On the images of Sobolev spaces under the heat kernel transform on the Heisenberg group

The aim of this paper is to obtain certain characterizations for the image of a Sobolev space on the Heisenberg group under the heat kernel transform. We give three types of characterizations for the image of a Sobolev space of positive order H-m (H-n), m is an element of N-n, under the heat kernel transform on H-n, using direct sum and direct integral of Bergmann spaces and certain unitary representations of H-n which can be realized on the Hilbert space of Hilbert-Schmidt operators on L-2 (R-n). We also show that the image of Sobolev space of negative order H-s (H-n), s(> 0) is an element of R is a direct sum of two weighted Bergman spaces. Finally, we try to obtain some pointwise estimates for the functions in the image of Schwartz class on H-n under the heat kernel transform. (C) 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

CFT(4) partition functions and the heat kernel on AdS(5)

We consider four-dimensional CFTs which admit a large-N expansion, and whose spectrum contains states whose conformal dimensions do not scale with N. We explicitly reorganise the partition function obtained by exponentiating the one-particle partition function of these states into a heat kernel form for the dual string spectrum on AdS(5). On very general grounds, the heat kernel answer can be expressed in terms of a convolution of the one-particle partition function of the light states in the four-dimensional CFT. (C) 2013 Elsevier B.V. All rights reserved.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

Unconstrained Homooligomeric gamma-Peptides Show High Propensity for C-14 Helix Formation

Monosubstituted gamma(4)-residues (gamma(4)Leu, gamma(4)Ile, and gamma(4)Val) form helices even in short homooligomeric sequences. C-14 helix formation is established by X-ray diffraction in homooligomeric (gamma)(n) tetra-, hexa- and decapeptide sequences demonstrating the high propensity of gamma residues, with proteinogenic side chains, to adopt locally folded conformations.

Spatially Adaptive Kernel Regression Using Risk Estimation

An important question in kernel regression is one of estimating the order and bandwidth parameters from available noisy data. We propose to solve the problem within a risk estimation framework. Considering an independent and identically distributed (i.i.d.) Gaussian observations model, we use Stein's unbiased risk estimator (SURE) to estimate a weighted mean-square error (MSE) risk, and optimize it with respect to the order and bandwidth parameters. The two parameters are thus spatially adapted in such a manner that noise smoothing and fine structure preservation are simultaneously achieved. On the application side, we consider the problem of image restoration from uniform/non-uniform data, and show that the SURE approach to spatially adaptive kernel regression results in better quality estimation compared with its spatially non-adaptive counterparts. The denoising results obtained are comparable to those obtained using other state-of-the-art techniques, and in some scenarios, superior.

C-12 Helices in Long Hybrid (alpha gamma)(n) Peptides Composed Entirely of Unconstrained Residues with Proteinogenic Side Chains

Unconstrained gamma(4) amino acid residues derived by homologation of proteinogenic amino acids facilitate helical folding in hybrid (alpha gamma)(n) sequences. The C-12 helical conformation for the decapeptide, Boc-Leu-gamma(4)(R)Val](5)-OMe, is established in crystals by X-ray diffraction. A regular C-12 helix is demonstrated by NMR studies of the 18 residue peptide, Boc-Leu-gamma(4)(AR)Val](9)-OMe, and a designed 16 residue (alpha gamma)(n) peptide, incorporating variable side chains. Unconstrained (alpha gamma)(n) peptides show an unexpectedly high propensity for helical folding in long polypeptide sequences.

Novel synthesis of carbohydrate fused alpha-amino gamma-lactams and glycopeptides by NIS mediated ring opening of donor-acceptor substituted cyclopropanes

alpha-Amino gamma-lactams have been synthesized from carbohydrate derived cyclopropanecarboxylates using N-iodosuccinimide (NIS) and NaN3. Cyclopropane ring opening with NIS and NaN3 in different solvents has been studied. Reductive cyclization of the intermediate di-azides leads to the carbohydrate fused alpha-amino gamma-lactam and gamma-lactams. Additionally, the methodology has been successfully extended to the synthesis of a glycopeptide. (C) 2014 Elsevier Ltd. All rights reserved.

Regional flood frequency analysis using kernel- based fuzzy clustering approach

Regionalization approaches are widely used in water resources engineering to identify hydrologically homogeneous groups of watersheds that are referred to as regions. Pooled information from sites (depicting watersheds) in a region forms the basis to estimate quantiles associated with hydrological extreme events at ungauged/sparsely gauged sites in the region. Conventional regionalization approaches can be effective when watersheds (data points) corresponding to different regions can be separated using straight lines or linear planes in the space of watershed related attributes. In this paper, a kernel-based Fuzzy c-means (KFCM) clustering approach is presented for use in situations where such linear separation of regions cannot be accomplished. The approach uses kernel-based functions to map the data points from the attribute space to a higher-dimensional space where they can be separated into regions by linear planes. A procedure to determine optimal number of regions with the KFCM approach is suggested. Further, formulations to estimate flood quantiles at ungauged sites with the approach are developed. Effectiveness of the approach is demonstrated through Monte-Carlo simulation experiments and a case study on watersheds in United States. Comparison of results with those based on conventional Fuzzy c-means clustering, Region-of-influence approach and a prior study indicate that KFCM approach outperforms the other approaches in forming regions that are closer to being statistically homogeneous and in estimating flood quantiles at ungauged sites. Key Points Kernel-based regionalization approach is presented for flood frequency analysis Kernel procedure to estimate flood quantiles at ungauged sites is developed A set of fuzzy regions is delineated in Ohio, USA

