We present the design of the eXtreme Scale Mote, a new sensor network platform for reliably detecting and classifying, and quickly reporting, rare, random, and ephemeral events in a largescale, long-lived, and retaskable manner. This new mote was designed for the ExScal project which seeks to demonstrate a 10,000 node network capable of discriminating civilians, soldiers and vehicles, spread out over a 10km 2 area, with node lifetimes approaching 1,000 hours of continuous operation on two AA alkaline batteries. This application posed unique functional, usability, scalability, and robustness requirements which could not be met with existing hardware, and therefore motivated the design of a new platform. The detection and classification requirements are met using infrared, magnetic, and acoustic sensors. The infrared and acoustic sensors are designed for low-power continuous operation and include asynchronous processor wakeup circuitry. The usability and scalability requirements are met by minimizing the frequency and cost of human-in-the-loop operations during node deployment, activation, and verification through improvements in the user interface, packaging, and configurability of the platform. Recoverable retasking is addressed by using a grenade timer that periodically forces a system reset. The key contributions of this work are a specific design point and general design methods for building sensor network platforms to detect exceptional events.
As the world population grows, there is a pressing need to improve productivity from water use in irrigated and rain-fed agriculture. Foliar diseases have been reported to decrease crop water-use efficiency (WUE) substantially, yet the effects of plant pathogens are seldom considered when methods to improve WUE are debated. We review the effects of foliar pathogens on plant water relations and the consequences for WUE. The effects reported vary between host and pathogen species and between host genotypes. Some general patterns emerge however. Higher fungi and oomycetes cause physical disruption to the cuticle and stomata, and also cause impairment of stomatal closing in the dark. Higher fungi and viruses are associated with impairment of stomatal opening in the light. A number of toxins produced by bacteria and higher fungi have been identified that impair stomatal function. Deleterious effects are not limited to compatible plant-pathogen interactions. Resistant and non-host interactions have been shown to result in stomatal impairment in light and dark conditions. Mitigation of these effects through selection of favourable resistance responses could be an important breeding target in the future. The challenges for researchers are to understand how the effects reported from work under controlled conditions translate to crops in the field, and to elucidate underlying mechanisms.
Rhizomania is a soil-borne disease that occurs throughout the major sugar beet growing regions of the world, causing severe yield losses in the absence of effective control measures. It is caused by Beet necrotic yellow vein virus (BNYVV), which is transmitted by the obligate root-infecting parasite Polymyxa betae. BNYVV has a multipartite RNA genome with all natural isolates containing four RNA species, although some isolates have a fifth RNA. The larger RNA1 and RNA2 contain the housekeeping genes of the virus and are always required for infection, whereas the smaller RNAs are involved in pathogenicity and vector transmission. RNA5-containing isolates are restricted to Asia and some parts of Europe, and these isolates tend to be more aggressive. With no acceptable pesticides available to restrict the vector, the control of rhizomania is now achieved almost exclusively through the use of resistant cultivars. A single dominant resistance gene, Rz1, has been used to manage the disease worldwide in recent years, although this gene confers only partial resistance. More recently, new variants of BNYVV have evolved (both with and without RNA5) that are able to cause significant yield penalties on resistant cultivars. These isolates are not yet widespread, but their appearance has resulted in accelerated searches for new sources of resistance to both the virus and the vector. Combined virus and vector resistance, achieved either by conventional or transgenic breeding, offers the sugar beet industry a new approach in its continuing struggle against rhizomania.
SummaryThe maize endosperm transcriptome was investigated through cDNA libraries developed at three characteristic stages: (i) lag phase [10 days after pollination (DAP)]; (ii) beginning of storage (14 DAP); and (iii) maximum starch accumulation rate (21 DAP). Expressed sequence tags for 711, 757 and 384 relevant clones, respectively, were obtained and checked manually. The proportion of sequences with no clear function decreased from 35% to 20%, and a large increase in storage protein sequences (i.e. 5% to 38%) was observed from stages (i) to (iii). The remaining major categories included metabolism (11%-13%), transcription-RNA processing-protein synthesis (13%-20%), protein destination (5%-9%), cellular communication (3%-9%) and cell rescue-defence (4%).Good agreement was generally found between category rank in the 10-DAP transcriptome and the recently reported 14-DAP proteome, except that kinases and proteins for RNA processing were not detected in the latter. In the metabolism category, the respiratory pathway transcripts represented the largest proportion (25%-37%), and showed a shift in favour of glycolysis at 21 DAP. At this stage, amino acid metabolism increased to 17%, whereas starch metabolism surprisingly decreased to 7%. A second experiment focused on carbohydrate metabolism by comparing gene expression at three levels (transcripts, proteins and enzyme activities) in relation to substrate or product from 10 to 40 DAP. Here, two distinct patterns were observed: invertases and hexoses were predominant at the beginning, whereas enzyme patterns in the starch pathway, at the three levels, anticipated and paralleled starch accumulation, suggesting that, in most cases, transcriptional control is responsible for the regulation of starch biosynthesis.
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