across eukaryotes. The tight association of the hybrid TvTIM with ADP/ATP carriers (AAC) suggests that AAC may directly supply ATP for the protein import since ATP synthesis is limited in hydrogenosomes.ConclusionsThe hybrid TvTIM in hydrogenosomes represents an original structural solution that evolved for protein import when Δψ is negligible and remarkable example of evolutionary adaptation to an anaerobic lifestyle.

Modulating effect of the divergent and rotational wind induced by mesoscale sea surface temperature perturbations in the Kuroshio Extension

AbstractMesoscale wind stress perturbations induced by sea surface temperature (SST) perturbations have a feedback effect on the ocean by influencing air–sea heat and momentum fluxes. Unlike the thermal feedback mechanism, which is well understood, the momentum feedback still needs to be studied, especially the respective roles of divergent and rotational wind components. In this study, momentum feedback was examined using an ocean model and an empirical equation, which solved wind stress field perturbations from their divergence and curl estimated from time‐evolving downwind and crosswind SST gradients. Through several numerical experiments, it was found that both the divergent and rotational wind can induce positive and negative temperature changes at varying regions and depths. This modulating effect is weak, with a maximum SST change of about 0.4°C on average, but it can reach the deep ocean beyond 1000 m.

The Rotational and Divergent Kinetic Energy Spectra of Geostrophic Vortices and Inertia‐Gravity Waves

AbstractThe rotational and divergent kinetic energy (RKE and DKE) spectra of geostrophic vortices (Rossby waves; RWs) and inertia‐gravity waves (IGWs) in the global atmosphere are investigated with ERA5 reanalysis. The separation of RWs and IGWs in physical space is based on the normal‐mode decomposition, and the Helmholtz decomposition produces their RKE and DKE spectra at different layers, with a focus on spherical wavenumbers 10 ≤ l ≤ 100. In the upper troposphere and the middle and lower stratosphere, the RKE spectra of the total mode closely resemble the horizontal kinetic energy (HKE) spectra of RWs over most wavenumbers; the DKE spectra of the total mode are more comparable to the DKE spectra rather than the HKE spectra of IGWs, although their slopes are similar. The HKE of RWs is dominated by its rotational component, accounting for more than 80% of the HKE in most ranges of concern. Although the HKE of IGWs is dominated by its divergent component, its rotation component is also significant, with an average percentage exceeding 25% in all three vertical layers analyzed. Care must be taken when employing divergence as a proxy of IGWs, as the DKE may underestimate the HKE of IGWs. With the increase of altitude and the decrease of scale, the contribution of the divergent component increases in the horizontal circulation of both RWs and IGWs.

Enhancing speed recovery rapidity in bipedal walking with limited foot area using DCM predictions

The research on bipedal robots with limited foot area is gaining increasing attention. To tackle the challenge of dealing with unknown disturbances in the environment, the adjustment of footstep placement plays a vital role in maintaining stable motion during bipedal walking. This paper introduces an innovative approach based on the relationship between the Divergent Component of Motion (DCM) and footstep. It utilizes a DCM prediction model to optimize the optimal speed for recovering the foothold position. The goal is to enable quick and relevant footstep selection for bipedal robots, thereby facilitating the swift recovery of robot speed. The paper provides insights into the process of designing the desired DCM for achieving an optimal average walking speed without relying on predefined footstep sequences. By establishing a state equation between the DCM and footstep placement, this approach enables the prediction of multiple footstep positions within a fixed walking cycle, thereby facilitating the desired average motion speed. Extensive numerical simulations are conducted to compare the proposed method with various conventional footstep adjustment algorithms. The results emphasize our method’s ability to converge more rapidly to the target speed, even with minor step adjustments. To validate the feasibility and robustness of the algorithm, we conduct experiments on the bipedal robot BHR-B2. These experiments further confirm the algorithm’s effectiveness. Given its promising performance, this algorithm holds potential for applications in legged robots with point feet.

Divergent Component of Motion Planning and Adaptive Repetitive Control for Wearable Walking Exoskeletons.

Wearable walking exoskeletons show great potentials in helping patients with neuro musculoskeletal stroke. Key to the successful applications is the design of effective walking trajectories that enable smooth walking for exoskeletons. This work proposes a walking planning method based on the divergent component of motion to obtain a stable joint angle trajectory. Since periodic and nonperiodic disturbances are ubiquitous in the repeating walking motion of an exoskeleton system, a major challenge in the walking control of wearable exoskeleton is the joint angle drift problem, that is, the joint angle motion trajectories are not necessarily periodic due to the presence of disturbance. To address this challenge, this work develops an adaptive repetitive control strategy to guarantee that the motion trajectories of joint angle are repetitive. In particular, by treating the disturbance as system uncertainties, an adaptive controller is designed to compensate for the uncertainties based on an integral-type Lyapunov function. A fully saturated learning approach is then developed to achieve asymptotic tracking of repetitive walking trajectories. Extensive experiments are carried out to demonstrate the effectiveness of the tracking performance.

What Effects the Generalization in Visual Reinforcement Learning: Policy Consistency with Truncated Return Prediction

In visual Reinforcement Learning (RL), the challenge of generalization to new environments is paramount. This study pioneers a theoretical analysis of visual RL generalization, establishing an upper bound on the generalization objective, encompassing policy divergence and Bellman error components. Motivated by this analysis, we propose maintaining the cross-domain consistency for each policy in the policy space, which can reduce the divergence of the learned policy during the test. In practice, we introduce the Truncated Return Prediction (TRP) task, promoting cross-domain policy consistency by predicting truncated returns of historical trajectories. Moreover, we also propose a Transformer-based predictor for this auxiliary task. Extensive experiments on DeepMind Control Suite and Robotic Manipulation tasks demonstrate that TRP achieves state-of-the-art generalization performance. We further demonstrate that TRP outperforms previous methods in terms of sample efficiency during training.

Analysis of a two phase flow model of biofilm spread

We consider a quasi-stationary problem describing the status of velocities, pressures and chemicals affecting cell behavior within a biofilm. The model couples stationary transport equations and compressible Stokes systems with convection–reaction–diffusion equations. We establish existence, uniqueness and stability of solutions of the different submodels involved and then obtain well posedness results for the quasi-stationary system. Our analysis relies on the construction of weak solutions for the steady transport equations under sign assumptions and the reformulation of the compressible Stokes problem as an elliptic system with enhanced regularity properties on the pressure. We need to consider velocity fields whose divergence and normal boundary components satisfy sign conditions. Applications include the study of cells, biofilms and tissues, where one phase is a liquid solution, whereas the other one is assorted biomass.

Enhancement of humanoid robot locomotion on slippery floors using an adaptive controller

AbstractThis paper presents a comprehensive strategy to improve the locomotion performance of humanoid robots on various slippery floors. The strategy involves the implementation and adaptation of a divergent component of motion (DCM) based control architecture for the humanoid NAO, and the introduction of an embedded yaw controller (EYC), which is based on a proportional-integral-derivative (PID) control algorithm. The EYC is designed not only to address the slip behavior of the robot on low-friction floors but also to tackle the issue of non-straight walking patterns that we observed in this humanoid, even on non-slippery floors. To fine-tune the PID gains for the EYC, a systematic trial-and-error approach is employed. We iteratively adjusted the P (Proportional), I (Integral), and D (Derivative) parameters while keeping the others fixed. This process allowed us to optimize the PID controller’s response to different walking conditions and floor types. A series of locomotion experiments are conducted in a simulated environment, where the humanoid step frequency and PID gains are varied for each type of floor. The effectiveness of the strategy is evaluated using metrics such as robot stability, energy consumption, and task duration. The results of the study demonstrate that the proposed approach significantly improves humanoid locomotion on different slippery floors, by enhancing stability and reducing energy consumption. The study has practical implications for designing more versatile and effective solutions for humanoid locomotion on challenging surfaces and highlights the adaptability of the existing controller for different humanoid robots.

Rider Cooperative Control of Rear-Wheel-Swing Motorcycle Based on Divergent Component of Motion

Rider Cooperative Control of Rear-Wheel-Swing Motorcycle Based on Divergent Component of Motion

Spatiotemporal Characteristics of the Near-Surface Turbulent Cascade at the Submesoscale in the Drake Passage

Abstract Submesoscale currents and internal gravity waves achieve an intense turbulent cascade near the ocean surface [depth of 0–O(100) m], which is thought to give rise to significant energy sources and sinks for mesoscale eddies. Here, we characterize the contributions of nonwave currents (NWCs; including eddies and fronts) and internal gravity waves (IGWs; including near-inertial motions, lee waves, and the internal wave continuum) to near-surface submesoscale turbulence in the Drake Passage. Using a numerical simulation, we combine Lagrangian filtering and a Helmholtz decomposition to identify NWCs and IGWs and to characterize their dynamics (rotational versus divergent). We show that NWCs and IGWs contribute in different proportions to the inverse and forward turbulent kinetic energy cascades, based on their dynamics and spatiotemporal scales. Purely rotational NWCs cause most of the inverse cascade, while coupled rotational–divergent components of NWCs and coupled NWC–IGWs cause the forward cascade. The cascade changes direction at a spatial scale at which motions become increasingly divergent. However, the forward cascade is ultimately limited by the motions’ spatiotemporal scales. The bulk of the forward cascade (80%–95%) is caused by NWCs and IGWs of small spatiotemporal scales (L < 10 km; T < 6 h), which are primarily rotational: submesoscale eddies, fronts, and the internal wave continuum. These motions also cause a significant part of the inverse cascade (30%). Our results highlight the requirement for high spatiotemporal resolutions to diagnose the properties and large-scale impacts of near-surface submesoscale turbulence accurately, with significant implications for ocean energy cycle study strategies.

