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Journal articles on the topic 'Multiple response analysis'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Edwards, Yancy D., and Greg M. Allenby. "Multivariate Analysis of Multiple Response Data." Journal of Marketing Research 40, no. 3 (August 2003): 321–34. http://dx.doi.org/10.1509/jmkr.40.3.321.19233.

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Multiple response questions, also known as a pick any/J format, are frequently encountered in the analysis of survey data. The relationship among the responses is difficult to explore when the number of response options, J, is large. The authors propose a multivariate binomial probit model for analyzing multiple response data and use standard multivariate analysis techniques to conduct exploratory analysis on the latent multivariate normal distribution. A challenge of estimating the probit model is addressing identifying restrictions that lead to the covariance matrix specified with unit-diagonal elements (i.e., a correlation matrix). The authors propose a general approach to handling identifying restrictions and develop specific algorithms for the multivariate binomial probit model. The estimation algorithm is efficient and can easily accommodate many response options that are frequently encountered in the analysis of marketing data. The authors illustrate multivariate analysis of multiple response data in three applications.

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2

Ruzicka, Gene C., and Thomas L. Geers. "Transient response analysis of multiple submerged structures." Finite Elements in Analysis and Design 6, no. 2 (December 1989): 153–72. http://dx.doi.org/10.1016/0168-874x(89)90041-3.

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3

Li, Liang, and Xuesong Chu. "Multiple response surfaces for slope reliability analysis." International Journal for Numerical and Analytical Methods in Geomechanics 39, no. 2 (May 15, 2014): 175–92. http://dx.doi.org/10.1002/nag.2304.

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4

Gutiérrez, Ester, and Sebastián Lozano. "Data Envelopment Analysis of multiple response experiments." Applied Mathematical Modelling 34, no. 5 (May 2010): 1139–48. http://dx.doi.org/10.1016/j.apm.2009.08.001.

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5

Berry, Kenneth J., and Paul W. Mielke. "Longitudinal Analysis of Data with Multiple Binary Category Choices." Psychological Reports 93, no. 1 (August 2003): 127–31. http://dx.doi.org/10.2466/pr0.2003.93.1.127.

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In many experiments, subjects mark all categories that apply when responding to a cafeteria or multiple-response question. One exact and two approximate permutation methods are described to analyze binary answers to multiple-response questions in longitudinal experimental designs, wherein the same or matched subjects respond to the same multiple-response question over two or more trials. The described methods provide probabilities, under the null hypothesis, that the multiple binary responses do not differ over trials.

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Berry, Kenneth J., and P. W. Mielke. "Permutation Analysis of Data with Multiple Binary Category Choices." Psychological Reports 92, no. 1 (February 2003): 91–98. http://dx.doi.org/10.2466/pr0.2003.92.1.91.

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In many studies, respondents may mark all answers that apply when responding to a multiple-choice question, i.e., a cafeteria or multiple-response question. One exact and two approximate permutation methods are described to analyze multiple-response questions. The methods provide the probability, under the null hypothesis, that the multiple binary responses do not differ among specified groups.

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7

Lehmacher, Walter, Meinhard Kieser, and Ludwig Hothorn. "Sequential and Multiple Testing for Dose-Response Analysis." Drug Information Journal 34, no. 2 (April 2000): 591–97. http://dx.doi.org/10.1177/009286150003400227.

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8

Tomić, J. J., P. D. Poljak, and M. D. Kušljević. "Frequency‐response‐controlled multiple‐resonator‐based harmonic analysis." Electronics Letters 54, no. 4 (February 2018): 202–4. http://dx.doi.org/10.1049/el.2017.4180.

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9

Bonfa, E., R. Llovet, and K. Elkon. "Immunoblot analysis of IgG subclasses of multiple lupus autoantibodies." Journal of Immunology 140, no. 7 (April 1, 1988): 2231–36. http://dx.doi.org/10.4049/jimmunol.140.7.2231.

