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- Aaron Wildavsky (1)
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- BL Lacertae objects: individual (Mrk 501) (1)
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We report on the gamma-ray activity of the blazar Mrk 501 during the first 480 days of Fermi operation. We find that the average Large Area Telescope (LAT) gamma-ray spectrum of Mrk 501 can be well described by a single power-law function with a photon index of 1.78 +/- 0.03. While we observe relatively mild flux variations with the Fermi-LAT (within less than a factor of two), we detect remarkable spectral variability where the hardest observed spectral index within the LAT energy range is 1.52 +/- 0.14, and the softest one is 2.51 +/- 0.20. These unexpected spectral changes do not correlate with the measured flux variations above 0.3 GeV. In this paper, we also present the first results from the 4.5 month long multifrequency campaign (2009 March 15-August 1) on Mrk 501, which included the Very Long Baseline Array (VLBA), Swift, RXTE, MAGIC, and VERITAS, the F-GAMMA, GASP-WEBT, and other collaborations and instruments which provided excellent temporal and energy coverage of the source throughout the entire campaign. The extensive radio to TeV data set from this campaign provides us with the most detailed spectral energy distribution yet collected for this source during its relatively low activity. The average spectral energy distribution of Mrk 501 is well described by the standard one-zone synchrotron self-Compton (SSC) model. In the framework of this model, we find that the dominant emission region is characterized by a size less than or similar to 0.1 pc (comparable within a factor of few to the size of the partially resolved VLBA core at 15-43 GHz), and that the total jet power (similar or equal to 10(44) erg s(-1)) constitutes only a small fraction (similar to 10(-3)) of the Eddington luminosity. The energy distribution of the freshly accelerated radiating electrons required to fit the time-averaged data has a broken power-law form in the energy range 0.3 GeV-10 TeV, with spectral indices 2.2 and 2.7 below and above the break energy of 20 GeV. We argue that such a form is consistent with a scenario in which the bulk of the energy dissipation within the dominant emission zone of Mrk 501 is due to relativistic, proton-mediated shocks. We find that the ultrarelativistic electrons and mildly relativistic protons within the blazar zone, if comparable in number, are in approximate energy equipartition, with their energy dominating the jet magnetic field energy by about two orders of magnitude.
We determine the metallicity distribution function (MDF) of the Galactic halo by means of a sample of 1638 metal-poor stars selected from the Hamburg/ESO objective-prism survey (HES). The sample was corrected for minor biases introduced by the strategy for spectroscopic follow-up observations of the metal-poor candidates, namely "best and brightest stars first". Comparison of the metallicities [Fe/H] of the stars determined from moderate-resolution (i.e., R similar to 2000) follow-up spectra with results derived from abundance analyses based on high-resolution spectra (i.e., R > 20 000) shows that the [Fe/H] estimates used for the determination of the halo MDF are accurate to within 0.3 dex, once highly C-rich stars are eliminated. We determined the selection function of the HES, which must be taken into account for a proper comparison between the HES MDF with MDFs of other stellar populations or those predicted by models of Galactic chemical evolution. The latter show a reasonable agreement with the overall shape of the HES MDF for [Fe/H] > -3.6, but only a model of Salvadori et al. (2007) with a critical metallicity for low-mass star formation of Z(cr) = 10(-3.4) Z(circle dot) reproduces the sharp drop at [Fe/H] similar to -3.6 present in the HES MDF. Although currently about ten stars at [Fe/H] < -3.6 are known, the evidence for the existence of a tail of the halo MDF extending to [Fe/H] similar to -5.5 is weak from the sample considered in this paper, because it only includes two stars [Fe/H] < -3.6. Therefore, a comparison with theoretical models has to await larger statistically complete and unbiased samples. A comparison of the MDF of Galactic globular clusters and of dSph satellites to the Galaxy shows qualitative agreement with the halo MDF, derived from the HES, once the selection function of the latter is included. However, statistical tests show that the differences between these are still highly significant.
The amyloid precursor protein (APP) and its paralogs, amyloid precursor-like protein 1 (APLP1) and APLP2, are metalloproteins with a putative role both in synaptogenesis and in maintaining synapse structure. Here, we studied the effect of zinc on membrane localization, adhesion, and secretase cleavage of APP, APLP1, and APLP2 in cell culture and rat neurons. For this, we employed live-cell microscopy techniques, a microcontact printing adhesion assay and ELISA for protein detection in cell culture supernatants. We report that zinc induces the multimerization of proteins of the amyloid precursor protein family and enriches them at cellular adhesion sites. Thus, zinc facilitates the formation of de novo APP and APLP1 containing adhesion complexes, whereas it does not have such influence on APLP2. Furthermore, zinc-binding prevented cleavage of APP and APLPs by extracellular secretases. In conclusion, the complexation of zinc modulates neuronal functions of APP and APLPs by (i) regulating formation of adhesion complexes, most prominently for APLP1, and (ii) by reducing the concentrations of neurotrophic soluble APP/APLP ectodomains.
Meeting Reports
(2019)
Thirty-one scientists met at Aschauhof, Germany to discuss the role of beliefs and self-perception on body size. In view of apparent growth stimulatory effects of dominance within the social group that is observed in social mammals, they discussed various aspects of competitive growth strategies and growth adjustments. Presentations included new data from Indonesia, a cohort-based prospective study from Merida, Yucatan, and evidence from recent meta-analyses and patterns of growth in the socially deprived. The effects of stress experienced during pregnancy and adverse childhood events were discussed, as well as obesity in school children, with emphasis on problems when using z-scores in extremely obese children. Aspects were presented on body image in African-American women, and body perception and the disappointments of menopause in view of feelings of attractiveness in different populations. Secular trends in height were presented, including short views on so called 'racial types' vs bio-plasticity, and historic data on early-life nutritional status and later-life socioeconomic outcomes during the Dutch potato famine. New tools for describing body proportions in patients with variable degrees of phocomelia were presented along with electronic growth charts. Bio-statisticians discussed the influence of randomness, community and network structures, and presented novel tools and methods for analyzing social network data.
In his article, 'Social constructionism and climate science denial', Hansson claims to present empirical evidence that the cultural theory developed by Dame Mary Douglas, Aaron Wildavsky and ourselves (among others) leads to (climate) science denial. In this reply, we show that there is no validity to these claims. First, we show that Hansson's empirical evidence that cultural theory has led to climate science denial falls apart under closer inspection. Contrary to Hansson's claims, cultural theory has made significant contributions to understanding and addressing climate change. Second, we discuss various features of Douglas' cultural theory that differentiate it from other constructivist approaches and make it compatible with the scientific method. Thus, we also demonstrate that cultural theory cannot be accused of epistemic relativism.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.