Dynamic pricing with demand learning under competition

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 199-204).In this thesis, we focus on oligopolistic markets for a single perishable product, where firms compete by setting prices (Bertrand competition) or by allocating quantities (Cournot competition) dynamically over a finite selling horizon. The price-demand relationship is modeled as a parametric function, whose parameters are unknown, but learned through a data driven approach. The market can be either in disequilibrium or in equilibrium. In disequilibrium, we consider simultaneously two forms of learning for the firm: (i) learning of its optimal pricing (resp. allocation) strategy, given its belief regarding its competitors' strategy; (ii) learning the parameters in the price-demand relationship. In equilibrium, each firm seeks to learn the parameters in the price-demand relationship for itself and its competitors, given that prices (resp. quantities) are in equilibrium. In this thesis, we first study the dynamic pricing (resp. allocation) problem when the parameters in the price-demand relationship are known. We then address the dynamic pricing (resp. allocation) problem with learning of the parameters in the price-demand relationship. We show that the problem can be formulated as a bilevel program in disequilibrium and as a Mathematical Program with Equilibrium Constraints (MPECs) in equilibrium. Using results from variational inequalities, bilevel programming and MPECs, we prove that learning the optimal strategies as well as the parameters, is achieved. Furthermore, we design a solution method for efficiently solving the problem. We prove convergence of this method analytically and discuss various insights through a computational study.(cont.) Finally, we consider closed-loop strategies in a duopoly market when demand is stochastic. Unlike open-loop policies (such policies are computed once and for all at the beginning of the time horizon), closed loop policies are computed at each time period, so that the firm can take advantage of having observed the past random disturbances in the market. In a closed-loop setting, subgame perfect equilibrium is the relevant notion of equilibrium. We investigate the existence and uniqueness of a subgame perfect equilibrium strategy, as well as approximations of the problem in order to be able to compute such policies more efficiently.by Carine Simon.Ph.D

Hydrodynamic study of a monolith-type reactor for intensification of gas-liquid applications

Two-phase monolith-type reactors allow intensified heat and mass transfer rates, but often suffer from fluid maldistribution and undesired flow regimes in channels. A cold-flow monolith reactor (0.1 m diameter, 84 channels) is used here to assess liquid distribution and flow regimes at various air and water velocities: resistive probes give an insight of the flow patterns within 5 representative channels located at different radial positions, showing that regime transition to Taylor flow occurs in these channels simultaneously at lower gas and liquid superficial velocities than predicted by single capillary studies (namely uL and uG < 0.1 m s−1). nA full mapping of the partial liquid flow rates in the monolith channels is derived by a gravimetric method via specifically designed collectors. In the identified Taylor flow domain, liquid distribution exhibits a W-shaped profile with marked peaks at low liquid velocity (uL = 0.04 m s−1). Increasing the liquid flow rate significantly (uL = 0.1 m s−1) smooths liquid distribution, reducing the maldistribution factor by half. Gas velocity also helps phase uniformity but to a smaller extent. It is estimated that even higher fluid velocities (at least tripled) would be required to feed all channels equally. Adding stack of distribution plates of variable cell density at the top of the monolith does not enhance the quality of the liquid distribution, except at low liquid velocity

Enabling planetary science across light-years. Ariel Definition Study Report

Ariel, the Atmospheric Remote-sensing Infrared Exoplanet Large-survey, was adopted as the fourth medium-class mission in ESA's Cosmic Vision programme to be launched in 2029. During its 4-year mission, Ariel will study what exoplanets are made of, how they formed and how they evolve, by surveying a diverse sample of about 1000 extrasolar planets, simultaneously in visible and infrared wavelengths. It is the first mission dedicated to measuring the chemical composition and thermal structures of hundreds of transiting exoplanets, enabling planetary science far beyond the boundaries of the Solar System. The payload consists of an off-axis Cassegrain telescope (primary mirror 1100 mm x 730 mm ellipse) and two separate instruments (FGS and AIRS) covering simultaneously 0.5-7.8 micron spectral range. The satellite is best placed into an L2 orbit to maximise the thermal stability and the field of regard. The payload module is passively cooled via a series of V-Groove radiators; the detectors for the AIRS are the only items that require active cooling via an active Ne JT cooler. The Ariel payload is developed by a consortium of more than 50 institutes from 16 ESA countries, which include the UK, France, Italy, Belgium, Poland, Spain, Austria, Denmark, Ireland, Portugal, Czech Republic, Hungary, the Netherlands, Sweden, Norway, Estonia, and a NASA contribution

