Quantifying uncertainty in an industrial approach : an emerging consensus in an old epistemological debate

Uncertainty is ubiquitous in modern decision-making supported by quantitative modeling. While uncertainty treatment has been initially largely developed in risk or environmental assessment, it is gaining large-spread interest in many industrial fields generating knowledge and practices going beyond the classical risk versus uncertainty or epistemic versus aleatory debates. On the basis of years of applied research in different sectors at the European scale, this paper discusses the emergence of a methodological consensus throughout a number of fields of engineering and applied science such as metrology, safety and reliability, protection against natural risk, manufacturing statistics, numerical design and scientific computing etc. In relation with the applicable regula-tion and standards and a relevant quantity of interest for decision-making, this approach involves in particular the proper identification of key steps such as : the quantification (or modeling) of the sources of uncertainty, possibly involving an inverse approach ; their propagation through a pre-existing physical-industrial model; the ranking of importance or sensitivity analysis and sometimes a subsequent optimisation step. It aims at giving a consistent and industrially-realistic framework for practical mathematical modeling, assumingly restricted to quantitative and quantifiable uncertainty, and illustrated on three typical examples. Axes of further research proving critical for the environmental or industrial issues are outlined: the information challenges posed by uncertainty modeling in the context of data scarcity, and the corresponding calibration and inverse probabilistic techniques, bound to be developed to best value industrial or environmental monitoring and data acquisition systems under uncertainty; the numerical challenges entailing considerable development of high-performance computing in the field; the acceptability challenges in the context of the precautionary principle

Probing dynamics of HIV-1 nucleocapsid protein/target hexanucleotide complexes by 2-aminopurine

The nucleocapsid protein (NC) plays an important role in HIV-1, mainly through interactions with the genomic RNA and its DNA copies. Though the structures of several complexes of NC with oligonucleotides (ODNs) are known, detailed information on the ODN dynamics in the complexes is missing. To address this, we investigated the steady state and time-resolved fluorescence properties of 2-aminopurine (2Ap), a fluorescent adenine analog introduced at positions 2 and 5 of AACGCC and AATGCC sequences. In the absence of NC, 2Ap fluorescence was strongly quenched in the flexible ODNs, mainly through picosecond to nanosecond dynamic quenching by its neighboring bases. NC strongly restricted the ODN flexibility and 2Ap local mobility, impeding the collisions of 2Ap with its neighbors and thus, reducing its dynamic quenching. Phe16→Ala and Trp37→Leu mutations largely decreased the ability of NC to affect the local dynamics of 2Ap at positions 2 and 5, respectively, while a fingerless NC was totally ineffective. The restriction of 2Ap local mobility was thus associated with the NC hydrophobic platform at the top of the folded fingers. Since this platform supports the NC chaperone properties, the restriction of the local mobility of the bases is likely a mechanistic component of these properties

HIV-1 Protease and Reverse Transcriptase Control the Architecture of Their Nucleocapsid Partner

The HIV-1 nucleocapsid is formed during protease (PR)-directed viral maturation, and is transformed into pre-integration complexes following reverse transcription in the cytoplasm of the infected cell. Here, we report a detailed transmission electron microscopy analysis of the impact of HIV-1 PR and reverse transcriptase (RT) on nucleocapsid plasticity, using in vitro reconstitutions. After binding to nucleic acids, NCp15, a proteolytic intermediate of nucleocapsid protein (NC), was processed at its C-terminus by PR, yielding premature NC (NCp9) followed by mature NC (NCp7), through the consecutive removal of p6 and p1. This allowed NC co-aggregation with its single-stranded nucleic-acid substrate. Examination of these co-aggregates for the ability of RT to catalyse reverse transcription showed an effective synthesis of double-stranded DNA that, remarkably, escaped from the aggregates more efficiently with NCp7 than with NCp9. These data offer a compelling explanation for results from previous virological studies that focused on i) Gag processing leading to nucleocapsid condensation, and ii) the disappearance of NCp7 from the HIV-1 pre-integration complexes. We propose that HIV-1 PR and RT, by controlling the nucleocapsid architecture during the steps of condensation and dismantling, engage in a successive nucleoprotein-remodelling process that spatiotemporally coordinates the pre-integration steps of HIV-1. Finally we suggest that nucleoprotein remodelling mechanisms are common features developed by mobile genetic elements to ensure successful replication

Weighted space-filling designs

Many computer models or simulators have probabilistic dependencies between their input variables, which if not accounted for during design selection, may result in a large numbers of simulator runs being required for analysis. We propose a method which incorporates known dependencies between input variables into design selection for simulators and demonstrate the benefits of this approach via a simulator for atmospheric dispersion. We quantify the benefit of the new techniques over standard space-filling and Monte Carlo Simulation. The proposed methods are adaptations of computer-generated spread and coverage space-filling designs, with “distance” between two input points redefined to include a weight function. This weight function reflects any known multivariate dependencies between input variables and prior information on the design region. The methods can include quantitative and qualitative variables, and different types of prior information. Novel graphical methods, adapted from fraction of design space plots, are used to assess and compare the design