Christopher Lee - US grants

The goal of the Sutter graph database architecture is to help biologists make sense of the human genome, by enabling them to search genome sequence alignments for patterns of functional and structural relationships between genes. Sequence alignments are the key for discovering meaningful connections between diverse biological data, to make sense of the completed Human Genome. Yet no current database is designed to query detailed sequence alignment relationships as is needed. The Sutter architecture is designed to provide a fast, flexible, and intuitive query system for genomic alignment data, based on storing the entire graph database in a set of indexes, enabling direct lookup for any item to find its relationships. By focusing on indexing, Sutter can move away from the fixed, inflexible schema (table structure) of relational systems, while retaining some of the basis of their speed. A major design goal of Sutter is to implement genomic data objects efficiently, enabling it to store a full genome database in RAM, and achieve dramatically faster query performance. Sutter's first application is to serve the genome research community as an online resource for mining single-nucleotide polymorphisms, their effects on protein function, and mapping disease genes.

This NSF MRI award funds the acquisition of a hyper-frequency viscoelastic
spectroscopy (HFVS) instrument for materials characterization. It is especially well suited for
measuring viscoelastic properties of biological tissues and artificial polymers because it can
make non-contacting, non-destructive measurements on small-sized samples over a wide
excitation frequency range. The HFVS instrument will be immediately used in five current
research projects: 1) computational simulation of traumatic brain injury; 2) determining the role
of active and passive forces in microvascular network formation; 3) dynamic characterization of
underactuated legged locomotion, 4) design and fabrication of perching landing gear for microaerial
vehicles, and 5) characterization of a biodegradable, biocompatible co-polymer. The most
significant contribution resulting from use of the instrument on each project is: 1) constitutive
models for human brain tissue at high strain rates appropriate for blast-response simulation and
analysis; 2) characterization of a new extra-cellular matrix biomimetics for studying the effects
of both active and passive mechanical environments on cells, 3) material-tunable, dynamic
models of underactuated legged locomotion for milli-scale robots, 4) tunable-stiffness and ?
damping, polymer fabrication processes for perching landing gear mechanisms, and 5)
manufacturing processes for controlling the properties of a class of environmentally-friendly, copolymers
for medical applications. In addition to supporting ongoing research, the instrument
will enable future research involving related materials and will open new research areas in
bioengineering, material science, and mechanical engineering

The HFVS instrument will substantially enhance metrology capabilities at Olin College enabling
the characterization of materials ranging in stiffness from very compliant, nearly liquid (e.g.,
gels) to very rigid by quantitative measurement of mechanical stiffness and energy dissipation
related properties. The characterization of materials plays an integral part in a wide range of
research problems especially those including computer simulations and the custom design and
manufacturing of components or structures involving the given materials. The acquisition of a
HFVS instrument will have significant positive impact on Olin College?s research capability,
undergraduate research training efforts, and curriculum. The instrument will directly support the
training and education of undergraduates at Olin College where approximately 45% of students
and 55% of the bioengineering, material science, and mechanical engineering majors are women.
Research training is incorporated throughout the curriculum directly into project-based and
laboratory-based coursework. Students have numerous individual research opportunities to work
with faculty during the academic year and in the summer. The instrument will be specifically
utilized in a number of courses and will be particularly useful in the senior-year, engineering
capstone course in which student teams tackle industry-sponsored projects.

DESCRIPTION (provided by applicant): The proposed project will create online services, teaching materials sharing, and training for instructors and students to 1) expand and tailor Big Data To Knowedge (BD2K) learning for new audiences in bioinformatics, medical informatics and biomedical applications; 2) use active- learning to greatly increase conceptual understanding and real-world problem-solving ability; 3) directly measure learning effectiveness; and 4) boost the number of students that successfully complete BD2K courses. Tailoring the core concepts for BD2K success to teach diverse biomedical audiences is crucial both because these interdisciplinary concepts are a key barrier to entry, and because they are vital for real-world BD2K problem-solving ability. The UCLA/UCSD project team will: 1) provide an open, online repository where BD2K instructors worldwide can find, author, and share peer-reviewed active-learning exercises such as concept tests (already over 600), and immediately use them in class (with students answering with their smartphones or laptops); 2) catalyze the development, usage and validation of candidate BD2K concept inventories for rigorously measuring learning gains, via an accelerated approach of open- response concept testing and online data collection; 3) provide BD2K instructors a collaborative, peer-reviewed sharing and remixing platform for active-learning materials such as algorithm projects, hands-on data mining projects (via convenient cloud projects), exercises and problems, as well as courselet recording tools that automatically record video and audio on the instructor's laptop while they teach; 4) provide students anywhere free online courselets each about one key BD2K concept, consisting of brief videos tightly integrated with concept tests and all the active- learning exercises described above, and designed as an online persistent-learning community unified by concepts, in which students learn from the community's consolidated error models (common errors for a specific BD2K concept), effective remediations and counter-examples for each error model. Testing of this instructional approach for 3 years has doubled successful student completions of a BD2K methods course at UCLA, by reducing attrition, while simultaneously increasing conceptual understanding (mean exam scores). This approach will also be disseminated by: 1) pilot projects with BD2K instructors at UCLA and partner institutions, with detailed evaluation studies to identify critical success factors; 2) workshops (both online and onsite) for training instructors how to teach effectively with these tools in their BD2K courses; 3 online services and courselets.

