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At least 415 records · Page 23

Fractal mechanisms and heart rate dynamics. Long-range correlations and their breakdown with disease

Under healthy conditions, the normal cardiac (sinus) interbeat interval fluctuates in a complex manner. Quantitative analysis using techniques adapted from statistical physics reveals the presence of long-range power-law correlations extending over thousands of heartbeats. This scale-invariant (fractal) behavior suggests that the regulatory system generating these fluctuations is operating far from equilibrium. In contrast, it is found that for subjects at high risk of sudden death (e.g., congestive heart failure patients), these long-range correlations break down. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiologic models of systems that appear to be heterodynamic rather than homeostatic.

NASA Discipline Cardiopulmonary↗

Operational Assimilation of GOES Data into a Mesoscale Model

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite- observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the Global Hydrology and Climate Center (GHCC) within the Penn State/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) since 1 November 1998. We performed the assimilation on a model grid centered over the Southeastern US. In addition, a control run without assimilation was performed to provide insight into the performance of the assimilation technique. Bulk verification statistics (BIAS and RMSE) of surface air temperature and relative humidity of more than 250 case days has been performed to date. Results show that assimilation of the satellite data results reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. We are working with forecasters at the National Weather Service Forecast Office located in Birmingham, AL to evaluate the impact of the assimilation on precipitation forecasts. In addition, work is currently underway to determine the ability of both the assimilation technique and Early Eta to sense the significant changes that occur in both leaf expansion and soil moisture conditions during the Spring-Summer of 1999. This will be accomplished via examination of the simulated surface energy budgets from both modeling systems.

Lapenta, William↗

Reduction of flow-measurement uncertainties in laser velocimeters with nonorthogonal channels

An analysis of certain geometrical limitations inherent in the application of laser velocimeters with nonorthogonal channels has led to the development of advanced-LDA-calibration and data-acquisition techniques that minimize systematic and statistical errors, respectively. The data-acquisition technique optimizes the number of velocity samples collected from three velocimeter channels as a function of local turbulence intensity, vector direction, and prescribed confidence interval. Linear velocity surveys and streamline traces measured in a turbulent flow field with a three-dimensional laser velocimeter are presented and the validity and accuracy of the theoretical analysis are discussed.

Snyder, P. K.↗

Environmental Assessment and Monitoring with ICAMS (Image Characterization and Modeling System) Using Multiscale Remote-Sensing Data

With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.

Lam, N.↗

Print-Consistency and Process-Interaction for Inkjet-Printed Copper on Flexible Substrate

Printed electronics is a fastest growing and emerging technology that have shown much potential in several industries including automotive, wearables, healthcare, and aerospace. Its applications can be found not only in flexible but also in large area electronics. The technology provides an effective and convenient method to additively deposit conductive and insulating materials on any type of substrate. Comparing with traditional manufacturing processes, which involves chemical etching, this technology also comes to be relatively environmental friendly. Despite its status, it is not without its challenges. Starting from the material being compatible in the printer equipment to the point of achieving fine resolutions, and with excellent properties are some of the challenges that printed electronics face. Among the myriad of printing technologies such as Aerosol Jet, micro-dispensing, gravure printing, screen printing, Inkjet printing, Inkjet has gained much attention due to its low-cost, low material consumption, and roll-to-roll capability for mass manufacturing. The technology has been widely used in home and office, but recently gained interest in printed electronics in a research and development setting. Conductive materials used in Inkjet printing generally comprises of metal Nanoparticles that need to be thermally sintered for it to be conductive. The preferred metal of choice has been mostly silver due to its excellent electrical properties and ease in sintering. However, silver comes to be expensive than its counterpart copper. Since copper is prone to oxidation, much focus has been given towards photonic sintering that involves sudden burst of pulsed light at certain energy to sinter the copper Nanoparticles. With this technique, only the printed material gets sintered in a matter of seconds without having a great impact on its substrate, due to which it is also preferred in low temperature applications. With all the knowledge, there is still a large gap in the process side with copper where it is important to look how the print process affects the resolution of the print along with the effect of post-print processes on electrical and mechanical properties. In this paper, a copper Inkjet ink is utilized for understanding the effect of Inkjet print parameters on the ejected droplet and its resolution. Post-print process is also quantified using a photonic sintering equipment for excellent electrical and mechanical properties. To demonstrate the complete process, commercial-off-the-shelf components will also be mounted on the additively printed pads via Inkjet. Statistically, control charting technique will be utilized to understand the capability of the Inkjet process.

