Simulating Reionization: Character and Observability

In recent years there has been considerable progress in our understanding of the nature and properties of the reionization process. In particular, the numerical simulations of this epoch have made a qualitative leap forward, reaching sufficiently large scales to derive the characteristic scales of the reionization process and thus allowing for realistic observational predictions. Our group has recently performed the first such large-scale radiative transfer simulations of reionization, run on top of state-of-the-art simulations of early structure formation. This allowed us to make the first realistic observational predictions about the Epoch of Reionization based on detailed radiative transfer and structure formation simulations. We discuss the basic features of reionization derived from our simulations and some recent results on the observational implications for the high-redshift Ly-alpha sources.Comment: 3 pages, to appear in the Proceedings of First Stars III, Santa Fe, July 2007, AIP Conference Serie

Data consistency in the English Hospital Episodes Statistics database

BACKGROUND: To gain maximum insight from large administrative healthcare datasets it is important to understand their data quality. Although a gold standard against which to assess criterion validity rarely exists for such datasets, internal consistency can be evaluated. We aimed to identify inconsistencies in the recording of mandatory International Statistical Classification of Diseases and Related Health Problems, tenth revision (ICD-10) codes within the Hospital Episodes Statistics dataset in England. METHODS: Three exemplar medical conditions where recording is mandatory once diagnosed were chosen: autism, type II diabetes mellitus and Parkinson's disease dementia. We identified the first occurrence of the condition ICD-10 code for a patient during the period April 2013 to March 2021 and in subsequent hospital spells. We designed and trained random forest classifiers to identify variables strongly associated with recording inconsistencies. RESULTS: For autism, diabetes and Parkinson's disease dementia respectively, 43.7%, 8.6% and 31.2% of subsequent spells had inconsistencies. Coding inconsistencies were highly correlated with non-coding of an underlying condition, a change in hospital trust and greater time between the spell with the first coded diagnosis and the subsequent spell. For patients with diabetes or Parkinson's disease dementia, the code recording for spells without an overnight stay were found to have a higher rate of inconsistencies. CONCLUSIONS: Data inconsistencies are relatively common for the three conditions considered. Where these mandatory diagnoses are not recorded in administrative datasets, and where clinical decisions are made based on such data, there is potential for this to impact patient care

World scientists’ warnings into action, local to global

‘We have kicked the can down the road once again – but we are running out of road.’ – Rachel Kyte, Dean of Fletcher School at Tufts University. We, in our capacities as scientists, economists, governance and policy specialists, are shifting from warnings to guidance for action before there is no more ‘road.’ The science is clear and irrefutable; humanity is in advanced ecological overshoot. Our overexploitation of resources exceeds ecosystems’ capacity to provide them or to absorb our waste. Society has failed to meet clearly stated goals of the UN Framework Convention on Climate Change. Civilization faces an epochal crossroads, but with potentially much better, wiser outcomes if we act now. What are the concrete and transformative actions by which we can turn away from the abyss? In this paper we forcefully recommend priority actions and resource allocation to avert the worst of the climate and nature emergencies, two of the most pressing symptoms of overshoot, and lead society into a future of greater wellbeing and wisdom. Humanity has begun the social, economic, political and technological initiatives needed for this transformation. Now, massive upscaling and acceleration of these actions and collaborations are essential before irreversible tipping points are crossed in the coming decade. We still can overcome significant societal, political and economic barriers of our own making. Previously, we identified six core areas for urgent global action – energy, pollutants, nature, food systems, population stabilization and economic goals. Here we identify an indicative, systemic and time-limited framework for priority actions for policy, planning and management at multiple scales from household to global. We broadly follow the ‘Reduce-Remove-Repair’ approach to rapid action. To guide decision makers, planners, managers, and budgeters, we cite some of the many experiments, mechanisms and resources in order to facilitate rapid global adoption of effective solutions. Our biggest challenges are not technical, but social, economic, political and behavioral. To have hope of success, we must accelerate collaborative actions across scales, in different cultures and governance systems, while maintaining adequate social, economic and political stability. Effective and timely actions are still achievable on many, though not all fronts. Such change will mean the difference for billions of children and adults, hundreds of thousands of species, health of many ecosystems, and will determine our common future

