The case for new academic workspaces

Executive summary: This report draws upon the combined efforts of a number of estates professionals, architects, academics, designers, and senior managers involved in the planning of new university buildings for the 21st century. Across these perspectives, all would agree – although perhaps for different reasons - that this planning is difficult and that a number of particular considerations apply in the design of academic workspaces. Despite these difficulties, they will also agree that when this planning goes well, ‘good’ buildings are truly transformational – for both the university as a whole and the people who work and study in them. The value of well-designed buildings goes far beyond their material costs, and endures long after those costs have been forgotten ..

BacillOndex: An Integrated Data Resource for Systems and Synthetic Biology

BacillOndex is an extension of the Ondex data integration system, providing a semantically annotated, integrated knowledge base for the model Gram-positive bacterium Bacillus subtilis. This application allows a user to mine a variety of B. subtilis data sources, and analyse the resulting integrated dataset, which contains data about genes, gene products and their interactions. The data can be analysed either manually, by browsing using Ondex, or computationally via a Web services interface. We describe the process of creating a BacillOndex instance, and describe the use of the system for the analysis of single nucleotide polymorphisms in B. subtilis Marburg. The Marburg strain is the progenitor of the widely-used laboratory strain B. subtilis 168. We identified 27 SNPs with predictable phenotypic effects, including genetic traits for known phenotypes. We conclude that BacillOndex is a valuable tool for the systems-level investigation of, and hypothesis generation about, this important biotechnology workhorse. Such understanding contributes to our ability to construct synthetic genetic circuits in this organism

Antibacterial activity of fractions from three Chumash medicinal plant extracts and in vitro inhibition of the enzyme enoyl reductase by the flavonoid jaceosidin

We have investigated the in vitro antibacterial bioactivity of dichloromethane-soluble fractions of Artemisia californica, Trichostema lanatum, Salvia apiana, Sambucus nigra ssp. cerulea and Quercus agrifolia Née against a ΔtolC mutant strain of E. coli. These plants are traditional medicinal plants of the Chumash Native Americans of Southern California. Bioassay-guided fractionation led to the isolation of three flavonoid compounds from A. californica: jaceosidin (1), jaceidin (2), and chrysoplenol B (3). Compounds 1 and 2 exhibited anti-bacterial activity against E. coli ΔtolC in liquid cultures. The in vitro activity of 1 against the enoyl reductase enzyme (FabI) was measured using a spectrophotometric assay and found to completely inhibit FabI activity at a concentration of 100 μM. However, comparison of MIC values for 1-3 against E. coli ΔtolC and an equivalent strain containing a plasmid constitutively expressing fabI did not reveal any selectivity for FabI in vivo

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

The Effects of COVID-19 on the Placenta During Pregnancy.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic. The virus primarily affects the lungs where it induces respiratory distress syndrome ranging from mild to acute, however, there is a growing body of evidence supporting its negative effects on other system organs that also carry the ACE2 receptor, such as the placenta. The majority of newborns delivered from SARS-CoV-2 positive mothers test negative following delivery, suggesting that there are protective mechanisms within the placenta. There appears to be a higher incidence of pregnancy-related complications in SARS-CoV-2 positive mothers, such as miscarriage, restricted fetal growth, or still-birth. In this review, we discuss the pathobiology of COVID-19 maternal infection and the potential adverse effects associated with viral infection, and the possibility of transplacental transmission

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

Choice Models in Marketing: Economic Assumptions, Challenges and Trends

Direct utility models of consumer choice are reviewed and developed for understanding consumer preferences. We begin with a review of statistical models of choice, posing a series of modeling challenges that are resolved by considering economic foundations based on con-strained utility maximization. Direct utility models differ from other choice models by directly modeling the consumer utility function used to derive the likelihood of the data through Kuhn-Tucker con-ditions. Recent advances in Bayesian estimation make the estimation of these models computationally feasible, offering advantages in model interpretation over models based on indirect utility, and descriptive models that tend to be highly parameterized. Future trends are dis-cussed in terms of the antecedents and enhancements of utility function specification.

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