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1. Detection of Bearing Fault in Induction Motor Based on Improved Adaptive Local Iterative Filtering

Author

Wang, Guomin, Qiu, Chidong, Hong, Shuai, Xue, Zhengyu, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, Li, Zewen, editor, and Luo, An, editor

Published
2024
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5. Corrigendum

Author

Lim, Eun-Pa, Hendon, Harry H., Butler, Amy H., Thompson, David W.J., Lawrence, Zachary D., Scaife, Adam A., Shepherd, Theodore G., Polichtchouk, Inna, Nakamura, Hisashi, Kobayashi, Chiaki, Comer, Ruth, Coy, Lawrence, Dowdy, Andrew, Garreaud, Rene D., Newman, Paul A., and Wang, Guomin

Subjects
Business, Earth sciences
Abstract

The authors of Lim et al. (2021) have found an error in the code that processed the data displayed in Fig. 2c in the article. The bar graph is supposed [...]

Published
2024
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9. EXPLAINING EXTREME EVENTS OF 2016 : From A Climate Perspective

Author

Herring, Stephanie C., Christidi, Nikolaos, Hoell, Andrew, Kossin, James P., Schreck, Carl J., Stott, Peter A., Webb, Robert S., Werner, Francisco E., Knutson, Thomas R., Kam, Jonghun, Zeng, Fanrong, Wittenberg, Andrew T., Brainard, Russell E., Oliver, Thomas, McPhaden, Michael J., Cohen, Anne, Venegas, Robert o, Heenan, Adel, Vargas-Ángel, Bernardo, Rotjan, Randi, Mangubhai, Sangeeta, Flint, Elizabeth, Hunter, Susan A., Oliver, Eric C. J., Perkins-Kirkpatrick, Sarah E., Holbrook, Neil J., Bindoff, Nathaniel L., Tett, Simon F. B., Falk, Alexander, Rogers, Megan, Spuler, Fiona, Turner, Calum, Wainwright, Joshua, Dimdore-Miles, Oscar, Knight, Sam, Freychet, Nicolas, Mineter, Michael J., Lehmann, Caroline E. R., Martins, Eduardo S. P. R., Coelho, Caio A. S., Haarsma, Rein, Otto, Friederike E. L., King, Andrew D., van Oldenborgh, Geert Jan, Kew, Sarah, Philip, Sjoukje, Vasconcelos, Francisco C., Cullen, Heidi, Jézéquel, Aglaé, Yiou, Pascal, Radanovics, Sabine, Vautard, Robert, Sippel, Sebastian, El-Madany, Tarek S., Migliavacca, Mirco, Mahecha, Miguel D., Carrara, Arnaud, Flach, Milan, Kaminski, Thomas, Otto, Friederike E. L., Thonicke, Kirsten, Vossbeck, Michael, Reichstein, Markus, Yuan, Xing, Wang, Linying, Wood, Eric F., Funk, Chris, Davenport, Frank, Harrison, Laura, Magadzire, Tamuka, Galu, Gideon, Artan, Guleid A., Shukla, Shraddhanand, Korecha, Diriba, Indeje, Matayo, Pomposi, Catherine, Macharia, Denis, Husak, Gregory, Nsadisa, Faka Dieudonne, Imada, Yukiko, Shiogama, Hideo, Takahashi, Chiharu, Watanabe, Masahiro, Mori, Masato, Kamae, Youichi, Maeda, Shuhei, Sun, Qiaohong, Miao, Chiyuan, Zhou, Chunlüe, Wang, Kaicun, Qi, Dan, Yuan, Xing, Wang, Shanshan, Hu, Zeng-Zhen, Qian, Cheng, Wang, Jun, Dong, Siyan, Yin, Hong, Burke, Claire, Ciavarella, Andrew, Dong, Buwen, Freychet, Nicolas, Lott, Fraser C., Tett, Simon F. B., Sun, Ying, Hu, Ting, Zhang, Xuebin, Wan, Hui, Stott, Peter, Lu, Chunhui, Christidis, Nikolaos, Manomaiphiboon, Kasemsan, Ciavarella, Andrew, Stott, Peter A., Hope, Pandora, Lim, Eun-Pa, Hendon, Harry, Wang, Guomin, Lewis, Sophie C., Mallela, Jennie, Grose, Michael R., Black, Mitchell, Risbey, James S., Uhe, Peter, Hope, Pandora K., Haustein, Karsten, Mitchell, Dann, Stott, Peter A., Christidis, Nikos, Herring, Stephanie C., Hoell, Andrew, Kossin, James P., and Schreck, Carl J.

