A systematic review of diapoma (teleostei: characiformes: characidae: stevardiinae: diapomini) with descriptions of two new species from southern Brazil

Diapoma is reviewed and four species are recognized: (1) Diapoma thauma, new species, from streams of the rio Jacuí basin, state of Rio Grande do Sul; (2) D. pyrrhopteryx, new species collected from the rio Canoas and streams flowing into this basin in the states of Rio Grande do Sul and Santa Catarina, Brazil; (3) Diapoma terofali, from streams flowing into rio Uruguay in Uruguay and Rio Grande do Sul, Brazil and streams flowing into rio de la Plata, Argentina; and (4) Diapoma speculiferum, from lowland coastal streams in Rio Grande do Sul, Brazil and Uruguay. Diapoma pyrrhopteryx possess the posteroventral opercular elongation typical of D. speculiferum, type species of the genus, but which is absent in D. thauma and D. terofali. Nonetheless, all the diapomin species have the caudal pouch organ about equally developed in both sexes and the dorsal portion of the pouch opening bordered by a series of 3 to 8 elongated scales, the two derived features that characterize the group. The two previously described species, D. speculiferum and D. terofali, are redescribed. Previous hypotheses of relationships among the diapomin genera Planaltina, Diapoma and Acrobrycon are discussed on the basis of preliminary morphological information. It is proposed that the Diapomini is a monophyletic group. An identification key, information on sexual dimorphism, gonad anatomy, reproductive mode and distribution of the species of Diapoma are provided.

Model for Differential Nursing Diagnosis of Alterations in Urinary Elimination Based on Fuzzy Logic

Nursing diagnoses associated with alterations of urinary elimination require different interventions, Nurses, who are not specialists, require support to diagnose and manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for differential diagnosis of alterations in urinary elimination, considering nursing diagnosis approved by the North American Nursing Diagnosis Association, 2001-2002. Fuzzy relations and the maximum-minimum composition approach were used to develop the system. The model performance was evaluated with 195 cases from the database of a previous study, resulting in 79.0% of total concordance and 19.5% of partial concordance, when compared with the panel of experts. Total discordance was observed in only three cases (1.5%). The agreement between model and experts was excellent (kappa = 0.98, P < .0001) or substantial (kappa = 0.69, P < .0001) when considering the overestimative accordance (accordance was considered when at least one diagnosis was equal) and the underestimative discordance (discordance was considered when at least one diagnosis was different), respectively. The model herein presented showed good performance and a simple theoretical structure, therefore demanding few computational resources.