Information, complexity and efficiency: The automobile model

The new, rapidly evolving field of industrial ecology - the objective, multidisciplinary study of industrial and economic systems and their linkages with fundamental natural systems - provides strong ground for believing that a more environmentally and economically efficient economy will be more information intensive and complex. Information and intellectual capital will be substituted for the more traditional inputs of materials and energy in producing a desirable, yet sustainable, quality of life. While at this point this remains a strong hypothesis, the evolution of the automobile industry can be used to illustrate how such substitution may, in fact, already be occurring in an environmentally and economically critical sector

Closed-Form Bayesian Inferences for the Logit Model via Polynomial Expansions

Articles in Marketing and choice literatures have demonstrated the need for incorporating person-level heterogeneity into behavioral models (e.g., logit models for multiple binary outcomes as studied here). However, the logit likelihood extended with a population distribution of heterogeneity doesn't yield closed-form inferences, and therefore numerical integration techniques are relied upon (e.g., MCMC methods). We present here an alternative, closed-form Bayesian inferences for the logit model, which we obtain by approximating the logit likelihood via a polynomial expansion, and then positing a distribution of heterogeneity from a flexible family that is now conjugate and integrable. For problems where the response coefficients are independent, choosing the Gamma distribution leads to rapidly convergent closed-form expansions; if there are correlations among the coefficients one can still obtain rapidly convergent closed-form expansions by positing a distribution of heterogeneity from a Multivariate Gamma distribution. The solution then comes from the moment generating function of the Multivariate Gamma distribution or in general from the multivariate heterogeneity distribution assumed. Closed-form Bayesian inferences, derivatives (useful for elasticity calculations), population distribution parameter estimates (useful for summarization) and starting values (useful for complicated algorithms) are hence directly available. Two simulation studies demonstrate the efficacy of our approach.Comment: 30 pages, 2 figures, corrected some typos. Appears in Quantitative Marketing and Economics vol 4 (2006), no. 2, 173--20

Undergraduate medical textbooks do not provide adequate information on intravenous fluid therapy: a systematic survey and suggestions for improvement

<b>Background</b><p></p> Inappropriate prescribing of intravenous (IV) fluid, particularly 0.9% sodium chloride, causes post-operative complications. Fluid prescription is often left to junior medical staff and is frequently poorly managed. One reason for poor intravenous fluid prescribing practices could be inadequate coverage of this topic in the textbooks that are used.<p></p> <b>Methods</b><p></p> We formulated a comprehensive set of topics, related to important common clinical situations involving IV fluid therapy, (routine fluid replacement, fluid loss, fluids overload) to assess the adequacy of textbooks in common use. We assessed 29 medical textbooks widely available to students in the UK, scoring the presence of information provided by each book on each of the topics. The scores indicated how fully the topics were considered: not at all, partly, and adequately. No attempt was made to judge the quality of the information, because there is no consensus on these topics.<p></p> <b>Results</b><p></p> The maximum score that a book could achieve was 52. Three of the topics we chose were not considered by any of the books. Discounting these topics as “too esoteric”, the maximum possible score became 46. One textbook gained a score of 45, but the general score was poor (median 11, quartiles 4, 21). In particular, coverage of routine postoperative management was inadequate.<p></p> <b>Conclusions</b><p></p> Textbooks for undergraduates cover the topic of intravenous therapy badly, which may partly explain the poor knowledge and performance of junior doctors in this important field. Systematic revision of current textbooks might improve knowledge and practice by junior doctors. Careful definition of the remit and content of textbooks should be applied more widely to ensure quality and “fitness for purpose”, and avoid omission of vital knowledge

A practitioner's guide to Bayesian estimation of discrete choice dynamic programming models

This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai et al., Econometrica 77:1865–1899, 2009a) (IJC). In the conventional nested fixed point algorithm, most of the information obtained in the past iterations remains unused in the current iteration. In contrast, the IJC algorithm extensively uses the computational results obtained from the past iterations to help solve the DDP model at the current iterated parameter values. Consequently, it has the potential to significantly alleviate the computational burden of estimating DDP models. To illustrate this new estimation method, we use a simple dynamic store choice model where stores offer “frequent-buyer” type rewards programs. Our Monte Carlo results demonstrate that the IJC method is able to recover the true parameter values of this model quite precisely. We also show that the IJC method could reduce the estimation time significantly when estimating DDP models with unobserved heterogeneity, especially when the discount factor is close to 1

Interdependent Infrastructure as Linked Social, Ecological, and Technological Systems (SETSs) to Address Lock‐in and Enhance Resilience

