Hydrogen reliquifier Quarterly report, 27 Sept. - 26 Dec. 1967

Computer analyzed hydrogen reliquefier cycles for selection of optimal cycle, rates, and heat exchanger

Egg Production Costs and Returns

Methods of producing and marketing eggs have changed rapidly. Egg producers must adopt practices that reduce production costs per dozen eggs - Even then, they generally cannot be successful unless they can sell their eggs through stable and well-organized market outlets

Probing Arabidopsis Chloroplast Diacylglycerol Pools by Selectively Targeting Bacterial Diacylglycerol Kinase to Suborganellar Membranes

Diacylglycerol (DAG) is an intermediate in metabolism of both triacylglycerols and membrane lipids. Probing the steady-state pools of DAG and understanding how they contribute to the synthesis of different lipids is important when designing plants with altered lipid metabolism. However, traditional methods of assaying DAG pools are difficult, because its abundance is low and because fractionation of subcellular membranes affects DAG pools. To manipulate and probe DAG pools in an in vivo context, we generated multiple stable transgenic lines of Arabidopsis (Arabidopsis thaliana) that target an Escherichia coli DAGkinase (DAGK) to each leaflet of each chloroplast envelope membrane. E. coli DAGKis small, self inserts into membranes, and has catalytic activity on only one side of each membrane. By comparing whole-tissue lipid profiles between our lines, we show that each line has an individual pattern of DAG, phosphatidic acid, phosphatidylcholine, and triacylglycerol steady-state levels, which supports an individual function of DAG in each membrane leaflet. Furthermore, conversion of DAG in the leaflets facing the chloroplast intermembrane space by DAGK impairs plant growth. As a result of DAGK presence in the outer leaflet of the outer envelope membrane, phosphatidic acid accumulation is not observed, likely because it is either converted into other lipids or removed to othermembranes. Finally, we use the outer envelope-targeted DAGK line as a tool to probe the accessibility of DAG generated in response to osmotic stress

Deep learning as optimal control problems: Models and numerical methods

We consider recent work of Haber and Ruthotto 2017 and Chang et al. 2018, where deep learning neural networks have been interpreted as discretisations of an optimal control problem subject to an ordinary differential equation constraint. We review the first order conditions for optimality, and the conditions ensuring optimality after discretisation. This leads to a class of algorithms for solving the discrete optimal control problem which guarantee that the corresponding discrete necessary conditions for optimality are fulfilled. The differential equation setting lends itself to learning additional parameters such as the time discretisation. We explore this extension alongside natural constraints (e.g. time steps lie in a simplex). We compare these deep learning algorithms numerically in terms of induced flow and generalisation ability

Deep learning as optimal control problems

We briefly review recent work where deep learning neural networks have been interpreted as discretisations of an optimal control problem subject to an ordinary differential equation constraint. We report here new preliminary experiments with implicit symplectic Runge-Kutta methods. In this paper, we discuss ongoing and future research in this area

An entropic Landweber method for linear ill-posed problems

The aim of this paper is to investigate the use of a Landweber-type method involving the Shannon entropy for the regularization of linear ill-posed problems. We derive a closed form solution for the iterates and analyze their convergence behaviour both in a case of reconstructing general nonnegative unknowns as well as for the sake of recovering probability distributions. Moreover, we discuss several variants of the algorithm and relations to other methods in the literature. The effectiveness of the approach is studied numerically in several examples

Cryogenic Origin for Mars Analog Carbonates in the Bockfjord Volcanic Complex Svalbard (Norway)

The Sverrefjell and Sigurdfjell eruptive centers in the Bockfjord Volcanic Complex (BVC) on Svalbard (Norway) formed by subglacial eruptions ca. 1 Ma ago. These eruptive centers carry ubiquitous magnesian carbonate deposits including dolomitemagnesite globules similar to those in the Martian meteorite ALH84001. Carbonates in mantle xenoliths are dominated by ALH84001 type carbonate globules that formed during quenching of CO2-rich mantle fluids. Lava hosted carbonates include ALH84001 type carbonate globules occurring throughout lava vesicles and microfractures and massive carbonate deposits associated with vertical volcanic vents. Massive carbonates include < or equal 5 cm thick magnesite deposits protruding downwards into clear blue ice within volcanic vents and carbonate cemented lava breccias associated with volcanic vents. Carbonate cements comprise layered deposits of calcite, dolomite, huntite, magnesite and aragonite associated with ALH84001 type carbonate globules lining lava vesicles. Combined Mossbauer, XRD and VNIR data show that breccia carbonate cements at Sverrefjell are analog to Comanche carbonates at Gusev crater

