LabAutomation 2006 - SLAS

MP19
Ismet Celebi
National Institute of Standards and Technology
Gaithersburg, Maryland
mail@ismet.net
Incorporating UnitsML into AnIML
LabAutomation2006
Co-Author(s)
Reinhold Schaefer
University of Applied Sciences Wiesbaden
Robert A. Dragoset
Gary W. Kramer
National Institute of Standards and Technology
Maintaining the integrity of analytical data over time is a challenge. Years ago, data were recorded on paper that was pasted directly
into a laboratory notebook. The digital age has made maintaining the integrity of data harder. Nowadays, digitized analytical data are
often separated from information about how the sample was collected and prepared for analysis and how the data were acquired. The
data are stored on digital media, while the related information about the data may be written in a paper notebook or stored separately in
other digital files. Sometimes the connection between this “scientific metadata” and the analytical data is lost, rendering the spectrum or
chromatogram useless. We have been working with ASTM Subcommittee E13.15 on Analytical Data to create the Analytical Information
Markup Language or AnIML — a new way to interchange and store spectroscopy and chromatography data based on XML (Extensible
Markup Language). XML is a language for describing what data are by enclosing them in computer-useable tags. Recording the units
associated with the analytical data and metadata is an essential issue for any data representation scheme that must be addressed by all
domain-specific markup languages. As scientific markup languages proliferate, it is very desirable to have a single scheme for handling
units to facilitate moving information between different data domains. At NIST, we have been developing a general markup language just for
units that we call UnitsML. This presentation will describe how UnitsML is used and how it is being incorporated into AnIML.
MP20
Changhoon Chai
Rutgers University
New Brunswick, New Jersey
chchai@eden.rutgers.edu
Co-Author(s)
Paul Takhistov
Rutgers University, The State University of New Jersey
Smart Automated System for the Assessment of Biosensor’s Performance
The portable, quick, and automatic multi-sensing system for biological agent is regarded necessary as the concern of public. However
current detection techniques cannot be applied to the field since they are based on large instruments or highly skilled manipulation. The
detection system can be developed when electrochemical impedance analysis (EIA) is employed as biosensor’s signal transducer however
the absence of appropriate technique to associate antibody onto biosensor’s surface and the lack of understanding of the electrochemical
dynamics at the interface of biosensor are the bottleneck to develop. We propose the smart automated system for the assessment of
biosensor’s performance, able to accelerate evolution of biosensing technology to be applied for environmental and biological samples
with complex matrix (human clinical samples, foods, and beverages). We’ve succeeded to detect 0.1ng/ml of Staphylococcus aureus
Enterotoxin B (SEB) with new impedimetric bioosensor. To achieve the high sensitivity, aluminum, the module of signal transducer,
was fabricated electrochemically in nano-scale as well as the technique to associate anti-SEB on nano-porous aluminum surface was
developed. The biosensor differentiated SEB and anti-SEB reaction at the specific AC frequency (30-100kHz) in 20min. The dynamics
of multi-analyte and the algorithm to differentiate multiplexed signals are being studied to establish the basis of automated multi-target
biosensor. Developed algorithm will allow the automation of the impedimetric multi-biosensor, the evaluation of individual sensor’s
performance, and the improvement of reliability. LabView based software will allow to perform 4D (electrical amplitude, phase angle,
frequency, and time) chemical screening of target analysts.
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