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The self-excited oscillation system, owing to its capability of harvesting environmental energy, exhibits immense potential in diverse fields, such as micromachines, biomedicine, communications, and construction, with its adaptability, efficiency, and sustainability being highly regarded. Despite the current interest in track sliders in self-vibrating systems, LCE fiber-propelled track sliders face significant limitations in two-dime nsional movement, especially self-rotation, necessitating the development of more flexible and mobile designs. In this paper, we design a spatial slider system which ensures the self-rotation of the slider propelled by a light-fueled LCE fiber on a rigid circular track. A nonlinear dynamic model is introduced to analyze the system's dynamic behaviors. The numerical simulations reveal a smooth transition from the static to self-rotating states, supported by ambient illumination. Quantitative analysis shows that increased light intensity, the contraction coefficient, and the elastic coefficient enhance the self-rotating frequency, while more damping decreases it. The track radius exhibits a non-monotonic effect. The initial tangential velocity has no impact. The reliable self-rotating performance under steady light suggests potential applications in periodic motion-demanding fields, especially in the construction industry where energy dissipation and utilization are of utmost urgency. Furthermore, this spatial slider system possesses the ability to rotate and self-vibrate, and it is capable of being adapted to other non-circular curved tracks, thereby highlighting its flexibility and multi-use capabilities. [ABSTRACT FROM AUTHOR]

Self-oscillatory systems have great utility in energy harvesting, engines, and actuators due to their ability to convert ambient energy directly into mechanical work. This characteristic makes their design and implementation highly valuable. Due to the complexity of the motion process and the simultaneous influence of multiple parameters, computing self-oscillatory systems proves to be challenging, especially when conducting inverse parameter design. To simplify the computational process, a combined approach o0f Random Forest (RF) and Backpropagation Neural Network (BPNN) algorithms is employed. The example used is a self-rotating skipping rope made of liquid crystal elastomer (LCE) fiber and a mass block under illumination. Numerically solving the governing equations yields precise solutions for the rotation frequency of the LCE skipping rope under various system parameters. A database containing 138,240 sets of parameter conditions and their corresponding rotation frequencies is constructed to train the RF and BPNN models. The training outcomes indicate that RF and BPNN can accurately predict the self-rotating skipping rope frequency under various parameters, demonstrating high stability and computational efficiency. This approach allows us to discover the influences of distinct parameters on the rotation frequency as well. Moreover, it is capable of inverse design, meaning it can derive the corresponding desired parameter combination from a given rotation frequency. Through this study, a deeper understanding of the dynamic behavior of self-oscillatory systems is achieved, offering a new approach and theoretical foundation for their implementation and construction. [ABSTRACT FROM AUTHOR]

Self-oscillating systems can directly convert ambient energy to mechanical work, and new type self-oscillating systems are worth designing for applications in energy harvesters, engines, and actuators. Taking inspiration from the hand drill, we have developed a novel self-rotating drill system, which is consist of a turnplate and a liquid crystal elastomer (LCE) fiber under steady illumination. To investigate the self-rotating behaviors of the LCE drill, we have proposed a nonlinear theoretical model of the LCE drill under steady illumination based on the well-established dynamic LCE model. Numerical calculation reveals that the LCE drill can undergo a supercritical Hopf bifurcation between the static regime and the self-rotation regime. The self-rotation of drill originates from the contraction of winding portion of LCE fiber in illumination at winding state, and its continuous periodic motion is sustained by the interrelation between light energy and damping dissipation. The Hopf bifurcation conditions are also investigated in detail, as well as the vital system parameters affecting its frequency and amplitude. In contrast to the abundant existing self-oscillating systems, this self-rotating drill stands out due to its simple and lightweight structure, customizable dimensions, and high speed, and thus facilitates the design of compact and integrated systems, enhancing their applicability in microdevices and systems. This bears great significance in fields like micro-robotics, micro-sensors, and medical instruments, enabling the realization of smaller and higher-performance devices.

Pin coupling anti-rotation mechanism is adopted in mechanically driven automotive scroll compressor due to its simple structure and high reliability. However, the sidewall of anti-rotation hole in pin coupling anti-rotation mechanism is easy to be worn out, deteriorating the performance of scroll compressor. To figure out the cause and take measures, a dynamic model for pin coupling anti-rotation mechanism is developed in this paper. The dynamic model takes two important factors into consideration, offsetting scroll wraps and radial compliance mechanism. Using the dynamic model, the contact force between the anti-rotation pin and anti-rotation hole can be determined, thus the wear zone can be predicted during one rotation cycle. A simulation program adopting the above dynamic model is developed to predict the performance of automotive scroll compressor. The error between simulated shaft power of compressor and experimental result is no more than 4% for all test conditions. The wear zone predicted by the simulation program agrees well with the actual scroll compressor which survived a durability test. [ABSTRACT FROM AUTHOR]

