Interaction Data

2010 ◽  
pp. 51-68 ◽  
Author(s):  
Oliver Duke-Williams
Keyword(s):  
Aggregate Data ◽  
Data Sets ◽  
Interaction Data ◽  
Disclosure Control ◽  
Data Form ◽  
Increased Risk ◽  
Different Types ◽  
Zero Values

As we saw in Chapter 1, interaction data sets have been derived from a number of sources, including censuses, other surveys and from a range of administrative sources. These typically have the characteristic that the data form large, sparsely populated matrices. Where the matrices do have non-zero values, those numbers are often small. This is highly significant when confidentiality is concerned – small numbers in aggregate data are generally seen as representing an increased risk of disclosure of data. This chapter looks at confidentiality issues with particular regard to interaction data. Different types of disclosure are considered, together with the reasons why interaction data are thought to pose particular disclosure problems. Methods of disclosure control are outlined, and then two particular methods are studied: those used in the 1991 and the 2001 UK Censuses. The methods used and the extent of their effects are described, and suggestions for how best to use the affected data sets are given.

The Small State Challenge

2018 ◽  
Author(s):  
Jack Corbett ◽  
Wouter Veenendaal
Keyword(s):  
Comparative Politics ◽  
Institutional Design ◽  
Small States ◽  
Small State ◽  
Informal Politics ◽  
Different Types ◽  
Approach Method ◽  
Key Terms ◽  
First Time

Chapter 1 introduces the main arguments of the book; outlines the approach, method, and data; defines key terms; and provides a chapter outline. Global theories of democratization have systematically excluded small states, which make up roughly 20 per cent of countries. These cases debunk mainstream theories of why democratization succeeds or fails. This book brings small states into the comparative politics fold for the first time. It is organized thematically, with each chapter tackling one of the main theories from the democratization literature. Different types of data are examined—case studies and other documentary evidence, interviews and observation. Following an abductive approach, in addition to examining the veracity of existing theory, each chapter is also used to build an explanation of how democracy is practiced in small states. Specifically, we highlight how small state politics is shaped by personalization and informal politics, rather than formal institutional design.

Epidemiological Evidence that Maternal Influenza Contributes to the Aetiology of Schizophrenia

1993 ◽  
Vol 163 (4) ◽  
pp. 522-534 ◽  
Author(s):  
W. Adams ◽  
R. E. Kendell ◽  
E. H. Hare ◽  
P. Munk-Jørgensen
Keyword(s):  
Data Sets ◽  
Time Lags ◽  
Epidemiological Evidence ◽  
Intrauterine Development ◽  
Increased Risk ◽  
Schizophrenic Patients ◽  
The Relationship ◽  
Monthly Incidence ◽  
Maternal Influenza

The epidemiological evidence that the offspring of women exposed to influenza in pregnancy are at increased risk of schizophrenia is conflicting. In an attempt to clarify the issue we explored the relationship between the monthly incidence of influenza (and measles) in the general population and the distribution of birth dates of three large series of schizophrenic patients - 16 960 Scottish patients born in 1932–60; 22 021 English patients born in 1921–60; and 18 723 Danish patients born in 1911–65. Exposure to the 1957 epidemic of A2 influenza in midpregnancy was associated with an increased incidence of schizophrenia, at least in females, in all three data sets. We also confirmed the previous report of a statistically significant long-term relationship between patients' birth dates and outbreaks of influenza in the English series, with time lags of - 2 and - 3 months (the sixth and seventh months of pregnancy). Despite several other negative studies by ourselves and others we conclude that these relationships are probably both genuine and causal; and that maternal influenza during the middle third of intrauterine development, or something closely associated with it, is implicated in the aetiology of some cases of schizophrenia.

scholarly journals Inter- and Intralaboratory Comparison of JC Polyomavirus Antibody Testing Using Two Different Virus-Like Particle-Based Assays

2014 ◽  
Vol 21 (11) ◽  
pp. 1581-1588 ◽  
Author(s):  
Piotr Kardas ◽  
Mohammadreza Sadeghi ◽  
Fabian H. Weissbach ◽  
Tingting Chen ◽  
Lea Hedman ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Data Sets ◽  
Antibody Testing ◽  
Jc Polyomavirus ◽  
Virus Like Particle ◽  
Interlaboratory Variability ◽  
Increased Risk ◽  
Basic Protocol ◽  
Data Points ◽  
Reference Serum

