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558 results on '"Greiner, D."'

2. The Double Chooz antineutrino detectors

Author

de Kerret, H., Abe, Y., Aberle, C., Abrahão, T., Ahijado, J. M., Akiri, T., Alarcón, J. M., Alba, J., Almazan, H., dos Anjos, J. C., Appel, S., Ardellier, F., Barabanov, I., Barriere, J. C., Baussan, E., Baxter, A., Bekman, I., Bergevin, M., Bernstein, A., Bertoli, W., Bezerra, T. J. C., Bezrukov, L., Blanco, C., Bleurvacq, N., Blucher, E., Bonet, H., Bongrand, M., Bowden, N. S, Brugière, T., Buck, C., Avanzini, M. Buizza, Busenitz, J., Cabrera, A., Caden, E., Calvo, E., Camilleri, L., Carr, R., Cazaux, S., Cela, J. M., Cerrada, M., Chang, P. J., Charon, P., Chauveau, E., Chimenti, P., Classen, T., Collin, A. P., Conover, E., Conrad, J. M, Cormon, S., Corpace, O., Courty, B., Crespo-Anadón, J. I., Cribier, M., Crum, K., Cuadrado, S., Cucoanes, A., D’Agostino, M., Damon, E., Dawson, J. V., Dazeley, S., Dierckxsens, M., Dietrich, D., Djurcic, Z., Dorigo, F., Dracos, M., Durand, V., Efremeko, Y., Elnimr, M., Etenko, A., Falk, E., Fallot, M., Fechner, M., Felde, J., Fernandes, S. M., Fernández-Bedoya, C., Francia, D., Franco, D., Fischer, V., Franke, A. J., Franke, M., Furuta, H., Garcia, F., Garcia, J., Gil-Botella, I., Giot, L., Givaudan, A., Göger-Neff, M., Gomez, H., Gonzalez, L. F. G., Goodenough, L., Goodman, M. C., Goon, J., Gramlich, B., Greiner, D., Guertin, A., Guillon, B., Habib, S. M., Haddad, Y., Hara, T., Hartmann, F. X., Hartnell, J., Haser, J., Hatzikoutelis, A., Hellwig, D., Hervé, S., Hofacker, R., Horton-Smith, G., Hourlier, A., Ishitsuka, M., Jänner, K., Jiménez, S., Jochum, J., Jollet, C., Kaether, F., Kale, K., Kalousis, L., Kamyshkov, Y., Kaneda, M., Kaplan, D. M., Karakac, M., Kawasaki, T., Kemp, E., Kibe, Y., Kirchner, T., Konno, T., Kryn, D., Kutter, T., Kuze, M., Lachenmaier, T., Lane, C. E., Langbrandtner, C., Lasserre, T., Lastoria, C., Latron, L., Leonardo, C., Letourneau, A., Lhuillier, D., Lima, Jr, H. P., Lindner, M., López-Castaño, J. M., LoSecco, J. M., Lubsandorzhiev, B., Lucht, S., Maeda, J., Maesano, C. N., Mariani, C., Maricic, J., Marie, F., Martinez, J. J., Martino, J., Matsubara, T., McKee, D., Meigner, F., Mention, G., Meregaglia, A., Meyer, J. P., Miletic, T., Milincic, R., Millot, J. F., Minotti, A., Mirones, V., Miyata, H., Mueller, Th. A., Nagasaka, Y., Nakajima, K., Navas-Nicolás, D., Nikitenko, Y., Novella, P., Oberauer, L., Obolensky, M., Onillon, A., Oralbaev, A., Ostrovskiy, I., Palomares, C., Peeters, S. J. M., Pepe, I. M., Perasso, S., Perrin, P., Pfahler, P., Porta, A., Pronost, G., Puras, J. C., Quéval, R., Ramirez, J. L., Reichenbacher, J., Reinhold, B., Reissfelder, M., Remoto, A., Reyna, D., Rodriguez, I., Röhling, M., Roncin, R., Rudolf, N., Rybolt, B., Sakamoto, Y., Santorelli, R., Sato, F., Schwan, U., Schönert, S., Schoppmann, S., Scola, L., Settimo, M., Shaevitz, M. A., Sharankova, R., Sibille, V., Sida, J.-L., Sinev, V., Shrestha, D., Skorokhvatov, M., Soldin, P., Spitz, J., Stahl, A., Stancu, I., Starzynski, P., Stock, M. R., Stokes, L. F. F., Strait, M., Stüken, A., Suekane, F., Sukhotin, S., Sumiyoshi, T., Sun, Y., Sun, Z., Svoboda, R., Tabata, H., Tamura, N., Terao, K., Tonazzo, A., Toral, F., Toups, M., Thi, H. Trinh, Valdivia, F., Valdiviesso, G., Vassilopoulos, N., Verdugo, A., Veyssiere, C., Viaud, B., Vignaud, D., Vivier, M., Wagner, S., Wiebusch, C., White, B., Winslow, L., Worcester, M., Wurm, M., Wurtz, J., Yang, G., Yáñez, J., Yermia, F., and Zbiri, K.