Self-oscillatory systems have great utility in energy harvesting, engines, and actuators due to their ability to convert ambient energy directly into mechanical work. This characteristic makes their design and implementation highly valuable. Due to the complexity of the motion process and the simultaneous influence of multiple parameters, computing self-oscillatory systems proves to be challenging, especially when conducting inverse parameter design. To simplify the computational process, a combined approach o0f Random Forest (RF) and Backpropagation Neural Network (BPNN) algorithms is employed. The example used is a self-rotating skipping rope made of liquid crystal elastomer (LCE) fiber and a mass block under illumination. Numerically solving the governing equations yields precise solutions for the rotation frequency of the LCE skipping rope under various system parameters. A database containing 138,240 sets of parameter conditions and their corresponding rotation frequencies is constructed to train the RF and BPNN models. The training outcomes indicate that RF and BPNN can accurately predict the self-rotating skipping rope frequency under various parameters, demonstrating high stability and computational efficiency. This approach allows us to discover the influences of distinct parameters on the rotation frequency as well. Moreover, it is capable of inverse design, meaning it can derive the corresponding desired parameter combination from a given rotation frequency. Through this study, a deeper understanding of the dynamic behavior of self-oscillatory systems is achieved, offering a new approach and theoretical foundation for their implementation and construction.

• The steady self-rotation of an LCE rod under constant illumination is observed experimentally. • The self-rotation originates from a combination of gravity and photothermal-driven deformation. • The angular velocity of self-rotation can be controlled by the system parameters. • The self-rotation can be achieved under small area illumination. Self-sustaining systems can generate and maintain periodic or chaotic motion under constant external stimulation, and has potential applications in fields such as soft robotics, energy harvesting, and active machinery. However, self-sustaining systems often come with excessive oscillations and increased friction, which limit their applications. Unlike oscillatory self-sustaining systems, we have developed a novel steadily self-sustaining system, which is composed of a liquid crystal elastomer rod and a support sleeve. Experiments demonstrate that the liquid crystal elastomer rod on a support sleeve can self-rotate steadily and continuously under constant small area illumination. During the self-rotation, the shape of the liquid crystal elastomer rod remains unchanged, which avoids excessive oscillations and decreases friction. Based on a photothermal-responsive liquid crystal elastomer model, we derived the lateral curvature and the actuating rotation moment. Numerical simulations reveal that the liquid crystal elastomer system balances damping dissipation during motion by absorbing heat converted from constant illumination. The angular velocity of the self-rotation is influenced by parameters such as heat flux, heat transfer coefficient, length of the rod, and damping rotation moment. The theoretical predictions match the experimental results. The novel steadily self-rotating system not only has the advantages of maintaining shape and reducing friction, but also offers benefits such as structural simplicity, small illumination area, and higher energy efficiency compared to other steadily self-sustaining systems driven by large illumination areas or hot surfaces. This research is anticipated to offer valuable insights for applications in soft robotics, energy harvesting, and active machinery. In this study, we conducted both experimental and theoretical investigations on a novel steadily self-sustaining system using an LCE rod, which maintains its shape and self-rotates under constant small area illumination, with the angular velocity determined by system parameters. [Display omitted] [ABSTRACT FROM AUTHOR]

• Anisotropic friction surface is introduced to enable light-fueled self-rotation-eversion in a LCE torus. • A model of a light-fueled self-rotating and self-everting LCE torus is proposed. • The mechanism behind the self-rotation-eversion is elucidated. • The self-rotation and self-eversion angular velocities can be controlled by several parameter. Recent experiments have revealed a new end-to-end ribbon spiral structure capable of demonstrating two interconnected periodic zero-energy-mode self-rotation-eversion in reaction to constant temperature or constant light sources, yet its fabrication is challenging due to its intricate nature. Differently, this paper develops a light-fueled self-rotating and everting liquid crystal elastomer torus on an isotropic frictional plane, by imparting anisotropic frictional properties to the surface of the torus. Based on a mature dynamic liquid crystal elastomer model, we constructed the theoretical model of the torus system. The torus is capable of absorbing the illumination energy to counteract damping dissipation and produce zero-energy-mode self-eversion-rotation. Theoretical findings demonstrate that the angular velocity of self-eversion is influenced by light intensity, light penetration depth, gravitational acceleration and anisotropic friction surface. Moreover, there is a proportional relationship between the self-rotation and self-eversion angular velocities, which is determined by the anisotropic frictional surface. The detailed criterion for the self-rotation direction is also established. Theoretical findings exhibit several similar phenomena to experimental observations. This paper proposes a new simple strategy that utilizes anisotropic friction surface to control self-eversion-rotation, which has guiding significance for the application of soft robots, active devices, and energy harvesters. This study introduces an anisotropic friction surface to facilitate light-driven self-rotation and eversion in a LCE torus, alongside providing criteria for determining the direction of self-rotation. [Display omitted] [ABSTRACT FROM AUTHOR]

