A critical appraisal of appendage disparity and homology in fishes

Fishes are both extremely diverse and morphologically disparate. Part of this disparity can be observed in the numerous possible fin configurations that may differ in terms of the number of fins as well as fin shapes, sizes and relative positions on the body. Here, we thoroughly review the major patterns of disparity in fin configurations for each major group of fishes and discuss how median and paired fin homologies have been interpreted over time. When taking into account the entire span of fish diversity, including both extant and fossil taxa, the disparity in fin morphologies greatly complicates inferring homologies for individual fins. Given the phylogenetic scope of this review, structural and topological criteria appear to be the most useful indicators of fin identity. We further suggest that it may be advantageous to consider some of these fin homologies as nested within the larger framework of homologous fin‐forming morphogenetic fields. We also discuss scenarios of appendage evolution and suggest that modularity may have played a key role in appendage disparification. Fin modules re‐expressed within the boundaries of fin‐forming fields could explain how some fins may have evolved numerous times independently in separate lineages (e.g., adipose fin), or how new fins may have evolved over time (e.g., anterior and posterior dorsal fins, pectoral and pelvic fins). We favour an evolutionary scenario whereby median appendages appeared from a unique field of competence first positioned throughout the dorsal and ventral midlines, which was then redeployed laterally leading to paired appendages.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151971/1/faf12402_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151971/2/faf12402.pd

Changes to the Fossil Record of Insects through Fifteen Years of Discovery

The first and last occurrences of hexapod families in the fossil record are compiled from publications up to end-2009. The major features of these data are compared with those of previous datasets (1993 and 1994). About a third of families (>400) are new to the fossil record since 1994, over half of the earlier, existing families have experienced changes in their known stratigraphic range and only about ten percent have unchanged ranges. Despite these significant additions to knowledge, the broad pattern of described richness through time remains similar, with described richness increasing steadily through geological history and a shift in dominant taxa, from Palaeoptera and Polyneoptera to Paraneoptera and Holometabola, after the Palaeozoic. However, after detrending, described richness is not well correlated with the earlier datasets, indicating significant changes in shorter-term patterns. There is reduced Palaeozoic richness, peaking at a different time, and a less pronounced Permian decline. A pronounced Triassic peak and decline is shown, and the plateau from the mid Early Cretaceous to the end of the period remains, albeit at substantially higher richness compared to earlier datasets. Origination and extinction rates are broadly similar to before, with a broad decline in both through time but episodic peaks, including end-Permian turnover. Origination more consistently exceeds extinction compared to previous datasets and exceptions are mainly in the Palaeozoic. These changes suggest that some inferences about causal mechanisms in insect macroevolution are likely to differ as well

Dynamic threshold selection method for multi-label newspaper topic identification

Nowadays, the multi-label classification is increasingly required in modern categorization systems. It is especially essential in the task of newspaper article topics identification. This paper presents a method based on general topic model normalisation for finding a threshold defining the boundary between the "correct" and the "incorrect" topics of a newspaper article. The proposed method is used to improve the topic identification algorithm which is a part of a complex system for acquisition and storing large volumes of text data. The topic identification module uses the Naive Bayes classifier for the multiclass and multi-label classification problem and assigns to each article the topics from a defined quite extensive topic hierarchy - it contains about 450 topics and topic categories. The results of the experiments with the improved topic identification algorithm are presented in this paper