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964 results on '"Beyer, D."'

3. Author Response: Disulfide bridge-dependent dimerization triggers FGF2 membrane translocation into the extracellular space

Author

Lolicato, F, primary, Steringer, JP, primary, Saleppico, R, additional, Beyer, D, additional, Fernandez-Sobaberas, J, additional, Unger, S, additional, Klein, S, additional, Riegerová, P, additional, Wegehingel, S, additional, Müller, HM, additional, Schmitt, XJ, additional, Kaptan, S, additional, Freund, C, additional, Hof, M, additional, Šachl, R, additional, Chlanda, P, additional, Vattulainen, I, additional, and Nickel, W, additional

Published
2023
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4. Disulfide bridge-dependent dimerization triggers FGF2 membrane translocation into the extracellular space

Author

Lolicato, F, primary, Steringer, JP, primary, Saleppico, R, additional, Beyer, D, additional, Fernandez-Sobaberas, J, additional, Unger, S, additional, Klein, S, additional, Riegerová, P, additional, Wegehingel, S, additional, Müller, HM, additional, Schmitt, XJ, additional, Kaptan, S, additional, Freund, C, additional, Hof, M, additional, Šachl, R, additional, Chlanda, P, additional, Vattulainen, I, additional, and Nickel, W, additional

Published
2023
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10. A case of the burning heart: myopericarditis

Author

Beyer, D, primary, Correa, F, additional, Reyes-Ramirez, M, additional, Harris, CH, additional, Van Dreumel, C, additional, Jodari-Karimi, M, additional, Engel, LS, additional, Imsais, W, additional, and Rahman, M, additional

Published
2023
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12. Kontrazeption und Familienplanung

Author

Amari, F., Beyer, D. A., Ludwig, M., Felberbaum, R. E., Weiss, J. M., Diedrich, K., Kaufmann, Manfred, editor, Costa, Serban D., editor, and Scharl, Anton, editor

Published
2013
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13. <scp>SNAPSHOT USA</scp> 2020: A second coordinated national camera trap survey of the United States during the <scp>COVID</scp> ‐19 pandemic