Previous studies on perceptual grouping found that people can use spatiotemporal and featural information to group spatially separated rigid objects into a unit while tracking moving objects. However, few studies have tested the role of objects' self‐motion information in perceptual grouping, although it is of great significance to the motion perception in the three‐dimensional space. In natural environments, objects always move in translation and rotation at the same time. The self‐rotation of the objects seriously destroys objects' rigidity and topology, creates conflicting movement signals and results in crowding effects. Thus, this study sought to examine the specific role played by self‐rotation information on grouping spatially separated non‐rigid objects through a modified multiple object tracking (MOT) paradigm with self‐rotating objects. Experiment 1 found that people could use self‐rotation information to group spatially separated non‐rigid objects, even though this information was deleterious for attentive tracking and irrelevant to the task requirements, and people seemed to use it strategically rather than automatically. Experiment 2 provided stronger evidence that this grouping advantage did come from the self‐rotation per se rather than surface‐level cues arising from self‐rotation (e.g. similar 2D motion signals and common shapes). Experiment 3 changed the stimuli to more natural 3D cubes to strengthen the impression of self‐rotation and again found that self‐rotation improved grouping. Finally, Experiment 4 demonstrated that grouping by self‐rotation and grouping by changing shape were statistically comparable but additive, suggesting that they were two different sources of the object information. Thus, grouping by self‐rotation mainly benefited from the perceptual differences in motion flow fields rather than in deformation. Overall, this study is the first attempt to identify self‐motion as a new feature that people can use to group objects in dynamic scenes and shed light on debates about what entities/units we group and what kinds of information about a target we process while tracking objects. [ABSTRACT FROM AUTHOR]

This study applies deep reinforcement learning (DRL) to reduce lift forces on a circular object in the wake of another. The proximal policy optimization (PPO) method is utilized to control the self-rotation of the cylinder using the feedback of sensors. The flow environment is simulated using a high-fidelity computational fluid dynamics (CFD) solver, accelerated by graphics processing unit (GPU). Remarkably, even in the most challenging tandem distance L ∗ = 5.0, the DRL agent devises an effective strategy within 800 episodes, resulting in a 98% reduction in lift fluctuation. Flow structure analysis reveals that the learned policy speeds up the shear layer development of the rear cylinder, subsequently adjusting its interaction with the front cylinder's wake. Furthermore, the policy's generalization is assessed at different distances, observing a notable reduction in the effectiveness of lift fluctuation suppression (ranging from 75% to 80%). To enhance the generalization of trained strategies, we optimize the sensors distribution based on the Proper Orthogonal Decomposition (POD) analysis. This leads to faster convergence and consistently better performance, achieving over 88% reduction in lift fluctuation across various distances. This study sheds light on a promising approach for mitigating bluff-body vibrations in complex flows. • Extend DRL control into unsteady wake flow for lift mitigation. • Achieve 98% lift fluctuation reduction even at most challenging distance. • Learned policy tunes the wake-cylinder and wake-wake interaction mode. • Policy effectiveness weakens with tandem distance in linear sensor model. • Enhance policy generalization through refining sensor arrangement by POD method. [ABSTRACT FROM AUTHOR]

Cells are complex biological units that can sense physicochemical stimuli from their surroundings and respond positively to them through characterization of the cell behavior. Thus, understanding the motions of cells is important for investigating their intrinsic properties and reflecting their various states. Computer-vision-based methods for elucidating cell behavior offer a novel approach to accurately extract cell motions. Here, we propose an algorithm based on area change to automatically extract the self-rotation of cells in an optically induced dielectrophoresis field. To obtain a clear and complete outline of the cell structure, dark corner removal and contrast stretching techniques are used in the pre-processing stage. The self-rotation speed is calculated by determining the frequency of the cell area changes in all of the captured images. The algorithm is suitable for calculating in-plane and out-of-plane rotations, while addressing the problem of identical images at different rotation angles when dealing with rotations of spherical and flat cells. In addition, the algorithm can be used to determine the motion trajectory of cells. The experimental results show that the algorithm can efficiently and accurately calculate cell rotation speeds of up to ~155 rpm. Potential applications of the proposed algorithm include cell morphology extraction, cell classification, and characterization of the cell mechanical properties. The algorithm can be very helpful for those who are interested in using computer vision and artificial-intelligence-based ideology in single-cell studies, drug treatment, and other bio-related fields. [ABSTRACT FROM AUTHOR]

Cells are complex biological units that can sense physicochemical stimuli from their surroundings and respond positively to them through characterization of the cell behavior. Thus, understanding the motions of cells is important for investigating their intrinsic properties and reflecting their various states. Computer-vision-based methods for elucidating cell behavior offer a novel approach to accurately extract cell motions. Here, we propose an algorithm based on area change to automatically extract the self-rotation of cells in an optically induced dielectrophoresis field. To obtain a clear and complete outline of the cell structure, dark corner removal and contrast stretching techniques are used in the pre-processing stage. The self-rotation speed is calculated by determining the frequency of the cell area changes in all of the captured images. The algorithm is suitable for calculating in-plane and out-of-plane rotations, while addressing the problem of identical images at different rotation angles when dealing with rotations of spherical and flat cells. In addition, the algorithm can be used to determine the motion trajectory of cells. The experimental results show that the algorithm can efficiently and accurately calculate cell rotation speeds of up to ~155 rpm. Potential applications of the proposed algorithm include cell morphology extraction, cell classification, and characterization of the cell mechanical properties. The algorithm can be very helpful for those who are interested in using computer vision and artificial-intelligence-based ideology in single-cell studies, drug treatment, and other bio-related fields.

Conical picks have a harsh working environment and 70% of their failures are caused by wear. It has been found that conical picks can rotate while interacting with the working material. This self-rotation ability is an important factor affecting pick wear, but the self-rotation mechanism remains unclear. Researching the mechanism involves the impact and friction dynamics of the interaction between a pick and its holder. Thus, a dynamic finite-element numerical model for the pick–holder interaction is established. How the handle–holder gap width, pick body and handle lengths and pick handle diameter affect the settling time and the percentage of time with no contact is studied to compare the numerical results with the equivalent effects on the rotation angle in experiments. Doing so indicates that the main factor in the self-rotation ability of a conical pick is not the magnitude of the contact load but its duration. The present research provides a new method for revealing the mechanism for the self-rotation of conical picks.

