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Abstract. Adverse commodity prices can cause significant negative cash flows and expose firms that deal in commodities to financial distress. In this paper we consider the dynamic risk management problem [...]

Abstract. We consider an e-commerce retailer (e-tailer) who sells a catalog of products to customers from different regions during a finite selling season and fulfills orders through multiple fulfillment centers. [...]

An omnichannel retailer with a network of physical stores and online fulfillment centers facing two demands (online and in‐store) has to make important, interlinked decisions—how much inventory to keep at each location and where to fulfill each online order from, as online demand can be fulfilled from any location with available inventory. We consider inventory decisions at the start of the selling horizon for a seasonal product, with online fulfillment decisions made multiple times over the horizon. To address the intractability in considering inventory and fulfillment decisions together, we relax the problem using a hindsight‐optimal bound, for which the inventory decision can be made independent of the optimal fulfillment decisions, while still incorporating virtual pooling of online demands across locations. We develop a computationally fast and scalable inventory heuristic for the multilocation problem based on the two‐store analysis. The inventory heuristic directly informs dynamic fulfillment decisions that guide online demand fulfillment from stores. Using a numerical study based on a fictitious network embedded in the United States, we show that our heuristic significantly outperforms traditional strategies. The value of centralized inventory planning is highest when there is a moderate mix of online and in‐store demands leading to synergies between pooling within and across locations, and this value increases with the size of the network. The inventory‐aware fulfillment heuristic considerably outperforms myopic policies seen in practice, and is found to be near‐optimal under a wide range of problem parameters. [ABSTRACT FROM AUTHOR]

Background: The present study was conducted to assess risk factors and prevalence of potentially malignant disorders (PMDs) among Indian population. Materials and Methods: 1280 Indian population of both genders were enrolled. Habits such as smoking bidi, cigarette, consumption of tobacco such as in the form of zarda, chaini khaini, pan masala, arecanut, and alcohol were recorded. Risk factors and prevalence rate of disorders were recorded. Results: There were 750 (58.6%) males and 530 (41.4%) females. Speckled leukoplakia was seen among 470 (36.7%), oral lichen planus (OLP) in 246 (19.2%), oral submucous fibrosis (OSMF) in 274 (21.4%), erythroplakia in 120 (9.3%), and oral squamous cell carcinoma (OSCC) in 107 (8.3%) participants. Maximum cases of speckled leukoplakia (162) was seen in the age group of 31-40 years, OLP (99) in 41-50 years, OSMF (95) in 31-40 years, erythroplakia (48) in 21-30 years, OSCC (44) in 41-50 years. Conclusion: Risks factors associated with PMDs were found to be tobacco and arecanut. There was higher prevalence of leukoplakia. Age group of 31-40 years had higher cases and most common site was buccal mucosa and vestibule. [ABSTRACT FROM AUTHOR]

Background: Root canal (RC) treatment is most common and effective method for treatment of diseases related to periapical area and pulp of teeth. With the increase in age, the formation of secondary dentin, calcification of canals, and reduction of medullary cavity volume, it becomes increasingly difficult to accomplish a perfect RC treatment, hence the understanding of RC variation and changes in variation with increasing age improves the success rates. Aim: The aim of this study was to study the RC variation in the age-group of 10–14 years and to find if the gradual increase in age plays a role in increasing the complexity of RC variation. Materials and Methods: This study was carried out in Government Medical College, Patna, Bihar, India, from January 2018 to April 2019. Subjects within the age range of 10–14 years were selected conferring to predetermined inclusion and exclusion criteria. The subjects were divided into the groups according to age—Group I: 10–11 years, Group II: 11–12 years, Group III: 12–13 years, and Group IV: 13–14 years. The subjects were further divided into Group A and B according to sex to study if there is any significant difference in RC variation. Three intraoral periapical (IOPA) radiography with radiovisiography (RVG) of each subject were taken from three different predetermined angles and these IOPAs were then analyzed by three independent observers and the most agreed on value was included. The IOPAs were analyzed for the number of roots, the number of canals in each root and the variation of each RC were classified according to Vertucci's Classification. Results: The most common T of RC variation in mesial root of mandibular first molar was T IV succeeded by T II and T I. For distal canal of mandibular first molar, the most common variation was T I, followed by T II and T III. In our study we found that 98.88% of mandibular molars were having two roots. No significant difference was found in the variation of canal according to age or sex in our study. Conclusion: Hence, we conclude that no significant difference is seen in RC variation according to sex and age. As the groups we included in our study were not wide apart enough in age, a further long-term study is needed to ascertain if the complexity of RC increases with age. [ABSTRACT FROM AUTHOR]

We consider an e-commerce retailer (e-tailer) who sells a catalog of products to customers from different regions during a finite selling season and fulfills orders through multiple fulfillment centers. The e-tailer faces a joint pricing and fulfillment (JPF) optimization problem: at the beginning of each period, the e-tailer needs to jointly decide the price for each product and how to fulfill an incoming order (i.e., from which warehouse to ship the order). The objective of the e-tailer is to maximize its total expected profits defined as total expected revenues minus total expected shipping costs. (All other costs are fixed in this problem.) The exact optimal policy for JPF is difficult to solve; so, we propose two heuristic controls that have provably good performance compared to reasonable benchmarks. Our first heuristic control directly uses the solution of a deterministic approximation of JPF as its control parameters. Our second heuristic control improves the first one by adaptively adjusting the original control parameters according to the realized demand. An important feature of the second heuristic control is that it decouples the real-time pricing and fulfillment decisions, making it easy to implement. We show theoretically and numerically that the second heuristic control significantly outperforms the first heuristic control and is very close to a benchmark that jointly reoptimizes the full deterministic problem at the beginning of every period. [ABSTRACT FROM AUTHOR]