A hybrid forecasting model for ageing breast deformation during yoga practice

2021 ◽  
pp. 004051752110408
Author(s):  
Jie Zhou ◽  
Jianming Chen ◽  
Newman Lau ◽  
Qian Mao ◽  
Zidan Gong ◽  
...  
Keyword(s):  
Left Breast ◽  
Forecasting Model ◽  
Yoga Practice ◽  
Grey Relation Analysis ◽  
Senior Women ◽  
Hybrid Forecasting ◽  
Learning Machine ◽  
The Right ◽  
Grey Relation ◽  
Motion Amplitude

In this work, the deformation of bilateral breasts was investigated with an established hybrid model to predict the nipple movement specifically for senior women during yoga exercise. A motion capture system was used to collect the displacement of 10 markers on the breasts from 11 senior women (average age of 62) during yoga practice and then the data were analyzed by integrating the absolute grey relation analysis (AGRA) and extreme learning machine (ELM). The right and left breasts had the maximum motion amplitude in the horizontal direction but they were respectively featured with contraction and extension during yoga practice. AGRA showed that the nipple motion was highly associated with the vertical region above the nipple for the left breast but the parallel region along with the nipple for the right breast. The ELM model is able to predict the nipple movement within tolerable error (∼0.0037). This study lays a foundation for a better understanding of ageing breast kinematics during yoga poses with limited practical experiments. Besides, the accurate and efficient results can be used not only for yoga pose instruction but also for ergonomic sports bra design.

Fuzzy grey relation analysis on torque influence factors of alternating current electrodyna-mometer

2013 ◽  
Vol 26 (8) ◽  
pp. 693-698 ◽  
Author(s):  
Zhigang Zhang ◽  
Guixiang Zhang ◽  
Teng Liu ◽  
Cheng Qian ◽  
Yuanwang Deng
Keyword(s):  
Influence Factors ◽  
Alternating Current ◽  
Grey Relation Analysis ◽  
Relation Analysis ◽  
Grey Relation

scholarly journals Bilateral Phyllodes Giant Tumor. A Case Report Analyzed by Array-CGH

Diagnostics ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 825
Author(s):  
Francesco Fortarezza ◽  
Federica Pezzuto ◽  
Gerardo Cazzato ◽  
Clelia Punzo ◽  
Antonio d’Amati ◽  
...  
Keyword(s):  
Array Cgh ◽  
Phyllodes Tumor ◽  
Molecular Classification ◽  
Left Breast ◽  
Comparative Genomic ◽  
Fish Analysis ◽  
Molecular Tests ◽  
Giant Tumor ◽  
Metastatic Risk ◽  
The Right

The breast phyllodes tumor is a biphasic tumor that accounts for less than of 1% of all breast neoplasms. It is classified as benign, borderline, or malignant, and can mimic benign masses. Some recurrent alterations have been identified. However, a precise molecular classification of these tumors has not yet been established. Herein, we describe a case of a 43-year-old woman that was admitted to the emergency room for a significant bleeding from the breast skin. A voluminous ulcerative mass of the left breast and multiple nodules with micro-calcifications on the right side were detected at a physical examination. A left total mastectomy and a nodulectomy of the right breast was performed. The histological diagnosis of the surgical specimens reported a bilateral giant phyllodes tumor, showing malignant features on the left and borderline characteristics associated with a fibroadenoma on the right. A further molecular analysis was carried out by an array-Comparative Genomic Hybridization (CGH) to characterize copy-number alterations. Many losses were detected in the malignant mass, involving several tumor suppressor genes. These findings could explain the malignant growth and the metastatic risk. In our study, genomic profiling by an array-CGH revealed a greater chromosomal instability in the borderline mass (40 total defects) than in the malignant (19 total defects) giant phyllodes tumor, reflecting the tumor heterogeneity. Should our results be confirmed with more sensitive and specific molecular tests (DNA sequencing and FISH analysis), they could allow a better selection of patients with adverse pathological features, thus optimizing and improving patient’s management.

