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Journal articles on the topic 'Combination model'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Burt, Tim, and J. R. O'Callaghan. "Novel Combination Model." Global Ecology and Biogeography Letters 7, no. 2 (1998): 152. http://dx.doi.org/10.2307/2997822.

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2

Zhang, X., and Y. Lei. "A linkage among whole-stand model, individual-tree model and diameter-distribution model." Journal of Forest Science 56, No. 12 (2010): 600–608. http://dx.doi.org/10.17221/102/2009-jfs.

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Stand growth and yield models include whole-stand models, individual-tree models and diameter-distribution models. In this study, the three models were linked by forecast combination and parameter recovery methods one after another. Individual-tree models combine with whole-stand models through forecast combination. Forecast combination method combines information from different models, disperses errors generated from different models, and then improves forecast accuracy. And then the forecast combination model was linked to diameter-distribution models via parameter recovery methods. During t

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3

N, Musliha, Liyana Faisal PP, and Raneem Ahammed Rashid K. "Neuropharmacological Assessment of Dual Herbal Combination Using Zebrafish Model." International Journal of Science and Research (IJSR) 11, no. 7 (2022): 1368–73. http://dx.doi.org/10.21275/sr22718201607.

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4

Lees, Kirdan, and Shaun P. Vahey. "Nowcasting and model combination." North American Journal of Economics and Finance 22, no. 1 (2011): 3–4. http://dx.doi.org/10.1016/j.najef.2011.01.003.

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5

de Moura, Leonardo, and Nikolaj Bjørner. "Model-based Theory Combination." Electronic Notes in Theoretical Computer Science 198, no. 2 (2008): 37–49. http://dx.doi.org/10.1016/j.entcs.2008.04.079.

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6

Lavanya, G., and D. Jasmine. "A Mathematical Model for Differentiated Thyroid Cancer with Combination Therapy." Indian Journal Of Science And Technology 17, no. 25 (2024): 2557–69. http://dx.doi.org/10.17485/ijst/v17i25.355.

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Objectives: Differentiated thyroid cancer (DTC) is usually treated with surgery and radioactive iodine therapy. However, in advanced stages, molecular changes can lead to a progressive loss of sensitivity to iodine, making the cancer resistant to radioactive iodine treatment (known as radioactive iodine-refractory, or RAIR). For cases of RAIR-DTC, alternative treatments such as tyrosine kinase inhibitors and immunotherapy are explored. To better understand the dynamics of these alternative treatments, a new mathematical model has been developed. In this model, Sorafenib represents the tyrosine

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7

Ting, Kai Ming, Boon Toh Low, and Ian H. Witten. "Learning from Batched Data: Model Combination Versus Data Combination." Knowledge and Information Systems 1, no. 1 (1999): 83–106. http://dx.doi.org/10.1007/bf03325092.

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8

Franses, Philip Hans. "Model selection for forecast combination." Applied Economics 43, no. 14 (2011): 1721–27. http://dx.doi.org/10.1080/00036840902762753.

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9

INOUE, Hiroyuki, and Yoshiyuki MURAMOTO. "Color Combination System Using Emotion Color Combination Model and Image Emotion Model and its Application to Uniform Color Combination." Transactions of Japan Society of Kansei Engineering 11, no. 2 (2012): 273–80. http://dx.doi.org/10.5057/jjske.11.273.

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10

Zhao, Wei, Kris Sachsenmeier, Lanju Zhang, Erin Sult, Robert E. Hollingsworth, and Harry Yang. "A New Bliss Independence Model to Analyze Drug Combination Data." Journal of Biomolecular Screening 19, no. 5 (2014): 817–21. http://dx.doi.org/10.1177/1087057114521867.

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The Bliss independence model is widely used to analyze drug combination data when screening for candidate drug combinations. The method compares the observed combination response ( YO) with the predicted combination response ( YP), which was obtained based on the assumption that there is no effect from drug-drug interactions. Typically, the combination effect is declared synergistic if YO is greater than YP. However, this method lacks statistical rigor because it does not take into account the variability of the response measures and can frequently cause false-positive claims. In this article,

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11

Che, JinXing. "Optimal sub-models selection algorithm for combination forecasting model." Neurocomputing 151 (March 2015): 364–75. http://dx.doi.org/10.1016/j.neucom.2014.09.028.

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12

Choi, Sook-Nam, and Hyun-Yeol Chung. "Noise Robust Speech Recognition Based on Parallel Model Combination Adaptation Using Frequency-Variant." Journal of the Acoustical Society of Korea 32, no. 3 (2013): 252–61. http://dx.doi.org/10.7776/ask.2013.32.3.252.