Coconut kernel-derived activated carbon as electrode material for electrical double-layer capacitors

Carbonization of milk-free coconut kernel pulp is carried out at low temperatures. The carbon samples are activated using KOH, and electrical double-layer capacitor (EDLC) properties are studied. Among the several samples prepared, activated carbon prepared at 600 A degrees C has a large surface area (1,200 m(2) g(-1)). There is a decrease in surface area with increasing temperature of preparation. Cyclic voltammetry and galvanostatic charge-discharge studies suggest that activated carbons derived from coconut kernel pulp are appropriate materials for EDLC studies in acidic, alkaline, and non-aqueous electrolytes. Specific capacitance of 173 F g(-1) is obtained in 1 M H2SO4 electrolyte for the activated carbon prepared at 600 A degrees C. The supercapacitor properties of activated carbon sample prepared at 600 A degrees C are superior to the samples prepared at higher temperatures.

A FUNCTIONAL MODEL FOR PURE Gamma-CONTRACTIONS

A pair of commuting operators (S,P) defined on a Hilbert space H for which the closed symmetrized bidisc Gamma = {(z(1) + z(2), z(1)z(2)) : vertical bar z(1)vertical bar <= 1, vertical bar z(2)vertical bar <= 1} subset of C-2 is a spectral set is called a Gamma-contraction in the literature. A Gamma-contraction (S, P) is said to be pure if P is a pure contraction, i.e., P*(n) -> 0 strongly as n -> infinity Here we construct a functional model and produce a set of unitary invariants for a pure Gamma-contraction. The key ingredient in these constructions is an operator, which is the unique solution of the operator equation S - S*P = DpXDp, where X is an element of B(D-p), and is called the fundamental operator of the Gamma-contraction (S, P). We also discuss some important properties of the fundamental operator.

New physics in e(+)e(-) -> Z(gamma) at the ILC with polarized beams: explorations beyond conventional anomalous triple gauge boson couplings

One of the most-studied signals for physics beyond the standard model in the production of gauge bosons in electron-positron collisions is due to the anomalous triple gauge boson couplings in the Z(gamma) final state. In this work, we study the implications of this at the ILC with polarized beams for signals that go beyond traditional anomalous triple neutral gauge boson couplings. Here we report a dimension-8 CP-conserving Z(gamma)Z vertex that has not found mention in the literature. We carry out a systematic study of the anomalous couplings in general terms and arrive at a classification. We then obtain linear-order distributions with and without CP violation. Furthermore, we place the study in the context of general BSM interactions represented by e(+)e(-)Z(gamma) contact interactions. We set up a correspondence between the triple gauge boson couplings and the four-point contact interactions. We also present sensitivities on these anomalous couplings, which will be achievable at the ILC with realistic polarization and luminosity.

Interferon-gamma induced cell death: Regulation and contributions of nitric oxide, cJun N-terminal kinase, reactive oxygen species and peroxynitrite

Interferon-gamma (Ifn gamma), a known immunomodulatory cytokine, regulates cell proliferation and survival. In this study, the mechanisms leading to the selective susceptibility of some tumor cells to Ifn gamma were deciphered. Seven different mouse tumor cell lines tested demonstrated upregulation of MHC class I to variable extents with Ifn gamma; however, only the cell lines, H6 hepatoma and L929 fibrosarcoma, that produce higher amounts of nitric oxide (NO) and reactive oxygen species (ROS) are sensitive to Ifn gamma-induced cell death. NO inhibitors greatly reduce Ifn gamma-induced ROS; however, ROS inhibitors did not affect the levels of Ifn gamma-induced NO, demonstrating that NO regulates ROS. Consequently, NO inhibitors are more effective, compared to ROS inhibitors, in reducing Ifn gamma-induced cell death. Further analysis revealed that Ifn gamma induces peroxynitrite and 3-nitrotyrosine amounts and a peroxynitrite scavenger, FeTPPS, reduces cell death. Ifn gamma treatment induces the phosphorylation of c-jun N-terminal kinase (Jnk) in H6 and L929 but not CT26, a colon carcinoma cell line, which is resistant to Ifn gamma-mediated death. Jnk activation downstream to NO leads to induction of ROS, peroxynitrite and cell death in response to Ifn gamma. Importantly, three cell lines tested, i.e. CT26, EL4 and Neuro2a, that are resistant to cell death with Ifn gamma alone become sensitive to the combination of Ifn gamma and NO donor or ROS inducer in a peroxynitrite-dependent manner. Overall, this study delineates the key roles of NO as the initiator and Jnk, ROS, and peroxynitrite as the effectors during Ifn gamma-mediated cell death. The implications of these findings in the Ifn gamma-mediated treatment of malignancies are discussed. (C) 2014 Elsevier B.V. All rights reserved.

