1,237 research outputs found
Use of genetic algorithms and gradient based optimization techniques for calcium phosphate precipitation
Phase equilibrium computations constitute an important problem for designing and optimizing crystallization processes. The Gibbs free
energy is generally used as an objective function to find phase amount and composition at equilibrium. In such problems, the Gibbs free
energy may be a quite complex function, with several local minima. This paper presents a contribution to handle this kind of problems by
implementation of an optimization technique based on the successive use of a genetic algorithm (GA) and of a classical sequential quadratic
programming (SQP) method: the GA is used to perform a preliminary search in the solution space for locating the neighborhood of the
solution. Then, the SQP method is employed to refine the best solution provided by the GA. The basic operations involved in the design of
the GA developed in this study (encoding with binary representation of real values, evaluation function, adaptive plan) are presented. Several
test problems are first presented to demonstrate the validity of the approach. Then, calcium phosphate precipitation which is of major interest
for P-recovery from wastewater, has been chosen as an illustration of the implemented algorithm
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Mild Cognitive Impairment in the Elderly is Associated with Volume Loss of the Cholinergic Basal Forebrain Region
Background
Cholinergic neurons within the basal forebrain are assumed to be an early (preclinical) manifestation site of pathological changes in Alzheimer's disease (AD).
Methods
We used morphometric magnetic resonance imaging (MRI) to detect and quantify atrophic changes in the basal forebrain of subjects suffering from amnestic mild cognitive impairment (aMCI). Three Tesla magnetic resonance (MR) data of 26 aMCI patients, 46 cognitively normal elderly control subjects (CO), and 12 patients suffering from Alzheimer's dementia were analyzed, including segmentation and quantification of brain tissue as well as a segmentation of basal forebrain structures (substantia innominata [SI]).
Results
We found the volume of the SI to be significantly different between groups in that control subjects showed the largest SI volumes, followed by aMCI and AD patients.
Conclusions
These results are in line with the hypothesis that cell loss within the cholinergic basal forebrain regions occurs already in the early (predementia) stage of AD. In vivo quantification of these changes might be of use as a novel neuroimaging marker of cholinergic neurodegeneration in AD
Effects of Air Pollution on Heart Rate Variability: The VA Normative Aging Study
Reduced heart rate variability (HRV), a marker of poor cardiac autonomic function, has been associated with air pollution, especially fine particulate matter [< 2.5 μm in aerodynamic diameter (PM(2.5))]. We examined the relationship between HRV [standard deviation of normal-to-normal intervals (SDNN), power in high frequency (HF) and low frequency (LF), and LF:HF ratio] and ambient air pollutants in 497 men from the Normative Aging Study in greater Boston, Massachusetts, seen between November 2000 and October 2003. We examined 4-hr, 24-hr, and 48-hr moving averages of air pollution (PM(2.5), particle number concentration, black carbon, ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide). Controlling for potential confounders, HF decreased 20.8% [95% confidence interval (CI), 4.6–34.2%] and LF:HF ratio increased 18.6% (95% CI, 4.1–35.2%) per SD (8 μg/m(3)) increase in 48-hr PM(2.5). LF was reduced by 11.5% (95% CI, 0.4–21.3%) per SD (13 ppb) increment in 4-hr O(3). The associations between HRV and PM(2.5) and O(3) were stronger in people with ischemic heart disease (IHD) and hypertension. The associations observed between SDNN and LF and PM(2.5) were stronger in people with diabetes. People using calcium-channel blockers and beta-blockers had lower associations between O(3) and PM(2.5) with LF. No effect modification by other cardiac medications was found. Exposures to PM(2.5) and O(3) are associated with decreased HRV, and history of IHD, hypertension, and diabetes may confer susceptibility to autonomic dysfunction by air pollution
An Approach to Web-Scale Named-Entity Disambiguation
We present a multi-pass clustering approach to large scale. wide-scope named-entity disambiguation (NED) oil collections of web pages. Our approach Uses name co-occurrence information to cluster and hence disambiguate entities. and is designed to handle NED on the entire web. We show that on web collections, NED becomes increasing), difficult as the corpus size increases, not only because of the challenge of scaling the NED algorithm, but also because new and surprising facets of entities become visible in the data. This effect limits the potential benefits for data-driven approaches of processing larger data-sets, and suggests that efficient clustering-based disambiguation methods for the web will require extracting more specialized information front documents
Electroresistance effects in ferroelectric tunnel barriers
Electron transport through fully depleted ferroelectric tunnel barriers
sandwiched between two metal electrodes and its dependence on ferroelectric
polarization direction are investigated. The model assumes a polarization
direction dependent ferroelectric barrier. The transport mechanisms, including
direct tunneling, Fowler-Nordheim tunneling and thermionic injection, are
considered in the calculation of the electroresistance as a function of
ferroelectric barrier properties, given by the properties of the ferroelectric,
the barrier thickness, and the metal properties, and in turn of the