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13

CHEN, Jia-lin, and Rui-fan LI. "Fuzzy reasoning model based on universal combination operation model." Journal of China Universities of Posts and Telecommunications 19, no. 6 (2012): 89–93. http://dx.doi.org/10.1016/s1005-8885(11)60322-1.

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14

Shen, Xiaotong, and Hsin-Cheng Huang. "Optimal Model Assessment, Selection, and Combination." Journal of the American Statistical Association 101, no. 474 (2006): 554–68. http://dx.doi.org/10.1198/016214505000001078.

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15

Zirka, S. E., Y. I. Moroz, and E. Della Torre. "Combination hysteresis model for accommodation magnetization." IEEE Transactions on Magnetics 41, no. 9 (2005): 2426–31. http://dx.doi.org/10.1109/tmag.2005.854335.

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16

Freitas, Paulo S. A., and António J. L. Rodrigues. "Model combination in neural-based forecasting." European Journal of Operational Research 173, no. 3 (2006): 801–14. http://dx.doi.org/10.1016/j.ejor.2005.06.057.

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17

Xu, Yi-ping. "A combination model for image denoising." Acta Mathematicae Applicatae Sinica, English Series 32, no. 3 (2016): 781–92. http://dx.doi.org/10.1007/s10255-016-0604-7.

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18

Yang, Yang-Guang, Jun Song, Feng-Lan Shao, Zuo-Tang Liang, and Qun Wang. "Statistical method in quark combination model." Chinese Physics C 44, no. 3 (2020): 034103. http://dx.doi.org/10.1088/1674-1137/44/3/034103.

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19

Samuels, Jon D., and Rodrigo M. Sekkel. "Model Confidence Sets and forecast combination." International Journal of Forecasting 33, no. 1 (2017): 48–60. http://dx.doi.org/10.1016/j.ijforecast.2016.07.004.

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20

Zanderigo, Eleonora, Valentina Sartori, Gorazd Sveticic, et al. "The Well-being Model." Anesthesiology 104, no. 4 (2006): 742–53. http://dx.doi.org/10.1097/00000542-200604000-00019.

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Background Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account. Methods By extension of a previously published interaction model, the authors propose a method to study drug interactions considering also their side effects. A general outcome parameter identified as patient's well-being is defined by

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21

Dong, Xiuze, Yunchuan Guo, Fenghua Li, Liju Dong, and Arshad Khan. "Combination Model of Heterogeneous Data for Security Measurement." JUCS - Journal of Universal Computer Science 25, no. (3) (2019): 270–81. https://doi.org/10.3217/jucs-025-03-0270.

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Measuring security is a core step for guaranteeing security of network and information systems. Due to massiveness and heterogeneity of measurement data, it is difficult to classify and combine them on demand. In this paper, considering implication relationship of metrics, we propose a combination model and combination policy for security measurement. Several examples demonstrate the effectiveness of our model.

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22

Iversen, Edwin S., Giovanni Parmigiani, and Sining Chen. "Multiple Model Evaluation Absent the Gold Standard Through Model Combination." Journal of the American Statistical Association 103, no. 483 (2008): 897–909. http://dx.doi.org/10.1198/016214507000001012.

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23

Zhou, Fengqi, Yu Xiao, Zhi gang Yan, and Fenlin Yang. "Combination of LLT Model and TV Model for Image Denoising." International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no. 2 (2016): 393–404. http://dx.doi.org/10.14257/ijsip.2016.9.2.33.

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24

Rexfort, Claudia. "Combination of a fire model and a smoke sensor model." Fire Safety Journal 41, no. 4 (2006): 252–57. http://dx.doi.org/10.1016/j.firesaf.2005.12.006.

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25

Xu, Guoyan, Yuwei Lu, Zixu Jing, Chunyan Wu, and Qirui Zhang. "IEALL: Dam Deformation Prediction Model Based on Combination Model Method." Applied Sciences 13, no. 8 (2023): 5160. http://dx.doi.org/10.3390/app13085160.

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The accuracy of dam deformation prediction is a key issue that needs to be addressed due to the many factors that influence dam deformation. In this paper, a dam deformation prediction model based on IEALL (IGWO-EEMD-ARIMA-LSTM-LSTM) is proposed for a single-point scenario. The IEALL model is based on the idea of a combination model. Firstly, EEMD is used to decompose the dam deformation data, and then the ARIMA and LSTM models are selected for prediction. To address the problem of low prediction accuracy caused by simple linear addition of prediction results from different models in tradition

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26

Dan Liu, Dan Liu, Shu-Wen Yao Dan Liu, Yan Zeng Shu-Wen Yao, Ke Zhao Yan Zeng, Yan-An Guo Ke Zhao, and Li Li Yan-An Guo. "Research of the Service Composition Optimization Model Based on Petri Net." 電腦學刊 32, no. 5 (2021): 101–14. http://dx.doi.org/10.53106/199115992021103205008.

