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TruePAL – An AI Assistant for First Responder Safety
This paper presents the development of an AI assistant, Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL), to provide real-time warning of risks of potential crashes to the first responders. The TruePAL system employs an AI and deep learning technology for saving first responders and roadside crews lives in and around active traffic. A deep neural network (DNN) and a Non-Axiomatic Reasoning System (NARS) are implemented as an AI system. A mobile app with AI interface is developed to perform verbal communication with the first responders. The TruePAL team has developed an explainable AI approach by opening up the DNN blackbox to extract the activation filters of various features and parts of the targeted objects. The combination of DNN and NARS makes the TruePAL system explainable to the users. TruePAL ingests on-board cameras, radar, and other sensor signals, analyzes the environment and traffic patterns to generate timely warning to drivers and roadside crews to avoid crashes. The TruePAL team, in collaboration with the Miami/Dade Police Dept., has designed five use cases and multiple sub-scenarios in a CARLA driving simulator to test the capability of TruePAL in timely warning to the first responder drivers in potential crash scenarios. We have successfully demonstrated its capability of timely warning in over a dozen scenarios based on the use cases. The preliminary test simulation results show that TruePAL could provide the drivers and crew members advanced warning before a crash occurs.
Two-Color Laser Speckle Shift Strain Measurement System
A two color laser speckle shift strain measurement system based on the technique of Yamaguchi was designed. The dual wavelength light output from an Argon Ion laser was coupled into two separate single-mode optical fibers (patchcords). The output of the patchcords is incident on the test specimen (here a structural fiber). Strain on the fiber, in one direction, is produced using an Instron 4502. Shifting interference patterns or speckle patterns will be detected at real-time rates using 2 CCD cameras with image processing performed by a hardware correlator. Strain detected in fibers with diameters from 21 microns to 143 microns is expected to be resolved to 15 mu epsilon. This system was designed to be compact and robust and does not require surface preparation of the structural fibers.
Patterns of Local-Regional Management Following Neoadjuvant Chemotherapy in Breast Cancer: Results From ACOSOG Z1071 (Alliance)
Purpose: American College of Surgeons Oncology Group Z1071 was a prospective trial evaluating the false negative rate of sentinel lymph node (SLN) surgery after neoadjuvant chemotherapy (NAC) in breast cancer patients with initial node-positive disease. Radiation therapy (RT) decisions were made at the discretion of treating physicians, providing an opportunity to evaluate variability in practice patterns following NAC. Methods and Materials: Of 756 patients enrolled from July 2009 to June 2011, 685 met all eligibility requirements. Surgical approach, RT, and radiation field design were analyzed based on presenting clinical and pathologic factors. Results: Of 401 node-positive patients, mastectomy was performed in 148 (36.9%), mastectomy with immediate reconstruction in 107 (26.7%), and breast-conserving surgery (BCS) in 146 patients (36.4%). Of the 284 pathologically node-negative patients, mastectomy was performed in 84 (29.6%), mastectomy with immediate reconstruction in 69 (24.3%), and BCS in 131 patients (46.1%). Bilateral mastectomy rates were higher in women undergoing reconstruction than in those without (66.5% vs 32.2%, respectively, P<.0001). Use of internal mammary RT was low (7.8%-11.2%) and did not differ between surgical approaches. Supraclavicular RT rate ranged from 46.6% to 52.2% and did not differ between surgical approaches but was omitted in 193 or 408 node-positive patients (47.3%). Rate of axillary RT was more frequent in patients who remained node-positive (P=.002). However, 22% of patients who converted to node-negative still received axillary RT. Post-mastectomy RT was more frequently omitted after reconstruction than mastectomy (23.9% vs 12.1%, respectively, P=.002) and was omitted in 19 of 107 patients (17.8%) with residual node-positive disease in the reconstruction group. Conclusions: Most clinically node-positive patients treated with NAC undergoing mastectomy receive RT. RT is less common in patients undergoing reconstruction. There is wide variability in RT fields. These practice patterns conflict with expert recommendations and ongoing trial guidelines. There is a significant need for greater uniformity and guidelines regarding RT following NAC.
