Charged-particle multiplicity density at midrapidity in central Pb-Pb collisions at sqrt[S(NN)] = 2.76 TeV

The first measurement of the charged-particle multiplicity density at midrapidity in Pb-Pb collisions at a center-of-mass energy per nucleon pair √ S NN = 2.76 TeV is presented. For an event sample corresponding to the most central 5% of the hadronic cross section, the pseudorapidity density of primary charged particles at midrapidity is 1584 ± 4(stat) ± 76(syst), which corresponds to 8.3 ± 0.4(syst) per participating nucleon pair. This represents an increase of about a factor 1.9 relative to pp collisions at similar collision energies, and about a factor 2.2 to central Au-Au collisions at √ S NN = 2.76 TeV. This measurement provides the first experimental constraint for models of nucleus-nucleus collisions at LHC energies.     

Elliptic flow of charged particles in Pb-Pb collisions at sqrt[S(NN)] = 2.76 TeV

We report the first measurement of charged particle elliptic flow in Pb-Pb collisions at sqrt[S(NN)] =2.76 TeV with the ALICE detector at the CERN Large Hadron Collider. The measurement is performed in the central pseudorapidity region (|η|<0.8) and transverse momentum range 0.2

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Fabrication and comparison of PMN-PT single crystal, PZT and PZT-based 1-3 composite ultrasonic transducers for NDE applications

This paper describes fabrication and comparison of PMN-PT single crystal, PZT, and PZT-based 1-3 composite ultrasonic transducers for NDE applications. As a front matching layer between test material (Austenite stainless steel, SUS316) and piezoelectric materials, alumina ceramics was selected. The appropriate acoustic impedance of the backing materials for each transducer was determined based on the results of KLM model simulation. Prototype ultrasonic transducers with the center frequencies of approximately 2.25 and 5 MHz for contact measurement were fabricated and compared to each other. The PMN-PT single crystal ultrasonic transducer shows considerably improved performance in sensitivity over the PZT and PZT-based 1-3 composite ultrasonic transducers.     

Generalized Hénon Mappings and Foliation by Injective Brody Curves

We consider a finite composition of generalized Hénon mappings \({\mathfrak {f}}:{\mathbb {C}}^2\rightarrow {\mathbb {C}}^2\) and its Green function \({\mathfrak {g}}^+:{\mathbb {C}}^2\rightarrow {\mathbb {R}}_{\ge 0}\) (see Sect. 2). It is well known that each level set \(\{{\mathfrak {g}}^+=c\}\) for \(c>0\) is foliated by biholomorphic images of \({\mathbb {C}}\) and each leaf is dense. In this paper, we prove that each leaf is actually an injective Brody curve in \(\mathbb {P}^2\) (see Sect. 4). We also study the behavior of the level sets of \({\mathfrak {g}}^+\) near infinity.     

Fuzzy delayed output feedback synchronization for time-delayed chaotic systems

In this paper, we propose a new fuzzy delayed output feedback synchronization (FDOFS) method for time-delayed chaotic systems. Based on Lyapunov–Krasovskii theory, T–S fuzzy model, and delayed feedback control scheme, the FDOFS controller is designed and an analytic expression of the controller is shown. The proposed controller can guarantee asymptotical synchronization of both drive and response systems. The FDOFS controller can be obtained by solving the linear matrix inequality (LMI) problem. A numerical example for time-delayed Lorenz system is presented to demonstrate the validity of the proposed FDOFS method.     

Using Gd-EOB-DTPA-enhanced 3-T MRI for the differentiation of infiltrative hepatocellular carcinoma and focal confluent fibrosis in liver cirrhosis

Purpose

The purpose of the study was to determine significant imaging features to differentiate between infiltrative hepatocellular carcinoma (HCC) and confluent fibrosis (CF) in liver cirrhosis using Gd-EOB-DTPA-enhanced 3-T magnetic resonance imaging.

Material and methods

Nineteen infiltrative HCCs and eight CFs were included. We evaluated the difference in imaging findings and apparent diffusion coefficient (ADC) between the two entities. We compared T2-weighted image (WI) and hepatobiliary phase (HBP) in terms of the clarity of the lesion outer margin.

Results

Seventeen infiltrative HCCs showed lobulated margin, while focal CFs showed either straight (n = 3) or irregular margins (n = 5) (P = .001). All infiltrative HCCs had intact or bulging contours, and all focal CFs showed capsular retraction (P = .001). Fourteen infiltrative HCCs and two focal CFs showed arterial enhancement (P = .035). The ADC of infiltrative HCCs was significantly lower than that of CFs (P = .001). Satellite nodules were noted in 10 infiltrative HCCs. In terms of outer margin clarity, infiltrative HCCs showed a more distinct margin on HBP than on T2-WI (P = .005), while these two sequences were not significantly different in focal CFs (P = 1.000).

Conclusion

HBP improved the imaging characteristics of infiltrative HCC, allowing it to be distinguished from focal CF. Infiltrative HCC showed lower ADC values than focal CF. Lobular configuration, contour bulging, enhancement pattern, associated satellite nodules and portal vein thrombosis were still found to be highly suggestive MR findings for infiltrative HCC.     

Manipulation of light at the nanoscale for high-performance spectroscopic and optical applications

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Penalized Orthogonal Iteration for Sparse Estimation of Generalized Eigenvalue Problem

We propose a new algorithm for sparse estimation of eigenvectors in generalized eigenvalue problems (GEPs). The GEP arises in a number of modern data-analytic situations and statistical methods, including principal component analysis (PCA), multiclass linear discriminant analysis (LDA), canonical correlation analysis (CCA), sufficient dimension reduction (SDR), and invariant co-ordinate selection. We propose to modify the standard generalized orthogonal iteration with a sparsity-inducing penalty for the eigenvectors. To achieve this goal, we generalize the equation-solving step of orthogonal iteration to a penalized convex optimization problem. The resulting algorithm, called penalized orthogonal iteration, provides accurate estimation of the true eigenspace, when it is sparse. Also proposed is a computationally more efficient alternative, which works well for PCA and LDA problems. Numerical studies reveal that the proposed algorithms are competitive, and that our tuning procedure works well. We demonstrate applications of the proposed algorithm to obtain sparse estimates for PCA, multiclass LDA, CCA, and SDR. Supplementary materials for this article are available online.