The Democratization of U.S. Research and Development after 1980

Using Compustat data, we document that prior to 1980, large R&D per-forming firms had higher R&D intensity (R&D/Sales) than small firms in the same industries. Over the course of the next two decades, in these same in-dustries, small firms came to rival and even surpass large firms in terms of R&D intensity. During this period, corporate R&D intensity nearly doubled and most of the aggregate increase is due to the substantial increase in R&D intensity among small firms. Little of the change in composition is explained by changes in the industrial distribution of R&D. Why did small firms increase their R&D after 1980 and not before? We argue that, after 1980, small firms were able to compete on better terms in industries already dominated by large firms. We show that the patterns we observe in the data are consistent with a straightforward dynamic model of R&D with falling barriers to entry. But what barriers fell? We argue the shift in R&D intensity by small firms was largely due to the electronics revolution. Prior to the 1980s, a large corporate sales and clerical force was an essential factor for the rapid and widespread distribution of new products. This technology clearly favored large, established firms. But the electronics revolution obviated the need for these factors, making entry easier.R&D, barriers to entry, innovation

The Adaptive Priority Queue with Elimination and Combining

Priority queues are fundamental abstract data structures, often used to manage limited resources in parallel programming. Several proposed parallel priority queue implementations are based on skiplists, harnessing the potential for parallelism of the add() operations. In addition, methods such as Flat Combining have been proposed to reduce contention by batching together multiple operations to be executed by a single thread. While this technique can decrease lock-switching overhead and the number of pointer changes required by the removeMin() operations in the priority queue, it can also create a sequential bottleneck and limit parallelism, especially for non-conflicting add() operations. In this paper, we describe a novel priority queue design, harnessing the scalability of parallel insertions in conjunction with the efficiency of batched removals. Moreover, we present a new elimination algorithm suitable for a priority queue, which further increases concurrency on balanced workloads with similar numbers of add() and removeMin() operations. We implement and evaluate our design using a variety of techniques including locking, atomic operations, hardware transactional memory, as well as employing adaptive heuristics given the workload.Comment: Accepted at DISC'14 - this is the full version with appendices, including more algorithm

The HI content of extremely metal-deficient blue compact dwarf galaxies

We have obtained new HI observations with the 100m Green Bank Telescope (GBT) for a sample of 29 extremely metal-deficient star-forming Blue Compact Dwarf (BCD) galaxies, selected from the Sloan Digital Sky Survey spectral data base to be extremely metal-deficient (12+logO/H<7.6). Neutral hydrogen was detected in 28 galaxies, a 97% detection rate. Combining the HI data with SDSS optical spectra for the BCD sample and adding complementary galaxy samples from the literature to extend the metallicity and mass ranges, we have studied how the HI content of a galaxy varies with various global galaxian properties. There is a clear trend of increasing gas mass fraction with decreasing metallicity, mass and luminosity. We obtain the relation M(HI)/L(g)~L(g)^{-0.3}, in agreement with previous studies based on samples with a smaller luminosity range. The median gas mass fraction f(gas) for the GBT sample is equal to 0.94 while the mean gas mass fraction is 0.90+/-0.15, with a lower limit of ~0.65. The HI depletion time is independent of metallicity, with a large scatter around the median value of 3.4 Gyr. The ratio of the baryonic mass to the dynamical mass of the metal-deficient BCDs varies from 0.05 to 0.80, with a median value of ~0.2. About 65% of the BCDs in our sample have an effective yield larger than the true yield, implying that the neutral gas envelope in BCDs is more metal-deficient by a factor of 1.5-20, as compared to the ionized gas.Comment: 21 pages, 13 figures, accepted for publication in MNRA

The Spitzer View of Low-Metallicity Star Formation: II. Mrk 996, a Blue Compact Dwarf Galaxy with an Extremely Dense Nucleus

(abridged) We present new Spitzer, UKIRT and MMT observations of the blue compact dwarf galaxy (BCD) Mrk 996, with an oxygen abundance of 12+log(O/H)=8.0. This galaxy has the peculiarity of possessing an extraordinarily dense nuclear star-forming region, with a central density of ~10^6 cm^{-3}. The nuclear region of Mrk 996 is characterized by several unusual properties: a very red color J-K = 1.8, broad and narrow emission-line components, and ionizing radiation as hard as 54.9 eV, as implied by the presence of the OIV 25.89 micron line. The nucleus is located within an exponential disk with colors consistent with a single stellar population of age >1 Gyr. The infrared morphology of Mrk 996 changes with wavelength. The IRS spectrum shows strong narrow Polycyclic Aromatic Hydrocarbon (PAH) emission, with narrow line widths and equivalent widths that are high for the metallicity of Mrk 996. Gaseous nebular fine-structure lines are also seen. A CLOUDY model requires that they originate in two distinct HII regions: a very dense HII region of radius ~580 pc with densities declining from ~10^6 at the center to a few hundreds cm^{-3} at the outer radius, where most of the optical lines arise; and a HII region with a density of ~300 cm^{-3} that is hidden in the optical but seen in the MIR. We suggest that the infrared lines arise mainly in the optically obscured HII region while they are strongly suppressed by collisional deexcitation in the optically visible one. The hard ionizing radiation needed to account for the OIV 25.89 micron line is most likely due to fast radiative shocks propagating in an interstellar medium. A hidden population of Wolf-Rayet stars of type WNE-w or a hidden AGN as sources of hard ionizing radiation are less likely possibilities.Comment: 48 pages, 13 figures, accepted for publication in the Astrophysical Journa

K3-fibered Calabi-Yau threefolds I, the twist map

A construction of Calabi-Yaus as quotients of products of lower-dimensional spaces in the context of weighted hypersurfaces is discussed, including desingularisation. The construction leads to Calabi-Yaus which have a fiber structure, in particular one case has K3 surfaces as fibers. These Calabi-Yaus are of some interest in connection with Type II -heterotic string dualities in dimension 4. A section at the end of the paper summarises this for the non-expert mathematician.Comment: 31 pages LaTeX, 11pt, 2 figures. To appear in International Journal of Mathematics. On the web at http://personal-homepages.mis.mpg.de/bhunt/preprints.html , #

Benjamin-Ono Kadomtsev-Petviashvili’s models in interfacial electro-hydrodynamics

Three-dimensional nonlinear potential free surface flows in the presence of vertical electric fields are considered. Both the effects of gravity and surface tension are included in the dynamic boundary condition. An asymptotic analysis (based on the assumptions of small depth and small free surface displacements) is presented. It is shown that the problem can be modelled by a Benjamin-Ono Kadomtsev-Petviashvili equation. Furthermore a fifth order Benjamin-Ono Kadomtsev-Petviashvili equation is derived to describe the flows in the particular case of values of the Bond number close to 1/3

Neural Modeling and Control of Diesel Engine with Pollution Constraints

The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identification and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are flexible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The presented work extends optimal neuro-control to the multivariable case and shows the flexibility of neural optimisers. Considering the preliminary results, it appears that neural networks can be used as embedded models for engine control, to satisfy the more and more restricting pollutant emission legislation. Particularly, they are able to model nonlinear dynamics and outperform during transients the control schemes based on static mappings.Comment: 15 page