Rotating black holes at future colliders: Greybody factors for brane fields

We study theoretical aspects of the rotating black hole production and evaporation in the extra dimension scenarios with TeV scale gravity, within the mass range in which the higher dimensional Kerr solution provides good description. We evaluate the production cross section of black holes taking their angular momenta into account. We find that it becomes larger than the Schwarzschild radius squared, which is conventionally utilized in literature, and our result nicely agrees with the recent numerical study by Yoshino and Nambu within a few percent error for higher dimensional case. In the same approximation to obtain the above result, we find that the production cross section becomes larger for the black hole with larger angular momentum. Second, we derive the generalized Teukolsky equation for spin 0, 1/2 and 1 brane fields in the higher dimensional Kerr geometry and explicitly show that it is separable in any dimensions. For five-dimensional (Randall-Sundrum) black hole, we obtain analytic formulae for the greybody factors in low frequency expansion and we present the power spectra of the Hawking radiation as well as their angular dependence. Phenomenological implications of our result are briefly sketched.Comment: Typo in basic equation corrected; Following calculations and results unchange

Further developments in correlator product states: deterministic optimization and energy evaluation

Correlator product states (CPS) are a class of tensor network wavefunctions applicable to strongly correlated problems in arbitrary dimensions. Here, we present a method for optimizing and evaluating the energy of the CPS wavefunction that is non-variational but entirely deterministic. The fundamental assumption underlying our technique is that the CPS wavefunction is an exact eigenstate of the Hamiltonian, allowing the energy to be obtained approximately through a projection of the Schr\"odinger equation. The validity of this approximation is tested on two dimensional lattices for the spin-1/2 antiferromagnetic Heisenberg model, the spinless Hubbard model, and the full Hubbard model. In each of these models, the projected method reproduces the variational CPS energy to within 1%. For fermionic systems, we also demonstrate the incorporation of a Slater determinant reference into the ansatz, which allows CPS to act as a generalization of the Jastrow-Slater wavefunction.Comment: 8 pages, 2 tables, 3 figure

Cell-type phylogenetics and the origin of endometrial stromal cells

SummaryA challenge of genome annotation is the identification of genes performing specific biological functions. Here, we propose a phylogenetic approach that utilizes RNA-seq data to infer the historical relationships among cell types and to trace the pattern of gene-expression changes on the tree. The hypothesis is that gene-expression changes coincidental with the origin of a cell type will be important for the function of the derived cell type. We apply this approach to the endometrial stromal cells (ESCs), which are critical for the initiation and maintenance of pregnancy. Our approach identified well-known regulators of ESCs, PGR and FOXO1, as well as genes not yet implicated in female fertility, including GATA2 and TFAP2C. Knockdown analysis confirmed that they are essential for ESC differentiation. We conclude that phylogenetic analysis of cell transcriptomes is a powerful tool for discovery of genes performing cell-type-specific functions

Seeing many-body effects in single- and few-layer graphene: Observation of two-dimensional saddle-point excitons

Significant excitonic effects were observed in graphene by measuring its optical conductivity in a broad spectral range including the two-dimensional {\pi}-band saddle-point singularities in the electronic structure. The strong electron-hole interactions manifest themselves in an asymmetric resonance peaked at 4.62 eV, which is red-shifted by nearly 600 meV from the value predicted by ab-initio GW calculations for the band-to-band transitions. The observed excitonic resonance is explained within a phenomenological model as a Fano interference of a strongly coupled excitonic state and a band continuum. Our experiment also showed a weak dependence of the excitonic resonance in few-layer graphene on layer thickness. This result reflects the effective cancellation of the increasingly screened repulsive electron-electron (e-e) and attractive electron-hole (e-h) interactions.Comment: 9 pages, 3 figures, In PR

Novel Omega-3 Fatty Acid Epoxygenase Metabolite Reduces Kidney Fibrosis.

