RESUMO
Acoustic energy mapping provides the functionality to obtain characteristics of acoustic sources, as: presence, localization, type and trajectory of sound sources. Several beamforming-based techniques can be used for this purpose. However, they rely on the difference of arrival times of the signal at each capture node (or microphone), so it is of major importance to have synchronized multi-channel recordings. A Wireless Acoustic Sensor Network (WASN) can be very practical to install when used for mapping the acoustic energy of a given acoustic environment. However, they are known for having low synchronization between the recordings from each node. The objective of this paper is to characterize the impact of current popular synchronization methodologies as part of the WASN to capture reliable data to be used for acoustic energy mapping. The two evaluated synchronization protocols are: Network Time Protocol (NTP) y Precision Time Protocol (PTP). Additionally, three different audio capture methodologies were proposed for the WASN to capture the acoustic signal: two of them, recording the data locally and one sending the data through a local wireless network. As a real-life evaluation scenario, a WASN was built using nodes conformed by a Raspberry Pi 4B+ with a single MEMS microphone. Experimental results demonstrate that the most reliable methodology is using the PTP synchronization protocol and audio recording locally.
RESUMO
The ability of bacteria and archaea to modulate metabolic process, defensive response, and pathogenic capabilities depend on their repertoire of genes and capacity to regulate the expression of them. Transcription factors (TFs) have fundamental roles in controlling these processes. TFs are proteins dedicated to favor and/or impede the activity of the RNA polymerase. In prokaryotes these proteins have been grouped into families that can be found in most of the different taxonomic divisions. In this work, the association between the expansion patterns of 111 protein regulatory families was systematically evaluated in 1351 non-redundant prokaryotic genomes. This analysis provides insights into the functional and evolutionary constraints imposed on different classes of regulatory factors in bacterial and archaeal organisms. Based on their distribution, we found a relationship between the contents of some TF families and genome size. For example, nine TF families that represent 43.7% of the complete collection of TFs are closely associated with genome size; i.e., in large genomes, members of these families are also abundant, but when a genome is small, such TF family sizes are decreased. In contrast, almost 102 families (56.3% of the collection) do not exhibit or show only a low correlation with the genome size, suggesting that a large proportion of duplication or gene loss events occur independently of the genome size and that various yet-unexplored questions about the evolution of these TF families remain. In addition, we identified a group of families that have a similar distribution pattern across Bacteria and Archaea, suggesting common functional and probable coevolution processes, and a group of families universally distributed among all the genomes. Finally, a specific association between the TF families and their additional domains was identified, suggesting that the families sense specific signals or make specific protein-protein contacts to achieve the regulatory roles.
