We analyze a sample of galaxies chosen to have F 24 μm > 0.5 mJy and satisfy a certain IRAC color criterion. Infrared Spectrograph (IRS) spectra yield redshifts, spectral types, and polycyclic aromatic hydrocarbons (PAH) luminosities, to which we add broadband photometry from optical through IRAC wavelengths, MIPS from 24-160 μm, 1.1 mm, and radio at 1.4 GHz. Stellar population modeling and IRS spectra together demonstrate that the double criteria used to select this sample have efficiently isolated massive star-forming galaxies at z ∼ 1.9. This is the first starburst (SB)-dominated ultraluminous infrared galaxies (ULIRG) sample at high redshift with total infrared luminosity measured directly from FIR and millimeter photometry, and as such gives us the first accurate view of broadband spectral energy distributions for SB galaxies at extremely high luminosity and at all wavelengths. Similar broadband data are assembled for three other galaxy samples-local SB galaxies, local active galactic nucleus (AGN)/ULIRGs, and a second 24 μm-luminous z ∼ 2 sample dominated by AGN. L PAH /L IR for the new z ∼ 2 SB sample is the highest ever seen, some three times higher than in local SBs, whereas in AGNs this ratio is depressed below the SB trend, often severely. Several pieces of evidence imply that AGNs exist in this SBdominated sample, except two of which even host very strong AGN, while they still have very strong PAH emission. The Advanced Camera for Surveys images show that most objects have very extended morphologies in the restframe ultraviolet band, thus extended distribution of PAH molecules. Such an extended distribution prevents further destruction PAH molecules by central AGNs. We conclude that objects in this sample are ULIRGs powered mainly by SB; and the total infrared luminosity density contributed by this type of objects is 0.9-2.6 × 10 7 L Mpc −3 .

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A total of 2,718 bp of DNA fragment was amplified from the C-KCE strain of duck enteritis virus (DEV) genome using thermal asymmetric interlaced PCR. This newly identified viral DNA fragment contained two non-overlapping open reading frames (ORFs) oriented from the 5' to 3' direction. The first ORF was comprised of 43.5% G + C and contained the full-length genomic sequence of the UL44 gene (1,296 bp) encoding 431 amino acid residues of DEV glycoprotein C (gC). The second ORF encoded a partial peptide of the UL43 gene. The sequences of DNA and deduced amino acids of the DEV gC gene shared high homology with other members of known herpesviruses, supporting the classification of DEV. Phylogenetic analysis of the DEV gC gene revealed that the gC gene had a close evolutionary relationship with the subfamily of Alphaherpesvirinae.

We present infrared galaxy luminosity functions (LFs) in the AKARI North Ecliptic Pole (NEP) deep field using recently-obtained, wider CFHT optical/near-IR images. AKARI has obtained deep images in the mid-infrared (IR), covering 0.6 deg 2 of the NEP deep field. However, our previous work was limited to the central area of 0.25 deg 2 due to the lack of optical coverage of the full AKARI NEP survey. To rectify the situation, we recently obtained CFHT optical and near-IR images over the entire AKARI NEP deep field. These new CFHT images are used to derive accurate photometric redshifts, allowing us to fully exploit the whole AKARI NEP deep field.AKARI's deep, continuous filter coverage in the mid-IR wavelengths (2.4, 3.2, 4.1, 7, 9, 11, 15, 18, and 24µm) exists nowhere else, due to filter gaps of other space telescopes. It allows us to estimate restframe 8µm and 12µm luminosities without using a large extrapolation based on spectral energy distribution (SED) fitting, which was the largest uncertainty in previous studies. Total infrared luminosity (TIR) is also obtained more reliably due to the superior filter coverage. The resulting restframe 8µm, 12µm, and TIR LFs at 0.15 < z < 2.2 are consistent with previous works, but with reduced uncertainties, especially at the high luminosity-end, thanks to the wide field coverage. In terms of cosmic infrared luminosity density (Ω IR ), we found that the Ω IR evolves as ∝ (1 + z) 4.2±0.4 .

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This paper proposes a method to diagnose the open-circuit faulty phases and faulty points of the six-phase permanent magnet synchronous motor (PMSM) drive circuit. The current sensor is used to obtain the six-phase current signal, and the least mean square error (LMS) adaptive filtering algorithm is used to filter out the vibration and noise. Empirical Mode Decomposition (EMD) is performed on the filtered current signals, and the EMD energy entropy of each phase current signal is calculated. The change of energy entropy can simplify the double-bridge arm open-circuit fault to the single-bridge arm opencircuit fault, which reduces the number of fault characteristics. After the faulty phase is judged by the change of energy entropy, the fault diagnosis system can diagnose the specific faulty point according to the normalized average value of each phase current signal. Finally, the current data of normal state and fault state are used to train the support vector machine (SVM) and classify the fault state. Each type of fault can be accurately diagnosed by substituting experimental data into the SVM. Experimental results prove that the proposed method can accurately diagnose the open-circuit faults of the six-phase PMSM drive system. INDEX TERMS Six-phase permanent magnet synchronous motor, open-circuit fault, empirical mode decomposition, energy entropy, support vector machine.