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Dong Sun

Publications and source records attributed to Dong Sun.

At least 37 records · Page 2Linked to original sources

Autonomous Intelligent Navigation for Flexible Endoscopy Using Monocular Depth Guidance and 3-D Shape Planning

Recent advancements toward perception and decision-making of flexible endoscopes have shown great potential in computer-aided surgical interventions. However, owing to modeling uncertainty and inter-patient anatomical variation in flexible endoscopy, the challenge remains for efficient and safe navigation in patient-specific scenarios. This paper presents a novel data-driven framework with self-contained visual-shape fusion for autonomous intelligent navigation of flexible endoscopes requiring no priori knowledge of system models and global environments. A learning-based adaptive visual servoing controller is proposed to online update the eye-in-hand vision-motor configuration and steer the endoscope, which is guided by monocular depth estimation via a vision transformer (ViT). To prevent unnecessary and excessive interactions with surrounding anatomy, an energy-motivated shape planning algorithm is introduced through entire endoscope 3-D proprioception from embedded fiber Bragg grating (FBG) sensors. Furthermore, a model predictive control (MPC) strategy is developed to minimize the elastic potential energy flow and simultaneously optimize the steering policy. Dedicated navigation experiments on a robotic-assisted flexible endoscope with an FBG fiber in several phantom environments demonstrate the effectiveness and adaptability of the proposed framework.

cs.RO↗

Light-induced emergent phenomena in 2D materials and topological materials

Light-matter interaction in 2D and topological materials provides a fascinating control knob for inducing emergent, non-equilibrium properties and achieving new functionalities in the ultrafast time scale (from fs to ps). Over the past decade, intriguing light-induced phenomena, e.g., Bloch-Floquet states and photo-induced phase transitions, have been reported experimentally, but many still await experimental realization. In this Review, we discuss recent progress on the light-induced phenomena, in which the light field could act as a time-periodic field to drive Floquet states, induce structural and topological phase transitions in quantum materials, couple with spin and various pseudospins, and induce nonlinear optical responses that are affected by the geometric phase. Perspectives on the opportunities of proposed light-induced phenomena as well as open experimental challenges are also discussed.

cond-mat.mes-hall↗

Dual-View Selective Instance Segmentation Network for Unstained Live Adherent Cells in Differential Interference Contrast Images

Despite recent advances in data-independent and deep-learning algorithms, unstained live adherent cell instance segmentation remains a long-standing challenge in cell image processing. Adherent cells' inherent visual characteristics, such as low contrast structures, fading edges, and irregular morphology, have made it difficult to distinguish from one another, even by human experts, let alone computational methods. In this study, we developed a novel deep-learning algorithm called dual-view selective instance segmentation network (DVSISN) for segmenting unstained adherent cells in differential interference contrast (DIC) images. First, we used a dual-view segmentation (DVS) method with pairs of original and rotated images to predict the bounding box and its corresponding mask for each cell instance. Second, we used a mask selection (MS) method to filter the cell instances predicted by the DVS to keep masks closest to the ground truth only. The developed algorithm was trained and validated on our dataset containing 520 images and 12198 cells. Experimental results demonstrate that our algorithm achieves an AP_segm of 0.555, which remarkably overtakes a benchmark by a margin of 23.6%. This study's success opens up a new possibility of using rotated images as input for better prediction in cell images.

cs.CV↗

Distilled Visual and Robot Kinematics Embeddings for Metric Depth Estimation in Monocular Scene Reconstruction