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Abstract Sera from 35 patients with systemic lupus erythematosus were analyzed for the subclass distribution of IgG autoantibodies to saline-soluble intracellular proteins. To assess the response to all Ag, an immunoblot technique was used, and strips were sequentially probed with patient sera, monoclonal anti-subclass sera, and a labeled anti-mouse reagent. The relative proportions of each subclass reactive with a specific Ag was determined semi-quantitatively by densitometric scanning. Overall, all of the IgG subclasses were involved in the autoantibody response, although the frequency of detection was highest for IgG1 and lowest for IgG4. When the subclass responses to different Ag were compared, IgG1 was the major subclass reactive with the Ro, La, and U1 ribonucleoprotein Ag, whereas IgG1 and IgG2 were almost equally represented in the responses to the Sm BB' and D Ag as well as to the ribosomal P proteins. Individual patient sera frequently showed discordance between the dominant subclass reactive against apparently unrelated proteins and even against proteins within the same antigenic particle (e.g., the Sm BB' and D proteins). These observations indicate that there are two major patterns of subclass response to the common lupus autoantigens but that considerable variation between patients and even within the same patient (to different Ag) occurs.

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10

Ko, Sungbae. "Multiple-response sequences in classroom talk." Australian Review of Applied Linguistics 32, no. 1 (January 1, 2009): 4.1–4.18. http://dx.doi.org/10.2104/aral0904.

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This paper examines multiple-response sequences (MRSs), occurring in adult Korean TESOL classrooms, to show the responses produced by students in the language classroom are not always confined within the boundaries of a single response, but are likely to be seen as mutually orienting to, and collaborating to produce a comprehensible outcome to the sequence. To analyse and consider what types of multiple response (MR) can be identified, and how the different types occur within those MRSs, this study adopts Conversation Analysis principles. By using conversation analytic perspectives, this study identifies four major types of MR (identical, complementary, collaborative and competitive).

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Ko, Sungbae. "Multiple-response sequences in classroom talk." Australian Review of Applied Linguistics 32, no. 1 (2009): 4.1–4.18. http://dx.doi.org/10.1075/aral.32.1.02ko.

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This paper examines multiple-response sequences (MRSs), occurring in adult Korean TESOL classrooms, to show the responses produced by students in the language classroom are not always confined within the boundaries of a single response, but are likely to be seen as mutually orienting to, and collaborating to produce a comprehensible outcome to the sequence. To analyse and consider what types of multiple response (MR) can be identified, and how the different types occur within those MRSs, this study adopts Conversation Analysis principles. By using conversation analytic perspectives, this study identifies four major types of MR (identical, complementary, collaborative and competitive).

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12

Xiao, Dongmei, and Shigui Ruan. "Multiple Bifurcations in a Delayed Predator–Prey System with Nonmonotonic Functional Response." Journal of Differential Equations 176, no. 2 (November 2001): 494–510. http://dx.doi.org/10.1006/jdeq.2000.3982.

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13

Zhang, S., J. Hu, and C. H. Gao. "Response surface analysis for principal component of multiple variables - a method to select the optimal conditions for seed treatments." Seed Science and Technology 33, no. 3 (October 1, 2005): 699–703. http://dx.doi.org/10.15258/sst.2005.33.3.17.

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14

Yoo, Chul-Sang, Ha-Young Kim, and Joo-Young Park. "Analysis of Runoff Characteristics Using Multiple Impulse Response Functions." Journal of Korea Water Resources Association 43, no. 6 (June 30, 2010): 571–81. http://dx.doi.org/10.3741/jkwra.2010.43.6.571.

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15

Kusljevic, Miodrag D., Josif J. Tomic, and Predrag D. Poljak. "Maximally Flat-Frequency-Response Multiple-Resonator-Based Harmonic Analysis." IEEE Transactions on Instrumentation and Measurement 66, no. 12 (December 2017): 3387–98. http://dx.doi.org/10.1109/tim.2017.2751799.

