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Thematische Bibliographien / Testing the factors / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Testing the factors“

Autor: Grafiati

Veröffentlicht am 23. Juni 2021

Zuletzt aktualisiert am 8. Februar 2022

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1

Bertovic, M., M. Gaal, C. Müller und B. Fahlbruch. „Investigating human factors in manual ultrasonic testing: testing the human factors model“. Insight - Non-Destructive Testing and Condition Monitoring 53, Nr. 12 (01.12.2011): 673–76. http://dx.doi.org/10.1784/insi.2011.53.12.673.

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2

Maurissen, Jacques P. J., Brian R. Marable, Amanda K. Andrus und Kenneth E. Stebbins. „Factors affecting grip strength testing“. Neurotoxicology and Teratology 25, Nr. 5 (September 2003): 543–53. http://dx.doi.org/10.1016/s0892-0362(03)00073-4.

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3

Salkovskis, Paul M., und Katharine A. Rimes. „Predictive genetic testing: Psychological factors“. Journal of Psychosomatic Research 43, Nr. 5 (November 1997): 477–87. http://dx.doi.org/10.1016/s0022-3999(97)00170-0.

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4

Kacew, Sam. „Confounding factors in toxicity testing“. Toxicology 160, Nr. 1-3 (März 2001): 87–96. http://dx.doi.org/10.1016/s0300-483x(00)00440-6.

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5

Auckland, D. W., J. M. Cooper und B. R. Varlow. „Factors affecting electrical tree testing“. IEE Proceedings A Science, Measurement and Technology 139, Nr. 1 (1992): 9. http://dx.doi.org/10.1049/ip-a-3.1992.0002.

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6

Bailer, A. John, Sean E. Walker und Kyle J. Venis. „Estimating and testing bioconcentration factors“. Environmental Toxicology and Chemistry 19, Nr. 9 (September 2000): 2338–40. http://dx.doi.org/10.1002/etc.5620190925.

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7

Collins, Megan, Jessica Whitaker, Tina Simpson und Latesha Elopre. „Factors Influencing Genital Herpes Testing“. Journal of Adolescent Health 58, Nr. 2 (Februar 2016): S108. http://dx.doi.org/10.1016/j.jadohealth.2015.10.227.

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8

Schönbrodt, Felix D., Eric-Jan Wagenmakers, Michael Zehetleitner und Marco Perugini. „Sequential hypothesis testing with Bayes factors: Efficiently testing mean differences.“ Psychological Methods 22, Nr. 2 (Juni 2017): 322–39. http://dx.doi.org/10.1037/met0000061.

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9

Menendez, Mariano E., Arjan G. J. Bot, Michiel G. J. S. Hageman, Valentin Neuhaus, Chaitanya S. Mudgal und David Ring. „Computerized Adaptive Testing of Psychological Factors“. Journal of Bone & Joint Surgery 95, Nr. 20 (Oktober 2013): e149. http://dx.doi.org/10.2106/jbjs.l.01614.

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10

Fosten, Jack, und Daniel Gutknecht. „Testing Nowcast Monotonicity with Estimated Factors“. Journal of Business & Economic Statistics 38, Nr. 1 (18.06.2018): 107–23. http://dx.doi.org/10.1080/07350015.2018.1458623.

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11

Clark, Shannon, und P. E. ,. Denise Forkey. „Clinical Actual Use Human Factors Testing“. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 7, Nr. 1 (Juni 2018): 152–54. http://dx.doi.org/10.1177/2327857918071039.

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Due to perceived cost and time savings, medical device and combination product manufacturers frequently consider the option to combine human factors testing with clinical studies. There are some scenarios in which human factors and clinical testing of medical products can be combined to save time and resources. While guidance documents published by the Food and Drug Administration (FDA) emphasize that most human factors validation testing can fully evaluate use-related safety via simulated use usability testing, there are some cases in which clinical actual use usability testing is needed to fully evaluate use-related safety. This paper suggests synergies between clinical testing and human factors testing, presents challenges faced by human factors practitioners when the two types of testing are combined, and offers best practice recommendations to maximize the chance of successfully evaluating the human factors endpoints.