Estimating precise metric depth and scene reconstruction from monocular endoscopy is a fundamental task for surgical navigation in robotic surgery. However, traditional stereo matching adopts binocular images to perceive the depth information, which is difficult to transfer to the soft robotics-based surgical systems due to the use of monocular endoscopy. In this paper, we present a novel framework that combines robot kinematics and monocular endoscope images with deep unsupervised learning into a single network for metric depth estimation and then achieve 3D reconstruction of complex anatomy. Specifically, we first obtain the relative depth maps of surgical scenes by leveraging a brightness-aware monocular depth estimation method. Then, the corresponding endoscope poses are computed based on non-linear optimization of geometric and photometric reprojection residuals. Afterwards, we develop a Depth-driven Sliding Optimization (DDSO) algorithm to extract the scaling coefficient from kinematics and calculated poses offline. By coupling the metric scale and relative depth data, we form a robust ensemble that represents the metric and consistent depth. Next, we treat the ensemble as supervisory labels to train a metric depth estimation network for surgeries (i.e., MetricDepthS-Net) that distills the embeddings from the robot kinematics, endoscopic videos, and poses. With accurate metric depth estimation, we utilize a dense visual reconstruction method to recover the 3D structure of the whole surgical site. We have extensively evaluated the proposed framework on public SCARED and achieved comparable performance with stereo-based depth estimation methods. Our results demonstrate the feasibility of the proposed approach to recover the metric depth and 3D structure with monocular inputs.

cs.RO↗

Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery

Objective: The computation of anatomical information and laparoscope position is a fundamental block of surgical navigation in Minimally Invasive Surgery (MIS). Recovering a dense 3D structure of surgical scene using visual cues remains a challenge, and the online laparoscopic tracking primarily relies on external sensors, which increases system complexity. Methods: Here, we propose a learning-driven framework, in which an image-guided laparoscopic localization with 3D reconstructions of complex anatomical structures is obtained. To reconstruct the 3D structure of the whole surgical environment, we first fine-tune a learning-based stereoscopic depth perception method, which is robust to the texture-less and variant soft tissues, for depth estimation. Then, we develop a dense visual reconstruction algorithm to represent the scene by surfels, estimate the laparoscope poses and fuse the depth maps into a unified reference coordinate for tissue reconstruction. To estimate poses of new laparoscope views, we achieve a coarse-to-fine localization method, which incorporates our reconstructed 3D model. Results: We evaluate the reconstruction method and the localization module on three datasets, namely, the stereo correspondence and reconstruction of endoscopic data (SCARED), the ex-vivo phantom and tissue data collected with Universal Robot (UR) and Karl Storz Laparoscope, and the in-vivo DaVinci robotic surgery dataset, where the reconstructed 3D structures have rich details of surface texture with an accuracy error under 1.71 mm and the localization module can accurately track the laparoscope with only images as input. Conclusions: Experimental results demonstrate the superior performance of the proposed method in 3D anatomy reconstruction and laparoscopic localization. Significance: The proposed framework can be potentially extended to the current surgical navigation system.

cs.CV↗

Analysis of Wall Heat Flux of a Hypersonic Shock Wave / Boundary Layer Interaction with a Novel Decomposition Formula

The generation mechanism of wall heat flux is one of the fundamental problems in supersonic/hypersonic turbulent boundary layers. A novel heat decomposition formula under the curvilinear coordinate was proposed in this paper. The new formula has wider application scope and can be applied in the configurations with grid deformed. The wall heat flux of an interaction between shock wave and the turbulent boundary layer over a compression corner is analyzed by the new formula. The results indicated good performance of the formula in the complex interaction region. The contributions of different energy transport processes were obtained. The contributions by the turbulent fluctuations e.g., Reynolds stresses and turbulent transport of heat flux, were significantly increased, while the processes by the mean profile e.g., molecular stresses and heat conduction, can be neglected. In addition, the pressure work is another contributor to the wall heat flux and the streamwise component works mainly in the shear layer and the reattachment point, while pressure in the wall-normal direction is concentrated in the vicinity of the reattachment point.

physics.flu-dyn↗

Ultrafast photothermoelectric effect in Dirac semimetallic Cd3As2 revealed by terahertz emission