[Display omitted] • An axial-flow hydrocyclone achieve in-situ desorption of catalyst attachment. • Catalyst self-rotation and coupled centrifugal force models were analyzed. • Self-rotation and revolution speeds are affected by flow rate and insertion depth. • Increasing flow rate and insertion depth enhance the oil phase centrifugal force. • The oil phase is subjected to a periodically varying coupled centrifugal force. As a renewable and environmentally friendly resource, biomass energy has been widely used and is considered to be a promising alternative to petroleum-based liquid fuels. At present, the ebullated bed reactor is generally used to upgrade the biomass pyrolysis liquid, but the catalyst is prone to deactivation due to the polycondensation and coking of bio-oil. This paper proposes an ebullated bed with a built-in axial hydrocyclone to achieve in-situ activation of the catalyst. The influences of the vortex finder insertion depth and the inlet flow rate on the particles' revolution and self-rotation were investigated by numerical simulation, high-speed imaging technology and particle image velocimetry (PIV), and the coupling principle of revolution and self-rotation of catalysts was also analyzed. The results show that increasing flow rate and decreasing vortex finder insertion depth will increase the particles' revolution speed, which varies in the range of 18–78 rad/min. The particles' self-rotation speed varies in the range of 240–1200 rad/min. With the increase of flow rate and vortex finder insertion depth, the particles' self-rotation speed increases, the attached oil phase on particle pores and surfaces receives greater centrifugal force, the coupled centrifugal separation factor increases, and the oscillation period of the coupled centrifugal force decreases, which is beneficial to the desorption of the oil phase. The self-rotation, revolution and their coupling principle are beneficial to the removal of pore pollutants in the catalyst. [ABSTRACT FROM AUTHOR]

• A self-rotating liquid crystal elastomer-based system under steady illumination is established. • The system undergoes supercritical Hopf bifurcation between self-rotation and static regimes. • The frequency of self-rotation can be modulated by several parameters. • Asymmetrical lighting has different effects on the clockwise and counterclockwise self-rotations. Self-oscillating systems possess the capability to convert ambient energy directly into mechanical work. Consequently, the development of novel self-oscillating systems holds significant potential for applications in energy harvesting, engines, and actuators, making them highly worthwhile to be designed and implemented. Inspired by the rotation of a skipping rope, we creatively developed a self-rotating liquid crystal elastomer (LCE)-based system composed of a LCE fiber and a mass, which triggers self-rotation under steady illumination. In this work, a nonlinear dynamic model is proposed to study the dynamic behaviors of optically-responsive LCE-based systems. Numerical calculations show that the self-rotating LCE-based system can undergo a supercritical Hopf bifurcation between the static state and the self-rotation state, which is maintained by the energy input of ambient illumination to compensate the damping dissipation. In addition, the Hopf bifurcation conditions, as well as the important system parameters affecting the frequency of self-rotation, are studied in detail. Especially for the cases of unilateral asymmetrical lighting, the system parameters have different effects on the clockwise and counterclockwise rotation. Different from the existing abundant self-oscillating system, the self-rotating LCE-based system has the advantages of simple structure, customizable size and multimode rotation, and is expected to provide more diversified design ideas for soft robotics, energy harvesters, micro-machines, etc. [Display omitted] [ABSTRACT FROM AUTHOR]

Self-oscillating systems can directly convert ambient energy to mechanical work, and new type self-oscillating systems are worth designing for applications in energy harvesters, engines, and actuators. Taking inspiration from the hand drill, we have developed a novel self-rotating drill system, which is consist of a turnplate and a liquid crystal elastomer (LCE) fiber under steady illumination. To investigate the self-rotating behaviors of the LCE drill, we have proposed a nonlinear theoretical model of the LCE drill under steady illumination based on the well-established dynamic LCE model. Numerical calculation reveals that the LCE drill can undergo a supercritical Hopf bifurcation between the static regime and the self-rotation regime. The self-rotation of drill originates from the contraction of winding portion of LCE fiber in illumination at winding state, and its continuous periodic motion is sustained by the interrelation between light energy and damping dissipation. The Hopf bifurcation conditions are also investigated in detail, as well as the vital system parameters affecting its frequency and amplitude. In contrast to the abundant existing self-oscillating systems, this self-rotating drill stands out due to its simple and lightweight structure, customizable dimensions, and high speed, and thus facilitates the design of compact and integrated systems, enhancing their applicability in microdevices and systems. This bears great significance in fields like micro-robotics, micro-sensors, and medical instruments, enabling the realization of smaller and higher-performance devices., Competing Interests: The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the submitted manuscript entitled “A light-powered self-rotating liquid crystal elastomer drill”., (© 2024 The Authors.)

