应用数学(英文)最新文献

Determination of Statistical Properties of Microtubule Populations. 微管种群统计特性的测定。

应用数学(英文) Pub Date : 2016-08-01 Epub Date: 2016-08-15 DOI: 10.4236/am.2016.713125

Tyson DiLorenzo, Lee Ligon, Donald Drew

{"title":"Determination of Statistical Properties of Microtubule Populations.","authors":"Tyson DiLorenzo, Lee Ligon, Donald Drew","doi":"10.4236/am.2016.713125","DOIUrl":"https://doi.org/10.4236/am.2016.713125","url":null,"abstract":"Microtubules are structures within the cell that form a transportation network along which motor proteins tow cargo to destinations. To establish and maintain a structure capable of serving the cell's tasks, microtubules undergo deconstruction and reconstruction regularly. This change in structure is critical to tasks like wound repair and cell motility. Images of fluorescing microtubule networks are captured in grayscale at different wavelengths, displaying different tagged proteins. The analysis of these polymeric structures involves identifying the presence of the protein and the direction of the structure in which it resides. This study considers the problem of finding statistical properties of sections of microtubules. We consider the research done on directional filters and utilize a basic solution to find the center of a ridge. The method processes the captured image by centering a circle around pre-determined pixel locations so that the highest possible average pixel intensity is found within the circle, thus marking the center of the microtubule. The location of these centers allows us to estimate angular direction and curvature of the microtubules, statistically estimate the direction of microtubules in a region of the cell, and compare properties of different types of microtubule networks in the same region. To verify accuracy, we study the results of the method on a test image.","PeriodicalId":64940,"journal":{"name":"应用数学(英文)","volume":"7 13","pages":"1456-1475"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528678/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36993236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fraction of Missing Information (γ) at Different Missing Data Fractions in the 2012 NAMCS Physician Workflow Mail Survey. 2012年NAMCS医师工作流程邮件调查中不同缺失数据部分的缺失信息比例(γ)

应用数学(英文) Pub Date : 2016-06-01 Epub Date: 2016-06-15 DOI: 10.4236/am.2016.710093

Qiyuan Pan, Rong Wei

{"title":"Fraction of Missing Information (γ) at Different Missing Data Fractions in the 2012 NAMCS Physician Workflow Mail Survey.","authors":"Qiyuan Pan, Rong Wei","doi":"10.4236/am.2016.710093","DOIUrl":"https://doi.org/10.4236/am.2016.710093","url":null,"abstract":"In his 1987 classic book on multiple imputation (MI), Rubin used the fraction of missing information, γ, to define the relative efficiency (RE) of MI as RE = (1 + γ/m)-1/2, where m is the number of imputations, leading to the conclusion that a small m (≤5) would be sufficient for MI. However, evidence has been accumulating that many more imputations are needed. Why would the apparently sufficient m deduced from the RE be actually too small? The answer may lie with γ. In this research, γ was determined at the fractions of missing data (δ) of 4%, 10%, 20%, and 29% using the 2012 Physician Workflow Mail Survey of the National Ambulatory Medical Care Survey (NAMCS). The γ values were strikingly small, ranging in the order of 10-6 to 0.01. As δ increased, γ usually increased but sometimes decreased. How the data were analysed had the dominating effects on γ, overshadowing the effect of δ. The results suggest that it is impossible to predict γ using δ and that it may not be appropriate to use the γ-based RE to determine sufficient m.","PeriodicalId":64940,"journal":{"name":"应用数学(英文)","volume":"7 10","pages":"1057-1067"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934387/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34653832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Determining Sufficient Number of Imputations Using Variance of Imputation Variances: Data from 2012 NAMCS Physician Workflow Mail Survey. 利用方差的方差确定足够数量的Imputation:来自2012年NAMCS医师工作流程邮件调查的数据。

应用数学(英文) Pub Date : 2014-12-01 DOI: 10.4236/am.2014.521319

Qiyuan Pan, Rong Wei, Iris Shimizu, Eric Jamoom

引用次数: 3

Automated Cell Detection and Morphometry on Growth Plate Images of Mouse Bone. 小鼠骨生长板图像的自动细胞检测和形态测定。

应用数学(英文) Pub Date : 2014-10-01 DOI: 10.4236/am.2014.518273

Maria-Grazia Ascenzi, Xia Du, James I Harding, Emily N Beylerian, Brian M de Silva, Ben J Gross, Hannah K Kastein, Weiguang Wang, Karen M Lyons, Hayden Schaeffer

