Asymptotics for incidence matrix classes

We define {\em incidence matrices} to be zero-one matrices with no zero rows or columns. A classification of incidence matrices is considered for which conditions of symmetry by transposition, having no repeated rows/columns, or identification by permutation of rows/columns are imposed. We find asymptotics and relationships for the number of matrices with $n$ ones in these classes as $n\to\infty$.Comment: updated and slightly expanded versio

Asymptotic enumeration of 2-covers and line graphs

In this paper we find asymptotic enumerations for the number of line graphs on $n$-labelled vertices and for different types of related combinatorial objects called 2-covers. We find that the number of 2-covers, $s_n$, and proper 2-covers, $t_n$, on $[n]$ both have asymptotic growth $$s_n\sim t_n\sim B_{2n}2^{-n}\exp(-\frac12\log(2n/\log n))= B_{2n}2^{-n}\sqrt{\frac{\log n}{2n}},$$ where $B_{2n}$ is the $2n$th Bell number, while the number of restricted 2-covers, $u_n$, restricted, proper 2-covers on $[n]$, $v_n$, and line graphs $l_n$, all have growth $$u_n\sim v_n\sim l_n\sim B_{2n}2^{-n}n^{-1/2}\exp(-[\frac12\log(2n/\log n)]^2).$$ In our proofs we use probabilistic arguments for the unrestricted types of 2-covers and and generating function methods for the restricted types of 2-covers and line graphs

The public perception and discussion of falling birth rates: the recent debate over low fertility in the popular press

Aspects of below-replacement fertility have long been debated among academics. Analyzing 437 popular newspaper and magazine articles from eleven developed countries during 1998-99, this study documents and investigates the corresponding public debate about low fertility. Despite the diversity in the debates of eleven countries, due to the countries´ different socioeconomic, political and demographic backrounds, our study finds important commonalties of the public debates about low fertility: First, countries emphasize consequences and potential interventions rather than causes in their public debate over lover fertility. Second, our study undoubtedly reveals that the public media perceives low fertility as a serious concern with mostly negative implications, despite the fact that many of the causes of low fertility are associated with social and economic progress. Third, the variety of issues and perspectives revealed in the public debate, while cohesive in general ways, invites a role for demographers in informing an accurate public discussion of low fertility, which will help form the most appropriate policy outcomes. (AUTHORS)

Multi-View Priors for Learning Detectors from Sparse Viewpoint Data

While the majority of today's object class models provide only 2D bounding boxes, far richer output hypotheses are desirable including viewpoint, fine-grained category, and 3D geometry estimate. However, models trained to provide richer output require larger amounts of training data, preferably well covering the relevant aspects such as viewpoint and fine-grained categories. In this paper, we address this issue from the perspective of transfer learning, and design an object class model that explicitly leverages correlations between visual features. Specifically, our model represents prior distributions over permissible multi-view detectors in a parametric way -- the priors are learned once from training data of a source object class, and can later be used to facilitate the learning of a detector for a target class. As we show in our experiments, this transfer is not only beneficial for detectors based on basic-level category representations, but also enables the robust learning of detectors that represent classes at finer levels of granularity, where training data is typically even scarcer and more unbalanced. As a result, we report largely improved performance in simultaneous 2D object localization and viewpoint estimation on a recent dataset of challenging street scenes.Comment: 13 pages, 7 figures, 4 tables, International Conference on Learning Representations 201

The Insurance Climate for Small Satellites and ELVs: 1990

The space insurance industry provides coverage for physical damage and liability risks to which space ventures are exposed as part of their business. The Insured party obtains insurance coverage through a Broker, who represents the Insured in soliciting coverage from the various Insurers in the world market. Physical damage insurance is designed to cover the value of an asset or the revenue it may provide, while liability insurance covers damage to the person or property of parties unrelated to those involved in launch activities. To date, five commercial launches of small ELVs have been conducted, and the necessary insurance has proven to be available at affordable rates. The forecast growth in the market for small spacecraft should prove attractive for insurers, and coverages should continue to be readily available for some time

Insurance Issues for Small Satellites and ELVs

This paper is intended to identify to those considering the use of small satellites and expendable launch vehicles the issues which may affect their ability to obtain insurance for their activities. It first discusses the types of insurance which are presently associated with space activities, including physical damage and liability coverages. It then addresses those aspects of small satellites and ELVs which appear to be different than present insurable space activities, and concludes by discussing how those differences might affect insurance requirements

3D Object Class Detection in the Wild

Object class detection has been a synonym for 2D bounding box localization for the longest time, fueled by the success of powerful statistical learning techniques, combined with robust image representations. Only recently, there has been a growing interest in revisiting the promise of computer vision from the early days: to precisely delineate the contents of a visual scene, object by object, in 3D. In this paper, we draw from recent advances in object detection and 2D-3D object lifting in order to design an object class detector that is particularly tailored towards 3D object class detection. Our 3D object class detection method consists of several stages gradually enriching the object detection output with object viewpoint, keypoints and 3D shape estimates. Following careful design, in each stage it constantly improves the performance and achieves state-ofthe-art performance in simultaneous 2D bounding box and viewpoint estimation on the challenging Pascal3D+ dataset

Photometric identification and MMT spectroscopy of new extremely metal-poor galaxies: towards a better understanding of young stellar populations at low metallicity

Extremely metal-poor star-forming galaxies (XMPs) represent one of our only laboratories for study of the low-metallicity stars we expect to encounter at early epochs. But as our understanding of the $z>6$ universe has improved, it has become clear that the majority of known XMPs within 100 Mpc host significantly less prominent massive star populations than their reionization-era counterparts, severely limiting their utility as testbeds for interpreting spectral features found at the highest redshifts. Here we present a new photometric selection technique designed to identify nearby XMPs dominated by young stellar populations comparable to those expected in the reionization era. We apply our technique to uncover candidate XMPs in SDSS imaging at magnitudes $16<i'<23$, extending significantly below the completeness limits of the SDSS spectroscopic survey. Spectroscopic observations with the MMT confirm that 32 of the 53 uniformly metal-poor and high specific star formation rate targets we observed have gas-phase oxygen abundances $12+\log\mathrm{O/H}<7.7$ ($Z/Z_\odot<0.1$), including two in the range of the lowest-metallicity galaxies known, $Z/Z_\odot<0.05$. Our observations shed new light onto the longstanding mystery of He II emission in star-forming galaxies: we find that the equivalent width of the He II $\lambda 4686$ high-ionization emission line does not scale with that of H$\beta$ in our sample, suggesting that binary evolution or other processes on $>10$ Myr timescales contribute substantially to the $\mathrm{He^+}$-ionizing photon budget in this metallicity regime. Applying such selection techniques coupled with deep spectroscopy to next-generation photometric surveys like LSST may eventually provide a basis for an empirical understanding of metal-poor massive stars.Comment: 16 pages, 10 figures, accepted for publication in MNRA