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16

Jann, Ben. "Tabulation of Multiple Responses." Stata Journal: Promoting communications on statistics and Stata 5, no. 1 (February 2005): 92–122. http://dx.doi.org/10.1177/1536867x0500500113.

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Although multiple-response questions are quite common in survey research, Stata's official release does not provide much capability for an effective analysis of multiple-response variables. For example, in a study on drug addiction an interview question might be, “Which substances did you consume during the last four weeks?” The respondents just list all the drugs they took, if any; e.g., an answer could be “cannabis, cocaine, heroin” or “ecstasy, cannabis” or “none”, etc. Usually, the responses to such questions are stored as a set of variables and, therefore, cannot be easily tabulated. I will address this issue here and present a new module to compute one- and two-way tables of multiple responses. The module supports several types of data structure, provides significance tests, and offers various options to control the computation and display of the results. In addition, tools to create graphs of multiple-response distributions are presented.

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17

Sevin, Bart M., Charles S. Gulotta, Barbara J. Sierp, Leigh A. Rosica, and Lorionna J. Miller. "ANALYSIS OF RESPONSE COVARIATION AMONG MULTIPLE TOPOGRAPHIES OF FOOD REFUSAL." Journal of Applied Behavior Analysis 35, no. 1 (March 2002): 65–68. http://dx.doi.org/10.1901/jaba.2002.35-65.

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18

Lee, Do-Hyung, Jong-Su Jeon, and Tae-Hyo Park. "Response Analysis of RC Bridge Piers due In Multiple Earthquakes." Journal of the Korea Concrete Institute 16, no. 3 (June 1, 2004): 357–67. http://dx.doi.org/10.4334/jkci.2004.16.3.357.

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19

Walters, Frederick H. "Statistical Analysis of Multivariate Multiple Wavelength Liquid Chromatographic Response Data." Analytical Letters 22, no. 3 (March 1989): 635–45. http://dx.doi.org/10.1080/00032718908051354.

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20

Han, Karen E., Paul J. Catalano, Pralay Senchaudhuri, and Cyrus Mehta. "Exact Analysis of Dose Response for Multiple Correlated Binary Outcomes." Biometrics 60, no. 1 (March 2004): 216–24. http://dx.doi.org/10.1111/j.0006-341x.2004.00152.x.

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21

Smith, T. H., B. E. Goodlin, D. S. Boning, and H. H. Sawin. "A statistical analysis of single and multiple response surface modeling." IEEE Transactions on Semiconductor Manufacturing 12, no. 4 (1999): 419–30. http://dx.doi.org/10.1109/66.806119.

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22

Harrison, R. F., and J. K. Hammond. "Analysis of the Nonstationary Response of Vehicles With Multiple Wheels." Journal of Dynamic Systems, Measurement, and Control 108, no. 1 (March 1, 1986): 69–73. http://dx.doi.org/10.1115/1.3143745.

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Vehicles moving on rough surfaces are subject to inputs which are often conveniently regarded as random processes. In general, the excitation process is “perceived” by the vehicle as a nonstationary random process either due to inhomogeneity in the ground profile or variations in the vehicle’s velocity, or both, Hitherto this second case has not been tractable analytically due to the time variable delay between inputs. In this paper this difficulty is overcome and expressions are derived for the propagation of the mean vector and zero-lag autocovariance matrix. An example of a vehicle modelled by a bicycle configuration is discussed.

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23

Merchant, Aparna, Melinda McCann, and Don Edwards. "Improved Multiple Comparisons With a Control in Response Surface Analysis." Technometrics 40, no. 4 (November 1998): 297–303. http://dx.doi.org/10.1080/00401706.1998.10485558.

