The activity of French Research Ethics Committees and characteristics of biomedical research protocols involving humans: a retrospective cohort study

BACKGROUND: Clinical trials throughout the world must be evaluated by research ethics committees. No one has yet attempted to clearly quantify at the national level the activity of ethics committees and describe the characteristics of the protocols submitted. The objectives of this study were to describe 1) the workload and the activity of Research Ethics Committees in France, and 2) the characteristics of protocols approved on a nation-wide basis. METHODS: Retrospective cohort of 976 protocols approved by a representative sample of 25/48 of French Research Ethics Committees in 1994. Protocols characteristics (design, study size, investigator), number of revisions requested by the ethics committee before approval, time to approval and number of amendments after approval were collected for each protocol by trained research assistant using the committee's files and archives. RESULTS: Thirty-one percent of protocols were approved with no modifications requested in 16 days (95% CI: 14–17). The number of revisions requested by the committee, and amendments submitted by the investigator was on average respectively 39 (95% CI: 25–53) and 37 (95% CI: 27–46), per committee and per year. When revisions were requested, the main reasons were related to information to the patient (28%) and consent modalities (18%). Drugs were the object of research in 68% of the protocols examined. The majority of the research was national (80%) with a predominance of single-centre studies. Workload per protocol has been estimated at twelve and half hours on average for administrative support and at eleven and half hours for expertise. CONCLUSION: The estimated workload justifies specific and independent administrative and financial support for Research Ethics Committees

Learning Unions of k-Testable Languages

A classical problem in grammatical inference is to identify a language from a set of examples. In this paper, we address the problem of identifying a union of languages from examples that belong to several different unknown languages. Indeed, decomposing a language into smaller pieces that are easier to represent should make learning easier than aiming for a too generalized language. In particular, we consider k-testable languages in the strict sense (k-TSS). These are defined by a set of allowed prefixes, infixes (sub-strings) and suffixes that words in the language may contain. We establish a Galois connection between the lattice of all languages over alphabet {\Sigma}, and the lattice of k-TSS languages over {\Sigma}. We also define a simple metric on k-TSS languages. The Galois connection and the metric allow us to derive an efficient algorithm to learn the union of k-TSS languages. We evaluate our algorithm on an industrial dataset and thus demonstrate the relevance of our approach

On the equivalence between hierarchical segmentations and ultrametric watersheds

We study hierarchical segmentation in the framework of edge-weighted graphs. We define ultrametric watersheds as topological watersheds null on the minima. We prove that there exists a bijection between the set of ultrametric watersheds and the set of hierarchical segmentations. We end this paper by showing how to use the proposed framework in practice in the example of constrained connectivity; in particular it allows to compute such a hierarchy following a classical watershed-based morphological scheme, which provides an efficient algorithm to compute the whole hierarchy.Comment: 19 pages, double-colum

Semantic mapping of discourse and activity, using Habermas’s theory of communicative action to analyze process

Our primary objective is evaluation of quality of process. This is addressed through semantic mapping of process. We note how this is complementary to the primacy of output results or products. We use goal-oriented discourse as a case study. We draw benefit from how social and political theorist, Jürgen Habermas, uses what was termed “communicative action”. An orientation in Habermas’s work, that we use, is analysis of communication or discourse. For this, we take Twitter social media. In our case study, we map the discourse semantically, using the Correspondence Analysis platform for such latent semantic analysis. This permits qualitative and quantitative analytics. Our case study is a set of eight carefully planned Twitter campaigns relating to environmental issues. The aim of these campaigns was to increase environmental awareness and behaviour. Each campaign was launched by an initiating tweet. Using the data gathered in these Twitter campaigns, we sought to map them, and hence to track the flow of the Twitter discourse. This mapping was achieved through semantic embedding. The semantic distance between an initiating act and the aggregate semantic outcome is used as a measure of process effectiveness

On the Schoenberg Transformations in Data Analysis: Theory and Illustrations

The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on the arc lengths, angles and curvature of the transformations are proposed, and visualized on artificial data sets by classical multidimensional scaling. A simple distance-based discriminant algorithm illustrates the theory, intimately connected to the Gaussian kernels of Machine Learning

On morphological hierarchical representations for image processing and spatial data clustering

