Abstract. The zero-error capacity of quantum channels was defined as the least upper bound of rates at which classical information is transmitted through a quantum channel with probability of error equal to zero. This paper investigates some properties of input states used to attain the zero-error capacity of quantum channels. Initially, we reformulate the problem of finding the zero-error capacity in the language of graph theory. We use this alternative definition to prove that the zero-error capacity of any quantum channel is reached by using only pure states.

Background and objectives: The severity of liver disease among hepatitis C patients on hemodialysis is controversial. The aim of this study was to compare the clinical, biochemical, and liver histologic characteristics of hepatitis C virus (HCV) in hemodialysis patients and in those with normal renal function.Design, setting, participants, & measurements: A case-control study was carried out with 36 HCV patients on hemodialysis and 37 HCV patients with normal renal function matched for gender, age at infection, and estimated time of infection.Results: HCV patients on hemodialysis had lower levels of alanina aminotransferase and lower viral load. Hepatic fibrosis was significantly higher in the patients with normal renal function (73%) than in hemodialysis patients (47.2%, P < 0.025); the same was observed for inflammatory activity (control group 59.5% versus hemodialysis patients 27.7%, P ‫؍‬ 0.003). In addition, the risk of tissue inflammation was four times lower in hemodialysis patients (odds ratio ‫؍‬ 0.23, P < 0.004), and severe inflammatory activity on biopsy was the only independent risk factor for fibrosis (P < 0.001).Conclusions: The lower biochemical and inflammatory activities observed in hemodialysis patients suggest that hemodialysis and uremia may have a protective role against progression of the disease caused by HCV.

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Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. However, a considerable number of current methods of analysis are based on parametric statistics. Alternatively, some methods in Computational Intelligence are inspired by biology and other sciences. Here we claim that Philosophy can be also considered as a source of inspiration. This work proposes the Objective Dialectical Method (ODM), which is a computational intelligent method for classification based on the Philosophy of Praxis. Here, ODM is instrumental in assembling evolvable mathematical tools to analyze multispectral images. In the case study described in this paper, such multispectral images are composed of diffusionweighted (DW) magnetic resonance (MR) images. The results are compared to ground-truth images produced by polynomial networks using a morphological similarity index.

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