Publications

Abstract not provided.

Understanding the role of emotional states is critical for predicting the kind of decisions people will make in risky situations. Currently, there is little understanding as to how emotion influences decision-making in situations such as terrorist attacks, natural disasters, pandemics, and combat. To help address this, we used behavioral and neuroimaging methods to examine how emotion states and traits influence decisions. Specifically, this study used a wheel of fortune behavioral task and functional magnetic resonance imaging (fMRI) to examine the effects of emotional states and traits on decision-making pertaining to the degree of risk people are willing to make in specific situations. The behavioral results are reported here. The neural data requires additional time to analyze and will be reported at a future date. Biases caused by emotion states and traits were found regarding the likelihood of making risky decisions. The behavioral results will help provide a solid empirical foundation for modeling the effects of emotion on decision in risky situations.

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Public mediated resource planning is quickly becoming the norm rather than the exception. Unfortunately, supporting tools are lacking that interactively engage the public in the decision-making process and integrate over the myriad values that influence water policy. In the pages of this report we document the first steps toward developing a specialized decision framework to meet this need; specifically, a modular and generic resource-planning ''toolbox''. The technical challenge lies in the integration of the disparate systems of hydrology, ecology, climate, demographics, economics, policy and law, each of which influence the supply and demand for water. Specifically, these systems, their associated processes, and most importantly the constitutive relations that link them must be identified, abstracted, and quantified. For this reason, the toolbox forms a collection of process modules and constitutive relations that the analyst can ''swap'' in and out to model the physical and social systems unique to their problem. This toolbox with all of its modules is developed within the common computational platform of system dynamics linked to a Geographical Information System (GIS). Development of this resource-planning toolbox represents an important foundational element of the proposed interagency center for Computer Aided Dispute Resolution (CADRe). The Center's mission is to manage water conflict through the application of computer-aided collaborative decision-making methods. The Center will promote the use of decision-support technologies within collaborative stakeholder processes to help stakeholders find common ground and create mutually beneficial water management solutions. The Center will also serve to develop new methods and technologies to help federal, state and local water managers find innovative and balanced solutions to the nation's most vexing water problems. The toolbox is an important step toward achieving the technology development goals of this center.

Control of nanoparticle size is crucial to the development of nanotechnology. At this point in time, no general, rational synthetic strategy for controlling nanocrystal diameters and producing narrow diameter distributions has emerged. This is a reflection of a poor understanding of the mechanisms for nanocrystal growth. Based on previous studies of bismuth and gold nanoparticle growth, this work clearly establishes two new synthetic approaches to controlled growth of colloidal Pt nanocrystals, both based on aggregative-growth mechanisms, which afford narrow size distributions and size control over a wide and relevant size regime. The first new method is a phase transfer process, where growth is controlled by varying ligand stabilizer concentrations. The second method involves rapid reduction of a molecular platinum precursor in the presence of a polymer stabilizer. At present the size control is empirical, and incompletely understood and incompletely developed. However, the new synthetic pathways are amenable to kinetic study and analysis, establishing that a quantitative, rational control of sizes and size distributions can be achieved.

The goal of this project was to develop a risk analysis meta tool--a tool that enables security analysts both to combine and analyze data from multiple other risk assessment tools on demand. Our approach was based on the innovative self-assembling software technology under development by the project team. This technology provides a mechanism for the user to specify his intentions at a very high level (e.g., equations or English-like text), and then the code self-assembles itself, taking care of the implementation details. The first version of the meta tool focused specifically in importing and analyzing data from Joint Conflict and Tactical Simulation (JCATS) force-on-force simulation. We discuss the problem, our approach, technical risk, and accomplishments on this project, and outline next steps to be addressed with follow-on funding.

Nonlinear FM (NLFM) waveforms offer a radar matched filter output with inherently low range sidelobes. This yields a 1-2 dB advantage in Signal-to-Noise Ratio over the output of a Linear FM (LFM) waveform with equivalent sidelobe filtering. This report presents details of processing NLFM waveforms in both range and Doppler dimensions, with special emphasis on compensating intra-pulse Doppler, often cited as a weakness of NLFM waveforms.

