Competitive Multi-period Pricing with Fixed Inventories

This paper studies the problem of multi-period pricing for perishable products in a competitive (oligopolistic) market. We study non cooperative Nash equilibrium policies for sellers. At the beginning of the time horizon, the total inventories are given and additional production is not an available option. The analysis for periodic production-review models, where production decisions can be made at the end of each period at some production cost after incurring holding or backorder costs, does not extend to this model. Using results from game theory and variational inequalities we study the existence and uniqueness of equilibrium policies. We also study convergence results for an algorithm that computes the equilibrium policies. The model in this paper can be used in a number of application areas including the airline, service and retail industries. We illustrate our results through some numerical examples.Singapore-MIT Alliance (SMA

Anaerobic infections in patients admitted in various surgical units of a tertiary care hospital of north India: neglected but important

Background and Objectives: Anaerobic infections are usually caused by the host’s endogenous flora due to a breach in the anatomical barriers and Bacteroides spp. are the most notorious organisms associated with anaerobic infections. The identification of anaerobes has been a challenge since times. MALDI-TOF-MS is a boon for aiding the rapid detection of anaerobic organisms and has helped us to enlist the distribution of various anaerobic pathogens. Materials and Methods: This retrospective analysis (January 2018 to December 2019) was carried out in a tertiary care hospital in North India, in which the anaerobic microbiological profile of all patients admitted to surgical wards, ICU, and OPD of various departments (Orthopedics, Surgery, Gynecology, and Obstetrics) was reviewed. Samples received were immediately processed aerobically (5% sheep blood agar and Mac Conkeyagar) as well as anaerobically (RCM and freshly prepared sheep blood agar) as per the laboratory protocols. Results: Bacteroides fragilis (19.12%) was the most common anaerobe whereas among aerobes Escherichia coli (30.2%) followed by Klebsiella pneumoniae (10.34%) were most commonly isolated. The majority of patients were males (56%) and the most common presentation was with abscesses (21.4%). Polymicrobial infections (69.51%) outnumbered monomicrobial ones (30.48%). Conclusion: There is a paucity of literature on anaerobe isolation from surgical infections from our country which motivated us to study anaerobic infections and the high sample size in our institute enabled us to study surgical infections from an anaerobic perspective. This will add to the knowledge of microbiologists and clinicians. MALDI-TOF MS helped in rapid and accurate identification and hence we could report a wider spectrum of organisms in our study

UAV Battery Prognostics and Flight Time Estimation

Lithium-based battery systems are extensively used in the electric mobility industry. The safety, prognostics, and longevity of the batteries are assured by battery management systems. One of the features of these management systems is to accurately determine the charge in a battery which is used to estimate the remaining run time of the electric vehicle, in this case, a drone. It is currently not possible to evaluate the charge of a battery by simply measuring the external parameters such as voltage or current. This problem is also known as the state of charge estimation in scientific literature. \\In this thesis, a highly accurate battery state of charge estimation method is developed and the result from this estimation is further used to predict the remaining flight time of the drone. This is done by developing an estimation algorithm based on data-driven approach. An Artificial Neural Network takes the voltage, current, and temperature information as input to predict the State of Charge. Since this is a time-series forecasting problem, the estimation algorithm specifically utilizes a type of Neural Network called the Recurrent Neural Network. This can capture long-term dependencies and model sequential data without requiring any accurate physics-based system modeling knowledge. Using the battery charge estimation, the remaining battery charging or discharging time can be predicted based on the current consumption of the drone. The performance of the proposed model is compared to existing methods that use various variations and combinations of Recurrent Neural Networks and other types of neural networks to predict the state of charge of a lithium-based batteries. The results showed that the proposed model achieved superior accuracy for state of charge prediction in UAV batteries

Competitive multi-period pricing for perishable products

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2004.Includes bibliographical references (p. 161-165).Pricing of a perishable product over a multi-period time horizon is a challenging problem under an oligopolistic market framework. We propose and study a model for multi-period pricing in an oligopolistic market for a single perishable product. Each participating seller in the market has a fixed inventory of the product at the beginning of the time horizon and additional production is not an available option. Any unsold inventory at the end of the horizon is worthless. The sellers do not have the option of periodically reviewing and replenishing their inventory. Such a model is appropriate for modelling competition in situations where inventory replenishment decisions are made over a longer time horizon and can be considered exogenous to the pricing decision process. This kind of a setup can be used to model pricing of air fares, hotel reservations, bandwidth in communication networks, etc. In this thesis, we study two issues related to multi-period pricing of a perishable product. First we study the competitive aspect of the problem. Second we study the setup where the demand function for each seller has some associated uncertainty. We assume that the sellers would like to adopt a policy that is robust to adverse uncertain circumstances. We discuss the challenges associated with the analysis for this model.(cont.) We study non-cooperative Nash equilibrium policies for the sellers. We discuss why known results from the literature do not extend to this model. We introduce an optimization approach using results from variational inequality theory and robust optimization to establish existence of the pricing equilibrium policy and comment on the uniqueness of the pricing equilibrium policy. We also introduce an iterative learning algorithm for computing the equilibrium policy and analyze its convergence. We study how much is lost in terms of efficiency (in terms of total system profit) due to competition. Finally, we illustrate our results with some numerical examples and discuss some insights.by Anshul Sood.Ph.D

A Comparative Study of OLTP and OLAP Technologies

Abstract This paper provides an overview of Data warehousing and comparative study of OLAP, OLTP technologies. The data warehouse supports On-Line Analytical Processing (OLAP) who's functional and performance requirements are different from those of the On-Line Transaction Processing (OLTP) applications supported by the operational databases. Data warehousing and On-Line Analytical Processing (OLAP) are essential elements of decision support. OLTP is a class of program that facilitates and manages transaction-oriented applications. An OLAP system is used for data analysis by knowledge workers, including managers, business executives and market analysts. Data warehousing and OLAP have emerged as leading technologies that facilitate data storage, organization and retrieval

Dynamic Pricing in a Competitive Environment

We present a dynamic optimization approach for perishable products in a competitive and dynamically changing market. We build a general optimization framework that ties together the competetive and the dynamic nature of pricing. This approach also allows differential pricing for large customers as well as demand learning for the seller. We analyze special cases of the model and illustrate the policies numerically.Singapore-MIT Alliance (SMA

Extrinsic compression of left main coronary artery due to dilated pulmonary trunk resulting in ischaemic symptoms

<p>Left coronary artery compression syndrome is an uncommon entity and characterized by compression of the LMCA in-between the aorta and an enlarged main pulmonary arterial trunk. It is usually associated with a congenital cardiac defect. Cardiac 64-slice MDCT provides a non-invasive and an accurate method for assessing the degree of dynamic LMCA compression throughout the cardiac cycle, its angulation relative to the left sinus of Valsalva and depiction of pulmonary pathology, making it a valuable tool in the workup of patients suspected of left coronary artery compression.</p

Midgut Non Rotation in a Middle-aged Male with Suspected Pancreatitis

Midgut development is a dynamic process that begins from the fifth week of development. During this process, the midgut undergoes physiological herniation in the umbilical cord. Subsequently, it returns to the abdominal cavity through a complex 270° counterclockwise rotation [1]. This normal rotation results in the formation of a duodenojejunal loop on the left-side of the midline, a peripheral large bowel, a centrally located small bowel with the caecum in the right iliac fossa, and the duodenojejunal flexure on the left-side near the pylorus [2]. Disruption of this sequential return can lead to anomalies in midgut rotation, such as non rotation, malrotation, or reverse rotation [1]