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This is the first story in a new series of success stories focused on restorative justice work. The work featured in these stories seeks to acknowledge the impact of harmful practices and creates opportunities to heal that harm between those who enacted it and those impacted by it to transform the community. This report discusses The Hive, which is a Black-led, intergenerational and multi-racial community that believes in a world where all young people feel like they belong and have the resources they need to become independent, healthy and thriving adults. Its model challenges conventional pathways through the juvenile justice and child welfare systems by engaging legacy work, where helping emerging adults build their skills and healing practices enables them to be drivers of generational transformation. The Hive believe that tangible investments in the diverse needs of young people can reverse the intergenerational trauma caused by systemic racism and solve our community's most pressing issues.

Background: We extend recently proposed design-based capture-recapture methods for prevalence estimation among registry participants, in order to support causal inference among a trial-eligible target population. The proposed design for CRC analysis integrates an observational study cohort with a randomized trial involving a small representative study sample, and enhances the generalizability and transportability of the findings. Methods: We develop a novel CRC-type estimator derived via multinomial distribution-based maximum-likelihood that exploits the design to deliver benefits in terms of validity and efficiency for comparing the effects of two treatments on a binary outcome. Additionally, the design enables a direct standardization-type estimator for efficient estimation of general means (e.g., of biomarker levels) under a specific treatment, and for their comparison across treatments. For inference, we propose a tailored Bayesian credible interval approach to improve coverage properties in conjunction with the proposed CRC estimator for binary outcomes, along with a bootstrap percentile interval approach for use in the case of continuous outcomes. Results: Simulations demonstrate the proposed estimators derived from the CRC design. The multinomial-based maximum-likelihood estimator shows benefits in terms of validity and efficiency in treatment effect comparisons, while the direct standardization-type estimator allows comprehensive comparison of treatment effects within the target population. Conclusion: The extended CRC methods provide a useful framework for causal inference in a trial-eligible target population by integrating observational and randomized trial data. The novel estimators enhance the generalizability and transportability of findings, offering efficient and valid tools for treatment effect comparisons on both binary and continuous outcomes.

The field of artificial intelligence (AI) is rapidly influencing health and healthcare, but bias and poor performance persists for populations who face widespread structural oppression. Previous work has clearly outlined the need for more rigorous attention to data representativeness and model performance to advance equity and reduce bias. However, there is an opportunity to also improve the explainability of AI by leveraging best practices of social epidemiology and health equity to help us develop hypotheses for associations found. In this paper, we focus on explainable AI (XAI) and describe a framework for interdisciplinary expert panel review to discuss and critically assess AI model explanations from multiple perspectives and identify areas of bias and directions for future research. We emphasize the importance of the interdisciplinary expert panel to produce more accurate, equitable interpretations which are historically and contextually informed. Interdisciplinary panel discussions can help reduce bias, identify potential confounders, and identify opportunities for additional research where there are gaps in the literature. In turn, these insights can suggest opportunities for AI model improvement.

The OraQuick In-Home HIV self-test represents a fast, inexpensive, and convenient method for users to assess their HIV status. If integrated thoughtfully into existing testing practices, accompanied by efficient pathways to formal diagnosis, self-testing could both enhance HIV awareness and reduce HIV incidence. However, currently available self-tests are less sensitive, particularly for recent infection, than gold-standard laboratory tests. It is important to understand the impact if some portion of standard testing is replaced by self-tests. We introduced a novel compartmental model to evaluate the effects of self-testing among gay, bisexual and other men who have sex with men (MSM) in the United States for the period 2020 to 2030. We varied the model for different screening rates, self-test proportions, and delays to diagnosis for those identified through self-tests to determine the potential impact on HIV incidence and awareness of status. When HIV self-tests are strictly supplemental, self-testing can decrease HIV incidence among MSM in the US by up to 10% and increase awareness of status among MSM from 85% to 91% over a 10-year period, provided linkage to care and formal diagnosis occur promptly following a positive self-test (90 days or less). As self-tests replace a higher percentage laboratory-based testing algorithms, increases in overall testing rates were necessary to ensure reductions in HIV incidence. However, such increases were small (under 10% for prompt engagement in care and moderate levels of replacement). Improvements in self-test sensitivity and/or decreases in the detection period may further reduce any necessary increases in overall testing. Our study suggests that, if properly utilized, self-testing can provide significant long-term reductions to HIV incidence and improve awareness of HIV status.

