Estimation of volumetric breast density for breast cancer risk prediction
Pawluczyk, Olga; Yaffe, Martin J.; Boyd, Norman F.; Jong, Roberta A.
2000-04-01
Mammographic density (MD) has been shown to be a strong risk predictor for breast cancer. Compared to subjective assessment by a radiologist, computer-aided analysis of digitized mammograms provides a quantitative and more reproducible method for assessing breast density. However, the current methods of estimating breast density based on the area of bright signal in a mammogram do not reflect the true, volumetric quantity of dense tissue in the breast. A computerized method to estimate the amount of radiographically dense tissue in the overall volume of the breast has been developed to provide an automatic, user-independent tool for breast cancer risk assessment. The procedure for volumetric density estimation consists of first correcting the image for inhomogeneity, then performing a volume density calculation. First, optical sensitometry is used to convert all images to the logarithm of relative exposure (LRE), in order to simplify the image correction operations. The field non-uniformity correction, which takes into account heel effect, inverse square law, path obliquity and intrinsic field and grid non- uniformity is obtained by imaging a spherical section PMMA phantom. The processed LRE image of the phantom is then used as a correction offset for actual mammograms. From information about the thickness and placement of the breast, as well as the parameters of a breast-like calibration step wedge placed in the mammogram, MD of the breast is calculated. Post processing and a simple calibration phantom enable user- independent, reliable and repeatable volumetric estimation of density in breast-equivalent phantoms. Initial results obtained on known density phantoms show the estimation to vary less than 5% in MD from the actual value. This can be compared to estimated mammographic density differences of 30% between the true and non-corrected values. Since a more simplistic breast density measurement based on the projected area has been shown to be a strong indicator
Breast density estimation from high spectral and spatial resolution MRI.
Li, Hui; Weiss, William A; Medved, Milica; Abe, Hiroyuki; Newstead, Gillian M; Karczmar, Gregory S; Giger, Maryellen L
2016-10-01
A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists' breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 ([Formula: see text]) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 ([Formula: see text]) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 ([Formula: see text]) was observed between HiSS-based breast density estimations and radiologists' BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy.
Mammography density estimation with automated volumetic breast density measurement
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Ko, Su Yeon; Kim, Eun Kyung; Kim, Min Jung; Moon, Hee Jung [Dept. of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul (Korea, Republic of)
2014-06-15
To compare automated volumetric breast density measurement (VBDM) with radiologists' evaluations based on the Breast Imaging Reporting and Data System (BI-RADS), and to identify the factors associated with technical failure of VBDM. In this study, 1129 women aged 19-82 years who underwent mammography from December 2011 to January 2012 were included. Breast density evaluations by radiologists based on BI-RADS and by VBDM (Volpara Version 1.5.1) were compared. The agreement in interpreting breast density between radiologists and VBDM was determined based on four density grades (D1, D2, D3, and D4) and a binary classification of fatty (D1-2) vs. dense (D3-4) breast using kappa statistics. The association between technical failure of VBDM and patient age, total breast volume, fibroglandular tissue volume, history of partial mastectomy, the frequency of mass > 3 cm, and breast density was analyzed. The agreement between breast density evaluations by radiologists and VBDM was fair (k value = 0.26) when the four density grades (D1/D2/D3/D4) were used and moderate (k value = 0.47) for the binary classification (D1-2/D3-4). Twenty-seven women (2.4%) showed failure of VBDM. Small total breast volume, history of partial mastectomy, and high breast density were significantly associated with technical failure of VBDM (p 0.001 to 0.015). There is fair or moderate agreement in breast density evaluation between radiologists and VBDM. Technical failure of VBDM may be related to small total breast volume, a history of partial mastectomy, and high breast density.
Volumetric breast density estimation from full-field digital mammograms.
Engeland, S. van; Snoeren, P.R.; Huisman, H.J.; Boetes, C.; Karssemeijer, N.
2006-01-01
A method is presented for estimation of dense breast tissue volume from mammograms obtained with full-field digital mammography (FFDM). The thickness of dense tissue mapping to a pixel is determined by using a physical model of image acquisition. This model is based on the assumption that the breast
X-Ray Methods to Estimate Breast Density Content in Breast Tissue
Maraghechi, Borna
This work focuses on analyzing x-ray methods to estimate the fat and fibroglandular contents in breast biopsies and in breasts. The knowledge of fat in the biopsies could aid in their wide-angle x-ray scatter analyses. A higher mammographic density (fibrous content) in breasts is an indicator of higher cancer risk. Simulations for 5 mm thick breast biopsies composed of fibrous, cancer, and fat and for 4.2 cm thick breast fat/fibrous phantoms were done. Data from experimental studies using plastic biopsies were analyzed. The 5 mm diameter 5 mm thick plastic samples consisted of layers of polycarbonate (lexan), polymethyl methacrylate (PMMA-lucite) and polyethylene (polyet). In terms of the total linear attenuation coefficients, lexan ≡ fibrous, lucite ≡ cancer and polyet ≡ fat. The detectors were of two types, photon counting (CdTe) and energy integrating (CCD). For biopsies, three photon counting methods were performed to estimate the fat (polyet) using simulation and experimental data, respectively. The two basis function method that assumed the biopsies were composed of two materials, fat and a 50:50 mixture of fibrous (lexan) and cancer (lucite) appears to be the most promising method. Discrepancies were observed between the results obtained via simulation and experiment. Potential causes are the spectrum and the attenuation coefficient values used for simulations. An energy integrating method was compared to the two basis function method using experimental and simulation data. A slight advantage was observed for photon counting whereas both detectors gave similar results for the 4.2 cm thick breast phantom simulations. The percentage of fibrous within a 9 cm diameter circular phantom of fibrous/fat tissue was estimated via a fan beam geometry simulation. Both methods yielded good results. Computed tomography (CT) images of the circular phantom were obtained using both detector types. The radon transforms were estimated via four energy integrating
Effect of compression paddle tilt correction on volumetric breast density estimation.
Kallenberg, Michiel G J; van Gils, Carla H; Lokate, Mariëtte; den Heeten, Gerard J; Karssemeijer, Nico
2012-08-21
For the acquisition of a mammogram, a breast is compressed between a compression paddle and a support table. When compression is applied with a flexible compression paddle, the upper plate may be tilted, which results in variation in breast thickness from the chest wall to the breast margin. Paddle tilt has been recognized as a major problem in volumetric breast density estimation methods. In previous work, we developed a fully automatic method to correct the image for the effect of compression paddle tilt. In this study, we investigated in three experiments the effect of paddle tilt and its correction on volumetric breast density estimation. Results showed that paddle tilt considerably affected accuracy of volumetric breast density estimation, but that effect could be reduced by tilt correction. By applying tilt correction, a significant increase in correspondence between mammographic density estimates and measurements on MRI was established. We argue that in volumetric breast density estimation, tilt correction is both feasible and essential when mammographic images are acquired with a flexible compression paddle.
2006-07-01
mammographic density: Implications for under- standing breast cancer,’’ J. Natl. Cancer Inst. 89, 531–532 ~1997!. 10 W. Leung, F. Goldberg, B. Zee ... Mexico . Radiology 1998;209:511–518. 4. Boyd NF, Byng RA, Jong EK, et al. Quantita- tive classification of mammographic densi- ties and breast cancer risk
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Khodr, Zeina G.; Pfeiffer, Ruth M.; Gierach, Gretchen L., E-mail: GierachG@mail.nih.gov [Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive MSC 9774, Bethesda, Maryland 20892 (United States); Sak, Mark A.; Bey-Knight, Lisa [Karmanos Cancer Institute, Wayne State University, 4100 John R, Detroit, Michigan 48201 (United States); Duric, Nebojsa; Littrup, Peter [Karmanos Cancer Institute, Wayne State University, 4100 John R, Detroit, Michigan 48201 and Delphinus Medical Technologies, 46701 Commerce Center Drive, Plymouth, Michigan 48170 (United States); Ali, Haythem; Vallieres, Patricia [Henry Ford Health System, 2799 W Grand Boulevard, Detroit, Michigan 48202 (United States); Sherman, Mark E. [Division of Cancer Prevention, National Cancer Institute, Department of Health and Human Services, 9609 Medical Center Drive MSC 9774, Bethesda, Maryland 20892 (United States)
2015-10-15
Purpose: High breast density, as measured by mammography, is associated with increased breast cancer risk, but standard methods of assessment have limitations including 2D representation of breast tissue, distortion due to breast compression, and use of ionizing radiation. Ultrasound tomography (UST) is a novel imaging method that averts these limitations and uses sound speed measures rather than x-ray imaging to estimate breast density. The authors evaluated the reproducibility of measures of speed of sound and changes in this parameter using UST. Methods: One experienced and five newly trained raters measured sound speed in serial UST scans for 22 women (two scans per person) to assess inter-rater reliability. Intrarater reliability was assessed for four raters. A random effects model was used to calculate the percent variation in sound speed and change in sound speed attributable to subject, scan, rater, and repeat reads. The authors estimated the intraclass correlation coefficients (ICCs) for these measures based on data from the authors’ experienced rater. Results: Median (range) time between baseline and follow-up UST scans was five (1–13) months. Contributions of factors to sound speed variance were differences between subjects (86.0%), baseline versus follow-up scans (7.5%), inter-rater evaluations (1.1%), and intrarater reproducibility (∼0%). When evaluating change in sound speed between scans, 2.7% and ∼0% of variation were attributed to inter- and intrarater variation, respectively. For the experienced rater’s repeat reads, agreement for sound speed was excellent (ICC = 93.4%) and for change in sound speed substantial (ICC = 70.4%), indicating very good reproducibility of these measures. Conclusions: UST provided highly reproducible sound speed measurements, which reflect breast density, suggesting that UST has utility in sensitively assessing change in density.
Comparing measurements of breast density
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Highnam, R [Highnam Associates Limited, Wellington (New Zealand); Jeffreys, M [Massey University, Wellington (New Zealand); McCormack, V [Department of Epidemiology and Population Health, London School of Hygiene and Medicine, London (United Kingdom); Warren, R [Addenbrooke' s Hospital, Cambridge (United Kingdom); Smith, G Davey [Department of Clinical Epidemiology, University of Bristol, Bristol (United Kingdom); Brady, M [Department of Engineering Science, University of Oxford, Oxford (United Kingdom)
2007-09-21
Breast density measurements can be made from mammograms using either area-based methods, such as the six category classification (SCC), or volumetric based methods, such as the standard mammogram form (SMF). Previously, we have shown how both types of methods generate breast density estimates which are generally close. In this paper, we switch our attention to the question of why, for certain cases, they provide widely differing estimates. First, we show how the underlying physical models of the breast employed in the methods need to be consistent, and how area-based methods are susceptible to projection effects. We then analyse a set of patients whose mammograms show large differences between their SCC and SMF assessments. More precisely, 12% of 657 patients were found to fall into this category. Of these, 2.7% were attributable to errors either in the SMF segmentation algorithms, human error in SCC categorization or poor image exposure. More importantly, 9.3% of the cases appear to be due to fundamental differences between the area- and volume-based techniques. We conclude by suggesting how we might remove half of those discrepancies by introducing a new categorization of the SMF estimates based on the breast thickness. We note however, that this still leaves 6% of patients with large differences between SMF and SCC estimates. We discuss why it might not be appropriate to assume SMF (or any volume measure) has a similar breast cancer risk prediction capability to SCC.
Effect of compression paddle tilt correction on volumetric breast density estimation
Kallenberg, M.G.J.; Gils, C.H. van; Lokate, M.; Heeten, G.J. den; Karssemeijer, N.
2012-01-01
For the acquisition of a mammogram, a breast is compressed between a compression paddle and a support table. When compression is applied with a flexible compression paddle, the upper plate may be tilted, which results in variation in breast thickness from the chest wall to the breast margin. Paddle
Imaging Breast Density: Established and Emerging Modalities
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Jeon-Hor Chen
2015-12-01
Full Text Available Mammographic density has been proven as an independent risk factor for breast cancer. Women with dense breast tissue visible on a mammogram have a much higher cancer risk than women with little density. A great research effort has been devoted to incorporate breast density into risk prediction models to better estimate each individual’s cancer risk. In recent years, the passage of breast density notification legislation in many states in USA requires that every mammography report should provide information regarding the patient’s breast density. Accurate definition and measurement of breast density are thus important, which may allow all the potential clinical applications of breast density to be implemented. Because the two-dimensional mammography-based measurement is subject to tissue overlapping and thus not able to provide volumetric information, there is an urgent need to develop reliable quantitative measurements of breast density. Various new imaging technologies are being developed. Among these new modalities, volumetric mammographic density methods and three-dimensional magnetic resonance imaging are the most well studied. Besides, emerging modalities, including different x-ray–based, optical imaging, and ultrasound-based methods, have also been investigated. All these modalities may either overcome some fundamental problems related to mammographic density or provide additional density and/or compositional information. The present review article aimed to summarize the current established and emerging imaging techniques for the measurement of breast density and the evidence of the clinical use of these density methods from the literature.
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Abbas Cheddad
Full Text Available INTRODUCTION: Mammographic density, the white radiolucent part of a mammogram, is a marker of breast cancer risk and mammographic sensitivity. There are several means of measuring mammographic density, among which are area-based and volumetric-based approaches. Current volumetric methods use only unprocessed, raw mammograms, which is a problematic restriction since such raw mammograms are normally not stored. We describe fully automated methods for measuring both area and volumetric mammographic density from processed images. METHODS: The data set used in this study comprises raw and processed images of the same view from 1462 women. We developed two algorithms for processed images, an automated area-based approach (CASAM-Area and a volumetric-based approach (CASAM-Vol. The latter method was based on training a random forest prediction model with image statistical features as predictors, against a volumetric measure, Volpara, for corresponding raw images. We contrast the three methods, CASAM-Area, CASAM-Vol and Volpara directly and in terms of association with breast cancer risk and a known genetic variant for mammographic density and breast cancer, rs10995190 in the gene ZNF365. Associations with breast cancer risk were evaluated using images from 47 breast cancer cases and 1011 control subjects. The genetic association analysis was based on 1011 control subjects. RESULTS: All three measures of mammographic density were associated with breast cancer risk and rs10995190 (p0.10 for risk, p>0.03 for rs10995190. CONCLUSIONS: Our results show that it is possible to obtain reliable automated measures of volumetric and area mammographic density from processed digital images. Area and volumetric measures of density on processed digital images performed similar in terms of risk and genetic association.
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Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.; Kontos, Despina, E-mail: despina.kontos@uphs.upenn.edu [Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States)
2013-12-15
Purpose: Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment. Methods: In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandular tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's pairedt-test, and Dice's similarity coefficients (DSC). Results: The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers’ manual segmentation, the proposed FCM-Atlas method achieves a
Association between Mammographic Breast Density and Lifestyle in Japanese Women
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Komoike,Yoshifumi
2013-06-01
Full Text Available A high mammographic breast density is considered to be a risk factor for breast cancer. However, only a small number of studies on the association between breast density and lifestyle have been performed. A cross-sectional study was performed using a survey with 29 questions on life history and lifestyle. The breast density on mammography was classified into 4 categories following the BI-RADS criteria. The subjects were 522 women with no medical history of breast cancer. The mean age was 53.3 years old. On multivariate analysis, only BMI was a significant factor determining breast density in premenopausal women (parameter estimate, －0.403;p value, 0.0005, and the density decreased as BMI rose. In postmenopausal women, BMI (parameter estimate, －0.196;p value, 0.0143 and number of deliveries (parameter estimate, －0.388;p value, 0.0186 were significant factors determining breast density;breast density decreased as BMI and number of deliveries increased. Only BMI and number of deliveries were identified as factors significantly influencing breast density. BMI was inversely correlated with breast density before and after menopause, whereas the influence of number of deliveries on breast density was significant only in postmenopausal women in their 50 and 60s.
Contingent kernel density estimation.
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Scott Fortmann-Roe
Full Text Available Kernel density estimation is a widely used method for estimating a distribution based on a sample of points drawn from that distribution. Generally, in practice some form of error contaminates the sample of observed points. Such error can be the result of imprecise measurements or observation bias. Often this error is negligible and may be disregarded in analysis. In cases where the error is non-negligible, estimation methods should be adjusted to reduce resulting bias. Several modifications of kernel density estimation have been developed to address specific forms of errors. One form of error that has not yet been addressed is the case where observations are nominally placed at the centers of areas from which the points are assumed to have been drawn, where these areas are of varying sizes. In this scenario, the bias arises because the size of the error can vary among points and some subset of points can be known to have smaller error than another subset or the form of the error may change among points. This paper proposes a "contingent kernel density estimation" technique to address this form of error. This new technique adjusts the standard kernel on a point-by-point basis in an adaptive response to changing structure and magnitude of error. In this paper, equations for our contingent kernel technique are derived, the technique is validated using numerical simulations, and an example using the geographic locations of social networking users is worked to demonstrate the utility of the method.
Postmortem validation of breast density using dual-energy mammography
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Molloi, Sabee, E-mail: symolloi@uci.edu; Ducote, Justin L.; Ding, Huanjun; Feig, Stephen A. [Department of Radiological Sciences, University of California, Irvine, California 92697 (United States)
2014-08-15
Purpose: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. Methods: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. Results: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. Conclusions: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer.
Endocrine determinants of breast density and breast cancer
Verheus, M.
2007-01-01
Worldwide, breast cancer is the most common malignancy among females. The total breast area on a mammogram can be dived in a radiologicaly dense area (glandular and stromal tissue) and a non-dense area (mainly fat tissue). Women with a high proportion of dense breast tissue (percent breast density)
A novel ultrasonic method for measuring breast density and breast cancer risk
Glide-Hurst, Carri K.; Duric, Neb; Littrup, Peter J.
2008-03-01
Women with high mammographic breast density are at 4- to 6-fold increased risk of developing breast cancer compared to women with fatty breasts. However, current breast density estimations rely on mammography, which cannot provide accurate volumetric breast representation. Therefore, we explored two techniques of breast density evaluation via ultrasound tomography. A sample of 93 patients was imaged with our clinical prototype; each dataset contained 45-75 tomograms ranging from near the chest wall through the nipple. Whole breast acoustic velocity was determined by creating image stacks and evaluating the sound speed frequency distribution. Ultrasound percent density (USPD) was determined by segmenting high sound speed areas from each tomogram using k-means clustering, integrating over the entire breast, and dividing by total breast area. Both techniques were independently evaluated using two mammographic density measures: (1) qualitative, determined by a radiologist's visual assessment using BI-RADS Categories, and (2) quantitative, via semi-automatic segmentation to calculate mammographic percent density (MPD) for craniocaudal and medio-lateral oblique mammograms. ~140 m/s difference in acoustic velocity was observed between fatty and dense BI-RADS Categories. Increased sound speed was found with increased BI-RADS Category and quantitative MPD. Furthermore, strong positive associations between USPD, BI-RADS Category, and calculated MPD were observed. These results confirm that utilizing sound speed, both for whole-breast evaluation and segmenting locally, can be implemented to evaluate breast density.
Mammographic Breast Density and Serum Phytoestrogen Levels
Lowry, Sarah J.; Sprague, Brian L; Bowles, Erin J. Aiello; Hedman, Curtis J.; Hemming, Jocelyn; Hampton, John M.; Burnside, Elizabeth S.; Sisney, Gale A.; Buist, Diana S. M.; Trentham-Dietz, Amy
2012-01-01
Some forms of estrogen are associated with breast cancer risk as well as with mammographic density (MD), a strong marker of breast cancer risk. Whether phytoestrogen intake affects breast density, however, remains unclear. We evaluated the association between serum levels of phytoestrogens and MD in postmenopausal women. We enrolled 269 women, ages 55–70 yr, who received a screening mammogram and had no history of postmenopausal hormone use. Subjects completed a survey on diet and factors rel...
Breast Density May Be Leading Indicator of Cancer Risk
... https://medlineplus.gov/news/fullstory_163386.html Breast Density May Be Leading Indicator of Cancer Risk Study ... on their study of 200,000 women, breast density may be the most important gauge of breast ...
Comparison of density estimators. [Estimation of probability density functions
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Kao, S.; Monahan, J.F.
1977-09-01
Recent work in the field of probability density estimation has included the introduction of some new methods, such as the polynomial and spline methods and the nearest neighbor method, and the study of asymptotic properties in depth. This earlier work is summarized here. In addition, the computational complexity of the various algorithms is analyzed, as are some simulations. The object is to compare the performance of the various methods in small samples and their sensitivity to change in their parameters, and to attempt to discover at what point a sample is so small that density estimation can no longer be worthwhile. (RWR)
Parallel Multiscale Autoregressive Density Estimation
Reed, Scott; Oord, Aäron van den; Kalchbrenner, Nal; Colmenarejo, Sergio Gómez; Wang, Ziyu; Belov, Dan; de Freitas, Nando
2017-01-01
PixelCNN achieves state-of-the-art results in density estimation for natural images. Although training is fast, inference is costly, requiring one network evaluation per pixel; O(N) for N pixels. This can be sped up by caching activations, but still involves generating each pixel sequentially. In this work, we propose a parallelized PixelCNN that allows more efficient inference by modeling certain pixel groups as conditionally independent. Our new PixelCNN model achieves competitive density e...
A Review of Segmentation of Mammographic Images Based on Breast Density
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Anusree Mohan
2015-03-01
Full Text Available Breast cancer is one of the leading causes of fatality in women. Mammogram is the effectual modality for early detection of breast cancer. Increased mammographic breast density is a moderate independent risk factor for breast cancer, Radiologists have estimated breast density using four broad categories (BI-RADS swearing on visual assessment of mammograms. The aim of this paper is to review approaches for segmentation of breast regions in mammograms according to breast density. Studies based on density have been undertaken because of the relationship between breast cancer and density. Breast cancer usually occurs in the fibroglandular area of breast tissue, which appears bright on mammograms and is described as breast density. Most of the studies are focused on the classification methods for glandular tissue detection. Others highlighted on the segmentation methods for fibroglandular tissue, while few researchers performed segmentation of the breast anatomical regions based on density. There have also been works on the segmentation of other specific parts of breast regions such as either detection of nipple position, skin-air interface or pectoral muscles. The problems on the evaluation performance of the segmentation results in relation to ground truth are also discussed in this paper.
Cumulative sum quality control for calibrated breast density measurements
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Heine, John J.; Cao Ke; Beam, Craig [Cancer Prevention and Control Division, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, Florida 33612 (United States); Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, 1603 W. Taylor St., Chicago, Illinois 60612 (United States)
2009-12-15
Purpose: Breast density is a significant breast cancer risk factor. Although various methods are used to estimate breast density, there is no standard measurement for this important factor. The authors are developing a breast density standardization method for use in full field digital mammography (FFDM). The approach calibrates for interpatient acquisition technique differences. The calibration produces a normalized breast density pixel value scale. The method relies on first generating a baseline (BL) calibration dataset, which required extensive phantom imaging. Standardizing prospective mammograms with calibration data generated in the past could introduce unanticipated error in the standardized output if the calibration dataset is no longer valid. Methods: Sample points from the BL calibration dataset were imaged approximately biweekly over an extended timeframe. These serial samples were used to evaluate the BL dataset reproducibility and quantify the serial calibration accuracy. The cumulative sum (Cusum) quality control method was used to evaluate the serial sampling. Results: There is considerable drift in the serial sample points from the BL calibration dataset that is x-ray beam dependent. Systematic deviation from the BL dataset caused significant calibration errors. This system drift was not captured with routine system quality control measures. Cusum analysis indicated that the drift is a sign of system wear and eventual x-ray tube failure. Conclusions: The BL calibration dataset must be monitored and periodically updated, when necessary, to account for sustained system variations to maintain the calibration accuracy.
Physical activity and mammographic breast density: a systematic review
Yaghjyan, Lusine; Colditz, Graham A.; Wolin, Kathleen
2012-01-01
Studies show a protective relationship between physical activity and breast cancer risk across the life course from menarche to postmenopausal years. Mammographic breast density is a known and strong breast cancer risk factor. Whether the association of physical activity with breast cancer risk is mediated through mammographic breast density is poorly understood. This systematic review summarizes published studies that investigated the association between physical activity and mammographic br...
Changes in mammographic density and breast cancer risk
Lokate, A.J.M.
2012-01-01
Breast cancer is the most frequently occurring cancer among women worldwide. One of the most important risk factors for breast cancer is high mammographic density. Mammographic density represents the amount of fibroglandular tissue relative to the fat tissue in the breast. Women with >75% of their b
Breast Cancer Risk Estimation Using Parenchymal Texture Analysis in Digital Breast Tomosynthesis
Ikejimba, Lynda C.; Kontos, Despina; Maidment, Andrew D. A.
2010-10-01
Mammographic parenchymal texture has been shown to correlate with genetic markers of developing breast cancer. Digital breast tomosynthesis (DBT) is a novel x-ray imaging technique in which tomographic images of the breast are reconstructed from multiple source projections acquired at different angles of the x-ray tube. Compared to digital mammography (DM), DBT eliminates breast tissue overlap, offering superior parenchymal tissue visualization. We hypothesize that texture analysis in DBT could potentially provide a better assessment of parenchymal texture and ultimately result in more accurate assessment of breast cancer risk. As a first step towards validating this hypothesis, we investigated the association between DBT parenchymal texture and breast percent density (PD), a known breast cancer risk factor, and compared it to DM. Bilateral DBT and DM images from 71 women participating in a breast cancer screening trial were analyzed. Filtered-backprojection was used to reconstruct DBT tomographic planes in 1 mm increments with 0.22 mm in-plane resolution. Corresponding DM images were acquired at 0.1 mm pixel resolution. Retroareolar regions of interest (ROIs) equivalent to 2.5 cm3 were segmented from the DBT images and corresponding 2.5 cm2 ROIs were segmented from the DM images. Breast PD was mammographically estimated using the Cumulus scale. Overall, DBT texture features demonstrated a stronger correlation than DM to PD. The Pearson correlation coefficients for DBT were r = 0.40 (pbreast cancer risk assessment in the future.
Mammographic Breast Density and Common Genetic Variants in Breast Cancer Risk Prediction.
Directory of Open Access Journals (Sweden)
Charmaine Pei Ling Lee
Full Text Available Known prediction models for breast cancer can potentially by improved by the addition of mammographic density and common genetic variants identified in genome-wide associations studies known to be associated with risk of the disease. We evaluated the benefit of including mammographic density and the cumulative effect of genetic variants in breast cancer risk prediction among women in a Singapore population.We estimated the risk of breast cancer using a prospective cohort of 24,161 women aged 50 to 64 from Singapore with available mammograms and known risk factors for breast cancer who were recruited between 1994 and 1997. We measured mammographic density using the medio-lateral oblique views of both breasts. Each woman's genotype for 75 SNPs was simulated based on the genotype frequency obtained from the Breast Cancer Association Consortium data and the cumulative effect was summarized by a genetic risk score (GRS. Any improvement in the performance of our proposed prediction model versus one containing only variables from the Gail model was assessed by changes in receiver-operating characteristic and predictive values.During 17 years of follow-up, 680 breast cancer cases were diagnosed. The multivariate-adjusted hazard ratios (95% confidence intervals were 1.60 (1.22-2.10, 2.20 (1.65-2.92, 2.33 (1.71-3.20, 2.12 (1.43-3.14, and 3.27 (2.24-4.76 for the corresponding mammographic density categories: 11-20cm2, 21-30cm2, 31-40cm2, 41-50cm2, 51-60cm2, and 1.10 (1.03-1.16 for GRS. At the predicted absolute 10-year risk thresholds of 2.5% and 3.0%, a model with mammographic density and GRS could correctly identify 0.9% and 0.5% more women who would develop the disease compared to a model using only the Gail variables, respectively.Mammographic density and common genetic variants can improve the discriminatory power of an established breast cancer risk prediction model among females in Singapore.
Diffuse optical tomography with structured-light patterns to quantify breast density
Kwong, Jessica; Nouizi, Farouk; Cho, Jaedu; Zheng, Jie; Li, Yifan; Chen, Jeon-hor; Su, Min-Ying; Gulsen, Gultekin
2016-02-01
Breast density is an independent risk factor for breast cancer, where women with denser breasts are more likely to develop cancer. By identifying women at higher risk, healthcare providers can suggest screening at a younger age to effectively diagnose and treat breast cancer in its earlier stages. Clinical risk assessment models currently do not incorporate breast density, despite its strong correlation with breast cancer. Current methods to measure breast density rely on mammography and MRI, both of which may be difficult to use as a routine risk assessment tool. We propose to use diffuse optical tomography with structured-light to measure the dense, fibroglandular (FGT) tissue volume, which has a different chromophore signature than the surrounding adipose tissue. To test the ability of this technique, we performed simulations by creating numerical breast phantoms from segmented breast MR images. We looked at two different cases, one with a centralized FGT distribution and one with a dispersed distribution. As expected, the water and lipid volumes segmented at half-maximum were overestimated for the dispersed case. However, it was noticed that the recovered water and lipid concentrations were lower and higher, respectively, than the centralized case. This information may provide insight into the morphological distribution of the FGT and can be a correction in estimating the breast density.
Vision 20/20: Mammographic breast density and its clinical applications
Energy Technology Data Exchange (ETDEWEB)
Ng, Kwan-Hoong, E-mail: ngkh@ummc.edu.my; Lau, Susie [Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur (Malaysia)
2015-12-15
Breast density is a strong predictor of the failure of mammography screening to detect breast cancer and is a strong predictor of the risk of developing breast cancer. The many imaging options that are now available for imaging dense breasts show great promise, but there is still the question of determining which women are “dense” and what imaging modality is suitable for individual women. To date, mammographic breast density has been classified according to the Breast Imaging-Reporting and Data System (BI-RADS) categories from visual assessment, but this is known to be very subjective. Despite many research reports, the authors believe there has been a lack of physics-led and evidence-based arguments about what breast density actually is, how it should be measured, and how it should be used. In this paper, the authors attempt to start correcting this situation by reviewing the history of breast density research and the debates generated by the advocacy movement. The authors review the development of breast density estimation from pattern analysis to area-based analysis, and the current automated volumetric breast density (VBD) analysis. This is followed by a discussion on seeking the ground truth of VBD and mapping volumetric methods to BI-RADS density categories. The authors expect great improvement in VBD measurements that will satisfy the needs of radiologists, epidemiologists, surgeons, and physicists. The authors believe that they are now witnessing a paradigm shift toward personalized breast screening, which is going to see many more cancers being detected early, with the use of automated density measurement tools as an important component.
Varying kernel density estimation on ℝ+
Mnatsakanov, Robert; Sarkisian, Khachatur
2015-01-01
In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is proposed. This method is natural when estimating an unknown density function of a positive random variable. The rates of Mean Squared Error, Mean Integrated Squared Error, and the L1-consistency are investigated. Simulation studies are conducted to compare a new estimator and its modified version with traditional kernel density construction. PMID:26740729
Density Estimation Trees in High Energy Physics
Anderlini, Lucio
2015-01-01
Density Estimation Trees can play an important role in exploratory data analysis for multidimensional, multi-modal data models of large samples. I briefly discuss the algorithm, a self-optimization technique based on kernel density estimation, and some applications in High Energy Physics.
Yaghjyan, Lusine; Colditz, Graham A; Rosner, Bernard; Tamimi, Rulla M
2015-02-01
We investigated if associations of breast density and breast cancer differ according to the level of other known breast cancer risk factors, including body mass index (BMI), age at menarche, parity, age at first child's birth, age at menopause, alcohol consumption, a family history of breast cancer, a history of benign breast disease, and physical activity. This study included 1,044 postmenopausal incident breast cancer cases diagnosed within the Nurses' Health Study cohort and 1,794 matched controls. Percent breast density, absolute dense, and non-dense areas were measured from digitized film images with computerized techniques. Information on breast cancer risk factors was obtained prospectively from biennial questionnaires. Percent breast density was more strongly associated with breast cancer risk in current postmenopausal hormone users (≥50 vs. 10 %: OR 5.34, 95 % CI 3.36-8.49) as compared to women with past (OR 2.69, 95 % CI 1.32-5.49) or no hormone history (OR 2.57, 95 % CI 1.18-5.60, p-interaction = 0.03). Non-dense area was inversely associated with breast cancer risk in parous women, but not in women without children (p-interaction = 0.03). Associations of density with breast cancer risk did not differ by the levels of BMI, age at menarche, parity, age at first child's birth, age at menopause, alcohol consumption, a family history of breast cancer, a history of benign breast disease, and physical activity. Women with dense breasts, who currently use menopausal hormone therapy are at a particularly high risk of breast cancer. Most breast cancer risk factors do not modify the association between mammographic breast density and breast cancer risk.
Breast density changes associated with postmenopausal hormone replacement therapy
DEFF Research Database (Denmark)
Nielsen, Mads; Pettersen, Paola; Alexandersen, P
2010-01-01
Objective: The aim of this study was to assess the impact of oral hormone therapy (HT) on breast density in postmenopausal women and to compare the use of computer-based automated approaches for the assessment of breast density with reference to traditional methods. Methods: Low-dose oral estrogen...... (1 mg) continuously combined with drospirenone (2 mg) was administered to postmenopausal women for up to 2 years (26 treatment cycles, 28 d/cycle) in a randomized, placebo-controlled trial. This post hoc analysis assessed the changes in breast density measured from digitized images by two radiologist.......01) but not in the placebo group. Conclusions: HT for 2 years in postmenopausal women significantly increased radiologist-assessed breast density compared with placebo, in addition to significant changes in estrogen levels, markers of bone metabolism, and bone mineral density. Computer-automated techniques may be comparable...
Chen, Jeon-Hor; Lee, Yan-Wei; Chan, Si-Wa; Yeh, Dah-Cherng; Chang, Ruey-Feng
2016-05-01
In this study, a semi-automatic breast segmentation method was proposed on the basis of the rib shadow to extract breast regions from 3-D automated whole-breast ultrasound (ABUS) images. The density results were correlated with breast density values acquired with 3-D magnetic resonance imaging (MRI). MRI images of 46 breasts were collected from 23 women without a history of breast disease. Each subject also underwent ABUS. We used Otsu's thresholding method on ABUS images to obtain local rib shadow information, which was combined with the global rib shadow information (extracted from all slice projections) and integrated with the anatomy's breast tissue structure to determine the chest wall line. The fuzzy C-means classifier was used to extract the fibroglandular tissues from the acquired images. Whole-breast volume (WBV) and breast percentage density (BPD) were calculated in both modalities. Linear regression was used to compute the correlation of density results between the two modalities. The consistency of density measurement was also analyzed on the basis of intra- and inter-operator variation. There was a high correlation of density results between MRI and ABUS (R(2) = 0.798 for WBV, R(2) = 0.825 for PBD). The mean WBV from ABUS images was slightly smaller than the mean WBV from MR images (MRI: 342.24 ± 128.08 cm(3), ABUS: 325.47 ± 136.16 cm(3), p MRI: 24.71 ± 15.16%, ABUS: 28.90 ± 17.73%, p breast density measurement variation between the two modalities. Our results revealed a high correlation in WBV and BPD between MRI and ABUS. Our study suggests that ABUS provides breast density information useful in the assessment of breast health.
Breast density and outcome of mammography screening: a cohort study
DEFF Research Database (Denmark)
Olsen, A H; Bihrmann, K; Jensen, M-B
2009-01-01
The purpose of this study was to investigate the effect of breast density on breast cancer (BC) mortality in a mammography screening programme. The cohort included 48 052 women participating in mammography screening in Copenhagen, Denmark, where biennial screening is offered to women aged 50...
Parametric Return Density Estimation for Reinforcement Learning
Morimura, Tetsuro; Kashima, Hisashi; Hachiya, Hirotaka; Tanaka, Toshiyuki
2012-01-01
Most conventional Reinforcement Learning (RL) algorithms aim to optimize decision- making rules in terms of the expected re- turns. However, especially for risk man- agement purposes, other risk-sensitive crite- ria such as the value-at-risk or the expected shortfall are sometimes preferred in real ap- plications. Here, we describe a parametric method for estimating density of the returns, which allows us to handle various criteria in a unified manner. We first extend the Bellman equation for the conditional expected return to cover a conditional probability density of the returns. Then we derive an extension of the TD-learning algorithm for estimating the return densities in an unknown environment. As test instances, several parametric density estimation algorithms are presented for the Gaussian, Laplace, and skewed Laplace dis- tributions. We show that these algorithms lead to risk-sensitive as well as robust RL paradigms through numerical experiments.
Estimating stellar mean density through seismic inversions
Reese, D R; Goupil, M J; Thompson, M J; Deheuvels, S
2012-01-01
Determining the mass of stars is crucial both to improving stellar evolution theory and to characterising exoplanetary systems. Asteroseismology offers a promising way to estimate stellar mean density. When combined with accurate radii determinations, such as is expected from GAIA, this yields accurate stellar masses. The main difficulty is finding the best way to extract the mean density from a set of observed frequencies. We seek to establish a new method for estimating stellar mean density, which combines the simplicity of a scaling law while providing the accuracy of an inversion technique. We provide a framework in which to construct and evaluate kernel-based linear inversions which yield directly the mean density of a star. We then describe three different inversion techniques (SOLA and two scaling laws) and apply them to the sun, several test cases and three stars. The SOLA approach and the scaling law based on the surface correcting technique described by Kjeldsen et al. (2008) yield comparable result...
Assessment of two mammographic density related features in predicting near-term breast cancer risk
Zheng, Bin; Sumkin, Jules H.; Zuley, Margarita L.; Wang, Xingwei; Klym, Amy H.; Gur, David
2012-02-01
In order to establish a personalized breast cancer screening program, it is important to develop risk models that have high discriminatory power in predicting the likelihood of a woman developing an imaging detectable breast cancer in near-term (e.g., breast cancer risk models, mammographic density is considered the second highest breast cancer risk factor (second to woman's age). In this study we explored a new feature, namely bilateral mammographic density asymmetry, and investigated the feasibility of predicting near-term screening outcome. The database consisted of 343 negative examinations, of which 187 depicted cancers that were detected during the subsequent screening examination and 155 that remained negative. We computed the average pixel value of the segmented breast areas depicted on each cranio-caudal view of the initial negative examinations. We then computed the mean and difference mammographic density for paired bilateral images. Using woman's age, subjectively rated density (BIRADS), and computed mammographic density related features we compared classification performance in estimating the likelihood of detecting cancer during the subsequent examination using areas under the ROC curves (AUC). The AUCs were 0.63+/-0.03, 0.54+/-0.04, 0.57+/-0.03, 0.68+/-0.03 when using woman's age, BIRADS rating, computed mean density and difference in computed bilateral mammographic density, respectively. Performance increased to 0.62+/-0.03 and 0.72+/-0.03 when we fused mean and difference in density with woman's age. The results suggest that, in this study, bilateral mammographic tissue density is a significantly stronger (p<0.01) risk indicator than both woman's age and mean breast density.
Houssami, Nehmat; Turner, Robin M
2016-12-01
High breast tissue density increases breast cancer (BC) risk, and the risk of an interval BC in mammography screening. Density-tailored screening has mostly used adjunct imaging to screen women with dense breasts, however, the emergence of tomosynthesis (3D-mammography) provides an opportunity to steer density-tailored screening in new directions potentially obviating the need for adjunct imaging. A rapid review (a streamlined evidence synthesis) was performed to summarise data on tomosynthesis screening in women with heterogeneously dense or extremely dense breasts, with the aim of estimating incremental (additional) BC detection attributed to tomosynthesis in comparison with standard 2D-mammography. Meta-analysed data from prospective trials comparing these mammography modalities in the same women (N = 10,188) in predominantly biennial screening showed significant incremental BC detection of 3.9/1000 screens attributable to tomosynthesis (P mammography (N = 177,814) yielded a pooled difference in BC detection of 1.4/1000 screens representing significantly higher BC detection in tomosynthesis-screened women (P mammography. These estimates can inform planning of future trials of density-tailored screening and may guide discussion of screening women with dense breasts.
Particle Size Estimation Based on Edge Density
Institute of Scientific and Technical Information of China (English)
WANG Wei-xing
2005-01-01
Given image sequences of closely packed particles, the underlying aim is to estimate diameters without explicit segmentation. In a way, this is similar to the task of counting objects without directly counting them. Such calculations may, for example, be useful fast estimation of particle size in different application areas. The topic is that of estimating average size (=average diameter) of packed particles, from formulas involving edge density, and the edges from moment-based thresholding are used. An average shape factor is involved in the calculations, obtained for some frames from crude partial segmentation. Measurement results from about 80 frames have been analyzed.
Implementation of several mathematical algorithms to breast tissue density classification
Quintana, C.; Redondo, M.; Tirao, G.
2014-02-01
The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.
Directory of Open Access Journals (Sweden)
Hori,Keisuke
2013-08-01
Full Text Available A relatively large number of women in their 40s with high-density breasts, in which it can be difficult to detect lesions, are encountered in mammography cancer screenings in Japan. Here, we retrospectively investigated factors related to breast density. Two hundred women (40-49 years old were examined at the screening center in our hospital. Multivariate analysis showed that factors such as small abdominal circumference, high HDL cholesterol, and no history of childbirth were related to high breast density in women in their 40s undergoing mammography. Other non-mammographic screening methods should be considered in women with abdominal circumferences ＜76cm, HDL-C >53mg/dl, and no history of childbirth, as there is a strong possibility of these women having high-density breasts that can make lesion detection difficult.
Anisotropic Density Estimation in Global Illumination
DEFF Research Database (Denmark)
Schjøth, Lars
2009-01-01
Density estimation employed in multi-pass global illumination algorithms gives cause to a trade-off problem between bias and noise. The problem is seen most evident as blurring of strong illumination features. This thesis addresses the problem, presenting four methods that reduce both noise...... and bias in estimates. Good results are obtained by the use of anisotropic filtering. Two methods handles the most common cases; filtering illumination reflected from object surfaces. One methods extends filtering to the temporal domain and one performs filtering on illumination from participating media...
Reproductive factors related to childbearing and mammographic breast density.
Yaghjyan, Lusine; Colditz, Graham A; Rosner, Bernard; Bertrand, Kimberly A; Tamimi, Rulla M
2016-07-01
We investigated the associations of reproductive factors related to childbearing with percent breast density, absolute dense and nondense areas, by menopausal status. This study included 4110 cancer-free women within the Nurses' Health Study and Nurses' Health Study II cohorts. Percent breast density, absolute dense and nondense areas were measured from digitized mammography film images with computerized techniques. All density measures were square root-transformed in all the analyses to improve normality. The data on reproductive variables and other breast cancer risk factors were obtained from biennial questionnaires, at the time of the mammogram date. As compared to nulliparous women, parous postmenopausal women had lower percent density (β = -0.60, 95 % CI -0.84; -0.37), smaller absolute dense area (β = -0.66, 95 % CI -1.03; -0.29), and greater nondense area (β = 0.72, 95 % CI 0.27; 1.16). Among parous women, number of children was inversely associated with percent density in pre- (β per one child = -0.12, 95 % CI -0.20; -0.05) and postmenopausal women (β per one child = -0.07, 95 % CI -0.12; -0.02). The positive associations of breastfeeding with absolute dense and nondense areas were limited to premenopausal women, while the positive association of the age at first child's birth with percent density and the inverse association with nondense area were limited to postmenopausal women. Women with greater number of children and younger age at first child's birth have more favorable breast density patterns that could explain subsequent breast cancer risk reduction.
Bird population density estimated from acoustic signals
Dawson, D.K.; Efford, M.G.
2009-01-01
Many animal species are detected primarily by sound. Although songs, calls and other sounds are often used for population assessment, as in bird point counts and hydrophone surveys of cetaceans, there are few rigorous methods for estimating population density from acoustic data. 2. The problem has several parts - distinguishing individuals, adjusting for individuals that are missed, and adjusting for the area sampled. Spatially explicit capture-recapture (SECR) is a statistical methodology that addresses jointly the second and third parts of the problem. We have extended SECR to use uncalibrated information from acoustic signals on the distance to each source. 3. We applied this extension of SECR to data from an acoustic survey of ovenbird Seiurus aurocapilla density in an eastern US deciduous forest with multiple four-microphone arrays. We modelled average power from spectrograms of ovenbird songs measured within a window of 0??7 s duration and frequencies between 4200 and 5200 Hz. 4. The resulting estimates of the density of singing males (0??19 ha -1 SE 0??03 ha-1) were consistent with estimates of the adult male population density from mist-netting (0??36 ha-1 SE 0??12 ha-1). The fitted model predicts sound attenuation of 0??11 dB m-1 (SE 0??01 dB m-1) in excess of losses from spherical spreading. 5.Synthesis and applications. Our method for estimating animal population density from acoustic signals fills a gap in the census methods available for visually cryptic but vocal taxa, including many species of bird and cetacean. The necessary equipment is simple and readily available; as few as two microphones may provide adequate estimates, given spatial replication. The method requires that individuals detected at the same place are acoustically distinguishable and all individuals vocalize during the recording interval, or that the per capita rate of vocalization is known. We believe these requirements can be met, with suitable field methods, for a significant
Breast cancer research output, 1945-2008: a bibliometric and density-equalizing analysis
LENUS (Irish Health Repository)
Glynn, Ronan W
2010-12-22
Abstract Introduction Breast cancer is the most common form of cancer among women, with an estimated 194,280 new cases diagnosed in the United States in 2009 alone. The primary aim of this work was to provide an in-depth evaluation of research yield in breast cancer from 1945 to 2008, using large-scale data analysis, the employment of bibliometric indicators of production and quality, and density-equalizing mapping. Methods Data were retrieved from the Web of Science (WOS) Science Citation Expanded database; this was searched using the Boolean operator, \\'OR\\
Automated volumetric breast density derived by shape and appearance modeling
Malkov, Serghei; Kerlikowske, Karla; Shepherd, John
2014-03-01
The image shape and texture (appearance) estimation designed for facial recognition is a novel and promising approach for application in breast imaging. The purpose of this study was to apply a shape and appearance model to automatically estimate percent breast fibroglandular volume (%FGV) using digital mammograms. We built a shape and appearance model using 2000 full-field digital mammograms from the San Francisco Mammography Registry with known %FGV measured by single energy absorptiometry method. An affine transformation was used to remove rotation, translation and scale. Principal Component Analysis (PCA) was applied to extract significant and uncorrelated components of %FGV. To build an appearance model, we transformed the breast images into the mean texture image by piecewise linear image transformation. Using PCA the image pixels grey-scale values were converted into a reduced set of the shape and texture features. The stepwise regression with forward selection and backward elimination was used to estimate the outcome %FGV with shape and appearance features and other system parameters. The shape and appearance scores were found to correlate moderately to breast %FGV, dense tissue volume and actual breast volume, body mass index (BMI) and age. The highest Pearson correlation coefficient was equal 0.77 for the first shape PCA component and actual breast volume. The stepwise regression method with ten-fold cross-validation to predict %FGV from shape and appearance variables and other system outcome parameters generated a model with a correlation of r2 = 0.8. In conclusion, a shape and appearance model demonstrated excellent feasibility to extract variables useful for automatic %FGV estimation. Further exploring and testing of this approach is warranted.
Multivariate density estimation theory, practice, and visualization
Scott, David W
2015-01-01
David W. Scott, PhD, is Noah Harding Professor in the Department of Statistics at Rice University. The author of over 100 published articles, papers, and book chapters, Dr. Scott is also Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics. He is recipient of the ASA Founder's Award and the Army Wilks Award. His research interests include computational statistics, data visualization, and density estimation. Dr. Scott is also Coeditor of Wiley Interdisciplinary Reviews: Computational Statistics and previous Editor of the Journal of Computational and
Genetic Plymorphisms, Estrogens, and Breast Density
2005-01-01
and ovaries, did not ethnic backgrounds that applied to themselves and to their parents. use oral contraceptives or any hormone preparations at the...criteria for the 2 intervention studies, only 7 premeno- (p = 0.08). For premenopausal women, the difference in density pausal women were taking oral ...Kansas City, KS, USA ANTONIO LLOMBART-BOSCH Director, Departamento de Patologia Facultad de Medicina y Odontologia Universidad de Valencia Valencia
Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation.
Yamane, Ikko; Sasaki, Hiroaki; Sugiyama, Masashi
2016-07-01
Log-density gradient estimation is a fundamental statistical problem and possesses various practical applications such as clustering and measuring nongaussianity. A naive two-step approach of first estimating the density and then taking its log gradient is unreliable because an accurate density estimate does not necessarily lead to an accurate log-density gradient estimate. To cope with this problem, a method to directly estimate the log-density gradient without density estimation has been explored and demonstrated to work much better than the two-step method. The objective of this letter is to improve the performance of this direct method in multidimensional cases. Our idea is to regard the problem of log-density gradient estimation in each dimension as a task and apply regularized multitask learning to the direct log-density gradient estimator. We experimentally demonstrate the usefulness of the proposed multitask method in log-density gradient estimation and mode-seeking clustering.
Density Estimations in Laboratory Debris Flow Experiments
Queiroz de Oliveira, Gustavo; Kulisch, Helmut; Malcherek, Andreas; Fischer, Jan-Thomas; Pudasaini, Shiva P.
2016-04-01
Bulk density and its variation is an important physical quantity to estimate the solid-liquid fractions in two-phase debris flows. Here we present mass and flow depth measurements for experiments performed in a large-scale laboratory set up. Once the mixture is released and it moves down the inclined channel, measurements allow us to determine the bulk density evolution throughout the debris flow. Flow depths are determined by ultrasonic pulse reflection, and the mass is measured with a total normal force sensor. The data were obtained at 50 Hz. The initial two phase material was composed of 350 kg debris with water content of 40%. A very fine pebble with mean particle diameter of 3 mm, particle density of 2760 kg/m³ and bulk density of 1400 kg/m³ in dry condition was chosen as the solid material. Measurements reveal that the debris bulk density remains high from the head to the middle of the debris body whereas it drops substantially at the tail. This indicates lower water content at the tail, compared to the head and the middle portion of the debris body. This means that the solid and fluid fractions are varying strongly in a non-linear manner along the flow path, and from the head to the tail of the debris mass. Importantly, this spatial-temporal density variation plays a crucial role in determining the impact forces associated with the dynamics of the flow. Our setup allows for investigating different two phase material compositions, including large fluid fractions, with high resolutions. The considered experimental set up may enable us to transfer the observed phenomena to natural large-scale events. Furthermore, the measurement data allows evaluating results of numerical two-phase mass flow simulations. These experiments are parts of the project avaflow.org that intends to develop a GIS-based open source computational tool to describe wide spectrum of rapid geophysical mass flows, including avalanches and real two-phase debris flows down complex natural
Directory of Open Access Journals (Sweden)
Thomas Jerry A
2010-11-01
Full Text Available Abstract Background Calibrating mammograms to produce a standardized breast density measurement for breast cancer risk analysis requires an accurate spatial measure of the compressed breast thickness. Thickness inaccuracies due to the nominal system readout value and compression paddle orientation induce unacceptable errors in the calibration. Method A thickness correction was developed and evaluated using a fully specified two-component surrogate breast model. A previously developed calibration approach based on effective radiation attenuation coefficient measurements was used in the analysis. Water and oil were used to construct phantoms to replicate the deformable properties of the breast. Phantoms consisting of measured proportions of water and oil were used to estimate calibration errors without correction, evaluate the thickness correction, and investigate the reproducibility of the various calibration representations under compression thickness variations. Results The average thickness uncertainty due to compression paddle warp was characterized to within 0.5 mm. The relative calibration error was reduced to 7% from 48-68% with the correction. The normalized effective radiation attenuation coefficient (planar representation was reproducible under intra-sample compression thickness variations compared with calibrated volume measures. Conclusion Incorporating this thickness correction into the rigid breast tissue equivalent calibration method should improve the calibration accuracy of mammograms for risk assessments using the reproducible planar calibration measure.
Directory of Open Access Journals (Sweden)
Mary Mockus
2015-06-01
Conclusions and general significance: While reproductive characteristics, in particular parity, generally demonstrated independent associations with postmenopausal breast density and E, P and DHEA levels, T levels showed concordant inverse associations with age-at-first birth and breast density. These findings suggest that reproductive effects and later life salivary sex steroid hormone levels may have independent effects on later life breast density and cancer risk.
Kernel density estimation using graphical processing unit
Sunarko, Su'ud, Zaki
2015-09-01
Kernel density estimation for particles distributed over a 2-dimensional space is calculated using a single graphical processing unit (GTX 660Ti GPU) and CUDA-C language. Parallel calculations are done for particles having bivariate normal distribution and by assigning calculations for equally-spaced node points to each scalar processor in the GPU. The number of particles, blocks and threads are varied to identify favorable configuration. Comparisons are obtained by performing the same calculation using 1, 2 and 4 processors on a 3.0 GHz CPU using MPICH 2.0 routines. Speedups attained with the GPU are in the range of 88 to 349 times compared the multiprocessor CPU. Blocks of 128 threads are found to be the optimum configuration for this case.
Cox, B.; Ballard-Barbash, R.; Broeders, M.J.M.; Dowling, E.; Malila, N.; Shumak, R.; Taplin, S.; Buist, D.; Miglioretti, D.
2010-01-01
Breast density and the use of hormone therapy (HT) for menopausal symptoms alter the risk of breast cancer and both factors influence screening mammography performance. The International Cancer Screening Network (ICSN) surveyed its 29 member countries and found that few programs record breast densit
Mammographic Breast Density Patterns in Asymptomatic Mexican Women
Directory of Open Access Journals (Sweden)
Ana Laura Calderón-Garcidueñas
2012-01-01
Full Text Available Breast density (BD is a risk factor for breast cancer. Aims. To describe BD patterns in asymptomatic Mexican women and the pathological mammographic findings. Methods and Material. Prospective, descriptive, and comparative study. Women answered a questionnaire and their mammograms were analyzed according to BI-RADS. Univariate ( and conditional logistic regression analyses were performed. Results. In 300 women studied the BD patterns were fat 56.7% (170, fibroglandular 29% (87, heterogeneously dense 5.7% (17, and dense pattern 8.6% (26. Prevalence of fat pattern was significantly different in women under 50 years (37.6%, 44/117 and older than 50 (68.8%, 126/183. Patterns of high breast density (BD (dense + heterogeneously dense were observed in 25.6% (30/117 of women ≤50 years and 7.1% (13/183 of women >50. Asymmetry in BD was observed in 22% (66/300. Compression cone ruled out underlying disease in 56 cases. In the remaining 10, biopsy revealed one fibroadenoma, one complex cyst, and 6 invasive and 2 intraductal carcinomas. 2.6% (8/300 of patients had non-palpable carcinomas. Benign lesions were observed in 63.3% (190/300 of cases, vascular calcification in 150 cases (78.9%, and fat necrosis in 38 cases (20%. Conclusions. Mexican women have a low percentage of high-density patterns.
Mammographic Breast Density Patterns in Asymptomatic Mexican Women
Calderón-Garcidueñas, Ana Laura; Sanabria-Mondragón, Mónica; Hernández-Beltrán, Lourdes; López-Amador, Noé; Cerda-Flores, Ricardo M.
2012-01-01
Breast density (BD) is a risk factor for breast cancer. Aims. To describe BD patterns in asymptomatic Mexican women and the pathological mammographic findings. Methods and Material. Prospective, descriptive, and comparative study. Women answered a questionnaire and their mammograms were analyzed according to BI-RADS. Univariate (χ2) and conditional logistic regression analyses were performed. Results. In 300 women studied the BD patterns were fat 56.7% (170), fibroglandular 29% (87), heterogeneously dense 5.7% (17), and dense pattern 8.6% (26). Prevalence of fat pattern was significantly different in women under 50 years (37.6%, 44/117) and older than 50 (68.8%, 126/183). Patterns of high breast density (BD) (dense + heterogeneously dense) were observed in 25.6% (30/117) of women ≤50 years and 7.1% (13/183) of women >50. Asymmetry in BD was observed in 22% (66/300). Compression cone ruled out underlying disease in 56 cases. In the remaining 10, biopsy revealed one fibroadenoma, one complex cyst, and 6 invasive and 2 intraductal carcinomas. 2.6% (8/300) of patients had non-palpable carcinomas. Benign lesions were observed in 63.3% (190/300) of cases, vascular calcification in 150 cases (78.9%), and fat necrosis in 38 cases (20%). Conclusions. Mexican women have a low percentage of high-density patterns. PMID:23346398
Association between body mass index and breast density using digital mammography
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Kim, Mi Young [Dept. of Diagnostic Radiology, Dankook University Hospital, Cheonan (Korea, Republic of); Kim, Hwa Sun [Dept. of Radiological Technology, Ansan University, Ansan (Korea, Republic of)
2014-12-15
It is well known that low body mass index and younger age are associated with high breast density. Mammographic dense breast has been reported both as a cause of false-negative findings on mammography and as an indicator of increased breast cancer risk. The purpose of this study was to evaluate the association between breast density and body mass index. Furthermore, we considered proper screening method of breast cancer in Korean women. The study was performed on 496 women who underwent health checkup in a university hospital. Age and body mass index were negatively associated with breast density respectively. In postmenopausal women, age and body mass index showed statistically significant association with breast density. Therefore, we should consider sensitive additional method for breast cancer screening especially in younger age and underweight women.
