231 research outputs found
Copolymerization and activation of peroxide decomposition with acrylic derivatives of tertiary aromatic amines
No full textThe reactivity parameters of the copolymerization of N,N-bis(2-methacryloyloxyethyl)-p-toluidine (BMAT) (M1) with methyl methacrylate (MMA) (M2) in 1,4-dioxane, i.e. r1 = 1.07 ± 0.20, and r2 = 0.11 ± 0.19, and with bisphenol-A bis(2-hydroxypropyl methacrylate) (Bis-GMA) (M2) in benzene, i.e. r1 = 0.58 ± 0.04, and r2 = 0.03 ± 0.03, were determined at 60°C at low concentration and low conversion (∼5%) of the monomers. Strongly delayed gelation occurred during the copolymerization of BMAT and MMA at monomer conversions of 20–30%, relatively independently of the composition of the monomer mixture. The efficiency of BMAT and N-acryloyl-N′-phenylpiperazine as activators in the redox initiated copolymerization of Bis-GMA in dental composites at ambient temperatures was found to be comparatively low. In the case where BMAT was used in equimolar proportions to benzoyl peroxide the former component was not detectable in the extract of the cured composit
To what extent airborne particulate matters are influenced by ammonia and nitrogen oxides?
No full textIntensive farming is known to significantly impact air quality, particularly f ine particulate matter (PM. 2.5). Understanding in detail their relation is important for scientific reasons and policymaking. Ammonia emissions convey the impact of farming but are not directly observed. They are computed through emission inventories based on administrative data and provided on a regular spatial grid at daily resolution. In this chapter, we aim to validate lato sensu the approach mentioned above by considering ammonia concentrations instead of emissions in the Lombardy Region, Italy. While the former are available only in few monitoring stations around the region, they are direct observations. Hence, we build a model explaining PM2.5 based on precursors, ammonia (NH3) and nitrogen oxides (NOX), and meteorological variables. To do this, we use a seasonal interaction regression model allowing for temporal autocorrelation, correlation between stations, and heteroskedasticity. It is found that ..
supplemental_data_re-re-revision – Supplemental material for Evaluation of the New ISGLS Definitions of Typical Posthepatectomy Complications
No full textSupplemental material, supplemental_data_re-re-revision for Evaluation of the New ISGLS Definitions of Typical Posthepatectomy Complications by E. Birgin, W. Tesfazgi, M. Knoth, T.J. Wilhelm, S. Post and F. Rückert in Scandinavian Journal of Surgery</p
Minimax Optimality of CUSUM for an Autoregressive Model
No full textDifferent change point models for AR(1) processes are reviewed. For some models, the change is in the distribution conditional on earlier observations. For others the change is in the unconditional distribution. Some models include an observation before the first possible change time — others not. Earlier and new CUSUM type methods are given and minimax optimality is examined. For the conditional model with an observation before the possible change there are sharp results of optimality in the literature. The unconditional model with possible change at (or before) the first observation is of interest for applications. We examined this case and derived new variants of four earlier suggestions. By numerical methods and Monte Carlo simulations it was demonstrated that the new variants dominate the original ones. However, none of the methods is uniformly minimax optimal.Autoregressive; Change point; Monitoring; Online detection
docker-interimage: Running the latest InterIMAGE Linux release in a Docker container with user interface
No full text<p>This release can run the latest available release of InterIMAGE for Linux, 1.27, in a Docker container by forwarding a local X11 socket into the container and thereby showing the application's user interface.</p>
Bountiful Found
No full textReview of In the Footsteps of Lehi: New Evidence for Lehi\u27s Journey across Arabia to Bountiful (1994), by Warren P. Aston and Michaela Knoth Aston
Effective Distributed Representations for Academic Expert Search
No full textExpert search aims to find and rank experts based on a user's query. In
academia, retrieving experts is an efficient way to navigate through a large
amount of academic knowledge. Here, we study how different distributed
representations of academic papers (i.e. embeddings) impact academic expert
retrieval. We use the Microsoft Academic Graph dataset and experiment with
different configurations of a document-centric voting model for retrieval. In
particular, we explore the impact of the use of contextualized embeddings on
search performance. We also present results for paper embeddings that
incorporate citation information through retrofitting. Additionally,
experiments are conducted using different techniques for assigning author
weights based on author order. We observe that using contextual embeddings
produced by a transformer model trained for sentence similarity tasks produces
the most effective paper representations for document-centric expert retrieval.
However, retrofitting the paper embeddings and using elaborate author
contribution weighting strategies did not improve retrieval performance.Comment: To be published in the Scholarly Document Processing 2020 Workshop @
EMNLP 2020 proceeding
Distribution-Free Multivariate Phase I Shewhart Control Charts: Analysis, Comparisons and Recommendations
No full textThe need to develop nonparametric techniques for multivariate Phase I analysis has received increasing attention in the statistical process monitoring literature. Some critical issues related to univariate Phase I analysis become even more challenging when several quality characteristics need to be analysed simultaneously. Multivariate Shewhart-type control charts, such as Hotelling’s control chart, are simple to use and effective in detecting large outliers in Phase I applications. However, the traditional design of the chart assumes that the underlying process distribution is multivariate normal. When this assumption is violated, the chart’s signals become questionable. This study investigates a class of distribution-free Phase I Shewhart-type control charts for detecting shifts in the location vector of a multivariate process. This class contains the original Hotelling’s control statistic, as well as other -type control statistics based on affine invariant transformations of the original multivariate data, such as the ranks of the Mahalanobis depths, the spatial signs and the multivariate spatial and signed ranks. To attain the desired in-control properties independently of the underlying process distribution, a permutation-based approach is used and recommended to compute the control limits. A simulation study is carried out to investigate the out-of-control performance of these distribution-free Phase I Shewhart control charts and provide practical recommendations to users
EWMA p charts for detecting changes in mean or scale of normal variates
No full textMethods of Statistical Process Control (SPC) are used for detecting deviations from regular processing. SPC is applied in manufacturing implementations where statistical tools are used to monitor the performance of production processes in order to identify and correct considerable changes in the process performance. Today, SPC methods are incorporated by organizations around the world as a suitable tool to improve product quality by reducing process variation. The current method of SPC is the application of control charts which are used to monitor process parameters (e. g., mean μ, standard deviation σ or percent defective p) over time. Well-established control chart schemes are, amongst others, exponentially weighted moving average charts (EWMA), cumulative sum charts (CUSUM) or, of course, the classical Shewhart charts. In this article, an EWMA control chart for variables calculating the percent defective p = f (μ, σ) will be presented where both process parameters are under risk to change. The scheme will be compared to several other control chart applications (EWMA X, EWMA X-S2, and an alternative EWMA p chart). Numerical methods and Monte Carlo simulations are used for computing the average run length (ARL) as the measure of performance
CORE's use of ResourceSync
No full textThis presentation was given as part of COAR Webinar and Discussion Series on 20/09/2018.</p
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