A solution to the MiniBooNE excess invoking rare three-body decays of the charged pions and kaons to new states in the MeV mass scale was recently proposed as a dark-sector explanation. This class of solution illuminates the fact that, while the charged pions were focused in the target-mode run, their decay products were isotropically suppressed in the beam-dump-mode run in which no excess was observed. This suggests a new physics solution correlated to the mesonic sector. We investigate an extended set of phenomenological models that can explain the MiniBooNE excess as a dark sector solution, utilizing long-lived particles that might be produced in the three-body decays of the charged mesons and the two-body anomalous decays of the neutral mesons. Over a broad set of interactions with the long-lived particles, we show that these scenarios can be compatible with constraints from LSND, KARMEN, and MicroBooNE, and evaluate the sensitivity of the ongoing and future data taken by the Coherent CAPTAIN Mills experiment (CCM) to a potential discovery in this parameter space. See addendum for updated predictions for future MicroBooNE sensitivity., Comment: Addendum (in preparation for PRD) appended with forecast for MicroBooNE sensitivity to the MiniBooNE excess. Added reference to open source code for simulation of the horn-focused charged mesons

Monitoring key elements of disease dynamics (e.g., prevalence, case counts) is of great importance in infectious disease prevention and control, as emphasized during the COVID-19 pandemic. To facilitate this effort, we propose a new capture-recapture (CRC) analysis strategy that takes misclassification into account from easily-administered, imperfect diagnostic test kits, such as the Rapid Antigen Test-kits or saliva tests. Our method is based on a recently proposed "anchor stream" design, whereby an existing voluntary surveillance data stream is augmented by a smaller and judiciously drawn random sample. It incorporates manufacturer-specified sensitivity and specificity parameters to account for imperfect diagnostic results in one or both data streams. For inference to accompany case count estimation, we improve upon traditional Wald-type confidence intervals by developing an adapted Bayesian credible interval for the CRC estimator that yields favorable frequentist coverage properties. When feasible, the proposed design and analytic strategy provides a more efficient solution than traditional CRC methods or random sampling-based biased-corrected estimation to monitor disease prevalence while accounting for misclassification. We demonstrate the benefits of this approach through simulation studies that underscore its potential utility in practice for economical disease monitoring among a registered closed population.

In epidemiological studies, the capture-recapture (CRC) method is a powerful tool that can be used to estimate the number of diseased cases or potentially disease prevalence based on data from overlapping surveillance systems. Estimators derived from log-linear models are widely applied by epidemiologists when analyzing CRC data. The popularity of the log-linear model framework is largely associated with its accessibility and the fact that interaction terms can allow for certain types of dependency among data streams. In this work, we shed new light on significant pitfalls associated with the log-linear model framework in the context of CRC using real data examples and simulation studies. First, we demonstrate that the log-linear model paradigm is highly exclusionary. That is, it can exclude, by design, many possible estimates that are potentially consistent with the observed data. Second, we clarify the ways in which regularly used model selection metrics (e.g., information criteria) are fundamentally deceiving in the effort to select a best model in this setting. By focusing attention on these important cautionary points and on the fundamental untestable dependency assumption made when fitting a log-linear model to CRC data, we hope to improve the quality of and transparency associated with subsequent surveillance-based CRC estimates of case counts.

AI models have shown promise in many medical imaging tasks. However, our ability to explain what signals these models have learned is severely lacking. Explanations are needed in order to increase the trust in AI-based models, and could enable novel scientific discovery by uncovering signals in the data that are not yet known to experts. In this paper, we present a method for automatic visual explanations leveraging team-based expertise by generating hypotheses of what visual signals in the images are correlated with the task. We propose the following 4 steps: (i) Train a classifier to perform a given task (ii) Train a classifier guided StyleGAN-based image generator (StylEx) (iii) Automatically detect and visualize the top visual attributes that the classifier is sensitive towards (iv) Formulate hypotheses for the underlying mechanisms, to stimulate future research. Specifically, we present the discovered attributes to an interdisciplinary panel of experts so that hypotheses can account for social and structural determinants of health. We demonstrate results on eight prediction tasks across three medical imaging modalities: retinal fundus photographs, external eye photographs, and chest radiographs. We showcase examples of attributes that capture clinically known features, confounders that arise from factors beyond physiological mechanisms, and reveal a number of physiologically plausible novel attributes. Our approach has the potential to enable researchers to better understand, improve their assessment, and extract new knowledge from AI-based models. Importantly, we highlight that attributes generated by our framework can capture phenomena beyond physiology or pathophysiology, reflecting the real world nature of healthcare delivery and socio-cultural factors. Finally, we intend to release code to enable researchers to train their own StylEx models and analyze their predictive tasks., Comment: 43 pages, 1 figure

