High-dimensional Ising model selection using ℓ1{\ell_1}-regularized logistic regression

We consider the problem of estimating the graph associated with a binary Ising Markov random field. We describe a method based on $\ell_1$-regularized logistic regression, in which the neighborhood of any given node is estimated by performing logistic regression subject to an $\ell_1$-constraint. The method is analyzed under high-dimensional scaling in which both the number of nodes $p$ and maximum neighborhood size $d$ are allowed to grow as a function of the number of observations $n$. Our main results provide sufficient conditions on the triple $(n,p,d)$ and the model parameters for the method to succeed in consistently estimating the neighborhood of every node in the graph simultaneously. With coherence conditions imposed on the population Fisher information matrix, we prove that consistent neighborhood selection can be obtained for sample sizes $n=\Omega(d^3\log p)$ with exponentially decaying error. When these same conditions are imposed directly on the sample matrices, we show that a reduced sample size of $n=\Omega(d^2\log p)$ suffices for the method to estimate neighborhoods consistently. Although this paper focuses on the binary graphical models, we indicate how a generalization of the method of the paper would apply to general discrete Markov random fields.Comment: Published in at http://dx.doi.org/10.1214/09-AOS691 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Inducing Features of Random Fields

We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing the Kullback-Leibler divergence between the model and the empirical distribution of the training data. A greedy algorithm determines how features are incrementally added to the field and an iterative scaling algorithm is used to estimate the optimal values of the weights. The statistical modeling techniques introduced in this paper differ from those common to much of the natural language processing literature since there is no probabilistic finite state or push-down automaton on which the model is built. Our approach also differs from the techniques common to the computer vision literature in that the underlying random fields are non-Markovian and have a large number of parameters that must be estimated. Relations to other learning approaches including decision trees and Boltzmann machines are given. As a demonstration of the method, we describe its application to the problem of automatic word classification in natural language processing. Key words: random field, Kullback-Leibler divergence, iterative scaling, divergence geometry, maximum entropy, EM algorithm, statistical learning, clustering, word morphology, natural language processingComment: 34 pages, compressed postscrip

Infrared spectra of van de Waals complexes of importance in planetary atmospheres

It has been suggested that (CO2)2 and Ar-CO2 are important constituents of the planetary atmospheres of Venus and Mars. Recent results on the laboratory spectroscopy of CO2 containing van der Waals complexes which may be of use in the modeling of the spectra of planetary atmospheres are presented. Sub-Doppler infrared spectra were obtained for (CO2)2, (CO2)3, and rare-gas-CO2 complexes in the vicinity of the CO2 Fermi diad at 2.7 micrometers using a color-center-laser optothermal spectrometer. From the spectroscopic constants the geometries of the complexes have been determined and van der Waals vibrational frequencies have been estimated. The equilibrium configurations are C2h, C3h, and C2v, for (CO2)2, (CO2)3, and the rare-gas-CO2 complexes, respectively. Most of the homogeneous linewidths for the revibrational transitions range from 0.5 to 22 MHz, indicating that predissociation is as much as four orders of magnitude faster than radiative processes for vibrational relaxation in these complexes

Does Maternal Methadone Dose Correlate with Severity of Intrauterine Growth Restriction in Infants with Neonatal Abstinence Syndrome?

Introduction : Previous studies demonstrate a relationship between maternal opioid use during pregnancy and smaller head circumference of infants with neonatal abstinence syndrome (NAS). The goal of this study is to correlate maternal methadone dose and severity of growth restriction in infants with NAS admitted to the neonatal intensive care unit (NICU). Methods: This is a retrospective analysis of infants (≥35 weeks gestation) exposed to in utero methadone, born between August 2006 and May 2018, and admitted to a Philadelphia NICU for medical therapy for NAS. Growth parameters (birth weight, birth length, and birth head circumference) were compared between infants exposed various doses of methadone. The groups were compared using ANOVA, Post-Hoc Tukey, Chi-square and extended Fisher exact tests. Results: A total of 686 infants met the study criteria; 109 in the High dose group, 359 in the Intermediate dose group, and 218 in the Low dose group. There was no significant difference in the use of other drugs or smoking during the pregnancy. Infants exposed to higher doses of methadone displayed significantly smaller head circumferences and lengths at birth. The mean birth weight was similar between the three groups. Discussion: There may be a danger in prescribing high doses of methadone to pregnant mothers, as they may hinder the growth of the infant. We need to conduct more studies investigating how low head circumference and length affect long term developmental outcomes. These findings may help guide physicians toward the optimum dose of methadone for mothers

Study of hot-cathode magnetron ion gauge

Hot cathode magnetron ion gaug

Performance and selection of winter durum wheat genotypes in different European conventional and organic fields

Sustainability is a key factor for the future of agriculture. Productivity in agriculture has more than tripled in developed countries since the 1950s. Beyond the success of plant breeding, the increased use of inorganic fertilizers, application of pesticides, and spread of irrigation also contributed to this success. However, impressive yield increases started to decline in the 1980s because of the lack of sustainability. One of the most beneficial ways to increase sustainability is organic agriculture. In such agro-ecosystem-based holistic production systems the prerequisite of successful farming is the availability of crop genotypes that perform well. However, selection of winter durum wheat for sub-optimal growing conditions is still mainly neglected, and the organic seed market also lacks of information on credibly tested winter durum varieties suitable for organic agriculture

To Balloon or Not to Balloon, The Current State of Management of Eustachian Tube Dysfunction.

While otologic complaints are a common reason for patients to present to an otolaryngologist, Eustachian tube dysfunction (ETD) remains a poorly understood disease whose management is unclear. Among the general population in the United States, ETD has a prevalence of 4.6% among adults and 6.1% among children. Eustachian tube dysfunction is not just a common diagnosis for otolaryngologists, ETD accounted for 2 million visits for patients less than 20 years old to primary care providers and over 2 million visits for patients older than 20 years old between 2005 and 2012. Despite the commonality of ETD, opinions differ wildly among otolaryngologist on the management of these patients

A feasibility study of limb volume measuring systems

Evaluation of the various techniques by which limb volume can be measured indicates that the odometric (electromechanical) method and the reflective scanner (optical) have a high probability of meeting the specifications of the LBNP experiments. Both of these methods provide segmental measurements from which the cross sectional area of the limb can be determined