Bayesian optimization for materials design

We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian process regression, which allows predicting the performance of a new design based on previously tested designs. After providing a detailed introduction to Gaussian process regression, we introduce two Bayesian optimization methods: expected improvement, for design problems with noise-free evaluations; and the knowledge-gradient method, which generalizes expected improvement and may be used in design problems with noisy evaluations. Both methods are derived using a value-of-information analysis, and enjoy one-step Bayes-optimality

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

The Cosmology of Composite Inelastic Dark Matter

Composite dark matter is a natural setting for implementing inelastic dark matter - the O(100 keV) mass splitting arises from spin-spin interactions of constituent fermions. In models where the constituents are charged under an axial U(1) gauge symmetry that also couples to the Standard Model quarks, dark matter scatters inelastically off Standard Model nuclei and can explain the DAMA/LIBRA annual modulation signal. This article describes the early Universe cosmology of a minimal implementation of a composite inelastic dark matter model where the dark matter is a meson composed of a light and a heavy quark. The synthesis of the constituent quarks into dark mesons and baryons results in several qualitatively different configurations of the resulting dark matter hadrons depending on the relative mass scales in the system.Comment: 31 pages, 4 figures; references added, typos correcte

Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome

BACKGROUND: There has been little research on design of studies based on routinely collected data when the clinical endpoint of interest is not recorded, but can be inferred from a prescription. This often happens when exploring the effect of a drug on chronic diseases. Using the LifeLink claims database in studying the possible anti-inflammatory effects of statins in rheumatoid arthritis (RA), oral steroids (OS) were treated as surrogate of inflammatory flare-ups. We compared two cohort study designs, the first using time to event outcomes and the second using quantitative amount of the surrogate. METHODS: RA patients were extracted from the LifeLink database. In the first study, patients were split into two sub-cohorts based on whether they were using OS within a specified time window of the RA index date (first record of RA). Using Cox models we evaluated the association between time-varying exposure to statins and (i) initiation of OS therapy in the non-users of OS at RA index date and (ii) cessation of OS therapy in the users of OS at RA index date. In the second study, we matched new statin users to non users on age and sex. Zero inflated negative binomial models were used to contrast the number of days' prescriptions of OS in the year following date of statin initiation for the two exposure groups. RESULTS: In the unmatched study, the statin exposure hazard ratio (HR) of initiating OS in the 31451 non-users of OS at RA index date was 0.96(95% CI 0.9,1.1) and the statin exposure HR of cessation of OS therapy in the 6026 users of OS therapy at RA index date was 0.95 (0.87,1.05). In the matched cohort of 6288 RA patients the statin exposure rate ratio for duration on OS therapy was 0.88(0.76,1.02). There was digit preference for outcomes in multiples of 7 and 30 days. CONCLUSIONS: The 'time to event' study design was preferable because it better exploits information on all available patients and provides a degree of robustness toward confounding. We found no convincing evidence that statins reduce inflammation in RA patients

The Occurrence of Photorhabdus-Like Toxin Complexes in Bacillus thuringiensis

Recently, genomic sequencing of a Bacillus thuringiensis (Bt) isolate from our collection revealed the presence of an apparent operon encoding an insecticidal toxin complex (Tca) similar to that first described from the entomopathogen Photorhabdus luminescens. To determine whether these genes are widespread among Bt strains, we screened isolates from the collection for the presence of tccC, one of the genes needed for the expression of fully functional toxin complexes. Among 81 isolates chosen to represent commonly encountered biochemical phenotypes, 17 were found to possess a tccC. Phylogenetic analysis of the 81 isolates by multilocus sequence typing revealed that all the isolates possessing a tccC gene were restricted to two sequence types related to Bt varieties morrisoni, tenebrionis, israelensis and toumanoffi. Sequencing of the ∼17 kb tca operon from two isolates representing each of the two sequence types revealed >99% sequence identity. Optical mapping of DNA from Bt isolates representing each of the sequence types revealed nearly identical plasmids of ca. 333 and 338 kbp, respectively. Selected isolates were found to be toxic to gypsy moth larvae, but were not as effective as a commercial strain of Bt kurstaki. Some isolates were found to inhibit growth of Colorado potato beetle. Custom Taqman® relative quantitative real-time PCR assays for Tc-encoding Bt revealed both tcaA and tcaB genes were expressed within infected gypsy moth larvae

Vascular relaxation of canine visceral arteries after ischemia by means of supraceliac aortic cross-clamping followed by reperfusion

