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At least 397 records · Page 22

Phase segregation mechanisms of small molecule-polymer blends unraveled by varying polymer chain architecture

As phase separation between the small-molecule semiconductor and the polymer binder is the key enabler of blend-based organic field-effect transistors (OFETs) fabricated by low-cost solution processing, it is crucial to understand the underlying phase separation mechanisms that determine the phase morphology, which significantly impacts device performance. Beyond the parameter space investigated in previous work, here we investigate the formation of blends by varying the branch architecture of the polymer binder and by shortening the solvent dry time using ultrasonic spray casting. The phase morphologies of the resulting blend films have been thoroughly characterized with a variety of techniques in three dimensions over multiple length scales, including AFM, energy-filtered transmission electron microscope, and neutron reflectivity, and have been correlated with electrical transport performance. From the results, we have inferred that the phase morphology is kinetically determined, limited by the inherent slow movement of polymer macromolecules. The kinetic picture, supported by molecular dynamics modeling, not only consistently explains our observations but also resolves inconsistencies in previous works. The achieved mechanistic understanding will guide further optimization of blend-based organic electronics, such as OFETs and organic photovoltaics.

36 MATERIALS SCIENCE↗

Lunar surface chemistry - A new imaging technique

Detailed chemical maps of the lunar surface have been constructed by applying a new weighted-filter imaging technique to Apollo 15 and Apollo 16 X-ray fluorescence data. The data quality improvement is amply demonstrated by (1) modes in the frequency distribution, representing highland and mare soil suites, which are not evident before data filtering, and (2) numerous examples of chemical variations which are correlated with small-scale (about 15 kilometer) lunar topographic features.

Andre, C. G.↗

Inclusion of filter modulation in synthetic-discriminant-function construction

A technique in which the filter modulation is included in the synthesis of a synthetic-discriminant-function (SDF) matched spatial filter is presented. In the filter synthesis, a system of simultaneous nonlinear equations is solved with an iteration procedure. A computer simulation of the new method using thresholded images of the Space Shuttle over a range of aspect angles was performed for phase-only filters (POFs) and binary-phase-only filters (BPOFs). The filters constructed are capable of obtaining the specified peak-correlation response to within 1 percent with a high signal-to-clutter-ratio for the one-class problem, the two-class problem, and the multilevel problem. In contrast, conventional projection SDF POFs and BPOFs are unable to produce the desired peak-correlation response.

Jared, David A.↗

Maximized gust loads for a nonlinear airplane using matched filter theory and constrained optimization

This paper describes and illustrates two matched-filter-theory based schemes for obtaining maximized and time-correlated gust-loads for a nonlinear airplane. The first scheme is computationally fast because it uses a simple one-dimensional search procedure to obtain its answers. The second scheme is computationally slow because it uses a more complex multidimensional search procedure to obtain its answers, but it consistently provides slightly higher maximum loads than the first scheme. Both schemes are illustrated with numerical examples involving a nonlinear control system.

Scott, Robert C.↗

User Interactive Software for Analysis of Human Physiological Data

Ambulatory physiological monitoring has been used to study human health and performance in space and in a variety of Earth-based environments (e.g., military aircraft, armored vehicles, small groups in isolation, and patients). Large, multi-channel data files are typically recorded in these environments, and these files often require the removal of contaminated data prior to processing and analyses. Physiological data processing can now be performed with user-friendly, interactive software developed by the Ames Psychophysiology Research Laboratory. This software, which runs on a Windows platform, contains various signal-processing routines for both time- and frequency- domain data analyses (e.g., peak detection, differentiation and integration, digital filtering, adaptive thresholds, Fast Fourier Transform power spectrum, auto-correlation, etc.). Data acquired with any ambulatory monitoring system that provides text or binary file format are easily imported to the processing software. The application provides a graphical user interface where one can manually select and correct data artifacts utilizing linear and zero interpolation and adding trigger points for missed peaks. Block and moving average routines are also provided for data reduction. Processed data in numeric and graphic format can be exported to Excel. This software, PostProc (for post-processing) requires the Dadisp engineering spreadsheet (DSP Development Corp), or equivalent, for implementation. Specific processing routines were written for electrocardiography, electroencephalography, electromyography, blood pressure, skin conductance level, impedance cardiography (cardiac output, stroke volume, thoracic fluid volume), temperature, and respiration