We report a pulsed squeezed vacuum in a warm 87 Rb vapor cell with one linearly polarized optical pulse near resonant on D1 transition. The experimental results show that the squeezing degree decreases from -3 ± 0.2 dB to 0 dB when the pulse width decreases from 400 ns to 50 ns with pulse period of 1 μ s. By theoretical analysis of the time evolution of the light-atom interaction, we determine that the effect of pulse width on the squeezing degree is mainly due to the evolution time that the population of each atomic level reaches a steady state. The pulsed quantum light is crucial for quantum information processing and precision measurements. Our results should be helpful to improve the performance of pulsed quantum light for quantum information, especially for precision measurements based on atomic systems, such as atomic magnetometers and atom interferometers. [ABSTRACT FROM AUTHOR]

The self-rotation of liquid metal droplets (LMDs) has garnered potential for numerous applications, such as chip cooling, fluid mixture, and robotics. However, the controllable self-rotation of LMDs utilizing magnetic fields is still underexplored. Here, we report a novel method to induce self-rotation of LMDs solely utilizing a rotating magnetic field. This is achieved by rotating a pair of permanent magnets around a LMD located at the magnetic field center. The LMD experiences Lorenz force generated by the relative motion between the droplet and the permanent magnets and can be rotated. Remarkably, unlike the actuation induced by electrochemistry, the rotational motion of the droplet induced by magnetic fields avoids the generation of gas bubbles and behaves smoothly and steadily. We investigate the main parameters that affect the self-rotational behaviors of LMDs and validate the theory of this approach. We further demonstrate the ability of accelerating cooling and a mixer enabled by the self-rotation of a LMD. We believe that the presented technique can be conveniently adapted by other systems after necessary modifications and enables new progress in microfluidics, microelectromechanical (MEMS) applications, and micro robotics. [ABSTRACT FROM AUTHOR]

• A light-powered liquid crystal elastomer semi-rotary motor is proposed. • Two motion modes distinguished as the static mode and the self-rotation are presented. • The influences of system parameters on the triggering conditions, frequency and amplitude of self-rotation are investigated. • Results provide a reference for the design and control of self-rotating LCE semi-rotary motor. Self-excited oscillators are characterized by active energy harvesting from the stable external environment, autonomy and portability, which allow them to act as engines to drive other working devices. Taking inspiration from the pump drill, a semi-rotary motor consisting of a motor rotor and three liquid crystal elastomer (LCE) fibers is constructed in this paper, which can realize self-rotation under stable illumination. Considering the existing twisted wire model and the dynamic LCE model, a nonlinear dynamics model for the semi-rotary motor under stable illumination is established. Numerical calculations witness the existence of two motion modes for the semi-rotary motor under stable illumination, namely the static mode and the self-rotation mode. Under stable illumination, the light-driven contraction of twisted segments in LCE fibers for the winding state can trigger the self-rotation and maintain the continuous periodic motion through the interrelationship between optical energy and damping dissipation. The critical conditions required to trigger the self-rotation are also investigated in detail, as well as the crucial system parameters affecting the self-rotation frequency and amplitude. The proposed self-rotating semi-rotary motor has a simple structure, customizable dimensions and high speed, prompting its potential use in soft robots, energy harvesters, and micro-machines. [ABSTRACT FROM AUTHOR]

The self-rotation of liquid metal droplets (LMDs) has garnered potential for numerous applications, such as chip cooling, fluid mixture, and robotics. However, the controllable self-rotation of LMDs utilizing magnetic fields is still underexplored. Here, we report a novel method to induce self-rotation of LMDs solely utilizing a rotating magnetic field. This is achieved by rotating a pair of permanent magnets around a LMD located at the magnetic field center. The LMD experiences Lorenz force generated by the relative motion between the droplet and the permanent magnets and can be rotated. Remarkably, unlike the actuation induced by electrochemistry, the rotational motion of the droplet induced by magnetic fields avoids the generation of gas bubbles and behaves smoothly and steadily. We investigate the main parameters that affect the self-rotational behaviors of LMDs and validate the theory of this approach. We further demonstrate the ability of accelerating cooling and a mixer enabled by the self-rotation of a LMD. We believe that the presented technique can be conveniently adapted by other systems after necessary modifications and enables new progress in microfluidics, microelectromechanical (MEMS) applications, and micro robotics.

We present an image-matching-based automated algorithm capable of accurately determining the self-rotational speed of cancer cells in an optically-induced electrokinetics-based microfluidic chip. To automatically track a specific cell in a video featuring more than one cell, a background subtraction technique was used. To determine the rotational speeds of cells, a reference frame was automatically selected and curve fitting was performed to improve the stability and accuracy. Results show that the algorithm was able to accurately calculate the self-rotational speeds of cells up to ~150 rpm. In addition, the algorithm could be used to determine the motion trajectories of the cells. Potential applications for the developed algorithm include the differentiation of cell morphology and characterization of cell electrical properties. [ABSTRACT FROM AUTHOR]

Nowadays, the disposal of spent catalysts caused growing concerns on the environmental status, human health and industrial safety. The non-regenerable catalysts were either sent to metal reclaimers or disposed of in commercial landfills. The de-oiling and the following mechanical (hydraulic) separation are essential operations, which will minimize the amount of the spent catalysts as well as control the toxic substances deposited on the used catalysts. In the present study, a hydrothermal–hydrocyclone process was proposed to enhance the management of the waste catalyst for residue oil hydro-treating. Under the optimal conditions, the removal efficiencies of the contaminated hydrocarbons for the artificial and real system were 93.5% and 70.3%, respectively. The enhancement of de-oil was originated from the self-rotation behavior of the catalyst particles. The rotation speed was estimated to be ∼6870 rad/min by using the high-speed digital imaging and the numeric calculation. The application of hydrocyclone and the design process can also be used for the treatment of other solid wastes including contaminated soil, oily sludge and so forth. Moreover, it indicated that on the basis of the throughout understanding on the flow characteristics, the traditional operational equipment could be well manipulated in the treatment of environmental pollution. [ABSTRACT FROM AUTHOR]

• For the first time, constant light illumination is explored to control the large amplitude self-oscillation and self-rotation of liquid crystal elastomer (LCE) pendulum. • The critical conditions for the three typical motion regimes of the LCE pendulum under constant illumination is found. • It is easily accessible to manipulate the self-oscillation and self-rotation by tuning the illumination angle, light intensity, damping coefficient, and gravitational acceleration. Liquid crystal elastomers (LCEs) have been widely used in active machinery, optical machinery, robotics, biological materials, medical and other fields, with advantage of good optical sensing performance. In this work, dynamics of a LCE-based optically-responsive pendulum system is theoretically investigated by proposing a nonlinear dynamic model. The self-oscillation and self-rotation can be triggered by steady illumination, in which the damping dissipation is compensated by the energy input from environment illumination to maintain the periodic motion. With theoretical modeling and numerical calculation, three typical motion regimes of the LCE pendulum are found, namely, static regime, self-oscillation regime and self-rotation regime. For different physical parameters, the critical conditions to excite the three motion regimes are given quantitatively. Results demonstrate that the motion regime, amplitude, and period of the LCE pendulum can be controlled by adjusting the illumination region, light intensity, damping coefficient, and gravitational acceleration. The proposed optically-responsive LCE pendulum can provide potential applications in research on sensing environment, energy harvesting and motion actuation of active machines, etc. Graphical Abstract [Display omitted]. [ABSTRACT FROM AUTHOR]

It is known that non-clinical subjects with high levels of schizotypal personality traits (High-S), as well as schizophrenic patients, have difficulties to judge how a scene would appear (so-called Appearance questions) from a point of view other than their own after having performed a disembodied perspective taking (D-PT, a mental self-rotation cued by an object like a chair). This inability has been defined allocentric simulation deficit. However, it is still unclear whether this inability might also regard an embodied transformation (E-PT), which is a self-rotation cued by another individual in the scene, and whether the observed deficit regards the pure mental transformation phase. In the present study, we took advantage of a virtual reality environment to explore both embodied and disembodied allocentric simulation in healthy volunteers with low and high levels of schizotypal personality traits, as assessed by the Schizotypal Personality Questionnaire. All subjects performed a pure self-rotation cued by a chair (D-PT) or by an avatar (E-PT), or a control array rotation. Each rotation was followed by classical Appearance and Item questions. Results revealed no between-groups differences in the mental transformation phase, while High-S subjects were significantly slower than Low-S subjects in the Appearance task after D-PT, but not after E-PT. Accordingly, higher schizotypy levels (cognitive-perceptual subscale) were positively correlated with slower reaction times in the Appearance task after D-PT. These data suggest the existence of a disembodied allocentric simulation deficit in non-clinical High-S, paving the way to future studies on clinical populations. [ABSTRACT FROM AUTHOR]

Using atomic motion to coherently spread light information stored in atoms provides a means to manipulate atom-light interactions. We demonstrate light splitting with moving atoms in a paraffin-coated vapor cell by using phase-sensitive degenerate four-wave mixing, or self-rotation. This scheme amplifies the slow light beam splitter signal, and, in the meantime, maintains the phase coherence between the beam-splitter channels. Light storage efficiency in the beam-splitting channel can also be enhanced. Furthermore, we demonstrate an optical memory exceeding 1 s, taking advantage of the gain from self-rotation and an atomic coherence composed of a fast-decaying part and a slow-decaying part. These results should find applications in optical memory, optical routers, and atomic coherence control. [ABSTRACT FROM AUTHOR]

Abstract: The DC corona discharge in air and the induced ionic wind were investigated in the needle-to-water system at atmospheric pressure. The water deformation was measured under various conditions, and wind pressure and active areas were estimated accordingly. The effects of applied voltage, gap spacing and tip radius on the corona ionic wind were studied and the qualitative analysis was provided. Self-rotation of corona discharge was observed in experiments. The results show that higher voltage or electric field strength results in a stronger ionic wind. The active area increases with applied voltage below a voltage threshold. There is an optimal gap distance for a wider as well as stronger ionic wind and blunter needle we used leads to an enhancement on both the active area and the wind strength. The wind velocity reaches 7 m/s at optimized condition in the present system. The rotation of corona discharge helps to improve the active area and uniformity of the treating area which may be associated with the chemical reaction of the water surface. [Copyright &y& Elsevier]

In many situations people need to mentally adopt the (spatial) perspective of other persons, an ability that is referred to as "Level 2 perspective taking." Its underlying processes have been ascribed to mental self-rotation that can be dissociated from mental object-rotation. Recent findings suggest that perspective taking/self-rotation may not require central capacity. By using the psychological refractory period (PRP) paradigm and the locus-of-slack logic, the present study scrutinized these results, ruled out alternative explanations, and extended the conclusions. In sum, the findings converge on the notion that Level 2 perspective taking entails 2 processes: a first effortless process that handles rotations of 60° or less, and a second capacity-limited process of mental self-rotation proper that is only invoked at higher degrees of required perspective taking. [ABSTRACT FROM AUTHOR]

