Rapid virological surveillance of community influenza infection in general practice

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Alleviating Naive Bayes attribute independence assumption by attribute weighting

Despite the simplicity of the Naive Bayes classifier, it has continued to perform well against more sophisticated newcomers and has remained, therefore, of great interest to the machine learning community. Of numerous approaches to refining the naive Bayes classifier, attribute weighting has received less attention than it warrants. Most approaches, perhaps influenced by attribute weighting in other machine learning algorithms, use weighting to place more emphasis on highly predictive attributes than those that are less predictive. In this paper, we argue that for naive Bayes attribute weighting should instead be used to alleviate the conditional independence assumption. Based on this premise, we propose a weighted naive Bayes algorithm, called WANBIA, that selects weights to minimize either the negative conditional log likelihood or the mean squared error objective functions. We perform extensive evaluations and find that WANBIA is a competitive alternative to state of the art classifiers like Random Forest, Logistic Regression and A1DE. © 2013 Nayyar A. Zaidi, Jesus Cerquides, Mark J. Carman and Geoffrey I. Webb.This research has been supported by the Australian Research Council under grant DP110101427 and Asian Office of Aerospace Research and Development, Air Force Office of Scientific Research under contract FA23861214030. The authors would like to thank Mark Hall for providing the code for CFS and MH. The authors would also like to thank anonymous reviewers for their insightful comments that helped improving the paper tremendously.Peer Reviewe

Clogging by sieving in microchannels: Application to the detection of contaminants in colloidal suspensions

We report on a microfluidic method that allows measurement of a small concentration of large contaminants in suspensions of solid micrometer-scale particles. To perform the measurement, we flow the colloidal suspension through a series of constrictions, i.e. a microchannel of varying cross-section. We show and quantify the role of large contaminants in the formation of clogs at a constriction and the growth of the resulting filter cake. By measuring the time interval between two clogging events in an array of parallel microchannels, we are able to estimate the concentration of contaminants whose size is selected by the geometry of the microfluidic device. This technique for characterizing colloidal suspensions offers a versatile and rapid tool to explore the role of contaminants on the properties of the suspensions

Coherent control using adaptive learning algorithms

We have constructed an automated learning apparatus to control quantum systems. By directing intense shaped ultrafast laser pulses into a variety of samples and using a measurement of the system as a feedback signal, we are able to reshape the laser pulses to direct the system into a desired state. The feedback signal is the input to an adaptive learning algorithm. This algorithm programs a computer-controlled, acousto-optic modulator pulse shaper. The learning algorithm generates new shaped laser pulses based on the success of previous pulses in achieving a predetermined goal.Comment: 19 pages (including 14 figures), REVTeX 3.1, updated conten

Drying of complex suspensions

We investigate the 3D structure and drying dynamics of complex mixtures of emulsion droplets and colloidal particles, using confocal microscopy. Air invades and rapidly collapses large emulsion droplets, forcing their contents into the surrounding porous particle pack at a rate proportional to the square of the droplet radius. By contrast, small droplets do not collapse, but remain intact and are merely deformed. A simple model coupling the Laplace pressure to Darcy's law correctly estimates both the threshold radius separating these two behaviors, and the rate of large-droplet evacuation. Finally, we use these systems to make novel hierarchical structures.Comment: 4 pages, 4 figure

Risk of Depression in a Suburban Primary Care Setting Before and During the COVID-19 Pandemic.

INTRODUCTION: Major depression is a common disorder affecting millions of adults each year. Many population-based surveys showed an increase in the number people with symptoms of depression at the onset of the COVID-19 pandemic. Our aim was to determine and compare the prevalence of depression risk in a primary care setting before and during the COVID-19 pandemic. METHODS: We conducted a cross-sectional study based on retrospective review of medical records from a large suburban primary care clinic. Records of adults 18 years and older, seen between January 1, 2019 and December 31, 2020 and who had also been screened for depression using the 9-item Patient Health Questionnaire (PHQ-9) were analyzed. RESULTS: Adults 18 years and older who completed the PHQ-9 assessment in 2019 and 2020 were 5078 and 4338, respectively. Risk of depression was 18.2% in 2019 and 14.8% in 2020 ( CONCLUSION: Although our results did not reflect the published literature reporting a higher prevalence of depression during the COVID-19 pandemic, they were consistent with reports of increased risk in females and younger adults

Generation of ultra-short light pulses by a rapidly ionizing thin foil

A thin and dense plasma layer is created when a sufficiently strong laser pulse impinges on a solid target. The nonlinearity introduced by the time-dependent electron density leads to the generation of harmonics. The pulse duration of the harmonic radiation is related to the risetime of the electron density and thus can be affected by the shape of the incident pulse and its peak field strength. Results are presented from numerical particle-in-cell-simulations of an intense laser pulse interacting with a thin foil target. An analytical model which shows how the harmonics are created is introduced. The proposed scheme might be a promising way towards the generation of attosecond pulses. PACS number(s): 52.40.Nk, 52.50.Jm, 52.65.RrComment: Second Revised Version, 13 pages (REVTeX), 3 figures in ps-format, submitted for publication to Physical Review E, WWW: http://www.physik.tu-darmstadt.de/tqe