Virtual Surface Research Articles

Image formation through aspheric concave Fresnel-type mirrors

We study the formation of caustic surfaces produced by concave Fresnel-type mirrors, whose parent curve is defined by an aspherical curve rotationally symmetric about the optical axis. We assume that a point light source is placed at arbitrary distances along the optical axis considering three different cases, providing either real or virtual caustic surfaces. Alternatively, varying the parameters of design, it is possible to reduce the size and modify the shape of the caustic surfaces, which have wide potential applications in both fields of imaging and non-imaging optical systems based on Fresnel-type mirrors. Finally, the cuspid of the caustics formed around the central groove near the optical axis coincides with the position of paraxial images in such a way that we provide the mirror-image equation for Fresnel-type mirrors.

Seeing the piles of the velvet bending under our finger sliding over a tactile stimulator improves the feeling of the fabric.

Using friction modulation to simulate fabrics with a tactile stimulator (i.e. virtual surface) is not sufficient to render fabric touch and even more so for hairy fabrics. We hypothesized that seeing the pile of the velvet darken or lighten depending on changes in the finger movement direction on the virtual surface should improve the velvet fabric rendering. Participants actively rubbed a tactile device or a velvet fabric looking at a screen that showed a synthesized image of a velvet that either remained static (V-static) or darkening/lightening with the direction of touch (V-moving). We showed that in V-moving condition, the touched surface was always perceived rougher, which is a descriptor of a real velvet (Experiment 1). Using electroencephalography and sources localization analyses, we found increased activity in the occipital and inferior parietal lobes (Experiment 2) when seeing dark and shining traces during back-and-forth finger movements over the virtual surface. This suggests that these two posterior cortical regions work together to evaluate visuo-tactile congruence between the seen and the felt (tactile). The visuo-tactile binding, evidenced by neural synchronization (specifically, theta band (5-7 Hz) oscillation) in the left inferior posterior parietal lobule, is consistent with enhanced integration of information and probably contributed to the emergence of a more realistic velvet representation.

Joint Effects of Virtual Surfaces on Anti-Icing and Drag Reduction

The operation of the anti-icing system of an airplane can modulate its aerodynamics, whilst an aerodynamic control can alter the icing condition. Therefore, one well-designed control strategy can be expected to yield two benefits, which, however, has not been actively investigated. In this work, the constant leading-edge blowing technique is deployed to achieve joint effects on anti-icing and drag reduction, first on an airfoil and then on a half-airplane model. The results indicate that dual virtual surfaces (an inner one and an outer one) wrapping the leading edge are generated by the blowing control. The inner one prevents water droplets from impacting and accumulating on the airfoil by changing their trajectories. The outer one redirects the shear generated by the blowing and promotes its rolling up and vortex shedding, generating low-pressure zones around the upper leading edge and subsequently reducing drag significantly.

Research on circulation control mechanisms based on Lagrangian dynamics

Circulation control technology greatly improves an aircraft's aerodynamic efficiency by employing high-speed jets at the wing's trailing edge, which generates the Coanda effect. This paper analyzes and reveals the mechanism of circulation control from the perspective of Lagrangian dynamics. First, simulate the circulation control airfoil using the shear stress transport turbulence model to obtain instantaneous flow field data under various jet momentum coefficients (Cμ) and angles of attack. Subsequently, from the perspective of Lagrangian dynamics, the mixing, material transport, and momentum transfer processes between the jet and the trailing-edge separation zone are analyzed using attracting Lagrangian Coherent Structures (aLCSs) under different jet momentum coefficients. Next, through the perspective of particle motion in the Lagrangian framework, the study reveals the accelerating effect of the Coanda jet on the low-speed fluid over the upper wing surface. Additionally, repelling Lagrangian Coherent Structures are used to characterize the downward movement of the leading-edge stagnation point after applying circulation control, and the impact of this movement on the flow state is analyzed. Finally, the analysis using aLCSs assesses the flow control effectiveness of Coanda jets as “virtual aerodynamic flaps.” This analysis helps to further understand the advantages of the “virtual rudder surface” formed by Coanda jet.