Segmentation of Breast Regions in Mammogram Based on Density: A Review
Directory of Open Access Journals (Sweden)
Nafiza Saidin
2012-07-01
Full Text Available The focus of this paper is to review approaches for segmentation of breast regions in mammograms according to breast density. Studies based on density have been undertaken because of the relationship between breast cancer and density. Breast cancer usually occurs in the fibroglandular area of breast tissue, which appears bright on mammograms and describes as breast density. Most of the studies focused on the classification method for the glandular tissue detection. Others highlighted on the segmentation method of fibroglandular tissue, while few researchers performed segmentation of the anatomical regions based on density. There have also been works on the segmentation of other specific parts of breast regions such as either detection of nipple position, skin-air interface or pectoral muscle. The problem on evaluation performance of the segmentation result in relation to ground truth is also discussed in this paper.
Concrete density estimation by rebound hammer method
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Ismail, Mohamad Pauzi bin, E-mail: pauzi@nm.gov.my; Masenwat, Noor Azreen bin; Sani, Suhairy bin; Mohd, Shukri [NDT Group, Nuclear Malaysia, Bangi, Kajang, Selangor (Malaysia); Jefri, Muhamad Hafizie Bin; Abdullah, Mahadzir Bin [Material Technology Program, Faculty of Applied Sciences, UiTM, Shah Alam, Selangor (Malaysia); Isa, Nasharuddin bin; Mahmud, Mohamad Haniza bin [Pusat Penyelidikan Mineral, Jabatan Mineral dan Geosains, Ipoh, Perak (Malaysia)
2016-01-22
Concrete is the most common and cheap material for radiation shielding. Compressive strength is the main parameter checked for determining concrete quality. However, for shielding purposes density is the parameter that needs to be considered. X- and -gamma radiations are effectively absorbed by a material with high atomic number and high density such as concrete. The high strength normally implies to higher density in concrete but this is not always true. This paper explains and discusses the correlation between rebound hammer testing and density for concrete containing hematite aggregates. A comparison is also made with normal concrete i.e. concrete containing crushed granite.
Concrete density estimation by rebound hammer method
Ismail, Mohamad Pauzi bin; Jefri, Muhamad Hafizie Bin; Abdullah, Mahadzir Bin; Masenwat, Noor Azreen bin; Sani, Suhairy bin; Mohd, Shukri; Isa, Nasharuddin bin; Mahmud, Mohamad Haniza bin
2016-01-01
Concrete is the most common and cheap material for radiation shielding. Compressive strength is the main parameter checked for determining concrete quality. However, for shielding purposes density is the parameter that needs to be considered. X- and -gamma radiations are effectively absorbed by a material with high atomic number and high density such as concrete. The high strength normally implies to higher density in concrete but this is not always true. This paper explains and discusses the correlation between rebound hammer testing and density for concrete containing hematite aggregates. A comparison is also made with normal concrete i.e. concrete containing crushed granite.
Efficient estimation of analytic density under random censorship
Belitser, E.
2001-01-01
The nonparametric minimax estimation of an analytic density at a given point, under random censorship, is considered. Although the problem of estimating density is known to be irregular in a certain sense, we make some connections relating this problem to the problem of estimating smooth functionals
Breast density mapping based upon system calibration, x-ray techniques, and FFDM images
Chen, Biao; Smith, Andrew P.; Jing, Zhenxue; Wu, Tao
2007-03-01
Clinical studies have correlated a high breast density to a women's risk of breast cancer. A breast density measurement that can quantitatively depict the volume distribution and percentage of dense tissues in breasts would be very useful for risk factor assessment of breast cancer, and might be more predictive of risks than the common but subjective and coarse 4-point BIRADS scale. This paper proposes to use a neural-network mapping to compute the breast density information based upon system calibration data, x-ray techniques, and Full Field Digital Mammography (FFDM) images. The mapping consists of four modules, namely, system calibration, generator of beam quality, generator of normalized absorption, and a multi-layer feed-forward neural network. As the core of breast density mapping, the network accepts x-ray target/filter combination, normalized x-ray absorption, pixel-wise breast thickness map, and x-ray beam quality during image acquisition as input elements, and exports a pixel-wise breast density distribution and a single breast density percentage for the imaged breast. Training and testing data sets for the design and verification of the network were formulated from calibrated x-ray beam quality, imaging data with a step wedge phantom under a variety x-ray imaging techniques, and nominal breast densities of tissue equivalent materials. The network was trained using a Levenberg-Marquardt algorithm based back-propagation learning method. Various thickness and glandular density phantom studies were performed with clinical x-ray techniques. Preliminary results showed that the neural network mapping is promising in accurately computing glandular density distribution and breast density percentage.
Saadatmand, Sepideh; Rutgers, Emiel J. T.; Tollenaar, Rob A. E. M.; Zonderland, Hermien M.; Ausems, Margreet G. E. M.; Keymeulen, Kristien B. M. I.; Schlooz-Vries, Margreet S.; Koppert, Linetta B.; Heijnsdijk, Eveline A. M.; Seynaeve, Caroline; Verhoef, Cees; Oosterwijk, Jan C.; Obdeijn, Inge-Marie; de Koning, Harry J.; Tilanus-Linthorst, Madeleine M. A.
2012-01-01
Background: To reduce mortality, women with a family history of breast cancer often start mammography screening at a younger age than the general population. Breast density is high in over 50% of women younger than 50 years. With high breast density, breast cancer incidence increases, but sensitivit
Lokate, M.; Kallenberg, M.G.J.; Karssemeijer, N.; Bosch, M.H.J. van den; Peeters, P.H.M.; Gils, C.H. van
2010-01-01
INTRODUCTION: Breast density, a strong breast cancer risk factor, is usually measured on the projected breast area from film screen mammograms. This is far from ideal, as breast thickness and technical characteristics are not taken into account. We investigated whether volumetric density measurement
Work, Meghan E; Reimers, Laura L; Quante, Anne S; Crew, Katherine D; Whiffen, Amy; Terry, Mary Beth
2014-10-01
High mammographic breast density is one of the strongest intermediate markers of breast cancer risk, and decreases in density over time have been associated with decreases in breast cancer risk. Using repeated measures of mammographic density in a cohort of high-risk women, the Women at Risk (WAR) cohort at Columbia University Medical Center (N = 2670), we examined whether changes in prediagnostic mammographic density differed among 85 prospectively-ascertained breast cancer cases and 85 age-matched controls, using a nested case-control design. Median age at first mammogram was 51 years (range, 29-77 years), with a median of 4 years between first and second prediagnostic mammogram (range, 1-15 years). Using linear regression with change in percent density as the outcome, we found that in women who did not go on to be diagnosed with breast cancer, change in percent density decreased as time between first and second mammogram increased (β = -1.62% per year, p = 0.004). However, in women who did go on to be diagnosed with breast cancer, there was no overall change in percent density associated with time between first and second mammogram (β = 0.29% per year, p = 0.61); the change over time was statistically significantly different between cases versus controls (p breast cancer risk.
Large Scale Density Estimation of Blue and Fin Whales (LSD)
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...sensors, or both. The goal of this research is to develop and implement a new method for estimating blue and fin whale density that is effective over...develop and implement a density estimation methodology for quantifying blue and fin whale abundance from passive acoustic data recorded on sparse
Directory of Open Access Journals (Sweden)
Nafiza Saidin
2013-01-01
Full Text Available Breast cancer mostly arises from the glandular (dense region of the breast. Consequently, breast density has been found to be a strong indicator for breast cancer risk. Therefore, there is a need to develop a system which can segment or classify dense breast areas. In a dense breast, the sensitivity of mammography for the early detection of breast cancer is reduced. It is difficult to detect a mass in a breast that is dense. Therefore, a computerized method to separate the existence of a mass from the glandular tissues becomes an important task. Moreover, if the segmentation results provide more precise demarcation enabling the visualization of the breast anatomical regions, it could also assist in the detection of architectural distortion or asymmetry. This study attempts to segment the dense areas of the breast and the existence of a mass and to visualize other breast regions (skin-air interface, uncompressed fat, compressed fat, and glandular in a system. The graph cuts (GC segmentation technique is proposed. Multiselection of seed labels has been chosen to provide the hard constraint for segmentation of the different parts. The results are promising. A strong correlation ( was observed between the segmented dense breast areas detected and radiological ground truth.
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Baek, Ji Eun [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea (Korea, Republic of); Kim, Sung Hun, E-mail: rad-ksh@catholic.ac.kr [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea (Korea, Republic of); Lee, Ah Won [Department of Hospital Pathology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea (Korea, Republic of)
2014-08-15
Objective: To evaluate whether the degree of background parenchymal enhancement affects the accuracy of tumor size estimation based on breast MRI. Methods: Three hundred and twenty-two patients who had known breast cancer and underwent breast MRIs were recruited in our study. The total number of breast cancer cases was 339. All images were assessed retrospectively for the level of background parenchymal enhancement based on the BI-RADS criteria. Maximal lesion diameters were measured on the MRIs, and tumor types (mass vs. non-mass) were assessed. Tumor size differences between the MRI-based estimates and estimates based on pathological examinations were analyzed. The relationship between accuracy and tumor types and clinicopathologic features were also evaluated. Results: The cases included minimal (47.5%), mild (28.9%), moderate (12.4%) and marked background parenchymal enhancement (11.2%). The tumors of patients with minimal or mild background parenchymal enhancement were more accurately estimated than those of patients with moderate or marked enhancement (72.1% vs. 56.8%; p = 0.003). The tumors of women with mass type lesions were significantly more accurately estimated than those of the women with non-mass type lesions (81.6% vs. 28.6%; p < 0.001). The tumor of women negative for HER2 was more accurately estimated than those of women positive for HER2 (72.2% vs. 51.6%; p = 0.047). Conclusion: Moderate and marked background parenchymal enhancement is related to the inaccurate estimation of tumor size based on MRI. Non-mass type breast cancer and HER2-positive breast cancer are other factors that may cause inaccurate assessment of tumor size.
Zakariyah, N.; Pathy, N. B.; Taib, N. A. M.; Rahmat, K.; Judy, C. W.; Fadzil, F.; Lau, S.; Ng, K. H.
2016-03-01
It has been shown that breast density and obesity are related to breast cancer risk. The aim of this study is to investigate the relationships of breast volume, breast dense volume and volumetric breast density (VBD) with body mass index (BMI) and body fat mass (BFM) for the three ethnic groups (Chinese, Malay and Indian) in Malaysia. We collected raw digital mammograms from 2450 women acquired on three digital mammography systems. The mammograms were analysed using Volpara software to obtain breast volume, breast dense volume and VBD. Body weight, BMI and BFM of the women were measured using a body composition analyser. Multivariable logistic regression was used to determine the independent predictors of increased overall breast volume, breast dense volume and VBD. Indians have highest breast volume and breast dense volume followed by Malays and Chinese. While Chinese are highest in VBD, followed by Malay and Indian. Multivariable analysis showed that increasing BMI and BFM were independent predictors of increased overall breast volume and dense volume. Moreover, BMI and BFM were independently and inversely related to VBD.
Awareness of Breast Density and Its Impact on Breast Cancer Detection and Risk
Rhodes, Deborah J.; Radecki Breitkopf, Carmen; Ziegenfuss, Jeanette Y.; Jenkins, Sarah M.; Vachon, Celine M.
2015-01-01
Purpose Legislation mandating disclosure of breast density (BD) information has passed in 21 states; however, actual awareness of BD and knowledge of its impact on breast cancer detection and risk are unknown. Methods We conducted a national cross-sectional survey administered in English and Spanish using a probability-based sample of screening-age women, with oversampling of Connecticut, the only state with BD legislation in effect for > 1 year before the survey. Results Of 2,311 women surveyed, 65% responded. Overall, 58% of women had heard of BD, 49% knew that BD affects breast cancer detection, and 53% knew that BD affects cancer risk. After multivariable adjustment, increased BD awareness was associated with white non-Hispanic race/ethnicity (Hispanic v white non-Hispanic: odds ratio [OR], 0.23; P < .001), household income (OR, 1.07 per category increase; P < .001), education (OR, 1.19 per category increase; P < .001), diagnostic evaluation after a mammogram (OR, 2.64; P < .001), and postmenopausal hormone therapy (OR, 1.69; P = .002). Knowledge of the masking effect of BD was associated with higher household income (OR, 1.10; P < .001), education (OR, 1.22; P = .01), prior breast biopsy (OR, 2.16; P < .001), and residing in Connecticut (Connecticut v other states: OR, 3.82; P = .003). Connecticut residents were also more likely to have discussed their BD with a health care provider (67% v 43% for residents of other US states; P = .001). Conclusion Disparities in BD awareness and knowledge exist by race/ethnicity, education, and income. BD legislation seems to be effective in increasing knowledge of BD impact on breast cancer detection. These findings support continued and targeted efforts to improve BD awareness and knowledge among women eligible for screening mammography. PMID:25732156
Using ultrasound tomography to identify the distributions of density throughout the breast
Sak, Mark; Duric, Neb; Littrup, Peter; Sherman, Mark E.; Gierach, Gretchen L.
2016-04-01
Women with high breast density are at increased risk of developing breast cancer. Breast density has usually been defined using mammography as the ratio of fibroglandular tissue to total breast area. Ultrasound tomography (UST) is an emerging modality that can also be used to measure breast density. UST creates tomographic sound speed images of the patient's breast which is useful as sound speed is directly proportional to tissue density. Furthermore, the volumetric and quantitative information contained in the sound speed images can be used to describe the distribution of breast density. The work presented here measures the UST sound speed density distributions of 165 women with negative screening mammography. Frequency distributions of the sound speed voxel information were examined for each patient. In a preliminary analysis, the UST sound speed distributions were averaged across patients and grouped by various patient and density-related factors (e.g., age, body mass index, menopausal status, average mammographic breast density). It was found that differences in the distribution of density could be easily visualized for different patient groupings. Furthermore, findings suggest that the shape of the distributions may be used to identify participants with varying amounts of dense and non-dense tissue.
Diet across the Lifespan and the Association with Breast Density in Adulthood
Directory of Open Access Journals (Sweden)
Jessica Lindgren
2013-01-01
Full Text Available Studies have shown inconsistent results regarding the association between dietary factors across the lifespan and breast density and breast cancer in women. Breast density is a strong risk factor for breast cancer, and the mechanism through which it influences cancer risk remains unclear. Breast density has been shown to be modifiable, potentially through dietary modifications. The goal of this paper is to summarize the current studies on diet and diet-related factors across all ages, determine which dietary factors show the strongest association with breast density, the most critical age of exposure, and identify future directions. We identified 28 studies, many of which are cross-sectional, and found that the strongest associations are among vitamin D, calcium, dietary fat, and alcohol in premenopausal women. Longitudinal studies with repeated dietary measures as well as the examination of overall diet over time are needed to confirm these findings.
Current Source Density Estimation for Single Neurons
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Dorottya Cserpán
2014-03-01
Full Text Available Recent developments of multielectrode technology made it possible to measure the extracellular potential generated in the neural tissue with spatial precision on the order of tens of micrometers and on submillisecond time scale. Combining such measurements with imaging of single neurons within the studied tissue opens up new experimental possibilities for estimating distribution of current sources along a dendritic tree. In this work we show that if we are able to relate part of the recording of extracellular potential to a specific cell of known morphology we can estimate the spatiotemporal distribution of transmembrane currents along it. We present here an extension of the kernel CSD method (Potworowski et al., 2012 applicable in such case. We test it on several model neurons of progressively complicated morphologies from ball-and-stick to realistic, up to analysis of simulated neuron activity embedded in a substantial working network (Traub et al, 2005. We discuss the caveats and possibilities of this new approach.
Highway traffic model-based density estimation
Morarescu, Irinel - Constantin; CANUDAS DE WIT, Carlos
2011-01-01
International audience; The travel time spent in traffic networks is one of the main concerns of the societies in developed countries. A major requirement for providing traffic control and services is the continuous prediction, for several minutes into the future. This paper focuses on an important ingredient necessary for the traffic forecasting which is the real-time traffic state estimation using only a limited amount of data. Simulation results illustrate the performances of the proposed ...
Nayak, Lina; Miyake, Kanae K; Leung, Jessica W T; Price, Elissa R; Liu, Yueyi I; Joe, Bonnie N; Sickles, Edward A; Thomas, William R; Lipson, Jafi A; Daniel, Bruce L; Hargreaves, Jonathan; Brenner, R James; Bassett, Lawrence W; Ojeda-Fournier, Haydee; Lindfors, Karen K; Feig, Stephen A; Ikeda, Debra M
2016-09-01
Breast density notification laws, passed in 19 states as of October 2014, mandate that patients be informed of their breast density. The purpose of this study is to assess the impact of this legislation on radiology practices, including performance of breast cancer risk assessment and supplemental screening studies. A 20-question anonymous web-based survey was emailed to radiologists in the Society of Breast Imaging between August 2013 and March 2014. Statistical analysis was performed using Fisher's exact test. Around 121 radiologists from 110 facilities in 34 USA states and 1 Canadian site responded. About 50% (55/110) of facilities had breast density legislation, 36% of facilities (39/109) performed breast cancer risk assessment (one facility did not respond). Risk assessment was performed as a new task in response to density legislation in 40% (6/15) of facilities in states with notification laws. However, there was no significant difference in performing risk assessment between facilities in states with a law and those without (p facilities in states with laws implemented handheld whole breast ultrasound (WBUS), automated WBUS, and tomosynthesis, respectively. The ratio of facilities offering handheld WBUS was significantly higher in states with a law than in states without (p facilities are offering supplemental screening with WBUS and tomosynthesis, and many are performing formal risk assessment for determining patient management.
Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina
2014-03-01
Accurate assessment of a woman's risk to develop specific subtypes of breast cancer is critical for appropriate utilization of chemopreventative measures, such as with tamoxifen in preventing estrogen-receptor positive breast cancer. In this context, we investigate quantitative measures of breast density and parenchymal texture, measures of glandular tissue content and tissue structure, as risk factors for estrogen-receptor positive (ER+) breast cancer. Mediolateral oblique (MLO) view digital mammograms of the contralateral breast from 106 women with unilateral invasive breast cancer were retrospectively analyzed. Breast density and parenchymal texture were analyzed via fully-automated software. Logistic regression with feature selection and was performed to predict ER+ versus ER- cancer status. A combined model considering all imaging measures extracted was compared to baseline models consisting of density-alone and texture-alone features. Area under the curve (AUC) of the receiver operating characteristic (ROC) and Delong's test were used to compare the models' discriminatory capacity for receptor status. The density-alone model had a discriminatory capacity of 0.62 AUC (p=0.05). The texture-alone model had a higher discriminatory capacity of 0.70 AUC (p=0.001), which was not significantly different compared to the density-alone model (p=0.37). In contrast the combined density-texture logistic regression model had a discriminatory capacity of 0.82 AUC (pbreast density and texture measures may have the potential to identify women specifically at risk for estrogen-receptor positive breast cancer and could be useful in triaging women into appropriate risk-reduction strategies.
Quantification of breast density with dual energy mammography: An experimental feasibility study
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Ducote, Justin L.; Molloi, Sabee [Department of Radiological Sciences, University of California, Irvine, California 92697 (United States)
2010-02-15
Purpose: Breast density, the percentage of glandular breast tissue, has been shown to be a strong indicator of breast cancer risk. A quantitative method to measure breast density with dual energy mammography was investigated using physical phantoms. Methods: The dual energy mammography system used a tungsten anode x-ray tube with a 50 {mu}m rhodium beam filter for low energy images and a 300 {mu}m copper beam filter for high energy images. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Four different phantom studies were used to evaluate the technique. The first study consisted of phantoms with thicknesses of 2.5-8.5 cm in 0.5 cm steps with variable densities centered at a mean of 28%. The second study consisted of phantoms at a fixed thickness of 4.0 cm, which ranged in densities from 0% to 100% in increments of 12.5%. The third study consisted of 4.0 cm thick phantoms at densities of 25%, 50% and 75% each imaged at three areal sizes, approximately 62.5, 125, and 250 cm{sup 2}, in order to assess the effect of breast size on density measurement. The fourth study consisted of step phantoms designed to more closely mimic the shape of a female breast with maximal thicknesses from 3.0 to 7.0 cm at a fixed density of 50%. All images were corrected for x-ray scatter. Results: The RMS errors in breast density measurements were 0.44% for the variable thickness phantoms, 0.64% for the variable density phantoms, 2.87% for the phantoms of different areal sizes, and 4.63% for step phantoms designed to closely resemble the shape of a breast. Conclusions: The results of the phantom studies indicate that dual energy mammography can be used to measure breast density with an RMS error of approximately 5%.
Fusion of Hard and Soft Information in Nonparametric Density Estimation
2015-06-10
estimation exploiting, in concert, hard and soft information. Although our development, theoretical and numerical, makes no distinction based on sample...Fusion of Hard and Soft Information in Nonparametric Density Estimation∗ Johannes O. Royset Roger J-B Wets Department of Operations Research...univariate density estimation in situations when the sample ( hard information) is supplemented by “soft” information about the random phenomenon. These
Comparison of density estimation methods for astronomical datasets
Ferdosi, B.J.; Buddelmeijer, H.; Trager, S.C.; Wilkinson, M.H.F.; Roerdink, J.B.T.M.
2011-01-01
Context. Galaxies are strongly influenced by their environment. Quantifying the galaxy density is a difficult but critical step in studying the properties of galaxies. Aims. We aim to determine differences in density estimation methods and their applicability in astronomical problems. We study the p
Density estimators in particle hydrodynamics - DTFE versus regular SPH
Pelupessy, FI; Schaap, WE; van de Weygaert, R
2003-01-01
We present the results of a study comparing density maps reconstructed by the Delaunay Tessellation Field Estimator (DTFE) and by regular SPH kernel-based techniques. The density maps are constructed from the outcome of an SPH particle hydrodynamics simulation of a multiphase interstellar medium. Th
Estimating maritime snow density from seasonal climate variables
Bormann, K. J.; Evans, J. P.; Westra, S.; McCabe, M. F.; Painter, T. H.
2013-12-01
Snow density is a complex parameter that influences thermal, optical and mechanical snow properties and processes. Depth-integrated properties of snowpacks, including snow density, remain very difficult to obtain remotely. Observations of snow density are therefore limited to in-situ point locations. In maritime snowfields such as those in Australia and in parts of the western US, snow densification rates are enhanced and inter-annual variability is high compared to continental snow regions. In-situ snow observation networks in maritime climates often cannot characterise the variability in snowpack properties at spatial and temporal resolutions required for many modelling and observations-based applications. Regionalised density-time curves are commonly used to approximate snow densities over broad areas. However, these relationships have limited spatial applicability and do not allow for interannual variability in densification rates, which are important in maritime environments. Physically-based density models are relatively complex and rely on empirical algorithms derived from limited observations, which may not represent the variability observed in maritime snow. In this study, seasonal climate factors were used to estimate late season snow densities using multiple linear regressions. Daily snow density estimates were then obtained by projecting linearly to fresh snow densities at the start of the season. When applied spatially, the daily snow density fields compare well to in-situ observations across multiple sites in Australia, and provide a new method for extrapolating existing snow density datasets in maritime snow environments. While the relatively simple algorithm for estimating snow densities has been used in this study to constrain snowmelt rates in a temperature-index model, the estimates may also be used to incorporate variability in snow depth to snow water equivalent conversion.
Towards accurate and precise estimates of lion density.
Elliot, Nicholas B; Gopalaswamy, Arjun M
2016-12-13
Reliable estimates of animal density are fundamental to our understanding of ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation biology since wildlife authorities rely on these figures to make decisions. However, it is notoriously difficult to accurately estimate density for wide-ranging species such as carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores. African lions (Panthera leo) provide an excellent example as although abundance indices have been shown to produce poor inferences, they continue to be used to estimate lion density and inform management and policy. In this study we adapt a Bayesian spatially explicit capture-recapture model to estimate lion density in the Maasai Mara National Reserve (MMNR) and surrounding conservancies in Kenya. We utilize sightings data from a three-month survey period to produce statistically rigorous spatial density estimates. Overall posterior mean lion density was estimated to be 16.85 (posterior standard deviation = 1.30) lions over one year of age per 100km(2) with a sex ratio of 2.2♀:1♂. We argue that such methods should be developed, improved and favored over less reliable methods such as track and call-up surveys. We caution against trend analyses based on surveys of differing reliability and call for a unified framework to assess lion numbers across their range in order for better informed management and policy decisions to be made. This article is protected by copyright. All rights reserved.
2015-12-01
women with a diagnosis of breast cancer from 2003 to 2012 and enrolled in a larger study on MD were evaluated. Operative and pathology reports were...AD______________ AWARD NUMBER: W81XWH-11-1-0545 TITLE: Building a Better Model: A Personalized Breast Cancer Risk Model Incorporating Breast ...Better Model: A Personalized Breast Cancer Risk Model Incorporating Breast Density to Stratify Risk and Improve Application of Resources 5a. CONTRACT
Maximum likelihood estimation for semiparametric density ratio model.
Diao, Guoqing; Ning, Jing; Qin, Jing
2012-06-27
In the statistical literature, the conditional density model specification is commonly used to study regression effects. One attractive model is the semiparametric density ratio model, under which the conditional density function is the product of an unknown baseline density function and a known parametric function containing the covariate information. This model has a natural connection with generalized linear models and is closely related to biased sampling problems. Despite the attractive features and importance of this model, most existing methods are too restrictive since they are based on multi-sample data or conditional likelihood functions. The conditional likelihood approach can eliminate the unknown baseline density but cannot estimate it. We propose efficient estimation procedures based on the nonparametric likelihood. The nonparametric likelihood approach allows for general forms of covariates and estimates the regression parameters and the baseline density simultaneously. Therefore, the nonparametric likelihood approach is more versatile than the conditional likelihood approach especially when estimation of the conditional mean or other quantities of the outcome is of interest. We show that the nonparametric maximum likelihood estimators are consistent, asymptotically normal, and asymptotically efficient. Simulation studies demonstrate that the proposed methods perform well in practical settings. A real example is used for illustration.
2015-12-01
found high correlation (12); Pearson correlation coefficients were 0.93, 0.97, and 0.85 for volumetric breast density, breast volume, and fi...cancer risk, and her score on the four-point scale of accuracy of breast cancer knowledge, described above. The strongest single correlate for each...women (622 cases). Breast density measurement has been evaluated for accuracy using a second test set showing very good correlation with 2D methods
Directory of Open Access Journals (Sweden)
Kristina M Blackmore
Full Text Available Mammographic density (MD, associated with higher water and lower fat content in the breast, is strongly related to breast cancer risk. Optical attenuation spectroscopy (OS is a non-imaging method of evaluating breast tissue composition by red and near-infrared light transmitted through the breast that, unlike mammography, does not involve radiation. OS provides information on wavelength dependent light scattering of tissue and on absorption by water, lipid, oxy-, deoxy-hemoglobin. We propose that OS could be an alternative marker of breast cancer risk and that OS breast tissue measures will be associated with MD. In the present analysis, we developed an algorithm to estimate breast tissue composition and light scattering parameters using a spectrally constrained global fitting procedure employing a diffuse light transport model. OS measurements were obtained from 202 pre- and post-menopausal women with normal mammograms. Percent density (PD and dense area (DA were measured using Cumulus. The association between OS tissue composition and PD and DA was analyzed using linear regression adjusted for body mass index. Among pre-menopausal women, lipid content was significantly inversely associated with square root transformed PD (β = -0.05, p = 0.0002 and DA (β = -0.05, p = 0.019; water content was significantly positively associated with PD (β = 0.06, p = 0.008. Tissue oxygen saturation was marginally inversely associated with PD (β = -0.03, p = 0.057 but significantly inversely associated with DA (β = -0.10, p = 0.002. Among post-menopausal women lipid and water content were significantly associated (negatively and positively, respectively with PD (β lipid = -0.08, β water = 0.14, both p<0.0001 and DA (β lipid = -0.10, p<0.0001; β water = 0.11, p = 0.001. The association between OS breast content and PD and DA is consistent with more proliferation in dense tissue of younger women, greater lipid content in low density tissue and higher water
Age as a predictive factor of mammographic breast density in Jamaican women
Energy Technology Data Exchange (ETDEWEB)
Soares, Deanne; Reid, Marvin; James, Michael
2002-06-01
AIM: We sought to determine the relationship between age, and other clinical characteristics such as parity, oestrogen use, dietary factors and menstrual history on breast density in Jamaican women. METHODS AND MATERIALS: A retrospective study was done of 891 patients who attended the breast imaging unit. The clinical characteristics were extracted from the patient records. Mammograms were assessed independently by two radiologists who were blinded to the patient clinical characteristics. Breast densities were assigned using the American College of Radiology (ACR) classification. RESULTS: The concordance between the ACR classification of breast density between the two independent radiologists was 92% with k = 0.76 (SE = 0.02, P < 0.001). Women with low breast density were heavier (81.3 {+-} 15.5 kg vs 68.4 {+-} 14.3 kg,P < 0.0001, mean {+-} standard deviation (SD)) and more obese (body mass index (BMI), 30.3 {+-} 5.8 kg m{sup -2} vs 26.0 {+-} 5.2 kg m{sup -2}, P < 0.0001). Mammographic breast density decreased with age. The age adjusted odds ratios (ORs) for predictors significantly related to high breast density were parity, OR = 0.79 (95%CI:0.71, 0.88), weight, OR = 0.92 (95% CI:0.91, 0.95), BMI, OR = 0.83 (95% CI:0.78, 0.89), menopause, OR = 0.51 (95% CI:0.36, 0.74) and a history of previous breast surgery, OR 1.6 (95% CI:1.1, 2.3). CONCLUSION: The rate decline of breast density with age in our population was influenced by parity and body composition. Soares, D. et al. (2002)
A morpho-density approach to estimating neural connectivity.
Directory of Open Access Journals (Sweden)
Michael P McAssey
Full Text Available Neuronal signal integration and information processing in cortical neuronal networks critically depend on the organization of synaptic connectivity. Because of the challenges involved in measuring a large number of neurons, synaptic connectivity is difficult to determine experimentally. Current computational methods for estimating connectivity typically rely on the juxtaposition of experimentally available neurons and applying mathematical techniques to compute estimates of neural connectivity. However, since the number of available neurons is very limited, these connectivity estimates may be subject to large uncertainties. We use a morpho-density field approach applied to a vast ensemble of model-generated neurons. A morpho-density field (MDF describes the distribution of neural mass in the space around the neural soma. The estimated axonal and dendritic MDFs are derived from 100,000 model neurons that are generated by a stochastic phenomenological model of neurite outgrowth. These MDFs are then used to estimate the connectivity between pairs of neurons as a function of their inter-soma displacement. Compared with other density-field methods, our approach to estimating synaptic connectivity uses fewer restricting assumptions and produces connectivity estimates with a lower standard deviation. An important requirement is that the model-generated neurons reflect accurately the morphology and variation in morphology of the experimental neurons used for optimizing the model parameters. As such, the method remains subject to the uncertainties caused by the limited number of neurons in the experimental data set and by the quality of the model and the assumptions used in creating the MDFs and in calculating estimating connectivity. In summary, MDFs are a powerful tool for visualizing the spatial distribution of axonal and dendritic densities, for estimating the number of potential synapses between neurons with low standard deviation, and for obtaining
Mammographic Breast Density in Chinese Women: Spatial Distribution and Autocorrelation Patterns.
Directory of Open Access Journals (Sweden)
Christopher W K Lai
Full Text Available Mammographic breast density (MBD is a strong risk factor for breast cancer. The spatial distribution of MBD in the breast is variable and dependent on physiological, genetic, environmental and pathological factors. This pilot study aims to define the spatial distribution and autocorrelation patterns of MBD in Chinese women aged 40-60. By analyzing their digital mammographic images using a public domain Java image processing program for segmentation and quantification of MBD, we found their left and right breasts were symmetric to each other in regard to their breast size (Total Breast Area, the amount of BMD (overall PD and Moran's I values. Their MBD was also spatially autocorrelated together in the anterior part of the breast in those with a smaller breast size, while those with a larger breast size tend to have their MBD clustered near the posterior part of the breast. Finally, we observed that the autocorrelation pattern of MBD was dispersed after a 3-year observation period.
Quantitative assessment of breast density from digitized mammograms into Tabar's patterns
Energy Technology Data Exchange (ETDEWEB)
Jamal, N [Medical Technology Division, Malaysian Institute for Nuclear Technology Research (MINT) 43000 Kajang (Malaysia); Ng, K-H [Department of Radiology, University of Malaya, 50603 Kuala Lumpur (Malaysia); Looi, L-M [Department of Pathology, University of Malaya, 50603 Kuala Lumpur (Malaysia); McLean, D [Medical Physics Department, Westmead Hospital, Sydney, NSW 2145 (Australia); Zulfiqar, A [Department of Radiology, Hospital Universiti Kebangsaan Malaysia, 56000 Malaysia, Kuala Lumpur, Malaysia (Malaysia); Tan, S-P [Department of Radiology, Hospital Universiti Kebangsaan Malaysia, 56000 Malaysia, Kuala Lumpur, Malaysia (Malaysia); Liew, W-F [Department of Radiology, Hospital Universiti Kebangsaan Malaysia, 56000 Malaysia, Kuala Lumpur, Malaysia (Malaysia); Shantini, A [Department of Radiology, Kuala Lumpur Hospital, 50586 Kuala Lumpur (Malaysia); Ranganathan, S [Department of Radiology, University of Malaya, 50603 Kuala Lumpur (Malaysia)
2006-11-21
We describe a semi-automated technique for the quantitative assessment of breast density from digitized mammograms in comparison with patterns suggested by Tabar. It was developed using the MATLAB-based graphical user interface applications. It is based on an interactive thresholding method, after a short automated method that shows the fibroglandular tissue area, breast area and breast density each time new thresholds are placed on the image. The breast density is taken as a percentage of the fibroglandular tissue to the breast tissue areas. It was tested in four different ways, namely by examining: (i) correlation of the quantitative assessment results with subjective classification, (ii) classification performance using the quantitative assessment technique, (iii) interobserver agreement and (iv) intraobserver agreement. The results of the quantitative assessment correlated well (r{sup 2} = 0.92) with the subjective Tabar patterns classified by the radiologist (correctly classified 83% of digitized mammograms). The average kappa coefficient for the agreement between the readers was 0.63. This indicated moderate agreement between the three observers in classifying breast density using the quantitative assessment technique. The kappa coefficient of 0.75 for intraobserver agreement reflected good agreement between two sets of readings. The technique may be useful as a supplement to the radiologist's assessment in classifying mammograms into Tabar's pattern associated with breast cancer risk.
Quantification of Regional Breast Density in Four Quadrants Using 3D MRI—A Pilot Study
Directory of Open Access Journals (Sweden)
Peter T. Fwu
2015-08-01
Full Text Available PURPOSE: This study presented a three-dimensional magnetic resonance (MR–based method to separate a breast into four quadrants for quantitative measurements of the quadrant breast volume (BV and density. METHODS: Breast MR images from 58 healthy women were studied. The breast and the fibroglandular tissue were segmented by using a computer-based algorithm. A breast was divided into four quadrants using two perpendicular planes intersecting at the nipple or the nipple-centroid line. After the separation, the BV, the fibroglandular tissue volume, and the percent density (PD were calculated. The symmetry of the quadrant BV in the left and right breasts separated by using the nipple alone, or the nipple-centroid line, was compared. RESULTS: The quadrant separation made on the basis of the nipple-centroid line showed closer BVs in four quadrants than using the nipple alone. The correlation and agreement for the BV in corresponding quadrants of the left and the right breasts were improved after the nipple-centroid reorientation. Among the four quadrants, PD was the highest in the lower outer and the lowest in the upper outer (significant than the other three quadrants (P < .05. CONCLUSIONS: We presented a quantitative method to divide a breast into four quadrants. The reorientation based on the nipple-centroid line improved the left to right quadrant symmetry, and this may provide a better standardized method to measure quantitative quadrant density. The cancer occurrence rates are known to vary in different sites of a breast, and our method may provide a tool for investigating its association with the quantitative breast density.
Quantiles, parametric-select density estimation, and bi-information parameter estimators
Parzen, E.
1982-01-01
A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.
Density Estimation in Several Populations With Uncertain Population Membership
Ma, Yanyuan
2011-09-01
We devise methods to estimate probability density functions of several populations using observations with uncertain population membership, meaning from which population an observation comes is unknown. The probability of an observation being sampled from any given population can be calculated. We develop general estimation procedures and bandwidth selection methods for our setting. We establish large-sample properties and study finite-sample performance using simulation studies. We illustrate our methods with data from a nutrition study.
Green's function based density estimation
Energy Technology Data Exchange (ETDEWEB)
Kovesarki, Peter; Brock, Ian C.; Nuncio Quiroz, Adriana Elizabeth [Physikalisches Institut, Universitaet Bonn (Germany)
2012-07-01
A method was developed based on Green's function identities to estimate probability densities. This can be used for likelihood estimations and for binary classifications. It offers several advantages over neural networks, boosted decision trees and other, regression based classifiers. For example, it is less prone to overtraining, and it is much easier to combine several samples. Some capabilities are demonstrated using ATLAS data.
Energy Technology Data Exchange (ETDEWEB)
Poellinger, Alexander, E-mail: alexander.poellinger@charite.de [Charité, Universitätsmedizin Berlin, Department of Radiology, Augustenburger Platz 1, 13353 Berlin (Germany); El-Ghannam, Sahra; Diekmann, Susanne; Fischer, Thomas [Charité, Universitätsmedizin Berlin, Department of Radiology, Augustenburger Platz 1, 13353 Berlin (Germany); Kristiansen, Glen [Universitätsklinikum Bonn, Department of Pathology, Sigmund-Freud-Str. 25, D-53127 Bonn (Germany); Fritzsche, Florian [Institut für Histologie und Zytologie, Bahnhofplatz 11, Postfach, 9101 Herisau (Switzerland); Fallenberg, Eva [Charité, Universitätsmedizin Berlin, Department of Radiology, Augustenburger Platz 1, 13353 Berlin (Germany); Morawietz, Lars [Diagnostik Ernst von Bergmann GmbH, Charlottenstr. 72, 14467 Potsdam (Germany); Diekmann, Felix [Charité, Universitätsmedizin Berlin, Department of Radiology, Augustenburger Platz 1, 13353 Berlin (Germany)
2014-12-15
Highlights: • We correlate capillary density of breast lesions with MRM. • Capillary density correlates with tumor enhancement for all lesions. • However no such correlation exists for the malignant or benign groups separately. • Mean vessel number of lymphatic vessels do not correlate with tumor enhancement.These results might be of help in the workup of MR-guided breast biopsies. • These results might be of help in the workup of MR-guided breast biopsies. - Abstract: Objective: To correlate capillary density of breast lesions using the markers D2-40, CD31, and CD34 with early and late enhancement of magnetic resonance mammography (MRM). Materials and methods: The local ethics committee approved this study, and informed consent was available from all patients. The study included 64 women with 66 histologically proven breast lesions (41 malignant, 25 benign). MR-enhancement 1 min after contrast medium administration was determined in the tumor (I{sub t1}/I{sub t0} ratio) and in comparison to the surrounding tissue (I{sub t1}/I{sub t1-fat} ratio). Capillary density was quantified based on immunohistological staining with D2-40, CD31, and CD34 in breast tumors and surrounding breast tissue. Mean capillary densities were correlated with contrast enhancement in the tumor and surrounding breast tissue. The Kruskal–Wallis test was used to test whether lesions with different MR enhancement patterns differed in terms of capillary density. Results: For CD34, there was statistically significant correlation between capillary density and tumor enhancement (r = 0.329, p = 0.012), however not for the malignant or benign groups separately. Mean vessel number identified by staining with D2-40 and CD31 did not correlate significantly with tumor enhancement (D2-40: r = −0.188, p = 0.130; CD31: r = 0.095, p = 0.448). There were no statistically significant differences in capillary density between breast lesions with delayed enhancement or a plateau and lesions showing
2013-10-01
Visual aids were developed to inform viewers of the study recruitment status, such as thermometers and pie charts. We produced two 2-minutes videos...ANTIPERSPIRANT USE 5 BIRTH CONTROL PILL USE 6 BREAST BIOPSY WITH OR WITHOUT ATYPIA/HIGH RISK LESION 7 BREAST SIZE 8 BREAST TISSUE DENSITY 9
BREAST CANCER RISK EVALUATION - A CORRELATION BETWEEN MAMMOGRAPHIC DENSITY AND THE GAIL MODEL
Directory of Open Access Journals (Sweden)
George Baytchev
2015-05-01
Full Text Available The Gail model is a statistical tool, which assesses breast cancer probability, based on nonmodifiable risk factors. In contrast, the evaluation of mammographic breast density is an independent and dynamic risk factor influenced by interventions modifying breast cancer risk incidence. The aim of the present study is to compare the possibilities for risk factor integration and analysis and to search for a correlation between mammographic density and the Gail model for breast cancer risk evaluation. The subject of this prospective study is a cohort of 107 women at ages from 37 to 71 years, who have had benign breast diseases, digital mammograms, and Gail model risk evaluation. Mammographic density is evaluated in craniocaudal projection subjectively visually and objectively using the computer imaging software. (Image J software The Gail risk evaluation is completed using the standardized NCI questionnaire (Breast Cancer Risk Assessment Tool. In concordance with the Breast Imaging Reporting and Data System (BI-RAD by ACR, mammographic density is evaluated using a four-grade scale. Low density D1 (less than 25% was determined in 24 cases, D2 (25-50% in 36 cases, D3 (51-75% in 31 cases and high density D4 (greater than 75% in 16 cases. According to the Gail model, 80 (74,8% of the examined patients did not have an increased risk (less than 1,67% for a five-year period, whereas the remaining 27 (25,2% had a statistically significant increase in risk (greater than 1,67% for a five-year period. Women with increased risk more often present with denser breast (34% with D3, D4 versus 18,3% for D1, D2. The Gail model does not adequately explain the correlation between breast density and statistically calculated risk. The development of more detailed tools, which take into consideration breast density, as well as other risk factors, may be helpful for a more accurate evaluation of the individual risk for breast cancer.
Face Value: Towards Robust Estimates of Snow Leopard Densities.
Directory of Open Access Journals (Sweden)
Justine S Alexander
Full Text Available When densities of large carnivores fall below certain thresholds, dramatic ecological effects can follow, leading to oversimplified ecosystems. Understanding the population status of such species remains a major challenge as they occur in low densities and their ranges are wide. This paper describes the use of non-invasive data collection techniques combined with recent spatial capture-recapture methods to estimate the density of snow leopards Panthera uncia. It also investigates the influence of environmental and human activity indicators on their spatial distribution. A total of 60 camera traps were systematically set up during a three-month period over a 480 km2 study area in Qilianshan National Nature Reserve, Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trap-days, representing an average capture success of 2.62 captures/100 trap-days. We identified a total number of 20 unique individuals from photographs and estimated snow leopard density at 3.31 (SE = 1.01 individuals per 100 km2. Results of our simulation exercise indicate that our estimates from the Spatial Capture Recapture models were not optimal to respect to bias and precision (RMSEs for density parameters less or equal to 0.87. Our results underline the critical challenge in achieving sufficient sample sizes of snow leopard captures and recaptures. Possible performance improvements are discussed, principally by optimising effective camera capture and photographic data quality.
State of the Art in Photon-Density Estimation
DEFF Research Database (Denmark)
Hachisuka, Toshiya; Jarosz, Wojciech; Georgiev, Iliyan
2013-01-01
Photon-density estimation techniques are a popular choice for simulating light transport in scenes with complicated geometry and materials. This class of algorithms can be used to accurately simulate inter-reflections, caustics, color bleeding, scattering in participating media, and subsurface sc...
Estimation of the space density of low surface brightness galaxies
Briggs, FH
1997-01-01
The space density of low surface brightness and tiny gas-rich dwarf galaxies are estimated for two recent catalogs: the Arecibo Survey of Northern Dwarf and Low Surface Brightness Galaxies and the Catalog of Low Surface Brightness Galaxies, List II. The goals are (1) to evaluate the additions to the
State of the Art in Photon Density Estimation
DEFF Research Database (Denmark)
Hachisuka, Toshiya; Jarosz, Wojciech; Bouchard, Guillaume
2012-01-01
scattering. Since its introduction, photon-density estimation has been significantly extended in computer graphics with the introduction of: specialized techniques that intelligently modify the positions or bandwidths to reduce visual error using a small number of photons, approaches that eliminate error...
Corruption clubs: empirical evidence from kernel density estimates
Herzfeld, T.; Weiss, Ch.
2007-01-01
A common finding of many analytical models is the existence of multiple equilibria of corruption. Countries characterized by the same economic, social and cultural background do not necessarily experience the same levels of corruption. In this article, we use Kernel Density Estimation techniques to
Density estimation in tiger populations: combining information for strong inference
Gopalaswamy, Arjun M.; Royle, J. Andrew; Delampady, Mohan; Nichols, James D.; Karanth, K. Ullas; Macdonald, David W.
2012-01-01
A productive way forward in studies of animal populations is to efficiently make use of all the information available, either as raw data or as published sources, on critical parameters of interest. In this study, we demonstrate two approaches to the use of multiple sources of information on a parameter of fundamental interest to ecologists: animal density. The first approach produces estimates simultaneously from two different sources of data. The second approach was developed for situations in which initial data collection and analysis are followed up by subsequent data collection and prior knowledge is updated with new data using a stepwise process. Both approaches are used to estimate density of a rare and elusive predator, the tiger, by combining photographic and fecal DNA spatial capture–recapture data. The model, which combined information, provided the most precise estimate of density (8.5 ± 1.95 tigers/100 km2 [posterior mean ± SD]) relative to a model that utilized only one data source (photographic, 12.02 ± 3.02 tigers/100 km2 and fecal DNA, 6.65 ± 2.37 tigers/100 km2). Our study demonstrates that, by accounting for multiple sources of available information, estimates of animal density can be significantly improved.
Regularized Regression and Density Estimation based on Optimal Transport
Burger, M.
2012-03-11
The aim of this paper is to investigate a novel nonparametric approach for estimating and smoothing density functions as well as probability densities from discrete samples based on a variational regularization method with the Wasserstein metric as a data fidelity. The approach allows a unified treatment of discrete and continuous probability measures and is hence attractive for various tasks. In particular, the variational model for special regularization functionals yields a natural method for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations and provide a detailed analysis. Moreover, we compute special self-similar solutions for standard regularization functionals and we discuss several computational approaches and results. © 2012 The Author(s).
Simplified large African carnivore density estimators from track indices
Directory of Open Access Journals (Sweden)
Christiaan W. Winterbach
2016-12-01
Full Text Available Background The range, population size and trend of large carnivores are important parameters to assess their status globally and to plan conservation strategies. One can use linear models to assess population size and trends of large carnivores from track-based surveys on suitable substrates. The conventional approach of a linear model with intercept may not intercept at zero, but may fit the data better than linear model through the origin. We assess whether a linear regression through the origin is more appropriate than a linear regression with intercept to model large African carnivore densities and track indices. Methods We did simple linear regression with intercept analysis and simple linear regression through the origin and used the confidence interval for ß in the linear model y = αx + ß, Standard Error of Estimate, Mean Squares Residual and Akaike Information Criteria to evaluate the models. Results The Lion on Clay and Low Density on Sand models with intercept were not significant (P > 0.05. The other four models with intercept and the six models thorough origin were all significant (P < 0.05. The models using linear regression with intercept all included zero in the confidence interval for ß and the null hypothesis that ß = 0 could not be rejected. All models showed that the linear model through the origin provided a better fit than the linear model with intercept, as indicated by the Standard Error of Estimate and Mean Square Residuals. Akaike Information Criteria showed that linear models through the origin were better and that none of the linear models with intercept had substantial support. Discussion Our results showed that linear regression through the origin is justified over the more typical linear regression with intercept for all models we tested. A general model can be used to estimate large carnivore densities from track densities across species and study areas. The formula observed track density = 3.26
SVM for density estimation and application to medical image segmentation
Institute of Scientific and Technical Information of China (English)
ZHANG Zhao; ZHANG Su; ZHANG Chen-xi; CHEN Ya-zhu
2006-01-01
A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the structure from training images. When segmenting a novel image similar to the training images, the technique of narrow level set method is used. The higher dimensional surface evolution metric is defined by the prior model instead of by energy minimization function. This method offers several advantages. First, SVM for density estimation is consistent and its solution is sparse. Second, compared to the traditional level set methods, this method incorporates shape information on the object to be segmented into the segmentation process.Segmentation results are demonstrated on synthetic images, MR images and ultrasonic images.
Institute of Scientific and Technical Information of China (English)
Lukui Yang; Long Li; Xiangyu Cui; Dalei Yang
2015-01-01
Objective The purpose of this study was to evaluate the distribution of vascular endothelial growth factor (VEGF) and CD105-microvessel density (MVD) in invasive breast carcinomas. We also aimed to analyze the relationship between VEGF and MVD expression with other standard prognostic parameters associated with invasive breast cancer, such as size, grade, stage of the cancer, metastases, and tumor recurrence. Methods Immunohistochemistry via the Ultra SensitiveTM S-P method was used to detect VEGF and MVD expression in 128 cases of invasive breast carcinoma. Specimens were evaluated for CD105 expres-sion. Positively stained microvessels were counted in dense vascular foci under 400× magnification. MVD in the peripheral area adjacent to the lesion and in the central area within the lesion in invasive breast carcinomas and benign leisions groups were also assessed. Fifty cases of benign breast disease tissue were selected as the control group. Results Results showed that 64.1% of invasive breast cancer samples were VEGF-positive, higher than in benign breast disease tissue (22.0%, P 0.05). MVD of the peripheral area adja-cent to the lesion was significantly higher than those central area within the lesion in both invasive breast cancer and benign breast disease groups (P 50 years) or the two tumor diameter groups (≤2 cm vs.>2 cm), P > 0.05. Conclusion Overexpression of VEGF and MVD may be important biological markers for invasion and lymph node and distant metastases of invasive breast cancer. Combined detection of the two tumor mark-ers could provide better prognostic monitoring for disease recurrence and metastasis, as wel as aid with clinical staging of breast tumors. Prediction of the risk for metastasis and recurrence, as wel as recurrence patterns based on VEGF and MVD post-surgery, could aid design of better fol ow-up regimens and appro-priate treatment strategies for breast cancer patients.
The prognostic relevance of estimates of proliferative activity in early breast cancer
DEFF Research Database (Denmark)
Offersen, B V; Sørensen, Flemming Brandt; Knoop, A;
2003-01-01
clinicopathological parameters at diagnosis in early breast cancer patients. MATERIALS AND METHODS: Tumour specimens from 365 consecutively treated breast cancer patients were immunostained for MIB-1 and evaluated under the microscope using systematic random sampling accomplished by the CAST-grid system. RESULTS...... and number of mitoses included in the analysis, MIB-1 estimates showed no independent prognostic impact. CONCLUSIONS: High MIB-1 estimates did not add independent prognostic information at diagnosis when evaluated together with classical prognostic markers of early breast cancer....
Evaluating lidar point densities for effective estimation of aboveground biomass
Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason M.; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.
2016-01-01
The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.
2013-01-01
AD_________________ Award Number: W81XWH-08-1-0503 TITLE: Noninvasive Subharmonic Pressure...SUBTITLE 5a. CONTRACT NUMBER Noninvasive Subharmonic Pressure Estimation for Monitoring Breast Cancer Response to Neoadjuvant Therapy 5b. GRANT...SUBTITLE Noninvasive Subharmonic Pressure Estimation for Monitoring Breast Cancer 5. FUNDING NUMBERS W81XWH-08-1-0503 6. AUTHOR(S) Flemming
Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring
DEFF Research Database (Denmark)
Kallenberg, Michiel Gijsbertus J.; Petersen, Peter Kersten; Nielsen, Mads
2016-01-01
Mammographic risk scoring has commonly been automated by extracting a set of handcrafted features from mammograms, and relating the responses directly or indirectly to breast cancer risk. We present a method that learns a feature hierarchy from unlabeled data. When the learned features are used...... as the input to a simple classifier, two different tasks can be addressed: i) breast density segmentation, and ii) scoring of mammographic texture. The proposed model learns features at multiple scales. To control the models capacity a novel sparsity regularizer is introduced that incorporates both lifetime...... and population sparsity. We evaluated our method on three different clinical datasets. Our state-of-the-art results show that the learned breast density scores have a very strong positive relationship with manual ones, and that the learned texture scores are predictive of breast cancer. The model is easy...
Comparison of bone mineral density in young patients with breast cancer and healthy women
Directory of Open Access Journals (Sweden)
Sousan Kolahi
2014-05-01
Full Text Available BACKGROUND: Almost 1 in 8 women will have breast cancer during their lifetime. Several risk factors were identified; however, 70% of females with breast cancer have no risk factors. Many risk factors are associated with sex steroid hormones. Some studies have been focused on identification of the indices of cumulative exposures to estrogen during the patients’ life. One of these indicators is bone mineral density (BMD. Our aim was the comparison of BMD in young patients with and without breast cancer, and finding a relationship between breast cancer and bone density. METHODS: In this case-control study, 120 people were enrolled; 40 patients with breast cancer and 80 normal healthy persons as control group. Measurement of BMD was performed in both groups and compared. RESULTS: Both groups were matched in age, weight, age at menarche, age at first marriage and first pregnancy, number of pregnancies over 32 weeks and lactation period, and taking supplemental calcium and vitamin D. However, there was a significant difference between the two groups in terms of estrogen intake, family history of breast cancer, and history of breast masses (P = 0.03, P = 0.03, P ≤ 0.01, respectively. A significant difference was found between BMD, bone mineral content (BMC, and t-scores of lumbar spine of the two groups; they were higher in the control group (P = 0.08, P ≤ 0.01, P = 0.06, respectively. CONCLUSIONS: This study shows that bone mineral density of young patients with breast cancer is not higher than normal similar age females; thus, BMD is not directly a risk factor for breast cancer.
Open-cluster density profiles derived using a kernel estimator
Seleznev, Anton F
2016-01-01
Surface and spatial radial density profiles in open clusters are derived using a kernel estimator method. Formulae are obtained for the contribution of every star into the spatial density profile. The evaluation of spatial density profiles is tested against open-cluster models from N-body experiments with N = 500. Surface density profiles are derived for seven open clusters (NGC 1502, 1960, 2287, 2516, 2682, 6819 and 6939) using Two-Micron All-Sky Survey data and for different limiting magnitudes. The selection of an optimal kernel half-width is discussed. It is shown that open-cluster radius estimates hardly depend on the kernel half-width. Hints of stellar mass segregation and structural features indicating cluster non-stationarity in the regular force field are found. A comparison with other investigations shows that the data on open-cluster sizes are often underestimated. The existence of an extended corona around the open cluster NGC 6939 was confirmed. A combined function composed of the King density pr...
Bayesian error estimation in density-functional theory
DEFF Research Database (Denmark)
Mortensen, Jens Jørgen; Kaasbjerg, Kristen; Frederiksen, Søren Lund;
2005-01-01
We present a practical scheme for performing error estimates for density-functional theory calculations. The approach, which is based on ideas from Bayesian statistics, involves creating an ensemble of exchange-correlation functionals by comparing with an experimental database of binding energies...... for molecules and solids. Fluctuations within the ensemble can then be used to estimate errors relative to experiment on calculated quantities such as binding energies, bond lengths, and vibrational frequencies. It is demonstrated that the error bars on energy differences may vary by orders of magnitude...
Photo-z Estimation: An Example of Nonparametric Conditional Density Estimation under Selection Bias
Izbicki, Rafael; Freeman, Peter E
2016-01-01
Redshift is a key quantity for inferring cosmological model parameters. In photometric redshift estimation, cosmologists use the coarse data collected from the vast majority of galaxies to predict the redshift of individual galaxies. To properly quantify the uncertainty in the predictions, however, one needs to go beyond standard regression and instead estimate the full conditional density f(z|x) of a galaxy's redshift z given its photometric covariates x. The problem is further complicated by selection bias: usually only the rarest and brightest galaxies have known redshifts, and these galaxies have characteristics and measured covariates that do not necessarily match those of more numerous and dimmer galaxies of unknown redshift. Unfortunately, there is not much research on how to best estimate complex multivariate densities in such settings. Here we describe a general framework for properly constructing and assessing nonparametric conditional density estimators under selection bias, and for combining two o...
Large Scale Density Estimation of Blue and Fin Whales (LSD)
2014-09-30
interactions with human activity requires knowledge of how many animals are present in an area during a specific time period. Many marine mammal species ...Ocean at Wake Island will then be applied to the same species in the Indian Ocean at the CTBTO location at Diego Garcia. 1. Develop and implement...proposed density estimation method is also highly dependent on call rate inputs, which are used in the development of species specific multipliers for
Some Bayesian statistical techniques useful in estimating frequency and density
Johnson, D.H.
