The eclipse of the goal of zero inflation

William J. Barber's study of Alvin H. Hansen (1887-1975) emphasized the importance of the intellectual transformation that led to the "'Keynes-Hansen intellectual system that appeared to have compelling diagnostic and prescriptive power" (Barber 19X7. 205).1 Between 1936 and 1938, Hansen became a convert to Keynesian economics, and this led to the Hicks-Hansen IS-LM model. Subsequent authors (including Phillips in the 1950s) concluded that this approach, being an equilibrium model, did not capture the disequilibrium "essence" of Keynes (Lipsey 19X I, 547). The purpose of this article is to highlight a second intellectual transformation in Hansen's policy advocacy, and to suggest the possibility that, once again, Hansen contributed to a Keynesian economics that was in conflict with Keynes's stated position. I will also discuss a parallel transformation in the policy advocacy of Sumner H. Slichter ( 1892-1959), who was, like Hansen, a Harvard University professor

Cluster-based ensemble means for climate model intercomparison

Clustering – the automated grouping of similar data – can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model–observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry–climate model (CCM) output of tropospheric ozone – an important greenhouse gas – from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to  ∼  20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at  ∼  62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere – where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and useful framework in which to assess and visualise model spread, offering insight into geographical areas of agreement among models and a measure of diversity across an ensemble. Finally, we discuss caveats of the clustering techniques and note that while we have focused on tropospheric ozone, the principles underlying the cluster-based MMMs are applicable to other prognostic variables from climate models

Nonequilibrium spectral diffusion due to laser heating in stimulated photon echo spectroscopy of low temperature glasses

A quantitative theory is developed, which accounts for heating artifacts in three-pulse photon echo (3PE) experiments. The heat diffusion equation is solved and the average value of the temperature in the focal volume of the laser is determined as a function of the 3PE waiting time. This temperature is used in the framework of nonequilibrium spectral diffusion theory to calculate the effective homogeneous linewidth of an ensemble of probe molecules embedded in an amorphous host. The theory fits recently observed plateaus and bumps without introducing a gap in the distribution function of flip rates of the two-level systems or any other major modification of the standard tunneling model.Comment: 10 pages, Revtex, 6 eps-figures, accepted for publication in Phys. Rev.

Nitrous oxide emissions from a peatbog after 13 years of experimental nitrogen deposition

Nitrogen deposition was experimentally increased on a Scottish peatbog over a period of 13 years (2002–2015). Nitrogen was applied in three forms, NH3 gas, NH4Cl solution, and NaNO3 solution, at rates ranging from 8 (ambient) to 64 kg N ha−1 yr−1, and higher near the NH3 fumigation source. An automated system was used to apply the nitrogen, such that the deposition was realistic in terms of rates and high frequency of deposition events. We measured the response of nitrous oxide (N2O) flux to the increased nitrogen input. Prior expectations, based on the IPCC default emission factor, were that 1 % of the added nitrogen would be emitted as N2O. In the plots treated with NH4+ and NO3− solution, no response was seen, and there was a tendency for N2O fluxes to be reduced by additional nitrogen, though this was not significant. Areas subjected to high NH3 emitted more N2O than expected, up to 8.5 % of the added nitrogen. Differences in the response are related to the impact of the nitrogen treatments on the vegetation. In the NH4+ and NO3− treatments, all the additional nitrogen is effectively immobilised in the vegetation and top 10 cm of peat. In the NH3 treatment, much of the vegetation was killed off by high doses of NH3, and the nitrogen was presumably more available to denitrifying bacteria. The design of the wet and dry experimental treatments meant that they differed in statistical power, and we are less likely to detect an effect of the NH4+ and NO3− treatments, though they avoid issues of pseudo-replication

LOOKING INTO THE ENERGY LANDSCAPE OF MYOGLOBIN

Using the haem group of myoglobin as a probe in optical experiments makes it possible to study its conformational fluctuations in real time. Results of these experiments can be directly interpreted in terms of the structure of the potential energy surface of the protein. The current view is that proteins have rough energy landscapes comprising a large number of minima which represent conformational substates, and that these substates are hierarchically organized. Here, we show that the energy landscape is characterized by a number of discrete distributions of;barrier heights each representing a tier within a hierarchy of conformational substates. Furthermore, we provide evidence that the energy surface is self-similar and offer suggestions for a characterization of the protein fluctuations

Automated pipeline for rapid production and screening of HIV-specific monoclonal antibodies using pichia pastoris

