15,141 research outputs found

    Unanticipated Money

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    The role of unanticipated changes in money growth for aggregate fluctuations is reexamined using the methods of quantitative equilibrium business cycle theory. A stochastic growth model with money is constructed that has the feature, following Lucas (1972, 1975), that production and trade take place in spatially separated markets (islands). Individuals must infer changes in the aggregate price level from observing local relative prices. This causes individuals to react to changes in the average price level, due to unanticipated changes in the aggregate money supply, as though they were changes in market specific relative prices. We show that this mechanism can lead to quantitatively large fluctuations in real economic activity. The statistical properties of these fluctuations, however, are quite different from the properties of fluctuations observed in the U.S. economy.Business Cycles, Monetary Policy, Aggregate Fluctuations, Real Business Cycles

    Faster Algorithms for Computing Maximal 2-Connected Subgraphs in Sparse Directed Graphs

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    Connectivity related concepts are of fundamental interest in graph theory. The area has received extensive attention over four decades, but many problems remain unsolved, especially for directed graphs. A directed graph is 2-edge-connected (resp., 2-vertex-connected) if the removal of any edge (resp., vertex) leaves the graph strongly connected. In this paper we present improved algorithms for computing the maximal 2-edge- and 2-vertex-connected subgraphs of a given directed graph. These problems were first studied more than 35 years ago, with O~(mn)\widetilde{O}(mn) time algorithms for graphs with m edges and n vertices being known since the late 1980s. In contrast, the same problems for undirected graphs are known to be solvable in linear time. Henzinger et al. [ICALP 2015] recently introduced O(n2)O(n^2) time algorithms for the directed case, thus improving the running times for dense graphs. Our new algorithms run in time O(m3/2)O(m^{3/2}), which further improves the running times for sparse graphs. The notion of 2-connectivity naturally generalizes to k-connectivity for k>2k>2. For constant values of k, we extend one of our algorithms to compute the maximal k-edge-connected in time O(m3/2logn)O(m^{3/2} \log{n}), improving again for sparse graphs the best known algorithm by Henzinger et al. [ICALP 2015] that runs in O(n2logn)O(n^2 \log n) time.Comment: Revised version of SODA 2017 paper including details for k-edge-connected subgraph

    Measurement of calcium isotopes (δ44Ca) using a multicollector TIMS technique

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    We propose a new“multicollector technique” for the thermal ionization mass spectrometer (TIMS) measurement of calcium (Ca) isotope ratios improving average internal statistical uncertainty of the 44Ca/40Ca measurements by a factor of 2–4 and average sample throughput relative to the commonly used “peak jumping method” by a factor of 3. Isobaric interferences with potassium (40K+) and titanium (48Ti+) or positively charged molecules like 24Mg19F+, 25Mg19F+, 24Mg16O+ and 27Al16O+ can either be corrected or are negligible. Similar, peak shape defects introduced by the large dispersion of the whole Ca isotope mass range from 40–48 atomic mass units (amu) do not influence Ca-isotope ratios. We use a 43Ca/48Ca double spike with an iterative double spike correction algorithm for precise isotope measurement

    The finite element method for neutron diffusion problems in hexagonal geometry

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    Originally presented as the first author's thesis (Ph. D.), M.I.T. Dept. of Nuclear Engineering, 1975Includes bibliographical references (pages 163-164)Energy Research and Development Agency report AT(11-1)-226

    A strategic model for the simulation of drug resistance in African animal trypanosomiasis

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    African Animal Trypanosomiasis (AAT) is a major constraint to the productivity of African agricultural systems, both where animals are used for dairy or meat production and where traction power is needed to cultivate the land. Tsetse flies of the genus Glossina act as vectors that transport the parasitic protozoan Trypanosoma spp. between hosts. The strategy most widely used to manage the disease is application of trypanocidal drugs, but the emergence of resistance has put into question the long-term viability of their use. In certain areas of West Africa, drug resistant and drug susceptible strains of trypanosomes co-exist. When in such an area the disease prevalence is successfully reduced by removal of the majority of the tsetse vectors, the remaining numbers of diseased animals is so small that it becomes difficult to measure the impact of vector control on the development of drug resistance. Moreover, little is known about how resistance is likely to evolve if vector control is subsequently discontinued. Dynamic system models can simulate the processes that drive the dynamics of vector, host and parasite populations. Such models can increase our understanding of the diseases dynamics even in situations where empirical measurement is problematic. We describe a model in which cattle hosts are represented as individuals. Cattle can be infected by a drug resistant or drug susceptible strain of the pathogen, or a mix of both. Tsetse flies, represented as cohorts, can spread disease between hosts. The model incorporates processes that potentially alter the ratio of drug resistant to drug susceptible trypanosomes, such as reaction to medication, and keeps track of the proportions of drug resistance and drug susceptible strains in the trypanosome population. The model is strategic in the sense that it doesn't attempt to represent a particular situation in a particular region, but more generally aims to improve our understanding of a situation in which empirical science is constrained

    Numerical solution of the two-dimensional time-dependent multigroup equations

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    Also issued as a Ph. D. thesis in the Dept. of Nuclear Engineering, MIT, 1969"MIT-3903-1."Includes bibliographical references (leaves 60-61)Contract AT(30-1)-390

    Cluster evolution in steady-state two-phase flow in porous media

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    We report numerical studies of the cluster development of two-phase flow in a steady-state environment of porous media. This is done by including biperiodic boundary conditions in a two-dimensional flow simulator. Initial transients of wetting and non-wetting phases that evolve before steady-state has occurred, undergo a cross-over where every initial patterns are broken up. For flow dominated by capillary effects with capillary numbers in order of 10510^{-5}, we find that around a critical saturation of non-wetting fluid the non-wetting clusters of size ss have a power-law distribution nssτn_s \sim s^{-\tau} with the exponent τ=1.92±0.04\tau = 1.92 \pm 0.04 for large clusters. This is a lower value than the result for ordinary percolation. We also present scaling relation and time evolution of the structure and global pressure.Comment: 12 pages, 11 figures. Minor corrections. Accepted for publication in Phys. Rev.
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