Published
2018

15. Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Author

Schumacher, Fredrick R, Al Olama, Ali Amin, Berndt, Sonja I, Benlloch, Sara, Ahmed, Mahbubl, Saunders, Edward J, Dadaev, Tokhir, Leongamornlert, Daniel, Anokian, Ezequiel, Cieza-Borrella, Clara, Goh, Chee, Brook, Mark N, Sheng, Xin, Fachal, Laura, Dennis, Joe, Tyrer, Jonathan, Muir, Kenneth, Lophatananon, Artitaya, Stevens, Victoria L, Gapstur, Susan M, Carter, Brian D, Tangen, Catherine M, Goodman, Phyllis J, Thompson, Ian M, Batra, Jyotsna, Chambers, Suzanne, Moya, Leire, Clements, Judith, Horvath, Lisa, Tilley, Wayne, Risbridger, Gail P, Gronberg, Henrik, Aly, Markus, Nordström, Tobias, Pharoah, Paul, Pashayan, Nora, Schleutker, Johanna, Tammela, Teuvo LJ, Sipeky, Csilla, Auvinen, Anssi, Albanes, Demetrius, Weinstein, Stephanie, Wolk, Alicja, Håkansson, Niclas, West, Catharine ML, Dunning, Alison M, Burnet, Neil, Mucci, Lorelei A, Giovannucci, Edward, Andriole, Gerald L, Cussenot, Olivier, Cancel-Tassin, Géraldine, Koutros, Stella, Beane Freeman, Laura E, Sorensen, Karina Dalsgaard, Orntoft, Torben Falck, Borre, Michael, Maehle, Lovise, Grindedal, Eli Marie, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Travis, Ruth C, Key, Tim J, Hamilton, Robert J, Fleshner, Neil E, Finelli, Antonio, Ingles, Sue Ann, Stern, Mariana C, Rosenstein, Barry S, Kerns, Sarah L, Ostrer, Harry, Lu, Yong-Jie, Zhang, Hong-Wei, Feng, Ninghan, Mao, Xueying, Guo, Xin, Wang, Guomin, Sun, Zan, Giles, Graham G, Southey, Melissa C, MacInnis, Robert J, FitzGerald, Liesel M, Kibel, Adam S, Drake, Bettina F, Vega, Ana, Gómez-Caamaño, Antonio, Szulkin, Robert, Eklund, Martin, Kogevinas, Manolis, Llorca, Javier, Castaño-Vinyals, Gemma, Penney, Kathryn L, Stampfer, Meir, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Stanford, Janet L, and Cybulski, Cezary

Subjects
Cancer, Aging, Prostate Cancer, Genetics, Urologic Diseases, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Case-Control Studies, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Risk, Profile Study, Australian Prostate Cancer BioResource, IMPACT Study, Canary PASS Investigators, Breast and Prostate Cancer Cohort Consortium, PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium, Cancer of the Prostate in Sweden, Prostate Cancer Genome-wide Association Study of Uncommon Susceptibility Loci, Genetic Associations and Mechanisms in Oncology (GAME-ON)/Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE) Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Published
2018

16. Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Author

Dadaev, Tokhir, Saunders, Edward J, Newcombe, Paul J, Anokian, Ezequiel, Leongamornlert, Daniel A, Brook, Mark N, Cieza-Borrella, Clara, Mijuskovic, Martina, Wakerell, Sarah, Olama, Ali Amin Al, Schumacher, Fredrick R, Berndt, Sonja I, Benlloch, Sara, Ahmed, Mahbubl, Goh, Chee, Sheng, Xin, Zhang, Zhuo, Muir, Kenneth, Govindasami, Koveela, Lophatananon, Artitaya, Stevens, Victoria L, Gapstur, Susan M, Carter, Brian D, Tangen, Catherine M, Goodman, Phyllis, Thompson, Ian M, Batra, Jyotsna, Chambers, Suzanne, Moya, Leire, Clements, Judith, Horvath, Lisa, Tilley, Wayne, Risbridger, Gail, Gronberg, Henrik, Aly, Markus, Nordström, Tobias, Pharoah, Paul, Pashayan, Nora, Schleutker, Johanna, Tammela, Teuvo LJ, Sipeky, Csilla, Auvinen, Anssi, Albanes, Demetrius, Weinstein, Stephanie, Wolk, Alicja, Hakansson, Niclas, West, Catharine, Dunning, Alison M, Burnet, Neil, Mucci, Lorelei, Giovannucci, Edward, Andriole, Gerald, Cussenot, Olivier, Cancel-Tassin, Géraldine, Koutros, Stella, Freeman, Laura E Beane, Sorensen, Karina Dalsgaard, Orntoft, Torben Falck, Borre, Michael, Maehle, Lovise, Grindedal, Eli Marie, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Travis, Ruth C, Key, Tim J, Hamilton, Robert J, Fleshner, Neil E, Finelli, Antonio, Ingles, Sue Ann, Stern, Mariana C, Rosenstein, Barry, Kerns, Sarah, Ostrer, Harry, Lu, Yong-Jie, Zhang, Hong-Wei, Feng, Ninghan, Mao, Xueying, Guo, Xin, Wang, Guomin, Sun, Zan, Giles, Graham G, Southey, Melissa C, MacInnis, Robert J, FitzGerald, Liesel M, Kibel, Adam S, Drake, Bettina F, Vega, Ana, Gómez-Caamaño, Antonio, Fachal, Laura, Szulkin, Robert, Eklund, Martin, Kogevinas, Manolis, Llorca, Javier, Castaño-Vinyals, Gemma, Penney, Kathryn L, Stampfer, Meir, Park, Jong Y, and Sellers, Thomas A

Subjects
Genetics, Aging, Urologic Diseases, Prostate Cancer, Prevention, Human Genome, Cancer, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Algorithms, Bayes Theorem, Black People, Chromosome Mapping, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Molecular Sequence Annotation, Multivariate Analysis, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Quantitative Trait Loci, Risk, White People, PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium
Abstract

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Published
2018

31. DYNAMICS AND PREDICTABILITY OF EL NIÑO–SOUTHERN OSCILLATION : An Australian Perspective on Progress and Challenges

Author

Santoso, Agus, Hendon, Harry, Watkins, Andrew, Power, Scott, Dommenget, Dietmar, England, Matthew H., Frankcombe, Leela, Holbrook, Neil J., Holmes, Ryan, Hope, Pandora, Lim, Eun-Pa, Luo, Jing-Jia, McGregor, Shayne, Neske, Sonja, Nguyen, Hanh, Pepler, Acacia, Rashid, Harun, Gupta, Alex Sen, Taschetto, Andréa S., Wang, Guomin, Abellán, Esteban, Sullivan, Arnold, Huguenin, Maurice F., Gamble, Felicity, and Delage, Francois

