Motion Energy Research Articles

“Vulnerability can breed strength”: The role of borderline personality disorder severity in movement synchrony among patients with major depressive disorder

Objective: Patients with Major depressive disorder (MDD) and a comorbid Borderline personality disorder (BPD) show a poorer prognosis for MDD compared to patients without BPD. Little is known about the therapeutic processes underlying this prognosis. The goal of the present study was to investigate whether patients with more severe BPD symptoms experience less strengthening in patient-therapist movement synchrony (MS) throughout treatment, and whether less strengthening in MS is associated with less effective sessions. Method: Ninety-five patients participating in a randomized control trial were assessed for BPD (N = 9) using the Structured Interview for DSM-IV Personality. 1367 video-taped sessions were analyzed for MS using Motion Energy Analysis. Session effectiveness was evaluated following each session using a one-item scale taken from the Helping Skills Measure. Multilevel models were used to assess whether BPD severity predicted MS throughout treatment, and whether MS predicted session effectiveness. Results: Patients with more severe BPD symptoms experienced greater strengthening in MS throughout treatment. Less MS strengthening was associated with less session effectiveness. Conclusion: These findings indicate unique therapeutic processes that characterize individuals with more severe BPD symptoms. Shedding light on these unique processes has the potential to contribute to the personalization of MDD treatment for patients with BPD.

Compound nucleus formation cross sections in lead-induced reactions

The formation of the compound nucleus in heavy-ion collisions is considered in two steps. The first step is related to the penetration of the ions through the capture barrier, the formation of the sticking nuclei in the capture well, and the transfer of kinetic energy of relative motion into the intrinsic energy of the sticking nuclei. The second step is associated with the compound-nucleus formation from the sticking nuclei in competition to the quasielastic scattering. The compound nucleus is preferably formed when the height of the compound nucleus formation barrier is substantially smaller than the height of the quasielastic barrier. This leads to the values of the capture and compound nucleus formation cross sections being close. In contrast, the formation of the compound nuclei is suppressed when the height of the compound-nucleus formation barrier is close to or larger than that of the quasielastic barrier. In this case, the capture cross sections are greater than the compound-nucleus formation cross sections. The suppression of the compound-nucleus formation is increased with the mass and charge of ions colliding with lead because the quasielastic barrier height obtained relative to the compound nucleus ground state is decreased with the mass and charge of ions colliding with lead and the role of the compound-nucleus formation barrier rises. The dependence of the compound-nucleus formation suppression on the shell-correction energy of the compound nucleus is shown. The available experimental data for 14 heavy-ion reactions induced by lead are well described in the model. Published by the American Physical Society 2025

Landau levels induced by synthetic strain in plasmonic metasurface

The quantum Hall effect arises when electrons in a two-dimensional plane are subjected to a magnetic field, causing them to undergo cyclotron motion and form discrete energy levels, known as Landau levels. These levels play a critical role in condensed matter physics. However, practical limitations of applying a magnetic field have led to the introduction of pseudomagnetic fields, which can similarly induce Landau levels. Such pseudomagnetic fields are typically generated through synthetic strain, achieved by deforming geometric patterns, and have been applied to systems like graphene, photons, and phonon crystals. Building on previous research in electronics and optics, we present a plasmonic metasurface that induces Landau levels via synthetic strain in the microwave frequency range. This strain is realized by printing metal structures of specific shapes on a dielectric substrate using printed circuit board technology. The fundamental unit of the plasmonic metasurface is a C6 symmetric structure composed of six localized surface plasmon patches. By applying a displacement function along the transmission direction, we discretize the dispersion curve, leading to band degeneration and the emergence of edge states. The distribution of these edge states is influenced by the strength of the pseudomagnetic field, which is controlled by the magnitude of the displacement function. We validate our design through fabricated models and demonstrate the existence of edge states using near-field scanning experiments. Our work, which combines synthetic magnetic fields and plasmonic metasurface, provides valuable insights for the development and application of integrated photonic devices.