Optimal carbon storage reservoir management through deep reinforcement learning
Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decision-making problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Finally, experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.
Multi-Maneuver Clohessy-Wiltshire Targeting
Orbital rendezvous involves execution of a sequence of maneuvers by a chaser vehicle to bring the chaser to a desired state relative to a target vehicle while meeting intermediate and final relative constraints. Intermediate and final relative constraints are necessary to meet a multitude of requirements such as to control approach direction, ensure relative position is adequate for operation of space-to-space communication systems and relative sensors, provide fail-safe trajectory features, and provide contingency hold points. The effect of maneuvers on constraints is often coupled, so the maneuvers must be solved for as a set. For example, maneuvers that affect orbital energy change both the chaser's height and downrange position relative to the target vehicle. Rendezvous designers use experience and rules-of-thumb to design a sequence of maneuvers and constraints. A non-iterative method is presented for targeting a rendezvous scenario that includes a sequence of maneuvers and relative constraints. This method is referred to as Multi-Maneuver Clohessy-Wiltshire Targeting (MM_CW_TGT). When a single maneuver is targeted to a single relative position, the classic CW targeting solution is obtained. The MM_CW_TGT method involves manipulation of the CW state transition matrix to form a linear system. As a starting point for forming the algorithm, the effects of a series of impulsive maneuvers on the state are derived. Simple and moderately complex examples are used to demonstrate the pattern of the resulting linear system. The general form of the pattern results in an algorithm for formation of the linear system. The resulting linear system relates the effect of maneuver components and initial conditions on relative constraints specified by the rendezvous designer. Solution of the linear system includes the straight-forward inverse of a square matrix. Inversion of the square matrix is assured if the designer poses a controllable scenario - a scenario where the the constraints can be met by the sequence of maneuvers. Matrices in the linear system are dependent on selection of maneuvers and constraints by the designer, but the matrices are independent of the chaser's initial conditions. For scenarios where the sequence of maneuvers and constraints are fixed, the linear system can be formed and the square matrix inverted prior to real-time operations. Example solutions are presented for several rendezvous scenarios to illustrate the utility of the method. The MM_CW_TGT method has been used during the preliminary design of rendezvous scenarios and is expected to be useful for iterative methods in the generation of an initial guess and corrections.
Closing the Gap Between Modeling and Experiments in the Self-assembly of Biomolecules at Interfaces and in Solution
Molecular self-assembly is a powerful tool in materials design, wherein non-covalent interactions like electrostatic, hydrophobic, hydrogen bonding, and van der Waals can be exploited to produce supramolecular nanostructures that are functional and highly tunable. Biomolecules are attractive building blocks, as they are biocompatible, biodegradable and adopt a wide array of higher order structures. Moreover, naturally occurring protein systems display a manifold of structures and interactions that can be replicated in synthetic biomolecules. In this perspective, we highlight advances in multiscale simulation techniques across broad spatiotemporal scales that can aid in characterizing self-assembly of hybrid and hierarchical bionanomaterial systems, with an emphasis on physics-based simulation approaches currently employed to study biomolecules at mineral interfaces. The power of these approaches is highlighted across a few recent areas where molecular simulations have advanced our understanding of self-assembly spanning peptides to protein self-assembly. Looking forward, we discuss how in the near future emerging methods in statistical and machine learning will advance this research field in all areas from expanding the capabilities of physics-based simulation methods to enabling new analyses of high throughput experiments. These advances will pave the way for understanding the molecular recognition patterns in systems that are dictated by self-assembly - biomineralizing peptides, hierarchical peptoids, and large protein assemblies, and will aid in the development of a new synthesis science for achieving precise molecular control in materials design
Subsonic Aircraft With Regression and Neural-Network Approximators Designed
