Accuracy of numerical relativity waveforms from binary neutron star mergers and their comparison with post-Newtonian waveforms

We present numerical relativity simulations of nine-orbit equal-mass binary neutron star covering the quasicircular late inspiral and merger. The extracted gravitational waveforms are analyzed for convergence and accuracy. Second order convergence is observed up to contact, i.e. about 3-4 cycles to merger; error estimates can be made up to this point. The uncertainties on the phase and the amplitude are dominated by truncation errors and can be minimized to 0.13 rad and less then 1%, respectively, by using several simulations and extrapolating in resolution. In the latter case finite-radius extraction uncertainties become a source of error of the same order and have to be taken into account. The waveforms are tested against accuracy standards for data analysis. The uncertainties on the waveforms are such that accuracy standards are generically not met for signal-to-noise ratios relevant for detection, except for some best cases using extrapolation from several runs. A detailed analysis of the errors is thus imperative for the use of numerical relativity waveforms from binary neutron stars in quantitative studies. The waveforms are compared with the post-Newtonian Taylor T4 approximants both for point-particle and including the analytically known tidal corrections. The T4 approximants accumulate significant phase differences of 2 rad at contact and 4 rad at merger, underestimating the influence of finite size effects. Tidal signatures in the waveforms are thus important at least during the last six orbits of the merger process.Comment: Physical Review D (Vol.85, No.10) 201

Conversion coefficients for superheavy elements

In this paper we report on internal conversion coefficients for Z = 111 to Z = 126 superheavy elements obtained from relativistic Dirac-Fock (DF) calculations. The effect of the atomic vacancy created during the conversion process has been taken into account using the so called "Frozen Orbital" approximation. The selection of this atomic model is supported by our recent comparison of experimental and theoretical conversion coefficients across a wide range of nuclei. The atomic masses, valence shell electron configurations, and theoretical atomic binding energies required for the calculations were adopted from a critical evaluation of the published data. The new conversion coefficient data tables presented here cover all atomic shells, transition energies from 1 keV up to 6000 keV, and multipole orders of 1 to 5. A similar approach was used in our previous calculations [1] for Z = 5 - 110.Comment: Accepted for publication in Atomic Data and Nuclear Data Table

, Nuclear quadrupole moment of 139La from relativistic electronic structure calculations of the electric field gradients in LaF, LaCl, LaBr and LaI

Relativistic coupled cluster theory is used to determine accurate electric field gradients in order to provide a theoretical value for the nuclear quadrupole moment of La139. Here we used the diatomic lanthanum monohalides LaF, LaCl, LaBr, and LaI as accurate nuclear quadrupole coupling constants are available from rotational spectroscopy by Rubinoff [J. Mol. Spectrosc. 218, 169 (2003)]. The resulting nuclear quadrupole moment for La139 (0.200±0.006 barn) is in excellent agreement with earlier work using atomic hyperfine spectroscopy [0.20 (1) barn]. © 2007 American Institute of Physics

How climate-smart is conservation agriculture (CA)? – its potential to deliver on adaptation, mitigation and productivity on smallholder farms in southern Africa

Climate resilient cropping systems are required to adapt to the increasing threats of climate change projected for Southern Africa and to better manage current climate variability. Conservation agriculture (CA) has been proposed among technologies that are climate-smart. For a cropping system to be labelled “climate-smart” it has to deliver three benefits: a) adapt to the effects of climate and be of increased resilience; b) mitigate climate effects by sequestering carbon (C) and reducing greenhouse gas emissions (GHG); and c) sustainably increase productivity and income. Research on smallholder farms from Southern Africa was analysed to assess if CA can deliver on the three principles of climate-smart agriculture. Results from Southern Africa showed that CA systems have a positive effect on adaptation and productivity, but its mitigation potential lags far behind expectations. CA systems maintain higher infiltration rates and conserve soil moisture, which helps to overcome seasonal dry-spells. Increased productivity and profitability were recorded although a lag period of 2–5 cropping seasons is common until yield benefits become significant. Immediate economic benefits such as reduced labour requirements in some systems will make CA more attractive in the short term to farmers who cannot afford to wait for several seasons until yield benefits accrue. The available data summarizing the effects of CA on soil organic C (SOC) and reductions in greenhouse gases, are often contradictory and depend a great deal on the agro-ecological environment and the available biomass for surface residue retention. There is an urgent need for more research to better quantify the mitigation effects, as the current data are scanty. Possible co-interventions such as improved intercropping/relay cropping systems, agroforestry and other tree-based systems may improve delivery of mitigation benefits and need further exploration