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12

Ahmed, Debra S., Amy M. Karch und Fred E. Karch. „Hidden Factors in Occult Blood Testing“. American Journal of Nursing 100, Nr. 12 (Dezember 2000): 25. http://dx.doi.org/10.1097/00000446-200012000-00034.

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13

Roberts, C. L., C. Morin, D. G. Addiss, S. P. Wahlquist, P. A. Mshar und J. L. Hadler. „Factors influencing Cryptosporidium testing in Connecticut.“ Journal of clinical microbiology 34, Nr. 9 (1996): 2292–93. http://dx.doi.org/10.1128/jcm.34.9.2292-2293.1996.

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14

Tucker, Mary J. „Factors Influencing Carcinogenicity Testing in Rodents“. Human Toxicology 6, Nr. 2 (März 1987): 107–9. http://dx.doi.org/10.1177/096032718700600201.

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15

Bertolino, Francesco, Ludovico Piccinato und Walter Racugno. „Multiple Bayes Factors for Testing Hypotheses“. Journal of the American Statistical Association 90, Nr. 429 (März 1995): 213–19. http://dx.doi.org/10.1080/01621459.1995.10476504.

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16

Marden, John I. „Hypothesis Testing: FrompValues to Bayes Factors“. Journal of the American Statistical Association 95, Nr. 452 (Dezember 2000): 1316–20. http://dx.doi.org/10.1080/01621459.2000.10474339.

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17

Marek, T., und C. Noworol. „Human factors in testing and evaluation“. International Journal of Industrial Ergonomics 3, Nr. 3 (April 1989): 281–83. http://dx.doi.org/10.1016/0169-8141(89)90031-0.

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18

Uysal, Muzaffer, und Claudia Jurowski. „Testing the push and pull factors“. Annals of Tourism Research 21, Nr. 4 (Januar 1994): 844–46. http://dx.doi.org/10.1016/0160-7383(94)90091-4.

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19

Seo, Inseok, und Wonhee Jung. „Testing the effectiveness of competitive value model organizational culture factors on organizational performance“. Korean Public Administration Review 55, Nr. 1 (25.03.2021): 121–60. http://dx.doi.org/10.18333/kpar.55.1.121.

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20

Waters, Susan, Melody Carswell, Eric Stephens und Ada Sue Selwit. „Usability Testing“. Ergonomics in Design: The Quarterly of Human Factors Applications 9, Nr. 2 (April 2001): 15–20. http://dx.doi.org/10.1177/106480460100900206.

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21

Fry, A. T., und E. M. Piedra. „Review of factors affecting steam oxidation testing“. Materials at High Temperatures 28, Nr. 4 (Dezember 2011): 290–96. http://dx.doi.org/10.3184/096034011x13185043039504.

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22

Kasi, Urmika, und Shreyas Prasad. „Hypothesis-Testing Factors Affecting Students’ Academic Performance“. International Journal of Computer Applications 175, Nr. 30 (17.11.2020): 32–36. http://dx.doi.org/10.5120/ijca2020920846.

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23

Spezzaferri, Fulvio, Isabella Verdinelli und Massimo Zeppieri. „Bayes factors for goodness of fit testing“. Journal of Statistical Planning and Inference 137, Nr. 1 (Januar 2007): 43–56. http://dx.doi.org/10.1016/j.jspi.2005.09.002.

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24

Pospíšil, J., J. Pilař, N. C. Billingham, A. Marek, Z. Horák und S. Nešpůrek. „Factors affecting accelerated testing of polymer photostability“. Polymer Degradation and Stability 91, Nr. 3 (März 2006): 417–22. http://dx.doi.org/10.1016/j.polymdegradstab.2005.01.049.