Published
2022
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16. Investigation of near-stoichiometric polycrystalline CuInSe2 thin films by photoreflectance spectroscopy.

Author

Levcenko, S., Stange, H., Choubrac, L., Greiner, D., Heinemann, M. D., Mainz, R., and Unold, T.

Subjects
THIN films, SPECTROMETRY, INVESTIGATIONS, ENERGY level transitions, HETEROJUNCTIONS
Abstract

The bandgap of CuInSe2 thin film photovoltaic absorbers depends on the Cu content, although the nature of this dependence is still a matter of debate. While theoretical results predicted a widening or stable bandgap with decreasing Cu content, the few experimental data available point to a narrowing of the bandgap. Here, we apply photoreflectance spectroscopy at room temperature to near-stoichiometric polycrystalline CuInSe2/CdS heterojunctions with a lateral Cu gradient to analyze the electronic transitions in the vicinity of the fundamental absorption edge of CuInSe2 absorber as a function of Cu deficiency. The results indicate that the lowest bandgap transition at 1.02 eV notably decreases by 20–30 meV for slightly Cu deficient samples, strengthening the case for an association of a lower Cu content with a narrower bandgap. In contrast, the higher energy transition at 1.25 eV does not show a redshift, which requires further theoretical explanation. [ABSTRACT FROM AUTHOR]

Published
2020
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21. Authors' reply to the Discussion of 'Experimental evaluation of algorithm-assisted human decision-making: application to pretrial public safety assessment.'.

Author

Imai, Kosuke, Jiang, Zhichao, Greiner, D James, Halen, Ryan, and Shin, Sooahn

Subjects
PUBLIC safety, DECISION making, SOCIAL scientists, DECISION theory, STATISTICS
Abstract

This consideration is critical in our study because judges' decisions can affect individual arrestees. Instead of engaging with this philosophical debate, we examine Dawid's recommendation to use the statistical decision theory for answering the following questions: (1) 'should we present PSA to the judge before she makes her decision, or not? As explained above, to decide on the use of PSA, policy makers need to understand if PSA helps judges achieve their goal of preventing a negative outcome while avoiding unnecessarily harsh decisions. Finally, several commentators asked why our study design did not involve blinding of judges either to the intervention or to the fact of the study. [Extracted from the article]

Published
2023
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22. Experimental evaluation of algorithm-assisted human decision-making: application to pretrial public safety assessment.

Author

Imai, Kosuke, Jiang, Zhichao, Greiner, D James, Halen, Ryan, and Shin, Sooahn

Subjects
PUBLIC safety, DECISION making, RANDOMIZED controlled trials, CRIMINAL justice system
Abstract

Despite an increasing reliance on fully-automated algorithmic decision-making in our day-to-day lives, humans still make consequential decisions. While the existing literature focuses on the bias and fairness of algorithmic recommendations, an overlooked question is whether they improve human decisions. We develop a general statistical methodology for experimentally evaluating the causal impacts of algorithmic recommendations on human decisions. We also examine whether algorithmic recommendations improve the fairness of human decisions and derive the optimal decision rules under various settings. We apply the proposed methodology to the first-ever randomized controlled trial that evaluates the pretrial Public Safety Assessment in the United States criminal justice system. Our analysis of the preliminary data shows that providing the PSA to the judge has little overall impact on the judge's decisions and subsequent arrestee behaviour. [ABSTRACT FROM AUTHOR]

