Design of an inert fluid injection system, phase 3 Final report

Research, development, and design of velocity trim system for third stage of Delta launch vehicl

Towards understanding Regge trajectories in holographic QCD

We reassess a work done by Migdal on the spectrum of low-energy vector mesons in QCD in the light of the AdS-QCD correspondence. Recently, a tantalizing parallelism was suggested between Migdal's work and a family of holographic duals of QCD. Despite the intriguing similarities, both approaches face a major drawback: the spectrum is in conflict with well-tested Regge scaling. However, it has recently been shown that holographic duals can be modified to accomodate Regge behavior. Therefore, it is interesting to understand whether Regge behavior can also be achieved in Migdal's approach. In this paper we investigate this issue. We find that Migdal's approach, which is based on a modified Pade approximant, is closely related to the issue of quark-hadron duality breakdown in QCD.Comment: 17 pages, 1 figure. Typos fixed, references added, improved discussion. Minor changes to match the journal versio

Ignition of binary alloys of uranium

Experiments determine the effect of alloying additives on the ignition of uranium. Data on oxidation rates, ignition temperatures, and burning curves are provided in the report

Input guide for computer programs to generate thermodynamic data for air and Freon CF4

FORTRAN computer programs were developed to calculate the thermodynamic properties of Freon 14 and air for isentropic expansion from given plenum conditions. Thermodynamic properties for air are calculated with equations derived from the Beattie-Bridgeman nonstandard equation of state and, for Freon 14, with equations derived from the Redlich-Quang nonstandard equation of state. These two gases are used in scale model testing of model rocket nozzle flow fields which requires simulation of the prototype plume shape with a cold flow test approach. Utility of the computer programs for use in analytical prediction of flow fields is enhanced by arranging card or tape output of the data in a format compatible with a method-of-characteristics computer program

Analysis of SRM model nozzle calibration test data in support of IA12B, IA12C and IA36 space shuttle launch vehicle aerodynamics tests

Variations of nozzle performance characteristics of the model nozzles used in the Space Shuttle IA12B, IA12C, IA36 power-on launch vehicle test series are shown by comparison between experimental and analytical data. The experimental data are nozzle wall pressure distributions and schlieren photographs of the exhaust plume shapes. The exhaust plume shapes were simulated experimentally with cold flow while the analytical data were generated using a method-of-characteristics solution. Exhaust plume boundaries, boundary shockwave locations and nozzle wall pressure measurements calculated analytically agree favorably with the experimental data from the IA12C and IA36 test series. For the IA12B test series condensation was suspected in the exhaust plumes at the higher pressure ratios required to simulate the prototype plume shapes. Nozzle calibration tests for the series were conducted at pressure ratios where condensation either did not occur or if present did not produce a noticeable effect on the plume shapes. However, at the pressure ratios required in the power-on launch vehicle tests condensation probably occurs and could significantly affect the exhaust plume shapes

Age, growth, mortality, and radiometric age validation of gray snapper (Lutjanus griseus) from Louisiana

The gray snapper (Lutjanus griseus) is a temperate and tropical reef fish that is found along the Gulf of Mexico and Atlantic coasts of the southeastern United States. The recreational fishery for gray snapper has developed rapidly in south Louisiana with the advent of harvest and seasonal restrictions on the established red snapper (L. campechanus) fishery. We examined the age and growth of gray snapper in Louisiana with the use of cross-sectioned sagittae. A total of 833 specimens, (441 males, 387 females, and 5 of unknown sex) were opportunistically sampled from the recreational fishery from August 1998 to August 2002. Males ranged in size from 222 to 732 mm total length (TL) and from 280 g to 5700 g total weight (TW) and females ranged from 254 to 756 mm TL and from 340 g to 5800 g TW. Both edge analysis and bomb radiocarbon analyses were used to validate otolith-based age estimates. Ages were estimated for 718 individuals; both males and females ranged from 1 to 28 years. The von Bertalanffy growth models derived from TL at age were Lt = 655.4{1–e[–0.23(t)]} for males, Lt = 657.3{1–e[– 0.21(t)]} for females, and L t = 656.4{1–e[– 0.22 (t)]} for all specimens of known sex. Catch curves were used to produce a total mortality (Z) estimate of 0.17. Estimates of M calculated with various methods ranged from 0.15 to 0.50; however we felt that M= 0.15 was the most appropriate estimate based on our estimate of Z. Full recruitment to the gray snapper recreational fishery began at age 4, was completed by age 8, and there was no discernible peak in the catch curve dome

