Erik Satie’s Socrate (1918), Myths of Marsyas, and un style dépouillé

In arguing that underneath the placid, 'stripped-down' style of Socrate there lurks a hidden violence, this essay does not focus on Satie's compositional process, documented in his notebooks; instead, it examines Socrate's performance history and the creation of the work's libretto, which the composer completed before sketching his musical ideas. Satie's novel selection and setting of the text is critical to this reading. The author examines how Satie reinterprets the violent myth of Marsyas and Apollo in the first movement, and how he ruminates on Socrates's dying words in the last movement. Understanding the ideas and events that led to the creation of Satie's enigmatic masterpiece allows us to view Socrate's portrayal of Plato's dialogues as part of a project of dépouillement, a neoclassical aesthetic that sought to strip down musical material in favor of an ascetic aesthetic uniting musical and moral Hellenism. This reading of Socrate allows us to reexamine the early 20th-century style dépouillé and to place Socrate at the center of debates on Socrates, Hellenism, and morality

Building a Generation Knowledge Source using Internet-Accessible Newswire

In this paper, we describe a method for automatic creation of a knowledge source for text generation using information extraction over the Internet. We present a prototype system called PROFILE which uses a client-server architecture to extract noun-phrase descriptions of entities such as people, places, and organizations. The system serves two purposes: as an information extraction tool, it allows users to search for textual descriptions of entities; as a utility to generate functional descriptions (FD), it is used in a functional-unification based generation system. We present an evaluation of the approach and its applications to natural language generation and summarization.Comment: 8 pages, uses eps

Mediation and peace

This paper applies mechanism design to conflict resolution. We determine when and how unmediated communication and mediation reduce the ex ante probability of conflict in a game with asymmetric information. Mediation improves upon unmediated communication when the intensity of conflict is high, or when asymmetric information is significant. The mediator improves upon unmediated communication by not precisely reporting information to conflicting parties, and precisely, by not revealing to a player with probability one that the opponent is weak. Arbitrators who can enforce settlements are no more effective than mediators who only make non-binding recommendations

Toward an integrative understanding of social behavior: new models and new opportunities.

Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur

Uncertainties in Dielectronic Recombination Rate Coefficients: Effects on Solar and Stellar Upper Atmosphere Abundance Determinations

We have investigated how the relative elemental abundances inferred from the solar upper atmosphere are affected by uncertainties in the dielectronic recombination (DR) rate coefficients used to analyze the spectra. We find that the inferred relative abundances can be up to a factor of ~5 smaller or ~1.6 times larger than those inferred using the currently recommended DR rate coefficients. We have also found a plausible set of variations to the DR rate coefficients which improve the inferred (and expected) isothermal nature of solar coronal observations at heights of >~ 50 arcsec off the solar limb. Our results can be used to help prioritize the enormous amount of DR data needed for modeling solar and stellar upper atmospheres. Based on the work here, our list of needed rate coefficients for DR onto specific isoelectronic sequences reads, in decreasing order of importance, as follows: O-like, C-like, Be-like, N-like, B-like, F-like, Li-like, He-like, and Ne-like. It is our hope that this work will help to motivate and prioritize future experimental and theoretical studies of DR.Comment: 33 pages, including 3 figures and 4 tables. To be published in Ap

Automatic Classification of Text Databases through Query Probing

Many text databases on the web are "hidden" behind search interfaces, and their documents are only accessible through querying. Search engines typically ignore the contents of such search-only databases. Recently, Yahoo-like directories have started to manually organize these databases into categories that users can browse to find these valuable resources. We propose a novel strategy to automate the classification of search-only text databases. Our technique starts by training a rule-based document classifier, and then uses the classifier's rules to generate probing queries. The queries are sent to the text databases, which are then classified based on the number of matches that they produce for each query. We report some initial exploratory experiments that show that our approach is promising to automatically characterize the contents of text databases accessible on the web.Comment: 7 pages, 1 figur

Cryogenic micro-calorimeters for mass spectrometric identification of neutral molecules and molecular fragments

