577 research outputs found

    On the probabilistic min spanning tree Problem

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    We study a probabilistic optimization model for min spanning tree, where any vertex vi of the input-graph G(V,E) has some presence probability pi in the final instance G′ ⊂ G that will effectively be optimized. Suppose that when this “real” instance G′ becomes known, a spanning tree T, called anticipatory or a priori spanning tree, has already been computed in G and one can run a quick algorithm (quicker than one that recomputes from scratch), called modification strategy, that modifies the anticipatory tree T in order to fit G ′. The goal is to compute an anticipatory spanning tree of G such that, its modification for any G ′ ⊆ G is optimal for G ′. This is what we call probabilistic min spanning tree problem. In this paper we study complexity and approximation of probabilistic min spanning tree in complete graphs under two distinct modification strategies leading to different complexity results for the problem. For the first of the strategies developed, we also study two natural subproblems of probabilistic min spanning tree, namely, the probabilistic metric min spanning tree and the probabilistic min spanning tree 1,2 that deal with metric complete graphs and complete graphs with edge-weights either 1, or 2, respectively

    Slepian functions and their use in signal estimation and spectral analysis

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    It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and on the surface of a sphere.Comment: Submitted to the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verla

    Spatial and Temporal Variations in SO₂ and PM₂.₅ Levels Around Kīlauea Volcano, Hawai'i During 2007–2018

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    Among the hazards posed by volcanoes are the emissions of gases and particles that can affect air quality and damage agriculture and infrastructure. A recent intense episode of volcanic degassing associated with severe impacts on air quality accompanied the 2018 lower East Rift Zone (LERZ) eruption of Kīlauea volcano, Hawai'i. This resulted in a major increase in gas emission rates with respect to usual emission values for this volcano, along with a shift in the source of the dominant plume to a populated area on the lower flank of the volcano. This led to reduced air quality in downwind communities. We analyse open-access data from the permanent air quality monitoring networks operated by the Hawai'i Department of Health (HDOH) and National Park Service (NPS), and report on measurements of atmospheric sulfur dioxide (SO2) between 2007 and 2018 and PM2.5 (aerosol particulate matter with diameter <2.5 μm) between 2010 and 2018. Additional air quality data were collected through a community-operated network of low-cost PM2.5 sensors during the 2018 LERZ eruption. From 2007 to 2018 the two most significant escalations in Kīlauea's volcanic emissions were: the summit eruption that began in 2008 (Kīlauea emissions averaged 5–6 kt/day SO2 from 2008 until summit activity decreased in May 2018) and the LERZ eruption in 2018 when SO2 emission rates reached a monthly average of 200 kt/day during June. In this paper we focus on characterizing the airborne pollutants arising from the 2018 LERZ eruption and the spatial distribution and severity of volcanic air pollution events across the Island of Hawai'i. The LERZ eruption caused the most frequent and severe exceedances of the Environmental Protection Agency (EPA) PM2.5 air quality threshold (35 μg/m3 as a daily average) in Hawai'i in the period 2010–2018. In Kona, for example, the maximum 24-h-mean mass concentration of PM2.5 was recorded as 59 μg/m3 on the twenty-ninth of May 2018, which was one of eight recorded exceedances of the EPA air quality threshold during the 2018 LERZ eruption, where there had been no exceedances in the previous 8 years as measured by the HDOH and NPS networks. SO2 air pollution during the LERZ eruption was most severe in communities in the south and west of the island, as measured by selected HDOH and NPS stations in this study, with a maximum 24-h-mean mass concentration of 728 μg/m3 recorded in Ocean View (100 km west of the LERZ emission source) in May 2018. Data from the low-cost sensor network correlated well with data from the HDOH PM2.5 instruments, confirming that these low-cost sensors provide a robust means to augment reference-grade instrument networks

    Scalar and vector Slepian functions, spherical signal estimation and spectral analysis

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    It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and, particularly for applications in the geosciences, for scalar and vectorial signals defined on the surface of a unit sphere.Comment: Submitted to the 2nd Edition of the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verlag. This is a slightly modified but expanded version of the paper arxiv:0909.5368 that appeared in the 1st Edition of the Handbook, when it was called: Slepian functions and their use in signal estimation and spectral analysi

