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

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

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

Analisis Penguasaan Pemilikan Penggunaan Dan Pemanfaatan Tanah (P4t) Berbasis Bidang Menggunakan Sistem Informasi Geografis (Sig) (Studi Kasus : Kelurahan Tembalang Tahun 2015)

Tembalang merupakan wilayah yang memiliki perkembangan yang sangat dinamis, karena selain fungsinya sebagai kawasan pemukiman, Tembalang juga merupakan kawasan pendidikan. Pembangunan kampus Univesitas Diponegoro (UNDIP) yang dimulai sejak tahun 1990-an sampai dengan saat ini membuat banyak Perubahan bagi TembalangData yang digunakan dalam penelitian ini berupa peta administrasi Kelurahan Tembalang, citra GeoEye terkoreksi tahun 2013 dan sebaran persil BPN. Metode yang digunakan dalam penelitian ini adalah identifikasi pada obyek bidang tanah berupa poin penggunaan, pemanfaatan, pemilikan, dan penguasaan tanah.Penelitian ini dilakukan untuk mendapatkan hasil berupa peta yang akurat dan teliti mengenai sebaran bidang tanah lengkap dengan penggunaan, pemanfaatan, pemilikan, dan penguasaan tanah di Kelurahan Tembalang. Penggunaan tanah di Kelurahan Tembalang sebagian besar merupakan tanah kosong sudah diperuntukan dengan persentase 33,930%, pemanfaatan terbanyak adalah pemanfaatan campuran sebesar 29,68%, pemilikan tanah oleh negara sebesar 67,80% dan penguasaan tanah oleh negara sebesar 67,80%. Pola hubungan yang terjadi antara penguasaan, pemilikan, penggunaan, dan pemanfaatan tanah di Kelurahan Tembalang sebanyak 103 pola dengan pola yang mendominasi adalah pola penguasaan oleh negara dengan status kepemilikan tanah milik negara yang penggunaannya sebagai tanah kosong sudah diperuntukan dan dimanfaatkan sebagai pemanfaatan campuran dengan persentase 24,3454 % dan luas 93,045 Ha.Kata Kunci : Penguasaan, Pemilikan, Penggunaan, Pemanfaatan ABSTRACKTembalang is an area that has a very dynamic growth. It has a function not only for settlement area but also as an education area. The establishment of Diponegoro University (UNDIP) that started since 1990s until now, makes much changes for Tembalang.The data that is used in this study is a map of Tembalang, corrected GeoEye images from 2013 and BPN plot distribution. This study uses a method of identification of land area objects that are in the form of land use, utilization, ownership and authorization point.This study is being done to get a result that is in the form of accurate and precise maps about land area distribution with their land use, utilization,ownership and authorization at Tembalang. Land use at Tembalang district is mostly reserved barren land at 33,93%, the most use is mixed use at 29,68%, land ownership by the government at 67,80% and land authority by the government at 67,80%. The amount of correlation pattern that happens between land authority, land ownership, land use and utilization in Tembalang district is 103 pattern. With the dominating pattern which is authority by the government – land ownership by government – land use of reserved barren land – mixed use at 24,3454% and the area is 93,045 Hectare

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

Identification of black sturgeon caviar pigment as eumelanin

Reported herein is the purification of the pigment of black sturgeon caviar and its unambiguous identification as a typical eumelanin by means of chemical degradation coupled with electron paramagnetic resonance (EPR) evidence. HPLC and LC-MS analysis of oxidative degradation mixtures revealed the formation of pyrrole-2,3,5-tricarboxylic acid (PTCA), a specific marker of eumelanin pigments, in yields compatible with a 6.5% w/w pigment content. EPR spectral features and parameters were in close agreement with those reported for a typical natural eumelanin such as Sepia melanin from squid ink. The identification for the first time of eumelanin in a fish roe is expected to provide a novel molecular basis for the valorization of black caviar and production wastes thereof in food chemistry and diet

Xyloglucan is released by plants and promotes soil particle aggregation.

