Global analysis of dynamical decision-making models through local computation around the hidden saddle

Bistable dynamical switches are frequently encountered in mathematical modeling of biological systems because binary decisions are at the core of many cellular processes. Bistable switches present two stable steady-states, each of them corresponding to a distinct decision. In response to a transient signal, the system can flip back and forth between these two stable steady-states, switching between both decisions. Understanding which parameters and states affect this switch between stable states may shed light on the mechanisms underlying the decision-making process. Yet, answering such a question involves analyzing the global dynamical (i.e., transient) behavior of a nonlinear, possibly high dimensional model. In this paper, we show how a local analysis at a particular equilibrium point of bistable systems is highly relevant to understand the global properties of the switching system. The local analysis is performed at the saddle point, an often disregarded equilibrium point of bistable models but which is shown to be a key ruler of the decision-making process. Results are illustrated on three previously published models of biological switches: two models of apoptosis, the programmed cell death and one model of long-term potentiation, a phenomenon underlying synaptic plasticity. © 2012 Trotta et al.

Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering

Semi-supervised clustering is the task of clustering data points into clusters where only a fraction of the points are labelled. The true number of clusters in the data is often unknown and most models require this parameter as an input. Dirichlet process mixture models are appealing as they can infer the number of clusters from the data. However, these models do not deal with high dimensional data well and can encounter difficulties in inference. We present a novel nonparameteric Bayesian kernel based method to cluster data points without the need to prespecify the number of clusters or to model complicated densities from which data points are assumed to be generated from. The key insight is to use determinants of submatrices of a kernel matrix as a measure of how close together a set of points are. We explore some theoretical properties of the model and derive a natural Gibbs based algorithm with MCMC hyperparameter learning. The model is implemented on a variety of synthetic and real world data sets.

Decision making at the front end of innovation: The hidden influence of knowledge and decision criteria

Decision making at the front end of innovation is critical for the success of companies. This paper presents a method, called decision making based on knowledge (DeBK), which was created to analyze the decision-making process at the front end. The method evaluates the knowledge of project information and the importance of decision criteria, compiling a measure that indicates whether decisions are founded on available knowledge and what criteria are in fact being considered to delineate them. The potential contribution of DeBK is corroborated through two projects that faced decision-making issues at the front end of innovation. © 2014 RADMA and John Wiley & Sons Ltd.

Delayed-decision making in noisy bistable switches

Bistable switches are frequently encountered in biological systems. Typically, a bistable switch models a binary decision where each decision corresponds to one of the two stable equilibria. Recently, we showed that the global decision-making process in bistable switches strongly depends on a particular equilibrium point of these systems, their saddle point. In particular, we showed that a saddle point with a time-scale separation between its attractive and repulsive directions can delay the decision-making process. In this paper, we study the effects of white Gaussian noise on this mechanism of delayed decision-making induced by the saddle point. Results show that the mean decision-time strongly depends on the balance between the initial distance to the separatrix and the noise strength. © IFAC.

Bayesian inference and learning in Gaussian process state-space models with Particle MCMC

State-space models are successfully used in many areas of science, engineering and economics to model time series and dynamical systems. We present a fully Bayesian approach to inference and learning (i.e. state estimation and system identification) in nonlinear nonparametric state-space models. We place a Gaussian process prior over the state transition dynamics, resulting in a flexible model able to capture complex dynamical phenomena. To enable efficient inference, we marginalize over the transition dynamics function and, instead, infer directly the joint smoothing distribution using specially tailored Particle Markov Chain Monte Carlo samplers. Once a sample from the smoothing distribution is computed, the state transition predictive distribution can be formulated analytically. Our approach preserves the full nonparametric expressivity of the model and can make use of sparse Gaussian processes to greatly reduce computational complexity.

Compact Reconfigurable Binary-Decision-Diagram Logic Circuit on a GaAs Nanowire Network

We describe a reconfigurable binary-decision-diagram logic circuit based on Shannon's expansion of Boolean logic function and its graphical representation on a semiconductor nanowire network. The circuit is reconfigured by using programmable switches that electrically connect and disconnect a small number of branches. This circuit has a compact structure with a small number of devices compared with the conventional look-up table architecture. A variable Boolean logic circuit was fabricated on an etched GaAs nanowire network having hexagonal topology with Schottky wrap gates and SiN-based programmable switches, and its correct logic operation together with dynamic reconfiguration was demonstrated.

Realization of extremely broadband quantum-dot superluminescent light-emitting diodes by rapid thermal-annealing process

The first demonstration, to our knowledge, of the creation of ultrabroadband superluminescent light-emitting diodes using multiple quantum-dot layer structure by rapid thermal-annealing process is reported. The device exhibits a 3 dB emission bandwidth of 146 nm centered at 984 mm with cw output power as high as 15 mW at room temperature corresponding to an extremely small coherence length of 6.6 mu m. (C) 2008 Optical Society of America.

