The rats in Hawaiian sugarcane

Heavy losses In Hawaiian sugarcane are caused by Polynesian rats (Rattus exulans), Norway rats (R. norvegicus), and black rats (R. rattus). Relative population levels, movement patterns, damage to sugarcane, and suggested timing of control during five stages of the 2-year crop cycle are described. The progress toward the registering of zinc phosphide for use in crops and the development of other rodenticides are mentioned

Polynomial Chaos Expansion method as a tool to evaluate and quantify field homogeneities of a novel waveguide RF Wien Filter

For the measurement of the electric dipole moment of protons and deuterons, a novel waveguide RF Wien filter has been designed and will soon be integrated at the COoler SYnchrotron at J\"ulich. The device operates at the harmonic frequencies of the spin motion. It is based on a waveguide structure that is capable of fulfilling the Wien filter condition ($\vec{E} \perp \vec{B}$) \textit{by design}. The full-wave calculations demonstrated that the waveguide RF Wien filter is able to generate high-quality RF electric and magnetic fields. In reality, mechanical tolerances and misalignments decrease the simulated field quality, and it is therefore important to consider them in the simulations. In particular, for the electric dipole moment measurement, it is important to quantify the field errors systematically. Since Monte-Carlo simulations are computationally very expensive, we discuss here an efficient surrogate modeling scheme based on the Polynomial Chaos Expansion method to compute the field quality in the presence of tolerances and misalignments and subsequently to perform the sensitivity analysis at zero additional computational cost.Comment: 12 pages, 19 figure

On the evolutionary behaviour of BL Lac objects

We present a new well defined sample of BL Lac objects selected from the ROSAT All-Sky Survey (RASS). The sample consists of 39 objects with 35 forming a flux limited sample down to f_X = 8 x 10^{-13} cgs, redshifts are known for 33 objects (and 31 of the complete sample). X-ray spectral properties were determined for each object individually with the RASS data. The luminosity function of RASS selected BL Lac objects is compatible with results provided by objects selected with the Einstein observatory, but the RASS selected sample contains objects with luminosities at least tenfold higher. Our analysis confirms the negative evolution for X-ray selected BL Lac objects found in a sample by the Einstein observatory, the parameterization provides similar results. A subdivision of the sample into halves according to the X-ray to optical flux ratio yielded unexpected results. The extremely X-ray dominated objects have higher redshifts and X-ray luminosities and only this subgroup shows clear signs of strong negative evolution. The evolutionary behaviour of objects with an intermediate spectral energy distribution between X-ray and radio dominated is compatible with no evolution at all. Consequences for unified schemes of X-ray and radio selected BL Lac objects are discussed.We suggest that the intermediate BL Lac objects are the basic BL Lac population. The distinction between the two subgroups can be explained if extreme X-ray dominated BL Lac objects are observed in a state of enhanced X-ray activity.Comment: 14 pages incl. 8 figures, accepted by A&

Electromagnetic Simulation and Design of a Novel Waveguide RF Wien Filter for Electric Dipole Moment Measurements of Protons and Deuterons

The conventional Wien filter is a device with orthogonal static magnetic and electric fields, often used for velocity separation of charged particles. Here we describe the electromagnetic design calculations for a novel waveguide RF Wien filter that will be employed to solely manipulate the spins of protons or deuterons at frequencies of about 0.1 to 2 MHz at the COoler SYnchrotron COSY at J\"ulich. The device will be used in a future experiment that aims at measuring the proton and deuteron electric dipole moments, which are expected to be very small. Their determination, however, would have a huge impact on our understanding of the universe.Comment: 10 pages, 10 figures, 4 table

Emissions Savings in the Corn-Ethanol Life Cycle from Feeding Coproducts to Livestock