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Cloud service systems bring together a wide variety of flexible and scalable mass services. The service combination scheme which can meet the user&rsquo;s needs is provided to the user through the flexible and changing service mode of service combination technology. However, service combination failures often occur. In view of the above problems, this paper establishes the cloud service combination optimization model. Firstly, it is proposed that the Service Combination Optimization Petri Net models and analyzes the service selection and combination. In order to avoid local convergence, co

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27

Jeong, Jaemin, Ji-Ho Cho, and Jeong-Gun Lee. "Filter combination learning for CNN model compression." ICT Express 7, no. 1 (2021): 5–9. http://dx.doi.org/10.1016/j.icte.2021.01.001.

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28

&NA;. "Gemcitabine combination effective in heart transplantation model." Inpharma Weekly &NA;, no. 1414 (2003): 11. http://dx.doi.org/10.2165/00128413-200314140-00026.

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29

Chen, Qingming. "Combination Model for Short-Term Load Forecasting." Open Automation and Control Systems Journal 5, no. 1 (2013): 124–32. http://dx.doi.org/10.2174/1874444301305010124.

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30

Wang, Xiao Gang, Qing Xue Huang, and Jian Mei Wang. "Research on Leveling Model of Combination Leveler." Advanced Materials Research 145 (October 2010): 453–57. http://dx.doi.org/10.4028/www.scientific.net/amr.145.453.

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The evolvement of plate in 15-roller combination leveler has been studied in this paper using both geometrical analysis and FEM. The results show that the bending deformation and curvature evolvement are different from those obtained by general leveler. The technologies of parallel leveling and tension leveling are adaptive to the roll system of combination leveler, which not only can improve leveling precision, but also can erase the influence of negative torque on leveling roll, thus improving the leveling strength capacity of leveling materials. Meanwhile, a new calculating method of leveli

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31

Weighuo, Hu, and Hu He. "FLOOD FORECASTING MODEL USING THE COMBINATION APPROACH." Computer Science & IT Research Journal 1, no. 2 (2020): 59–64. http://dx.doi.org/10.51594/csitrj.v1i2.136.

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This paper reviews the qualities of a good flood forecasting model such as timeliness, accuracy, and reliability. The article reviews the current forecasting models which are based on fuzzy logic, artificial neural network, as well as combination. The combination approach is gaining popularity and is found to be more flexible, accurate, reliable, and highly efficient in terms of development and output.

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32

Banks, M. S., and M. O. Ernst. "A biologically plausible model of cue combination." Journal of Vision 3, no. 9 (2010): 31. http://dx.doi.org/10.1167/3.9.31.

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33

Lee, S., and A. Dobbins. "A Multi-scale model of Binocular combination." Journal of Vision 7, no. 9 (2010): 815. http://dx.doi.org/10.1167/7.9.815.

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34

Cheng, Maolin, and Minyin Xiang. "Application of a combination production function model." Applied Mathematics and Computation 236 (June 2014): 33–40. http://dx.doi.org/10.1016/j.amc.2014.02.076.

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35

Song, Yafei, Xiaodan Wang, Lei Lei, and Yaqiong Xing. "Credibility decay model in temporal evidence combination." Information Processing Letters 115, no. 2 (2015): 248–52. http://dx.doi.org/10.1016/j.ipl.2014.09.022.

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36

Pons Bordería, Salvador. "The combination of discourse markers in spontaneous conversations." Revue Romane / Langue et littérature. International Journal of Romance Languages and Literatures 53, no. 1 (2018): 121–58. http://dx.doi.org/10.1075/rro.00008.pon.

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Abstract This paper attempts to establish some basis for the combination of discourse markers in conversations. The analysis presented here will be based on Spanish spontaneous conversations and will make use of the Val.Es.Co model of discourse units developed in the last ten years (Briz et al. 2003; Grupo Val.Es.Co 2014) and a corpus of spontaneous conversations. As a result, patterns of combination of DMs will be established; some types of combinations will be described, and a distinction will be drawn between lexicalization of DMs, adjacency of DMs in two neighboring discourse units, and co

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37

Sadarang, Fazrul Rafsanjani, and Fitria Puspita Sari. "WRF-model sensitivity test and assimilation studies of Cempaka tropical cyclone." IOP Conference Series: Earth and Environmental Science 893, no. 1 (2021): 012029. http://dx.doi.org/10.1088/1755-1315/893/1/012029.

