Study on the Geographic Variation and Trophic Variation of Todarodes pacificus in Different Areas Based on Stable Isotope Information from the Gladius.

The Japanese flying squid (Todarodes pacificus) is an important cephalopod in the northwest Pacific Ocean. In this study, the proostracum of the gladius of T. pacificus samples collected by Chinese squid fishing vessels in the East China Sea and the Sea of Japan in August and December 2018 were continuously cut, and stable isotope values of the cut fragments were used to analyze the migration path and feeding ecology of T. pacificus. The results showed that when the proostracum grew to 120 mm from the distal end, T. pacificus began to migrate. In the East China Sea, T. pacificus migrated to low latitudes and nearshore areas, and the trophic level of their food showed no large changes during migration. In the Sea of Japan, T. pacificus migrated to high latitudes and offshore areas, and the trophic level of their food showed a decreasing trend during migration. There was no significant difference in migration or feeding ecology between females and males, but the competitive capacity of the females may be stronger than that of the males. The results provided a scientific basis for the scientific management and development of T. pacificus resources.

A novel intelligent system based on adjustable classifier models for diagnosing heart sounds.

A novel intelligent diagnostic system is proposed to diagnose heart sounds (HSs). The innovations of this system are primarily reflected in the automatic segmentation and extraction of the first complex sound [Formula: see text] and second complex sound [Formula: see text]; the automatic extraction of the secondary envelope-based diagnostic features [Formula: see text], [Formula: see text], and [Formula: see text] from [Formula: see text] and [Formula: see text]; and the adjustable classifier models that correspond to the confidence bounds of the Chi-square ([Formula: see text]) distribution and are adjusted by the given confidence levels (denoted as [Formula: see text]). The three stages of the proposed system are summarized as follows. In stage 1, the short time modified Hilbert transform (STMHT)-based curve is used to segment and extract [Formula: see text] and [Formula: see text]. In stage 2, the envelopes [Formula: see text] and [Formula: see text] for periods [Formula: see text] and [Formula: see text] are obtained via a novel method, and the frequency features are automatically extracted from [Formula: see text] and [Formula: see text] by setting different threshold value ([Formula: see text]) lines. Finally, the first three principal components determined based on principal component analysis (PCA) are used as the diagnostic features. In stage 3, a Gaussian mixture model (GMM)-based component objective function [Formula: see text] is generated. Then, the [Formula: see text] distribution for component k is determined by calculating the Mahalanobis distance from [Formula: see text] to the class mean [Formula: see text] for component k, and the confidence region of component k is determined by adjusting the optimal confidence level [Formula: see text] and used as the criterion to diagnose HSs. The performance evaluation was validated by sounds from online HS databases and clinical heart databases. The accuracy of the proposed method was compared to the accuracies of other state-of-the-art methods, and the highest classification accuracies of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], 99.67[Formula: see text] and 99.91[Formula: see text] in the detection of MR, MS, ASD, NM, AS, AR and VSD sounds were achieved by setting [Formula: see text] to 0.87,0.65,0.67,0.65,0.67,0.79 and 0.87, respectively.