Some aspects of hyperaltitude photogrammetry Report no. 1

Photograph interpretation and photogrammetry of hyperaltitude photography - astrodynamic aspects, camera orientation, and location of objects image

Oxidative stress dependent microRNA-34a activation via PI3Kα reduces the expression of sirtuin-1 and sirtuin-6 in epithelial cells

Sirtuin-1 (SIRT1) and SIRT6, NAD(+)-dependent Class III protein deacetylases, are putative anti-aging enzymes, down-regulated in patients with chronic obstructive pulmonary disease (COPD), which is characterized by the accelerated ageing of the lung and associated with increased oxidative stress. Here, we show that oxidative stress (hydrogen peroxide) selectively elevates microRNA-34a (miR-34a) but not the related miR-34b/c, with concomitant reduction of SIRT1/-6 in bronchial epithelial cells (BEAS2B), which was also observed in peripheral lung samples from patients with COPD. Over-expression of a miR-34a mimic caused a significant reduction in both mRNA and protein of SIRT1/-6, whereas inhibition of miR-34a (antagomir) increased these sirtuins. Induction of miR-34a expression with H2O2 was phosphoinositide-3-kinase (PI3K) dependent as it was associated with PI3Kα activation as well as phosphatase and tensin homolog (PTEN) reduction. Importantly, miR-34a antagomirs increased SIRT1/-6 mRNA levels, whilst decreasing markers of cellular senescence in airway epithelial cells from COPD patients, suggesting that this process is reversible. Other sirtuin isoforms were not affected by miR-34a. Our data indicate that miR-34a is induced by oxidative stress via PI3K signaling, and orchestrates ageing responses under oxidative stress, therefore highlighting miR-34a as a new therapeutic target and biomarker in COPD and other oxidative stress-driven aging diseases

8. Issues in Intelligent Computer-Assisted Instruction: Eval uation and Measurement

In this chapter we plan to explore two issues in the field of intelligent computer assisted instruction (ICAI) that we feel offer opportunities to advance the state of the art. These issues are evaluation of ICAI systems and the use of the underlying technology in ICAI systems to develop tests. For each issue we will provide a theoretical context, discuss key constructs, provide a brief window to the appropriate literature, suggest methodological solutions and conclude with a concrete example of the feasibility of the solution from our own research. INTELLIGENT COMPUTER-ASSISTED INSTRUCTION (ICAI) ICAI is the application of artificial intelligence to computer-assisted instruction. Artificial intelligence, a branch of computer science, is making computers smart in order to (a) make them more useful and (b) understand intelligence (Winston, 1977). Topic areas in artificial intelligence have included natural language processing (Schank, 1980), vision (Winston, 1975), knowledge representation (Woods, 1983), spoken language (Lea, 1980), planning (Hayes-Roth, 1980), and expert systems (Buchanan, 1981). The field of Artificial Intelligence (AI) has matured in both hardware and software. The most commonly used language in the field is LISP (List Processing). A major development in the hardware area is that personal LISP machines are now available at a relatively low cost (20-50K) with the power of prior mainframes. In the software area two advances stand out: (a) programming support environments such as LOOPS (Bobrow & Stefik, 1983) and (b) expert system tools. These latter tools are now running on powerful micros. The application of expert systems technology to a host of real-world problems has demonstrated the utility of artificial intelligence techniques in a very dramatic style. Expert system technology is the branch of artificial intelligence at this point most relevant to ICAI. Expert Systems Knowledge-based systems or expert systems are a collection of problem-solving computer programs containing both factual and experiential knowledge and data in a particular domain. When the knowledge embodied in the program is a result of a human expert elicitation, these systems are called expert systems. A typical expert system consists of a knowledge base, a reasoning mechanism popularly called an inference engine and a friendly user interface. The knowledge base consists of facts, concepts, and numerical data (declarative knowledge), procedures based on experience or rules of thumb (heuristics), and causal or conditional relationships (procedural knowledge). The inference engine searches or reasons with or about the knowledge base to arrive at intermediate conclusions or final results during the course of problem solving. It effectively decides when and what knowledge should be applied, applies the knowledge and determines when an acceptable solution has been found. The inference engine employs several problem-solving strategies in arriving at conclusions. Two of the popular schemes involve starting with a good description or desired solution and working backwards to the known facts or current situation (backward chaining), and starting with the current situation or known facts and working toward a goal or desired solution (forward chaining). The user interface may give the user choices (typically menu-driven) or allow the user to participate in the control of the process (mixed initiative). The interface allows the user: to describe a problem, input knowledge or data, browse through the knowledge base, pose question, review the reasoning process of the system, intervene as necessary, and control overall system operation. Successful expert systems have been developed in fields as diverse as mineral exploration (Duda & Gaschnig, 1981) and medical diagnosis (Clancy, 1981). ICAI Systems ICAI systems use approaches artificial intelligence and cognitive science to teach a range of subject matters. Representative types of subjects include: (a) collection of facts, for example, South American geography in SCHOLAR (Carbonell & Collins, 1973); (b) complete system models, for example, a ship propulsion system in STEAMER (Stevens & Steinberg, 1981) and a power supply in SOPHIE (Brown, Burton, & de Kleer, 1982); (c) completely described procedural rules, for example, strategy learning, WEST (Brown, Burton, & de Kleer, 1982), or arithmetic in BUGGY (Brown & Burton, 1978); (d) partly described procedural rules, for example, computer programming in PROUST (Johnson & Soloway, 1983); LISP Tutor (Anderson, Boyle, & Reiser, 1985); rules in ALGEBRA (McArthur, Stasz, & Hotta, 1987); diagnosis of infectious diseases in GUIDON (Clancey, 1979); and an imperfectly understood complex domain, causes of rainfall in WHY (Stevens, Collins, & Goldin, 1978). Excellent reviews by Barr and Feigenbaum (1982) and Wenger (1987) document many of these ICAI systems. Representative research in ICAI is described by O\u27Neil, Anderson, and Freeman (1986) and Wenger (1987). Although suggestive evidence has been provided by Anderson et al. (1985), few of these ICAI projects have been evaluated in any rigorous fashion. In a sense they have all been toy systems for research and demonstration. Yet, they have raised a good deal of excitement and enthusiasm about their likelihood of being effective instructional environments. With respect to cognitive science, progress has been made in the following areas: identification and analysis of misconceptions or bugs (Clement, Lockhead, & Soloway, 1980), the use of learning strategies (O\u27Neil & Spielberger, 1979; Weinstein & Mayer, 1986), expert versus novice distinction (Chi, Glaser, & Rees, 1982), the role of mental models in learning (Kieras & Bovair, 1983), and the role of self-explanations in problem solving (Chi, Bassok, Lewis, Reimann, & Glaser, 1987). The key components of an ICAI system consist of a knowledge base: that is, (a) what the student is to learn; (b) a student model, either where the student is now with respect to subject matter or how student characteristics interact with subject matters, and (c) a tutor, that is, instructional techniques for teaching the declarative or procedural knowledge. These components are described in more detail by Fletcher (1985)