Research on mixed steel and ceramic balls in tumbling mills: Motion behavior and energy evolution

Research on mixed steel and ceramic balls in tumbling mills: Motion behavior and energy evolution

An elbow passive exoskeleton with controllable assistance: Design and experimental.

A passive exoskeleton is a wearable robotic device that is worn on the exterior of the user's body to provide physical support and facilitate movement. Existing elbow passive exoskeletons have limitations in their assistance capabilities and range of applications. In this paper, we propose a controllable elbow passive exoskeleton (CEPE) to address these limitations. The CEPE features a ratchet-based self-energy storage mechanism (RSSM) and a Candan gravity compensation mechanism (CGCM). The CGCM counteracts gravitational forces, while the RSSM stores and releases motion energy. This paper establishes a mathematical model for the RSSM, outlines design specifications for both the RSSM and CEPE, and analyzes the influence of design parameters on the power assistance performance. Three experiments were conducted to validate the feasibility of CEPE, including static strength testing, power assistance without load, and power assistance with load. Results show that, without loading, the CEPE provides compensation effects on elbow joint torque of 68.8%, 93.8%, and 70.7% at shoulder joint angles of 0°, 30°, and 60°, respectively. With a 5kg loading, adjusting the shoulder joint angle from 30° to 60° results in an increase in the decrease of the average absolute torque directly acting on the elbow joint, from 86% to 91.2%. The adjustable RSSM enables the CEPE to operate in four different modes, expanding its potential applications.

A Honeycomb-Structured Triboelectric Nanogenerator Based on Polyester Cloth for Smart Running Application.

Self-powered devices for human motion monitoring and energy harvesting have garnered widespread attention in recent research. In this work, we designed a honeycomb-structured triboelectric nanogenerator (H-TENG) using polyester cloth and Teflon tape, with aluminum foil as the conductive electrode. This design leverages the large surface area and flexibility of textiles, resulting in significant performance improvements. The H-TENG achieves an output voltage of 350 V, an output current of 42 μA, and a transfer charge (QSC) of 77 nC, with a maximum output power of 465 μW. Additionally, the H-TENG demonstrates the ability to monitor running activities and various gait patterns, providing real-time bio-mechanical data for smart running applications. The introduction of a stacked structure further enhances the output performance by increasing contact area and scalability, making the H-TENG a robust and high-performance energy harvester suitable for advanced wearable and flexible electronics.

Applying cognitive diagnostic models to mechanics concept inventories

In physics education research, instructors and researchers often use research-based assessments (RBAs) to assess students’ skills and knowledge. In this paper, we support the development of a mechanics cognitive diagnostic to test and implement effective and equitable pedagogies for physics instruction. Adaptive assessments using cognitive diagnostic models provide significant advantages over fixed-length RBAs commonly used in physics education research. As part of a broader project to develop a cognitive diagnostic assessment for introductory mechanics within an evidence-centered design framework, we identified and tested the student models of four skills that cross content areas in introductory physics: apply vectors, conceptual relationships, algebra, and visualizations. We developed the student models in three steps. First, we based the model on learning objectives from instructors. Second, we coded the items on RBAs using the student models. Finally, we then tested and refined this coding using a common cognitive diagnostic model, the deterministic inputs, noisy “and” gate model. The data included 19 889 students who completed either the Force Concept Inventory, Force and Motion Conceptual Evaluation, or Energy and Momentum Conceptual Survey on the LASSO platform. The results indicated a good to adequate fit for the student models with high accuracies for classifying students with many of the skills. The items from these three RBAs do not cover all of the skills in enough detail, however, they will form a useful initial item bank for the development of the mechanics cognitive diagnostic. Published by the American Physical Society 2025

Automatic multisensory integration follows subjective confidence rather than objective performance.