1977-01-01
This paper presents some elementary applications of Bayesian statistics to problems faced by wildlife biologists. Bayesian confidence limits for frequency of occurrence are shown to be generally superior to classical confidence limits. Population density can be estimated from frequency data if the species is sparsely distributed relative to the size of the sample plot. For other situations, limits are developed based on the normal distribution and prior knowledge that the density is non-negative, which insures that the lower confidence limit is non-negative. Conditions are described under which Bayesian confidence limits are superior to those calculated with classical methods; examples are also given on how prior knowledge of the density can be used to sharpen inferences drawn from a new sample.
Hreshchyshyn, M M; Hopkins, A; Zylstra, S; Anbar, M
1988-08-01
The relationships between parity, breast-feeding, and the use of birth control pills and the bone densities of the lumbar spine and the femoral neck, measured by dual-photon densitometry, were studied in normal women. Femoral neck density was found to decrease by 1.1% per live-birth, whereas lumbar spine density showed no significant association with parity. Breast-feeding was found to increase lumbar spine density by 1.5% per breast-fed child, whereas femoral neck density was not significantly correlated. No significant relationships between the use of birth control pills and the bone densities were found.
Estimation of health state utilities in breast cancer
Directory of Open Access Journals (Sweden)
Kim SH
2017-03-01
Full Text Available Seon-Ha Kim,1 Min-Woo Jo,2 Minsu Ock,2 Hyeon-Jeong Lee,2 Jong-Won Lee3,4 1Department of Nursing, College of Nursing, Dankook University, Cheonan, 2Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, 3Department of Breast and Endocrine Surgery, Asan Medical Center, Seoul, 4Department of Surgery, University of Ulsan College of Medicine, Seoul, South Korea Purpose: The aim of this study is to determine the utility of breast cancer health states using the standard gamble (SG and visual analog scale (VAS methods in the Korean general population.Materials and methods: Eight hypothetical breast cancer health states were developed based on patient education material and previous publications. Data from 509 individuals from the Korean general population were used to evaluate breast cancer health states using the VAS and the SG methods, which were obtained via computer-assisted personal interviews. Mean utility values were calculated for each human papillomavirus (HPV-related health state.Results: The rank of health states was identical between two valuation methods. SG values were higher than VAS values in all health states. The utility values derived from SG were 0.801 (noninvasive breast cancer with mastectomy and followed by reconstruction, 0.790 (noninvasive breast cancer with mastectomy only, 0.779 (noninvasive breast cancer with breast-conserving surgery and radiation therapy, 0.731 (invasive breast cancer with surgery, radiation therapy, and/or chemotherapy, 0.610 (locally advanced breast cancer with radical mastectomy with radiation therapy, 0.587 (inoperable locally advanced breast cancer, 0.496 (loco-regional recurrent breast cancer, and 0.352 (metastatic breast cancer.Conclusion: Our findings might be useful for economic evaluation of breast cancer screening and interventions in general populations. Keywords: breast neoplasm, Korea, quality-adjusted life years, quality of life
Fu, Wanyi; Tian, Xiaoyu; Sturgeon, Gregory; Agasthya, Greeshma; Segars, William Paul; Goodsitt, Mitchell M.; Kazerooni, Ella A.; Samei, Ehsan
2016-04-01
In thoracic CT, organ-based tube current modulation (OTCM) reduces breast dose by lowering the tube current in the 120° anterior dose reduction zone of patients. However, in practice the breasts usually expand to an angle larger than the dose reduction zone. This work aims to simulate a breast positioning technique (BPT) to constrain the breast tissue to within the dose reduction zone for OTCM and to evaluate the corresponding potential reduction in breast dose. Thirteen female anthropomorphic computational phantoms were studied (age range: 27-65 y.o., weight range: 52-105.8 kg). Each phantom was modeled in the supine position with and without application of the BPT. Attenuation-based tube current (ATCM, reference mA) was generated by a ray-tracing program, taking into account the patient attenuation change in the longitudinal and angular plane (CAREDose4D, Siemens Healthcare). OTCM was generated by reducing the mA to 20% between +/- 60° anterior of the patient and increasing the mA in the remaining projections correspondingly (X-CARE, Siemens Healthcare) to maintain the mean tube current. Breast tissue dose was estimated using a validated Monte Carlo program for a commercial scanner (SOMATOM Definition Flash, Siemens Healthcare). Compared to standard tube current modulation, breast dose was significantly reduced using OTCM by 19.8+/-4.7%. With the BPT, breast dose was reduced by an additional 20.4+/-6.5% to 37.1+/-6.9%, using the same CTDIvol. BPT was more effective for phantoms simulating women with larger breasts with the average breast dose reduction of 30.2%, 39.2%, and 49.2% from OTCMBP to ATCM, using the same CTDIvol for phantoms with 0.5, 1.5, and 2.5 kg breasts, respectively. This study shows that a specially designed BPT improves the effectiveness of OTCM.
Accurate photometric redshift probability density estimation - method comparison and application
Rau, Markus Michael; Brimioulle, Fabrice; Frank, Eibe; Friedrich, Oliver; Gruen, Daniel; Hoyle, Ben
2015-01-01
We introduce an ordinal classification algorithm for photometric redshift estimation, which vastly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples. As a use case we apply our method to CFHTLS galaxies. The ordinal classification algorithm treats distinct redshift bins as ordered values, which improves the quality of photometric redshift PDFs, compared with non-ordinal classification architectures. We also propose a new single value point estimate of the galaxy redshift, that can be used to estimate the full redshift PDF of a galaxy sample. This method is competitive in terms of accuracy with contemporary algorithms, which stack the full redshift PDFs of all galaxies in the sample, but requires orders of magnitudes less storage space. The methods described in this paper greatly improve the log-likelihood of individual object redshift PDFs, when compared with a popular Neural Network code (ANNz). In our use case, this improvemen...
Eskelson, Bianca N.I.; Hagar, Joan; Temesgen, Hailemariam
2012-01-01
Snags (standing dead trees) are an essential structural component of forests. Because wildlife use of snags depends on size and decay stage, snag density estimation without any information about snag quality attributes is of little value for wildlife management decision makers. Little work has been done to develop models that allow multivariate estimation of snag density by snag quality class. Using climate, topography, Landsat TM data, stand age and forest type collected for 2356 forested Forest Inventory and Analysis plots in western Washington and western Oregon, we evaluated two multivariate techniques for their abilities to estimate density of snags by three decay classes. The density of live trees and snags in three decay classes (D1: recently dead, little decay; D2: decay, without top, some branches and bark missing; D3: extensive decay, missing bark and most branches) with diameter at breast height (DBH) ≥ 12.7 cm was estimated using a nonparametric random forest nearest neighbor imputation technique (RF) and a parametric two-stage model (QPORD), for which the number of trees per hectare was estimated with a Quasipoisson model in the first stage and the probability of belonging to a tree status class (live, D1, D2, D3) was estimated with an ordinal regression model in the second stage. The presence of large snags with DBH ≥ 50 cm was predicted using a logistic regression and RF imputation. Because of the more homogenous conditions on private forest lands, snag density by decay class was predicted with higher accuracies on private forest lands than on public lands, while presence of large snags was more accurately predicted on public lands, owing to the higher prevalence of large snags on public lands. RF outperformed the QPORD model in terms of percent accurate predictions, while QPORD provided smaller root mean square errors in predicting snag density by decay class. The logistic regression model achieved more accurate presence/absence classification
Zheng, Yuanjie; Wang, Yan; Keller, Brad M.; Conant, Emily; Gee, James C.; Kontos, Despina
2013-02-01
Estimating a woman's risk of breast cancer is becoming increasingly important in clinical practice. Mammographic density, estimated as the percent of dense (PD) tissue area within the breast, has been shown to be a strong risk factor. Studies also support a relationship between mammographic texture and breast cancer risk. We have developed a fullyautomated software pipeline for computerized analysis of digital mammography parenchymal patterns by quantitatively measuring both breast density and texture properties. Our pipeline combines advanced computer algorithms of pattern recognition, computer vision, and machine learning and offers a standardized tool for breast cancer risk assessment studies. Different from many existing methods performing parenchymal texture analysis within specific breast subregions, our pipeline extracts texture descriptors for points on a spatial regular lattice and from a surrounding window of each lattice point, to characterize the local mammographic appearance throughout the whole breast. To demonstrate the utility of our pipeline, and optimize its parameters, we perform a case-control study by retrospectively analyzing a total of 472 digital mammography studies. Specifically, we investigate the window size, which is a lattice related parameter, and compare the performance of texture features to that of breast PD in classifying case-control status. Our results suggest that different window sizes may be optimal for raw (12.7mm2) versus vendor post-processed images (6.3mm2). We also show that the combination of PD and texture features outperforms PD alone. The improvement is significant (p=0.03) when raw images and window size of 12.7mm2 are used, having an ROC AUC of 0.66. The combination of PD and our texture features computed from post-processed images with a window size of 6.3 mm2 achieves an ROC AUC of 0.75.
A projection and density estimation method for knowledge discovery.
Directory of Open Access Journals (Sweden)
Adam Stanski
Full Text Available A key ingredient to modern data analysis is probability density estimation. However, it is well known that the curse of dimensionality prevents a proper estimation of densities in high dimensions. The problem is typically circumvented by using a fixed set of assumptions about the data, e.g., by assuming partial independence of features, data on a manifold or a customized kernel. These fixed assumptions limit the applicability of a method. In this paper we propose a framework that uses a flexible set of assumptions instead. It allows to tailor a model to various problems by means of 1d-decompositions. The approach achieves a fast runtime and is not limited by the curse of dimensionality as all estimations are performed in 1d-space. The wide range of applications is demonstrated at two very different real world examples. The first is a data mining software that allows the fully automatic discovery of patterns. The software is publicly available for evaluation. As a second example an image segmentation method is realized. It achieves state of the art performance on a benchmark dataset although it uses only a fraction of the training data and very simple features.
Directory of Open Access Journals (Sweden)
Svjetlana Mujagić
2011-11-01
Full Text Available Objective. Th e aim of this study was to analyse the sensitivity and specificity of ultrasound and mammography according to breast densityand determine which of these diagnostic imagings is a more accuratetest for diagnosis of breast cancer. Patients and methods. By meansof a cross-sectional study, ultrasound and mammographic examinationsof 148 women with breast disease symptoms were analysed.All women underwent surgery and all lesions were examined by histological examination which revealed the presence of 63 breast cancers,and 85 benign lesions. Histological examination was used as the “goldstandard”. In relation to breast density, the women were separated into two groups, group A: women with “fatty breast” (ACR BI-RADS density categories 1 and 2 and group B: women with “dense breast”(categories 3 and 4. Ultrasound and mammographic findings were classified on the BI-RADS categorical scale of 1-5. For statistical data processing, the logistic regression analysis and the McNemar chi-square test for paired proportions was used. Th e differences on the level of p<0.05 were considered statistically significant. Results. In the group of women with breast density categories 1 and 2 the difference in the sensitivities (p=1 as well as in the specificities (p=0.11 of the two imaging tests was not statistically significant. In the group of women with breast density categories 3 and 4 the ultrasound sensitivity was significantly higher than the mammographic sensitivity (p=0.03 without a statistically significant difference in specificity (p=0.26. Sensitivity of mammography was (linearly – ex; linearity exists between breast density and the logarithm of odds for a positive result associated with breast density (likelihood ratio χ2 =15.99, p =0.0001. Th e odds ratio for (the probability of – ex a positive mammographic result was 0.25 (95% CI, 0.11-0.58. Thesensitivity of ultrasound and specificity of each test were not (linearly - ex
Effect of Random Clustering on Surface Damage Density Estimates
Energy Technology Data Exchange (ETDEWEB)
Matthews, M J; Feit, M D
2007-10-29
Identification and spatial registration of laser-induced damage relative to incident fluence profiles is often required to characterize the damage properties of laser optics near damage threshold. Of particular interest in inertial confinement laser systems are large aperture beam damage tests (>1cm{sup 2}) where the number of initiated damage sites for {phi}>14J/cm{sup 2} can approach 10{sup 5}-10{sup 6}, requiring automatic microscopy counting to locate and register individual damage sites. However, as was shown for the case of bacteria counting in biology decades ago, random overlapping or 'clumping' prevents accurate counting of Poisson-distributed objects at high densities, and must be accounted for if the underlying statistics are to be understood. In this work we analyze the effect of random clumping on damage initiation density estimates at fluences above damage threshold. The parameter {psi} = a{rho} = {rho}/{rho}{sub 0}, where a = 1/{rho}{sub 0} is the mean damage site area and {rho} is the mean number density, is used to characterize the onset of clumping, and approximations based on a simple model are used to derive an expression for clumped damage density vs. fluence and damage site size. The influence of the uncorrected {rho} vs. {phi} curve on damage initiation probability predictions is also discussed.
A Concept of Approximated Densities for Efficient Nonlinear Estimation
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Virginie F. Ruiz
2002-10-01
Full Text Available This paper presents the theoretical development of a nonlinear adaptive filter based on a concept of filtering by approximated densities (FAD. The most common procedures for nonlinear estimation apply the extended Kalman filter. As opposed to conventional techniques, the proposed recursive algorithm does not require any linearisation. The prediction uses a maximum entropy principle subject to constraints. Thus, the densities created are of an exponential type and depend on a finite number of parameters. The filtering yields recursive equations involving these parameters. The update applies the Bayes theorem. Through simulation on a generic exponential model, the proposed nonlinear filter is implemented and the results prove to be superior to that of the extended Kalman filter and a class of nonlinear filters based on partitioning algorithms.
Estimation of probability densities using scale-free field theories.
Kinney, Justin B
2014-07-01
The question of how best to estimate a continuous probability density from finite data is an intriguing open problem at the interface of statistics and physics. Previous work has argued that this problem can be addressed in a natural way using methods from statistical field theory. Here I describe results that allow this field-theoretic approach to be rapidly and deterministically computed in low dimensions, making it practical for use in day-to-day data analysis. Importantly, this approach does not impose a privileged length scale for smoothness of the inferred probability density, but rather learns a natural length scale from the data due to the tradeoff between goodness of fit and an Occam factor. Open source software implementing this method in one and two dimensions is provided.
Othman, Khairulnizam; Ahmad, Afandi
2016-11-01
In this research we explore the application of normalize denoted new techniques in advance fast c-mean in to the problem of finding the segment of different breast tissue regions in mammograms. The goal of the segmentation algorithm is to see if new denotes fuzzy c- mean algorithm could separate different densities for the different breast patterns. The new density segmentation is applied with multi-selection of seeds label to provide the hard constraint, whereas the seeds labels are selected based on user defined. New denotes fuzzy c- mean have been explored on images of various imaging modalities but not on huge format digital mammograms just yet. Therefore, this project is mainly focused on using normalize denoted new techniques employed in fuzzy c-mean to perform segmentation to increase visibility of different breast densities in mammography images. Segmentation of the mammogram into different mammographic densities is useful for risk assessment and quantitative evaluation of density changes. Our proposed methodology for the segmentation of mammograms on the basis of their region into different densities based categories has been tested on MIAS database and Trueta Database.
2013-10-01
thermometers and pie charts. We produced two 2-minutes videos about the UVA Mammography Project. The last video was posted on September 6, 2013 and...HIGH RISK LESION 7 BREAST SIZE 8 BREAST TISSUE DENSITY 9 BREASTFEEDING 10 CHEST RADIATION EXPOSURE 11 DIET/WHAT YOU EAT 12 FAMILY HISTORY OF
Time of flight estimation for breast cancer margin thickness using embedded tumors
Bowman, Tyler; El-Shenawee, Magda; Campbell, Lucas
2016-03-01
This work aims to enact a quick and reasonable estimation of breast cancer margin thickness using time of flight analysis of embedded breast cancer tissue. A pulsed terahertz system is used to obtain reflection imaging scans from breast cancer tumors that are formalin-fixed and embedded in paraffin blocks. Time of flight analysis is then used to compare the reflection patterns seen within the block to pathology sections and paraffin-embedded sections that are taken throughout the depth of the tumor in order to estimate the three-dimensional boundaries of the tumor.
2009-09-01
TITLE AND SUBTITLE Noninvasive Subharmonic Pressure Estimation for Monitoring Breast Cancer 5. FUNDING NUMBERS W81XWH-08-1-0503 6. AUTHOR(S...u sing subharmonic aided p ressure estimation (SHAPE ) to estimate the inte rstitial fluid pressure (IFP) in LABC. To date, in vitr o experiments
Change-in-ratio density estimator for feral pigs is less biased than closed mark-recapture estimates
Hanson, L.B.; Grand, J.B.; Mitchell, M.S.; Jolley, D.B.; Sparklin, B.D.; Ditchkoff, S.S.
2008-01-01
Closed-population capture-mark-recapture (CMR) methods can produce biased density estimates for species with low or heterogeneous detection probabilities. In an attempt to address such biases, we developed a density-estimation method based on the change in ratio (CIR) of survival between two populations where survival, calculated using an open-population CMR model, is known to differ. We used our method to estimate density for a feral pig (Sus scrofa) population on Fort Benning, Georgia, USA. To assess its validity, we compared it to an estimate of the minimum density of pigs known to be alive and two estimates based on closed-population CMR models. Comparison of the density estimates revealed that the CIR estimator produced a density estimate with low precision that was reasonable with respect to minimum known density. By contrast, density point estimates using the closed-population CMR models were less than the minimum known density, consistent with biases created by low and heterogeneous capture probabilities for species like feral pigs that may occur in low density or are difficult to capture. Our CIR density estimator may be useful for tracking broad-scale, long-term changes in species, such as large cats, for which closed CMR models are unlikely to work. ?? CSIRO 2008.
Probability Density and CFAR Threshold Estimation for Hyperspectral Imaging
Energy Technology Data Exchange (ETDEWEB)
Clark, G A
2004-09-21
The work reported here shows the proof of principle (using a small data set) for a suite of algorithms designed to estimate the probability density function of hyperspectral background data and compute the appropriate Constant False Alarm Rate (CFAR) matched filter decision threshold for a chemical plume detector. Future work will provide a thorough demonstration of the algorithms and their performance with a large data set. The LASI (Large Aperture Search Initiative) Project involves instrumentation and image processing for hyperspectral images of chemical plumes in the atmosphere. The work reported here involves research and development on algorithms for reducing the false alarm rate in chemical plume detection and identification algorithms operating on hyperspectral image cubes. The chemical plume detection algorithms to date have used matched filters designed using generalized maximum likelihood ratio hypothesis testing algorithms [1, 2, 5, 6, 7, 12, 10, 11, 13]. One of the key challenges in hyperspectral imaging research is the high false alarm rate that often results from the plume detector [1, 2]. The overall goal of this work is to extend the classical matched filter detector to apply Constant False Alarm Rate (CFAR) methods to reduce the false alarm rate, or Probability of False Alarm P{sub FA} of the matched filter [4, 8, 9, 12]. A detector designer is interested in minimizing the probability of false alarm while simultaneously maximizing the probability of detection P{sub D}. This is summarized by the Receiver Operating Characteristic Curve (ROC) [10, 11], which is actually a family of curves depicting P{sub D} vs. P{sub FA}parameterized by varying levels of signal to noise (or clutter) ratio (SNR or SCR). Often, it is advantageous to be able to specify a desired P{sub FA} and develop a ROC curve (P{sub D} vs. decision threshold r{sub 0}) for that case. That is the purpose of this work. Specifically, this work develops a set of algorithms and MATLAB
Collagen Matrix Density Drives the Metabolic Shift in Breast Cancer Cells
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Brett A. Morris
2016-11-01
Full Text Available Increased breast density attributed to collagen I deposition is associated with a 4–6 fold increased risk of developing breast cancer. Here, we assessed cellular metabolic reprogramming of mammary carcinoma cells in response to increased collagen matrix density using an in vitro 3D model. Our initial observations demonstrated changes in functional metabolism in both normal mammary epithelial cells and mammary carcinoma cells in response to changes in matrix density. Further, mammary carcinoma cells grown in high density collagen matrices displayed decreased oxygen consumption and glucose metabolism via the tricarboxylic acid (TCA cycle compared to cells cultured in low density matrices. Despite decreased glucose entry into the TCA cycle, levels of glucose uptake, cell viability, and ROS were not different between high and low density matrices. Interestingly, under high density conditions the contribution of glutamine as a fuel source to drive the TCA cycle was significantly enhanced. These alterations in functional metabolism mirrored significant changes in the expression of metabolic genes involved in glycolysis, oxidative phosphorylation, and the serine synthesis pathway. This study highlights the broad importance of the collagen microenvironment to cellular expression profiles, and shows that changes in density of the collagen microenvironment can modulate metabolic shifts of cancer cells.
Collagen Matrix Density Drives the Metabolic Shift in Breast Cancer Cells.
Morris, Brett A; Burkel, Brian; Ponik, Suzanne M; Fan, Jing; Condeelis, John S; Aguire-Ghiso, Julio A; Castracane, James; Denu, John M; Keely, Patricia J
2016-11-01
Increased breast density attributed to collagen I deposition is associated with a 4-6 fold increased risk of developing breast cancer. Here, we assessed cellular metabolic reprogramming of mammary carcinoma cells in response to increased collagen matrix density using an in vitro 3D model. Our initial observations demonstrated changes in functional metabolism in both normal mammary epithelial cells and mammary carcinoma cells in response to changes in matrix density. Further, mammary carcinoma cells grown in high density collagen matrices displayed decreased oxygen consumption and glucose metabolism via the tricarboxylic acid (TCA) cycle compared to cells cultured in low density matrices. Despite decreased glucose entry into the TCA cycle, levels of glucose uptake, cell viability, and ROS were not different between high and low density matrices. Interestingly, under high density conditions the contribution of glutamine as a fuel source to drive the TCA cycle was significantly enhanced. These alterations in functional metabolism mirrored significant changes in the expression of metabolic genes involved in glycolysis, oxidative phosphorylation, and the serine synthesis pathway. This study highlights the broad importance of the collagen microenvironment to cellular expression profiles, and shows that changes in density of the collagen microenvironment can modulate metabolic shifts of cancer cells.
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...Utilizing Sparse Array Data to Develop and Implement a New Method for Estimating Blue and Fin Whale Density Len Thomas & Danielle Harris Centre...to develop and implement a new method for estimating blue and fin whale density that is effective over large spatial scales and is designed to cope
Some asymptotic results on density estimators by wavelet projections
Varron, Davit
2012-01-01
Let $(X_i)_{i\\geq 1}$ be an i.i.d. sample on $\\RRR^d$ having density $f$. Given a real function $\\phi$ on $\\RRR^d$ with finite variation and given an integer valued sequence $(j_n)$, let $\\fn$ denote the estimator of $f$ by wavelet projection based on $\\phi$ and with multiresolution level equal to $j_n$. We provide exact rates of almost sure convergence to 0 of the quantity $\\sup_{x\\in H}\\mid \\fn(x)-\\EEE(\\fn)(x)\\mid$, when $n2^{-dj_n}/\\log n \\rar \\infty$ and $H$ is a given hypercube of $\\RRR^d$. We then show that, if $n2^{-dj_n}/\\log n \\rar c$ for a constant $c>0$, then the quantity $\\sup_{x\\in H}\\mid \\fn(x)-f\\mid$ almost surely fails to converge to 0.
An Adaptive Background Subtraction Method Based on Kernel Density Estimation
Directory of Open Access Journals (Sweden)
Mignon Park
2012-09-01
Full Text Available In this paper, a pixel-based background modeling method, which uses nonparametric kernel density estimation, is proposed. To reduce the burden of image storage, we modify the original KDE method by using the first frame to initialize it and update it subsequently at every frame by controlling the learning rate according to the situations. We apply an adaptive threshold method based on image changes to effectively subtract the dynamic backgrounds. The devised scheme allows the proposed method to automatically adapt to various environments and effectively extract the foreground. The method presented here exhibits good performance and is suitable for dynamic background environments. The algorithm is tested on various video sequences and compared with other state-of-the-art background subtraction methods so as to verify its performance.
Cortical cell and neuron density estimates in one chimpanzee hemisphere.
Collins, Christine E; Turner, Emily C; Sawyer, Eva Kille; Reed, Jamie L; Young, Nicole A; Flaherty, David K; Kaas, Jon H
2016-01-19
The density of cells and neurons in the neocortex of many mammals varies across cortical areas and regions. This variability is, perhaps, most pronounced in primates. Nonuniformity in the composition of cortex suggests regions of the cortex have different specializations. Specifically, regions with densely packed neurons contain smaller neurons that are activated by relatively few inputs, thereby preserving information, whereas regions that are less densely packed have larger neurons that have more integrative functions. Here we present the numbers of cells and neurons for 742 discrete locations across the neocortex in a chimpanzee. Using isotropic fractionation and flow fractionation methods for cell and neuron counts, we estimate that neocortex of one hemisphere contains 9.5 billion cells and 3.7 billion neurons. Primary visual cortex occupies 35 cm(2) of surface, 10% of the total, and contains 737 million densely packed neurons, 20% of the total neurons contained within the hemisphere. Other areas of high neuron packing include secondary visual areas, somatosensory cortex, and prefrontal granular cortex. Areas of low levels of neuron packing density include motor and premotor cortex. These values reflect those obtained from more limited samples of cortex in humans and other primates.
2014-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Cheap DECAF: Density Estimation for Cetaceans from... cetaceans using passive fixed acoustics rely on large, dense arrays of cabled hydrophones and/or auxiliary information from animal tagging projects...estimating cetacean density. Therefore, the goal of Cheap DECAF is to focus on the development of cetacean density estimation methods using sensors that
Fiora, Alessandro; Cescatti, Alessandro
2006-09-01
Daily and seasonal patterns in radial distribution of sap flux density were monitored in six trees differing in social position in a mixed coniferous stand dominated by silver fir (Abies alba Miller) and Norway spruce (Picea abies (L.) Karst) in the Alps of northeastern Italy. Radial distribution of sap flux was measured with arrays of 1-cm-long Granier probes. The radial profiles were either Gaussian or decreased monotonically toward the tree center, and seemed to be related to social position and crown distribution of the trees. The ratio between sap flux estimated with the most external sensor and the mean flux, weighted with the corresponding annulus areas, was used as a correction factor (CF) to express diurnal and seasonal radial variation in sap flow. During sunny days, the diurnal radial profile of sap flux changed with time and accumulated photosynthetic active radiation (PAR), with an increasing contribution of sap flux in the inner sapwood during the day. Seasonally, the contribution of sap flux in the inner xylem increased with daily cumulative PAR and the variation of CF was proportional to the tree diameter, ranging from 29% for suppressed trees up to 300% for dominant trees. Two models were developed, relating CF with PAR and tree diameter at breast height (DBH), to correct daily and seasonal estimates of whole-tree and stand sap flow obtained by assuming uniform sap flux density over the sapwood. If the variability in the radial profile of sap flux density was not accounted for, total stand transpiration would be overestimated by 32% during sunny days and 40% for the entire season.
Total Xenoestrogen Body Burden in Relation to Mammographic Density, a Marker of Breast Cancer Risk
2010-10-01
study population. NIH is providing funds to analyze serum levels of vitamin D, parathyroid hormone, calcium, IGF1, IGFBP3, and retinol . We presented...analysis of serum levels of 25-hydroxy vitamin D [25(OH)D], parathyroid hormone (PTH), insulin-like growth factor-1 (IGF1), retinol , and calcium...parathyroid hormone (PTH) and IGF-1. 3)To determine if the relation between Vitamin D and breast density is modified by blood levels of retinol and/or
El-Gohary, Yasser M; Metwally, Ghada; Saad, Reda S; Robinson, Morton J; Mesko, Thomas; Poppiti, Robert J
2009-01-01
We investigated the significance of periductal lymphatic and blood vascular densities in intraductal carcinomas (IDC) of the breast. Thirty five cases of pure IDC treated by partial or total mastectomy were reviewed. Seven cases with normal breast tissue and 48 cases of invasive breast carcinoma were included as controls. All cases were immunostained with D2-40 and CD31. Positively stained microvessels were counted in densely vascular/lymphatic foci (hot spots) at 400x (=0.17 mm(2)) in the periductal areas. IDC without comedonecrosis showed a mean periductal D2-40 lymphatic microvessel density (LMD) of 5.8 +/- 5 (range 0-18), and a CD31 microvessel density (MD) of 14 +/- 8.9 (range 1-40). IDC with comedonecrosis showed periductal D2-40 LMD of 8.4 +/- 3.8 (range 4-18), and a CD31 MD of 24.3 +/- 7.6 (range 14-40). There was a significant difference between periductal D2-40 LMD and CD31 MD counts in IDC with and without comedonecrosis. There was a positive correlation of periductal D2-40 LMD and CD31 MD counts with high nuclear grade (r = 0.39 and 0.56) of IDC as well as with the presence of comedonecrosis (r = 0.49 and 0.59). Both D2-40 LMD and CD31 MD did not correlate significantly with tumor size, estrogen status, or progesterone status. As IDC with comedonecrosis and/or high nuclear grade has a worse prognosis than IDC without comedonecrosis and/or with low nuclear grade, it appears that lymphatic and blood vascular density evaluated by D2-40 and CD31, respectively, are independent prognostic indicators for patients with IDC of the breast and may be an indicator of early or unrecognized invasion or "regression."
Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment
Energy Technology Data Exchange (ETDEWEB)
Zheng, Bin, E-mail: zhengb@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Sumkin, Jules H., E-mail: jsumkin@mail.magee.edu [Department of Radiology, Magee Womens Hospital, 300 Halket Street, Pittsburgh, PA 15213 (United States); Zuley, Margarita L., E-mail: zuleyml@upmc.edu [Department of Radiology, Magee Womens Hospital, 300 Halket Street, Pittsburgh, PA 15213 (United States); Wang, Xingwei, E-mail: wangx6@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Klym, Amy H., E-mail: klymah@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Gur, David, E-mail: gurd@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States)
2012-11-15
To improve efficacy of breast cancer screening and prevention programs, it requires a risk assessment model with high discriminatory power. This study aimed to assess classification performance of using computed bilateral mammographic density asymmetry to predict risk of individual women developing breast cancer in near-term. The database includes 451 cases with multiple screening mammography examinations. The first (baseline) examinations of all case were interpreted negative. In the next sequential examinations, 187 cases developed cancer or surgically excised high-risk lesions, 155 remained negative (not-recalled), and 109 were recalled benign cases. From each of two bilateral cranio-caudal view images acquired from the baseline examination, we computed two features of average pixel value and local pixel value fluctuation. We then computed mean and difference of each feature computed from two images. When applying the computed features and other two risk factors (woman's age and subjectively rated mammographic density) to predict risk of cancer development, areas under receiver operating characteristic curves (AUC) were computed to evaluate the discriminatory/classification performance. The AUCs are 0.633 {+-} 0.030, 0.535 {+-} 0.036, 0.567 {+-} 0.031, and 0.719 {+-} 0.027 when using woman's age, subjectively rated, computed mean and asymmetry of mammographic density, to classify between two groups of cancer-verified and negative cases, respectively. When using an equal-weighted fusion method to combine woman's age and computed density asymmetry, AUC increased to 0.761 {+-} 0.025 (p < 0.05). The study demonstrated that bilateral mammographic density asymmetry could be a significantly stronger risk factor associated to the risk of women developing breast cancer in near-term than woman's age and assessed mean mammographic density.
Estimating basic wood density and its uncertainty for Pinus densiflora in the Republic of Korea
Directory of Open Access Journals (Sweden)
Jung Kee Pyo
2012-05-01
Full Text Available According to the Intergovernmental Panel on Climate Change(IPCC guidelines, uncertainty assessment is an important aspect of a greenhouse gas inventory, and effort should be made to incorporate it into the reporting. The goal of this study was to estimate basic wood density (BWD and its uncertainty for Pinus densiflora (Siebold & Zucc. in Korea. In this study, P. densiflora forests throughout the country were divided into two regional variants, which were the Gangwon region variant, distributed on the northeastern part of the country, and the central region variant. A total of 36 representative sampling plots were selected in both regions to collect sampletrees for destructive sampling. The trees were selected considering the distributions of tree age and diameter at breast height. Hypothesis testing was carried out to test the BWD differences between two age groups, i.e. age ≥ 20 and < 20, and differences between the two regions. The test suggested that there was no statistically significant difference between the two age classes. On the other hand, it is suggested a strong evidence of a statistically significant difference between regions. The BWD and its uncertainty were0.418 g/cm3 and 11.9% for the Gangwon region, whereas they were 0.471g/ cm3 and 3.8% for the central region. As a result, the estimated BWD for P.densiflora was more precise than the value provided by the IPCC guidelines.
Estimating the mass density of neutral gas at $z < 1$
Natarajan, P; Natarajan, Priyamvada; Pettini, Max
1997-01-01
We use the relationships between galactic HI mass and B-band luminosity determined by Rao & Briggs to recalculate the mass density of neutral gas at the present epoch based on more recent measures of the galaxy luminosity function than were available to those authors. We find $\\Omega_{gas}(z=0) value, suggesting that this quantity is now reasonably secure. We then show that, if the scaling between H I mass and B-band luminosity has remained approximately constant since $z = 1$, the evolution of the luminosity function found by the Canada-France redshift survey translates to an increase of obtained quite independently from consideration of the luminosity function of Mg II absorbers at $z = 0.65$. By combining these new estimates with data from damped \\lya systems at higher redshift, it is possible to assemble a rough sketch of the evolution of $Ømega_{gas}$ over the last 90% of the age of the universe. The consumption of H I gas with time is in broad agreement with models of chemical evolution which inclu...
Directory of Open Access Journals (Sweden)
Saadatmand Sepideh
2012-10-01
Full Text Available Abstract Background To reduce mortality, women with a family history of breast cancer often start mammography screening at a younger age than the general population. Breast density is high in over 50% of women younger than 50 years. With high breast density, breast cancer incidence increases, but sensitivity of mammography decreases. Therefore, mammography might not be the optimal method for breast cancer screening in young women. Adding MRI increases sensitivity, but also the risk of false-positive results. The limitation of all previous MRI screening studies is that they do not contain a comparison group; all participants received both MRI and mammography. Therefore, we cannot empirically assess in which stage tumours would have been detected by either test. The aim of the Familial MRI Screening Study (FaMRIsc is to compare the efficacy of MRI screening to mammography for women with a familial risk. Furthermore, we will assess the influence of breast density. Methods/Design This Dutch multicentre, randomized controlled trial, with balanced randomisation (1:1 has a parallel grouped design. Women with a cumulative lifetime risk for breast cancer due to their family history of ≥20%, aged 30–55 years are eligible. Identified BRCA1/2 mutation carriers or women with 50% risk of carrying a mutation are excluded. Group 1 receives yearly mammography and clinical breast examination (n = 1000, and group 2 yearly MRI and clinical breast examination, and mammography biennially (n = 1000. Primary endpoints are the number and stage of the detected breast cancers in each arm. Secondary endpoints are the number of false-positive results in both screening arms. Furthermore, sensitivity and positive predictive value of both screening strategies will be assessed. Cost-effectiveness of both strategies will be assessed. Analyses will also be performed with mammographic density as stratification factor. Discussion Personalized breast cancer screening
Institute of Scientific and Technical Information of China (English)
张路平; 王鲁平; 李飚; 赵明
2015-01-01
In order to improve the performance of the probability hypothesis density (PHD) algorithm based particle filter (PF) in terms of number estimation and states extraction of multiple targets, a new probability hypothesis density filter algorithm based on marginalized particle and kernel density estimation is proposed, which utilizes the idea of marginalized particle filter to enhance the estimating performance of the PHD. The state variables are decomposed into linear and non-linear parts. The particle filter is adopted to predict and estimate the nonlinear states of multi-target after dimensionality reduction, while the Kalman filter is applied to estimate the linear parts under linear Gaussian condition. Embedding the information of the linear states into the estimated nonlinear states helps to reduce the estimating variance and improve the accuracy of target number estimation. The meanshift kernel density estimation, being of the inherent nature of searching peak value via an adaptive gradient ascent iteration, is introduced to cluster particles and extract target states, which is independent of the target number and can converge to the local peak position of the PHD distribution while avoiding the errors due to the inaccuracy in modeling and parameters estimation. Experiments show that the proposed algorithm can obtain higher tracking accuracy when using fewer sampling particles and is of lower computational complexity compared with the PF-PHD.
Breast cancer size estimation with MRI in BRCA mutation carriers and other high risk patients
Energy Technology Data Exchange (ETDEWEB)
Mann, R.M., E-mail: r.mann@rad.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Radiology, Nijmegen (Netherlands); Bult, P., E-mail: p.bult@path.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Pathology, Nijmegen (Netherlands); Laarhoven, H.W.M. van, E-mail: h.vanlaarhoven@amc.uva.nl [Academic Medical Centre, University of Amsterdam, Department of Medical Oncology, Amsterdam (Netherlands); Radboud University Nijmegen Medical Centre, Department of Medical Oncology, Nijmegen (Netherlands); Span, P.N., E-mail: p.span@rther.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Radiation Oncology, Nijmegen (Netherlands); Schlooz, M., E-mail: m.schlooz@chir.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Surgery, Nijmegen (Netherlands); Veltman, J., E-mail: j.veltman@zgt.nl [Hospital group Twente (ZGT), Department of Radiology, Almelo (Netherlands); Hoogerbrugge, N., E-mail: n.hoogerbrugge@gen.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Human Genetics, Nijmegen (Netherlands)
2013-09-15
Objective: To assess the value of breast MRI in size assessment of breast cancers in high risk patients, including those with a BRCA 1 or 2 mutation. Guidelines recommend invariably breast MRI screening for these patients and therapy is thus based on these findings. However, the accuracy of breast MRI for staging purposes is only tested in sporadic cancers. Methods: We assessed concordance of radiologic staging using MRI with histopathology in 49 tumors in 46 high risk patients (23 BRCA1, 12 BRCA2 and 11 Non-BRCA patients). The size of the total tumor area (TTA) was compared to pathology. In invasive carcinomas (n = 45) the size of the largest focus (LF) was also addressed. Results: Correlation of MRI measurements with pathology was 0.862 for TTA and 0.793 for LF. TTA was underestimated in 8(16%), overestimated in 5(10%), and correctly measured in 36(73%) cases. LF was underestimated in 4(9%), overestimated in 5(11%), and correctly measured in 36(80%) cases. Impact of BRCA 1 or 2 mutations on the quality of size estimation was not observed. Conclusions: Tumor size estimation using breast MRI in high risk patients is comparable to its performance in sporadic cancers. Therefore, breast MRI can safely be used for treatment planning.
González, Francisco Javier
2011-01-01
In this work the metabolic heat generated by breast tumors was estimated indirectly and noninvasively from digital infrared images and numerically simulating a simplified breast model and a cancerous tumor, this parameter can be of clinical importance since it has been related to the doubling volume's time and malignancy for that particular tumor. The results indicate that digital infrared imaging has the potential to estimate in a non-invasive way the malignancy of a tumor by calculating its metabolic heat generation from bioheat thermal transfer models.
Medical image segmentation to estimate HER2 gene status in breast cancer
Palacios-Navarro, Guillermo; Acirón-Pomar, José Manuel; Vilchez-Sorribas, Enrique; Zambrano, Eddie Galarza
2016-02-01
This work deals with the estimation of HER2 Gene status in breast tumour images treated with in situ hybridization techniques (ISH). We propose a simple algorithm to obtain the amplification factor of HER2 gene. The obtained results are very close to those obtained by specialists in a manual way. The developed algorithm is based on colour image segmentation and has been included in a software application tool for breast tumour analysis. The developed tool focus on the estimation of the seriousness of tumours, facilitating the work of pathologists and contributing to a better diagnosis.
Nonparametric estimation of population density for line transect sampling using FOURIER series
Crain, B.R.; Burnham, K.P.; Anderson, D.R.; Lake, J.L.
1979-01-01
A nonparametric, robust density estimation method is explored for the analysis of right-angle distances from a transect line to the objects sighted. The method is based on the FOURIER series expansion of a probability density function over an interval. With only mild assumptions, a general population density estimator of wide applicability is obtained.
Li, Ying; Wei, Xi; Zhang, Sheng; Zhang, Jin
2015-11-01
The aim of this study was to investigate the role of ultrasonographic microvascular imaging in the evaluation of prognosis of patients with invasive breast cancer treated by adjuvant therapies. A total of 121 patients with invasive breast cancer underwent ultrasonographic contrast-enhanced imaging, vascular endothelial growth factor (VEGF) staining, and microvessel density (MVD) counts. The parameters of microvascular imaging and the expression of VEGF and MVD in primary breast cancer were calculated. The correlation between these factors and the overall and progression-free survival rate were analyzed using the Kaplan-Meier method. Among 121 cases, the positive VEGF cases were 75 and negative ones were 46. The cut point of 52.3 was calculated by the regressive curve for MVD counts. The data showed the mean intensity (MI) was positively associated with both the MVD counts (r = .51, p prognosis of patients, high VEGF expression and MVD counts were associated with reduced progressive and survival times (PFS, p = .032 and p = .034; OS, p = .041 and p = .038, respectively). The correlation between parameters of microvascular imaging, VEGF expressive status, and the MVD counts were established. The cut point of mean intensity (MI = 40) was used to investigate as an independent predictor for PFS (p = .021) and OS (p = .025), respectively, due to a strong correlation between MVD counts and VEGF expression in patients with invasive breast cancer. The microvascular imaging could be a visual and helpful tool to predict the prognosis of patients with invasive breast cancer treated by adjuvant therapies.
DEFF Research Database (Denmark)
Buch-Kromann, Tine; Nielsen, Jens
2012-01-01
This paper introduces a multivariate density estimator for truncated and censored data with special emphasis on extreme values based on survival analysis. A local constant density estimator is considered. We extend this estimator by means of tail flattening transformation, dimension reducing prio...
Theoretical and Experimental Estimations of Volumetric Inductive Phase Shift in Breast Cancer Tissue
González, C. A.; Lozano, L. M.; Uscanga, M. C.; Silva, J. G.; Polo, S. M.
2013-04-01
Impedance measurements based on magnetic induction for breast cancer detection has been proposed in some studies. This study evaluates theoretical and experimentally the use of a non-invasive technique based on magnetic induction for detection of patho-physiological conditions in breast cancer tissue associated to its volumetric electrical conductivity changes through inductive phase shift measurements. An induction coils-breast 3D pixel model was designed and tested. The model involves two circular coils coaxially centered and a human breast volume centrally placed with respect to the coils. A time-harmonic numerical simulation study addressed the effects of frequency-dependent electrical properties of tumoral tissue on the volumetric inductive phase shift of the breast model measured with the circular coils as inductor and sensor elements. Experimentally; five female volunteer patients with infiltrating ductal carcinoma previously diagnosed by the radiology and oncology departments of the Specialty Clinic for Women of the Mexican Army were measured by an experimental inductive spectrometer and the use of an ergonomic inductor-sensor coil designed to estimate the volumetric inductive phase shift in human breast tissue. Theoretical and experimental inductive phase shift estimations were developed at four frequencies: 0.01, 0.1, 1 and 10 MHz. The theoretical estimations were qualitatively in agreement with the experimental findings. Important increments in volumetric inductive phase shift measurements were evident at 0.01MHz in theoretical and experimental observations. The results suggest that the tested technique has the potential to detect pathological conditions in breast tissue associated to cancer by non-invasive monitoring. Further complementary studies are warranted to confirm the observations.
Digital Repository Service at National Institute of Oceanography (India)
Madhupratap, M.; Achuthankutty, C.T.; Nair, S.R.S.
Direct sampling of the sandy substratus of the Agatti Lagoon with a corer showed the presence of vary high densities of epibenthic forms. On average, densities were about 25 times higher than previously estimated with emergence traps. About 80...
Gabrielson, Marike; Chiesa, Flaminia; Paulsson, Janna; Strell, Carina; Behmer, Catharina; Rönnow, Katarina; Czene, Kamila; Östman, Arne; Hall, Per
2016-07-01
Following female sex and age, mammographic density is considered one of the strongest risk factors for breast cancer. Despite the association between mammographic density and breast cancer risk, little is known about the underlying histology and biological basis of breast density. To better understand the mechanisms behind mammographic density we assessed morphology, proliferation and hormone receptor status in relation to mammographic density in breast tissues from healthy women. Tissues were obtained from 2012-2013 by ultrasound-guided core needle biopsy from 160 women as part of the Karma (Karolinska mammography project for risk prediction for breast cancer) project. Mammograms were collected through routine mammography screening and mammographic density was calculated using STRATUS. The histological composition, epithelial and stromal proliferation status and hormone receptor status were assessed through immunohistochemical staining. Higher mammographic density was significantly associated with a greater proportion of stromal and epithelial tissue and a lower proportion of adipose tissue. Epithelial expression levels of Ki-67, oestrogen receptor (ER) and progesterone receptor (PR) were not associated with mammographic density. Epithelial Ki-67 was associated with a greater proportion of epithelial tissue, and epithelial PR was associated with a greater proportion of stromal and a lower proportion of adipose tissue. Epithelial ER was not associated with any tissues. In contrast, expression of ER in the stroma was significantly associated with a greater proportion of stroma, and negatively associated with the amount of adipose tissue. High mammographic density is associated with higher amount of stroma and epithelium and less amount of fat, but is not associated with a change in epithelial proliferation or receptor status. Increased expressions of both epithelial PR and stromal ER are associated with a greater proportion of stroma, suggesting hormonal involvement
EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area
DEFF Research Database (Denmark)
Proietti, Tommaso; Marczak, Martyna; Mazzi, Gianluigi
EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom–up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model of ...... and evaluated with different tests based on the probability integral transform and by applying scoring rules....
Directory of Open Access Journals (Sweden)
Hendra Gunawan
2014-06-01
Full Text Available http://dx.doi.org/10.17014/ijog.vol3no3.20084The precision of topographic density (Bouguer density estimation by the Nettleton approach is based on a minimum correlation of Bouguer gravity anomaly and topography. The other method, the Parasnis approach, is based on a minimum correlation of Bouguer gravity anomaly and Bouguer correction. The precision of Bouguer density estimates was investigated by both methods on simple 2D syntetic models and under an assumption free-air anomaly consisting of an effect of topography, an effect of intracrustal, and an isostatic compensation. Based on simulation results, Bouguer density estimates were then investigated for a gravity survey of 2005 on La Soufriere Volcano-Guadeloupe area (Antilles Islands. The Bouguer density based on the Parasnis approach is 2.71 g/cm3 for the whole area, except the edifice area where average topography density estimates are 2.21 g/cm3 where Bouguer density estimates from previous gravity survey of 1975 are 2.67 g/cm3. The Bouguer density in La Soufriere Volcano was uncertainly estimated to be 0.1 g/cm3. For the studied area, the density deduced from refraction seismic data is coherent with the recent Bouguer density estimates. New Bouguer anomaly map based on these Bouguer density values allows to a better geological intepretation.
Rigorous home range estimation with movement data: a new autocorrelated kernel density estimator.
Fleming, C H; Fagan, W F; Mueller, T; Olson, K A; Leimgruber, P; Calabrese, J M
2015-05-01
Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routinely used as inputs to KDEs, are inherently autocorrelated and violate this key assumption. As we demonstrate, using realistically autocorrelated data in conventional KDEs results in grossly underestimated home ranges. We further show that the performance of conventional KDEs actually degrades as data quality improves, because autocorrelation strength increases as movement paths become more finely resolved. To remedy these flaws with the traditional KDE method, we derive an autocorrelated KDE (AKDE) from first principles to use autocorrelated data, making it perfectly suited for movement data sets. We illustrate the vastly improved performance of AKDE using analytical arguments, relocation data from Mongolian gazelles, and simulations based upon the gazelle's observed movement process. By yielding better minimum area estimates for threatened wildlife populations, we believe that future widespread use of AKDE will have significant impact on ecology and conservation biology.
Uncertainties in estimating heart doses from 2D-tangential breast cancer radiotherapy
DEFF Research Database (Denmark)
Laugaard Lorenzen, Ebbe; Brink, Carsten; Taylor, Carolyn W.;
2016-01-01
heart dose estimated from individual CT-scans varied from 8Gy, and maximum dose from 5 to 50Gy for all three regimens, so that estimates based only on regimen had substantial uncertainty. When maximum heart distance was taken into account, the uncertainty was reduced and was comparable......BACKGROUND AND PURPOSE: We evaluated the accuracy of three methods of estimating radiation dose to the heart from two-dimensional tangential radiotherapy for breast cancer, as used in Denmark during 1982-2002. MATERIAL AND METHODS: Three tangential radiotherapy regimens were reconstructed using CT...... to the uncertainty of estimates based on individual CT-scans. For right-sided breast cancer patients, mean heart dose based on individual CT-scans was always
Density and hazard rate estimation for censored and a-mixing data using gamma kernels
2006-01-01
In this paper we consider the nonparametric estimation for a density and hazard rate function for right censored -mixing survival time data using kernel smoothing techniques. Since survival times are positive with potentially a high concentration at zero, one has to take into account the bias problems when the functions are estimated in the boundary region. In this paper, gamma kernel estimators of the density and the hazard rate function are proposed. The estimators use adaptive weights depe...
Estimating basic wood density and its uncertainty for Pinus densiflora in the Republic of Korea
Directory of Open Access Journals (Sweden)
Jung Kee Pyo
2012-06-01
Full Text Available According to the Intergovernmental Panel on Climate Change (IPCC guidelines, uncertainty assessment is an important aspect of a greenhouse gas inventory, and effort should be made to incorporate it into the reporting. The goal of this study was to estimate basic wood density (BWD and its uncertainty for Pinus densiflora (Siebold & Zucc. in Korea. In this study, P. densiflora forests throughout the country were divided into two regional variants, which were the Gangwon region variant, distributed on the northeastern part of the country, and the central region variant. A total of 36 representative sampling plots were selected in both regions to collect sample trees for destructive sampling. The trees were selected considering the distributions of tree age and diameter at breast height. Hypothesis testing was carried out to test the BWD differences between two age groups, i.e. age over 20 and less than 20, and differences between the two regions. The test suggested that there was no statistically significant difference between the two age classes. On the other hand, it is suggested a strong evidence of a statistically significant difference between regions. The BWD and its uncertainty were 0.418 g/cm3 and 11.9% for the Gangwon region, whereas they were 0.471g/cm3 and 3.8% for the central region. As a result, the estimated BWD for P. densiflora was more precise than the value provided by the IPCC guidelines.
Glycemic index, glycemic load and mammographic breast density: the EPIC Florence longitudinal study.
Masala, Giovanna; Assedi, Melania; Bendinelli, Benedetta; Ermini, Ilaria; Occhini, Daniela; Sieri, Sabina; Brighenti, Furio; Del Turco, Marco Rosselli; Ambrogetti, Daniela; Palli, Domenico
2013-01-01
A few studies have evaluated the association between diet and mammographic breast density (MBD) and results are inconsistent. MBD, a well-recognized risk factor for breast cancer, has been proposed as a marker of cumulative exposure to hormones and growth factors. Diets with a high glycemic index (GI) or glycemic load (GL) may increase breast cancer risk, via an effect on the insulin-like growth factor axis. We have investigated the association between carbohydrate intake, GI, GL and MBD in a prospective study. We identified a large series of women, in the frame of the EPIC-Florence cohort, with a mammogram taken five years after enrolment, when detailed information on dietary and lifestyle habits and anthropometric measurements had been collected. Mammograms have been retrieved (1,668, 83%) and MBD assessed according to Wolfe's classification. We compared women with high MBD (P2+DY Wolfe's categories) with those with low MBD (N1+P1) through logistic models adjusted for age, education, body mass index, menopause, number of children, breast feeding, physical activity, non-alcohol energy, fibers, saturated fat and alcohol. A direct association between GL and high MBD emerged in the highest quintile of intake in comparison with the lowest quintile (OR = 1.73, 95%CI 1.13-2.67, p for trend = 0.048) while no association with glycemic index was evident. These results were confirmed after exclusion of women reporting to be on a diet or affected with diabetes, and when Hormone Replacement Therapy at the date of mammographic examination used to assess MBD was considered. The effect was particularly evident among leaner women, although no interaction was found. A positive association was suggested for increasing simple sugar and total carbohydrates intakes limited to the highest quintiles. In this Italian population we observed an association between glycemic load, total and rapidly absorbed carbohydrates and high MBD. These novel results warrant further investigations.
Glycemic index, glycemic load and mammographic breast density: the EPIC Florence longitudinal study.
Directory of Open Access Journals (Sweden)
Giovanna Masala
Full Text Available A few studies have evaluated the association between diet and mammographic breast density (MBD and results are inconsistent. MBD, a well-recognized risk factor for breast cancer, has been proposed as a marker of cumulative exposure to hormones and growth factors. Diets with a high glycemic index (GI or glycemic load (GL may increase breast cancer risk, via an effect on the insulin-like growth factor axis. We have investigated the association between carbohydrate intake, GI, GL and MBD in a prospective study. We identified a large series of women, in the frame of the EPIC-Florence cohort, with a mammogram taken five years after enrolment, when detailed information on dietary and lifestyle habits and anthropometric measurements had been collected. Mammograms have been retrieved (1,668, 83% and MBD assessed according to Wolfe's classification. We compared women with high MBD (P2+DY Wolfe's categories with those with low MBD (N1+P1 through logistic models adjusted for age, education, body mass index, menopause, number of children, breast feeding, physical activity, non-alcohol energy, fibers, saturated fat and alcohol. A direct association between GL and high MBD emerged in the highest quintile of intake in comparison with the lowest quintile (OR = 1.73, 95%CI 1.13-2.67, p for trend = 0.048 while no association with glycemic index was evident. These results were confirmed after exclusion of women reporting to be on a diet or affected with diabetes, and when Hormone Replacement Therapy at the date of mammographic examination used to assess MBD was considered. The effect was particularly evident among leaner women, although no interaction was found. A positive association was suggested for increasing simple sugar and total carbohydrates intakes limited to the highest quintiles. In this Italian population we observed an association between glycemic load, total and rapidly absorbed carbohydrates and high MBD. These novel results warrant further
Directory of Open Access Journals (Sweden)
Rongda Chen
Full Text Available Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.
Lindström, Sara; Thompson, Deborah J; Paterson, Andrew D; Li, Jingmei; Gierach, Gretchen L; Scott, Christopher; Stone, Jennifer; Douglas, Julie A; dos-Santos-Silva, Isabel; Fernandez-Navarro, Pablo; Verghase, Jajini; Smith, Paula; Brown, Judith; Luben, Robert; Wareham, Nicholas J; Loos, Ruth J F; Heit, John A; Pankratz, V Shane; Norman, Aaron; Goode, Ellen L; Cunningham, Julie M; deAndrade, Mariza; Vierkant, Robert A; Czene, Kamila; Fasching, Peter A; Baglietto, Laura; Southey, Melissa C; Giles, Graham G; Shah, Kaanan P; Chan, Heang-Ping; Helvie, Mark A; Beck, Andrew H; Knoblauch, Nicholas W; Hazra, Aditi; Hunter, David J; Kraft, Peter; Pollan, Marina; Figueroa, Jonine D; Couch, Fergus J; Hopper, John L; Hall, Per; Easton, Douglas F; Boyd, Norman F; Vachon, Celine M; Tamimi, Rulla M
2014-10-24
Mammographic density reflects the amount of stromal and epithelial tissues in relation to adipose tissue in the breast and is a strong risk factor for breast cancer. Here we report the results from meta-analysis of genome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense area and percent density in up to 7,916 women in stage 1 and an additional 10,379 women in stage 2. We identify genome-wide significant (P<5 × 10(-8)) loci for dense area (AREG, ESR1, ZNF365, LSP1/TNNT3, IGF1, TMEM184B and SGSM3/MKL1), non-dense area (8p11.23) and percent density (PRDM6, 8p11.23 and TMEM184B). Four of these regions are known breast cancer susceptibility loci, and four additional regions were found to be associated with breast cancer (P<0.05) in a large meta-analysis. These results provide further evidence of a shared genetic basis between mammographic density and breast cancer and illustrate the power of studying intermediate quantitative phenotypes to identify putative disease-susceptibility loci.
Institute of Scientific and Technical Information of China (English)
Xiaojing Guo; Ling Chen; Ronggang Lang; Yu Fan; Li Fu
2006-01-01
OBJECTIVE To investigate the relationship between lymphatic vessel density and lymph node metastasis of invasive micropapillary carcinoma (IMPC) of the breast.METHODS The immunohistochemical study for vascular endothelial growth factor-c (VEGF-C), VEGF Receptor-3 (VEGFR-3) and lymphatic vessel density of 51 cases of IMPC were performed, and lymph node metastases were examined by microscopic analysis of these cases.RESULTS In IMPC, VEGF-C was expressed in the cytoplasm and/or on the membrane of the tumor cells, and the expression of VEGF-C showed a positive correlation with lymph node metastasis (P＜0.01). Lymphatic vessel density was determined by the number of micro-lymphatic vessels with VEGFR-3 positive staining. Lymphatic vessel density was positively correlated with VEGF-C expression (P＜0.01) and lymph node metastasis (P＜0.01). The percentage of IMPC in the tumor was not associated with the incidence of lymph node metastasis. The metastatic foci in lymph nodes were either pure or predominant micropapillary carcinoma.CONCLUSION The results suggested that VEGF-C overexpression stimulated tumor lymphangiogenesis, and the increased lymphatic vessel density may be the key factor that influenced lymph node metastasis of IMPC.