Published
2019

32. EXPLAINING EXTREME EVENTS OF 2017 : From A Climate Perspective

Author

Herring, Stephanie C., Christidis, Nikolaos, Hoell, Andrew, Hoerling, Marty, Stott, Peter A., Owen, Rebecca, Vano, Julie A., Dettinger, Michael D., Cifelli, Rob, Curtis, David, Dufour, Alexis, Miller, Kathleen, Olsen, J. Rolf, Wilson, Anna M., Nerem, R. S., Fasullo, J., Hoell, Andrew, Perlwitz, Judith, Dewes, Candida, Wolter, Klaus, Rangwala, Imtiaz, Quan, Xiao-Wei, Eischeid, Jon, Wang, Hailan, Schubert, Siegfried D., Koster, Randal D., Chang, Yehui, Christidis, Nikolaos, Betts, Richard A., Stott, Peter A., de Abreu, Rafael C., Cunningham, Christopher, Rudorff, Conrado M., Rudorff, Natalia, Abatan, Abayomi A., Dong, Buwen, Lott, Fraser C., Tett, Simon F. B., Sparrow, Sarah N., Navarro, Juan C. Acosta, Ortega, Pablo, García-Serrano, Javier, Guemas, Virginie, Tourigny, Etienne, Cruz-García, Rubén, Massonnet, François, Doblas-Reyes, Francisco J., Kew, Sarah F., Philip, Sjoukje Y., van Oldenborgh, Geert Jan, Otto, Friederike E. L., Vautard, Robert, van der Schrier, Gerard, Funk, Chris, Hoell, Andrew, Nicholson, Sharon, Korecha, Diriba, Galu, Gideon, Artan, Guleid, Teshome, Fetene, Hailermariam, Kinfe, Segele, Zewdu, Harrison, Laura, Tadege, Abebe, Atheru, Zachary, Pomposi, Catherine, Pedreros, Diego, Rimi, Ruksana H., Haustein, Karsten, Barbour, Emily J., Allen, Myles R., Takahashi, Chiharu, Shiogama, Hideo, Imada, Yukiko, Kosaka, Yu, Mori, Masato, Arai, Miki, Kamae, Youichi, Watanabe, Masahiro, Min, Seung-Ki, Kim, Yeon-Hee, Park, In-Hong, Lee, Donghyun, Sparrow, Sarah, Wallom, David, Stone, Dáithí, Sun, Ying, Dong, Siyan, Zhang, Xuebin, Stott, Peter, Hu, Ting, Wang, Shanshan, Yuan, Xing, Wu, Renguang, Chen, Yang, Chen, Wei, Su, Qin, Luo, Feifei, Sparrow, Sarah, Tian, Fangxing, Dong, Buwen, Tett, Simon F. B., Lott, Fraser C., Wallom, David, Zhou, Chunlüe, Wang, Kaicun, Qi, Dan, Tan, Jianguo, Perkins-Kirkpatrick, S. E., King, A. D., Cougnon, E. A., Grose, M. R., Oliver, E. C. J., Holbrook, N. J., Lewis, S. C., Pourasghar, F., Hope, Pandora, Black, Mitchell T., Lim, Eun-Pa, Dowdy, Andrew, Wang, Guomin, Pepler, Acacia S., and Fawcett, Robert J. B.

Published
2019

39. The nonlinear association between HbA1c and cognitive impairment in patients with alcohol use disorder.

Author

Deng, Mengling, Wang, Guomin, Gao, Xiaofeng, Wang, Yan, Ni, Yanfei, Chen, Yunyu, Xu, Jiating, and Jiang, Weifeng

Subjects
*COGNITION disorder risk factors, *GLYCOSYLATED hemoglobin, *STATISTICS, *ALCOHOLISM, *MULTIPLE regression analysis, *RISK assessment, *DESCRIPTIVE statistics, *RESEARCH funding
Abstract

Background: Extensive research has indicated that higher levels of glycated hemoglobin (HbA1c) are associated with poor cognitive performance regardless of the presence of diabetes. To our knowledge, the association between HbA1c levels and cognitive decline in patients with alcohol use disorder is not well understood. This study aimed to investigate whether HbA1c was associated with cognitive impairment in patients with alcohol use disorder. Methods: Patients admitted to the Psychiatry Department of the Third Hospital of Quzhou with a confirmed diagnosis of alcohol-related cognitive impairment were recruited between January 2019 and February 2022. Their HbA1c levels were measured, and they completed the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) after at least one week of monitored abstinence from alcohol. Univariate linear regression, multivariate linear regression and generalized additive models (GAMs) were used to investigate the association of HbA1c with MMSE and MoCA scores. Results: In total, 227 patients were included. Univariate and multivariate regression analyses suggested that HbA1c was negatively associated with MMSE and MoCA scores after adjustment for potential confounders (P < 0.05). The GAM analysis revealed that the relationships between the HbA1c level and the MMSE and MoCA scores were bell-shaped. The inflection points were 5.3% and 5.2% for the MMSE and MoCA respectively. Conclusion: The results of this study suggest that HbA1c levels are significantly related to cognitive impairment in patients with alcohol use disorder. Future studies are required to determine the effects of optimal glucose control in people with alcohol use disorder. [ABSTRACT FROM AUTHOR]

Published
2024
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42. ON DETERMINING THE IMPACT OF INCREASING ATMOSPHERIC C[O.sub.2] ON THE RECORD FIRE WEATHER IN EASTERN AUSTRALIA IN FEBRUARY 2017

Author

Hope, Pandora, Black, Mitchell T., Lim, Eun-Pa, Dowdy, Andrew, Wang, Guomin, Pepler, Acacia S., and Fawcett, Robert J.B.

