arXiv subjects

Jin Yang

Publications and source records attributed to Jin Yang.

123 records · Page 7Linked to original sources

arXiv2018

Three-Leaf Dart-Shaped Single-Crystal BN Formation Promoted by Surface Oxygen

Two-dimensional hexagonal boron nitride (h-BN) single crystals with various shapes have been synthesized by chemical vapor deposition over the past several years. Here we report the formation of three-leaf dart (3LD)-shaped single crystals of h-BN on Cu foil by atmospheric-pressure chemical vapor deposition. The leaves of the 3LD-shaped h-BN are as long as 18 μm and their edges are smooth armchair on one side and stepped armchair on the other. Careful analysis revealed that surface oxygen plays an important role in the formation of the 3LD shape. Oxygen suppressed h-BN nucleation by passivating Cu surface active sites and lowered the edge attachment energy, which caused the growth kinetics to change to a diffusion-controlled mode.

cond-mat.mtrl-sci↗

arXiv2016

SYSTRAN's Pure Neural Machine Translation Systems

Since the first online demonstration of Neural Machine Translation (NMT) by LISA, NMT development has recently moved from laboratory to production systems as demonstrated by several entities announcing roll-out of NMT engines to replace their existing technologies. NMT systems have a large number of training configurations and the training process of such systems is usually very long, often a few weeks, so role of experimentation is critical and important to share. In this work, we present our approach to production-ready systems simultaneously with release of online demonstrators covering a large variety of languages (12 languages, for 32 language pairs). We explore different practical choices: an efficient and evolutive open-source framework; data preparation; network architecture; additional implemented features; tuning for production; etc. We discuss about evaluation methodology, present our first findings and we finally outline further work. Our ultimate goal is to share our expertise to build competitive production systems for "generic" translation. We aim at contributing to set up a collaborative framework to speed-up adoption of the technology, foster further research efforts and enable the delivery and adoption to/by industry of use-case specific engines integrated in real production workflows. Mastering of the technology would allow us to build translation engines suited for particular needs, outperforming current simplest/uniform systems.

cs.CL↗

arXiv2014

Modeling Epidermis Homeostasis and Psoriasis Pathogenesis

We present a computational model to study the spatiotemporal dynamics of the epidermis homeostasis under normal and pathological conditions. The model consists of a population kinetics model of the central transition pathway of keratinocyte proliferation, differentiation and loss and an agent-based model that propagates cell movements and generates the stratified epidermis. The model recapitulates observed homeostatic cell density distribution, the epidermal turnover time and the multilayered tissue structure. We extend the model to study the onset, recurrence and phototherapy-induced remission of psoriasis. The model considers the psoriasis as a parallel homeostasis of normal and psoriatic keratinocytes originated from a shared stem-cell niche environment and predicts two homeostatic modes of the psoriasis: a disease mode and a quiescent mode. Interconversion between the two modes can be controlled by interactions between psoriatic stem cells and the immune system and by the normal and psoriatic stem cells competing for growth niches. The prediction of a quiescent state potentially explains the efficacy of the multi-episode UVB irradiation therapy and recurrence of psoriasis plaques, which can further guide designs of therapeutics that specifically target the immune system and/or the keratinocytes.

q-bio.MN↗

arXiv2014

Production of trilobite Rydberg molecule dimers with thousand-Debye permanent electric dipole moments

We observe that when an ultracold ground state cesium (Cs) atom becomes bound within the electronic cloud of an extended Cs electronic orbit, ultralong-range molecules with giant (kilo-Debye) permanent electric dipole moments form. Large molecular permanent electric dipole moments are challenging to experimentally realize. Meeting this challenge has garnered significant interest because permanent electric dipole moments are important for understanding symmetry breaking in molecular physics, control of chemical reactions and realization of strongly correlated many-body quantum systems. These new hybrid class of `trilobite' molecules are predominated with degenerate Rydberg manifolds, making them difficult to produce with conventional optical association. Their behavior is quantitatively reproduced with detailed coupled-channel calculations.

physics.atom-ph↗

arXiv2013

The Myogenic Response in Isolated Rat Cerebrovascular Arteries: Smooth Muscle Cell Model

Previous models of the cerebrovascular smooth muscle cell have not addressed the interaction between the electrical, chemical and mechanical components of cell function during the development of active tension. These models are primarily electrical, biochemical or mechanical in their orientation, and do not permit a full exploration of how the smooth muscle responds to electrical or mechanical forcing. To address this issue, we have developed a new model that consists of two major components: electrochemical and chemomechanical subsystems of the cell. Included in the electrochemical model are models of the electrophysiological behavior of the cell membrane, fluid compartments, Ca2+ release and uptake by the sarcoplasmic reticulum, and cytosolic Ca2+ buffering, particularly by calmodulin. With this subsystem model, we can study the mechanics of the production of intracellular Ca2+ transient in response to membrane voltage clamp pulses. The chemomechanical model includes models of: (a) the chemical kinetics of myosin phosphorylation, and the formation of phosphorylated myosin cross-bridges with actin, as well as, attached latch-type cross-bridges; and (b) a model of force generation and mechanical coupling to the contractile filaments and their attachments to protein structures and the skeletal framework of the cell. The two subsystem models are tested independently and compared with data. Likewise, the complete (combined) cell model responses to voltage pulse stimulation under isometric and isotonic conditions are calculated and compared with measured single cell length-force and force-velocity data obtained from literature. This integrated cell model provides biophysically-based explanations of electrical, chemical and mechanical phenomena in cerebrovascular smooth muscle, and has considerable utility as an adjunct to laboratory research and experimental design.

q-bio.CB↗

arXiv2013

Chemical sensing by cell-surface chemoreceptor arrays: the roles of receptor cooperativity and adaptation

Most sensory cells use cross-membrane chemoreceptors to detect chemical signals in the environment. The biochemical properties and spatial organization of chemoreceptors play important roles in achieving and maintaining sensitivity and accuracy of chemical sensing. Here we investigate the effects of receptor cooperativity and adaptation on the limits of gradient sensing. We study a single cell with aggregated chemoreceptor arrays on the cell surface and derive general formula to the limits for gradient sensing from the uncertainty of instantaneous receptor activity. In comparison to independent receptors, we find that cooperativity by non-adaptative receptors could significantly lower the sensing limit in a chemical concentration range determined by the biochemical properties of ligand-receptor binding and ligand-induced receptor activity. Cooperativity by adaptative receptors are beneficial to gradient sensing within a broad range of background concentrations. Our results also show that isotropic receptor aggregate layout on the cell surface represents an optimal configuration to gradient sensing.

q-bio.CB↗

arXiv2012

Origins of concentration dependence of waiting times for single-molecule fluorescence binding

Binary fluorescence time series obtained from single-molecule imaging experiments can be used to infer protein binding kinetics, in particular, association and dissociation rate constants from waiting time statistics of fluorescence intensity changes. In many cases, rate constants inferred from fluorescence time series exhibit nonintuitive dependence on ligand concentration. Here we examine several possible mechanistic and technical origins that may induce ligand dependence of rate constants. Using aggregated Markov models, we show under the condition of detailed balance that non-fluorescent bindings and missed events due to transient interactions, instead of conformation fluctuations, may underly the dependence of waiting times and thus apparent rate constants on ligand concentrations. In general, waiting times are rational functions of ligand concentration. The shape of concentration dependence is qualitatively affected by the number of binding sites in the single molecule and is quantitatively tuned by model parameters. We also show that ligand dependence can be caused by non-equilibrium conditions which result in violations of detailed balance and require an energy source. As to a different but significant mechanism, we examine the effect of ambient buffers that can substantially reduce the effective concentration of ligands that interact with the single molecules. To demonstrate the effects by these mechanisms, we applied our results to analyze the concentration dependence in a single-molecule experiment EGFR binding to fluorophore-labeled adaptor protein Grb2 by Morimatsu et al. (PNAS,104:18013,2007).

q-bio.QM↗

arXiv2011

Monte Carlo Algorithm for Simulating Reversible Aggregation of Multisite Particles

We present an efficient and exact Monte Carlo algorithm to simulate reversible aggregation of particles with dedicated binding sites. This method introduces a novel data structure of dynamic bond tree to record clusters and sequences of bond formations. The algorithm achieves a constant time cost for processing cluster association and a cost between $\mathcal{O}(\log M)$ and $\mathcal{O}(M)$ for processing bond dissociation in clusters with $M$ bonds. The algorithm is statistically exact and can reproduce results obtained by the standard method. We applied the method to simulate a trivalent ligand and a bivalent receptor clustering system and obtained an average scaling of $\mathcal{O}(M^{0.45})$ for processing bond dissociation in acyclic aggregation, compared to a linear scaling with the cluster size in standard methods. The algorithm also demands substantially less memory than the conventional method.

q-bio.QM↗

arXiv2011

Scaffold-mediated Nucleation of Protein Signaling Complexes: Elementary Principles