beta gamma-fused turn structures in sugar amino acid (SAA) containing cyclic tetrapeptides with alpha 3 delta architecture

The current manuscript describes conformational analysis of 15-membered cyclic tetrapeptides (CTPs), with alpha 3 delta architecture, containing sugar amino acids (SAA) having variation in the stereocenter at C5 carbon. Conformational analyses of both the series, in protected and deprotected forms, were carried out in DMSO-d(6) using various NMR techniques, supported by restrained MD calculations. It was intriguing to notice that the alpha 3 delta macrocycles got stabilized by both 10-membered beta-turn as well as a seven-membered gamma-turn, fused within the same macrocycle. The presence of fused sub-structures within a 15-membered macrocycle is rare to see. Also, the stereocenter variation at C5 did not affect the fused turn structures and exhibited similar conformations in both the series. The design becomes highly advantageous as fused reverse turn structures are occurring in the cyclic structure with minimalistic size macrocycle and this can be applied to develop suitable pharmacophores in the drug development process. (C) 2014 Elsevier Ltd. All rights reserved.

Interferon-gamma induced cell death: Regulation and contributions of nitric oxide, cJun N-terminal kinase, reactive oxygen species and peroxynitrite

Interferon-gamma (Ifn gamma), a known immunomodulatory cytokine, regulates cell proliferation and survival. In this study, the mechanisms leading to the selective susceptibility of some tumor cells to Ifn gamma were deciphered. Seven different mouse tumor cell lines tested demonstrated upregulation of MHC class I to variable extents with Ifn gamma; however, only the cell lines, H6 hepatoma and L929 fibrosarcoma, that produce higher amounts of nitric oxide (NO) and reactive oxygen species (ROS) are sensitive to Ifn gamma-induced cell death. NO inhibitors greatly reduce Ifn gamma-induced ROS; however, ROS inhibitors did not affect the levels of Ifn gamma-induced NO, demonstrating that NO regulates ROS. Consequently, NO inhibitors are more effective, compared to ROS inhibitors, in reducing Ifn gamma-induced cell death. Further analysis revealed that Ifn gamma induces peroxynitrite and 3-nitrotyrosine amounts and a peroxynitrite scavenger, FeTPPS, reduces cell death. Ifn gamma treatment induces the phosphorylation of c-jun N-terminal kinase (Jnk) in H6 and L929 but not CT26, a colon carcinoma cell line, which is resistant to Ifn gamma-mediated death. Jnk activation downstream to NO leads to induction of ROS, peroxynitrite and cell death in response to Ifn gamma. Importantly, three cell lines tested, i.e. CT26, EL4 and Neuro2a, that are resistant to cell death with Ifn gamma alone become sensitive to the combination of Ifn gamma and NO donor or ROS inducer in a peroxynitrite-dependent manner. Overall, this study delineates the key roles of NO as the initiator and Jnk, ROS, and peroxynitrite as the effectors during Ifn gamma-mediated cell death. The implications of these findings in the Ifn gamma-mediated treatment of malignancies are discussed. (C) 2014 Elsevier B.V. All rights reserved.

Temperature-Induced Reversible First-Order Single Crystal to Single Crystal Phase Transition in Boc-gamma(4)(R)Val-Val-OH: Interplay of Enthalpy and Entropy

Crystals of Boc-gamma y(4)(R)Val-Val-OH undergo a reversible first-order single crystal to single crystal phase transition at T-c approximate to 205 K from the orthorhombic space group P22(1)2(1) (Z' = 1) to the monoclinic space group P2(1) (Z' = 2) with a hysteresis of similar to 2.1 K. The low-temperature monoclinic form is best described as a nonmerohedral twin with similar to 50% contributions from its two components. The thermal behavior of the dipeptide crystals was characterized by differential scanning calorimetry experiments. Visual changes in birefringence of the sample during heating and cooling cycles on a hot-stage microscope with polarized light supported the phase transition. Variable-temperature unit cell check measurements from 300 to 100 K showed discontinuity in the volume and cell parameters near the transition temperature, supporting the first-order behavior. A detailed comparison of the room-temperature orthorhombic form with the low-temperature (100 K) monoclinic form revealed that the strong hydrogen-bonding motif is retained in both crystal systems, whereas the non-covalent interactions involving side chains of the dipeptide differ significantly, leading to a small change in molecular conformation in the monoclinic form as well as a small reorientation of the molecules along the ac plane. A rigid-body thermal motion analysis (translation, libration, screw; correlation of translation and libration) was performed to study the crystal entropy. The reversible nature of the phase transition is probably the result of an interplay between enthalpy and entropy: the low-temperature monoclinic form is enthalpically favored, whereas the room-temperature orthorhombic form is entropically favored.