With the onset of areas such as complex systems, network science, and artificial intelligence, efforts have been invested in modeling science itself. In the present work, we report a related approach to modeling the influence of the complexity of knowledge on the respective prospects for scientific advancement. More specifically, we focus on the question of how much the topological complexity of the knowledge network can influence the prospects for scientific advancement. Once the knowledge has been represented as a complex network, we consider one of its subnetworks, the nucleus, as representing the currently known portion of that network. The relative number of nodes adjacent to the nucleus, and the ratio between this quantity and the quantity of edges interconnecting the nucleus with the remainder of the network, are taken as quantifications of the potential for scientific advancement and the efficiency with which these advances can take place. Subsequent nucleus sizes are considered in both a simpler network (Erdos-Renyi) and a more complex model (Barabasi-Albert). The results surprisingly tended to vary little between these two models, suggesting that the complexity of the knowledge network may have little effect on the prospects for scientific advancement as modeled in the present approach.

O objetivo deste trabalho foi avaliar alterações histomorfológicas na região do osso cortical de frangos de corte alimentados, nas fases de crescimento e engorda, com rações contendo cinco diferentes fontes de fósforo - fosfato dicálcico, superfosfato simples, superfosfato triplo, fosfato monoamônio e fosfato de rocha de Araxá. Imagens histológicas foram digitalizadas, segmentadas em regiões de interesse (ROI) e analisadas por meio de algoritmos desenvolvidos no ambiente de programação SCILAB. Consideraram-se onze características para descrição das imagens: porcentagem de osso por área, área da ROI, perímetro da ROI, alongamento da ROI, ângulo da ROI, os respectivos desvios-padrão dessas medidas, a entropia dos ângulos das ROI e uma medida orientada de textura (lacunaridade). A substituição do fosfato dicálcico, nas rações de crescimento e engorda, por qualquer uma das outras fontes de fósforo testadas, causou mudanças significativas na histomorfologia do córtex ósseo dos frangos de corte, tais como: menor porcentagem de osso por área, aumento da área das lacunas e menor homogeneidade da matriz. As alterações foram mais pronunciadas nos tratamentos que receberam fosfato de rocha de Araxá, fonte de maior nível de flúor, do que nos tratamentos com superfosfato simples, superfosfato triplo e fosfato monoamônio, os quais foram semelhantes entre si.

The objective of this work was to identify alterations in the histomorphology of the cortical bone tissue of broilers submitted to growing and finisher rations formulated with five different sources of phosphorus: dicalcium phosphate, simple superphosphate, triple superphosphate, monoammonium phosphate and Araxá rock phosphate. Histological images had their components segmented, and were called regions of interest (ROI). Images were analyzed through developed algorithms, using the SCILAB mathematical environment. Eleven features were considered in order to obtain a complete description of the bone images: percentage of bone by area, ROI area, ROI perimeters, ROI elongation, ROI angle and their respective standard deviations, besides entropy of ROI angles and a texture-oriented measure (lacunarity). The substitution of dicalcium phosphate in growing and finisher rations for any other tested source of phosphorus caused significant changes on the hystomorphology of the cortical broilers bones, for example: diminution of bone percentage by area, increase of lacuna area and worse matrix homogeneity. Changes were more pronounced in the Araxá rock phosphate treatments, with the highest fluorine content, than in simple superphosphate, triple superphosphate and monoammonium phosphate treatments, which were similar.

Após motivarmos o método científico como a maneira mais promissora de aquisição de conhecimento e previsão, discutimos como o mesmo estará sendo revisto sob a perspectiva de aplicações em biologia.

After reviewing the scientific methods as the most promising means for knowledge acquisition and prediction, we discuss how it is being changed in order to be more effectively applicable to biological problems.