Proteins with multiple binding sites play important roles in cell signaling systems by nucleating protein complexes in which, for example, enzymes and substrates are co-localized. Proteins that specialize in this function are called by a variety names, including adapter, linker and scaffold. Scaffold-mediated nucleation of protein complexes can be either constitutive or induced. Induced nucleation is commonly mediated by a docking site on a scaffold that is activated by phosphorylation. Here, by considering minimalist mathematical models, which recapitulate scaffold effects seen in more mechanistically detailed models, we obtain analytical and numerical results that provide insights into scaffold function. These results elucidate how recruitment of a pair of ligands to a scaffold depends on the concentrations of the ligands, on the binding constants for ligand-scaffold interactions, on binding cooperativity, and on the milieu of the scaffold, as ligand recruitment is affected by competitive ligands and decoy receptors. For the case of a bivalent scaffold, we obtain an expression for the unique scaffold concentration that maximally recruits a pair of monovalent ligands. Through simulations, we demonstrate that a bivalent scaffold can nucleate distinct sets of ligands to equivalent extents when the scaffold is present at different concentrations. Thus, the function of a scaffold can potentially change qualitatively with a change in copy number. We also demonstrate how a scaffold can change the catalytic efficiency of an enzyme and the sensitivity of the rate of reaction to substrate concentration. The results presented here should be useful for understanding scaffold function and for engineering scaffolds to have desired properties.

q-bio.MN↗

arXiv2011

Energy efficient prediction clustering algorithm for multilevel heterogeneous wireless sensor networks

In designing wireless sensor networks, it is important to reduce energy dissipation and prolong network lifetime. In this paper, a new model with energy and monitored objects heterogeneity is proposed for heterogeneous wireless sensor networks. We put forward an energy-efficient prediction clustering algorithm, which is adaptive to the heterogeneous model. This algorithm enables the nodes to select the cluster head according to factors such as energy and communication cost, thus the nodes with higher residual energy have higher probability to become a cluster head than those with lower residual energy, so that the network energy can be dissipated uniformly. In order to reduce energy consumption when broadcasting in clustering phase and prolong network lifetime, an energy consumption prediction model is established for regular data acquisition nodes. Simulation results show that compared with current clustering algorithms, this algorithm can achieve longer sensor network lifetime, higher energy efficiency and superior network monitoring quality.

cs.NI↗

arXiv2010

Rule-based Modeling and Simulation of Biochemical Systems with Molecular Finite Automata

We propose a theoretical formalism, molecular finite automata (MFA), to describe individual proteins as rule-based computing machines. The MFA formalism provides a framework for modeling individual protein behaviors and systems-level dynamics via construction of programmable and executable machines. Models specified within this formalism explicitly represent the context-sensitive dynamics of individual proteins driven by external inputs and represent protein-protein interactions as synchronized machine reconfigurations. Both deterministic and stochastic simulations can be applied to quantitatively compute the dynamics of MFA models. We apply the MFA formalism to model and simulate a simple example of a signal transduction system that involves a MAP kinase cascade and a scaffold protein.

q-bio.QM↗

arXiv2010

A Non-Cooperative Method for Path Loss Estimation in Femtocell Networks

A macrocell superposed by indoor deployed femtocells forms a geography-overlapped and spectrum-shared two tier network, which can efficiently improve coverage and enhance system capacity. It is important for reducing inter-tier co-channel interference that any femtocell user (FU) can select suitable access channel according to the path losses between itself and the macrocell users (MUs). Path loss should be estimated non-cooperatively since information exchange is difficult between macrocell and femtocells. In this paper, a novel method is proposed for FU to estimate the path loss between itself and any MU independently. According to the adaptive modulation and coding (AMC) mode information broadcasted by the macrocell base station (BS), FU first estimates the path loss between BS and a MU by using Maximum a Posteriori (MAP) method. The probability distribution function (PDF) and statistics of the transmission power of the MU is then derived. According to the sequence of received powers from the MU, FU estimates the path loss between itself and the MU by using minimum mean square error (MMSE) method. Simulation results show that the proposed method can efficiently estimate the path loss between any FU and any MU in all kinds of conditions.

cs.NI↗

arXiv2010

Rejection-free kinetic Monte Carlo simulation of multivalent biomolecular interactions

The system-level dynamics of multivalent biomolecular interactions can be simulated using a rule-based kinetic Monte Carlo method in which a rejection sampling strategy is used to generate reaction events. This method becomes inefficient when simulating aggregation processes with large biomolecular complexes. Here, we present a rejection-free method for determining the kinetics of multivalent biomolecular interactions, and we apply the method to simulate simple models for ligand-receptor interactions. Simulation results show that performance of the rejection-free method is equal to or better than that of the rejection method over wide parameter ranges, and the rejection-free method is more efficient for simulating systems in which aggregation is extensive. The rejection-free method reported here should be useful for simulating a variety of systems in which multisite molecular interactions yield large molecular aggregates.

q-bio.QM↗

arXiv2008

Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena.

q-bio.QM↗

arXiv1999

On the time evolution of the entropic index

We adapt the Kolmogorov-Sinai entropy to the non-extensive perspective recently advocated by Tsallis. The resulting expression is an average on the invariant distribution, which should be used to detect the genuine entropic index Q. We argue that the condition Q >1 is time dependent.

cond-mat↗