Recursive time-varying filter banks for subband image coding

Filter banks and wavelet decompositions that employ recursive filters have been considered previously and are recognized for their efficiency in partitioning the frequency spectrum. This paper presents an analysis of a new infinite impulse response (IIR) filter bank in which these computationally efficient filters may be changed adaptively in response to the input. The filter bank is presented and discussed in the context of finite-support signals with the intended application in subband image coding. In the absence of quantization errors, exact reconstruction can be achieved and by the proper choice of an adaptation scheme, it is shown that IIR time-varying filter banks can yield improvement over conventional ones

Novel results in STM, ARPES, HREELS, Nernst, neutron, Raman, and isotope substitution experiments and their relation to bosonic modes and charge inhomogeneity, from perspective of negative-Ueff boson-fermion modelling of HTSC

This paper seeks to synthesize much recent work on the HTSC materials around the latest STM results from Davis and coworkers. The conductance diffuse scattering results in particular are used as point of entry to discuss bosonic modes, both of condensed and uncondensed form. The bosonic mode picture is essential to understanding an ever growing range of observations within the HTSC field. The work is expounded within the context of the negative-U, boson-fermion modelling long advocated by the author. This general approach is presently seeing much theoretical development, into which I have looked to couple many of the experimental advances. While the formal theory is not yet sufficiently detailed to cover adequately all the experimental complexities presented by the real cuprate systems, it is clear that it affords very appreciable support to the line taken. An attempt is made throughout to say why and how it is that these events are tied so very closely to this particular set of materials.Comment: 36 pages pdf with 3 figures and 1 table included, Submitted to J. Phys. Cond. Mat

Ontogenesis of Gonadotropin-Releasing Hormone Neurons: A Model for Hypothalamic Neuroendocrine Cell Development

The vertebrate hypothalamo–pituitary–gonadal axis is the anatomical framework responsible for reproductive competence and species propagation. Essential to the coordinated actions of this three-tiered biological system is the fact that the regulatory inputs ultimately converge on the gonadotropin-releasing hormone (GnRH) neuronal system, which in rodents primarily resides in the preoptic/hypothalamic region. In this short review we will focus on: (1) the general embryonic temporal and spatial development of the rodent GnRH neuronal system, (2) the origin(s) of GnRH neurons, and (3) which transcription – and growth factors have been found to be critical for GnRH neuronal ontogenesis and cellular fate-specification. Moreover, we ask the question whether the molecular and cellular mechanisms involved in GnRH neuronal development may also play a role in the development of other hypophyseal secreting neuroendocrine cells in the hypothalamus

Some families of density matrices for which separability is easily tested

We reconsider density matrices of graphs as defined in [quant-ph/0406165]. The density matrix of a graph is the combinatorial laplacian of the graph normalized to have unit trace. We describe a simple combinatorial condition (the "degree condition") to test separability of density matrices of graphs. The condition is directly related to the PPT-criterion. We prove that the degree condition is necessary for separability and we conjecture that it is also sufficient. We prove special cases of the conjecture involving nearest point graphs and perfect matchings. We observe that the degree condition appears to have value beyond density matrices of graphs. In fact, we point out that circulant density matrices and other matrices constructed from groups always satisfy the condition and indeed are separable with respect to any split. The paper isolates a number of problems and delineates further generalizations.Comment: 14 pages, 4 figure

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

This paper introduces an extension of entropy-constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements. Moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction

Low bit rate coding of Earth science images

In this paper, the authors discuss compression based on some new ideas in vector quantization and their incorporation in a sub-band coding framework. Several variations are considered, which collectively address many of the individual compression needs within the earth science community. The approach taken in this work is based on some recent advances in the area of variable rate residual vector quantization (RVQ). This new RVQ method is considered separately and in conjunction with sub-band image decomposition. Very good results are achieved in coding a variety of earth science images. The last section of the paper provides some comparisons that illustrate the improvement in performance attributable to this approach relative the the JPEG coding standard

Subband Image Coding with Jointly Optimized Quantizers

An iterative design algorithm for the joint design of complexity- and entropy-constrained subband quantizers and associated entropy coders is proposed. Unlike conventional subband design algorithms, the proposed algorithm does not require the use of various bit allocation algorithms. Multistage residual quantizers are employed here because they provide greater control of the complexity-performance tradeoffs, and also because they allow efficient and effective high-order statistical modeling. The resulting subband coder exploits statistical dependencies within subbands, across subbands, and across stages, mainly through complexity-constrained high-order entropy coding. Experimental results demonstrate that the complexity-rate-distortion performance of the new subband coder is exceptional

Baryonic contributions to the dilepton spectrum of nucleon-nucleon collisions

We study the production of dileptons in relativistic nucleon-nucleon collisions. Additionally to the traditional dilepton production channels (vector meson decays, meson and Delta(1232) Dalitz decays) we included in our model as new dilepton sources the Dalitz decay of higher unflavored baryon resonances with spin<=5/2 and mass<=2.25 GeV/c^2. The contributions of these new channels are estimated using experimental information about the Ngamma decays of the resonances and have large uncertainties. The obtained dilepton spectra are compared to the experimental data by the DLS collaboration. Predictions for the HADES detector (SIS, GSI) are also discussed. In spite of the large uncertainties of the higher resonance Dalitz decay contributions we are able to draw the conclusion that these contributions are negligible compared to the other dilepton sources and do not influence the detectability of the phi and omega vector meson peaks.Comment: 9 pages, 4 figures, version accepted for publication in Phys. Rev.

Differential Fibroblast Growth Factor 8 (FGF8)-Mediated Autoregulation of Its Cognate Receptors, Fgfr1 and Fgfr3, in Neuronal Cell Lines

Fibroblast growth factors (FGFs) mediate a vast range of CNS developmental processes including neural induction, proliferation, migration, and cell survival. Despite the critical role of FGF signaling for normal CNS development, few reports describe the mechanisms that regulate FGF receptor gene expression in the brain. We tested whether FGF8 could autoregulate two of its cognate receptors, Fgfr1 and Fgfr3, in three murine cell lines with different lineages: fibroblast-derived cells (3T3 cells), neuronal cells derived from hippocampus (HT-22 cells), and neuroendocrine cells derived from hypothalamic gonadotropin-releasing hormone (GnRH) neurons (GT1-7 cells). GnRH is produced by neurons in the hypothalamus and is absolutely required for reproductive competence in vertebrate animals. Several lines of evidence strongly suggest that Fgf8 is critical for normal development of the GnRH system, therefore, the GT1-7 cells provided us with an additional endpoint, Gnrh gene expression and promoter activity, to assess potential downstream consequences of FGF8-induced modulation of FGF receptor levels. Results from this study suggest that the autoregulation of its cognate receptor represents a common downstream effect of FGF8. Further, we show that Fgfr1 and Fgfr3 are differentially regulated within the same cell type, implicating these two receptors in different biological roles. Moreover, Fgfr1 and Fgfr3 are differentially regulated among different cell types, suggesting such autoregulation occurs in a cell type-specific fashion. Lastly, we demonstrate that FGF8b decreases Gnrh promoter activity and gene expression, possibly reflecting a downstream consequence of altered FGF receptor populations. Together, our data bring forth the possibility that, in addition to the FGF synexpression group, autoregulation of FGFR expression by FGF8 represents a mechanism by which FGF8 could fine-tune its regulatory actions