Divisive latent class modeling as a density estimation method for categorical data
van der Palm, D.W.; van der Ark, L.A.; Vermunt, J.K.
2016-01-01
Traditionally latent class (LC) analysis is used by applied researchers as a tool for identifying substantively meaningful clusters. More recently, LC models have also been used as a density estimation tool for categorical variables. We introduce a divisive LC (DLC) model as a density estimation too
Inference-less Density Estimation using Copula Bayesian Networks
Elidan, Gal
2012-01-01
We consider learning continuous probabilistic graphical models in the face of missing data. For non-Gaussian models, learning the parameters and structure of such models depends on our ability to perform efficient inference, and can be prohibitive even for relatively modest domains. Recently, we introduced the Copula Bayesian Network (CBN) density model - a flexible framework that captures complex high-dimensional dependency structures while offering direct control over the univariate marginals, leading to improved generalization. In this work we show that the CBN model also offers significant computational advantages when training data is partially observed. Concretely, we leverage on the specialized form of the model to derive a computationally amenable learning objective that is a lower bound on the log-likelihood function. Importantly, our energy-like bound circumvents the need for costly inference of an auxiliary distribution, thus facilitating practical learning of highdimensional densities. We demonstr...
Confidence estimates in simulation of phase noise or spectral density.
Ashby, Neil
2017-02-13
In this paper we apply the method of discrete simulation of power law noise, developed in [1],[3],[4], to the problem of simulating phase noise for a combination of power law noises. We derive analytic expressions for the probability of observing a value of phase noise L(f) or of any of the onesided spectral densities S(f); Sy(f), or Sx(f), for arbitrary superpositions of power law noise.
Optimisation of in-situ dry density estimation
Directory of Open Access Journals (Sweden)
Morvan Mathilde
2016-01-01
Full Text Available Nowadays, field experiments are mostly used to determine the resistance and settlements of a soil before building. The needed devices were heavy so they cannot be used in every situation. It is the reason why Gourves et al (1998 developed a light dynamic penetrometer called Panda. For this penetrometer, a standardized hammer has to be blown on the head of the piston. For each blow, it measures the driving energy as well as the driving depth of the cone into the soil. The obtained penetrogram gives us the cone resistance variation with depth. For homogeneous soils, three parameters can determined: the critical depth zc, the initial cone resistance qd0 and the cone resistance in depth qd1. In parallel to the improvement of this apparatus, some researches were lead to obtain a relationship between the dry density of soil and the cone resistance in depth qd1. Knowing dry density of soil can allow to evaluate compaction efficiency for example. To achieve this point, a database of soils was initiated. Each of these soils was tested and classified using laboratory tests, among others, grain size distribution, proctor results, Atterberg limits. Penetrometer tests were also performed for three to five densities and for three to five water contents. Using this database, Chaigneau managed to obtain a logarithmic relation linking qd1 and dry density. But this relation varies with the water content. This article presents our recent researches on a mean to obtain a unified relation using water content, saturation degree or suction. To achieve this point, at first we studied the CNR silt responses with saturation degree and water content. Its water retention curve was realised using filter paper method so we can obtain suction. Then we verified the conclusion of this study to seven soils of the database to validate our hypotheses.
Energy Technology Data Exchange (ETDEWEB)
Singh, Harpreet; Arvind; Dorai, Kavita, E-mail: kavita@iisermohali.ac.in
2016-09-07
Estimation of quantum states is an important step in any quantum information processing experiment. A naive reconstruction of the density matrix from experimental measurements can often give density matrices which are not positive, and hence not physically acceptable. How do we ensure that at all stages of reconstruction, we keep the density matrix positive? Recently a method has been suggested based on maximum likelihood estimation, wherein the density matrix is guaranteed to be positive definite. We experimentally implement this protocol on an NMR quantum information processor. We discuss several examples and compare with the standard method of state estimation. - Highlights: • State estimation using maximum likelihood method was performed on an NMR quantum information processor. • Physically valid density matrices were obtained every time in contrast to standard quantum state tomography. • Density matrices of several different entangled and separable states were reconstructed for two and three qubits.
Directory of Open Access Journals (Sweden)
Ashot Davtian
2011-05-01
Full Text Available Two methods for the estimation of number per unit volume NV of spherical particles are discussed: the (physical disector (Sterio, 1984 and Saltykov's estimator (Saltykov, 1950; Fullman, 1953. A modification of Saltykov's estimator is proposed which reduces the variance. Formulae for bias and variance are given for both disector and improved Saltykov estimator for the case of randomly positioned particles. They enable the comparison of the two estimators with respect to their precision in terms of mean squared error.
Estimation of the cost of treatment by chemotherapy for early breast cancer in Morocco
Directory of Open Access Journals (Sweden)
Boutayeb Saber
2010-09-01
Full Text Available Abstract Background Breast cancer is the first cancer in women both in incidence and mortality. The treatment of breast cancer benefited from the progress of chemotherapy and targeted therapies, but there was a parallel increase in treatment costs. Despite a relatively high incidence of many sites of cancer, so far, there is no national register for this disease in Morocco. The main goal of this paper is to estimate the total cost of chemotherapy in the early stages of breast cancer due to its frequency and the chances of patients being cured. This study provides health decision-makers with a first estimate of costs and the opportunity to achieve the optimal use of available data to estimate the needs of antimitotics and trastuzumab in Morocco. Method We start by evaluating the individual cost according to the therapeutic sub-groups, namely: 1. Patients needing chemotherapy with only anthracycline-based therapy. 2. Patients needing chemotherapy with both anthracycline and taxane but without trastuzumab. 3. Patients needing trastuzumab in addition to chemotherapy. For each sub-group, the protocol of treatment is described, and the individual costs per unit, and for the whole cycle, are evaluated. Then we estimate the number of women suffering from breast cancer on the basis of two data bases available in Morocco. Finally, we calculate the total annual cost of treatment of breast cancer in Morocco. Results The total cost of breast cancer in Morocco is given in Moroccan dirhams (MAD, the US dollar at the current exchange rate (MAD 10 = USD 1.30 and in international dollars or purchasing power parity (MAD 10 = PPP 1.95. The cost of a therapy with trastuzumab is 8.4 times the cost of a sequential chemotherapy combining anthracycline and taxane, and nearly 60 times the cost of chemotherapy based on anthracycline alone. Globally, between USD 13.3 million and USD 28.6 million need to be devoted every year by the Moroccan health authorities to treat
Efficient estimation of dynamic density functions with an application to outlier detection
Qahtan, Abdulhakim Ali Ali
2012-01-01
In this paper, we propose a new method to estimate the dynamic density over data streams, named KDE-Track as it is based on a conventional and widely used Kernel Density Estimation (KDE) method. KDE-Track can efficiently estimate the density with linear complexity by using interpolation on a kernel model, which is incrementally updated upon the arrival of streaming data. Both theoretical analysis and experimental validation show that KDE-Track outperforms traditional KDE and a baseline method Cluster-Kernels on estimation accuracy of the complex density structures in data streams, computing time and memory usage. KDE-Track is also demonstrated on timely catching the dynamic density of synthetic and real-world data. In addition, KDE-Track is used to accurately detect outliers in sensor data and compared with two existing methods developed for detecting outliers and cleaning sensor data. © 2012 ACM.
An Efficient Acoustic Density Estimation Method with Human Detectors Applied to Gibbons in Cambodia.
Directory of Open Access Journals (Sweden)
Darren Kidney
Full Text Available Some animal species are hard to see but easy to hear. Standard visual methods for estimating population density for such species are often ineffective or inefficient, but methods based on passive acoustics show more promise. We develop spatially explicit capture-recapture (SECR methods for territorial vocalising species, in which humans act as an acoustic detector array. We use SECR and estimated bearing data from a single-occasion acoustic survey of a gibbon population in northeastern Cambodia to estimate the density of calling groups. The properties of the estimator are assessed using a simulation study, in which a variety of survey designs are also investigated. We then present a new form of the SECR likelihood for multi-occasion data which accounts for the stochastic availability of animals. In the context of gibbon surveys this allows model-based estimation of the proportion of groups that produce territorial vocalisations on a given day, thereby enabling the density of groups, instead of the density of calling groups, to be estimated. We illustrate the performance of this new estimator by simulation. We show that it is possible to estimate density reliably from human acoustic detections of visually cryptic species using SECR methods. For gibbon surveys we also show that incorporating observers' estimates of bearings to detected groups substantially improves estimator performance. Using the new form of the SECR likelihood we demonstrate that estimates of availability, in addition to population density and detection function parameters, can be obtained from multi-occasion data, and that the detection function parameters are not confounded with the availability parameter. This acoustic SECR method provides a means of obtaining reliable density estimates for territorial vocalising species. It is also efficient in terms of data requirements since since it only requires routine survey data. We anticipate that the low-tech field requirements will
Impact of Building Heights on 3d Urban Density Estimation from Spaceborne Stereo Imagery
Peng, Feifei; Gong, Jianya; Wang, Le; Wu, Huayi; Yang, Jiansi
2016-06-01
In urban planning and design applications, visualization of built up areas in three dimensions (3D) is critical for understanding building density, but the accurate building heights required for 3D density calculation are not always available. To solve this problem, spaceborne stereo imagery is often used to estimate building heights; however estimated building heights might include errors. These errors vary between local areas within a study area and related to the heights of the building themselves, distorting 3D density estimation. The impact of building height accuracy on 3D density estimation must be determined across and within a study area. In our research, accurate planar information from city authorities is used during 3D density estimation as reference data, to avoid the errors inherent to planar information extracted from remotely sensed imagery. Our experimental results show that underestimation of building heights is correlated to underestimation of the Floor Area Ratio (FAR). In local areas, experimental results show that land use blocks with low FAR values often have small errors due to small building height errors for low buildings in the blocks; and blocks with high FAR values often have large errors due to large building height errors for high buildings in the blocks. Our study reveals that the accuracy of 3D density estimated from spaceborne stereo imagery is correlated to heights of buildings in a scene; therefore building heights must be considered when spaceborne stereo imagery is used to estimate 3D density to improve precision.
Importance of tree basic density in biomass estimation and associated uncertainties
DEFF Research Database (Denmark)
Njana, Marco Andrew; Meilby, Henrik; Eid, Tron
2016-01-01
Key message Aboveground and belowground tree basic densities varied between and within the three mangrove species. If appropriately determined and applied, basic density may be useful in estimation of tree biomass. Predictive accuracy of the common (i.e. multi-species) models including abovegroun...... in estimation of tree biomass and hence contribute to improved accuracy of carbon stock estimates for REDD+ and sustainable management of mangroves in general.......Key message Aboveground and belowground tree basic densities varied between and within the three mangrove species. If appropriately determined and applied, basic density may be useful in estimation of tree biomass. Predictive accuracy of the common (i.e. multi-species) models including aboveground...... of sustainable forest management, conservation and enhancement of carbon stocks (REDD+) initiatives offer an opportunity for sustainable management of forests including mangroves. In carbon accounting for REDD+, it is required that carbon estimates prepared for monitoring reporting and verification schemes...
Institute of Scientific and Technical Information of China (English)
陈颖; 史春颖; 杨予川; 李睿; 刘源; 崔春玲
2015-01-01
Objective To explore the correlation between breast cancer and breast density in Heilongjiang region .Methods X-ray data and epidemiological data of 487 women from June 2010 to November 2010 in the First Affiliated Hospital of Harbin Medical University were col-lected, including 105 cases of breast cancer and 382 cases of healthy controls ( breast benign disease ) .Breast imaging reporting and data system recommended by americaradiology doctors was the standard for evaluation of breast density , breast density percentage was used to analyze the relationship between different levels of mammary gland photography density and breast canc -er risk factors .Results Based on 487 cases of mammary X-ray data , breast density was statis-tically different between breast cancer groups and healthy controls in Heilongjiang area , the oc-currence of breast cancer was associated with a high breast density , menopausal status did not affect breast density;breast density was associated with menarche age and history of lactation . Conclusion Breast X-ray photography density is associated with breast cancer risk factors .%目的：探讨黑龙江地区乳腺癌与其乳腺密度是否存在相关性。方法收集2010年6月至2010年11月哈尔滨医科大学附属第一医院就诊的487例黑龙江地区女性的乳腺钼靶X线检查资料及流行病学资料，其中105例为乳腺癌，382例为健康对照组，以美国放射医师学会推荐的乳腺影像报告和数据系统（ breast imaging reporting and data system ，BI-RADS）作为评估乳腺密度的标准，以乳腺密度百分比分析不同等级乳腺摄影密度和乳腺癌危险因素的关系。结果乳腺癌组与健康对照组乳腺密度有统计学差异。绝经状态未对乳腺密度产生影响；乳腺密度与初潮年龄、哺乳史相关。结论乳腺X线摄影密度与乳腺癌危险因素均相关联。
A generalized model for estimating the energy density of invertebrates
James, Daniel A.; Csargo, Isak J.; Von Eschen, Aaron; Thul, Megan D.; Baker, James M.; Hayer, Cari-Ann; Howell, Jessica; Krause, Jacob; Letvin, Alex; Chipps, Steven R.
2012-01-01
Invertebrate energy density (ED) values are traditionally measured using bomb calorimetry. However, many researchers rely on a few published literature sources to obtain ED values because of time and sampling constraints on measuring ED with bomb calorimetry. Literature values often do not account for spatial or temporal variability associated with invertebrate ED. Thus, these values can be unreliable for use in models and other ecological applications. We evaluated the generality of the relationship between invertebrate ED and proportion of dry-to-wet mass (pDM). We then developed and tested a regression model to predict ED from pDM based on a taxonomically, spatially, and temporally diverse sample of invertebrates representing 28 orders in aquatic (freshwater, estuarine, and marine) and terrestrial (temperate and arid) habitats from 4 continents and 2 oceans. Samples included invertebrates collected in all seasons over the last 19 y. Evaluation of these data revealed a significant relationship between ED and pDM (r2 = 0.96, p calorimetry approaches. This model should prove useful for a wide range of ecological studies because it is unaffected by taxonomic, seasonal, or spatial variability.
Huerga, Iker; Gerrikagoitia, Jon Kepa
2010-01-01
Risk estimation of developing breast cancer poses as the first prevention method for early diagnosis. Furthermore, data integration from different departments involved in the process plays a key role. In order to guarantee patient safety, the whole process should be orchestrated and monitored automatically. Support for the solution will be a linked data cloud, composed by all the departments that take part in the process, combined with rule engines.
DEFF Research Database (Denmark)
Winkel, Rikke Rass; von Euler-Chelpin, My Catarina; Nielsen, Mads
2016-01-01
in Denmark in 2007 (followed until 31 December 2010). Mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, Tabár's classification on parenchymal patterns and a fully automated texture quantification technique. The individual and combined association...... to future personalized screening strategies....
Lance, Amanda; Yang, Chih-Chao; Swamydas, Muthulekha; Dean, Delphine; Deitch, Sandy; Burg, Karen J L; Dréau, Didier
2016-01-01
The extracellular matrix (ECM) contributes to the generation and dynamic of normal breast tissue, in particular to the generation of polarized acinar and ductal structures. In vitro 3D culture conditions, including variations in the composition of the ECM, have been shown to directly influence the formation and organization of acinus-like and duct-like structures. Furthermore, the density of the ECM appears to also play a role in the normal mammary tissue and tumour formation. Here we show that the density of the ECM directly influences the number, organization and function of breast acini. Briefly, non-malignant human breast MCF10A cells were incubated in increasing densities of a Matrigel®-collagen I matrix. Elastic moduli near and distant to the acinus structures were measured by atomic force microscopy, and the number of acinus structures was determined. Immunochemistry was used to investigate the expression levels of E-cadherin, laminin, matrix metalloproteinase-14 and ß-casein in MCF10A cells. The modulus of the ECM was significantly increased near the acinus structures and the number of acinus structures decreased with the increase in Matrigel-collagen I density. As evaluated by the expression of laminin, the organization of the acinus structures present was altered as the density of the ECM increased. Increases in both E-cadherin and MMP14 expression by MCF10A cells as ECM density increased were also observed. In contrast, MCF10A cells expressed lower ß-casein levels as the ECM density increased. Taken together, these observations highlight the key role of ECM density in modulating the number, organization and function of breast acini.
2015-01-01
Traditionally, mammographic density (MD) of the breast has been assessed by a radiologist visually. This subjective evaluation requires significant experience to distinguish the relative proportions of the fibrous connective tissue and adipose tissue in the mammary gland correctly. The aim of this study is to compare the capabilities of the different methods (visual and computer-assisted) for assessing mammographic density. Our sample in this study consists of 66 patients with digital m...
EnviroAtlas Estimated Intersection Density of Walkable Roads Web Service
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in each EnviroAtlas community....
EnviroAtlas - Memphis, TN - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Cleveland, OH - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Fresno, CA - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Green Bay, WI - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Tampa, FL - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Portland, ME - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Paterson, NJ - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Minneapolis/St. Paul, MN - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - New Bedford, MA - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Pittsburgh, PA - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - New York, NY - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Des Moines, IA - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Austin, TX - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Woodbine, IA - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Milwaukee, WI - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Portland, OR - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Durham, NC - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Phoenix, AZ - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
2014-10-01
for Survey Research ( CSR ) conducted two initial focus groups in January 2012. The results were very enlightening. The purpose was : 1. To understand...Results: Just over half (54.6%) of women are definitely or probably willing to reduce their frequency of breast cancer screening compared to...81.9% who are definitely or probably willing to increase screening. The most cited disadvantage for reduced screening was delayed detection of breast
Compressive and Noncompressive Power Spectral Density Estimation from Periodic Nonuniform Samples
Lexa, Michael A; Thompson, John S
2011-01-01
This paper presents a novel power spectral density estimation technique for bandlimited, wide-sense stationary signals from sub-Nyquist sampled data. The technique employs multi-coset sampling and applies to spectrally sparse and nonsparse power spectra alike. For sparse density functions, we apply compressed sensing theory and the resulting compressive estimates exhibit better tradeoffs among the estimator's resolution, system complexity, and average sampling rate compared to their noncompressive counterparts. Both compressive and noncompressive estimates, however, can be computed at arbitrarily low sampling rates. The estimator does not require signal reconstruction and can be directly obtained from solving either a least squares or a nonnegative least squares problem. The estimates are piecewise constant approximations whose resolutions (width of the piecewise constant segments) are controlled by the periodicity of the multi-coset sampling. The estimates are also statistically consistent. This method is wi...
Cetacean Density Estimation from Novel Acoustic Datasets by Acoustic Propagation Modeling
2014-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Cetacean Density Estimation from Novel Acoustic Datasets...OBJECTIVES The objectives of this research are to apply existing methods for cetacean density estimation from passive acoustic recordings made by single...sensors, to novel data sets and cetacean species, as well as refine the existing techniques in order to develop a more generalized model that can be
The importance of spatial models for estimating the strength of density dependence
DEFF Research Database (Denmark)
Thorson, James T.; Skaug, Hans J.; Kristensen, Kasper;
2014-01-01
Identifying the existence and magnitude of density dependence is one of the oldest concerns in ecology. Ecologists have aimed to estimate density dependence in population and community data by fitting a simple autoregressive (Gompertz) model for density dependence to time series of abundance...... for an entire population. However, it is increasingly recognized that spatial heterogeneity in population densities has implications for population and community dynamics. We therefore adapt the Gompertz model to approximate local densities over continuous space instead of population-wide abundance......, and to allow productivity to vary spatially. Using simulated data generated from a spatial model, we show that the conventional (nonspatial) Gompertz model will result in biased estimates of density dependence, e.g., identifying oscillatory dynamics when not present. By contrast, the spatial Gompertz model...
Directory of Open Access Journals (Sweden)
YU Wenhao
2015-01-01
Full Text Available The distribution pattern and the distribution density of urban facility POIs are of great significance in the fields of infrastructure planning and urban spatial analysis. The kernel density estimation, which has been usually utilized for expressing these spatial characteristics, is superior to other density estimation methods (such as Quadrat analysis, Voronoi-based method, for that the Kernel density estimation considers the regional impact based on the first law of geography. However, the traditional kernel density estimation is mainly based on the Euclidean space, ignoring the fact that the service function and interrelation of urban feasibilities is carried out on the network path distance, neither than conventional Euclidean distance. Hence, this research proposed a computational model of network kernel density estimation, and the extension type of model in the case of adding constraints. This work also discussed the impacts of distance attenuation threshold and height extreme to the representation of kernel density. The large-scale actual data experiment for analyzing the different POIs' distribution patterns (random type, sparse type, regional-intensive type, linear-intensive type discusses the POI infrastructure in the city on the spatial distribution of characteristics, influence factors, and service functions.
KDE-Track: An Efficient Dynamic Density Estimator for Data Streams
Qahtan, Abdulhakim Ali Ali
2016-11-08
Recent developments in sensors, global positioning system devices and smart phones have increased the availability of spatiotemporal data streams. Developing models for mining such streams is challenged by the huge amount of data that cannot be stored in the memory, the high arrival speed and the dynamic changes in the data distribution. Density estimation is an important technique in stream mining for a wide variety of applications. The construction of kernel density estimators is well studied and documented. However, existing techniques are either expensive or inaccurate and unable to capture the changes in the data distribution. In this paper, we present a method called KDE-Track to estimate the density of spatiotemporal data streams. KDE-Track can efficiently estimate the density function with linear time complexity using interpolation on a kernel model, which is incrementally updated upon the arrival of new samples from the stream. We also propose an accurate and efficient method for selecting the bandwidth value for the kernel density estimator, which increases its accuracy significantly. Both theoretical analysis and experimental validation show that KDE-Track outperforms a set of baseline methods on the estimation accuracy and computing time of complex density structures in data streams.
DEFF Research Database (Denmark)
Hansen, S; Grabau, D A; Rose, C;
1998-01-01
The purpose of this study was to evaluate the reliability of different methods for estimating neovascularization in breast cancer and to compare them in terms of observer variability. The microvessel endothelium was stained immunohistochemically by antibodies against CD34. The investigated method...
Nonparametric estimate of spectral density functions of sample covariance matrices: A first step
2012-01-01
The density function of the limiting spectral distribution of general sample covariance matrices is usually unknown. We propose to use kernel estimators which are proved to be consistent. A simulation study is also conducted to show the performance of the estimators.
An asymptotically unbiased minimum density power divergence estimator for the Pareto-tail index
DEFF Research Database (Denmark)
Dierckx, G.; Goegebeur, Y.; Guillou, A.
2013-01-01
We introduce a robust and asymptotically unbiased estimator for the tail index of Pareto-type distributions. The estimator is obtained by fitting the extended Pareto distribution to the relative excesses over a high threshold with the minimum density power divergence criterion. Consistency and as...... by a small simulation experiment involving both uncontaminated and contaminated samples. (C) 2013 Elsevier Inc. All rights reserved....
Preoperative TRAM free flap volume estimation for breast reconstruction in lean patients.
Minn, Kyung Won; Hong, Ki Yong; Lee, Sang Woo
2010-04-01
To obtain pleasing symmetry in breast reconstruction with transverse rectus abdominis myocutaneous (TRAM) free flap, a large amount of abdominal flap is elevated and remnant tissue is trimmed in most cases. However, elevation of abundant abdominal flap can cause excessive tension in donor site closure and increase the possibility of hypertrophic scarring especially in lean patients. The TRAM flap was divided into 4 zones in routine manner; the depth and dimension of the 4 zones were obtained using ultrasound and AutoCAD (Autodesk Inc., San Rafael, CA), respectively. The acquired numbers were then multiplied to obtain an estimate of volume of each zone and the each zone volume was added. To confirm the relation between the estimated volume and the actual volume, authors compared intraoperative actual TRAM flap volumes with preoperative estimated volumes in 30 consecutive TRAM free flap breast reconstructions. The estimated volumes and the actual elevated volumes of flap were found to be correlated by regression analysis (r = 0.9258, P AutoCAD (Autodesk Inc.) allow the authors to attain the precise volume desired for elevation. This method provides advantages in terms of minimal flap trimming, easier closure of donor sites, reduced scar widening and symmetry, especially in lean patients.
DEFF Research Database (Denmark)
Winkel, Rikke Rass; von Euler-Chelpin, My; Nielsen, Mads;
2016-01-01
BACKGROUND: Mammographic density is a well-established risk factor for breast cancer. We investigated the association between three different methods of measuring density or parenchymal pattern/texture on digitized film-based mammograms, and examined to what extent textural features independently......-RADS alone). CONCLUSION: Our findings suggest that the (relative) amount of fibroglandular tissue (density) and mammographic structural features (texture/parenchymal pattern) jointly can improve risk segregation of screening women, using information already available from normal screening routine, in respect...... to future personalized screening strategies....
Kocovsky, Patrick M.; Rudstam, Lars G.; Yule, Daniel L.; Warner, David M.; Schaner, Ted; Pientka, Bernie; Deller, John W.; Waterfield, Holly A.; Witzel, Larry D.; Sullivan, Patrick J.
2013-01-01
Standardized methods of data collection and analysis ensure quality and facilitate comparisons among systems. We evaluated the importance of three recommendations from the Standard Operating Procedure for hydroacoustics in the Laurentian Great Lakes (GLSOP) on density estimates of target species: noise subtraction; setting volume backscattering strength (Sv) thresholds from user-defined minimum target strength (TS) of interest (TS-based Sv threshold); and calculations of an index for multiple targets (Nv index) to identify and remove biased TS values. Eliminating noise had the predictable effect of decreasing density estimates in most lakes. Using the TS-based Sv threshold decreased fish densities in the middle and lower layers in the deepest lakes with abundant invertebrates (e.g., Mysis diluviana). Correcting for biased in situ TS increased measured density up to 86% in the shallower lakes, which had the highest fish densities. The current recommendations by the GLSOP significantly influence acoustic density estimates, but the degree of importance is lake dependent. Applying GLSOP recommendations, whether in the Laurentian Great Lakes or elsewhere, will improve our ability to compare results among lakes. We recommend further development of standards, including minimum TS and analytical cell size, for reducing the effect of biased in situ TS on density estimates.
Rojas-Lima, J. E.; Domínguez-Pacheco, A.; Hernández-Aguilar, C.; Cruz-Orea, A.
2016-09-01
Considering the necessity of photothermal alternative approaches for characterizing nonhomogeneous materials like maize seeds, the objective of this research work was to analyze statistically the amplitude variations of photopyroelectric signals, by means of nonparametric techniques such as the histogram and the kernel density estimator, and the probability density function of the amplitude variations of two genotypes of maize seeds with different pigmentations and structural components: crystalline and floury. To determine if the probability density function had a known parametric form, the histogram was determined which did not present a known parametric form, so the kernel density estimator using the Gaussian kernel, with an efficiency of 95 % in density estimation, was used to obtain the probability density function. The results obtained indicated that maize seeds could be differentiated in terms of the statistical values for floury and crystalline seeds such as the mean (93.11, 159.21), variance (1.64× 103, 1.48× 103), and standard deviation (40.54, 38.47) obtained from the amplitude variations of photopyroelectric signals in the case of the histogram approach. For the case of the kernel density estimator, seeds can be differentiated in terms of kernel bandwidth or smoothing constant h of 9.85 and 6.09 for floury and crystalline seeds, respectively.
Institute of Scientific and Technical Information of China (English)
付小娜; 王丽; 康欣梅
2015-01-01
Mammographic breast density( BD)is independent risk factor for breast cancer,sex hormones also play a role in the development of breast cancer,but it is unclear whether mammographic breast density associate with sex hormone. In this review,we describe the association of BD and sex hormone with breast cancer.%乳腺密度（ mammographic breast density，BD）是乳腺癌危险性独立的预测指标，性激素也在乳腺癌的发展中扮演重要角色，而乳腺密度与性激素的关系仍不明确。本文将对乳腺密度，性激素，乳腺癌的关系进行综述。
Wavelet Optimal Estimations for Density Functions under Severely Ill-Posed Noises
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Rui Li
2013-01-01
Full Text Available Motivated by Lounici and Nickl's work (2011, this paper considers the problem of estimation of a density f based on an independent and identically distributed sample Y1,…,Yn from g=f*φ. We show a wavelet optimal estimation for a density (function over Besov ball Br,qs(L and Lp risk (1≤p<∞ in the presence of severely ill-posed noises. A wavelet linear estimation is firstly presented. Then, we prove a lower bound, which shows our wavelet estimator optimal. In other words, nonlinear wavelet estimations are not needed in that case. It turns out that our results extend some theorems of Pensky and Vidakovic (1999, as well as Fan and Koo (2002.
Glacial density and GIA in Alaska estimated from ICESat, GPS and GRACE measurements
Jin, Shuanggen; Zhang, T. Y.; Zou, F.
2017-01-01
The density of glacial volume change in Alaska is a key factor in estimating the glacier mass loss from altimetry observations. However, the density of Alaskan glaciers has large uncertainty due to the lack of in situ measurements. In this paper, using the measurements of Ice, Cloud, and land Elevation Satellite (ICESat), Global Positioning System (GPS), and Gravity Recovery and Climate Experiment (GRACE) from 2003 to 2009, an optimal density of glacial volume change with 750 kg/m3 is estimated for the first time to fit the measurements. The glacier mass loss is -57.5 ± 6.5 Gt by converting the volumetric change from ICESat with the estimated density 750 kg/m3. Based on the empirical relation, the depth-density profiles are constructed, which show glacial density variation information with depths in Alaska. By separating the glacier mass loss from glacial isostatic adjustment (GIA) effects in GPS uplift rates and GRACE total water storage trends, the GIA uplift rates are estimated in Alaska. The best fitting model consists of a 60 km elastic lithosphere and 110 km thick asthenosphere with a viscosity of 2.0 × 1019 Pa s over a two-layer mantle.
Estimating population density and connectivity of American mink using spatial capture-recapture
Fuller, Angela K.; Sutherland, Christopher S.; Royle, Andy; Hare, Matthew P.
2016-01-01
Estimating the abundance or density of populations is fundamental to the conservation and management of species, and as landscapes become more fragmented, maintaining landscape connectivity has become one of the most important challenges for biodiversity conservation. Yet these two issues have never been formally integrated together in a model that simultaneously models abundance while accounting for connectivity of a landscape. We demonstrate an application of using capture–recapture to develop a model of animal density using a least-cost path model for individual encounter probability that accounts for non-Euclidean connectivity in a highly structured network. We utilized scat detection dogs (Canis lupus familiaris) as a means of collecting non-invasive genetic samples of American mink (Neovison vison) individuals and used spatial capture–recapture models (SCR) to gain inferences about mink population density and connectivity. Density of mink was not constant across the landscape, but rather increased with increasing distance from city, town, or village centers, and mink activity was associated with water. The SCR model allowed us to estimate the density and spatial distribution of individuals across a 388 km2 area. The model was used to investigate patterns of space usage and to evaluate covariate effects on encounter probabilities, including differences between sexes. This study provides an application of capture–recapture models based on ecological distance, allowing us to directly estimate landscape connectivity. This approach should be widely applicable to provide simultaneous direct estimates of density, space usage, and landscape connectivity for many species.
Ferreira, P; Baptista, M; Di Maria, S; Vaz, P
2016-05-01
The aim of this work was to estimate the risk of radiation induced cancer following the Portuguese breast screening recommendations for Digital Mammography (DM) when applied to Digital Breast Tomosynthesis (DBT) and to evaluate how the risk to induce cancer could influence the energy used in breast diagnostic exams. The organ doses were calculated by Monte Carlo simulations using a female voxel phantom and considering the acquisition of 25 projection images. Single organ cancer incidence risks were calculated in order to assess the total effective radiation induced cancer risk. The screening strategy techniques considered were: DBT in Cranio-Caudal (CC) view and two-view DM (CC and Mediolateral Oblique (MLO)). The risk of cancer incidence following the Portuguese screening guidelines (screening every two years in the age range of 50-80years) was calculated by assuming a single CC DBT acquisition view as standalone screening strategy and compared with two-view DM. The difference in the total effective risk between DBT and DM is quite low. Nevertheless in DBT an increase of risk for the lung is observed with respect to DM. The lung is also the organ that is mainly affected when non-optimal beam energy (in terms of image quality and absorbed dose) is used instead of an optimal one. The use of non-optimal energies could increase the risk of lung cancer incidence by a factor of about 2.
Maccione, Alessandro; Garofalo, Matteo; Nieus, Thierry; Tedesco, Mariateresa; Berdondini, Luca; Martinoia, Sergio
2012-06-15
We used electrophysiological signals recorded by CMOS Micro Electrode Arrays (MEAs) at high spatial resolution to estimate the functional-effective connectivity of sparse hippocampal neuronal networks in vitro by applying a cross-correlation (CC) based method and ad hoc developed spatio-temporal filtering. Low-density cultures were recorded by a recently introduced CMOS-MEA device providing simultaneous multi-site acquisition at high-spatial (21 μm inter-electrode separation) as well as high-temporal resolution (8 kHz per channel). The method is applied to estimate functional connections in different cultures and it is refined by applying spatio-temporal filters that allow pruning of those functional connections not compatible with signal propagation. This approach permits to discriminate between possible causal influence and spurious co-activation, and to obtain detailed maps down to cellular resolution. Further, a thorough analysis of the links strength and time delays (i.e., amplitude and peak position of the CC function) allows characterizing the inferred interconnected networks and supports a possible discrimination of fast mono-synaptic propagations, and slow poly-synaptic pathways. By focusing on specific regions of interest we could observe and analyze microcircuits involving connections among a few cells. Finally, the use of the high-density MEA with low density cultures analyzed with the proposed approach enables to compare the inferred effective links with the network structure obtained by staining procedures.
Royle, J. Andrew; Chandler, Richard B.; Gazenski, Kimberly D.; Graves, Tabitha A.
2013-01-01
Population size and landscape connectivity are key determinants of population viability, yet no methods exist for simultaneously estimating density and connectivity parameters. Recently developed spatial capture–recapture (SCR) models provide a framework for estimating density of animal populations but thus far have not been used to study connectivity. Rather, all applications of SCR models have used encounter probability models based on the Euclidean distance between traps and animal activity centers, which implies that home ranges are stationary, symmetric, and unaffected by landscape structure. In this paper we devise encounter probability models based on “ecological distance,” i.e., the least-cost path between traps and activity centers, which is a function of both Euclidean distance and animal movement behavior in resistant landscapes. We integrate least-cost path models into a likelihood-based estimation scheme for spatial capture–recapture models in order to estimate population density and parameters of the least-cost encounter probability model. Therefore, it is possible to make explicit inferences about animal density, distribution, and landscape connectivity as it relates to animal movement from standard capture–recapture data. Furthermore, a simulation study demonstrated that ignoring landscape connectivity can result in negatively biased density estimators under the naive SCR model.
Fotin, Sergei V.; Yin, Yin; Haldankar, Hrishikesh; Hoffmeister, Jeffrey W.; Periaswamy, Senthil
2016-03-01
Computer-aided detection (CAD) has been used in screening mammography for many years and is likely to be utilized for digital breast tomosynthesis (DBT). Higher detection performance is desirable as it may have an impact on radiologist's decisions and clinical outcomes. Recently the algorithms based on deep convolutional architectures have been shown to achieve state of the art performance in object classification and detection. Similarly, we trained a deep convolutional neural network directly on patches sampled from two-dimensional mammography and reconstructed DBT volumes and compared its performance to a conventional CAD algorithm that is based on computation and classification of hand-engineered features. The detection performance was evaluated on the independent test set of 344 DBT reconstructions (GE SenoClaire 3D, iterative reconstruction algorithm) containing 328 suspicious and 115 malignant soft tissue densities including masses and architectural distortions. Detection sensitivity was measured on a region of interest (ROI) basis at the rate of five detection marks per volume. Moving from conventional to deep learning approach resulted in increase of ROI sensitivity from 0:832 +/- 0:040 to 0:893 +/- 0:033 for suspicious ROIs; and from 0:852 +/- 0:065 to 0:930 +/- 0:046 for malignant ROIs. These results indicate the high utility of deep feature learning in the analysis of DBT data and high potential of the method for broader medical image analysis tasks.
Estimating detection and density of the Andean cat in the high Andes
Reppucci, Juan; Gardner, Beth; Lucherini, Mauro
2011-01-01
The Andean cat (Leopardus jacobita) is one of the most endangered, yet least known, felids. Although the Andean cat is considered at risk of extinction, rigorous quantitative population studies are lacking. Because physical observations of the Andean cat are difficult to make in the wild, we used a camera-trapping array to photo-capture individuals. The survey was conducted in northwestern Argentina at an elevation of approximately 4,200 m during October–December 2006 and April–June 2007. In each year we deployed 22 pairs of camera traps, which were strategically placed. To estimate detection probability and density we applied models for spatial capture–recapture using a Bayesian framework. Estimated densities were 0.07 and 0.12 individual/km2 for 2006 and 2007, respectively. Mean baseline detection probability was estimated at 0.07. By comparison, densities of the Pampas cat (Leopardus colocolo), another poorly known felid that shares its habitat with the Andean cat, were estimated at 0.74–0.79 individual/km2 in the same study area for 2006 and 2007, and its detection probability was estimated at 0.02. Despite having greater detectability, the Andean cat is rarer in the study region than the Pampas cat. Properly accounting for the detection probability is important in making reliable estimates of density, a key parameter in conservation and management decisions for any species.
Estimation of tiger densities in India using photographic captures and recaptures
Karanth, U.; Nichols, J.D.
1998-01-01
Previously applied methods for estimating tiger (Panthera tigris) abundance using total counts based on tracks have proved unreliable. In this paper we use a field method proposed by Karanth (1995), combining camera-trap photography to identify individual tigers based on stripe patterns, with capture-recapture estimators. We developed a sampling design for camera-trapping and used the approach to estimate tiger population size and density in four representative tiger habitats in different parts of India. The field method worked well and provided data suitable for analysis using closed capture-recapture models. The results suggest the potential for applying this methodology for estimating abundances, survival rates and other population parameters in tigers and other low density, secretive animal species with distinctive coat patterns or other external markings. Estimated probabilities of photo-capturing tigers present in the study sites ranged from 0.75 - 1.00. The estimated mean tiger densities ranged from 4.1 (SE hat= 1.31) to 11.7 (SE hat= 1.93) tigers/100 km2. The results support the previous suggestions of Karanth and Sunquist (1995) that densities of tigers and other large felids may be primarily determined by prey community structure at a given site.
Energy Technology Data Exchange (ETDEWEB)
Antoniassi, M.; Conceicao, A.L.C. [Departamento de Fisica-Faculdade de Filosofia Ciencias e Letras de Ribeirao Preto-Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo (Brazil); Poletti, M.E., E-mail: poletti@ffclrp.usp.br [Departamento de Fisica-Faculdade de Filosofia Ciencias e Letras de Ribeirao Preto-Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo (Brazil)
2012-07-15
Electron densities of 33 samples of normal (adipose and fibroglangular) and neoplastic (benign and malignant) human breast tissues were determined through Compton scattering data using a monochromatic synchrotron radiation source and an energy dispersive detector. The area of Compton peaks was used to determine the electron densities of the samples. Adipose tissue exhibits the lowest values of electron density whereas malignant tissue the highest. The relationship with their histology was discussed. Comparison with previous results showed differences smaller than 4%. - Highlights: Black-Right-Pointing-Pointer Electron density of normal and neoplastic breast tissues was measured using Compton scattering. Black-Right-Pointing-Pointer Monochromatic synchrotron radiation was used to obtain the Compton scattering data. Black-Right-Pointing-Pointer The area of Compton peaks was used to determine the electron densities of samples. Black-Right-Pointing-Pointer Adipose tissue shows the lowest electron density values whereas the malignant tissue the highest. Black-Right-Pointing-Pointer Comparison with previous results showed differences smaller than 4%.
LSTA, Rawane Samb
2010-01-01
This thesis deals with the nonparametric estimation of density f of the regression error term E of the model Y=m(X)+E, assuming its independence with the covariate X. The difficulty linked to this study is the fact that the regression error E is not observed. In a such setup, it would be unwise, for estimating f, to use a conditional approach based upon the probability distribution function of Y given X. Indeed, this approach is affected by the curse of dimensionality, so that the resulting estimator of the residual term E would have considerably a slow rate of convergence if the dimension of X is very high. Two approaches are proposed in this thesis to avoid the curse of dimensionality. The first approach uses the estimated residuals, while the second integrates a nonparametric conditional density estimator of Y given X. If proceeding so can circumvent the curse of dimensionality, a challenging issue is to evaluate the impact of the estimated residuals on the final estimator of the density f. We will also at...
[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].
Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong
2015-11-01
With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.
Fast and accurate probability density estimation in large high dimensional astronomical datasets
Gupta, Pramod; Connolly, Andrew J.; Gardner, Jeffrey P.
2015-01-01
Astronomical surveys will generate measurements of hundreds of attributes (e.g. color, size, shape) on hundreds of millions of sources. Analyzing these large, high dimensional data sets will require efficient algorithms for data analysis. An example of this is probability density estimation that is at the heart of many classification problems such as the separation of stars and quasars based on their colors. Popular density estimation techniques use binning or kernel density estimation. Kernel density estimation has a small memory footprint but often requires large computational resources. Binning has small computational requirements but usually binning is implemented with multi-dimensional arrays which leads to memory requirements which scale exponentially with the number of dimensions. Hence both techniques do not scale well to large data sets in high dimensions. We present an alternative approach of binning implemented with hash tables (BASH tables). This approach uses the sparseness of data in the high dimensional space to ensure that the memory requirements are small. However hashing requires some extra computation so a priori it is not clear if the reduction in memory requirements will lead to increased computational requirements. Through an implementation of BASH tables in C++ we show that the additional computational requirements of hashing are negligible. Hence this approach has small memory and computational requirements. We apply our density estimation technique to photometric selection of quasars using non-parametric Bayesian classification and show that the accuracy of the classification is same as the accuracy of earlier approaches. Since the BASH table approach is one to three orders of magnitude faster than the earlier approaches it may be useful in various other applications of density estimation in astrostatistics.
Statistical Analysis of the Spectral Density Estimate Obtained via Coifman Scaling Function
2007-01-01
Spectral density built as Fourier transform of covariance sequence of stationary random process is determining the process characteristics and makes for analysis of it’s structure. Thus, one of the main problems in time series analysis is constructing consistent estimates of spectral density via successive, taken after equal periods of time observations of stationary random process. This article is devoted to investigation of problems dealing with application of wavelet anal...
Bulk density estimation using a 3-dimensional image acquisition and analysis system
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Heyduk Adam
2016-01-01
Full Text Available The paper presents a concept of dynamic bulk density estimation of a particulate matter stream using a 3-d image analysis system and a conveyor belt scale. A method of image acquisition should be adjusted to the type of scale. The paper presents some laboratory results of static bulk density measurements using the MS Kinect time-of-flight camera and OpenCV/Matlab software. Measurements were made for several different size classes.
Estimation Prospects of the Source Number Density of Ultra-high-energy Cosmic Rays
Takami, Hajime; Sato, Katsuhiko
2007-01-01
We discuss the possibility of accurately estimating the source number density of ultra-high-energy cosmic rays (UHECRs) using small-scale anisotropy in their arrival distribution. The arrival distribution has information on their source and source distribution. We calculate the propagation of UHE protons in a structured extragalactic magnetic field (EGMF) and simulate their arrival distribution at the Earth using our previously developed method. The source number density that can best reprodu...
Pruitt, Sandi L.; Tiro, Jasmin A.; Xuan, Lei; Lee, Simon J. Craddock
2016-01-01
To test the Hispanic and Immigrant Paradoxes—i.e., survival advantages despite a worse risk factor profile—and the modifying role of neighborhood context, we examined associations between patient ethnicity, birthplace, neighborhood Hispanic density and neighborhood poverty among 166,254 female breast cancer patients diagnosed 1995–2009 in Texas, U.S. Of all, 79.9% were non-Hispanic White, 15.8% Hispanic U.S.-born, and 4.2% Hispanic foreign-born. We imputed birthplace for the 60.7% of Hispanics missing birthplace data using multiple imputation. Shared frailty Cox proportional hazard models (patients nested within census tracts) adjusted for age, diagnosis year, stage, grade, histology, urban/rural residence, and local mammography capacity. Whites (vs. U.S.-born Hispanics) had increased all-cause and breast cancer mortality. Foreign-born (vs. U.S.-born) Hispanics had increased all-cause and breast cancer mortality. Living in higher Hispanic density neighborhoods was generally associated with increased mortality, although associations differed slightly in magnitude and significance by ethnicity, birthplace, and neighborhood poverty. We found no evidence of an Immigrant Paradox and some evidence of a Hispanic Paradox where protective effects were limited to U.S.-born Hispanics. Contrary to prior studies, foreign birthplace and residence in higher Hispanic density neighborhoods were associated with increased mortality. More research on intersections between ethnicity, birthplace and neighborhood context are needed. PMID:27983668
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Sandi L. Pruitt
2016-12-01
Full Text Available To test the Hispanic and Immigrant Paradoxes—i.e., survival advantages despite a worse risk factor profile—and the modifying role of neighborhood context, we examined associations between patient ethnicity, birthplace, neighborhood Hispanic density and neighborhood poverty among 166,254 female breast cancer patients diagnosed 1995–2009 in Texas, U.S. Of all, 79.9% were non-Hispanic White, 15.8% Hispanic U.S.-born, and 4.2% Hispanic foreign-born. We imputed birthplace for the 60.7% of Hispanics missing birthplace data using multiple imputation. Shared frailty Cox proportional hazard models (patients nested within census tracts adjusted for age, diagnosis year, stage, grade, histology, urban/rural residence, and local mammography capacity. Whites (vs. U.S.-born Hispanics had increased all-cause and breast cancer mortality. Foreign-born (vs. U.S.-born Hispanics had increased all-cause and breast cancer mortality. Living in higher Hispanic density neighborhoods was generally associated with increased mortality, although associations differed slightly in magnitude and significance by ethnicity, birthplace, and neighborhood poverty. We found no evidence of an Immigrant Paradox and some evidence of a Hispanic Paradox where protective effects were limited to U.S.-born Hispanics. Contrary to prior studies, foreign birthplace and residence in higher Hispanic density neighborhoods were associated with increased mortality. More research on intersections between ethnicity, birthplace and neighborhood context are needed.
Estimate of the density of Eucalyptus grandis W. Hill ex Maiden using near infrared spectroscopy
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Silviana Rosso
2013-12-01
Full Text Available This study aimed to analyze use of near infrared spectroscopy (NIRS to estimate wood density of Eucalyptus grandis. For that, 66 27-year-old trees were logged and central planks were removed from each log. Test pieces 2.5 x 2.5 x 5.0 cm in size were removed from the base of each plank, in the pith-bark direction, and subjected to determination of bulk and basic density at 12% moisture (dry basis, followed by spectral readings in the radial, tangential and transverse directions using a Bruker Tensor 37 infrared spectrophotometer. The calibration to estimate wood density was developed based on the matrix of spectra obtained from the radial face, containing 216 samples. The partial least squares regression to estimate bulk wood density of Eucalyptus grandis provided a coefficient of determination of validation of 0.74 and a ratio performance deviation of 2.29. Statistics relating to the predictive models had adequate magnitudes for estimating wood density from unknown samples, indicating that the above technique has potential for use in replacement of conventional testing.
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Anjali
2015-12-01
Full Text Available Breast cancer is the most common site specific cancer in women. Lots of etiological factors have been suggested regarding its causation. The risk is influenced by obesity, parity, exogenous and endogenous hormones, exposure to chemicals and radiation and many more. Various studies suggest that as HDL-C seems to be cardio protective, it is also protective for breast cancer. Serum HDL-C levels are found to be low in breast cancer patients. We studied this hypothesis in local population of Southern Rajasthan and nearby region to see if low serum HDL-C is associated with increased risk of breast cancer. We studied serum HDL-C level in 50 female patients of breast cancer along with their menopausal status and compared it to their respective controls. We found that breast cancer patients had significantly low level of serum HDL-C and presented in advanced stage of cancer. It supports that low serum HDL-C level is associated with increased risk of breast cancer. So one should think about those dietary and lifestyle measures, which maintain high serum HDL-C level so that it might become preventive measure for breast cancer.
Energy Technology Data Exchange (ETDEWEB)
Ramos, M [Chemical and Nuclear Engineering Department, Polytechnic University of Valencia, Camino de Vera s/n 46022 Valencia (Spain); Ferrer, S [Chemical and Nuclear Engineering Department, Polytechnic University of Valencia, Camino de Vera s/n 46022 Valencia (Spain); Villaescusa, J I [Radiation Protection Service, Hospital Universitario La Fe, Avda Campanar, 21 46009 Valencia (Spain); Verdu, G [Chemical and Nuclear Engineering Department, Polytechnic University of Valencia, Camino de Vera s/n 46022 Valencia (Spain); Salas, M D [Public Health General Direction, Conselleria de Sanitat de Valencia, C/Micer Masco, 31 46021 Valencia (Spain); Cuevas, M D [Assistential Service General Direction, Conselleria de Sanitat de Valencia, C/Micer Masco, 31 46021 Valencia (Spain)
2005-02-07
The authors report on a method to calculate radiological risks, applicable to breast screening programs and other controlled medical exposures to ionizing radiation. In particular, it has been applied to make a risk assessment in the Valencian Breast Cancer Early Detection Program (VBCEDP) in Spain. This method is based on a parametric approach, through Markov processes, of hazard functions for radio-induced breast cancer incidence and mortality, with mean glandular breast dose, attained age and age-at-exposure as covariates. Excess relative risk functions of breast cancer mortality have been obtained from two different case-control studies exposed to ionizing radiation, with different follow-up time: the Canadian Fluoroscopy Cohort Study (1950-1987) and the Life Span Study (1950-1985 and 1950-1990), whereas relative risk functions for incidence have been obtained from the Life Span Study (1958-1993), the Massachusetts tuberculosis cohorts (1926-1985 and 1970-1985), the New York post-partum mastitis patients (1930-1981) and the Swedish benign breast disease cohort (1958-1987). Relative risks from these cohorts have been transported to the target population undergoing screening in the Valencian Community, a region in Spain with about four and a half million inhabitants. The SCREENRISK software has been developed to estimate radiological detriments in breast screening. Some hypotheses corresponding to different screening conditions have been considered in order to estimate the total risk associated with a woman who takes part in all screening rounds. In the case of the VBCEDP, the total radio-induced risk probability for fatal breast cancer is in a range between [5 x 10{sup -6}, 6 x 10{sup -4}] versus the natural rate of dying from breast cancer in the Valencian Community which is 9.2 x 10{sup -3}. The results show that these indicators could be included in quality control tests and could be adequate for making comparisons between several screening programs.
PEDO-TRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY IN CENTRAL AMAZONIA
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Henrique Seixas Barros
2015-04-01
Full Text Available Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R2 and Akaike information criterion (AIC and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R2 = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region.
Estimating the amount and distribution of radon flux density from the soil surface in China.
Zhuo, Weihai; Guo, Qiuju; Chen, Bo; Cheng, Guan
2008-07-01
Based on an idealized model, both the annual and the seasonal radon ((222)Rn) flux densities from the soil surface at 1099 sites in China were estimated by linking a database of soil (226)Ra content and a global ecosystems database. Digital maps of the (222)Rn flux density in China were constructed in a spatial resolution of 25 km x 25 km by interpolation among the estimated data. An area-weighted annual average (222)Rn flux density from the soil surface across China was estimated to be 29.7+/-9.4 mBq m(-2)s(-1). Both regional and seasonal variations in the (222)Rn flux densities are significant in China. Annual average flux densities in the southeastern and northwestern China are generally higher than those in other regions of China, because of high soil (226)Ra content in the southeastern area and high soil aridity in the northwestern one. The seasonal average flux density is generally higher in summer/spring than winter, since relatively higher soil temperature and lower soil water saturation in summer/spring than other seasons are common in China.
Brassine, Eléanor; Parker, Daniel
2015-01-01
Camera trapping studies have become increasingly popular to produce population estimates of individually recognisable mammals. Yet, monitoring techniques for rare species which occur at extremely low densities are lacking. Additionally, species which have unpredictable movements may make obtaining reliable population estimates challenging due to low detectability. Our study explores the effectiveness of intensive camera trapping for estimating cheetah (Acinonyx jubatus) numbers. Using both a more traditional, systematic grid approach and pre-determined, targeted sites for camera placement, the cheetah population of the Northern Tuli Game Reserve, Botswana was sampled between December 2012 and October 2013. Placement of cameras in a regular grid pattern yielded very few (n = 9) cheetah images and these were insufficient to estimate cheetah density. However, pre-selected cheetah scent-marking posts provided 53 images of seven adult cheetahs (0.61 ± 0.18 cheetahs/100 km²). While increasing the length of the camera trapping survey from 90 to 130 days increased the total number of cheetah images obtained (from 53 to 200), no new individuals were recorded and the estimated population density remained stable. Thus, our study demonstrates that targeted camera placement (irrespective of survey duration) is necessary for reliably assessing cheetah densities where populations are naturally very low or dominated by transient individuals. Significantly our approach can easily be applied to other rare predator species.
Marques, Tiago A; Thomas, Len; Ward, Jessica; DiMarzio, Nancy; Tyack, Peter L
2009-04-01
Methods are developed for estimating the size/density of cetacean populations using data from a set of fixed passive acoustic sensors. The methods convert the number of detected acoustic cues into animal density by accounting for (i) the probability of detecting cues, (ii) the rate at which animals produce cues, and (iii) the proportion of false positive detections. Additional information is often required for estimation of these quantities, for example, from an acoustic tag applied to a sample of animals. Methods are illustrated with a case study: estimation of Blainville's beaked whale density over a 6 day period in spring 2005, using an 82 hydrophone wide-baseline array located in the Tongue of the Ocean, Bahamas. To estimate the required quantities, additional data are used from digital acoustic tags, attached to five whales over 21 deep dives, where cues recorded on some of the dives are associated with those received on the fixed hydrophones. Estimated density was 25.3 or 22.5 animals/1000 km(2), depending on assumptions about false positive detections, with 95% confidence intervals 17.3-36.9 and 15.4-32.9. These methods are potentially applicable to a wide variety of marine and terrestrial species that are hard to survey using conventional visual methods.
Williams, C R; Johnson, P H; Ball, T S; Ritchie, S A
2013-09-01
New mosquito control strategies centred on the modifying of populations require knowledge of existing population densities at release sites and an understanding of breeding site ecology. Using a quantitative pupal survey method, we investigated production of the dengue vector Aedes aegypti (L.) (Stegomyia aegypti) (Diptera: Culicidae) in Cairns, Queensland, Australia, and found that garden accoutrements represented the most common container type. Deliberately placed 'sentinel' containers were set at seven houses and sampled for pupae over 10 weeks during the wet season. Pupal production was approximately constant; tyres and buckets represented the most productive container types. Sentinel tyres produced the largest female mosquitoes, but were relatively rare in the field survey. We then used field-collected data to make estimates of per premises population density using three different approaches. Estimates of female Ae. aegypti abundance per premises made using the container-inhabiting mosquito simulation (CIMSiM) model [95% confidence interval (CI) 18.5-29.1 females] concorded reasonably well with estimates obtained using a standing crop calculation based on pupal collections (95% CI 8.8-22.5) and using BG-Sentinel traps and a sampling rate correction factor (95% CI 6.2-35.2). By first describing local Ae. aegypti productivity, we were able to compare three separate population density estimates which provided similar results. We anticipate that this will provide researchers and health officials with several tools with which to make estimates of population densities.
Directory of Open Access Journals (Sweden)
Eléanor Brassine
Full Text Available Camera trapping studies have become increasingly popular to produce population estimates of individually recognisable mammals. Yet, monitoring techniques for rare species which occur at extremely low densities are lacking. Additionally, species which have unpredictable movements may make obtaining reliable population estimates challenging due to low detectability. Our study explores the effectiveness of intensive camera trapping for estimating cheetah (Acinonyx jubatus numbers. Using both a more traditional, systematic grid approach and pre-determined, targeted sites for camera placement, the cheetah population of the Northern Tuli Game Reserve, Botswana was sampled between December 2012 and October 2013. Placement of cameras in a regular grid pattern yielded very few (n = 9 cheetah images and these were insufficient to estimate cheetah density. However, pre-selected cheetah scent-marking posts provided 53 images of seven adult cheetahs (0.61 ± 0.18 cheetahs/100 km². While increasing the length of the camera trapping survey from 90 to 130 days increased the total number of cheetah images obtained (from 53 to 200, no new individuals were recorded and the estimated population density remained stable. Thus, our study demonstrates that targeted camera placement (irrespective of survey duration is necessary for reliably assessing cheetah densities where populations are naturally very low or dominated by transient individuals. Significantly our approach can easily be applied to other rare predator species.
