Methods for local gravity field approximation

The most widely known modern method for estimating gravity field values from observed data is least-squares collocation. Its advantages are that it can make estimates at arbitrary locations based on irregularly spaced observations, and that it makes use of statistical information about errors in the input data while providing corresponding information about the quality of the output estimates. Disadvantages of collocation include the necessity of inverting square matrices of dimension equal to the number of data values and the need to assume covariance models for the gravity field and the data errors. Fourier methods are an important alternative to collocation; having the advantage of greater computational efficiency, but requiring data estimates to be on a regular grid and not using or providing statistical accuracy information. The GEOFAST algorithm is an implementation of collocation that achieves high computational efficiency by transforming the estimation equations into the frequency domain where an accurate approximation may be made to reduce the workload. The forward and inverse Fast Fourier Transforms (FFTs) are utilized. The accuracy and computational efficiency of the GEOFAST algorithm is demonstrated using two sets of synthetic gravity data: marine gravity for an ocean trench region including wavelengths longer than 200 km; and local land gravity containing wavelengths as short as 5 km. These results are discussed along with issues such as the advantages of first removing reference field models before carrying out the estimation algorithm

SIMPEL: Circuit model for photonic spike processing laser neurons

We propose an equivalent circuit model for photonic spike processing laser neurons with an embedded saturable absorber---a simulation model for photonic excitable lasers (SIMPEL). We show that by mapping the laser neuron rate equations into a circuit model, SPICE analysis can be used as an efficient and accurate engine for numerical calculations, capable of generalization to a variety of different laser neuron types found in literature. The development of this model parallels the Hodgkin--Huxley model of neuron biophysics, a circuit framework which brought efficiency, modularity, and generalizability to the study of neural dynamics. We employ the model to study various signal-processing effects such as excitability with excitatory and inhibitory pulses, binary all-or-nothing response, and bistable dynamics.Comment: 16 pages, 7 figure

Evaluation of Commercial Genomic Tests for Maternal Traits in Crossbred Beef Cattle

DNA samples were collected from beef heifers born at the Gudmundsen Sandhills Laboratory and analyzed with a genomic test. Phenotypic data from these females were compiled and used in a regression analysis to evaluate the utility of these genomic scores as predictors for phenotypic outcomes. Th e genomic score for birth body weight (BW) was signifi cantly associated with animal birth BW. Th e genomic score for heifer pregnancy was not a statistically significant predictor of actual pregnancy. Neither dam age or the genomic score for stayability were significant predictors of actual reproductive longevity

Highly syntenic and yet divergent: a tale of two Theilerias

The published genomic sequences of the two major host-transforming Theileria species of cattle represent a rich resource of information that has allowed novel bioinformatic and experimental studies into these important apicomplexan parasites. Since their publication in 2005, the genomes of T. annulata and T. parva have been utilised for a diverse range of applications, ranging from candidate antigen discovery to the identification of genetic markers for population analysis. This has led to advancements in the quest for a sub-unit vaccine, while providing a greater understanding of variation among parasite populations in the field. The unique ability of these Theileria species to induce host cell transformation is the subject of considerable scientific interest and the availability of full genomic sequences has provided new insights into this area of research. This article reviews the data underlying published comparative analyses, focussing on the general features of gene expression, the major Tpr/Tar multi-copy gene family and a re-examination of the predicted macroschizont secretome. Codon usage between the Theileria species is reviewed in detail, as this underpins ongoing comparative studies investigating selection at the intra- and inter-species level. The TashAT/TpshAT family of genes, conserved between T. annulata and T. parva, encodes products targeted to the host nucleus and has been implicated in contributing to the transformed bovine phenotype. Species-specific expansion and diversification at this critical locus is discussed with reference to the availability, in the near future, of genomic datasets which are based on non-transforming Theileria species

Dynamical laser spike processing

Novel materials and devices in photonics have the potential to revolutionize optical information processing, beyond conventional binary-logic approaches. Laser systems offer a rich repertoire of useful dynamical behaviors, including the excitable dynamics also found in the time-resolved "spiking" of neurons. Spiking reconciles the expressiveness and efficiency of analog processing with the robustness and scalability of digital processing. We demonstrate that graphene-coupled laser systems offer a unified low-level spike optical processing paradigm that goes well beyond previously studied laser dynamics. We show that this platform can simultaneously exhibit logic-level restoration, cascadability and input-output isolation---fundamental challenges in optical information processing. We also implement low-level spike-processing tasks that are critical for higher level processing: temporal pattern detection and stable recurrent memory. We study these properties in the context of a fiber laser system, but the addition of graphene leads to a number of advantages which stem from its unique properties, including high absorption and fast carrier relaxation. These could lead to significant speed and efficiency improvements in unconventional laser processing devices, and ongoing research on graphene microfabrication promises compatibility with integrated laser platforms.Comment: 13 pages, 7 figure

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

Electroweak Corrections to the Top Quark Decay

We have calculated the one-loop electroweak corrections to the decay t-> bW+, including the counterterm for the CKM matrix elements V(tb). Previous calculations used an incorrect delta V(tb) that led to a gauge dependent amplitude. However, since the contribution stemming from delta V(tb) is small, those calculations only underestimate the width by roughly one part in 10^5.Comment: 7 pages, 2 figure

Characterization of Megatrypanum trypanosomes from European Cervidae

Megatrypanum trypanosomes have been isolated from a number of different European Cervidae, but on the basis of morphology it has not been possible to define the species to which these isolates belong. We isolated Trypanosoma (Megatrypanum) theileri from 10 cattle, and Megatrypanum trypanosomes from 11 fallow deer (Cervus dama), 9 red deer (Cervus elaphus), and 4 roe deer (Capreolus capreolus) by blood culture on a biphasic medium (NNN agar slopes). Trypanosomes were propagated in Schneider's Drosophila medium and characterized by isoenzyme analysis and molecular karyotyping. Isocitrate dehydrogenase and phosphoglucomutase were visualized after starch gel electrophoresis of trypanosome lysates. By cluster analysis of this data all isolates from deer were clearly separated from the T. (M.) theileri isolates from cattle. Isolates from roe deer were different not only from T. (M.) theileri but also from the other deer isolates. Isolates from fallow deer and red deer were grouped together. Thus, there are probably at least two different species of Megatrypanum trypanosomes in the three Cervidae. One parasitizing roe deer, the other, apparently less host specific species, infecting red deer and fallow deer. Separation of the chromosomes of Megatrypanum trypanosomes by pulsed-field gradient gel electrophoresis (PFGE) showed that each isolate contained a large number (> 18) of chromosomes ranging in size from 300 to > 2200 kb. The molecular karyotypes were similar for all isolates, although no isolate was identical to anothe

Four Generations and Higgs Physics

In the light of the LHC, we revisit the implications of a fourth generation of chiral matter. We identify a specific ensemble of particle masses and mixings that are in agreement with all current experimental bounds as well as minimize the contributions to electroweak precision observables. Higgs masses between 115-315 (115-750) GeV are allowed by electroweak precision data at the 68% and 95% CL. Within this parameter space, there are dramatic effects on Higgs phenomenology: production rates are enhanced, weak-boson-fusion channels are suppressed, angular distributions are modified, and Higgs pairs can we observed. We also identify exotic signals, such as Higgs decay to same-sign dileptons. Finally, we estimate the upper bound on the cutoff scale from vacuum stability and triviality.Comment: 11 pages, 7 figures, REVTe