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24

Lee, Soo-Hyoung, Se-Yeong Hamm, Kyoochul Ha, Kyung-Seok Ko, and Jae-Yeol Cheong. "Groundwater response analysis to multiple earthquakes on Jeju volcanic island." Geosciences Journal 16, no. 4 (December 2012): 469–78. http://dx.doi.org/10.1007/s12303-012-0033-4.

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25

Hyun, C. H., C. B. Yun, and D. G. Lee. "Nonstationary response analysis of suspension bridges for multiple support excitations." Probabilistic Engineering Mechanics 7, no. 1 (January 1992): 27–35. http://dx.doi.org/10.1016/0266-8920(92)90006-4.

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26

Stewart, TJ. "Data envelopment analysis and multiple criteria decision making: A response." Omega 22, no. 2 (March 1994): 205–6. http://dx.doi.org/10.1016/0305-0483(94)90079-5.

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27

Konagai, Kazuo, and Toyoaki Nogami. "Subgrade model for transient response analysis of multiple embedded bodies." Earthquake Engineering & Structural Dynamics 23, no. 10 (October 1994): 1097–114. http://dx.doi.org/10.1002/eqe.4290231005.

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28

Wang, Ziqi, and Armen Der Kiureghian. "Multiple-support response spectrum analysis using load-dependent Ritz vectors." Earthquake Engineering & Structural Dynamics 43, no. 15 (July 3, 2014): 2283–97. http://dx.doi.org/10.1002/eqe.2447.

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29

MATSUDA, Tomoyuki, and Akira SONE. "G1000802 Response Analysis of Multiple Supported Elastic-Plastic Piping Systems for Its Maximum Response." Proceedings of Mechanical Engineering Congress, Japan 2015 (2015): _G1000802——_G1000802—. http://dx.doi.org/10.1299/jsmemecj.2015._g1000802-.

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30

Khiem, N. T., and P. T. Hang. "Spectral analysis of multiple cracked beam subjected to moving load." Vietnam Journal of Mechanics 36, no. 4 (November 27, 2014): 245–54. http://dx.doi.org/10.15625/0866-7136/36/4/3369.

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In present paper, the spectral approach is proposed for analysis of multiple cracked beam subjected to general moving load that allows us to obtain explicitly dynamic response of the beam in frequency domain. The obtained frequency response is straightforward to calculate time history response by using the FFT algorithm and provides a novel tool to investigate effect of position and depth of multiple cracks on the dynamic response. The analysis is important to develop the spectral method for identification of multiple cracked beam by using its response to moving load. The theoretical development is illustrated and validated by numerical case study.

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31

Casneuf, Tineke, Andrew Lysaght, Clare LeFave, Jaime Bald, Brendan Weiss, Niels W. C. J. van de Donk, Henk M. Lokhorst, Tahamtan Ahmadi, and A. Kate Sasser. "Serum Proteomic Analysis of Multiple Myeloma Subjects Treated with Daratumumab Monotherapy." Blood 126, no. 23 (December 3, 2015): 1837. http://dx.doi.org/10.1182/blood.v126.23.1837.1837.