Epidemiologic screening programs often make use of tests with small, but non-zero probabilities of misdiagnosis. In this article, we assume the target population is finite with a fixed number of true cases, and that we apply an imperfect test with known sensitivity and specificity to a sample of individuals from the population. In this setting, we propose an enhanced inferential approach for use in conjunction with sampling-based bias-corrected prevalence estimation. While ignoring the finite nature of the population can yield markedly conservative estimates, direct application of a standard finite population correction (FPC) conversely leads to underestimation of variance. We uncover a way to leverage the typical FPC indirectly toward valid statistical inference. In particular, we derive a readily estimable extra variance component induced by misclassification in this specific but arguably common diagnostic testing scenario. Our approach yields a standard error estimate that properly captures the sampling variability of the usual bias-corrected maximum likelihood estimator of disease prevalence. Finally, we develop an adapted Bayesian credible interval for the true prevalence that offers improved frequentist properties (i.e., coverage and width) relative to a Wald-type confidence interval. We report the simulation results to demonstrate the enhanced performance of the proposed inferential methods.

We propose a monitoring strategy for efficient and robust estimation of disease prevalence and case numbers within closed and enumerated populations such as schools, workplaces, or retirement communities. The proposed design relies largely on voluntary testing, notoriously biased (e.g., in the case of COVID-19) due to non-representative sampling. The approach yields unbiased and comparatively precise estimates with no assumptions about factors underlying selection of individuals for voluntary testing, building on the strength of what can be a small random sampling component. This component unlocks a previously proposed "anchor stream" estimator, a well-calibrated alternative to classical capture-recapture (CRC) estimators based on two data streams. We show here that this estimator is equivalent to a direct standardization based on "capture", i.e., selection (or not) by the voluntary testing program, made possible by means of a key parameter identified by design. This equivalency simultaneously allows for novel two-stream CRC-like estimation of general means (e.g., of continuous variables such as antibody levels or biomarkers). For inference, we propose adaptations of a Bayesian credible interval when estimating case counts and bootstrapping when estimating means of continuous variables. We use simulations to demonstrate significant precision benefits relative to random sampling alone.

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database.

Temporal computing promises to mitigate the stringent area constraints and clock distribution overheads of traditional superconducting digital computing. To design a scalable, area- and power-efficient superconducting network on chip (NoC), we propose packet-switched superconducting temporal NoC (PaST-NoC). PaST-NoC operates its control path in the temporal domain using race logic (RL), combined with bufferless deflection flow control to minimize area. Packets encode their destination using RL and carry a collection of data pulses that the receiver can interpret as pulse trains, RL, serialized binary, or other formats. We demonstrate how to scale up PaST-NoC to arbitrary topologies based on 2x2 routers and 4x4 butterflies as building blocks. As we show, if data pulses are interpreted using RL, PaST-NoC outperforms state-of-the-art superconducting binary NoCs in throughput per area by as much as 5x for long packets., Comment: 14 pages, 18 figures, 2 tables. In press in IEEE Transactions on Applied Superconductivity

The front end of Los Alamos Neutron Science Center (LANSCE) linear accelerator uses four 201.25-MHz Drift-Tube Linacs (DTLs) to accelerate the H+ and H- beams to 100 MeV. Three of the 201.25-MHz DTLs are powered by diacrodes and the first DTL is powered by a tetrode. A 20-kW solid-state power amplifier (SSPA) is used to provide ~15 kW drive power to the tetrode. The SSPA is water-cooled and consists of 24 push-pull LDMOS transistors operating at 45% of their power saturation capability, providing ample power headroom and excellent linearity. However, the phase of the SSPA is perturbed at +/-20 degrees over a few ten minutes partially caused by the temperature dependent phase variation of the air-cooled SSPA driver circulator. This phase variation consumes most of the phase control margin of the cavity field feedback controller. In order to mitigate the effect of the SSPA phase variation on the cavity field, a disturbance observer controller (DOBC) has been designed and implemented on the cavity field control FPGA, which functions in parallel with the cavity field feedback controller. In this paper, the DOBC design and its function as well as its short- and long-term performance are addressed., Comment: Poster presented at LLRF Workshop 2022 (LLRF2022, arXiv:2208.13680)