Radon-domain acoustic and elastodynamic interferometric redatuming of VSP data

Summary The virtual source method (VSM) is a useful tool for imaging and monitoring below complex and time-varying overburden. When it is applied to VSP geometries, the redatumed virtual source data often suffer from artifacts and aliasing due to the violation of theoretical acquisition conditions and partial focusing of virtual multiples, which further degrade seismic imaging quality. While the conventional Radon-domain VSM (R-VSM) mitigates these issues to some extent, it is still possible to improve upon the imaging. This study develops a simple and effective high-resolution Radon-domain VSM (HR-VSM) to effectively address these issues, offering superior noise and artifact suppression compared to traditional VSM and R-VSM. HR-VSM shows a strong performance across a wide range of VSP configurations and data types, especially in applications to multi-component and passive seismic data, demonstrating its versatility and effectiveness in seismic exploration and showing potential for use in earthquake seismology. To extend subsurface illumination, we combined correlation-type and convolution-type HR-VSM for automatically redatuming virtual surface seismic profile (SSP) shot gathers with a complete receiver array covering all surface source locations, without the additional pre-processing steps typically required by VSM. It was also tested on reverse VSP (RVSP) synthetic active data and passive seismic data, proving effective in constructing virtual shot gathers and showing potential for extending its use to earthquake data and ambient-noise seismology. Moreover, HR-VSM can perform elastodynamic interferometric redatuming, enabling the redatuming of pure P-P and pure P-SV waves from multi-component VSP data. We applied HR-VSM to redatum virtual single well profile (SWP) data containing fault-related P-P and P-SV reflections from VSP data, which were further used for fault imaging. Finally, HR-VSM was used to generate virtual crosswell data with receivers in both boreholes, eliminating the need for downhole sources. The obtained virtual crosswell containing direct waves, as well as P-P and P-SV reflections, enable constructing a velocity model and imaging the structure between wells.

Rapid detection of depression by volatile organic compounds from exhalation

Depression is a pervasive and often undetected mental health condition, which poses significant challenges for early diagnosis due to its silent and subtle nature. To evaluate exhaled volatile organic compounds (VOCs) as non-invasive biomarkers for the detection of depression using a virtual surface acoustic wave sensors array (VSAW-SA). A total of 245 participants were recruited from the Hangzhou Community Health Service Center, including 38 individuals diagnosed with depression and 207 control subjects. Breath samples were collected from all participants and subjected to analysis using VSAW-SA. Univariate and multivariate analyses were employed to assess the relationship between VOCs and depression. The findings revealed that the responses of virtual sensor ID 14, 44, 59, and 176, which corresponded respectively to ethanol, trichloroethylene or isoleucine, octanoic acid or lysine, and an unidentified compound, were sensitive to depression. Taking into account potential confounders, these sensor responses were utilized to calculate a depression detection indicator. It has a sensitivity of 81.6% and a specificity of 81.6%, with an area under the curve of 0.870 (95% CI = 0.816-0.923). Conclusions: exhaled VOCs as non-invasive biomarkers of depression could be detected by a VSAW-SA. Large-scale cohort studies should be conducted to confirm the potential ability of the VSAW-SA to diagnose depression.

Enhancing Robot End‐Effector Trajectory Tracking Using Virtual Force‐Tracking Impedance Control

This article presents an extended Cartesian space robot control framework that features a virtual force tracking impedance control to enhance the end‐effector trajectory tracking performance. Initially, the concept of a virtual surface is introduced, which is assumed to be at some constant distance from the desired end‐effector trajectory. This virtual surface generates a virtual contact force when interacting with the torque‐controlled robot end‐effector. The interaction is then manipulated using an impedance control model to track a constant desired force. If the robot end‐effector deviates from the desired trajectory, the constant force‐tracking impedance control generates a compliance trajectory that regulates the end‐effector movements, constraining it to the desired trajectory. For robust force tracking, impedance parameters are optimally tuned using a closed‐loop dynamic model incorporating both robot and impedance dynamics. Additionally, super twisting sliding mode control (STSMC) is integrated to overcome uncertainties and the impact of robot dynamics on force‐tracking performance. Experimental validation confirms the theoretical claims of the proposed approach. It demonstrates that force‐tracking impedance control improves the end‐effector trajectory tracking by quickly reacting to the dynamic trajectories compared to position control only and effectively maintains it on the desired trajectories.