DEDICOM is a linear algebra model for analyzing intrinsically asymmetric relationships, such as trade among nations or the exchange of emails among individuals. DEDICOM decomposes a complex pattern of observed relations among objects into a sum of simpler patterns of inferred relations among latent components of the objects. Three-way DEDICOM is a higher-order extension of the model that incorporates a third mode of the data, such as time, giving it stronger uniqueness properties and consequently enhancing interpretability of solutions. In this paper, we present algorithms for computing these decompositions on large, sparse data as well as a variant for computing an asymmetric nonnegative factorization. When we apply these techniques to adjacency arrays arising from directed graphs with edges labeled by time, we obtain a smaller graph on latent semantic dimensions and gain additional information about their changing relationships over time. We demonstrate these techniques on the Enron email corpus to learn about the social networks and their transient behavior. The mixture of roles assigned to individuals by DEDICOM showed strong correspondence with known job classifications and revealed the patterns of communication between these roles. Changes in the communication pattern over time, e.g., between top executives and the legal department, were also apparent in the solutions.

Electronic components such as bipolar junction transistors (BJTs) are damaged when they are exposed to radiation and, as a result, their performance can significantly degrade. In certain environments the radiation consists of short, high flux pulses of neutrons. Electronics components have traditionally been tested against short neutron pulses in pulsed nuclear reactors. These reactors are becoming less and less available; many of them were shut down permanently in the past few years. Therefore, new methods using radiation sources other than pulsed nuclear reactors needed to be developed. Neutrons affect semiconductors such as Si by causing atomic displacements of Si atoms. The recoiled Si atom creates a collision cascade which leads to displacements in Si. Since heavy ions create similar cascades in Si we can use them to create similar damage to what neutrons create. This LDRD successfully developed a new technique using easily available particle accelerators to provide an alternative to pulsed nuclear reactors to study the displacement damage and subsequent transient annealing that occurs in various transistor devices and potentially qualify them against radiation effects caused by pulsed neutrons.

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This one year LDRD addressed the problem of rapid characterization of bacterial spores such as those from the genus Bacillus, the group that contains pathogenic spores such as B. anthracis. In this effort we addressed the feasibility of using a proteomics based approach to spore characterization using a subset of conserved spore proteins known as the small acid soluble proteins or SASPs. We proposed developing techniques that built on our previous expertise in microseparations to rapidly characterize or identify spores. An alternative SASP extraction method was developed that was amenable to both the subsequent fluorescent labeling required for laser-induced fluorescence detection and the low ionic strength requirements for isoelectric focusing. For the microseparations, both capillary isoelectric focusing and chip gel electrophoresis were employed. A variety of methods were evaluated to improve the molecular weight resolution for the SASPs, which are in a molecular weight range that is not well resolved by the current methods. Isoelectric focusing was optimized and employed to resolve the SASPs using UV absorbance detection. Proteomic signatures of native wild type Bacillus spores and clones genetically engineered to produce altered SASP patterns were assessed by slab gel electrophoresis, capillary isoelectric focusing with absorbance detection as well as microchip based gel electrophoresis employing sensitive laser-induced fluorescence detection.

We define a new diagnostic method where computationally-intensive numerical solutions are used as an integral part of making difficult, non-contact, nanometer-scale measurements. The limited scope of this report comprises most of a due diligence investigation into implementing the new diagnostic for measuring dynamic operation of Sandia's RF Ohmic Switch. Our results are all positive, providing insight into how this switch deforms during normal operation. Future work should contribute important measurements on a variety of operating MEMS devices, with insights that are complimentary to those from measurements made using interferometry and laser Doppler methods. More generally, the work opens up a broad front of possibility where exploiting massive high-performance computers enable new measurements.

This report summarizes our findings during the study of a novel system that yields multi-colored materials as products. This system is quite unusual as it leads to multi-chromic behavior in single crystals, where one would expect that only a single color would exist. We have speculated that these novel solids might play a role in materials applications such as non-linear optics, liquid crystal displays, piezoelectric devices, and other similar applications. The system examined consisted of a main-group alkyl compound (a p block element such as gallium or aluminum) complexed with various organic di-imines. The di-imines had substituents of two types--either alkyl or aromatic groups attached to the nitrogen atoms. We observed that single crystals, characterized by X-ray crystallography, were obtained in most cases. Our research during January-July, 2006, was geared towards understanding the factors leading to the multi-chromic nature of the complexes. The main possibilities put forth initially considered (a) the chiral nature of the main group metal, (b) possible reduction of the metal to a lower-valent, radical state, (c) the nature of the ligand(s) attached to the main group metal, and (d) possible degradation products of the ligand leading to highly-colored products. The work carried out indicates that the most likely explanation considered involves degradation of the aromatic ligands (a combination of (c) and (d)), as the experiments performed can clearly rule out (a) and (b).