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Abstract The WRF model was used to forecast the most intensive stage of Cempaka Tropical Cyclone (TC) on 27 - 29 November 2017. This study evaluates the combination of cumulus and microphysics parameterization and the efficiency of assimilation method to predict pressure values at the center of the cyclone, maximum wind speed, and cyclone track. This study tested 18 combinations of cumulus and microphysics parameterization schemes to obtain the best combination of both parameterization schemes which later on called as control model (CTL). Afterward, assimilation schemes using 3DVAR cycles of 1

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38

Haghroosta, T., W. R. Ismail, P. Ghafarian, and S. M. Barekati. "The efficiency of the WRF model for simulating typhoons." Natural Hazards and Earth System Sciences Discussions 2, no. 1 (2014): 287–313. http://dx.doi.org/10.5194/nhessd-2-287-2014.

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Abstract. The Weather Research Forecast (WRF) model includes various configuration options related to physics parameters, which can affect the performance of the model. In this study, different numerical experiments were conducted to determine the best combination of physics parameterization schemes for the simulation of sea surface temperatures, latent heat flux, sensible heat flux, precipitation rate, and wind speed that characterized typhoons. Through these experiments, several physics parameterization options within the WRF model were exhaustively tested for typhoon Noul, which had origina

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39

Lei, Liu, and Qian Yan. "A combination forecasting model based on IOWA operators." Journal of Progressive Research in Mathematics 12, no. 1 (2017): 1772–79. https://doi.org/10.5281/zenodo.3975940.

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With respect to the combination forecasting problems with forecast value and actual value which are actual numbers. The relative distance measure is used as the induced value of the IOWA operator. A new fuzzy combination forecasting model is presented to minimize the error sum of squares. Finally, an example is illustrated to show this model improved the combination forecasting accuracy efficiently

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40

Jian-jie, Gao, Wang Yong-li, Zhou Jun-chao, and Shao Yi-ming. "Combination model of urban tourism transportation based on nested logit model." Systems Science & Control Engineering 10, no. 1 (2022): 865–76. http://dx.doi.org/10.1080/21642583.2022.2132544.

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41

Zhan, Y. C. "Comparison between UofC Model and Ionosphere-free Combination Model in PPP." Journal of Physics: Conference Series 1187, no. 2 (2019): 022060. http://dx.doi.org/10.1088/1742-6596/1187/2/022060.

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42

Yang, J. F., L. F. Xiao, J. X. Qian, and H. Li. "Nonlinear model predictive control using parameter varying BP-ARX combination model." International Journal of Systems Science 43, no. 3 (2012): 475–90. http://dx.doi.org/10.1080/00207721.2010.517855.

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43

Chukwunonso C Onwuzuligbo and Amarachukwu U Onwuzuligbo. "Fixed dose combination, a model therapy optimization strategy: A review." GSC Advanced Research and Reviews 20, no. 2 (2024): 036–46. http://dx.doi.org/10.30574/gscarr.2024.20.2.0296.

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Therapy optimization involves a continuous improvement process of treatment interventions in the management of specific health challenges. Such optimization practices will not only help in achieving the desired treatment goals but will also improve the overall patients’ quality of life. One of the available therapy optimization strategy is the use of fixed dose combinations over monotherapies or poly-pharmacy. Fixed dose combination (FDC) is combination product that includes two or more active pharmaceutical ingredients (APIs) with similar or different pharmacological activity and different me

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44

Chukwunonso, C. Onwuzuligbo, and U. Onwuzuligbo Amarachukwu. "Fixed dose combination, a model therapy optimization strategy: A review." GSC Advanced Research and Reviews 20, no. 2 (2024): 036–46. https://doi.org/10.5281/zenodo.14948638.

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Therapy optimization involves a continuous improvement process of treatment interventions in the management of specific health challenges. Such optimization practices will not only help in achieving the desired treatment goals but will also improve the overall patients’ quality of life. One of the available therapy optimization strategy is the use of fixed dose combinations over monotherapies or poly-pharmacy. Fixed dose combination (FDC) is combination product that includes two or more active pharmaceutical ingredients (APIs) with similar or different pharmacological activity and differ

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45

Seignères, Béatrice, Perrine Martin, Bettina Werle, et al. "Effects of Pyrimidine and Purine Analog Combinations in the Duck Hepatitis B Virus Infection Model." Antimicrobial Agents and Chemotherapy 47, no. 6 (2003): 1842–52. http://dx.doi.org/10.1128/aac.47.6.1842-1852.2003.

