Network routing capacity

We define the routing capacity of a network to be the supremum of all possible fractional message throughputs achievable by routing. We prove that the routing capacity of every network is achievable and rational, we present an algorithm for its computation, and we prove that every rational number in (0, 1] is the routing capacity of some solvable network. We also determine the routing capacity for various example networks. Finally, we discuss the extension of routing capacity to fractional coding solutions and show that the coding capacity of a network is independent of the alphabet used.     

Empirical quantizer design in the presence of source noise orchannel noise

The problem of vector quantizer empirical design for noisy channels or for noisy sources is studied. It is shown that the average squared distortion of a vector quantizer designed optimally from observing clean independent and identically distributed (i.i.d.) training vectors converges in expectation, as the training set size grows, to the minimum possible mean-squared error obtainable for quantizing the clean source and transmitting across a discrete memoryless noisy channel. Similarly, it is shown that if the source is corrupted by additive noise, then the average squared distortion of a vector quantizer designed optimally from observing i.i.d. noisy training vectors converges in expectation, as the training set size grows, to the minimum possible mean-squared error obtainable for quantizing the noisy source and transmitting across a noiseless channel. Rates of convergence are also provided     

Tradeoff between source and channel coding

A fundamental problem in the transmission of analog information across a noisy discrete channel is the choice of channel code rate that optimally allocates the available transmission rate between lossy source coding and block channel coding. We establish tight bounds on the channel code rate that minimizes the average distortion of a vector quantizer cascaded with a channel coder and a binary-symmetric channel. Analytic expressions are derived in two cases of interest: small bit-error probability and arbitrary source vector dimension; arbitrary bit-error probability and large source vector dimension. We demonstrate that the optimal channel code rate is often substantially smaller than the channel capacity, and obtain a noisy-channel version of the Zador (1982) high-resolution distortion formula     

A versatile and practical synthesis toward the development of novel HIV-1 integrase inhibitors

As a continuation of our previous work, which resulted in the identification of a new hit compound as an HIV-1 integrase inhibitor, three novel series of salicylic acid derivatives were synthesized using three versatile and practical synthetic strategies and were assayed for their capacity to inhibit the catalytic activity of HIV-1 integrase. Biological evaluations revealed that some of the synthesized compounds possess good inhibitory potency in enzymatic assays and are able to inhibit viral replication in MT-4 cells at low micromolar concentrations. Finally, docking studies were conducted to analyze the binding mode of the synthesized compounds within the DNA binding site of integrase in order to refine their structure-activity relationships.     

Quantizers with uniform encoders and channel optimized decoders

Scalar quantizers with uniform encoders and channel optimized decoders are studied for uniform sources and binary symmetric channels. It is shown that the natural binary code (NBC) and folded binary code (FBC) induce point density functions that are uniform on proper subintervals of the source support, whereas the Gray code (GC) does not induce a point density function. The mean-squared errors (MSE) for the NBC, FBC, GC, and for randomly chosen index assignments are calculated and the NBC is shown to be mean-squared optimal among all possible index assignments, for all bit-error rates and all quantizer transmission rates. In contrast, it is shown that almost all index assignments perform poorly and have degenerate codebooks.     

Corrections to `Gradient algorithms for designing predictive vectorquantizers'

An error in a paper by Chang and Gray (see ibid., vol.34, no.4, p.679-90, 1986) is pointed out and corrected. The error invalidates their observation that the generalized Lloyd algorithm is a gradient descent technique but the generalized Lloyd algorithm is a member of the related class of coordinate descent techniques. Convergence rate analysis of gradient descent algorithms for vector quantizer design is provided     

Quantizers with uniform decoders and channel-optimized encoders

Scalar quantizers with uniform decoders and channel-optimized encoders are studied for a uniform source on [0,1] and binary symmetric channels. Two families of affine index assignments are considered: the complemented natural code (CNC), introduced here, and the natural binary code (NBC). It is shown that the NBC never induces empty cells in the quantizer encoder, whereas the CNC can. Nevertheless, we show that the asymptotic distributions of quantizer encoder cells for the NBC and the CNC are equal and are uniform over a proper subset of the source's support region. Empty cells act as a form of implicit channel coding. An effective channel code rate associated with a quantizer designed for a noisy channel is defined and computed for the codes studied. By explicitly showing that the mean-squared error (MSE) of the CNC can be strictly smaller than that of the NBC, we also demonstrate that the NBC is suboptimal for a large range of transmission rates and bit error probabilities. This contrasts with the known optimality of the NBC when either both the encoder and decoder are not channel optimized, or when only the decoder is channel optimized.     

IAEA/IDEAS intercomparison exercise on internal dose assessment

An Internet based intercomparison exercise on assessment of occupational exposure due to intakes of radionuclides has been performed to check the applicability of the 'General Guidelines for the Assessment of Internal Dose from Monitoring Data' developed by the IDEAS group. There were six intake cases presented on the Internet and 81 participants worldwide reported solutions to these cases. Results of the exercise indicate that the guidelines have a positive influence on the methodologies applied for dose assessments and, if correctly applied, improve the harmonisation of assessed doses.     

Progressive source coding for a power constrained Gaussian channel

We consider the progressive transmission of a lossy source across a power constrained Gaussian channel using binary phase-shift keying modulation. Under the theoretical assumptions of infinite bandwidth, arbitrarily complex channel coding, and lossless transmission, we derive the optimal channel code rate and the optimal energy allocation per transmitted bit. Under the practical assumptions of a low complexity class of algebraic channel codes and progressive image coding, we numerically optimize the choice of channel code rate and the energy per bit allocation. This model provides an additional degree of freedom with respect to previously proposed schemes, and can achieve a higher performance for sources such as images. It also allows one to control bandwidth expansion or reduction     

High-resolution source coding for non-difference distortionmeasures: multidimensional companding

Entropy-coded vector quantization is studied using high-resolution multidimensional companding over a class of nondifference distortion measures. For distortion measures which are “locally quadratic” a rigorous derivation of the asymptotic distortion and entropy-coded rate of multidimensional companders is given along with conditions for the optimal choice of the compressor function. This optimum compressor, when it exists, depends on the distortion measure but not on the source distribution. The rate-distortion performance of the companding scheme is studied using an asymptotic expression for the rate-distortion function which parallels the Shannon lower bound for difference distortion measures. It is proved that the high-resolution performance of the scheme is arbitrarily close to the rate-distortion limit for large quantizer dimensions if the compressor function and the lattice quantizer used in the companding scheme are optimal, extending an analogous statement for entropy-coded lattice quantization and MSE distortion. The companding approach is applied to obtain a high-resolution quantizing scheme for noisy sources