4,614 research outputs found

    A review of melt and vapor growth techniques for polydiacetylene thin films for nonlinear optical applications

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    Methods for the growth of polydiacetylene thin films by melt and vapor growth and their subsequent polymerization are summarized. Films with random orientations were obtained when glass or quartz were used as substrates in the vapor growth process. Oriented polydiacetylene films were fabricated by the vapor deposition of diacetylene monomer onto oriented polydiacetylene on a glass substrate and its subsequent polymerization by UV light. A method for the growth of oriented thin films by a melt-shear growth process as well as a method of film growth by seeded recrstallization from the melt between glass plates, that may be applied to the growth of polydiacetylene films, are described. Moreover, a method is presented for the fabrication of single crystal thin films of polyacetylenes by irradiation of the surface of diacetylene single crystals to a depth between 100 and 2000 angstroms

    A preliminary review of organic materials single crystal growth by the Czochralski technique

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    The growth of single crystals of organic compounds by the Czochralski method is reviewed. From the literature it is found that single crystals of benzil, a nonlinear optical material with a d sub 11 value of 11.2 + or - 1.5 x d sub 11 value of alpha quartz, has fewer dislocations than generally contained in Bridgman crystals. More perfect crystals were grown by repeated Czochralski growth. This consists of etching away the defect-containing portion of a Czochralski grown crystal and using it as a seed for further growth. Other compounds used to grow single crystals are benzophenone, 12-tricosanone (laurone), and salol. The physical properties, growth apparatus, and processing conditions presented in the literature are discussed. Moreover, some of the possible advantages of growing single crystals of organic compounds in microgravity to obtain more perfect crystals than on Earth are reviewed

    Risperidone-induced psychosis and depression in a child with a mitochondrial disorder

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    OBJECTIVE: To our knowledge, this is the first published case report of an adolescent girl with a mitochondrial disorder and depression who displayed both new-onset psychotic and increased mood symptoms during treatment with risperidone. DATA: A 16-year-old girl was treated with risperidone for mood lability and impulsivity at a community hospital. Within days, she developed paranoid ideation, profound psychomotor retardation, increased depression, and fatigue. She was transferred to an inpatient psychiatric hospital, where she was taken off risperidone. Within 48 hours after discontinuation of the medication, she had complete resolution of psychotic symptoms, fatigue, and psychomotor retardation, and her depression improved. CONCLUSIONS: This observation of on-off risperidone treatment suggests that risperidone may have worsened both psychiatric and physical manifestations of the mitochondrial disorder in this adolescent. These findings are consistent with recent in vitro literature, which implicate a series of neuroleptic medications with mitochondrial dysfunction. Furthermore, the authors provide diagnostic and treatment options that are available for mitochondrial disorders, which are of interest to child psychiatrists due to the central nervous system manifestations of these disorders

    Bayesian optimization for materials design

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    We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian process regression, which allows predicting the performance of a new design based on previously tested designs. After providing a detailed introduction to Gaussian process regression, we introduce two Bayesian optimization methods: expected improvement, for design problems with noise-free evaluations; and the knowledge-gradient method, which generalizes expected improvement and may be used in design problems with noisy evaluations. Both methods are derived using a value-of-information analysis, and enjoy one-step Bayes-optimality

    Data Citation in Neuroimaging: Proposed Best Practices for Data Identification and Attribution

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    Data sharing and reuse, while widely accepted as good ideas, have been slow to catch on in any concrete and consistent way. One major hurdle within the scientific community has been the lack of widely accepted standards for citing that data, making it difficult to track usage and measure impact. Within the neuroimaging community, there is a need for a way to not only clearly identify and cite datasets, but also to derive new aggregate sets from multiple sources while clearly maintaining lines of attribution. This work presents a functional prototype of a system to integrate Digital Object Identifiers (DOI) and a standardized metadata schema into a XNAT-based repository workflow, allowing for identification of data at both the project and image level. These item and source level identifiers allow any newly defined combination of images, from any number of projects, to be tagged with a new group-level DOI that automatically inherits the individual attributes and provenance information of its constituent parts. This system enables the tracking of data reuse down to the level of individual images. The implementation of this type of data identification system would impact researchers and data creators, data hosting facilities, and data publishers, but the benefit of having widely accepted standards for data identification and attribution would go far toward making data citation practical and advantageous

