A Constrained L1 Minimization Approach to Sparse Precision Matrix Estimation

A constrained L1 minimization method is proposed for estimating a sparse inverse covariance matrix based on a sample of $n$ iid $p$-variate random variables. The resulting estimator is shown to enjoy a number of desirable properties. In particular, it is shown that the rate of convergence between the estimator and the true $s$-sparse precision matrix under the spectral norm is $s\sqrt{\log p/n}$ when the population distribution has either exponential-type tails or polynomial-type tails. Convergence rates under the elementwise $L_{\infty}$ norm and Frobenius norm are also presented. In addition, graphical model selection is considered. The procedure is easily implementable by linear programming. Numerical performance of the estimator is investigated using both simulated and real data. In particular, the procedure is applied to analyze a breast cancer dataset. The procedure performs favorably in comparison to existing methods.Comment: To appear in Journal of the American Statistical Associatio

Graphical Nonbinary Quantum Error-Correcting Codes

In this paper, based on the nonbinary graph state, we present a systematic way of constructing good non-binary quantum codes, both additive and nonadditive, for systems with integer dimensions. With the help of computer search, which results in many interesting codes including some nonadditive codes meeting the Singleton bounds, we are able to construct explicitly four families of optimal codes, namely, $[[6,2,3]]_p$, $[[7,3,3]]_p$, $[[8,2,4]]_p$ and $[[8,4,3]]_p$ for any odd dimension $p$ and a family of nonadditive code $((5,p,3))_p$ for arbitrary $p>3$. In the case of composite numbers as dimensions, we also construct a family of stabilizer codes $((6,2\cdot p^2,3))_{2p}$ for odd $p$, whose coding subspace is {\em not} of a dimension that is a power of the dimension of the physical subsystem.Comment: 12 pages, 5 figures (pdf

Estimating Sparse Precision Matrix: Optimal Rates of Convergence and Adaptive Estimation

Precision matrix is of significant importance in a wide range of applications in multivariate analysis. This paper considers adaptive minimax estimation of sparse precision matrices in the high dimensional setting. Optimal rates of convergence are established for a range of matrix norm losses. A fully data driven estimator based on adaptive constrained ℓ1 minimization is proposed and its rate of convergence is obtained over a collection of parameter spaces. The estimator, called ACLIME, is easy to implement and performs well numerically. A major step in establishing the minimax rate of convergence is the derivation of a rate-sharp lower bound. A “two-directional” lower bound technique is applied to obtain the minimax lower bound. The upper and lower bounds together yield the optimal rates of convergence for sparse precision matrix estimation and show that the ACLIME estimator is adaptively minimax rate optimal for a collection of parameter spaces and a range of matrix norm losses simultaneously

Greenberger-Horne-Zeilinger paradoxes from qudit graph states

One fascinating way of revealing the quantum nonlocality is the all-versus-nothing test due to Greenberger, Horne, and Zeilinger (GHZ) known as GHZ paradox. So far genuine multipartite and multilevel GHZ paradoxes are known to exist only in systems containing an odd number of particles. Here we shall construct GHZ paradoxes for an arbitrary number (greater than 3) of particles with the help of qudit graph states on a special kind of graphs, called as GHZ graphs. Based on the GHZ paradox arising from a GHZ graph, we derive a Bell inequality with two $d$-outcome observables for each observer, whose maximal violation attained by the corresponding graph state, and a Kochen-Specker inequality testing the quantum contextuality in a state-independent fashion

Doping effects on the electronic and structural properties of CoO2: An LSDA+U study

A systematic LSDA+U study of doping effects on the electronic and structural properties of single layer CoO2 is presented. Undoped CoO2 is a charge transfer insulator within LSDA+U and a metal with a high density of states (DOS) at the Fermi level within LSDA. (CoO2)$^{1.0-}$, on the other hand, is a band insulator with a gap of 2.2 eV. Systems with fractional doping are metals if no charge orderings are present. Due to the strong interaction between the doped electron and other correlated Co d electrons, the calculated electronic structure of (CoO2)$^{x-}$ depends sensitively on the doping level x. Zone center optical phonon energies are calculated under the frozen phonon approximation and are in good agreement with measured values. Softening of the $E_g$ phonon at doping x ~0.25 seems to indicate a strong electron-phonon coupling in this system. Possible intemediate spin states of Co ions, Na ordering, as well as magnetic and charge orderings in this system are also discussed.Comment: 11 pages, 12 figure

