arXiv subjects

Bin Huang

Publications and source records attributed to Bin Huang.

At least 73 records · Page 4Linked to original sources

arXiv2020

Computational prediction of RNA tertiary structures using machine learning methods

RNAs play crucial and versatile roles in biological processes. Computational prediction approaches can help to understand RNA structures and their stabilizing factors, thus providing information on their functions, and facilitating the design of new RNAs. Machine learning (ML) techniques have made tremendous progress in many fields in the past few years. Although their usage in protein-related fields has a long history, the use of ML methods in predicting RNA tertiary structures is new and rare. Here, we review the recent advances of using ML methods on RNA structure predictions and discuss the advantages and limitation, the difficulties and potentials of these approaches when applied in the field.

physics.bio-ph↗

arXiv2020

Decoding the mechanisms underlying cell-fate decision-making during stem cell differentiation by Random Circuit Perturbation

Stem cells can precisely and robustly undergo cellular differentiation and lineage commitment, referred to as stemness. However, how the gene network underlying stemness regulation reliably specifies cell fates is not well understood. To address this question, we applied a recently developed computational method, Random Circuit Perturbation (RACIPE), to a nine-component gene regulatory network (GRN) governing stemness, from which we identified fifteen robust gene states. Among them, four out of the five most probable gene states exhibit gene expression patterns observed in single mouse embryonic cells at 32-cell and 64-cell stages. These gene states can be robustly predicted by the stemness GRN but not by randomized versions of the stemness GRN. Strikingly, we found a hierarchical structure of the GRN with the Oct4/Cdx2 motif functioning as the first decision-making module followed by Gata6/Nanog. We propose that stem cell populations, instead of being viewed as all having a specific cellular state, can be regarded as a heterogeneous mixture including cells in various states. Upon perturbations by external signals, stem cells lose the capacity to access certain cellular states, thereby becoming differentiated. The findings demonstrate that the functions of the stemness GRN is mainly determined by its well-evolved network topology rather than by detailed kinetic parameters.

q-bio.MN↗

arXiv2019

Large-time Behavior of Magnetohydrodynamics with Temperature-Dependent Heat-Conductivity

We study the large-time behavior of strong solutions to the equations of a planar magnetohydrodynamic compressible flow with the heat conductivity proportional to a nonnegative power of the temperature. Both the specific volume and the temperature are proved to be bounded from below and above independently of time. Moreover, it is shown that the global strong solution is nonlinearly exponentially stable as time tends to infinity. Our result can be regarded as a natural generalization of the previous ones for the compressible Navier-Stokes system to MHD system with either constant heat-conductivity or nonlinear and temperature-dependent heat-conductivity.

math.AP↗

arXiv2019

Review of Cost Reduction Methods in Photoacoustic Computed Tomography

Photoacoustic Computed Tomography (PACT) is a major configuration of photoacoustic imaging, a hybrid noninvasive modality for both functional and molecular imaging. PACT has rapidly gained importance in the field of biomedical imaging due to superior performance as compared to conventional optical imaging counterparts. However, the overall cost of developing a PACT system is one of the challenges towards clinical translation of this novel technique. The cost of a typical commercial PACT system originates from optical source, ultrasound detector, and data acquisition unit. With growing applications of photoacoustic imaging, there is a tremendous demand towards reducing its cost. In this review article, we have discussed various approaches to reduce the overall cost of a PACT system, and provided a cost estimation to build a low-cost PACT system.