polarization direction. Large electroresistance is favored in thicker films for
all three transport mechanisms but on the expense of current density. However,
switching between two transport mechanisms, i.e., direct tunneling and
Fowler-Nordheim tunneling, by polarization switching yields a large
electroresistance. Furthermore, the most versatile playground in optimizing the
device performance was found to be the electrode properties, especially
screening length and band offset with the ferroelectric.Comment: 24pages, 7 figures, revised, one figure adde
Improving estimation and prediction in linear regression incorporating external information from an established reduced model
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143779/1/sim7600_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143779/2/sim7600.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143779/3/sim7600-sup-0001-Supplementary.pd
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Structural equation modeling of parasympathetic and sympathetic response to traffic air pollution in a repeated measures study
Background: Traffic-related air pollution has been associated to a range of adverse health impacts, including decreased heart rate variability (HRV). The association between traffic-related pollution and HRV, however, has varied by traffic-related or HRV marker as well as by study, suggesting the need for a more comprehensive and integrative approach to examining air pollution-mediated biological impacts on these outcomes. In a Bayesian framework, we examined the effect of traffic pollution on HRV using structural equation models (SEMs) and looked at effect modification by participant characteristics. Methods: We studied measurements of 5 HRV markers [high frequency (HF), low frequency (LF), 5-min standard deviation of normal-to-normal intervals (SDNN), square root of the mean squared differences of successive normal-to-normal intervals (rMSSD), and LF/HF ratio (LF/HF)] for 700 elderly men from the Normative Aging Study. Using SEMs, we fit a latent variable for traffic pollution that is reflected by levels of carbon monoxide, nitrogen monoxide, nitrogen dioxide, and black carbon (BC) to estimate its effect on latent variable for parasympathetic tone that included HF, SDNN and rMSSD, and the sympathetic tone marker, LF/HF. Exposure periods were assessed using 4-, 24-, 48-, 72-hour moving average pre-visit. We compared our main effect findings using SEMs with those obtained using linear mixed models. Results: Traffic pollution was not associated with mean parasympathetic tone and LF/HF for all examined moving averages. In Bayesian linear mixed models, however, BC was related to increased LF/HF, an inter quartile range (IQR) increase in BC was associated with a 6.5% (95% posterior interval (PI): -0.7%, 14.2%) increase in mean LF/HF 24-hours later. The strongest association observed was for the 4-hour moving average (10.1%; 95% PI: 3.0%, 17.6%). The effect of traffic on parasympathetic tone was stronger among diabetic as compared to non-diabetic participants. Specifically, an IQR increase in traffic pollution in the 48-hr prior to the clinic visit was associated with a 44.3% (95% PI: -67.7%, -4.2%) lower mean parasympathetic tone among diabetics, and a 7.7% (95% PI: -18.0%, 41.4%) higher mean parasympathetic tone among non-diabetics. Conclusions: BC was associated with adverse changes LF/HF in the elderly. Traffic pollution may decrease parasympathetic tone among diabetic elderly
Document Filtering for Long-tail Entities
Filtering relevant documents with respect to entities is an essential task in
the context of knowledge base construction and maintenance. It entails
processing a time-ordered stream of documents that might be relevant to an
entity in order to select only those that contain vital information.
State-of-the-art approaches to document filtering for popular entities are
entity-dependent: they rely on and are also trained on the specifics of
differentiating features for each specific entity. Moreover, these approaches
tend to use so-called extrinsic information such as Wikipedia page views and
related entities which is typically only available only for popular head
entities. Entity-dependent approaches based on such signals are therefore
ill-suited as filtering methods for long-tail entities. In this paper we
propose a document filtering method for long-tail entities that is
entity-independent and thus also generalizes to unseen or rarely seen entities.
It is based on intrinsic features, i.e., features that are derived from the
documents in which the entities are mentioned. We propose a set of features
that capture informativeness, entity-saliency, and timeliness. In particular,
we introduce features based on entity aspect similarities, relation patterns,
and temporal expressions and combine these with standard features for document
filtering. Experiments following the TREC KBA 2014 setup on a publicly
available dataset show that our model is able to improve the filtering
performance for long-tail entities over several baselines. Results of applying
the model to unseen entities are promising, indicating that the model is able
to learn the general characteristics of a vital document. The overall
performance across all entities---i.e., not just long-tail entities---improves
upon the state-of-the-art without depending on any entity-specific training
data.Comment: CIKM2016, Proceedings of the 25th ACM International Conference on
Information and Knowledge Management. 201
Forced Expiratory Volume in 1 Second and Cognitive Aging in Men
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87022/1/j.1532-5415.2011.03487.x.pd
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