Environmental regulations on greenhouse gas (GHG) emissions from corn (Zea mays L.)-ethanol production require accurate assessment methods to determine emissions savings from coproducts that are fed to livestock. We investigated current use of coproducts in livestock diets and estimated the magnitude and variability in the GHG emissions credit for coproducts in the corn-ethanol life cycle. The coproduct GHG emissions credit varied by more than twofold, from 11.5 to 28.3 g CO2e per MJ of ethanol produced, depending on the fraction of coproducts used without drying, the proportion of coproduct used to feed beef cattle (Bos taurus) vs. dairy or swine (Sus scrofa), and the location of corn production. Regional variability in the GHG intensity of crop production and future livestock feeding trends will determine the magnitude of the coproduct GHG offset against GHG emissions elsewhere in the corn-ethanol life cycle. Expansion of annual U.S. corn-ethanol production to 57 billion liters by 2015, as mandated in current federal law, will require feeding of coproduct at inclusion levels near the biological limit to the entire U.S. feedlot cattle, dairy, and swine herds. Under this future scenario, the coproduct GHG offset will decrease by 8% from current levels due to expanded use by dairy and swine, which are less efficient in use of coproduct than beef feedlot cattle. Because the coproduct GHG credit represents 19 to 38% of total life cycle GHG emissions, accurate estimation of the coproduct credit is important for determining the net impact of corn-ethanol production on atmospheric warming and whether corn-ethanol producers meet state- and national-level GHG emissions regulations

Parsec-scale Magnetic-Field Structures in HEAO-1 BL Lacs

We present very long baseline interferometry polarization images of an X-ray selected sample of BL Lacertae objects belonging to the first High Energy Astronomy Observatory (HEAO-1) and the ROSAT-Green Bank (RGB) surveys. These are primarily high-energy-peaked BL Lacs (HBLs) and exhibit core-jet radio morphologies on pc-scales. They show moderately polarized jet components, similar to those of low-energy-peaked BL Lacs (LBLs). The fractional polarization in the unresolved cores of the HBLs is, on average, lower than in the LBLs, while the fractional polarizations in the pc-scale jets of HBLs and LBLs are comparable. However a difference is observed in the orientation of the inferred jet magnetic fields -- while LBL jets are well-known to preferentially exhibit transverse magnetic fields, the HBL jets tend to display longitudinal magnetic fields. Although a `spine-sheath' jet velocity structure, along with larger viewing angles for HBLs could produce the observed magnetic field configuration, differences in other properties of LBLs and HBLs, such as their total radio power, cannot be fully reconciled with the different-angle scenario alone. Instead it appears that LBLs and HBLs differ intrinsically, perhaps in the spin rates of their central black holes.Comment: 41 pages, 21 figures, accepted for publication in MNRA

Performance of ECG-based seizure detection algorithms strongly depends on training and test conditions

Objective To identify non-EEG-based signals and algorithms for detection of motor and non-motor seizures in people lying in bed during video-EEG (VEEG) monitoring and to test whether these algorithms work in freely moving people during mobile EEG recordings. Methods Data of three groups of adult people with epilepsy (PwE) were analyzed. Group 1 underwent VEEG with additional devices (accelerometry, ECG, electrodermal activity); group 2 underwent VEEG; and group 3 underwent mobile EEG recordings both including one-lead ECG. All seizure types were analyzed. Feature extraction and machine-learning techniques were applied to develop seizure detection algorithms. Performance was expressed as sensitivity, precision, F$_{1}$ score, and false positives per 24 hours. Results The algorithms were developed in group 1 (35 PwE, 33 seizures) and achieved best results (F$_{1}$ score 56%, sensitivity 67%, precision 45%, false positives 0.7/24 hours) when ECG features alone were used, with no improvement by including accelerometry and electrodermal activity. In group 2 (97 PwE, 255 seizures), this ECG-based algorithm largely achieved the same performance (F$_{1}$ score 51%, sensitivity 39%, precision 73%, false positives 0.4/24 hours). In group 3 (30 PwE, 51 seizures), the same ECG-based algorithm failed to meet up with the performance in groups 1 and 2 (F$_{1}$ score 27%, sensitivity 31%, precision 23%, false positives 1.2/24 hours). ECG-based algorithms were also separately trained on data of groups 2 and 3 and tested on the data of the other groups, yielding maximal F1 scores between 8% and 26%. Significance Our results suggest that algorithms based on ECG features alone can provide clinically meaningful performance for automatic detection of all seizure types. Our study also underscores that the circumstances under which such algorithms were developed, and the selection of the training and test data sets need to be considered and limit the application of such systems to unseen patient groups behaving in different conditions