Author

Kays R., Cove M. V., Diaz J., Todd K., Bresnan C., Snider M., Lee T. E., Jasper J. G., Douglas B., Crupi A. P., Weiss K. C. B., Rowe H., Sprague T., Schipper J., Lepczyk C. A., Fantle-Lepczyk J. E., Davenport J., Zimova M., Farris Z., Williamson J., Fisher-Reid M. C., Rezendes D., King S. M., Chrysafis P., Jensen A. J., Jachowski D. S., King K. C., Herrera D. J., Moore S., van der Merwe M., Lombardi J. V., Sergeyev M., Tewes M. E., Horan R. V., Rentz M. S., Driver A., Brandt L. R. S. E., Nagy C., Alexander P., Maher S. P., Darracq A. K., Barr E. G., Hess G., Webb S. L., Proctor M. D., Vanek J. P., Lafferty D. J. R., Hubbard T., Jimenez J. E., McCain C., Favreau J., Fogarty J., Hill J., Hammerich S., Gray M., Rega-Brodsky C. C., Durbin C., Flaherty E. A., Brooke J., Coster S. S., Lathrop R. G., Russell K., Bogan D. A., Shamon H., Rooney B., Rockhill A., Lonsinger R. C., O'Mara M. T., Compton J. A., Barthelmess E. L., Andy K. E., Belant J. L., Petroelje T., Wehr N. H., Beyer D. E., Scognamillo D. G., Schalk C., Day K., Ellison C. N., Ruthven C., Nunley B., Fritts S., Whittier C. A., Neiswenter S. A., Pelletier R., DeGregorio B. A., Kuprewicz E. K., Davis M. L., Baruzzi C., Lashley M. A., McDonald B., Mason D., Risch D. R., Allen M. L., Whipple L. S., Sperry J. H., Alexander E., Wolff P. J., Hagen R. H., Mortelliti A., Bolinjcar A., Wilson A. M., Van Norman S., Powell C., Coletto H., Schauss M., Bontrager H., Beasley J., Ellis-Felege S. N., Wehr S. R., Giery S. T., Pekins C. E., LaRose S. H., Revord R. S., Hansen C. P., Hansen L., Millspaugh J. J., Zorn A., Gerber B. D., Rezendes K., Adley J., Sevin J., Green A. M., Sekercioglu C. H., Pendergast M. E., Mullen K., Bird T., Edelman A. J., Romero A., O'Neill B. J., Schmitz N., Vandermus R. A., Alston J. M., Kuhn K. M., Hasstedt S. C., Lesmeister D. B., Appel C. L., Rota C., Stenglein J. L., Anhalt-Depies C., Nelson C. L., Long R. A., Remine K. R., Jordan M. J., Elbroch L. M., Bergman D., Cendejas-Zarelli S., Sager-Fradkin K., Conner M., Morris G., Parsons E., Hernandez-Yanez H., McShea W. J., Kays, R., Cove, M. V., Diaz, J., Todd, K., Bresnan, C., Snider, M., Lee, T. E., Jasper, J. G., Douglas, B., Crupi, A. P., Weiss, K. C. B., Rowe, H., Sprague, T., Schipper, J., Lepczyk, C. A., Fantle-Lepczyk, J. E., Davenport, J., Zimova, M., Farris, Z., Williamson, J., Fisher-Reid, M. C., Rezendes, D., King, S. M., Chrysafis, P., Jensen, A. J., Jachowski, D. S., King, K. C., Herrera, D. J., Moore, S., van der Merwe, M., Lombardi, J. V., Sergeyev, M., Tewes, M. E., Horan, R. V., Rentz, M. S., Driver, A., Brandt, L. R. S. E., Nagy, C., Alexander, P., Maher, S. P., Darracq, A. K., Barr, E. G., Hess, G., Webb, S. L., Proctor, M. D., Vanek, J. P., Lafferty, D. J. R., Hubbard, T., Jimenez, J. E., Mccain, C., Favreau, J., Fogarty, J., Hill, J., Hammerich, S., Gray, M., Rega-Brodsky, C. C., Durbin, C., Flaherty, E. A., Brooke, J., Coster, S. S., Lathrop, R. G., Russell, K., Bogan, D. A., Shamon, H., Rooney, B., Rockhill, A., Lonsinger, R. C., O'Mara, M. T., Compton, J. A., Barthelmess, E. L., Andy, K. E., Belant, J. L., Petroelje, T., Wehr, N. H., Beyer, D. E., Scognamillo, D. G., Schalk, C., Day, K., Ellison, C. N., Ruthven, C., Nunley, B., Fritts, S., Whittier, C. A., Neiswenter, S. A., Pelletier, R., Degregorio, B. A., Kuprewicz, E. K., Davis, M. L., Baruzzi, C., Lashley, M. A., Mcdonald, B., Mason, D., Risch, D. R., Allen, M. L., Whipple, L. S., Sperry, J. H., Alexander, E., Wolff, P. J., Hagen, R. H., Mortelliti, A., Bolinjcar, A., Wilson, A. M., Van Norman, S., Powell, C., Coletto, H., Schauss, M., Bontrager, H., Beasley, J., Ellis-Felege, S. N., Wehr, S. R., Giery, S. T., Pekins, C. E., Larose, S. H., Revord, R. S., Hansen, C. P., Hansen, L., Millspaugh, J. J., Zorn, A., Gerber, B. D., Rezendes, K., Adley, J., Sevin, J., Green, A. M., Sekercioglu, C. H., Pendergast, M. E., Mullen, K., Bird, T., Edelman, A. J., Romero, A., O'Neill, B. J., Schmitz, N., Vandermus, R. A., Alston, J. M., Kuhn, K. M., Hasstedt, S. C., Lesmeister, D. B., Appel, C. L., Rota, C., Stenglein, J. L., Anhalt-Depies, C., Nelson, C. L., Long, R. A., Remine, K. R., Jordan, M. J., Elbroch, L. M., Bergman, D., Cendejas-Zarelli, S., Sager-Fradkin, K., Conner, M., Morris, G., Parsons, E., Hernandez-Yanez, H., and Mcshea, W. J.