Soil is a crucial component of the biosphere and is a major sink for organic carbon. Plant roots are known to release a wide range of carbon-based compounds into soils, including polysaccharides, but the functions of these are not known in detail. Using a monoclonal antibody to plant cell wall xyloglucan, we show that this polysaccharide is secreted by a wide range of angiosperm roots, and relatively abundantly by grasses. It is also released from the rhizoids of liverworts, the earliest diverging lineage of land plants. Using analysis of water-stable aggregate size, dry dispersion particle analysis and scanning electron microscopy, we show that xyloglucan is effective in increasing soil particle aggregation, a key factor in the formation and function of healthy soils. To study the possible roles of xyloglucan in the formation of soils, we analysed the xyloglucan contents of mineral soils of known age exposed upon the retreat of glaciers. These glacial forefield soils had significantly higher xyloglucan contents than detected in a UK grassland soil. We propose that xyloglucan released from plant rhizoids/roots is an effective soil particle aggregator and may, in this role, have been important in the initial colonization of land

Quantitative mapping of chemical compositions with MRI using compressed sensing.

In this work, a magnetic resonance (MR) imaging method for accelerating the acquisition time of two dimensional concentration maps of different chemical species in mixtures by the use of compressed sensing (CS) is presented. Whilst 2D-concentration maps with a high spatial resolution are prohibitively time-consuming to acquire using full k-space sampling techniques, CS enables the reconstruction of quantitative concentration maps from sub-sampled k-space data. First, the method was tested by reconstructing simulated data. Then, the CS algorithm was used to reconstruct concentration maps of binary mixtures of 1,4-dioxane and cyclooctane in different samples with a field-of-view of 22mm and a spatial resolution of 344μm×344μm. Spiral based trajectories were used as sampling schemes. For the data acquisition, eight scans with slightly different trajectories were applied resulting in a total acquisition time of about 8min. In contrast, a conventional chemical shift imaging experiment at the same resolution would require about 17h. To get quantitative results, a careful weighting of the regularisation parameter (via the L-curve approach) or contrast-enhancing Bregman iterations are applied for the reconstruction of the concentration maps. Both approaches yield relative errors of the concentration map of less than 2mol-% without any calibration prior to the measurement. The accuracy of the reconstructed concentration maps deteriorates when the reconstruction model is biased by systematic errors such as large inhomogeneities in the static magnetic field. The presented method is a powerful tool for the fast acquisition of concentration maps that can provide valuable information for the investigation of many phenomena in chemical engineering applications.The authors thank for the financial support by the following grants: Microsoft Research Cambridge, and EPSRC (EP/K039318/1 and EP/K008218/1). Erik von Harbou was the recipient of a scholarship from the German Academic Exchange Service (DAAD).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.jmr.2015.09.01

Formation of Silica-Lysozyme Composites Through Co-Precipitation and Adsorption

Interactions between silica and proteins are crucial for the formation of biosilica and the production of novel functional hybrid materials for a range of industrial applications. The proteins control both precipitation pathway and the properties of the resulting silica-organic composites. Here we present data on the formation of silica-lysozyme composites through two different synthesis approaches (co-precipitation vs. adsorption) and show that the chemical and structural properties of these composites, when analyzed using a combination of synchrotron-based scattering (total scattering and SAXS), spectroscopic, electron microscopy and potentiometric methods vary dramatically. We document that while lysozyme was not incorporated into nor did its presence alter the molecular structure of silica, it strongly enhanced the aggregation of silica particles due to electrostatic and potentially hydrophobic interactions, leading to the formation of composites with characteristics differing from pure silica. The differences increased with increasing lysozyme content for both synthesis approaches. Yet, the absolute changes differ substantially between the two sets of composites, as lysozyme did not just affect aggregation during co-precipitation but also particle growth and likely polymerization during co-precipitation. Our results improve the fundamental understanding of how organic macromolecules interact with dissolved and nanoparticulate silica and how these interactions control the formation pathway of silica-organic composites from sodium silicate solutions, a widely available and cheap starting material

Convergence rates in expectation for Tikhonov-type regularization of Inverse Problems with Poisson data

In this paper we study a Tikhonov-type method for ill-posed nonlinear operator equations \gdag = F( ag) where \gdag is an integrable, non-negative function. We assume that data are drawn from a Poisson process with density t\gdag where $t>0$ may be interpreted as an exposure time. Such problems occur in many photonic imaging applications including positron emission tomography, confocal fluorescence microscopy, astronomic observations, and phase retrieval problems in optics. Our approach uses a Kullback-Leibler-type data fidelity functional and allows for general convex penalty terms. We prove convergence rates of the expectation of the reconstruction error under a variational source condition as $t\to\infty$ both for an a priori and for a Lepski{\u\i}-type parameter choice rule