arXiv subjects

Xu Liu

Publications and source records attributed to Xu Liu.

At least 271 records · Page 15Linked to original sources

arXiv2018

Controlling DNA Tug-of-War in a Dual Nanopore Device

Methods for reducing and directly controlling the speed of DNA through a nanopore are needed to enhance sensing performance for direct strand sequencing and detection/mapping of sequence-specific features. We have created a method for reducing and controlling the speed of DNA that uses two independently controllable nanopores operated with an active control logic. The pores are positioned sufficiently close to permit co-capture of a single DNA by both pores. Once co-capture occurs, control logic turns on constant competing voltages at the pores leading to a `tug-of-war' whereby the molecule is pulled from both ends by opposing forces. These forces exert both conformational and speed control over the co-captured molecule, removing folds and reducing the translocation rate. When the voltages are tuned so that the electrophoretic force applied to both ends of the molecule comes into balance, the life-time of the tug-of-war state is limited purely by diffusive sliding of the DNA between the pores. We are able to produce a tug-of-war state on 76.8% of molecules that are captured with a maximum two-order of magnitude increase in average pore translocation time relative to the average time for single-pore translocation. Moreover, we quantify the translocation slow-down as a function of voltage tuning and show that the slow-down is well described by a first passage analysis for a one-dimensional sub-diffusive process. The ionic current of each nanopore provides an independent sensor that synchronously measures a different region of the same molecule, enabling sequential detection of physical labels, such as mono-streptavidin tags. With advances in devices and control logic, future dual-pore applications include genome mapping and enzyme-free sequencing.

physics.bio-ph↗

arXiv2018

Finite Codimensional Controllability, and Optimal Control Problems with Endpoint State Constraints

In this paper, motivated by the study of optimal control problems for infinite dimensional systems with endpoint state constraints, we introduce the notion of finite codimensional (exact/approximate) controllability. Some equivalent criteria on the finite codimensional controllability are presented. In particular, the finite codimensional exact controllability is reduced to deriving a Gårding type inequality for the adjoint system, which is new for many evolution equations. This inequality can be verified for some concrete problems (and hence applied to the corresponding optimal control problems), say the wave equations with both time and space dependent potentials. Moreover, under some mild assumptions, we show that the finite codimensional exact controllability of this sort of wave equations is equivalent to the classical geometric control condition.

math.OC↗

arXiv2018

Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motion

We present a novel fruit counting pipeline that combines deep segmentation, frame to frame tracking, and 3D localization to accurately count visible fruits across a sequence of images. Our pipeline works on image streams from a monocular camera, both in natural light, as well as with controlled illumination at night. We first train a Fully Convolutional Network (FCN) and segment video frame images into fruit and non-fruit pixels. We then track fruits across frames using the Hungarian Algorithm where the objective cost is determined from a Kalman Filter corrected Kanade-Lucas-Tomasi (KLT) Tracker. In order to correct the estimated count from tracking process, we combine tracking results with a Structure from Motion (SfM) algorithm to calculate relative 3D locations and size estimates to reject outliers and double counted fruit tracks. We evaluate our algorithm by comparing with ground-truth human-annotated visual counts. Our results demonstrate that our pipeline is able to accurately and reliably count fruits across image sequences, and the correction step can significantly improve the counting accuracy and robustness. Although discussed in the context of fruit counting, our work can extend to detection, tracking, and counting of a variety of other stationary features of interest such as leaf-spots, wilt, and blossom.

cs.CV↗

arXiv2018

Deep Adaptive Proposal Network for Object Detection in Optical Remote Sensing Images

Object detection is a fundamental and challenging problem in aerial and satellite image analysis. More recently, a two-stage detector Faster R-CNN is proposed and demonstrated to be a promising tool for object detection in optical remote sensing images, while the sparse and dense characteristic of objects in remote sensing images is complexity. It is unreasonable to treat all images with the same region proposal strategy, and this treatment limits the performance of two-stage detectors. In this paper, we propose a novel and effective approach, named deep adaptive proposal network (DAPNet), address this complexity characteristic of object by learning a new category prior network (CPN) on the basis of the existing Faster R-CNN architecture. Moreover, the candidate regions produced by DAPNet model are different from the traditional region proposal network (RPN), DAPNet predicts the detail category of each candidate region. And these candidate regions combine the object number, which generated by the category prior network to achieve a suitable number of candidate boxes for each image. These candidate boxes can satisfy detection tasks in sparse and dense scenes. The performance of the proposed framework has been evaluated on the challenging NWPU VHR-10 data set. Experimental results demonstrate the superiority of the proposed framework to the state-of-the-art.

cs.CV↗

arXiv2018

Start Late or Finish Early: A Distributed Graph Processing System with Redundancy Reduction

Graph processing systems are important in the big data domain. However, processing graphs in parallel often introduces redundant computations in existing algorithms and models. Prior work has proposed techniques to optimize redundancies for the out-of-core graph systems, rather than the distributed graph systems. In this paper, we study various state-of-the-art distributed graph systems and observe root causes for these pervasively existing redundancies. To reduce redundancies without sacrificing parallelism, we further propose SLFE, a distributed graph processing system, designed with the principle of "start late or finish early". SLFE employs a novel preprocessing stage to obtain a graph's topological knowledge with negligible overhead. SLFE's redundancy-aware vertex-centric computation model can then utilize such knowledge to reduce the redundant computations at runtime. SLFE also provides a set of APIs to improve the programmability. Our experiments on an 8-node high-performance cluster show that SLFE outperforms all well-known distributed graph processing systems on real-world graphs (yielding up to 74.8x speedup). SLFE's redundancy-reduction schemes are generally applicable to other vertex-centric graph processing systems.

cs.DC↗

arXiv2018

Chiral Flow in One-dimensional Floquet Topological Insulators

We propose a bulk topological invariant for one-dimensional Floquet systems with chiral symmetry which quantifies the particle transport on each sublattice during the evolution. This chiral flow is physically motivated, locally computable, and improves on existing topological invariants by being applicable to systems with disorder. We derive a bulk-edge correspondence which relates the chiral flow to the number of protected dynamical edge modes present on a boundary at the end of the evolution. In the process, we introduce two real-space edge invariants which classify the dynamical topological boundary behavior at various points during the evolution. Our results provide the first explicit bulk-boundary correspondence for Floquet systems in this symmetry class.

cond-mat.str-el↗

arXiv2018

Deep Hashing with Category Mask for Fast Video Retrieval

This paper proposes an end-to-end deep hashing framework with category mask for fast video retrieval. We train our network in a supervised way by fully exploiting inter-class diversity and intra-class identity. Classification loss is optimized to maximize inter-class diversity, while intra-pair is introduced to learn representative intra-class identity. We investigate the binary bits distribution related to categories and find out that the effectiveness of binary bits is highly correlated with data categories, and some bits may degrade classification performance of some categories. We then design hash code generation scheme with category mask to filter out bits with negative contribution. Experimental results demonstrate the proposed method outperforms several state-of-the-arts under various evaluation metrics on public datasets.

cs.CV↗

arXiv2018

Three-dimensional visible-light invisibility cloak

The concept of an invisibility cloak is a fixture of science fiction, fantasy, and the collective imagination. However, a real device that could hide an object from sight in visible light from absolutely any viewpoint would be extremely challenging to build. The main obstacle to creating such a cloak is the coupling of the electromagnetic components of light, which would necessitate the use of complex materials with specific permittivity and permeability tensors. Previous cloaking solutions have involved circumventing this obstacle by functioning either in static (or quasi-static) fields where these electromagnetic components are uncoupled or in diffusive light scattering media where complex materials are not required. In this paper, we report concealing a large-scale spherical object from human sight from three orthogonal directions. We achieve this result by developing a three-dimensional (3D) homogeneous polyhedral transformation and a spatially invariant refractive index discretization that considerably reduce the coupling of the electromagnetic components of visible light. This approach allows for a major simplification in the design of 3D invisibility cloaks, which can now be created at a large scale using homogeneous and isotropic materials.

physics.optics↗

arXiv2018

Orbital Origin of Extremely Anisotropic Superconducting Gap in Nematic Phase of FeSe Superconductor

The iron-based superconductors are characterized by multiple-orbital physics where all the five Fe 3$d$ orbitals get involved. The multiple-orbital nature gives rise to various novel phenomena like orbital-selective Mott transition, nematicity and orbital fluctuation that provide a new route for realizing superconductivity. The complexity of multiple-orbital also asks to disentangle the relationship between orbital, spin and nematicity, and to identify dominant orbital ingredients that dictate superconductivity. The bulk FeSe superconductor provides an ideal platform to address these issues because of its simple crystal structure and unique coexistence of superconductivity and nematicity. However, the orbital nature of the low energy electronic excitations and its relation to the superconducting gap remain controversial. Here we report direct observation of highly anisotropic Fermi surface and extremely anisotropic superconducting gap in the nematic state of FeSe superconductor by high resolution laser-based angle-resolved photoemission measurements. We find that the low energy excitations of the entire hole pocket at the Brillouin zone center are dominated by the single $d_{xz}$ orbital. The superconducting gap exhibits an anti-correlation relation with the $d_{xz}$ spectral weight near the Fermi level, i.e., the gap size minimum (maximum) corresponds to the maximum (minimum) of the $d_{xz}$ spectral weight along the Fermi surface. These observations provide new insights in understanding the orbital origin of the extremely anisotropic superconducting gap in FeSe superconductor and the relation between nematicity and superconductivity in the iron-based superconductors.

