Cellular factors that may protect against human immunodeficiency virus (HIV) infection were investigated in 27 HIV-exposed seronegative (ESN) female sex workers (FSWs) and 27 HIV-seronegative female blood donors. Compared with blood donors, ESN FSWs had significantly decreased expression levels of C-X-C chemokine receptor 4 (CXCR4), but not of C-C chemokine receptor 5, on both memory (P<.001) a...

Immune parameters were analyzed in peripheral blood mononuclear cells (PBMC) and cervical mucosa biopsy specimens of human immunodeficiency virus (HIV)-seronegative women sexually exposed to HIV (exposed seronegative [ESN]), HIV-infected women, and healthy women without HIV exposure. HIV was not detected in PBMC or cervical mucosa biopsy specimens of ESN women. However, interleukin (IL)-6, IL-1...

Repeated exposure to human immunodeficiency virus (HIV) does not always result in seroconversion. Modifications in coreceptors for HIV entrance to target cells are one of the factors that block the infection. We studied the frequency of Delta-32 mutation in ccr5 gene in Medellin, Colombia. Two hundred and eighteen individuals distributed in three different groups were analyzed for Delta-32 muta...

Constructing non-invasive Brain-Computer Interfaces (BCI) that are practical for use in assistive technology has proven to be a challenging problem. We assert that classification algorithms that are capable of capturing sophisticated spatiotemporal patterns in Electroencephalography (EEG) signals are necessary in order for BCI to deliver fluid and reliable control. Since Echo State Networks (ES...

Echo State Networks (ESNs) have tremendous potential on a variety of problems if successfully designed. The effects of varying two important ESN parameters, the spectral radius (alpha) and settling time (ST) are studied in this letter. Spectral radius of an ESN is the maximum of all eigenvalues of the reservoir weights whereas ST is measured by the number of iterations allowed in the reservoir ...

Abstract Forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. This paper studies load consumption modeling in Hamedan city province distribution network by applying ESN neural network. Weather forecasting data such as minimum day temperature, average day temp...

abstract forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. this paper studies load consumption modeling in hamedan city province distribution network by applying esn neural network. weather forecasting data such as minimum day temperature, average day temp...

As one of the most important paradigms of recurrent neural networks, the echo state network (ESN) has been applied to a wide range of fields, from robotics to medicine to finance, and language processing. A key feature of the ESN paradigm is its reservoir —a directed and weighted network— that represents the connections between neurons and projects the input signals into a high dimensional spac...

In this paper we investigate the problem of learning Echo State Networks (ESN) with adaptable filter neurons and delay&sum readouts. A brute-force solution to this learning problem is often impractical due to nonlinearity and high dimensionality of the resulting optimization problem. In this work we propose an approximate solution to the ESN learning by appealing to the variational Bayesian EMt...