Putting mechanics into quantum mechanics

Nanoelectromechanical structures are starting to approach the ultimate quantum mechanical limits for detecting and exciting motion at the nanoscale. Nonclassical states of a mechanical resonator are also on the horizon

The Attraction of Foreign Manufacturing Investments: Investment Promotion and Agglomeration Economies

We study Japanese investments between 1980 and 1992 to assess the effectiveness of state promotion efforts in light of strong agglomeration economies in Japanese investment. Two policy variables are consistently shown to influence the location of investment - foreign trade zones and labor subsidies. We use simulations to explore the impact these policies had on the geographic distribution of Japanese investment. The simulations reveal that in aggregate promotion programs largely offset each other; however, unilateral withdrawal of promotion causes individual states to lose substantial amounts of foreign investment.

Effect of Phenolic Matrix Microcracking on the Structural Response of a 3-D Woven Thermal Protection System

The effect of microcracking in the phenolic matrix of a three-dimensional woven thermal protection system (TPS) and the resulting material stiffness reduction was studied via a comparison of finite element analysis results from a linear analysis and an iterative linear analysis. A TPS is necessary to protect space vehicles from the aerodynamic heating of planetary entry. The Heatshield for Extreme Entry Environment Technology (HEEET) project has developed a TPS for use in high heat-flux and pressure missions. The material is a dual-layer continuous dry weave, which is then infiltrated with a low-density phenolic resin matrix to form a rigid ablator. The phenolic resin matrix does not have structural load transfer requirements, and testing has shown that the phenolic resin can fully satisfy thermal requirements when the matrix contains microcracks. Due to high stresses in the through-the-thickness direction of the material, phenolic microcracks may form in the matrix material, which would result in a reduction of stiffness. An exploratory study was conducted to determine if reduction in material stiffness would change the load paths and/or decrease the structural margins. A comparison was performed between a linear finite element analysis that did not take into account phenolic microcracking and an iterative linear finite element analysis that accounted for propagation of phenolic microcracking. Four subcases using varying assumptions were analyzed and the results indicate that the assumed strength at which the phenolic microcracking propagates was the critical parameter for determining the extent of microcracking in the phenolic matrix. Phenolic microcracking does not have an adverse effect on the structural response of the test article and is not a critical failure

Innovative Hybridisation of Genetic Algorithms and Neural Networks in Detecting Marker Genes for Leukaemia Cancer

Methods for extracting marker genes that trigger the growth of cancerous cells from a high level of complexity microarrays are of much interest from the computing community. Through the identified genes, the pathology of cancerous cells can be revealed and early precaution can be taken to prevent further proliferation of cancerous cells. In this paper, we propose an innovative hybridised gene identification framework based on genetic algorithms and neural networks to identify marker genes for leukaemia disease. Our approach confirms that high classification accuracy does not ensure the optimal set of genes have been identified and our model delivers a more promising set of genes even with a lower classification accurac

Using decision-tree classifier systems to extract knowledge from databases

One difficulty in applying artificial intelligence techniques to the solution of real world problems is that the development and maintenance of many AI systems, such as those used in diagnostics, require large amounts of human resources. At the same time, databases frequently exist which contain information about the process(es) of interest. Recently, efforts to reduce development and maintenance costs of AI systems have focused on using machine learning techniques to extract knowledge from existing databases. Research is described in the area of knowledge extraction using a class of machine learning techniques called decision-tree classifier systems. Results of this research suggest ways of performing knowledge extraction which may be applied in numerous situations. In addition, a measurement called the concept strength metric (CSM) is described which can be used to determine how well the resulting decision tree can differentiate between the concepts it has learned. The CSM can be used to determine whether or not additional knowledge needs to be extracted from the database. An experiment involving real world data is presented to illustrate the concepts described

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base

Nanoscale, Phonon-Coupled Calorimetry with Sub-Attojoule/Kelvin Resolution

We have developed an ultrasensitive nanoscale calorimeter that enables heat capacity measurements upon minute, externally affixed (phonon-coupled) samples at low temperatures. For a 5 s measurement at 2 K, we demonstrate an unprecedented resolution of ΔC ~ 0.5 aJ/K (~36 000 k_B). This sensitivity is sufficient to enable heat capacity measurements upon zeptomole-scale samples or upon adsorbates with sub-monolayer coverage across the minute cross sections of these devices. We describe the fabrication and operation of these devices and demonstrate their sensitivity by measuring an adsorbed ^4He film with optimum resolution of ~3 × 10^(-5) monolayers upon an active surface area of only ~1.2 × 10^(-9) m^2

