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作者： McCormack, Jay Beyerlein, Steve Davis, Denny Trevisan, Michael Lebeau, Jennifer Davis, Howard Howe, Susannah Brackin, Patricia Thompson, Phillip Gerlick, Robert Javed Khan, M. Leiffer, Paul Mechanical Engineering Department University of Idaho Moscow ID 83844-0902 United States Voiland School of Chemical Engineering and Bioengineering Washington State University Pullman WA 99164-2710 United States College of Education Washington State University Pullman WA 99164-2114 United States College of Education Washington State University Pullman WA 99164-2136 United States Picker Engineering Program Smith College Northampton MA 01063 United States Mechanical Engineering Department Rose-Hulman Institute of Technology Terre-Haute IN 47803 United States Civil and Environmental Engineering Seattle University Seattle WA 98122-4340 United States Mechanical Engineering Technology Pittsburg State University Pittsburg KS 66762 United States Aerospace Science Engineering Tuskegee University Tuskegee AL 36088 United States Electrical Engineering Le Tourneau University Longview TX 75605 United States

Professionalism, which includes engineering ethics, is recognized as a valued topic in industry and education but it is difficult to teach and assess. This paper presents a web-based professional responsibility instrument and accompanying rubric, which is used to assess student understanding and skillinanalyzing areas of strength and opportunity surrounding a professional responsibility issue associated with the student's design project. Students completing the assessment most frequently rated work competence asboth highly important and an area of team strength while issues of sustainability were least frequently cited. The scored results of this assessment revealed that students were moderately effective at relating issues of professional responsibility tosituations within their projects as well asaddressing themin a responsible manner. In a post-assessment survey, students and faculty rated the assessment as somewhat accurate to mostly accurate. An interrater agreement study of the assessment showed that scorers were on average within one level of difference on the scoring rubric 97% of the time. Results of administering the assessment in a capstone course can be easily packaged and presented as part of a program accreditation self-study. © 2012 TEMPUS Publications.

关键词： Students

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On-chip western blotting: In-situ renaturation of SDS-protein complexes unifies sodium dodecyl sulfate (SDS) sizing & blotting in one microdevice

On-chip western blotting: In-situ renaturation of SDS-protei...

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15th International Conference on Miniaturized Systems for Chemistry and Life sciences 2011, MicroTAS 2011

作者： Hou, Chenlu Herr, Amy E. University of California Electrical Engineering and Computer Science Berkeley United States University of California Bioengineering Berkeley United States University of California UCSF Graduate Program in Bioengineering Berkeley United States

ISBN: (纸本)9781618395955

Western blotting readily identifies specific proteins amidst complex biological backgrounds [1, 2]. Nevertheless, immunob-lotting suffers from tremendous labor-intensive and time-intensive requirements [3]. The slab-gel assays require 1-2 days for completion with multiple hands-on "blotting" steps and yield semi-quantitative information. Recently, our group has introduced new approaches for completing Western blotting. The microfluidic integration strategies introduced and used allow rapid results reporting, full assay automation, and limited sample consumption (1-10 uL). Our integration strategies use spatial, temporal, and spatiotemporal modulation of separation mechanisms in fully electrophoretic systems. The present study reports on recapitulation of immunoaffinity in previously sized proteins, using novel in-transit electrophoretic removal of SDS from SDS-protein complexes. Early results show both the length- and timescales for protein 'renaturation' are compatible with on-chip operation. Further, substantial binding affinity is recapitulated using this streamlined and promising approach.

关键词： Sodium dodecyl sulfate

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Research Highlights: Highlights from the last year in nanomedicine

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Nanomedicine 2012年第1期8卷 13-15页

作者： Brian Dorvel Gregory Damhorst Vincent Chan Jiwook Shim Shouvik Banerjee Caroline Cvetkovic Ritu Raman Rashid Bashir Department of Biophysics & Computational Biology University of Illinois at Urbana–Champaign IL USA Micro & Nanotechnology Laboratory University of Illinois at Urbana–Champaign 208 N Wright St Urbana IL 61801 USA Department of Bioengineering University of Illinois at Urbana–Champaign IL USA Department of Electrical & Computer Engineering University of Illinois at Urbana–Champaign IL USA Department of Materials Science & Engineering University of Illinois at Urbana–Champaign IL USA Micro & Nanotechnology Laboratory University of Illinois at Urbana–Champaign 208 N Wright St Urbana IL 61801 USA.

