Supporting flight data analysis for Space Shuttle Orbiter experiments at NASA Ames Research Center

The space shuttle orbiter experiments program is responsible for collecting flight data to extend the research and technology base for future aerospace vehicle design. The infrared imagery of shuttle (IRIS), catalytic surface effects, and tile gap heating experiments sponsored by Ames Research Center are part of this program. The software required to process the flight data which support these experiments is described. In addition, data analysis techniques, developed in support of the IRIS experiment, are discussed. Using the flight data base, the techniques provide information useful in analyzing and correcting problems with the experiment, and in interpreting the IRIS image obtained during the entry of the third shuttle mission

Elimination Theory for Nonlinear Parameter Estimation

The work presented here exploits elimination theory (solving systems of polynomial equations in several variables) [1][2] to perform nonlinear parameter identification. In particular show how this technique can be used to estimate the rotor time constant and the stator resistance values of an induction machine. Although the example here is restricted to an induction machine, parameter estimation is applicable to many practical engineering problems. In [3], L. Ljung has outlined many of the challenges of nonlinear system identification as well as its particular importance for biological systems. In these types of problems, the model developed for analysis is typically a nonlinear state space model with unknown parameter values. The typical situation is that only a few of the state variables are measurable requiring that the system be reformulated as a nonlinear input-output model. In turn, resulting the nonlinear input-output model is almost always nonlinear in the parameters. Towards that end, differential algebra tools for analysis of nonlinear systems have been developed by Michel Fliess [4][5] and Diop [6]. Moreover, Ollivier [7] as well as Ljung and Glad [8] have developed the use of the characteristic set of an ideal as a tool for identification problems. The use of these differential algebraic methods for system identification have also been considered in [9], [10]. The focus of their research has been the determination of a priori identifiability of a given system model. However, as stated in [10], the development of an efficient algorithm using these differential algebraic techniques is still unknown. Here, in contrast, a method for which one can actually numerically obtain the numerical value of the parameters is presented. We also point out that [11] has also done work applying elimination theory to systems problems

Polynomial approximation of quasipolynomials based on digital filter design principles

This contribution is aimed at a possible procedure approximating quasipolynomials by polynomials. Quasipolynomials appear in linear time-delay systems description as a natural consequence of the use of the Laplace transform. Due to their infinite root spectra, control system analysis and synthesis based on such quasipolynomial models are usually mathematically heavy. In the light of this fact, there is a natural research endeavor to design a sufficiently accurate yet simple engineeringly acceptable method that approximates them by polynomials preserving basic spectral information. In this paper, such a procedure is presented based on some ideas of discrete-time (digital) filters designing without excessive math. Namely, the particular quasipolynomial is subjected to iterative discretization by means of the bilinear transformation first; consequently, linear and quadratic interpolations are applied to obtain integer powers of the approximating polynomial. Since dominant roots play a decisive role in the spectrum, interpolations are made in their very neighborhood. A simulation example proofs the algorithm efficiency. © Springer International Publishing Switzerland 2016

Upravljanje asimetričnim inverterom ujednačenog koraka s 13 razina korištenjem optimizacije roja čestica

Harmonic Elimination Strategy (HES) has been a widely researched alternative to traditional PWM techniques. This paper presents the harmonic elimination strategy of a Uniform Step Asymmetrical Multilevel Inverter (USAMI) using Particle Swarm Optimization (PSO) which eliminates specified higher order harmonics while maintaining the required fundamental voltage. This method can be applied to USAMI with any number of levels. As an example, in this paper a 13-level USAMI is considered and the optimum switching angles are calculated to eliminate the 5th, 7th, 11th, 13th and 17th harmonics. The HES-PSO approach is compared to the well-known Sinusoidal Pulse-Width Modulation (SPWM) strategy. Simulation results demonstrate the better performances and technical advantages of the HES-PSO controller in feeding an asynchronous machine. Indeed, the harmonic distortions are efficiently cancelled providing thus an optimized control signal for the asynchronous machine. Moreover, the technique presented here substantially reduces the torque undulations.Strategija eliminacije harmonika je dobro istražena alternativa tradicionalnoj pulso-širinskoj modulaciji. U ovom radu opisana je strategija eliminacije harmonika asimetričnog višerazinskog invertera ujednačenog koraka uz korištenje optimizacije roja čestica čime se eliminiraju harmonici višeg reda uz zadržavanje fundamentalnog napona. Takva metoda može se primijeniti neovisno o broju razina invertera. Kao primjer korišten je inverter s 13 razina kod kojeg se eliminiraju peti, sedmi, jedanaesti, trinaesti i sedamnaesti harmonik. Predloženo rješenje uspoređeno je s dobro poznatom sinusnom pulsno-širinskom modulacijom. Simulacijski rezultati pokazuju prednosti predloženog rješenja. Harmonička distorzija je uspješno poništena te je upravljački signal za asinkroni stroj optimalan. Štoviše, predložena tehnika znatno smanjuje promjene momenta