ABSTRACTJC polyomavirus (JCPyV) can cause progressive multifocal leukoencephalopathy (PML), a debilitating, often fatal brain disease in immunocompromised patients. JCPyV-seropositive multiple sclerosis (MS) patients treated with natalizumab have a 2- to 10-fold increased risk of developing PML. Therefore, JCPyV serology has been recommended for PML risk stratification. However, different antibody tests may not be equivalent. To study intra- and interlaboratory variability, sera from 398 healthy blood donors were compared in 4 independent enzyme-linked immunoassay (ELISA) measurements generating >1,592 data points. Three data sets (Basel1, Basel2, and Basel3) used the same basic protocol but different JCPyV virus-like particle (VLP) preparations and introduced normalization to a reference serum. The data sets were also compared with an independent method using biotinylated VLPs (Helsinki1). VLP preadsorption reducing ≥35% activity was used to identify seropositive sera. The results indicated that Basel1, Basel2, Basel3, and Helsinki1 were similar regarding overall data distribution (P= 0.79) and seroprevalence (58.0, 54.5, 54.8, and 53.5%, respectively;P= 0.95). However, intra-assay intralaboratory comparison yielded 3.7% to 12% discordant results, most of which were close to the cutoff (0.080 < optical density [OD] < 0.250) according to Bland-Altman analysis. Introduction of normalization improved overall performance and reduced discordance. The interlaboratory interassay comparison between Basel3 and Helsinki1 revealed only 15 discordant results, 14 (93%) of which were close to the cutoff. Preadsorption identified specificities of 99.44% and 97.78% and sensitivities of 99.54% and 95.87% for Basel3 and Helsinki1, respectively. Thus, normalization to a preferably WHO-approved reference serum, duplicate testing, and preadsorption for samples around the cutoff may be necessary for reliable JCPyV serology and PML risk stratification.

scholarly journals Machine learning for improved data analysis of biological aerosol using the WIBS

2018 ◽  
Vol 11 (11) ◽  
pp. 6203-6230 ◽  
Author(s):  
Simon Ruske ◽  
David O. Topping ◽  
Virginia E. Foot ◽  
Andrew P. Morse ◽  
Martin W. Gallagher
Keyword(s):  
Ultraviolet Light ◽  
Fungal Spores ◽  
Laboratory Data ◽  
Misclassification Rate ◽  
Gradient Boosting ◽  
Classification Error ◽  
Data Sets ◽  
Data Preparation ◽  
Different Types ◽  
Selection Of

Abstract. Primary biological aerosol including bacteria, fungal spores and pollen have important implications for public health and the environment. Such particles may have different concentrations of chemical fluorophores and will respond differently in the presence of ultraviolet light, potentially allowing for different types of biological aerosol to be discriminated. Development of ultraviolet light induced fluorescence (UV-LIF) instruments such as the Wideband Integrated Bioaerosol Sensor (WIBS) has allowed for size, morphology and fluorescence measurements to be collected in real-time. However, it is unclear without studying instrument responses in the laboratory, the extent to which different types of particles can be discriminated. Collection of laboratory data is vital to validate any approach used to analyse data and ensure that the data available is utilized as effectively as possible. In this paper a variety of methodologies are tested on a range of particles collected in the laboratory. Hierarchical agglomerative clustering (HAC) has been previously applied to UV-LIF data in a number of studies and is tested alongside other algorithms that could be used to solve the classification problem: Density Based Spectral Clustering and Noise (DBSCAN), k-means and gradient boosting. Whilst HAC was able to effectively discriminate between reference narrow-size distribution PSL particles, yielding a classification error of only 1.8 %, similar results were not obtained when testing on laboratory generated aerosol where the classification error was found to be between 11.5 % and 24.2 %. Furthermore, there is a large uncertainty in this approach in terms of the data preparation and the cluster index used, and we were unable to attain consistent results across the different sets of laboratory generated aerosol tested. The lowest classification errors were obtained using gradient boosting, where the misclassification rate was between 4.38 % and 5.42 %. The largest contribution to the error, in the case of the higher misclassification rate, was the pollen samples where 28.5 % of the samples were incorrectly classified as fungal spores. The technique was robust to changes in data preparation provided a fluorescent threshold was applied to the data. In the event that laboratory training data are unavailable, DBSCAN was found to be a potential alternative to HAC. In the case of one of the data sets where 22.9 % of the data were left unclassified we were able to produce three distinct clusters obtaining a classification error of only 1.42 % on the classified data. These results could not be replicated for the other data set where 26.8 % of the data were not classified and a classification error of 13.8 % was obtained. This method, like HAC, also appeared to be heavily dependent on data preparation, requiring a different selection of parameters depending on the preparation used. Further analysis will also be required to confirm our selection of the parameters when using this method on ambient data. There is a clear need for the collection of additional laboratory generated aerosol to improve interpretation of current databases and to aid in the analysis of data collected from an ambient environment. New instruments with a greater resolution are likely to improve on current discrimination between pollen, bacteria and fungal spores and even between different species, however the need for extensive laboratory data sets will grow as a result.