A hierarchical model for estimating density in camera-trap studies
Royle, J. Andrew; Nichols, James D.; Karanth, K.Ullas; Gopalaswamy, Arjun M.
2009-01-01
Estimating animal density using capture–recapture data from arrays of detection devices such as camera traps has been problematic due to the movement of individuals and heterogeneity in capture probability among them induced by differential exposure to trapping.We develop a spatial capture–recapture model for estimating density from camera-trapping data which contains explicit models for the spatial point process governing the distribution of individuals and their exposure to and detection by traps.We adopt a Bayesian approach to analysis of the hierarchical model using the technique of data augmentation.The model is applied to photographic capture–recapture data on tigers Panthera tigris in Nagarahole reserve, India. Using this model, we estimate the density of tigers to be 14·3 animals per 100 km2 during 2004.Synthesis and applications. Our modelling framework largely overcomes several weaknesses in conventional approaches to the estimation of animal density from trap arrays. It effectively deals with key problems such as individual heterogeneity in capture probabilities, movement of traps, presence of potential ‘holes’ in the array and ad hoc estimation of sample area. The formulation, thus, greatly enhances flexibility in the conduct of field surveys as well as in the analysis of data, from studies that may involve physical, photographic or DNA-based ‘captures’ of individual animals.
Scent Lure Effect on Camera-Trap Based Leopard Density Estimates.
Directory of Open Access Journals (Sweden)
Alexander Richard Braczkowski
Full Text Available Density estimates for large carnivores derived from camera surveys often have wide confidence intervals due to low detection rates. Such estimates are of limited value to authorities, which require precise population estimates to inform conservation strategies. Using lures can potentially increase detection, improving the precision of estimates. However, by altering the spatio-temporal patterning of individuals across the camera array, lures may violate closure, a fundamental assumption of capture-recapture. Here, we test the effect of scent lures on the precision and veracity of density estimates derived from camera-trap surveys of a protected African leopard population. We undertook two surveys (a 'control' and 'treatment' survey on Phinda Game Reserve, South Africa. Survey design remained consistent except a scent lure was applied at camera-trap stations during the treatment survey. Lures did not affect the maximum movement distances (p = 0.96 or temporal activity of female (p = 0.12 or male leopards (p = 0.79, and the assumption of geographic closure was met for both surveys (p >0.05. The numbers of photographic captures were also similar for control and treatment surveys (p = 0.90. Accordingly, density estimates were comparable between surveys (although estimates derived using non-spatial methods (7.28-9.28 leopards/100km2 were considerably higher than estimates from spatially-explicit methods (3.40-3.65 leopards/100km2. The precision of estimates from the control and treatment surveys, were also comparable and this applied to both non-spatial and spatial methods of estimation. Our findings suggest that at least in the context of leopard research in productive habitats, the use of lures is not warranted.
Variational estimation of the drift for stochastic differential equations from the empirical density
Batz, Philipp; Opper, Manfred
2016-01-01
We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the Fokker-Planck equation. The minimization of an empirical estimate of the variational functional using kernel based regularization can be performed in closed form. We demonstrate the performance of the method on second order, Langevin-type equations and show how the method can be generalized to other noise models.
Application of Density Estimation Methods to Datasets Collected From a Glider
2015-09-30
buoyancy. The methodology employed in this study to estimate population density of marine mammals is based on the works of Zimmer et al. (2008), Marques ...estimation modalities (Thomas and Marques , 2012), such as individual or group counting. In this sense, bearings to received sounds on both hydrophones will...the sea trial. Figure 2. Left: Image showing the area of REP14-MED sea-trial (red box) in the context of the Western Mediterranean Sea and
Variational estimation of the drift for stochastic differential equations from the empirical density
Batz, Philipp; Ruttor, Andreas; Opper, Manfred
2016-08-01
We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the Fokker-Planck equation. The minimization of an empirical estimate of the variational functional using kernel based regularization can be performed in closed form. We demonstrate the performance of the method on second order, Langevin-type equations and show how the method can be generalized to other noise models.
Estimation of current density distribution of PAFC by analysis of cell exhaust gas
Energy Technology Data Exchange (ETDEWEB)
Kato, S.; Seya, A. [Fuji Electric Co., Ltd., Ichihara-shi (Japan); Asano, A. [Fuji Electric Corporate, Ltd., Yokosuka-shi (Japan)
1996-12-31
To estimate distributions of Current densities, voltages, gas concentrations, etc., in phosphoric acid fuel cell (PAFC) stacks, is very important for getting fuel cells with higher quality. In this work, we leave developed a numerical simulation tool to map out the distribution in a PAFC stack. And especially to Study Current density distribution in the reaction area of the cell, we analyzed gas composition in several positions inside a gas outlet manifold of the PAFC stack. Comparing these measured data with calculated data, the current density distribution in a cell plane calculated by the simulation, was certified.
Parameter estimation of breast tumour using dynamic neural network from thermal pattern
Directory of Open Access Journals (Sweden)
Elham Saniei
2016-11-01
Full Text Available This article presents a new approach for estimating the depth, size, and metabolic heat generation rate of a tumour. For this purpose, the surface temperature distribution of a breast thermal image and the dynamic neural network was used. The research consisted of two steps: forward and inverse. For the forward section, a finite element model was created. The Pennes bio-heat equation was solved to find surface and depth temperature distributions. Data from the analysis, then, were used to train the dynamic neural network model (DNN. Results from the DNN training/testing confirmed those of the finite element model. For the inverse section, the trained neural network was applied to estimate the depth temperature distribution (tumour position from the surface temperature profile, extracted from the thermal image. Finally, tumour parameters were obtained from the depth temperature distribution. Experimental findings (20 patients were promising in terms of the model’s potential for retrieving tumour parameters.
Retrieval of mesospheric electron densities using an optimal estimation inverse method
Grant, J.; Grainger, R. G.; Lawrence, B. N.; Fraser, G. J.; von Biel, H. A.; Heuff, D. N.; Plank, G. E.
2004-03-01
We present a new method to determine mesospheric electron densities from partially reflected medium frequency radar pulses. The technique uses an optimal estimation inverse method and retrieves both an electron density profile and a gradient electron density profile. As well as accounting for the absorption of the two magnetoionic modes formed by ionospheric birefringence of each radar pulse, the forward model of the retrieval parameterises possible Fresnel scatter of each mode by fine electronic structure, phase changes of each mode due to Faraday rotation and the dependence of the amplitudes of the backscattered modes upon pulse width. Validation results indicate that known profiles can be retrieved and that χ2 tests upon retrieval parameters satisfy validity criteria. Application to measurements shows that retrieved electron density profiles are consistent with accepted ideas about seasonal variability of electron densities and their dependence upon nitric oxide production and transport.
Estimating abundance and density of Amur tigers along the Sino-Russian border.
Xiao, Wenhong; Feng, Limin; Mou, Pu; Miquelle, Dale G; Hebblewhite, Mark; Goldberg, Joshua F; Robinson, Hugh S; Zhao, Xiaodan; Zhou, Bo; Wang, Tianming; Ge, Jianping
2016-07-01
As an apex predator the Amur tiger (Panthera tigris altaica) could play a pivotal role in maintaining the integrity of forest ecosystems in Northeast Asia. Due to habitat loss and harvest over the past century, tigers rapidly declined in China and are now restricted to the Russian Far East and bordering habitat in nearby China. To facilitate restoration of the tiger in its historical range, reliable estimates of population size are essential to assess effectiveness of conservation interventions. Here we used camera trap data collected in Hunchun National Nature Reserve from April to June 2013 and 2014 to estimate tiger density and abundance using both maximum likelihood and Bayesian spatially explicit capture-recapture (SECR) methods. A minimum of 8 individuals were detected in both sample periods and the documentation of marking behavior and reproduction suggests the presence of a resident population. Using Bayesian SECR modeling within the 11 400 km(2) state space, density estimates were 0.33 and 0.40 individuals/100 km(2) in 2013 and 2014, respectively, corresponding to an estimated abundance of 38 and 45 animals for this transboundary Sino-Russian population. In a maximum likelihood framework, we estimated densities of 0.30 and 0.24 individuals/100 km(2) corresponding to abundances of 34 and 27, in 2013 and 2014, respectively. These density estimates are comparable to other published estimates for resident Amur tiger populations in the Russian Far East. This study reveals promising signs of tiger recovery in Northeast China, and demonstrates the importance of connectivity between the Russian and Chinese populations for recovering tigers in Northeast China.
Goldenshluger, Alexander
2010-01-01
We address the problem of density estimation with $\\bL_p$--loss by selection of kernel estimators. We develop a selection procedure and derive corresponiding $\\bL_p$--risk oracle inequalities. It is shown that the proposed selection rule leads to the minimax estimator that is adaptive over a scale of the anisotropic Nikol'ski classes. The main technical tools used in our derivations are uniform bounds on the $\\bL_p$--norms of empirical processes developed recently in Goldenshluger and Lepski~(2010).
DEFF Research Database (Denmark)
Rosholm, A; Hyldstrup, L; Backsgaard, L
2002-01-01
A new automated radiogrammetric method to estimate bone mineral density (BMD) from a single radiograph of the hand and forearm is described. Five regions of interest in radius, ulna and the three middle metacarpal bones are identified and approximately 1800 geometrical measurements from these bon...
ASYMPTOTIC NORMALITY OF KERNEL ESTIMATES OF A DENSITY FUNCTION UNDER ASSOCIATION DEPENDENCE
Institute of Scientific and Technical Information of China (English)
林正炎
2003-01-01
Let {Xn,n> _ 1} be a strictly stationary sequence of random variables,which are either associated or negatively associated,f(·)be their common density.In this paper,the author shows a central limit theorem for a kernel estimate of f(·)under certain regular conditions.
Gao, Nuo; Zhu, S A; He, Bin
2005-06-01
We have developed a new algorithm for magnetic resonance electrical impedance tomography (MREIT), which uses only one component of the magnetic flux density to reconstruct the electrical conductivity distribution within the body. The radial basis function (RBF) network and simplex method are used in the present approach to estimate the conductivity distribution by minimizing the errors between the 'measured' and model-predicted magnetic flux densities. Computer simulations were conducted in a realistic-geometry head model to test the feasibility of the proposed approach. Single-variable and three-variable simulations were performed to estimate the brain-skull conductivity ratio and the conductivity values of the brain, skull and scalp layers. When SNR = 15 for magnetic flux density measurements with the target skull-to-brain conductivity ratio being 1/15, the relative error (RE) between the target and estimated conductivity was 0.0737 +/- 0.0746 in the single-variable simulations. In the three-variable simulations, the RE was 0.1676 +/- 0.0317. Effects of electrode position uncertainty were also assessed by computer simulations. The present promising results suggest the feasibility of estimating important conductivity values within the head from noninvasive magnetic flux density measurements.
Mohd Salleh, M. R.; Rahman, M. Z. Abdul; Abu Bakar, M. A.; Rasib, A. W.; Omar, H.
2016-09-01
This paper presents a framework to estimate aerodynamic roughness over specific height (zo/H) and zero plane displacement (d/H) over various landscapes in Kelantan State using airborne LiDAR data. The study begins with the filtering of airborne LiDAR, which produced ground and non-ground points. The ground points were used to generate digital terrain model (DTM) while the non-ground points were used for digital surface model (DSM) generation. Canopy height model (CHM) was generated by subtracting DTM from DSM. Individual trees in the study area were delineated by applying the Inverse Watershed segmentation method on the CHM. Forest structural parameters including tree height, height to crown base (HCB) and diameter at breast height (DBH) were estimated using existing allometric equations. The airborne LiDAR data was divided into smaller areas, which correspond to the size of the zo/H and d/H maps i.e. 50 m and 100 m. For each area individual tree were reconstructed based on the tree properties, which accounts overlapping between crowns and trunks. The individual tree models were used to estimate individual tree frontal area and the total frontal area over a specific ground surface. Finally, three roughness models were used to estimate zo/H and d/H for different wind directions, which were assumed from North/South and East/West directions. The results were shows good agreements with previous studies that based on the wind tunnel experiments.
Topological Pressure and Coding Sequence Density Estimation in the Human Genome
Koslicki, David
2011-01-01
Inspired by concepts from ergodic theory, we give new insight into coding sequence (CDS) density estimation for the human genome. Our approach is based on the introduction and study of topological pressure: a numerical quantity assigned to any finite sequence based on an appropriate notion of `weighted information content'. For human DNA sequences, each codon is assigned a suitable weight, and using a window size of approximately 60,000bp, we obtain a very strong positive correlation between CDS density and topological pressure. The weights are selected by an optimization procedure, and can be interpreted as quantitative data on the relative importance of different codons for the density estimation of coding sequences. This gives new insight into codon usage bias which is an important subject where long standing questions remain open. Inspired again by ergodic theory, we use the weightings on the codons to define a probability measure on finite sequences. We demonstrate that this measure is effective in disti...
Application of Kernel Density Estimation in Lamb Wave-Based Damage Detection
Directory of Open Access Journals (Sweden)
Long Yu
2012-01-01
Full Text Available The present work concerns the estimation of the probability density function (p.d.f. of measured data in the Lamb wave-based damage detection. Although there was a number of research work which focused on the consensus algorithm of combining all the results of individual sensors, the p.d.f. of measured data, which was the fundamental part of the probability-based method, was still given by experience in existing work. Based on the analysis about the noise-induced errors in measured data, it was learned that the type of distribution was related with the level of noise. In the case of weak noise, the p.d.f. of measured data could be considered as the normal distribution. The empirical methods could give satisfied estimating results. However, in the case of strong noise, the p.d.f. was complex and did not belong to any type of common distribution function. Nonparametric methods, therefore, were needed. As the most popular nonparametric method, kernel density estimation was introduced. In order to demonstrate the performance of the kernel density estimation methods, a numerical model was built to generate the signals of Lamb waves. Three levels of white Gaussian noise were intentionally added into the simulated signals. The estimation results showed that the nonparametric methods outperformed the empirical methods in terms of accuracy.
Distributed Density Estimation Based on a Mixture of Factor Analyzers in a Sensor Network
Directory of Open Access Journals (Sweden)
Xin Wei
2015-08-01
Full Text Available Distributed density estimation in sensor networks has received much attention due to its broad applicability. When encountering high-dimensional observations, a mixture of factor analyzers (MFA is taken to replace mixture of Gaussians for describing the distributions of observations. In this paper, we study distributed density estimation based on a mixture of factor analyzers. Existing estimation algorithms of the MFA are for the centralized case, which are not suitable for distributed processing in sensor networks. We present distributed density estimation algorithms for the MFA and its extension, the mixture of Student’s t-factor analyzers (MtFA. We first define an objective function as the linear combination of local log-likelihoods. Then, we give the derivation process of the distributed estimation algorithms for the MFA and MtFA in details, respectively. In these algorithms, the local sufficient statistics (LSS are calculated at first and diffused. Then, each node performs a linear combination of the received LSS from nodes in its neighborhood to obtain the combined sufficient statistics (CSS. Parameters of the MFA and the MtFA can be obtained by using the CSS. Finally, we evaluate the performance of these algorithms by numerical simulations and application example. Experimental results validate the promising performance of the proposed algorithms.
Energy Technology Data Exchange (ETDEWEB)
Koo, Hye Ryoung, E-mail: huilings@hanmail.net [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Moon, Woo Kyung, E-mail: moonwk@snu.ac.kr [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Chun, In Kook, E-mail: inkook.chun@gmail.com [Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Eo, Jae Seon, E-mail: jaeseon76@gmail.com [Department of Nuclear Medicine, Korea University Guro Hospital, 148 Gurodongro, Guro-gu, Seoul 152-703 (Korea, Republic of); Jeyanth, Joseph Xavier, E-mail: jeyanth7@snu.ac.kr [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Chang, Jung Min, E-mail: imchangjm@gmail.com [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Cho, Nariya, E-mail: river7774@gmail.com [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Kang, Keon Wook, E-mail: kangkw@snu.ac.kr [Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of)
2013-10-01
We aimed to determine whether background {sup 18}F-FDG uptake in positron emission mammography (PEM) was related to mammographic density or background parenchymal enhancement in breast MRI. Methods: We studied a total of 52 patients (mean age, 50.9 years, 26 premenopausal, 26 postmenopausal) with newly diagnosed breast cancer who underwent {sup 18}F-FDG PEM (positron emission mammography), conventional mammography and breast MRI. The background mean {sup 18}F-FDG uptake value on PEM was obtained by drawing a user-defined region of interest (ROI) in a normal area of the contralateral breast. We reviewed the mammography retrospectively for overall breast density of contralateral breast according to the four-point scale (grade 1–4) of the Breast Imaging Reporting and Data System (BI-RADS) classification. The background parenchymal enhancement of breast MRI was classified as minimal, mild, moderate, or marked. All imaging findings were interpreted by two readers in consensus without knowledge of image findings of other modalities. Results: Multiple linear regression analysis revealed a significant correlation between background {sup 18}F-FDG uptake on PEM and mammographic density after adjustment for age and menopausal status (P < 0.01), but not between background {sup 18}F-FDG uptake on PEM and background parenchymal enhancement on MRI. Conclusion: Background {sup 18}F-FDG uptake on PEM significantly increases as mammographic density increases. Background parenchymal enhancement in breast MRI was not an independent predictor of the background {sup 18}F-FDG uptake on PEM unlike mammographic density.
Noninvasive assessment of breast cancer risk using time-resolved diffuse optical spectroscopy
Taroni, Paola; Pifferi, Antonio; Quarto, Giovanna; Spinelli, Lorenzo; Torricelli, Alessandro; Abbate, Francesca; Villa, Anna; Balestreri, Nicola; Menna, Simona; Cassano, Enrico; Cubeddu, Rinaldo
2010-11-01
Breast density is a recognized strong and independent risk factor for breast cancer. We propose the use of time-resolved transmittance spectroscopy to estimate breast tissue density and potentially provide even more direct information on breast cancer risk. Time-resolved optical mammography at seven wavelengths (635 to 1060 nm) is performed on 49 subjects. Average information on breast tissue of each subject is obtained on oxy- and deoxyhemoglobin, water, lipids, and collagen content, as well as scattering amplitude and power. All parameters, except for blood volume and oxygenation, correlate with mammographic breast density, even if not to the same extent. A synthetic optical index proves to be quite effective in separating different breast density categories. Finally, the estimate of collagen content as a more direct means for the assessment of breast cancer risk is discussed.
Estimation of dislocation density from precession electron diffraction data using the Nye tensor.
Leff, A C; Weinberger, C R; Taheri, M L
2015-06-01
The Nye tensor offers a means to estimate the geometrically necessary dislocation density of a crystalline sample based on measurements of the orientation changes within individual crystal grains. In this paper, the Nye tensor theory is applied to precession electron diffraction automated crystallographic orientation mapping (PED-ACOM) data acquired using a transmission electron microscope (TEM). The resulting dislocation density values are mapped in order to visualize the dislocation structures present in a quantitative manner. These density maps are compared with other related methods of approximating local strain dependencies in dislocation-based microstructural transitions from orientation data. The effect of acquisition parameters on density measurements is examined. By decreasing the step size and spot size during data acquisition, an increasing fraction of the dislocation content becomes accessible. Finally, the method described herein is applied to the measurement of dislocation emission during in situ annealing of Cu in TEM in order to demonstrate the utility of the technique for characterizing microstructural dynamics.
Estimation of energy density of Li-S batteries with liquid and solid electrolytes
Li, Chunmei; Zhang, Heng; Otaegui, Laida; Singh, Gurpreet; Armand, Michel; Rodriguez-Martinez, Lide M.
2016-09-01
With the exponential growth of technology in mobile devices and the rapid expansion of electric vehicles into the market, it appears that the energy density of the state-of-the-art Li-ion batteries (LIBs) cannot satisfy the practical requirements. Sulfur has been one of the best cathode material choices due to its high charge storage (1675 mAh g-1), natural abundance and easy accessibility. In this paper, calculations are performed for different cell design parameters such as the active material loading, the amount/thickness of electrolyte, the sulfur utilization, etc. to predict the energy density of Li-S cells based on liquid, polymeric and ceramic electrolytes. It demonstrates that Li-S battery is most likely to be competitive in gravimetric energy density, but not volumetric energy density, with current technology, when comparing with LIBs. Furthermore, the cells with polymer and thin ceramic electrolytes show promising potential in terms of high gravimetric energy density, especially the cells with the polymer electrolyte. This estimation study of Li-S energy density can be used as a good guidance for controlling the key design parameters in order to get desirable energy density at cell-level.
A method to estimate the neutral atmospheric density near the ionospheric main peak of Mars
Zou, Hong; Ye, Yu Guang; Wang, Jin Song; Nielsen, Erling; Cui, Jun; Wang, Xiao Dong
2016-04-01
A method to estimate the neutral atmospheric density near the ionospheric main peak of Mars is introduced in this study. The neutral densities at 130 km can be derived from the ionospheric and atmospheric measurements of the Radio Science experiment on board Mars Global Surveyor (MGS). The derived neutral densities cover a large longitude range in northern high latitudes from summer to late autumn during 3 Martian years, which fills the gap of the previous observations for the upper atmosphere of Mars. The simulations of the Laboratoire de Météorologie Dynamique Mars global circulation model can be corrected with a simple linear equation to fit the neutral densities derived from the first MGS/RS (Radio Science) data sets (EDS1). The corrected simulations with the same correction parameters as for EDS1 match the derived neutral densities from two other MGS/RS data sets (EDS2 and EDS3) very well. The derived neutral density from EDS3 shows a dust storm effect, which is in accord with the Mars Express (MEX) Spectroscopy for Investigation of Characteristics of the Atmosphere of Mars measurement. The neutral density derived from the MGS/RS measurements can be used to validate the Martian atmospheric models. The method presented in this study can be applied to other radio occultation measurements, such as the result of the Radio Science experiment on board MEX.
Energy Technology Data Exchange (ETDEWEB)
Burke, TImothy P. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kiedrowski, Brian C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Martin, William R. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-11-19
Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics for one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.
Joint estimation of crown of thorns (Acanthaster planci) densities on the Great Barrier Reef.
MacNeil, M Aaron; Mellin, Camille; Pratchett, Morgan S; Hoey, Jessica; Anthony, Kenneth R N; Cheal, Alistair J; Miller, Ian; Sweatman, Hugh; Cowan, Zara L; Taylor, Sascha; Moon, Steven; Fonnesbeck, Chris J
2016-01-01
Crown-of-thorns starfish (CoTS; Acanthaster spp.) are an outbreaking pest among many Indo-Pacific coral reefs that cause substantial ecological and economic damage. Despite ongoing CoTS research, there remain critical gaps in observing CoTS populations and accurately estimating their numbers, greatly limiting understanding of the causes and sources of CoTS outbreaks. Here we address two of these gaps by (1) estimating the detectability of adult CoTS on typical underwater visual count (UVC) surveys using covariates and (2) inter-calibrating multiple data sources to estimate CoTS densities within the Cairns sector of the Great Barrier Reef (GBR). We find that, on average, CoTS detectability is high at 0.82 [0.77, 0.87] (median highest posterior density (HPD) and [95% uncertainty intervals]), with CoTS disc width having the greatest influence on detection. Integrating this information with coincident surveys from alternative sampling programs, we estimate CoTS densities in the Cairns sector of the GBR averaged 44 [41, 48] adults per hectare in 2014.
Joint estimation of crown of thorns (Acanthaster planci densities on the Great Barrier Reef
Directory of Open Access Journals (Sweden)
M. Aaron MacNeil
2016-08-01
Full Text Available Crown-of-thorns starfish (CoTS; Acanthaster spp. are an outbreaking pest among many Indo-Pacific coral reefs that cause substantial ecological and economic damage. Despite ongoing CoTS research, there remain critical gaps in observing CoTS populations and accurately estimating their numbers, greatly limiting understanding of the causes and sources of CoTS outbreaks. Here we address two of these gaps by (1 estimating the detectability of adult CoTS on typical underwater visual count (UVC surveys using covariates and (2 inter-calibrating multiple data sources to estimate CoTS densities within the Cairns sector of the Great Barrier Reef (GBR. We find that, on average, CoTS detectability is high at 0.82 [0.77, 0.87] (median highest posterior density (HPD and [95% uncertainty intervals], with CoTS disc width having the greatest influence on detection. Integrating this information with coincident surveys from alternative sampling programs, we estimate CoTS densities in the Cairns sector of the GBR averaged 44 [41, 48] adults per hectare in 2014.
Density estimation in a wolverine population using spatial capture-recapture models
Royle, J. Andrew; Magoun, Audrey J.; Gardner, Beth; Valkenbury, Patrick; Lowell, Richard E.; McKelvey, Kevin
2011-01-01
Classical closed-population capture-recapture models do not accommodate the spatial information inherent in encounter history data obtained from camera-trapping studies. As a result, individual heterogeneity in encounter probability is induced, and it is not possible to estimate density objectively because trap arrays do not have a well-defined sample area. We applied newly-developed, capture-recapture models that accommodate the spatial attribute inherent in capture-recapture data to a population of wolverines (Gulo gulo) in Southeast Alaska in 2008. We used camera-trapping data collected from 37 cameras in a 2,140-km2 area of forested and open habitats largely enclosed by ocean and glacial icefields. We detected 21 unique individuals 115 times. Wolverines exhibited a strong positive trap response, with an increased tendency to revisit previously visited traps. Under the trap-response model, we estimated wolverine density at 9.7 individuals/1,000-km2(95% Bayesian CI: 5.9-15.0). Our model provides a formal statistical framework for estimating density from wolverine camera-trapping studies that accounts for a behavioral response due to baited traps. Further, our model-based estimator does not have strict requirements about the spatial configuration of traps or length of trapping sessions, providing considerable operational flexibility in the development of field studies.
Lennox, Kristin P; Dahl, David B; Vannucci, Marina; Tsai, Jerry W
2009-06-01
Interest in predicting protein backbone conformational angles has prompted the development of modeling and inference procedures for bivariate angular distributions. We present a Bayesian approach to density estimation for bivariate angular data that uses a Dirichlet process mixture model and a bivariate von Mises distribution. We derive the necessary full conditional distributions to fit the model, as well as the details for sampling from the posterior predictive distribution. We show how our density estimation method makes it possible to improve current approaches for protein structure prediction by comparing the performance of the so-called "whole" and "half" position distributions. Current methods in the field are based on whole position distributions, as density estimation for the half positions requires techniques, such as ours, that can provide good estimates for small datasets. With our method we are able to demonstrate that half position data provides a better approximation for the distribution of conformational angles at a given sequence position, therefore providing increased efficiency and accuracy in structure prediction.
Limit Distribution Theory for Maximum Likelihood Estimation of a Log-Concave Density.
Balabdaoui, Fadoua; Rufibach, Kaspar; Wellner, Jon A
2009-06-01
We find limiting distributions of the nonparametric maximum likelihood estimator (MLE) of a log-concave density, i.e. a density of the form f(0) = exp varphi(0) where varphi(0) is a concave function on R. Existence, form, characterizations and uniform rates of convergence of the MLE are given by Rufibach (2006) and Dümbgen and Rufibach (2007). The characterization of the log-concave MLE in terms of distribution functions is the same (up to sign) as the characterization of the least squares estimator of a convex density on [0, infinity) as studied by Groeneboom, Jongbloed and Wellner (2001b). We use this connection to show that the limiting distributions of the MLE and its derivative are, under comparable smoothness assumptions, the same (up to sign) as in the convex density estimation problem. In particular, changing the smoothness assumptions of Groeneboom, Jongbloed and Wellner (2001b) slightly by allowing some higher derivatives to vanish at the point of interest, we find that the pointwise limiting distributions depend on the second and third derivatives at 0 of H(k), the "lower invelope" of an integrated Brownian motion process minus a drift term depending on the number of vanishing derivatives of varphi(0) = log f(0) at the point of interest. We also establish the limiting distribution of the resulting estimator of the mode M(f(0)) and establish a new local asymptotic minimax lower bound which shows the optimality of our mode estimator in terms of both rate of convergence and dependence of constants on population values.
Chalkley estimates of angiogenesis in early breast cancer--relevance to prognosis
DEFF Research Database (Denmark)
Offersen, Birgitte V; Sørensen, Flemming Brandt; Yilmaz, Mette;
2002-01-01
The aim of this study was to investigate whether Chalkley estimates of angiogenesis add new knowledge regarding prediction of prognosis in 455 consecutive early breast carcinomas, both node-positive (52%) and node-negative (48%). Median follow-up was 101 months. Intense vascularization indicated...... poor disease-specific (p = 0.003) and overall (p = 0.004) survival. In node-negative patients, Chalkley counts were not associated with prognosis, whereas in node-positive patients, high Chalkley scores indicated poor disease-specific (p = 0.0006) and overall (p = 0.0008) survival. A multivariate...... analysis showed that positive lymph nodes, high histopathological grades, and negative oestrogen receptors were independent markers of cancer-related death. A high histopathological grade was associated with cancer-related death in node-negative patients, whereas in node-positive patients, many lymph nodes...
Gupta, Cherry; Cobre, Juliana; Polpo, Adriano; Sinha, Debjayoti
2016-09-01
Existing cure-rate survival models are generally not convenient for modeling and estimating the survival quantiles of a patient with specified covariate values. This paper proposes a novel class of cure-rate model, the transform-both-sides cure-rate model (TBSCRM), that can be used to make inferences about both the cure-rate and the survival quantiles. We develop the Bayesian inference about the covariate effects on the cure-rate as well as on the survival quantiles via Markov Chain Monte Carlo (MCMC) tools. We also show that the TBSCRM-based Bayesian method outperforms existing cure-rate models based methods in our simulation studies and in application to the breast cancer survival data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database.
Efficient Estimation of Dynamic Density Functions with Applications in Streaming Data
Qahtan, Abdulhakim
2016-05-11
Recent advances in computing technology allow for collecting vast amount of data that arrive continuously in the form of streams. Mining data streams is challenged by the speed and volume of the arriving data. Furthermore, the underlying distribution of the data changes over the time in unpredicted scenarios. To reduce the computational cost, data streams are often studied in forms of condensed representation, e.g., Probability Density Function (PDF). This thesis aims at developing an online density estimator that builds a model called KDE-Track for characterizing the dynamic density of the data streams. KDE-Track estimates the PDF of the stream at a set of resampling points and uses interpolation to estimate the density at any given point. To reduce the interpolation error and computational complexity, we introduce adaptive resampling where more/less resampling points are used in high/low curved regions of the PDF. The PDF values at the resampling points are updated online to provide up-to-date model of the data stream. Comparing with other existing online density estimators, KDE-Track is often more accurate (as reflected by smaller error values) and more computationally efficient (as reflected by shorter running time). The anytime available PDF estimated by KDE-Track can be applied for visualizing the dynamic density of data streams, outlier detection and change detection in data streams. In this thesis work, the first application is to visualize the taxi traffic volume in New York city. Utilizing KDE-Track allows for visualizing and monitoring the traffic flow on real time without extra overhead and provides insight analysis of the pick up demand that can be utilized by service providers to improve service availability. The second application is to detect outliers in data streams from sensor networks based on the estimated PDF. The method detects outliers accurately and outperforms baseline methods designed for detecting and cleaning outliers in sensor data. The
Institute of Scientific and Technical Information of China (English)
XUE Yun-feng; WANG Yu-jia; YANG Jie
2009-01-01
A new algorithm for linear instantaneous independent component analysis is proposed based on max-imizing the log-likelihood contrast function which can be changed into a gradient equation. An iterative method is introduced to solve this equation efficiently. The unknown probability density functions as well as their first and second derivatives in the gradient equation are estimated by kernel density method. Computer simulations on artificially generated signals and gray scale natural scene images confirm the efficiency and accuracy of the proposed algorithm.
Recursive Density Estimation of NA Samples%样本的递归密度估计
Institute of Scientific and Technical Information of China (English)
张冬霞; 梁汉营
2008-01-01
Let{Xn,n≥1} be a strictly stationary sequence of negatively associated random variables with the marginal probability density function f (x). In this paper, we discuss the point asymptotic normality for recursive kernel density estimator of f (x).%设{{Xn, n≥1}是一个严平稳的负相协的随机变量序列,其概率密谋函数为f(x).本文讨论了f(x)的递归核估计量的联合渐近正态性.
Institute of Scientific and Technical Information of China (English)
LI Ning; SHI Tielin
2007-01-01
Blind source Separation and estimation of the number of sources usually demand that the number of sensors should be greater than or equal to that of the sources, which, however, is very difficult to satisfy for the complex Systems. A new estimating method based on power spectral density (PSD) is presented. When the relation between the number of sensors and that of sources is unknown, the PSD matrix is first obtained by the ratio of PSD of the observation signals, and then the bound of the number of correlated sources with common frequencies can be estimated by comparing every column vector of PSD matrix. The effectiveness of the proposed method is verified by theoretical analysis and experiments, and the influence of noise on the estimation of number of source is simulated.
Cavuoti, Stefano; Brescia, Massimo; Vellucci, Civita; Tortora, Crescenzo; Longo, Giuseppe
2016-01-01
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z's). A wide plethora of methods have been developed, based either on template models fitting or on empirical explorations of the photometric parameter space. Machine learning based techniques are not explicitly dependent on the physical priors and able to produce accurate photo-z estimations within the photometric ranges derived from the spectroscopic training set. These estimates, however, are not easy to characterize in terms of a photo-z Probability Density Function (PDF), due to the fact that the analytical relation mapping the photometric parameters onto the redshift space is virtually unknown. We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method designed to provide a reliable PDF of the error distribution for empirical techniques. The method is implemented as a modular workflow, whose internal engine for photo-z estimation makes use...
Directory of Open Access Journals (Sweden)
Marco Lombardo
Full Text Available PURPOSE: To investigate the influence of various technical factors on the variation of cone packing density estimates in adaptive optics flood illuminated retinal images. METHODS: Adaptive optics images of the photoreceptor mosaic were obtained in fifteen healthy subjects. The cone density and Voronoi diagrams were assessed in sampling windows of 320×320 µm, 160×160 µm and 64×64 µm at 1.5 degree temporal and superior eccentricity from the preferred locus of fixation (PRL. The technical factors that have been analyzed included the sampling window size, the corrected retinal magnification factor (RMFcorr, the conversion from radial to linear distance from the PRL, the displacement between the PRL and foveal center and the manual checking of cone identification algorithm. Bland-Altman analysis was used to assess the agreement between cone density estimated within the different sampling window conditions. RESULTS: The cone density declined with decreasing sampling area and data between areas of different size showed low agreement. A high agreement was found between sampling areas of the same size when comparing density calculated with or without using individual RMFcorr. The agreement between cone density measured at radial and linear distances from the PRL and between data referred to the PRL or the foveal center was moderate. The percentage of Voronoi tiles with hexagonal packing arrangement was comparable between sampling areas of different size. The boundary effect, presence of any retinal vessels, and the manual selection of cones missed by the automated identification algorithm were identified as the factors influencing variation of cone packing arrangements in Voronoi diagrams. CONCLUSIONS: The sampling window size is the main technical factor that influences variation of cone density. Clear identification of each cone in the image and the use of a large buffer zone are necessary to minimize factors influencing variation of Voronoi
Somershoe, S.G.; Twedt, D.J.; Reid, B.
2006-01-01
We combined Breeding Bird Survey point count protocol and distance sampling to survey spring migrant and breeding birds in Vicksburg National Military Park on 33 days between March and June of 2003 and 2004. For 26 of 106 detected species, we used program DISTANCE to estimate detection probabilities and densities from 660 3-min point counts in which detections were recorded within four distance annuli. For most species, estimates of detection probability, and thereby density estimates, were improved through incorporation of the proportion of forest cover at point count locations as a covariate. Our results suggest Breeding Bird Surveys would benefit from the use of distance sampling and a quantitative characterization of habitat at point count locations. During spring migration, we estimated that the most common migrant species accounted for a population of 5000-9000 birds in Vicksburg National Military Park (636 ha). Species with average populations of 300 individuals during migration were: Blue-gray Gnatcatcher (Polioptila caerulea), Cedar Waxwing (Bombycilla cedrorum), White-eyed Vireo (Vireo griseus), Indigo Bunting (Passerina cyanea), and Ruby-crowned Kinglet (Regulus calendula). Of 56 species that bred in Vicksburg National Military Park, we estimated that the most common 18 species accounted for 8150 individuals. The six most abundant breeding species, Blue-gray Gnatcatcher, White-eyed Vireo, Summer Tanager (Piranga rubra), Northern Cardinal (Cardinalis cardinalis), Carolina Wren (Thryothorus ludovicianus), and Brown-headed Cowbird (Molothrus ater), accounted for 5800 individuals.
Nearest neighbor density ratio estimation for large-scale applications in astronomy
Kremer, J.; Gieseke, F.; Steenstrup Pedersen, K.; Igel, C.
2015-09-01
In astronomical applications of machine learning, the distribution of objects used for building a model is often different from the distribution of the objects the model is later applied to. This is known as sample selection bias, which is a major challenge for statistical inference as one can no longer assume that the labeled training data are representative. To address this issue, one can re-weight the labeled training patterns to match the distribution of unlabeled data that are available already in the training phase. There are many examples in practice where this strategy yielded good results, but estimating the weights reliably from a finite sample is challenging. We consider an efficient nearest neighbor density ratio estimator that can exploit large samples to increase the accuracy of the weight estimates. To solve the problem of choosing the right neighborhood size, we propose to use cross-validation on a model selection criterion that is unbiased under covariate shift. The resulting algorithm is our method of choice for density ratio estimation when the feature space dimensionality is small and sample sizes are large. The approach is simple and, because of the model selection, robust. We empirically find that it is on a par with established kernel-based methods on relatively small regression benchmark datasets. However, when applied to large-scale photometric redshift estimation, our approach outperforms the state-of-the-art.
Directory of Open Access Journals (Sweden)
Sabouri
2007-05-01
Full Text Available Background and Objective: The main purpose of this study was determination of the frequency and distri-bution of dense mammograms among the diverse age groups of women who underwent mammography effect and other clinical characteristics such as parity, age at first conception, use of hormone replacement therapy (HRT, and family history of breast carci-noma on breast density. Materials and Methods: We considered 1000 women between 25 and 79 years old consecutively undergo-ing mammography in Mashhad Qaem hospital from April 2003 to April 2004 were grouped in 5-year age cohorts. Breast density, breast size and presence of benign calcifications were analyzed. Clinical data such as age, parity, age at first conception, use of hormone replacement therapy (HRT, and family his-tory of breast carcinoma were recorded. Results: Radiological parenchymal density on mam-mograms was found to correlate with age (decreased progressively in patient cohorts 25-29 years old through 75-79 years old, P<0.0001. Increased paren-chymal density was more common in women who underwent HRT (P<0.0001, had smaller breast (P<0.0001 and had less than two pregnancies (P<0.0001. Prevalence of benign calcifications in-creased with age. Conclusion: This study confirms the effect of age and HRT on radiological breast density suggesting a pos-sible reduction of sensitivity and efficacy of mam-mography for detecting malignancy in women who undergo HRT. Such a hypothesis still needs validation by means of a prospective analysis of the correlation between HRT and the frequency of interval cancer occurrence (the best indicator of sensitivity. Never-theless a significant percentage (38% of women who were 25-39 years old had predominantly fatty breast tissue that should not impede selective mammo-graghic screening or diagnostic efforts in this age group.
Pedotransfer functions for Irish soils - estimation of bulk density (ρb) per horizon type
Reidy, B.; Simo, I.; Sills, P.; Creamer, R. E.
2016-01-01
Soil bulk density is a key property in defining soil characteristics. It describes the packing structure of the soil and is also essential for the measurement of soil carbon stock and nutrient assessment. In many older surveys this property was neglected and in many modern surveys this property is omitted due to cost both in laboratory and labour and in cases where the core method cannot be applied. To overcome these oversights pedotransfer functions are applied using other known soil properties to estimate bulk density. Pedotransfer functions have been derived from large international data sets across many studies, with their own inherent biases, many ignoring horizonation and depth variances. Initially pedotransfer functions from the literature were used to predict different horizon type bulk densities using local known bulk density data sets. Then the best performing of the pedotransfer functions were selected to recalibrate and then were validated again using the known data. The predicted co-efficient of determination was 0.5 or greater in 12 of the 17 horizon types studied. These new equations allowed gap filling where bulk density data were missing in part or whole soil profiles. This then allowed the development of an indicative soil bulk density map for Ireland at 0-30 and 30-50 cm horizon depths. In general the horizons with the largest known data sets had the best predictions, using the recalibrated and validated pedotransfer functions.
Couto, E; Hemminki, K
2007-01-01
Using the Swedish Family-Cancer Database, the increased risk of breast cancer in women with relatives with the disease did not vary with paternal/maternal lineage. Familial breast cancer heritable component was 73% and the environmental proportion 27%. Familial aggregation of breast cancer in women below age 51 years is mainly due to heritable causes.
Directory of Open Access Journals (Sweden)
José Fajardo
2012-12-01
Full Text Available This paper uses the Liu et al. (2007 approach to estimate the optionimplied Risk-Neutral Densities (RND, real-world density (RWD, and relative risk aversion from the Brazilian Real/US Dollar exchange rate distribution. Our empirical application uses a sample of exchange-traded Brazilian Real currency options from 1999 to 2011. Our estimated value of the relative risk aversion is around 2.7, which is in line with other articles for the Brazilian Economy. Our out-of-sample results showed that the RND has some ability to forecast the Brazilian Real exchange rate, but when we incorporate the risk aversion, the out-of-sample performance improves substantially.
Haben, Stephen
2016-01-01
We present a model for generating probabilistic forecasts by combining kernel density estimation (KDE) and quantile regression techniques, as part of the probabilistic load forecasting track of the Global Energy Forecasting Competition 2014. The KDE method is initially implemented with a time-decay parameter. We later improve this method by conditioning on the temperature or the period of the week variables to provide more accurate forecasts. Secondly, we develop a simple but effective quantile regression forecast. The novel aspects of our methodology are two-fold. First, we introduce symmetry into the time-decay parameter of the kernel density estimation based forecast. Secondly we combine three probabilistic forecasts with different weights for different periods of the month.
Energy Technology Data Exchange (ETDEWEB)
Stewart, Robert N [ORNL; White, Devin A [ORNL; Urban, Marie L [ORNL; Morton, April M [ORNL; Webster, Clayton G [ORNL; Stoyanov, Miroslav K [ORNL; Bright, Eddie A [ORNL; Bhaduri, Budhendra L [ORNL
2013-01-01
The Population Density Tables (PDT) project at the Oak Ridge National Laboratory (www.ornl.gov) is developing population density estimates for specific human activities under normal patterns of life based largely on information available in open source. Currently, activity based density estimates are based on simple summary data statistics such as range and mean. Researchers are interested in improving activity estimation and uncertainty quantification by adopting a Bayesian framework that considers both data and sociocultural knowledge. Under a Bayesian approach knowledge about population density may be encoded through the process of expert elicitation. Due to the scale of the PDT effort which considers over 250 countries, spans 40 human activity categories, and includes numerous contributors, an elicitation tool is required that can be operationalized within an enterprise data collection and reporting system. Such a method would ideally require that the contributor have minimal statistical knowledge, require minimal input by a statistician or facilitator, consider human difficulties in expressing qualitative knowledge in a quantitative setting, and provide methods by which the contributor can appraise whether their understanding and associated uncertainty was well captured. This paper introduces an algorithm that transforms answers to simple, non-statistical questions into a bivariate Gaussian distribution as the prior for the Beta distribution. Based on geometric properties of the Beta distribution parameter feasibility space and the bivariate Gaussian distribution, an automated method for encoding is developed that responds to these challenging enterprise requirements. Though created within the context of population density, this approach may be applicable to a wide array of problem domains requiring informative priors for the Beta distribution.
Institute of Scientific and Technical Information of China (English)
Farah Yasmeen[1; Sidra Zaheer[2
2014-01-01
Background： Breast cancer is the most common female cancer in Pakistan. The incidence of breast cancer in Pakistan is about 2.5 times higher than that in the neighboring countries India and Iran. In Karachi, the most populated city of Pakistan, the age-standardized rate of breast cancer was 69.1 per 100,000 women during 1998-2002, which is the highest recorded rate in Asia. The carcinoma of breast in Pakistan is an enormous public health concern. In this study, we examined the recent trends of breast cancer incidence rates among the women in Karachi. Methods： We obtained the secondary data of breast cancer incidence from various hospitals. They included Jinnah Hospital, KIRAN （Karachi Institute of Radiotherapy and Nuclear Medicine）, and Civil hospital, where the data were available for the years 2004-2011. A total of 5331 new cases of female breast cancer were registered during this period. We analyzed the data in 5-year age groups 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75＋. Nonparametric smoothing were used to obtained age-specific incidence curves, and then the curves are decomposed using principal components analysis to fit FTS （functional time series） model. We then used exponential smoothing statspace models to estimate the forecasts of incidence curve and construct prediction intervals. Results： The breast cancer incidence rates in Karachi increased with age for all available years. The rates increased monotonically and are relatively sharp with the age from 15 years to 50 years and then they show variability after the age of 50 years. 10-year forecasts for the female breast cancer incidence rates in Karachi show that the future rates are expected to remain stable for the age-groups 15-50 years, but they will increase for the females of 50-years and over. Hence in future, the newly diagnosed breast cancer cases in the older women in Karachi are expected to increase. Conclusion： Prediction of age
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Effect of Broadband Nature of Marine Mammal Echolocation...modeled for different marine mammal species and detectors and assess the magnitude of error on the estimated density due to various commonly used...noise were then fed through two detectors: 1) a sub-band energy detector; 2) a power-law Page test detector (van IJsselmuide and Beerens, 2004
2014-06-29
Centra de Geofisica Universidade de Lisboa Lisbon, Portugal. Award Number: N00014-11 -1 -0615 This project was a collaborative project between...submitted or in prep) from the University of St Andrews (UStA) and Universidade de Lisboa (UL) research effort. The work has also generated multiple...routines. Task 1.4. Use distance sampling software , Distance (Thomas et al. 2010), to estimate seasonal density, incorporating covariates affecting
On the rate of convergence of the maximum likelihood estimator of a k-monotone density
Institute of Scientific and Technical Information of China (English)
WELLNER; Jon; A
2009-01-01
Bounds for the bracketing entropy of the classes of bounded k-monotone functions on [0,A] are obtained under both the Hellinger distance and the Lp(Q) distance,where 1 p < ∞ and Q is a probability measure on [0,A].The result is then applied to obtain the rate of convergence of the maximum likelihood estimator of a k-monotone density.
On the rate of convergence of the maximum likelihood estimator of a K-monotone density
Institute of Scientific and Technical Information of China (English)
GAO FuChang; WELLNER Jon A
2009-01-01
Bounds for the bracketing entropy of the classes of bounded K-monotone functions on [0, A] are obtained under both the Hellinger distance and the LP(Q) distance, where 1 ≤ p < ∞ and Q is a probability measure on [0, A]. The result is then applied to obtain the rate of convergence of the maximum likelihood estimator of a K-monotone density.
Use of spatial capture-recapture modeling and DNA data to estimate densities of elusive animals
Kery, Marc; Gardner, Beth; Stoeckle, Tabea; Weber, Darius; Royle, J. Andrew
2011-01-01
Assessment of abundance, survival, recruitment rates, and density (i.e., population assessment) is especially challenging for elusive species most in need of protection (e.g., rare carnivores). Individual identification methods, such as DNA sampling, provide ways of studying such species efficiently and noninvasively. Additionally, statistical methods that correct for undetected animals and account for locations where animals are captured are available to efficiently estimate density and other demographic parameters. We collected hair samples of European wildcat (Felis silvestris) from cheek-rub lure sticks, extracted DNA from the samples, and identified each animals' genotype. To estimate the density of wildcats, we used Bayesian inference in a spatial capture-recapture model. We used WinBUGS to fit a model that accounted for differences in detection probability among individuals and seasons and between two lure arrays. We detected 21 individual wildcats (including possible hybrids) 47 times. Wildcat density was estimated at 0.29/km2 (SE 0.06), and 95% of the activity of wildcats was estimated to occur within 1.83 km from their home-range center. Lures located systematically were associated with a greater number of detections than lures placed in a cell on the basis of expert opinion. Detection probability of individual cats was greatest in late March. Our model is a generalized linear mixed model; hence, it can be easily extended, for instance, to incorporate trap- and individual-level covariates. We believe that the combined use of noninvasive sampling techniques and spatial capture-recapture models will improve population assessments, especially for rare and elusive animals.
Estimation of Plasma Density by Surface Plasmons for Surface-Wave Plasmas
Institute of Scientific and Technical Information of China (English)
CHEN Zhao-Quan; LIU Ming-Hai; LAN Chao-Hui; CHEN Wei; LUO Zhi-Qing; HU Xi-Wei
2008-01-01
@@ An estimation method of plasma density based on surface plasmons theory for surface-wave plasmas is proposed. The number of standing-wave is obtained directly from the discharge image, and the propagation constant is calculated with the trim size of the apparatus in this method, then plasma density can be determined with the value of 9.1 × 1017 m-3. Plasma density is measured using a Langmuir probe, the value is 8.1 × 1017 m-3 which is very close to the predicted value of surface plasmons theory. Numerical simulation is used to check the number of standing-wave by the finite-difference time-domain (FDTD) method also. All results are compatible both of theoretical analysis and experimental measurement.
Vlachopoulou, Vassiliki; Malatara, Georgia; Delis, Harry; Kardamakis, Dimitrios; Panayiotakis, George
2013-04-01
The purpose of this study was to measure the peripheral dose which is the absorbed dose in organs located outside the treatment volume such as the thyroid gland and the breast in patients undergoing radiotherapy, utilising the MOSFET dosemeters, as well as to estimate the probability of secondary cancer. The thyroid gland doses, expressed as a percentage of the prescribed dose (%TD), were measured to be 2.0±0.3 %, in whole brain irradiation, 10.0±8.0 % in mediastinum treatment and 8.0±2.0 and 2.0±0.8 % in breast treatment, with and without the supraclavicular irradiation, respectively, with a corresponding risk of 0.2, 2.0, 1.0 and 0.3 %. The dose to the breast was 7.0±2.0 %, in the mediastinum treatment, and 4.0±1.0 and 2.0±0.8 %, in the breast treatment, with and without supraclavicular irradiation, respectively, with a corresponding risk of 4.0, 2.0 and 1.0 %. Although the results indicate that the risk is not negligible, its significance should be considered in conjunction with the existing pathology and age of the patients.
A new approach on seismic mortality estimations based on average population density
Zhu, Xiaoxin; Sun, Baiqing; Jin, Zhanyong
2016-12-01
This study examines a new methodology to predict the final seismic mortality from earthquakes in China. Most studies established the association between mortality estimation and seismic intensity without considering the population density. In China, however, the data are not always available, especially when it comes to the very urgent relief situation in the disaster. And the population density varies greatly from region to region. This motivates the development of empirical models that use historical death data to provide the path to analyze the death tolls for earthquakes. The present paper employs the average population density to predict the final death tolls in earthquakes using a case-based reasoning model from realistic perspective. To validate the forecasting results, historical data from 18 large-scale earthquakes occurred in China are used to estimate the seismic morality of each case. And a typical earthquake case occurred in the northwest of Sichuan Province is employed to demonstrate the estimation of final death toll. The strength of this paper is that it provides scientific methods with overall forecast errors lower than 20 %, and opens the door for conducting final death forecasts with a qualitative and quantitative approach. Limitations and future research are also analyzed and discussed in the conclusion.
Wavelet-based density estimation for noise reduction in plasma simulations using particles
van yen, Romain Nguyen; del-Castillo-Negrete, Diego; Schneider, Kai; Farge, Marie; Chen, Guangye
2010-04-01
For given computational resources, the accuracy of plasma simulations using particles is mainly limited by the noise due to limited statistical sampling in the reconstruction of the particle distribution function. A method based on wavelet analysis is proposed and tested to reduce this noise. The method, known as wavelet-based density estimation (WBDE), was previously introduced in the statistical literature to estimate probability densities given a finite number of independent measurements. Its novel application to plasma simulations can be viewed as a natural extension of the finite size particles (FSP) approach, with the advantage of estimating more accurately distribution functions that have localized sharp features. The proposed method preserves the moments of the particle distribution function to a good level of accuracy, has no constraints on the dimensionality of the system, does not require an a priori selection of a global smoothing scale, and its able to adapt locally to the smoothness of the density based on the given discrete particle data. Moreover, the computational cost of the denoising stage is of the same order as one time step of a FSP simulation. The method is compared with a recently proposed proper orthogonal decomposition based method, and it is tested with three particle data sets involving different levels of collisionality and interaction with external and self-consistent fields.
Energy Technology Data Exchange (ETDEWEB)
Balsa Terzic, Gabriele Bassi
2011-07-01
In this paper we discuss representations of charge particle densities in particle-in-cell (PIC) simulations, analyze the sources and profiles of the intrinsic numerical noise, and present efficient methods for their removal. We devise two alternative estimation methods for charged particle distribution which represent significant improvement over the Monte Carlo cosine expansion used in the 2d code of Bassi, designed to simulate coherent synchrotron radiation (CSR) in charged particle beams. The improvement is achieved by employing an alternative beam density estimation to the Monte Carlo cosine expansion. The representation is first binned onto a finite grid, after which two grid-based methods are employed to approximate particle distributions: (i) truncated fast cosine transform (TFCT); and (ii) thresholded wavelet transform (TWT). We demonstrate that these alternative methods represent a staggering upgrade over the original Monte Carlo cosine expansion in terms of efficiency, while the TWT approximation also provides an appreciable improvement in accuracy. The improvement in accuracy comes from a judicious removal of the numerical noise enabled by the wavelet formulation. The TWT method is then integrated into Bassi's CSR code, and benchmarked against the original version. We show that the new density estimation method provides a superior performance in terms of efficiency and spatial resolution, thus enabling high-fidelity simulations of CSR effects, including microbunching instability.
Use of prediction methods to estimate true density of active pharmaceutical ingredients.
Cao, Xiaoping; Leyva, Norma; Anderson, Stephen R; Hancock, Bruno C
2008-05-01
True density is a fundamental and important property of active pharmaceutical ingredients (APIs). Using prediction methods to estimate the API true density can be very beneficial in pharmaceutical research and development, especially when experimental measurements cannot be made due to lack of material or sample handling restrictions. In this paper, two empirical prediction methods developed by Girolami and Immirzi and Perini were used to estimate the true density of APIs, and the estimation results were compared with experimentally measured values by helium pycnometry. The Girolami method is simple and can be used for both liquids and solids. For the tested APIs, the Girolami method had a maximum error of -12.7% and an average percent error of -3.0% with a 95% CI of (-3.8, -2.3%). The Immirzi and Perini method is more involved and is mainly used for solid crystals. In general, it gives better predictions than the Girolami method. For the tested APIs, the Immirzi and Perini method had a maximum error of 9.6% and an average percent error of 0.9% with a 95% CI of (0.3, 1.6%).
Directory of Open Access Journals (Sweden)
George Baytchev
2015-09-01
Full Text Available Traditionally, mammographic density (MD of the breast has been assessed by a radiologist visually. This subjective evaluation requires significant experience to distinguish the relative proportions of the fibrous connective tissue and adipose tissue in the mammary gland correctly. The aim of this study is to compare the capabilities of the different methods (visual and computer-assisted for assessing mammographic density. Our sample in this study consists of 66 patients with digital mammography. The mammographic density has been evaluated using the four-grade scale of the American College of Radiology (ACR; visually, visually using an analog scale and semi-automated using UTHSCSA Image Tool 3.0, Image J and Adobe Photoshop CS6 software. The average mammographic density calculated using the different methods is as follows: 34.8% (from 10% to 70%; 32.1% (from 10% to 60%; 23% (from 0% to 70.9%; 22.7% (from 2.5% to 78.1% and 22.5% (from 1.5% to 72.4%. There is a strong correlation between the results obtained visually and those calculated using a computer-assisted measurement (p< 0.0001. A strong correlation was found also between the results acquired using the different semi-automated programs (p< 0.0001. Precise measurement of mammographic density is of great importance for the mammographic screening and evaluation of breast cancer risk. The semi-automated methods, used for this purpose are objective, accessible and reproducible tools and have some advantages over the subjective visual assessment.
