Missing mixed mode: elemental structures

One of the main concerns is the nature of the missing values. Let’s consider extremes for simplicity. If missing at random we have not to care about. But if missing shows structures that covariate with substantive variables we have to make decisions. There are, in fact, several options to take. We are speaking about one country, one mode. But if you go cross-cultural (or more precisely, cross-state nations) and mixed modes many questions raise. For example, the simple one. What are we comparing? Reports and books usually go straight into variables distributions and coefficient comparisons. This is possible because the annalist presume "tabula rasa" effect from data collections procedures. But this is not, frequently, the real situation. This paper will expose the mixed missing mode imprint in international surveys. This will help to evaluate how deal with this problem. Also, to consider the real meaning of observed cross-national differences.

Multiple imputation of missing blood alcohol concentration (BAC) values in FARS.

National Highway Traffic Safety Administration, Washington, D.C.

Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing

Thesis (Ph.D.)--University of Washington, 2016-08

Columnar cell lesions of the breast: The missing link in breast cancer progression? A morphological and molecular analysis

Columnar cell lesions (CCLs) of the breast are a spectrum of lesions that have posed difficulties to pathologists for many years, prompting discussion concerning their biologic and clinical significance. We present a study of CCL in context with hyperplasia of usual type (HUT) and the more advanced lesions ductal carcinoma in situ (DCIS) and invasive ductal carcinoma. A total of 81 lesions from 18 patients were subjected to a comprehensive morphologic review based upon a modified version of Schnitt's classification system for CCL, immunophenotypic analysis (estrogen receptor [ER], progesterone receptor [PgR], Her2/neu, cytokeratin 5/6 [CK5/6], cytokeratin 14 [CK14], E-cadherin, p53) and for the first time, a whole genome molecular analysis by comparative genomic hybridization. Multiple CCLs from 3 patients were studied in particular detail, with topographic information and/or showing a morphologic spectrum of CCL within individual terminal duct lobular units. CCLs were ER an PgR positive, CK5/6 and CK14 negative, exhibit low numbers of genetic alterations and recurrent 16q loss, features that are similar to those of low grade in situ and invasive carcinoma. The molecular genetic profiles closely reflect the degree of proliferation and atypia in CCL, indicating some of these lesions represent both a morphologic and molecular continuum. In addition, overlapping chromosomal alterations between CCL and more advanced lesions within individual terminal duct lobular units suggest a commonality in molecular evolution. These data further support the hypothesis that CCLs are a nonobligate, intermediary step in the development of some forms of low grade in situ and invasive carcinoma. Copyright: © 2005 Lippincott Williams & Wilkins, Inc.

GTM-based data visualisation with incomplete data

We analyse how the Generative Topographic Mapping (GTM) can be modified to cope with missing values in the training data. Our approach is based on an Expectation -Maximisation (EM) method which estimates the parameters of the mixture components and at the same time deals with the missing values. We incorporate this algorithm into a hierarchical GTM. We verify the method on a toy data set (using a single GTM) and a realistic data set (using a hierarchical GTM). The results show our algorithm can help to construct informative visualisation plots, even when some of the training points are corrupted with missing values.

Industrial policy, FDI and employment:still a 'missing a strategy'

This paper contrasts the effects of trade, inward FDI and technological development upon the demand for skilled and unskilled workers in the UK. By focussing on industry level data panel data on smaller firms, the paper also contrasts these effects with those generated by large scale domestic investment. The analysis is placed within the broader context of shifts in British industrial policy, which has seen significant shifts from sectoral to horizontal measures and towards stressing the importance of SMEs, clusters and new technology, all delivered at the regional scale. This, however, is contrasted with continued elements of British and EU regional policy which have emphasised the attraction of inward investment in order to alleviate regional unemployment. The results suggest that such policies are not naturally compatible; that while both trade and FDI benefit skilled workers, they have adverse effects on the demand for unskilled labour in the UK. At the very least this suggests the need for a range of policies to tackle various targets (including in this case unemployment and social inclusion) and the need to integrate these into a coherent industrial strategy at various levels of governance, whether regional and/or national. This has important implications for the form of any 'new' industrial policy.