Modeling of the meteorological balloon-cube with LoRabased ground station

Every day 80,000 weather balloons are launched to the Earth's upper atmosphere with meteorology payloads to provide accurate meteorological data. Meteorological data could be used for airport stations and weather stations. Meanwhile, there are many remote sensing satellites above the Earth’s atmosphere, but balloons are still essential due to increased weather prediction accuracy. Many balloons launch into the atmosphere daily, but it would be a one trip tripe because this balloon goes to the atmosphere then transmits the meteorological data to the ground segment, and that is all no one looks to recycle it, on the other hand, if the balloon could be recycled there would be many financial benefits. This project presents a high altitude meteorological balloon-Cube relative to measuring atmosphere humidity, temperature, air pressure, and a photography payload for surface imaging that ascended up to 20Km altitude Cube reach this altitude will eject box on the ground. The telemetry data are transmitted to the ground station through two communication applications, first using a LoRa based transceiver at which it receives a command from the LoRa ground station and the second one, and payload transmits the data by an SMS in 5min after it lands on the ground. Therefore, it could be recycled. This paper presents a Cube-Balloon fabrication and flight test information to acknowledge this Cube's feasibility for real meteorological projects

Glutamate prevents intestinal atrophy via luminal nutrient sensing in a mouse model of total parenteral nutrition

Small intestine luminal nutrient sensing may be crucial for modulating physiological functions. However, its mechanism of action is incompletely understood. We used a model of enteral nutrient deprivation, or total parenteral nutrition (TPN), resulting in intestinal mucosal atrophy and decreased epithelial barrier function (EBF). We examined how a single amino acid, glutamate (GLM), modulates intestinal epithelial cell (IEC) growth and EBF. Controls were chow‐fed mice, T1 receptor‐3 (T1R3)‐knockout (KO) mice, and treatment with the metabotropic glutamate receptor (mGluR)‐5 antagonist MTEP. TPN significantly changed the amount of T1Rs, GLM receptors, and transporters, and GLM prevented these changes. GLM significantly prevented TPN‐associated intestinal atrophy (2.5‐fold increase in IEC proliferation) and was dependent on up‐regulation of the protein kinase pAkt, but independent of T1R3 and mGluR5 signaling. GLM led to a loss of EBF with TPN (60% increase in FITC‐dextran permeability, 40% decline in transepithelial resistance); via T1R3, it protected EBF, whereas mGluR5 was associated with EBF loss. GLM led to a decline in circulating glucagon‐like peptide 2 (GLP‐2) during TPN. The decline was regulated by T1R3 and mGluR5, suggesting a novel negative regulator pathway for IEC proliferation not previously described. Loss of luminal nutrients with TPN administration may widely affect intestinal taste sensing. GLM has previously unrecognized actions on IEC growth and EBF. Restoring luminal sensing via GLM could be a strategy for patients on TPN.—Xiao, W., Feng, Y., Holst, J. J., Hartmann, B., Yang, H., Teitelbaum, D. H. Glutamate prevents intestinal atrophy via luminal nutrient sensing in a mouse model of total parenteral nutrition. FASEB J. 28, 2073–2087 (2014). www.fasebj.orgPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154477/1/fsb2fj13238311.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154477/2/fsb2fj13238311-sup-0001.pd

Decreased lung function with mediation of blood parameters linked to e-waste lead and cadmium exposure in preschool children

Blood lead (Pb) and cadmium (Cd) levels have been associated with lower lung function in adults and smokers, but whether this also holds for children from electronic waste (e-waste) recycling areas is still unknown. To investigate the contribution of blood heavy metals and lung function levels, and the relationship among living area, the blood parameter levels, and the lung function levels, a total of 206 preschool children from Guiyu (exposed area), and Haojiang and Xiashan (reference areas) were recruited and required to undergo blood tests and lung function tests during the study period. Preschool children living in e-waste exposed areas were found to have a 1.37 mu g/dL increase in blood Pb, 1.18 mu g/L. increase in blood Cd, and a 41.00 x 10(9)/L increase in platelet counts, while having a 2.82 decrease in hemoglobin, 92 mL decrease in FVC and 86 mL decrease in FEV1. Each unit of hemoglobin (1 g/L) decline was associated with 5 mL decrease in FVC and 4 mL decrease in FEV1. We conclude that children living in e-waste exposed area have higher levels of blood Pb, Cd and platelets, and lower levels of hemoglobin and lung function. Hemoglobin can be a good predictor for lung function levels. (C) 2017 Elsevier Ltd. All rights reserved.</p

Prediction and analysis of fabric-evoked prickle properties of different textile woven fabrics using Artificial Neural Networks method

This paper aims to discuss the design and development of an Artificial Neural&nbsp;Networks (ANNs) model to understand a human perception of the tactile prickliness properties of textile wear fabric materials, and create an objective system to express those prickle perceptions in terms of measurable mechanical properties. The objective and also subjective hand measurement of the textile materials used for wear fabric has been check up on with consideration given the aspects of both dermatitis and comfort. In this study, attempt to predict the prickliness (itchiness) of wear fabric by their physical properties using a back-propagation network and a stepwise regression. Handle properties of fabrics were measured by universal test equipment (KES-F) and total prickle-score (TPS) values of the wear fabrics were determined by a group of panelists consisting of some textile experts. The optimum construction of neural network was investigated through the change of layer and neuron number. The results showed that the back-propagation network could predict the (TPS) values of wear fabric with a meaningful difference. These wear fabrics were used to show that the results of neural network were in good agreement with subjective test results