Impact of In-store Promotion and Spillover Effect onPrivate Label Introduction

This paper investigates the impact of in-store promotion and its spillover effect on private label introductions. We study different retail supply chain scenarios where the retailer carrying a national brand may introduce its own private label product and promote either the national brand or the private label inside the store. The in-store promotion on one product has a positive spillover effect on the other product. Without in-store promotion and spillover effect, the conventional wisdom indicates that, in a retail supply chain, the national brand manufacturer will be negatively impacted by the introduction of a private label product. With in-store promotion and spillover effect, however, the national brand manufacturer can actually benefit from the private label introduction. When the spillover from national brand to private label is high, the retailer prefers to promote the national brand product. When the spillover from private label to national brand is high, promoting the private label product can also benefit the national brand manufacturer. With symmetric spillover rate, the national brand manufacturer can still benefit from the private label introduction, as long as the retailer promotes the national brand product, the horizontal competition is not intense, or the private label product quality is sufficiently low

A note on "The Economic Lot Sizing Problem with Inventory Bounds"

In a recent paper, Liu (2008) considers the lot-sizing problem with lower and upper bounds on the inventory levels. He proposes an O(n^2) algorithm for the general problem, and an O(n) algorithm for the special case with non-speculative motives. We show that neither of the algorithms provides an optimal solution in general. Furthermore, we propose a fix for the former algorithm that maintains the O(n^2) complexity

Estimation and Testing of Gene Expression Heterosis

Heterosis, also known as the hybrid vigor, occurs when the mean phenotype of hybrid offspring is superior to that of its two inbred parents. The heterosis phenomenon is extensively utilized in agriculture though the molecular basis is still unknown. In an effort to understand phenotypic heterosis at the molecular level, researchers have begun to compare expression levels of thousands of genes between parental inbred lines and their hybrid offspring to search for evidence of gene expression heterosis. Standard statistical approaches for separately analyzing expression data for each gene can produce biased and highly variable estimates and unreliable tests of heterosis. To address these shortcomings, we develop a hierarchical model to borrow information across genes. Using our modeling framework, we derive empirical Bayes estimators and an inference strategy to identify gene expression heterosis. Simulation results show that our proposed method outperforms the more traditional strategy used to detect gene expression heterosis. This article has supplementary material online

Revenue management models in the manufacturing industry

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2005.Includes bibliographical references (p. 107-110).In recent years, many manufacturing companies have started exploring innovative revenue management technologies in an effort to improve their operations and ultimately their bottom lines. Methods such as differentiating customers based on their sensitivity to price and delays are employed by firms to increase their profits. These developments call for models that have the potential to radically improve supply chain efficiencies in much the same way that revenue management has changed the airline industry. In this dissertation, we study revenue management models where customers can be separated into different classes depending on their sensitivity to price, lead time, and service. Specifically, we focus on identifying effective models to coordinate production, inventory and admission controls in face of multiple classes of demand and time- varying parameters. We start with a single-class-customer problem with both backlogged and discretionary sales. Demand may be fulfilled no later than N periods with price discounts if the inventory is not available. If profitable, demand may be rejected even if the inventory is still available.(cont.) For this problem we analyze the structure of the optimal policy and show that it is characterized by three state-independent control parameters: the produce-up-to level (S), the reserve-up-to level (R), and the backlog-up-to level (B). At the beginning of each period, the manufacturer will produce to bring the inventory level up to S or to the maximum capacity; during the period, s/he will set aside R units of inventory for the next period, and satisfy some customers with the remaining inventory, if expected future profit is higher; otherwise, s/he will satisfy customers with the inventory and backlog up to B units of demands. Then, we analyze a single-product, two-class-customer model in which demanding (high priority) customers would like to receive products immediately, while other customers are willing to wait in order to pay lower prices. For this model, we provide a heuristic policy characterized by three threshold levels: S, R, B.(cont.) In this policy, during each period, the manufacturer will set aside R units of inventory for the next period, and satisfy some high priority customers with the remaining inventory, if expected future profit is higher; otherwise, s/he will satisfy as many of the high priority customers as possible and backlog up to B units of lower priority customers. Finally, we examine production, rationing, and admission control policies in manufacturing systems with both make-to-stock(MTS) and make-to-order(MTO) products. Two models are analyzed. In the first model, which is motivated by the automobile industry, the make-to-stock product has higher priority than the make-to-order product. In the second model, which is motivated by the PC industry, the manufacturer gives higher priority to the make-to-order product over the make-to-stock product. We characterize the optimal production and order admission policies with linear threshold levels. We also extend those results to problems where low-priority backorders can be canceled by the manufacturer, as well as to problems with multiple types of make-to-order products.by Tieming Liu.Ph.D

Aloperine attenuates high glucose-induced oxidative injury in Schwann cells via activation of NRF2/HO-1 pathway

Purpose: To determine the involvement of nuclear factor erythroid 2-related factor 2 (NRF2) and heme oxygenase-1 (HO-1) in the action of aloperine on Schwann cell injury caused by high glucose (HG).Methods: Cell viability was determined using MTT assay while the release of lactate dehydrogenase (LDH) was determined by biochemical assay. Apoptosis was assessed using flow cytometry, while the levels of malondialdehyde (MDA) were determined by Annexin V-FIT staining. Glutathione Stransferase (GST), glutathione peroxidase (GPX), and reactive oxygen species (ROS) were determined using enzyme-linked immunosorbent assay.Results: Treatment with HG suppressed RSC96 cell viability and increased LDH release, while aloperine reversed these results (p < 0.05). Apoptosis of RSC96 cells was induced by HG stimulation, but was abolished by aloperine. The levels of ROS, MDA, and GST were enhanced in cells followingtreatment with HG, but was reversed by aloperine (p < 0.05). The decreased level of GPX caused by HG in RSC96 cells was elevated by aloperine. Moreover, aloperine upregulated NRF2 and HO-1 in RSC96 cells treated with HG (p < 0.05).Conclusion: Aloperine attenuates HG-induced oxidative injury in Schwann cells via activation of NRF2/HO-1 pathway, suggesting its potential as a potent drug for the management of diabetic peripheral neuropathy. Keywords: Aloperine, Schwann cells, High glucose, Oxidative stress, NRF2, HO-

Formalizing and verifying stochastic system architectures using Monterey Phoenix

The analysis of software architecture plays an important role in understanding the system structures and facilitate proper implementation of user requirements. Despite its importance in the software engineering practice, the lack of formal description and verification support in this domain hinders the development of quality architectural models. To tackle this problem, in this work, we develop an approach for modeling and verifying software architectures specified using Monterey Phoenix (MP) architecture description language. MP is capable of modeling system and environment behaviors based on event traces, as well as supporting different architecture composition operations and views. First, we formalize the syntax and operational semantics for MP; therefore, formal verification of MP models is feasible. Second, we extend MP to support shared variables and stochastic characteristics, which not only increases the expressiveness of MP, but also widens the properties MP can check, such as quantitative requirements. Third, a dedicated model checker for MP has been implemented, so that automatic verification of MP models is supported. Finally, several experiments are conducted to evaluate the applicability and efficiency of our approachNo Full Tex