286 research outputs found

    Observation of eliminative cationic polymerization within van der Waals clusters

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    We report the first observation of eliminative cationic polymerization within van der Waals (vdW) clusters following electron impact ionization at pressures of 10−8 Torr. The elimination reactions of C2H3Cl+ within the clusters terminate after three successive steps, each involving elimination of HCl or Cl. The results provide a mechanism for the early stages of gas phase cationic polymerization of vinyl chloride and demonstrate the feasibility of using vdW clusters as a means of studying gas phase cationic polymerization

    Comparative Solubility of Protein in Cottonseed Flakes Extracted by Hexane and by Ethanol

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    The solvent commonly used in the United States for the extraction of vegetable oils is a petroleum fraction consisting mainly of hexane. Experimental work has been done in this country on the extraction by ethanol of soybean oil by Beckel and associates (1) and of cottonseed and other oils by Rao and associates (4, 5). Ethanol appears promising for use in Asian countries such as India and China largely because it is more readily available than commercial hexane (6). The ethanol extracted cottonseed meal has a lower gossypol content than the hexane extracted meal and for that reason is preferable. However, it is known that ethanol may coagulate some proteins, thus reducing their solubility in water and in aqueous solutions. Because of this relation of solubility and the nutritional value of the protein, determinations of the solubilities of meals produced by the extraction of cottonseed with ethanol and meals produced by the extraction with commercial hexane were made

    Work functions, ionization potentials, and in-between: Scaling relations based on the image charge model

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    We revisit a model in which the ionization energy of a metal particle is associated with the work done by the image charge force in moving the electron from infinity to a small cut-off distance just outside the surface. We show that this model can be compactly, and productively, employed to study the size dependence of electron removal energies over the range encompassing bulk surfaces, finite clusters, and individual atoms. It accounts in a straightforward manner for the empirically known correlation between the atomic ionization potential (IP) and the metal work function (WF), IP/WF\sim2. We formulate simple expressions for the model parameters, requiring only a single property (the atomic polarizability or the nearest neighbor distance) as input. Without any additional adjustable parameters, the model yields both the IP and the WF within \sim10% for all metallic elements, as well as matches the size evolution of the ionization potentials of finite metal clusters for a large fraction of the experimental data. The parametrization takes advantage of a remarkably constant numerical correlation between the nearest-neighbor distance in a crystal, the cube root of the atomic polarizability, and the image force cutoff length. The paper also includes an analytical derivation of the relation of the outer radius of a cluster of close-packed spheres to its geometric structure.Comment: Original submission: 8 pages with 7 figures incorporated in the text. Revised submission (added one more paragraph about alloy work functions): 18 double spaced pages + 8 separate figures. Accepted for publication in PR

    ARTEMIS Science Objectives

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    NASA's two spacecraft ARTEMIS mission will address both heliospheric and planetary research questions, first while in orbit about the Earth with the Moon and subsequently while in orbit about the Moon. Heliospheric topics include the structure of the Earth's magnetotail; reconnection, particle acceleration, and turbulence in the Earth's magnetosphere, at the bow shock, and in the solar wind; and the formation and structure of the lunar wake. Planetary topics include the lunar exosphere and its relationship to the composition of the lunar surface, the effects of electric fields on dust in the exosphere, internal structure of the Moon, and the lunar crustal magnetic field. This paper describes the expected contributions of ARTEMIS to these baseline scientific objectives

    Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19

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    Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19–25%), cerebrovascular diseases (24%, 13–35%), nontraumatic intracranial hemorrhage (34%, 20–50%), encephalitis and/or myelitis (37%, 17–60%) and myopathy (72%, 67–77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease

    The effect of a warm electron beam on slow electron-acoustic solitons

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    The effects of the inclusion of finite drift speed of a warm electron component on the existence of arbitrary amplitude slow electron-acoustic solitons are investigated in a model with ions and cool, warm, and hot electrons. All plasma species are treated as adiabatic fluids. For fixed densities of the cool, warm, and hot electrons, the admissible Mach number ranges of the supported negative potential solitons are found to widen with increasing warm electron beam speed, up to a maximum value of vdbwo = 0.7. Beyond this maximum value, the soliton Mach number ranges become narrower and vanish completely at vdbwo = 1.084 where a switch to positive polarity solitons occurs. For a fixed value of the drift speed of the warm electrons, the cool electron density value at which the switch to positive polarity soliton occurs is the lowest when there is no streaming of the warm electrons but increases with increasing drift speed

    Oxidation behavior of graphene-coated copper at intrinsic graphene defects of different origins

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    The development of ultrathin barrier films is vital to the advanced semiconductor industry. Graphene appears to hold promise as a protective coating; however, the polycrystalline and defective nature of engineered graphene hinders its practical applications. Here, we investigate the oxidation behavior of graphene-coated Cu foils at intrinsic graphene defects of different origins. Macro-scale information regarding the spatial distribution and oxidation resistance of various graphene defects is readily obtained using optical and electron microscopies after the hot-plate annealing. The controlled oxidation experiments reveal that the degree of structural deficiency is strongly dependent on the origins of the structural defects, the crystallographic orientations of the underlying Cu grains, the growth conditions of graphene, and the kinetics of the graphene growth. The obtained experimental and theoretical results show that oxygen radicals, decomposed from water molecules in ambient air, are effectively inverted at Stone-Wales defects into the graphene/Cu interface with the assistance of facilitators

    International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

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    Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach
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