781,117 research outputs found
Overnight consolidation aids the transfer of statistical knowledge from the medial temporal lobe to the striatum
Sleep is important for abstraction of the underlying principles (or gist) which bind together conceptually related stimuli, but little is known about the neural correlates of this process. Here, we investigate this issue using overnight sleep monitoring and functional magnetic resonance imaging (fMRI). Participants were exposed to a statistically structured sequence of auditory tones then tested immediately for recognition of short sequences which conformed to the learned statistical pattern. Subsequently, after consolidation over either 30min or 24h, they performed a delayed test session in which brain activity was monitored with fMRI. Behaviorally, there was greater improvement across 24h than across 30min, and this was predicted by the amount of slow wave sleep (SWS) obtained. Functionally, we observed weaker parahippocampal responses and stronger striatal responses after sleep. Like the behavioral result, these differences in functional response were predicted by the amount of SWS obtained. Furthermore, connectivity between striatum and parahippocampus was weaker after sleep, whereas connectivity between putamen and planum temporale was stronger. Taken together, these findings suggest that abstraction is associated with a gradual shift from the hippocampal to the striatal memory system and that this may be mediated by SWS
DOH: A Content Delivery Peer-to-Peer Network
Many SMEs and non-pro¯t organizations su®er when their Web
servers become unavailable due to °ash crowd e®ects when their web site
becomes popular. One of the solutions to the °ash-crowd problem is to place
the web site on a scalable CDN (Content Delivery Network) that replicates
the content and distributes the load in order to improve its response time.
In this paper, we present our approach to building a scalable Web Hosting
environment as a CDN on top of a structured peer-to-peer system of collaborative
web-servers integrated to share the load and to improve the overall
system performance, scalability, availability and robustness. Unlike clusterbased
solutions, it can run on heterogeneous hardware, over geographically
dispersed areas. To validate and evaluate our approach, we have developed a
system prototype called DOH (DKS Organized Hosting) that is a CDN implemented
on top of the DKS (Distributed K-nary Search) structured P2P
system with DHT (Distributed Hash table) functionality [9]. The prototype
is implemented in Java, using the DKS middleware, the Jetty web-server, and
a modi¯ed JavaFTP server. The proposed design of CDN has been evaluated
by simulation and by evaluation experiments on the prototype
Community Lynching and the US Asthma Epidemic
We explore the implications of IR Cohen's work on immune cognition for understanding rising rates of asthma morbidity and mortality in the US. Immune cognition is inherently linked with central nervous system cognition, and with the cognitive function of the embedding sociocultural networks by which individuals are acculturated and through which they work with others to meet challenges of threat and opportunity. Externally-imposed patterns of 'structured stress' can, through their effect on a child's socioculture, become synergistic with the development of immune cognition, triggering the persistence of an atopic Th2 phenotype, a necessary precursor to asthma and other immune diseases. Structured stress in the US particularly includes the cross sectional and longitudinal effects of a systematic destruction of minority urban communities occurring since the end of World War II which we characterize as community lynching. Reversal of the rising tide of asthma and related chronic diseases in the US thus seems unlikely without a 21st Century version of the earlier Great Urban Reforms which ended the scourge of infectious diseases, in particular an end to the de-facto ethnic cleansing of minority neighborhoo
Immune cognition, social justice and asthma: structured stress and the developing immune system
We explore the implications of IR Cohen's work on immune
cognition for understanding rising rates of asthma morbidity
and mortality in the US. Immune cognition is conjoined with
central nervous system cognition, and with the cognitive
function of the embedding sociocultural networks by which
individuals are acculturated and through which they work with others to meet challenges of threat and opportunity.
Using a mathematical model, we find that externally-
imposed patterns of 'structured stress' can, through their
effect on a child's socioculture, become synergistic with
the development of immune cognition, triggering the persistence of an atopic Th2 phenotype, a necessary precursor to asthma and other immune disease. Reversal of the rising tide of asthma and related chronic diseases in the US thus seems unlikely without a 21st Century version of the earlier Great Urban Reforms which ended the scourge of infectious diseases
Optimally Efficient Prefix Search and Multicast in Structured P2P Networks
Searching in P2P networks is fundamental to all overlay networks.
P2P networks based on Distributed Hash Tables (DHT) are optimized for single
key lookups, whereas unstructured networks offer more complex queries at the
cost of increased traffic and uncertain success rates. Our Distributed Tree
Construction (DTC) approach enables structured P2P networks to perform prefix
search, range queries, and multicast in an optimal way. It achieves this by
creating a spanning tree over the peers in the search area, using only
information available locally on each peer. Because DTC creates a spanning
tree, it can query all the peers in the search area with a minimal number of
messages. Furthermore, we show that the tree depth has the same upper bound as
a regular DHT lookup which in turn guarantees fast and responsive runtime
behavior. By placing objects with a region quadtree, we can perform a prefix
search or a range query in a freely selectable area of the DHT. Our DTC
algorithm is DHT-agnostic and works with most existing DHTs. We evaluate the
performance of DTC over several DHTs by comparing the performance to existing
application-level multicast solutions, we show that DTC sends 30-250% fewer
messages than common solutions
Measuring and Managing Answer Quality for Online Data-Intensive Services
Online data-intensive services parallelize query execution across distributed
software components. Interactive response time is a priority, so online query
executions return answers without waiting for slow running components to
finish. However, data from these slow components could lead to better answers.
We propose Ubora, an approach to measure the effect of slow running components
on the quality of answers. Ubora randomly samples online queries and executes
them twice. The first execution elides data from slow components and provides
fast online answers; the second execution waits for all components to complete.
Ubora uses memoization to speed up mature executions by replaying network
messages exchanged between components. Our systems-level implementation works
for a wide range of platforms, including Hadoop/Yarn, Apache Lucene, the
EasyRec Recommendation Engine, and the OpenEphyra question answering system.
Ubora computes answer quality much faster than competing approaches that do not
use memoization. With Ubora, we show that answer quality can and should be used
to guide online admission control. Our adaptive controller processed 37% more
queries than a competing controller guided by the rate of timeouts.Comment: Technical Repor
Network constraints on learnability of probabilistic motor sequences
Human learners are adept at grasping the complex relationships underlying
incoming sequential input. In the present work, we formalize complex
relationships as graph structures derived from temporal associations in motor
sequences. Next, we explore the extent to which learners are sensitive to key
variations in the topological properties inherent to those graph structures.
Participants performed a probabilistic motor sequence task in which the order
of button presses was determined by the traversal of graphs with modular,
lattice-like, or random organization. Graph nodes each represented a unique
button press and edges represented a transition between button presses. Results
indicate that learning, indexed here by participants' response times, was
strongly mediated by the graph's meso-scale organization, with modular graphs
being associated with shorter response times than random and lattice graphs.
Moreover, variations in a node's number of connections (degree) and a node's
role in mediating long-distance communication (betweenness centrality) impacted
graph learning, even after accounting for level of practice on that node. These
results demonstrate that the graph architecture underlying temporal sequences
of stimuli fundamentally constrains learning, and moreover that tools from
network science provide a valuable framework for assessing how learners encode
complex, temporally structured information.Comment: 29 pages, 4 figure
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