Cell-based therapies for ischemic cardiomyopathy : investigations of intramyocardial retention and safety of high dose intracoronary delivery of c-kit positive cardiac progenitor cells, and therapeutic utility of a novel population of cardiac mesenchymal stem cells expressing stage-specific embryonic antigen-3 (SSEA-3).

Over the last decade attempts at reducing morbidity and mortality of patients with chronic heart failure have been made via the development and implementation of novel cell based therapies. Substantial advances in cell based therapies with indications of efficacy have been shown along with a robust safety profile. Despite these advances, there is a substantial unmet need for novel therapies, specifically addressing repair and regeneration of the damaged or lost myocardium and its vasculature. Accordingly, cardiac cell-based therapies have gained attention. Various cell-types have been utilized, including bone marrow-derived mononuclear cells, bone marrow-derived mesenchymal stem cells, mobilized CD34+ cells, and more recently, cardiosphere-derived cells and cardiac-derived c-kit positive progenitor cells. Early studies have suggested a potential of cell-based therapies to reduce cardiac scar size and to improve cardiac function in patients with ischemic cardiomyopathy. However, variability of results has been observed necessitating improvement of current methodologies related to optimizing the cell type(s), infusion techniques, timing, dosage, acuity related to ischemic injury, and perhaps repeat dosing over time among others, all the while ensuring complete and total patient safety. Accordingly, present efforts and goals of my research are aimed at i.) Optimizing methodologies utilized within the recent phase I clinical trial (SCIPIO) that showed intracoronary infusion of 1 million c-kit positive cardiac progenitor cells was safe with indications of efficacy in cardiac repair, as well as, ii.) Development of a novel cell based approach with a newly discovered cardiac cell type. Within the present dissertation, I explored the impact of coronary stop-flow on cardiac retention of intracoronarily infused c-kit positive cardiac progenitor cells given that balloon inflation in a non-stented coronary artery is inherently dangerous, especially in already damaged hearts. I demonstrate that intracardiac retention with or without stop-flow is equivalent and balloon inflation confers an undue risk to patients. Furthermore, I investigated the safety of intracoronary infusion of 20 million c-kit positive cardiac progenitor cells in pigs, an equivalent dose 40 times larger than was used in the SCIPIO trial. High dose of cells delivered intracoronarily is safe and does not result in myocardial injury or functional deficit. Therefore, larger doses may reasonably be utilized in future clinical trials. Finally, I describe a novel adult cardiac cell type that maintains expression of an embryonic stem cell associated marker, stage-specific embryonic antigen (SSEA)-3, resides within the native adult heart, and can be isolated and utilized for cardiac repair as a cell based therapy

Kinetics and Inhibition Studies of the L205R Mutant of cAMP-Dependent Protein Kinase Involved in Cushing’s Syndrome

Overproduction of cortisol by the hypothalamus–pituitary–adrenal hormone system results in the clinical disorder known as Cushing\u27s syndrome. Genomics studies have identified a key mutation (L205R) in the α‐isoform of the catalytic subunit of cAMP‐dependent protein kinase (PKACα) in adrenal adenomas of patients with adrenocorticotropic hormone‐independent Cushing\u27s syndrome. Here, we conducted kinetics and inhibition studies on the L205R‐PKACα mutant. We have found that the L205R mutation affects the kinetics of both Kemptide and ATP as substrates, decreasing the catalytic efficiency (kcat/KM) for each substrate by 12‐fold and 4.5‐fold, respectively. We have also determined the IC50 and Ki for the peptide substrate‐competitive inhibitor PKI(5–24) and the ATP‐competitive inhibitor H89. The L205R mutation had no effect on the potency of H89, but causes a \u3e 250‐fold loss in potency for PKI(5–24). Collectively, these data provide insights for the development of L205R‐PKACα inhibitors as potential therapeutics