The Automatic Synthesis of Fault Tolerant and Fault Secure VLSI Systems

This thesis investigates the design of fault tolerant and fault secure (FTFS) systems within the framework of silicon compilation. Automatic design modification is used to introduce FTFS characteristics into a design. A taxonomy of FTFS techniques is introduced and is used to identify a number of features which an "automatic design for FTFS" system should exhibit. A silicon compilation system, Chip Churn 2 (CC2), has been implemented and has been used to demonstrate the feasibility of automatic design of FTFS systems. The CC2 system provides a design language, simulation facilities and a back-end able to produce CMOS VLSI designs. A number of FTFS design methods have been implemented within the CC2 environment; these methods range from triple modular redundancy to concurrent parity code checking. The FTFS design methods can be applied automatically to general designs in order to realise them as FTFS systems. A number of example designs are presented; these are used to illustrate the FTFS modification techniques which have been implemented. Area results for CMOS devices are presented; this allows the modification methods to be compared. A number of problems arising from the methods are highlighted and some solutions suggested

New potent inhibitors of angiotensin converting enzyme

AbstractUsing an earlier model of the favoured orientation of binding functions of angiotensin converting enzyme (ACE) inhibitors, it has been possible to postulate a new, 7,6-bicyclic system, based on hexahydropyridazine, which might be expected to have high potency. Some members of this system which have been synthesised have been shown to be very active ACE inhibitors, in vitro and in vivo

Economics methods in Cochrane systematic reviews of health promotion and public health related interventions.

Peer reviewedPublisher PD

A tetraoxane-based antimalarial drug candidate that overcomes PfK13-C580Y dependent artemisinin resistance.

K13 gene mutations are a primary marker of artemisinin resistance in Plasmodium falciparum malaria that threatens the long-term clinical utility of artemisinin-based combination therapies, the cornerstone of modern day malaria treatment. Here we describe a multinational drug discovery programme that has delivered a synthetic tetraoxane-based molecule, E209, which meets key requirements of the Medicines for Malaria Venture drug candidate profiles. E209 has potent nanomolar inhibitory activity against multiple strains of P. falciparum and P. vivax in vitro, is efficacious against P. falciparum in in vivo rodent models, produces parasite reduction ratios equivalent to dihydroartemisinin and has pharmacokinetic and pharmacodynamic characteristics compatible with a single-dose cure. In vitro studies with transgenic parasites expressing variant forms of K13 show no cross-resistance with the C580Y mutation, the primary variant observed in Southeast Asia. E209 is a superior next generation endoperoxide with combined pharmacokinetic and pharmacodynamic features that overcome the liabilities of artemisinin derivatives

A broadband thermal emission spectrum of the ultra-hot Jupiter WASP-18b

Close-in giant exoplanets with temperatures greater than 2,000 K (''ultra-hot Jupiters'') have been the subject of extensive efforts to determine their atmospheric properties using thermal emission measurements from the Hubble and Spitzer Space Telescopes. However, previous studies have yielded inconsistent results because the small sizes of the spectral features and the limited information content of the data resulted in high sensitivity to the varying assumptions made in the treatment of instrument systematics and the atmospheric retrieval analysis. Here we present a dayside thermal emission spectrum of the ultra-hot Jupiter WASP-18b obtained with the NIRISS instrument on JWST. The data span 0.85 to 2.85 $\mu$m in wavelength at an average resolving power of 400 and exhibit minimal systematics. The spectrum shows three water emission features (at $>$6$\sigma$ confidence) and evidence for optical opacity, possibly due to H$^-$, TiO, and VO (combined significance of 3.8$\sigma$). Models that fit the data require a thermal inversion, molecular dissociation as predicted by chemical equilibrium, a solar heavy element abundance (''metallicity'', M/H = 1.03$_{-0.51}^{+1.11}$ $\times$ solar), and a carbon-to-oxygen (C/O) ratio less than unity. The data also yield a dayside brightness temperature map, which shows a peak in temperature near the sub-stellar point that decreases steeply and symmetrically with longitude toward the terminators.Comment: JWST ERS bright star observations. Uploaded to inform JWST Cycle 2 proposals. Manuscript under review. 50 pages, 14 figures, 2 table

Early Release Science of the exoplanet WASP-39b with JWST NIRISS

Transmission spectroscopy provides insight into the atmospheric properties and consequently the formation history, physics, and chemistry of transiting exoplanets. However, obtaining precise inferences of atmospheric properties from transmission spectra requires simultaneously measuring the strength and shape of multiple spectral absorption features from a wide range of chemical species. This has been challenging given the precision and wavelength coverage of previous observatories. Here, we present the transmission spectrum of the Saturn-mass exoplanet WASP-39b obtained using the SOSS mode of the NIRISS instrument on the JWST. This spectrum spans $0.6 - 2.8 \mu$m in wavelength and reveals multiple water absorption bands, the potassium resonance doublet, as well as signatures of clouds. The precision and broad wavelength coverage of NIRISS-SOSS allows us to break model degeneracies between cloud properties and the atmospheric composition of WASP-39b, favoring a heavy element enhancement ("metallicity") of $\sim 10 - 30 \times$ the solar value, a sub-solar carbon-to-oxygen (C/O) ratio, and a solar-to-super-solar potassium-to-oxygen (K/O) ratio. The observations are best explained by wavelength-dependent, non-gray clouds with inhomogeneous coverage of the planet's terminator.Comment: 48 pages, 12 figures, 2 tables. Under review at Natur

Phylogeny and Biogeography of Hawkmoths (Lepidoptera: Sphingidae): Evidence from Five Nuclear Genes

The 1400 species of hawkmoths (Lepidoptera: Sphingidae) comprise one of most conspicuous and well-studied groups of insects, and provide model systems for diverse biological disciplines. However, a robust phylogenetic framework for the family is currently lacking. Morphology is unable to confidently determine relationships among most groups. As a major step toward understanding relationships of this model group, we have undertaken the first large-scale molecular phylogenetic analysis of hawkmoths representing all subfamilies, tribes and subtribes.The data set consisted of 131 sphingid species and 6793 bp of sequence from five protein-coding nuclear genes. Maximum likelihood and parsimony analyses provided strong support for more than two-thirds of all nodes, including strong signal for or against nearly all of the fifteen current subfamily, tribal and sub-tribal groupings. Monophyly was strongly supported for some of these, including Macroglossinae, Sphinginae, Acherontiini, Ambulycini, Philampelini, Choerocampina, and Hemarina. Other groupings proved para- or polyphyletic, and will need significant redefinition; these include Smerinthinae, Smerinthini, Sphingini, Sphingulini, Dilophonotini, Dilophonotina, Macroglossini, and Macroglossina. The basal divergence, strongly supported, is between Macroglossinae and Smerinthinae+Sphinginae. All genes contribute significantly to the signal from the combined data set, and there is little conflict between genes. Ancestral state reconstruction reveals multiple separate origins of New World and Old World radiations.Our study provides the first comprehensive phylogeny of one of the most conspicuous and well-studied insects. The molecular phylogeny challenges current concepts of Sphingidae based on morphology, and provides a foundation for a new classification. While there are multiple independent origins of New World and Old World radiations, we conclude that broad-scale geographic distribution in hawkmoths is more phylogenetically conserved than previously postulated

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages