Solid state photomultiplier for astronomy, phase 2

Epitaxial layers with varying donor concentration profiles were grown on silicon substrate wafers using chemical vapor deposition (CVD) techniques, and solid state photomultiplier (SSPM) devices were fabricated from the wafers. Representative detectors were tested in a low background photon flux, low temperature environment to determine the device characteristics for comparison to NASA goals for astronomical applications. The SSPM temperatures varied between 6 and 11 K with background fluxes in the range from less than 5 x 10 to the 6th power to 10 to the 13th power photons/square cm per second at wavelengths of 3.2 and 20 cm. Measured parameters included quantum efficiency, dark count rate and bias current. Temperature for optimal performance is 10 K, the highest ever obtained for SSPMs. The devices exhibit a combination of the lowest dark current and highest quantum efficiency yet achieved. Experimental data were reduced, analyzed and used to generate recommendations for future studies. The background and present status of the microscopic theory of SSPM operation were reviewed and summarized. Present emphasis is on modeling of the avalanche process which is the basis for SSPM operation. Approaches to the solution of the Boltzmann transport equation are described and the treatment of electron scattering mechanisms is presented. The microscopic single-electron transport theory is ready to be implemented for large-scale computations

Vitrification and determination of the crystallization time scales of the bulk-metallic-glass-forming liquid Zr58.5Nb2.8Cu15.6Ni12.8Al10.3

The crystallization kinetics of Zr58.5Nb2.8Cu15.6Ni12.8Al10.3 were studied in an electrostatic levitation (ESL) apparatus. The measured critical cooling rate is 1.75 K/s. Zr58.5Nb2.8Cu15.6Ni12.8Al10.3 is the first bulk-metallic-glass-forming liquid that does not contain beryllium to be vitrified by purely radiative cooling in the ESL. Furthermore, the sluggish crystallization kinetics enable the determination of the time-temperature-transformation (TTT) diagram between the liquidus and the glass transition temperatures. The shortest time to reach crystallization in an isothermal experiment; i.e., the nose of the TTT diagram is 32 s. The nose of the TTT diagram is at 900 K and positioned about 200 K below the liquidus temperature

Direct microwave measurement of Andreev-bound-state dynamics in a proximitized semiconducting nanowire

The modern understanding of the Josephson effect in mesosopic devices derives from the physics of Andreev bound states, fermionic modes that are localized in a superconducting weak link. Recently, Josephson junctions constructed using semiconducting nanowires have led to the realization of superconducting qubits with gate-tunable Josephson energies. We have used a microwave circuit QED architecture to detect Andreev bound states in such a gate-tunable junction based on an aluminum-proximitized InAs nanowire. We demonstrate coherent manipulation of these bound states, and track the bound-state fermion parity in real time. Individual parity-switching events due to non-equilibrium quasiparticles are observed with a characteristic timescale $T_\mathrm{parity} = 160\pm 10~\mathrm{\mu s}$. The $T_\mathrm{parity}$ of a topological nanowire junction sets a lower bound on the bandwidth required for control of Majorana bound states

A Monte Carlo Approach to Modeling the Breakup of the Space Launch System EM-1 Core Stage with an Integrated Blast and Fragment Catalogue

The Liquid Propellant Fragment Overpressure Acceleration Model (L-FOAM) is a tool developed by Bangham Engineering Incorporated (BEi) that produces a representative debris cloud from an exploding liquid-propellant launch vehicle. Here it is applied to the Core Stage (CS) of the National Aeronautics and Space Administration (NASA) Space Launch System (SLS launch vehicle). A combination of Probability Density Functions (PDF) based on empirical data from rocket accidents and applicable tests, as well as SLS specific geometry are combined in a MATLAB script to create unique fragment catalogues each time L-FOAM is run-tailored for a Monte Carlo approach for risk analysis. By accelerating the debris catalogue with the BEi blast model for liquid hydrogen / liquid oxygen explosions, the result is a fully integrated code that models the destruction of the CS at a given point in its trajectory and generates hundreds of individual fragment catalogues with initial imparted velocities. The BEi blast model provides the blast size (radius) and strength (overpressure) as probabilities based on empirical data and anchored with analytical work. The coupling of the L-FOAM catalogue with the BEi blast model is validated with a simulation of the Project PYRO S-IV destruct test. When running a Monte Carlo simulation, L-FOAM can accelerate all catalogues with the same blast (mean blast, 2 blast, etc.), or vary the blast size and strength based on their respective probabilities. L-FOAM then propagates these fragments until impact with the earth. Results from L-FOAM include a description of each fragment (dimensions, weight, ballistic coefficient, type and initial location on the rocket), imparted velocity from the blast, and impact data depending on user desired application. LFOAM application is for both near-field (fragment impact to escaping crew capsule) and far-field (fragment ground impact footprint) safety considerations. The user is thus able to use statistics from a Monte Carlo set of L-FOAM catalogues to quantify risk for a multitude of potential CS destruct scenarios. Examples include the effect of warning time on the survivability of an escaping crew capsule or the maximum fragment velocities generated by the ignition of leaking propellants in internal cavities

