Analysis of tethered balloon, ceilometer and class sounding data taken on San Nicolas Island during the FIRE project

During the FIRE Marine Stratocumulus Program on San Nicolas Island, Colorado State University (CSU) and the British Meteorological Office (BMO) operated separate instrument packages on the NASA tethered balloon. The CSU package contained instrumentation for the measurement of temperature, pressure, humidity, cloud droplet concentration, and long and short wave radiation. Eight research flights, performed between July 7 and July 14, are summarized. An analysis priority to the July 7, 8 and 11 flights was assigned for the purposes of comparing the CSU and BMO data. Results are presented. In addition, CSU operated a laser ceilometer for the determination of cloud base, and a CLASS radiosonde site which launched 69 sondes. Data from all of the above systems are being analyzed

Cyclopenta[c]phenanthrene induction of CYP1A in brain of rainbow trout (Oncorhynchus mykiss)

We assessed the effects of cyclopenta[c]phenanthrene (CP[c]Ph) and benzo[a]pyrene (B[a]P; positive control) on CYP1A gene expression in brain of juvenile rainbow trout (Oncorhynchus mykiss) using the quantitative reverse transcription polymerase chain reaction (Q-RT-PCR). A group of hatchery raised rainbow trout, with an average body mass of 49.4 g and total length of 15.5 cm were given an intraperitoneal injection (10 mg*kg-1) of either CP[c]Ph or B[a]P in corn oil (2 mg*mi-1 corn oil) or corn oil alone (control). After 24 and 48 h, trout brains were collected for mRNA isolation and analysis. After 24 hours of the exposure, only B[a]P-treated rainbow trout had 10-fold higher number of CYP1A transcripts (mean = 3.63*106 transcripts*µg-1 total RNA) than control fish (3.24*105 transcripts*µg-1 total RNA; Tukey test, P<0.05). After 48 hrs, significantly higher levels of CYP1A expression (Tukey test, P<0.001) were found in either CP[c]Ph- or B[a]P- induced group (1.45*106 and 6.92*106 transcriptsźµg-1 total RNA, respectively) over a control group (mean=1.41*105 transcripts*µg-1 total RNA). The finding that CYP1A in brain tissue was inducible by CP[c]Ph, a polycyclic aromatic hydrocarbon (PAH) of different than B[a]P planar characteristics, may further validate the use of rainbow trout brain CYP1A mRNA levels as a biomarker of PAH exposure

Multi-objective improvement of software using co-evolution and smart seeding

Optimising non-functional properties of software is an important part of the implementation process. One such property is execution time, and compilers target a reduction in execution time using a variety of optimisation techniques. Compiler optimisation is not always able to produce semantically equivalent alternatives that improve execution times, even if such alternatives are known to exist. Often, this is due to the local nature of such optimisations. In this paper we present a novel framework for optimising existing software using a hybrid of evolutionary optimisation techniques. Given as input the implementation of a program or function, we use Genetic Programming to evolve a new semantically equivalent version, optimised to reduce execution time subject to a given probability distribution of inputs. We employ a co-evolved population of test cases to encourage the preservation of the program’s semantics, and exploit the original program through seeding of the population in order to focus the search. We carry out experiments to identify the important factors in maximising efficiency gains. Although in this work we have optimised execution time, other non-functional criteria could be optimised in a similar manner

On inversions and Doob hh-transforms of linear diffusions

Let $X$ be a regular linear diffusion whose state space is an open interval $E\subseteq\mathbb{R}$. We consider a diffusion $X^*$ which probability law is obtained as a Doob $h$-transform of the law of $X$, where $h$ is a positive harmonic function for the infinitesimal generator of $X$ on $E$. This is the dual of $X$ with respect to $h(x)m(dx)$ where $m(dx)$ is the speed measure of $X$. Examples include the case where $X^*$ is $X$ conditioned to stay above some fixed level. We provide a construction of $X^*$ as a deterministic inversion of $X$, time changed with some random clock. The study involves the construction of some inversions which generalize the Euclidean inversions. Brownian motion with drift and Bessel processes are considered in details.Comment: 19 page

Few-nucleon systems in translationally invariant harmonic oscillator basis

We present a translationally invariant formulation of the no-core shell model approach for few-nucleon systems. We discuss a general method of antisymmetrization of the harmonic-oscillator basis depending on Jacobi coordinates. The use of a translationally invariant basis allows us to employ larger model spaces than in traditional shell-model calculations. Moreover, in addition to two-body effective interactions, three- or higher-body effective interactions as well as real three-body interactions can be utilized. In the present study we apply the formalism to solve three and four nucleon systems interacting by the CD-Bonn nucleon-nucleon potential. Results of ground-state as well as excited-state energies, rms radii and magnetic moments are discussed. In addition, we compare charge form factor results obtained using the CD-Bonn and Argonne V8' NN potentials.Comment: 25 pages. RevTex. 13 Postscript figure

Four-nucleon shell-model calculations in a Faddeev-like approach

We use equations for Faddeev amplitudes to solve the shell-model problem for four nucleons in the model space that includes up to 14 hbar Omega harmonic-oscillator excitations above the unperturbed ground state. Two- and three-body effective interactions derived from the Reid93 and Argonne V8' nucleon-nucleon potentials are used in the calculations. Binding energies, excitations energies, point-nucleon radii and electromagnetic and strangeness charge form factors for 4He are studied. The structure of the Faddeev-like equations is discussed and a formula for matrix elements of the permutation operators in a harmonic-oscillator basis is given. The dependence on harmonic-oscillator excitations allowed in the model space and on the harmonic-oscillator frequency is investigated. It is demonstrated that the use of the three-body effective interactions improves the convergence of the results.Comment: 22 pages, 13 figures, REVTe

The use of remotely sensed data and polish NFI plots for prediction of growing stock volume using different predictive methods

Forest growing stock volume (GSV) is an important parameter in the context of forest resource management. National Forest Inventories (NFIs) are routinely used to estimate forest parameters, including GSV, for national or international reporting. Remotely sensed data are increasingly used as a source of auxiliary information for NFI data to improve the spatial precision of forest parameter estimates. In this study, we combine data from the NFI in Poland with satellite images of Landsat 7 and 3D point clouds collected with airborne laser scanning (ALS) technology to develop predictive models of GSV. We applied an area-based approach using 13,323 sample plots measured within the second cycle of the NFI in Poland (2010&ndash;2014) with poor positional accuracy from several to 15 m. Four different predictive approaches were evaluated: multiple linear regression, k-Nearest Neighbours, Random Forest and Deep Learning fully connected neural network. For each of these predictive methods, three sets of predictors were tested: ALS-derived, Landsat-derived and a combination of both. The developed models were validated at the stand level using field measurements from 360 reference forest stands. The best accuracy (RMSE% = 24.2%) and lowest systematic error (bias% = &minus;2.2%) were obtained with a deep learning approach when both ALS- and Landsat-derived predictors were used. However, the differences between the evaluated predictive approaches were marginal when using the same set of predictor variables. Only a slight increase in model performance was observed when adding the Landsat-derived predictors to the ALS-derived ones. The obtained results showed that GSV can be predicted at the stand level with relatively low bias and reasonable accuracy for coniferous species, even using field sample plots with poor positional accuracy for model development. Our findings are especially important in the context of GSV prediction in areas where NFI data are available but the collection of accurate positions of field plots is not possible or justified because of economic reasons