This project, developing CyberCANOE (Cyber-enabled Collaboration Analysis Navigation and Observation Environment), aims to serve as an eyepiece, providing researchers with powerful and easy-to-use information-rich instrumentation in support of cyberinfrastructure-enabled data-intensive scientific discovery. CyberCANOE will provide users with the ability to see both 2D and 3D stereoscopic content in a completely seamless display environment with almost 50 Megapixels of resolution.

CyberCANOE provides a unique alternative approach to constructing ultra-resolution display environments by using new and completely seamless direct view Light Emitting Diode displays, rather than traditional projection technologies or Liquid Crystal Displays. The net effect is a visual instrument that exceeds the capabilities and overcomes the limitations of the current best-in-class systems such as the CAVE2 at EVL and the WAVE at CALIT2 at UC San Diego. Immediately 46 researchers, 28 postdocs, 833 undergraduates, 45 graduate students spanning disciplines that include Oceanography, Astrobiology, Mathematics, Computer Science, Electrical Engineering, Biomedical Research, Archeology, and Computational Media are poised to use the CyberCANOE for their large-scale data visualization needs. The instrument opens up new opportunities in computer science research at the intersection of data-intensive analysis and visualization, human-computer interaction, and virtual reality. It enables the Laboratory for Advanced Visualization and Applications (LAVA) at the University of Hawaii at Manoa (UHM), to provide an EPSCoR and Native Hawaiian Serving Institution, with state-of-the-art equipment, opportunities, and supervision to enhance undergraduate and graduate research and education; to provide scientific communities with highly integrated visually rich collaboration environments; to work with industry to facilitate the creation of new technologies for the advancement of science and engineering; and to continue ongoing partnerships with many of the worlds best domain scientists and computer scientists in academia and industry, who readily become early adopters of new instrumentation, and who provide students with summer internships and jobs upon graduation.

PI: Chen, Kai Loon
#: 1605815
COLLABORATIVE
PI: Aravamudhan, Shyam
#: 1604647

Chemical Mechanical Planarization (CMP) is one of the important semiconductor manufacturing processes used in the production of advanced electronic devices such as computers, smart phones, and tablets. The CMP process uses huge volumes (millions of tons) of silica, ceria, or alumina particles in the form of abrasive slurries to planarize electronic circuits during the manufacturing process. However, environmental safety and health (ESH) impacts from the release of used CMP slurries containing nanoparticles into the natural environment and workplace exposure are largely unknown. The objective of this research is to study the ESH impacts and interactions of both pristine and used CMP nanoparticles with artificial cell membranes and human cell lines.

Even though NPs are used in a large-scale in the CMP process during the manufacture of integrated circuits, little is known about their environmental and human health impacts, particularly the transformation of nanoparticles during the CMP process and their corresponding workplace exposure, fate, behavior, and toxicity. This is mainly due to the inability to obtain access to the transformed nanoparticle slurries from the CMP process. The main objectives of this project are to (1) systematically investigate, detect, and characterize the transformation of nanoparticle slurries during the CMP processes; (2) examine the influence of CMP and incidental nanoparticles to attach to and disrupt artificial cell membranes and their ability to affect human cell lines; and (3) determine the role of nanoparticle-membrane interactions on nanoparticle toxicity.

This research has the potential to be transformative because a strong understanding of the biological interactions of pristine and transformed CMP NPs is not only relevant to the electronics industry, but also has wider applicability for a number of other nanoparticle applications, which routinely undergo life-cycle transformations through different physical and chemical processes. The research results will be disseminated through publications in peer-reviewed journals and student presentations at national scientific meetings. They will also be incorporated into undergraduate and graduate courses and community outreach programs, including K-12 scientific activities for an inner-city Baltimore elementary/middle school, NanoDay activities for the local community, NanoBus after-school program, and community college engagement. Lastly, the active involvement of an industrial partner will result in implementation of better engineering controls and safer CMP processes.