Subjects
Australia -- Environmental aspects, Global warming -- Influence, Wildfires -- Environmental aspects, Atmospheric carbon dioxide -- Influence, Business, Earth sciences
Abstract

February 2017 saw a broad region with record fire weather across central-eastern Australia. A hybrid attribution technique using modified observations and a seasonal forecast framework did not give a clear [...]

Published
2019
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45. A Novel Multiplex Assay Combining Autoantibodies Plus PSA Has Potential Implications for Classification of Prostate Cancer from Non-malignant Cases

Author

Xie, Chong, Kim, Hyun J, Haw, Jonathan G, Kalbasi, Anusha, Gardner, Brian K, Li, Gang, Rao, Jianyu, Chia, David, Liong, Monty, Punzalan, Rubio R, Marks, Leonard S, Pantuck, Allan J, de la Taille, Alexandre, Wang, Guomin, Mukouyama, Hideki, and Zeng, Gang

Abstract

Abstract Background The lack of sufficient specificity and sensitivity among conventional cancer biomarkers, such as prostate specific antigen (PSA) for prostate cancer has been widely recognized after several decades of clinical implications. Autoantibodies (autoAb) among others are being extensively investigated as potential substitute markers, but remain elusive. One major obstacle is the lack of a sensitive and multiplex approach for quantifying autoAb against a large panel of clinically relevant tumor-associated antigens (TAA). Methods To circumvent preparation of phage lysates and purification of recombinant proteins, we identified B cell epitopes from a number of previously defined prostate cancer-associated antigens (PCAA). Peptide epitopes from cancer/testis antigen NY-ESO-1, XAGE-1b, SSX-2,4, as well as prostate cancer overexpressed antigen AMACR, p90 autoantigen, and LEDGF were then conjugated with seroMAP microspheres to allow multiplex measurement of autoAb present in serum samples. Moreover, simultaneous quantification of autoAb plus total PSA was achieved in one reaction, and termed the "A+PSA" assay. Results Peptide epitopes from the above 6 PCAA were identified and confirmed that autoAb against these peptide epitopes reacted specifically with the full-length protein. A pilot study was conducted with the A+PSA assay using pre-surgery sera from 131 biopsy-confirmed prostate cancer patients and 121 benign prostatic hyperplasia and/or prostatitis patients. A logistic regression-based A+PSA index was found to enhance sensitivities and specificities over PSA alone in distinguishing prostate cancer from nonmalignant cases. The A+PSA index also reduced false positive rate and improved the area under a receiver operating characteristic curve. Conclusions The A+PSA assay represents a novel platform that integrates autoAb signatures with a conventional cancer biomarker, which may aid in the diagnosis and prognosis of prostate cancer and others.

Published
2011

47. Calculation of Mesh Stiffness for ZC3 Worm Gear and Worm based on the Finite Element Method

Author

Chen Wei, Wang Guomin, Lin Jiajie, and Zhang Zhiyong

Subjects
ZC3 worm gear, Loading contact analysis, Mesh stiffness, Finite element method, Mechanical engineering and machinery, TJ1-1570
Abstract

The calculation of the meshing stiffness of the worm gear is the basis of the foundation of dynamics analysis. In view of the Uzbekistan Maidanak observatory 1 m telescope worm gear and worm drive renovation project,based on the theory of finite element analysis for ZC3 worm gear with loaded contact,a method for calculating the time-varying meshing stiffness of ZC3 worm gear is proposed. The finite element model is built by using Workbench and the meshing stiffness curve is obtained. The results show that the meshing curve of ZC3 worm has obvious periodicity. The minimum value of the meshing stiffness is 104. 4 MN·m,which appears at the position where the front pair of teeth exits meshing in the double tooth contact area of the teeth.And the maximum value of the meshing stiffness is 219. 7 MN·m,which appears in the middle of the single tooth contact zone. The basic conditions for the dynamics analysis of reconstruction project is provided by the research result.

Published
2018
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