Mass spectrometer with magnetic pole pieces providing the magnetic fields for both the magnetic sector and an ion-type vacuum pump

A mass spectrometer (MS) with unique magnetic pole pieces which provide a homogenous magnetic field across the gap of the MS magnetic sector as well as the magnetic field across an ion-type vacuum pump is disclosed. The pole pieces form the top and bottom sides of a housing. The housing is positioned so that portions of the pole pieces form part of the magnetic sector with the space between them defining the gap region of the magnetic sector, through which an ion beam passes. The pole pieces extend beyond the magnetic sector with the space between them being large enough to accommodate the electrical parts of an ion-type vacuum pump. The pole pieces which provide the magnetic field for the pump, together with the housing form the vacuum pump enclosure or housing

Mission to a comet - Preliminary scientific objectives and experiments for use in advanced mission studies

Scientific objectives and experiments for comet missio

Computations in the social brain

This thesis consists of three empirical chapters that investigate elements of human social behavior, adherence to and violations of social norms, and the computational and neurological underpinnings thereof. I focus on three behavioral paradigms in particular – the attacker-defender contest, the trust game, and the ultimatum game – which model asymmetrical conflicts, generosity and reciprocity, and norms of fairness, respectively. Ultimately, each chapter acts as a building block contributing a different perspective to the study of human sociality. Using economic games, computational models based on the principle of utility, and model-based neuroimaging, my research contributes to the scientific endeavor working to crack the “elaborate and secret code that is written nowhere, known by none, and understood by all” (Sapir, 1927, p.137)Social decision makin

Complexity Characterization in a Probabilistic Approach to Dynamical Systems Through Information Geometry and Inductive Inference

Information geometric techniques and inductive inference methods hold great promise for solving computational problems of interest in classical and quantum physics, especially with regard to complexity characterization of dynamical systems in terms of their probabilistic description on curved statistical manifolds. In this article, we investigate the possibility of describing the macroscopic behavior of complex systems in terms of the underlying statistical structure of their microscopic degrees of freedom by use of statistical inductive inference and information geometry. We review the Maximum Relative Entropy (MrE) formalism and the theoretical structure of the information geometrodynamical approach to chaos (IGAC) on statistical manifolds. Special focus is devoted to the description of the roles played by the sectional curvature, the Jacobi field intensity and the information geometrodynamical entropy (IGE). These quantities serve as powerful information geometric complexity measures of information-constrained dynamics associated with arbitrary chaotic and regular systems defined on the statistical manifold. Finally, the application of such information geometric techniques to several theoretical models are presented.Comment: 29 page

The role of knowledge structures in fault diagnosis

The use of human memory and knowledge structures to direct fault diagnosis performance was investigated. The performances of 20 pilots with instrument flight ratings were studied in a fault diagnosis task. The pilots were read a scenario which described flight conditions under which the symptoms which are indicative of a problem were detected. They were asked to think out loud as they requested and interpreted various pieces of information to diagnose the cause of the problem. Only 11 of the 20 pilots successfully diagnosed the problem. Pilot performance on this fault diagnosis task was modeled in the use of domain specific knowledge organized in a frame system. Eighteen frames, with a common structure, were necessary to account for the data from all twenty subjects

Neurocognitive Underpinnings of Aggressive Predation in Economic Contests

Competitions are part and parcel of daily life and require people to invest time and energy to gain advantage over others and to avoid (the risk of) falling behind. Whereas the behavioral mechanisms underlying competition are well documented, its neurocognitive underpinnings remain poorly understood. We addressed this using neuroimaging and computational modeling of individual investment decisions aimed at exploiting one's counterpart (“attack”) or at protecting against exploitation by one's counterpart (“defense”). Analyses revealed that during attack relative to defense (i) individuals invest less and are less successful; (ii) computations of expected reward are strategically more sophisticated (reasoning level k = 4 vs. k = 3 during defense); (iii) ventral striatum activity tracks reward prediction errors; (iv) risk prediction errors were not correlated with neural activity in either ROI or whole-brain analyses; and (v) successful exploitation correlated with neural activity in the bilateral ventral striatum, left OFC, left anterior insula, left TPJ, and lateral occipital cortex. We conclude that, in economic contests, coming out ahead (vs. not falling behind) involves sophisticated strategic reasoning that engages both reward and value computation areas and areas associated with theory of mind

Professional Development Needs for Educators Working with Children with Autism Spectrum Disorders in Inclusive School Environments

The primary objective of this mixed methods study was to identify educators’ professional development needs to determine how best to support them in providing quality programming for children with Autism Spectrum Disorders (ASD) within an inclusive educational system. Information was collected through focus groups with key school board informants (n = 33) and a survey of educators (n = 225). The results indicate that educators have found it difficult to meet the wide-ranging and varying needs of children with ASD within a strictly defined model of inclusive education. Educators consistently emphasized the need for multileveled and multipronged professional development that is accessible in a timely fashion and available as needs arise. The need for educational programs that work for children with ASD being taught within inclusive education settings is highlighted

Lessons about likelihood functions from nuclear physics

Least-squares data analysis is based on the assumption that the normal (Gaussian) distribution appropriately characterizes the likelihood, that is, the conditional probability of each measurement d, given a measured quantity y, p(d | y). On the other hand, there is ample evidence in nuclear physics of significant disagreements among measurements, which are inconsistent with the normal distribution, given their stated uncertainties. In this study the histories of 99 measurements of the lifetimes of five elementary particles are examined to determine what can be inferred about the distribution of their values relative to their stated uncertainties. Taken as a whole, the variations in the data are somewhat larger than their quoted uncertainties would indicate. These data strongly support using a Student t distribution for the likelihood function instead of a normal. The most probable value for the order of the t distribution is 2.6 +/- 0.9. It is shown that analyses based on long-tailed t-distribution likelihoods gracefully cope with outlying data.Comment: presented at 27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (Maxent 2007), 10 pages, 12 figure