Stable commutator length in Baumslag-Solitar groups and quasimorphisms for tree actions

This paper has two parts, on Baumslag-Solitar groups and on general G-trees. In the first part we establish bounds for stable commutator length (scl) in Baumslag-Solitar groups. For a certain class of elements, we further show that scl is computable and takes rational values. We also determine exactly which of these elements admit extremal surfaces. In the second part we establish a universal lower bound of 1/12 for scl of suitable elements of any group acting on a tree. This is achieved by constructing efficient quasimorphisms. Calculations in the group BS(2,3) show that this is the best possible universal bound, thus answering a question of Calegari and Fujiwara. We also establish scl bounds for acylindrical tree actions. Returning to Baumslag-Solitar groups, we show that their scl spectra have a uniform gap: no element has scl in the interval (0, 1/12).Comment: v2: minor changes, incorporates referee suggestions; v1: 36 pages, 10 figure

Linearizing the Observed Power Spectrum

Reconstruction of the linear power spectrum from observational data provides a way to compare cosmological models to a large amount of data, as Peacock & Dodds (1994, 1996) have shown. By applying the appropriate corrections to the observational power spectrum it is possible to recover the underlying linear power spectrum for any cosmological model. Using extensive N-body simulations we demonstrate that the method is applicable to a wide range of cosmological models. However, we find that the recovery of the linear power spectrum from observations following PD94 is misleading because the corrections are model- dependent. When we apply the proper corrections for a given model to the observational power spectrum, we find that no model in our test group recovers the linear power spectrum well for the bias suggested by PD94 between Abell, Radio, Optical, and IRAS catalogs 4.5:1.9:1.3:1, with b_IRAS=1. When we allow b_IRAS to vary we find that: (i)CHDM models give very good fits to observations if optically-selected galaxies are slightly biased b_Opt=1.1 (ii) Most LCDM models give worse but acceptable fits if blue galaxies are considerably antibiased: 0.6<b_Opt<0.9 and fail if optical galaxies are biased. (iii)There is a universal shape of the recovered linear power spectrum of all LCDM models over their entire range of explored wavenumbers,0.01<k<0.6h\Mpc. Recovered spectra of CDM and CHDM models are nearly the same as that of LCDM in the region 0.01<k<0.2h/Mpc but diverge from this spectrum at higher k.Comment: submitted to the Mon.Not.R.Astron.Soc., LaTeX (uses mn.sty, graphics.sty, endfloat.sty, trig.sty), 15 pages, 10 figures, also available at http://astro.nmsu.edu/~akravtso/GROUP/group_publications.html or at ftp://charon.nmsu.edu/pub/aklypin/LINOB

Shifting Sands

Tells the story of Griswold Point and shoreline change

Characterization of Soybean Yield Variability Using Crop Growth Models and 13C Discrimination

During the past several years, crop models have successfully been used to test the hypothesis that water stress is the primary factor that causes spatial yield variability in soybean [Glycine max (L.) Merr.] fields. However, there have been few attempts to validate this hypothesis through direct temporal and spatial measurements of water stress during the season. Recently, a technique has been developed to relate plant tissue 13C levels to the temporal water stress experienced by soybean plants. The purpose of this work was to compare the spatial yield loss simulated by a crop model with yield loss measured by 13C discrimination (∆) for a soybean field in South Dakota. The field was divided into 0.9-ha grids and the CROPGRO-Soybean model was calibrated to minimize error between simulated and observed yield in each grid over two seasons (1998, 2000). 13C discrimination was measured at 50 points representing 23 of the grids used in the crop modeling analysis in 2000. Simulated yield loss in grids that encompassed each 13C point in 2000 were compared to measurements of yield loss using the 13C discrimination technique. Initially, the root mean square error and r2 between simulated and measured yield loss was 259 kg ha-1 and 0.24, respectively. Upon closer inspection, it was observed that yield in 5 grids with the highest error likely were influenced by processes that are not represented in the crop model. Removing these values dramatically improved the agreement between simulated and observed yield loss, giving an RMSE of 216 kg ha-1 and r2 of 0.81. Both 13C discrimination and simulation results indicated that substantial yield loss occurred due to water stress in the summit/backslope areas of the field

Raman spectroscopy as a powerful technique in the characterization of ferrofluids

Raman spectroscopy has been used to get some insight into the chemical composition and structure of magnetic fluids based on ferrites. The inner as well as the surface structure of Fe-maghemite and Zn-maghemite have characterized by Raman spectroscopy. It has been shown that different chemical species are present on the maghemite surface by changing the laser excitation energy. Maghemites modified by the adsorption of aspartic and glutamic acids as well as those modified by the adsorption of methylene blue(MB) have also been investigated by Raman spectroscopy. It has been shown that while FTIR (Fourier transform infrared) spectroscopy gives almost no information regarding to the surface species, Raman spectroscopy in and off resonance gives suitable information regarding to the adsorbate structure and bonding. The Raman spectroscopy study of the modified maghemites have shown that the organic acids adsorb on the maghemite surfarce as glutamate and aspartate chemically bounded to Fe(III) ions on the maghemite surface, and that MB, a cation, adsorbs on the maghemite surface as a monomer by ion pair formation with coadsorbed nitrate