It is well known that sensory information from one modality can automatically affect judgments from a different sensory modality. However, it remains unclear what determines the strength of the influence of an irrelevant sensory cue from one modality on a perceptual judgment for a different modality. Here we test whether the strength of multisensory impact by an irrelevant sensory cue depends on participants' objective accuracy or subjective confidence for that cue. We created visual motion stimuli with low vs. high overall motion energy, where high-energy stimuli yielded higher confidence but lower accuracy in a visual-only task. We then tested the impact of the low- and high-energy visual stimuli on auditory motion perception. We found that the high-energy visual stimuli influenced the auditory motion judgments more strongly than the low-energy visual stimuli, consistent with their higher confidence but contrary to their lower accuracy. A computational model assuming common principles underlying confidence reports and multisensory integration captured these effects. Our findings show that automatic multisensory integration follows subjective confidence rather than objective performance and suggest the existence of common computations across vastly different stages of perceptual decision making.

Structural Origin of Dynamic Heterogeneity in Supercooled Liquids.

As a liquid is supercooled toward the glass transition point, its dynamics slow significantly, provided that crystallization is avoided. With increased supercooling, the particle dynamics become more spatially heterogeneous, a phenomenon known as dynamic heterogeneity. Since its discovery, this characteristic of metastable supercooled liquids has garnered considerable attention in glass science. However, the precise physical origins of dynamic heterogeneity remain elusive and widely debated. In this perspective, we examine the relationship between dynamic heterogeneity and structural order, based on numerical simulations of fragile liquids with isotropic potentials and strong liquids with directional interactions. We demonstrate that angular ordering, arising from many-body steric interactions, plays a crucial role in the slow dynamics and dynamic cooperativity of fragile liquids. Additionally, we explore how the growth of static order correlates with slower dynamics. In fragile liquids exhibiting super-Arrhenius behavior, the spatial extent of regions with high angular order grows upon cooling, and the sequential propagation of particle rearrangements within these ordered regions increases the activation energy for particle motion. In contrast, strong liquids with spatially constrained local ordering display a distinct "two-state" dynamic characteristic, marked by a transition between two Arrhenius-type behaviors. We argue that dynamic heterogeneity, irrespective of a liquid's fragility, arises from underlying structural order, with its spatial extent determined by static ordering. This perspective aims to deepen our understanding of the interplay between structural and dynamic properties in metastable supercooled liquids.

Constrained Nuclear-Electronic Orbital Transition State Theory Using Energy Surfaces with Nuclear Quantum Effects.

Hydrogen-atom transfer is crucial in a myriad of chemical and biological processes, yet the accurate and efficient description of hydrogen-atom transfer reactions and kinetic isotope effects remains challenging due to significant quantum effects on hydrogenic motion, especially tunneling and zero-point energy. In this paper, we combine transition state theory (TST) with the recently developed constrained nuclear-electronic orbital (CNEO) theory to propose a new transition state theory denoted CNEO-TST. We use CNEO-TST with CNEO density functional theory (CNEO-DFT) to predict reaction rate constants for two prototypical gas-phase hydrogen-atom transfer reactions and their deuterated isotopologic reactions. CNEO-TST is similar to conventional TST except that it employs constrained minimized energy surfaces to include zero-point energy and shallow tunneling effects in the effective potential. We find that the new theory predicts reaction rates quite accurately at room temperature. The effective potential surface must be generated by CNEO theory rather than by ordinary electronic structure theory, but because of the favorable computational scaling of CNEO-DFT, the cost is economical even for large systems. Our results show that dynamics calculations with this approach achieve accuracy comparable to variational TST with a semiclassical multidimensional tunneling transmission coefficient at and above room temperature. Therefore, CNEO-TST can be a useful tool for rate prediction, even for reactions involving highly quantal motion, such as many chemical and biochemical reactions involving transfers of hydrogen atoms, protons, or hydride ions.

The Dynamic Universe

Abstract We are accustomed to thinking that the relativity of observations results from variations in time and distance, as taught by the theory of relativity. This theory is built on kinematics and metrics. Historically, this observer-centered approach was natural due to the lack of a deeper understanding of physics and space. The Dynamic Universe theory offers a different perspective. It incorporates our current understanding of space and the physics underlying atomic processes. In this framework, relativity can be understood as a direct consequence of the conservation of total energy and the connection between the local and the whole. DU uses time and distance as universal coordinate quantities, essential for human comprehension. DU describes space as a spherically closed entity, specifically a 3-dimensional surface of a 4-dimensional sphere (often called a “3-sphere” in mathematics). In this model, the energies of gravitation and motion are in balance, which links the speed of light and the rest energy of matter to the expansion of space. As a result, the locally available rest energy and the rate of physical processes become functions of the state of motion and gravitation. DU offers a framework that unifies relativity and quantum phenomena. It provides precise predictions for observations ranging from microsystems to cosmology, along with a comprehensible picture of the universe as a whole.

Intelligent control for accurate fast response and minimum energy of motion for industrial robotic manipulator

Intelligent control for accurate fast response and minimum energy of motion for industrial robotic manipulator

Within- and between therapist variability in movement and physiological synchrony and its effects on symptom change.

The predictive power of movement and electrodermal activity (EDA) synchrony has been demonstrated in various studies. Although most studies have examined each synchrony modality separately, a growing interest in the simultaneous investigation of multiple modalities has emerged. Previous research has demonstrated the importance of disentangling within and between-dyad effects, however within and between-therapist effects have yet to be investigated. The aim of the present study was to test whether movement and EDA synchrony (measured both within and between therapists) predict across-session symptom change in two types of interventions (emotion-focused vs. cognitive). The results are based on 990 session segments of 90 clients with test anxiety who were treated with a six-session treatment program by 22 therapists, treating 3-15 clients each. Movement synchrony (on the basis of motion energy analysis (MEA) values) and EDA synchrony were quantified using cross-correlations. Symptom severity was assessed before each session using the state test anxiety measure. Movement and EDA synchrony correlated negatively (-0.19, p < .001). Moreover, higher movement synchrony as well as an interaction between movement and EDA synchrony was significantly associated with symptom improvement within, but not between therapists. In addition, an interaction between EDA synchrony and cognitive (versus emotion-focused) interventions was significantly associated with symptom improvement. These results provide initial evidence that therapists' average levels of synchrony may matter less than how synchronous they are with a specific client.

Efficient Locomotion for Space Robots Inspired by the Flying Snake

Robots are becoming an integral part of space facilities construction and maintenance, and may need to move to and from different work locations. Robotic arms that are widely employed, which are mounted on fixed bases, have difficulty coping with increasingly complex missions. The challenge discussed in this paper is the problem of the efficient locomotion of robotic systems. Inspired by the gliding motion of a flying snake launched from a tree and combined with the weightlessness of the space environment, we design similar motions for the robot, including the following three steps. First, the robot folds its body like a snake and initiates flight by accelerating the global center of mass (CM), focusing on the movement direction and generating suitable momentum. Then, during the flight (free-floating) phase, the joint motions are planned using a nonlinear optimization technique, considering the nonholonomic constraints introduced by the momentum conservation and the system states at the initial and final states of the floating. Meanwhile, the difficulties caused by long-distance flights are addressed to reduce the motion computational cost and energy consumption by introducing the phase plane analysis method. Finally, the landing motion is designed to avoid rigid collisions and rollover on the radial plane. The numerical simulations illustrate that the three phases of maneuvers are smooth and continuous, which can help the space robots efficiently traverse the environment.

Behaviorally-relevant features of observed actions dominate cortical representational geometry in natural vision.

We effortlessly extract behaviorally relevant information from dynamic visual input in order to understand the actions of others. In the current study, we develop and test a number of models to better understand the neural representational geometries supporting action understanding. Using fMRI, we measured brain activity as participants viewed a diverse set of 90 different video clips depicting social and nonsocial actions in real-world contexts. We developed five behavioral models using arrangement tasks: two models reflecting behavioral judgments of the purpose (transitivity) and the social content (sociality) of the actions depicted in the video stimuli; and three models reflecting behavioral judgments of the visual content (people, objects, and scene) depicted in still frames of the stimuli. We evaluated how well these models predict neural representational geometry and tested them against semantic models based on verb and nonverb embeddings and visual models based on gaze and motion energy. Our results revealed that behavioral judgments of similarity better reflect neural representational geometry than semantic or visual models throughout much of cortex. The sociality and transitivity models in particular captured a large portion of unique variance throughout the action observation network, extending into regions not typically associated with action perception, like ventral temporal cortex. Overall, our findings expand the action observation network and indicate that the social content and purpose of observed actions are predominant in cortical representation.