    Beam characterisation and machine development at VELA

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    An overview is presented of developments on VELA (Versatile Electron Linear Accelerator), an RF photoinjector with two user stations (beam areas BA1, and BA2) at Daresbury Laboratory. Numerous machine development, commissioning, beam characterisation and user experiments have been completed in the past year. A new beamline and a dedicated multi-purpose chamber have been commissioned in BA1 and the first experiments performed. A number of measures have been taken to improve the stability of machine by mitigating problems with a phase drift, laser beam transport drift and a coherent beam oscillation. The 6D phase space of the electron beam has been characterised through quadrupole scans, transverse tomography and with a transverse deflecting cavity

    Ferromagnetic Semiconductors: Moving Beyond (Ga,Mn)As

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    The recent development of MBE techniques for growth of III-V ferromagnetic semiconductors has created materials with exceptional promise in spintronics, i.e. electronics that exploit carrier spin polarization. Among the most carefully studied of these materials is (Ga,Mn)As, in which meticulous optimization of growth techniques has led to reproducible materials properties and ferromagnetic transition temperatures well above 150 K. We review progress in the understanding of this particular material and efforts to address ferromagnetic semiconductors as a class. We then discuss proposals for how these materials might find applications in spintronics. Finally, we propose criteria that can be used to judge the potential utility of newly discovered ferromagnetic semiconductors, and we suggest guidelines that may be helpful in shaping the search for the ideal material.Comment: 37 pages, 4 figure

    Comparative Proteomics Analyses Reveal the virB of B. melitensis Affects Expression of Intracellular Survival Related Proteins

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    BACKGROUND: Brucella melitensis is a facultative, intracellular, pathogenic bacterium that replicates within macrophages. The type IV secretion system encoded by the virB operon (virB) is involved in Brucella intracellular survival. However, the underlying molecular mechanisms, especially the target proteins affected by the virB, remain largely unclear. METHODOLOGY/PRINCIPAL FINDINGS: In order to define the proteins affected by virB, the proteomes of wild-type and the virB mutant were compared under in vitro conditions where virB was highly activated. The differentially expressed proteins were identified by MALDI-TOF-MS. Forty-four down-regulated and eighteen up-regulated proteins which exhibited a 2-fold or greater change were identified. These proteins included those involved in amino acid transport and metabolism, lipid metabolism, energy production, cell membrane biogenesis, translation, post-translational modifications and protein turnover, as well as unknown proteins. Interestingly, several important virulence related proteins involved in intracellular survival, including VjbR, DnaK, HtrA, Omp25, and GntR, were down-regulated in the virB mutant. Transcription analysis of virB and vjbR at different growth phase showed that virB positively affect transcription of vjbR in a growth phase dependent manner. Quantitative RT-PCR showed that transcription of these genes was also affected by virB during macrophage cell infection, consistent with the observed decreased survival of the virB mutant in macrophage. CONCLUSIONS/SIGNIFICANCE: These data indicated that the virB operon may control the intracellular survival of Brucella by affecting the expression of relevant proteins

    Fermi Large Area Telescope observations of PSR J1836+5925

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    The discovery of the gamma-ray pulsar PSR J1836+5925, powering the formerly unidentified EGRET source 3EG J1835+5918, was one of the early accomplishments of the Fermi Large Area Telescope (LAT). Sitting 25 degrees off the Galactic plane, PSR J1836+5925 is a 173 ms pulsar with a characteristic age of 1.8 million years, a spindown luminosity of 1.1×1034\times10^{34} erg s1^{-1}, and a large off-peak emission component, making it quite unusual among the known gamma-ray pulsar population. We present an analysis of one year of LAT data, including an updated timing solution, detailed spectral results and a long-term light curve showing no indication of variability. No evidence for a surrounding pulsar wind nebula is seen and the spectral characteristics of the off-peak emission indicate it is likely magnetospheric. Analysis of recent XMM observations of the X-ray counterpart yields a detailed characterization of its spectrum, which, like Geminga, is consistent with that of a neutron star showing evidence for both magnetospheric and thermal emission.Comment: Accepted to Astrophysical Journa
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