Clustering of Floating Tracers in a Random Velocity Field Modulated by an Ellipsoidal Vortex Flow

The influence of a background vortex flow on the clustering of floating tracers is addressed. The vortex flow considered is induced by an ellipsoidal vortex evolving in a deformation. The system exhibits various vortex motion regimes: (1) a steady state, (2) oscillation and (3) rotation of the ellipsoidal vortex core. The latter two induce an unsteady velocity field for the tracer, thus leading to irregular (chaotic) tracer motion. Superimposing a stochastic divergent velocity field onto the deterministic vortex flow allows us to observe significantly different tracer evolution. An ellipsoidal vortex has ellipsoidal symmetry, and the tracer’s trajectories exhibit the same symmetry inside the vortex. Outside the vortex, the external deformation flow symmetry dominates. Diffusion scattering and chaotic advection give tracers the opportunity to leave the region of ellipsoidal symmetry and form a picture of shear flow symmetry. We use the method of characteristics to integrate the floating tracer density evolution equation and the Euler Ito scheme for obtaining the floating tracer trajectories with a random velocity field. The cluster area and cluster mass from the statistical topography are used as the quantitative diagnostics of a floating tracer’s clustering. For the case of a steady ellipsoidal vortex embedded into the deformation flow with a random velocity field component, we found that the clustering characteristics were weakened by the steady vortex. For the cases of an unsteady ellipsoidal vortex, we observed clustering in the floating tracer density field if the contribution of the divergent component was greater than or equal to that of the rotational (nondivergent) component. Even when the initial floating tracer patch was set on the boundary of the oscillating ellipsoidal vortex, we observed the formation of clusters. In the case of a rotating ellipsoidal vortex, we also observed pronounced clustering. Thus, we argue that unsteady ellipsoidal vortex regimes (oscillation and rotation), which induce chaotic motion of the nearby passive tracer’s trajectories, are still conducive to clustering of floating tracers observed in the density field, despite the intense deformation introduced by strain and shear.

Quantifying the impact of assimilating sensitive observations on heavy precipitation forecast with ensemble-based forecast sensitivity to observations technique

In this study, the Ensemble-based Forecast Sensitivity to Observations (EFSO) technique was used to examine the impact of assimilated sensitive observations on the forecast of heavy rainfall through three data assimilation strategies, i.e., running without observation assimilation (CNTL); with assimilation of all observations (CNTL_DA); with assimilation of sensitive observations (SEN_DA). The Infrared Atmospheric Sounder Interferometer presented the largest positive impact on the forecast, followed by the Advanced Microwave Sounding Unit A and surface land reports. The top 10% of observations contributing the largest positive impact on the forecast were located in the upstream ocean of the low-level winds associated with precipitation maximum. Compared to ensemble CNTL and CNTL_DA experiments, ensemble SEN_DA exhibited better precipitation probability, in which the representative member in ensemble SEN_DA successfully predicted the precipitation magnitude and location. Based upon the representative experiments of the ensemble CNTL, CNTL_DA, and SEN_DA, synoptic conditions were examined to understand how the SEN_DA improves the forecast of heavy precipitation. The three representative experiments exhibited similar characteristics and variations in large-scale circulation, horizontal water vapor transport, and wind fields. However, compared to the representative experiments of CNTL and CNTL_DA, the advection and barotropic components of potential divergence contributed to the increase and persistence of convective instability throughout heavy rainfall in SEN_DA. Heavy precipitation was closely associated with the intensity, duration, and location of the maximum convective instability. Furthermore, the release of convective instability depended on the mesoscale ascent, which determined the maximum and location of the precipitation. These results help to understand the optimization of observational design and assimilation strategy.

Unified Motion Planner for Walking, Running, and Jumping Using the Three-Dimensional Divergent Component of Motion

Unified Motion Planner for Walking, Running, and Jumping Using the Three-Dimensional Divergent Component of Motion

Road crossings change functional diversity and trait composition of stream-dwelling macroinvertebrate assemblages

Functional diversity is regarded as a key concept in understanding the link between ecosystem function and biodiversity, and is therefore widely investigated in relation to human-induced impacts. However, information on how the intersection of roads and streams (hereafter road crossings, representing a widespread habitat transformation in relation to human development), influences the functional diversity of stream-dwelling macroinvertebrates is still missing. The general aim of our study was to provide a comprehensible picture on the impacts of road crossing structures on multiple facets of the functional diversity of stream-dwelling macroinvertebrates. In addition, we also investigated changes in trait structure. Our research showed that road crossing structures had negative impacts on functional richness and dispersion; i.e., functional diversification. However, we found no significant impact on functional divergence and evenness components. We found a decrease in functional redundancy at road crossing structures. This indicates a reduced ability of the community to recover from disturbances. Finally, we found that road crossings drive stream habitat and hydrological changes in parallel with modification of the trait composition of stream-dwelling macroinvertebrate assemblages. All these results suggest that road crossings cause notable changes in the functional diversity of stream-dwelling macroinvertebrate assemblages.

