Design and Algorithm Integration of High-Precision Adaptive Underwater Detection System Based on MEMS Vector Hydrophone.

Real-time DOA (direction of arrival) estimation of surface or underwater targets is of great significance to the research of marine environment and national security protection. When conducting real-time DOA estimation of underwater targets, it can be difficult to extract the prior characteristics of noise due to the complexity and variability of the marine environment. Therefore, the accuracy of target orientation in the absence of a known noise is significantly reduced, thereby presenting an additional challenge for the DOA estimation of the marine targets in real-time. Aiming at the problem of real-time DOA estimation of acoustic targets in complex environments, this paper applies the MEMS vector hydrophone with a small size and high sensitivity to sense the conditions of the ocean environment and change the structural parameters in the adaptive adjustments system itself to obtain the desired target signal, proposes a signal processing method when the prior characteristics of noise are unknown. Theoretical analysis and experimental verification show that the method can achieve accurate real-time DOA estimation of the target, achieve an error within 3.1° under the SNR (signal-to-noise ratio) of the X channel of -17 dB, and maintain a stable value when the SNR continues to decrease. The results show that this method has a very broad application prospect in the field of ocean monitoring.

The role of the gut microbiota in depressive-like behavior induced by chlorpyrifos in mice.

Chlorpyrifos (CPF) is associated with depression, cognitive dysfunction, and other neurological disorders. Increasing evidence has suggested that the gut microbiota plays a vital role in regulating the development of depression. However, it is unknown whether gut microbiota is associated with CPF-related depression. This study aimed to explore the effect of CPF on depressive-like behavior in mice and investigated the role of gut microbiota in this behavior. In our study, we selected fifty male C57BL/6 J mice for the model and subjected them to CPF poisoning by gavage for 14 days. The depressive-like behaviors of mice were assessed by the open field test (OFT), sucrose preference test (SPT), and forced swimming test (FST). Furthermore, we selected the high-dose group (CPF10) with obvious changes in depressive-like behaviors for the hippocampus and colon histopathological analysis, examined the changes in the gut microbiota by 16 S rRNA sequencing, screened the different microbiota among groups by linear discriminant analysis effect size (LEfSe), analyzed the correlation between intestinal bacteria and depression-like behavior indicators by Spearman analysis, and evaluated the predictive ability of different bacteria to CPF-induced depressive-like behavior using the receiver operator characteristic (ROC) curve. The results showed that CPF caused depressive-like behaviors with pathological changes in the hippocampus and colon. CPF induced changes in gut microbiota, including 49 differential bacteria. Among the top 10 abundant bacteria, Actinobacteria and Deferribacteres were increased, and Cyanobacteria, Patescibacteria and Verrucomicrobia were decreased at the phylum level. Muribaculum, Ruminococcaceae.UCG.014 and uncultured Bacteroides bacterium were decreased at the genus level. Correlation analysis demonstrated that 18 differentially abundant bacteria were correlated with CPF-induced depression. ROC curves revealed that Deferribacteres, Mucispirillum, Rikenella and GCA900066575 are potential biomarkers for depression caused by CPF. These findings will provide an experimental basis for the neurological health of the pesticide-exposed population.