Further reading Blander, J.M., and Medzhitov, R. (2006). On regulation of phagosome maturation and antigen presentation. Nat. Immunol. 7, 1029–1035. Brumell, J.H., and Scidmore, M.A. (2007). Manipulation of rab GTPase function by intracellular bacterial pathogens. Microbiol. Mol. Biol. Rev. 71, 636–652. Fairn, G.D., Ogata, K., Botelho, R.J., Stahl, P.D., Anderson, R.A., De Camilli, P., Meyer, T...

In the last twenty years, because of the application of the electron microscope, there has been a considerable increase in knowledge concerning the origin and mechanism of formation of collagen. Since the work of Schmitt, Hall, and Jakus' in 1942 illustrated that collagen was composed of a unit structure of fibrils, renewed interest has appeared in this area. Porter2 in 1952 and Wasserman3 in 1...

AMS 1991 subject classifications: primary 62G07 secondary 62M10 Keywords: Spatial long memory Local Whittle method a b s t r a c t A local Whittle estimator is developed to simultaneously estimate the long memory parameters for stationary anisotropic scalar random fields. It is shown that these estimators are consistent and asymptotically normal, under some weak technical conditions. A brief si...

sentimentalist pietism that looked to such contemporary continental mystics as Antoinette Bourginon and Madame Guyon. At first sight a heap of contradictions, as Anita Guerrini concludes, Cheyne "was a man of the Enlightenment" not the Enlightenment of "relentless secularisation" but rather that of "sensibility and sociability". In recent years, Cheyne's self-embodied concern with what Guerrini...

Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant features using feature selection, an algorithm can be given this knowledge of feature importance based on expert opinion or prior learning. Learning can be faster and more accurate if learners take feature importance int...

Parametric methods first choose the form of the model or hypotheses and estimates the necessary parameters from the given dataset. The form, which is chosen, based on experience or domain knowledge, often, need not be the same thing as that which actually exists (Duda, Hart & Stork, 2000). Further, apart from being highly error-prone, this type of methods shows very poor adaptability for dynami...

Citation: Ransohoff RM and Trettel F (2015) Editorial Research Topic " Chemokines and chemokine receptors in brain homeostasis ". The present Frontiers eBook " Chemokines and chemokine receptors in brain homeostasis " grew from a delightful conference held in Rome, Italy from 25th to 27th, 2013. It's our hope that this eBook will enable you to sense the conviviality and intellectual ferment of ...

Based on the tropical cyclone (TC) forecasting literature, hurricane intensity prediction is one of the most challenging tasks. To date, the problem has been addressed through statistical models (SHIFOPR, ST5D), statistical-dynamical models (SHIPS) and primitive equation numerical models (GFDL), predicting the intensity changes for up to five days. For the first two kinds of models, both multip...

This tutorial will cover recent advances in sparse modeling with diverse applications in natural language processing (NLP). A sparse model is one that uses a relatively small number of features to map an input to an output, such as a label sequence or parse tree. The advantages of sparsity are, among others, compactness and interpretability; in fact, sparsity is currently a major theme in stati...

A heuristic method for simulating time dependent data from oo-line character input is proposed. The method involves extracting strokes from a thinned bitmap and then ordering them along with simulated pen-up strokes to achieve a pseudo-time-dependent representation. Features used for input to time-delay neural nets 1] and 2] are then extracted. The algorithm is tested on fortyinputs and the fea...