Hierarchical data representations in the context of classi cation and data clustering were put forward during the fties. Recently, hierarchical image representations have gained renewed interest for segmentation purposes. In this paper, we briefly survey fundamental results on hierarchical clustering and then detail recent paradigms developed for the hierarchical representation of images in the framework of mathematical morphology: constrained connectivity and ultrametric watersheds. Constrained connectivity can be viewed as a way to constrain an initial hierarchy in such a way that a set of desired constraints are satis ed. The framework of ultrametric watersheds provides a generic scheme for computing any hierarchical connected clustering, in particular when such a hierarchy is constrained. The suitability of this framework for solving practical problems is illustrated with applications in remote sensing

Algorithms for Hierarchical Clustering: An Overview, II

We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations that are available in R and other software environments. We look at hierarchical self-organizing maps, and mixture models. We review grid-based clustering, focusing on hierarchical density-based approaches. Finally we describe a recently developed very efficient (linear time) hierarchical clustering algorithm, which can also be viewed as a hierarchical grid-based algorithm. This review adds to the earlier version, Murtagh and Contreras (2012)

Fast, Linear Time Hierarchical Clustering using the Baire Metric

The Baire metric induces an ultrametric on a dataset and is of linear computational complexity, contrasted with the standard quadratic time agglomerative hierarchical clustering algorithm. In this work we evaluate empirically this new approach to hierarchical clustering. We compare hierarchical clustering based on the Baire metric with (i) agglomerative hierarchical clustering, in terms of algorithm properties; (ii) generalized ultrametrics, in terms of definition; and (iii) fast clustering through k-means partititioning, in terms of quality of results. For the latter, we carry out an in depth astronomical study. We apply the Baire distance to spectrometric and photometric redshifts from the Sloan Digital Sky Survey using, in this work, about half a million astronomical objects. We want to know how well the (more costly to determine) spectrometric redshifts can predict the (more easily obtained) photometric redshifts, i.e. we seek to regress the spectrometric on the photometric redshifts, and we use clusterwise regression for this.Comment: 27 pages, 6 tables, 10 figure

Fast, Linear Time, m-Adic Hierarchical Clustering for Search and Retrieval using the Baire Metric, with linkages to Generalized Ultrametrics, Hashing, Formal Concept Analysis, and Precision of Data Measurement

We describe many vantage points on the Baire metric and its use in clustering data, or its use in preprocessing and structuring data in order to support search and retrieval operations. In some cases, we proceed directly to clusters and do not directly determine the distances. We show how a hierarchical clustering can be read directly from one pass through the data. We offer insights also on practical implications of precision of data measurement. As a mechanism for treating multidimensional data, including very high dimensional data, we use random projections.Comment: 17 pages, 45 citations, 2 figure

Functional traits of hyporheic and benthic invertebrates reveal importance of wood-driven geomorphological processes to rivers

1.Large wood (LW) is a natural element of river environments and an integral component of many river restoration schemes to promote biodiversity. It is an important habitat in itself, but it also induces a wide range of hydraulic, hydrological, geomorphological, and chemical conditions that influence the ecological community. However, the effects of hydro‐geomorphological processes induced by LW on local benthic and hyporheic invertebrates have not been well characterized. 2.A functional approach was applied to invertebrate data collected in a field survey at sites with LW and without LW (control), to investigate the response of hyporheic and benthic invertebrates’ trait profiles in response to local LW‐induced processes. 3.We hypothesized LW sites to be associated with different trait modalities than control sites in relation to wood‐induced processes and conditions (i.e. hyporheic exchange flow, oxygen availability, temporal stability, organic matter, denitrification, hydraulic conductivity). Multivariate analyses and Partial Least Squares (PLS) Path Modelling were used to detect the differences in trait profiles between LW and control sites and to study the variation of traits as a function of hydrological, sedimentological, physical and chemical variables. 4.Biological (i.e. aquatic stages, reproduction), physiological (i.e. dispersal, feeding habits) and behavioural (i.e. substrate preferences) trait utilization by the hyporheic meiofauna differed between LW and control sites. At LW sites, the hyporheic meiofaunal assemblage was significantly associated with aquatic active dispersal, aquatic eggs and hard substrate preferences. This trait category selection was linked to changes in physical‐sedimentological processes at LW sites when compared to control sites. Macrofaunal benthic and hyporheic functional traits did not differ significasignificantly between wood and control sites, suggesting similar functioning of these assemblages at the surface‐subsurface interface. 5.This study found that LW affects invertebrate traits by altering fluvial processes to produce, locally, a mosaic of habitats. Hyporheic meiofauna trait responses to LW‐processes have suggested (i) the crucial role of LW in supporting river benthic zone functioning, and thus (ii) a possible benefit to river restoration by enhancing functional interactions among different ecological niches