arXiv subjects

Yang Jiao

Publications and source records attributed to Yang Jiao.

At least 127 records · Page 7Linked to original sources

arXiv2020

Translate Reverberated Speech to Anechoic Ones: Speech Dereverberation with BERT

Single channel speech dereverberation is considered in this work. Inspired by the recent success of Bidirectional Encoder Representations from Transformers (BERT) model in the domain of Natural Language Processing (NLP), we investigate its applicability as backbone sequence model to enhance reverberated speech signal. We present a variation of the basic BERT model: a pre-sequence network, which extracts local spectral-temporal information and/or provides order information, before the backbone sequence model. In addition, we use pre-trained neural vocoder for implicit phase reconstruction. To evaluate our method, we used the data from the 3rd CHiME challenge, and compare our results with other methods. Experiments show that the proposed method outperforms traditional method WPE, and achieve comparable performance with state-of-the-art BLSTM-based sequence models.

eess.AS↗

arXiv2020

Optical nonreciprocal response and conversion in a Tavis-Cummings coupling optomechanical system

We propose a scheme to realize optical nonreciprocal response and conversion in a Tavis-Cummings coupling optomechanical system, where a single cavity mode interacts with the vibrational mode of a flexible membrane with an embedded ensemble of two-level quantum emitters. Due to the introduction of the Tavis-Cummings interaction, we find that the phases between the mechanical mode and the optical mode, as well as between the mechanical mode and the dopant mode, are correlated with each other, and further give the analytical relationship between them. By optimizing the system parameters, especially the relative phase between two paths, the optimal nonreciprocal response can be achieved. Under the frequency domain, we derive the transmission matrix of the system analytically based on the input-output relation and study the influence of the system parameters on the nonreciprocal response of the quantum input signal. Moreover, compared with the conventional optomechanical systems, the Tavis-Cummings coupling optomechanical system exhibits richer nonreciprocal conversion phenomena among the optical mode, mechanical mode, and dopant mode, which provide a new applicable way of achieving the phonon-photon transducer and the optomechanical circulator in future practice.

quant-ph↗

arXiv2020

Stone-Wales Defects Preserve Hyperuniformity in Amorphous Two-Dimensional Materials

Crystalline two-dimensional (2D) materials such as graphene possess unique physical properties absent in their bulk form, enabling many novel device applications. Yet, little is known about their amorphous counterparts, which can be obtained by introducing the Stone-Wales (SW) topological defects via proton radiation. Here we provide strong numerical evidence that SW defects preserve hyperuniformity in hexagonal 2D materials, a recently discovered new state of matter characterized by vanishing normalized infinite-wavelength density fluctuations, which implies that all amorphous states of these materials are hyperuniform. Specifically, the static structure factor S(k) of these materials possesses the scaling S(k) ~ k^α for small wave number k, where 1<=α(p)<=2 is monotonically decreasing as the SW defect concentration p increases, indicating a transition from type-I to type-II hyperuniformity at p ~= 0.12 induced by the saturation of the SW defects. This hyperuniformity transition marks a structural transition from perturbed lattice structures to truly amorphous structures, and underlies the onset of strong correlation among the SW defects as well as a transition between distinct electronic transport mechanisms associated with different hyperuniformity classes.

cond-mat.mtrl-sci↗

arXiv2020

Information Content of Hierarchical n-Point Polytope Functions for Quantifying and Reconstructing Disordered Systems

Disordered systems are ubiquitous in physical, biological and material sciences. Examples include liquid and glassy states of condensed matter, colloids, granular materials, porous media, composites, alloys, packings of cells in avian retina and tumor spheroids, to name but a few. A comprehensive understanding of such disordered systems requires, as the first step, systematic quantification, modeling and representation of the underlying complex configurations and microstructure, which is generally very challenging to achieve. Recently, we introduce a set of hierarchical statistical microstructural descriptors, i.e., the n-point polytope functions Pn, which are derived from the standard n-point correlation functions Sn, and successively include higher-order n-point statistics of the morphological features of interest in a concise, explainable, and expressive manner. Here we investigate the information content of the Pn functions via optimization-based realization rendering. This is achieved by successively incorporating higher order Pn functions up to n = 8 and quantitatively assessing the accuracy of the reconstructed systems via un-constrained statistical morphological descriptors (e.g., the lineal-path function). We examine a wide spectrum of representative random systems with distinct geometrical and topological features. We find that generally, successively incorporating higher order Pn functions, and thus, the higher-order morphological information encoded in these descriptors, leads to superior accuracy of the reconstructions. However, incorporating more Pn functions into the reconstruction also significantly increases the complexity and roughness of the associated energy landscape for the underlying stochastic optimization, making it difficult to convergence numerically.

