Dynamic Procurement of New Products with Covariate Information: The Residual Tree Method

Problem definition: We study the practice-motivated problem of dynamically procuring a new, short life-cycle product under demand uncertainty. The firm does not know the demand for the new product but has data on similar products sold in the past, including demand histories and covariate information such as product characteristics. Academic/practical relevance: The dynamic procurement problem has long attracted academic and practitioner interest, and we solve it in an innovative data-driven way with proven theoretical guarantees. This work is also the first to leverage the power of covariate data in solving this problem. Methodology:We propose a new, combined forecasting and optimization algorithm called the Residual Tree method, and analyze its performance via epi-convergence theory and computations. Our method generalizes the classical Scenario Tree method by using covariates to link historical data on similar products to construct demand forecasts for the new product. Results: We prove, under fairly mild conditions, that the Residual Tree method is asymptotically optimal as the size of the data set grows. We also numerically validate the method for problem instances derived using data from the global fashion retailer Zara. We find that ignoring covariate information leads to systematic bias in the optimal solution, translating to a 6–15% increase in the total cost for the problem instances under study. We also find that solutions based on trees using just 2–3 branches per node, which is common in the existing literature, are inadequate, resulting in 30–66% higher total costs compared with our best solution. Managerial implications: The Residual Tree is a new and generalizable approach that uses past data on similar products to manage new product inventories. We also quantify the value of covariate information and of granular demand modeling

Signal Processing

Contains reports on three research projects.Joint Services Electronics Programs (U.S. Army, U. S. Navy, and U. S. Air Force) under Contract DAAB07-71-C-0300U. S. Coast Guard (Contract DOT-CG -13446-A)M.I.T. Lincoln Laboratory Purchase Order CC-57

Digital Signal Processing

Contains research objectives and summary of research.National Science Foundation (Grant GK-31353)U. S. Navy Office of Naval Research (Contract N00014-67-A-0204-0064

Longitudinal Effects of Embryonic Exposure to Cocaine on Morphology, Cardiovascular Physiology, and Behavior in Zebrafish

A sizeable portion of the societal drain from cocaine abuse results from the complications of in utero drug exposure. Because of challenges in using humans and mammalian model organisms as test subjects, much debate remains about the impact of in utero cocaine exposure. Zebrafish offer a number of advantages as a model in longitudinal toxicology studies and are quite sensitive physiologically and behaviorally to cocaine. In this study, we have used zebrafish to model the effects of embryonic pre-exposure to cocaine on development and on subsequent cardiovascular physiology and cocaine-induced conditioned place preference (CPP) in longitudinal adults. Larval fish showed a progressive decrease in telencephalic size with increased doses of cocaine. These treated larvae also showed a dose dependent response in heart rate that persisted 24 h after drug cessation. Embryonic cocaine exposure had little effect on overall health of longitudinal adults, but subtle changes in cardiovascular physiology were seen including decreased sensitivity to isoproterenol and increased sensitivity to cocaine. These longitudinal adult fish also showed an embryonic dose-dependent change in CPP behavior, suggesting an increased sensitivity. These studies clearly show that pre-exposure during embryonic development affects subsequent cocaine sensitivity in longitudinal adults

What next for preimplantation genetic screening? A polar body approach!

Screening of human preimplantation embryos for numerical chromosome abnormalities has been conducted mostly at the preimplantation stage using fluorescence in situ hybridization. However, it is clear that preimplantation genetic screening (PGS) as it is currently practiced does not improve live birth rates. Therefore the ESHRE PGS Task Force has decided to start a proof of principle study with the aim of determining whether biopsy of the first and second polar body followed by subsequent analysis of the complete chromosome complement of these polar bodies using an array based technique enables a timely identification of the chromosomal status of an oocyte. If the principle of this approach can be proven, it is obvious that a multicentre randomized controlled trial should then be started to determine the clinical value of this technique. In this way the ESHRE PGS Task Force hopes to redirect preimplantation screening from the blind alley to the main road of assisted reproduction

Polar body array CGH for prediction of the status of the corresponding oocyte. Part I: clinical results

Several randomized controlled trials have not shown a benefit from preimplantation genetic screening (PGS) biopsy of cleavage-stage embryos and assessment of up to 10 chromosomes for aneuploidy. Therefore, a proof-of-principle study was planned to determine the reliability of alternative form of PGS, i.e. PGS by polar body (PB) biopsy, with whole genome amplification and microarray-based comparative genomic hybridization (array CGH) analysis. In two centres, all mature metaphase II oocytes from patients who consented to the study were fertilized by ICSI. The first and second PBs (PB1and PB2) were biopsied and analysed separately for chromosome copy number by array CGH. If either or both of the PBs were found to be aneuploid, the corresponding zygote was then also processed by array CGH for concordance analysis. Both PBs were biopsied from a total of 226 zygotes from 42 cycles (average 5.5 per cycle; range 1-15) in 41 couples with an average maternal age of 40.0 years. Of these, the ploidy status of the zygote could be predicted in 195 (86%): 55 were euploid (28%) and 140 were aneuploid (72%). With only one exception, there was at least one predicted aneuploid zygote in each cycle and in 19 out of 42 cycles (45%), all zygotes were predicted to be aneuploid. Fresh embryos were transferred in the remaining 23 cycles (55%), and one frozen transfer was done. Eight patients had a clinical pregnancy of which seven were evolutive (ongoing pregnancy rates: 17% per cycle and 30% per transfer). The ploidy status of 156 zygotes was successfully analysed by array CGH: 38 (24%) were euploid and 118 (76%) were aneuploid. In 138 cases complete information was available on both PBs and the corresponding zygotes. In 130 (94%), the ploidy status of the zygote was concordant with the ploidy status of the PBs and in 8 (6%), the results were discordant. This proof-of-principle study indicates that the ploidy of the zygote can be predicted with acceptable accuracy by array CGH analysis of both PB