printed electronics↗

Quantitative measurements of dislocations in metals for advancing predictive simulations

LLNL applications require scientists to predict how materials evolve under various thermomechanical conditions. While this is achieved through physics-based simulations, uncertainty in the predictions of mechanical properties remains a serious challenge that limits the predictive capabilities of models because we lack methods to compare predictions of atomic-scale defects (dislocations) with experimental measurements. High energy X-ray diffraction (HEXRD) is the most relevant technique that can provide the necessary statistical information on dislocations. However, this technique is not yet quantitative because we lack a precise understanding of the relationship between X-ray diffraction patterns and the underlying material dislocation content and arrangements. To address this need, we used our novel computational X-ray diffraction method to simulate the effect of dislocations on the diffraction patterns. We compared virtual and experimental diffraction patterns. Results allowed us to clearly establish the relationship between X-ray diffraction patterns and the underlying dislocation structures, proving that it is feasible to quantitatively measure dislocation statistics with HEXRD. This project delivered a method that can provide the missing piece to LLNL’s mechanical property simulations in advanced metals by obtaining experimentally long-needed quantitative dislocation data, which could fully enable predictive capabilities.

36 MATERIALS SCIENCE↗

CV4Quantum: Reducing the Sampling Overhead in Probabilistic Error Cancellation Using Control Variates

Quasiprobabilistic decompositions (QPDs) play a key role in maximizing the utility of near-term quantum hardware. For example, Probabilistic Error Cancellation (PEC) (an error mitigation technique) and circuit cutting (which enables large quantum computations to be performed on quantum hardware with a limited number of qubits) both involve QPDs. Computations based on QPDs typically incur large sampling overheads that grow exponentially with the number of error-terms mitigated or number of circuit-cuts employed, limiting their practical feasibility. In this work, we adapt the control variates variance reduction technique from the statistics literature in order to reduce the sampling overhead in QPD-based computations. We demonstrate our method using simulation experiments that mimic a realistic PEC scenario. In our experiments, we observed a more than 50% reduction in the number of samples needed to achieve a given precision, in more than 50% of the PEC-based estimations performed in the study when using our approach. We discuss how future research on constructing good control variates can lead to even stronger sampling overhead reduction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Prediction analysis and management decisions.

Prediction analysis techniques /PAT/ using statistical methods, computers, error analysis, etc, for system weight, performance and other parameter predictions in Apollo program

PROGRAM MANAGEMENT↗

The analysis of Gemini 7 EEG data by three different computer oriented methods

The problem in assessment of electroencephalograms has been the subject element in visual evaluations of such records as well as the need for extensive training (2 or 3 years) before suitable candidate is capable to perform this task. There have been variety of computer type analyses of EEG during the past ten years or more, and we are still searching for a reliable, inexpensive, online data processing procedure for this task. We are aware our Soviet colleagues are routinely using computer assessment of EEGs, using relatively inexpensive hardware. In our report we endeavor to show how four different assessment procedures (visual assessment, zero crossing technique, smoothing and peak counting technique, and Weibull Statistic) may be utilized, and indicate the advantages and disadvantages peculiar to each. We wish to point out that in the Gemini 7 EEG analog records supplied to the Henry Ford Hospital, Channel II (mid-line central to mid-line occipital electrodes) could not be assessed reliably after approximately 26 hours of flight. Channel I (left central to left occipital electrodes) provided the more assessable EEG up to approximately 54 hours of flight. These channels were compared during the first 26 hours of flight, and no significant difference was found by our various assessment procedures. We, therefore, have limited this report to the findings on the analyses of Channel I during its approximate 54 hours of flight.