The thermoelectric effects of topological semimetals have attracted tremendous research interest because many topological semimetals are excellent thermoelectric materials and thermoelectricity serves as one of their most important potential applications. In this work, we reveal the transient photothermoelectric response of Dirac semimetallic Cd3As2, namely the photo-Seebeck effect and photo-Nernst effect, by studying the terahertz (THz) emission from the transient photocurrent induced by these effects. Our excitation polarization and power dependence confirm that the observed THz emission is due to photothermoelectric effect instead of other nonlinear optical effect. Furthermore, when a weak magnetic field (~0.4 T) is applied, the response clearly indicates an order of magnitude enhancement on transient photothermoelectric current generation compared to the photo-Seebeck effect. Such enhancement supports an ambipolar transport nature of the photo-Nernst current generation in Cd3As2. These results highlight the enhancement of thermoelectric performance can be achieved in topological Dirac semimetals based on the Nernst effect, and our transient studies pave the way for thermoelectric devices applicable for high field circumstance when nonequilibrium state matters. The large THz emission due to highly efficient photothermoelectric conversion is comparable to conventional semiconductors through optical rectification and photo-Dember effect.

cond-mat.mtrl-sci↗

Direct Light Orbital Angular Momentum Detection in Mid-Infrared based on Type-II Weyl Semimetal TaIrTe4

The capability of direct photocurrent detection of orbital angular momentum (OAM) of light has recently been realized with topological Weyl semimetal, but limited to near infrared wavelength range. The extension of direct OAM detection to midinfrared, a wavelength range that plays important role in a vast range of applications, such as autonomous driving, night vision and motion detection, is challenging and has not yet been realized. This is because most studies of photocurrent responses are not sensitive to the phase information and the photo response is usually very poor in the mid-infrared. In this study, we designed a photodetector based on Type-II Weyl semimetal tantalum iridium tellurides with designed electrode geometries for direct detection of the topological charge of OAM through orbital photogalvanic effect. Our results indicate helical phase gradient of light can be distinguished by a current winding around the optical beam axis with a magnitude proportional to its quantized OAM mode number. The topological enhanced response at mid-infrared of TaIrTe4 further help overcome the low responsivity issues and finally render the direct orbital angular momentum detection capability in mid-infrared. Our study enables on-chip integrated OAM detection, and thus OAM sensitive focal plane arrays in mid-infrared. Such capability triggers new route to explore applications of light carrying OAM, especially that it can crucially promote the performance of many mid-infrared imaging related applications, such as intricate target recognition and night vision.

physics.optics↗

Population inversion and Dirac fermion cooling in 3D Dirac semimetal Cd$_3$As$_2$

Revealing the ultrafast dynamics of three-dimensional (3D) Dirac fermions upon photoexcitation is critical for both fundamental science and device applications. So far, how the cooling of 3D Dirac fermions differs from that of two-dimensional (2D) Dirac fermions and whether there is population inversion are fundamental questions that remain to be answered. Here we reveal the ultrafast dynamics of Dirac fermions in a model 3D Dirac semimetal Cd$_3$As$_2$ by ultrafast time- and angle-resolved photoemission spectroscopy (TrARPES) with a tunable probe photon energy from 5.3 - 6.9 eV. The energy- and momentum-resolved relaxation rate shows a linear dependence on the energy, suggesting Dirac fermion cooling through intraband relaxation. Moreover, a population inversion is reported based on the observation of accumulated photoexcited carriers in the conduction band with a lifetime of $τ_n$ = 3.0 ps. Our work provides direct experimental evidence for a long-lived population inversion in a 3D Dirac semimetal, which is in contrast to 2D graphene where the interband relaxation occurs on a much faster timescale.

cond-mat.mes-hall↗

Decomposition Formula for the Wall Heat Flux of a Compressible Boundary Layer

Understanding the generation mechanism of the heating flux is essential for the design of hypersonic vehicles. We proposed a novel formula to decompose the heat flux coefficient into the contributions of different terms by integrating the conservative equation of the total energy. The reliability of the formula is well demonstrated by the direct numerical simulation results of a hypersonic transitional boundary layer. Through this formula, the exact process of the energy transport in the boundary layer can be explained and the dominant contributors to the heat flux can be explored, which are beneficial for the prediction of the heat and design of the thermal protection devices

physics.flu-dyn↗

Radio frequency polarization modulation based on an optical frequency comb

We propose a method to generate stabilized radio-frequency polarization modulation based on optical frequency combs. Two pulse trains with the same repetition rate and different offset frequencies generate arbitrary polarization states that are modulated at the offset frequency difference. Long-term stability of the polarization modulation is demonstrated with the modulation frequency at frep/2. Modulation at frep/4 is also demonstrated to show the flexibility of the technique. We employ an electrical delay line to fine-tune the polarization states that constitute the time-dependent modulation.