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25

Caccia-Bava, Maria do Carmo, Valerie C. K. Guimaraes und Tor Guimaraes. „Empirically testing some factors affecting HMS usage“. International Journal of Health Care Quality Assurance 29, Nr. 6 (11.07.2016): 628–45. http://dx.doi.org/10.1108/ijhcqa-10-2015-0123.

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Purpose – Without use the expected benefits from healthcare management systems (HMS) cannot be derived. Thus, while use alone may not guarantee success, one can safely assume that the more use the better. HMS has been instrumental in facilitating care providers’ work. However, many hospitals have encountered usage problems and some user-related factors have been recognized in the literature as potentially important to make HMS more successful. The purpose of this paper is to test the importance of the factors proposed in the literature as important determinants of HMS usage measured by the number of hours used and the frequency of use. Design/methodology/approach – Several user-related variables such as user participation, user expertise, and user training previously studied separately by different authors are brought together into an integrated model to be tested empirically. Data from 213 nurses using their hospital HMS have been used to test proposed relationships between the independent variables and HMS usage results. Findings – The results confirm the importance of these factors and provide the basis for managerial recommendations. Hospital managers can use the resources validated by this study to improve their own operations and improve the likelihood of success implementing HMS. Future research projects may identify other possible factors important for HMS implementation success to improve the model proposed here. Originality/value – HMS is a very widely used and an important system for hospitals, but has been neglected in research. This is one of the first rigorous studies of HMS, and the results provide new practical insights for hospital administrators.

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26

Gengenbach, Christian, Franz C. Palm und Jean-Pierre Urbain. „Cointegration Testing in Panels with Common Factors*“. Oxford Bulletin of Economics and Statistics 68 (23.11.2006): 683–719. http://dx.doi.org/10.1111/j.1468-0084.2006.00452.x.

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27

DICKENS, C. J., J. J. McAUGHEY, D. A. KNIGHT und S. T. BAKER. „Factors Affecting In Vitro Testing of Inhalers“. Journal of Aerosol Medicine 7, Nr. 2 (Januar 1994): 193–96. http://dx.doi.org/10.1089/jam.1994.7.193.

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28

Hnatek, Eugene R. „Factors involved in electrically testing vlsi circuits“. Quality and Reliability Engineering International 2, Nr. 2 (April 1986): 81–100. http://dx.doi.org/10.1002/qre.4680020204.

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29

Duffy, Vincent G. „Handbook of Human Factors Testing and Evaluation“. Human Factors and Ergonomics in Manufacturing 8, Nr. 4 (1998): 369–70. http://dx.doi.org/10.1002/(sici)1520-6564(199823)8:4<369::aid-hfm7>3.0.co;2-1.

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30

Berger, J. O., und J. Mortera. „Default Bayes Factors for Nonnested Hypothesis Testing“. Journal of the American Statistical Association 94, Nr. 446 (Juni 1999): 542–54. http://dx.doi.org/10.1080/01621459.1999.10474149.

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31

He, Shui Ming. „Several Related Factors on Highway Nondestructive Testing“. Advanced Materials Research 594-597 (November 2012): 1363–66. http://dx.doi.org/10.4028/www.scientific.net/amr.594-597.1363.

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Highway engineering quality is the lifeline of highway. Ground-penetrating radar is a new nondestructive testing technology of the road quality detection. This thesis takes advantage of ground-penetrating radar to analyze and discuss several related factors on highway nondestructive testing, for instance, the water content and compact degree of the base course, identification of cavity beneath the rigid pavement, and the differential settlement of the base course beneath the flexible pavement. Results of this research provide an excellent detection method for engineers and technicians.

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32

Robert, Christian P., und Nathalie Caron. „Noninformative Bayesian testing and neutral Bayes factors“. Test 5, Nr. 2 (Dezember 1996): 411–37. http://dx.doi.org/10.1007/bf02562626.

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33

Tintinger, Jonathan, und Lawrence Simkins. „Mandatory Aids Testing: Factors Influencing Public Opinion“. Psychological Reports 65, Nr. 3 (Dezember 1989): 835–43. http://dx.doi.org/10.2466/pr0.1989.65.3.835.