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Abstract Introduction: Daratumumab (DARA) is a human IgG1κ monoclonal antibody that binds with high affinity to a unique epitope on CD38. DARA monotherapy has shown promising activity in relapsed and/or refractory multiple myeloma (MM) patients with a median of 5 prior lines of therapy in two clinical studies (Study GEN501; Lokhorst HM. J Clin Oncol. 2014;32 Suppl:abstr 8513 and Study MMY2002; Lonial S. J Clin Oncol. 2015;33 Suppl:abstr LBA8512). The aim of this analysis was to identify proteins indicative of DARA's multiple mechanisms of action (MOA) and potential predictive pharmacodynamic response markers. A broad aptamer based proteomics platform (SomaSCANTM) evaluated clinical serum samples at study entry and during treatment to determine proteins and biological pathways associated with DARA MOA or clinical response. Methods: All patients were treated with 16 mg/kg DARA and whole blood samples were collected at baseline and after 8 weeks of treatment. Blood samples were processed for serum and stored frozen until batch analysis. Profiling of 1129 serum proteins was performed using the SOMAscan assay. Patients were classified based on overall best response: responders (stringent and complete responses, very good partial and partial responses), stable disease (stable disease or minimal response) and non-responders (progressive disease). Differential level testing included application of the Wilcoxon rank sum test and Limma for responder versus non-responder analysis, and ANOVA for repeated-measures with post-hoc test validation, Wilcoxon signed rank and Friedman tests for baseline versus on-treatment analysis. Results: In MMY2002 at baseline, 51 proteins were significantly different between responders and non-responders. Many have known associations with MM or CD38, and interestingly a subset is associated with T-cell biology. We recently observed that DARA induces a multi-factorial T-cell response in patients including CD8+ T-cell expansion and activation, and increased clonality. Proteins differentially expressed between responders/non-responders at baseline included tumor necrosis factor subfamily 8 (TNFSF8/CD30L), TNFSF9/CD137L, macrophage stimulating 1 (MST1), interleukin-1B (IL1B), cadherin 1 (CDH1) and cadherin 3 (CDH3). Protein profiles were evaluated at baseline and at 8 weeks (Cycle 3 Day 1) to study pharmacodynamic changes. Significant treatment-induced changes were identified in 142 proteins. Of particular interest were the 60 proteins that changed differentially over time in responders vs non-responders. Proteins associated with MM tumor load, such as beta-2-microglobulin [B2M], and immunoglobulins decreased in responders and increased in non-responders. Novel MM therapeutic targets such as signaling lymphocyte activation molecule F7 [SLAMF7] (i.e. CS1) and B-cell maturation antigen [BCMA] decreased in responders and increased in non-responders during DARA treatment. Many proteins associated with immune or T-cell response were also significantly changed by DARA treatment, including TNFRSF1B, CD163, TNFRSF25, TLR2, CCL5, IL5RA, FCGR2A, ICOS, Granzyme B, and programmed cell death ligand 1 [PD-L1] many of which were differential between responders and non-responders. Differential level testing of GEN501 samples identified a small set of proteins that were significantly altered by DARA treatment over time. Many of these proteins overlapped with those identified in the MMY2002 analysis, increasing confidence in the statistical results. Conclusions: This exploratory serum proteomic analysis identified proteins that were differentially expressed between responders and non-responders at baseline, including proteins associated with immune response and T-cell biology (TNFSF8/CD30L, TNFSF9/CD137L, IL1B). In addition, significant differential changes in protein expression between responders and non-responders after DARA treatment were seen. Many of these are associated with MM tumor load (BCMA, immunoglobulins, SLAMF7, and B2M) and decreased in responders and increased in non-responders. In addition, proteins related to T-cell activity, immune checkpoints and immune response (TNFRSF1B, CD163, TNFRSF25, TLR2, CCL5, IL5RA, FCGR2A, ICOS, Granzyme B, PD-L1) also showed changes associated with DARA treatment, supporting the recent findings that DARA induces a T-cell response in MM patients that may contribute to clinical response. Disclosures Casneuf: Janssen: Employment. Lysaght:Immuneering Corp: Employment, Other: Stockholder. LeFave:Immuneering Corp.: Employment. Bald:Janssen: Employment. Weiss:Janssen and Millennium: Consultancy; Janssen and Onclave: Research Funding. van de Donk:Janssen Pharmaceuticals: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Lokhorst:Amgen: Honoraria; Janssen: Honoraria, Research Funding; Genmab: Honoraria, Research Funding. Ahmadi:Janssen: Employment.

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32

Wang, Hui Wen, Zai Lin Yang, and Hua Nan Xu. "Dynamic Stress Concentration Analysis of Multiple Circular Cavities near Multiple Semi-Cylindrical Alluvial Valleys." Applied Mechanics and Materials 121-126 (October 2011): 3253–57. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.3253.