Subjects
United State, Carnivora, Wild, mammal, Animals, Wild, Didelphimorphia, species distribution modeling, Birds, Bird, camera traps, biodiversity, biogeography, Cetartiodactyla, Lagomorpha, mammals, occupancy modeling, Animals, Humans, Mammals, Pandemics, United States, COVID-19, Ecology, Evolution, Behavior and Systematics, Pandemic, camera trap, Animal, Human
Abstract

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

Published
2022
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19. Akutes Abdomen

Author

Swart, B., Beyer, D., Köster, R., Heuck, F., editor, Fuchs, H.-F., editor, Donner, M. W., editor, Beyer, D., editor, Hellstern, A., editor, Hofmann-Preiss, K., editor, Jessen, K., editor, Jones, B., editor, Köster, R., editor, Mathias, K., editor, Nitz, Ch., editor, Reeders, J. W. A. J., editor, Rödl, W., editor, Rosenbusch, G., editor, Rübesam, D., editor, Swart, B., editor, Trüber, E., editor, and Worlicek, H., editor

Published
1990
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24. Clarifying space use concepts in ecology: range vs. occurrence distributions

Author

Alston, J., Fleming, C., Noonan, M., Tucker, M., Silva, I., Folta, C., Akre, T., Ali, A., Belant, J., Beyer, D., Blaum, N., Boehning-Gaese, K., Cunha De Paula, R., Dekker, J., Drescher-Lehman, J., Farwig, N., Fichtel, C., Fischer, C., Ford, A., Janssen, R., Jeltsch, F., Kappeler, P., Lapoint, S., Markham, A., Medici, P., Morato, R., Nathan, R., Olson, K., Patterson, B., Petroelje, T., Ramalho, E., Roesner, S., Santos, L., Schabo, D., Selva, N., Sergiel, A., Spiegel, O., Ullman, W., Zieba, F., Zwijacz-Kozica, T., Wittemyer, G., Fagan, W., Mueller, T., (0000-0003-0575-6408) Calabrese, J., Alston, J., Fleming, C., Noonan, M., Tucker, M., Silva, I., Folta, C., Akre, T., Ali, A., Belant, J., Beyer, D., Blaum, N., Boehning-Gaese, K., Cunha De Paula, R., Dekker, J., Drescher-Lehman, J., Farwig, N., Fichtel, C., Fischer, C., Ford, A., Janssen, R., Jeltsch, F., Kappeler, P., Lapoint, S., Markham, A., Medici, P., Morato, R., Nathan, R., Olson, K., Patterson, B., Petroelje, T., Ramalho, E., Roesner, S., Santos, L., Schabo, D., Selva, N., Sergiel, A., Spiegel, O., Ullman, W., Zieba, F., Zwijacz-Kozica, T., Wittemyer, G., Fagan, W., Mueller, T., and (0000-0003-0575-6408) Calabrese, J.

Abstract

Quantifying animal movements is necessary for answering a wide array of research questions in ecology and conservation biology. Consequently, ecologists have made considerable efforts to identify the best way to estimate an animal’s home range, and many methods of estimating home ranges have arisen over the past half century. Most of these methods fall into two distinct categories of estimators that have only recently been described in statistical detail: those that measure range distributions (methods such as Kernel Density Estimation that quantify the long-run behavior of a movement process that features restricted space use) and those that measure occurrence distributions (methods such as Brownian Bridge Movement Models and the Correlated Random Walk Library that quantify uncertainty in an animal movement path during a specific period of observation). In this paper, we use theory, simulations, and empirical analysis to demonstrate the importance of applying these two classes of space use estimators appropriately and distinctly. Conflating range and occurrence distributions can have serious consequences for ecological inference and conservation practice. For example, in most situations, home-range estimates quantified using occurrence estimators are too small, and this problem is exacerbated by ongoing improvements in tracking technology that enable more frequent and more accurate data on animal movements. We encourage researchers to use range estimators to estimate the area of home ranges and occurrence estimators to answer other questions in movement ecology, such as when and where an animal crosses a linear feature, visits a location of interest, or interacts with other animals.

Published
2022

25. Learning to Sieve: Prediction of Grading Curves from Images of Concrete Aggregate

Author

Yilmaz, A., Wegner, J.D., Qin, R., Remondino, F., Fuse, T., Toschi, I., Coenen, M., Beyer, D., Heipke, C., Haist, M., Yilmaz, A., Wegner, J.D., Qin, R., Remondino, F., Fuse, T., Toschi, I., Coenen, M., Beyer, D., Heipke, C., and Haist, M.