Comparative Analysis of the Frequency and Distribution of Stem and Progenitor Cells in the Adult Mouse Brain

cells (NSCs) and progenitor cells, but it cannot discriminate between these two populations. Given two assays have purported to overcome this shortfall, we performed a comparative analysis of the distribution and frequency of NSCs and progenitor cells detected in 400 m coronal segments along the ventricular neuraxis of the adult mouse brain using the neurosphere assay, the neural colony forming cell assay (N-CFCA), and label-retaining cell (LRC) approach. We observed a large variation in the number of progenitor/stem cells detected in serial sections along the neuraxis, with the number of neurosphereforming cells detected in individual 400 m sections varying from a minimum of eight to a maximum of 891 depending upon the rostral-caudal coordinate assayed. Moreover, the greatest variability occurred in the rostral portion of the lateral ventricles, thereby explaining the large variation in neurosphere frequency previously reported. Whereas the overall number of neurospheres (3730 276) or colonies (4275 124) we detected along the neuraxis did not differ significantly, LRC numbers were significantly reduced (1186 188, 7 month chase) in comparison to both total colonies and neurospheres. Moreover, approximately two orders of magnitude fewer NSC-derived colonies (50 10) were detected using the N-CFCA as compared to LRCs. Given only 5% of the LRCs are cycling (BrdU/Ki-67) or competent to divide (BrdU/Mcm-2), and proliferate upon transfer to culture, it is unclear whether this technique selectively detects endogenous NSCs. Overall, caution should be taken with the interpretation and employment of all these techniques

Effects of Prandial Versus Fasting Glycemia on Cardiovascular Outcomes in Type 2 Diabetes: The HEART2D trial

OBJECTIVE—Hyperglycemia and Its Effect After Acute Myocardial Infarction on Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus (HEART2D) is a multinational, randomized, controlled trial designed to compare the effects of prandial versus fasting glycemic control on risk for cardiovascular outcomes in patients with type 2 diabetes after acute myocardial infarction (AMI)

Ten-Year Mortality and Cardiovascular Morbidity in the Finnish Diabetes Prevention Study—Secondary Analysis of the Randomized Trial

The Finnish Diabetes Prevention Study (DPS) was a randomized controlled trial, which showed that it is possible to prevent type 2 diabetes by lifestyle changes. The aim of the present study was to examine whether the lifestyle intervention had an effect on the ten-year mortality and cardiovascular morbidity in the DPS participants originally randomized either into an intervention or control group. Furthermore, we compared these results with a population-based cohort comprising individuals of varying glucose tolerance states.Middle-aged, overweight people with IGT (n = 522) were randomized into intensive intervention (including physical activity, weight reduction and dietary counseling), or control "mini-intervention" group. Median length of the intervention period was 4 years and the mean follow-up was 10.6 years. The population-based reference study cohort included 1881 individuals (1570 with normal glucose tolerance, 183 with IGT, 59 with screen-detected type 2 diabetes, 69 with previously known type 2 diabetes) with the mean follow-up of 13.8 years. Mortality and cardiovascular morbidity data were collected from the national Hospital Discharge Register and Causes of Death Register. Among the DPS participants who consented for register linkage (n = 505), total mortality (2.2 vs. 3.8 per 1000 person years, hazard ratio HR = 0.57, 95% CI 0.21-1.58) and cardiovascular morbidity (22.9 vs. 22.0 per 1000 person years, HR = 1.04, 95% CI 0.72-1.51) did not differ significantly between the intervention and control groups. Compared with the population-based cohort with impaired glucose tolerance, adjusted HRs were 0.21 (95% CI 0.09-0.52) and 0.39 (95% CI 0.20-0.79) for total mortality, and 0.89 (95% CI 0.62-1.27) and 0.87 (0.60-1.27) for cardiovascular morbidity in the intervention and control groups of the DPS, respectively. The risk of death in DPS combined cohort was markedly lower than in FINRISK IGT cohort (adjusted HR 0.30, 95% CI 0.17-0.54), but there was no significant difference in the risk of CVD (adjusted HR 0.88, 95% CI 0.64-1.21).Lifestyle intervention among persons with IGT did not decrease cardiovascular morbidity during the first 10 years of follow-up. However, the statistical power may not be sufficient to detect small differences between the intervention and control groups. Low total mortality among participants of the DPS compared with individuals with IGT in the general population could be ascribed to a lower cardiovascular risk profile at baseline and regular follow-up.ClinicalTrials.gov NCT00518167

Simple Nudges for Better Password Creation

Recent security breaches have highlighted the consequences of reusing passwords across online accounts. Recent guidance on password policies by the UK government recommend an emphasis on password length over an extended character set for generating secure but memorable passwords without cognitive overload. This paper explores the role of three nudges in creating website-specific passwords: financial incentive (present vs absent), length instruction (long password vs no instruction) and stimulus (picture present vs not present). Mechanical Turk workers were asked to create a password in one of these conditions and the resulting passwords were evaluated based on character length, resistance to automated guessing attacks, and time taken to create the password. We found that users created longer passwords when asked to do so or when given a financial incentive and these longer passwords were harder to guess than passwords created with no instruction. Using a picture nudge to support password creation did not lead to passwords that were either longer or more resistant to attacks but did lead to account-specific passwords