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The problem of dynamic response of multiple circular cavities near multiple semi-cylindrical alluvial valleys under incident plane SH-waves is investigated by the methods of complex function and multi-polar coordinates in this paper. Firstly, the solution domain is divided into two parts, Domain I is multiple semi-cylindrical alluvial valleys, and Domain Ⅱ is an elastic half space with several subsurface circular cavities near multiple semi-cylindrical alluvial valleys. A series of infinite algebraic equations is then obtained based on the displacement and stress continuity condition on “common boundary” of two parts after constructing the associated displacement and stresses expressions of each part. Finally some numerical expamples are prensented and dynamic response of subsurface circular cavities near semi-cylindrical alluvial valleys with respect to different parameters is discussed.

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33

Corral-De-Witt, Danilo, Enrique Carrera, Sergio Muñoz-Romero, Kemal Tepe, and José Rojo-Álvarez. "Multiple Correspondence Analysis of Emergencies Attended by Integrated Security Services." Applied Sciences 9, no. 7 (April 3, 2019): 1396. http://dx.doi.org/10.3390/app9071396.

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A public safety answering point (PSAP) receives thousands of security alerts and attends a similar number of emergencies every day, and all the information related to those events is saved to be post-processed and scrutinized. Visualization and interpretation of emergency data can provide fundamental feedback to the first-response institutions, to managers planning resource distributions, and to all the instances participating in the emergency-response cycle. This paper develops the application of multiple correspondence analysis (MCA) of emergency responses in a PSAP, with the objective of finding informative relationships among the different categories of registered and attended events. We propose a simple yet statistically meaningful method to scrutinize the variety of events and recorded information in conventional PSAPs. For this purpose, MCA is made on the categorical features of the available report forms, and a statistical description is achieved from it by combining bootstrap resampling and Parzen windowing, in order to provide the user with the most relevant factors, their significance, and a meaningful representation of the event grouping trends in a given database. We analyzed the case of the 911-emergency database from Quito, Ecuador, which includes 1,078,846 events during 2014. Individual analysis of the first-response institutions showed that there are groups with very related categories, whereas their joint analysis showed significant relationships among several types of events. This was the case for fire brigades, military, and municipal services attending large-scale forest fires, where they work in a combined way. Independence could be established among actions in other categories, which was the case for specific police events (as drug selling and distribution) or fire brigades events (as fire threats). We also showed that a very low number of factors can be enough to accurately represent the dynamics of frequent events.

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34

Lauer, Georg M., Kei Ouchi, Raymond T. Chung, Tam N. Nguyen, Cheryl L. Day, Deborah R. Purkis, Markus Reiser, et al. "Comprehensive Analysis of CD8+-T-Cell Responses against Hepatitis C Virus Reveals Multiple Unpredicted Specificities." Journal of Virology 76, no. 12 (June 15, 2002): 6104–13. http://dx.doi.org/10.1128/jvi.76.12.6104-6113.2002.

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ABSTRACT The hepatitis C virus (HCV)-specific CD8+-T-cell response is thought to play a critical role in HCV infection. Studies of these responses have largely relied on the analysis of a small number of previously described or predicted HCV epitopes, mostly restricted by HLA A2. In order to determine the actual breadth and magnitude of CD8+-T-cell responses in the context of diverse HLA class I alleles, we performed a comprehensive analysis of responses to all expressed HCV proteins. By using a panel of 301 overlapping peptides, we analyzed peripheral blood mononuclear cells (PBMC) from a cohort of 14 anti-HCV-positive, HLA A2-positive individuals in an enzyme-linked immunospot assay. Only four subjects had detectable HLA A2-restricted responses in PBMC, and only 3 of 19 predicted A2 epitopes were targeted, all of which were confirmed by tetramer analysis. In contrast, 9 of 14 persons showed responses with more comprehensive analyses, with many responses directed against previously unreported epitopes. These results indicate that circulating HCV-specific CD8+-T-cell responses can be detected in PBMC in the majority of infected persons and that these responses are heterogeneous with no immunodominant epitopes consistently recognized. Since responses to epitopes restricted by single HLA alleles such as HLA A2 do not predict the overall response in an individual, more comprehensive approaches, as shown here, should facilitate definition of the role of the CD8+-T-cell response in HCV infection. Moreover, the low level or absence of responses to many predicted epitopes provides a rationale for immunotherapeutic interventions to broaden cytotoxic-T-lymphocyte recognition.

