Model Reduction for Large-Scale Systems with High Dimensional Parametric Input Space

A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a reduced basis approach, which requires the computation of high-fidelity solutions at a number of sample points throughout the parametric input space. A key challenge that must be addressed in the optimization, control, and probabilistic settings is the need for the reduced models to capture variation over this parametric input space, which, for many applications, will be of high dimension. We pose the task of determining appropriate sample points as a PDE-constrained optimization problem, which is implemented using an efficient adaptive algorithm that scales well to systems with a large number of parameters. The methodology is demonstrated for examples with parametric input spaces of dimension 11 and 21, which describe thermal analysis and design of a heat conduction fin, and compared with statistically-based sampling methods. For this example, the model-constrained adaptive sampling leads to reduced models that, for a given basis size, have error several orders of magnitude smaller than that obtained using the other methods

Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems

We explore using neural operators, or neural network representations of nonlinear maps between function spaces, to accelerate infinite-dimensional Bayesian inverse problems (BIPs) with models governed by nonlinear parametric partial differential equations (PDEs). Neural operators have gained significant attention in recent years for their ability to approximate the parameter-to-solution maps defined by PDEs using as training data solutions of PDEs at a limited number of parameter samples. The computational cost of BIPs can be drastically reduced if the large number of PDE solves required for posterior characterization are replaced with evaluations of trained neural operators. However, reducing error in the resulting BIP solutions via reducing the approximation error of the neural operators in training can be challenging and unreliable. We provide an a priori error bound result that implies certain BIPs can be ill-conditioned to the approximation error of neural operators, thus leading to inaccessible accuracy requirements in training. To reliably deploy neural operators in BIPs, we consider a strategy for enhancing the performance of neural operators, which is to correct the prediction of a trained neural operator by solving a linear variational problem based on the PDE residual. We show that a trained neural operator with error correction can achieve a quadratic reduction of its approximation error, all while retaining substantial computational speedups of posterior sampling when models are governed by highly nonlinear PDEs. The strategy is applied to two numerical examples of BIPs based on a nonlinear reaction--diffusion problem and deformation of hyperelastic materials. We demonstrate that posterior representations of the two BIPs produced using trained neural operators are greatly and consistently enhanced by error correction

Computer-aided discovery of antimicrobial agents as potential enoyl acyl carrier protein reductase inhibitors

Purpose: To perform a virtual screening for a set of drug-like ligand library against the Staphylococcus aureus enoyl acyl carrier protein reductase, saFabI.Methods: The virtual screening was conducted based on a previously validated pharmacophoreconstrained docking. Consequently, the top list obtained was filtered using visual inspection where forty compounds were selected for experimental testing using disk-diffusion test and broth dilution method. The hits obtained were checked for their toxicity against human fibroblasts cell lines.Results: Three compounds were active against Staphylococcus aureus and other tested gram-positive bacteria. However, no significant inhibitory activity (p < 0.05) was detected against Escherichia coli or Candida albicans. The minimum inhibitory concentration (MIC) values for the most active compounds were identified using the broth dilution method; all of them exhibited inhibitory activity within micromolar range.The docking results showed that the hits obtained exhibited a small size with a nice binding mode to saFabI enzyme, forming the important interactions with the key residues. Furthermore, the best three hits demonstrated good safety profile as they did not show any significant toxicity against human fibroblast cell line.Conclusion: Overall, the newly discovered hits can act as a good starting point in the future for the development of safe and potent antibacterial agents.Keywords: Enoyl acyl carrier protein reductase, saFabI, Antibacterial agents, Docking, Constraint, Virtual screening Tropical Journal of Pharmaceutica

International Standards on Auditing (ISAs): conflicting influences on implementation

This chapter sets the scene for further research and empirical forays on the adoption and use of auditing standards generally, and ISAs specifically, by providing (i) a review of the (limited) academic literature on ISAs, (ii) a broad picture of ISA ‘implementation’ (or the apparent variations or lack of implementation) in developing and emerging economies and (iii) a specific illustration of how ISAs have permeated a developing economy (Egypt)

Implications of Synchronous IVR Radio on Syrian Refugee Health and Community Dynamics

With 1,033,513 Syrian refugees adding a strain on the Lebanese healthcare system, innovation is key to improving access to healthcare. Our previous work identified the potential for technology to improve access to antenatal care services and increase refugee agency. Using (1) paper mock ups and a mobile based prototype, (2) process mapping, (3) focus groups and interviews and (4) key informant meetings, we explored the concept of refugee led community radio shows to deliver peer-led healthcare. We observed the influence of community radio shows on Syrian refugee health education, community dynamics and community agency in relationships between healthcare providers and refugees. Refugees were positively impacted through situating the technology within the community. We highlight issues around trust, agency, understanding, sel-forganization and privacy that resulted from running the shows through mock ups and a mobile based prototype. Our findings inform future work in community run radio shows