Monoclonal antibodies (mAbs) that bind and neutralize human pathogens have great therapeutic potential. Advances in automated screening and liquid handling have resulted in the ability to discover antigen-specific antibodies either directly from human blood or from various combinatorial libraries (phage, bacteria or yeast). There remain, however, bottlenecks in the cloning, expression and evaluation of such lead antibodies identified in primary screens that hinder high-throughput screening. As such, ‘hit-to-lead identification’ remains both expensive and time-consuming. By combining the advantages of overlap extension PCR (OE-PCR) and a genetically stable yet easily manipulatable microbial expression host Pichia pastoris, we have developed an automated pipeline for the rapid production and screening of full-length antigenspecific mAbs. Here, we demonstrate the speed, feasibility and cost-effectiveness of our approach by generating several broadly neutralizing antibodies against human immunodeficiency virus (HIV).Bill & Melinda Gates FoundationUnited States. Defense Advanced Research Projects AgencySpace and Naval Warfare Systems Center San Diego (U.S.) (Contract N66001-13-C-4025)W. M. Keck FoundationNational Institute of Allergy and Infectious Diseases (U.S.) (U19AI090970).National Cancer Institute (U.S.) (David H. Koch Institute for Integrative Cancer Research at MIT. Support (Core) Grant P30-CA14051

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed

Water soluble aerosols and gases at a UK background site. Part 1: Controls of PM2.5 and PM10 aerosol composition

There is limited availability of long-term, high temporal resolution, chemically speciated aerosol measurements which can provide further insight into the health and environmental impacts of particulate matter. The Monitor for AeRosols and Gases (MARGA, Applikon B.V., NL) allows for the characterisation of the inorganic components of PM10 and PM2.5 (NH4+, NO3-, SO42-, Cl-, Na+, K+, Ca2+, Mg2+) and inorganic reactive gases (NH3, SO2, HCl, HONO and HNO3) at hourly resolution. The following study presents 6.5 years (June 2006 to December 2012) of quasi-continuous observations of PM2.5 and PM10 using the MARGA at the UK EMEP supersite, Auchencorth Moss, SE Scotland. Auchencorth Moss was found to be representative of a remote European site with average total water soluble inorganic mass of PM2.5 of 3.82 μg m−3. Anthropogenically derived secondary inorganic aerosols (sum of NH4+, NO3- and nss-SO42−) were the dominating species (63 %) of PM2.5. In terms of equivalent concentrations, NH4+ provided the single largest contribution to PM2.5 fraction in all seasons. Sea salt was the main component (73 %) of the PMcoarse fraction (PM10-PM2.5), though NO3- was also found to make a relatively large contribution to the measured mass (17 %) providing evidence of considerable processing of sea salt in the coarse mode. There was on occasions evidence of aerosol from combustion events being transported to the site in 2012 as high K+ concentrations (deviating from the known ratio in sea salt) coincided with increases in black carbon at the site. Pollution events in PM10 (defined as concentrations > 12 μg m−3) were on average dominated by NH4+ and NO3-, where smaller loadings at the site tended to be dominated by sea salt. As with other western European sites, the charge balance of the inorganic components resolved were biased towards cations, suggesting the aerosol was basic or more likely that organic acids contributed to the charge balance. This study demonstrates the UK background atmospheric composition is primarily driven by meteorology with sea salt dominating air masses from the Atlantic Ocean and the Arctic, whereas secondary inorganic aerosols tended to dominate air masses from continental Europe

Investigating situated cultural practices through cross-sectoral digital collaborations: policies, processes, insights

The (Belfast) Good Friday Agreement represents a major milestone in Northern Ireland's recent political history, with complex conditions allowing for formation of a ‘cross-community’ system of government enabling power sharing between parties representing Protestant/loyalist and Catholic/nationalist constituencies. This article examines the apparent flourishing of community-focused digital practices over the subsequent ‘post-conflict’ decade, galvanised by Northern Irish and EU policy initiatives armed with consolidating the peace process. Numerous digital heritage and storytelling projects have been catalysed within programmes aiming to foster social processes, community cohesion and cross-community exchange. The article outlines two projects—‘digital memory boxes’ and ‘interactive galleon’—developed during 2007–2008 within practice-led PhD enquiry conducted in collaboration with the Nerve Centre, a third-sector media education organisation. The article goes on to critically examine the processes involved in practically realising, and creatively and theoretically reconciling, community-engaged digital production in a particular socio-political context of academic-community collaboration