Learn More
The olfactory bulb plays a central role in olfactory information processing through its connections with both peripheral and cortical structures. Axons projecting from the olfactory bulb to the telencephalon are guided by a repulsive activity in the septum. The molecular nature of the repellent is not known. We report here the isolation of vertebrate(More)
Formation of the normal mammalian cerebral cortex requires the migration of GABAergic inhibitory interneurons from an extracortical origin, the lateral ganglionic eminence (LGE). Mechanisms guiding the migratory direction of these neurons, or other neurons in the neocortex, are not well understood. We have used an explant assay to study GABAergic neuronal(More)
AIMS Previous studies have revealed that the increased shedding of syncytiotrophoblast extracellular vesicles (STBM) may lead to preeclampsia (PE). We aimed to identify the proteins carried by STBM and their potential pathological roles in early-onset severe PE. METHODS In this study, we performed a differential proteomic analysis of STBM from early-onset(More)
A system is described that amplifies an electroneurographic signal (ENG) from a tripolar electrode nerve cuff and transmits it from the implanted amplifier to an external drive box. The output was raw ENG, bandpass filtered from 800 to 8000 Hz. The implant was powered by radio-frequency induction and operated for coil-to-coil separations up to 30 mm. The(More)
Huanglongbing (HLB) is a destructive disease of citrus trees caused by phloem-limited bacteria, Candidatus Liberibacter spp. One of the early microscopic manifestations of HLB is excessive starch accumulation in leaf chloroplasts. We hypothesize that the causative bacteria in the phloem may intervene photoassimilate export, causing the starch to(More)
This dissertation proposes a new algorithm of distributed mining association rules using the improved Apriori algorithm, based on analyses and introduction of the basic concepts and algorithms of mining association rules and mining association rules in distributed databases. Using improved Apriori algorithm to directly produce all of local frequent itemset(More)
As a simple, effective and nonparametric classification method, k Nearest Neighbor (KNN) is widely used in document classification for dealing with the much more difficult problem such as large-scale or many of categories. But KNN classifier may have a problem when training samples are uneven. The problem is that KNN classifier may decrease the precision of(More)