At the NASA Glenn Research Center, NASA Langley Research Center's Flight Optimization System (FLOPS) and the design optimization testbed COMETBOARDS with regression and neural-network-analysis approximators have been coupled to obtain a preliminary aircraft design methodology. For a subsonic aircraft, the optimal design, that is the airframe-engine combination, is obtained by the simulation. The aircraft is powered by two high-bypass-ratio engines with a nominal thrust of about 35,000 lbf. It is to carry 150 passengers at a cruise speed of Mach 0.8 over a range of 3000 n mi and to operate on a 6000-ft runway. The aircraft design utilized a neural network and a regression-approximations-based analysis tool, along with a multioptimizer cascade algorithm that uses sequential linear programming, sequential quadratic programming, the method of feasible directions, and then sequential quadratic programming again. Optimal aircraft weight versus the number of design iterations is shown. The central processing unit (CPU) time to solution is given. It is shown that the regression-method-based analyzer exhibited a smoother convergence pattern than the FLOPS code. The optimum weight obtained by the approximation technique and the FLOPS code differed by 1.3 percent. Prediction by the approximation technique exhibited no error for the aircraft wing area and turbine entry temperature, whereas it was within 2 percent for most other parameters. Cascade strategy was required by FLOPS as well as the approximators. The regression method had a tendency to hug the data points, whereas the neural network exhibited a propensity to follow a mean path. The performance of the neural network and regression methods was considered adequate. It was at about the same level for small, standard, and large models with redundancy ratios (defined as the number of input-output pairs to the number of unknown coefficients) of 14, 28, and 57, respectively. In an SGI octane workstation (Silicon Graphics, Inc., Mountainview, CA), the regression training required a fraction of a CPU second, whereas neural network training was between 1 and 9 min, as given. For a single analysis cycle, the 3-sec CPU time required by the FLOPS code was reduced to milliseconds by the approximators. For design calculations, the time with the FLOPS code was 34 min. It was reduced to 2 sec with the regression method and to 4 min by the neural network technique. The performance of the regression and neural network methods was found to be satisfactory for the analysis and design optimization of the subsonic aircraft.
Self-organization of nanoparticles and molecules in periodic Liesegang-type structures
Chemical organization in reaction-diffusion systems offers a strategy for the generation of materials with ordered morphologies and structural hierarchy. Periodic structures are formed by either molecules or nanoparticles. On the premise of new directing factors and materials, an emerging frontier is the design of systems in which the precipitation partners are nanoparticles and molecules. We show that solvent evaporation from a suspension of cellulose nanocrystals (CNCs) and L -(+)-tartaric acid [ L -(+)-TA] causes phase separation and precipitation, which, being coupled with a reaction/diffusion, results in rhythmic alternation of CNC-rich and L -(+)-TA–rich rings. The CNC-rich regions have a cholesteric structure, while the L -(+)-TA–rich bands are formed by radially aligned elongated bundles. The moving edge of the pattern propagates with a finite constant velocity, which enables control of periodicity by varying film preparation conditions. This work expands knowledge about self-organizing reaction-diffusion systems and offers a strategy for the design of self-organizing materials.
Faster Antenna Noise Temperature Calculations Using a Novel Approximation Technique
In order to properly tradeoff the various antenna and feed configurations for the Square Kilometre Array (SKA) optical design it is necessary to evaluate the gain and noise temperature of each configuration over a wide range of frequencies. German Cortes describes the standard technique for computing antenna noise temperature. However, since the total antenna pattern needs to be calculated over the entire 4 pi steradians at a fine enough resolution to accurately include the main beam, the computer time required is enormous. Even at modest frequencies and reflector sizes (approximately 5 to 10 GHz for a 12 meter main reflector) the technique can take days on a single node of a supercomputer. Utilizing the standard technique to compute the noise temperature for all the cases required to properly characterize the SKA design is clearly not feasible. At least a 100 to 1000 speedup in the computation time is required. This paper describes an approximation technique that can accomplish this improvement with extremely small errors in noise temperature calculation of a few tenths of Kelvin.
The first radio astronomy from space - RAE
The spacecraft design, instrumentation, and performance of the Radio Astronomy Explorer (RAE) satellites (RAE-1 launched to earth orbit in 1968 and RAE-2 launched to lunar orbit in 1972) are reviewed and illustrated with drawings, diagrams, and graphs of typical data. Consideration is given to the three pairs of antennas, the Ryle-Vonberg and burst radiometers, and problems encountered with antenna deployment and observing patterns. Results summarized include observations of type III solar bursts, the spectral distribution of cosmic noise in broad sky regions, Jupiter at low frequencies, and auroral kilometric radiation (AKR) from the earth. The importance of avoiding the AKR bands in designing future space observatories is stressed.
