Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy. © 2013 Elsevier B.V. All rights reserved.

Dynamic pricing for used products in remanufacturing with back orders(ABS 3* Journal, Accepted with Revision on 2nd December 2011).

In remanufacturing, the supply of used products and the demand for remanufactured products are usually mismatched because of the great uncertainties on both sides. In this paper, we propose a dynamic pricing policy to balance this uncertain supply and demand. Specifically, we study a remanufacturer’s problem of pricing a single class of cores with random price-dependent returns and random demand for the remanufactured products with backlogs. We model this pricing task as a continuous-time Markov decision process, which addresses both the finite and infinite horizon problems, and provide managerial insights by analyzing the structural properties of the optimal policy. We then use several computational examples to illustrate the impacts of particular system parameters on pricing policy.

Vasoactivity of Rucaparib, a PARP-1 Inhibitor, is a Complex Process that Involves Myosin Light Chain Kinase, P2 Receptors, and PARP Itself

Therapeutic inhibition of poly(ADP-ribose) polymerase (PARP), as monotherapy or to supplement the potencies of other agents, is a promising strategy in cancer treatment. We previously reported that the first PARP inhibitor to enter clinical trial, rucaparib (AG014699), induced vasodilation in vivo in xenografts, potentiating response to temozolomide. We now report that rucaparib inhibits the activity of the muscle contraction mediator myosin light chain kinase (MLCK) 10-fold more potently than its commercially available inhibitor ML-9. Moreover, rucaparib produces additive relaxation above the maximal degree achievable with ML-9, suggesting that MLCK inhibition is not solely responsible for dilation. Inhibition of nitric oxide synthesis using L-NMMA also failed to impact rucaparib's activity. Rucaparib contains the nicotinamide pharmacophore, suggesting it may inhibit other NAD+-dependent processes. NAD+ exerts P2 purinergic receptor-dependent inhibition of smooth muscle contraction. Indiscriminate blockade of the P2 purinergic receptors with suramin abrogated rucaparib-induced vasodilation in rat arterial tissue without affecting ML-9-evoked dilation, although the specific receptor subtypes responsible have not been unequivocally identified. Furthermore, dorsal window chamber and real time tumor vessel perfusion analyses in PARP-1-/- mice indicate a potential role for PARP in dilation of tumor-recruited vessels. Finally, rucaparib provoked relaxation in 70% of patient-derived tumor-associated vessels. These data provide tantalising evidence of the complexity of the mechanism underlying rucaparib-mediated vasodilation.

Characterisation of Bioresorbable Composite Performance for Validation of New On-Line Process Monitoring Technology

There is an increasing interest in the biomedical field to create implantable medical devices to provide a temporary mechanical function for use inside the human body. In many of these applications bioresorbable polymer composites using PLLA with β-TCP , are increasingly being used due to their biocompatability, biodegradability and mechanical strength.1,3 These medical devices can be manufactured using conventional plastics processing methods such as injection moulding and extrusion, however there is great need to understand and control the process due to a lack of knowledge on the influence of processing on material properties. With the addition of biocompatible additives there is also a requirement to be able to predict the quality and level of dispersion within the polymer matrix. On-line UV-Vis spectroscopy has been shown to monitor the quality of fillers in polymers. This can eliminate time consuming and costly post-process evaluation of additive dispersion. The aim of this work was to identify process and performance relationships of PLLA/β-TCP composites with respect to melt-extrusion conditions. This is part of a wider study into on-line process monitoring of bioresorbable polymers as used in the medical industry.
These results show that final properties of the PLLA/ β-TCP composite are highly influenced by the particle size and loading. UV-Vis spectroscopy can be used on-line to monitor the final product and this can be utilised as a valuable tool for quality control in an application where consistent performance is of paramount importance.

An optimized process design for oxymethylene ether production from woody-biomass-derived syngas

The conversion of biomass for the production of liquid fuels can help reduce the greenhouse gas (GHG) emissions that are predominantly generated by the combustion of fossil fuels. Oxymethylene ethers (OMEs) are a series of liquid fuel additives that can be obtained from syngas, which is produced from the gasification of biomass. The blending of OMEs in conventional diesel fuel can reduce soot formation during combustion in a diesel engine. In this research, a process for the production of OMEs from woody biomass has been simulated. The process consists of several unit operations including biomass gasifi- cation, syngas cleanup, methanol production, and conversion of methanol to OMEs. The methodology involved the development of process models, the identification of the key process parameters affecting OME production based on the process model, and the development of an optimal process design for high OME yields. It was found that up to 9.02 tonnes day1 of OME3, OME4, and OME5 (which are suitable as diesel additives) can be produced from 277.3 tonnes day1 of wet woody biomass. Furthermore, an optimal combination of the parameters, which was generated from the developed model, can greatly enhance OME production and thermodynamic efficiency. This model can further be used in a techno- economic assessment of the whole biomass conversion chain to produce OMEs. The results of this study can be helpful for petroleum-based fuel producers and policy makers in determining the most attractive pathways of converting bio-resources into liquid fuels.