cond-mat.stat-mech↗

arXiv2020

Modeling Multi-Cellular Dynamics Regulated by ECM-Mediated Mechanical Communication via Active Particles with Polarized Effective Attraction

Collective cell migration is crucial to many physiological and pathological processes. Recent experimental studies have indicated that the active traction forces generated by migrating cells in fibrous extracellular matrix (ECM) can mechanically remodel the ECM, enabling long-range propagation of cellular forces and leading to correlated migration dynamics regulated by the mechanical communication among the cells. Motivated by these experimental discoveries, we develop an active-particle model with polarized effective attractions (APPA) for modeling emergent multi-cellular migration dynamics regulated by ECM-mediated mechanical communications. Active particles with polarized pairwise attractions exhibit enhanced aggregation behaviors compared to classic active Brownian particles, especially at lower particle densities and larger rotational diffusivities. Importantly, in contrast to the classic ABP system, the high-density phase of APPA system exhibits strong dynamic correlation, which is characterized by the slowly decaying velocity correlation functions with a correlation length comparable to the linear size of high-density phase domain (i.e., cluster of the particles). The strongly correlated multi-cellular dynamics predicted by the APPA model are subsequently verified in {\it in vitro} experiments using MCF-10A cells. Our studies also indicate the importance of incorporating ECM-mediated mechanical coupling among the migrating cells for appropriately modeling emergent multi-cellular dynamics in complex micro-environments.

cond-mat.soft↗

arXiv2020

Microstructure Design of Low-Melting-Point Alloy (LMPA)/ Polymer Composites for Dynamic Dry Adhesion Tuning in Soft Gripping

Tunable dry adhesion is a crucial mechanism in compliant manipulation. The gripping force, mainly originated from the van der Waals force between the adhesive composite and the object to be gripped, can be controlled by reversibly varying the physical properties (e.g., stiffness) of the composite via external stimuli. The maximal gripping force Fmax and its tunability depend on, among other factors, the stress distribution on the gripping interface and its fracture dynamics (during detaching), which in turn are determined by the composite microstructure. Here, we present a computational framework for the modeling and design of a class of binary smart composites containing a porous low-melting-point alloy (LMPA) phase and a polymer phase, in order to achieve desirable dynamically tunable dry adhesion. In particular, we employ spatial correlation functions to quantify, model and represent the complex bi-continuous microstructure of the composites, from which a wide spectrum of realistic virtual 3D composite microstructures can be generated using stochastic optimization. A recently developed volume-compensated lattice-particle (VCLP) method is then employed to model the dynamic interfacial fracture process to compute Fmax for different composite microstructures. We focus on the interface defect tuning (IDT) mechanism for dry adhesion tuning enabled by the composite, in which the thermal expansion of the LMPA phase due to Joule heating initializes small cracks on the adhesion interface, subsequently causing the detachment of the gripper from the object due to interfacial fracture. We find that for an optimal microstructure among the ones studied here, a 10-fold dynamic tuning of Fmax before and after the thermal expansion of the LMPA phase can be achieved. Our computational results can provide valuable guidance for experimental fabrication of the LMPA-polymer composites.

physics.app-ph↗

arXiv2019

Multi-Object Portion Tracking in 4D Fluorescence Microscopy Imagery with Deep Feature Maps

3D fluorescence microscopy of living organisms has increasingly become an essential and powerful tool in biomedical research and diagnosis. An exploding amount of imaging data has been collected, whereas efficient and effective computational tools to extract information from them are still lagging behind. This is largely due to the challenges in analyzing biological data. Interesting biological structures are not only small, but are often morphologically irregular and highly dynamic. Although tracking cells in live organisms has been studied for years, existing tracking methods for cells are not effective in tracking subcellular structures, such as protein complexes, which feature in continuous morphological changes including split and merge, in addition to fast migration and complex motion. In this paper, we first define the problem of multi-object portion tracking to model the protein object tracking process. A multi-object tracking method with portion matching is proposed based on 3D segmentation results. The proposed method distills deep feature maps from deep networks, then recognizes and matches object portions using an extended search. Experimental results confirm that the proposed method achieves 2.96% higher on consistent tracking accuracy and 35.48% higher on event identification accuracy than the state-of-art methods.

eess.IV↗

arXiv2019

Enhanced Electronic Transport in Disordered Hyperuniform Two-Dimensional Amorphous Silica