Cytochrome P450 (CYP) monooxygenases epoxidize the omega-3 polyunsaturated fatty acid (PUFA) docosahexaenoic acid into novel epoxydocosapentaenoic acids (EDPs) that have multiple biological actions. The present study determined the ability of the most abundant EDP regioisomer, 19,20-EDP to reduce kidney injury in an experimental unilateral ureteral obstruction (UUO) renal fibrosis mouse model. Mice with UUO developed kidney tubular injury and interstitial fibrosis. UUO mice had elevated kidney hydroxyproline content and five-times greater collagen positive fibrotic area than sham control mice. 19,20-EDP treatment to UUO mice for 10 days reduced renal fibrosis with a 40%-50% reduction in collagen positive area and hydroxyproline content. There was a six-fold increase in kidney α-smooth muscle actin (α-SMA) positive area in UUO mice compared to sham control mice, and 19,20-EDP treatment to UUO mice decreased α-SMA immunopositive area by 60%. UUO mice demonstrated renal epithelial-to-mesenchymal transition (EMT) with reduced expression of the epithelial marker E-cadherin and elevated expression of multiple mesenchymal markers (FSP-1, α-SMA, and desmin). Interestingly, 19,20-EDP treatment reduced renal EMT in UUO by decreasing mesenchymal and increasing epithelial marker expression. Overall, we demonstrate that a novel omega-3 fatty acid metabolite 19,20-EDP, prevents UUO-induced renal fibrosis in mice by reducing renal EMT

The dataset for validation of customer inspiration construct in Malaysian context

This study intended to validate customer inspiration (CI)in Malaysian/developing country context. Data were collected from two different respondents for two studies - from Millennial customers of the auto industry and Generation Z customers of the smartphone industry. The survey conducted through a standardized and structured questionnaire. The variables of the both studies were customer-defined market orientation (MO) (customer orientation, competitor orientation, and interfunctional coordination), CI (inspired-by and inspired-to), and customer loyalty (CL). This research strategy, in terms of quantity, is descriptive and correlational. Statistical analysis of the data was carried out, using ADANCO 2.0. The finding of the study suggests all results of data 1 and data 2 were significant, and CI mediates the sub-constructs of MO with CL

The role of electron-electron interactions in two-dimensional Dirac fermions

The role of electron-electron interactions on two-dimensional Dirac fermions remains enigmatic. Using a combination of nonperturbative numerical and analytical techniques that incorporate both the contact and long-range parts of the Coulomb interaction, we identify the two previously discussed regimes: a Gross-Neveu transition to a strongly correlated Mott insulator, and a semi-metallic state with a logarithmically diverging Fermi velocity accurately described by the random phase approximation. Most interestingly, experimental realizations of Dirac fermions span the crossover between these two regimes providing the physical mechanism that masks this velocity divergence. We explain several long-standing mysteries including why the observed Fermi velocity in graphene is consistently about 20 percent larger than the best values calculated using ab initio and why graphene on different substrates show different behavior.Comment: 11 pages, 4 figure

Enhancement of a CNN-Based Denoiser Based on Spatial and Spectral Analysis

Convolutional neural network (CNN)-based image denoising methods have been widely studied recently, because of their high-speed processing capability and good visual quality. However, most of the existing CNN-based denoisers learn the image prior from the spatial domain, and suffer from the problem of spatially variant noise, which limits their performance in real-world image denoising tasks. In this paper, we propose a discrete wavelet denoising CNN (WDnCNN), which restores images corrupted by various noise with a single model. Since most of the content or energy of natural images resides in the low-frequency spectrum, their transformed coefficients in the frequency domain are highly imbalanced. To address this issue, we present a band normalization module (BNM) to normalize the coefficients from different parts of the frequency spectrum. Moreover, we employ a band discriminative training (BDT) criterion to enhance the model regression. We evaluate the proposed WDnCNN, and compare it with other state-of-the-art denoisers. Experimental results show that WDnCNN achieves promising performance in both synthetic and real noise reduction, making it a potential solution to many practical image denoising applications.Comment: ICIP 201