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ABSTRACT To design new strategies of antiviral therapy for chronic hepatitis B, we have evaluated the antiviral activity of the combination of amdoxovir (DAPD), emtricitabine [(−)FTC], and clevudine (l-FMAU) in the duck hepatitis B virus (DHBV) model. Using their triphosphate (TP) derivatives in a cell-free system expressing a wild-type active DHBV reverse transcriptase (RT), the three dual combinations exhibited a greater additive inhibitory effect on viral minus-strand DNA synthesis than the single drugs, according to the Bliss independence model. Both dual combinations with DAPD TP were the

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46

Bhowmik, R. Das, A. Sharma, and A. Sankarasubramanian. "Reducing Model Structural Uncertainty in Climate Model Projections—A Rank-Based Model Combination Approach." Journal of Climate 30, no. 24 (2017): 10139–54. http://dx.doi.org/10.1175/jcli-d-17-0225.1.

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Future changes in monthly precipitation are typically evaluated by estimating the shift in the long-term mean/variability or based on the change in the marginal distribution. General circulation model (GCM) precipitation projections deviate across various models and emission scenarios and hence provide no consensus on the expected future change. The current study proposes a rank/percentile-based multimodel combination approach to account for the fact that alternate model projections do not share a common time indexing. The approach is evaluated using 10 GCM historical runs for the current peri

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47

Hwangbo, Haeun, and Adam C. Palmer. "Abstract 2739: Defining and evaluating drug additivity in clinical trials of combination cancer therapy." Cancer Research 82, no. 12_Supplement (2022): 2739. http://dx.doi.org/10.1158/1538-7445.am2022-2739.

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Abstract BACKGROUND The benefits of combination therapy are often attributed to synergy, that is, drug interactions resulting in an anti-cancer effect that is more than the sum of its parts. Accordingly, the rationale for designing new drug combinations is often based on synergy measured in preclinical models. However, preclinical metrics of drug interaction are not applicable to clinical trial data, and there has been no established quantitative method to assess synergy versus additivity in clinical settings. We recently showed that because of extensive patient-to-patient heterogeneity in sin

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48

Jiao, R., K. J. H. Allen, M. E. Malo, D. Rickles, and E. Dadachova. "Evaluating the Combination of Radioimmunotherapy and Immunotherapy in a Melanoma Mouse Model." International Journal of Molecular Sciences 21, no. 3 (2020): 773. http://dx.doi.org/10.3390/ijms21030773.

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Immunotherapy has changed the oncology landscape during the last decade and become standard of care for several cancers. The combinations of immunotherapy with other treatment modalities are also being investigated. One of the challenges to investigate such combinations is to identify suitable mouse models for the pre-clinical experiments. In the past, we and other researchers showed that murine B16-F10 melanoma in C57Bl6 mice is refractory to treatment with immune checkpoint inhibitors. In this work we studied the suitability of an alternative syngeneic model, Cloudman S91 murine melanoma in

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49

Ehara, Tatsuya, Hirohisa Izumi, Muneya Tsuda, et al. "Combinational effects of prebiotic oligosaccharides on bifidobacterial growth and host gene expression in a simplified mixed culture model and neonatal mice." British Journal of Nutrition 116, no. 2 (2016): 270–78. http://dx.doi.org/10.1017/s0007114516001987.

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AbstractIt is important to provide formula-fed infants with a bifidobacteria-enriched gut microbiota similar to those of breastfed infants to ensure intestinal health. Prebiotics, such as certain oligosaccharides, are a useful solution to this problem, but the combinational benefits of these oligosaccharides have not been evaluated. This study investigated the benefits of oligosaccharide combinations and screened for an optimal combination of oligosaccharides to promote healthy gut microbiota of formula-fed infants. In vitro and in vivo experiments were performed to assess the bifidogenic effe

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50

Luo, Jiaoyang, Dan Yan, Meihua Yang, Xiaoping Dong, and Xiaohe Xiao. "Multicomponent Therapeutics of Berberine Alkaloids." Evidence-Based Complementary and Alternative Medicine 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/545898.

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Although berberine alkaloids (BAs) are reported to be with broad-spectrum antibacterial and antiviral activities, the interactions among BAs have not been elucidated. In the present study, methicillin-resistantStaphylococcus aureus(MRSA) was chosen as a model organism, and modified broth microdilution was applied for the determination of the fluorescence absorption values to calculate the anti-MRSA activity of BAs. We have initiated four steps to seek the optimal combination of BAs that are (1) determining the anti-MRSA activity of single BA, (2) investigating the two-component combination to

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