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A multivariate logistical model for identifying the compressive sensitivity of single rat tactile receptors as nanobiosensors

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Journal of Nanotechnology in engineering and Medicine 2011年第1期2卷 011002页

作者： Kohles, Sean S. Bradshaw, Sam Mason, Shelley S. Looft, Fred J. Reparative Bioengineering Laboratory Department of Mechanical and Materials Engineering Portland State University Portland OR 97201 United States Department of Surgery Oregon Health and Science University Portland OR 97239 United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA 01609 United States Reparative Bioengineering Laboratory Department of Mechanical and Materials Engineering Department of Biology Portland State University Portland OR 97201 United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA 01609 United States PMC-Sierra Roseville CA United States

Tactile sensation is a complex manifestation of mechanical stimuli applied to the skin. At the most fundamental level of the somatosensory system is the cutaneous mechanoreceptor. The objective here was to establish a framework for modeling afferent mechanoreceptor behavior as a nanoscale biosensor under dynamic compressive loads using multivariate regression techniques. A multivariate logistical model was chosen because the system contains continuous input variables and a singular binary-output variable corresponding to the nerve action potential. Subsequently, this method was used to quantify the sensitivity of ten rapidly adapting afferents from rat hairy skin due to the stimulus metrics of compressive stress, strain, their respective time derivatives, and interactions. In vitro experiments involving compressive stimulation of isolated afferents using pseudorandom and nonrepeating noise sequences were completed. An analysis of the data was performed using multivariate logistical regression producing odds ratios (ORs) as a metric associated with mechanotransduction. It was determined that cutaneous mechanoreceptors are preferentially sensitive to stress (mean ORmax=26.10), stress rate (mean ORmax=15.03), strain (mean ORmax=12.01), and strain rate (mean ORmax=7.29) typically occurring within 7.3 ms of the nerve response. As a novel approach to receptor characterization, this analytical framework was validated for the multiple-input, binaryoutput neural system. © 2010 by ASME.

关键词： Rats

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Microstructural and electrical properties of Ce_0.9Gd_0.1O1.95 thin film electrolyte in solid oxide fuel cells (vol 26, pg 854, 2011)

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JOURNAL OF MATERIALS RESEARCH 2011年第11期26卷 854-859页

作者： Cho, Sungmee Yoon, Jongsik Kim, Jung-Hyun Zhang, Xinghang Manthiram, Arumugam Wang, Haiyan [a1 ]Department of Electrical and Computer Engineering Texas A&M University College Station Texas 77843-3128[a2 ]Electrochemical Energy Laboratory and Materials Science and Engineering Program University of Texas at Austin Austin Texas 78712[a3 ]Department of Mechanical Engineering Texas A&M University College Station Texas 77843-3123[a4 ]Electrochemical Energy Laboratory and Materials Science and Engineering Program University of Texas at Austin Austin Texas 78712[a5 ]Department of Electrical and Computer Engineering Texas A&M University College Station Texas 77843-3128

Microstructural and electrical properties of Gd-doped CeO2 (GDC; Ce0.9Gd0.1O1.95) thin films prepared by pulsed laser deposition as an electrolyte in solid-oxide fuel cells (SOFCs) were investigated. The GDC thin film... 详细信息

Microstructural and electrical properties of Gd-doped CeO₂ (GDC; Ce_0.9Gd_0.1O_1.95) thin films prepared by pulsed laser deposition as an electrolyte in solid-oxide fuel cells (SOFCs) were investigated. The GDC thin films were prepared on various substrates including single-crystal yttria-stabilized zirconia (YSZ) and magnesium oxide (MgO) substrates. The GDC thin-film electrolytes with different grain sizes and grain morphologies were prepared by varying the deposition parameters, such as substrate temperature, oxygen partial pressure, target repetition rate, and laser ablation energy. The microstructural properties of these films were examined using X-ray diffraction (XRD), transmission electron microscopy (TEM), and atomic force microscopy (AFM). Alternating-current (AC) and direct-current (DC) electrical measurements through in-plane method show that the electrical property of the GDC thin film strongly depends on grain size, e.g., the total conductivity of the films deposited at 700 C (7.3 10³ S/cm) is about 20 times higher than the ones deposited at room temperature (3.6 10⁴ S/cm) at the measurement temperature of 600 C.

关键词： Thin Film electrical Properties Physical Vapor Deposition (PVD)

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Adaptive resolution ADC array for an implantable neural sensor

Adaptive resolution ADC array for an implantable neural sens...

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作者： O'Driscoll, Stephen Shenoy, Krishna V. Meng, Teresa H. Department of Electrical and Computer Engineering University of California Davis CA 95161 United States Departments of Electrical Engineering and Bioengineering Neurosciences Program Stanford University Stanford CA 94305 United States Department of Electrical Engineering Stanford University Stanford CA 94305 United States

This paper describes an analog-to-digital converter (ADC) array for an implantable neural sensor which digitizes neural signals sensed by a microelectrode array. The ADC array consists of 96 variable resolution ADC base cells. The resolution of each ADC cell in the array is varied according to neural data content of the signal from the corresponding electrode. The resolution adaptation algorithm is essentially to periodically recalibrate the required resolution and this is done without requiring any additional ADC cells. The adaptation implementation and results are described. The base ADC cell is implemented using a successive approximation charge redistribution architecture. The choice of architecture and circuit design are presented. The base ADC has been implemented in 0.13 \mum CMOS as a 100 kS/s SAR ADC whose resolution can be varied from 3 to 8 bits with corresponding power consumption of 0.23 \muW to 0.90 \muW achieving an ENOB of 7.8 at the 8-bit setting. The energy per conversion step figure of merit is 48 fJ/step at the 8-bit setting. Resolution adaptation reduces power consumption by a factor of 2.3 for typical motor neuron signals while maintaining an effective 7.8-bit resolution across all channels. © 2011 IEEE.