Proctor, L. D.↗

Designing for auto safety

Safety design features in the motor vehicle and highway construction fields result from systems analysis approach to prevent or lessen death, injury, and property damage results. Systems analysis considers the prevention of crashes, increased survivability in crashes, and prompt medical attention to injuries as well as other postcrash salvage measures. The interface of these system elements with the driver, the vehicle, and the environment shows that action on the vehicle system produces the greatest safety payoff through design modifications. New and amended safety standards developed through hazard analysis technique improved accident statistics in the 70'; these regulations include driver qualifications and countermeasures to identify the chronic drunken driver who is involved in more than two-thirds of all auto deaths.

Elwood T. Driver↗

A note on signal enhancement for dual magnetometer systems.

Demonstration of the value of cross-correlation signal enhancement achieved by means of a dual magnetometer system. A unique feature of a dual magnetometer system is, as pointed out by Ness et al. (1971), the opportunity it allows for signal enhancement by using cross-correlation techniques developed in statistical communication theory. Their use is shown to make it possible to overcome the limitations that the intrinsic sensor ambient noise and the measurement-contaminating spacecraft field fluctuations impose upon the signal detection performance of a single magnetometer.

Ness, N. F.↗

User oriented ERTS-1 images

Photographic reproduction of ERTS-1 images are capable of displaying only a portion of the total information available from the multispectral scanner. Methods are being developed to generate ERTS-1 images oriented towards special users such as agriculturists, foresters, and hydrologists by applying image enhancement techniques and interactive statistical classification schemes. Spatial boundaries and linear features can be emphasized and delineated using simple filters. Linear and nonlinear transformations can be applied to the spectral data to emphasize certain ground information. An automatic classification scheme was developed to identify particular ground cover classes such as fallow, grain, rape seed or various vegetation covers. The scheme applies the maximum likelihood decision rule to the spectral information and classifies the ERTS-1 image on a pixel by pixel basis. Preliminary results indicate that the classifier has limited success in distinguishing crops, but is well adapted for identifying different types of vegetation.

Shlien, S.↗

Cloud type pattern recognition using environmental satellite data

A classification analysis is conducted concerning the tropical cloud types as remotely sensed in the visual and infrared range by ITOS scanning radiometers. A statistical pattern recognition technique is used to examine the ability of coincident dual-channel and single-channel data to classify four main forms of clouds, including cumulus, stratocumulus, cumulonimbus, and cirrus.

Booth, A. L.↗

Influences of physical training on the heart of dogs

To investigate the effects of physical training on cardiac dimensions and function, eight dogs were exercised for 12 weeks by treadmill running 1 hour/day, 5 days/week. Five dogs were confined in cages as controls for an 8-week period. Heart rates were monitored by telemetry during rest and exercise. Maximum QRS spatial magnitudes were calculated from records of McFee lead electrocardiograms. Left ventricular end-diastolic dimensions were determined radiographically by the bead and clip technique. Training produced statistically significant decreases in heart rate at rest and at a standard work load of 6.1 mph on a level treadmill and statistically significant increases in work load at a standard heart rate of 194 beats/min. Improvements were rapid during the first 4 weeks of training but gradual during the remaining 8 weeks. Training caused small but statistically significant increases in left ventricular end-diastolic wall thickness, estimated left ventricular mass, and maximum QRS spatial magnitude.

Wyatt, H. L.↗

Operations analysis (study 2.1): Program manual and users guide for the LOVES computer code

Information is provided necessary to use the LOVES Computer Program in its existing state, or to modify the program to include studies not properly handled by the basic model. The Users Guide defines the basic elements assembled together to form the model for servicing satellites in orbit. As the program is a simulation, the method of attack is to disassemble the problem into a sequence of events, each occurring instantaneously and each creating one or more other events in the future. The main driving force of the simulation is the deterministic launch schedule of satellites and the subsequent failure of the various modules which make up the satellites. The LOVES Computer Program uses a random number generator to simulate the failure of module elements and therefore operates over a long span of time typically 10 to 15 years. The sequence of events is varied by making several runs in succession with different random numbers resulting in a Monte Carlo technique to determine statistical parameters of minimum value, average value, and maximum value.

Wray, S. T., Jr.↗