Stabilizing Ni-rich layered cathode for high-voltage operation through hierarchically heterogeneous doping with concentration gradient
High-nickel LiNi x Mn y Co 1-x-y O 2 (NMC) cathodes have demonstrated superior energy density, yet their stability is compromised under high voltage conditions. To address this, here we propose a strategy of heterogeneous doping with a concentration gradient, specifically through Sr–Zr co-modification. We synthesized Ni-rich NMC particles featuring several micron-sized secondary particles composed of micron-sized primary grains. This design aims to harness the structural robustness of single-crystalline grains and the favorable diffusion kinetics of polycrystalline secondary particles. Systematic characterization using a combination of electrochemical measurements and synchrotron analytics reveals an intriguing pattern of hierarchically heterogeneous Sr–Zr co-doping. It demonstrates a depth-dependent concentration gradient at the secondary particle level and competing dopant segregation over the buried grain boundaries. This unique characteristic creates opportunities for enhancing battery performance, particularly by optimizing precursors and implementing advanced modulation techniques. We also investigate the dissolution and precipitation of the cathode's transition metal cations upon high-voltage cycling. These insights suggest that a tailored compositional variation can be a viable approach to effectively design the next-generation high-Ni NMC cathode materials for high-voltage lithium batteries.
Recent progress in the development of transition radiation detectors
Transition-radiation detectors have been used in several recent cosmic-ray experiments for particle identification at energies E/mc-squared of at least about 1000. In order to optimize the design of such detectors and to use them for energy measurements over a broad energy range, it is necessary to study the details of the transition-radiation process. Experimental results are presented which test the theoretical predictions more precisely and at higher energies than in previous experiments. The dependence of the interference pattern in the frequency spectrum on the radiator dimensions is studied, and the total transition-radiation yield generated by electrons in various radiators is measured over a very wide energy range, from 5 to 300 GeV. The significance of the individual experimental parameters in the design of transition radiation detectors is reviewed, and the characteristics of transition-radiation detectors capable of measuring particle energies over the range E/mc-squared from about 300 to 100,000 are discussed.
Organizing bacterial vortex lattices by periodic obstacle arrays
Recent experiments have shown that the complex spatio-temporal vortex structures emerging in active fluids are susceptible to weak geometrical constraints. This observation poses the fundamental question of how boundary effects stabilize a highly ordered pattern from seemingly turbulent motion. Here we show, by a combination of continuum theory and experiments on a bacterial suspension, how artificial obstacles guide the flow profile and reorganize topological defects, which enables the design of bacterial vortex lattices with tunable properties. To this end, the continuum model is extended by appropriate boundary conditions. Beyond the stabilization of square and hexagonal lattices, we also provide a striking example of a chiral, antiferromagnetic lattice exhibiting a net rotational flow, which is induced by arranging the obstacles in a Kagome-like array. Recent experiments showed that weak geometrical constraints can organize topological defects in turbulent bacterial suspensions. Here, the authors use a continuum model to study the connection between symmetry and stability of emergent vortex patterns and the geometry of constraining pillar arrays.
Flow studies in close-coupled ventral nozzles for STOVL aircraft
Flow in a generic ventral nozzle system was studied experimentally and analytically with the PARC3D computational fluid dynamics program (a full Navier-Stokes equations solver) in order to evaluate the program's ability to predict system performance and internal flow patterns. A generic model of a tailpipe with a rectangular ventral nozzle, about one-third of full size, was tested with unheated air at steady-state pressure ratios up to 4.0. Measurements showed about 5.5 percent flow-turning loss and reasonable nozzle performance coefficients. The flow turned more than the designed 90 deg, causing an aftward axial component in the total thrust. Flow behavior into and through the ventral duct is discussed and illustrated with paint streak flow visualization photographs. PARC3D graphic images are shown for comparison with the experiment photographs. The program successfully predicted internal flow patterns; it also computed thrust and discharge coefficients within 1 percent of measured values.