Cowings, Patricia S.↗

Measurements of dimethyl sulfide and SO2 during GTE/CITE 3

As part of NASA's Tropospheric Experiment Chemical Instrumentation Test and Evaluation (GTE/CITE 3) Sulfur Gas Intercomparison, we conducted measurements of dimethyl sulfide (DMS) and SO2 using two techniques well suited for sampling from an aircraft due to their simplicity of design. DMS was collected by preconcentration on gold wire preceded by a KOH-impregnated filter oxidant scrubber, and analyzed by gas chromatography with flame photometric detection. SO2 was collected on K2CO3/glycerol-impregnated filters and analyzed by ion chromatography. In blind tests, both techniques produced excellent agreement with National Institutes of Standards and Technology (NIST) standards. For field measurements, the DMS technique produced excellent correlation with the mean of the six different techniques intercompared. For SO2, the five techniques intercompared were rather poorly correlated, but correlations between the three techniques which passed NIST standards tests were somewhat better. Our SO2 filter measurements exhibited rather large uncertainties due to higher than normal variabiltiy of the filter blanks, which we believe was caused by extended storage in the field. In measurements conducted off the coast of Natal, Brazil, a diurnal afternoon minimum in DMS concentrations accompanied by a corresponding maximum in SO2 concentrations was observed. However, due to rather large uncertainties in the SO2 measurements, any conclusions about the SO2 trend must by considered tentative.

Ferek, Ronald J.↗

A matched filter method for ground-based sub-noise detection of terrestrial extrasolar planets in eclipsing binaries: application to CM Draconis

The photometric detection of extrasolar planets by transits in eclipsing binary systems can be significantly improved by cross-correlating the observational light curves with synthetic models of possible planetary transit features, essentially a matched filter approach. We demonstrate the utility and application of this transit detection algorithm for ground-based detections of terrestrial-sized (Earth-to-Neptune radii) extrasolar planets in the dwarf M-star eclipsing binary system CM Draconis. Preliminary photometric observational data of this system demonstrate that the observational noise is well characterized as white and Gaussian at the observational time steps required for precision photometric measurements. Depending on planet formation scenarios, terrestrial-sized planets may form quite close to this low-luminosity system. We demonstrate, for example, that planets as small as 1.4 Earth radii with periods on the order of a few months in the CM Draconis system could be detected at the 99.9% confidence level in less than a year using 1-m class telescopes from the ground. This result contradicts commonly held assumptions limiting present ground-based efforts to, at best, detections of gas giant planets after several years of observation. This method can be readily extended to a number of other larger star systems with the utilization of larger telescopes and longer observing times. Its extension to spacecraft observations should also allow the determination of the presence of terrestrial-sized planets in nearly 100 other known eclipsing binary systems.

NASA Discipline Number 52-10↗

Achromatical Optical Correlator

Signal-to-noise ratio exceeds that of monochromatic correlator. Achromatical optical correlator uses multiple-pinhole diffraction of dispersed white light to form superposed multiple correlations of input and reference images in output plane. Set of matched spatial filters made by multiple-exposure holographic process, each exposure using suitably-scaled input image and suitable angle of reference beam. Recording-aperture mask translated to appropriate horizontal position for each exposure. Noncoherent illumination suitable for applications involving recognition of color and determination of scale. When fully developed achromatical correlators will be useful for recognition of patterns; for example, in industrial inspection and search for selected features in aerial photographs.