physics.med-ph↗

arXiv2019

FoxNet: A Multi-face Alignment Method

Multi-face alignment aims to identify geometry structures of multiple faces in an image, and its performance is essential for the many practical tasks, such as face recognition, face tracking, and face animation. In this work, we present a fast bottom-up multi-face alignment approach, which can simultaneously localize multi-person facial landmarks with high precision.In more detail, our bottom-up architecture maps the landmarks to the high-dimensional space with which landmarks of all faces are represented. By clustering the features belonging to the same face, our approach can align the multi-person facial landmarks synchronously.Extensive experiments show that our method can achieve high performance in the multi-face landmark alignment task while our model is extremely fast. Moreover, we propose a new multi-face dataset to compare the speed and precision of bottom-up face alignment method with top-down methods. Our dataset is publicly available at https://github.com/AISAResearch/FoxNet

cs.CV↗

arXiv2019

The structural and electronic properties of Stone-Wales defective zigzag/armchair antimonene nanotubes: First-principles calculations

Geometric optimization and electronic properties of Stone-Wales defective antimonene nanotubes are calculated by the method of first -principle calculations based on density functional theory. Various nanotubes are investigated according to the possible orientations of zigzag/armchair nanostructures when Stone-Wales defects are formed. The band structures, partial density of states and atomic orbitals are calculated to reveal the mechanism of influence of Stone-Wales defects on antimonene nanotubes. When the structure of antimonene changes from monolayer to tube, the indirect gap semiconductor antimonene transforms to a direct gap one. Moreover, the character of direct band gap for the antimonene nanotube is preserved with the Stone-Wales defect forming, while the energy of conduction band bottoms change due to the intervene of the defect energy level in the band gaps. These results may provide valuable references to the development and design of novel nanotubes based on antimonene nanotubes.

cond-mat.mtrl-sci↗

arXiv2019

GPMatch: A Bayesian Doubly Robust Approach to Causal Inference with Gaussian Process Covariance Function As a Matching Tool

Gaussian process (GP) covariance function is proposed as a matching tool in GPMatch within a full Bayesian framework under relatively weaker causal assumptions. The matching is accomplished by utilizing GP prior covariance function to define matching distance. We show that GPMatch provides a doubly robust estimate of the averaged treatment effect (ATE) much like the G-estimation, the ATE is correctly estimated when either conditions are satisfied: 1) the GP mean function correctly specifies potential outcome $Y^{(0)}$; or 2) the GP covariance function correctly specifies matching structure. Simulation studies were carried out without assuming any known matching structure nor functional form of the outcomes. The results demonstrate that GPMatch enjoys well calibrated frequentist properties, and outperforms many widely used methods including Bayesian Additive Regression Trees. The case study compares effectiveness of early aggressive use of biological medication in treating children with newly diagnosed Juvenile Idiopathic Arthritis, using data extracted from electronic medical records.

stat.ME↗

arXiv2018

Global Strong Solutions to Magnetohydrodynamics with Density-Dependent Viscosity and Degenerate Heat-Conductivity

We deal with the equations of a planar magnetohydrodynamic compressible flow with the viscosity depending on the specific volume of the gas and the heat conductivity proportional to a positive power of the temperature. Under the same conditions on the initial data as those of the constant viscosity and heat conductivity case ([Kazhikhov (1987)], we obtain the global existence and uniqueness of strong solutions which means no shock wave, vacuum, or mass or heat concentration will be developed in finite time, although the motion of the flow has large oscillations and the interaction between the hydrodynamic and magnetodynamic effects is complex. Our result can be regarded as a natural generalization of the Kazhikhov's theory for the constant viscosity and heat conductivity case to that of nonlinear viscosity and degenerate heat-conductivity.

math.AP↗

arXiv2018

Global Strong Solutions to Compressible Navier-Stokes System with Degenerate Heat Conductivity and Density-Depending Viscosity

We consider the compressible Navier-Stokes system where the viscosity depends on density and the heat conductivity is proportional to a positive power of the temperature under stress-free and thermally insulated boundary conditions. Under the same conditions on the initial data as those of the constant viscosity and heat conductivity case ([Kazhikhov-Shelukhin. J. Appl. Math. Mech. 41 (1977)], we obtain the existence and uniqueness of global strong solutions. Our result can be regarded as a natural generalization of the Kazhikhov's theory for the constant heat conductivity case to the degenerate and nonlinear one under stress-free and thermally insulated boundary conditions.