We show results from the Coherent CAPTAIN Mills (CCM) 2019 engineering run which begin to constrain regions of parameter space for axion-like particles (ALPs) produced in electromagnetic particle showers in an 800 MeV proton beam dump, and further investigate the sensitivity of ongoing data-taking campaigns for the CCM200 upgraded detector. Based on beam-on background estimates from the engineering run, we make realistic extrapolations for background reduction based on expected shielding improvements, reduced beam width, and analysis-based techniques for background rejection. We obtain reach projections for two classes of signatures; ALPs coupled primarily to photons can be produced in the tungsten target via the Primakoff process, and then produce a gamma-ray signal in the Liquid Argon (LAr) CCM detector either via inverse Primakoff scattering or decay to a photon pair. ALPs with significant electron couplings have several additional production mechanisms (Compton scattering, $e^+e^-$ annihilation, ALP-bremsstrahlung) and detection modes (inverse Compton scattering, external $e^+e^-$ pair conversion, and decay to $e^+e^-$). In some regions, the constraint is marginally better than both astrophysical and terrestrial constraints. With the beginning of a three year run, CCM will be more sensitive to this parameter space by up to an order of magnitude for both ALP-photon and ALP-electron couplings. The CCM experiment will also have sensitivity to well-motivated parameter space of QCD axion models. It is only a recent realization that accelerator-based large volume liquid argon detectors designed for low energy coherent neutrino and dark matter scattering searches are also ideal for probing ALPs in the unexplored $\sim$MeV mass scale., Comment: Accepted for publication in Physical Review D, in production

We study efficient quantum error correction schemes for the fully correlated channel on an $n$-qubit system with error operators that assume the form $\sigma_x^{\otimes n}$, $\sigma_y^{\otimes n}$, $\sigma_z^{\otimes n}$. Previous schemes are improved to facilitate implementation. In particular, when $n$ is odd and equals $2k+1$, we describe a quantum error correction scheme using one arbitrary qubit $\sigma$ to protect the data state $\rho$ in a $2k$-qubit system. The encoding operation $\sigma \otimes \rho \mapsto \Phi(\sigma \otimes \rho)$ only requires $3k$ CNOT gates (each with one control bit and one target bit). After the encoded state $\Phi(\sigma\otimes \rho)$ goes through the channel, we can apply the inverse operation $\Phi^{-1}$ to produce $\tilde \sigma \otimes \rho$ so that a partial trace operation can recover $\rho$. When $n$ is even and equals $2k+2$, we describe a hybrid quantum error correction scheme using any one of the two classical bits $\sigma \in \{|ij\rangle \langle ij|: i, j \in \{0,1\}\}$ to protect a $2k$-qubit state $\rho$ and 2 classical bits. The encoding operation $\sigma \otimes \rho \mapsto \Phi(\sigma \otimes \rho)$ can be done by $3k+2$ CNOT gates and a single quibt Hadamard gate. After the encoded state $\Phi(\sigma\otimes \rho)$ goes through the channel, we can apply the inverse operation $\Phi^{-1}$ to produce $\sigma \otimes \rho$ so that a perfect protection of the two classical bits $\sigma$ and the $2k$-qubit state is achieved. If one uses an arbitrary $2$-qubit state $\sigma$, the same scheme will protect $2k$-qubit states. The scheme was implemented using Matlab, Mathematica, Python, and the IBM's quantum computing framework qiskit., Comment: 18 pages, 4 figures

A field experiment tested effects of "Channel One" commercials on impulsive preadolescent students' purchasing preferences, such as product liking and likelihood of buying regularly advertised products. A total of 67 sixth-grade middle school students participated in the field experiment. Students who viewed "Channel One' daily were in eight first-period classes while students from the control school were in their homeroom class (experimental, N=51; control, N=16). The most significant findings were that more impulsive students were slightly (10%) more likely to want to buy products advertised on "Channel One" than were less impulsive students. Females, regardless of impulsivity, were more likely to predict they would spend more on products advertised, and exhibited more impulsive-type purchasing, compared to their male peers. Future research should concentrate on changes in attitude to products advertised on the program--studies should compare beginning of the school year and end of the school year attitudes. (Contains 5 tables of data, 2 figures, and 31 references.) (Author/NKA)

