Scalable Inference for Markov Processes with Intractable Likelihoods

Bayesian inference for Markov processes has become increasingly relevant in recent years. Problems of this type often have intractable likelihoods and prior knowledge about model rate parameters is often poor. Markov Chain Monte Carlo (MCMC) techniques can lead to exact inference in such models but in practice can suffer performance issues including long burn-in periods and poor mixing. On the other hand approximate Bayesian computation techniques can allow rapid exploration of a large parameter space but yield only approximate posterior distributions. Here we consider the combined use of approximate Bayesian computation (ABC) and MCMC techniques for improved computational efficiency while retaining exact inference on parallel hardware

Electro-optic bunch diagnostics on ALICE

An electro-optic longitudinal bunch profile monitor has been implemented on ALICE (Accelerators and Lasers in Combined Experiments) at the Daresbury Laboratories and will be used both to characterise the electron bunch and to provide a testbed for electro-optic techniques. The electro-optic station is located immediately after the bunch compressor, within the FEL cavity; its location allows nearby OTR, beam profile monitors and Coherent Synchrontron Radiation (CSR) diagnostics to be used for calibration and benchmarking. We discuss the implementation and the planned studies on electro-optic diagnostics using this diagnostic station

The Agriculture-Nutrition Disconnect in India: What Do We Know?

India is home to one-third of the world’s malnourished children. This figure that remains stubbornly high, despite the country having the second-fastest growing economy in the world, with agriculture accounting for a significant part of that growth. Agriculture continues to be the primary source of livelihood for the majority of nutritionally vulnerable households in India. In order to maximize the nutrition-sensitivity of agriculture, we need to first map existing evidence of the various links, pathways and disconnects between agriculture and nutrition. We start with a narrative review of the background literature for India, including an assessment of trends in nutrition and agriculture indicators. A conceptual framework is then put forward to aid in the systematic search for links and disconnects, delineating seven key pathways between agriculture and nutrition. Evidence is then mapped to these pathways through a summary of the literature for each pathway as well as a fully annotated bibliography. A data audit assesses gaps and overlaps in survey data containing information on agriculture and nutrition indicators, on which future analyses could be built. Overall, the authors find that the conceptual framework is useful in this process, and conclude that there are some significant gaps in the literature and in the data currently available to analyze linkages between agriculture and nutrition. Data and policy disconnects need to be bridged to enhance the nutrition sensitivity of agriculture in India

Upconversion of a relativistic Coulomb field terahertz pulse to the near infrared

We demonstrate the spectral upconversion of a unipolar subpicosecond terahertz (THz) pulse, where the THz pulse is the Coulomb field of a single relativistic electron bunch. The upconversion to the optical allows remotely located detection of long wavelength and nonpropagating components of the THz spectrum, as required for ultrafast electron bunch diagnostics. The upconversion of quasimonochromatic THz radiation has also been demonstrated, allowing the observation of distinct sum- and difference-frequency mixing components in the spectrum. Polarization dependence of first and second order sidebands at ωopt±ωTHz, and ωopt±2ωTHz, respectively, confirms the χ(2) frequency mixing mechanism

Stronger computational modelling of signalling pathways using both continuous and discrete-state methods

Starting from a biochemical signalling pathway model expresses in a process algebra enriched with quantitative information, we automatically derive both continuous-space and discrete-space representations suitable for numerical evaluation. We compare results obtained using approximate stochastic simulation thereby exposing a flaw in the use of the differentiation procedure producing misleading results

Evaluating the effects of turf-replacement programs in Los Angeles

Water utilities incentivize turf replacement to promote water conservation, but the effects of such programs have received limited evaluations. In 2014, the Metropolitan Water District of Southern California (MWD) undertook an unprecedented investment to incentive turf replacement throughout Southern California in response to a serious Statewide drought. MWD devoted $350 million to the program, resulting in more than 46,000 rebate payments (25,000 in Los Angeles County) to remove 15.3 million square meters of turf. The program implementation provided a unique opportunity to address research gaps on turf replacement implementation. We analyzed socioeconomic and spatial trends of program participants and assessed landscape changes from turf replacement using a random sample of properties (4% of LA County participants in 2014–16). Specifically, we used a novel and cost-effective approach Google Earth Street View to characterize landscapes in front yards and created a typology of land cover types. Results showed: post-replacement landscapes had a diversity of land cover types – diverse yards with several land cover types, as well as more homogenous yards with a single land cover such as woodchips, bare soil, gravel, and artificial turf. Analysis also indicated some evidence of “neighborhood adoption” effects. We describe the need for longitudinal studies to understand long-term effects of turf replacement and associated water use, and suggest that water utilities should also evaluate results in backyards, which requires site visits. This study provides a novel contribution that can be replicated over space and time to further knowledge of turf replacement program implementations and evaluation

A Twin Study of Early-Childhood Asthma in Puerto Ricans

Background:The relative contributions of genetics and environment to asthma in Hispanics or to asthma in children younger than 3 years are not well understood.Objective:To examine the relative contributions of genetics and environment to early-childhood asthma by performing a longitudinal twin study of asthma in Puerto Rican children ≤3 years old.Methods:678 twin infants from the Puerto Rico Neo-Natal Twin Registry were assessed for asthma at age 1 year, with follow-up data obtained for 624 twins at age 3 years. Zygosity was determined by DNA microsatellite profiling. Structural equation modeling was performed for three phenotypes at ages 1 and 3 years: physician-diagnosed asthma, asthma medication use in the past year, and ≥1 hospitalization for asthma in the past year. Models were additionally adjusted for early-life environmental tobacco smoke exposure, sex, and age.Results:The prevalences of physician-diagnosed asthma, asthma medication use, and hospitalization for asthma were 11.6%, 10.8%, 4.9% at age 1 year, and 34.1%, 40.1%, and 8.5% at 3 years, respectively. Shared environmental effects contributed to the majority of variance in susceptibility to physician-diagnosed asthma and asthma medication use in the first year of life (84%-86%), while genetic effects drove variance in all phenotypes (45%-65%) at age 3 years. Early-life environmental tobacco smoke, sex, and age contributed to variance in susceptibility.Conclusion:Our longitudinal study in Puerto Rican twins demonstrates a changing contribution of shared environmental effects to liability for physician-diagnosed asthma and asthma medication use between ages 1 and 3 years. Early-life environmental tobacco smoke reduction could markedly reduce asthma morbidity in young Puerto Rican children. © 2013 Bunyavanich et al