cond-mat.supr-con↗

arXiv2018

3D super-resolved multi-angle TIRF via polarization modulation

Measuring the three dimension nanoscale organization of protein or cellular structures is challenging, especially when the structure is dynamic. Owing to the informative total internal reflection fluorescence (TIRF) imaging under varied illumination angles, multi-angle (MA) TIRF has been examined to offer a nanoscale axial and a sub-second temporal resolution. However, conventional MA-TIRF still performs badly in lateral resolution and fail to characterize the depth-image in densely-distributed regions, leaving a huge contrast between the nanoscale axial resolution and the diffraction limited lateral resolution. Moreover, the previous reconstructions are highly restricted by the efficiency with the increased amount of illumination angles. Here, we for the first time, emphasize the lateral super-resolution in the MA-TIRF and exampled by simply introducing polarization modulation into the illumination procedure. Equipped with a sparsity and accelerated proximal algorithm, we examine a more precise 3D sample structure compared with previous methods, enabling live cell imaging with temporal-resolution of 2 seconds, recovering high-resolution mitochondria fission and fusion process. Since the introduced vortex half wave retarder is an add-on component to the existing MA-TRIF system and the algorithm is the first open sourced and the fastest, we anticipate that the method and algorithm introduced here would be adopted rapidly by the biological community.

physics.optics↗

arXiv2017

Nonlinear focal modulation microscopy

Here we report nonlinear focal modulation microscopy (NFOMM) to achieve super-resolution imaging. Abandoning the previous persistence on minimizing the size of Gaussian emission pattern by directly narrowing (e.g. Minimizing the detection pinhole in Airyscan, Zeiss) or by indirectly peeling its outer profiles (e.g., Depleting the outer emission region in STED, stimulated emission microscopy) in pointwise scanning scenarios, we stick to a more general basis------ maximizing the system frequency shifting ability. In NFOMM, we implement a nonlinear focal modulation by applying phase modulations with high-intensity illumination, thereby extending the effective spatial-frequency bandwidth of the imaging system for reconstructing super-resolved images. NFOMM employs a spatial light modulator (SLM) for assisting pattern-modulated pointwise scanning, making the system single beam path while achieving a transverse resolution of 60 nm on imaging fluorescent nanoparticles. While exploring a relatively simple and flexible system, the imagingperformance of NFOMM is comparable with STED as evidenced in imaging nuclear pore complexes, demonstrating NFOMM is a suitable observation tool for fundamental studies in biology. Since NFOMM is implemented as an add-on module to an existing laser scanning microscope and easy to be aligned, we anticipate it will be adopted rapidly by the biological community.

physics.optics↗

arXiv2017

Unsupervised Submodular Rank Aggregation on Score-based Permutations

Unsupervised rank aggregation on score-based permutations, which is widely used in many applications, has not been deeply explored yet. This work studies the use of submodular optimization for rank aggregation on score-based permutations in an unsupervised way. Specifically, we propose an unsupervised approach based on the Lovasz Bregman divergence for setting up linear structured convex and nested structured concave objective functions. In addition, stochastic optimization methods are applied in the training process and efficient algorithms for inference can be guaranteed. The experimental results from Information Retrieval, Combining Distributed Neural Networks, Influencers in Social Networks, and Distributed Automatic Speech Recognition tasks demonstrate the effectiveness of the proposed methods.

cs.LG↗

arXiv2017

Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration

Tracking of multiple objects is an important application in AI City geared towards solving salient problems related to safety and congestion in an urban environment. Frequent occlusion in traffic surveillance has been a major problem in this research field. In this challenge, we propose a model-based vehicle localization method, which builds a kernel at each patch of the 3D deformable vehicle model and associates them with constraints in 3D space. The proposed method utilizes shape fitness evaluation besides color information to track vehicle objects robustly and efficiently. To build 3D car models in a fully unsupervised manner, we also implement evolutionary camera self-calibration from tracking of walking humans to automatically compute camera parameters. Additionally, the segmented foreground masks which are crucial to 3D modeling and camera self-calibration are adaptively refined by multiple-kernel feedback from tracking. For object detection/classification, the state-of-the-art single shot multibox detector (SSD) is adopted to train and test on the NVIDIA AI City Dataset. To improve the accuracy on categories with only few objects, like bus, bicycle and motorcycle, we also employ the pretrained model from YOLO9000 with multi-scale testing. We combine the results from SSD and YOLO9000 based on ensemble learning. Experiments show that our proposed tracking system outperforms both state-of-the-art of tracking by segmentation and tracking by detection.

