A distributional checklist of the leaf-cutting bees (Hymenoptera: Megachilidae) of Florida

The leaf-cutting bees are a diverse group which is commonly encountered all across the country. With over 600 North American species, most of which are in the genera Anthidium, Dianthidium, Stelis, Heriades, Hoplitis, Osmia, Megachile and Coelioxys, there are numerous “non-Apis” pollinators. Being an important taxon, there is a definite need for an awareness of their distribution across the United States and, perhaps in time, everywhere. This may allow us to follow the establishment of exotic species such as Megachile [Callomegachile] torrida Smith, M. [Pseudomegachile] lanata Fabricius, and an unidentified exotic which is listed below in the subgenus Callomegachile

Monte Carlo simulation of the treatment of uveal melanoma using measured heterogeneous 106Ru plaques

Background/Aims: Ruthenium plaques are used for the treatment of ocular tumors. The aim of this work is the comparison between simulated absorbed dose distributions tallied in an anthropomorphic phantom, obtained from ideal homogeneous plaques, and real eye plaques in which the actual heterogeneous distribution of 106Ru was measured. The placement of the plaques with respect to the tumor location was taken into consideration to optimize the effectiveness of the treatment. Methods: The generic CCA and CCB, and the specific CCA1364 and CCB1256 106Ru eye plaques were modeled with the Monte Carlo code PENELOPE. To compare the suitability of each treatment for an anterior, equatorial and posterior tumor location, cumulative dose-volume histograms for the tumors and structures at risk were calculated. Results: Eccentric placements of the plaques, taking into account the inhomogeneities of the emitter map, can substantially reduce the dose delivered to structures at risk while maintaining the prescribed dose at the tumor apex. Conclusions: The emitter map distribution of the plaque and the computerized tomography of the patient used in a Monte Carlo simulation allow an accurate determination of the plaque position with respect to the tumor with the potential to reduce the dose to sensitive structures. © 2018 S. Karger AG, BaselPostprint (published version

Neural-network selection of high-redshift radio quasars, and the luminosity function at z~4

We obtain a sample of 87 radio-loud QSOs in the redshift range 3.6<z<4.4 by cross-correlating sources in the FIRST radio survey S{1.4GHz} > 1 mJy with star-like objects having r <20.2 in SDSS Data Release 7. Of these 87 QSOs, 80 are spectroscopically classified in previous work (mainly SDSS), and form the training set for a search for additional such sources. We apply our selection to 2,916 FIRST-DR7 pairs and find 15 likely candidates. Seven of these are confirmed as high-redshift quasars, bringing the total to 87. The candidates were selected using a neural-network, which yields 97% completeness (fraction of actual high-z QSOs selected as such) and an efficiency (fraction of candidates which are high-z QSOs) in the range of 47 to 60%. We use this sample to estimate the binned optical luminosity function of radio-loud QSOs at $z\sim 4$, and also the LF of the total QSO population and its comoving density. Our results suggest that the radio-loud fraction (RLF) at high z is similar to that at low-z and that other authors may be underestimating the fraction at high-z. Finally, we determine the slope of the optical luminosity function and obtain results consistent with previous studies of radio-loud QSOs and of the whole population of QSOs. The evolution of the luminosity function with redshift was for many years interpreted as a flattening of the bright end slope, but has recently been re-interpreted as strong evolution of the break luminosity for high-z QSOs, and our results, for the radio-loud population, are consistent with this.Comment: 20 pages. Accepted for publication in MNRAS on 3 March 201