On the Relationships between Decision Management and Performance Measurement

Decision management is of utmost importance for the achievement of strategic and operational goals in any organisational context. Therefore, decisions should be considered as first-class citizens that need to be modelled, analysed, monitored to track their performance, and redesigned if necessary. Up to now, existing literature that studies decisions in the context of business processes has focused on the analysis of the definition of decisions themselves, in terms of accuracy, certainty, consistency, covering and correctness. However, to the best of our knowledge, no prior work exists that analyses the relationship between decisions and performance measurement. This paper identifies and analyses this relationship from three different perspectives, namely: the impact of decisions on process performance, the performance measurement of decisions, and the use of performance indicators in the definition of decisions. Furthermore, we also introduce solutions for the representation of these relationships based, amongst others, on the DMN standard.Ministerio de Economía y Competitividad BELI (TIN2015-70560-R)Junta de Andalucía P12-TIC-1867Junta de Andalucía P10-TIC-590

The effects of iron fortification on the gut microbiota in African children: a randomized controlled trial in Cote d'Ivoire.

BACKGROUND: Iron is essential for the growth and virulence of many pathogenic enterobacteria, whereas beneficial barrier bacteria, such as lactobacilli, do not require iron. Thus, increasing colonic iron could select gut microbiota for humans that are unfavorable to the host. OBJECTIVE: The objective was to determine the effect of iron fortification on gut microbiota and gut inflammation in African children. DESIGN: In a 6-mo, randomized, double-blind, controlled trial, 6-14-y-old Ivorian children (n = 139) received iron-fortified biscuits, which contained 20 mg Fe/d, 4 times/wk as electrolytic iron or nonfortifoed biscuits. We measured changes in hemoglobin concentrations, inflammation, iron status, helminths, diarrhea, fecal calprotectin concentrations, and microbiota diversity and composition (n = 60) and the prevalence of selected enteropathogens. RESULTS: At baseline, there were greater numbers of fecal enterobacteria than of lactobacilli and bifidobacteria (P < 0.02). Iron fortification was ineffective; there were no differences in iron status, anemia, or hookworm prevalence at 6 mo. The fecal microbiota was modified by iron fortification as shown by a significant increase in profile dissimilarity (P < 0.0001) in the iron group as compared with the control group. There was a significant increase in the number of enterobacteria (P < 0.005) and a decrease in lactobacilli (P < 0.0001) in the iron group after 6 mo. In the iron group, there was an increase in the mean fecal calprotectin concentration (P < 0.01), which is a marker of gut inflammation, that correlated with the increase in fecal enterobacteria (P < 0.05). CONCLUSIONS: Anemic African children carry an unfavorable ratio of fecal enterobacteria to bifidobacteria and lactobacilli, which is increased by iron fortification. Thus, iron fortification in this population produces a potentially more pathogenic gut microbiota profile, and this profile is associated with increased gut inflammation. This trial was registered at controlled-trials.com as ISRCTN21782274

A Biobrick Library for Cloning Custom Eukaryotic Plasmids

Researchers often require customised variations of plasmids that are not commercially available. Here we demonstrate the applicability and versatility of standard synthetic biological parts (biobricks) to build custom plasmids. For this purpose we have built a collection of 52 parts that include multiple cloning sites (MCS) and common protein tags, protein reporters and selection markers, amongst others. Importantly, most of the parts are designed in a format to allow fusions that maintain the reading frame. We illustrate the collection by building several model contructs, including concatemers of protein binding-site motifs, and a variety of plasmids for eukaryotic stable cloning and chromosomal insertion. For example, in 3 biobrick iterations, we make a cerulean-reporter plasmid for cloning fluorescent protein fusions. Furthermore, we use the collection to implement a recombinase-mediated DNA insertion (RMDI), allowing chromosomal site-directed exchange of genes. By making one recipient stable cell line, many standardised cell lines can subsequently be generated, by fluorescent fusion-gene exchange. We propose that this biobrick collection may be distributed peer-to-peer as a stand-alone library, in addition to its distribution through the Registry of Standard Biological Parts (http://partsregistry.org/)

Product Lifecycle Management for Digital Transformation of Industries.

Currently, organizations tend to reuse their past knowledge to make good decisions quickly and effectively and thus, to improve their business processes performance in terms of time, quality, efficiency, etc. Process mining techniques allow organizations to achieve this objective through process discovery. This paper develops a semi-automated approach that supports decision making by discovering decision rules from the past process executions. It identifies a ranking of the process patterns that satisfy the discovered decision rules and which are the most likely to be executed by a given user in a given context. The approach is applied on a supervision process of the gas network exploitationFU