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35

Kusljevic, Miodrag D., Josif J. Tomic, and Predrag D. Poljak. "Erratum to “Maximally Flat-Frequency-Response Multiple-Resonator-Based Harmonic Analysis”." IEEE Transactions on Instrumentation and Measurement 70 (2021): 1. http://dx.doi.org/10.1109/tim.2021.3062103.

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36

FUKUYAMA, Takako, Yoshinobu AKIYAMA, Toshihiko TAKAHASHI, Kazuhiro IIDA, and Nobuyuki IWAMAE. "APPLICATION OF DYNAMIC RESPONSE ANALYSIS FOR MULTIPLE BODIES TO EXECUTION PLANNING." Journal of Japan Society of Civil Engineers, Ser. B3 (Ocean Engineering) 71, no. 2 (2015): I_239—I_244. http://dx.doi.org/10.2208/jscejoe.71.i_239.

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37

Takane, Yoshio. "An Item Response Model for Multidimensional Analysis of Multiple-Choice Data." Behaviormetrika 23, no. 2 (July 1996): 153–67. http://dx.doi.org/10.2333/bhmk.23.153.

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38

Sun, Jian Mei, and Hao Cui. "The Seismic Response Analysis of the Jacket under Multiple Support Excitation." Applied Mechanics and Materials 295-298 (February 2013): 2021–25. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.2021.

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The effect of incoherency of seismic waves and wave travel on the displacement and force response of jacket structure are investigated from the maximum force, reaction force, the displacement, and so on. The conclusions illustrate it is necessary to consider the effect of multiple support excitation. The research of the differences of seismic response under multiple support excitation from uniform excitation presents the theoretical foundation on aseismatic projects for long span space structures such as jacket.

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39

Fishtik, Ilie, István Nagypál, and Ivan Gutman. "Sensitivity analysis of multiple chemical equilibria: Sensitivity coefficients and response equilibria." Journal of Chemical Physics 103, no. 17 (November 1995): 7545–55. http://dx.doi.org/10.1063/1.470271.

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40

Zhang, Jie, Hao Zhang, Lan Zhang, and Zheng Liang. "Buckling Response Analysis of Buried Steel Pipe under Multiple Explosive Loadings." Journal of Pipeline Systems Engineering and Practice 11, no. 2 (May 2020): 04020010. http://dx.doi.org/10.1061/(asce)ps.1949-1204.0000431.

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Kułakowska, Alina, Barbara Mroczko, Maria Mantur, Natalia Lelental, Joanna Tarasiuk, Katarzyna Kapica-Topczewska, Ute Schulz, et al. "Multiplexing analysis of the polyspecific intrathecal immune response in multiple sclerosis." Methods 56, no. 4 (April 2012): 528–31. http://dx.doi.org/10.1016/j.ymeth.2012.03.002.

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42

Hibbert, D. Brynn, Peter W. Alexander, Sri Rachmawati, and Sylvia A. Caruana. "Multiple sensor response in segmented flow analysis with ion-selective electrodes." Analytical Chemistry 62, no. 10 (May 15, 1990): 1015–19. http://dx.doi.org/10.1021/ac00209a010.

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Ferron, John, and Peggy K. Jones. "Tests for the Visual Analysis of Response-Guided Multiple-Baseline Data." Journal of Experimental Education 75, no. 1 (October 1, 2006): 66–81. http://dx.doi.org/10.3200/jexe.75.1.66-81.

