Design of a Highly Portable Data Logging Embedded System for Naturalistic Motorcycle Study

According to Motorcycle Industrial Council (MIC), in USA the number of owned motorcycle increased during last few years and most likely will keep increasing. However, the number of the deadly crash accidents associated with motorcycles is on the rise. Although MIC doesn\u27t explain why the accident rate has increased, the unprotected motorcyclist gear can be one of the reasons. The most recent National Highway Traffic Safety Administration (NHTSA) annual report stated that its data analyses are based on their experiences and the best judgment is not based on solid scientific experiment [3]. Thus, building a framework for the data acquisition about the motorcyclist environment is a first step towards decreasing motorcyclist crashes. There are a few naturalistic motorcycle studies reported in the literature. The naturalistic motorcycle study also identifies the behaviors and environmental crash hazards. The primary objective of this thesis work is to design a highly portable data logging embedded system for naturalistic motorcycle study with capability of collecting many types of data such as images, speed, acceleration, time, location, distance approximation, etc. This thesis work is the first phase (of three phases) of a naturalistic motorcycle study project. The second phase is to optimize system area, form factor, and power consumption. The third phase will be concerned with aggressive low power design and energy harvesting. The proposed embedded system design is based on an Arduino microcontroller. A whole suite of Arduino based prototype boards, sensor boards, support software, and user forum is available. The system is high portable with capability to store up to eight (8) hours of text/image data during a one month study period. We have successfully designed and implemented the system and performed three trial runs. The data acquired has been validated and found to be accurate

Functional annotation of the transcriptome of Sorghum bicolor in response to osmotic stress and abscisic acid

<p>Abstract</p> <p>Background</p> <p>Higher plants exhibit remarkable phenotypic plasticity allowing them to adapt to an extensive range of environmental conditions. Sorghum is a cereal crop that exhibits exceptional tolerance to adverse conditions, in particular, water-limiting environments. This study utilized next generation sequencing (NGS) technology to examine the transcriptome of sorghum plants challenged with osmotic stress and exogenous abscisic acid (ABA) in order to elucidate genes and gene networks that contribute to sorghum's tolerance to water-limiting environments with a long-term aim of developing strategies to improve plant productivity under drought.</p> <p>Results</p> <p>RNA-Seq results revealed transcriptional activity of 28,335 unique genes from sorghum root and shoot tissues subjected to polyethylene glycol (PEG)-induced osmotic stress or exogenous ABA. Differential gene expression analyses in response to osmotic stress and ABA revealed a strong interplay among various metabolic pathways including abscisic acid and 13-lipoxygenase, salicylic acid, jasmonic acid, and plant defense pathways. Transcription factor analysis indicated that groups of genes may be co-regulated by similar regulatory sequences to which the expressed transcription factors bind. We successfully exploited the data presented here in conjunction with published transcriptome analyses for rice, maize, and Arabidopsis to discover more than 50 differentially expressed, drought-responsive gene orthologs for which no function had been previously ascribed.</p> <p>Conclusions</p> <p>The present study provides an initial assemblage of sorghum genes and gene networks regulated by osmotic stress and hormonal treatment. We are providing an RNA-Seq data set and an initial collection of transcription factors, which offer a preliminary look into the cascade of global gene expression patterns that arise in a drought tolerant crop subjected to abiotic stress. These resources will allow scientists to query gene expression and functional annotation in response to drought.</p