We have systematically investigated the energy resolution of a magnetic micro-calorimeter (MMC) for atomic and molecular projectiles at impact energies ranging from $E\approx13$ to 150 keV. For atoms we obtained absolute energy resolutions down to $\Delta E \approx 120$ eV and relative energy resolutions down to $\Delta E/E\approx10^{-3}$. We also studied in detail the MMC energy-response function to molecular projectiles of up to mass 56 u. We have demonstrated the capability of identifying neutral fragmentation products of these molecules by calorimetric mass spectrometry. We have modeled the MMC energy-response function for molecular projectiles and conclude that backscattering is the dominant source of the energy spread at the impact energies investigated. We have successfully demonstrated the use of a detector absorber coating to suppress such spreads. We briefly outline the use of MMC detectors in experiments on gas-phase collision reactions with neutral products. Our findings are of general interest for mass spectrometric techniques, particularly for those desiring to make neutral-particle mass measurements

Lagrangian space consistency relation for large scale structure

Consistency relations, which relate the squeezed limit of an (N+1)-point correlation function to an N-point function, are non-perturbative symmetry statements that hold even if the associated high momentum modes are deep in the nonlinear regime and astrophysically complex. Recently, Kehagias & Riotto and Peloso & Pietroni discovered a consistency relation applicable to large scale structure. We show that this can be recast into a simple physical statement in Lagrangian space: that the squeezed correlation function (suitably normalized) vanishes. This holds regardless of whether the correlation observables are at the same time or not, and regardless of whether multiple-streaming is present. The simplicity of this statement suggests that an analytic understanding of large scale structure in the nonlinear regime may be particularly promising in Lagrangian space.Comment: 19 pages, no figure

Synaptic state matching: a dynamical architecture for predictive internal representation and feature perception

Here we consider the possibility that a fundamental function of sensory cortex is the generation of an internal simulation of sensory environment in real-time. A logical elaboration of this idea leads to a dynamical neural architecture that oscillates between two fundamental network states, one driven by external input, and the other by recurrent synaptic drive in the absence of sensory input. Synaptic strength is modified by a proposed synaptic state matching (SSM) process that ensures equivalence of spike statistics between the two network states. Remarkably, SSM, operating locally at individual synapses, generates accurate and stable network-level predictive internal representations, enabling pattern completion and unsupervised feature detection from noisy sensory input. SSM is a biologically plausible substrate for learning and memory because it brings together sequence learning, feature detection, synaptic homeostasis, and network oscillations under a single parsimonious computational framework. Beyond its utility as a potential model of cortical computation, artificial networks based on this principle have remarkable capacity for internalizing dynamical systems, making them useful in a variety of application domains including time-series prediction and machine intelligence

Latent demographic profile estimation in hard-to-reach groups

The sampling frame in most social science surveys excludes members of certain groups, known as hard-to-reach groups. These groups, or subpopulations, may be difficult to access (the homeless, e.g.), camouflaged by stigma (individuals with HIV/AIDS), or both (commercial sex workers). Even basic demographic information about these groups is typically unknown, especially in many developing nations. We present statistical models which leverage social network structure to estimate demographic characteristics of these subpopulations using Aggregated relational data (ARD), or questions of the form "How many X's do you know?" Unlike other network-based techniques for reaching these groups, ARD require no special sampling strategy and are easily incorporated into standard surveys. ARD also do not require respondents to reveal their own group membership. We propose a Bayesian hierarchical model for estimating the demographic characteristics of hard-to-reach groups, or latent demographic profiles, using ARD. We propose two estimation techniques. First, we propose a Markov-chain Monte Carlo algorithm for existing data or cases where the full posterior distribution is of interest. For cases when new data can be collected, we propose guidelines and, based on these guidelines, propose a simple estimate motivated by a missing data approach. Using data from McCarty et al. [Human Organization 60 (2001) 28-39], we estimate the age and gender profiles of six hard-to-reach groups, such as individuals who have HIV, women who were raped, and homeless persons. We also evaluate our simple estimates using simulation studies.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS569 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org