Superimposition of 3D cone-beam CT models of orthognathic surgery patients

To evaluate the registration of 3D models from cone-beam CT (CBCT) images taken before and after orthognathic surgery for the assessment of mandibular anatomy and position

Search algorithms as a framework for the optimization of drug combinations

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.Comment: 36 pages, 10 figures, revised versio

Efficient importance sampling in low dimensions using affine arithmetic

Despite the development of sophisticated techniques such as sequential Monte Carlo, importance sampling (IS) remains an important Monte Carlo method for low dimensional target distributions. This paper describes a new technique for constructing proposal distributions for IS, using affine arithmetic. This work builds on the Moore rejection sampler to which we provide a comparison

Heterogeneity and the dynamics of technology adoption

We estimate the demand for a videocalling technology in the presence of both network effects and heterogeneity. Using a unique dataset from a large multinational firm, we pose and estimate a fully dynamic model of technology adoption. We propose a novel identification strategy based on post-adoption technology usage to disentangle equilibrium beliefs concerning the evolution of the network from observed and unobserved heterogeneity in technology adoption costs and use benefits. We find that employees have significant heterogeneity in both adoption costs and network benefits, and have preferences for diverse networks. Using our estimates, we evaluate a number of counterfactual adoption policies, and find that a policy of strategically targeting the right subtype for initial adoption can lead to a faster-growing and larger network than a policy of uncoordinated or diffuse adoption

Nonthermal Emission from Star-Forming Galaxies

The detections of high-energy gamma-ray emission from the nearby starburst galaxies M82 & NGC253, and other local group galaxies, broaden our knowledge of star-driven nonthermal processes and phenomena in non-AGN star-forming galaxies. We review basic aspects of the related processes and their modeling in starburst galaxies. Since these processes involve both energetic electrons and protons accelerated by SN shocks, their respective radiative yields can be used to explore the SN-particle-radiation connection. Specifically, the relation between SN activity, energetic particles, and their radiative yields, is assessed through respective measures of the particle energy density in several star-forming galaxies. The deduced energy densities range from O(0.1) eV/cm^3 in very quiet environments to O(100) eV/cm^3 in regions with very high star-formation rates.Comment: 17 pages, 5 figures, to be published in Astrophysics and Space Science Proceeding

Testing the isotropy of the dark energy Survey's extreme trans-neptunian objects

We test whether the population of "extreme"trans-Neptunian objects (eTNOs) detected in the first four years of the Dark Energy Survey (DES Y4) data exhibit azimuthal asymmetries that might be evidence of gravitational perturbations from an unseen super-Earth in a distant orbit. By rotating the orbits of the detected eTNOs, we construct a synthetic population that, when subject to the DES selection function, reproduces the detected distribution of eTNOs in the orbital elements a, e, and i as well as absolute magnitude H, but has uniform distributions in mean anomaly M, longitude of ascending node Ω, and argument of perihelion ω. We then compare the detected distributions in each of Ω, ω, and the longitude of perihelion {equation presented} to those expected from the isotropic population, using Kuiper's variant of the Kolmogorov-Smirnov test. The three angles are tested for each of four definitions of the eTNO population, choosing among a > (150, 250) au and perihelion q > (30, 37) au. These choices yield 3-7 eTNOs in the DES Y4 sample. Among the 12 total tests, two have the likelihood of drawing the observed angles from the isotropic population at p 250 and q > 37 au and the four detections at a > 250 and q > 30 au have a Ω distribution with p ≈ 0.03 coming from the isotropic construction, but this is not strong evidence of anisotropy given the 12 different tests. The DES data taken on their own are thus consistent with azimuthal isotropy and do not require a "Planet 9"hypothesis. The limited sky coverage and object count mean, however, that the DES data by no means falsify this hypothesis