A national digital data policy for the United States: to be or not to be?

As countries worldwide are coming to terms with establishing a national data policy, the United States is approaching the issue in a piecemeal manner. With numerous federal, state and private agencies in control of funding, it is unlikely that a national policy will emerge for the United States in the near future. Regardless, efforts are moving forward on digital initiatives, including open access to scholarly publications, access to digital data-sets, creation of standards for data-set management, and national repositories for scanned images. Consortiums of research libraries such as the Committee on Institutional Cooperation (CIC), Association of Research Libraries (ARL), Coalition of Networked Information (CNI) and the Digital Library Federation (DLF) are facing these issues and assisting with definition of challenges and options. Several not-for-profit agencies are investigating ways in which they can participate, including OCLC, JSTOR, Portico and LOCKSS. Commercial firms such as Google are establishing partnerships with research libraries. Major federal funding agencies including the National Science Foundation and the National Institutes of Health have issued statements about the need for a digital policy. Federal agencies such as the National Archives and the Library of Congress are participating by actively managing massive amounts of data. Although there is activity on numerous fronts, there is no forum for a nationally concerted effort. While it is unlikely that a national policy on digital management will emerge in the United States, it is likely that within five to ten years a patch-work quilt of digital policies will emerge. This paper will explore issues faced by the scientific and technical disciplines and the collaborative approaches developing between the research and library communities to meet these challenges

Obtaining a Pure Protein Using an ELP-Tagged TEV Protease

We present here use of GLGVP for tagging and purifying a gadolinium binding protein domain.https://engagedscholarship.csuohio.edu/u_poster_2012/1027/thumbnail.jp

Obtaining a Pure Protein Using an ELP-Tagged TEV Protease

We present here use of GLGVP for tagging and purifying a gadolinium binding protein domain.https://engagedscholarship.csuohio.edu/u_poster_2012/1027/thumbnail.jp

A plan for spacecraft automated rendezvous

An automated rendezvous approach has been developed that utilizes advances in technology to reduce real-time/near real-time flight operations support personnel to an acceptable level that is near the minimum without jeopardizing the success of the mission. The on-board flight targeting uses a rule-based system to select the pursuit vehicle phasing orbits and uses precise navigation updates from the pursuit/target spacecraft made possible by the global positioning system receivers/processors on both spacecraft to adjust the phasing orbits and achieve rendezvous. The ascent-to-orbit targeting for the pursuit vehicle has been successfully decoupled from the on-orbit orbit transfer phasing targeting. Typical launch window data have been developed for the heavy lift launch vehicle and cargo transfer vehicle for a Space Station Freedom rendezvous mission

SSVEP-based BCI performance in children

The first contribution of this thesis is to show that children (9-11 years old) can achieve good performance when using a Brain-Computer Interface (BCI) based on the steady-state visually evoked potential (SSVEP). In our study, ten children (mean 9.9 years old) used an SSVEP-based BCI with a mean accuracy rate of 85.6% and a task completion rate of 97.5%. In contrast, a prior study of children (mean 9.8 years old) using an SSVEP-based BCI reported mean accuracy rates of between 50%-76% (depending on stimulation frequency) and a task completion rate of 59%. The second contribution of this thesis is to provide evidence that factors such as motivation or distraction may influence performance by children using SSVEP-based BCI more than the choice of stimulation frequency. Frequencies used by both our study (6-10Hz) and the prior study (7-11Hz) were similar. In contrast, our study asked children to play a computer game in a quiet environment, while the prior study asked children to perform text entry in a noisy environment. The game, which we developed and used for the first time in our study, is ``Brain Storm" --- it allows a single player to pretend to be a farmer protecting crops from malicious lightning clouds using the power of his or her brain. All participants in our study were asked both to complete a target selection task and to play the game. Our results show participants perform better when playing the game (88.6% accuracy rate) than when completing the target selection task (82.5% accuracy rate). Performance in both conditions was better than reported in the prior study (approximately 50% accuracy rate with the 7-11Hz frequency range)