Optimizing the GaAs capping layer growth of 1.3 mu m InAs/GaAs quantum dots by a combined two-temperature and annealing process at low temperatures

We report on optimizing the GaAs capping layer growth of 1.3 mu m InAs quantum dots (QDs) by a combined two-temperature and annealing process at low temperatures using metalorganic chemical vapor deposition. The initial part (tnm) of the capping layer is deposited at a low temperature of 500 degrees C, which is the same for the growth of both the QDs and a 5-nm-thick In0.15Ga0.85As strain-reducing capping layer on the QDs, while the remaining part is grown at a higher temperature of 560 degrees C after a rapid temperature rise and subsequent annealing period at this temperature. The capping layer is deposited at the low temperatures (<= 560 degrees C) to avoid postgrowth annealing effect that can blueshift the emission wavelength of the QDs. We demonstrate the existence of an optimum t (=5 nm) and a critical annealing time (>= 450s) during the capping, resulting in significantly enhanced photoluminescence from the QDs. This significant enhancement in photoluminescence is attributed to a dramatic reduction of defects due to the optimized capping growth. The technique reported here has important implications for realizing stacked 1.3 mu m InAs/GaAs QD lasers. (C) 2008 Elsevier B.V. All rights reserved.

Enhancement of the spectral width of high-power 1.5 mu m integrated superluminescent light source by quantum well intermixing process

A novel type of integrated InGaAsP superluminescent light source was fabricated based on the tilted ridge-waveguide structure with selective-area quantum well (QW) intermixing. The bandgap structure along the length of the device was modified by impurity free vacancy diffusion QW intermixing, The spectral width was broadened from the 16 nm of the normal devices to 37 nm of the QW intermixing enhanced devices at the same output power level. High superluminescent power (210 mW) was obtained under pulsed conditions with a spectral width of 37 nm.

1.55 mu m spot-size converter with monolithically integrated laser diode by conventional process

A novel 1.55 mum laser diode (LD) with monolithically integrated spot-size converter (SSC) is designed and fabricated using conventional photolithography and the chemical wet etching process. For the laser diode, a ridge double-core structure is employed. For the spot-size converter, a buried double-waveguide structure is incorporated. The laterally tapered active core is designed and optically combined with the thin passive core to control the size of the mode. The threshold current was measured to be 40 mA together with high slope efficiency of 0.35 W A(-1). The beam divergence angles in the horizontal and vertical directions were as small as 14.9degrees and 18.2degrees, respectively.

As-doped p-type ZnO films by sputtering and thermal diffusion process

As-doped p-type ZnO films were grown on GaAs by sputtering and thermal diffusion process. Hall effect measurements showed that the as-grown films were of n-type conductivity and they were converted to p-type behavior after thermal annealing. Moreover, the hole concentration of As-doped p-type ZnO was very impressible to the oxygen ambient applied during the annealing process. In addition, the bonding state of As in the films was investigated by x-ray photoelectron spectroscopy. This study not only demonstrated an effective method for reliable and reproducible p-type ZnO fabrication but also helped to understand the doping mechanism of As-doped ZnO. (c) 2006 American Institute of Physics.

Preparation and AFM characterization of self-ordered porous alumina films on semi-insulated gaas substrate

Self-ordered porous alumina films on a semi-insulated GaAs substrate were prepared in oxalic acid aqueous solutions by three-step anodization. The I-t curve of anodization process was recorded to observe time effects of anodization. Atomic force microscopy was used to investigate structure and morphology of alumina films. It was revealed that the case of oxalic acid resulted in a self-ordered porous structure, with the pore diameters of 60-70 nm, the pore density of the order of about 10(10) pore cm(-2), and interpore distances of 95-100nm. At the same time the pore size and shape change with the pore widening time. Field-enhanced dissolution model and theory of deformation relaxation combined were brought forward to be the cause of self-ordered pore structure according to I-t curve of anodization and structure characteristics of porous alumina films. (c) 2006 Elsevier Ltd. All rights reserved.

Investigation of a chemically treated InP(100) surface during hydrophilic wafer bonding process

Surface micro-roughness, surface chemical properties, and surface wettability are three important aspects of wafer surfaces during a wafer cleaning process, which determine the bonding quality of ordinary direct wafer bonding. In this study, InP wafers are divided into four groups and treated by different chemical processes. Subsequently, the characteristics of the treated InP surfaces are carefully studied by X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), and contact angle measurements. The optimal wafer treatment method for wafer bonding is determined by comparing the results of the processes as a whole. This optimization is later evaluated by a scanning electronic microscope (SEM), and the ridge waveguide 1.55 mu m Si-based InP/InGaAsP multi-quantum-well laser chips are also fabricated. (c) 2005 Elsevier B.V. All rights reserved.

Fabrication process and power and lifetime characteristics of very-small-aperture laser

High output power very-small-aperture laser has been created on 650 nm edge emitting laser diodes. The far-field output power is 0.4 mW at the 25 mA driving current, and the highest output power exceeds 1 mW. The special fabrication process is described and the failure mechanism leading to the short lifetime of the devices is discussed.

Measurement of gain spectrum for Fabry-Perot semiconductor lasers by the Fourier transform method with a deconvolution process

To improve the accuracy of measured gain spectra, which is usually limited by the resolution of the optical spectrum analyzer (OSA), a deconvolution process based on the measured spectrum of a narrow linewidth semiconductor laser is applied in the Fourier transform method. The numerical simulation shows that practical gain spectra can be resumed by the Fourier transform method with the deconvolution process. Taking the OSA resolution to be 0.06, 0.1, and 0.2 nm, the gain-reflectivity product spectra with the difference of about 2% are obtained for a 1550-nm semiconductor laser with the cavity length of 720 pm. The spectra obtained by the Fourier transform method without the deconvolution process and the Hakki-Paoli method are presented and compared. The simulation also shows that the Fourier transform method has less sensitivity to noise than the Hakki-Paoli method.