Analysis of Shear Lag in Steel Angle Connectors

Previous research has found an empirically based method for calculating the effective net area defined by stress distributions created by tensile loads in steel connections. Based on the results from that method a theoretical alternative is explored to simplify the process of determining the effective net area

Applied Error Related Negativity: Single Electrode Electroencephalography in Complex Visual Stimuli

Error related negativity (ERN) is a pronounced negative evoked response potential (ERP) that follows a known error. This neural pattern has the potential to communicate user awareness of incorrect actions within milliseconds. While the implications for human-machine interface and augmented cognition are exciting, the ERN has historically been evoked only in the laboratory using complex equipment while presenting simple visual stimuli such as letters and symbols. To effectively harness the applied potential of the ERN, detection must be accomplished in complex environments using simple, preferably single-electrode, EEG systems feasible for integration into field and workplace-ready equipment. The present project attempted to use static photographs to evoke and successfully detect the ERN in a complex visual search task: motorcycle conspicuity. Drivers regularly fail to see motorcycles, with tragic results. To reproduce the issue in the lab, static pictures of traffic were presented, either including or not including motorcycles. A standard flanker letter task replicated from a classic ERN study (Gehring et al., 1993) was run alongside, with both studies requiring a binary response. Results showed that the ERN could be clearly detected in both tasks, even when limiting data to a single electrode in the absence of artifact correction. These results support the feasibility of applied ERN detection in complex visual search in static images. Implications and opportunities will be discussed, limitations of the study explained, and future directions explored

Estimation and uncertainty of reversible Markov models

Reversibility is a key concept in Markov models and Master-equation models of molecular kinetics. The analysis and interpretation of the transition matrix encoding the kinetic properties of the model relies heavily on the reversibility property. The estimation of a reversible transition matrix from simulation data is therefore crucial to the successful application of the previously developed theory. In this work we discuss methods for the maximum likelihood estimation of transition matrices from finite simulation data and present a new algorithm for the estimation if reversibility with respect to a given stationary vector is desired. We also develop new methods for the Bayesian posterior inference of reversible transition matrices with and without given stationary vector taking into account the need for a suitable prior distribution preserving the meta- stable features of the observed process during posterior inference. All algorithms here are implemented in the PyEMMA software - http://pyemma.org - as of version 2.0

Microwave state transfer and adiabatic dynamics of magnetically trapped polar molecules

Cold and ultracold polar molecules with nonzero electronic angular momentum are of great interest for studies in quantum chemistry and control, investigations of novel quantum systems, and precision measurement. However, in mixed electric and magnetic fields, these molecules are generically subject to a large set of avoided crossings among their Zeeman sublevels; in magnetic traps, these crossings lead to distorted potentials and trap loss from electric bias fields. We have characterized these crossings in OH by microwave-transferring trapped OH molecules from the upper |f; M = +3/2> parity state to the lower |e; +3/2> state and observing their trap dynamics under an applied electric bias field. Our observations are very well described by a simple Landau-Zener model, yielding insight to the rich spectra and dynamics of polar radicals in mixed external fields.Comment: 5 pages, 4 figures plus supplementary materia

Magneto-electrostatic trapping of ground state OH molecules

We report the magnetic confinement of neutral, ground state hydroxyl radicals (OH) at a density of $\sim3\times10^{3}$ cm$^{-3}$ and temperature of $\sim$30 mK. An adjustable electric field of sufficient magnitude to polarize the OH is superimposed on the trap in either a quadrupole or homogenous field geometry. The OH is confined by an overall potential established via molecular state mixing induced by the combined electric and magnetic fields acting on the molecule's electric dipole and magnetic dipole moments, respectively. An effective molecular Hamiltonian including Stark and Zeeman terms has been constructed to describe single molecule dynamics inside the trap. Monte Carlo simulation using this Hamiltonian accurately models the observed trap dynamics in various trap configurations. Confinement of cold polar molecules in a magnetic trap, leaving large, adjustable electric fields for control, is an important step towards the study of low energy dipole-dipole collisions.Comment: 4 pages, 4 figure