This paper aims to study the possibility of swirl generation in the sink flow in the absence of external factors, i.e., self-rotation. It is motivated by the fact that there is no consensus among the researchers about either the possibility or impossibility of this phenomenon. The axisymmetric model of the problem is simulated using a stream function-vorticity-circulation formulation. The results showed that there is not sudden change in the value of azimuthal velocity and circulation. Therefore the flow is stable for all the Re numbers tested (i.e., 0.265 < Re < 5.3). In addition, it is concluded that, in general, the self-rotation phenomenon would not occur for two reasons: first, the net value of circulation in the flow domain would not increase relative to its inlet value; second, the current numerical simulations, which also agree with the previous experimental results, show that appearance and non-appearance of swirl is related to viscous force. [ABSTRACT FROM AUTHOR]

Registration of ego-motion is important to accurately navigate through space. Movements of the head and eye relative to space are registered through the vestibular system and optical flow, respectively. Here, we address three questions concerning the visual registration of self-rotation. (1) Eye-in-head movements provide a link between the motion signals received by sensors in the moving eye and sensors in the moving head. How are these signals combined into an ego-rotation percept? We combined optic flow of simulated forward and rotational motion of the eye with different levels of eye-in-head rotation for a stationary head. We dissociated simulated gaze rotation and head rotation by different levels of eye-in-head pursuit. We found that perceived rotation matches simulated head- not gaze-rotation. This rejects a model for perceived self-rotation that relies on the rotation of the gaze line. Rather, eye-in-head signals serve to transform the optic flow's rotation information, that specifies rotation of the scene relative to the eye, into a rotation relative to the head. This suggests that transformed visual self-rotation signals may combine with vestibular signals. (2) Do transformed visual self-rotation signals reflect the arrangement of the semi-circular canals (SCC)? Previously, we found sub-regions within MST and V6+ that respond to the speed of the simulated head rotation. Here, we re-analyzed those Blood oxygenated level-dependent (BOLD) signals for the presence of a spatial dissociation related to the axes of visually simulated head rotation, such as have been found in sub-cortical regions of various animals. Contrary, we found a rather uniform BOLD response to simulated rotation along the three SCC axes. (3) We investigated if subject's sensitivity to the direction of the head rotation axis shows SCC axes specifcity. We found that sensitivity to head rotation is rather uniformly distributed, suggesting that in human cortex, visuo-vestibular integration is not arranged into the SCC frame. [ABSTRACT FROM AUTHOR]

Abstract: We present a theoretical and experimental study of self-rotation of incident elliptically polarized light on a rubidium atomic vapor. We construct density matrix equations, which are then solved numerically, and further averaged over atomic transit times and a Maxwell–Boltzmann velocity distribution. We calculate the rotation angle as a function of detuning for various laser intensities and polarizations. We compare the calculated results with experimental results and find good agreement between them. [Copyright &y& Elsevier]

Abstract: This study compares mental rotation with three stimuli: letters, body parts and complex scenes. Twenty-four subjects saw letters and judged whether they were mirror-reversed or not (task LETTER), saw pictures of a hand and indicated whether it was a right or a left one (task HAND), and saw drawings of a person at a table on which a weapon and a rose laid and decided whether the weapon was to the person’s right or left (task SCENE). Stimuli were presented in canonical orientation or rotated by up to 180°. Our analyses focused on intra-subject correlations between reaction times of the different tasks. We found that reaction times for stimuli in canonical orientation co-varied in HAND and LETTER, the increase of reaction times with increasing object rotation co-varied in HAND and SCENE, and reaction times for 180° rotations co-varied between all tasks. We suggest that basic processes like visual perception and decision-making are distinct for scenes versus letters and body parts, that the mechanism for mental rotation of letters is distinct from that for mental self- and body part rotation, and suggest an extra mechanism for 180° rotations that shared among all tasks. These findings confirm and expand hypotheses about mental rotation that were based on comparisons of between-subject means. [Copyright &y& Elsevier]

Abstract: The ability to model astronaut reorientations computationally provides a simple way to develop and study human motion control strategies. Since the cost of experimenting in microgravity is high, and underwater training can lead to motions inappropriate for microgravity, these techniques allow for motions to be developed and well-understood prior to any microgravity exposure. By including a model of the current space suit, we have the ability to study both intravehicular and extravehicular activities. We present several techniques for rotating about the axes of the body and show that motions performed by the legs create a greater net rotation than those performed by the arms. Adding a space suit to the motions was seen to increase the resistance torque and limit the available range of motion. While rotations about the body axes can be performed in the current space suit, the resulting motions generated a reduced rotation when compared to the unsuited configuration. [ABSTRACT FROM AUTHOR]

Optokinetic responses in several species are compared, describing differences in afoveate and foveate animals, and the effects of visual testing conditions, including directions of stimulus motion. Smooth pursuit contributes to responses to full-field visual motion in foveate species; in the latter, measurement of optokinetic after-nystagmus in darkness allows investigation of the optokinetic system. The concept of optokinetic-vestibular symbiosis and velocity storage are discussed, pertinent electrophysiological studies (such as vestibular nucleus neurons that respond to both optokinetic and vestibular stimuli) are reviewed and a model is developed. The different purposes and properties of optokinetic responses (to maintain clear vision during self-rotation) and smooth pursuit (to visually track a moving target) are clarified., (Copyright © 2022 Elsevier B.V. All rights reserved.)

