Deductive and Analogical Reasoning on a Semantically Embedded Knowledge Graph

Representing knowledge as high-dimensional vectors in a continuous semantic vector space can help overcome the brittleness and incompleteness of traditional knowledge bases. We present a method for performing deductive reasoning directly in such a vector space, combining analogy, association, and deduction in a straightforward way at each step in a chain of reasoning, drawing on knowledge from diverse sources and ontologies.Comment: AGI 201

Electrochemical Deposition Method Utilizing Microdroplets of Solution

A method of electrochemical deposition uses microdroplets of electrolytic solution over a targeted small circuit element. Only the targeted circuit element is electrically biased so that deposition occurs on the surface of that element, underneath the microdroplet, and nowhere else unless it is under other microdroplet(s). The invented method achieves extremely accurate and selective electrochemical deposition with a tiny amount of electrolytic solution, compared to conventional submersive and/or immersive methods, and eliminates the need for masking or etching, reducing the costs of manufacture and amount of waste electrolytic solution produced

Undergraduate Research Opportunities in Microelectronics at Boise State University

Several opportunities exist for undergraduates in the Microelectronics area at Boise State University. This paper will describe the Research Experience for Undergraduates (REU) program funded by the National Science Foundation and other opportunities that have resulted for undergraduates due to external support. BSU became a NSF REU site for Microelectronics research in 1999. Each year 10 students are recruited nation-wide from various engineering and science disciplines to come to BSU for 8 weeks. The students work intensively with various faculty advisors and graduate student mentors. Another unique feature of our program is the tie to local industry. In 1999-2001, three students have and will benefit from an interaction with a local company, SCP Global Technologies, and this will be described

An Efficient Data Structure for Dynamic Two-Dimensional Reconfiguration

In the presence of dynamic insertions and deletions into a partially reconfigurable FPGA, fragmentation is unavoidable. This poses the challenge of developing efficient approaches to dynamic defragmentation and reallocation. One key aspect is to develop efficient algorithms and data structures that exploit the two-dimensional geometry of a chip, instead of just one. We propose a new method for this task, based on the fractal structure of a quadtree, which allows dynamic segmentation of the chip area, along with dynamically adjusting the necessary communication infrastructure. We describe a number of algorithmic aspects, and present different solutions. We also provide a number of basic simulations that indicate that the theoretical worst-case bound may be pessimistic.Comment: 11 pages, 12 figures; full version of extended abstract that appeared in ARCS 201

Integrating Through-Wafer Interconnects with Active Devices and Circuits

Through wafer interconnects (TWIs) enable vertical stacking of integrated circuit chips in a single package. A complete process to fabricate TWIs has been developed and demonstrated using blank test wafers. The next step in integrating this technology into 3D microelectronic packaging is the demonstration of TWIs on wafers with preexisting microcircuitry. The circuitry must be electrically accessible from the backside of the wafer utilizing the TWIs; the electrical performance of the circuitry must be unchanged as a result of the TWI processing; and the processing must be as cost effective as possible. With these three goals in mind, several options for creating TWIs were considered. This paper explores the various processing options and describes in detail, the final process flow that was selected for testing, the accompanying masks that were designed, the actual processing of the wafers, and the electrical test results

On the Thermal Activation of Negative Bias Temperature Instability

The temperature dependence of negative bias temperature instability (NBTI) is investigated on 2.0nm SiO2 devices from temperatures ranging from 300K down to 6K with a measurement window of ~12ms to 100s. Results indicate that classic NBTI degradation is observed down to ~200K and rarely observed at temperatures below 140K in the experimental window. Since experimental results show the charge trapping component contributing to NBTI is thermally activated, the results cannot be explained with the conventionally employed elastic tunneling theory. A new mechanism is observed at temperatures below 200K where device performance during stress conditions improves rather than degrades with time, which is opposite to the classical NBTI phenomenon

White Matter Abnormalities in Patients with Treatment-Resistant Genetic Generalized Epilepsies.

BACKGROUND Genetic generalized epilepsies (GGEs) are associated with microstructural brain abnormalities that can be evaluated with diffusion tensor imaging (DTI). Available studies on GGEs have conflicting results. Our primary goal was to compare the white matter structure in a cohort of patients with video/EEG-confirmed GGEs to healthy controls (HCs). Our secondary goal was to assess the potential effect of age at GGE onset on the white matter structure. MATERIAL AND METHODS A convenience sample of 23 patients with well-characterized treatment-resistant GGEs (13 female) was compared to 23 HCs. All participants received MRI at 3T. DTI indices, including fractional anisotropy (FA) and mean diffusivity (MD), were compared between groups using Tract-Based Spatial Statistics (TBSS). RESULTS After controlling for differences between groups, abnormalities in DTI parameters were observed in patients with GGEs, including decreases in functional anisotropy (FA) in the hemispheric (left>right) and brain stem white matter. The examination of the effect of age at GGE onset on the white matter integrity revealed a significant negative correlation in the left parietal white matter region FA (R=-0.504; p=0.017); similar trends were observed in the white matter underlying left motor cortex (R=-0.357; p=0.103) and left posterior limb of the internal capsule (R=-0.319; p=0.148). CONCLUSIONS Our study confirms the presence of widespread white matter abnormalities in patients with GGEs and provides evidence that the age at GGE onset may have an important effect on white matter integrity

The Behavior of Granular Materials under Cyclic Shear

The design and development of a parallel plate shear cell for the study of large scale shear flows in granular materials is presented. The parallel plate geometry allows for shear studies without the effects of curvature found in the more common Couette experiments. A system of independently movable slats creates a well with side walls that deform in response to the motions of grains within the pack. This allows for true parallel plate shear with minimal interference from the containing geometry. The motions of the side walls also allow for a direct measurement of the velocity profile across the granular pack. Results are presented for applying this system to the study of transients in granular shear and for shear-induced crystallization. Initial shear profiles are found to vary from packing to packing, ranging from a linear profile across the entire system to an exponential decay with a width of approximately 6 bead diameters. As the system is sheared, the velocity profile becomes much sharper, resembling an exponential decay with a width of roughly 3 bead diameters. Further shearing produces velocity profiles which can no longer be fit to an exponential decay, but are better represented as a Gaussian decay or error function profile. Cyclic shear is found to produce large scale ordering of the granular pack, which has a profound impact on the shear profile. There exist periods of time in which there is slipping between layers as well as periods of time in which the layered particles lock together resulting in very little relative motion.Comment: 10 pages including 12 figure

Enhanced DNA Sensing via Catalytic Aggregation of Gold Nanoparticles

A catalytic colorimetric detection scheme that incorporates a DNA-based hybridization chain reaction into gold nanoparticles was designed and tested. While direct aggregation forms an inter-particle linkagefrom only one target DNA strand, catalytic aggregation forms multiple linkages from a single target DNA strand. Gold nanoparticles were functionalized with thiol-modified DNA strands capable of undergoing hybridization chain reactions. The changes in their absorption spectra were measured at different times and target concentrations and compared against direct aggregation. Catalytic aggregation showed a multifold increase in sensitivity at low target concentrations when compared to direct aggregation. Gelelectrophoresis was performed to compare DNA hybridization reactions in catalytic and direct aggregation schemes, and the product formation was confirmed in the catalytic aggregation scheme at low levels of target concentrations. The catalytic aggregation scheme also showed high target specificity. This application of a DNA reaction network to gold nanoparticle-based colorimetric detection enables highly-sensitive, field-deployable, colorimetric readout systems capable of detecting a variety of biomolecules