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44

Tsuchikawa, Kazumasa, Akira Sone, Arata Masuda, and Daisuke Iba. "C07 Seismic Response Analysis of Piping System to Multiple Support Excitations." Proceedings of the Symposium on the Motion and Vibration Control 2009.11 (2009): 142–47. http://dx.doi.org/10.1299/jsmemovic.2009.11.142.

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Friedman, Linda Weiser. "The analysis of multiple response simulation output data: Experiments of comparison." Computers & Operations Research 13, no. 6 (January 1986): 647–52. http://dx.doi.org/10.1016/0305-0548(86)90071-7.

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Loh, Chin-Hsiung, and Bao-Ding Ku. "An efficient analysis of structural response for multiple-support seismic excitations." Engineering Structures 17, no. 1 (January 1995): 15–26. http://dx.doi.org/10.1016/0141-0296(95)91037-2.

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Ciocanel, Maria-Veronica, Steffen S. Docken, Rebecca E. Gasper, Caron Dean, Brian E. Carlson, and Mette S. Olufsen. "Cardiovascular regulation in response to multiple hemorrhages: analysis and parameter estimation." Biological Cybernetics 113, no. 1-2 (September 12, 2018): 105–20. http://dx.doi.org/10.1007/s00422-018-0781-y.

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Yamamura, Nobumichi, and Hiroshi Tanaka. "Response analysis of flexible MDF systems for multiple-support seismic excitations." Earthquake Engineering & Structural Dynamics 19, no. 3 (1990): 345–57. http://dx.doi.org/10.1002/eqe.4290190305.

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Muralidharan, Kumar Kandadi, Deb Steiner, Diogo Amarante, Pei-Ran Ho, Dan Mikol, Jacob Elkins, Meena Subramanyam, and Ivan Nestorov. "Exposure–disease response analysis of natalizumab in subjects with multiple sclerosis." Journal of Pharmacokinetics and Pharmacodynamics 44, no. 3 (March 1, 2017): 263–75. http://dx.doi.org/10.1007/s10928-017-9514-4.

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Lin, Zhenwei, Chao Zhang, Jucan Dong, Jianliang Ou, and Li Yu. "Dynamic Response Analysis of a Multiple Square Loops-String Dome under Seismic Excitation." Symmetry 13, no. 11 (November 1, 2021): 2062. http://dx.doi.org/10.3390/sym13112062.

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Abstract:

The interaction between multiple loops and string cables complicates the dynamic response of triple square loops-string dome structures under seismic excitation. The internal connection between the multiple square loops-string cables and the grid beams was studies to provide a favorable reference for an anti-seismic structure. With a finite element model of the Fuzhou Strait Olympic Sports Center Gymnasium, established by SAP2000 software, the structural dynamic characteristic parameters were obtained first, and then this study adopted a time-history analysis method to study the internal force response of the cables and the roof grid beams of the multiple square loops-string dome (MSLSD) under three types of seismic array excitation. The influence of two factors, namely the seismic pulse and the near and far seismic fields, on the dynamic response of this structure was analyzed by three groups of different types of seismic excitation (PNF, NNF, PFF). As shown from the results, the first three-order vibration modes were torsional deformations caused by cables, the last five were mainly the overall roof plane vibration and antisymmetric vibration. Under the excitation of the three seismic arrays, the internal force responses of stay cables, square cables in the outer ring and the string cables were largest, while the maximum internal force response of the struts changed with the direction of seismic excitation. The largest internal force response of the roof grid beams occurred in local components such as BX3, BX7 and BY7, and the largest deformation of the beam nodes occurred in JX7, JX12 and JY4. In general, the seismic pulse and the near seismic field weakened the internal force response of the struts and cables but increased the internal force response and deformation of the dome beams, while the near and far seismic fields outweighed the seismic pulse. All the above provides an important reference for structural monitoring and seismic resistance.

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