Лингвокультурные универсалии как доминирующий фактор восприятия мемов

The current study discusses the meme as a polycode text from the standpoint of linguoculturology. Based on the theories on exististing congruent cultural universals and divergent linguoculturemes, in the present paper a classification of memes is offered. It suggests to differentiate between three types of both the visual and verbal components of the meme: congruent, divergent or lacunary. Validity of the elaborated classification is evidenced using the results of the study investigating the way Russian and Chinese COVID-19 Internet memes may be perceived by Russian and Chinese recipients. The conclusion to be drawn is that congruent visual component allows for a more profound understanding of the meme by representatives of a different culture; at that, the verbal component might be either congruent, or divergent, or lacunary. On the contrary, the models including a divergent or lacunary visual component cannot be properly perceived by other cultures, irrespective of the type of the visual component.

The male's scent triggered a neural response in females despite ambiguous behavioral response in Asian house rats.

Pheromones and olfactory communication play vital roles in sex recognition and mate choice in rodents. Asian house rats (Rattus tanezumi) (RT) often startle easily, making behavioral measurements difficult to carry out accurately in the laboratory. Here, the behavioral and olfactory preferences of the female RT between males and females were not observed using a conventional two-choice device; we then explored the neuro-immunohistochemical evidence in the brains of RT females. We found that male urine elicited significantly higher c-fos expression in the accessory olfactory system and sex-related brain regions in females than female urine did. On the other hand, the differences of volatile compounds and major urinary proteins (MUPs) in both voided urine and preputial glands (PGs) of the RT were detected using gas chromatography-mass spectrometer, sodium dodecyl sulfate-polyacrylamide gel electrophoresis, isoelectric focusing electrophoresis, and liquid chromatography-electrospray ionization mass spectrometry. We found that PG-derived 1-(4,5-dihydro-2-thiazolyl)-ethanone and total MUPs were more abundant in males versus females, suggesting these sexually divergent components might activate the female's accessory olfactory system. In conclusion, the neuro-immunohistochemical evidence indicated that potential sex pheromones might exist in RT; however, the strength of the chemical signal might be too weak to cause behavioral responses in females.

Intercomparison of tropospheric and stratospheric mesoscale kinetic energy resolved by the high‐resolution global reanalysis datasets

AbstractWith the development of advanced data assimilation and computing techniques, many modern global reanalysis datasets aim to resolve the atmospheric mesoscale spectrum. However, large uncertainties remain with respect to the representation of mesoscale motions in these reanalysis datasets, for which a clear understanding is lacking. The aforementioned challenges have served as a strong motivation to reveal and quantify their mesoscale differences. This study presents the first comprehensive global intercomparison of the tropospheric and stratospheric mesoscale kinetic energy and its spectra over two selected periods of summer and winter events among six leading high‐resolution atmospheric reanalysis products: European Centre for Medium‐Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), China Meteorological Administration Reanalysis, Modern‐Era Retrospective Analysis for Research and Applications version 2, National Centers for Environmental Prediction's Climate Forecast System version 2 (CFSv2), Japanese 55‐year Reanalysis, and ECMWF Reanalysis‐Interim. A state‐of‐the‐art global operational model is adopted as a supplementary reference. Although all reanalysis datasets can reproduce broad distribution characteristics that are grossly consistent with the 9 km model, there are substantial discrepancies among them in magnitudes. The ability to capture mesoscale signals is closely linked to their resolutions, but it is also impacted by other factors, including, but not limited to, the selected types of energy, seasons, altitudes, latitudes, model diffusions, parametrization schemes, moist condition, assimilation methods, and observation inputs. Moreover, all datasets illustrate conclusive behaviors for the prevalence of the rotational component in the troposphere, whereas only very few products fail to exhibit the dominance of the divergent component in the stratosphere. Overall, stratospheric ERA5 and CFSv2 outperform the other reanalysis datasets, and only these two can reproduce the feature of the canonical kinetic energy spectrum with a distinct shift from a steeper slope (approximately −3) at lower wave numbers to a shallower slope (approximately −5/3) at higher wave numbers. In addition, the relative disparities among datasets increase dramatically with height, and they are more pronounced in the divergent component. It is also found that the correlations among these datasets are much weaker in the Tropics.