A Massively-Parallel 3D Simulator for Soft and Hybrid Robots

Simulation is an important step in robotics for creating control policies and testing various physical parameters. Soft robotics is a field that presents unique physical challenges for simulating its subjects due to the nonlinearity of deformable material components along with other innovative, and often complex, physical properties. Because of the computational cost of simulating soft and heterogeneous objects with traditional techniques, rigid robotics simulators are not well suited to simulating soft robots. Thus, many engineers must build their own one-off simulators tailored to their system, or use existing simulators with reduced performance. In order to facilitate the development of this exciting technology, this work presents an interactive-speed, accurate, and versatile simulator for a variety of types of soft robots. Cronos, our open-source 3D simulation engine, parallelizes a mass-spring model for ultra-fast performance on both deformable and rigid objects. Our approach is applicable to a wide array of nonlinear material configurations, including high deformability, volumetric actuation, or heterogenous stiffness. This versatility provides the ability to mix materials and geometric components freely within a single robot simulation. By exploiting the flexibility and scalability of nonlinear Hookean mass-spring systems, this framework simulates soft and rigid objects via a highly parallel model for near real-time speed. We describe an efficient GPU CUDA implementation, which we demonstrate to achieve computation of over 1 billion elements per second on consumer-grade GPU cards. Dynamic physical accuracy of the system is validated by comparing results to Euler-Bernoulli beam theory, natural frequency predictions, and empirical data of a soft structure under large deformation

Substance P Causes Seizures in Neurocysticercosis

Neurocysticercosis (NCC), a helminth infection of the brain, is a major cause of seizures. The mediators responsible for seizures in NCC are unknown, and their management remains controversial. Substance P (SP) is a neuropeptide produced by neurons, endothelial cells and immunocytes. The current studies examined the hypothesis that SP mediates seizures in NCC. We demonstrated by immunostaining that 5 of 5 brain biopsies from NCC patients contained substance P (SP)-positive (+) cells adjacent to but not distant from degenerating worms; no SP+ cells were detected in uninfected brains. In a rodent model of NCC, seizures were induced after intrahippocampal injection of SP alone or after injection of extracts of cysticercosis granuloma obtained from infected wild type (WT), but not from infected SP precursor-deficient mice. Seizure activity correlated with SP levels within WT granuloma extracts and was prevented by intrahippocampal pre-injection of SP receptor antagonist. Furthermore, extracts of granulomas from WT mice caused seizures when injected into the hippocampus of WT mice, but not when injected into SP receptor (NK1R) deficient mice. These findings indicate that SP causes seizures in NCC, and, suggests that seizures in NCC in humans may be prevented and/or treated with SP-receptor antagonists

Fiction Fix 14

https://digitalcommons.unf.edu/fiction_fix/1009/thumbnail.jp

Local Conditions, Not Regional Gradients, Drive Demographic Variation of Giant Ragweed (Ambrosia trifida) and Common Sunflower (Helianthus annuus) Across Northern U.S. Maize Belt

Knowledge of environmental factors influencing demography of weed species will improve understanding of current and future weed invasions. The objective of this study was to quantify regional-scale variation in vital rates of giant ragweed and common sunflower. To accomplish this objective, a common field experiment was conducted across seven sites between 2006 and 2008 throughout the north central U.S. maize belt. Demographic parameters of both weed species were measured in intra- and interspecific competitive environments, and environmental data were collected within site-years. Site was the strongest predictor of belowground vital rates (summer and winter seed survival and seedling recruitment), indicating sensitivity to local abiotic conditions. However, biotic factors influenced aboveground vital rates (seedling survival and fecundity). Partial least squares regression (PLSR) indicated that demography of both species was most strongly influenced by thermal time and precipitation. The first PLSR components, both characterized by thermal time, explained 63.2% and 77.0% of variation in the demography of giant ragweed and common sunflower, respectively; the second PLSR components, both characterized by precipitation, explained 18.3% and 8.5% of variation, respectively. The influence of temperature and precipitation is important in understanding the population dynamics and potential distribution of these species in response to climate change

Pathways: lessons learned and future directions for school-based interventions among American Indians

Pathways, a multicenter study to test the effect of a school-based program to prevent obesity in American Indian children, yielded many benefits and encountered many challenges. This paper explores what we have learned from this study and examines possible future directions