{"title":"Automated Cell Detection and Morphometry on Growth Plate Images of Mouse Bone.","authors":"Maria-Grazia Ascenzi, Xia Du, James I Harding, Emily N Beylerian, Brian M de Silva, Ben J Gross, Hannah K Kastein, Weiguang Wang, Karen M Lyons, Hayden Schaeffer","doi":"10.4236/am.2014.518273","DOIUrl":"https://doi.org/10.4236/am.2014.518273","url":null,"abstract":"Microscopy imaging of mouse growth plates is extensively used in biology to understand the effect of specific molecules on various stages of normal bone development and on bone disease. Until now, such image analysis has been conducted by manual detection. In fact, when existing automated detection techniques were applied, morphological variations across the growth plate and heterogeneity of image background color, including the faint presence of cells (chondrocytes) located deeper in tissue away from the image's plane of focus, and lack of cell-specific features, interfered with identification of cell. We propose the first method of automated detection and morphometry applicable to images of cells in the growth plate of long bone. Through ad hoc sequential application of the Retinex method, anisotropic diffusion and thresholding, our new cell detection algorithm (CDA) addresses these challenges on bright-field microscopy images of mouse growth plates. Five parameters, chosen by the user in respect of image characteristics, regulate our CDA. Our results demonstrate effectiveness of the proposed numerical method relative to manual methods. Our CDA confirms previously established results regarding chondrocytes' number, area, orientation, height and shape of normal growth plates. Our CDA also confirms differences previously found between the genetic mutated mouse Smad1/5CKO and its control mouse on fluorescence images. The CDA aims to aid biomedical research by increasing efficiency and consistency of data collection regarding arrangement and characteristics of chondrocytes. Our results suggest that automated extraction of data from microscopy imaging of growth plates can assist in unlocking information on normal and pathological development, key to the underlying biological mechanisms of bone growth.","PeriodicalId":64940,"journal":{"name":"应用数学(英文)","volume":"5 18","pages":"2866-2880"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267696/pdf/nihms617421.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32921143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

The Effect of Ligament Modeling Technique on Knee Joint Kinematics: A Finite Element Study. 韧带建模技术对膝关节运动学影响的有限元研究。

应用数学(英文) Pub Date : 2014-05-01 DOI: 10.4236/am.2013.45A011

Ata M Kiapour, Vikas Kaul, Ali Kiapour, Carmen E Quatman, Samuel C Wordeman, Timothy E Hewett, Constantine K Demetropoulos, Vijay K Goel

{"title":"The Effect of Ligament Modeling Technique on Knee Joint Kinematics: A Finite Element Study.","authors":"Ata M Kiapour, Vikas Kaul, Ali Kiapour, Carmen E Quatman, Samuel C Wordeman, Timothy E Hewett, Constantine K Demetropoulos, Vijay K Goel","doi":"10.4236/am.2013.45A011","DOIUrl":"https://doi.org/10.4236/am.2013.45A011","url":null,"abstract":"Finite element (FE) analysis has become an increasingly popular technique in the study of human joint biomechanics, as it allows for detailed analysis of the joint/tissue behavior under complex, clinically relevant loading conditions. A wide variety of modeling techniques have been utilized to model knee joint ligaments. However, the effect of a selected constitutive model to simulate the ligaments on knee kinematics remains unclear. The purpose of the current study was to determine the effect of two most common techniques utilized to model knee ligaments on joint kinematics under functional loading conditions. We hypothesized that anatomic representations of the knee ligaments with anisotropic hyperelastic properties will result in more realistic kinematics. A previously developed, extensively validated anatomic FE model of the knee developed from a healthy, young female athlete was used. FE models with 3D anatomic and simplified uniaxial representations of main knee ligaments were used to simulate four functional loading conditions. Model predictions of tibiofemoral joint kinematics were compared to experimental measures. Results demonstrated the ability of the anatomic representation of the knee ligaments (3D geometry along with anisotropic hyperelastic material) in more physiologic prediction of the human knee motion with strong correlation (r ≥ 0.9 for all comparisons) and minimum deviation (0.9º ≤ RMSE ≤ 2.29°) from experimental findings. In contrast, non-physiologic uniaxial elastic representation of the ligaments resulted in lower correlations (r ≤ 0.6 for all comparisons) and substantially higher deviation (2.6° ≤ RMSE ≤ 4.2°) from experimental results. Findings of the current study support our hypothesis and highlight the critical role of soft tissue modeling technique on the resultant FE predicted joint kinematics.","PeriodicalId":64940,"journal":{"name":"应用数学(英文)","volume":"4 5A","pages":"91-97"},"PeriodicalIF":0.0,"publicationDate":"2014-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4236/am.2013.45A011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32668658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 50

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains. 具有动态生长域的高性能肿瘤生长细胞自动机模型

应用数学(英文) Pub Date : 2014-01-01 DOI: 10.4236/am.2014.51017

Jan Poleszczuk, Heiko Enderling

引用次数: 0