cs.CV↗

arXiv2017

Saturated absorption competition microscopy

We introduce the concept of saturated absorption competition (SAC) microscopy as a means of providing sub-diffraction spatial resolution in fluorescence imaging. Unlike the post-competition process between stimulated and spontaneous emission that is used in stimulated emission depletion (STED) microscopy, SAC microscopy breaks the diffraction limit by emphasizing a pre-competition process that occurs in the fluorescence absorption stage in a manner that shares similarities with ground-state depletion (GSD) microscopy. Moreover, unlike both STED and GSD microscopy, SAC microscopy offers a reduction in complexity and cost by utilizing only a single continuous-wave laser diode and an illumination intensity that is ~ 20x smaller than that used in STED. Our approach can be physically implemented in a confocal microscope by dividing the input laser source into a time-modulated primary excitation beam and a doughnut-shaped saturation beam, and subsequently employing a homodyne detection scheme to select the modulated fluorescence signal. Herein, we provide both a physico-chemical model of SAC and experimentally demonstrate by way of a proof-of-concept experiment a transverse spatial resolution of ~lambda/6.

physics.optics↗

arXiv2016

Correctness of Hierarchical MCS Locks with Timeout

This manuscript serves as a correctness proof of the Hierarchical MCS locks with Timeout (HMCS-T) described in our paper titled "An Efficient Abortable-locking Protocol for Multi-level NUMA Systems" appearing in the proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. HMCS-T is a very involved protocol. The system is stateful; the values of prior acquisition efforts affect the subsequent acquisition efforts. Also, the status of successors, predecessors, ancestors, and descendants affect steps followed by the protocol. The ability to make the protocol fully non-blocking leads to modifications to the \texttt{next} field, which causes deviation from the original MCS lock protocol both in acquisition and release. At several places, unconditional field updates are replaced with SWAP or CAS operations. We follow a multi-step approach to prove the correctness of HMCS-T. To demonstrate the correctness of the HMCS-T lock, we use the Spin model checking. Model checking causes a combinatorial explosion even to simulate a handful of threads. First, we understand the minimal, sufficient configurations necessary to prove safety properties of a single level of lock in the tree. We construct HMCS-T locks that represent these configurations. We model check these configurations, which proves the correctness of components of an HMCS-T lock. Finally, building upon these facts, we argue logically for the correctness of HMCS-T .

cs.DC↗

arXiv2016

Finite Codimensional Controllability for Evolution Equations

Motivated by infinite-dimensional optimal control problems with endpoint state constraints, in this Note, we introduce the notion of finite codimensional exact controllability for evolution equations. It is shown that this new controllability is equivalent to the finite codimensionality condition in the literatures to guarantee Pontryagin's maximum principle. As examples, LQ problems with fixed endpoint state constraints for a wave and a heat equation are analyzed, respectively.

math.OC↗

arXiv2016

An Internal Observability Estimate for Stochastic Hyperbolic Equations

This paper is addressed to establishing an internal observability estimate for some linear stochastic hyperbolic equations. The key is to establish a new global Carleman estimate for forward stochastic hyperbolic equations in the $L^2$-space. Different from the deterministic case, a delicate analysis of the adaptedness for some stochastic processes is required in the stochastic setting.

math.OC↗

arXiv2015

Concealing arbitrary objects remotely with multi-folded transformation optics

An invisibility cloak that can hide an arbitrary object external to the cloak itself has not been devised before. In this Letter, we introduce a novel way to design a remote cloaking device that makes any object located at a certain distance invisible. This is accomplished using multi-folded transformation optics to remotely generate a hidden region around the object that no field can penetrate and that does not disturb the far-field scattering electromagnetic field. As a result, any object in the hidden region can stay in position or move freely within that region and remain invisible. Our idea is further extended in order to design a remote illusion optics that can transform any arbitrary object into another one. Unlike other cloaking methods, this method would require no knowledge of the details of the object itself. The proposed multi-folded transformation optics will be crucial in the design of remote devices in a variety of contexts.

physics.optics↗