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A survey of 341 persons, 82% of whom were university students whose median age was 27.0 yr., was conducted to investigate the relationship between their attitudes regarding mandatory AIDS testing for various groups, attitudes toward the disease, sexual orientation and behavior, and attitudes toward homosexuals. Homosexual and bisexual respondents were less supportive of mandatory testing for anyone than were heterosexual respondents. Greater homophobia and attitudes in favor of legal sanctions against persons with AIDS were correlated for heterosexual respondents, with attitudes supporting mandatory testing for everyone and homosexuals in particular. However, concern about contracting AIDS was unrelated to heterosexual attitudes favoring mandatory testing. Social and political considerations in an era of growing and potentially militant public health concern are discussed.

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34

Kudriashova, A. V., I. Yu Sosnovskyi, N. M. Nadybska und O. V. Seraphym. „Research of quality factors of software testing“. Scientific Papers (Ukrainian Academy of Printing) 2, Nr. 61 (2020): 11–18. http://dx.doi.org/10.32403/1998-6912-2020-2-61-11-18.

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35

Hammami, Yacine, und Faouzi Jilani. „Testing Factor Pricing Models in Tunisia: Macroeconomic Factors vs. Fundamental Factors“. Review of Middle East Economics and Finance 7, Nr. 2 (29.01.2011): 1–22. http://dx.doi.org/10.2202/1475-3693.1334.

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36

Creel, Alisha H., und Rajiv N. Rimal. „Factors related to HIV-testing behavior and interest in testing in Namibia“. AIDS Care 23, Nr. 7 (09.03.2011): 901–7. http://dx.doi.org/10.1080/09540121.2010.540227.

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37

Kumar, Anil R., Kevin Cluff und Tim McLeroy. „Is Remote Human Factors Testing an Acceptable Approach for Human Factors Validation“. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 10, Nr. 1 (Juni 2021): 152–56. http://dx.doi.org/10.1177/2327857921101083.

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Human factors (HF) validation of medical devices is vital for approval of use by the Food and Drug Administration (FDA). Historically, validation testing of medical devices has taken place within laboratory-controlled environments where conditions are controlled, and testing is executed in accordance with similar circumstance. Due to the COVID-19 pandemic, laboratory research has decreased in a wide range of disciplines or in instances continued with masks and many other COVID mitigations. As a result, medical device manufacturers who need to provide human factors validation to receive U.S. Food and Drug Administration (FDA) approval were impacted. Remote usability testing, while a fairly new phenomenon for physical devices, affords the ability to functionally test a product within naturalistic environments that are indistinguishable from the settings in which they would be used (e.g. the user’s home). However, published literature to support whether remote HF testing could potentially be an acceptable approach is rare. The objective of this study is to replicate the objectives and structure of an original in-person study, which was conducted using migraine patients who performed one unaided simulated injection using a 2-step autoinjector. The original methodology has been modified to adapt to the remote testing. This paper reports the procedures that has been developed for this ongoing endeavor.

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38

Dunlap, William P., und Robert S. Kennedy. „Testing for Statistical Power“. Ergonomics in Design: The Quarterly of Human Factors Applications 3, Nr. 3 (Juli 1995): 6–31. http://dx.doi.org/10.1177/106480469500300303.

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39

Mitchell, Jason W., und Andrew E. Petroll. „HIV Testing Rates and Factors Associated With Recent HIV Testing Among Male Couples“. Sexually Transmitted Diseases 39, Nr. 5 (Mai 2012): 379–81. http://dx.doi.org/10.1097/olq.0b013e3182479108.

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40

Iddrisu, Abdul-Karim, Kwaku Opoku-Ameyaw, Francis Kwame Bukari, Bashiru Mahama und Jerry John Amaasende Akooti. „HIV Testing Decision and Determining Factors in Ghana“. World Journal of AIDS 09, Nr. 02 (2019): 85–104. http://dx.doi.org/10.4236/wja.2019.92007.