Abstract not provided.

Traditional cluster monitoring approaches consider nodes in singleton, using manufacturer-specified extreme limits as thresholds for failure ''prediction''. We have developed a tool, OVIS, for monitoring and analysis of large computational platforms which, instead, uses a statistical approach to characterize single device behaviors from those of a large number of statistically similar devices. Baseline capabilities of OVIS include the visual display of deterministic information about state variables (e.g., temperature, CPU utilization, fan speed) and their aggregate statistics. Visual consideration of the cluster as a comparative ensemble, rather than as singleton nodes, is an easy and useful method for tuning cluster configuration and determining effects of real-time changes.

This minireview outlines the synthetic efforts, from our research group, to produce nanomaterials for use as imaging agents to study cell signaling pathways. An overview of our approach to the synthesis and biofunctionalization of metal, semiconductor, and ceramic nanomaterials is presented. The probes investigated include coinage metals, Cd-based, Geo, naturally occurring fluorescent (NOF) minerals, and Ln-based nanoparticles which were synthesized from novel metal alkoxide, amide, and alkyl precursors. We illustrate the applications of some of these materials as imaging probes to detect signaling pathway components and cellular responses to signals (apoptosis and degranulation) in inflammatory and cancer cells. © 2006 IEEE.

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Monitoring programs for nuclear-waste repositories are now conceived as an exercise in performance confirmation: the purpose of the monitoring program is to provide objective evidence that the repository system is functioning as expected. However, monitoring is still largely seen as being entirely focused on the near-repository environment, with the aim of verifying predictions made about such things as temperature or rock mass behavior that are relevant to the designed functioning of the repository. A more comprehensive approach comes from recognizing that the repository is embedded in a larger natural system that may be affected by factors in addition to the repository. At some current or prospective repository sites, various human activities that are amenable to monitoring might potentially (or actually) affect the natural system. Observing these anthropogenically induced changes in the natural system and being able to simulate them accurately using the models already constructed for repository performance assessment provide an additional opportunity for performance confirmation. Water-level changes induced by oil and gas exploration and/or potash mining activities near the Waste Isolation Pilot Plant site provided an opportunity to confirm important features of the groundwater model used in performance assessment calculations. Repository programs should evaluate the potential for ongoing or future human activities to affect the systems in which their repositories are situated and provide an opportunity for performance confirmation.

We investigate the magnetostriction of field-structured magnetoelastomers, which are an important class of materials that have great potential as both sensors and actuators. Field-structured magnetoelastomers are synthesized by suspending magnetic particles in a polymeric resin and subjecting these to magnetic structuring fields during polymerization. These structuring fields can consist of as many as three orthogonal ac components, allowing a wide variety of particles structures-chains, sheets, or networks-to be formed. A principal issue is how particle structure and loading affects the magnetostriction of these materials. To investigate magnetostriction in these field-structured composites we have constructed a constant stress, optical cantilever apparatus capable of 1 ppm strain resolution. Magnetoelastomers having a wide range of particle loadings and structures are investigated, and it is shown that the observed deformation depends strongly on composite structure. The best magnetoelastomers exhibit a contractive strain of 10 000 ppm, the worst materials exhibit a negative, tensile response, which we show is due to the dominance of demagnetizing field effects over magnetostriction. Finally, some discussion is given to the surprising finding that magnetostriction is proportional to the sample prestrain. Simulations of a chain of particles in an elastomer show that particle clumping transitions can occur, but this does not account for the dependence of magnetostriction on prestrain. © 2006 The American Physical Society.

