No abstract

At present, Chinese electrical fire prevention and control is still in the development stage. The existing electrical fire monitoring products have technical defects, the false alarm rate is high, and the monitoring effect on electrical fire is limited. Because of these situations, the microcontroller STM32WLE5CCU6 and the sharp micro power quality chip RN8302B is used as the core, combined with the LSTM neural network, an intelligent front-end device with real-time monitoring of electrical fire data and data depth processing functions are designed, which realizes the monitoring and prediction of an electrical fire. And composed an intelligent electrical fire warning system capable of wireless communication and information interaction with intelligent front-end equipment, LoRa wireless communication, RS485 communication, and cloud platform.

No abstract

Simple sequence repeats (SSRs) are molecular genetic markers that are powerful tools in genomics studies; SSR markers are routinely mined as a part of genetic workflows. Here, we developed a novel SSR mining algorithm based on regular expression that can reduce the complexity of commonly used SSR mining software. We used the following SSR mining regular expression: ({i, j}?) (\1) {k}, where i and j denote the minimum and maximum lengths of the motifs of the SSR sequence, respectively, and k is the minimum number of repeat motifs. From this SSR mining algorithm, we developed an SSR sequence analysis software (named "regexSSRw") that is capable of mining eligible SSR loci from FASTA format sequences; regexSSRw can be accessed at https://github.com/renm79/rgxSSRw. This SSR mining algorithm can aid a range of applications, from being used by programmers in the development of SSR mining software to being implemented by scholars into their SSR marker workflow.