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41

Nall, Allison, Tiffany Chenneville, Lindsey M. Rodriguez und Jennifer L. O’Brien. „Factors Affecting HIV Testing among Youth in Kenya“. International Journal of Environmental Research and Public Health 16, Nr. 8 (24.04.2019): 1450. http://dx.doi.org/10.3390/ijerph16081450.

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With the high prevalence of HIV among youth in sub-Saharan Africa, it is vital to better understand factors affecting HIV testing among this population; this is the first step in the HIV treatment cascade. The purpose of this study was to examine factors related to behavioral intentions regarding HIV testing using existing pre-test data from the HIV SEERs (Stigma-reduction via Education, Empowerment, and Research) Project, a community-based participatory research program targeting 13–24-year-olds in Kenya. It was hypothesized that HIV knowledge, social support, subjective well-being, and mental health (depression, anxiety, and stress) would serve as facilitators to HIV testing while projected stigma and substance use would serve as barriers to HIV testing. In partial support of our hypotheses, findings from logistic regression analyses revealed that HIV knowledge, substance use, depression, and social support were significant predictors of HIV testing intentions. However, HIV knowledge and substance use served as facilitators while depression and social support served as barriers. While projected stigma was correlated with HIV testing intentions, it was not a significant predictor in the regression analysis. Subjective well-being, anxiety, and stress were not significant predictors in the regression analysis. These findings have important implications for HIV testing initiatives designed for youth in Kenya as well as future research on HIV testing with this population.

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42

Marden, John I. „Hypothesis Testing: From p Values to Bayes Factors“. Journal of the American Statistical Association 95, Nr. 452 (Dezember 2000): 1316. http://dx.doi.org/10.2307/2669779.

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43

Okada, Y. „Human Factors at flaw-sizing by ultrasonic testing“. Japanese journal of ergonomics 30, Supplement (1994): 330–31. http://dx.doi.org/10.5100/jje.30.supplement_330.

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44

Ahmed, Debra S., Amy M. Karch und Fred E. Karch. „Practice Errors: Hidden Factors in Occult Blood Testing“. American Journal of Nursing 100, Nr. 12 (Dezember 2000): 25. http://dx.doi.org/10.2307/3522185.

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45

Kedzia, Boleslaw, Danuta Pieczyrak, Grazyna Tondel und Willis C. Maples. „Factors affecting the clinical testing of accommodative facility“. Ophthalmic and Physiological Optics 19, Nr. 1 (Januar 1999): 12–21. http://dx.doi.org/10.1046/j.1475-1313.1999.00396.x.

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46

Duffy, Vincent G. „Human factors in system design, development and testing“. Human Factors and Ergonomics in Manufacturing 12, Nr. 1 (06.12.2001): 123–24. http://dx.doi.org/10.1002/hfm.10012.

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47

Kepka, Deanna, Nancy Breen, Jessica B. King, Helen I. Meissner, Katherine B. Roland, Vicki B. Benard und Mona Saraiya. „Demographic Factors Associated with Overuse of Pap Testing“. American Journal of Preventive Medicine 47, Nr. 5 (November 2014): 629–33. http://dx.doi.org/10.1016/j.amepre.2014.07.034.

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48

Bailey, F. Lee. „Legal Factors Surrounding Drug Testing in the Workplace“. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy 7, Nr. 3 (06.05.1987): 58–60. http://dx.doi.org/10.1002/j.1875-9114.1987.tb03518.x.

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49

Martins, Alexandra, Catarina Chaves, Maria Cristina Canavarro und Marco Pereira. „WHAT PSYCHOSOCIAL FACTORS ARE ASSOCIATED WITH HIV TESTING?“ Psicologia, Saúde & Doença 19, Nr. 1 (29.03.2018): 03–10. http://dx.doi.org/10.15309/18psd190102.

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50

Evans, C. W., und T. R. Manley. „Factors affecting the impulse testing of hydraulic hose“. Polymer Testing 6, Nr. 2 (1986): 135–49. http://dx.doi.org/10.1016/0142-9418(86)90012-7.

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