Associating land cover changes with patterns of incidences of climate-sensitive infections: an example on tick-borne diseases in the Nordic area

Some of the climate-sensitive infections (CSIs) affecting humans are zoonotic vector-borne diseases, such as Lyme borreliosis (BOR) and tick-borne encephalitis (TBE), mostly linked to various species of ticks as vectors. Due to climate change, the geographical distribution of tick species, their hosts, and the prevalence of pathogens are likely to change. A recent increase in human incidences of these CSIs in the Nordic regions might indicate an expansion of the range of ticks and hosts, with vegetation changes acting as potential predictors linked to habitat suitability. In this paper, we study districts in Fennoscandia and Russia where incidences of BOR and TBE have steadily increased over the 1995–2015 period (defined as ’Well Increasing districts’). This selection is taken as a proxy for increasing the prevalence of tick-borne pathogens due to increased habitat suitability for ticks and hosts, thus simplifying the multiple factors that explain incidence variations. This approach allows vegetation types and strengths of correlation specific to the WI districts to be differentiated and compared with associations found over all districts. Land cover types and their changes found to be associated with increasing human disease incidence are described, indicating zones with potential future higher risk of these diseases. Combining vegetation cover and climate variables in regression models shows the interplay of biotic and abiotic factors linked to CSI incidences and identifies some differences between BOR and TBE. Regression model projections up until 2070 under different climate scenarios depict possible CSI progressions within the studied area and are consistent with the observed changes over the past 20 years

Incremental Value of Computed Tomography Perfusion for Final Infarct Prediction in Acute Ischemic Cerebellar Stroke

Background The diagnosis of ischemic cerebellar stroke is challenging because of nonspecific symptoms and very limited accuracy of commonly applied computed tomography (CT) imaging. Advances in CT perfusion imaging provide increasing value in the detection of posterior circulation stroke, but the prognostic value remains unclear. We aimed to identify imaging parameters that predict morphologic outcome in cerebellar stroke patients using advanced CT including whole‐brain CT perfusion (WB‐CTP). Methods and Results We selected all subjects with cerebellar WB‐CTP perfusion deficits and follow‐up‐confirmed cerebellar infarction from a consecutive cohort with suspected stroke who underwent WB‐CTP. Posterior‐circulation‐Acute‐Stroke‐Prognosis‐Early‐CT‐Score (pc‐ASPECTS) was determined on noncontrast CT, CT angiography source images, and on parametric WB‐CTP maps. Cerebellar perfusion deficit volumes on all maps and the final infarction volume on follow‐up imaging were quantified. Uni‐ and multivariate regression analyses were performed. Sixty patients fulfilled the inclusion criteria. pc‐ASPECTS on CT angiography source images (ß, −9.239; 95% CI, −14.220 to −4.259; P0.05). Conclusions In contrast to noncontrast CT and CT angiography, WB‐CTP imaging contains prognostic information for morphologic outcome in patients with acute cerebellar stroke

Effects of maize residue and mineral nitrogen applications on maize yield in conservation-agriculture-based cropping systems of Southern Africa

Conservation agriculture (CA) and no-till (NT)-based cropping systems could address soil degradation and fertility decline in southern Africa. A multi-location and multi-year experiment was carried out between 2008 and 2014 to assess the effects of different levels of maize residue biomass (0, 2, 4, 6 and 8 t ha−1) and nitrogen (N) fertilizer (0, 30, 90 kg ha−1) on maize performance under no-tillage. In some sites, different (N) fertilizer levels were superimposed to test their effects on maize grain yield and leaf chlorophyll content under different maize residue biomass levels. The different residue levels had no significant effect on maize yield in most growing seasons. Maize residue cover increased grain yield in eight out of 39 site-years across the sites used. However, in some sites, maize yield decreased with increases in residue level in cropping seasons that had average to above average rainfall. At a few sites maize yield increased with increase in residue level. Seasonal rainfall pattern influenced the effect of different residue levels on grain yield at most sites. Nitrogen fertilizer increased maize yield regardless of the residue level applied. This study demonstrates that mulching with maize residues in CA/NT systems results in limited maize yield gains – at least within the first 6 years in different agro-ecological conditions of southern Africa