NASA's Space Launch System (SLS) has moved from design and manufacturing into testing and integration for its first flight as early as December 2019. In 2017, the NASA/industry team completed manufacturing of all major structural elements for the launch vehicle for Exploration Mission-I (EM-1 ). That work included shipping the first major flight hardware element to the launch site. The team processed all four RS-25 engines for stage integration, cast all 10 booster flight motor segments, and manufactured all five major sections of the core stage. The program also completed major structural work on the B-2 test stand at Stennis Space Center, which will be used for the core stage "green run" test; delivered the core stage and engine simulators used for training; and much of the transportation equipment for the core stage. Engineers completed structural testing on the upper stage/payload section of the vehicle as well as the engine section test article. In 2018, the program will deliver the Orion Stage Adapter (OSA) to Exploration Ground Systems (EGS) at KSC and send the test articles for the core stage liquid hydrogen tank, liquid oxygen tank, and intertank to NASA's Marshall Space Flight center for structural testing. Additionally, workers will begin the challenging process of integrating the major sections of the 212-foot EM-1 core stage. This work is focused on the initial Block 1 variant of SLS, capable of launching more than 70 metric tons (t) to low Earth orbit (LEO). However, work concurrently is underway on the Block lB variant, which will enable 105 t to LEO and more than 37t to trans-lunar injection (TLI). Block lB will be the workhorse vehicle of NASA's lunar exploration plans. As the needs of the nation's deep space exploration program grow, SLS performance is designed to evolve to a payload mass of 130 t to LEO and up to 45t to TLI. The advantages of this mass - as well as volume- are critical to the entire exploration architecture for deep space exploration. They translate to greater capability, greater infrastructure and operational simplicity, less overall mission risk, and opportunities to accomplish unprecedented exploration and discovery. This paper will discuss SLS progress to date and planned future work.

After more than four decades exploring the space environment from low Earth orbit and developing long-duration spaceflight operational experience with the International Space Station (ISS), NASA is once again preparing to send explorers into deep space. Development, test and manufacturing is now underway on the launch vehicle, the crew spacecraft and the ground processing and launch facilities to support human and robotic missions to the moon, Mars and the outer solar system. The enabling launch vehicle for these ambitious new missions is the Space Launch System (SLS), managed by NASA's Marshall Space Flight Center (MSFC). Since the program began in 2011, the design has passed Critical Design Review, and extensive development, test and flight hardware has been produced by every major element of the SLS vehicle. Testing continues on engines, boosters, tanks and avionics. While the program has experienced engineering challenges typical of a new development, it continues to make steady progress toward the first SLS mission in roughly two years and a sustained cadence of missions thereafter. This paper will discuss these and other technical and SLS programmatic successes and challenges over the past year and provide a preview of work ahead before first flight.

NASA's Space Launch System (SLS) continued to make significant progress in 2015, completing hardware and testing that brings NASA closer to a new era of deep space exploration. The most significant program milestone of the year was completion of Critical Design Review (CDR). A team of independent reviewers concluded that the vehicle design is technically and programmatically ready to move to Design Certification Review (DCR) and launch readiness in 2018. Just four years after program start, every major element has amassed development and flight hardware and completed key tests that will set the stage for a growing schedule of manufacturing and testing in 2016. Key to SLS' rapid progress has been the use of existing technologies adapted to the new launch vehicle. The space shuttle-heritage RS-25 engine is undergoing adaptation tests to prove it can meet SLS requirements and environments with minimal change. The four-segment shuttle-era booster has been modified and updated with an additional propellant segment, new insulation, and new avionics. The Interim Cryogenic Upper Stage is a modified version of an existing upper stage. The first Block I SLS configuration will launch a minimum of 70 metric tons (t) of payload to low Earth orbit (LEO). The vehicle architecture has a clear evolutionary path to more than 100t and, ultimately, to 130t. Among the program's major accomplishments in 2015 were the first booster qualification hotfire test, a series of seven RS-25 adaptation hotfire tests, manufacturing of most of the major components for both core stage test articles and first flight tank, delivery of the Pegasus core stage barge, and the upper stage simulator. Renovations to the B-2 test stand for stage green run testing was completed at NASA Stennis Space Center. This year will see the second booster qualification motor hotfire, flight and additional development RS-25 engine tests, and completion of core stage test articles and test stands and several flight article sections. This paper will discuss these and other technical and programmatic successes and challenges over the past year and provide a preview of work ahead before the first flight of this new capability.

