3,546 research outputs found
Memristor-Based Edge Detection for Spike Encoded Pixels
Memristors have many uses in machine learning and neuromorphic hardware. From
memory elements in dot product engines to replicating both synapse and neuron wall
behaviors, the memristor has proved a versatile component. Here we demonstrate
an analog mode of operation observed in our silicon oxide memristors and apply this
to the problem of edge detection. We demonstrate how a potential divider exploiting
this analog behavior can prove a scalable solution to edge detection. We confirm its
behavior experimentally and simulate its performance on a standard testbench. We show
good performance comparable to existing memristor based work with a benchmark
score of 0.465 on the BSDS500 dataset, while simultaneously maintaining a lower
component count
Improving the accuracy of defect mobilities and observing interface effects of resistive switching memories using the current transient phenomenon
Reference-free detection of semiconductor assembly defect
This paper aims at developing a novel defect detection algorithm for the semiconductor assembly process by image analysis of a single captured image, without reference to another image during inspection. The integrated circuit (IC) pattern is usually periodic and regular. Therefore, we can implement a classification scheme whereby the regular pattern in the die image is classified as the acceptable circuit pattern and the die defect can be modeled as irregularity on the image. The detection of irregularity in image is thus equivalent to the detection of die defect. We propose a method where the defect detection algorithm first segments the die image into different regions according to the circuit pattern by a set of morphological segmentations with different structuring element sizes. Then, a feature vector, which consists of many image attributes, is calculated for each segmented region. Lastly, the defective region is extracted by the feature vector classification. © 2005 SPIE and IS&T.published_or_final_versio
Kinetic Analysis of Discrete Path Sampling Stationary Point Databases
Analysing stationary point databases to extract phenomenological rate
constants can become time-consuming for systems with large potential energy
barriers. In the present contribution we analyse several different approaches
to this problem. First, we show how the original rate constant prescription
within the discrete path sampling approach can be rewritten in terms of
committor probabilities. Two alternative formulations are then derived in which
the steady-state assumption for intervening minima is removed, providing both a
more accurate kinetic analysis, and a measure of whether a two-state
description is appropriate. The first approach involves running additional
short kinetic Monte Carlo (KMC) trajectories, which are used to calculate
waiting times. Here we introduce `leapfrog' moves to second-neighbour minima,
which prevent the KMC trajectory oscillating between structures separated by
low barriers. In the second approach we successively remove minima from the
intervening set, renormalising the branching probabilities and waiting times to
preserve the mean first-passage times of interest. Regrouping the local minima
appropriately is also shown to speed up the kinetic analysis dramatically at
low temperatures. Applications are described where rates are extracted for
databases containing tens of thousands of stationary points, with effective
barriers that are several hundred times kT.Comment: 28 pages, 1 figure, 4 table
2-Substituted-2,3-dihydro-1H-quinolin-4-ones via Acid-Catalyzed Tandem Rupe Rearrangement-Donnelly-Farrell Ring Closure of 2-(3 '-Hydroxypropynyl)anilines
Secretin facilitates GABA transmission in the cerebellum
Secretin was the first hormone discovered in human history, and yet, its function as a neuropeptide has been overlooked in the past. The recent discovery of the potential use of secretin in treating autistic patients, together with the conflicting reports on its effectiveness, urges an in-depth investigation of this issue. We show here that in the rat cerebellar cortex, mRNAs encoding secretin are localized in the Purkinje cells, whereas those of its receptor are found in both Purkinje cells and GABAergic interneurons. Immunoreactivity for secretin is localized in the soma and dendrites of Purkinje cells. In addition, secretin facilitates evoked, spontaneous, and miniature IPSCs recorded from Purkinje cells. We propose that secretin is released from the somatodendritic region of Purkinje cells and serves as a retrograde messenger modulating GABAergic afferent activity.published_or_final_versio
Controlling and modelling the wetting properties of III-V semiconductor surfaces using re-entrant nanostructures
Inorganic semiconductors such as III-V materials are very important in our everyday life as they are used
for manufacturing optoelectronic and microelectronic components with important applications span
from energy harvesting to telecommunications. In some applications, these components are required
to operate in harsh environments. In these cases, having waterproofng capability is essential. Here
we demonstrate design and control of the wettability of indium phosphide based multilayer material
(InP/InGaAs/InP) using re-entrant structures fabricated by a fast electron beam lithography technique.
This patterning technique enabled us to fabricate highly uniform nanostructure arrays with at least
one order of magnitude shorter patterning times compared to conventional electron beam lithography
methods. We reduced the surface contact fraction signifcantly such that the water droplets may be
completely removed from our nanostructured surface. We predicted the wettability of our patterned
surface by modelling the adhesion energies between the water droplet and both the patterned
surface and the dispensing needle. This is very useful for the development of coating-free waterproof
optoelectronic and microelectronic components where the coating may hinder the performance of such
devices and cause problems with semiconductor fabrication compatibility
Incidence and predictors of upper gastrointestinal bleeding in patients receiving low-dose aspirin for secondary prevention of cardiovascular events in patients with coronary artery disease
Aim: The use of low-dose aspirin to prevent cardiovascular disease events is well established. However, the incidence and predictors of upper gastrointestinal bleeding (UGIB) with its use are unknown. We studied prospectively the incidence and outcome of peptic ulceration in low-dose aspirin users. Methods: A total of 991 patients with coronary artery disease (CAD) on low-dose aspirin were prospectively followed-up for two years for the occurrence and clinical features of first hospitalized episode of UGIB. Results: UGIB had a bimodal presentation with 45% occurring within four months of aspirin initiation and had an overall prevalence of 1.5% per year. There was no UGIB-related death. Hypertension (OR = 4.6, 95%CI 1.5 - 14.7, P = 0.009), history of peptic ulceration (OR = 3.1, 95%CI 1.1 - 9.0, P = 0.039), tertiary education (OR = 3.08, 95%CI 1.1 - 9.0, P = 0.039) and higher lean body mass (P = 0.016) were independent factors associated with UGIB. Use of nitrate did not reduce UGIB. Conclusion: The incidence of UGIB in patients with CAD on long-term low-dose aspirin is low, but is accompanied with significant morbidity. With prolonged use of aspirin, UGIB continues to be a problem for those with risk factors and especially in patients with a history of peptic ulcers, in which UGIB tends to occur early after aspirin therapy. © 2006 The WJG Press. All rights reserved.published_or_final_versio
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