math.AP↗

arXiv2018

Nonlinearly Exponential Stability of Compressible Navier-Stokes System with Degenerate Heat-Conductivity

We study the large-time behavior of strong solutions to the one-dimensional, compressible Navier-Stokes system for a viscous and heat conducting ideal polytropic gas, when the viscosity is constant and the heat conductivity is proportional to a positive power of the temperature. Both the specific volume and the temperature are proved to be bounded from below and above independently of time. Moreover, it is shown that the global solution is nonlinearly exponentially stable as time tends to infinity. Note that the conditions imposed on the initial data are the same as those of the constant heat conductivity case ([Kazhikhov-Shelukhin. J. Appl. Math. Mech. 41 (1977); Kazhikhov. Boundary Value Problems for Hydrodynamical Equations, 50 (1981)] and can be arbitrarily large. Therefore, our result can be regarded as a natural generalization of the Kazhikhov's ones for the constant heat conductivity case to the degenerate and nonlinear one.

math.AP↗

arXiv2018

Tuning electronic heat transport in graphene/metal heterostructures with ultralow thermal conductivity

Prior ultralow thermal conductivity materials are not suitable for thermoelectric applications due to the limited electronic transport in the materials. Here, we present a new class of ultralow thermal conductivity materials with substantial electronic heat transport. Our samples are graphene/metal heterostructures of transferred graphene and ultrathin metal films (Pd, Au and Ni) deposited by either thermal evaporation or rf magnetron sputtering. For the evaporated samples, we achieve an ultralow thermal conductivity of 0.06 W m-1 K-1, with phonons as the dominant heat carriers. The ultralow thermal conductivity is due to a huge disparity in phonon energy in graphene and metals. Interestingly, for the sputtered samples, we find that about 50 % of heat is carried by electrons, even when thermal conductivity is about 0.1 W m-1 K-1. We attribute the electronic contribution to transmission of electrons across atomic-scale pinholes in graphene. With the ultralow thermal conductivity and substantial electronic transport, the new materials could be explored for thermoelectric applications.

cond-mat.mtrl-sci↗

arXiv2018

Achieving huge thermal conductance of metallic nitride on graphene through enhanced elastic and inelastic phonon transmission

Low thermal conductance of metal contacts is one of the main challenges in thermal management of nanoscale devices of graphene and other 2D materials. Previous attempts to search for metal contacts with high thermal conductance yielded limited success due to incomplete understanding of the origins of the low thermal conductance. In this paper, we carefully study the intrinsic thermal conductance across metal/graphene/metal interfaces to identify the heat transport mechanisms across graphene interfaces. We find that unlike metal contacts on diamond, the intrinsic thermal conductance of most graphene interfaces (except Ti and TiNx) is only about 50 % of the phonon radiation limit, suggesting that heat is carried across graphene interfaces mainly through elastic transmission of phonons. We thus propose a convenient approach to substantially enhance the phononic heat transport across metal contacts on graphene, by better matching the energy of phonons in metals and graphene, e.g., using metallic nitrides. We test the idea with TiNx, with phonon frequencies of up to 1.18*10^14 rad/s, 47 % of the highest phonon frequencies in graphene of 2.51*10^14 rad/s . Interestingly, we obtain a huge thermal conductance of 270 MW m-2 K-1 for TiNx/graphene interfaces, which is about 140 % of the phonon radiation limit. The huge thermal conductance could be partially attributed to inelastic phonon transport across the TiNx/graphene interface. Our work provides guidance for the search for good metal contacts on 2D materials and devices.

physics.app-ph↗

arXiv2017

Atomistic simulation of the Coupled adsorption and unfolding of protein GB1 on the polystyrenes nanoparticle surface