physics.optics↗

DFSeer: A Visual Analytics Approach to Facilitate Model Selection for Demand Forecasting

Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users' demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model comparison and selection with different levels of details. Besides, it shows the difference in model performance on similar products to reveal the risk of model selection and increase users' confidence in choosing a forecasting model. Two case studies and interviews with domain experts demonstrate the effectiveness and usability of DFSeer.

cs.HC↗

Semimetals for high performance photodetection

Semimetals are being explored for their unique advantages in low-energy high-speed photodetection, although they suffer from serious drawbacks such as an intrinsically high dark current. In this perspective, we envision the exploitation of topological effects in the photoresponse of these materials as a promising route to circumvent these problems. We overview recent studies on photodetection based on graphene and other semimetals, and further discuss the exciting opportunities created by the topological effects, along with the additional requirements that they impose on photodetector designs.

physics.app-ph↗

Observation of Fano resonance in photoluminescence of a two-dimensional magnetic semiconductor

Quantum interference gives rise to the asymmetric Fano resonance line shape when the final states of an electronic transition follows within a continuum of states and a discrete state, which has significant applications in optical switching and sensing. The resonant optical phenomena associated with Fano resonance have been observed by absorption spectra, Raman spectra, transmission spectra, etc., but have rarely been reported in photoluminescence (PL) spectroscopy. In this work, we performed spectroscopic studies on layered chromium thiophosphate (CrPS4), a promising ternary antiferromagnetic semiconductor with PL in near-infrared wavelength region and observed Fano resonance when CrPS4 experiences phase transition into the antiferromagnetic state below Néel temperature (38 K). The photoluminescence of the continuum states results from the d band transitions localized at Cr3+ ions, while the discrete state reaches saturation at high excitation power and can be enhanced by the external magnetic field, suggesting it is formed by an impurity level from extra atomic phosphorus. Our findings provide insights into the electronic transitions of CrPS4 and their connection to its intrinsic magnetic properties.

cond-mat.mtrl-sci↗

Robust edge photocurrent response on layered Type II Weyl semimetal WTe2

Photo sensing and energy harvesting based on exotic properties of quantum materials and new operation principles have great potentials to break the fundamental performance limit of conventional photodetectors and solar cells. As topological nontrivial materials, Weyl semimetals have demonstrated novel optoelectronic properties that promise potential applications in photo detection and energy harvesting arising from their gapless linear dispersion near Weyl nodes and Berry field enhanced nonlinear optical effect at the vicinity of Weyl nodes. In this work, we demonstrate robust photocurrent generation from charge separation of photoexctied electron-hole pairs at the edge of Td-WTe2, a type-II Weyl semimetal, due to crystalline-symmetry breaking along certain crystal fracture directions and possibly enhanced by robust fermi-arc type surface states. Using scanning photocurrent microscopy (SPCM) measurements, we further demonstrate that the edge current response is robust over a wide excitation photon energy. We find that this robust feature is highly generic, and shall arise universally in a wide class of quantum materials with similar crystal symmetries. In addition, possible connections between these edge photocurrents and topological properties of Weyl semimetals are explored. The robust and generic edge current response demonstrated in this work provides a new type of charge separation mechanism for photosensing and energy harvesting over broad wavelength range.

cond-mat.mes-hall↗

PlanningVis: A Visual Analytics Approach to Production Planning in Smart Factories