Chao, Tien-Hsin↗

Compact Optical Correlator

Optical cross-correlator indicates position of target (if any) in scene matching target encoded in matched filter. Size reduced by use of prisms to fold optical path. Device designed, assembled from commercial components, and tested to verify feasibility of miniaturization for eventual incorporation into navigational and/or control systems of autonomous vehicles. For example, aircraft equipped with optical correlator recognizes prescribed target and measures its position, so that it lands on target under automatic control.

Scholl, Marija S.↗

Improved Discrete Approximation of Laplacian of Gaussian

An improved method of computing a discrete approximation of the Laplacian of a Gaussian convolution of an image has been devised. The primary advantage of the method is that without substantially degrading the accuracy of the end result, it reduces the amount of information that must be processed and thus reduces the amount of circuitry needed to perform the Laplacian-of- Gaussian (LOG) operation. Some background information is necessary to place the method in context. The method is intended for application to the LOG part of a process of real-time digital filtering of digitized video data that represent brightnesses in pixels in a square array. The particular filtering process of interest is one that converts pixel brightnesses to binary form, thereby reducing the amount of information that must be performed in subsequent correlation processing (e.g., correlations between images in a stereoscopic pair for determining distances or correlations between successive frames of the same image for detecting motions). The Laplacian is often included in the filtering process because it emphasizes edges and textures, while the Gaussian is often included because it smooths out noise that might not be consistent between left and right images or between successive frames of the same image.

Shuler, Robert L., Jr.↗

Optimizing binary phase and amplitude filters for PCE, SNR, and discrimination

Binary phase-only filters (BPOFs) have generated much study because of their implementation on currently available spatial light modulator devices. On polarization-rotating devices such as the magneto-optic spatial light modulator (SLM), it is also possible to encode binary amplitude information into two SLM transmission states, in addition to the binary phase information. This is done by varying the rotation angle of the polarization analyzer following the SLM in the optical train. Through this parameter, a continuum of filters may be designed that span the space of binary phase and amplitude filters (BPAFs) between BPOFs and binary amplitude filters. In this study, we investigate the design of optimal BPAFs for the key correlation characteristics of peak sharpness (through the peak-to-correlation energy (PCE) metric), signal-to-noise ratio (SNR), and discrimination between in-class and out-of-class images. We present simulation results illustrating improvements obtained over conventional BPOFs, and trade-offs between the different performance criteria in terms of the filter design parameter.

Downie, John D.↗

Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures

Decades of drug development research have explored a vast chemical space for highly active compounds. The exponential growth of virtual libraries enables easy access to billions of synthesizable molecules. Computational modeling, particularly molecular docking, utilizes physics-based calculations to prioritize molecules for synthesis and testing. Nevertheless, the molecular docking process often yields docking poses with favorable scores that prove to be inaccurate with experimental testing. To address these issues, several approaches using machine learning (ML) have been proposed to filter incorrect poses based on the crystal structures. However, most of the methods are limited by the availability of structure data. Here, we propose a new pose classification approach, PECAN2 (Pose Classification with 3D Atomic Network 2), without the need for crystal structures, based on a 3D atomic neural network with Point Cloud Network (PCN). The new approach uses the correlation between docking scores and experimental data to assign labels, instead of relying on the crystal structures. We validate the proposed classifier on multiple datasets including human mu, delta, and kappa opioid receptors and SARS-CoV-2 Mpro. Our results demonstrate that leveraging the correlation between docking scores and experimental data alone enhances molecular docking performance by filtering out false positives and false negatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Block Lanczos algorithm for lattice QCD spectroscopy and matrix elements