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P &lt; 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The ongoing French metastatic breast cancer (MBC) cohort: the example-based methodology of the Epidemiological Strategy and Medical Economics (ESME)

International audiencePurpose The currently ongoing Epidemiological Strategy and Medical Economics (ESME) research programme aims at centralising real-life data on oncology care for epidemiological research purposes. We draw on results from the metastatic breast cancer (MBC) cohort to illustrate the methodology used for data collection in the ESME research programme. Participants All consecutive ≥18 years patients with MBC treatment initiated between 2008 and 2014 in one of the 18 French Comprehensive Cancer Centres were selected. Diagnostic, therapeutic and follow-up data (demographics, primary tumour, metastatic disease, treatment patterns and vital status) were collected through the course of the disease. Data collection is updated annually. Finding to date With a recruitment target of 30 000 patients with MBC by 2019, we currently screened a total of 45 329 patients, and >16 700 patients with a metastatic disease treatment initiated after 2008 have been selected. 20.7% of patients had an hormone receptor (HR)-negative MBC, 73.7% had a HER2-negative MBC and 13.9% were classified as triple-negative BC (ie, HER2 and HR status both negative). Median follow-up duration from MBC diagnosis was 48.55 months for the whole cohort. Future plans These real-world data will help standardise the management of MBC and improve patient care. A dozen of ancillary research projects have been conducted and some of them are already accepted for publication or ready to be issued. The ESME research programme is expanding to ovarian cancer and advanced/metastatic lung cancer. Our ultimate goal is to achieve a continuous link to the data of the cohort to the French national Health Data System for centralising data on healthcare reimbursement (drugs, medical procedures), inpatient/outpatient stays and visits in primary/secondary care settings

Travel Med Infect Dis

BACKGROUND: Literature on health events in HIV-infected travellers is scarce, particularly in sub-Saharan African (SSA) migrants. METHODS: We investigated health events in HIV-infected SSA migrants living in France during and after travel to their native country. All had a pre-travel plasma viral load (pVL) below 200 copies/mL and were on stable combined antiretroviral therapy (cART). Logistic regression models were used to assess the risk factors for at least one adverse health event or febrile event. RESULTS: Among 264 HIV migrants, pre-travel median CD4 count was 439/mm3 and 27 migrants (6%) experienced a low-level viremia between 50 and 200 copies/mL. One hundred (38%) experienced at least one event (13 experienced two events). The most common events were gastrointestinal, including diarrhoea (n=29, 26%), respiratory events (n=20, 18%), and malaria (n=17, 15%; 1 death). In multivariable analysis, a pre-travel low-level viremia and a lack of pre-travel medical advice significantly increased the risk for any event (OR 4.31, 95% CI, 1.41-13.1; and OR 3.62, 95% CI, 1.38-9.47; respectively). A lack of pre-travel advice significantly increased the risk for febrile event. CONCLUSIONS: Early and tailored counselling on pre-travel medical advice regarding diarrhoea and vector-borne diseases prophylactic measures in HIV-infected SSA migrants should be emphasised before travel to Africa

Prenatal exome sequencing, a powerful tool for improving the description of prenatal features associated with genetic disorders

International audienceAbstract Objective Prenatal exome sequencing (pES) is now commonly used in clinical practice. It can be used to identifiy an additional diagnosis in around 30% of fetuses with structural defects and normal chromosomal microarray analysis (CMA). However, interpretation remains challenging due to the limited prenatal data for genetic disorders. Method We conducted an ancillary study including fetuses with pathogenic/likely pathogenic variants identified by trio‐pES from the “AnDDI‐Prenatome” study. The prenatal phenotype of each patient was categorized as typical, uncommon, or unreported based on the comparison of the prenatal findings with documented findings in the literature and public phenotype‐genotype databases (ClinVar, HGMD, OMIM, and Decipher). Results Prenatal phenotypes were typical for 38/56 fetuses (67.9%). For the others, genotype‐phenotype associations were challenging due to uncommon prenatal features (absence of recurrent hallmark, rare, or unreported). We report the first prenatal features associated with LINS1 and PGM1 variants. In addition, a double diagnosis was identified in three fetuses. Conclusion Standardizing the description of prenatal features, implementing longitudinal prenatal follow‐up, and large‐scale collection of prenatal features are essential steps to improving pES data interpretation