Production planning in the manufacturing industry is crucial for fully utilizing factory resources (e.g., machines, raw materials and workers) and reducing costs. With the advent of industry 4.0, plenty of data recording the status of factory resources have been collected and further involved in production planning, which brings an unprecedented opportunity to understand, evaluate and adjust complex production plans through a data-driven approach. However, developing a systematic analytics approach for production planning is challenging due to the large volume of production data, the complex dependency between products, and unexpected changes in the market and the plant. Previous studies only provide summarized results and fail to show details for comparative analysis of production plans. Besides, the rapid adjustment to the plan in the case of an unanticipated incident is also not supported. In this paper, we propose PlanningVis, a visual analytics system to support the exploration and comparison of production plans with three levels of details: a plan overview presenting the overall difference between plans, a product view visualizing various properties of individual products, and a production detail view displaying the product dependency and the daily production details in related factories. By integrating an automatic planning algorithm with interactive visual explorations, PlanningVis can facilitate the efficient optimization of daily production planning as well as support a quick response to unanticipated incidents in manufacturing. Two case studies with real-world data and carefully designed interviews with domain experts demonstrate the effectiveness and usability of PlanningVis.

cs.HC↗

Hybridizing WENO implementations of interpolation and reconstruction-wise operation for upwind-biased schemes with free-stream preservation

Cases have shown that WENO schemes usually behave robustly on problems containing shocks with high pressure ratios when uniformed or smooth grids are present, while nonlinear schemes based on WENO interpolations might relatively be liable to numerical instability. In the meanwhile, the latter have manifested their advantages in computations on grids of bad quality, because the free-stream preservation is easily realized there, and what is more flux-splitting schemes with low dissipations can be engaged inherently as well. Targeting at above dissatisfactions, a method by hybridizing WENO implementations of interpolation and reconstruction-wise operation for upwind-biased schemes with flux splitting employed is proposed and corresponding third-, fifth- and seventh-order upwind-biased schemes are proposed. Based on the understandings of [Q. Li, et al. Commun. Comput. Phys. 22 (2017) 64-94], the free-stream preservation of proposed schemes is achieved with incorporation of frozen grid metrics in WENO reconstructions-wise operations on split fluxes. In proposed schemes, flux-splitting schemes with low dissipation can also be applied for the flux on a cell edge. As a byproduct, an implementation of WENO scheme with free-stream preservation is obtained. Numerical examples are provided as following with the third- and fifth-order schemes being tested. In tests of free-stream preservation, the property is achieved as expected (including two implementations of WENO). The computation of 1-D Sod problem shows the capability of proposed schemes on solving ordinary shock discontinuity. 2-D vortex preservation and double Mach reflection are tested on uniformed and randomized grids. The accomplishment by proposed schemes manifests their capability and robustness on solving problems under rigorous circumstances.

physics.comp-ph↗

WENO interpolation-based and upwind-biased schemes with free-stream preservation

Based on the understandings regarding linear upwind schemes with flux splitting to achieve free-stream preservation (Q. Li, etc. Commun. Comput. Phys., 22 (2017) 64-94), a series of WENO interpolation-based and upwind-biased nonlinear schemes are proposed in this study. By means of engagement of fluxes on midpoints, the nonlinearity of schemes is introduced through WENO interpolations, and upwind-biased features are acquired through the choice of dependent grid stencil. Regarding the third- and fifth-order versions, schemes with one and two midpoints are devised and carefully tested. With the integration of the piecewise-polynomial mapping function methods (Q. Li, etc. Commun. Comput. Phys. 18 (2015) 1417-1444), the proposed schemes are found to achieve the designed orders and free-stream preservation property. In 1-D Sod and Shu-Osher problems, all schemes succeed in yielding well predictions. In 2-D cases, the vortex preservation, supersonic inviscid flow around cylinder at M=4, Riemann problem and Shock-vortex interaction problems are tested. In each problem, two types of grids are employed, i.e. the uniformed/smooth grids and the randomized/partially-randomized grids. On the latter, the shock wave and complex flow structures are located/partially located. All schemes fulfill computations in uniformed/smooth grids with satisfactory results. On randomized grids, all schemes accomplish computations and yield reasonable results except the third-order one with two midpoints engaged fails in Riemann problem and shock-vortex interaction problem. Overall speaking, the proposed schemes manifest the capability to solve problems on grids with bad quality, and therefore indicate their potential in engineering applications.

physics.comp-ph↗