Examining the impact of the precision of address geocoding on estimated density of crime locations
Harada, Yutaka; Shimada, Takahito
2006-10-01
This study examines the impact of the precision of address geocoding on the estimated density of crime locations in a large urban area of Japan. The data consist of two separate sets of the same Penal Code offenses known to the police that occurred during a nine-month period of April 1, 2001 through December 31, 2001 in the central 23 wards of Tokyo. These two data sets are derived from older and newer recording system of the Tokyo Metropolitan Police Department (TMPD), which revised its crime reporting system in that year so that more precise location information than the previous years could be recorded. Each of these data sets was address-geocoded onto a large-scale digital map, using our hierarchical address-geocoding schema, and was examined how such differences in the precision of address information and the resulting differences in address-geocoded incidence locations affect the patterns in kernel density maps. An analysis using 11,096 pairs of incidences of residential burglary (each pair consists of the same incidents geocoded using older and newer address information, respectively) indicates that the kernel density estimation with a cell size of 25×25 m and a bandwidth of 500 m may work quite well in absorbing the poorer precision of geocoded locations based on data from older recording system, whereas in several areas where older recording system resulted in very poor precision level, the inaccuracy of incident locations may produce artifactitious and potentially misleading patterns in kernel density maps.
Carroll, Raymond J.
2011-03-01
In many applications we can expect that, or are interested to know if, a density function or a regression curve satisfies some specific shape constraints. For example, when the explanatory variable, X, represents the value taken by a treatment or dosage, the conditional mean of the response, Y , is often anticipated to be a monotone function of X. Indeed, if this regression mean is not monotone (in the appropriate direction) then the medical or commercial value of the treatment is likely to be significantly curtailed, at least for values of X that lie beyond the point at which monotonicity fails. In the case of a density, common shape constraints include log-concavity and unimodality. If we can correctly guess the shape of a curve, then nonparametric estimators can be improved by taking this information into account. Addressing such problems requires a method for testing the hypothesis that the curve of interest satisfies a shape constraint, and, if the conclusion of the test is positive, a technique for estimating the curve subject to the constraint. Nonparametric methodology for solving these problems already exists, but only in cases where the covariates are observed precisely. However in many problems, data can only be observed with measurement errors, and the methods employed in the error-free case typically do not carry over to this error context. In this paper we develop a novel approach to hypothesis testing and function estimation under shape constraints, which is valid in the context of measurement errors. Our method is based on tilting an estimator of the density or the regression mean until it satisfies the shape constraint, and we take as our test statistic the distance through which it is tilted. Bootstrap methods are used to calibrate the test. The constrained curve estimators that we develop are also based on tilting, and in that context our work has points of contact with methodology in the error-free case.
Review on Vehicular Speed, Density Estimation and Classification Using Acoustic Signal
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Prashant Borkar
2013-09-01
Full Text Available Traffic monitoring and parameters estimation from urban to non urban (battlefield environment traffic is fast-emerging field based on acoustic signals. We present here a comprehensive review of the state-of-the-art acoustic signal for vehicular speed estimation, density estimation and classification, critical analysis and an outlook to future research directions. This field is of increasing relevance for intelligent transport systems (ITSs. In recent years video monitoring and surveillance systems has been widely used in traffic management and hence traffic parameters can be achieved using such systems, but installation, operational and maintenance cost associated with these approaches are relatively high compared to the use of acoustic signal which is having very low installation and maintenance cost. The classification process includes sensing unit, class definition, feature extraction, classifier application and system evaluation. The acoustic classification system is part of a multi sensor real time environment for traffic surveillance and monitoring. Classification accuracy achieved by various studied algorithms shows very good performance for the ‘Heavy Weight’ class of vehicles as compared to the other category “Light Weight”. Also a slight performance degrades as vehicle speed increases. Vehicular speed estimation corresponds to average speed and traffic density measurement, and can be substantially used for traffic signal timings optimization.
Verdoolaege, G.; Von Hellermann, M. G.; Jaspers, R.; Ichir, M. M.; Van Oost, G.
2006-11-01
The validation of diagnostic date from a nuclear fusion experiment is an important issue. The concept of an Integrated Data Analysis (IDA) allows the consistent estimation of plasma parameters from heterogeneous data sets. Here, the determination of the ion effective charge (Zeff) is considered. Several diagnostic methods exist for the determination of Zeff, but the results are in general not in agreement. In this work, the problem of Zeff estimation on the TEXTOR tokamak is approached from the perspective of IDA, in the framework of Bayesian probability theory. The ultimate goal is the estimation of a full Zeff profile that is consistent both with measured bremsstrahlung emissivities, as well as individual impurity spectral line intensities obtained from Charge Exchange Recombination Spectroscopy (CXRS). We present an overview of the various uncertainties that enter the calculation of a Zeff profile from bremsstrahlung date on the one hand, and line intensity data on the other hand. We discuss a simple linear and nonlinear Bayesian model permitting the estimation of a central value for Zeff and the electron density ne on TEXTOR from bremsstrahlung emissivity measurements in the visible, and carbon densities derived from CXRS. Both the central Zeff and ne are sampled using an MCMC algorithm. An outlook is given towards possible model improvements.
Sadeh, Iftach; Lahav, Ofer
2015-01-01
We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister and Lahav (2004). Large photometric galaxy surveys are important for cosmological studies, and in particular for characterizing the nature of dark energy. The success of such surveys greatly depends on the ability to measure photo-zs, based on limited spectral data. ANNz2 utilizes multiple machine learning methods, such as artificial neural networks, boosted decision/regression trees and k-nearest neighbours. The objective of the algorithm is to dynamically optimize the performance of the photo-z estimation, and to properly derive the associated uncertainties. In addition to single-value solutions, the new code also generates full probability density functions (PDFs) in two different ways. In addition, estimators are incorporated to mitigate possible problems of spectroscopic training samples which are not representative or are incomplete. ANNz2 is also adapted to provide optimized solution...
Optimal diffusion MRI acquisition for fiber orientation density estimation: an analytic approach.
White, Nathan S; Dale, Anders M
2009-11-01
An important challenge in the design of diffusion MRI experiments is how to optimize statistical efficiency, i.e., the accuracy with which parameters can be estimated from the diffusion data in a given amount of imaging time. In model-based spherical deconvolution analysis, the quantity of interest is the fiber orientation density (FOD). Here, we demonstrate how the spherical harmonics (SH) can be used to form an explicit analytic expression for the efficiency of the minimum variance (maximally efficient) linear unbiased estimator of the FOD. Using this expression, we calculate optimal b-values for maximum FOD estimation efficiency with SH expansion orders of L = 2, 4, 6, and 8 to be approximately b = 1,500, 3,000, 4,600, and 6,200 s/mm(2), respectively. However, the arrangement of diffusion directions and scanner-specific hardware limitations also play a role in determining the realizable efficiency of the FOD estimator that can be achieved in practice. We show how some commonly used methods for selecting diffusion directions are sometimes inefficient, and propose a new method for selecting diffusion directions in MRI based on maximizing the statistical efficiency. We further demonstrate how scanner-specific hardware limitations generally lead to optimal b-values that are slightly lower than the ideal b-values. In summary, the analytic expression for the statistical efficiency of the unbiased FOD estimator provides important insight into the fundamental tradeoff between angular resolution, b-value, and FOD estimation accuracy.
DEFF Research Database (Denmark)
Pettersen, P.C.; Raundahl, Jakob; Loog, M.
2008-01-01
trial, active treatment induced a significant increase in breast density, which was consistent in all methods used (all p women receiving nasal HRT. The sensitivity of automated methods to discriminate HRT- from placebo......-treated women was equal or better than the sensitivity of methods performed by the radiologist. CONCLUSIONS: The markedly different pharmacokinetic profile of nasal estrogen seems to be associated with better breast safety. Automated computer-based analysis of digitized mammograms provides a sensitive measure...
Estimation of dislocation density from precession electron diffraction data using the Nye tensor
Energy Technology Data Exchange (ETDEWEB)
Leff, A.C. [Department of Materials Science & Engineering, Drexel University, Philadelphia, PA (United States); Weinberger, C.R. [Department of Mechanical Engineering and Mechanics, Drexel University, Philadelphia, PA (United States); Taheri, M.L., E-mail: mtaheri@coe.drexel.edu [Department of Materials Science & Engineering, Drexel University, Philadelphia, PA (United States)
2015-06-15
The Nye tensor offers a means to estimate the geometrically necessary dislocation density of a crystalline sample based on measurements of the orientation changes within individual crystal grains. In this paper, the Nye tensor theory is applied to precession electron diffraction automated crystallographic orientation mapping (PED-ACOM) data acquired using a transmission electron microscope (TEM). The resulting dislocation density values are mapped in order to visualize the dislocation structures present in a quantitative manner. These density maps are compared with other related methods of approximating local strain dependencies in dislocation-based microstructural transitions from orientation data. The effect of acquisition parameters on density measurements is examined. By decreasing the step size and spot size during data acquisition, an increasing fraction of the dislocation content becomes accessible. Finally, the method described herein is applied to the measurement of dislocation emission during in situ annealing of Cu in TEM in order to demonstrate the utility of the technique for characterizing microstructural dynamics. - Highlights: • Developed a method of mapping GND density using orientation mapping data from TEM. • As acquisition length-scale is decreased, all dislocations are considered GNDs. • Dislocation emission and corresponding grain rotation quantified.
mBEEF-vdW: Robust fitting of error estimation density functionals
Lundgaard, Keld T.; Wellendorff, Jess; Voss, Johannes; Jacobsen, Karsten W.; Bligaard, Thomas
2016-06-01
We propose a general-purpose semilocal/nonlocal exchange-correlation functional approximation, named mBEEF-vdW. The exchange is a meta generalized gradient approximation, and the correlation is a semilocal and nonlocal mixture, with the Rutgers-Chalmers approximation for van der Waals (vdW) forces. The functional is fitted within the Bayesian error estimation functional (BEEF) framework [J. Wellendorff et al., Phys. Rev. B 85, 235149 (2012), 10.1103/PhysRevB.85.235149; J. Wellendorff et al., J. Chem. Phys. 140, 144107 (2014), 10.1063/1.4870397]. We improve the previously used fitting procedures by introducing a robust MM-estimator based loss function, reducing the sensitivity to outliers in the datasets. To more reliably determine the optimal model complexity, we furthermore introduce a generalization of the bootstrap 0.632 estimator with hierarchical bootstrap sampling and geometric mean estimator over the training datasets. Using this estimator, we show that the robust loss function leads to a 10 % improvement in the estimated prediction error over the previously used least-squares loss function. The mBEEF-vdW functional is benchmarked against popular density functional approximations over a wide range of datasets relevant for heterogeneous catalysis, including datasets that were not used for its training. Overall, we find that mBEEF-vdW has a higher general accuracy than competing popular functionals, and it is one of the best performing functionals on chemisorption systems, surface energies, lattice constants, and dispersion. We also show the potential-energy curve of graphene on the nickel(111) surface, where mBEEF-vdW matches the experimental binding length. mBEEF-vdW is currently available in gpaw and other density functional theory codes through Libxc, version 3.0.0.
Estimating breast tomosynthesis performance in detection tasks with variable-background phantoms
Young, Stefano; Park, Subok; Anderson, S. Kyle; Badano, Aldo; Myers, Kyle J.; Bakic, Predrag
2009-02-01
Digital breast tomosynthesis (DBT) shows potential for improving breast cancer detection. However, this technique has not yet been fully characterized with consideration of the various uncertainties in the imaging chain and optimized with respect to system acquisition parameters. To obtain maximum diagnostic information in DBT, system optimization needs to be performed across a range of patients and acquisition parameters to quantify their impact on tumor detection performance. In addition, a balance must be achieved between x-ray dose and image quality to minimize risk to the patient while maximizing the system's detection performance. To date, researchers have applied a task-based approach to the optimization of DBT with use of mathematical observers for tasks in the signal-known-exactly background-known-exactly (SKE/BKE) and signal-known-exactly background-known statistically (SKE/BKS) paradigms1-3. However, previous observer models provided insufficient treatment of the spatial correlations between multi-angle DBT projections, so we incorporated this correlation information into the modeling methodology. We developed a computational approach that includes three-dimensional variable background phantoms for incorporating background variability, accurate ray-tracing and Poisson distributions for generating noise-free and noisy projections of the phantoms, and a channelized-Hotelling observer4 (CHO) for estimating performance in DBT. We demonstrated our method for a DBT acquisition geometry and calculated the performance of the CHO with Laguerre-Gauss channels as a function of the angular span of the system. Preliminary results indicate that the implementation of a CHO model that incorporates correlations between multi-angle projections gives different performance predictions than a CHO model that ignores multi-angle correlations. With improvement of the observer design, we anticipate more accurate investigations into the impact of multi-angle correlations and
THE USE OF MATHEMATICAL MODELS FOR ESTIMATING WOOD BASIC DENSITY OF Eucalyptus sp CLONES
Directory of Open Access Journals (Sweden)
Cláudio Roberto Thiersch
2006-09-01
Full Text Available This study aimed at identifying at what point in the stem, in the longitudinal and cardinal direction, the pylodin penetration depth should be measured, for determining wood basic density, envisaging forestry inventory Data base used in compassed 36 parcels of 400 m2. Around the parcels 216 trees were sealed. Two clones (hybrid of E. grandis and E. urophylla, at the ages of 3; 4, 5 and 6 years, belonging to three different sites in East Brazil, encompassing East and Northeast of Espirito Santo state and south of Bahia state. In each measuring height of diameters it was also measured the penetration depth of the pylodin (in mm. The average basic density of scaled trees, was determined, departing from the cheaps, using the immersion method. The main conclusions were: The density equation, as function of the pylodin measures, age, site, diameters at 1.3m of ground and total height, was more precise, exact and stable than the density equation as function of pylodin, age, site and diameter, which in turn was more exact and stable than the density equation, as function of pylodin measures, age, site, diameter at a 1.3m of the ground and of total height, was precise and exact for all ages and sites, in dependent on if the pylodin measurements were taken in the South or in North fares, or in the average position between them. The height for measurement with pylodin can also be taken in the more ergonomic position of 1.3m. The density estimation, as a function of the measures with the pylodin, or as a function of the use of the pylodin, age, average dominant tree height an diameter at 1.3m of the ground, for both clones, was more precise when the measure with the pylodin was taken at the North face. The average tree basic density must always be taken by a specific equation for each clone, given that these equations differ statistically.
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Tara Chestnut
Full Text Available Biodiversity losses are occurring worldwide due to a combination of stressors. For example, by one estimate, 40% of amphibian species are vulnerable to extinction, and disease is one threat to amphibian populations. The emerging infectious disease chytridiomycosis, caused by the aquatic fungus Batrachochytrium dendrobatidis (Bd, is a contributor to amphibian declines worldwide. Bd research has focused on the dynamics of the pathogen in its amphibian hosts, with little emphasis on investigating the dynamics of free-living Bd. Therefore, we investigated patterns of Bd occupancy and density in amphibian habitats using occupancy models, powerful tools for estimating site occupancy and detection probability. Occupancy models have been used to investigate diseases where the focus was on pathogen occurrence in the host. We applied occupancy models to investigate free-living Bd in North American surface waters to determine Bd seasonality, relationships between Bd site occupancy and habitat attributes, and probability of detection from water samples as a function of the number of samples, sample volume, and water quality. We also report on the temporal patterns of Bd density from a 4-year case study of a Bd-positive wetland. We provide evidence that Bd occurs in the environment year-round. Bd exhibited temporal and spatial heterogeneity in density, but did not exhibit seasonality in occupancy. Bd was detected in all months, typically at less than 100 zoospores L(-1. The highest density observed was ∼3 million zoospores L(-1. We detected Bd in 47% of sites sampled, but estimated that Bd occupied 61% of sites, highlighting the importance of accounting for imperfect detection. When Bd was present, there was a 95% chance of detecting it with four samples of 600 ml of water or five samples of 60 mL. Our findings provide important baseline information to advance the study of Bd disease ecology, and advance our understanding of amphibian exposure to free
Chestnut, Tara E.; Anderson, Chauncey; Popa, Radu; Blaustein, Andrew R.; Voytek, Mary; Olson, Deanna H.; Kirshtein, Julie
2014-01-01
Biodiversity losses are occurring worldwide due to a combination of stressors. For example, by one estimate, 40% of amphibian species are vulnerable to extinction, and disease is one threat to amphibian populations. The emerging infectious disease chytridiomycosis, caused by the aquatic fungus Batrachochytrium dendrobatidis (Bd), is a contributor to amphibian declines worldwide. Bd research has focused on the dynamics of the pathogen in its amphibian hosts, with little emphasis on investigating the dynamics of free-living Bd. Therefore, we investigated patterns of Bd occupancy and density in amphibian habitats using occupancy models, powerful tools for estimating site occupancy and detection probability. Occupancy models have been used to investigate diseases where the focus was on pathogen occurrence in the host. We applied occupancy models to investigate free-living Bd in North American surface waters to determine Bd seasonality, relationships between Bd site occupancy and habitat attributes, and probability of detection from water samples as a function of the number of samples, sample volume, and water quality. We also report on the temporal patterns of Bd density from a 4-year case study of a Bd-positive wetland. We provide evidence that Bd occurs in the environment year-round. Bd exhibited temporal and spatial heterogeneity in density, but did not exhibit seasonality in occupancy. Bd was detected in all months, typically at less than 100 zoospores L−1. The highest density observed was ∼3 million zoospores L−1. We detected Bd in 47% of sites sampled, but estimated that Bd occupied 61% of sites, highlighting the importance of accounting for imperfect detection. When Bd was present, there was a 95% chance of detecting it with four samples of 600 ml of water or five samples of 60 mL. Our findings provide important baseline information to advance the study of Bd disease ecology, and advance our understanding of amphibian exposure to free-living Bd in aquatic
Directory of Open Access Journals (Sweden)
Yongjun Ahn
Full Text Available The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive
A long-term evaluation of biopsy darts and DNA to estimate cougar density
Beausoleil, Richard A.; Clark, Joseph D.; Maletzke, Benjamin T.
2016-01-01
Accurately estimating cougar (Puma concolor) density is usually based on long-term research consisting of intensive capture and Global Positioning System collaring efforts and may cost hundreds of thousands of dollars annually. Because wildlife agency budgets rarely accommodate this approach, most infer cougar density from published literature, rely on short-term studies, or use hunter harvest data as a surrogate in their jurisdictions; all of which may limit accuracy and increase risk of management actions. In an effort to develop a more cost-effective long-term strategy, we evaluated a research approach using citizen scientists with trained hounds to tree cougars and collect tissue samples with biopsy darts. We then used the DNA to individually identify cougars and employed spatially explicit capture–recapture models to estimate cougar densities. Overall, 240 tissue samples were collected in northeastern Washington, USA, producing 166 genotypes (including recaptures and excluding dependent kittens) of 133 different cougars (8-25/yr) from 2003 to 2011. Mark–recapture analyses revealed a mean density of 2.2 cougars/100 km2 (95% CI=1.1-4.3) and stable to decreasing population trends (β=-0.048, 95% CI=-0.106–0.011) over the 9 years of study, with an average annual harvest rate of 14% (range=7-21%). The average annual cost per year for field sampling and genotyping was US$11,265 ($422.24/sample or $610.73/successfully genotyped sample). Our results demonstrated that long-term biopsy sampling using citizen scientists can increase capture success and provide reliable cougar-density information at a reasonable cost.
Ahn, Yongjun; Yeo, Hwasoo
2015-01-01
The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC) stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive adoption of electric
On the method of logarithmic cumulants for parametric probability density function estimation.
Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane
2013-10-01
Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible.
Soil Organic Carbon Density in Hebei Province, China:Estimates and Uncertainty
Institute of Scientific and Technical Information of China (English)
ZHAO Yong-Cun; SHI Xue-Zheng; YU Dong-Sheng; T. F. PAGELLA; SUN Wei-Xia; XU Xiang-Hua
2005-01-01
In order to improve the precision of soil organic carbon (SOC) estimates, the sources of uncertainty in soil organic carbon density (SOCD) estimates and SOC stocks were examined using 363 soil profiles in Hebei Province, China, with three methods: the soil profile statistics (SPS), GIS-based soil type (GST), and kriging interpolation (KI). The GST method, utilizing both pedological professional knowledge and GIS technology, was considered the most accurate method of the three estimations, with SOCD estimates for SPS 10% lower and KI 10% higher. The SOCD range for GST was 84% wider than KI as KI smoothing effect narrowed the SOCD range. Nevertheless, the coefficient of variation for SOCD with KI (41.7%) was less than GST and SPS. Comparing SOCD's lower estimates for SPS versus GST, the major sources of uncertainty were the conflicting area of proportional relations. Meanwhile, the fewer number of soil profiles and the necessity of using the smoothing effect with KI were its sources of uncertainty. Moreover, for local detailed variations of SOCD, GST was more advantageous in reflecting the distribution pattern than KI.
Large-sample study of the kernel density estimators under multiplicative censoring
Asgharian, Masoud; Fakoor, Vahid; 10.1214/11-AOS954
2012-01-01
The multiplicative censoring model introduced in Vardi [Biometrika 76 (1989) 751--761] is an incomplete data problem whereby two independent samples from the lifetime distribution $G$, $\\mathcal{X}_m=(X_1,...,X_m)$ and $\\mathcal{Z}_n=(Z_1,...,Z_n)$, are observed subject to a form of coarsening. Specifically, sample $\\mathcal{X}_m$ is fully observed while $\\mathcal{Y}_n=(Y_1,...,Y_n)$ is observed instead of $\\mathcal{Z}_n$, where $Y_i=U_iZ_i$ and $(U_1,...,U_n)$ is an independent sample from the standard uniform distribution. Vardi [Biometrika 76 (1989) 751--761] showed that this model unifies several important statistical problems, such as the deconvolution of an exponential random variable, estimation under a decreasing density constraint and an estimation problem in renewal processes. In this paper, we establish the large-sample properties of kernel density estimators under the multiplicative censoring model. We first construct a strong approximation for the process $\\sqrt{k}(\\hat{G}-G)$, where $\\hat{G}$ is...
The Effects of Surfactants on the Estimation of Bacterial Density in Petroleum Samples
Luna, Aderval Severino; da Costa, Antonio Carlos Augusto; Gonçalves, Márcia Monteiro Machado; de Almeida, Kelly Yaeko Miyashiro
The effect of the surfactants polyoxyethylene monostearate (Tween 60), polyoxyethylene monooleate (Tween 80), cetyl trimethyl ammonium bromide (CTAB), and sodium dodecyl sulfate (SDS) on the estimation of bacterial density (sulfate-reducing bacteria [SRB] and general anaerobic bacteria [GAnB]) was examined in petroleum samples. Three different compositions of oil and water were selected to be representative of the real samples. The first one contained a high content of oil, the second one contained a medium content of oil, and the last one contained a low content of oil. The most probable number (MPN) was used to estimate the bacterial density. The results showed that the addition of surfactants did not improve the SRB quantification for the high or medium oil content in the petroleum samples. On other hand, Tween 60 and Tween 80 promoted a significant increase on the GAnB quantification at 0.01% or 0.03% m/v concentrations, respectively. CTAB increased SRB and GAnB estimation for the sample with a low oil content at 0.00005% and 0.0001% m/v, respectively.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A method to estimate the probabilistic density function (PDF) of shear strength parameters was proposed. The second Chebyshev orthogonal polynomial(SCOP) combined with sample moments (the originmoments)was used to approximate the PDF of parameters. χ2 test was adopted to verify the availability of the method. It is distribution-free because no classical theoretical distributions were assumed in advance and the inference result provides a universal form of probability density curves. Six most commonly-used theoretical distributions named normal, lognormal, extreme value Ⅰ , gama, beta and Weibull distributions were used to verify SCOP method. An example from the observed data of cohesion c of a kind of silt clay was presented for illustrative purpose. The results show that the acceptance levels in SCOP are all smaller than those in the classical finite comparative method and the SCOP function is more accurate and effective in the reliability analysis of geotechnical engineering.
Lawrence, G.; Wallis, M.; Allgood, P.; Nagtegaal, I.D.; Warwick, J.; Cafferty, F.H.; Houssami, N.; Kearins, O.; Tappenden, N.; O'Sullivan, E.; Duffy, S.W.
2009-01-01
BACKGROUND: Evidence of the impact of breast screening is limited by biases inherent in non-randomised studies and often by lack of complete population data. We address this by estimating the effect of screen detection on cause-specific fatality in breast cancer, corrected for all potential biases,
Directory of Open Access Journals (Sweden)
Stefano Anile
2012-07-01
Full Text Available The wildcat is an elusive species that is threatened with extinction in many areas of its European distribution. In Sicily the wildcat lives in a wide range of habitats; this study was done on Mount Etna. A previous camera trap monitoring was conducted in 2006 (pilot study and 2007 (first estimation of wildcat population size using camera trapping with capture-recapture analyses in the same study area. In 2009 digital camera traps in pair were used at each station with the aim of obtaining photographs of the wildcat. Experience and data collected from previous studies were used to develop a protocol to estimate the density of the wildcat’s population using capture–recapture analyses and the coat-colour and markings system to recognize individuals. Two trap-lines adjacent to each other were run in two consecutive data collection periods. Camera traps worked together for 1080 trap-days and we obtained 42 pictures of wildcats from 32 events of photographic capture, from which 10 individuals ( excluding four kittens were determined. The history capture of each individual was constructed and the software CAPTURE was used to generate an estimation of the population density (0.22 to 0.44 wildcat/100 ha for our study area using two different approaches for the calculation of the effective area sampled. The wildcat’s population density on Mount Etna is higher than those found throughout Europe, and is favoured by the habitat structure, prey availability, Mediterranean climate and the protection status provided by the park.
"Prospecting Asteroids: Indirect technique to estimate overall density and inner composition"
Such, Pamela
2016-07-01
Spectroscopic studies of asteroids make possible to obtain some information on their composition from the surface but say little about the innermost material, porosity and density of the object. In addition, spectroscopic observations are affected by the effects of "space weathering" produced by the bombardment of charged particles for certain materials that change their chemical structure, albedo and other physical properties, partly altering their chances of identification. Data such as the mass, size and density of the asteroids are essential at the time to propose space missions in order to determine the best candidates for space exploration and is of great importance to determine a priori any of them remotely from Earth. From many years ago its determined masses of largest asteroids studying the gravitational effects they have on smaller asteroids when they approach them (see Davis and Bender, 1977; Schubart and Matson, 1979; School et al 1987; Hoffman, 1989b, among others), but estimates of the masses of the smallest objects is limited to the effects that occur in extreme close encounters to other asteroids of similar size. This paper presents the results of a search for approaches of pair of asteroids that approximate distances less than 0.0004 UA (50,000 km) of each other in order to study their masses through the astrometric method and to estimate in a future their densities and internal composition. References Davis, D. R., and D. F. Bender. 1977. Asteroid mass determinations: search for futher encounter opportunities. Bull. Am. Astron. Soc. 9, 502-503. Hoffman, M. 1989b. Asteroid mass determination: Present situation and perspectives. In asteroids II (R. P. Binzel, T. Gehreis, and M. S. Matthews, Eds.), pp 228-239. Univ. Arizona Press, Tucson. School, H. L. D. Schmadel and S. Roser 1987. The mass of the asteroid (10) Hygiea derived from observations of (829) Academia. Astron. Astrophys. 179, 311-316. Schubart, J. And D. L. Matson 1979. Masses and
Axonal and dendritic density field estimation from incomplete single-slice neuronal reconstructions
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Jaap evan Pelt
2014-06-01
Full Text Available Neuronal information processing in cortical networks critically depends on the organization of synaptic connectivity. Synaptic connections can form when axons and dendrites come in close proximity of each other. The spatial innervation of neuronal arborizations can be described by their axonal and dendritic density fields. Recently we showed that potential locations of synapses between neurons can be estimated from their overlapping axonal and dendritic density fields. However, deriving density fields from single-slice neuronal reconstructions is hampered by incompleteness because of cut branches.Here, we describe a method for recovering the lost axonal and dendritic mass. This so-called completion method is based on an estimation of the mass inside the slice and an extrapolation to the space outside the slice, assuming axial symmetry in the mass distribution. We validated the method using a set of neurons generated with our NETMORPH simulator. The model-generated neurons were artificially sliced and subsequently recovered by the completion method. Depending on slice thickness and arbor extent, branches that have lost their outside parents (orphan branches may occur inside the slice. Not connected anymore to the contiguous structure of the sliced neuron, orphan branches result in an underestimation of neurite mass. For 300 m thick slices, however, the validation showed a full recovery of dendritic and an almost full recovery of axonal mass.The completion method was applied to three experimental data sets of reconstructed rat cortical L2/3 pyramidal neurons. The results showed that in 300 m thick slices intracortical axons lost about 50% and dendrites about 16% of their mass. The completion method can be applied to single-slice reconstructions as long as axial symmetry can be assumed in the mass distribution. This opens up the possibility of using incomplete neuronal reconstructions from open-access data bases to determine population mean
Efficient 3D movement-based kernel density estimator and application to wildlife ecology
Tracey-PR, Jeff; Sheppard, James K.; Lockwood, Glenn K.; Chourasia, Amit; Tatineni, Mahidhar; Fisher, Robert N.; Sinkovits, Robert S.
2014-01-01
We describe an efficient implementation of a 3D movement-based kernel density estimator for determining animal space use from discrete GPS measurements. This new method provides more accurate results, particularly for species that make large excursions in the vertical dimension. The downside of this approach is that it is much more computationally expensive than simpler, lower-dimensional models. Through a combination of code restructuring, parallelization and performance optimization, we were able to reduce the time to solution by up to a factor of 1000x, thereby greatly improving the applicability of the method.
Cetacean Density Estimation from Novel Acoustic Datasets by Acoustic Propagation Modeling
2013-09-30
whales off Kona, Hawai’i, is based on the works of Zimmer et al. (2008), Marques et al. (2009), and Küsel et al. (2011). The density estimator formula...given by Marques et al. (2009) is applied here for the case of one (k=1) sensor, yielding the following formulation: � = (−�) ...2124 manually labeled false killer whale clicks, calculated in 1 kHz band intervals from 0 to 90 kHz. From the above image it can be observed the
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George Miliaresis
2009-04-01
Full Text Available The U.S National Elevation Dataset and the NLCD 2001 landcover data were used to test the correlation between SRTM elevation values and the height of evergreen forest vegetation in the Klamath Mountains of California.Vegetation height estimates (SRTM-NED are valid only for the two out of eight (N, NE, E, SE, S, SW, W, NW geographic directions, due to NED and SRTM grid data misregistration. Penetration depths of SRTM radar were found to linearly correlate to tree percent canopy density.
Pettersen, Klas H; Hagen, Espen; Einevoll, Gaute T
2008-06-01
This model study investigates the validity of methods used to interpret linear (laminar) multielectrode recordings. In computer experiments extracellular potentials from a synaptically activated population of about 1,000 pyramidal neurons are calculated using biologically realistic compartmental neuron models combined with electrostatic forward modeling. The somas of the pyramidal neurons are located in a 0.4 mm high and wide columnar cylinder, mimicking a stimulus-evoked layer-5 population in a neocortical column. Current-source density (CSD) analysis of the low-frequency part (estimates of the true underlying CSD. The high-frequency part (>750 Hz) of the potentials (multi-unit activity, MUA) is found to scale approximately as the population firing rate to the power 3/4 and to give excellent estimates of the underlying population firing rate for trial-averaged data. The MUA signal is found to decay much more sharply outside the columnar populations than the LFP.
Liu, Huaie; Feng, Guohua; Zeng, Weilin; Li, Xiaomei; Bai, Yao; Deng, Shuang; Ruan, Yonghua; Morris, James; Li, Siman; Yang, Zhaoqing; Cui, Liwang
2016-04-01
The conventional method of estimating parasite densities employ an assumption of 8000 white blood cells (WBCs)/μl. However, due to leucopenia in malaria patients, this number appears to overestimate parasite densities. In this study, we assessed the accuracy of parasite density estimated using this assumed WBC count in eastern Myanmar, where Plasmodium vivax has become increasingly prevalent. From 256 patients with uncomplicated P. vivax malaria, we estimated parasite density and counted WBCs by using an automated blood cell counter. It was found that WBC counts were not significantly different between patients of different gender, axillary temperature, and body mass index levels, whereas they were significantly different between age groups of patients and the time points of measurement. The median parasite densities calculated with the actual WBC counts (1903/μl) and the assumed WBC count of 8000/μl (2570/μl) were significantly different. We demonstrated that using the assumed WBC count of 8000 cells/μl to estimate parasite densities of P. vivax malaria patients in this area would lead to an overestimation. For P. vivax patients aged five years and older, an assumed WBC count of 5500/μl best estimated parasite densities. This study provides more realistic assumed WBC counts for estimating parasite densities in P. vivax patients from low-endemicity areas of Southeast Asia.
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Kaihan Fakhar
Full Text Available OBJECTIVE: We aimed in this investigation to study deep brain stimulation (DBS battery drain with special attention directed toward patient symptoms prior to and following battery replacement. BACKGROUND: Previously our group developed web-based calculators and smart phone applications to estimate DBS battery life (http://mdc.mbi.ufl.edu/surgery/dbs-battery-estimator. METHODS: A cohort of 320 patients undergoing DBS battery replacement from 2002-2012 were included in an IRB approved study. Statistical analysis was performed using SPSS 20.0 (IBM, Armonk, NY. RESULTS: The mean charge density for treatment of Parkinson's disease was 7.2 µC/cm(2/phase (SD = 3.82, for dystonia was 17.5 µC/cm(2/phase (SD = 8.53, for essential tremor was 8.3 µC/cm(2/phase (SD = 4.85, and for OCD was 18.0 µC/cm(2/phase (SD = 4.35. There was a significant relationship between charge density and battery life (r = -.59, p<.001, as well as total power and battery life (r = -.64, p<.001. The UF estimator (r = .67, p<.001 and the Medtronic helpline (r = .74, p<.001 predictions of battery life were significantly positively associated with actual battery life. Battery status indicators on Soletra and Kinetra were poor predictors of battery life. In 38 cases, the symptoms improved following a battery change, suggesting that the neurostimulator was likely responsible for symptom worsening. For these cases, both the UF estimator and the Medtronic helpline were significantly correlated with battery life (r = .65 and r = .70, respectively, both p<.001. CONCLUSIONS: Battery estimations, charge density, total power and clinical symptoms were important factors. The observation of clinical worsening that was rescued following neurostimulator replacement reinforces the notion that changes in clinical symptoms can be associated with battery drain.
Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation
Simon, Dan; Simon, Donald L.
2006-01-01
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters (e.g., the projection approach to constrained filtering).
Budka, Marcin; Gabrys, Bogdan
2013-01-01
Estimation of the generalization ability of a classification or regression model is an important issue, as it indicates the expected performance on previously unseen data and is also used for model selection. Currently used generalization error estimation procedures, such as cross-validation (CV) or bootstrap, are stochastic and, thus, require multiple repetitions in order to produce reliable results, which can be computationally expensive, if not prohibitive. The correntropy-inspired density-preserving sampling (DPS) procedure proposed in this paper eliminates the need for repeating the error estimation procedure by dividing the available data into subsets that are guaranteed to be representative of the input dataset. This allows the production of low-variance error estimates with an accuracy comparable to 10 times repeated CV at a fraction of the computations required by CV. This method can also be used for model ranking and selection. This paper derives the DPS procedure and investigates its usability and performance using a set of public benchmark datasets and standard classifiers.
High-density SNP arrays improve detection of HER2 amplification and polyploidy in breast tumors
DEFF Research Database (Denmark)
Hansen, Thomas V. O.; Vikesaa, Jonas; Buhl, Sine S
2015-01-01
) arrays can provide additional diagnostic power to assess HER2 gene status. METHODS: DNA from 65 breast tumor samples previously diagnosed by HER2 IHC and FISH analysis were blinded and examined for HER2 copy number variation employing SNP array analysis. RESULTS: SNP array analysis identified 24 (37......%) samples with selective amplification or imbalance of the HER2 region in the q-arm of chromosome 17. In contrast, only 15 (23%) tumors were found to have HER2 amplification by IHC and FISH analysis. In total, there was a discrepancy in 19 (29%) samples between SNP array and IHC/FISH analysis. In 12...
Density and Biomass Estimates by Removal for an Amazonian Crocodilian, Paleosuchus palpebrosus.
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Zilca Campos
Full Text Available Direct counts of crocodilians are rarely feasible and it is difficult to meet the assumptions of mark-recapture methods for most species in most habitats. Catch-out experiments are also usually not logistically or morally justifiable because it would be necessary to destroy the habitat in order to be confident that most individuals had been captured. We took advantage of the draining and filling of a large area of flooded forest during the building of the Santo Antônio dam on the Madeira River to obtain accurate estimates of the density and biomass of Paleosuchus palpebrosus. The density, 28.4 non-hatchling individuals per km2, is one of the highest reported for any crocodilian, except for species that are temporarily concentrated in small areas during dry-season drought. The biomass estimate of 63.15 kg*km-2 is higher than that for most or even all mammalian carnivores in tropical forest. P. palpebrosus may be one of the World´s most abundant crocodilians.
Power spectral density of velocity fluctuations estimated from phase Doppler data
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Jicha Miroslav
2012-04-01
Full Text Available Laser Doppler Anemometry (LDA and its modifications such as PhaseDoppler Particle Anemometry (P/DPA is point-wise method for optical nonintrusive measurement of particle velocity with high data rate. Conversion of the LDA velocity data from temporal to frequency domain – calculation of power spectral density (PSD of velocity fluctuations, is a non trivial task due to nonequidistant data sampling in time. We briefly discuss possibilities for the PSD estimation and specify limitations caused by seeding density and other factors of the flow and LDA setup. Arbitrary results of LDA measurements are compared with corresponding Hot Wire Anemometry (HWA data in the frequency domain. Slot correlation (SC method implemented in software program Kern by Nobach (2006 is used for the PSD estimation. Influence of several input parameters on resulting PSDs is described. Optimum setup of the software for our data of particle-laden air flow in realistic human airway model is documented. Typical character of the flow is described using PSD plots of velocity fluctuations with comments on specific properties of the flow. Some recommendations for improvements of future experiments to acquire better PSD results are given.
The Wegner Estimate and the Integrated Density of States for some Random Operators
Indian Academy of Sciences (India)
J M Combes; P D Hislop; Frédéric Klopp; Shu Nakamura
2002-02-01
The integrated density of states (IDS) for random operators is an important function describing many physical characteristics of a random system. Properties of the IDS are derived from the Wegner estimate that describes the influence of finite-volume perturbations on a background system. In this paper, we present a simple proof of the Wegner estimate applicable to a wide variety of random perturbations of deterministic background operators. The proof yields the correct volume dependence of the upper bound. This implies the local Hölder continuity of the integrated density of states at energies in the unperturbed spectral gap. The proof depends on the -theory of the spectral shift function (SSF), for ≥ 1, applicable to pairs of self-adjoint operators whose difference is in the trace ideal $\\mathcal{I}_p$, for 0 < ≤ 1. We present this and other results on the SSF due to other authors. Under an additional condition of the single-site potential, local Hölder continuity is proved at all energies. Finally, we present extensions of this work to random potentials with nonsign definite single-site potentials.
Error estimates for density-functional theory predictions of surface energy and work function
De Waele, Sam; Lejaeghere, Kurt; Sluydts, Michael; Cottenier, Stefaan
2016-12-01
Density-functional theory (DFT) predictions of materials properties are becoming ever more widespread. With increased use comes the demand for estimates of the accuracy of DFT results. In view of the importance of reliable surface properties, this work calculates surface energies and work functions for a large and diverse test set of crystalline solids. They are compared to experimental values by performing a linear regression, which results in a measure of the predictable and material-specific error of the theoretical result. Two of the most prevalent functionals, the local density approximation (LDA) and the Perdew-Burke-Ernzerhof parametrization of the generalized gradient approximation (PBE-GGA), are evaluated and compared. Both LDA and GGA-PBE are found to yield accurate work functions with error bars below 0.3 eV, rivaling the experimental precision. LDA also provides satisfactory estimates for the surface energy with error bars smaller than 10%, but GGA-PBE significantly underestimates the surface energy for materials with a large correlation energy.
Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong
2016-05-30
Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.
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Shanshan Yang
Full Text Available Detection of dysphonia is useful for monitoring the progression of phonatory impairment for patients with Parkinson's disease (PD, and also helps assess the disease severity. This paper describes the statistical pattern analysis methods to study different vocal measurements of sustained phonations. The feature dimension reduction procedure was implemented by using the sequential forward selection (SFS and kernel principal component analysis (KPCA methods. Four selected vocal measures were projected by the KPCA onto the bivariate feature space, in which the class-conditional feature densities can be approximated with the nonparametric kernel density estimation technique. In the vocal pattern classification experiments, Fisher's linear discriminant analysis (FLDA was applied to perform the linear classification of voice records for healthy control subjects and PD patients, and the maximum a posteriori (MAP decision rule and support vector machine (SVM with radial basis function kernels were employed for the nonlinear classification tasks. Based on the KPCA-mapped feature densities, the MAP classifier successfully distinguished 91.8% voice records, with a sensitivity rate of 0.986, a specificity rate of 0.708, and an area value of 0.94 under the receiver operating characteristic (ROC curve. The diagnostic performance provided by the MAP classifier was superior to those of the FLDA and SVM classifiers. In addition, the classification results indicated that gender is insensitive to dysphonia detection, and the sustained phonations of PD patients with minimal functional disability are more difficult to be correctly identified.
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Lingling Jiang
2016-01-01
Full Text Available A multiband and a single-band semianalytical model were developed to predict algae cell density distribution. The models were based on cell density (N dependent parameterizations of the spectral backscattering coefficients, bb(λ, obtained from in situ measurements. There was a strong relationship between bb(λ and N, with a minimum regression coefficient of 0.97 at 488 nm and a maximum value of 0.98 at other bands. The cell density calculated by the multiband inversion model was similar to the field measurements of the coastal waters (the average relative error was only 8.9%, but it could not accurately discern the red tide from mixed pixels, and this led to overestimation of the area affected by the red tide. While the single-band inversion model is less precise than the former model in the high chlorophyll water, it could eliminate the impact of the suspended sediments and make more accurate estimates of the red tide area. We concluded that the two models both have advantages and disadvantages; these methods lay the foundation for developing a remote sensing forecasting system for red tides.
Höing, Andrea; Quinten, Marcel C; Indrawati, Yohana Maria; Cheyne, Susan M; Waltert, Matthias
2013-02-01
Estimating population densities of key species is crucial for many conservation programs. Density estimates provide baseline data and enable monitoring of population size. Several different survey methods are available, and the choice of method depends on the species and study aims. Few studies have compared the accuracy and efficiency of different survey methods for large mammals, particularly for primates. Here we compare estimates of density and abundance of Kloss' gibbons (Hylobates klossii) using two of the most common survey methods: line transect distance sampling and triangulation. Line transect surveys (survey effort: 155.5 km) produced a total of 101 auditory and visual encounters and a density estimate of 5.5 gibbon clusters (groups or subgroups of primate social units)/km(2). Triangulation conducted from 12 listening posts during the same period revealed a similar density estimate of 5.0 clusters/km(2). Coefficients of variation of cluster density estimates were slightly higher from triangulation (0.24) than from line transects (0.17), resulting in a lack of precision in detecting changes in cluster densities of triangulation and triangulation method also may be appropriate.
Cavuoti, S.; Amaro, V.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.
2017-02-01
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z). A wide plethora of methods have been developed, based either on template models fitting or on empirical explorations of the photometric parameter space. Machine-learning-based techniques are not explicitly dependent on the physical priors and able to produce accurate photo-z estimations within the photometric ranges derived from the spectroscopic training set. These estimates, however, are not easy to characterize in terms of a photo-z probability density function (PDF), due to the fact that the analytical relation mapping the photometric parameters on to the redshift space is virtually unknown. We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method designed to provide a reliable PDF of the error distribution for empirical techniques. The method is implemented as a modular workflow, whose internal engine for photo-z estimation makes use of the MLPQNA neural network (Multi Layer Perceptron with Quasi Newton learning rule), with the possibility to easily replace the specific machine-learning model chosen to predict photo-z. We present a summary of results on SDSS-DR9 galaxy data, used also to perform a direct comparison with PDFs obtained by the LE PHARE spectral energy distribution template fitting. We show that METAPHOR is capable to estimate the precision and reliability of photometric redshifts obtained with three different self-adaptive techniques, i.e. MLPQNA, Random Forest and the standard K-Nearest Neighbors models.
How does spatial study design influence density estimates from spatial capture-recapture models?
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Rahel Sollmann
Full Text Available When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km(2. Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.
Shimizu, Noritaka; Futamura, Yasunori; Sakurai, Tetsuya; Mizusaki, Takahiro; Otsuka, Takaharu
2016-01-01
We introduce a novel method to obtain level densities in large-scale shell-model calculations. Our method is a stochastic estimation of eigenvalue count based on a shifted Krylov-subspace method, which enables us to obtain level densities of huge Hamiltonian matrices. This framework leads to a successful description of both low-lying spectroscopy and the experimentally observed equilibration of $J^\\pi=2^+$ and $2^-$ states in $^{58}$Ni in a unified manner.
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Noritaka Shimizu
2016-02-01
Full Text Available We introduce a novel method to obtain level densities in large-scale shell-model calculations. Our method is a stochastic estimation of eigenvalue count based on a shifted Krylov-subspace method, which enables us to obtain level densities of huge Hamiltonian matrices. This framework leads to a successful description of both low-lying spectroscopy and the experimentally observed equilibration of Jπ=2+ and 2− states in 58Ni in a unified manner.
Akune, Tadahiro; Sakamoto, Nobuyoshi
2009-03-01
In a multifilamentary wire proximity-currents between filaments show a close resemblance with the inter-grain current in a high-Tc superconductor. The critical current densities of the proximity-induced superconducting matrix Jcm can be estimated from measured twist-pitch dependence of magnetization and have been shown to follow the well-known scaling law of the pinning strength. The grained Bean model is applied on the multifilamentary wire to obtain Jcm, where the filaments are immersed in the proximity-induced superconducting matrix. Difference of the superconducting characteristics of the filament, the matrix and the filament content factor give a variety of deformation on the AC susceptibility curves. The computed AC susceptibility curves of multifilamentary wires using the grained Bean model are favorably compared with the experimental results. The values of Jcm estimated from the susceptibilities using the grained Bean model are comparable to those estimated from measured twist-pitch dependence of magnetization. The applicability of the grained Bean model on the multifilamentary wire is discussed in detail.
Energy Technology Data Exchange (ETDEWEB)
Akune, Tadahiro; Sakamoto, Nobuyoshi, E-mail: akune@te.kyusan-u.ac.j [Department of Electrical Engineering and Information Technology, Kyushu Sangyo University, 2-3-1 Matsukadai, Fukuoka 813-8503 (Japan)
2009-03-01
In a multifilamentary wire proximity-currents between filaments show a close resemblance with the inter-grain current in a high-T{sub c} superconductor. The critical current densities of the proximity-induced superconducting matrix J{sub cm} can be estimated from measured twist-pitch dependence of magnetization and have been shown to follow the well-known scaling law of the pinning strength. The grained Bean model is applied on the multifilamentary wire to obtain J{sub cm}, where the filaments are immersed in the proximity-induced superconducting matrix. Difference of the superconducting characteristics of the filament, the matrix and the filament content factor give a variety of deformation on the AC susceptibility curves. The computed AC susceptibility curves of multifilamentary wires using the grained Bean model are favorably compared with the experimental results. The values of J{sub cm} estimated from the susceptibilities using the grained Bean model are comparable to those estimated from measured twist-pitch dependence of magnetization. The applicability of the grained Bean model on the multifilamentary wire is discussed in detail.
Zaragosa, Gio P.; Paringit, Enrico C.; Ibañez, Carlyn Ann G.; Faelga, Regine Anne G.; Argamosa, Reginald Jay L.; Posilero, Mark Anthony V.; Tandoc, Fe Andrea M.; Malabanan, Matthew V.
2016-05-01
LiDAR Overlap is the area that is common to two or more flight lines. This is essential to ensure the continuity of data as the acquisition moves from one flight line to another. Looking into overlaps is important when doing DBH Estimation using point cloud data because it doubles the density of points in the overlap region. To remove this effect when determining the DBH of a forest area, the LiDAR data was processed using a point-cloud processing software. The processes include separating flight lines using the GPS time when the points were acquired. After separating, the number of points in the overlap region were decreased by removing excess points within the area of twice the point spacing. The parameters needed for DBH estimation were then obtained. The absolute number of points in the whole overlap area was originally 4,960,726 after decreasing the number of points, it was reduced to 1,479,884. The number of points would have an effect on DBH estimation because the values obtained were significantly different at 95% level of confidence.
Pascual-Marqui, R D; Gonzalez-Andino, S L; Valdes-Sosa, P A; Biscay-Lirio, R
1988-12-01
A method for the spatial analysis of EEG and EP data, based on the spherical harmonic Fourier expansion (SHE) of scalp potential measurements, is described. This model provides efficient and accurate formulas for: (1) the computation of the surface Laplacian and (2) the interpolation of electrical potentials, current source densities, test statistics and other derived variables. Physiologically based simulation experiments show that the SHE method gives better estimates of the surface Laplacian than the commonly used finite difference method. Cross-validation studies for the objective comparison of different interpolation methods demonstrate the superiority of the SHE over the commonly used methods based on the weighted (inverse distance) average of the nearest three and four neighbor values.
Current-source density analysis of slow brain potentials during time estimation.
Gibbons, Henning; Rammsayer, Thomas H
2004-11-01
Two event-related potential studies were conducted to investigate differential brain correlates of temporal processing of intervals below and above 3-4 s. In the first experiment, 24 participants were presented with auditorily marked target durations of 2, 4, and 6 s that had to be reproduced. Timing accuracy was similar for all three target durations. As revealed by current-source density analysis, slow-wave components during both presentation and reproduction were independent of target duration. Experiment 2 examined potential modulating effects of type of interval (filled and empty) and presentation mode (randomized and blocked presentation of target durations). Behavioral and slow-wave findings were consistent with those of Experiment 1. Thus, the present findings support the notion of a general timing mechanism irrespective of interval duration as proposed by scalar timing theory and pacemaker-counter models of time estimation.
Proactive Uniform Data Replication by Density Estimation in Apollonian P2P Networks
Bonnel, Nicolas; Ménier, Gildas; Marteau, Pierre-François
We propose a data replication scheme on a random apollonian P2P overlay that benefits from the small world and scale free properties. The proposed algorithm features a replica density estimation and a space filling mechanism designed to avoid redundant messages. Not only it provides uniform replication of the data stored into the network but it also improves on classical flooding approaches by removing any redundancy. This last property is obtained at the cost of maintaining a random apollonian overlay. Thanks to the small world and scale free properties of the random apollonian P2P overlay, the search efficiency of the space filling tree algorithm we propose has comparable performances with the classical flooding algorithm on a random network.
Dos Santos, Alessio Moreira; Mitja, Danielle; Delaître, Eric; Demagistri, Laurent; de Souza Miranda, Izildinha; Libourel, Thérèse; Petit, Michel
2017-05-15
High spatial resolution images as well as image processing and object detection algorithms are recent technologies that aid the study of biodiversity and commercial plantations of forest species. This paper seeks to contribute knowledge regarding the use of these technologies by studying randomly dispersed native palm tree. Here, we analyze the automatic detection of large circular crown (LCC) palm tree using a high spatial resolution panchromatic GeoEye image (0.50 m) taken on the area of a community of small agricultural farms in the Brazilian Amazon. We also propose auxiliary methods to estimate the density of the LCC palm tree Attalea speciosa (babassu) based on the detection results. We used the "Compt-palm" algorithm based on the detection of palm tree shadows in open areas via mathematical morphology techniques and the spatial information was validated using field methods (i.e. structural census and georeferencing). The algorithm recognized individuals in life stages 5 and 6, and the extraction percentage, branching factor and quality percentage factors were used to evaluate its performance. A principal components analysis showed that the structure of the studied species differs from other species. Approximately 96% of the babassu individuals in stage 6 were detected. These individuals had significantly smaller stipes than the undetected ones. In turn, 60% of the stage 5 babassu individuals were detected, showing significantly a different total height and a different number of leaves from the undetected ones. Our calculations regarding resource availability indicate that 6870 ha contained 25,015 adult babassu palm tree, with an annual potential productivity of 27.4 t of almond oil. The detection of LCC palm tree and the implementation of auxiliary field methods to estimate babassu density is an important first step to monitor this industry resource that is extremely important to the Brazilian economy and thousands of families over a large scale.
A new method for estimating the density of coal for resource and reserve calculation
Energy Technology Data Exchange (ETDEWEB)
Quinn, G.W. [BHP Minerals International Exploration Inc., Kuala Lumpur (Malaysia)
2000-01-01
It is generally agreed that it is currently impossible to measure accurately in situ coal moisture by direct sampling because once the sample is taken it is no longer representative of the in situ condition. This paper presents an alternative proposition that what is really relevant is the weight of coal after mining, on the surface, either as crushed run of mine (ROM) product or beneficiated product, not the weight of coal in the ground. This is the form in which the coal is first weighed and the form in which it is sold and utilised. Thus it is only essential to estimate as accurately as possible the volume of coal in the ground from thickness information. It is the relative density (RD) of the broken coal on the surface that is important, not that of the solid coal in situ. It is shown however, that on a dry basis the two are essentially the same. This could be a useful and realistic way to determine suitable relative densities for coal resource and reserve calculations. 2 refs., 3 figs., 1 tab.
Kamousi, Baharan; Amini, Ali Nasiri; He, Bin
2007-06-01
The goal of the present study is to employ the source imaging methods such as cortical current density estimation for the classification of left- and right-hand motor imagery tasks, which may be used for brain-computer interface (BCI) applications. The scalp recorded EEG was first preprocessed by surface Laplacian filtering, time-frequency filtering, noise normalization and independent component analysis. Then the cortical imaging technique was used to solve the EEG inverse problem. Cortical current density distributions of left and right trials were classified from each other by exploiting the concept of Von Neumann entropy. The proposed method was tested on three human subjects (180 trials each) and a maximum accuracy of 91.5% and an average accuracy of 88% were obtained. The present results confirm the hypothesis that source analysis methods may improve accuracy for classification of motor imagery tasks. The present promising results using source analysis for classification of motor imagery enhances our ability of performing source analysis from single trial EEG data recorded on the scalp, and may have applications to improved BCI systems.
Lussana, C.
2013-04-01
The presented work focuses on the investigation of gridded daily minimum (TN) and maximum (TX) temperature probability density functions (PDFs) with the intent of both characterising a region and detecting extreme values. The empirical PDFs estimation procedure has been realised using the most recent years of gridded temperature analysis fields available at ARPA Lombardia, in Northern Italy. The spatial interpolation is based on an implementation of Optimal Interpolation using observations from a dense surface network of automated weather stations. An effort has been made to identify both the time period and the spatial areas with a stable data density otherwise the elaboration could be influenced by the unsettled station distribution. The PDF used in this study is based on the Gaussian distribution, nevertheless it is designed to have an asymmetrical (skewed) shape in order to enable distinction between warming and cooling events. Once properly defined the occurrence of extreme events, it is possible to straightforwardly deliver to the users the information on a local-scale in a concise way, such as: TX extremely cold/hot or TN extremely cold/hot.
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Lal, Ratan, E-mail: rlal_npl_3543@yahoo.i [Superconductivity Division, National Physical Laboratory, Council of Scientific and Industrial Research, Dr. K.S. Krishnan Road, New Delhi 110012 (India)
2010-02-15
The critical current density J{sub c} of some of the superconducting samples, calculated on the basis of the Bean's model, shows negative curvature for low magnetic field with a downward bending near H = 0. To avoid this problem Kim's expression of the critical current density, J{sub c} = k/(H{sub 0} + H), where J{sub c} has positive curvature for all H, has been employed by connecting the positive constants k and H{sub 0} with the features of the hysteresis loop of a superconductor. A relation between the full penetration field H{sub p} and the magnetic field H{sub min}, at which the magnetization is minimum, is obtained from the Kim's theory. Taking the value of J{sub c} at H = H{sub p} according to the actual loop width, as in the Bean's theory, and at H = 0 according to an enhanced loop width due to the local internal field, values of k and H{sub 0} are obtained in terms of the magnetization values M{sup +}(-H{sub min}), M{sup -}(H{sub min}), M{sup +}(H{sub p}) and M{sup -}(H{sub p}). The resulting method of estimating J{sub c} from the hysteresis loop turns out to be as simple as the Bean's method.
Evaluation of a brushing machine for estimating density of spider mites on grape leaves.
Macmillan, Craig D; Costello, Michael J
2015-12-01
Direct visual inspection and enumeration for estimating field population density of economically important arthropods, such as spider mites, provide more information than alternative methods, such as binomial sampling, but is laborious and time consuming. A brushing machine can reduce sampling time and perhaps improve accuracy. Although brushing technology has been investigated and recommended as a useful tool for researchers and integrated pest management practitioners, little work to demonstrate the validity of this technique has been performed since the 1950's. We investigated the brushing machine manufactured by Leedom Enterprises (Mi-Wuk Village, CA, USA) for studies on spider mites. We evaluated (1) the mite recovery efficiency relative to the number of passes of a leaf through the brushes, (2) mite counts as generated by the machine compared to visual counts under a microscope, (3) the lateral distribution of mites on the collection plate and (4) the accuracy and precision of a 10% sub-sample using a double-transect counting grid. We found that about 95% of mites on a leaf were recovered after five passes, and 99% after nine passes, and mite counts from brushing were consistently higher than those from visual inspection. Lateral distribution of mites was not uniform, being highest in concentration at the center and lowest at the periphery. The 10% double-transect pattern did not result in a significant correlation with the total plate count at low mite density, but accuracy and precision improved at medium and high density. We suggest that a more accurate and precise sample may be achieved using a modified pattern which concentrates on the center plus some of the adjacent area.