NASA's Space Launch System (SLS) continued to make significant progress in 2015, completing hardware and testing that brings NASA closer to a new era of deep space exploration. The most significant program milestone of the year was completion of Critical Design Review (CDR). A team of independent reviewers concluded that the vehicle design is technically and programmatically ready to move to Design Certification Review (DCR) and launch readiness in 2018. Just four years after program start, every major element has amassed development and flight hardware and completed key tests that will set the stage for a growing schedule of manufacturing and testing in 2016. Key to SLS' rapid progress has been the use of existing technologies adapted to the new launch vehicle. The space shuttle-heritage RS-25 engine is undergoing adaptation tests to prove it can meet SLS requirements and environments with minimal change. The four-segment shuttle-era booster has been modified and updated with an additional propellant segment, new insulation, and new avionics. The Interim Cryogenic Upper Stage is a modified version of an existing upper stage. The first Block I SLS configuration will launch a minimum of 70 metric tons of payload to low Earth orbit (LEO). The vehicle architecture has a clear evolutionary path to more than 100 metric tons and, ultimately, to 130 metric tons. Among the program's major accomplishments in 2015 were the first booster qualification hotfire test, a series of seven RS-25 adaptation hotfire tests, manufacturing of most of the major components for both core stage test articles and first flight tank, delivery of the Pegasus core stage barge, and the upper stage simulator. Renovations to the B-2 test stand for stage green run testing was completed at NASA Stennis Space Center. This year will see the second booster qualification motor hotfire, flight and additional development RS-25 engine tests, and completion of core stage test articles and test stands and several flight article sections. This paper will discuss these and other technical and programmatic successes and challenges over the past year and provide a preview of work ahead before the first flight of this new capability.

NASA is embarked on a new era of space exploration that will lead to new capabilities, new destinations, and new discoveries by both human and robotic explorers. Today, the International Space Station (ISS) and robotic probes are yielding knowledge that will help make this exploration possible. NASA is developing both the Orion crew vehicle and the Space Launch System (SLS) (Figure 1), that will carry out a series of increasingly challenging missions leading to human exploration of Mars. This paper will discuss the development and progress on the SLS. The SLS architecture was designed to be safe, affordable, and sustainable. The current configuration is the result of literally thousands of trade studies involving cost, performance, mission requirements, and other metrics. The initial configuration of SLS, designated Block 1, will launch a minimum of 70 metric tons (mT) (154,324 pounds) into low Earth orbit - significantly greater capability than any current launch vehicle. It is designed to evolve to a capability of 130 mT (286,601 pounds) through the use of upgraded main engines, advanced boosters, and a new upper stage. With more payload mass and volume capability than any existing rocket, SLS offers mission planners larger payloads, faster trip times, simpler design, shorter design cycles, and greater opportunity for mission success. Since the program was officially created in fall 2011, it has made significant progress toward launch readiness in 2018. Every major element of SLS continued to make significant progress in 2015. Engineers fired Qualification Motor 1 (QM-1) in March 2015 to test the 5-segment motor, including new insulation, joint, and propellant grain designs. More than 70 major components of test article and flight hardware for the Core Stage have been manufactured. Seven test firings have been completed with an RS-25 engine under SLS operating conditions. The test article for the Interim Cryogenic Propulsion Stage (ICPS) has also been completed. Major work continues in 2016 as the program continues both flight and development RS-25 engine testing, begins welding test article and flight core stage tanks, completes stage adapter manufacturing, and test fires the second booster qualification motor. This paper will discuss the program's key accomplishments to date and the challenging work ahead for what will be the world's most capable launch vehicle.

In a survey, 214 of 232 Mississippi county extension coordinators, staff, and district/state administrators rated coordinators' administrative roles as important but had different expectations and perceptions of behavior for role performance. Inservice training should clarify expectations and emphasize four roles: program administration and personnel, financial, and office management. (SK)

Hardware and software for the world's most powerful launch vehicle for exploration is being welded, assembled, and tested today in high bays, clean rooms and test stands across the United States. NASA's Space Launch System (SLS) continued to make significant progress in the past year, including firing tests of both main propulsion elements, manufacturing of flight hardware, and the program Critical Design Review (CDR). Developed with the goals of safety, affordability, and sustainability, SLS will deliver unmatched capability for human and robotic exploration. The initial Block 1 configuration will deliver more than 70 metric tons (t) (154,000 pounds) of payload to low Earth orbit (LEO). The evolved Block 2 design will deliver some 130 t (286,000 pounds) to LEO. Both designs offer enormous opportunity and flexibility for larger payloads, simplifying payload design as well as ground and on-orbit operations, shortening interplanetary transit times, and decreasing overall mission risk. Over the past year, every vehicle element has manufactured or tested hardware, including flight hardware for Exploration Mission 1 (EM-1). This paper will provide an overview of the progress made over the past year and provide a glimpse of upcoming milestones on the way to a 2018 launch readiness date.