Recent work introduced a new framework for analyzing correlation functions with improved convergence and signal-to-noise properties, as well as rigorous quantification of excited-state effects, based on the Lanczos algorithm and spurious eigenvalue filtering with the Cullum-Willoughby test. Here, we extend this framework to the analysis of correlation-function matrices built from multiple interpolating operators in lattice quantum chromodynamics (QCD) by constructing an oblique generalization of the block Lanczos algorithm, as well as a new physically motivated reformulation of the Cullum-Willoughby test that generalizes to block Lanczos straightforwardly. The resulting block Lanczos method directly extends generalized eigenvalue problem (GEVP) methods, which can be viewed as applying a single iteration of block Lanczos. Block Lanczos provides qualitative and quantitative advantages over GEVP methods analogous to the benefits of Lanczos over the standard effective mass, including faster convergence to ground- and excited-state energies, explicitly computable two-sided error bounds, straightforward extraction of matrix elements of external currents, and asymptotically constant signal-to-noise. No fits or statistical inference are required. Proof-of-principle calculations are performed for noiseless mock-data examples as well as two-by-two proton correlation-function matrices in lattice QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

AI-based Cyber Event OSINT via Twitter Data

Open-Source Intelligence (OSINT) is largely regarded as a necessary component for cybersecurity intelligence gathering to secure network systems. With the advancement of artificial intelligence (AI) and increasing usage of social media, like Twitter, we have a unique opportunity to obtain and aggregate information from social media. In this study, we propose an AI-based scheme capable of automatically pulling information from Twitter, filtering out security-irrelevant tweets, performing natural language analysis to correlate the tweets about each cybersecurity event (e.g., a malware campaign), and validating the information. This scheme has many applications, such as providing a means for security operators to gain insight into ongoing events and helping them prioritize vulnerabilities to deal with. To give examples of the possible uses, we present three case studies demonstrating the event discovery and investigation processes.

Dale, Dakota↗

Square-root algorithm for evaluating mismodeled process noise

As the application of sequential filters has grown, the need has arisen to evaluate the sensitivity of these filters to mismodeling of the random process. A numerically reliable square-root algorithm is developed for calculating the covariances of estimates from a sequential filter which incorrectly models process noise. Mismodeling is restricted to the correlation time and standard deviation of a random process represented as a first-order Gauss-Markov sequence. Using a computer program which employs this algorithm, a sensitivity analysis was performed for several types of earth-based tracking data from an interplanetary spacecraft.

Thornton, C. L.↗

Automatic target recognition using a feature-based optical neural network

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

Chao, Tien-Hsin↗

Efficient Hybrid Actuation Using Solid-State Actuators

Piezohydraulic actuation is the use of fluid to rectify the motion of a piezoelectric actuator for the purpose of overcoming the small stroke limitations of the material. In this work we study a closed piezohydraulic circuit that utilizes active valves to rectify the motion of a hydraulic end affector. A linear, lumped parameter model of the system is developed and correlated with experiments. Results demonstrate that the model accurately predicts the filtering of the piezoelectric motion caused by hydraulic compliance. Accurate results are also obtained for predicting the unidirectional motion of the cylinder when the active valves are phased with respect to the piezoelectric actuator. A time delay associated with the mechanical response of the valves is incorporated into the model to reflect the finite time required to open or close the valves. This time delay is found to be the primary limiting factor in achieving higher speed and greater power from the piezohydraulic unit. Experiments on the piezohydraulic unit demonstrate that blocked forces on the order of 100 N and unloaded velocities of 180 micrometers/sec are achieved.

Leo, Donald J.↗

Inclusion of Linearized Moist Physics in Nasa's Goddard Earth Observing System Data Assimilation Tools

Inclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa-Schubert (RAS) convection scheme has been developed and tested in NASA's Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encountered. Efficient filtering of these profiles is achieved by diagnosis of steep gradients in a reduced version of the operator of the tangent linear model. With filtering turned on, the inclusion of linearized moist physics increases the correlation between the nonlinear perturbation trajectory and the linear approximation of the perturbation trajectory. A month-long observation impact experiment is performed and the effect of including moist physics on the impacts is discussed. Impacts from moist-sensitive instruments and channels are increased. The effect of including moist physics is examined for adjoint sensitivity studies. A case study examining an intensifying Northern Hemisphere Atlantic storm is presented. The results show a significant sensitivity with respect to moisture.

Convection↗