    An assessment of the autism neuroimaging literature for the prospects of re-executability

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    Background: The degree of reproducibility of the neuroimaging literature in psychiatric application areas has been called into question and the issues that relate to this reproducibility are extremely complex. Some of these complexities have to do with the underlying biology of the disorders that we study and others arise due to the technology we apply to the analysis of the data we collect. Ultimately, the observations we make get communicated to the rest of the community through publications in the scientific literature. Methods: We sought to perform a ‘re-executability survey’ to evaluate the recent neuroimaging literature with an eye toward seeing if the technical aspects of our publication practices are helping or hindering the overall quest for a more reproducible understanding of brain development and aging. The topic areas examined include availability of the data, the precision of the imaging method description and the reporting of the statistical analytic approach, and the availability of the complete results. We applied the survey to 50 publications in the autism neuroimaging literature that were published between September 16, 2017 to October 1, 2018. Results: The results of the survey indicate that for the literature examined, data that is not already part of a public repository is rarely available, software tools are usually named but versions and operating system are not, it is expected that reasonably skilled analysts could approximately perform the analyses described, and the complete results of the studies are rarely available. Conclusions: We have identified that there is ample room for improvement in research publication practices. We hope exposing these issues in the retrospective literature can provide guidance and motivation for improving this aspect of our reporting practices in the future

    Design of intelligent mesoscale periodic array structures utilizing smart hydrogel

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    Mesoscale Periodic Array Structures (MPAS, also known as crystalline colloidal arrays), composed of aqueous or nonaqueous dispersions of self-assembled submicron colloidal spheres are emerging toward the development of advanced optical devices for technological applications. This is because of their unique optical diffraction properties and the ease with which these intriguing properties can be modulated experimentally. Moreover our recent advancements in this area which include 'locking' the liquid MPAS into solid or semisolid polymer matrices for greater stability with longer life span, and incorporation of CdS quantum dots and laser dyes into colloidal spheres to obtain nonlinear optical (NLO) responses further corroborate the use of MPAS in optical technology. Our long term goal is fabrication of all-optical and electro-optical devices such as spatial light modulators for optical signal processing and flat panel display devices by utilizing intelligent nonlinear periodic array structural materials. Here we show further progress in the design of novel linear MPAS which have the ability to sense and respond to an external source such as temperature. This is achieved by combining the self-assembly properties of polymer colloidal spheres and thermoshrinking properties of smart polymer gels. At selected temperatures the periodic array efficiently Bragg diffracts light and transmits most of the light at other temperatures. Hence these intelligent systems are of potential use as fixed notch filters optical switches or limiters to protect delicate optical sensors from high intensity laser radiation

    Growth and Characteristics of Bulk Single Crystals Grown from Solution on Earth and in Microgravity

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    The growth of crystals has been of interest to physicists and engineers for a long time because of their unique properties. Single crystals are utilized in such diverse applications as pharmaceuticals, computers, infrared detectors, frequency measurements, piezoelectric devices, a variety of high technology devices and sensors. Solution crystal growth is one of the important techniques to grow a variety of crystals when the material decomposes at the melting point and a suitable solvent is available to make a saturated solution at a desired temperature. In this chapter an attempt is made to give some fundamentals of growing crystals from solution including improved designs of various crystallizers. Since the same solution crystal growth technique could not be used in microgravity, authors had proposed a new cooled sting technique to grow crystals in space. Authors? experiences of conducting two space shuttle experiments relating to solution crystal growth are also detailed in this work. The complexity of these solution growth experiments to grow crystals in space are discussed. These happen to be some of the early experiments performed in space, and various lessons learned are described. A brief discussion of protein crystal growth that also shares basic principles of solution growth technique is given along with some flight hardware information for its growth in microgravity
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