NASA's Space Launch System (SLS) is gaining momentum toward the first launch of a new exploration-class heavy lift launch vehicle for international exploration and science initiatives. The SLS comprises an architecture that begins with a vehicle capable of launching 70 metric tons (t) into low Earth orbit. It will launch the Orion Multi-Purpose Crew Vehicle (MPCV) on its first autonomous flight beyond the Moon and back in December 2017. Its first crewed flight follows in 2021. SLS can evolve to a130-t lift capability and serve as a baseline for numerous robotic and human missions ranging from a Mars sample return to delivering the first astronauts to explore another planet. The SLS Program formally transitioned from the formulation phase to implementation with the successful completion of the rigorous Key Decision Point C review in 2014. As a result, the Agency authorized the Program to move forward to Critical Design Review, scheduled for 2015. In the NASA project life cycle process, SLS has completed 50 percent of its major milestones toward first flight. Every SLS element manufactured development hardware for testing over the past year. Accomplishments during 2013/2014 included manufacture of core stage test articles, preparations for qualification testing the solid rocket boosters and the RS-25 main engines, and shipment of the first flight hardware in preparation for the Exploration Flight Test-1 (EFT-1) in 2014. SLS was conceived with the goals of safety, affordability, and sustainability, while also providing unprecedented capability for human exploration and scientific discovery beyond Earth orbit. In an environment of economic challenges, the SLS team continues to meet ambitious budget and schedule targets through the studied use of hardware, infrastructure, and workforce investments the United States made in the last half century, while selectively using new technologies for design, manufacturing, and testing, as well as streamlined management approaches that have increased decision velocity and reduced associated costs. This paper will summarize recent SLS Program accomplishments, as well as the challenges and opportunities ahead for the most powerful and capable launch vehicle in history.

Development of the National Aeronautics and Space Administration's (NASA's) Space Launch System (SLS) heavy lift rocket is shifting from the formulation phase into the implementation phase in 2014, a little more than 3 years after formal program establishment. Current development is focused on delivering a vehicle capable of launching 70 metric tons (t) into low Earth orbit. This "Block 1" configuration will launch the Orion Multi-Purpose Crew Vehicle (MPCV) on its first autonomous flight beyond the Moon and back in December 2017, followed by its first crewed flight in 2021. SLS can evolve to a130t lift capability and serve as a baseline for numerous robotic and human missions ranging from a Mars sample return to delivering the first astronauts to explore another planet. Benefits associated with its unprecedented mass and volume include reduced trip times and simplified payload design. Every SLS element achieved significant, tangible progress over the past year. Among the Program's many accomplishments are: manufacture of core stage test barrels and domes; testing of Solid Rocket Booster development hardware including thrust vector controls and avionics; planning for RS- 25 core stage engine testing; and more than 4,000 wind tunnel runs to refine vehicle configuration, trajectory, and guidance. The Program shipped its first flight hardware - the Multi-Purpose Crew Vehicle Stage Adapter (MSA) - to the United Launch Alliance for integration with the Delta IV heavy rocket that will launch an Orion test article in 2014 from NASA's Kennedy Space Center. The Program successfully completed Preliminary Design Review in 2013 and will complete Key Decision Point C in 2014. NASA has authorized the Program to move forward to Critical Design Review, scheduled for 2015 and a December 2017 first launch. The Program's success to date is due to prudent use of proven technology, infrastructure, and workforce from the Saturn and Space Shuttle programs, a streamlined management approach, and judicious use of new technologies. The result is a safe, affordable, sustainable, and evolutionary path to development of an unprecedented capability for future missions across the solar system. In an environment of economic challenges, the nationwide SLS team continues to meet ambitious budget and schedule targets. This paper will discuss SLS Program and technical accomplishments over the past year and provide a look at the milestones and challenges ahead.