Optimized Dropping and Rolling and Virtual Surface Method for High Packing Fraction of Dispersed Fuel Particles in Annular Container

Because of their favorable thermal conductivity and commendable fuel performance, dispersed fuel elements have been widely adopted in research reactors. However, the geometric complexity resulting from the high packing density of dispersed fuel poses challenges to current geometric modeling methods. Various implicit and explicit modeling techniques have been implemented in Monte Carlo codes. Implicit methods struggle to achieve the correct packing fraction and, therefore, lack accuracy. In this paper, we introduce the Optimized Dropping and Rolling and Virtual Surface method for precise and efficient geometric modeling of such structures. Simultaneously, we apply this novel method to the packing process of an annular container. Test results across various packing fraction cases demonstrate that our modified Optimized Dropping and Rolling method significantly enhances packing efficiency, surpassing the Distinct Element Method hundreds of times.

Placing the tibial component of an ankle prosthesis: results of a CT-based simulation in healthy adults.

To characterize the 3D geometry of the distal tibia resection area from healthy individuals using CT-based digital implantation for proper preoperative sizing of TAA tibia component placement. Standardized CT images of healthy ankle joints serving as intra-individual references for treatment of contralateral injuries were identified. The tibial cross section dedicated to virtually host the tibial component was digitally prepared, and the size of the virtual contact surface was calculated. Finally, out of five prototypes the one fitting best in terms of size and alignment was identified. CT scans taken from 319 subjects were used for the virtual implantation procedure. Body height and size of the distal tibia contact area correlated (r = 0.49 and 0.42 in females and males, each p < 0.001). Prosthesis sizes 2 and 3 fit well for the vast majority of patients, while the smallest and largest sizes are rarely required. Digital implantation of the tibial component should be considered a valuable tool for preoperative planning as well as for the development of new implant types.

Design of a Feed Array Antenna to Obtain a Uniform Near-Field Distribution on a Virtual Surface Placed within a Specified Wavelength

Design of a Feed Array Antenna to Obtain a Uniform Near-Field Distribution on a Virtual Surface Placed within a Specified Wavelength

A bioinspired tactile scanner for computer haptics

Computer haptics (CH) is about integration of tactile sensation and rendering in Metaverse. However, unlike computer vision (CV) where both hardware infrastructure and software programs are well developed, a generic tactile data capturing device that serves the same role as what a camera does for CV, is missing. Bioinspired by electrophysiological processes in human tactile somatosensory nervous system, here we propose a tactile scanner along with a neuromorphically-engineered system, in which a closed-loop tactile acquisition and rendering (re-creation) are preliminarily achieved. Based on the architecture of afferent nerves and intelligent functions of mechano-gating and leaky integrate-and-fire models, such a tactile scanner is designed and developed by using piezoelectric transducers as axon neurons and thin film transistor (TFT)-based neuromorphic circuits to mimic synaptic behaviours and neural functions. As an example, the neuron-like tactile information of surface textures is captured and further used to render the texture friction of a virtual surface for “recreating” a “true” feeling of touch.

Walking on Virtual Surface Patterns Leads to Changed Control Strategies.