Disordered hyperuniformity (DHU) is a recently proposed new state of matter, which has been observed in a variety of classical and quantum many-body systems. DHU systems are characterized by vanishing infinite-wavelength density fluctuations and are endowed with unique novel physical properties. Here we report the first discovery of disordered hyperuniformity in atomic-scale 2D materials, i.e., amorphous silica composed of a single layer of atoms, based on spectral-density analysis of high-resolution transmission electron microscope images. Subsequent simulations suggest that the observed DHU is closely related to the strong topological and geometrical constraints induced by the local chemical order in the system. Moreover, we show via large-scale density functional theory calculations that DHU leads to almost complete closure of the electronic band gap compared to the crystalline counterpart, making the material effectively a metal. This is in contrast to the conventional wisdom that disorder generally diminishes electronic transport and is due to the unique electron wave localization induced by the topological defects in the DHU state.

cond-mat.dis-nn↗

arXiv2019

Modeling and Reconstructing Complex Heterogeneous Materials From Lower-Order Spatial Correlation Functions Encoding Topological and Interface Statistics

The versatile physical properties of heterogeneous materials are intimately related to their complex microstructures, which can be statistically characterized and modelled using various spatial correlation functions containing key structural features of the material's phases. An important related problem is to inversely reconstruct the material microstructure from limited morphological information contained in the correlation functions. Here, we present in details a generalized lattice-point (GLP) method based on the lattice-gas model of heterogeneous materials that efficiently computes a specific correlation function by updating the corresponding function associated with a slightly different microstructure. This allows one to incorporate the widest class of lower-order correlation functions utilized to date, including those encoding topological connectedness information and interface statistics, into the Yeong-Torquato stochastic reconstruction procedure, and thus enables one to obtain much more accurate renditions of virtual material microstructure, to determine the information content of various correlation functions and to select the most sensitive microstructural descriptors for the material of interest. The utility of our GLP method is illustrated by modelling and reconstructing a wide spectrum of random heterogeneous materials, including "clustered" RSA disks, a metal-ceramic composite, a two-dimensional slice of a Fontainebleau sandstone and a binary laser-speckle pattern, among other examples.

cond-mat.mtrl-sci↗

arXiv2019

Modeling cell migration regulated by cell-ECM micromechanical coupling

Cell migration in fibreous extracellular matrix (ECM) is crucial to many physiological and pathological processes such as tissue regeneration, immune response and cancer progression. During migration, individual cells can generate active pulling forces via actin filament contraction, which are transmitted to the ECM fibers through focal adhesion complexes, remodel the ECM, and eventually propagate to and can be sensed by other cells in the system. The microstructure and physical properties of the ECM can also significantly influence cell migration, e.g., via durotaxis and contact guidance. Here, we develop a computational model for cell migration regulated by cell-ECM micro-mechanical coupling. Our model explicitly takes into account a variety of cellular level processes including focal adhesion formation and disassembly, active traction force generation and cell locomotion due to actin filament contraction, transmission and propagation of tensile forces in the ECM, as well as the resulting ECM remodeling. We validate our model by accurately reproducing single-cell dynamics of MCF-10A breast cancer cells migrating on collagen gels and show that the durotaxis and contact guidance effects naturally arise as a consequence of the cell-ECM micro-mechanical interactions considered in the model. Moreover, our model predicts strongly correlated multi-cellular migration dynamics, which are resulted from the ECM-mediated mechanical coupling among the migrating cell and are subsequently verified in {\it in vitro} experiments using MCF-10A cells. Our computational model provides a robust tool to investigate emergent collective dynamics of multi-cellular systems in complex {\it in vivo} micro-environment and can be utilized to design {\it in vitro} micro-environments to guide collective behaviors and self-organization of cells.

q-bio.CB↗

arXiv2019

Inventory Routing Problem with Facility Location

We study problems that integrate depot location decisions along with the inventory routing problem of serving clients from these depots over time balancing the costs of routing vehicles from the depots with the holding costs of demand delivered before they are due. Since the inventory routing problem is already complex, we study the version that assumes that the daily vehicle routes are direct connections from the depot thus forming stars as solutions, and call this problem the Star Inventory Routing Problem with Facility Location (SIRPFL). As a stepping stone to solving SIRPFL, we first study the Inventory Access Problem (IAP), which is the single depot, single client special case of IRP. The Uncapacitated IAP is known to have a polynomial time dynamic program. We provide an NP-hardness reduction for Capacitated IAP where each demand cannot be split among different trips. We give a $3$-approximation for the case when demands can be split and a $6$-approximation for the unsplittable case. For Uncapacitated SIRPFL, we provide a $12$-approximation by rounding an LP relaxation. Combining the ideas from Capacitated IAP and Uncapacitated SIRPFL, we obtain a $24$-approximation for Capacitated Splittable SIRPFL and a $48$-approximation for the most general version, the Capacitated Unsplittable SIRPFL.