<p>Abstract</p> <p>Background</p> <p>The supraceliac aortic cross-clamping can be an option to save patients with hipovolemic shock due to abdominal trauma. However, this maneuver is associated with ischemia/reperfusion (I/R) injury strongly related to oxidative stress and reduction of nitric oxide bioavailability. Moreover, several studies demonstrated impairment in relaxation after I/R, but the time course of I/R necessary to induce vascular dysfunction is still controversial. We investigated whether 60 minutes of ischemia followed by 30 minutes of reperfusion do not change the relaxation of visceral arteries nor the plasma and renal levels of malondialdehyde (MDA) and nitrite plus nitrate (NOx).</p> <p>Methods</p> <p>Male mongrel dogs (n = 27) were randomly allocated in one of the three groups: sham (no clamping, n = 9), ischemia (supraceliac aortic cross-clamping for 60 minutes, n = 9), and I/R (60 minutes of ischemia followed by reperfusion for 30 minutes, n = 9). Relaxation of visceral arteries (celiac trunk, renal and superior mesenteric arteries) was studied in organ chambers. MDA and NOx concentrations were determined using a commercially available kit and an ozone-based chemiluminescence assay, respectively.</p> <p>Results</p> <p>Both acetylcholine and calcium ionophore caused relaxation in endothelium-intact rings and no statistical differences were observed among the three groups. Sodium nitroprusside promoted relaxation in endothelium-denuded rings, and there were no inter-group statistical differences. Both plasma and renal concentrations of MDA and NOx showed no significant difference among the groups.</p> <p>Conclusion</p> <p>Supraceliac aortic cross-clamping for 60 minutes alone and followed by 30 minutes of reperfusion did not impair relaxation of canine visceral arteries nor evoke biochemical alterations in plasma or renal tissue.</p

Impact of High Mathematics Education on the Number Sense

In adult number processing two mechanisms are commonly used: approximate estimation of quantity and exact calculation. While the former relies on the approximate number sense (ANS) which we share with animals and preverbal infants, the latter has been proposed to rely on an exact number system (ENS) which develops later in life following the acquisition of symbolic number knowledge. The current study investigated the influence of high level math education on the ANS and the ENS. Our results showed that the precision of non-symbolic quantity representation was not significantly altered by high level math education. However, performance in a symbolic number comparison task as well as the ability to map accurately between symbolic and non-symbolic quantities was significantly better the higher mathematics achievement. Our findings suggest that high level math education in adults shows little influence on their ANS, but it seems to be associated with a better anchored ENS and better mapping abilities between ENS and ANS

Prognostic factors for patients with hepatic metastases from breast cancer

Median survival from liver metastases secondary to breast cancer is only a few months, with very rare 5-year survival. This study reviewed 145 patients with liver metastases from breast cancer to determine factors that may influence survival. Data were analysed using Kaplan–Meier survival curves, univariate and multivariate analysis. Median survival was 4.23 months (range 0.16–51), with a 27.6% 1-year survival. Factors that significantly predicted a poor prognosis on univariate analysis included symptomatic liver disease, deranged liver function tests, the presence of ascites, histological grade 3 disease at primary presentation, advanced age, oestrogen receptor (ER) negative tumours, carcinoembryonic antigen of over 1000 ng ml−1 and multiple vs single liver metastases. Response to treatment was also a significant predictor of survival with patients responding to chemo- or endocrine therapy surviving for a median of 13 and 13.9 months, respectively. Multivariate analysis of pretreatment variables identified a low albumin, advanced age and ER negativity as independent predictors of poor survival. The time interval between primary and metastatic disease, metastases at extrahepatic sites, histological subtype and nodal stage at primary presentation did not predict prognosis. Awareness of the prognostic implications of the above factors may assist in selecting the most appropriate treatment for these patients

Statistical inference and the replication crisis

The replication crisis has prompted many to call for statistical reform within the psychological sciences. Here we examine issues within Frequentist statistics that may have led to the replication crisis, and we examine the alternative—Bayesian statistics—that many have suggested as a replacement. The Frequentist approach and the Bayesian approach offer radically different perspectives on evidence and inference with the Frequentist approach prioritising error control and the Bayesian approach offering a formal method for quantifying the relative strength of evidence for hypotheses. We suggest that rather than mere statistical reform, what is needed is a better understanding of the different modes of statistical inference and a better understanding of how statistical inference relates to scientific inference

From the animal house to the field : are there consistent individual differences in immunological profile in wild populations of field voles (Microtus agrestis)?

Inbred mouse strains, living in simple laboratory environments far removed from nature, have been shown to vary consistently in their immune response. However, wildlife populations are typically outbreeding and face a multiplicity of challenges, parasitological and otherwise. In this study we seek evidence of consistent difference in immunological profile amongst individuals in the wild. We apply a novel method in this context, using longitudinal (repeated capture) data from natural populations of field voles, Microtus agrestis, on a range of life history and infection metrics, and on gene expression levels. We focus on three immune genes, IFN-γ, Gata3, and IL-10, representing respectively the Th1, Th2 and regulatory elements of the immune response. Our results show that there was clear evidence of consistent differences between individuals in their typical level of expression of at least one immune gene, and at most all three immune genes, after other measured sources of variation had been taken into account. Furthermore, individuals that responded to changing circumstances by increasing expression levels of Gata3 had a correlated increase in expression levels of IFN-γ. Our work stresses the importance of acknowledging immunological variation amongst individuals in studies of parasitological and infectious disease risk in wildlife populations