Inclusive design does not stop at removing physical obstacles such as staircases. It also involves identifying architectural features that impose sensory burdens, such as repetitive visual patterns that are known to potentially cause dizziness or visual discomfort. In order to assess their influence on human gait and its stability, three repetitive patterns-random dots, repetitive stripes, and repetitive waves (Lisbon pattern)-were displayed in a coloured and greyscale variant in a virtual reality (VR) environment. The movements of eight participants were recorded using a motion capture system and electromyography (EMG). During all test conditions, a significant increase in the muscular activity of leg flexor muscles was identified just before touchdown. Further, an increase in the activity of laterally stabilising muscles during the swing phase was observed for all of the test conditions. The lateral and vertical centre of mass (CoM) deviation was statistically evaluated using a linear mixed model (LMM). The patterns did cause a significant increase in the CoM excursion in the vertical direction but not in the lateral direction. These findings are indicative of an inhibited and more cautious gait style and a change in control strategy. Furthermore, we quantified the induced discomfort by using both algorithmic estimates and self-reports. The Fourier-based methods favoured the greyscaled random dots over repetitive stripes. The colour metric favoured the striped pattern over the random dots. The participants reported that the wavey Lisbon pattern was the most disruptive. For architectural and structural design, this study indicates (1) that highly repetitive patterns should be used with care in consideration of their impact on the human visuomotor system and its behavioural effects and (2) that coloured patterns should be used with greater caution than greyscale patterns.

Effect of airway wall motion on particle deposition and delivery in the neonatal trachea

Modeling pulmonary drug delivery in the airway using computational fluid dynamics (CFD) simulations tracks drug particles throughout the airway, providing valuable information on the deposition location of inhaled drugs. However, most studies simulate particle transport within static airway models that do not incorporate physiological airway motion; this choice limits accuracy since airway motion directly affects particle transport and deposition, notably in newborns with airway abnormalities such as tracheomalacia. The objective of this study is to determine the effect of airway motion on drug delivery in neonates with and without airway disease. For this study, two control subjects without any airway disease and three subjects with tracheomalacia (dynamic tracheal narrowing) were enrolled. Each subject was imaged at approximately 40-weeks post-menstrual age using magnetic resonance imaging (MRI). MRI data were retrospectively reconstructed to obtain static airway images gated to different time points of the breath (i.e., end expiration and end inspiration) and an image representing combined data from all timepoints (ungated). Virtual airway surfaces (pharynx to main bronchi) were made from each MR image. A moving airway surface was created from surface registration of these surfaces and used as the boundary for a CFD simulation of one inhalation, along with subject-specific inspiratory flow waveforms. To assess the effect of airway wall motion on particle deposition, static-walled simulations, based on the airway surfaces at end inspiration, end expiration, and the ungated airway surface, were also performed using the same flow boundary conditions. Particle transport (particles diameter range 0.5–15 μm) was compared between the simulations during the inhalation. Airway surface motion affected particle transport into the small airways by 65% on average (0.5–5 μm– 22%, 5-15 μm– 86%) compared to static-walled simulations, while comparison between static end expiration and other static-walled simulations using geometries acquired during different phases of breathing differed by more than 500% on average (0.5–5 μm– 45%, 5-15 μm– 741%). For particle deposition, airway surface motion affected by 43% on average (0.5–5 μm– 86%, 5-15 μm– 21%) compared to static-walled simulations and comparison between static end expiration and other static-walled simulations differed by 47% on average (0.5–5 μm– 58%, 5-15 μm– 41%). Differences between dynamic and static deposition results and between static simulations from different timepoints occurred in patients with and without airway disease. This study suggests the importance of using airway wall motion in CFD simulations to model aerosolized drug delivery in the airway. If a CFD simulation is limited to only a static airway image without physiological motion, particle deposition mapping may yield markedly inaccurate results, potentially resulting in higher or lower drug dosing than intended.

Fatigue life prediction of rubber suspension bushings based on virtual road load spectrum pulses

Rubber suspension bushings have mainly been studied under single- or multi-axis load cycling, while research on rubber suspension bushings under random load cycling is not deep enough. This study conducted uniaxial tensile and fatigue tests on N60 rubber dumbbell-shaped plate samples to obtain stress–strain curves and S–N curves. Using the uniaxial tensile test data, a Mooney–Rivlin hyperelastic constitutive model was fitted using Abaqus software, and a finite element model of the rubber suspension bushing was established. A 3D virtual road surface was constructed using Adams software, and characteristic features of typical road surfaces were extracted for statistical analysis, resulting in the generation of a load spectrum showing variations in force over time. Based on the Miner linear damage accumulation theory, finite element fatigue life prediction of the rubber suspension bushing was conducted using pulses from the 232 s region of the load spectrum. The predicted fatigue life was compared to the results from benchtop fatigue testing, resulting in a relative error of less than 6.443 %. The findings suggest that the method is effective in predicting the fatigue life of rubber suspension bushings under random loads.