Bayesian Policy Reuse

A long-lived autonomous agent should be able to respond online to novel instances of tasks from a familiar domain. Acting online requires 'fast' responses, in terms of rapid convergence, especially when the task instance has a short duration, such as in applications involving interactions with humans. These requirements can be problematic for many established methods for learning to act. In domains where the agent knows that the task instance is drawn from a family of related tasks, albeit without access to the label of any given instance, it can choose to act through a process of policy reuse from a library, rather than policy learning from scratch. In policy reuse, the agent has prior knowledge of the class of tasks in the form of a library of policies that were learnt from sample task instances during an offline training phase. We formalise the problem of policy reuse, and present an algorithm for efficiently responding to a novel task instance by reusing a policy from the library of existing policies, where the choice is based on observed 'signals' which correlate to policy performance. We achieve this by posing the problem as a Bayesian choice problem with a corresponding notion of an optimal response, but the computation of that response is in many cases intractable. Therefore, to reduce the computation cost of the posterior, we follow a Bayesian optimisation approach and define a set of policy selection functions, which balance exploration in the policy library against exploitation of previously tried policies, together with a model of expected performance of the policy library on their corresponding task instances. We validate our method in several simulated domains of interactive, short-duration episodic tasks, showing rapid convergence in unknown task variations.Comment: 32 pages, submitted to the Machine Learning Journa

Time to cancer treatment and reproductive outcomes after fertility preservation among adolescent and young adult women with cancer

Background: Fertility preservation (FP) may be underused after cancer diagnosis because of uncertainty around delays to cancer treatment and subsequent reproductive success. Methods: Women aged 15 to 39 years diagnosed with cancer between 2004 and 2015 were identified from the North Carolina Central Cancer Registry. Use of assisted reproductive technology (ART) after cancer diagnosis between 2004 and 2018 (including FP) was assessed through linkage to the Society for Assisted Reproductive Technology. Linear regression was used to examine time to cancer treatment among women who did (n = 95) or did not (n = 469) use FP. Modified Poisson regression was used to estimate risk ratios (RRs) and 95% CIs for pregnancy and birth based on timing of ART initiation relative to cancer treatment (n = 18 initiated before treatment for FP vs n = 26 initiated after treatment without FP). Results: The median time to cancer treatment was 9 to 33 days longer among women who used FP compared with women who did not, matched on clinical factors. Women who initiated ART before cancer treatment may be more likely to have a live birth given pregnancy compared with women who initiated ART after cancer treatment (age-adjusted RR, 1.47; 95% CI, 0.98-2.23), though this may be affected by the more frequent use of gestational carriers in the former group (47% vs 20% of transfer cycles, respectively). Conclusions: FP delayed gonadotoxic cancer treatment by up to 4.5 weeks, a delay that would not be expected to alter prognosis for many women. Further study of the use of gestational carriers in cancer populations is warranted to better understand its effect on reproductive outcomes

Parents' psychological adjustment in families of children with Spina Bifida: a meta-analysis

BACKGROUND: Spina Bifida (SB) is the second most common birth defect worldwide. Since the chances of survival in children with severe SB-forms have increased, medical care has shifted its emphasis from life-saving interventions to fostering the quality of life for these children and their families. Little is known, however, about the impact of SB on family adjustment. Reviewers have struggled to synthesize the few contradictory studies available. In this systematic review a new attempt was made to summarize the findings by using meta-analysis and by delimiting the scope of review to one concept of family adjustment: Parents' psychological adjustment. The questions addressed were: (a) do parents of children with SB have more psychological distress than controls? (b) do mothers and fathers differ? and (c) which factors correlate with variations in psychological adjustment? METHODS: PsycInfo, Medline, and reference lists were scanned. Thirty-three relevant studies were identified of which 15 were eligible for meta-analysis. RESULTS: SB had a negative medium-large effect on parents' psychological adjustment. The effect was more heterogeneous for mothers than for fathers. In the reviewed studies child factors (age, conduct problems, emotional problems, and mental retardation), parent factors (SES, hope, appraised stress, coping, and parenting competence), family factors (family income, partner relationship, and family climate), and environmental factors (social support) were found to be associated with variations in parents' psychological adjustment. CONCLUSION: Meta-analysis proved to be helpful in organizing studies. Clinical implications indicate a need to be especially alert to psychological suffering in mothers of children with SB. Future research should increase sample sizes through multi-center collaborations