Samuel Beckett and the Presence of Memory

Lois Oppenheim approaches the work of Samuel Beckett from a psychoanalytic point of view in the article “A Preoccupation With Object Representation: The Beckett–Bion Case Revisited.” Oppenheim asks, “why would an author endowed with as rich a visual memory as Beckett’s place the preoccupation with memory, the anxiety of remembrance, at the forefront of his art? . . . To what extent, more precisely, might there be a disturbance in object representation deriving from pathology in the writer’s own inner representational world?” In order to answer this question, Oppenheim brings Wilfred Bion, Beckett’s psychiatrist, to the forefront

Salix shiraii Seemen

原著和名: シラヰヤナギ科名: ヤナギ科 = Salicaceae採集地: 栃木県 日光市 東照宮裏〜雲竜入口 (下野 日光 東照宮裏〜雲竜入口)採集日: 1980/10/10採集者: 萩庭丈壽整理番号: JH006774国立科学博物館整理番号: TNS-VS-95677

Additional file 2: of Underreporting of hepatitis A in non-endemic countries: a systematic review and meta-analysis

Reference list of all articles reviewed in full-text. (DOCX 26 kb

Hybrid PDES Simulation of HPC Networks using Zombie Packets

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Enabling Efficient and Confident Annotation of LC−MS Metabolomics Data through MS1 Spectrum and Time Prediction

Liquid chromatography coupled to electrospray ionization-mass spectrometry (LC–ESI-MS) is a versatile and robust platform for metabolomic analysis. However, while ESI is a soft ionization technique, in-source phenomena including multimerization, nonproton cation adduction, and in-source fragmentation complicate interpretation of MS data. Here, we report chromatographic and mass spectrometric behavior of 904 authentic standards collected under conditions identical to a typical nontargeted profiling experiment. The data illustrate that the often high level of complexity in MS spectra is likely to result in misinterpretation during the annotation phase of the experiment and a large overestimation of the number of compounds detected. However, our analysis of this MS spectral library data indicates that in-source phenomena are not random but depend at least in part on chemical structure. These nonrandom patterns enabled predictions to be made as to which in-source signals are likely to be observed for a given compound. Using the authentic standard spectra as a training set, we modeled the in-source phenomena for all compounds in the Human Metabolome Database to generate a theoretical in-source spectrum and retention time library. A novel spectral similarity matching platform was developed to facilitate efficient spectral searching for nontargeted profiling applications. Taken together, this collection of experimental spectral data, predictive modeling, and informatic tools enables more efficient, reliable, and transparent metabolite annotation

Fractional abundance and stable carbon isotope composition of fatty acids in a muscle- and a stomach sample of the <i>Paralomis diomedeae</i> relative.

<p>Note that the stomach sample contained stomach contents and stomach epithelium. The bulk stable carbon isotope composition of the muscle is indicated (grey horizontal line).</p

Concentrations (µg g⁻¹ dry weight) and stable carbon isotope compositions of fatty acids, cholesterol and desmosterol.

<p>The sum of fatty acids comprises all analyzed fatty acids with chain length between 12–22 carbon atoms. The fatty acid stable carbon isotope compositions were calculated as abundance-weighted averages.</p

Differences of the mean and confidence interval for noise (a) and CT values (b) for bone, fat, fluid, lung, and muscle at different dose levels.

<p>Differences of the mean and confidence interval for noise (a) and CT values (b) for bone, fat, fluid, lung, and muscle at different dose levels.</p

Subjective image evaluation.

<p>The total of 160 images (80 original and 80 simulated) were presented to four radiologists. The four possible combinations of image type (original or simulation) and image rating (original and simulation) showed similar percentages of about 25% (range 24.5%–28.8%), suggesting a subjective rating by random.</p><p>Subjective image evaluation.</p

Image noise for different anatomical regions in original and simulated images at different dose levels.

<p>There were no significant differences between originals and simulations (p>0.05).</p><p>Image noise for different anatomical regions in original and simulated images at different dose levels.</p