Discovery of a novel Xanthone derivative P24 for anti-AD via targeting sTGFBR3

Soluble transforming growth factor beta receptor 3 (sTGFBR3) antagonist is a new focus in the research and development of Alzheimer's disease (AD) drugs. Our previous studies have identified sTGFBR3 as a promising new target for AD, with few targeted antagonists identified. In this study, we performed structural modeling of sTGFBR3 using AlphaFold2, followed by high-throughput virtual screening and surface plasmon resonance assays. which collectively identified Xanthone as potential compounds for targeting sTGFBR3. After optimizing the sTGFBR3-Xanthone complex using molecular dynamics (MD) simulations, we prepared a series of novel Xanthone derivatives and evaluated their anti-inflammatory activity, toxicity, and structure-activity relationship in BV2 cell model induced by lipopolysaccharides (LPS) or APP/PS1/tau mouse brain extract (BE). Several derivatives with the most potent anti-inflammatory activity were tested for blood-brain barrier permeability and sTGFBR3 affinity. Derivative P24, selected for its superior properties, was further evaluated in vitro. The results indicated that P24 increased the activation of TGF-β signaling and decreased the activation of IκBα/NF-κB signaling by targeting sTGFBR3, thereby regulating the inflammation-phagocytosis balance in microglia. Moreover, the low acute toxicity, long half-life, and low plasma clearance of P24 suggest that it can be sustained in vivo. This property may render P24 a more effective treatment modality for chronic diseases, particularly AD. The study demonstrates P24 serve as potential novel candidates for the treatment of AD via antagonizing sTGFBR3.

Improved mirror-assisted multi-view digital image correlation for accuracy-enhanced dual-surface profile and deformation measurement

Accurate measurement of dual-surface kinematic fields is essential for characterizing the mechanical behavior and anisotropic parameters of sheet specimens. To this end, a cost-efficient and simple-to-implement mirror-assisted multi-view digital image correlation (MV-DIC) was recently proposed and has been proven to be effective. Nevertheless, this method conventionally relies on reflection transformation calibration to map the measured virtual surfaces to their actual positions. The positional transformation for each surface is mutually independent and lacks constraint relationships. This work proposes an improved mirror-assisted MV-DIC method for accuracy-enhanced dual-surface deformation measurement by utilizing the overlapped region of the virtual surfaces instead of reflection transformation calibration. Through preliminary feature matching and precise matching of subsets for corresponding points in the overlapped regions, the relative positional transformations between the measured surfaces of the specimen can be accurately determined. As the accuracy of positional transformations primarily depends on the matching accuracy of corresponding points rather than the accuracy of multiple plane fitting, this method provides better relative positional relationships between the two surfaces compared to conventional methods. The results of several real experiments well validated the practicality and accuracy of the proposed method.

Pixantrone as a novel MCM2 inhibitor for ovarian cancer treatment

BackgroundMini-chromosome maintenance protein 2 (MCM2) is a potential target for the development of cancer therapeutics. However, small molecule inhibitors targeting MCM2 need further investigation. MethodsMolecular dynamics simulation was performed to identify active pockets in the MCM2 protein structure (6EYC). The active pocket was used as a docking model to discover MCM2 inhibitors by using structure-based virtual screening and surface plasmon resonance (SPR) assay. Furthermore, the efficacy of pixantrone targeting MCM2 in ovarian cancer was evaluated in vitro and in vivo. ResultsPixantrone was identified as a novel inhibitor of MCM2 by virtual screening. SPR binding affinity analysis confirmed the direct binding of pixantrone to MCM2 protein. Pixantrone significantly reduced the viability of ovarian cancer cells A2780 and SKOV3 in a dose- and time-dependent manner. In addition, pixantrone inhibited DNA replication, and induced cell cycle arrest and apoptosis in ovarian cancer cells via targeting MCM2. Knockdown of MCM2 could attenuate the inhibitory activity of pixantrone in ovarian cancer cells. Furthermore, pixantrone significantly suppressed ovarian cancer growth in the A2780 cell xenograft mouse model and showed favorable safety. ConclusionThese findings suggest that pixantrone may be a promising drug for ovarian cancer patients by targeting MCM2 in the clinic.

