Museums & Society 2034: Trends and Potential Futures

What challenges will society and museums face in the next quarter-century? How will the demographic profile of America change between now and 2034? How will energy and infrastructure costs affect the sustainability of museums? What will Web 3.0 -- or 5.0 or 6.0 -- look like? Will the "real" survive the assault of the "virtual"? Will the number of leisure-time alternatives continue to grow? Will the lines between work and leisure, public and private, continue to blur? Most importantly, how will museums face these challenges and shape the future they will have to inhabit?This report, commissioned by the Center for the Future of Museums at the American Association of Museums, projects current social trends to 2034 and suggests how museums can face future challenges while continuing to meet their mission of public service. The report focuses on four major trends: demographic shifts, globalization, the revolution in information and communication technologies, and new cultural assumptions about the primacy of the individual as creator and curator

A new flux conserving Newton's method scheme for the two-dimensional, steady Navier-Stokes equations

A new numerical method is developed for the solution of the two-dimensional, steady Navier-Stokes equations. The method that is presented differs in significant ways from the established numerical methods for solving the Navier-Stokes equations. The major differences are described. First, the focus of the present method is on satisfying flux conservation in an integral formulation, rather than on simulating conservation laws in their differential form. Second, the present approach provides a unified treatment of the dependent variables and their unknown derivatives. All are treated as unknowns together to be solved for through simulating local and global flux conservation. Third, fluxes are balanced at cell interfaces without the use of interpolation or flux limiters. Fourth, flux conservation is achieved through the use of discrete regions known as conservation elements and solution elements. These elements are not the same as the standard control volumes used in the finite volume method. Fifth, the discrete approximation obtained on each solution element is a functional solution of both the integral and differential form of the Navier-Stokes equations. Finally, the method that is presented is a highly localized approach in which the coupling to nearby cells is only in one direction for each spatial coordinate, and involves only the immediately adjacent cells. A general third-order formulation for the steady, compressible Navier-Stokes equations is presented, and then a Newton's method scheme is developed for the solution of incompressible, low Reynolds number channel flow. It is shown that the Jacobian matrix is nearly block diagonal if the nonlinear system of discrete equations is arranged approximately and a proper pivoting strategy is used. Numerical results are presented for Reynolds numbers of 100, 1000, and 2000. Finally, it is shown that the present scheme can resolve the developing channel flow boundary layer using as few as six to ten cells per channel width, depending on the Reynolds number

Supervised and Unsupervised Transfer Learning for Question Answering

Although transfer learning has been shown to be successful for tasks like object and speech recognition, its applicability to question answering (QA) has yet to be well-studied. In this paper, we conduct extensive experiments to investigate the transferability of knowledge learned from a source QA dataset to a target dataset using two QA models. The performance of both models on a TOEFL listening comprehension test (Tseng et al., 2016) and MCTest (Richardson et al., 2013) is significantly improved via a simple transfer learning technique from MovieQA (Tapaswi et al., 2016). In particular, one of the models achieves the state-of-the-art on all target datasets; for the TOEFL listening comprehension test, it outperforms the previous best model by 7%. Finally, we show that transfer learning is helpful even in unsupervised scenarios when correct answers for target QA dataset examples are not available.Comment: To appear in NAACL HLT 2018 (long paper

Silicon nanowire devices

Transport measurements were carried out on 15–35 nm diameter silicon nanowires grown using SiH4 chemical vapor deposition via Au or Zn particle-nucleated vapor-liquid-solid growth at 440°C. Both Al and Ti/Au contacts to the wires were investigated. The wires, as produced, were essentially intrinsic, although Au nucleated wires exhibited a slightly higher conductance. Thermal treatment of the fabricated devices resulted in better electrical contacts, as well as diffusion of dopant atoms into the nanowires, and increased the nanowire conductance by as much as 10^4. Three terminal devices indicate that the doping of the wires is p type

On the Structure and Stabilization Mechanisms of Planar and Cylindrical Premixed Flames

The configurational simplicity of the stationary one-dimensional flames renders them intrinsically attractive for fundamental flame structure studies. The possibility and fidelity of studies of such flames on earth, however, have been severely restricted by the unidirectional nature of the gravity vector. To demonstrate these complications, let us first consider the premixed flame. Here a stationary, one-dimensional flame can be established by using the flat-flame burner. We next consider nonpremixed flames. First it may be noted that in an unbounded gravity-free environment, the only stationary one-dimensional flame is the spherical flame. Indeed, this is a major motivation for the study of microgravity droplet combustion, in which the gas-phase processes can be approximated to be quasi-steady because of the significant disparity between the gas and liquid densities for subcritical combustion. In view of the above considerations, an experimental and theoretical program on cylindrical and spherical premixed and nonpremixed flames in microgravity has been initiated. For premixed flames, we are interested in: (1) assessing the heat loss versus flow divergence as the dominant stabilization mechanism; (2) determining the laminar flame speed by using this configuration; and (3) understanding the development of flamefront instability and the effects of the flame curvature on the burning intensity

An Unsupervised Autoregressive Model for Speech Representation Learning

This paper proposes a novel unsupervised autoregressive neural model for learning generic speech representations. In contrast to other speech representation learning methods that aim to remove noise or speaker variabilities, ours is designed to preserve information for a wide range of downstream tasks. In addition, the proposed model does not require any phonetic or word boundary labels, allowing the model to benefit from large quantities of unlabeled data. Speech representations learned by our model significantly improve performance on both phone classification and speaker verification over the surface features and other supervised and unsupervised approaches. Further analysis shows that different levels of speech information are captured by our model at different layers. In particular, the lower layers tend to be more discriminative for speakers, while the upper layers provide more phonetic content.Comment: Accepted to Interspeech 2019. Code available at: https://github.com/iamyuanchung/Autoregressive-Predictive-Codin

Excited ionic and neutral fragments produced by dissociation of the N2(+)* H band

N I and N II fluorescent radiation was observed when N2 was irradiated by undispersed synchrotron radiation with an upper energy limit of approximately 200 eV. The excited fragments originate from dissociation of a band of excited ionic states of N2 lying between 34.7 and 44 eV