Protein adsorption/desorption upon nanoparticle surfaces is an important process to understand for developing new nanotechnology involving biomaterials, while atomistic picture of the process and its coupling with protein conformational change is lacking. Here we report our study on the adsorption of protein GB1 upon a polystyrene nanoparticle surface using atomistic molecular dynamic simulations. Enabled by metadynamics, we explored the relevant phase space and identified three protein states; each protein state involved both the adsorbed and desorbed states. We also studied the change of secondary and tertiary structures of GB1 during adsorption, and the dominant interactions between protein and surface in different adsorbing stages. From the simulation results we obtained a scenario that is more rational and complete than the conventional one. We believe the new scenario is more appropriate as a theoretical model in understanding and explaining experimental signals. Introduction

physics.bio-ph↗

arXiv2017

Negligible electronic contribution to heat transfer across intrinsic metal/graphene interfaces

Despite the importance of high thermal conductance (i.e. low thermal resistance) of metal contacts to thermal management of graphene devices, prior reported thermal conductance of metal/graphene interfaces are all relatively low, only 20-40 MW m$^{-2}$ K$^{-1}$. One possible route to improve the thermal conductance ($G$) of metal/graphene interfaces is through additional heat conduction by electrons, since graphene can be easily doped by metals. In this paper, we evaluate the electronic heat conduction across metal/graphene interfaces by measuring the thermal conductance of Pd/transferred graphene (trG)/Pd interfaces, prepared by either thermal evaporation or radio-frequency (rf) magnetron sputtering, over a wide temperature range of 80 to 500 K. We find that for the samples prepared by thermal evaporation, the thermal conductance of Pd/trG/Pd is 42 MW m$^{-2}$ K$^{-1}$. The thermal conductance only weakly depends on temperature, which suggests that heat is predominantly carried by phonons across the intrinsic Pd/graphene interface. However, for Pd/trG/Pd samples with the top Pd films deposited by rf magnetron sputtering, we observe a significant increment of thermal conductance from the intrinsic value of 42 MW m$^{-2}$ K$^{-1}$ to 300 MW m$^{-2}$ K$^{-1}$, and $G$ is roughly proportional to $T$. We attribute the enhancement of thermal conductance to an additional channel of heat transport by electrons via atomic-scale pinholes formed in the graphene during the sputtering process. We thus conclude that electrons play a negligible role in heat conduction across intrinsic interfaces of metal and pristine graphene, and the contribution of electrons is only substantial if graphene is damaged.

cond-mat.mes-hall↗

arXiv2017

Distinguishing Mechanisms Underlying EMT Tristability

Background: The Epithelial-Mesenchymal Transition (EMT) endows epithelial-looking cells with enhanced migratory ability during embryonic development and tissue repair. EMT can also be co-opted by cancer cells to acquire metastatic potential and drug-resistance. Recent research has argued that epithelial (E) cells can undergo either a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype that typically displays collective migration, or a complete EMT to adopt a mesenchymal (M) phenotype that shows individual migration. The core EMT regulatory network - miR-34/SNAIL/miR-200/ZEB1 - has been identified by various studies, but how this network regulates the transitions among the E, E/M, and M phenotypes remains controversial. Two major mathematical models - ternary chimera switch (TCS) and cascading bistable switches (CBS) - that both focus on the miR-34/SNAIL/miR-200/ZEB1 network, have been proposed to elucidate the EMT dynamics, but a detailed analysis of how well either or both of these two models can capture recent experimental observations about EMT dynamics remains to be done. Results: Here, via an integrated experimental and theoretical approach, we first show that both these two models can be used to understand the two-step transition of EMT - E-E/M-M, the different responses of SNAIL and ZEB1 to exogenous TGF-b and the irreversibility of complete EMT. Next, we present new experimental results that tend to discriminate between these two models. We show that ZEB1 is present at intermediate levels in the hybrid E/M H1975 cells, and that in HMLE cells, overexpression of SNAIL is not sufficient to initiate EMT in the absence of ZEB1 and FOXC2. Conclusions: These experimental results argue in favor of the TCS model proposing that miR-200/ZEB1 behaves as a three-way decision-making switch enabling transitions among the E, hybrid E/M and M phenotypes.

