No-Holdback allocation rules for continuous-time assemble-to-order systems

This paper analyzes a class of common-component allocation rules, termed no-holdback (NHB) rules, in continuous-review assemble-to-order (ATO) systems with positive lead times. The inventory of each component is replenished following an independent base-stock policy. In contrast to the usually assumed first-come-first-served (FCFS) component allocation rule in the literature, an NHB rule allocates a component to a product demand only if it will yield immediate fulfillment of that demand. We identify metrics as well as cost and product structures under which NHB rules outperform all other component allocation rules. For systems with certain product structures, we obtain key performance expressions and compare them to those under FCFS. For general product structures, we present performance bounds and approximations. Finally, we discuss the applicability of these results to more general ATO systems. © 2010 INFORMS.

A genetically engineered thermally responsive sustained release curcumin depot to treat neuroinflammation.

Radiculopathy, a painful neuroinflammation that can accompany intervertebral disc herniation, is associated with locally increased levels of the pro-inflammatory cytokine tumor necrosis factor alpha (TNFα). Systemic administration of TNF antagonists for radiculopathy in the clinic has shown mixed results, and there is growing interest in the local delivery of anti-inflammatory drugs to treat this pathology as well as similar inflammatory events of peripheral nerve injury. Curcumin, a known antagonist of TNFα in multiple cell types and tissues, was chemically modified and conjugated to a thermally responsive elastin-like polypeptide (ELP) to create an injectable depot for sustained, local delivery of curcumin to treat neuroinflammation. ELPs are biopolymers capable of thermally-triggered in situ depot formation that have been successfully employed as drug carriers and biomaterials in several applications. ELP-curcumin conjugates were shown to display high drug loading, rapidly release curcumin in vitro via degradable carbamate bonds, and retain in vitro bioactivity against TNFα-induced cytotoxicity and monocyte activation with IC50 only two-fold higher than curcumin. When injected proximal to the sciatic nerve in mice via intramuscular (i.m.) injection, ELP-curcumin conjugates underwent a thermally triggered soluble-insoluble phase transition, leading to in situ formation of a depot that released curcumin over 4days post-injection and decreased plasma AUC 7-fold.

A COMPARISON OF MARKET CLEARING TOOLS IN ELECTRICITY SYSTEMS

To maintain a strict balance between demand and supply in the US power systems, the Independent System Operators (ISOs) schedule power plants and determine electricity prices using a market clearing model. This model determines for each time period and power plant, the times of startup, shutdown, the amount of power production, and the provisioning of spinning and non-spinning power generation reserves, etc. Such a deterministic optimization model takes as input the characteristics of all the generating units such as their power generation installed capacity, ramp rates, minimum up and down time requirements, and marginal costs for production, as well as the forecast of intermittent energy such as wind and solar, along with the minimum reserve requirement of the whole system. This reserve requirement is determined based on the likelihood of outages on the supply side and on the levels of error forecasts in demand and intermittent generation. With increased installed capacity of intermittent renewable energy, determining the appropriate level of reserve requirements has become harder. Stochastic market clearing models have been proposed as an alternative to deterministic market clearing models. Rather than using a fixed reserve targets as an input, stochastic market clearing models take different scenarios of wind power into consideration and determine reserves schedule as output. Using a scaled version of the power generation system of PJM, a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia, and wind scenarios generated from BPA (Bonneville Power Administration) data, this paper explores a comparison of the performance between a stochastic and deterministic model in market clearing. The two models are compared in their ability to contribute to the affordability, reliability and sustainability of the electricity system, measured in terms of total operational costs, load shedding and air emissions. The process of building the models and running for tests indicate that a fair comparison is difficult to obtain due to the multi-dimensional performance metrics considered here, and the difficulty in setting up the parameters of the models in a way that does not advantage or disadvantage one modeling framework. Along these lines, this study explores the effect that model assumptions such as reserve requirements, value of lost load (VOLL) and wind spillage costs have on the comparison of the performance of stochastic vs deterministic market clearing models.