• A self-rotation of catalyst particles in axial-flow hydrocyclone is found and explored. • The self-rotation speed can be mainly controlled by the inlet flowrate and vortex finder. • The further activation of catalyst particles is realized by swirling self-rotation. In the process of biomass pyrolysis oils hydrogenation in the ebullated bed, the catalyst faces several serious issues (e.g., short operation time, frequent addition, massive waste) due to coking and channel blocking. Based on the phenomenon of the self-rotation of particles in the rotation shear flow, an axial-flow hydrocyclone is developed to activate the catalyst. In this study, the self-rotation of particles was presented with the help of microfluidic technology and high-speed photogrammetry, and the effect of self-rotation on the deoiling efficiency of the catalysts was investigated using a catalyst activation cold model experiment. The results show that when the inlet flow rate Q and the vortex finder length h c increase, the self-rotation speed of the particles also increases. When the particles rotate, the periodic coupling centrifugal force causes interfacial turbulence between the oil attachments and the fluid, which promotes the mass transfer. When Q and h c were 0.22 m3/h and 335 mm, the self-rotation speed reaches the maximum, which is 887.4 rad/min, the content of guaiacol (coking precursor) decreases from 55.0% to 11.4%, and the content of n-Hexadecane decreases from 38.8% to 16.1%. This innovative technic will prolong the lifetime of catalysts used in the ebullated bed reactor and make biomass pyrolysis oils hydrogenation more competitive. [ABSTRACT FROM AUTHOR]

Conical picks have a harsh working environment and 70% of their failures are caused by wear. It has been found that conical picks can rotate while interacting with the working material. This self-rotation ability is an important factor affecting pick wear, but the self-rotation mechanism remains unclear. Researching the mechanism involves the impact and friction dynamics of the interaction between a pick and its holder. Thus, a dynamic finite-element numerical model for the pick-holder interaction is established. How the handle-holder gap width, pick body and handle lengths and pick handle diameter affect the settling time and the percentage of time with no contact is studied to compare the numerical results with the equivalent effects on the rotation angle in experiments. Doing so indicates that the main factor in the self-rotation ability of a conical pick is not the magnitude of the contact load but its duration. The present research provides a new method for revealing the mechanism for the self-rotation of conical picks., Competing Interests: We have no competing interests., (© 2020 The Authors.)

We present an image-matching-based automated algorithm capable of accurately determining the self-rotational speed of cancer cells in an optically-induced electrokinetics-based microfluidic chip. To automatically track a specific cell in a video featuring more than one cell, a background subtraction technique was used. To determine the rotational speeds of cells, a reference frame was automatically selected and curve fitting was performed to improve the stability and accuracy. Results show that the algorithm was able to accurately calculate the self-rotational speeds of cells up to ~150 rpm. In addition, the algorithm could be used to determine the motion trajectories of the cells. Potential applications for the developed algorithm include the differentiation of cell morphology and characterization of cell electrical properties., Competing Interests: The authors declare no conflict of interest.

Transformation from a film into a sphere, rapid merging of separate objects, controlled self-rotation, and planar locomotion are the very unusual phenomena observed in liquid metals under application of an electric field to a liquid metal immersed in or sprayed with water. A mechanism for these effects is suggested and potential applications - for example the recovery of liquid metal previously injected into the body for therapeutic purposes - are outlined., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Registration of ego-motion is important to accurately navigate through space. Movements of the head and eye relative to space are registered through the vestibular system and optical flow, respectively. Here, we address three questions concerning the visual registration of self-rotation. (1) Eye-in-head movements provide a link between the motion signals received by sensors in the moving eye and sensors in the moving head. How are these signals combined into an ego-rotation percept? We combined optic flow of simulated forward and rotational motion of the eye with different levels of eye-in-head rotation for a stationary head. We dissociated simulated gaze rotation and head rotation by different levels of eye-in-head pursuit. We found that perceived rotation matches simulated head- not gaze-rotation. This rejects a model for perceived self-rotation that relies on the rotation of the gaze line. Rather, eye-in-head signals serve to transform the optic flow's rotation information, that specifies rotation of the scene relative to the eye, into a rotation relative to the head. This suggests that transformed visual self-rotation signals may combine with vestibular signals. (2) Do transformed visual self-rotation signals reflect the arrangement of the semi-circular canals (SCC)? Previously, we found sub-regions within MST and V6(+) that respond to the speed of the simulated head rotation. Here, we re-analyzed those Blood oxygenated level-dependent (BOLD) signals for the presence of a spatial dissociation related to the axes of visually simulated head rotation, such as have been found in sub-cortical regions of various animals. Contrary, we found a rather uniform BOLD response to simulated rotation along the three SCC axes. (3) We investigated if subject's sensitivity to the direction of the head rotation axis shows SCC axes specifcity. We found that sensitivity to head rotation is rather uniformly distributed, suggesting that in human cortex, visuo-vestibular integration is not arranged into the SCC frame.