Railway transportation as a serious source of organic and inorganic pollution

Polycyclic aromatic hydrocarbons and heavy metal (Pb, Cd, Cu, Zn, Hg, Fe, Co, Cr, Mo) contents were established in soil and plant samples collected in different areas of the railway junction Iława Główna, Poland. Soil and plant samples were collected in four functional parts of the junction, i.e. the loading ramp, main track within platform area, rolling stock cleaning bay and the railway siding. It was found that all the investigated areas were strongly contaminated with polycyclic aromatic hydrocarbons (PAHs). The PAH contamination of the soil was the highest in the railway siding and in the platform area (59,508 and 49,670 μg kg−1, respectively). In the loading ramp and cleaning bay, the PAH concentration in soil was lower but still relatively very high (17,948 and 15,376 μg kg−1, respectively). The contamination in the railway siding exceeded the average control level up to about 80 times. In the soil of all the investigated areas, four- and five-ring PAHs prevailed. The concentrations of PAHs were determined in four dominating species of plants found at the junction. The highest concentration was found in the aerial parts of Taraxacum officinale (22,492 μg kg−1) growing in the cleaning bay. The comparison of the soil contamination with PAHs in the investigated railway junction showed a very significant increase of the PAHs level since 1995. It was found that the heavy metal contamination was also very high. Pb, Zn, Hg and Cd were established at the highest levels in the railway siding area, whereas Fe concentration was the highest in the platform area. A significant increase in mercury content was observed in the cleaning bay area. The investigations proved very significant increase of contamination with PAHs and similar heavy metals contamination in comparison with the concentration determined in the same areas 13 years ago

Error-analysis and comparison to analytical models of numerical waveforms produced by the NRAR Collaboration

The Numerical-Relativity-Analytical-Relativity (NRAR) collaboration is a joint effort between members of the numerical relativity, analytical relativity and gravitational-wave data analysis communities. The goal of the NRAR collaboration is to produce numerical-relativity simulations of compact binaries and use them to develop accurate analytical templates for the LIGO/Virgo Collaboration to use in detecting gravitational-wave signals and extracting astrophysical information from them. We describe the results of the first stage of the NRAR project, which focused on producing an initial set of numerical waveforms from binary black holes with moderate mass ratios and spins, as well as one non-spinning binary configuration which has a mass ratio of 10. All of the numerical waveforms are analysed in a uniform and consistent manner, with numerical errors evaluated using an analysis code created by members of the NRAR collaboration. We compare previously-calibrated, non-precessing analytical waveforms, notably the effective-one-body (EOB) and phenomenological template families, to the newly-produced numerical waveforms. We find that when the binary's total mass is ~100-200 solar masses, current EOB and phenomenological models of spinning, non-precessing binary waveforms have overlaps above 99% (for advanced LIGO) with all of the non-precessing-binary numerical waveforms with mass ratios <= 4, when maximizing over binary parameters. This implies that the loss of event rate due to modelling error is below 3%. Moreover, the non-spinning EOB waveforms previously calibrated to five non-spinning waveforms with mass ratio smaller than 6 have overlaps above 99.7% with the numerical waveform with a mass ratio of 10, without even maximizing on the binary parameters.Comment: 51 pages, 10 figures; published versio

Ground, Proximal, and Satellite Remote Sensing of Soil Moisture

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society. Potential applications include, but are not limited to, forecasting of weather and climate variability; prediction and monitoring of drought conditions; management and allocation of water resources; agricultural plant production and alleviation of famine; prevention of natural disasters such as wild fires, landslides, floods, and dust storms; or monitoring of ecosystem response to climate change. Because of the importance and wide‐ranging applicability of highly variable spatial and temporal SM information that links the water, energy, and carbon cycles, significant efforts and resources have been devoted in recent years to advance SM measurement and monitoring capabilities from the point to the global scales. This review encompasses recent advances and the state‐of‐the‐art of ground, proximal, and novel SM remote sensing techniques at various spatial and temporal scales and identifies critical future research needs and directions to further advance and optimize technology, analysis and retrieval methods, and the application of SM information to improve the understanding of critical zone moisture dynamics. Despite the impressive progress over the last decade, there are still many opportunities and needs to, for example, improve SM retrieval from remotely sensed optical, thermal, and microwave data and opportunities for novel applications of SM information for water resources management, sustainable environmental development, and food security