scholarly journals Replacement of Sedentary Behavior by Various Daily-Life Physical Activities and Structured Exercises: Genetic Risk and Incident Type 2 Diabetes

2021 ◽  
Author(s):  
Xiang Li ◽  
Tao Zhou ◽  
Hao Ma ◽  
Zhaoxia Liang ◽  
Vivian A Fonseca ◽  
...  
Keyword(s):  
Sedentary Behavior ◽  
Genetic Predisposition ◽  
Genetic Risk ◽  
Daily Life ◽  
Physical Activities ◽  
Sedentary Behaviors ◽  
Equal Time ◽  
Increased Risk ◽  
Different Types ◽  
Sedentary Behavior Time

<b>Objective: </b>To prospectively analyze the association of sedentary behavior time with T2D risk and perform the iso-temporal substitution analyses to estimate the effect of substituting sedentary behaviors by equal time of different types of daily-life physical activities and structured exercise. We also examined modifications by the genetic predisposition to T2D. <p><b>Research Design and Methods: </b>We included 475,502 participants free of T2D in the UK Biobank. Sedentary time was quantified by summing up the time spent on television watching, computer using, and driving.</p> <p><b>Results: </b>During a median follow-up of 11 years, we documented 18,169 incident T2D. Comparing the extreme categories (≥6 vs. <2 hours/day), the hazard ratio (HR) for T2D was 1.58 (95% CI, 1.47-1.71), after adjustment for age, race, sex, lifestyle factors, and other covariates. Replacing 30 minutes of sedentary behavior per day with an equal time of different types of daily-life activities and structured exercise were significantly associated with a 6-31% risk reduction of T2D, with strenuous sports showing the strongest (31%, 95% CI, 24%-37%) benefit. Moreover, we found a significant interaction between sedentary behavior and genetic predisposition on the risk of T2D (p-interaction=0.0008). The association was more profound among participants with a lower genetic risk of T2D.</p> <p><b>Conclusions: </b>Our study indicates that sedentary behavior time is associated with an increased risk of T2D; replacing sedentary behavior with a short-duration (30 minutes/day) daily-life physical activities or structured exercise is related to a significant reduction in T2D risk. Furthermore, such association was stronger among those with a lower genetic risk of T2D.</p>

scholarly journals WONKAandOOMMPPAA: analysis of protein–ligand interaction data to direct structure-based drug design

2017 ◽  
Vol 73 (3) ◽  
pp. 279-285
Author(s):  
Charlotte M. Deane ◽  
Ian D. Wall ◽  
Darren V. S. Green ◽  
Brian D. Marsden ◽  
Anthony R. Bradley
Keyword(s):  
Three Dimensional ◽  
Structural Data ◽  
Data Sets ◽  
Interaction Data ◽  
Activity Data ◽  
Ligand Interaction ◽  
Structure Based Drug Design ◽  
Web Based ◽  
Protein Ligand Interaction ◽  
Ligand Activity

In this work, two freely available web-based interactive computational tools that facilitate the analysis and interpretation of protein–ligand interaction data are described. Firstly,WONKA, which assists in uncovering interesting and unusual features (for example residue motions) within ensembles of protein–ligand structures and enables the facile sharing of observations between scientists. Secondly,OOMMPPAA, which incorporates protein–ligand activity data with protein–ligand structural data using three-dimensional matched molecular pairs.OOMMPPAAhighlights nuanced structure–activity relationships (SAR) and summarizes available protein–ligand activity data in the protein context. In this paper, the background that led to the development of both tools is described. Their implementation is outlined and their utility using in-house Structural Genomics Consortium (SGC) data sets and openly available data from the PDB and ChEMBL is described. Both tools are freely available to use and download at http://wonka.sgc.ox.ac.uk/WONKA/ and http://oommppaa.sgc.ox.ac.uk/OOMMPPAA/.

scholarly journals The Effects of Gasoline Prices on Bus Ridership for Different Types of Transit Systems

2012 ◽  
Vol 47 (3) ◽  
Author(s):  
Jeremy Mattson
Keyword(s):  
Great Plains ◽  
Aggregate Data ◽  
Gasoline Prices ◽  
Delayed Effect ◽  
Gasoline Price ◽  
Transit Systems ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Different Types ◽  
Lag Model