cs.DS↗

arXiv2019

Collective dynamics and self-organization of active particles on random networks

Collective cell migration in 3D extracellular matrix (ECM) is crucial to many physiological and pathological processes. Migrating cells can generate active pulling forces via actin filament contraction, which are transmitted to the ECM fibers and lead to a dynamically evolving force network in the system. Here, we elucidate the role of such force network in regulating collective cell behaviors using a minimal active-particle-on-network (APN) model, in which active particles can pull the fibers and hop between neighboring nodes of the network following local durotaxis. Our model reveals a dynamic transition as the particle number density approaches a critical value, from an "absorbing" state containing isolated stationary small particle clusters, to a "active" state containing a single large cluster undergone constant dynamic reorganization. This reorganization is dominated by a subset of highly dynamic "radical" particles in the cluster, whose number also exhibits a transition at the same critical density. The transition is underlaid by the percolation of "influence spheres" due to the particle pulling forces. Our results suggest a robust mechanism based on ECM-mediated mechanical coupling for collective cell behaviors in 3D ECM.

physics.bio-ph↗

arXiv2019

Modeling and simulation of nonlinear electro-thermo-mechanical continua with application to shape memory polymeric medical devices

Shape memory materials have gained considerable attention thanks to their ability to change physical properties when subjected to external stimuli such as temperature, pH, humidity, electromagnetic fields, etc. These materials are increasingly used for a large number of biomedical applications. For applications inside the human body, contactless control can be achieved by the addition of electric and/or magnetic particles that can react to electromagnetic fields, thus leading to a composite biomaterial. The difficulty of developing accurate numerical models for smart materials results from their multiscale nature and from the multiphysics coupling of involved phenomena. This coupling involves electromagnetic, thermal and mechanical problems. This paper contributes to the multiphysics modelling of a shape memory polymer material used as a medical stent. The stent is excited by electromagnetic fields produced by a coil which can be wrapped around a failing organ. In this paper we develop large deformation formulations for the coupled electro-thermo-mechanical problem using the electric potential to solve the electric problem. The formulations are then discretized and solved using the finite element method. Results are validated by comparison with results in the literature.

math.NA↗

arXiv2019

Collective ECM remodeling organizes 3D collective cancer invasion

Tumor metastasis, traditionally considered as random spreading of individual cancer cells, has been shown to also involve coordinated collective invasion in the tissue space. Here we demonstrate experimentally and computationally that physical interactions between cells and extracellular matrix (ECM) support coordinated dissemination of cells from tumor organoids. We find that collective remodeling of the ECM fibrous structure by cell-generated forces produces reciprocal cues to bias cell motility. As a result, dissemination of cells from tumor organoids are controlled by the organoid geometry. Our results indicate that mechanics and geometry are closely coupled in multicellular processes during metastasis and morphogenesis. This study also suggests that migrating cells in 3D ECM represent a distinct class of active particle system where the collective dynamics is governed by the micromechanical remodeling of the environment rather than direct particle-particle interactions.

physics.bio-ph↗

arXiv2018

Extent of Fock-exchange mixing for a hybrid van der Waals density functional?

The vdW-DF-cx0 exchange-correlation hybrid design has a truly nonlocal correlation component and aims to facilitate concurrent descriptions of both covalent and non-covalent molecular interactions. The vdW-DF-cx0 design mixes a fixed ratio, $a$, of Fock exchange into the consistent-exchange van der Waals density functional, vdW-DF-cx. The mixing value $a$ is sometimes taken as a semi-empirical parameter in hybrid formulations. Here, instead, we assert a plausible optimum average $a$ value for the vdW-DF-cx0 design from a formal analysis; A new, independent determination of the mixing $a$ is necessary since the Becke fit, yielding $a'=0.2$, is restricted to semilocal correlation and does not reflect non-covalent interactions. To proceed, we adapt the so-called two-legged hybrid construction to a starting point in the vdW-DF-cx functional. For our approach, termed vdW-DF-tlh, we estimate the properties of the adiabatic-connection specification of the exact exchange-correlation functional, by combining calculations of the Fock exchange and of the coupling-constant variation in vdW-DF-cx. We find that such vdW-DF-tlh hybrid constructions yield accurate characterizations of molecular. The accuracy motivates trust in the vdW-DF-tlh determination of system-specific values of the Fock-exchange mixing. We find that an average value $a'=0.2$ best characterizes the vdW-DF-tlh description of covalent and non-covalent interactions, although there exists some scatter. This finding suggests that the original Becke value, $a'=0.2$, also represents an optimal average Fock-exchange mixing for the new, truly nonlocal-correlation hybrids. To enable self-consistent calculations, we furthermore define and test a zero-parameter hybrid functional vdW-DF-cx0p (having fixed mixing $a'=0.2$) and document that this truly nonlocal correlation hybrid works for general molecular interactions.