Industrial policy, FDI and employment:still a 'missing a strategy'

This paper contrasts the effects of trade, inward FDI and technological development upon the demand for skilled and unskilled workers in the UK. By focussing on industry level data panel data on smaller firms, the paper also contrasts these effects with those generated by large scale domestic investment. The analysis is placed within the broader context of shifts in British industrial policy, which has seen significant shifts from sectoral to horizontal measures and towards stressing the importance of SMEs, clusters and new technology, all delivered at the regional scale. This, however, is contrasted with continued elements of British and EU regional policy which have emphasised the attraction of inward investment in order to alleviate regional unemployment. The results suggest that such policies are not naturally compatible; that while both trade and FDI benefit skilled workers, they have adverse effects on the demand for unskilled labour in the UK. At the very least this suggests the need for a range of policies to tackle various targets (including in this case unemployment and social inclusion) and the need to integrate these into a coherent industrial strategy at various levels of governance, whether regional and/or national. This has important implications for the form of any ‘new’ industrial policy.

Industrial policy, FDI and employment:Still 'missing a strategy'

This paper contrasts the effects of trade, inward FDI and technological development upon the demand for skilled and unskilled workers in the UK. By focussing on industry level data panel data on smaller firms, the paper also contrasts these effects with those generated by large scale domestic investment. The analysis is placed within the broader context of shifts in British industrial policy, which has seen significant shifts from sectoral to horizontal measures and towards stressing the importance of SMEs, clusters and new technology, all delivered at the regional scale. This, however, is contrasted with continued elements of British and EU regional policy which have emphasised the attraction of inward investment in order to alleviate regional unemployment. The results suggest that such policies are not naturally compatible; that while both trade and FDI benefit skilled workers, they have adverse effects on the demand for unskilled labour in the UK. At the very least this suggests the need for a range of policies to tackle various targets (including in this case unemployment and social inclusion) and the need to integrate these into a coherent industrial strategy at various levels of governance, whether regional and/or national. This has important implications for the form of any 'new' industrial policy.

Data compilation of dinoflagellates growth rate, grazing rate and gross gowth efficiency from field and labratory experiments

The present data compilation includes dinoflagellates growth rate, grazing rate and gross growth efficiency determined either in the field or in laboratory experiments. From the existing literature, we synthesized all data that we could find on dinoflagellates. Some sources might be missing but none were purposefully ignored. We did not include autotrophic dinoflagellates in the database, but mixotrophic organisms may have been included. This is due to the large uncertainty about which taxa are mixotrophic, heterotrophic or symbiont bearing. Field data on microzooplankton grazing are mostly comprised of grazing rate using the dilution technique with a 24h incubation period. Laboratory grazing and growth data are focused on pelagic ciliates and heterotrophic dinoflagellates. The experiment measured grazing or growth as a function of prey concentration or at saturating prey concentration (maximal grazing rate). When considering every single data point available (each measured rate for a defined predator-prey pair and a certain prey concentration) there is a total of 801 data points for the dinoflagellates, counting experiments that measured growth and grazing simultaneously as 1 data point.

Data compilation of ciliates growth rate, grazing rate and gross gowth efficiency from field and labratory experiments

The present data compilation includes ciliates growth rate, grazing rate and gross growth efficiency determined either in the field or in laboratory experiments. From the existing literature, we synthesized all data that we could find on cilliate. Some sources might be missing but none were purposefully ignored. Field data on microzooplankton grazing are mostly comprised of grazing rate using the dilution technique with a 24h incubation period. Laboratory grazing and growth data are focused on pelagic ciliates and heterotrophic dinoflagellates. The experiment measured grazing or growth as a function of prey concentration or at saturating prey concentration (maximal grazing rate). When considering every single data point available (each measured rate for a defined predator-prey pair and a certain prey concentration) there is a total of 1485 data points for the ciliates, counting experiments that measured growth and grazing simultaneously as 1 data point.

Social machines dictating social behaviors – When context is missing what is the fallout of uberveillance?

