Concurrent π\pi-vector fields and energy beta-change

The present paper deals with an \emph{intrinsic} investigation of the notion of a concurrent $\pi$-vector field on the pullback bundle of a Finsler manifold $(M,L)$. The effect of the existence of a concurrent $\pi$-vector field on some important special Finsler spaces is studied. An intrinsic investigation of a particular $\beta$-change, namely the energy $\beta$-change ($\widetilde{L}^{2}(x,y)=L^{2}(x,y)+ B^{2}(x,y) with \ B:=g(\bar{\zeta},\bar{\eta})$;$\bar{\zeta} $being a concurrent$\pi$-vector field), is established. The relation between the two Barthel connections$\Gamma$and$\widetilde{\Gamma}$, corresponding to this change, is found. This relation, together with the fact that the Cartan and the Barthel connections have the same horizontal and vertical projectors, enable us to study the energy$\beta$-change of the fundamental linear connection in Finsler geometry: the Cartan connection, the Berwald connection, the Chern connection and the Hashiguchi connection. Moreover, the change of their curvature tensors is concluded. It should be pointed out that the present work is formulated in a prospective modern coordinate-free form.Comment: 27 pages, LaTex file, Some typographical errors corrected, Some formulas simpifie

Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations

We construct a new framework for accelerating Markov chain Monte Carlo in posterior sampling problems where standard methods are limited by the computational cost of the likelihood, or of numerical models embedded therein. Our approach introduces local approximations of these models into the Metropolis-Hastings kernel, borrowing ideas from deterministic approximation theory, optimization, and experimental design. Previous efforts at integrating approximate models into inference typically sacrifice either the sampler's exactness or efficiency; our work seeks to address these limitations by exploiting useful convergence characteristics of local approximations. We prove the ergodicity of our approximate Markov chain, showing that it samples asymptotically from the \emph{exact} posterior distribution of interest. We describe variations of the algorithm that employ either local polynomial approximations or local Gaussian process regressors. Our theoretical results reinforce the key observation underlying this paper: when the likelihood has some \emph{local} regularity, the number of model evaluations per MCMC step can be greatly reduced without biasing the Monte Carlo average. Numerical experiments demonstrate multiple order-of-magnitude reductions in the number of forward model evaluations used in representative ODE and PDE inference problems, with both synthetic and real data.Comment: A major update of the theory and example

Knowledge Management Maturity in Universities and its Impact on Performance Excellence "Comparative study"

The paper assesses Knowledge Management Maturity(KMM) in the universities to determine the impact of knowledge management on performance excellence. This study was applied on Al-Azhar University and Al-Quds Open University in Gaza strip, Palestine. This paper depends on Asian productivity organization model that used to assess KMM. Second dimension which assess performance excellence was developed by the authors. The controlled sample was (610). Several statistical tools were used for data analysis and hypotheses testing, including reliability Correlation using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study suggest that KMM is suitable for measuring performance excellence. KMM assessment shows that both universities maturity level is in level three. Findings also support the main hypothesis and it is sub- hypotheses. The most important factors effecting performance excellence are: Processes, KM leadership, People, KM Outcomes. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first comparative study in the universities of Palestine explores the status of KMM using the Asian productivity Model

Isoprenoids determine Th1/Th2 fate in pathogenic T cells, providing a mechanism of modulation of autoimmunity by atorvastatin.

3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase is a critical enzyme in the mevalonate pathway that regulates the biosynthesis of cholesterol as well as isoprenoids that mediate the membrane association of certain GTPases. Blockade of this enzyme by atorvastatin (AT) inhibits the destructive proinflammatory T helper cell (Th)1 response during experimental autoimmune encephalomyelitis and may be beneficial in the treatment of multiple sclerosis and other Th1-mediated autoimmune diseases. Here we present evidence linking specific isoprenoid intermediates of the mevalonate pathway to signaling pathways that regulate T cell autoimmunity. We demonstrate that the isoprenoid geranylgeranyl-pyrophosphate (GGPP) mediates proliferation, whereas both GGPP and its precursor, farnesyl-PP, regulate the Th1 differentiation of myelin-reactive T cells. Depletion of these isoprenoid intermediates in vivo via oral AT administration hindered these T cell responses by decreasing geranylgeranylated RhoA and farnesylated Ras at the plasma membrane. This was associated with reduced extracellular signal-regulated kinase (ERK) and p38 phosphorylation and DNA binding of their cotarget c-fos in response to T cell receptor activation. Inhibition of ERK and p38 mimicked the effects of AT and induced a Th2 cytokine shift. Thus, by connecting isoprenoid availability to regulation of Th1/Th2 fate, we have elucidated a mechanism by which AT may suppress Th1-mediated central nervous system autoimmune disease