We study the spaces of string links and homotopy string links in an arbitrary manifold using multivariable manifold calculus of functors. We construct multi-cosimplicial models for both spaces and deduce certain convergence properties of the associated Bousfield-Kan homotopy and cohomology spectral sequences when the ambient manifold is a Euclidean space of dimension four or more.

The beginning of the XX century showed an increasing interest in studies about the plastic expression of mental people, which generated changes in scientific and artistic fields. In the 40s, Jean Dubuffet, in France, and Mario Pedrosa, in Brazil, recognized and defended the artistic productions that deviated from the academy style and showed more spontaneity. Both protested against the idea of a psychopathological art, which allowed the elimination of the barrier between art and madness. The simultaneity and syntony between Pedrosa and Dubuffet allows us to establish a dialogue towards the posture and discussions raised by them.

Many state-of-the art visualization techniques must be tailored to the specific type of dataset, its modality (CT, MRI, etc.), the recorded object or anatomical region (head, spine, abdomen, etc.) and other parameters related to the data acquisition process. While parts of the information (imaging modality and acquisition sequence) may be obtained from the meta-data stored with the volume scan, there is important information which is not stored explicitly (anatomical region, tracing compound). Also, meta-data might be incomplete, inappropriate or simply missing. This paper presents a novel and simple method of determining the type of dataset from previously defined categories. 2D histograms based on intensity and gradient magnitude of datasets are used as input to a neural network, which classifies it into one of several categories it was trained with. The proposed method is an important building block for visualization systems to be used autonomously by non-experts. The method has been tested on 80 datasets, divided into 3 classes and a "rest" class. A significant result is the ability of the system to classify datasets into a specific class after being trained with only one dataset of that class. Other advantages of the method are its easy implementation and its high computational performance.

In this work, the fatty acid (FA) composition of muscle tissue of baby-beef cattle was investigated with regard to its nutritional value. Twenty six Simmental cattle of both sexes produced under the intensive conditions of housing and feeding were slaughtered at the age of one year and final weight of 489.6p 46.5 kg. The portion of muscle (m.longissimus dorsi) was taken for the chemical analysis at the level of 8th rib on cooled halves 24 h post mortem. Muscle fat content was determined by Foss-Let apparatus after extraction of lipids with tetrachloroethylene. Fatty acid composition was determined by gas liquid chromatography using in situ transesterification method and given as % of total weight of fatty acids. The average muscle fat content was 18.96 g/kg (95% CI 14.09-23.83). The average proportions of saturated FA (SFA), monounsaturated FA (MUFA) and polyunsaturated FA (PUFA) in muscle tissue were 43.03 (95% CI 42.19-43.87), 43.05 (95% CI 40.74-45.36) and 13.08 % (95% CI 10.96-15.19), respectively. The indicators of nutritional quality of fats like ratios of PUFA to SFA (PUFA/SFA) and n-6 PUFA to n-3 PUFA (n-6/n-3), as well as the atherogenicity index (AI) in muscle were 0.31 (95% CI 0.25-0.36), 13.51 (95% CI 12.59-14.43), and 0.60 (95% CI 0.58-0.63), respectively. These results suggest a need for the improvement of nutritional value of baby-beef fats through the modifications of its FA composition, primarily through n-3 PUFA enrichment.