A framework for documenting and analyzing life-cycle costs using a simple network based representation

The introduction of high reliability systems combined with new ways of operating complex systems, particularly in aircraft design and operation has received much attention in recent years. Some systems are now being introduced into service, however, justifying such systems on a financial basis is difficult and may act to limit the rate of introduction on new products. Conventional life cycle costing based on a hierarchical cost breakdown structure is poor at recording and analysing the cost implications of introducing new technologies that have effects that span more than one phase in the life cycle. There is a risk that too much emphasis is put on ‘faith’ that a candidate technology will reduce cost because the cost analysis methods lack descriptive and analytical power. We describe an approach to representing the costs associated with introducing new technologies and evaluating their total cost. Our aim was to facilitate the comparison of different technological choices in new product development, with a particular interest in how the perceived benefits of enhanced reliability systems can be shown in a way that is inclusive, objective and easy to understand

Uncertainty quantification and weak approximation of an elliptic inverse problem

We consider the inverse problem of determining the permeability from the pressure in a Darcy model of flow in a porous medium. Mathematically the problem is to find the diffusion coefficient for a linear uniformly elliptic partial differential equation in divergence form, in a bounded domain in dimension $d \le 3$, from measurements of the solution in the interior. We adopt a Bayesian approach to the problem. We place a prior random field measure on the log permeability, specified through the Karhunen-Lo\`eve expansion of its draws. We consider Gaussian measures constructed this way, and study the regularity of functions drawn from them. We also study the Lipschitz properties of the observation operator mapping the log permeability to the observations. Combining these regularity and continuity estimates, we show that the posterior measure is well-defined on a suitable Banach space. Furthermore the posterior measure is shown to be Lipschitz with respect to the data in the Hellinger metric, giving rise to a form of well-posedness of the inverse problem. Determining the posterior measure, given the data, solves the problem of uncertainty quantification for this inverse problem. In practice the posterior measure must be approximated in a finite dimensional space. We quantify the errors incurred by employing a truncated Karhunen-Lo\`eve expansion to represent this meausure. In particular we study weak convergence of a general class of locally Lipschitz functions of the log permeability, and apply this general theory to estimate errors in the posterior mean of the pressure and the pressure covariance, under refinement of the finite dimensional Karhunen-Lo\`eve truncation.Comment: 19 pages, 0 figures, submitted to SIAM Journal on Numerical Analysi

A Bayesian Approach to the Detection Problem in Gravitational Wave Astronomy

The analysis of data from gravitational wave detectors can be divided into three phases: search, characterization, and evaluation. The evaluation of the detection - determining whether a candidate event is astrophysical in origin or some artifact created by instrument noise - is a crucial step in the analysis. The on-going analyses of data from ground based detectors employ a frequentist approach to the detection problem. A detection statistic is chosen, for which background levels and detection efficiencies are estimated from Monte Carlo studies. This approach frames the detection problem in terms of an infinite collection of trials, with the actual measurement corresponding to some realization of this hypothetical set. Here we explore an alternative, Bayesian approach to the detection problem, that considers prior information and the actual data in hand. Our particular focus is on the computational techniques used to implement the Bayesian analysis. We find that the Parallel Tempered Markov Chain Monte Carlo (PTMCMC) algorithm is able to address all three phases of the anaylsis in a coherent framework. The signals are found by locating the posterior modes, the model parameters are characterized by mapping out the joint posterior distribution, and finally, the model evidence is computed by thermodynamic integration. As a demonstration, we consider the detection problem of selecting between models describing the data as instrument noise, or instrument noise plus the signal from a single compact galactic binary. The evidence ratios, or Bayes factors, computed by the PTMCMC algorithm are found to be in close agreement with those computed using a Reversible Jump Markov Chain Monte Carlo algorithm.Comment: 19 pages, 12 figures, revised to address referee's comment

LISA Data Analysis using MCMC methods

The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50,000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analyses and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we super-cool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions.Comment: 14 pages, 7 figure

Distinct immune signatures in directly treated and distant tumors result from TLR adjuvants and focal ablation.

Both adjuvants and focal ablation can alter the local innate immune system and trigger a highly effective systemic response. Our goal is to determine the impact of these treatments on directly treated and distant disease and the mechanisms for the enhanced response obtained by combinatorial treatments. Methods: We combined RNA-sequencing, flow cytometry and TCR-sequencing to dissect the impact of immunotherapy and of immunotherapy combined with ablation on local and systemic immune components. Results: With administration of a toll-like receptor agonist agonist (CpG) alone or CpG combined with same-site ablation, we found dramatic differences between the local and distant tumor environments, where the directly treated tumors were skewed to high expression of F4/80, Cd11b and Tnf and the distant tumors to enhanced Cd11c, Cd3 and Ifng. When ablation was added to immunotherapy, 100% (n=20/20) of directly treated tumors and 90% (n=18/20) of distant tumors were responsive. Comparing the combined ablation-immunotherapy treatment to immunotherapy alone, we find three major mechanistic differences. First, while ablation alone enhanced intratumoral antigen cross-presentation (up to ~8% of CD45+ cells), systemic cross-presentation of tumor antigen remained low. Combining same-site ablation with CpG amplified cross-presentation in the draining lymph node (~16% of CD45+ cells) compared to the ablation-only (~0.1% of CD45+ cells) and immunotherapy-only cohorts (~10% of CD45+ cells). Macrophages and DCs process and present this antigen to CD8+ T-cells, increasing the number of unique T-cell receptor rearrangements in distant tumors. Second, type I interferon (IFN) release from tumor cells increased with the ablation-immunotherapy treatment as compared with ablation or immunotherapy alone. Type I IFN release is synergistic with toll-like receptor activation in enhancing cytokine and chemokine expression. Expression of genes associated with T-cell activation and stimulation (Eomes, Prf1 and Icos) was 27, 56 and 89-fold higher with ablation-immunotherapy treatment as compared to the no-treatment controls (and 12, 32 and 60-fold higher for immunotherapy-only treatment as compared to the no-treatment controls). Third, we found that the ablation-immunotherapy treatment polarized macrophages and dendritic cells towards a CD169 subset systemically, where CD169+ macrophages are an IFN-enhanced subpopulation associated with dead-cell antigen presentation. Conclusion: While the local and distant responses are distinct, CpG combined with ablative focal therapy drives a highly effective systemic immune response

