Nuclear Pairing: Surface or Bulk ?

We analyse how the spatial localisation properties of pairing correlations are changing in a major neutron shell of heavy nuclei. It is shown that the radial distribution of the pairing density depends strongly on whether the chemical potential is close to a low or a high angular momentum level and has very little sensitivity to whether the pairing force acts in the surface or in the bulk. The averaged pairing density over one major shell is however rather flat, practically independent of the pairing force. Hartree-Fock-Bogoliubov calculations for the isotopic chain $^{100-132}$Sn are presented for demonstration purposes.Comment: 12 pages, 5 figure

Quantum Dot in 2D Topological Insulator: The Two-channel Kondo Fixed Point

In this work, a quantum dot couples to two helical edge states of a 2D topological insulator through weak tunnelings is studied. We show that if the electron interactions on the edge states are repulsive, with Luttinger liquid parameter $K < 1$, the system flows to a stable two-channel fixed point at low temperatures. This is in contrast to the case of a quantum dot couples to two Luttinger liquid leads. In the latter case, a strong electron-electron repulsion is needed, with $K<1/2$, to reach the two-channel fixed point. This two-channel fixed point is described by a boundary Sine-Gordon Hamiltonian with a $K$ dependent boundary term. The impurity entropy at zero temperature is shown to be $\ln\sqrt{2K}$. The impurity specific heat is $C \propto T^{\frac{2}{K}-2}$ when $2/3 < K < 1$, and $C \propto T$ when $K<2/3$. We also show that the linear conductance across the two helical edges has non-trivial temperature dependence as a result of the renormalization group flow.Comment: 4+\epsilon page

Molecular characterization of S- and N-containing organic constituents in ambient aerosols by negative ion mode high-resolution Nanospray Desorption Electrospray Ionization Mass Spectrometry: CalNex 2010 field study

Samples of ambient aerosols from the 2010 California Research at the Nexus of Air Quality and Climate Change (CalNex) field study were analyzed using negative ion mode Nanospray Desorption Electrospray Ionization High-Resolution Mass Spectrometry (nano-DESI/MS). Four samples per day (6 h each) were collected in Bakersfield, CA on 20–24 June. Four characteristic groups were identified: molecules composed of carbon, hydrogen, and oxygen only (CHO), sulfur- (CHOS), nitrogen- (CHON), and both nitrogen- and sulfur-containing organics (CHONS). The chemical formula and elemental ratioswere consistent with the presence of organonitrates, organosulfate, and nitroxy organosulfates in the negative ion mode mass spectra. The number of observed CHO compounds increased in the afternoon samples, suggesting photochemical processing as a source. The average number of CHOS compounds had the smallest changes during the day, consistent with a more broadly distributed source. Both of the nitrogen-containing groups (CHONS and CHON) had greater numbers of compounds in the early morning (midnight to 6 A.M.) and night (6 P.M. to midnight) samples, respectively, consistent with nitrate radical chemistry as a likely source for those compounds. Most of the compounds were found in submicron particles. The size distribution of the number of CHON compounds was bimodal, potentially indicating two types of sources. We conclude that the majority of the compounds observed were secondary in nature with both biogenic and anthropogenic sources. These data are complementary to previous results from positive ion mode nano-DESI/MS analysis of a subset of the same samples providing a more complete view of aerosol chemical composition at Bakersfield

Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis

Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total 2manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake

Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: a meta-analysis

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Effects of Precursor Concentration and Acidic Sulfate in Aqueous Glyoxal−OH Radical Oxidation and Implications for Secondary Organic Aerosol

Previous experiments demonstrated that aqueous OH radical oxidation of glyoxal yields low-volatility compounds. When this chemistry takes place in clouds and fogs, followed by droplet evaporation (or if it occurs in aerosol water), the products are expected to remain partially in the particle phase, forming secondary organic aerosol (SOA). Acidic sulfate exists ubiquitously in atmospheric water and has been shown to enhance SOA formation through aerosol phase reactions. In this work, we investigate how starting concentrations of glyoxal (30−3000 μM) and the presence of acidic sulfate (0−840 μM) affect product formation in the aqueous reaction between glyoxal and OH radical. The oxalic acid yield decreased with increasing precursor concentrations, and the presence of sulfuric acid did not alter oxalic acid concentrations significantly. A dilute aqueous chemistry model successfully reproduced oxalic acid concentrations, when the experiment was performed at cloud-relevant concentrations (glyoxal <300 μM), but predictions deviated from measurements at increasing concentrations. Results elucidate similarities and differences in aqueous glyoxal chemistry in clouds and in wet aerosols. They validate for the first time the accuracy of model predictions at cloud-relevant concentrations. These results suggest that cloud processing of glyoxal could be an important source of SOA