303 research outputs found
Raw and preprocessed data: Talluri, Kang et al. 2022
No full textExample raw data, preprocessed data to reproduce analyses in Talluri, Kang et al. 2022 bioRxiv. doi: 10.1101/2022.09.08.507006. (now in press at Nature Neuroscience).The code to reproduce the analysis is in https://github.com/NienborgLab/TalluriKang_et_al_2022.Raw and preprocessed data files are in .mat format.If you use the data or the code, please cite: Talluri, B. C., Kang I., Lazere, A., Quinn, K. R., Kaliss, N., Yates, J.L., Butts, D.A., Nienborg, H. (2022). Activity in primate visual cortex is minimally driven by spontaneous movements. bioRxiv. 2022.09.08.507006. doi: https://doi.org/10.1101/2022.09.08.507006</p
Neonatal hyperbilirubinemia. Evidence for a role of the erythrocyte enzyme activities involved in the detoxification of oxygen radicals
No full textDeterminations of erythrocyte enzyme scavengers of oxygen radicals (glutathione-peroxidase, superoxide-dismutase and catalase) and determinations of erythrocytes age-dependent glycolytic activities (glucose-6-phosphatedehydrogenase, pyruvate-kinase and glucose-phosphate-isomerase) were carried out in cord blood and in the blood taken on the 4th day of life in 152 newborn infants with different peak bilirubin levels. The enzyme activities scavenging oxygen radicals, glutathione-peroxidase and superoxide-dismutase were significantly lower in infants with peak bilirubinemia higher than 214 μmol/l, compared to less-jaundiced neonates, both at birht and on the 4th day of life; their values correlated negatively with peak bilirubinemia at birth and on the 4th day of life. Glycolytic age-dependent enzyme activities were significantly higher in more jaundiced newborn infants only on the 4th day of life, when their values correlated positively with peak bilirubinemia. The results of this investigation suggest that a deficiency of factors protecting from oxygen toxicity, may play a role in the development of neonatal hemolysis and jaundice
Hypothalamo-pituitary-adrenal axis and adrenal function before and after ovariectomy in premenopausal women
No full textThe hypothalamo-pituitary-adrenal (HPA) axis is modulated by sex hormones. Few data exist on the relation between acute estrogen deficit and HPA axis response to corticotropin-releasing hormone (CRH). The effects of a sudden drop in estradiol levels on basal and CRH-stimulated levels of ACTH, cortisol, testosterone, androstenedione and 17-hydroxyprogesterone (17-OHP) were assessed in nine premenopausal women (44-48 years of age), before and after ovariectomy. The CRH test was performed before and 8 days after ovariectomy. A significant reduction in ACTH and adrenal steroids but not in cortisol response to CRH was observed after ovariectomy. The ratio of deltamax androstenedione/17-OHP after CRH stimulation was substantially the same before and after ovariectomy, whereas deltamax 17-OHP/cortisol was significantly lower in ovariectomized women showing increased 21- and 11beta-hydroxylase activity. The results show that the acute estrogen deficit induces changes in the HPA axis characterized by reduced stimulated secretion of ACTH and steroids but normal stimulated cortisol production
Hormonal and clinical effects of GnRH agonist alone, or in combination with a combined oral contraceptive or flutamide in women with severe hirsutism
No full textThe objective of this prospective randomized study was to evaluate and compare the hormonal and clinical effects of long-acting gonadotropin-releasing hormone (GnRH) agonist and a combination of GnRH agonist with combined oral contraceptive (COC) or flutamide in women with polycystic ovary syndrome (PCOS). Thirty-five hirsute women with PCOS, ranging in age from 19-27 years, were randomly divided into three groups: group A treated with GnRH agonist (n = 12), group B (n = 12) treated with GnRH agonist plus COC and group C (n = 11) treated with GnRH agonist plus flutamide for 6 months. Before, at the end and 6 months after the end of treatment, blood samples were drawn from all women (in early follicular phase in those with menstrual cycles) to measure ovarian and adrenal androgens, gonadotropins luteinizing hormone (LH) and follicle-stimulating hormone (FSH), estradiol and estrone plasma levels. The results showed that all three protocols had good therapeutic efficacy. A significant reduction in hirsutism was observed in all patients after 6 months of therapy, the Ferriman-Gallwey scores dropping to 9 +/- 3 in group A, 10 +/- 4 in group B and 11 +/- 5 in group C. Six months after the end of therapy, the hirsutism score continued to be significantly reduced in all groups. After 6 months of therapy, a reduction in plasma levels of LH, FSH, estrone, estradiol, testosterone, free testosterone, androstenedione and dehydroepiandrosterone sulfate (DHEAS) was observed in all groups although this was more pronounced in group B and group C. These therapies may be the basis of future treatments that quickly reduce hirsutism and remove its causes by reducing the secretion of ovarian and adrenal androgens and by blocking androgen receptors
A randomized concave programming method for choice network revenue management
No full textModels incorporating more realistic models of customer behavior, as customers choosing from an offer set, have recently become popular in assortment optimization and revenue management. The dynamic program for these models is intractable and approximated by a deterministic linear program called the CDLP which has an exponential number of columns. However, when the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has been proposed but finding an entering column has been shown to be NP-hard. In this paper we propose a new approach called SDCP to solving CDLP based on segments and their consideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound on the dynamic program but coincides with CDLP for the case of non-overlapping segments. If the number of elements in a consideration set for a segment is not very large (SDCP) can be applied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by (i) simulations, called the randomized concave programming (RCP) method, and (ii) by adding cuts to a recent compact formulation of the problem for a latent multinomial-choice model of demand (SBLP+). This latter approach turns out to be very effective, essentially obtaining CDLP value, and excellent revenue performance in simulations, even for overlapping segments. By formulating the problem as a separation problem, we give insight into why CDLP is easy for the MNL with non-overlapping considerations sets and why generalizations of MNL pose difficulties. We perform numerical simulations to determine the revenue performance of all the methods on reference data sets in the literature.assortment optimization, randomized algorithms, network revenue management.
An enhanced concave program relaxation for choice network revenue management
No full textThe network choice revenue management problem models customers as choosing from an offer-set, and the firm decides the best subset to offer at any given moment to maximize expected revenue. The resulting dynamic program for the firm is intractable and approximated by a deterministic linear program called the CDLP which has an exponential number of columns. However, under the choice-set paradigm when the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has been proposed but finding an entering column has been shown to be NP-hard. In this paper, starting with a concave program formulation based on segment-level consideration sets called SDCP, we add a class of constraints called product constraints, that project onto subsets of intersections. In addition we propose a natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methods on the benchmark data sets in the literature. Both the product constraints and the ?SDCP method are very simple and easy to implement and are applicable to the case of overlapping segment consideration sets. In our computational testing on the benchmark data sets in the literature, SDCP with product constraints achieves the CDLP value at a fraction of the CPU time taken by column generation and we believe is a very promising approach for quickly approximating CDLP when segment consideration sets overlap and the consideration sets themselves are relatively small.discrete-choice models, network revenue management, optimization
A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters
No full textMany dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.Revenue management, estimation, multi-nomial logit, risk-ratio
- …