Directory of Open Access Journals (Sweden)
Yang Zu
2015-07-01
Full Text Available This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observations and strong mixing observations are considered. The dependent case of the result is applied to obtain the pointwise asymptotic distribution of the deconvolution volatility density estimator in discrete-time stochastic volatility models.
Yeo, Ui Hyang; Choi, Chang Jin; Choi, Whan Seok; Kim, Kyung Soo
2016-01-01
Breast-feeding has the deleterious effect of hypoestrogenemia coupled with loss of calcium in the maternal bone mass. It is not clear whether changes in bone metabolism in lactating women lead to changes in maternal bone mineral density (BMD) over a longer period. The aim of the present study was to investigate the relationship between the duration of breast-feeding and BMD in healthy South Korean women. We analyzed data from the 2010 Korea National Health and Nutrition Examination Survey, a cross-sectional survey of Korean citizens. A total of 1342 women older than 19 years were selected for analysis. In postmenopausal women, the duration of breast-feeding per child was associated with low lumbar spine BMD after adjustment for age, body mass index, smoking, alcohol intake, physical activity, serum 25-hydroxyvitamin D level, and daily intake of calcium and calories (P < 0.05, P trend < 0.005). Prolonged breast-feeding for more than 1 year per child was associated with a deleterious effect on lumbar spine BMD compared with never breast-feeding or a shorter duration of breast-feeding (P < 0.05). These effects were not shown in premenopausal women or in femur BMD. In conclusion, the duration of breast-feeding per child is negatively correlated with lumbar spine BMD in postmenopausal women, but not in premenopausal women. Although the cause of the different results between postmenopausal and premenopausal women is not clear, our findings suggest that proper protective strategies should be recommended during prolonged breast-feeding to maintain bone health later in life.
Hong, Byung-Woo
2013-11-01
We propose a mathematical framework for simultaneously delineating the boundary of object and estimating its temporal motion in the application of lesion detection in a dynamic contrast-enhanced (DCE) breast MRI sequence where both the appearance and the shape of region of interest is assumed to change in time. A unified energy functional for a joint segmentation and registration is proposed based on the assumption that the statistical properties of dynamic intensity curves within a region of interest are homogeneous. Our algorithm is designed to provide the morphological properties of the enhanced region and its dynamic intensity profiles, called kinetic signatures, in the analysis of DCE imagery since these features are considered as significant cues in understanding images. The proposed energy comprises a combination of a segmentation energy and a registration energy. The segmentation energy is developed based on a convex formulation being insensitive to the initialization. The registration energy is designed to compensate motion artifacts that are usually involved in the temporal imaging procedure. The major objective of this work is to provide a mathematical framework for a joint segmentation and registration on a dynamic sequence of images, and we demonstrate the mutual benefit of the estimation of temporal deformations for the registration step and the localization of regions of interest for the segmentation step. The effectiveness of the developed algorithm has been demonstrated on a number of clinical DCE breast MRI data in the application of breast lesion detection and the results show its potential to improve the accuracy and the efficiency in the diagnosis of breast cancer.
Probability density function and estimation for error of digitized map coordinates in GIS
Institute of Scientific and Technical Information of China (English)
童小华; 刘大杰
2004-01-01
Traditionally, it is widely accepted that measurement error usually obeys the normal distribution. However, in this paper a new idea is proposed that the error in digitized data which is a major derived data source in GIS does not obey the normal distribution but the p-norm distribution with a determinate parameter. Assuming that the error is random and has the same statistical properties, the probability density function of the normal distribution,Laplace distribution and p-norm distribution are derived based on the arithmetic mean axiom, median axiom and pmedian axiom, which means that the normal distribution is only one of these distributions but not the least one.Based on this idea, distribution fitness tests such as Skewness and Kurtosis coefficient test, Pearson chi-square x2 test and Kolmogorov test for digitized data are conducted. The results show that the error in map digitization obeys the p-norm distribution whose parameter is close to 1.60. A least p-norm estimation and the least square estimation of digitized data are further analyzed, showing that the least p-norm adiustment is better than the least square adjustment for digitized data processing in GIS.
Methods for Estimating Environmental Effects and Constraints on NexGen: High Density Case Study
Augustine, S.; Ermatinger, C.; Graham, M.; Thompson, T.
2010-01-01
This document provides a summary of the current methods developed by Metron Aviation for the estimate of environmental effects and constraints on the Next Generation Air Transportation System (NextGen). This body of work incorporates many of the key elements necessary to achieve such an estimate. Each section contains the background and motivation for the technical elements of the work, a description of the methods used, and possible next steps. The current methods described in this document were selected in an attempt to provide a good balance between accuracy and fairly rapid turn around times to best advance Joint Planning and Development Office (JPDO) System Modeling and Analysis Division (SMAD) objectives while also supporting the needs of the JPDO Environmental Working Group (EWG). In particular this document describes methods applied to support the High Density (HD) Case Study performed during the spring of 2008. A reference day (in 2006) is modeled to describe current system capabilities while the future demand is applied to multiple alternatives to analyze system performance. The major variables in the alternatives are operational/procedural capabilities for airport, terminal, and en route airspace along with projected improvements to airframe, engine and navigational equipment.
Spatial Variation in Tree Density and Estimated Aboveground Carbon Stocks in Southern Africa
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Lulseged Tamene
2016-03-01
Full Text Available Variability in woody plant species, vegetation assemblages and anthropogenic activities derails the efforts to have common approaches for estimating biomass and carbon stocks in Africa. In order to suggest management options, it is important to understand the vegetation dynamics and the major drivers governing the observed conditions. This study uses data from 29 sentinel landscapes (4640 plots across the southern Africa. We used T-Square distance method to sample trees. Allometric models were used to estimate aboveground tree biomass from which aboveground biomass carbon stock (AGBCS was derived for each site. Results show average tree density of 502 trees·ha−1 with semi-arid areas having the highest (682 trees·ha−1 and arid regions the lowest (393 trees·ha−1. The overall AGBCS was 56.4 Mg·ha−1. However, significant site to site variability existed across the region. Over 60 fold differences were noted between the lowest AGBCS (2.2 Mg·ha−1 in the Musungwa plains of Zambia and the highest (138.1 Mg·ha−1 in the scrublands of Kenilworth in Zimbabwe. Semi-arid and humid sites had higher carbon stocks than sites in sub-humid and arid regions. Anthropogenic activities also influenced the observed carbon stocks. Repeated measurements would reveal future trends in tree cover and carbon stocks across different systems.
NEAR INFRARED SPECTROSCOPY FOR ESTIMATING SUGARCANE BAGASSE CONTENT IN MEDIUM DENSITY FIBERBOARD
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Ugo Leandro Belini
2011-04-01
Full Text Available Medium density fiberboard (MDF is an engineered wood product formed by breaking down selected lignin-cellulosic material residuals into fibers, combining it with wax and a resin binder, and then forming panels by applying high temperature and pressure. Because the raw material in the industrial process is ever-changing, the panel industry requires methods for monitoring the composition of their products. The aim of this study was to estimate the ratio of sugarcane (SC bagasse to Eucalyptus wood in MDF panels using near infrared (NIR spectroscopy. Principal component analysis (PCA and partial least square (PLS regressions were performed. MDF panels having different bagasse contents were easily distinguished from each other by the PCA of their NIR spectra with clearly different patterns of response. The PLS-R models for SC content of these MDF samples presented a strong coefficient of determination (0.96 between the NIR-predicted and Lab-determined values and a low standard error of prediction (~1.5% in the cross-validations. A key role of resins (adhesives, cellulose, and lignin for such PLS-R calibrations was shown. PLS-DA model correctly classified ninety-four percent of MDF samples by cross-validations and ninety-eight percent of the panels by independent test set. These NIR-based models can be useful to quickly estimate sugarcane bagasse vs. Eucalyptus wood content ratio in unknown MDF samples and to verify the quality of these engineered wood products in an online process.
Institute of Scientific and Technical Information of China (English)
YAN Hao; WANG Hu; WANG Yong-hui; ZHANG Yu-mei
2013-01-01
Background The classification of Alzheimer's disease (AD) from magnetic resonance imaging (MRI) has been challenged by lack of effective and reliable biomarkers due to inter-subject variability.This article presents a classification method for AD based on kernel density estimation (KDE) of local features.Methods First,a large number of local features were extracted from stable image blobs to represent various anatomical patterns for potential effective biomarkers.Based on distinctive descriptors and locations,the local features were robustly clustered to identify correspondences of the same underlying patterns.Then,the KDE was used to estimate distribution parameters of the correspondences by weighting contributions according to their distances.Thus,biomarkers could be reliably quantified by reducing the effects of further away correspondences which were more likely noises from inter-subject variability.Finally,the Bayes classifier was applied on the distribution parameters for the classification of AD.Results Experiments were performed on different divisions of a publicly available database to investigate the accuracy and the effects of age and AD severity.Our method achieved an equal error classification rate of 0.85 for subject aged 60-80 years exhibiting mild AD and outperformed a recent local feature-based work regardless of both effects.Conclusions We proposed a volumetric brain MRI classification method for neurodegenerative disease based on statistics of local features using KDE.The method may be potentially useful for the computer-aided diagnosis in clinical settings.
mBEEF: An accurate semi-local Bayesian error estimation density functional
Wellendorff, Jess; Lundgaard, Keld T.; Jacobsen, Karsten W.; Bligaard, Thomas
2014-04-01
We present a general-purpose meta-generalized gradient approximation (MGGA) exchange-correlation functional generated within the Bayesian error estimation functional framework [J. Wellendorff, K. T. Lundgaard, A. Møgelhøj, V. Petzold, D. D. Landis, J. K. Nørskov, T. Bligaard, and K. W. Jacobsen, Phys. Rev. B 85, 235149 (2012)]. The functional is designed to give reasonably accurate density functional theory (DFT) predictions of a broad range of properties in materials physics and chemistry, while exhibiting a high degree of transferability. Particularly, it improves upon solid cohesive energies and lattice constants over the BEEF-vdW functional without compromising high performance on adsorption and reaction energies. We thus expect it to be particularly well-suited for studies in surface science and catalysis. An ensemble of functionals for error estimation in DFT is an intrinsic feature of exchange-correlation models designed this way, and we show how the Bayesian ensemble may provide a systematic analysis of the reliability of DFT based simulations.
Dorgan, Joanne F.; Liu, Lea; Klifa, Catherine; Hylton, Nola; Shepherd, John A.; Stanczyk, Frank Z.; Snetselaar, Linda G.; Van Horn, Linda; Stevens, Victor J.; Robson, Alan; Kwiterovich, Peter O.; Lasser, Norman L.; Himes, John H.; Gabriel, Kelley Pettee; Kriska, Andrea; Ruder, Elizabeth H.; Fang, Carolyn Y.; Barton, Bruce A.
2010-01-01
Background: Adolescent diet is hypothesized to influence breast cancer risk. We evaluated the long-term effects of an intervention to lower fat intake among adolescent girls on biomarkers that are related to breast cancer risk in adults. Methods: A follow-up study was conducted on 230 girls who part
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Wolfe, Adam R. [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Atkinson, Rachel L. [Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Reddy, Jay P. [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Debeb, Bisrat G.; Larson, Richard; Li, Li [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Masuda, Hiroko; Brewer, Takae [Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Atkinson, Bradley J. [Department of Clinical Pharmacy Services, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Brewster, Abeena [Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Ueno, Naoto T. [Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Woodward, Wendy A., E-mail: wwoodward@mdanderson.org [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)
2015-04-01
Purpose: We previously demonstrated that cholesterol-lowering agents regulate radiation sensitivity of inflammatory breast cancer (IBC) cell lines in vitro and are associated with less radiation resistance among IBC patients who undergo postmastectomy radiation. We hypothesized that decreasing IBC cellular cholesterol induced by treatment with lipoproteins would increase radiation sensitivity. Here, we examined the impact of specific transporters of cholesterol (ie lipoproteins) on the responses of IBC cells to self-renewal and to radiation in vitro and on clinical outcomes in IBC patients. Methods and Materials: Two patient-derived IBC cell lines, SUM 149 and KPL4, were incubated with low-density lipoproteins (LDL), very-low-density lipoproteins (VLDL), or high-density lipoproteins (HDL) for 24 hours prior to irradiation (0-6 Gy) and mammosphere formation assay. Cholesterol panels were examined in a cohort of patients with primary IBC diagnosed between 1995 and 2011 at MD Anderson Cancer Center. Lipoprotein levels were then correlated to patient outcome, using the log rank statistical model, and examined in multivariate analysis using Cox regression. Results: VLDL increased and HDL decreased mammosphere formation compared to untreated SUM 149 and KPL4 cells. Survival curves showed enhancement of survival in both of the IBC cell lines when pretreated with VLDL and, conversely, radiation sensitization in all cell lines when pretreated with HDL. In IBC patients, higher VLDL values (>30 mg/dL) predicted a lower 5-year overall survival rate than normal values (hazard ratio [HR] = 1.9 [95% confidence interval [CI]: 1.05-3.45], P=.035). Lower-than-normal patient HDL values (<60 mg/dL) predicted a lower 5-year overall survival rate than values higher than 60 mg/dL (HR = 3.21 [95% CI: 1.25-8.27], P=.015). Conclusions: This study discovered a relationship among the plasma levels of lipoproteins, overall patient response, and radiation resistance in IBC patients
Lee, Sooyeul; Jeong, Ji-Wook; Lee, Jeong Won; Yoo, Done-Sik; Kim, Seunghwan
2006-01-01
Osteoporosis is characterized by an abnormal loss of bone mineral content, which leads to a tendency to non-traumatic bone fractures or to structural deformations of bone. Thus, bone density measurement has been considered as a most reliable method to assess bone fracture risk due to osteoporosis. In past decades, X-ray images have been studied in connection with the bone mineral density estimation. However, the estimated bone mineral density from the X-ray image can undergo a relatively large accuracy or precision error. The most relevant origin of the accuracy or precision error may be unstable X-ray image acquisition condition. Thus, we focus our attentions on finding a bone mineral density estimation method that is relatively insensitive to the X-ray image acquisition condition. In this paper, we develop a simple technique for distal radius bone mineral density estimation using the trabecular bone filling factor in the X-ray image and apply the technique to the wrist X-ray images of 20 women. Estimated bone mineral density shows a high linear correlation with a dual-energy X-ray absorptiometry (r=0.87).
Zeng, L.; Doyle, E. J.; Rhodes, T. L.; Wang, G.; Sung, C.; Peebles, W. A.; Bobrek, M.
2016-11-01
A new model-based technique for fast estimation of the pedestal electron density gradient has been developed. The technique uses ordinary mode polarization profile reflectometer time delay data and does not require direct profile inversion. Because of its simple data processing, the technique can be readily implemented via a Field-Programmable Gate Array, so as to provide a real-time density gradient estimate, suitable for use in plasma control systems such as envisioned for ITER, and possibly for DIII-D and Experimental Advanced Superconducting Tokamak. The method is based on a simple edge plasma model with a linear pedestal density gradient and low scrape-off-layer density. By measuring reflectometer time delays for three adjacent frequencies, the pedestal density gradient can be estimated analytically via the new approach. Using existing DIII-D profile reflectometer data, the estimated density gradients obtained from the new technique are found to be in good agreement with the actual density gradients for a number of dynamic DIII-D plasma conditions.
Kaye, Jason; Yang, Chao
2014-01-01
Kohn-Sham density functional theory is one of the most widely used electronic structure theories. The recently developed adaptive local basis functions form an accurate and systematically improvable basis set for solving Kohn-Sham density functional theory using discontinuous Galerkin methods, requiring a small number of basis functions per atom. In this paper we develop residual-based a posteriori error estimates for the adaptive local basis approach, which can be used to guide non-uniform basis refinement for highly inhomogeneous systems such as surfaces and large molecules. The adaptive local basis functions are non-polynomial basis functions, and standard a posteriori error estimates for $hp$-refinement using polynomial basis functions do not directly apply. We generalize the error estimates for $hp$-refinement to non-polynomial basis functions. We demonstrate the practical use of the a posteriori error estimator in performing three-dimensional Kohn-Sham density functional theory calculations for quasi-2D...
Directory of Open Access Journals (Sweden)
François Pimont
2015-06-01
Full Text Available Leaf biomass distribution is a key factor for modeling energy and carbon fluxes in forest canopies and for assessing fire behavior. We propose a new method to estimate 3D leaf bulk density distribution, based on a calibration of indices derived from T-LiDAR. We applied the method to four contrasted plots in a mature Quercus pubescens forest. Leaf bulk densities were measured inside 0.7 m-diameter spheres, referred to as Calibration Volumes. Indices were derived from LiDAR point clouds and calibrated over the Calibration Volume bulk densities. Several indices were proposed and tested to account for noise resulting from mixed pixels and other theoretical considerations. The best index and its calibration parameter were then used to estimate leaf bulk densities at the grid nodes of each plot. These LiDAR-derived bulk density distributions were used to estimate bulk density vertical profiles and loads and above four meters compared well with those assessed by the classical inventory-based approach. Below four meters, the LiDAR-based approach overestimated bulk densities since no distinction was made between wood and leaf returns. The results of our method are promising since they demonstrate the possibility to assess bulk density on small plots at a reasonable operational cost.
Optical Density Analysis of X-Rays Utilizing Calibration Tooling to Estimate Thickness of Parts
Grau, David
2012-01-01
This process is designed to estimate the thickness change of a material through data analysis of a digitized version of an x-ray (or a digital x-ray) containing the material (with the thickness in question) and various tooling. Using this process, it is possible to estimate a material's thickness change in a region of the material or part that is thinner than the rest of the reference thickness. However, that same principle process can be used to determine the thickness change of material using a thinner region to determine thickening, or it can be used to develop contour plots of an entire part. Proper tooling must be used. An x-ray film with an S-shaped characteristic curve or a digital x-ray device with a product resulting in like characteristics is necessary. If a film exists with linear characteristics, this type of film would be ideal; however, at the time of this reporting, no such film has been known. Machined components (with known fractional thicknesses) of a like material (similar density) to that of the material to be measured are necessary. The machined components should have machined through-holes. For ease of use and better accuracy, the throughholes should be a size larger than 0.125 in. (.3 mm). Standard components for this use are known as penetrameters or image quality indicators. Also needed is standard x-ray equipment, if film is used in place of digital equipment, or x-ray digitization equipment with proven conversion properties. Typical x-ray digitization equipment is commonly used in the medical industry, and creates digital images of x-rays in DICOM format. It is recommended to scan the image in a 16-bit format. However, 12-bit and 8-bit resolutions are acceptable. Finally, x-ray analysis software that allows accurate digital image density calculations, such as Image-J freeware, is needed. The actual procedure requires the test article to be placed on the raw x-ray, ensuring the region of interest is aligned for perpendicular x-ray exposure
Berzins, Juris; Sneiders, Uldis; Plegere, Daina; Freivalds, Talivaldis; Grigalinovica, Romalda
2000-04-01
We performed a multi parameter image analysis assessment of breast cancer cell population nuclear grade (NG), which is regarded as one of the main prognostic factors for treatment efficacy and survival of the patients and compared it with light microscopic estimation of NG. Cytological imprint slides from 20 ductal carcinomas were stained according to Leischmann-AzureII-eosine method, and NG was estimated by light microscopic observation according to Black in Fisher's modification. Simultaneously, using specially elaborated software, in each patient 100 cancer cells were analyzed for nuclear perimeter, diameter, area, nucleolar area, and average intensity of staining. The chromatin structure was assessed using mean diameter of chromatin grains and relatively chromatic are within the nucleus. Light microscopic estimation revealed 4/15 grade 2 and 7/15 grade 3 tumors out of 15 filtrating ductal carcinomas, with 4/15 classified as intermediate between grade 2-3. Multifactoral linear correlation coefficient r equals 0.39, p < 0.001 for ductal cancer, higher NG comes with increasing nucleolar area, nuclear roundness factor, nuclear are, and chromatin area within the cell nucleus. Image analysis may yield precise information on NG as a prognostic factor in breast cancer patients.
Taroni, Paola; Paganoni, Anna Maria; Ieva, Francesca; Pifferi, Antonio; Quarto, Giovanna; Abbate, Francesca; Cassano, Enrico; Cubeddu, Rinaldo
2017-01-01
Several techniques are being investigated as a complement to screening mammography, to reduce its false-positive rate, but results are still insufficient to draw conclusions. This initial study explores time domain diffuse optical imaging as an adjunct method to classify non-invasively malignant vs benign breast lesions. We estimated differences in tissue composition (oxy- and deoxyhemoglobin, lipid, water, collagen) and absorption properties between lesion and average healthy tissue in the same breast applying a perturbative approach to optical images collected at 7 red-near infrared wavelengths (635–1060 nm) from subjects bearing breast lesions. The Discrete AdaBoost procedure, a machine-learning algorithm, was then exploited to classify lesions based on optically derived information (either tissue composition or absorption) and risk factors obtained from patient’s anamnesis (age, body mass index, familiarity, parity, use of oral contraceptives, and use of Tamoxifen). Collagen content, in particular, turned out to be the most important parameter for discrimination. Based on the initial results of this study the proposed method deserves further investigation.
Taroni, Paola; Paganoni, Anna Maria; Ieva, Francesca; Pifferi, Antonio; Quarto, Giovanna; Abbate, Francesca; Cassano, Enrico; Cubeddu, Rinaldo
2017-01-01
Several techniques are being investigated as a complement to screening mammography, to reduce its false-positive rate, but results are still insufficient to draw conclusions. This initial study explores time domain diffuse optical imaging as an adjunct method to classify non-invasively malignant vs benign breast lesions. We estimated differences in tissue composition (oxy- and deoxyhemoglobin, lipid, water, collagen) and absorption properties between lesion and average healthy tissue in the same breast applying a perturbative approach to optical images collected at 7 red-near infrared wavelengths (635–1060 nm) from subjects bearing breast lesions. The Discrete AdaBoost procedure, a machine-learning algorithm, was then exploited to classify lesions based on optically derived information (either tissue composition or absorption) and risk factors obtained from patient’s anamnesis (age, body mass index, familiarity, parity, use of oral contraceptives, and use of Tamoxifen). Collagen content, in particular, turned out to be the most important parameter for discrimination. Based on the initial results of this study the proposed method deserves further investigation. PMID:28091596
Pomeroy, Kay M; Sawyer, Laura J; Evans, Martyn J
2005-09-01
Administration of a radiopharmaceutical may result in a radiation dose to an infant due to ingestion of the radiopharmaceutical secreted in the breast milk. Following a maternal administration of Co labelled to vitamin B12 (cyanocobalamin) as part of a Schilling test an estimate of the absorbed dose to a breast feeding infant was calculated. Milk samples were collected from every feed in the first 24 h, and at approximately 48 and 72 h post-administration. The absorbed dose to the infant's liver (the organ receiving the highest dose) was calculated to be 0.23 mGy. The effective dose to the infant was calculated to be 0.025 mSv, which is considerably lower than the current regulatory limit of 1 mSv. The Administration of Radioactive Substances Advisory Committee advise that the first feed, at approximately 4 h after administration, be discarded. The data show that this was unwarranted, and that the peak concentration of Co in the breast milk occurred at around 24 h.
Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites
Mitchard, Edward T A; Feldpausch, Ted R; Brienen, Roel J W; Lopez-Gonzalez, Gabriela; Monteagudo, Abel; Baker, Timothy R; Lewis, Simon L; Lloyd, Jon; Quesada, Carlos A; Gloor, Manuel; ter Steege, Hans; Meir, Patrick; Alvarez, Esteban; Araujo-Murakami, Alejandro; Aragão, Luiz E O C; Arroyo, Luzmila; Aymard, Gerardo; Banki, Olaf; Bonal, Damien; Brown, Sandra; Brown, Foster I; Cerón, Carlos E; Chama Moscoso, Victor; Chave, Jerome; Comiskey, James A; Cornejo, Fernando; Corrales Medina, Massiel; Da Costa, Lola; Costa, Flavia R C; Di Fiore, Anthony; Domingues, Tomas F; Erwin, Terry L; Frederickson, Todd; Higuchi, Niro; Honorio Coronado, Euridice N; Killeen, Tim J; Laurance, William F; Levis, Carolina; Magnusson, William E; Marimon, Beatriz S; Marimon Junior, Ben Hur; Mendoza Polo, Irina; Mishra, Piyush; Nascimento, Marcelo T; Neill, David; Núñez Vargas, Mario P; Palacios, Walter A; Parada, Alexander; Pardo Molina, Guido; Peña-Claros, Marielos; Pitman, Nigel; Peres, Carlos A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Restrepo Correa, Zorayda; Roopsind, Anand; Roucoux, Katherine H; Rudas, Agustin; Salomão, Rafael P; Schietti, Juliana; Silveira, Marcos; de Souza, Priscila F; Steininger, Marc K; Stropp, Juliana; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van Andel, Tinde R; van der Heijden, Geertje M F; Vieira, Ima C G; Vieira, Simone; Vilanova-Torre, Emilio; Vos, Vincent A; Wang, Ophelia; Zartman, Charles E; Malhi, Yadvinder; Phillips, Oliver L
2014-01-01
Aim The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Location Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1 Methods Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. Results The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. Main conclusions Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities
Brown, S; Gaston, G
1995-01-01
One of the most important databases needed for estimating emissions of carbon dioxide resulting from changes in the cover, use, and management of tropical forests is the total quantity of biomass per unit area, referred to as biomass density. Forest inventories have been shown to be valuable sources of data for estimating biomass density, but inventories for the tropics are few in number and their quality is poor. This lack of reliable data has been overcome by use of a promising approach that produces geographically referenced estimates by modeling in a geographic information system (GIS). This approach has been used to produce geographically referenced, spatial distributions of potential and actual (circa 1980) aboveground biomass density of all forests types in tropical Africa. Potential and actual biomass density estimates ranged from 33 to 412 Mg ha(-1) (10(6)g ha(-1)) and 20 to 299 Mg ha(-1), respectively, for very dry lowland to moist lowland forests and from 78 to 197 Mg ha(-1) and 37 to 105 Mg ha(-1), respectively, for montane-seasonal to montane-moist forests. Of the 37 countries included in this study, more than half (51%) contained forests that had less than 60% of their potential biomass. Actual biomass density for forest vegetation was lowest in Botswana, Niger, Somalia, and Zimbabwe (about 10 to 15 Mg ha(-1)). Highest estimates for actual biomass density were found in Congo, Equatorial Guinea, Gabon, and Liberia (305 to 344 Mg ha(-1)). Results from this research effort can contribute to reducing uncertainty in the inventory of country-level emission by providing consistent estimates of biomass density at subnational scales that can be used with other similarly scaled databases on change in land cover and use.
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Yu Xu
2016-06-01
Full Text Available Estimates of abundance or density are essential for wildlife management and conservation. There are few effective density estimates for the Buff-throated Partridge Tetraophasis szechenyii, a rare and elusive high-mountain Galliform species endemic to western China. In this study, we used the temporary emigration N-mixture model to estimate density of this species, with data acquired from playback point count surveys around a sacred area based on indigenous Tibetan culture of protection of wildlife, in Yajiang County, Sichuan, China, during April-June 2009. Within 84 125-m radius points, we recorded 53 partridge groups during three repeats. The best model indicated that detection probability was described by covariates of vegetation cover type, week of visit, time of day, and weather with weak effects, and a partridge group was present during a sampling period with a constant probability. The abundance component was accounted for by vegetation association. Abundance was substantially higher in rhododendron shrubs, fir-larch forests, mixed spruce-larch-birch forests, and especially oak thickets than in pine forests. The model predicted a density of 5.14 groups/km², which is similar to an estimate of 4.7 - 5.3 groups/km² quantified via an intensive spot-mapping effort. The post-hoc estimate of individual density was 14.44 individuals/km², based on the estimated mean group size of 2.81. We suggest that the method we employed is applicable to estimate densities of Buff-throated Partridges in large areas. Given importance of a mosaic habitat for this species, local logging should be regulated. Despite no effect of the conservation area (sacred on the abundance of Buff-throated Partridges, we suggest regulations linking the sacred mountain conservation area with the official conservation system because of strong local participation facilitated by sacred mountains in land conservation.
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Niels Halama
Full Text Available BACKGROUND: Determining the correct number of positive immune cells in immunohistological sections of colorectal cancer and other tumor entities is emerging as an important clinical predictor and therapy selector for an individual patient. This task is usually obstructed by cell conglomerates of various sizes. We here show that at least in colorectal cancer the inclusion of immune cell conglomerates is indispensable for estimating reliable patient cell counts. Integrating virtual microscopy and image processing principally allows the high-throughput evaluation of complete tissue slides. METHODOLOGY/PRINCIPAL FINDINGS: For such large-scale systems we demonstrate a robust quantitative image processing algorithm for the reproducible quantification of cell conglomerates on CD3 positive T cells in colorectal cancer. While isolated cells (28 to 80 microm(2 are counted directly, the number of cells contained in a conglomerate is estimated by dividing the area of the conglomerate in thin tissues sections (< or =6 microm by the median area covered by an isolated T cell which we determined as 58 microm(2. We applied our algorithm to large numbers of CD3 positive T cell conglomerates and compared the results to cell counts obtained manually by two independent observers. While especially for high cell counts, the manual counting showed a deviation of up to 400 cells/mm(2 (41% variation, algorithm-determined T cell numbers generally lay in between the manually observed cell numbers but with perfect reproducibility. CONCLUSION: In summary, we recommend our approach as an objective and robust strategy for quantifying immune cell densities in immunohistological sections which can be directly implemented into automated full slide image processing systems.
Institute of Scientific and Technical Information of China (English)
张凌; 常加峰; 张炜; 李颖颖; 钱金平; 徐国盛; 丁斯晔; 高伟; 吴振伟; 陈颖杰; 黄娟; 刘晓菊; 臧庆
2011-01-01
In this work, population coefficients of hydrogen＇s n = 3 excited state from the hydrogen collisional-radiative （CR） model, from the data file of DEGAS 2, are used to calculate the photon emissivity coefficients （PECs） of hydrogen Balmer-α （n = 3 →n = 2） （Hα）. The results are compared with the PECs from Atomic Data and Analysis Structure （ADAS） database, and a good agreement is found. A magnetic surface-averaged neutral density profile of typical double-null （DN） plasma in EAST is obtained by using FRANTIC, the 1.5-D fluid transport code. It is found that the sum of integral Dα and Hα emission intensity calculated via the neutral density agrees with the measured results obtained by using the absolutely calibrated multi-channel poloidal photodiode array systems viewing the lower divertor at the last closed flux surface （LCFS）. It is revealed that the typical magnetic surface-averaged neutral density at LCFS is about 3.5×10^16 m^-3 .
Semivariogram models for estimating fig fly population density throughout the year
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Mauricio Paulo Batistella Pasini
2014-07-01
Full Text Available The objective of this work was to select semivariogram models to estimate the population density of fig fly (Zaprionus indianus; Diptera: Drosophilidae throughout the year, using ordinary kriging. Nineteen monitoring sites were demarcated in an area of 8,200 m2, cropped with six fruit tree species: persimmon, citrus, fig, guava, apple, and peach. During a 24 month period, 106 weekly evaluations were done in these sites. The average number of adult fig flies captured weekly per trap, during each month, was subjected to the circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, hole effect, K-Bessel, J-Bessel, and stable semivariogram models, using ordinary kriging interpolation. The models with the best fit were selected by cross-validation. Each data set (months has a particular spatial dependence structure, which makes it necessary to define specific models of semivariograms in order to enhance the adjustment to the experimental semivariogram. Therefore, it was not possible to determine a standard semivariogram model; instead, six theoretical models were selected: circular, Gaussian, hole effect, K-Bessel, J-Bessel, and stable.
Measuring and Modeling Fault Density for Plume-Fault Encounter Probability Estimation
Energy Technology Data Exchange (ETDEWEB)
Jordan, P.D.; Oldenburg, C.M.; Nicot, J.-P.
2011-05-15
Emission of carbon dioxide from fossil-fueled power generation stations contributes to global climate change. Storage of this carbon dioxide within the pores of geologic strata (geologic carbon storage) is one approach to mitigating the climate change that would otherwise occur. The large storage volume needed for this mitigation requires injection into brine-filled pore space in reservoir strata overlain by cap rocks. One of the main concerns of storage in such rocks is leakage via faults. In the early stages of site selection, site-specific fault coverages are often not available. This necessitates a method for using available fault data to develop an estimate of the likelihood of injected carbon dioxide encountering and migrating up a fault, primarily due to buoyancy. Fault population statistics provide one of the main inputs to calculate the encounter probability. Previous fault population statistics work is shown to be applicable to areal fault density statistics. This result is applied to a case study in the southern portion of the San Joaquin Basin with the result that the probability of a carbon dioxide plume from a previously planned injection had a 3% chance of encountering a fully seal offsetting fault.
Park, Jung Hwan; Kim, Yong Chul; Koo, Ho Seok; Oh, Se Won; Kim, Suhnggwon; Chin, Ho Jun
2014-09-01
Stomach cancer is one of the most common cancers in Korea. The aim of this study was to identify the association between the prevalence of cancer, particularly stomach cancer, and the amount of 24-hr urine sodium excretion estimated from spot urine specimens. The study included 19,083 subjects who took part in the Korean National Health and Nutritional Examination Survey between 2009 and 2011. The total amount of urine sodium excreted in a 24-hr period was estimated by using two equations based on the values for spot urine sodium and creatinine. In subjects who had an estimated 24-hr urine sodium excretion of more than two standard deviations above the mean (group 2), the prevalence of stomach cancer was higher than in subjects with lower 24-hr sodium excretion (group 1). By using the Tanaka equation to estimate it, the prevalence of stomach cancer was 0.6% (114/18,331) in group 1, whereas it was 1.6% (9/568) in group 2 (P=0.006). By using the Korean equation, the prevalence was 0.6% (115/18,392) in group 1, and 1.6% in group 2 (8/507) (P=0.010). By using the Tanaka equation, breast cancer in women is more prevalent in group 2 (1.9%, 6/324) than group 1 (0.8%, 78/9,985, P=0.039). Higher salt intake, as defined by the estimated amount of 24-hr urine sodium excretion, is positively correlated with a higher prevalence of stomach or breast cancer in the Korean population.
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W. Chen
2015-11-01
Full Text Available Drought caused the most widespread damage in China, making up over 50 % of the total affected area nationwide in recent decades. In the paper, a Standardized Precipitation Index-based (SPI-based drought risk study is conducted using historical rainfall data of 19 weather stations in Shandong province, China. Kernel density based method is adopted to carry out the risk analysis. Comparison between the bivariate Gaussian kernel density estimation (GKDE and diffusion kernel density estimation (DKDE are carried out to analyze the effect of drought intensity and drought duration. The results show that DKDE is relatively more accurate without boundary-leakage. Combined with the GIS technique, the drought risk is presented which reveals the spatial and temporal variation of agricultural droughts for corn in Shandong. The estimation provides a different way to study the occurrence frequency and severity of drought risk from multiple perspectives.
Generalized Consistency for Kernel Density Estimation%密度核估计的广义相合性
Institute of Scientific and Technical Information of China (English)
王敏; 李开灿
2015-01-01
研究独立样本下密度核估计的相合性. 在 Peason-χ2距离和Kullback-Leibler距离意义下,提出密度核估计广义相合性的概念,并获得密度核估计的各种广义相合性.%In this paper, we discuss the consistency of the density kernel estimation under the independent sample. We give the definitions of generalized consistency for kernel density estimation and obtain several kinds of generalized consistency of kernel density estimation under thePeason-χ2distance and the Kullback-Leibler distance.
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Andrew J Hearn
Full Text Available The marbled cat Pardofelis marmorata is a poorly known wild cat that has a broad distribution across much of the Indomalayan ecorealm. This felid is thought to exist at low population densities throughout its range, yet no estimates of its abundance exist, hampering assessment of its conservation status. To investigate the distribution and abundance of marbled cats we conducted intensive, felid-focused camera trap surveys of eight forest areas and two oil palm plantations in Sabah, Malaysian Borneo. Study sites were broadly representative of the range of habitat types and the gradient of anthropogenic disturbance and fragmentation present in contemporary Sabah. We recorded marbled cats from all forest study areas apart from a small, relatively isolated forest patch, although photographic detection frequency varied greatly between areas. No marbled cats were recorded within the plantations, but a single individual was recorded walking along the forest/plantation boundary. We collected sufficient numbers of marbled cat photographic captures at three study areas to permit density estimation based on spatially explicit capture-recapture analyses. Estimates of population density from the primary, lowland Danum Valley Conservation Area and primary upland, Tawau Hills Park, were 19.57 (SD: 8.36 and 7.10 (SD: 1.90 individuals per 100 km2, respectively, and the selectively logged, lowland Tabin Wildlife Reserve yielded an estimated density of 10.45 (SD: 3.38 individuals per 100 km2. The low detection frequencies recorded in our other survey sites and from published studies elsewhere in its range, and the absence of previous density estimates for this felid suggest that our density estimates may be from the higher end of their abundance spectrum. We provide recommendations for future marbled cat survey approaches.
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Ehud Lebel
2014-01-01
Full Text Available Changes of bone during pregnancy and during lactation evaluated by bone mineral density (BMD may have implications for risk of osteoporosis and fractures. We studied BMD in women of differing ages, parity, and lactation histories immediately postpartum for BMD, T-scores, and Z-scores. Institutional Review Board approval was received. All women while still in hospital postpartum were asked to participate. BMD was performed by dual-energy X-ray absorptiometry (DXA machine at femoral neck (FN and lumbar spine (LS by a single technician. Of 132 participants, 73 (55.3% were ≤30 years; 27 (20.5% were primiparous; 36 (27.3% were grand multiparous; 35 (26.5% never breast fed. Mean FN T-scores and Z-scores were higher than respective mean LS scores, but all means were within the normal limits. Mean LS T-scores and Z-scores were highest in the grand multiparas. There were only 2 (1.5% outliers with low Z-scores. We conclude that, in a large cohort of Israeli women with BMD parameters assessed by DXA within two days postpartum, mean T-scores and Z-scores at both the LS and FN were within normal limits regardless of age (20–46 years, parity (1–13 viable births, and history of either no or prolonged months of lactation (up to 11.25 years.
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E. Carpenter
2014-06-01
Full Text Available Conservation and management of bats requires reliable and repeatable data regarding the size and patterns of variation in size of bat colonies. Counts and densities calculated via photography have proven more accurate and repeatable than visual counts and ocular estimates. Unfortunately, the potential of photography to investigate the size of a bat colony and roost density has rarely been explored. In the summer of 2006, a colony of Geoffroys Rousette Fruit Bat, Rousettus amplexicaudatus, was photo-documented in the Monfort Bat Cave, in the Island Garden City of Samal, Davao del Norte, Mindanao, Philippines. We selected 39 images to develop roost density estimates. Mean (+or-SE roosting density was 403+or-167.1 bats/m2 and 452.3+or-168.8 bats/m2 on the walls and ceiling of the cave, respectively; densities were not significantly different from each other (P=0.38. Based on these standardized data, we estimate that the initial 100m of the cave contained 883,526 bats. Ultimately, this photographic technique can be used to develop a statistical approach which involves repeatable estimates of colony size for Geoffroys Rousette Fruit Bats at Monfort Cave and will enhance ongoing monitoring activities throughout this species range.
Beckmann, Kerri R; Lynch, John W; Hiller, Janet E; Farshid, Gelareh; Houssami, Nehmat; Duffy, Stephen W; Roder, David M
2015-03-15
Debate about the extent of breast cancer over-diagnosis due to mammography screening has continued for over a decade, without consensus. Estimates range from 0 to 54%, but many studies have been criticized for having flawed methodology. In this study we used a novel study design to estimate over-diagnosis due to organised mammography screening in South Australia (SA). To estimate breast cancer incidence at and following screening we used a population-based, age-matched case-control design involving 4,931 breast cancer cases and 22,914 controls to obtain OR for yearly time intervals since women's last screening mammogram. The level of over-diagnosis was estimated by comparing the cumulative breast cancer incidence with and without screening. The former was derived by applying ORs for each time window to incidence rates in the absence of screening, and the latter, by projecting pre-screening incidence rates. Sensitivity analyses were undertaken to assess potential biases. Over-diagnosis was estimated to be 8% (95%CI 2-14%) and 14% (95%CI 8-19%) among SA women aged 45 to 85 years from 2006-2010, for invasive breast cancer and all breast cancer respectively. These estimates were robust when applying various sensitivity analyses, except for adjustment for potential confounding assuming higher risk among screened than non-screened women, which reduced levels of over-diagnosis to 1% (95%CI 5-7%) and 8% (95%CI 2-14%) respectively when incidence rates for screening participants were adjusted by 10%. Our results indicate that the level of over-diagnosis due to mammography screening is modest and considerably lower than many previous estimates, including others for Australia.
An SV-GMR Needle Sensor-Based Estimation of Volume Density of Magnetic Fluid inside Human Body
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C. P. Gooneratne
2008-01-01
Full Text Available A spin-valve giant magneto-resistive (SV-GMR sensor of needle-type configuration is reported to estimate the volume density of magnetic fluid inside human body. The magnetic fluid is usually injected into human body to kill cancerous cell using hyperthermia-based treatment. To control the heat treatment, a good knowledge of temperature is very much essential. The SV-GMR-based needle-type sensor is used to measure the magnetic flux density of the magnetic fluid inside the human body from which the temperature is estimated. The needle-type sensor provides a semi-invasive approach of temperature determination.
Karanth, K.Ullas; Chundawat, Raghunandan S.; Nichols, James D.; Kumar, N. Samba
2004-01-01
Tropical dry-deciduous forests comprise more than 45% of the tiger (Panthera tigris) habitat in India. However, in the absence of rigorously derived estimates of ecological densities of tigers in dry forests, critical baseline data for managing tiger populations are lacking. In this study tiger densities were estimated using photographic capture–recapture sampling in the dry forests of Panna Tiger Reserve in Central India. Over a 45-day survey period, 60 camera trap sites were sampled in a well-protected part of the 542-km2 reserve during 2002. A total sampling effort of 914 camera-trap-days yielded photo-captures of 11 individual tigers over 15 sampling occasions that effectively covered a 418-km2 area. The closed capture–recapture model Mh, which incorporates individual heterogeneity in capture probabilities, fitted these photographic capture history data well. The estimated capture probability/sample, p̂= 0.04, resulted in an estimated tiger population size and standard error (N̂(SÊN̂)) of 29 (9.65), and a density (D̂(SÊD̂)) of 6.94 (3.23) tigers/100 km2. The estimated tiger density matched predictions based on prey abundance. Our results suggest that, if managed appropriately, the available dry forest habitat in India has the potential to support a population size of about 9000 wild tigers.
Trolle, M.; Kery, M.
2003-01-01
Neotropical felids such as the ocelot (Leopardus pardalis) are secretive, and it is difficult to estimate their populations using conventional methods such as radiotelemetry or sign surveys. We show that recognition of individual ocelots from camera-trapping photographs is possible, and we use camera-trapping results combined with closed population capture-recapture models to estimate density of ocelots in the Brazilian Pantanal. We estimated the area from which animals were camera trapped at 17.71 km2. A model with constant capture probability yielded an estimate of 10 independent ocelots in our study area, which translates to a density of 2.82 independent individuals for every 5 km2 (SE 1.00).
Rosso, Aldana; Lång, Kristina; Petersson, Ingemar F; Zackrisson, Sophia
2015-10-01
In this study, we investigate which factors affect the false positive fraction (FPF) for digital breast tomosynthesis (DBT) compared to digital mammography (DM) in a screening population by using classification and regression trees (C&RT) and binary marginal generalized linear models. The data was obtained from the Malmö Breast Tomosynthesis Screening Trial, which aimed to compare the performance of DBT to DM in breast cancer screening. By using data from the first half of the study population (7500 women), a tree with the recall probability for different groups was calculated. The effect of age and breast density on the FPF was estimated using a binary marginal generalized linear model. Our results show that breast density and breast cancer were the main factors influencing recall. The FPF is mainly affected by breast density and increases with breast density for DBT and DM. In conclusion, the results obtained with C&RT are easy to interpret and similar to those obtained using binary marginal generalized linear models. The FPF is approximately 40% higher for DBT compared to DM for all breast density categories.
Oyang, Yen-Jen; Hwang, Shien-Ching; Ou, Yu-Yen; Chen, Chien-Yu; Chen, Zhi-Wei
2005-01-01
This paper presents a novel learning algorithm for efficient construction of the radial basis function (RBF) networks that can deliver the same level of accuracy as the support vector machines (SVMs) in data classification applications. The proposed learning algorithm works by constructing one RBF subnetwork to approximate the probability density function of each class of objects in the training data set. With respect to algorithm design, the main distinction of the proposed learning algorithm is the novel kernel density estimation algorithm that features an average time complexity of O(n log n), where n is the number of samples in the training data set. One important advantage of the proposed learning algorithm, in comparison with the SVM, is that the proposed learning algorithm generally takes far less time to construct a data classifier with an optimized parameter setting. This feature is of significance for many contemporary applications, in particular, for those applications in which new objects are continuously added into an already large database. Another desirable feature of the proposed learning algorithm is that the RBF networks constructed are capable of carrying out data classification with more than two classes of objects in one single run. In other words, unlike with the SVM, there is no need to resort to mechanisms such as one-against-one or one-against-all for handling datasets with more than two classes of objects. The comparison with SVM is of particular interest, because it has been shown in a number of recent studies that SVM generally are able to deliver higher classification accuracy than the other existing data classification algorithms. As the proposed learning algorithm is instance-based, the data reduction issue is also addressed in this paper. One interesting observation in this regard is that, for all three data sets used in data reduction experiments, the number of training samples remaining after a naive data reduction mechanism is
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Marianne Sandin
2015-09-01
Full Text Available Protein translocation between organelles in the cell is an important process that regulates many cellular functions. However, organelles can rarely be isolated to purity so several methods have been developed to analyse the fractions obtained by density gradient centrifugation. We present an analysis of the distribution of proteins amongst organelles in the human breast cell line, MDA-MB-231 using two approaches: an isotopic labelling and a label-free approach.
SU-D-204-01: Dual-Energy Calibration for Breast Density Measurement Using Spectral Mammography
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Ding, H; Cho, H; Kumar, N; Sennung, D; Molloi, S [Department of Radiological Sciences, University of California, Irvine, CA (United States)
2015-06-15
Purpose: To investigate the feasibility of minimizing the systematic errors in dual-energy breast density quantification induced by the use of tissue-equivalent plastic phantoms as the calibration basis materials. Methods: Dual-energy calibration using tissue-equivalent plastic phantoms was performed on a spectral mammography system based on scanning multi-slit Si strip photon-counting detectors. The plastic phantom calibration used plastic water and adipose-equivalent phantoms as the basis materials, which have different x-ray attenuation properties compared to water and lipid in actual breast tissue. Two methods were used to convert the dual-energy decomposition measurements in plastic phantom thicknesses into true water and lipid basis. The first method was based entirely on the theoretical x-ray attenuation coefficients of the investigated materials in the mammographic energy range. The conversion matrix was determined from least-squares fitting of the target material using the reported attenuation coefficients of water and lipid. The second method was developed based on experimental calibrations, which measured the low-and high-energy signals of pure water and lipid of known thicknesses. A non-linear rational function was used to correlate the decomposed thicknesses to the known values, so that the conversion coefficients can be determined. Both methods were validated using independent measurements of water and lipid mixture phantoms. The correlation of the dual-energy decomposition measurements and the known values were studied with linear regression analysis. Results: There was an excellent linear correlation between the converted water thicknesses and the known values. The slopes of the linear fits were determined to be 0.63 and 1.03 for the simulation and experimental results, respectively. The non-linear fitting in the experimental approach reduced the root-mean-square (RMS) errors from approximately 3.4 mm to 1.5 mm. Conclusion: The results suggested
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Md Nabiul Islam Khan
Full Text Available In the Point-Centred Quarter Method (PCQM, the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1 and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having 'random', 'aggregated' and 'regular' spatial patterns plant populations and empirical ones.PCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3 show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition. If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N - 1/(π ∑ R2 but not 12N/(π ∑ R2, of PCQM2 is 4(8N - 1/(π ∑ R2 but not 28N/(π ∑ R2 and of PCQM3 is 4(12N - 1/(π ∑ R2 but not 44N/(π ∑ R2 as published.If the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process
Kernel Density Estimation, Kernel Methods, and Fast Learning in Large Data Sets.
Wang, Shitong; Wang, Jun; Chung, Fu-lai
2014-01-01
Kernel methods such as the standard support vector machine and support vector regression trainings take O(N(3)) time and O(N(2)) space complexities in their naïve implementations, where N is the training set size. It is thus computationally infeasible in applying them to large data sets, and a replacement of the naive method for finding the quadratic programming (QP) solutions is highly desirable. By observing that many kernel methods can be linked up with kernel density estimate (KDE) which can be efficiently implemented by some approximation techniques, a new learning method called fast KDE (FastKDE) is proposed to scale up kernel methods. It is based on establishing a connection between KDE and the QP problems formulated for kernel methods using an entropy-based integrated-squared-error criterion. As a result, FastKDE approximation methods can be applied to solve these QP problems. In this paper, the latest advance in fast data reduction via KDE is exploited. With just a simple sampling strategy, the resulted FastKDE method can be used to scale up various kernel methods with a theoretical guarantee that their performance does not degrade a lot. It has a time complexity of O(m(3)) where m is the number of the data points sampled from the training set. Experiments on different benchmarking data sets demonstrate that the proposed method has comparable performance with the state-of-art method and it is effective for a wide range of kernel methods to achieve fast learning in large data sets.
Hall, S. A.; Burke, I.C.; Box, D. O.; Kaufmann, M. R.; Stoker, Jason M.
2005-01-01
The ponderosa pine forests of the Colorado Front Range, USA, have historically been subjected to wildfires. Recent large burns have increased public interest in fire behavior and effects, and scientific interest in the carbon consequences of wildfires. Remote sensing techniques can provide spatially explicit estimates of stand structural characteristics. Some of these characteristics can be used as inputs to fire behavior models, increasing our understanding of the effect of fuels on fire behavior. Others provide estimates of carbon stocks, allowing us to quantify the carbon consequences of fire. Our objective was to use discrete-return lidar to estimate such variables, including stand height, total aboveground biomass, foliage biomass, basal area, tree density, canopy base height and canopy bulk density. We developed 39 metrics from the lidar data, and used them in limited combinations in regression models, which we fit to field estimates of the stand structural variables. We used an information–theoretic approach to select the best model for each variable, and to select the subset of lidar metrics with most predictive potential. Observed versus predicted values of stand structure variables were highly correlated, with r2 ranging from 57% to 87%. The most parsimonious linear models for the biomass structure variables, based on a restricted dataset, explained between 35% and 58% of the observed variability. Our results provide us with useful estimates of stand height, total aboveground biomass, foliage biomass and basal area. There is promise for using this sensor to estimate tree density, canopy base height and canopy bulk density, though more research is needed to generate robust relationships. We selected 14 lidar metrics that showed the most potential as predictors of stand structure. We suggest that the focus of future lidar studies should broaden to include low density forests, particularly systems where the vertical structure of the canopy is important
Prado, Karl L; Kirsner, Steven M; Erice, Rolly C
2003-01-01
This paper describes an innovative method for correctly estimating the effective field size of tangential-breast fields. The method uses an "equivalent triangle" to verify intact breast tangential field monitor-unit settings calculated by a 3D planning system to within 2%. The effects on verification calculations of loss of full scatter due to beam oblique incidence, proximity to field boundaries, and reduced scattering volumes are handled properly. The methodology is validated by comparing calculations performed by the 3D planning system with the respective verification estimates. The accuracy of this technique is established for dose calculations both with and without heterogeneity corrections.
Pan, Guangming; Zhou, Wang
2010-01-01
A consistent kernel estimator of the limiting spectral distribution of general sample covariance matrices was introduced in Jing, Pan, Shao and Zhou (2010). The central limit theorem of the kernel estimator is proved in this paper.
Maadooliat, Mehdi
2015-10-21
This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.
Ghammraoui, Bahaa; Badal, Andreu; Popescu, Lucretiu M.
2016-04-01
Coherent scatter computed tomography (CSCT) is a reconstructive x-ray imaging technique that yields the spatially resolved coherent-scatter cross section of the investigated object revealing structural information of tissue under investigation. In the original CSCT proposals the reconstruction of images from coherently scattered x-rays is done at each scattering angle separately using analytic reconstruction. In this work we develop a maximum likelihood estimation of scatter components algorithm (ML-ESCA) that iteratively reconstructs images using a few material component basis functions from coherent scatter projection data. The proposed algorithm combines the measured scatter data at different angles into one reconstruction equation with only a few component images. Also, it accounts for data acquisition statistics and physics, modeling effects such as polychromatic energy spectrum and detector response function. We test the algorithm with simulated projection data obtained with a pencil beam setup using a new version of MC-GPU code, a Graphical Processing Unit version of PENELOPE Monte Carlo particle transport simulation code, that incorporates an improved model of x-ray coherent scattering using experimentally measured molecular interference functions. The results obtained for breast imaging phantoms using adipose and glandular tissue cross sections show that the new algorithm can separate imaging data into basic adipose and water components at radiation doses comparable with Breast Computed Tomography. Simulation results also show the potential for imaging microcalcifications. Overall, the component images obtained with ML-ESCA algorithm have a less noisy appearance than the images obtained with the conventional filtered back projection algorithm for each individual scattering angle. An optimization study for x-ray energy range selection for breast CSCT is also presented.
Ghammraoui, Bahaa; Badal, Andreu; Popescu, Lucretiu M
2016-04-21
Coherent scatter computed tomography (CSCT) is a reconstructive x-ray imaging technique that yields the spatially resolved coherent-scatter cross section of the investigated object revealing structural information of tissue under investigation. In the original CSCT proposals the reconstruction of images from coherently scattered x-rays is done at each scattering angle separately using analytic reconstruction. In this work we develop a maximum likelihood estimation of scatter components algorithm (ML-ESCA) that iteratively reconstructs images using a few material component basis functions from coherent scatter projection data. The proposed algorithm combines the measured scatter data at different angles into one reconstruction equation with only a few component images. Also, it accounts for data acquisition statistics and physics, modeling effects such as polychromatic energy spectrum and detector response function. We test the algorithm with simulated projection data obtained with a pencil beam setup using a new version of MC-GPU code, a Graphical Processing Unit version of PENELOPE Monte Carlo particle transport simulation code, that incorporates an improved model of x-ray coherent scattering using experimentally measured molecular interference functions. The results obtained for breast imaging phantoms using adipose and glandular tissue cross sections show that the new algorithm can separate imaging data into basic adipose and water components at radiation doses comparable with Breast Computed Tomography. Simulation results also show the potential for imaging microcalcifications. Overall, the component images obtained with ML-ESCA algorithm have a less noisy appearance than the images obtained with the conventional filtered back projection algorithm for each individual scattering angle. An optimization study for x-ray energy range selection for breast CSCT is also presented.
Plug-in error bounds for a mixing density estimate in $R^d,$ and for its derivatives
Yatracos, Yannis G.
2015-01-01
A mixture density, $f_p,$ is estimable in $R^d, \\ d \\ge 1,$ but an estimate for the mixing density, $p,$ is usually obtained only when $d$ is unity; $h$ is the mixture's kernel. When $f_p$'s estimate has form $f_{\\hat p_n}$ and $p$ is $\\tilde q$-smooth, vanishing outside a compact in $R^d,$ plug-in upper bounds are obtained herein for the $L_u$-error (and risk)of $\\hat p_n$ and its derivatives; $d \\ge 1, 1 \\le u \\le \\infty.$ The bounds depend on $f_{\\hat p_n}$'s $L_u$-error (or risk), $h$'s F...