X-Band CubeSat Communication System Demonstration
Today's CubeSats mostly operate their communications at UHF- and S-band frequencies. UHF band is presently crowded, thus downlink communications are at lower data rates due to bandwidth limitations and are unreliable due to interference. This research presents an end-to-end robust, innovative, compact, efficient and low cost S-band uplink and X-band downlink CubeSat communication system demonstration between a balloon and a Near Earth Network (NEN) ground system. Since communication systems serve as umbilical cords for space missions, demonstration of this X-band communication system is critical for successfully supporting current and future CubeSat communication needs. This research has three main objectives. The first objective is to design, simulate, and test a CubeSat S- and X-band communication system. Satellite Tool Kit (STK) dynamic link budget calculations and HFSS Simulations and modeling results have been used to trade the merit of various designs for small satellite applications. S- and X-band antennas have been tested in the compact antenna test range at Goddard Space Flight Center (GSFC) to gather radiation pattern data. The second objective is simulate and test a CubeSat compatible X-band communication system at 12.5Mbps including S-band antennas, X-band antennas, Laboratory for Atmospheric and Space Physics (LASP) /GSFC transmitter and an S-band receiver from TRL-5 to TRL-8 by the end of this effort. Different X-band communication system components (antennas, diplexers, etc.) from GSFC, other NASA centers, universities, and private companies have been investigated and traded, and a complete component list for the communication system baseline has been developed by performing analytical and numerical analysis. This objective also includes running simulations and performing trades between different X-band antenna systems to optimize communication system performance. The final objective is to perform an end-to-end X-band CubeSat communication system demonstration between a balloon and/or a sounding rocket and a Near Earth Network (NEN) ground system. This paper presents CubeSat communication systems simulation results, analysis of X-band and S-band antennas and RF front-end components, transceiver design, analysis and optimization of space-to-ground communication performance, subsystem development, as well as the test results for an end-to-end X-band CubeSat communication system demonstration. The outcome of this work will be used to pave the way for next generation NEN-compatible X-band CubeSat communication systems to support higher data rates with more advanced modulation and forward error correction (FEC) coding schemes, and to support and attract new science missions at lower cost. It also includes an abbreviated concept of operations for CubeSat users to utilize the NEN, starting from first contact with NASA's communication network and continuing through on-orbit operations.
Catalytic Upgrading of Renewable Feedstock (Final Technical Report)
The goal of this DOE-funded project was to investigate the fundamental science related to the development of homogeneous (de)hydrogenation catalysts in order to enable energy-relevant transformations of bio-relevant chemical feedstocks including ethanol. The primary focus was to improve the activity of ethanol upgrading catalysts, specifically informed through mechanistic studies, in order to enable rational design optimization strategies. Following in depth mechanistic studies, targeted reaction optimization approaches included ligand redesign to improve catalyst stability, developing new carbon-carbon bond forming reactions using ethanol as a precursor, and examining photochemically-mediated reactions, ultimately to integrate within other reactor designs such as continuous flow reactors. The high modularity of the catalyst components (ligands) has enabled the preparation and analyses of multiple catalyst precursors. These studies uncovered an unexpectedly beneficial substitution pattern of the ligand structure that led to the development of new catalysts that are the best in class for upgrading ethanol to butanol with a turnover number of 155,890 and a turnover frequency of 12,690 h –1 . In addition to upgrading ethanol to butanol, cascade reaction sequences were developed to form new C-C bonds using ethanol as a bio-relevant feedstock, providing access to platform chemicals from renewable sources. As part of the reaction discovery process, new mechanistic details were uncovered that provided insights into: a) catalyst speciation, b) decomposition pathways, c) carbon monoxide releasing pathways, and d) carbon-carbon and carbon hydrogen bond breaking pathways. Most of these outcomes were previously not known; however, they provide important directions for new catalyst design strategies. Finally, use of high throughput and in situ photochemical reaction analyses enabled detailed studies into changes to the catalyst structure upon irradiation. Irradiation was found to improve hydrogen transfer catalysis, by promoting a ligand dissociation event.
IDEAL: Images Across Domains, Experiments, Algorithms and Learning
Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this article, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.