Bronchopulmonary Dysplasia: Executive Summary of a Workshop

Comment in Bronchopulmonary Dysplasia: The Ongoing Search for One Definition to Rule Them All. [J Pediatr. 2018] Midlife crisis? In its 50th year, BPD redefines itself. [J Pediatr. 2018

Working towards fostering programming acceptance in the everyday lives of older and adult people with low levels of formal education:a qualitative case study

With the ever-increasing development of digital technologies, understanding their acceptance or rejection is important. A great deal of research, led by the Technology Acceptance Model (TAM), shows that technology acceptance is a hot and complex topic. Much of it has been quantitative and operationalized within mandatory—workplace/organizational—contexts, where instrumental aspects of technology use (e.g., efficiency and productivity) play a central role. In this chapter, we report on a qualitative case study—based on 3 in-person learning courses—of factors that can help us foster programming acceptance in the everyday lives of older and adult people with low levels of formal education. We discuss the relative relevance of technology acceptance constructs, showing that perceived ease-of-use is much less relevant than perceived usefulness, because all participants had to find the fit of programming in their lives. We show that two social aspects—the figure of the course instructor and the group—were key to introduce programming and encourage decision-making. We also discuss some methodological issues, such as the difficulties in asking validated items of TAM (e.g. “I have the knowledge necessary to use the system”) to our participants

A novel HLA-B18 restricted CD8+ T cell epitope is efficiently cross-presented by dendritic cells from soluble tumor antigen

NY-ESO-1 has been a major target of many immunotherapy trials because it is expressed by various cancers and is highly immunogenic. In this study, we have identified a novel HLA-B*1801-restricted CD8<sup>+</sup>T cell epitope, NY-ESO-1<sub>88–96</sub> (LEFYLAMPF) and compared its direct- and cross-presentation to that of the reported NY-ESO-1<sub>157–165</sub> epitope restricted to HLA-A*0201. Although both epitopes were readily cross-presented by DCs exposed to various forms of full-length NY-ESO-1 antigen, remarkably NY-ESO-1<sub>88–96</sub> is much more efficiently cross-presented from the soluble form, than NY-ESO-1<sub>157–165</sub>. On the other hand, NY-ESO-1<sub>157–165</sub> is efficiently presented by NY-ESO-1-expressing tumor cells and its presentation was not enhanced by IFN-γ treatment, which induced immunoproteasome as demonstrated by Western blots and functionally a decreased presentation of Melan A<sub>26–35</sub>; whereas NY-ESO-1<sub>88–96</sub> was very inefficiently presented by the same tumor cell lines, except for one that expressed high level of immunoproteasome. It was only presented when the tumor cells were first IFN-γ treated, followed by infection with recombinant vaccinia virus encoding NY-ESO-1, which dramatically increased NY-ESO-1 expression. These data indicate that the presentation of NY-ESO-1<sub>88–96</sub> is immunoproteasome dependent. Furthermore, a survey was conducted on multiple samples collected from HLA-B18+ melanoma patients. Surprisingly, all the detectable responses to NY-ESO-1<sub>88–96</sub> from patients, including those who received NY-ESO-1 ISCOMATRIX™ vaccine were induced spontaneously. Taken together, these results imply that some epitopes can be inefficiently presented by tumor cells although the corresponding CD8<sup>+</sup>T cell responses are efficiently primed in vivo by DCs cross-presenting these epitopes. The potential implications for cancer vaccine strategies are further discussed

Sensing of explosive vapor by hybrid perovskites : effect of dimensionality

Funding: Engineering and Physical Sciences Research Council under grants EP/T01119X/1 and EP/K503940/1, and the NATO Science for Peace & Security programme under grant agreement MYP G5355.Lead halide perovskites are very promising materials for many optoelectronic devices. They are low cost, photostable, and strongly photoluminescent materials, but so far have been little studied for sensing. In this article, we explore hybrid perovskites as sensors for explosive vapor. We tune the dimensionality of perovskite films in order to modify their exciton binding energy and film morphology and explore the effect on sensing response. We find that tuning from the 3D to the 0D regime increases the PL quenching response of perovskite films to the vapor of dinitrotoluene (DNT)—a molecule commonly found in landmines. We find that films of 0D perovskite nanocrystals work as sensitive and stable sensors, with strong PL responses to DNT molecules at concentrations in the parts per billion range. The PL quenching response can easily be reversed, making the sensors reusable. We compare the response to several explosive vapors and find that the response is strongest for DNT. These results show that hybrid perovskites have great potential for vapor sensing applications.Publisher PDFPeer reviewe

Cooperation of the Dam1 and Ndc80 kinetochore complexes enhances microtubule coupling and is regulated by aurora B

The Dam1 complex, regulated by aurora B phosphorylation, confers a more stable microtubule association for the Ndc80 complex at kinetochores (see also related paper by Lampert et al. in this issue)