Energy amplification in plasma crystals due to multiple torsions

Interacting torsions are examined within a two-dimensional monolayer crystal suspended in an argon complex plasma for 1–10 W discharge powers and pressures of 135–155 mTorr. Two torsions embedded in a lattice are shown to amplify the kinetic energy and range of motion of particles located between the torsions to nearly three times that observed in single torsion systems. It is also shown that multiple torsions can interact via amplified particle energy when separated by up to 14 interparticle distances (Δ). The torsion separation distance also showed a positive linear trend with power and a slightly positive correlation with the pressure. This amplification of energy is possible due to the fact that multiple torsions in a lattice increase the interparticle distance of the lattice by 16% more than single torsion systems, leading to additional freedom of motion in the lattice plane. These combined findings show that multiple torsions heat the lattice differently depending on their separation from the other torsion. The midpoint particles between torsions absorb the majority of energy from the two torsions, and energy addition at the midpoint is nonlinear. The addition of more torsions to the lattice may lead to melting of the plasma crystal.

Circular motion and particle collisions in ergoregion of rotating and twisting charged black holes

The presence of clouds of strings, quintessential fields, and NUT charges has significant consequences for spacetime geometry, and their study is much more important from an observational and theoretical perspective. Hence, in this article, we aim to explore the rotating and twisting charged black holes with the cloud of strings and quintessential field through horizons, ergoregions, photon regions, circular motion, and energy efficiency. First, we derive the equation of motion and the expressions for studying the photon region. To investigate circular motion, we derive the mathematical expressions of energy and angular momentum. The cloud of stings reduces the stability of angular momentum and energy in prograde particle motions and shifts their minima from the black hole’s center to the right. Static black holes with clouds of strings have the greatest angular momentum in prograde orbital motion, while rotating ones without clouds of strings have the least. Furthermore, we examine the efficiency of energy extraction through the Penrose process. The known energy extraction efficiency of the Penrose process for an extreme Kerr black hole is about 21%, but in the presence of clouds of strings, it exceeds 100%.

Novel vibratory compaction quality indices developed from particle migration and distribution characteristics for unbound aggregate materials

Unbound aggregate materials (UAM) with large air voids are increasingly used to construct pavement base and subbase layers as part of the initiative to create sponge cities and improve drainage performance. However, the motion of particles and the spatial distribution of kinetic energy during the particle rearrangement process induced by vibratory loading remain unclear. This study presents the results of laboratory vibratory plate compaction tests conducted on UAM specimens under various combinations of vibratory parameters and different levels of Gravel to Sand ratio (G/S). SmartRock (SR) sensors were placed within the specimens to monitor particle motion in real-time while kinematic energy and its spatial distribution were analyzed from the acceleration time-history signals collected by the SR sensors. Based on high-precision industrial X-ray computed tomography (XCT) and 3D reconstruction technology, this study analyzed the motion and migration rules of the UAM particles. A new compaction index was proposed based on particle motion and kinematic energy to evaluate the compaction quality of the specimens.The findings of this study reveal that vibratory compaction can be divided into two distinct stages. During the first stage, coarse particles primarily move vertically while energy dissipation occurs mainly through compression of air voids but does not form a dense skeleton structure. In the second stage, coarse particles translate horizontally while rotating vertically, resulting in a tendency of the particles to lie flat with their long axes oriented horizontally. During this stage, most of the energy is used to fill air voids, leading to the formation of a densely packed skeleton structure. Kinematic energy indices and particle movement in the middle of the specimen can be used to evaluate the compaction stage and quality. Additionally, the lateral particle motion in the specimen transitions from continuous ascent to gradual descent to almost no kinematic energy, indicating a relatively dense state of compaction. Reducing the void ratio and increasing the contact area between particles in these size ranges of 4.75-9.5mm and 2.36-4.75mm can significantly increase the compaction density and improve the stability and deformation resistance of the subgrade bed.The results of this study provide valuable insights into the mechanisms of vibratory compaction and can be used to optimize compaction methods and improve pavement performance.

