Supplier quality improvement: The value of information under uncertainty

We consider supplier development decisions for prime manufacturers with extensive supply bases producing complex, highly engineered products. We propose a novel modelling approach to support supply chain managers decide the optimal level of investment to improve quality performance under uncertainty. We develop a Poisson–Gamma model within a Bayesian framework, representing both the epistemic and aleatory uncertainties in non-conformance rates. Estimates are obtained to value a supplier quality improvement activity and assess if it is worth gaining more information to reduce epistemic uncertainty. The theoretical properties of our model provide new insights about the relationship between the degree of epistemic uncertainty, the effectiveness of development programmes, and the levels of investment. We find that the optimal level of investment does not have a monotonic relationship with the rate of effectiveness. If investment is deferred until epistemic uncertainty is removed then the expected optimal investment monotonically decreases as prior variance increases but only if the prior mean is above a critical threshold. We develop methods to facilitate practical application of the model to industrial decisions by a) enabling use of the model with typical data available to major companies and b) developing computationally efficient approximations that can be implemented easily. Application to a real industry context illustrates the use of the model to support practical planning decisions to learn more about supplier quality and to invest in improving supplier capability.     

Path components of the space of gradient vector fields on the two-dimensional disc

We present a short proof that if two gradient maps on the two-dimensional disc have the same degree, then they are gradient homotopic.     

Bootstrap robust prescriptive analytics

Mathematical Programming - We address the problem of prescribing an optimal decision in a framework where the cost function depends on uncertain problem parameters that need to be learned from...     

Thermal and Sc(OTf)3 catalyzed 1,3-dipolar cycloaddition of open-chain nitrones to α,β-unsaturated lactones: combined experimental and computational studies

The stereoselectivity of 1,3-dipolar cycloaddition reactions of C-phenyl open-chain nitrones and α,β-unsaturated γ- and δ-lactones was investigated under thermal and catalytic conditions. It was found that under thermal conditions, the endo approach of the reactants was preferred leading to the thermodynamic product. In the presence of Sc(OTf)₃ the exo adduct was obtained in high yield and selectivity. The energies of the cycloaddition reactions were investigated by means of molecular orbital calculations at the B3LYP/6-31+G(d,p) and MP3/6-31+G(d,p) theory level. Different reaction channels and reactant approaches, fitting the individual regio- and stereochemical preferences, are discussed. The computational results were compared with the corresponding experimental data and found to be in good agreement.     

Study of the interaction between ethanol and natural amino acids containing ionic side groups in water at T = 298.15 K

The enthalpies of solution of l-α-aspartic acid, l-α-glutamic acid, l-α-arginine, l-α-lysine, and l-α-histidine have been measured in aqueous ethanol solutions at 298.15 K. From the obtained experimental results, the standard enthalpies of solution of amino acids in water–ethanol solutions have been determined. These data were used to calculate the heterogeneous enthalpic pair interaction coefficients based on McMillan–Mayer’s formalism. These values were interpreted in the terms of the ionic or no polar effect of the side chains of l-α-amino acids on their interactions with a molecule of ethanol in water.     

Spatially resolved (semi)quantitative determination of iron (Fe) in plants by means of synchrotron micro X-ray fluorescence

Iron (Fe) is an essential element for plant growth and development; hence determining Fe distribution and concentration inside plant organs at the microscopic level is of great relevance to better understand its metabolism and bioavailability through the food chain. Among the available microanalytical techniques, synchrotron μ-XRF methods can provide a powerful and versatile array of analytical tools to study Fe distribution within plant samples. In the last years, the implementation of new algorithms and detection technologies has opened the way to more accurate (semi)quantitative analyses of complex matrices like plant materials. In this paper, for the first time the distribution of Fe within tomato roots has been imaged and quantified by means of confocal μ-XRF and exploiting a recently developed fundamental parameter-based algorithm. With this approach, Fe concentrations ranging from few hundreds of ppb to several hundreds of ppm can be determined at the microscopic level without cutting sections. Furthermore, Fe (semi)quantitative distribution maps were obtained for the first time by using two opposing detectors to collect simultaneously the XRF radiation emerging from both sides of an intact cucumber leaf.

Sugar-derived cyclic imines: one-pot synthesis and direct functionalization

A simple method for the synthesis of sugar-derived imines by a Schwartz's reagent reduction of easily available sugar lactams has been described. A direct addition of nucleophiles to the generated in situ cyclic imines and subsequent deprotection of hydroxyl function allows to convert sugar lactams in polyhydroxylated pyrrolidines and piperidines.