Traditional infrastructure adaptation to extreme weather events (and now climate change) has typically been techno‐centric and heavily grounded in robustness—the capacity to prevent or minimize disruptions via a risk‐based approach that emphasizes control, armoring, and strengthening (e.g., raising the height of levees). However, climate and nonclimate challenges facing infrastructure are not purely technological. Ecological and social systems also warrant consideration to manage issues of overconfidence, inflexibility, interdependence, and resource utilization—among others. As a result, techno‐centric adaptation strategies can result in unwanted tradeoffs, unintended consequences, and underaddressed vulnerabilities. Techno‐centric strategies that lock‐in today\u27s infrastructure systems to vulnerable future design, management, and regulatory practices may be particularly problematic by exacerbating these ecological and social issues rather than ameliorating them. Given these challenges, we develop a conceptual model and infrastructure adaptation case studies to argue the following: (1) infrastructure systems are not simply technological and should be understood as complex and interconnected social, ecological, and technological systems (SETSs); (2) infrastructure challenges, like lock‐in, stem from SETS interactions that are often overlooked and underappreciated; (3) framing infrastructure with a SETS lens can help identify and prevent maladaptive issues like lock‐in; and (4) a SETS lens can also highlight effective infrastructure adaptation strategies that may not traditionally be considered. Ultimately, we find that treating infrastructure as SETS shows promise for increasing the adaptive capacity of infrastructure systems by highlighting how lock‐in and vulnerabilities evolve and how multidisciplinary strategies can be deployed to address these challenges by broadening the options for adaptation

A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests

<p>Abstract</p> <p>Background</p> <p>Allergic contact dermatitis is an inflammatory skin disease that affects a significant proportion of the population. This disease is caused by an adverse immune response towards chemical haptens, and leads to a substantial economic burden for society. Current test of sensitizing chemicals rely on animal experimentation. New legislations on the registration and use of chemicals within pharmaceutical and cosmetic industries have stimulated significant research efforts to develop alternative, human cell-based assays for the prediction of sensitization. The aim is to replace animal experiments with in vitro tests displaying a higher predictive power.</p> <p>Results</p> <p>We have developed a novel cell-based assay for the prediction of sensitizing chemicals. By analyzing the transcriptome of the human cell line MUTZ-3 after 24 h stimulation, using 20 different sensitizing chemicals, 20 non-sensitizing chemicals and vehicle controls, we have identified a biomarker signature of 200 genes with potent discriminatory ability. Using a Support Vector Machine for supervised classification, the prediction performance of the assay revealed an area under the ROC curve of 0.98. In addition, categorizing the chemicals according to the LLNA assay, this gene signature could also predict sensitizing potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitization.</p> <p>Conclusions</p> <p>A gene signature predicting sensitization, using a human cell line in vitro, has been identified. This simple and robust cell-based assay has the potential to completely replace or drastically reduce the utilization of test systems based on experimental animals. Being based on human biology, the assay is proposed to be more accurate for predicting sensitization in humans, than the traditional animal-based tests.</p

Increasing the intracellular availability of all-trans retinoic acid in neuroblastoma cells

Recent data indicate that isomerisation to all-trans retinoic acid (ATRA) is the key mechanism underlying the favourable clinical properties of 13-cis retinoic acid (13cisRA) in the treatment of neuroblastoma. Retinoic acid (RA) metabolism is thought to contribute to resistance, and strategies to modulate this may increase the clinical efficacy of 13cisRA. The aim of this study was to test the hypothesis that retinoids, such as acitretin, which bind preferentially to cellular retinoic acid binding proteins (CRABPs), or specific inhibitors of the RA hydroxylase CYP26, such as R116010, can increase the intracellular availability of ATRA. Incubation of SH-SY5Y cells with acitretin (50 μM) or R116010 (1 or 10 μM) in combination with either 10 μM ATRA or 13cisRA induced a selective increase in intracellular levels of ATRA, while 13cisRA levels were unaffected. CRABP was induced in SH-SY5Y cells in response to RA. In contrast, acitretin had no significant effect on intracellular retinoid concentrations in those neuroblastoma cell lines that showed little or no induction of CRABP after RA treatment. Both ATRA and 13cisRA dramatically induced the expression of CYP26A1 in SH-SY5Y cells, and treatment with R116010, but not acitretin, potentiated the RA-induced expression of a reporter gene and CYP26A1. The response of neuroblastoma cells to R116010 was consistent with inhibition of CYP26, indicating that inhibition of RA metabolism may further optimise retinoid treatment in neuroblastoma