scholarly journals Hybrid forecasting model for non-linear time series

2020 ◽  
Author(s):  
E. Priyadarshini ◽  
G. Raj Gayathri ◽  
M. Vidhya ◽  
A. Govindarajan ◽  
Samuel Chakkravarthi
Keyword(s):  
Time Series ◽  
Linear Time ◽  
Forecasting Model ◽  
Non Linear ◽  
Hybrid Forecasting

Predominance of RAD21 and ERBB2 amplification and progesterone receptor positivity in tumors of the right breast support breast cancer lateralization.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12557-e12557
Author(s):  
Zachary Spigelman ◽  
Jo-Ellen Murphy
Keyword(s):  
Breast Cancer ◽  
Progesterone Receptor ◽  
Cancer Patients ◽  
Breast Tumors ◽  
Left Breast ◽  
Breast Cancers ◽  
Her2 Expression ◽  
Breast Cancer Patients ◽  
The Right ◽  
Chi Square Analysis

e12557 Background: Biologic lateralization broadly impacts breast cancer. Malignancies originating in the left breast compared to the right breast tend to be more frequent, larger and of poorer prognosis. Left breast tumors respond differently to HER2-neu signaling and have lateralized Ki67 expression. In a prior study a right-left asymmetry in the neutrophil/lymphocyte ratio (NLR) of breast cancers was identified (ASCO 2018, e13094). As a follow-up, retrospective analysis of results from comprehensive genomic profiling (CGP) of right and left side breast cancer specimens was performed to determine a potential genomic etiology for the observed NLR lateralization. Methods: Tumors from 43 consecutive breast cancer patients underwent analysis for all classes of genomic alterations by hybrid capture-based CGP (Foundation Medicine). The CGP results from the 25 left- and 18 right-sided breast cancer samples were analyzed along with the histologic grade and status of estrogen receptor (ER), progesterone receptor (PR), and HER2 expression. Results: In this cohort of advanced breast cancer patients (stage 3-4), no statistically significant differences in lateralization were identified based on patient age, tumor stage, or frequency of ER or Her2 expression (Table). A predominance of PR positivity (p=0.14 chi square analysis) and amplifications in the ERBB2 (p=0.37) and RAD21 (p=0.08) genes were detected in right side tumors. Conclusions: Together with the prior study, trends in asymmetry based on genomic, pathologic, and immunohistologic differences have been detected in breast cancers, including an increased incidence of ERBB2 and RAD21 amplification in right-side breast tumors in this cohort. The predominance of lower PR positivity in the left breast tumors may be due to preferential hypermethylation, consistent with reports that it mediates biologic lateralization changes, downregulates PR expression, and alters amplification rates. Epigenetic methylation, may contribute to asymmetric breast cancer biology and have implications for therapeutic strategy. Further study is warranted.[Table: see text]

Research on the Affective Factors of the High-Temperature Behavior of the Colored Asphalt Mixture Based on the Grey Relational

2012 ◽  
Vol 174-177 ◽  
pp. 127-130 ◽  
Author(s):  
Hong Wei Feng ◽  
Chun Han
Keyword(s):  
High Temperature ◽  
Asphalt Mixture ◽  
Temperature Behavior ◽  
Grey Relation Analysis ◽  
Affective Factors ◽  
High Temperature Behavior ◽  
Research Findings ◽  
Grey Relational ◽  
Negative Factors ◽  
Grey Relation

The negative factors of the colored asphalt mixture extremely correlate to its high-temperature behavior. With the Grey Relation Analysis, this paper makes a thorough analysis of the affective factors on the high-temperature behavior of the colored asphalt mixture, the result of which shows that the affective factors can be classified as the softening point of colored asphalt and the aggregate ratio of mixture. The research findings will provide a beneficial reference for the design of colored asphalt mixture.

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