Three-dimensional internal multiple elimination in complex structures using Marchenko autofocusing theory

Internal multiples are commonly present in seismic data due to variations in velocity or density of subsurface media. They can reduce the signal-to-noise ratio of seismic data and degrade the quality of the image. With the development of seismic exploration into deep and ultradeep events, especially those from complex targets in the western region of China, the internal multiple eliminations become increasingly challenging. Currently, three-dimensional (3D) seismic data are primarily used for oil and gas target recognition and drilling. Effectively eliminating internal multiples in 3D seismic data of complex structures and mitigating their adverse effects is crucial for enhancing the success rate of drilling. In this study, we propose an internal multiples prediction algorithm for 3D seismic data in complex structures using the Marchenko autofocusing theory. This method can predict the accurate internal multiples of time difference without an accurate velocity model and the implementation process mainly consists of several steps. Firstly, simulating direct waves with a 3D macroscopic velocity model. Secondly, using direct waves and 3D full seismic acquisition records to obtain the upgoing and downgoing Green’s functions between the virtual source point and surface. Thirdly, constructing internal multiples of the relevant layers by upgoing and downgoing Green’s functions. Finally, utilizing the adaptive matching subtraction method to remove predicted internal multiples from the original data to obtain seismic records without multiples. Compared with the two-dimensional (2D) Marchenko algorithm, the performance of the 3D Marchenko algorithm for internal multiple predictions has been significantly enhanced, resulting in higher computational accuracy. Numerical simulation test results indicate that our proposed method can effectively eliminate internal multiples in 3D seismic data, thereby exhibiting important theoretical and industrial application value.

Analytical Modeling of Steel Shielding Cylinder in Surface-Mounted Permanent Magnet Machines

Two-dimensional (2-D) analytical modeling of permanent magnet machines with shielding cylinder is a challenging task due to the saturation effect of the cylinder. This paper presents a 2-D hybrid analytical solution to model surface-mounted permanent magnet machines with a shielding cylinder attached to the exterior of the rotor body. The presented model provides an accurate representation of the motor response by accounting for the saturation effect of the shielding cylinder, as well as the stator slotting effect. For this purpose, the steel shielding cylinder is modeled by a vacuum cylinder (with the exact same size/dimension) and two inner and outer virtual surface currents. The values of the surface currents are determined by using the respective magnetic circuit model. Meanwhile, the slotting effect on the tangential flux component is modeled by injecting a virtual surface current onto a slotless stator surface. Next, the radial and tangential flux density are obtained by solving Poisson's equation via separation of variables theorem and applying relevant boundary conditions. The accuracy of the proposed model is verified by the finite element and experimental tests on the machine prototype.

Field curvature analysis and optimization method for near-eye display systems

Near-eye display (NED) systems with a large field of view (FOV) and a large pupil are often accompanied by field curvature. In such cases, there is often a significant deviation between the virtual image seen by the human eye and an ideal plane. Currently, there is a lack of precise methods for describing and controlling the shape of virtual images in visual space. In this paper, the system is modeled, and the curvature is controlled through optimization. Under limited conditions, the system’s field curvature is controlled to approach an ideal state. When the system’s field curvature cannot be completely corrected, a method for describing the virtual image surface is introduced. This method helps optical designers effectively predict the degree of curvature and the distance of the virtual image. The image quality of the system with a curved image is evaluated and optimized based on the focusing function of the human eye. Additionally, the field curvature and pupil swim are analyzed jointly. The effectiveness of the method is verified by designing two different types of NED systems.