Identifying cytokine signaling signatures in primary human Th-1 cells by phospho-proteomics analysis

Summary: Stable isotope labeling by amino acid-based high-resolution phosphoproteomics is a powerful technique that allows for direct comparison of cells stimulated under different experimental conditions. This feature makes it the ideal methodology to identify cytokine signaling networks. Here, we present an optimized protocol for the isolation and identification of phosphopeptides from IL-6-stimulated primary human Th-1 cells.For complete details on the use and execution of this protocol, please refer to Martinez-Fabregas et al. (2020)

A Recursive Quantizer Design Algorithm for Binary-Input Discrete Memoryless Channels

The optimal quantization of the outputs of binary-input discrete memoryless channels is considered, whereby the optimal quantizer preserves at least a constant α-fraction of the original mutual information, with the smallest output cardinality. Two recursive methods with top-down and bottom-up approaches are developed; these methods lead to a new necessary condition for the recursive quantizer design. An efficient algorithm with linear complexity, based on dynamic programming and the new necessary optimality condition, is proposed.This work has been funded in part by the European Research Council under grant 725411, and by the Spanish Ministry of Economy and Competitiveness under grant TEC2016-78434-C3-1-R

Importance Sampling for Coded-Modulation Error Probability Estimation

This paper proposes an efficient simulation method based on importance sampling to estimate the random-coding error probability of coded modulation. The technique is valid for complex-valued modulations over Gaussian channels, channels with memory, and naturally extends to fading channels. The simulation method is built on two nested importance samplers to respectively estimate the pairwise error probability and generate the channel input and output. The effect of the respective number of samples on the overall bias and variance of the estimate of the error probability is characterized. For a memoryless channel, the estimator is shown to be consistent and with a small variance, growing with the square root of the code length, rather than the exponential growth of a standard Monte Carlo estimator.This work has been funded in part by the European Research Council under ERC grant agreement 725411, and by the Spanish Ministry of Economy and Competitiveness under grant TEC2016-78434-C3-1-R

Analysis of the behavior of phase change material in solar energy storage using computational tools

In this study, the temperature profile of the sodium nitrate phase change material NaNO3 is characterized, using a spherical macro encapsulation technique to increase the heat transfer properties, simulating through computer tools the behavior of this material when it is used as an alternative source of energy for heat. exchange processes, where the primary energy source has interruptions in the heat supply, the data obtained show for the proposed model that the system is capable of maintaining the outlet temperature for at least 20s and a temperature drop of 50K for 60s, being promising data for the use of these materials in heat exchange processes as is the energy support of solar collectors

Mismatched decoding: Error exponents, second-order rates and saddlepoint approximations

This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error exponents and second-order coding rates matching those of constant-composition random coding, while being directly applicable to channels with infinite or continuous alphabets. The number of auxiliary costs required to match the error exponents and second-order rates of constant-composition coding is studied, and is shown to be at most two. For independent identically distributed random coding, asymptotic estimates of two well-known non-asymptotic bounds are given using saddlepoint approximations. Each expression is shown to characterize the asymptotic behavior of the corresponding random-coding bound at both fixed and varying rates, thus unifying the regimes characterized by error exponents, second-order rates, and moderate deviations. For fixed rates, novel exact asymptotics expressions are obtained to within a multiplicative 1+o(1) term. Using numerical examples, it is shown that the saddlepoint approximations are highly accurate even at short block lengths.This work was supported in part by the European Research Council under Grant 259663, in part by the European Union’s 7th Framework Programme under Grant 303633, and in part by the Spanish Ministry of Economy and Competitiveness under Grants RYC-2011-08150 and TEC2012-38800-C03-03

Mismatched Multi-Letter Successive Decoding for the Multiple-Access Channel

This paper studies channel coding for the discrete memoryless multiple-access channel with a given (possibly suboptimal) decoding rule. A multi-letter successive decoding rule depending on an arbitrary non-negative decoding metric is considered, and achievable rate regions and error exponents are derived both for the standard MAC (independent codebooks), and for the cognitive MAC (one user knows both messages) with superposition coding. In the cognitive case, the rate region and error exponent are shown to be tight with respect to the ensemble average. The rate regions are compared with those of the commonly considered decoder that chooses the message pair maximizing the decoding metric, and numerical examples are given for which successive decoding yields a strictly higher sum rate for a given pair of input distributions.This work was supported in part by the European Research Council through ERC under Grant 259663 and Grant 725411, in part by the European Union’s 7th Framework Programme under Grant 303633, and in part by the Spanish Ministry of Economy and Competitiveness under Grant RYC-2011-08150, Grant TEC2012-38800-C03- 03, and Grant TEC2016-78434-C3-1-R

Multiuser Random Coding Techniques for Mismatched Decoding

This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with respect to the ensemble average, and positive within the interior of Lapidoth's achievable rate region. This exponent proves the ensemble tightness of the exponent of Liu and Hughes in the case of maximum-likelihood decoding. An equivalent dual form of Lapidoth's achievable rate region is given, and the latter is shown to immediately extend to channels with infinite and continuous alphabets. In the setting of single-user mismatched decoding, similar analysis techniques are applied to a refined version of superposition coding, which is shown to achieve rates at least as high as standard superposition coding for any set of random-coding parameters