Modeling the non-recycled Fermi gamma-ray pulsar population

We use Fermi Gamma-ray Space Telescope detections and upper limits on non-recycled pulsars obtained from the Large Area Telescope (LAT) to constrain how the gamma-ray luminosity L depends on the period P and the period derivative \dot{P}. We use a Bayesian analysis to calculate a best-fit luminosity law, or dependence of L on P and \dot{P}, including different methods for modeling the beaming factor. An outer gap (OG) magnetosphere geometry provides the best-fit model, which is L \propto P^{-a} \dot{P}^{b} where a=1.36\pm0.03 and b=0.44\pm0.02, similar to but not identical to the commonly assumed L \propto \sqrt{\dot{E}} \propto P^{-1.5} \dot{P}^{0.5}. Given upper limits on gamma-ray fluxes of currently known radio pulsars and using the OG model, we find that about 92% of the radio-detected pulsars have gamma-ray beams that intersect our line of sight. By modeling the misalignment of radio and gamma-ray beams of these pulsars, we find an average gamma-ray beaming solid angle of about 3.7{\pi} for the OG model, assuming a uniform beam. Using LAT-measured diffuse fluxes, we place a 2{\sigma} upper limit on the average braking index and a 2{\sigma} lower limit on the average surface magnetic field strength of the pulsar population of 3.8 and 3.2 X 10^{10} G, respectively. We then predict the number of non-recycled pulsars detectable by the LAT based on our population model. Using the two-year sensitivity, we find that the LAT is capable of detecting emission from about 380 non-recycled pulsars, including 150 currently identified radio pulsars. Using the expected five-year sensitivity, about 620 non-recycled pulsars are detectable, including about 220 currently identified radio pulsars. We note that these predictions significantly depend on our model assumptions.Comment: 26 pages, 10 figures, Accepted by ApJ on 8 September 201

Recollapse of the closed Tolman spacetimes

The closed-universe recollapse conjecture is studied for the spherically symmetric spacetimes. It is proven that there exists an upper bound to the lengths of timelike curves in any Tolman spacetime that possesses $S^3$ Cauchy surfaces and whose energy density is positive. Furthermore, an explicit bound is constructed from the initial data for such a spacetime.Comment: 25 pages, REVTeX, NCSU-MP-930

Initiation and final failure via environmentally assisted cracking in high strength aluminium

Environmentally assisted cracking (EAC) is particularly important to understand and control in high strength aluminium used in engineering applications as moist air provides a suitable environment to assist cracking in these materials. Propagation of EAC has been widely investigated but initiation has been difficult to follow due to it’s stochastic nature. We show that time-lapse 3D imaging using X-ray computed tomography offers a way to survey large surface areas whilst maintaining site specific high resolution information giving new insights into this process. In addition the final failure of these materials occurs when the environmentally assisted cracks of intergranular or transgranular type grow to a critical length from the initiation sites. We show through mechanical testing assessment and high resolution fractography that the rapid fracture that follows is also assisted by the environment leading to reduced ductility during the final failure. Examples from AA5083-H131 and AA7085-T7651 are shown which appear to show the same general behaviour. Round dog bone specimens prepared in the Short Transverse direction were subjected to slow strain rate testing (SSRT) at different strain rates and in different environments. Samples were also pre-exposed to different environments to introduce small corrosion sites to act as ‘realistic’ stress raisers in the specimens

Just how long can you live in a black hole and what can be done about it?

We study the problem of how long a journey within a black hole can last. Based on our observations, we make two conjectures. First, for observers that have entered a black hole from an asymptotic region, we conjecture that the length of their journey within is bounded by a multiple of the future asymptotic ``size'' of the black hole, provided the spacetime is globally hyperbolic and satisfies the dominant-energy and non-negative-pressures conditions. Second, for spacetimes with ${\Bbb R}^3$ Cauchy surfaces (or an appropriate generalization thereof) and satisfying the dominant energy and non-negative-pressures conditions, we conjecture that the length of a journey anywhere within a black hole is again bounded, although here the bound requires a knowledge of the initial data for the gravitational field on a Cauchy surface. We prove these conjectures in the spherically symmetric case. We also prove that there is an upper bound on the lifetimes of observers lying ``deep within'' a black hole, provided the spacetime satisfies the timelike-convergence condition and possesses a maximal Cauchy surface. Further, we investigate whether one can increase the lifetime of an observer that has entered a black hole, e.g., by throwing additional matter into the hole. Lastly, in an appendix, we prove that the surface area $A$ of the event horizon of a black hole in a spherically symmetric spacetime with ADM mass $M_{\text{ADM}}$ is always bounded by $A \le 16\pi M_{\text{ADM}}^2$, provided that future null infinity is complete and the spacetime is globally hyperbolic and satisfies the dominant-energy condition.Comment: 20 pages, REVTeX 3.0, 6 figures included, self-unpackin

Re-engineering forensic anthropology : new techniques in sharp force trauma analysis

In forensic anthropology the analysis of microscopic tool marks found in skeletal sharp force trauma is a challenging area. Many different imaging methods have been employed to measure cut mark characteristics in aid of developing diagnostic tools for estimating knife type used for these marks. Furthermore numerous experimental methods for creating tool marks for analysis have been used. A novel method for creating, analysing and presenting tool marks using reverse engineering and metrology was investigated. 5 Pig torsos prepared to mimic human anatomy were stabbed using seven different knives. Following chemical defleshing the ribs were micro-CT scanned for the analysis of tool marks left from the knives. Other methods including SEM, Digital microscopy and Laser scanning were also considered. Various geometrical measurements of the cut mark micro-morphology were taken. These measurements were statistically analysed using SPSS. Knife types gave statistically significant different cut mark width, length, wall angle, floor radius and shape (p<0.001). Knife sub-types and individual knives also gave statistically significant differencing in width and shape (p<0.001). Statistical classification of cut marks as either serrated or non-serrated made marks was shown to be 90% if width, length, wall angle and floor radius were accounted for. This indicated that determining knife type quantitatively is possible and could aid criminal investigators with their enquires. 3D models of these cut marks could also be developed for potential use in court for forensic expert testimony

Where Are My Intelligent Assistant's Mistakes? A Systematic Testing Approach

Intelligent assistants are handling increasingly critical tasks, but until now, end users have had no way to systematically assess where their assistants make mistakes. For some intelligent assistants, this is a serious problem: if the assistant is doing work that is important, such as assisting with qualitative research or monitoring an elderly parent’s safety, the user may pay a high cost for unnoticed mistakes. This paper addresses the problem with WYSIWYT/ML (What You See Is What You Test for Machine Learning), a human/computer partnership that enables end users to systematically test intelligent assistants. Our empirical evaluation shows that WYSIWYT/ML helped end users find assistants’ mistakes significantly more effectively than ad hoc testing. Not only did it allow users to assess an assistant’s work on an average of 117 predictions in only 10 minutes, it also scaled to a much larger data set, assessing an assistant’s work on 623 out of 1,448 predictions using only the users’ original 10 minutes’ testing effort