Toward an Antiphony Framework for Dividing Tasks into Subtasks

Task analysis is a staple of ergonomics, neuroergonomics, human factors, and experimental psychology inquiry, and often benefits from granularity beyond the task level to the subtask level. The concept and challenge of identifying the subcomponents of tasks are neither new, nor solved. Practitioners routinely identify individually internally consistent and yet conflicting subdivisions. The challenge of producing reliable, valid subtask data across efforts recommends a unified framework for identifying consistent subtask divisions within tasks. A framework is here forwarded, based upon universal “antiphony” turn-taking behavior in human-human interaction, but adapted to address the highly scripted vocabulary of human-machine interaction. Practical application to a real-world vehicle interface is demonstrated, an example discussed in the light of research design, applied use, and future improvement

Effects of Signal Probability on Multitasking-Based Distraction in Driving, Cyberattack & Battlefield Simulation

Multitasking-based failures of perception and action are the focus of much research in driving, where they are attributed to distraction. Similar failures occur in contexts where the construct of distraction is little used. Such narrow application was attributed to methodology which cannot precisely account for experimental variables in time and space, limiting distraction\u27s conceptual portability to other contexts. An approach based upon vigilance methodology was forwarded as a solution, and highlighted a fundamental human performance question: Would increasing the signal probability (SP) of a secondary task increase associated performance, as is seen in the prevalence effect associated with vigilance tasks? Would it reduce associated performance, as is seen in driving distraction tasks? A series of experiments weighed these competing assumptions. In the first, a psychophysical task, analysis of accuracy and response data revealed an interaction between the number of concurrent tasks and SP of presented targets. The question was further tested in the applied contexts of driving, cyberattack and battlefield target decision-making. In line with previous prevalence effect inquiry, presentation of stimuli at higher SP led to higher accuracy. In line with existing distraction work, performance of higher numbers of concurrent tasks tended to elicit slower response times. In all experiments raising either number of concurrent tasks or SP of targets resulted in greater subjective workload, as measured by the NASA TLX, even when accompanied by improved accuracy. It would seem that distraction in previous experiments has been an aggregate effect including both delayed response time and prevalence-based accuracy effects. These findings support the view that superior experimental control of SP reveals nomothetic patterns of performance that allow better understanding and wider application of the distraction construct both within and in diverse contexts beyond driving

Low-energy molecular collisions in a permanent magnetic trap

Cold, neutral hydroxyl radicals are Stark decelerated and confined within a magnetic trap consisting of two permanent ring magnets. The OH molecules are trapped in the ro-vibrational ground state at a density of $\sim10^{6}$ cm$^{-3}$ and temperature of 70 mK. Collisions between the trapped OH sample and supersonic beams of atomic He and molecular D$_{2}$ are observed and absolute collision cross sections measured. The He--OH and D$_{2}$--OH center-of-mass collision energies are tuned from 60 cm$^{-1}$ to 230 cm$^{-1}$ and 145 cm$^{-1}$ to 510 cm$^{-1}$, respectively, yielding evidence of reduced He--OH inelastic cross sections at energies below 84 cm$^{-1}$, the OH ground rotational level spacing.Comment: 4 pages, 4 figure

Panel: Interdisciplinary Paradigms for IS Education: The Information School

Education for the information profession is in a state of radical change and re-design. Academic units are being reorganized around new interdisciplinary paradigms, while new curriculums are being developed to address the needs of a growing and diverse information profession. Existing schools, which offer multiple information degrees and are based upon interdisciplinary models, such as Syracuse, Pittsburgh, Drexel and Rutgers universities have been or are now joined by others, such as the University of Michigan and the University of California at Berkeley. Plans are in place to create new “information schools” at Penn State, Indiana University, UNC Charlotte, and other universities. New information colleges are being considered from the University of Arizona to the University of Rhode Island - and many points between

OH hyperfine ground state: from precision measurement to molecular qubits

We perform precision microwave spectroscopy--aided by Stark deceleration--to reveal the low magnetic field behavior of OH in its ^2\Pi_{3/2} ro-vibronic ground state, identifying two field-insensitive hyperfine transitions suitable as qubits and determining a differential Lande g-factor of 1.267(5)\times10^{-3} between opposite parity components of the \Lambda-doublet. The data are successfully modeled with an effective hyperfine Zeeman Hamiltonian, which we use to make a tenfold improvement of the magnetically sensitive, astrophysically important \Delta F=\pm1 satellite-line frequencies, yielding 1720529887(10) Hz and 1612230825(15) Hz.Comment: 4+ pages, 3 figure