Fermi Observations of the Very Hard Gamma-ray Blazar PG 1553+113

We report the observations of PG 1553+113 during the first ~200 days of Fermi Gamma-ray Space Telescope science operations, from 4 August 2008 to 22 February 2009 (MJD 54682.7-54884.2). This is the first detailed study of PG 1553+113 in the GeV gamma-ray regime and it allows us to fill a gap of three decades in energy in its spectral energy distribution. We find PG 1553+113 to be a steady source with a hard spectrum that is best fit by a simple power-law in the Fermi energy band. We combine the Fermi data with archival radio, optical, X-ray and very high energy (VHE) gamma-ray data to model its broadband spectral energy distribution and find that a simple, one-zone synchrotron self-Compton model provides a reasonable fit. PG 1553+113 has the softest VHE spectrum of all sources detected in that regime and, out of those with significant detections across the Fermi energy bandpass so far, the hardest spectrum in that energy regime. Thus, it has the largest spectral break of any gamma-ray source studied to date, which could be due to the absorption of the intrinsic gamma-ray spectrum by the extragalactic background light (EBL). Assuming this to be the case, we selected a model with a low level of EBL and used it to absorb the power-law spectrum from PG 1553+113 measured with Fermi (200 MeV - 157 GeV) to find the redshift which gave the best fit to the measured VHE data (90 GeV - 1.1 TeV) for this parameterisation of the EBL. We show that this redshift can be considered an upper limit on the distance to PG 1553+113.Comment: Accepted for publication in the Astrophysical Journal (28 pages, 5 figures

Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage

Background: Shunt-dependent hydrocephalus significantly complicates subarachnoid hemorrhage (SAH), and reliable prognosis methods have been sought in recent years to reduce morbidity and costs associated with delayed treatment or neglected onset. Machine learning (ML) defines modern data analysis techniques allowing accurate subject-based risk stratifications. We aimed at developing and testing different ML models to predict shunt-dependent hydrocephalus after aneurysmal SAH. Methods: We consulted electronic records of patients with aneurysmal SAH treated at our institution between January 2013 and March 2019. We selected variables for the models according to the results of the previous works on this topic. We trained and tested four ML algorithms on three datasets: one containing binary variables, one considering variables associated with shunt-dependency after an explorative analysis, and one including all variables. For each model, we calculated AUROC, specificity, sensitivity, accuracy, PPV, and also, on the validation set, the NPV and the Matthews correlation coefficient (ϕ). Results: Three hundred eighty-six patients were included. Fifty patients (12.9%) developed shunt-dependency after a mean follow-up of 19.7 (± 12.6) months. Complete information was retrieved for 32 variables, used to train the models. The best models were selected based on the performances on the validation set and were achieved with a distributed random forest model considering 21 variables, with a ϕ = 0.59, AUC = 0.88; sensitivity and specificity of 0.73 (C.I.: 0.39–0.94) and 0.92 (C.I.: 0.84–0.97), respectively; PPV = 0.59 (0.38–0.77); and NPV = 0.96 (0.90–0.98). Accuracy was 0.90 (0.82–0.95). Conclusions: Machine learning prognostic models allow accurate predictions with a large number of variables and a more subject-oriented prognosis. We identified a single best distributed random forest model, with an excellent prognostic capacity (ϕ = 0.58), which could be especially helpful in identifying low-risk patients for shunt-dependency

Preliminary results of a soft novel lumbar intervertebral prothesis (DIAM) in the degenerative spinal pathology

Summary The authors report a series of 43 patients su¤ering from lower limb pain, almost constantly associated with chronic or acute backpain, treated by microsurgical nerve root decompression and by implantation of a soft intervertebral prothesis (DIAM). Satisfying results were obtained in 97% of cases, inducing the authors to consider the device a reliable tool for curing low-back pain and sciatica. Selection criteria are exposed and discussed

Optical spectroscopy of BL Lacertae objects. Broad lines, companion galaxies and redshift lower limits

Aims: We present optical spectroscopy of a sample of BL Lac objects, to determine their redshift, to study their broad emission line properties and to characterize their close environment. Methods: Twelve objects were observed using the ESO 3.6m and the NOT 2.5m telescopes, obtaining spectra for the BL Lacs and for nearby sources. Results: For seven objects, nuclear emission lines and/or absorption lines from the host galaxy were detected. In all the four cases where absorption lines were revealed, the host galaxy has been resolved with HST or ground-based imaging. The broad H_alpha luminosities (or their upper limits) of the BL Lacs are similar to those of radio-loud quasars. For two BL Lacs, spectroscopy of close companions indicates that they are at the redshift of the BL Lacs, and therefore physically associated and likely interacting. Five BL Lacs have a featureless spectrum. In these cases, we apply a new technique to derive lower limits for their redshift. which are consistent with lower limits deduced from imaging.Comment: Accepted for publication on Astronomy & Astrophysics, 15 pages, 8 figure