physics.chem-ph↗

arXiv2018

Modeling Three-dimensional Invasive Solid Tumor Growth in Heterogeneous Microenvironment under Chemotherapy

A systematic understanding of the evolution and growth dynamics of invasive solid tumors in response to different chemotherapy strategies is crucial for the development of individually optimized oncotherapy. Here, we develop a hybrid three-dimensional (3D) computational model that integrates pharmacokinetic model, continuum diffusion-reaction model and discrete cell automaton model to investigate 3D invasive solid tumor growth in heterogeneous microenvironment under chemotherapy. Specifically, we consider the effects of heterogeneous environment on drug diffusion, tumor growth, invasion and the drug-tumor interaction on individual cell level. We employ the hybrid model to investigate the evolution and growth dynamics of avascular invasive solid tumors under different chemotherapy strategies. Our simulations reproduce the well-established observation that constant dosing is generally more effective in suppressing primary tumor growth than periodic dosing, due to the resulting continuous high drug concentration. In highly heterogeneous microenvironment, the malignancy of the tumor is significantly enhanced, leading to inefficiency of chemotherapies. The effects of geometrically-confined microenvironment and non-uniform drug dosing are also investigated. Our computational model, when supplemented with sufficient clinical data, could eventually lead to the development of efficient in silico tools for prognosis and treatment strategy optimization.

q-bio.TO↗

arXiv2018

Signatures of van der Waals binding: a coupling-constant scaling analysis

The van der Waals (vdW) density functional (vdW-DF) method [ROPP 78, 066501 (2015)] describes dispersion or vdW binding by tracking the effects of an electrodynamic coupling among pairs of electrons and their associated exchange-correlation holes. This is done in a nonlocal-correlation energy term $E_c^{nl}$, which permits density functional theory calculation in the Kohn-Sham scheme. However, to map the nature of vdW forces in the fully interacting materials system, it is necessary to compensate for associated kinetic-correlation energy effects. Here we present a coupling-constant scaling analysis that also permits us to compute the kinetic-correlation energy $T_c^{nl}$ that is specific to the vdW-DF account of nonlocal correlations. We thus provide a spatially-resolved analysis of the total nonlocal-correlation binding, including vdW forces, in both covalently and non-covalently bonded systems. We find that kinetic-correlation energy effects play a significant role in the account of vdW or dispersion interactions among molecules. We also find that the signatures that we reveal in our full-interaction mapping are typically given by the spatial variation in the $E_c^{nl}$ binding contributions, at least in a qualitative discussion. Furthermore, our full mapping shows that the total nonlocal-correlation binding is concentrated to pockets in the sparse electron distribution located between the material fragments.

cond-mat.str-el↗

arXiv2017

Approximation Algorithms for Replenishment Problems with Fixed Turnover Times

We introduce and study a class of optimization problems we coin replenishment problems with fixed turnover times: a very natural model that has received little attention in the literature. Nodes with capacity for storing a certain commodity are located at various places; at each node the commodity depletes within a certain time, the turnover time, which is constant but can vary between locations. Nodes should never run empty, and to prevent this we may schedule nodes for replenishment every day. The natural feature that makes this problem interesting is that we may schedule a replenishment (well) before a node becomes empty, but then the next replenishment will be due earlier also. This added workload needs to be balanced against the cost of routing vehicles to do the replenishments. In this paper, we focus on the aspect of minimizing routing costs. However, the framework of recurring tasks, in which the next job of a task must be done within a fixed amount of time after the previous one is much more general and gives an adequate model for many practical situations. Note that our problem has an infinite time horizon. However, it can be fully characterized by a compact input, containing only the location of each store and a turnover time. This makes determining its computational complexity highly challenging and indeed it remains essentially unresolved. We study the problem for two objectives: min-avg minimizes the average tour length and min-max minimizes the maximum tour length over all days. For min-max we derive a logarithmic factor approximation for the problem on general metrics and a 6-approximation for the problem on trees, for which we have a proof of NP-hardness. For min-avg we present a logarithmic approximation on general metrics, 2-approximation for trees, and a pseudopolynomial time algorithm for the line. Many intriguing problems remain open.

cs.DS↗