A Comparison of Algorithms for Learning Hidden Variables in Normal Graphs

A Bayesian factor graph reduced to normal form consists in the interconnection of diverter units (or equal constraint units) and Single-Input/Single-Output (SISO) blocks. In this framework localized adaptation rules are explicitly derived from a constrained maximum likelihood (ML) formulation and from a minimum KL-divergence criterion using KKT conditions. The learning algorithms are compared with two other updating equations based on a Viterbi-like and on a variational approximation respectively. The performance of the various algorithm is verified on synthetic data sets for various architectures. The objective of this paper is to provide the programmer with explicit algorithms for rapid deployment of Bayesian graphs in the applications.Comment: Submitted for journal publicatio

Towards Building Deep Networks with Bayesian Factor Graphs

We propose a Multi-Layer Network based on the Bayesian framework of the Factor Graphs in Reduced Normal Form (FGrn) applied to a two-dimensional lattice. The Latent Variable Model (LVM) is the basic building block of a quadtree hierarchy built on top of a bottom layer of random variables that represent pixels of an image, a feature map, or more generally a collection of spatially distributed discrete variables. The multi-layer architecture implements a hierarchical data representation that, via belief propagation, can be used for learning and inference. Typical uses are pattern completion, correction and classification. The FGrn paradigm provides great flexibility and modularity and appears as a promising candidate for building deep networks: the system can be easily extended by introducing new and different (in cardinality and in type) variables. Prior knowledge, or supervised information, can be introduced at different scales. The FGrn paradigm provides a handy way for building all kinds of architectures by interconnecting only three types of units: Single Input Single Output (SISO) blocks, Sources and Replicators. The network is designed like a circuit diagram and the belief messages flow bidirectionally in the whole system. The learning algorithms operate only locally within each block. The framework is demonstrated in this paper in a three-layer structure applied to images extracted from a standard data set.Comment: Submitted for journal publicatio

Nodal network generator for CAVE3

A new extension of CAVE3 code was developed that automates the creation of a finite difference math model in digital form ready for input to the CAVE3 code. The new software, Nodal Network Generator, is broken into two segments. One segment generates the model geometry using a Tektronix Tablet Digitizer and the other generates the actual finite difference model and allows for graphic verification using Tektronix 4014 Graphic Scope. Use of the Nodal Network Generator is described

CAVE3: A general transient heat transfer computer code utilizing eigenvectors and eigenvalues

The method of solution is a hybrid analytical numerical technique which utilizes eigenvalues and eigenvectors. The method is inherently stable, permitting large time steps even with the best of conductors with the finest of mesh sizes which can provide a factor of five reduction in machine time compared to conventional explicit finite difference methods when structures with small time constants are analyzed over long time periods. This code will find utility in analyzing hypersonic missile and aircraft structures which fall naturally into this class. The code is a completely general one in that problems involving any geometry, boundary conditions and materials can be analyzed. This is made possible by requiring the user to establish the thermal network conductances between nodes. Dynamic storage allocation is used to minimize core storage requirements. This report is primarily a user's manual for CAVE3 code. Input and output formats are presented and explained. Sample problems are included which illustrate the usage of the code as well as establish the validity and accuracy of the method

Emotion Regulation and Parental Bonding in Families of Adolescents With Internalizing and Externalizing Symptoms

Parental bonding and emotional regulation, while important to explain difficulties that may arise in child development, have mainly been studied at an individual level. The present study aims to examine alexithymia and parental bonding in families of adolescents with psychiatric disorders through different generations. The sample included a total of 102 adolescent patients with psychiatric disorders and their parents. In order to take a family level approach, a Latent Class Analysis was used to identify the latent relationships among alexithymia (Toronto Alexithymia Scale), perceived parental bonding (Parental Bonding Instrument) and the presence of adolescent internalizing or externalizing psychiatric symptoms (Youth Self-Report). Families of internalizing and externalizing adolescents present different and specific patterns of emotional regulation and parenting. High levels of adolescent alexithymia, along with a neglectful parenting style perceived by the adolescent and the father as well, characterized the families of patients with internalizing symptoms. On the other hand, in the families with externalizing adolescents, it was mainly the mother to remember an affectionless control parental style. These results suggest the existence of an intergenerational transmission of specific parental bonding, which may influence the emotional regulation and therefore the manifestation of psychiatric symptoms

3-D Hand Pose Estimation from Kinect's Point Cloud Using Appearance Matching

We present a novel appearance-based approach for pose estimation of a human hand using the point clouds provided by the low-cost Microsoft Kinect sensor. Both the free-hand case, in which the hand is isolated from the surrounding environment, and the hand-object case, in which the different types of interactions are classified, have been considered. The hand-object case is clearly the most challenging task having to deal with multiple tracks. The approach proposed here belongs to the class of partial pose estimation where the estimated pose in a frame is used for the initialization of the next one. The pose estimation is obtained by applying a modified version of the Iterative Closest Point (ICP) algorithm to synthetic models to obtain the rigid transformation that aligns each model with respect to the input data. The proposed framework uses a "pure" point cloud as provided by the Kinect sensor without any other information such as RGB values or normal vector components. For this reason, the proposed method can also be applied to data obtained from other types of depth sensor, or RGB-D camera

The Human SLC25A33 and SLC25A36 Genes of Solute Carrier Family 25 Encode Two Mitochondrial Pyrimidine Nucleotide Transporters

The human genome encodes 53 members of the solute carrier family 25 (SLC25), also called the mitochondrial carrier family, many of which have been shown to transport inorganic anions, amino acids, carboxylates, nucleotides, and coenzymes across the inner mitochondrial membrane, thereby connecting cytosolic and matrix functions. Here two members of this family, SLC25A33 and SLC25A36, have been thoroughly characterized biochemically. These proteins were overexpressed in bacteria and reconstituted in phospholipid vesicles. Their transport properties and kinetic parameters demonstrate that SLC25A33 transports uracil, thymine, and cytosine (deoxy)nucleoside di- and triphosphates by an antiport mechanism and SLC25A36 cytosine and uracil (deoxy)nucleoside mono-, di-, and triphosphates by uniport and antiport. Both carriers also transported guanine but not adenine (deoxy)nucleotides. Transport catalyzed by both carriers was saturable and inhibited by mercurial compounds and other inhibitors of mitochondrial carriers to various degrees. In confirmation of their identity (i) SLC25A33 and SLC25A36 were found to be targeted to mitochondria and (ii) the phenotypes of Saccharomyces cerevisiae cells lacking RIM2, the gene encoding the well characterized yeast mitochondrial pyrimidine nucleotide carrier, were overcome by expressing SLC25A33 or SLC25A36 in these cells. The main physiological role of SLC25A33 and SLC25A36 is to import/export pyrimidine nucleotides into and from mitochondria, i.e. to accomplish transport steps essential for mitochondrial DNA and RNA synthesis and breakdown

The relationship between charge distribution, charge packet formation and electroluminescence in XLPE under DC

Different reports describing the internal distribution of space charge in cross-linked polyethylene (XLPE) under DC field have been published recently. The most striking fact observed is the organization of the space charge into charge packets that cross the insulation. All models for charge packet formation imply that carrier recombination will occur. As the recombination region is potentially a luminescence one it is of interest to record the electroluminescence in this regime. This topic is addressed in this paper