A series of cerium alkoxides were synthesized from the reaction of Ce{N[Si(CH3)3]2}3 and the appropriate alcohol: neopentyl alcohol [H-OCH2C(CH3) 3 = H-ONep], tert-butyl alcohol [H-OC(CH3)3 = H-OtBu], o-(tert-butyl)phenol {H-OC6H4[C(CH 3)3]-2 = H-oBP), 2,6-dimethylphenol [H-OC 6H3(CH3)2-2,6 = H-DMP], 2,6-diisopropylphenol {H-OC6H3[CH(CH3) 2]2-2,6 = H-DIP}, 2,6-di-tert-butylphenol {H-OC 6H3[C(CH3)3]2-2,6 = H-DBP}, or 2,6-diphenylphenol [H-OC6H3(C6H 5)2-2,6 = H-DPP] using toluene (tol), tetrahydrofuran (THF) or pyridine (py). The precursors were characterized as [Ce(μ-ONep) 2(ONep)]4 (1), Ce4(μ3-OtBu) 3(μ-OtBu)4(OtBu)5 (2), Ce 3(μ3-OtBu)3(H-OtBu)2(OtBu) 3(H-OtBu)2 (2a), Ce(OBP)3(THF)3 (3), [Ce(μ-DMP)(DMP)2(solv)2]2 [solv = THF (4) and py (4a)], Ce(DIP)3(THF)3 (5), Ce(DPP) 3(THF)2 (6). Once isolated, several of these species were further reacted with a series of sterically varied carboxylic acid modifiers including isobutyric acid [H-O2CCH(CH3)2 = H-OPc] and trimethylacetic acid [H-O2CC(CH3)3 = H-OBc]. The products were isolated as [Ce(OR)(μ-ORc)(μc-ORc) (py)]2 [OR = oBP, OBc: 7; DMP, OPc: 8; DMP, OBc: 9; DIP, OPc: 10]. These compounds were identified by single-crystal X-ray diffraction and powder XRD analyses. Several novel structure types are added to the cerium alkoxide family of compounds. © Wiley-VCH Verlag GmbH & Co. KGaA, 2006.

Legacy plutonium-bearing materials are stored in shipping containers at the Savannah River Site (SRS) until their final disposition can be determined. This material has been stabilized and is maintained per the DOE’s standard for long-term storage of Pu-containing materials, DOE-STD-3013. As a part of its ongoing storage mission, Washington Savannah River Company’s (WSRC) Nuclear Materials Management (NMM) organization is tasked with a surveillance program that will ensure these materials have remained in their expected condition over the several years of storage. Information from this program will be used by multiple entities to further validate the safe storage of Pu-bearing materials per DOE-STD-3013. Part of the program entails cutting open selected 3013 containers and sampling the materials inside. These samples will then be analyzed by Savannah River National Laboratory (SRNL). The remaining material not used for samples will then be repackaged in non-3013 containers to be placed back into shipping packages for storage until disposition at SRS. These repackaged materials will be stored per the requirements of DOE’s Criteria for Interim Safe Storage of Plutonium Bearing Materials (ISSC).

The emission from a radiating source embedded in a photonic lattice is investigated. The photonic lattice spectrum was found to deviate from the blackbody distribution, with intracavity emission suppressed at certain frequencies and significantly enhanced at others. For rapid population relaxation, where the photonic lattice and blackbody populations are described by the same thermal distribution, it was found that the enhancement does not result in output intensities exceeding those of the blackbody. However, for slow population relaxation, the photonic lattice population has a greater tendency to deviate from thermal equilibrium, resulting in output intensities exceeding those of the blackbody.

In recent years, several researchers have constructed novel neural network models based on lattice algebra. Because of computational similarities to operations in the system of image morphology, these models are often called morphological neural networks. One neural model that has been successfully applied to many pattern recognition problems is the single-layer morphological perceptron with dendritic structure (SLMP). In this model, the fundamental computations are performed at dendrites connected to the body of a single neuron. Current training algorithms for the SLMP work by enclosing the target patterns in a set of hyperboxes orthogonal to the axes of the data space. This work introduces an alternate model of the SLMP, dubbed the synoptic morphological perceptron (SMP). In this model, each dendrite has one or more synapses that receive connections from inputs. The SMP can learn any region of space determined by an arbitrary configuration of hyperplanes, and is not restricted to forming hyperboxes during training. Thus, it represents a more general form of the morphological perceptron than previous architectures.