Acoustic communication signals are inevitably challenged by ambient noise. In response to noise, many animals adjust their calls to maintain signal detectability. However, the mechanisms by which the auditory system adapts to the adjusted pulses are unclear. Our previous study revealed that the echolocating bat, Hipposideros pratti, increased its pulse intensity in the presence of background white noise. In vivo single-neuron recording demonstrated that the auditory midbrain neurons tuned to the second harmonic (H2 neurons) increased their minimal threshold (MT) to a similar degree as the increment of pulse intensity in the presence of the background noise. Furthermore, the H2 neurons exhibited consistent spike rates at their best amplitudes and sharper intensity tuning with background white noise compared with silent conditions. The previous data indicated that sound intensity analysis by auditory midbrain neurons was adapted to the increased pulse intensity in the same noise condition. This study further examined the echolocation pulse frequency and frequency analysis of auditory midbrain neurons with noise conditions. The data revealed that H. pratti did not shift the resting frequency in the presence of background noise. The auditory midbrain neuronal frequency analysis highly linked to processing the resting frequency with the presence of noise by presenting the constant best frequency (BF), frequency sensitivity, and frequency selectivity. Thus, our results suggested that auditory midbrain neuronal responses in background white noise are adapted to process echolocation pulses in the noise conditions.
The impact of building the Belt and Road on the ecological environment and the health of the related cities along this belt deserves more attention. Currently, there are few relevant pieces of research in this area, and the problem of a time lag between the ecological environment and health (e.g., life expectancy, LE) has not been explored. This paper investigates the aforementioned problem based on five ecological indicators, i.e., normalized difference vegetation index, leaf area index, gross primary production (GPP), land surface temperature (LST), and wet, which were obtained from MODIS satellite remote-sensing products in 2010, 2015, and 2020. The research steps are as follows: firstly, a comprehensive ecological index (CEI) of the areas along the Belt and Road was calculated based on the principle of component analysis; secondly, the changes in the trends of the five ecological indicators and the CEI in the research area in the past 11 years were calculated by using the trend degree analysis method; then, the distributions of the cold and hot spots of each index in the research area were calculated via cold and hot spot analysis; finally, the time lag relationship between LE and the ecological environment was explored by using the proposed spatiotemporal lag spatial crosscorrelation analysis. The experimental results show that ① there is a positive correlation between LE and ecological environment quality in the study area; ② the ecological environment has a lagging impact on LE, and the impact of ecological indicators in 2010 on LE in 2020 is greater than that in 2015; ③ among the ecological indicators, GPP has the highest impact on LE, while LST and Wet have a negative correlation with LE.
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