Vienna Bread

Pfc. Joseph Winters tossed restlessly in his bed as he awakened from his evening nap..

THE BANKING ACT OF 1935

The purpose of this article is to consider in a non-technical manner the principal changes in federal central and commercial banking law which have been brought about by the enactment of the Banking Act of 1935, and in that connection to take some account of the preexisting law and the announced or ostensible reasons for the changes made

The Attrition Dynamics of Multilateral War

We extend classical force-on-force combat models to study the attrition dynamics of three-way and multilateral war. We introduce a new multilateral combat model (the multiduel) which generalizes the Lanchester models, and solve it under an objective function which values one's own surviving force minus that of one's enemies. The outcome is stark: either one side is strong enough to destroy all the others combined, or all sides are locked in a stalemate which results in collective mutual annihilation. The situation in Syria fits this paradigm

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved

Phylogenetic Analysis of the Zingiberales Based on \u3cem\u3erbc\u3c/em\u3eL Sequences

Morphological data have been used previously to construct phylogenies of the eight families of the Zingiberales one of the most widely accepted monophyletic groups of flowering plants. To provide additional support for phylogenetic relationships within the order, and placement of the order among monocots, we present a parsimony analysis of DNA sequences from the chloroplast-encoded gene, rbcL, for 21 species of Zingiberales and proposed relatives. Five analyses with equal, and differential weights were performed. All analyses resulted in the same most parsimonious tree for taxa within the Zingiberales and the immediate outgroup. The closest sister group to the Zingiberales based on these data is a clade containing Commelinaceae/Haemodoraceae/Pontederiacea. The tree topology within the order based on rbcL sequence data is different from previous morphological analyses. The order can be divided into two sister groups, one containing the Costaceae and Marantaceae, and the other, the remaining six families. All recognized families are monophyletic with the exception of the Musaceae, which is paraphyletic with the Cannaceae. Wtih trees one and two steps longer tha the most parsimonious trees, phylogenetic resolution is rapidly lost, suggesting that the phylogenetic utility of rbcL sequence date for the Zingiberales is limited to interordinal and intrafamilial relationships

Aerial Search Optimization Model (ASOM) for UAVs in Special Operations

We construct an optimization model that assists commanders, operators, and planners to effectively deploy and employ unmanned aerial vehicles (UAVs) in special operations missions. Specifically, we consider situations where targets (e.g., insurgents) operate in a region of interest and a small special operations team is assigned to search and detect these targets. The special operations team is equipped with short-range surveillance UAVs. We combine intelligence regarding the targets with availability and capability of UAVs in an integer linear programming model. The goal is to detect the largest possible number of targets with the given resources. The model prescribes optimal deployment locations for the ground units and optimal time-phased search areas for the UAVs. The model has been implemented successfully in four field experiments. Preliminary empirical evidence indicates that the model provides 50% increase in detection opportunities compared with a plan manually generated by experienced commanders

Baysian uncertainty quantification and calibration of a clean-coal design code

Current concerns about atmospheric carbon levels have sparked demands for massively reduced carbon emissions. These demands, both environmental and regulatory, exceed the capacity for near-term deployment of emission free technologies. Therefore, to simultaneously meet carbon emission targets and supply the vast global energy demands in the foreseeable future, energy generation must incorporate carbon-capture and sequestration technologies on point source CO­2 emitters such as coal-fired power plants. Coal-fired power plants have long been the primary energy pillar of industrialized nations, and while reduced utilization is an important target for CO2 reduction, coal combustion remains the most intensive and prevalent point emission source, and represents hundreds of billions of dollars globally in infrastructure that cannot easily be abandoned. As such, it is the most important target for carbon-capture technologies, particularly retrofit technologies that could allow for near-term, relatively rapid deployment in current infrastructure. The present work supports near-term deployment of oxy-coal combustion as a CO2 capture strategy through computer modeling for both retrofitted boilers and new construction. Oxy-coal combustion is a clean coal technology that uses either a high purity O2 stream, or a mixture of O2 and recycled flue gas to burn coal and produce a CO2 emission stream for capture without the need for post-combustion separation. This combustion environment is a radical departure from the air-fired pulverized coal boiler. Exa-scale Computational Fluid Dynamics (CFD) modeling codes enable relatively low-cost, rapid design in this new environment; however, they depend on physically accurate and predictive sub-models. The present work improves the predictive capacity and quantifies the uncertainty of the Carbon Conversion Kinetics oxy-fuel (CCK/oxy) code, a comprehensive coal char conversion model designed to predict coal char burnout in the intense oxy-fuel environment. A recent sensitivity analysis of the CCK/oxy model strongly implicated the char thermal deactivation routine as a key sub-model to accurately predict char conversion, and the present work uses Bayesian uncertainty quantification and calibration in conjunction with literature data to quantify and reduce the uncertainty in the vital annealing sub-model. The suite of Bayesian statistical tools used here were originally extended to facilitate computational design of CCS technologies. Specifically, the tools used here are based upon GPMSA (Gaussian Process Models for Simulation Analysis), and provide the capability for relatively low-cost calibration, uncertainty quantification, sensitivity analysis, and model response prediction based upon a reasonable number of model executions. We present the results of the calibration using these tools which incorporate the information from both empirical physical measurements and detailed physics-based simulation models. Acknowledgements: The work at LANL is supported by the Carbon Capture Simulation Initiative with funding through the Office of Fossil Energy, US Department of Energy. The work at BYU is supported by the Department of Energy, National Nuclear Security Administration, under Award Number DE-NA0002375

Mutant huntingtin enhances activation of dendritic Kv4 K+ channels in striatal spiny projection neurons

Huntington\u27s disease (HD) is initially characterized by an inability to suppress unwanted movements, a deficit attributable to impaired synaptic activation of striatal indirect pathway spiny projection neurons (iSPNs). To better understand the mechanisms underlying this deficit, striatal neurons in ex vivo brain slices from mouse genetic models of HD were studied using electrophysiological, optical and biochemical approaches. Distal dendrites of iSPNs from symptomatic HD mice were hypoexcitable, a change that was attributable to increased association of dendritic Kv4 potassium channels with auxiliary KChIP subunits. This association was negatively modulated by TrkB receptor signaling. Dendritic excitability of HD iSPNs was rescued by knocking-down expression of Kv4 channels, by disrupting KChIP binding, by restoring TrkB receptor signaling or by lowering mutant-Htt (mHtt) levels with a zinc finger protein. Collectively, these studies demonstrate that mHtt induces reversible alterations in the dendritic excitability of iSPNs that could contribute to the motor symptoms of HD