Integrated digital/electric aircraft concepts study

The integrated digital/electrical aircraft (IDEA) is an aircraft concept which employs all electric secondary power systems and advanced digital flight control systems. After trade analysis, preferred systems were applied to the baseline configuration. An additional configuration, the alternate IDEA, was also considered. For this concept the design ground rules were relaxed in order to quantify additional synergistic benefits. It was proposed that an IDEA configuration and technical risks associated with the IDEA systems concepts be defined and the research and development required activities to reduce these risks be identified. The selected subsystems include: power generation, power distribution, actuators, environmental control system and flight controls systems. When the aircraft was resized, block fuel was predicted to decrease by 11.3 percent, with 7.9 percent decrease in direct operating cost. The alternate IDEA shows a further 3.4 percent reduction in block fuel and 3.1 percent reduction in direct operating cost

Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.

ObjectivesEvaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral health. Parent and Child toolkits consist of short-form survey items (12 for children and 8 for parents) with and without children's demographic information (7 questions) to predict the child's oral health status and need for treatment.MethodsData were collected from 12 dental practices in Los Angeles County from 2015 to 2016. We predicted COHSI score and RFTN using random Bootstrap samples with manually introduced Gaussian noise together with machine learning algorithms, such as Extreme Gradient Boosting and Naive Bayesian algorithms (using R). The toolkits predicted the probability of treatment needs and the COHSI score with percentile (ranking). The performance of the toolkits was evaluated internally and externally by residual mean square error (RMSE), correlation, sensitivity and specificity.ResultsThe toolkits were developed based on survey responses from 545 families with children aged 2 to 17 y. The sensitivity and specificity for predicting RFTN were 93% and 49% respectively with the external data. The correlation(s) between predicted and clinically determined COHSI was 0.88 (and 0.91 for its percentile). The RMSEs of the COHSI toolkit were 4.2 for COHSI (and 1.3 for its percentile).ConclusionsSurvey responses from children and their parents/guardians are predictive for clinical outcomes. The toolkits can be used by oral health programs at baseline among school populations. The toolkits can also be used to quantify differences between pre- and post-dental care program implementation. The toolkits' predicted oral health scores can be used to stratify samples in oral health research.Knowledge transfer statementThis study creates the oral health toolkits that combine self- and proxy- reported short forms with children's demographic characteristics to predict children's oral health and treatment needs using Machine Learning algorithms. The toolkits can be used by oral health programs at baseline among school populations to quantify differences between pre and post dental care program implementation. The toolkits can also be used to stratify samples according to the treatment needs and oral health status

Technical Note: Fast two-dimensional GC-MS with thermal extraction for anhydro-sugars in fine aerosols

A fast two-dimensional gas chromatography (GC-MS) method that uses heart-cutting and thermal extraction (TE) and requires no chemical derivatization was developed for the determination of anhydro-sugars in fine aerosols. Evaluation of the TE-GC-GC-MS method shows high average relative accuracy (≥90%), reproducibility (≤10% relative standard deviation), detection limits of less than 3 ng/μL, and negligible carryover for levoglucosan, mannosan, and galactosan markers. TE-GC-GC-MS- and solvent extraction (SE)-GC-MS-measured levoglucosan concentrations correlate across several diverse types of biomass burning aerosols. Because the SE-GC-MS measurements were taken 8 years prior to the TE-GC-GC-MS ones, the stability of levoglucosan is established for quartz filter-collected biomass burning aerosol samples stored at ultra-low temperature (−50 °C). Levoglucosan concentrations (w/w) in aerosols collected following atmospheric dilution near open fires of varying intensity are similar to those in biomass burning aerosols produced in a laboratory enclosure. An average levoglucosan-mannosan-galactosan ratio of 15:2:1 is observed for these two aerosol sets. TE-GC-GC-MS analysis of atmospheric aerosols from the US and Africa produced levoglucosan concentrations (0.01–1.6 μg/m<sup>3</sup>) well within those reported for aerosols collected globally and examined using different analytical techniques (0.004–7.6 μg/m<sup>3</sup>). Further comparisons among techniques suggest that fast TE-GC-GC-MS is among the most sensitive, accurate, and precise methods for compound-specific quantification of anhydro-sugars. In addition, an approximately twofold increase in anhydro-sugar determination may be realized when combining TE with fast chromatography

Deep Markov Random Field for Image Modeling

Markov Random Fields (MRFs), a formulation widely used in generative image modeling, have long been plagued by the lack of expressive power. This issue is primarily due to the fact that conventional MRFs formulations tend to use simplistic factors to capture local patterns. In this paper, we move beyond such limitations, and propose a novel MRF model that uses fully-connected neurons to express the complex interactions among pixels. Through theoretical analysis, we reveal an inherent connection between this model and recurrent neural networks, and thereon derive an approximated feed-forward network that couples multiple RNNs along opposite directions. This formulation combines the expressive power of deep neural networks and the cyclic dependency structure of MRF in a unified model, bringing the modeling capability to a new level. The feed-forward approximation also allows it to be efficiently learned from data. Experimental results on a variety of low-level vision tasks show notable improvement over state-of-the-arts.Comment: Accepted at ECCV 201