Morphological identification of Nematodirus spathiger nematodes (Nematoda, Molineidae) obtained from the small intestine of sheep

Abstract

Strongyloidiases are caused by nematodes of the suborder Strongylida and are the most widely prevalent group of gastrointestinal helminthiases of sheep in many regions of the world. Among gastrointestinal strongylids, the helminths of the genus Nematodirus are represented by the largest number of species and highest infection rates in sheep. Nematodirosis causes significant economic losses in the sheep industry through decreased sheep productivity, delayed growth and development of young animals, and a reduced resistance to other diseases. Timely and accurate diagnosis of nematodirosis and identification of the pathogen will effectively prevent the disease and help to carry out treatment and prevention measures. Therefore, the aim of the work was to study the definitive morphometric characters of mature males and females of Nematodirus spathiger Railliet, 1896, obtained from the small intestine of domestic sheep. The results of experimental studies showed that nematodes of this species morphologically are characterized by a thin filiform body, a vesicle at the head end and a chitinous tooth in a short oral capsule. The differential morphological features of male nematodes of N. spathiger include specifics of the structure of spicules, their distal end and the shape and location of the rays of the caudal bursa; in females, those are the features of the structure of the vulva and tail end. In identification of male nematodes of N. spathiger, it is proposed to use 40 metric parameters, of which 11 characterize the overall size of the body, esophagus and vesicles, 24 refer to the size of the tail bursa, 5 to the size of the spicules and the enveloping membrane. To help identify the females of N. spathiger, 25 parameters are chosen, of which 14 also characterize the overall size of the body, esophagus and head vesicle, 6 refer to the size of the cuticular formations of the vulva and its location, and 5 to the size of the tail end, the location of the anus and the size of the tail spike.

Intelligent identification of segmental line losses in low-voltage networks under graphical consistency line variation relationship analysis

“…After completing the processing of the original power data set, the graph consistency line variation relationship analysis model can be constructed, for which three parameters are selected and the optimal parameter values are set, which are the dimensionality reduction, the similarity matrix function and the number of clusters of proximity relationship, the specific parameter meanings and the corresponding optimal parameters are shown in Table 1 [4][5][6][7]. Considering that the operating loads of the line areas differ at different analysis window scales, in order to keep such differences to a minimum, this paper chooses day as the minimum time unit, and establishes the line variation topology on this basis to construct a graphical consistency line variation relationship model [8].…”