Published
2023
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36. Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment

Author

Ben-Michael, Eli, Greiner, D. James, Imai, Kosuke, and Jiang, Zhichao

Subjects
Methodology (stat.ME), FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, Machine Learning (stat.ML), Statistics - Methodology, Machine Learning (cs.LG)
Abstract

Algorithmic recommendations and decisions have become ubiquitous in today's society. Many of these and other data-driven policies, especially in the realm of public policy, are based on known, deterministic rules to ensure their transparency and interpretability. For example, algorithmic pre-trial risk assessments, which serve as our motivating application, provide relatively simple, deterministic classification scores and recommendations to help judges make release decisions. How can we use the data based on existing deterministic policies to learn new and better policies? Unfortunately, prior methods for policy learning are not applicable because they require existing policies to be stochastic rather than deterministic. We develop a robust optimization approach that partially identifies the expected utility of a policy, and then finds an optimal policy by minimizing the worst-case regret. The resulting policy is conservative but has a statistical safety guarantee, allowing the policy-maker to limit the probability of producing a worse outcome than the existing policy. We extend this approach to common and important settings where humans make decisions with the aid of algorithmic recommendations. Lastly, we apply the proposed methodology to a unique field experiment on pre-trial risk assessment instruments. We derive new classification and recommendation rules that retain the transparency and interpretability of the existing instrument while potentially leading to better overall outcomes at a lower cost.

Published
2021

46. Sex Drives: Fantasies of Fascism in Literary Modernism

Author

Greiner, D. Rae

Subjects
Sex Drives: Fantasies of Fascism in Literary Modernism (Book) -- Frost, Laura, Books -- Book reviews
Abstract

Sex Drives: Fantasies of Fascism in Literary Modernism. By LAURA FROST. Ithaca, N.Y.: Cornell University Press, 2002. Pp. viii + 197. $45.00 (cloth); $17.95 (paper). In Sex Drives Laura Frost [...]

Published
2003

48. Human peripheral blood leucocyte non-obese diabetic-severe combined immunodeficiency interleukin-2 receptor gamma chain gene mouse model of xenogeneic graft-versus-host-like disease and the role of host major histocompatibility complex

Author

King, M. A., Covassin, L., Brehm, M. A., Racki, W., Pearson, T., Leif, J., Laning, J., Fodor, W., Foreman, O., Burzenski, L., Chase, T. H., Gott, B., Rossini, A. A., Bortell, R., Shultz, L. D., and Greiner, D. L.

Published
2009
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50. Glow discharge optical emission spectrometry for quantitative depth profiling of CIGS thin-films

Author

Kodalle, T., Greiner, D., Brackmann, V., Prietzel, K., Scheu, A., Bertram, T., Reyes-Figueroa, P., Unold, T., Abou-Ras, D., Schlatmann, R., Kaufmann, C.A., Hoffmann, V., and Publica

Abstract

Determining elemental distributions dependent on the thickness of a sample is of utmost importance for process optimization in different fields e.g. from quality control in the steel industry to controlling doping profiles in semiconductor labs. Glow discharge optical emission spectrometry (GD-OES) is a widely used tool for fast measurements of depth profiles. In order to be able to draw profound conclusions from GD-OES profiles, one has to optimize the measurement conditions for the given application as well as to ensure the suitability of the used emission lines. Furthermore a quantification algorithm has to be implemented to convert the measured properties (intensity of the emission lines versus sputtering time) to more useful parameters, e.g. the molar fractions versus sample depth (depth profiles). In this contribution a typical optimization procedure of the sputtering parameters is adapted to the case of polycrystalline Cu(In,Ga)(S,Se)2 thin films, which are used as absorber layers in solar cell devices, for the first time. All emission lines used are shown to be suitable for the quantification of the depth profiles and a quantification routine based on the assumption of constant emission yield is used. The accuracy of this quantification method is demonstrated on the basis of several examples. The bandgap energy profile of the compound semiconductor, as determined by the elemental distributions, is compared to optical measurements. The depth profiles of Na-the main dopant in these compounds-are correlated with measurements of the open-circuit voltage of the corresponding devices, and the quantification of the sample depth is validated by comparison with profilometry and X-ray fluorescence measurements.

Published
2019

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