Abstract: In the mid-1990s when I worked for a telecommunications giant I struggled to gain access to basic geodemographic data. It cost hundreds of thousands of dollars at the time to simply purchase a tile of satellite imagery from Marconi, and it was often cheaper to create my own maps using a digitizer and A0 paper maps. Everything from granular administrative boundaries to right-of-ways to points of interest and geocoding capabilities were either unavailable for the places I was working in throughout Asia or very limited. The control of this data was either in a government’s census and statistical bureau or was created by a handful of forward thinking corporations. Twenty years on we find ourselves inundated with data (location and other) that we are challenged to amalgamate, and much of it still “dirty” in nature. Open data initiatives such as ODI give us great hope for how we might be able to share information together and capitalize not only in the crowdsourcing behavior but in the implications for positive usage for the environment and for the advancement of humanity. We are already gathering and amassing a great deal of data and insight through excellent citizen science participatory projects across the globe. In early 2015, I delivered a keynote at the Data Made Me Do It conference at UC Berkeley, and in the preceding year an invited talk at the inaugural QSymposium. In gathering research for these presentations, I began to ponder on the effect that social machines (in effect, autonomous data collection subjects and objects) might have on social behaviors. I focused on studying the problem of data from various veillance perspectives, with an emphasis on the shortcomings of uberveillance which included the potential for misinformation, misinterpretation, and information manipulation when context was entirely missing. As we build advanced systems that rely almost entirely on social machines, we need to ponder on the risks associated with following a purely technocratic approach where machines devoid of intelligence may one day dictate what humans do at the fundamental praxis level. What might be the fallout of uberveillance? Bio: Dr Katina Michael is a professor in the School of Computing and Information Technology at the University of Wollongong. She presently holds the position of Associate Dean – International in the Faculty of Engineering and Information Sciences. Katina is the IEEE Technology and Society Magazine editor-in-chief, and IEEE Consumer Electronics Magazine senior editor. Since 2008 she has been a board member of the Australian Privacy Foundation, and until recently was the Vice-Chair. Michael researches on the socio-ethical implications of emerging technologies with an emphasis on an all-hazards approach to national security. She has written and edited six books, guest edited numerous special issue journals on themes related to radio-frequency identification (RFID) tags, supply chain management, location-based services, innovation and surveillance/ uberveillance for Proceedings of the IEEE, Computer and IEEE Potentials. Prior to academia, Katina worked for Nortel Networks as a senior network engineer in Asia, and also in information systems for OTIS and Andersen Consulting. She holds cross-disciplinary qualifications in technology and law.

Processing Argo oxygen data at the DAC level cookbook

This document does NOT address the issue of oxygen data quality control (either real-time or delayed mode). As a preliminary step towards that goal, this document seeks to ensure that all countries deploying floats equipped with oxygen sensors document the data and metadata related to these floats properly. We produced this document in response to action item 14 from the AST-10 meeting in Hangzhou (March 22-23, 2009). Action item 14: Denis Gilbert to work with Taiyo Kobayashi and Virginie Thierry to ensure DACs are processing oxygen data according to recommendations. If the recommendations contained herein are followed, we will end up with a more uniform set of oxygen data within the Argo data system, allowing users to begin analysing not only their own oxygen data, but also those of others, in the true spirit of Argo data sharing. Indications provided in this document are valid as of the date of writing this document. It is very likely that changes in sensors, calibrations and conversions equations will occur in the future. Please contact V. Thierry (vthierry@ifremer.fr) for any inconsistencies or missing information. A dedicated webpage on the Argo Data Management website (www) contains all information regarding Argo oxygen data management : current and previous version of this cookbook, oxygen sensor manuals, calibration sheet examples, examples of matlab code to process oxygen data, test data, etc..

Periodontitis as a risk factor for systemic disease: Are microparticles the missing link?

International audience

Production Lot Detection through Synthetic Generated Data

Correctness of information gathered in production environments is an essential part of quality assurance processes in many industries, this task is often performed by human resources who visually take annotations in various steps of the production flow. Depending on the performed task the correlation between where exactly the information is gathered and what it represents is more than often lost in the process. The lack of labeled data places a great boundary on the application of deep neural networks aimed at object detection tasks, moreover supervised training of deep models requires a great amount of data to be available. Reaching an adequate large collection of labeled images through classic techniques of data annotations is an exhausting and costly task to perform, not always suitable for every scenario. A possible solution is to generate synthetic data that replicates the real one and use it to fine-tune a deep neural network trained on one or more source domains to a different target domain. The purpose of this thesis is to show a real case scenario where the provided data were both in great scarcity and missing the required annotations. Sequentially a possible approach is presented where synthetic data has been generated to address those issues while standing as a training base of deep neural networks for object detection, capable of working on images taken in production-like environments. Lastly, it compares performance on different types of synthetic data and convolutional neural networks used as backbones for the model.