Development of NASA's Space Launch System (SLS) heavy lift rocket is shifting from the formulation phase into the implementation phase in 2014, a little more than three years after formal program approval. Current development is focused on delivering a vehicle capable of launching 70 metric tons (t) into low Earth orbit. This "Block 1" configuration will launch the Orion Multi-Purpose Crew Vehicle (MPCV) on its first autonomous flight beyond the Moon and back in December 2017, followed by its first crewed flight in 2021. SLS can evolve to a130-t lift capability and serve as a baseline for numerous robotic and human missions ranging from a Mars sample return to delivering the first astronauts to explore another planet. Benefits associated with its unprecedented mass and volume include reduced trip times and simplified payload design. Every SLS element achieved significant, tangible progress over the past year. Among the Program's many accomplishments are: manufacture of Core Stage test panels; testing of Solid Rocket Booster development hardware including thrust vector controls and avionics; planning for testing the RS-25 Core Stage engine; and more than 4,000 wind tunnel runs to refine vehicle configuration, trajectory, and guidance. The Program shipped its first flight hardware - the Multi-Purpose Crew Vehicle Stage Adapter (MSA) - to the United Launch Alliance for integration with the Delta IV heavy rocket that will launch an Orion test article in 2014 from NASA's Kennedy Space Center. Objectives of this Earth-orbit flight include validating the performance of Orion's heat shield and the MSA design, which will be manufactured again for SLS missions to deep space. The Program successfully completed Preliminary Design Review in 2013 and Key Decision Point C in early 2014. NASA has authorized the Program to move forward to Critical Design Review, scheduled for 2015 and a December 2017 first launch. The Program's success to date is due to prudent use of proven technology, infrastructure, and workforce from the Saturn and Space Shuttle programs, a streamlined management approach, and judicious use of new technologies. The result is a safe, affordable, sustainable, and evolutionary path to development of an unprecedented capability for future missions across the solar system. In an environment of economic challenges, the nationwide SLS team continues to meet ambitious budget and schedule targets. This paper will discuss SLS program and technical accomplishments over the past year and provide a look at the milestones and challenges ahead.

The Space Shuttle program has ended and elements of the Constellation Program have either been cancelled or transitioned to new NASA exploration endeavors. The National Aeronautics and Space Administration (NASA) has worked diligently to select an optimum configuration for the Space Launch System (SLS), a heavy lift vehicle that will provide the foundation for future beyond low earth orbit (LEO) large-scale missions for the next several decades. From Fall 2010 until Spring 2011, an SLS decision-making framework was formulated, tested, fully documented, and applied to multiple SLS vehicle concepts at NASA from previous exploration architecture studies. This was a multistep process that involved performing figure of merit (FOM)-based assessments, creating Pass/Fail gates based on draft threshold requirements, performing a margin-based assessment with supporting statistical analyses, and performing sensitivity analysis on each. This paper focuses on the various steps and methods of this process (rather than specific data) that allowed for competing concepts to be compared across a variety of launch vehicle metrics in support of the successful completion of the SLS Mission Concept Review (MCR) milestone.

Leaders from NASA's Space Launch System (SLS) will participate in a panel discussing the progress made on the program's propulsion systems. The SLS will be the nation's next human-rated heavy-lift vehicle for new missions beyond Earth's orbit. With a first launch slated for 2017, the SLS Program is turning plans into progress, with the initial rocket being built in the U.S.A. today, engaging the aerospace workforce and infrastructure. Starting with an overview of the SLS mission and programmatic status, the discussion will then delve into progress on each of the primary SLS propulsion elements, including the boosters, core stage engines, upper stage engines, and stage hardware. Included will be a discussion of the 5-segment solid rocket motors (ATK), which are derived from Space Shuttle and Ares developments, as well as the RS-25 core stage engines from the Space Shuttle inventory and the J- 2X upper stage engine now in testing (Pratt and Whitney Rocketdyne). The panel will respond to audience questions about this important national capability for human and scientific space exploration missions.

Exploration beyond Earth orbit will be an enduring legacy for future generations, as it provides a platform for science and exploration that will define new knowledge and redefine known boundaries. NASA s Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is responsible for designing and developing the first exploration-class rocket since the Apollo Program s Saturn V that sent Americans to the Moon in the 1960s and 1970s. The SLS offers a flexible design that may be configured for the Orion Multi-Purpose Crew Vehicle with associated life-support equipment and provisions for long journeys or may be outfitted with a payload fairing that will accommodate flagship science instruments and a variety of high-priority experiments. Building on legacy systems, facilities, and expertise, the SLS will have an initial lift capability of 70 tonnes (t) in 2017 and will be evolvable to 130 t after 2021. While commercial launch vehicle providers service the International Space Station market, this capability will surpass all vehicles, past and present, providing the means to do entirely new missions, such as human exploration of Mars. Building on the foundation laid by over 50 years of human and scientific space flight and on the lessons learned from the Apollo, Space Shuttle, and Constellation Programs the SLS team is delivering both technical trade studies and business case analyses to ensure that the SLS architecture will be safe, affordable, reliable, and sustainable. This panel will address the planning and progress being made by NASA s SLS Program.