Vacuum arc plasma thrusters with inductive energy storage driver

An apparatus for producing a vacuum arc plasma source device using a low mass, compact inductive energy storage circuit powered by a low voltage DC supply acts as a vacuum arc plasma thruster. An inductor is charged through a switch, subsequently the switch is opened and a voltage spike of Ldi/dt is produced initiating plasma across a resistive path separating anode and cathode. The plasma is subsequently maintained by energy stored in the inductor. Plasma is produced from cathode material, which allows for any electrically conductive material to be used. A planar structure, a tubular structure, and a coaxial structure allow for consumption of cathode material feed and thereby long lifetime of the thruster for long durations of time

\u3ci\u3eA\u3c/i\u3e-Optimality for Active Learning of Logistic Regression Classifiers

Over the last decade there has been growing interest in pool-based active learning techniques, where instead of receiving an i.i.d. sample from a pool of unlabeled data, a learner may take an active role in selecting examples from the pool. Queries to an oracle (a human annotator in most applications) provide label information for the selected observations, but at a cost. The challenge is to end up with a model that provides the best possible generalization error at the least cost. Popular methods such as uncertainty sampling often work well, but sometimes fail badly. We take the A-optimality criterion used in optimal experimental design, and extend it so that it can be used for pool-based active learning of logistic regression classifiers. A-optimality has attractive theoretical properties, and empirical evaluation confirms that it offers a more robust approach to active learning for logistic regression than alternatives

Change management: The case of the elite sport performance team

The effective and efficient implementation of change is often required for both successful performance and management survival across a host of contemporary domains. However, although of major theoretical and practical significance, research to date has overlooked the application of change management (hereafter CM) knowledge to the elite sport performance team environment. Considering that the success of ‘off-field’ sports businesses are largely dependent on the performances of their ‘on-field’ team, this article explores the application of current CM theorizing to this specific setting and the challenges facing its utility. Accordingly, we identify the need and importance of developing theory specific to this area, with practical application in both sport and business, through examination of current knowledge and identification of the domain's unique, dynamic and contested properties. Markers of successful change are then suggested to guide initial enquiry before the article concludes with proposed lines of research which may act to provide a valid and comprehensive theoretical account of CM to optimize the research and practice of those working in the field

Linguistics

Contains research summary and abstracts for nine theses

Culture change in elite sport performance teams: Examining and advancing effectiveness in the new era

Reflecting the importance of optimizing culture for elite teams, Fletcher and Arnold (2011) recently suggested the need for expertise in culture change. Acknowledging the dearth of literature on the specific process, however, the potential effectiveness of practitioners in this area is unknown. The present paper examines the activity's precise demands and the validity of understanding in sport psychology and organizational research to support its delivery. Recognizing that sport psychologists are being increasingly utilized by elite team management, initial evidence-based guidelines are presented. Finally, to stimulate the development of ecologically valid, practically meaningful knowledge, the paper identifies a number of future research directions

Energy spread of ultracold electron bunches extracted from a laser cooled gas

Ultrashort and ultracold electron bunches created by near-threshold femtosecond photoionization of a laser-cooled gas hold great promise for single-shot ultrafast diffraction experiments. In previous publications the transverse beam quality and the bunch length have been determined. Here the longitudinal energy spread of the generated bunches is measured for the first time, using a specially developed Wien filter. The Wien filter has been calibrated by determining the average deflection of the electron bunch as a function of magnetic field. The measured relative energy spread $\frac{\sigma_{U}}{U} = 0.64 \pm 0.09\%$ agrees well with the theoretical model which states that it is governed by the width of the ionization laser and the acceleration length

PennAspect: Two-Way Aspect Model Implementation

The two-way aspect model is a latent class statistical mixture model for performing soft clustering of co-occurrence data observations. It acts on data such as document/word pairs (words occurring in documents) or movie/people pairs (people see certain movies) to produce their joint distribution estimate. This document describes our software immplementation of the aspect model available under GNU Public License (included with the distribution). We call this package PennAspect. The distribution is packaged as Java source and class files. The software comes with no guarantees of any kind. We welcome user feedback and comments. To download PennAspect, visit: http://www.cis.upenn.edu/datamining/software_dist/PennAspect/index.html

Bayesian Example Selection Using BaBiES

Active learning is widely used to select which examples from a pool should be labeled to give best results when learning predictive models. It is, however, sometimes desirable to choose examples before any labeling or machine learning has occurred. The optimal experimental design literature has many theoretically attractive optimality criteria for example selection, but most are intractable when working with large numbers of predictive features. We present the BaBiES criterion, an approximation of Bayesian A-optimal design for linear regression using binary predictors, which is both simple and extremely fast. Empirical evaluations demonstrate that, in spite of selecting all examples prior to learning, BaBiES is competitive with standard active learning methods for a variety of document classification tasks

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts