Twenty-Nine Years of Geomorphic Change at Elkhorn Slough, California

This study utilized high-precision surveys to estimate 29 years of elevation change on the Elkhorn Slough marsh plain. There were 3 objectives to this study: 1) characterize the spatial variation in rates of net erosion/deposition and net vertical change with respect to the benchmark, 2) compare net vertical change rates to estimates of projected rate of sea-level rise in the region, and 3) determine linkages between land cover type and rate of net vertical change. We resurveyed 11 of the 13 original cross sections using the same methodology to collect new surface elevations for comparison with the original 1980 dataset. Overall, survey points on the marsh plain averaged 0.5 cm/yr of accretion (SD = 0.4 cm/yr), but an estimated rate of overall subsidence of 0.4 cm/yr across the slough reduced vertical movement to an average of 0.1 cm/yr. When compared to a low sea level rise scenario of 0.25 cm/yr, rapid marsh deterioration will result if no management actions mitigate a rising sea. Only 26 of the 149 survey points (17%) contain vertical change rates that will outcompete a 0.25 cm/yr sea level rise scenario. Additionally, mudflat and tidal creek categories had erosion rates relative to the benchmarks of 0.7 cm/yr and 1.6 cm/yr, respectively. Respective net vertical loss becomes 1.1 cm/yr and 2.0 cm/yr, when the estimated 0.4 cm/yr background subsidence rate is considered. Further study is needed to identify and quantify individual components of benchmark movement to be able to quantify observed subsidence at each cross section, as opposed to applying a best estimate given available data. Resource managers at Elkhorn Slough National Research Reserve have been weighing four management alternatives to reduce the rate of marsh plain loss: 1) no action, 2) a new mouth, 3) sill at the current mouth, and 4) sill at Parsons Slough to reduce tidalvolume. It is recommended that resource managers focus attention to restoration alternatives that directly mitigate erosion, increase deposition, and/or mute sea level rise effects, Restoration of Parsons Slough (Alternative 4) appears to be the most cost effective way to reduce tidal volumes below the junction and mitigate erosional forces. Cross sections closer to the mouth of the Slough show some of the highest accretion rates, so a tidal sill recommended in Alternative 3 might ultimately decrease these rates by limiting tidal inundation onto the marsh plain. With the restoration of Parsons Slough, the tidal volumes will be reduced below the Parsons Slough junction that will inherently reduce tidal forces and scour, while maintaining the healthy marsh plain accretion rates closer to the mouth of the Slough. Increased biologically productive area will be a further benefit of selecting Alternative 4

Introducing Agile/DevSecOps into the Space Acquisition Environment

Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThe University of Southern California (USC) and its Information Sciences Institute (USC-ISI) is undertaking research into improving the space-based systems acquisition process through the adoption of agile and DevSecOps methodologies. The USC-ISI team is currently undertaking research and systems engineering analysis to explore the mission engineering methods, analysis, metrics and training needed to transition from a traditional DoDI 5000.02 waterfall development environment to an agile/DevSecOps space systems acquisition environment. Over the past several years, the project team has been embedded at the U.S. Space Force’s Space Systems Command, Production Corps (SSC/PC), developing performance measuring tools, collecting performance metrics and providing subject matter expertise on three projects – a traditional waterfall project, a hybrid parallel waterfall and agile development project and an on-going long-term highly agile development effort that is subject to traditional waterfall acquisition reporting requirements. This paper summarizes initial research results and lessons learned along with a discussion on next steps.Approved for public release; distribution is unlimited

Introducing Agile/DevSecOps into the Space Acquisition Environment

Symposium PresentationApproved for public release; distribution is unlimited

COVARIATE-ADJUSTED NONPARAMETRIC ANALYSIS OF MAGNETIC RESONANCE IMAGES USING MARKOV CHAIN MONTE CARLO

Permutation tests are useful for drawing inferences from imaging data because of their flexibility and ability to capture features of the brain that are difficult to capture parametrically. However, most implementations of permutation tests ignore important confounding covariates. To employ covariate control in a nonparametric setting we have developed a Markov chain Monte Carlo (MCMC) algorithm for conditional permutation testing using propensity scores. We present the first use of this methodology for imaging data. Our MCMC algorithm is an extension of algorithms developed to approximate exact conditional probabilities in contingency tables, logit, and log-linear models. An application of our non-parametric method to remove potential bias due to the observed covariates is presented

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets

Ccdc11 is a novel centriolar satellite protein essential for ciliogenesis and establishment of left-right asymmetry

The establishment of left–right (L-R) asymmetry in vertebrates is dependent on the sensory and motile functions of cilia during embryogenesis. Mutations in CCDC11 disrupt L-R asymmetry and cause congenital heart disease in humans, yet the molecular and cellular functions of the protein remain unknown. Here we demonstrate that Ccdc11 is a novel component of centriolar satellites—cytoplasmic granules that serve as recruitment sites for proteins destined for the centrosome and cilium. Ccdc11 interacts with core components of satellites, and its loss disrupts the subcellular organization of satellite proteins and perturbs primary cilium assembly. Ccdc11 colocalizes with satellite proteins in human multiciliated tracheal epithelia, and its loss inhibits motile ciliogenesis. Similarly, depletion of CCDC11 in Xenopus embryos causes defective assembly and motility of cilia in multiciliated epidermal cells. To determine the role of CCDC11 during vertebrate development, we generated mutant alleles in zebrafish. Loss of CCDC11 leads to defective ciliogenesis in the pronephros and within the Kupffer’s vesicle and results in aberrant L-R axis determination. Our results highlight a critical role for Ccdc11 in the assembly and function of motile cilia and implicate centriolar satellite–associated proteins as a new class of proteins in the pathology of L-R patterning and congenital heart disease

Sunmaster: An SEP cargo vehicle for Mars missions

Options are examined for an unmanned solar powered electric propulsion cargo vehicle for Mars missions. The 6 prime areas of study include: trajectory, propulsion system, power system, supporting structure, control system, and launch consideration. Optimization of the low thrust trajectory resulted in a total round trip mission time just under 4 years. The argon propelled electrostatic ion thruster system consists of seventeen 5 N engines and uses a specific impulse of 10,300 secs. At Earth, the system uses 13 engines to produce 60 N of thrust; at Mars, five engines are used, producing 25 N thrust. The thrust of the craft is varied between 60 N at Earth and 24 N at Mars due to reduced solar power available. Solar power is collected by a Fresnel lens concentrator system using a multistacked cell. This system provides 3.5 MW to the propulsion system after losses. Control and positioning to the craft are provided by a system of three double gimballed control moment gyros. Four shuttle 'C' launches will be used to transport the unassembled vehicle in modular units to low Earth orbit where it will be assembled using the Mobile Transporter of the Space Station Freedom

POPULATION FUNCTIONAL DATA ANALYSIS OF GROUP ICA-BASED CONNECTIVITY MEASURES FROM fMRI

In this manuscript, we use a two-stage decomposition for the analysis of func- tional magnetic resonance imaging (fMRI). In the first stage, spatial independent component analysis is applied to the group fMRI data to obtain common brain networks (spatial maps) and subject-specific mixing matrices (time courses). In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population- level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact conditional logistic regression for matched pairs data. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and the major direction of variation in the mixing matrices. The method is applied to a novel fMRI study of Alzheimer\u27s disease risk under a verbal paired associates task. We found empirical evidence of alternative ICA-based metrics of connectivity in clinically asymptomatic at risk subjects when compared to controls

Two-stage Decompositions for the Analysis of Functional Connectivity for fMRI With Application to Alzheimer\u27s Disease Risk

Functional connectivity is the study of correlations in measured neurophysiological signals. Altered functional connectivity has been shown to be associated with numerous diseases including Alzheimer\u27s disease and mild cognitive impairment. In this manuscript we use a two-stage application of the singular value decomposition to obtain data driven population-level measures of functional connectivity in functional magnetic resonance imaging (fMRI). The method is computationally simple and amenable to high dimensional fMRI data with large numbers of subjects. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and their associated loadings. We further demonstrate the utility of these decompositions in a case-control functional logistic regression model. The method is applied to a novel fMRI study of Alzheimer\u27s disease risk under a verbal paired associates task. We found empirical evidence of alternative connectivity in clinically asymptomatic at-risk subjects when compared to controls. The relevant brain network loads primarily on the temporal lobe and overlaps significantly with the olfactory areas and temporal poles

How structural adaptability exists alongside HLA-A2 bias in the human alphabeta TCR repertoire

How T-cell receptors (TCRs) can be intrinsically biased toward MHC proteins while simultaneously display the structural adaptability required to engage diverse ligands remains a controversial puzzle. We addressed this by examining alphabeta TCR sequences and structures for evidence of physicochemical compatibility with MHC proteins. We found that human TCRs are enriched in the capacity to engage a polymorphic, positively charged hot-spot region that is almost exclusive to the alpha1-helix of the common human class I MHC protein, HLA-A*0201 (HLA-A2). TCR binding necessitates hot-spot burial, yielding high energetic penalties that must be offset via complementary electrostatic interactions. Enrichment of negative charges in TCR binding loops, particularly the germ-line loops encoded by the TCR Valpha and Vbeta genes, provides this capacity and is correlated with restricted positioning of TCRs over HLA-A2. Notably, this enrichment is absent from antibody genes. The data suggest a built-in TCR compatibility with HLA-A2 that biases receptors toward, but does not compel, particular binding modes. Our findings provide an instructional example for how structurally pliant MHC biases can be encoded within TCRs