q-bio.CB↗

arXiv2016

Role of remote interfacial phonon (RIP) scattering in heat transport across graphene/SiO2 interfaces

Heat transfer across interfaces of graphene and polar dielectrics (e.g. SiO2) could be mediated by direct phonon coupling, as well as electronic coupling with remote interfacial phonons (RIPs). To understand the relative contribution of each component, we develop a new pump-probe technique, called voltage-modulated thermoreflectance (VMTR), to accurately measure the change of interfacial thermal conductance under an electrostatic field. We employed VMTR on top gates of graphene field-effect transistors and find that the thermal conductance of SiO2/graphene/SiO2 interfaces increases by up to ΔG=0.8 MW m-2 K-1 under electrostatic fields of <0.2 V nm-1 . We propose two possible explanations for the observed ΔG. First, since the applied electrostatic field induces charge carriers in graphene, our VMTR measurements could originate from heat transfer between the charge carriers in graphene and RIPs in SiO2. Second, the increase in heat conduction could be caused by better conformity of graphene interfaces un-der electrostatic pressure exerted by the induced charge carriers. Regardless of the origins of the observed ΔG, our VMTR measurements establish an upper limit for heat transfer from unbiased graphene to SiO2 substrates via RIP scattering; i.e., only <2 % of the interfacial heat transport is facilitated by RIP scattering even at a carrier concentration of 4x10^12 cm-2.

cond-mat.mes-hall↗

arXiv2016

Accurate Measurements of Cross-plane Thermal Conductivity of Thin Films by Dual-Frequency Time-Domain Thermoreflectance (TDTR)

Accurate measurements of the cross-plane thermal conductivity Λ_cross of a high-thermal-conductivity thin film on a low-thermal-conductivity (Λ_s) substrate (e.g., Λ_cross/Λ_s>20) are challenging, due to the low thermal resistance of the thin film compared to that of the substrate. In principle, Λ_cross could be measured by time-domain thermoreflectance (TDTR), using a high modulation frequency f_h and a large laser spot size. However, with one TDTR measurement at f_h, the uncertainty of the TDTR measurement is usually high due to low sensitivity of TDTR signals to Λ_cross and high sensitivity to the thickness h_Al of Al transducer deposited on the sample for TDTR measurements. We observe that in most TDTR measurements, the sensitivity to h_Al only depends weakly on the modulation frequency f. Thus, we performed an additional TDTR measurement at a low modulation frequency f_0, such that the sensitivity to h_Al is comparable but the sensitivity to Λcross is near zero. We then analyze the ratio of the TDTR signals at f_h to that at f_0, and thus significantly improve the accuracy of our Λcross measurements. As a demonstration of the dual-frequency approach, we measured the cross-plane thermal conductivity of a 400-nm-thick nickel-iron alloy film and a 3-μm-thick Cu film, both with an accuracy of ~10%. The dual-frequency TDTR approach is useful for future studies of thin films.

cond-mat.mtrl-sci↗

arXiv2016

Modeling delayed processes in biological systems

Delayed processes are ubiquitous in biological systems and are often characterized by delay differential equations (DDEs) and their extension to include stochastic effects. DDEs do not explicitly incorporate intermediate states associated with a delayed process but instead use an estimated average delay time. In an effort to examine the validity of this approach, we study systems with significant delays by explicitly incorporating intermediate steps. We show by that such explicit models often yield significantly different equilibrium distributions and transition times as compared to DDEs with deterministic delay values. Additionally, different explicit models with qualitatively different dynamics can give rise to the same DDEs revealing important ambiguities. We also show that DDE-based predictions of oscillatory behavior may fail for the corresponding explicit model.

q-bio.QM↗