Abstract

A large component of the building material concrete consists of aggregate with varying particle sizes between 0.125 and 32 mm. Its actual size distribution significantly affects the quality characteristics of the final concrete in both, the fresh and hardened states. The usually unknown variations in the size distribution of the aggregate particles, which can be large especially when using recycled aggregate materials, are typically compensated by an increased usage of cement which, however, has severe negative impacts on economical and ecological aspects of the concrete production. In order to allow a precise control of the target properties of the concrete, unknown variations in the size distribution have to be quantified to enable a proper adaptation of the concrete's mixture design in real time. To this end, this paper proposes a deep learning based method for the determination of concrete aggregate grading curves. In this context, we propose a network architecture applying multi-scale feature extraction modules in order to handle the strongly diverse object sizes of the particles. Furthermore, we propose and publish a novel dataset of concrete aggregate used for the quantitative evaluation of our method.

Published
2022

27. Maternal smoking promotes chronic obstructive lung disease in the offspring as adults

Author

Beyer D, Mitfessel H, and Gillissen A

Subjects
chronic obstructive pulmonary disease, COPD, second hand smoking, Medicine
Abstract

Abstract Introduction In utero and/or childhood environmental tobacco smoke exposure is well known to adversely affect lung function and to depreciate child's health in many ways. Fewer studies have assessed the long-term effects on COPD development and disease severity in later adulthood. Methods COPD patients were interviewed using a structured questionnaire regarding their personal as well as the smoking habits of their parents. Data were compared with the disease history, e.g. COPD exacerbation rate, and their lung function data. Results Between 2003 and 2004 COPD patients were recruited a) in a private practice specialized in pulmonary medicine (n = 133) and b) in a hospital (n = 158). 75% of their fathers and only 15.4 of all mothers smoked regularly. COPD patients from smoking mothers had lower FEV1 predicted than those raised in household without maternal smoking exposure: 39.4 ± 9.5% vs. 51.9 ± 6.0% (P = 0.037). Fathers had no effect on FEV1 regardless if they are smokers or non-smokers. Rate of severe exacerbations requiring hospitalization remained unaffected by parental second hand smoke exposure. Conclusion Maternal smoking negatively affects lung function of their offspring even in late adulthood when they develop COPD. It even aggravates the cumulative effect of active cigarette consumption. Clinical course of the COPD remained unaffected.

Published
2009
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40. Semi-supervised segmentation of concrete aggregate using consensus regularisation and prior guidance

Author

Coenen, M., Schack, T., Beyer, D., Heipke, C., Haist, M., Coenen, M., Schack, T., Beyer, D., Heipke, C., and Haist, M.

Abstract

In order to leverage and profit from unlabelled data, semi-supervised frameworks for semantic segmentation based on consistency training have been proven to be powerful tools to significantly improve the performance of purely supervised segmentation learning. However, the consensus principle behind consistency training has at least one drawback, which we identify in this paper: imbalanced label distributions within the data. To overcome the limitations of standard consistency training, we propose a novel semi-supervised framework for semantic segmentation, introducing additional losses based on prior knowledge. Specifically, we propose a lightweight architecture consisting of a shared encoder and a main decoder, which is trained in a supervised manner. An auxiliary decoder is added as additional branch in order to make use of unlabelled data based on consensus training, and we add additional constraints derived from prior information on the class distribution and on auto-encoder regularisation. Experiments performed on our concrete aggregate dataset presented in this paper demonstrate the effectiveness of the proposed approach, outperforming the segmentation results achieved by purely supervised segmentation and standard consistency training.

Published
2021

45. Blood concentrations of everolimus are markedly increased by ketoconazole

Author

Kovarik, J.M., Beyer, D., Bizot, N., Jiang, Q., Shenouda, M., and Schmouder, R.L.

Subjects
Ketoconazole -- Dosage and administration -- Complications and side effects -- Research, Immunosuppressive agents -- Dosage and administration -- Complications and side effects -- Research, Drug interactions -- Research, Health, Complications and side effects, Research, Dosage and administration
Abstract

The authors sought to quantify the influence of the CYP3A and P-glycoprotein inhibitor ketoconazole on the pharmacokinetics of everolimus in healthy subjects. This was a 2-period, single-sequence, crossover study in [...]

Published
2005

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