Discovery of anti-Ebola virus multi-target inhibitors from traditional Chinese medicine database using molecular screening, biophysical investigation, and binding free energy calculations.

Ebola virus (EBOV) is a highly lethal RNA virus that causes severe hemorrhagic fever in humans and non-human primates. The lack of effective treatment or vaccine for this pathogen poses a serious threat to a global pandemic. Therefore, it is imperative to explore new drugs and therapies to combat this life-threatening infection. In this study, we employed in silico methods to assess the inhibitory activity of natural products from traditional Chinese medicine (TCM) against four EBOV proteins that are crucial for viral replication and assembly: VP40, VP35, VP30, and VP24. We performed molecular docking of TCM compounds with the EBOV proteins and screened them based on their docking scores, binding free energies, and pharmacokinetic properties. Our results pinpointed eight TCM compounds (TCM1797, TCM2872, TCM250, TCM2837, TCM2644, TCM4697, TCM2322, and TCM277) that exhibited superior efficacy in inhibiting all the EBOV proteins compared to the controls. These compounds interacted with key residues of the EBOV proteins through various types of bonds, such as hydrogen bonds, salt bridges, and π-π interactions, forming stable complexes that could disrupt the function of the EBOV proteins. These compounds were found to possess known antiviral activity, acceptable pharmacokinetic properties, and human usage history, which make them promising candidates for anti-EBOV drug development. Moreover, the molecular simulation analysis confirmed the binding stability, structural compactness, and residue flexibility properties of these compounds. Furthermore, the binding free energy results revealed that VP30-TCM2644, VP30-TCM4697, VP35-TCM2837, VP24-TCM250, and VP24-TCM277 complexes exhibit significant binding free energy values compared to the control ligands. Principal Component Analysis (PCA) and Free Energy Landscape (FEL) results revealed the trajectories' motion and conformational energy states. Our findings provide valuable insights into the molecular mechanisms driving the efficacy of TCM drugs against EBOV and suggest novel approaches for the development of anti-EBOV therapies.

Wearable Multifunctional Bilayer Nanofiber Films for Human Motion Energy Harvesting and Photothermal Therapy

AbstractIn light of the escalating requisites for portability, functionality, comfort, and health in electronic apparatus, the imperative advancement of sophisticated multifunctional textile‐based triboelectric nanogenerators (textile‐TENGs) is underscored. This research delineates the fabrication of an innovative multifunctional textile‐TENG, comprising a photosensitive stratum aimed at thermal regulation and photothermal therapy, alongside a tribo‐negative nanofiber film adorning its verso. Exhibiting superlative electrical prowess, the textile‐TENG generates remarkably elevated outputs over a wide temperature range, thereby facilitating the efficacious conversion of kinetic energy derived from human motion into electrical energy. Concurrently, the device manifests an exceptional photothermal conversion efficiency, achieving instantly modifiable saturation temperatures (41.52–60.97 °C) under diverse solar exposures, rendering it eminently suitable for a broad spectrum of applications in thermal therapy and regulation domains. Significantly, within cold environments, the textile‐TENG demonstrates a capability to augment temperature by approximately 7.4 °C, markedly surpassing conventional cotton textiles in performance. In summation, the textile‐TENG is characterized by its unparalleled electromechanical attributes and photothermal conversion efficacies, concurrently facilitating thermal regulation, therapy, and electricity generation. This investigation not only furnishes a referential methodology for the development of advanced multifunctional textile devices but also substantially expands the conceivable application ambit of textile‐based technologies.