关键词： Analog to digital conversion

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Modularity detection in protein-protein interaction networks

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BMC Research Notes 2011年第1期4卷 1-6页

作者： Narayanan, Tejaswini Gersten, Merril Subramaniam, Shankar Grama, Ananth Department of Electrical and Computer Engineering University of California San Diego United States Graduate Program in Bioinformatics and Systems Biology University of California San Diego United States Department of Bioengineering University of California San Diego United States Department of Computer Science Purdue University West Lafayette IN United States

Background: Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG) algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. Results: We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, *** and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. Conclusions: We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the underlying network, and the applic

关键词： Biological Network Jaccard Index Input Network High Betweenness Jaccard Similarity Coefficient

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A virtual eye for use in an Optometry clinic

A virtual eye for use in an Optometry clinic

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2nd International Conference on User science and engineering, i-USEr 2011

作者： Turuwhenua, Jason Naqvi, Husnain Sulayman, Muhammad Riaz, Mehwish Auckland Bioengineering Institute Department of Optometry and Vision Science University of Auckland Auckland New Zealand Department of Electrical and Computer Engineering University of Auckland Auckland New Zealand Department of Computer Science University of Auckland Auckland New Zealand

ISBN: (纸本)9781457716553

It is important that eye care professionals have access to tools that accurately and efficiently convey the results of an eye exam to students and patients. This paper describes work-in-progress on a software system that displays a patient specific 3-dimensional model of the eye, as well as the effects of refractive errors (errors of focus) to the patient. We have used a focus group as a means for gathering preliminary feedback on our software, some of the themes that emerged from our discussions are presented. Future directions for the software are mentioned. © 2011 IEEE.

关键词： computer software

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Surface Characterization: Non‐Invasive High‐Throughput Metrology of Functionalized Graphene Sheets (Adv. Funct. Mater. 21/2012)

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Advanced Functional Materials 2012年第21期22卷

作者： Maziar Ghazinejad Jennifer Reiber Kyle Shirui Guo Dennis Pleskot Duoduo Bao Valentine I. Vullev Mihrimah Ozkan Cengiz S. Ozkan Departments of Mechanical Engineering and Bioengineering Materials Science and Engineering Program University of California Riverside CA 92521 USA Departments of Electrical Engineering and Chemistry University of California Riverside CA 92521 USA Department of Bioengineering University of California Riverside CA 92521 USA

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Application of machine learning and numerical analysis to classify tremor in patients affected with essential tremor or Parkinson's disease

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Gerontechnology 2012年第4期10卷 208-219页

作者： Darnall, Nathan D. Donovan, Conrad K. Aktar, Syeda Tseng, Han-Yun Barthelmess, Paulo Cohen, Philip R. Lin, David C. School of Mechanical and Materials Engineering College of Engineering and Architecture Washington State University Pullman WA 99164 United States School of Electrical Engineering and Computer Science College of Engineering and Architecture Washington State University Pullman WA 99164 United States Department of Human Development College of Agricultural Human and Natural Resource Sciences Washington State University Pullman WA 99164 United States Adapx Inc Seattle WA United States Voiland School of Chemical Engineering and Bioengineering Department of Veterinary and Comparative Anatomy Pharmacology and Physiology Pullman WA 99164 United States

The overall goal of this study was to compare the accuracy of various data analysis techniques to quantify tremor severity (TS) in a clinical context, with the aim of improving the reliability (context consistency and inter-rater agreement) of tremor evaluation in patients with Parkinson's disease (PD) or essential tremor (ET). Ten patients with either PD or ET were asked to perform several tasks used in the clinical practice for the characterization of tremor. Three-axis gyroscopes in a Shimmer device measured angular velocities of the wrist of each subject for postural, kinetic, spiral tracing, and resting scenarios, and a digital pen recorded subjects' tracings of an Archimedes spiral printed on paper. Gyroscope data were used for training and testing a supervised machine learning algorithm to classify TS and for root mean squared (RMS) numerical rating of TS, while digital pen data were analyzed numerically to quantify tracing deviations from the spiral and obtain a tremor rating. We evaluated the performance of our proposed methods compared to clinicians' diagnostic rating. The machine learning method matched the clinical rating with 82% accuracy, the digital pen with 78% accuracy, and RMS with 42% accuracy. We obtained the best accuracy of 82% using the decision tree machine learning approach with gyroscope data measured with the Shimmer.

关键词： Digital pen Gyroscope Machine learning Spiral trace Tremor rating

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