Not just fractal surfaces, but surface fractal aggregates: Derivation of the expression for the structure factor and its applications

Densely packed surface fractal aggregates form in systems with high local volume fractions of particles with very short diffusion lengths, which effectively means that particles have little space to move. However, there are no prior mathematical models, which would describe scattering from such surface fractal aggregates and which would allow the subdivision between inter- and intraparticle interferences of such aggregates. Here, we show that by including a form factor function of the primary particles building the aggregate, a finite size of the surface fractal interfacial sub-surfaces can be derived from a structure factor term. This formalism allows us to define both a finite specific surface area for fractal aggregates and the fraction of particle interfacial sub-surfaces at the perimeter of an aggregate. The derived surface fractal model is validated by comparing it with an ab initio approach that involves the generation of a "brick-in-a-wall" von Koch type contour fractals. Moreover, we show that this approach explains observed scattering intensities from in situ experiments that followed gypsum (CaSO4 · 2H2O) precipitation from highly supersaturated solutions. Our model of densely packed "brick-in-a-wall" surface fractal aggregates may well be the key precursor step in the formation of several types of mosaic- and meso-crystals

Macrophages target Salmonella by Lc3-associated phagocytosis in a systemic infection model

Innate immune defense against intracellular pathogens, like Salmonella, relies heavily on the autophagy machinery of the host. This response is studied intensively in epithelial cells, the target of Salmonella during gastrointestinal infections. However, little is known of the role that autophagy plays in macrophages, the predominant carriers of this pathogen during systemic disease. Here we utilize a zebrafish embryo model to study the interaction of S. enterica serovar Typhimurium with the macroautophagy/autophagy machinery of macrophages in vivo. We show that phagocytosis of live but not heat-killed Salmonella triggers recruitment of the autophagy marker GFP-Lc3 in a variety of patterns labeling tight or spacious bacteria-containing compartments, also revealed by electron microscopy. Neutrophils display similar GFP-Lc3 associations, but genetic modulation of the neutrophil/macrophage balance and ablation experiments show that macrophages are critical for the defense response. Deficiency of atg5 reduces GFP-Lc3 recruitment and impairs host resistance, in contrast to atg13 deficiency, indicating that Lc3-Salmonella association at this stage is independent of the autophagy preinitiation complex and that macrophages target Salmonella by Lc3-associated phagocytosis (LAP). In agreement, GFP-Lc3 recruitment and host resistance are impaired by deficiency of Rubcn/Rubicon, known as a negative regulator of canonical autophagy and an inducer of LAP. We also found strict dependency on NADPH oxidase, another essential factor for LAP. Both Rubcn and NADPH oxidase are required to activate a Salmonella biosensor for reactive oxygen species inside infected macrophages. These results identify LAP as the major host protective autophagy-related pathway responsible for macrophage defense against Salmonella during systemic infection

A J-Like Protein Influences Fatty Acid Composition of Chloroplast Lipids in Arabidopsis

A comprehensive understanding of the lipid and fatty acid metabolic machinery is needed for optimizing production of oils and fatty acids for fuel, industrial feedstocks and nutritional improvement in plants. T-DNA mutants in the poorly annotated Arabidopsis thaliana gene At1g08640 were identified as containing moderately high levels (50–100%) of 16∶1Δ7 and 18∶1Δ9 leaf fatty acids and subtle decreases (5–30%) of 16∶3 and 18∶3 (http://www.plastid.msu.edu/). TLC separation of fatty acids in the leaf polar lipids revealed that the chloroplastic galactolipids monogalactosyldiacylglycerol (MGDG) and digalactosyldiacylglycerol (DGDG) were the main lipid types affected by this mutation. Analysis of the inferred amino acid sequence of At1g08640 predicted the presence of a transit peptide, three transmembrane domains and an N-terminal J-like domain, and the gene was named CJD1 for Chloroplast J-like Domain 1. GFP reporter experiments and in vitro chloroplast import assays demonstrated CJD1 is a chloroplast membrane protein. Screening of an Arabidopsis cDNA library by yeast-2-hybrid (Y2H) using the J-like domain of CJD1 as bait identified a plastidial inner envelope protein (Accumulation and Replication of Chloroplasts 6, ARC6) as the primary interacting partner in the Y2H assay. ARC6 plays a central role in chloroplast division and binds CJD1 via its own J-like domain along with an adjacent conserved region whose function is not fully known. These results provide a starting point for future investigations of how mutations in CJD1 affect lipid composition