This study estimates the effects of gas prices on bus ridership for different types of transit systems. Because the price of gas can have a delayed effect on the demand for transit, a dynamic polynomial distributed lag model is utilized which measures short- and longer-run effects. The model is first applied to aggregate data for cities of different sizes and then to three specific small urban and rural transit systems in the Upper Great Plains. The results show that bus ridership is fairly inelastic with respect to gasoline price. Most of the estimated elasticities are in the range of 0.08 to 0.22, with two estimates being as high as 0.5.

scholarly journals SATzilla: Portfolio-based Algorithm Selection for SAT

2008 ◽  
Vol 32 ◽  
pp. 565-606 ◽  
Author(s):  
L. Xu ◽  
F. Hutter ◽  
H. H. Hoos ◽  
K. Leyton-Brown
Keyword(s):  
Traditional Approach ◽  
Data Sets ◽  
Algorithm Selection ◽  
New Techniques ◽  
Algorithm Portfolios ◽  
Predicting Performance ◽  
Different Types ◽  
Sat Solver ◽  
Selection For ◽  
Problem Instances

It has been widely observed that there is no single "dominant" SAT solver; instead, different solvers perform best on different instances. Rather than following the traditional approach of choosing the best solver for a given class of instances, we advocate making this decision online on a per-instance basis. Building on previous work, we describe SATzilla, an automated approach for constructing per-instance algorithm portfolios for SAT that use so-called empirical hardness models to choose among their constituent solvers. This approach takes as input a distribution of problem instances and a set of component solvers, and constructs a portfolio optimizing a given objective function (such as mean runtime, percent of instances solved, or score in a competition). The excellent performance of SATzilla was independently verified in the 2007 SAT Competition, where our SATzilla07 solvers won three gold, one silver and one bronze medal. In this article, we go well beyond SATzilla07 by making the portfolio construction scalable and completely automated, and improving it by integrating local search solvers as candidate solvers, by predicting performance score instead of runtime, and by using hierarchical hardness models that take into account different types of SAT instances. We demonstrate the effectiveness of these new techniques in extensive experimental results on data sets including instances from the most recent SAT competition.

Digital Bookstore

2021 ◽  
Vol 9 (VII) ◽  
pp. 1326-1337
Author(s):  
Amey Thakur
Keyword(s):  
Programming Languages ◽  
Web Application ◽  
Credit Card ◽  
Sql Server ◽  
Data Sets ◽  
Frequent User ◽  
Web Browser ◽  
Book Store ◽  
Different Types ◽  
Online Book

The project's main goal is to build an online book store where users can search for and buy books based on title, author, and subject. The chosen books are shown in a tabular style and the customer may buy them online using a credit card. Using this Website, the user may buy a book online rather than going to a bookshop and spending time. Many online bookstores, such as Powell's and Amazon, were created using HTML. We suggest creating a comparable website with .NET and SQL Server. An online book store is a web application that allows customers to purchase ebooks. Through a web browser the customers can search for a book by its title or author, later can add it to the shopping cart and finally purchase using a credit card transaction. The client may sign in using his login credentials, or new clients can simply open an account. Customers must submit their full name, contact details, and shipping address. The user may also provide a review of a book by rating it on a scale of one to five. The books are classified into different types depending on their subject matter, such as software, databases, English, and architecture. Customers can shop online at the Online Book Store Website using a web browser. A client may create an account, sign in, add things to his shopping basket, and buy the product using his credit card information. As opposed to a frequent user, the Administrator has more abilities. He has the ability to add, delete, and edit book details, book categories, and member information, as well as confirm a placed order. This application was created with PHP and web programming languages. The Online Book Store is built using the Master page, data sets, data grids, and user controls.

Introduction

2017 ◽  
pp. 1-11
Keyword(s):  
Hong Kong ◽  
Design Codes ◽  
Different Types ◽  
The Usa

Chapter 1 is an introduction to the book and provides an overview of the areas in which temporary structures are used, namely the construction and repair of buildings and bridges. A description of the different types of temporary structures is given together with an overview of the problems which may arise in temporary structures projects. The differences between temporary structures projects and projects for permanent structures are highlighted. An introduction to the particularities of the design, assembly, maintenance and operation of temporary structures is presented in this chapter. It is also emphasised that the book compares the design codes used in the USA, Europe, Australia and Hong Kong. Finally, the chapter concludes with an overview of the remaining chapters of the book.

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