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Zhengyu eJiang
2012-12-01
Full Text Available Recent high-throughput transcript discoveries have yielded a growing recognition of long intergenic non-coding RNAs (lincRNAs, a class of arbitrarily defined transcripts (>200 nt that are primarily produced from the intergenic space. LincRNAs have been increasingly acknowledged for their expressional dynamics and likely functional associations with cancers. However, differential gene dosage of lincRNA genes between cancer genomes is less studied. By using the high-density Human Omni5-Quad BeadChips (Illumina, we investigated genomic copy number aberrations in a set of seven tumor-normal paired primary human mammary epithelial cells (HMECs established from patients with invasive ductal carcinoma. This Beadchip platform includes a total of 2,435,915 SNP loci dispersed at an average interval of ~700 nt throughout the intergenic region of the human genome. We mapped annotated or putative lincRNA genes to a subset of 332,539 SNP loci, which were included in our analysis for lincRNA-associated copy number variations (CNV. We have identified 122 lincRNAs, which were affected by somatic CNV with overlapped aberrations ranging from 0.14% to 100% in length. LincRNA-associated aberrations were detected predominantly with copy number losses and preferential clustering to the ends of chromosomes. Interestingly, lincRNA genes appear to be much less susceptible to CNV in comparison to both protein-coding and intergenic regions (CNV affected segments in percentage: 1.8%, 37.5% and 60.6%, respectively. In summary, our study established a novel approach utilizing high-resolution SNP array to identify lincRNA candidates, which could functionally link to tumorigenesis, and provide new strategies for the diagnosis and treatment of breast cancer.
Energy Technology Data Exchange (ETDEWEB)
Pires, L.A. [Laboratório de Metabolismo de Lípides, Instituto do Coração, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Departamento de Ginecologia, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Hegg, R. [Departamento de Ginecologia, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Freitas, F.R.; Tavares, E.R.; Almeida, C.P. [Laboratório de Metabolismo de Lípides, Instituto do Coração, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Baracat, E.C. [Departamento de Ginecologia, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Maranhão, R.C. [Laboratório de Metabolismo de Lípides, Instituto do Coração, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, SP (Brazil)
2012-05-04
Low-density lipoprotein (LDL) receptors are overexpressed in most neoplastic cell lines and provide a mechanism for the internalization and concentration of drug-laden nanoemulsions that bind to these receptors. The aim of the present study was to determine whether the administration of standard chemotherapeutic schemes can alter the expression of LDL and LDL receptor-related protein 1 (LRP-1) receptors in breast carcinoma. Fragments of tumoral and normal breast tissue from 16 consecutive volunteer women with breast cancer in stage II or III were obtained from biopsies before the beginning of neoadjuvant chemotherapy and after chemotherapy, from fragments excised during mastectomy. Tissues were analyzed by immunohistochemistry for both receptors. Because complete response to treatment was achieved in 4 patients, only the tumors from 12 were analyzed. Before chemotherapy, there was overexpression of LDL receptor in the tumoral tissue compared to normal breast tissue in 8 of these patients. LRP-1 receptor overexpression was observed in tumors of 4 patients. After chemotherapy, expression of both receptors decreased in the tumors of 6 patients, increased in 4 and was unchanged in 2. Nonetheless, even when chemotherapy reduced receptors expression, the expression was still above normal. The fact that chemotherapy does not impair LDL receptors expression supports the use of drug carrier systems that target neoplastic cells by the LDL receptor endocytic pathway in patients on conventional chemotherapy.
Freer, Phoebe E; Slanetz, Priscilla J; Haas, Jennifer S; Tung, Nadine M; Hughes, Kevin S; Armstrong, Katrina; Semine, A Alan; Troyan, Susan L; Birdwell, Robyn L
2015-09-01
Stemming from breast density notification legislation in Massachusetts effective 2015, we sought to develop a collaborative evidence-based approach to density notification that could be used by practitioners across the state. Our goal was to develop an evidence-based consensus management algorithm to help patients and health care providers follow best practices to implement a coordinated, evidence-based, cost-effective, sustainable practice and to standardize care in recommendations for supplemental screening. We formed the Massachusetts Breast Risk Education and Assessment Task Force (MA-BREAST) a multi-institutional, multi-disciplinary panel of expert radiologists, surgeons, primary care physicians, and oncologists to develop a collaborative approach to density notification legislation. Using evidence-based data from the Institute for Clinical and Economic Review, the Cochrane review, National Comprehensive Cancer Network guidelines, American Cancer Society recommendations, and American College of Radiology appropriateness criteria, the group collaboratively developed an evidence-based best-practices algorithm. The expert consensus algorithm uses breast density as one element in the risk stratification to determine the need for supplemental screening. Women with dense breasts and otherwise low risk (20% lifetime) should consider supplemental screening MRI in addition to routine mammography regardless of breast density. We report the development of the multi-disciplinary collaborative approach to density notification. We propose a risk stratification algorithm to assess personal level of risk to determine the need for supplemental screening for an individual woman.
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Park Jinho
2012-06-01
Full Text Available Abstract Background Myocardial ischemia can be developed into more serious diseases. Early Detection of the ischemic syndrome in electrocardiogram (ECG more accurately and automatically can prevent it from developing into a catastrophic disease. To this end, we propose a new method, which employs wavelets and simple feature selection. Methods For training and testing, the European ST-T database is used, which is comprised of 367 ischemic ST episodes in 90 records. We first remove baseline wandering, and detect time positions of QRS complexes by a method based on the discrete wavelet transform. Next, for each heart beat, we extract three features which can be used for differentiating ST episodes from normal: 1 the area between QRS offset and T-peak points, 2 the normalized and signed sum from QRS offset to effective zero voltage point, and 3 the slope from QRS onset to offset point. We average the feature values for successive five beats to reduce effects of outliers. Finally we apply classifiers to those features. Results We evaluated the algorithm by kernel density estimation (KDE and support vector machine (SVM methods. Sensitivity and specificity for KDE were 0.939 and 0.912, respectively. The KDE classifier detects 349 ischemic ST episodes out of total 367 ST episodes. Sensitivity and specificity of SVM were 0.941 and 0.923, respectively. The SVM classifier detects 355 ischemic ST episodes. Conclusions We proposed a new method for detecting ischemia in ECG. It contains signal processing techniques of removing baseline wandering and detecting time positions of QRS complexes by discrete wavelet transform, and feature extraction from morphology of ECG waveforms explicitly. It was shown that the number of selected features were sufficient to discriminate ischemic ST episodes from the normal ones. We also showed how the proposed KDE classifier can automatically select kernel bandwidths, meaning that the algorithm does not require any numerical
Soto, Julia Bellver; Ruiz, María-José; Manyes, Lara; Juan-García, Ana
2016-01-01
The purposes of this review are to study potential biomarkers of exposure for ochratoxin A (OTA) in biological fluids (blood, urine and breast milk) for the period 2005-14, calculate the estimated daily intake (EDI) of OTA by using database consumption for the Spanish population, and, finally, to correlate OTA levels detected in blood and EDI values calculated from food products. The values of OTA detected in potential biomarkers of exposure for blood, breast milk and urine ranged from 0.15 to 18.0, from 0.002 to 13.1, and from 0.013 to 0.2 ng ml(-1), respectively. The calculated EDI for OTA in plasma ranged from 0.15 to 26 ng kg(-1) bw day(-1), higher than that obtained in urine (0.017-0.4 ng kg(-1) bw day(-1)). All these values are correlated with the range of EDI for OTA calculated from food products: 0.0001-25.2 ng kg(-1) bw day(-1).
Calabia, Andres; Jin, Shuanggen
2017-02-01
The thermospheric mass density variations and the thermosphere-ionosphere coupling during geomagnetic storms are not clear due to lack of observables and large uncertainty in the models. Although accelerometers on-board Low-Orbit-Earth (LEO) satellites can measure non-gravitational accelerations and derive thermospheric mass density variations with unprecedented details, their measurements are not always available (e.g., for the March 2013 geomagnetic storm). In order to cover accelerometer data gaps of Gravity Recovery and Climate Experiment (GRACE), we estimate thermospheric mass densities from numerical derivation of GRACE determined precise orbit ephemeris (POE) for the period 2011-2016. Our results show good correlation with accelerometer-based mass densities, and a better estimation than the NRLMSISE00 empirical model. Furthermore, we statistically analyze the differences to accelerometer-based densities, and study the March 2013 geomagnetic storm response. The thermospheric density enhancements at the polar regions on 17 March 2013 are clearly represented by POE-based measurements. Although our results show density variations better correlate with Dst and k-derived geomagnetic indices, the auroral electroject activity index AE as well as the merging electric field Em picture better agreement at high latitude for the March 2013 geomagnetic storm. On the other side, low-latitude variations are better represented with the Dst index. With the increasing resolution and accuracy of Precise Orbit Determination (POD) products and LEO satellites, the straightforward technique of determining non-gravitational accelerations and thermospheric mass densities through numerical differentiation of POE promises potentially good applications for the upper atmosphere research community.
De Marco, Stefano
2011-01-01
We study smoothness of densities for the solutions of SDEs whose coefficients are smooth and nondegenerate only on an open domain $D$. We prove that a smooth density exists on $D$ and give upper bounds for this density. Under some additional conditions (mainly dealing with the growth of the coefficients and their derivatives), we formulate upper bounds that are suitable to obtain asymptotic estimates of the density for large values of the state variable ("tail" estimates). These results specify and extend some results by Kusuoka and Stroock [J. Fac. Sci. Univ. Tokyo Sect. IA Math. 32 (1985) 1--76], but our approach is substantially different and based on a technique to estimate the Fourier transform inspired from Fournier [Electron. J. Probab. 13 (2008) 135--156] and Bally [Integration by parts formula for locally smooth laws and applications to equations with jumps I (2007) The Royal Swedish Academy of Sciences]. This study is motivated by existing models for financial securities which rely on SDEs with non-...
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Urrutia Jackie D.
2016-01-01
Full Text Available Breast cancer is one of the leading causes of death in the Philippines. One out of four who are diagnosed with breast cancer die within the first five years, and no less than 40 percent die within 10 years and it has continous rise as time passes by. Therefore, it is very important to know the factors that can help for the survival rate of the patients. The purpose of this study is to identify the best possible treatment or combination of treatments. The researchers considered four independent variables namely: Completed Surgery, Completed Chemotherapy, Completed Hormonotherapy and Completed Radiotherapy. The researchers limit this study for only 160 patients with stage 2 and 135 with stage 3 for a total of 295 patients considering the data gathered from three hospitals from Metro Manila. The names of the hospitals were not declared due to confidentiality of data. In identifying the best treatment or combination of treatments, odds, probabilities and odds ratios of patients, Logistic Regression Analysis was used.
Després-Einspenner, Marie-Lyne; Howe, Eric J; Drapeau, Pierre; Kühl, Hjalmar S
2017-03-07
Empirical validations of survey methods for estimating animal densities are rare, despite the fact that only an application to a population of known density can demonstrate their reliability under field conditions and constraints. Here, we present a field validation of camera trapping in combination with spatially explicit capture-recapture (SECR) methods for enumerating chimpanzee populations. We used 83 camera traps to sample a habituated community of western chimpanzees (Pan troglodytes verus) of known community and territory size in Taï National Park, Ivory Coast, and estimated community size and density using spatially explicit capture-recapture models. We aimed to: (1) validate camera trapping as a means to collect capture-recapture data for chimpanzees; (2) validate SECR methods to estimate chimpanzee density from camera trap data; (3) compare the efficacy of targeting locations frequently visited by chimpanzees versus deploying cameras according to a systematic design; (4) evaluate the performance of SECR estimators with reduced sampling effort; and (5) identify sources of heterogeneity in detection probabilities. Ten months of camera trapping provided abundant capture-recapture data. All weaned individuals were detected, most of them multiple times, at both an array of targeted locations, and a systematic grid of cameras positioned randomly within the study area, though detection probabilities were higher at targeted locations. SECR abundance estimates were accurate and precise, and analyses of subsets of the data indicated that the majority of individuals in a community could be detected with as few as five traps deployed within their territory. Our results highlight the potential of camera trapping for cost-effective monitoring of chimpanzee populations.
Energy Technology Data Exchange (ETDEWEB)
Motas Guzmàn, Miguel [Área de Toxicología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia (Spain); Clementini, Chiara [University of Siena, Department of Physical Sciences, Earth and Environment, Via Mattioli, 4, 53100 Siena (Italy); Pérez-Cárceles, Maria Dolores; Jiménez Rejón, Sandra [Department of Legal Medicine, School of Medicine, University of Murcia & Instituto Murciano de Investigacion Biomedica (IMIB), (IMIB-VIRGEN DE LA ARRIXACA), Murcia (Spain); Cascone, Aurora; Martellini, Tania [Department of Chemistry “Ugo Schiff”, via della Lastruccia 3, 50019 Sesto Fiorentino, Firenze (Italy); Guerranti, Cristiana [University of Siena, Department of Physical Sciences, Earth and Environment, Via Mattioli, 4, 53100 Siena (Italy); Bioscience Research Center, Via Aurelia Vecchia 32, 58015 Orbetello, GR (Italy); Cincinelli, Alessandra, E-mail: acincinelli@unifi.it [Department of Chemistry “Ugo Schiff”, via della Lastruccia 3, 50019 Sesto Fiorentino, Firenze (Italy)
2016-02-15
Human milk samples were collected from 67 mothers in 2014 at a Primary Care Centre in Murcia (Spain) and analyzed for perfluorinated carboxylic acids (PFCAs). Concentrations measured for perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA) and perfluorododecanoic acid (PFDoDA) ranged from < LOQ (< 10 ng/L) to 397 ng/L with a mean concentration of 66 ± 68 ng/L and a median of 29 ng/L. The presence of these compounds was revealed in 50 samples out of 67 analyzed. Influence of number of pregnancies and food habits on PFCAs concentrations was also investigated. Statistically significant differences in PFCA levels were found when the women were divided into maternal age classes and into the categories primiparae and multiparae. A greater transfer of PFC during breastfeeding by primiparous was evidenced and thus a higher exposure to these contaminants for the first child. Moreover, it was possible to hypothesize that the content of PFCs is in general correlated to the eating habits of donors and, in particular, with the fish consumption. Finally, PFOA daily intakes and risk index (RI) were estimated for the first six months of life and we found that ingestion rates of PFOA did not exceed the tolerable daily intake (TDI) recommended by the European Food Safety Authority (EFSA). - Graphical abstract: Figure SI 1. Concentrations (ng/L) of PFCs recovered in 67 samples of human breast milk. - Highlights: • Perfluorinated carboxylic acids were analyzed in a set of 67 breast milk samples collected from Spanish women. • PFOA appeared as the major contributor to the total perfluorinated carboxylic acids. • PFOA concentrations were significantly higher in milk of primiparous participants. • PFOA daily intake and risk index were estimated for the firsts six month of life.
Analysis of the Influence of Plot Size and LiDAR Density on Forest Structure Attribute Estimates
Luis A. Ruiz; Txomin Hermosilla; Francisco Mauro; Miguel Godino
2014-01-01
Licencia Creative Commons: Attribution 3.0 Unported (CC BY 3.0) This paper assesses the combined effect of field plot size and LiDAR density on the estimation of four forest structure attributes: volume, total biomass, basal area and canopy cover. A total of 21 different plot sizes were considered, obtained by decreasing the field measured plot radius value from 25 to 5 m with regular intervals of 1 m. LiDAR data densities were simulated by randomly removing LiDAR pulses until ...
Minh, David D L; Vaikuntanathan, Suriyanarayanan
2011-01-21
The nonequilibrium fluctuation theorems have paved the way for estimating equilibrium thermodynamic properties, such as free energy differences, using trajectories from driven nonequilibrium processes. While many statistical estimators may be derived from these identities, some are more efficient than others. It has recently been suggested that trajectories sampled using a particular time-dependent protocol for perturbing the Hamiltonian may be analyzed with another one. Choosing an analysis protocol based on the nonequilibrium density was empirically demonstrated to reduce the variance and bias of free energy estimates. Here, we present an alternate mathematical formalism for protocol postprocessing based on the Feynmac-Kac theorem. The estimator that results from this formalism is demonstrated on a few low-dimensional model systems. It is found to have reduced bias compared to both the standard form of Jarzynski's equality and the previous protocol postprocessing formalism.
Baghi, Quentin; Bergé, Joël; Christophe, Bruno; Touboul, Pierre; Rodrigues, Manuel
2016-01-01
We present a Gaussian regression method for time series with missing data and stationary residuals of unknown power spectral density (PSD). The missing data are efficiently estimated by their conditional expectation as in universal Kriging, based on the circulant approximation of the complete data covariance. After initialization with an autoregessive fit of the noise, a few iterations of estimation/reconstruction steps are performed until convergence of the regression and PSD estimates, in a way similar to the expectation-conditional-maximization algorithm. The estimation can be performed for an arbitrary PSD provided that it is sufficiently smooth. The algorithm is developed in the framework of the MICROSCOPE space mission whose goal is to test the weak equivalence principle (WEP) with a precision of $10^{-15}$. We show by numerical simulations that the developed method allows us to meet three major requirements: to maintain the targeted precision of the WEP test in spite of the loss of data, to calculate a...
Haisma, H; Coward, WA; Albernaz, E; Barros, A; Victora, CG; Wright, A; Visser, GH
2005-01-01
Objective: Firstly, to compare food, and macronutrient intake as obtained from a single 24-h recall and a frequency questionnaire (FQ) covering a 14-day period in breast-fed infants aged 4 months of age. Secondly, nonbreast milk water intake (NB-WI, ml/day) was used as an estimation of energy and ma
Jaffé, Rodolfo; Dietemann, Vincent; Allsopp, Mike H; Costa, Cecilia; Crewe, Robin M; Dall'olio, Raffaele; DE LA Rúa, Pilar; El-Niweiri, Mogbel A A; Fries, Ingemar; Kezic, Nikola; Meusel, Michael S; Paxton, Robert J; Shaibi, Taher; Stolle, Eckart; Moritz, Robin F A
2010-04-01
Although pollinator declines are a global biodiversity threat, the demography of the western honeybee (Apis mellifera) has not been considered by conservationists because it is biased by the activity of beekeepers. To fill this gap in pollinator decline censuses and to provide a broad picture of the current status of honeybees across their natural range, we used microsatellite genetic markers to estimate colony densities and genetic diversity at different locations in Europe, Africa, and central Asia that had different patterns of land use. Genetic diversity and colony densities were highest in South Africa and lowest in Northern Europe and were correlated with mean annual temperature. Confounding factors not related to climate, however, are also likely to influence genetic diversity and colony densities in honeybee populations. Land use showed a significantly negative influence over genetic diversity and the density of honeybee colonies over all sampling locations. In Europe honeybees sampled in nature reserves had genetic diversity and colony densities similar to those sampled in agricultural landscapes, which suggests that the former are not wild but may have come from managed hives. Other results also support this idea: putative wild bees were rare in our European samples, and the mean estimated density of honeybee colonies on the continent closely resembled the reported mean number of managed hives. Current densities of European honeybee populations are in the same range as those found in the adverse climatic conditions of the Kalahari and Saharan deserts, which suggests that beekeeping activities do not compensate for the loss of wild colonies. Our findings highlight the importance of reconsidering the conservation status of honeybees in Europe and of regarding beekeeping not only as a profitable business for producing honey, but also as an essential component of biodiversity conservation.
Jasinski, Michael F.; Crago, Richard
1994-01-01
Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.
Age-And tumor subtype-specific breast cancer risk estimates for CHEK2∗1100delC Carriers
M.K. Schmidt (Marjanka); F.B.L. Hogervorst (Frans); R.R. van Hien (Richard); Cornelissen, S. (Sten); A. Broeks (Annegien); M.A. Adank (Muriel); Meijers, H. (Hanne); Q. Waisfisz (Quinten); A. Hollestelle (Antoinette); A.E.M. Schutte (Mieke); A.M.W. van den Ouweland (Ans); M.J. Hooning (Maartje); I.L. Andrulis (Irene); H. Anton-Culver (Hoda); Antonenkova, N.N. (Natalia N.); A.C. Antoniou (Antonis C.); Arndt, V. (Volker); M. Bermisheva (Marina); N.V. Bogdanova (Natalia); M.K. Bolla (Manjeet K.); H. Brauch (Hiltrud); H. Brenner (Hermann); T. Brüning (Thomas); B. Burwinkel (Barbara); J. Chang-Claude (Jenny); G. Chenevix-Trench (Georgia); F.J. Couch (Fergus); A. Cox (Angela); S.S. Cross (Simon); K. Czene (Kamila); A.M. Dunning (Alison); P.A. Fasching (Peter); J.D. Figueroa (Jonine); O. Fletcher (Olivia); H. Flyger (Henrik); Galle, E. (Eva); M. García-Closas (Montserrat); Giles, G.G. (Graham G.); L. Haeberle (Lothar); P. Hall (Per); P. Hillemanns (Peter); J.L. Hopper (John); A. Jakubowska (Anna); E.M. John (Esther); M. Jones (Michael); E.K. Khusnutdinova (Elza); J.A. Knight (Julia); V-M. Kosma (Veli-Matti); V. Kristensen (Vessela); A. Lee (Andrew); A. Lindblom (Annika); J. Lubinski (Jan); A. Mannermaa (Arto); S. Margolin (Sara); A. Meindl (Alfons); R.L. Milne (Roger); Muranen, T.A. (Taru A.); Newcomb, P.A. (Polly A.); K. Offit (Kenneth); T.-W. Park-Simon; J. Peto (Julian); P.D.P. Pharoah (Paul); M. Robson (Mark); Rudolph, A. (Anja); E.J. Sawyer (Elinor); R.K. Schmutzler (Rita); C.M. Seynaeve (Caroline); Soens, J. (Julie); M.C. Southey (Melissa); A.B. Spurdle (Amanda); H. Surowy (Harald); A.J. Swerdlow (Anthony ); Tollenaar, R.A.E.M. (Rob A.E.M.); I.P. Tomlinson (Ian); Trentham-Dietz, A. (Amy); C. Vachon (Celine); Wang, Q. (Qin); A.S. Whittemore (Alice); A. Ziogas (Argyrios); L. van der Kolk (Lizet); H. Nevanlinna (Heli); T. Dörk (Thilo); S.E. Bojesen (Stig); D.F. Easton (Douglas F.)
2016-01-01
textabstractPurpose CHEK2∗1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tu
Age- and Tumor Subtype-Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers
DEFF Research Database (Denmark)
Schmidt, Marjanka K; Hogervorst, Frans; van Hien, Richard;
2016-01-01
PURPOSE: CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subt...
Lapuerta, Magín; Rodríguez-Fernández, José; Armas, Octavio
2010-09-01
Biodiesel fuels (methyl or ethyl esters derived from vegetables oils and animal fats) are currently being used as a means to diminish the crude oil dependency and to limit the greenhouse gas emissions of the transportation sector. However, their physical properties are different from traditional fossil fuels, this making uncertain their effect on new, electronically controlled vehicles. Density is one of those properties, and its implications go even further. First, because governments are expected to boost the use of high-biodiesel content blends, but biodiesel fuels are denser than fossil ones. In consequence, their blending proportion is indirectly restricted in order not to exceed the maximum density limit established in fuel quality standards. Second, because an accurate knowledge of biodiesel density permits the estimation of other properties such as the Cetane Number, whose direct measurement is complex and presents low repeatability and low reproducibility. In this study we compile densities of methyl and ethyl esters published in literature, and proposed equations to convert them to 15 degrees C and to predict the biodiesel density based on its chain length and unsaturation degree. Both expressions were validated for a wide range of commercial biodiesel fuels. Using the latter, we define a term called Biodiesel Cetane Index, which predicts with high accuracy the Biodiesel Cetane Number. Finally, simple calculations prove that the introduction of high-biodiesel content blends in the fuel market would force the refineries to reduce the density of their fossil fuels.
Codis, Sandrine; Pichon, Christophe
2016-01-01
In order to quantify the error budget in the measured probability distribution functions of cell densities, the two-point statistics of cosmic densities in concentric spheres is investigated. Bias functions are introduced as the ratio of their two-point correlation function to the two-point correlation of the underlying dark matter distribution. They describe how cell densities are spatially correlated. They are computed here via the so-called large deviation principle in the quasi-linear regime. Their large-separation limit is presented and successfully compared to simulations for density and density slopes: this regime is shown to be rapidly reached allowing to get sub-percent precision for a wide range of densities and variances. The corresponding asymptotic limit provides an estimate of the cosmic variance of standard concentric cell statistics applied to finite surveys. More generally, no assumption on the separation is required for some specific moments of the two-point statistics, for instance when pre...
Canepa, Edward S.
2012-09-01
This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.
Kittisuwan, Pichid
2015-03-01
The application of image processing in industry has shown remarkable success over the last decade, for example, in security and telecommunication systems. The denoising of natural image corrupted by Gaussian noise is a classical problem in image processing. So, image denoising is an indispensable step during image processing. This paper is concerned with dual-tree complex wavelet-based image denoising using Bayesian techniques. One of the cruxes of the Bayesian image denoising algorithms is to estimate the statistical parameter of the image. Here, we employ maximum a posteriori (MAP) estimation to calculate local observed variance with generalized Gamma density prior for local observed variance and Laplacian or Gaussian distribution for noisy wavelet coefficients. Evidently, our selection of prior distribution is motivated by efficient and flexible properties of generalized Gamma density. The experimental results show that the proposed method yields good denoising results.
Independent component analysis of high-density electromyography in muscle force estimation.
Staudenmann, D.; Daffertshofer, A.; Kingma, I.; Stegeman, D.F.; Dieen, J.H. van
2007-01-01
Accurate force prediction from surface electromyography (EMG) forms an important methodological challenge in biomechanics and kinesiology. In a previous study (Staudenmann et al., 2006), we illustrated force estimates based on analyses lent from multivariate statistics. In particular, we showed the
Probability Density Estimation for Non-flat Functions%非平坦函数概率密度估计
Institute of Scientific and Technical Information of China (English)
汪洪桥; 蔡艳宁; 付光远; 王仕成
2016-01-01
Aiming at the probability density estimation problem for non-flat functions, this paper constructs a single slack factor multi-scale kernel support vector machine (SVM) probability density estimation model, by improving the form of constraint condition of the traditional SVM model and introducing the multi-scale kernel method. In the model, a single slack factor instead of two types of slack factors is used to control the learning error of SVM, which reduces the computational complexity of model. At the same time, by introducing the multi-scale kernel method, the model can well fit the functions with both the fiercely changed region and the flatly changed region. Through several probability density estimation experiments with typical non-flat functions, the results show that the single slack probability density estimation model has faster learning speed than the common SVM model. And compared with the single kernel method, the multi-scale kernel SVM probability density estimation model has better estimation precision.%针对非平坦函数的概率密度估计问题，通过改进支持向量机（support vector machine，SVM）概率密度估计模型约束条件的形式，并引入多尺度核方法，构建了一种单松弛因子多尺度核支持向量机概率密度估计模型。该模型采用合并的单个松弛因子来控制支持向量机的学习误差，减小了模型的计算复杂度；同时引入了多尺度核方法，使得模型既能适应函数剧烈变化的区域，也能适应平缓变化的区域。基于几种典型非平坦函数进行概率密度估计实验，结果证明，单松弛因子概率密度估计模型比常规支持向量机概率密度估计模型具有更快的学习速度；且相比于单核方法，多尺度核支持向量机概率密度估计模型具有更优的估计精度。
Jiménez-Donaire, M. J.; Bigiel, F.; Leroy, A. K.; Cormier, D.; Gallagher, M.; Usero, A.; Bolatto, A.; Colombo, D.; García-Burillo, S.; Hughes, A.; Kramer, C.; Krumholz, M. R.; Meier, D. S.; Murphy, E.; Pety, J.; Rosolowsky, E.; Schinnerer, E.; Schruba, A.; Tomičić, N.; Zschaechner, L.
2017-04-01
High critical density molecular lines like HCN (1-0) or HCO+ (1-0) represent our best tool to study currently star-forming, dense molecular gas at extragalactic distances. The optical depth of these lines is a key ingredient to estimate the effective density required to excite emission. However, constraints on this quantity are even scarcer in the literature than measurements of the high-density tracers themselves. Here, we combine new observations of HCN, HCO+ and HNC (1-0) and their optically thin isotopologues H13CN, H13CO+ and HN13C (1-0) to measure isotopologue line ratios. We use IRAM 30-m observations from the large programme EMPIRE and new Atacama Large Millimetre/submillimetre Array observations, which together target six nearby star-forming galaxies. Using spectral stacking techniques, we calculate or place strong upper limits on the HCN/H13CN, HCO+/H13CO+ and HNC/HN13C line ratios in the inner parts of these galaxies. Under simple assumptions, we use these to estimate the optical depths of HCN (1-0) and HCO+ (1-0) to be τ ∼ 2-11 in the active, inner regions of our targets. The critical densities are consequently lowered to values between 5 and 20 × 105 cm-3, 1 and 3 × 105 cm-3 and 9 × 104 cm-3 for HCN, HCO+ and HNC, respectively. We study the impact of having different beam-filling factors, η, on these estimates and find that the effective critical densities decrease by a factor of η _{12}/η _{13} τ_{12}. A comparison to existing work in NGC 5194 and NGC 253 shows the HCN/H13CN and HCO+/H13CO+ ratios in agreement with our measurements within the uncertainties. The same is true for studies in other environments such as the Galactic Centre or nuclear regions of active galactic nucleus dominated nearby galaxies.
Rivera-Milan, F. F.; Collazo, J.A.; Stahala, C.; Moore, W.J.; Davis, A.; Herring, G.; Steinkamp, M.; Pagliaro, R.; Thompson, J.L.; Bracey, W.
2005-01-01
Once abundant and widely distributed, the Bahama parrot (Amazona leucocephala bahamensis) currently inhabits only the Great Abaco and Great lnagua Islands of the Bahamas. In January 2003 and May 2002-2004, we conducted point-transect surveys (a type of distance sampling) to estimate density and population size and make recommendations for monitoring trends. Density ranged from 0.061 (SE = 0.013) to 0.085 (SE = 0.018) parrots/ha and population size ranged from 1,600 (SE = 354) to 2,386 (SE = 508) parrots when extrapolated to the 26,154 ha and 28,162 ha covered by surveys on Abaco in May 2002 and 2003, respectively. Density was 0.183 (SE = 0.049) and 0.153 (SE = 0.042) parrots/ha and population size was 5,344 (SE = 1,431) and 4,450 (SE = 1,435) parrots when extrapolated to the 29,174 ha covered by surveys on Inagua in May 2003 and 2004, respectively. Because parrot distribution was clumped, we would need to survey 213-882 points on Abaco and 258-1,659 points on Inagua to obtain a CV of 10-20% for estimated density. Cluster size and its variability and clumping increased in wintertime, making surveys imprecise and cost-ineffective. Surveys were reasonably precise and cost-effective in springtime, and we recommend conducting them when parrots are pairing and selecting nesting sites. Survey data should be collected yearly as part of an integrated monitoring strategy to estimate density and other key demographic parameters and improve our understanding of the ecological dynamics of these geographically isolated parrot populations at risk of extinction.
Estimation of the population density of the sweetpotato weevils on the Mariana Islands
Directory of Open Access Journals (Sweden)
Gadi V.P. Reddy
2012-05-01
Full Text Available The sweetpotato Ipomoea batatas L. (Convolvulaceae has been one of the most important foods for Pacific islanders for centuries. However, the yield levels have been declining in the recent past due to the presence of sweetpotato weevils Cylas formicarius (Fabricius (Coleoptera, Brentidae, Euscepes postfasciatus (Fairmaire and Daealus tuberosus (Zimmer man (Coleoptera, Curculionidae. Therefore, urgent management or eradication methods are sought in the Mariana Islands (Guam, Rota, Saipan, and Tinian. However, the management or eradication of these weevil pests requires accurate assessments of the target pest density. Currently, no advice is provided to growers on the best method for sampling sweetpotato for weevil pests, although pheromone-based traps or chemicals are being used. This study defines the results of field counts designed to adjust relative sampling techniques for three sweetpotato weevil pests by inspecting plants visually and at random in the field with an absolute measure of population density. Significant relationships were detected between the relative four sampling sites between the three weevil pests. In the dry and wet season, 90% and 35.5%, respectively, of population density of C. formicarius was noticed in Rota. This density of the population levels of this species is significantly lower in Saipan, Guam and Tinian. No incidence of E. postfasciatus and D. tuberosus was observed on Guam. However, E. postfasciatus is identified as the second most destructive pest in Rota, Tinian and Saipan in both the dry and wet seasons. Likewise, D. tuberosus is the third major pest as the recorded population density ranged from 12.5% to 2.5%. Also, it is evident from the sampling study that the population densities of all three weevils are significantly higher in the dry season than the wet season.
Energy Technology Data Exchange (ETDEWEB)
Tang, Robert Y., E-mail: rx-tang@laurentian.ca [Biomolecular Sciences Program, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada); Laamanen, Curtis, E-mail: cx-laamanen@laurentian.ca; McDonald, Nancy, E-mail: mcdnancye@gmail.com [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada); LeClair, Robert J., E-mail: rleclair@laurentian.ca [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6, Canada and Biomolecular Sciences Program, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada)
2014-05-15
Purpose: Develop a method to subtract fat tissue contributions to wide-angle x-ray scatter (WAXS) signals of breast biopsies in order to estimate the differential linear scattering coefficients μ{sub s} of fatless tissue. Cancerous and fibroglandular tissue can then be compared independent of fat content. In this work phantom materials with known compositions were used to test the efficacy of the WAXS subtraction model. Methods: Each sample 5 mm in diameter and 5 mm thick was interrogated by a 50 kV 2.7 mm diameter beam for 3 min. A 25 mm{sup 2} by 1 mm thick CdTe detector allowed measurements of a portion of the θ = 6° scattered field. A scatter technique provided means to estimate the incident spectrum N{sub 0}(E) needed in the calculations of μ{sub s}[x(E, θ)] where x is the momentum transfer argument. Values of μ{sup ¯}{sub s} for composite phantoms consisting of three plastic layers were estimated and compared to the values obtained via the sum μ{sup ¯}{sub s}{sup ∑}(x)=ν{sub 1}μ{sub s1}(x)+ν{sub 2}μ{sub s2}(x)+ν{sub 3}μ{sub s3}(x), where ν{sub i} is the fractional volume of the ith plastic component. Water, polystyrene, and a volume mixture of 0.6 water + 0.4 polystyrene labelled as fibphan were chosen to mimic cancer, fat, and fibroglandular tissue, respectively. A WAXS subtraction model was used to remove the polystyrene signal from tissue composite phantoms so that the μ{sub s} of water and fibphan could be estimated. Although the composite samples were layered, simulations were performed to test the models under nonlayered conditions. Results: The well known μ{sub s} signal of water was reproduced effectively between 0.5 < x < 1.6 nm{sup −1}. The μ{sup ¯}{sub s} obtained for the heterogeneous samples agreed with μ{sup ¯}{sub s}{sup ∑}. Polystyrene signals were subtracted successfully from composite phantoms. The simulations validated the usefulness of the WAXS models for nonlayered biopsies. Conclusions: The methodology to
Low-Density LiDAR and Optical Imagery for Biomass Estimation over Boreal Forest in Sweden
Directory of Open Access Journals (Sweden)
Iurii Shendryk
2014-05-01
Full Text Available Knowledge of the forest biomass and its change in time is crucial to understanding the carbon cycle and its interactions with climate change. LiDAR (Light Detection and Ranging technology, in this respect, has proven to be a valuable tool, providing reliable estimates of aboveground biomass (AGB. The overall goal of this study was to develop a method for assessing AGB using a synergy of low point density LiDAR-derived point cloud data and multi-spectral imagery in conifer-dominated forest in the southwest of Sweden. Different treetop detection algorithms were applied for forest inventory parameter extraction from a LiDAR-derived canopy height model. Estimation of AGB was based on the power functions derived from tree parameters measured in the field, while vegetation classification of a multi-spectral image (SPOT-5 was performed in order to account for dependences of AGB estimates on vegetation types. Linear regression confirmed good performance of a newly developed grid-based approach for biomass estimation (R2 = 0.80. Results showed AGB to vary from below 1 kg/m2 in very young forests to 94 kg/m2 in mature spruce forests, with RMSE of 4.7 kg/m2. These AGB estimates build a basis for further studies on carbon stocks as well as for monitoring this forest ecosystem in respect of disturbance and change in time. The methodology developed in this study can be easily adopted for assessing biomass of other conifer-dominated forests on the basis of low-density LiDAR and multispectral imagery. This methodology is hence of much wider applicability than biomass derivation based on expensive and currently still scarce high-density LiDAR data.
van Kuijk, Silvy M; García-Suikkanen, Carolina; Tello-Alvarado, Julio C; Vermeer, Jan; Hill, Catherine M
2015-01-01
We calculated the population density of the critically endangered Callicebus oenanthe in the Ojos de Agua Conservation Concession, a dry forest area in the department of San Martin, Peru. Results showed significant differences (p Agua an important cornerstone in the conservation of the species, because it is one of the largest protected areas where the species occurs.
Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods
Joshi, C.; Leeuw, de J.; Skidmore, A.K.; Duren, van I.C.; Oosten, van H.
2006-01-01
In recent years, a number of alternative methods have been proposed to predict forest canopy density from remotely sensed data. To date, however, it remains difficult to decide which method to use, since their relative performance has never been evaluated. In this study the performance of: (1) an ar
DEFF Research Database (Denmark)
Wellendorff, Jess; Lundgård, Keld Troen; Møgelhøj, Andreas
2012-01-01
A methodology for semiempirical density functional optimization, using regularization and cross-validation methods from machine learning, is developed. We demonstrate that such methods enable well-behaved exchange-correlation approximations in very flexible model spaces, thus avoiding the overfit...
Construction of New Electronic Density Functionals with Error Estimation Through Fitting
DEFF Research Database (Denmark)
Petzold, V.; Bligaard, T.; Jacobsen, K. W.
2012-01-01
We investigate the possibilities and limitations for the development of new electronic density functionals through large-scale fitting to databases of binding energies obtained experimentally or through high-quality calculations. We show that databases with up to a few hundred entries allow for up...
An estimate of the electron density in filaments of galaxies at z~0.1
Fraser-McKelvie, Amelia; Lazendic, Jasmina S
2011-01-01
Most of the baryons in the Universe are thought to be contained within filaments of galaxies, but as yet, no single study has published the observed properties of a large sample of known filaments to determine typical physical characteristics such as temperature and electron density. This paper presents a comprehensive large-scale search conducted for X-ray emission from a population of 41 bona fide filaments of galaxies to determine their X-ray flux and electron density. The sample is generated from Pimbblet et al.'s (2004) filament catalogue, which is in turn sourced from the 2 degree Field Galaxy Redshift Survey (2dFGRS). Since the filaments are expected to be very faint and of very low density, we used stacked ROSAT All-Sky Survey data. We detect a net surface brightness from our sample of filaments of (1.6 +/- 0.1) x 10^{-14} erg cm^{-2} s^{-1} arcmin^{-1} in the 0.9-1.3 keV energy band for 1 keV plasma, which implies an electron density of n_{e} = (4.7 +/- 0.2) x 10^{-4} h_{100}^{1/2} cm^{-3}. Finally, ...
Dynamics of photosynthetic photon flux density (PPFD) and estimates in coastal northern California
The seasonal trends and diurnal patterns of Photosynthetically Active Radiation (PAR) were investigated in the San Francisco Bay Area of Northern California from March through August in 2007 and 2008. During these periods, the daily values of PAR flux density (PFD), energy loading with PAR (PARE), a...
Using aerial surveys to estimate density and distribution of harbour porpoises in Dutch waters
Scheidat, M.; Verdaat, J.P.; Aarts, G.M.
2012-01-01
To investigate harbour porpoise density and distribution in Dutch waters, dedicated line transect distance sampling aerial surveys were conducted from May 2008 to March 2010. In total 10,557 km were covered on survey effort during 16 survey days in February to May, August, November and December. Usi
Sarangi, Bighnaraj; Aggarwal, Shankar G.; Sinha, Deepak; Gupta, Prabhat K.
2016-03-01
In this work, we have used a scanning mobility particle sizer (SMPS) and a quartz crystal microbalance (QCM) to estimate the effective density of aerosol particles. This approach is tested for aerosolized particles generated from the solution of standard materials of known density, i.e. ammonium sulfate (AS), ammonium nitrate (AN) and sodium chloride (SC), and also applied for ambient measurement in New Delhi. We also discuss uncertainty involved in the measurement. In this method, dried particles are introduced in to a differential mobility analyser (DMA), where size segregation is done based on particle electrical mobility. Downstream of the DMA, the aerosol stream is subdivided into two parts. One is sent to a condensation particle counter (CPC) to measure particle number concentration, whereas the other one is sent to the QCM to measure the particle mass concentration simultaneously. Based on particle volume derived from size distribution data of the SMPS and mass concentration data obtained from the QCM, the mean effective density (ρeff) with uncertainty of inorganic salt particles (for particle count mean diameter (CMD) over a size range 10-478 nm), i.e. AS, SC and AN, is estimated to be 1.76 ± 0.24, 2.08 ± 0.19 and 1.69 ± 0.28 g cm-3, values which are comparable with the material density (ρ) values, 1.77, 2.17 and 1.72 g cm-3, respectively. Using this technique, the percentage contribution of error in the measurement of effective density is calculated to be in the range of 9-17 %. Among the individual uncertainty components, repeatability of particle mass obtained by the QCM, the QCM crystal frequency, CPC counting efficiency, and the equivalence of CPC- and QCM-derived volume are the major contributors to the expanded uncertainty (at k = 2) in comparison to other components, e.g. diffusion correction, charge correction, etc. Effective density for ambient particles at the beginning of the winter period in New Delhi was measured to be 1.28 ± 0.12 g cm-3
DEFF Research Database (Denmark)
Lyng, Maria B.; Laenkholm, Anne-Vibeke; Pallisgaard, Niels
2007-01-01
BACKGROUND: Gene expression profiling is thought to be an important tool in determining treatment strategies for breast cancer patients. Tissues for such analysis may at a preoperative stage be obtained, by fine needle aspiration (FNA) allowing initiation of neoadjuvant treatment. To evaluate...... the extent of the genetic heterogeneity within primary breast carcinomas, we examined whether a gene expression profile obtained by FNA was representative of the tumor. METHODS: Tumors from 12 consecutive cases of early predominantly estrogen receptor positive (ER+) breast cancer patients undergoing primary...... by statistical analysis. High correlations between the gene profiles of tumor FNAs and tissue biopsies from the same patient were observed for all patients. A cluster analysis identified clustering of both the two FNAs and the tissue biopsy of the same 9 patients. CONCLUSION: The overall genetic heterogeneity...
Bone Density, Turnover, and Estimated Strength in Postmenopausal Women Treated With Odanacatib
DEFF Research Database (Denmark)
Brixen, Kim; Chapurlat, Roland; Cheung, Angela M;
2013-01-01
bone compartments and estimated strength at the hip and spine.Design:This was a randomized, double-blind, 2-year trial.Setting:The study was conducted at a private or institutional practice.Participants:Participants included 214 postmenopausal women with low areal BMD.Intervention:The intervention...... included odanacatib 50 mg or placebo weekly.Main Outcome Measures:Changes in areal BMD by dual-energy x-ray absorptiometry (primary end point, 1 year areal BMD change at lumbar spine), bone turnover markers, volumetric BMD by quantitative computed tomography (QCT), and bone strength estimated by finite......-formation marker procollagen I N-terminal peptide initially decreased with odanacatib but by 2 years did not differ from placebo. After 6 months, odanacatib-treated women had greater increases in trabecular volumetric BMD and estimated compressive strength at the spine and integral and trabecular volumetric BMD...
Directory of Open Access Journals (Sweden)
Jianlei Kong
2015-07-01
Full Text Available In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS, which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents.
Kong, Jianlei; Ding, Xiaokang; Liu, Jinhao; Yan, Lei; Wang, Jianli
2015-07-02
In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS), which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents.
Kong, Jianlei; Ding, Xiaokang; Liu, Jinhao; Yan, Lei; Wang, Jianli
2015-01-01
In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS), which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents. PMID:26147726
Rajamane, N. P.; Nataraja, M. C.; Jeyalakshmi, R.; Nithiyanantham, S.
2016-02-01
Geopolymer concrete is zero-Portland cement concrete containing alumino-silicate based inorganic polymer as binder. The polymer is obtained by chemical activation of alumina and silica bearing materials, blast furnace slag by highly alkaline solutions such as hydroxide and silicates of alkali metals. Sodium hydroxide solutions of different concentrations are commonly used in making GPC mixes. Often, it is seen that sodium hydroxide solution of very high concentration is diluted with water to obtain SHS of desired concentration. While doing so it was observed that the solute particles of NaOH in SHS tend to occupy lower volumes as the degree of dilution increases. This aspect is discussed in this paper. The observed phenomenon needs to be understood while formulating the GPC mixes since this influences considerably the relationship between concentration and density of SHS. This paper suggests an empirical formula to relate density of SHS directly to concentration expressed by w/w.
Estimation of 2-D and 3-D Fracture Densities from 1-D Data Experimental and Field Results
Institute of Scientific and Technical Information of China (English)
XU Jiandong; Robert D. JACOBI
2003-01-01
2-D and 3-D densities of fractures are commonly used in mining safety design, natural gas and oil productionin fractured reservoirs, and the characterization of subsurface flow and transportation systems in fractured rocks. However,many field data sets are collected in 1-D frequency (f) (e.g., scanlines and borehole data). We have developed an ARC/INFO-based technology to calculate fracture frequency and densities for a given fracture network. A series of numericalsimulations are performed in order to determine the optimal orientation of a scanline, along which the maximum fracturefrequency of a fracture network can be obtained. We calculated the frequency (f) and densities (both D1 and D2) of 36natural fracture trace maps, and investigated the statistical relationship between fracture frequency and fracture density D1,i.e. D1=l.340f + 0.034. We derived analytical solutions for converting dimensional density (D1) to non-dimensionaldensities (D2 and D3) assuming that fracture length distribution follows an exponential or power law. A comparisonbetween observed and calculated results based on the equations we developed shows that (1) there exists a linearrelationship between fracture frequency and fracture density (D1), and this relationship can be used to estimate fracturedensity (D1) if the fracture frequency is determined from a scanline survey or from borehole data; (2) the analyticalsolutions we derived can accurately determine the non-dimensional 2-D fracture density (D2) in practice and 3-D fracturedensity (D3) in theory if the fracture length distribution function is assumed.
Carbon pool densities and a first estimate of the total carbon pool in the Mongolian forest-steppe.
Dulamsuren, Choimaa; Klinge, Michael; Degener, Jan; Khishigjargal, Mookhor; Chenlemuge, Tselmeg; Bat-Enerel, Banzragch; Yeruult, Yolk; Saindovdon, Davaadorj; Ganbaatar, Kherlenchimeg; Tsogtbaatar, Jamsran; Leuschner, Christoph; Hauck, Markus
2016-02-01
The boreal forest biome represents one of the most important terrestrial carbon stores, which gave reason to intensive research on carbon stock densities. However, such an analysis does not yet exist for the southernmost Eurosiberian boreal forests in Inner Asia. Most of these forests are located in the Mongolian forest-steppe, which is largely dominated by Larix sibirica. We quantified the carbon stock density and total carbon pool of Mongolia's boreal forests and adjacent grasslands and draw conclusions on possible future change. Mean aboveground carbon stock density in the interior of L. sibirica forests was 66 Mg C ha(-1) , which is in the upper range of values reported from boreal forests and probably due to the comparably long growing season. The density of soil organic carbon (SOC, 108 Mg C ha(-1) ) and total belowground carbon density (149 Mg C ha(-1) ) are at the lower end of the range known from boreal forests, which might be the result of higher soil temperatures and a thinner permafrost layer than in the central and northern boreal forest belt. Land use effects are especially relevant at forest edges, where mean carbon stock density was 188 Mg C ha(-1) , compared with 215 Mg C ha(-1) in the forest interior. Carbon stock density in grasslands was 144 Mg C ha(-1) . Analysis of satellite imagery of the highly fragmented forest area in the forest-steppe zone showed that Mongolia's total boreal forest area is currently 73 818 km(2) , and 22% of this area refers to forest edges (defined as the first 30 m from the edge). The total forest carbon pool of Mongolia was estimated at ~ 1.5-1.7 Pg C, a value which is likely to decrease in future with increasing deforestation and fire frequency, and global warming.
Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites
Mitchard, Edward T. A.; Feldpausch, Ted R.; Brienen, Roel J. W.; Lopez-Gonzalez, Gabriela; Monteagudo, Abel; Baker, Timothy R.; Lewis, Simon L.; Lloyd, Jon; Quesada, Carlos A.; Gloor, Manuel; ter Steege, Hans; Meir, Patrick; Alvarez, Esteban; Araujo-Murakami, Alejandro; Aragao, Luiz E. O. C.; Arroyo, Luzmila; Aymard, Gerardo; Banki, Olaf; Bonal, Damien; Brown, Sandra; Brown, Foster I.; Ceron, Carlos E.; Chama Moscoso, Victor; Chave, Jerome; Comiskey, James A.; Cornejo, Fernando; Corrales Medina, Massiel; Da Costa, Lola; Costa, Flavia R. C.; Di Fiore, Anthony; Domingues, Tomas F.; Erwin, Terry L.; Frederickson, Todd; Higuchi, Niro; Honorio Coronado, Euridice N.; Levis, Carolina; Killeen, Tim J.; Laurance, William F.; Magnusson, William E.; Marimon, Beatriz S.; Marimon Junior, Ben Hur; Mendoza Polo, Irina; Mishra, Piyush; Nascimento, Marcelo T.; Neill, David; Nunez Vargas, Mario P.; Palacios, Walter A.; Parada, Alexander; Pardo Molina, Guido; Pena-Claros, Marielos; Pitman, Nigel; Peres, Carlos A.; Prieto, Adriana; Poorter, Lourens; Ramirez-Angulo, Hirma; Restrepo Correa, Zorayda; Roopsind, Anand; Roucoux, Katherine H.; Rudas, Agustin; Salomao, Rafael P.; Schietti, Juliana; Silveira, Marcos; de Souza, Priscila F.; Steininger, Marc K.; Stropp, Juliana; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van Andel, Tinde R.; van der Heijden, Geertje M. F.; Vieira, Ima C. G.; Vieira, Simone; Vilanova-Torre, Emilio; Vos, Vincent A.; Wang, Ophelia; Zartman, Charles E.; Malhi, Yadvinder; Phillips, Oliver L.; Cruz, A.P.; Cuenca, W.P.; Espejo, J.E.; Ferreira, L.; Germaine, A.; Penuela, M.C.; Silva, N.; Valenzuela Gamarra, L.
2014-01-01
Aim The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directl
Directory of Open Access Journals (Sweden)
B. Sarangi
2015-12-01
Full Text Available In this work, we have used scanning mobility particle sizer (SMPS and quartz crystal microbalance (QCM to estimate the effective density of aerosol particles. This approach is tested for aerosolized particles generated from the solution of standard materials of known density, i.e. ammonium sulfate (AS, ammonium nitrate (AN and sodium chloride (SC, and also applied for ambient measurement in New Delhi. We also discuss uncertainty involved in the measurement. In this method, dried particles are introduced in to a differential mobility analyzer (DMA, where size segregation was done based on particle electrical mobility. At the downstream of DMA, the aerosol stream is subdivided into two parts. One is sent to a condensation particle counter (CPC to measure particle number concentration, whereas other one is sent to QCM to measure the particle mass concentration simultaneously. Based on particle volume derived from size distribution data of SMPS and mass concentration data obtained from QCM, the mean effective density (ρeff with uncertainty of inorganic salt particles (for particle count mean diameter (CMD over a size range 10 to 478 nm, i.e. AS, SC and AN is estimated to be 1.76 ± 0.24, 2.08 ± 0.19 and 1.69 ± 0.28 g cm−3, which are comparable with the material density (ρ values, 1.77, 2.17 and 1.72 g cm−3, respectively. Among individual uncertainty components, repeatability of particle mass obtained by QCM, QCM crystal frequency, CPC counting efficiency, and equivalence of CPC and QCM derived volume are the major contributors to the expanded uncertainty (at k = 2 in comparison to other components, e.g. diffusion correction, charge correction, etc. Effective density for ambient particles at the beginning of winter period in New Delhi is measured to be 1.28 ± 0.12 g cm−3. It was found that in general, mid-day effective density of ambient aerosols increases with increase in CMD of particle size measurement but particle photochemistry is an
Institute of Scientific and Technical Information of China (English)
Lobna R Ezz Elarab; Menha Swellam; Manal M Abdel Wahab; Karima M Maher
2010-01-01
Objective:Postmenopausal women with breast cancer are at increased risk of bone loss because of age related estrogen deficiency face which accelerated with the use of aromatase inbibitors (AIs).We aimed to study the effect on bone mineral density (BMD) and bone formation biomarker osteocalcin level in postmenopausal breast cancer patients,for the first three years of adjuvant hormonal treatment of both groups Tamoxifen versus Anastrozol.Methods:One-hundered postmenopausal breast cancers were prospectively randomized to receive either Tamoxifen 20 rag/day (n=50) or Anastrozole 10 mg (n=50).Both BMD and osteocalcin were assessed initially before treatment and then at regular intervals for both groups.Results:Use of Tamoxifen was associated with significant annual decrease in osteocalcin (P=0.001),whereas Anastrozole group had gradual increase of the annual levels (P＜0.01).BMD decreased significantly in Anastrozole versus Tamoxifen groups (2.6% vs.0.4%,P＜0.001).Osteoporosis T＜-2.5 was reported significantly higher in Anastrozole group (P＜0.01).Women with initial osteopenia in Anastrozole group showed significant decrease in BMD (P＜0.05).The addition of bisphosphonate for patients with early osteoporosis markedly improved both osteocalcin level and BMD.Conclusion:Tamoxifen preserves BMD in postmenopausal breast cancer patients,whereas Anastrozole accelerates age associated fall in BMD especially in the first year of therapy,moreover,the addition of bisphosphonate can help to decrease the skeletal related events associated with treatment to ensure better quality of life with treatment.
Nishiyama, Takanori; Nakamura, Takuji; Tsutsumi, Masaki; Tanaka, Yoshi; Nishimura, Koji; Sato, Kaoru; Tomikawa, Yoshihiro; Kohma, Masashi
2016-07-01
Polar Mesosphere Winter Echo (PMWE) is known as back scatter echo from 55 to 85 km in the mesosphere, and it has been observed by MST and IS radar in polar region during non-summer period. Since density of free electrons as scatterer is low in the dark mesosphere during winter, it is suggested that PMWE requires strong ionization of neutral atmosphere associated with Energetic Particles Precipitations (EPPs) during Solar Proton Events [Kirkwood et al., 2002] or during geomagnetically disturbed periods [Nishiyama et al., 2015]. However, studies on relationship between occurrence of PMWE and background electron density has been limited yet [Lübken et al., 2006], partly because the PMWE occurrence rate is known to be quite low (2.9%) [Zeller et al., 2006]. The PANSY (Program of the Antarctic Syowa MST/IS) radar, which is the largest MST radar in Antarctica, observed many PMWE events since it has started mesosphere observations in June 2012. We established an application method of the PANSY radar as riometer, which makes it possible to estimate Cosmic Noise Absorptions (CNA) as proxy of relative variations on background electron density. In addition, electron density profiles from 60 to 150 km altitude are calculated by Ionospheric Model for the Auroral Zone (IMAZ) [McKinnell and Friedrich, 2007] and CNA estimated by the PANSY radar. In this presentation, we would like to focus on strong PMWE during two big geomagnetic storm events, St. Patrick's Day and the Summer Solstice 2015 Event, in order to compare observed PMWE characteristics to model background electron density. On March 19 and 22, recovery phase of St. Patrick's Day Storm, sudden PMWE intensification was detected near 60 km by the PANSY radar. At the same time, strong Cosmic Noise Absorptions (CNA) of 0.8 dB and 1.0 dB were measured, respectively. However, calculated electron density profiles did not show high electron density at the altitude where the PMWE intensification were observed. On June 22, the
Simultaneous QTL detection and genomic breeding value estimation using high density SNP chips
Directory of Open Access Journals (Sweden)
Veerkamp Roel F
2010-03-01
Full Text Available Abstract Background The simulated dataset of the 13th QTL-MAS workshop was analysed to i detect QTL and ii predict breeding values for animals without phenotypic information. Several parameterisations considering all SNP simultaneously were applied using Gibbs sampling. Results Fourteen QTL were detected at the different time points. Correlations between estimated breeding values were high between models, except when the model was used that assumed that all SNP effects came from one distribution. The model that used the selected 14 SNP found associated with QTL, gave close to unity correlations with the full parameterisations. Conclusions Nine out of 18 QTL were detected, however the six QTL for inflection point were missed. Models for genomic selection were indicated to be fairly robust, e.g. with respect to accuracy of estimated breeding values. Still, it is worthwhile to investigate the number QTL underlying the quantitative traits, before choosing the model used for genomic selection.
Directory of Open Access Journals (Sweden)
Abdelkader Mokkadem
2011-01-01
Full Text Available Let and denote the location and the size of the mode of a probability density. We study the joint convergence rates of semirecursive kernel estimators of and . We show how the estimation of the size of the mode allows measuring the relevance of the estimation of its location. We also enlighten that, beyond their computational advantage on nonrecursive estimators, the semirecursive estimators are preferable to use for the construction of confidence regions.
A probabilistic hypothesis density filter for traffic flow estimation in the presence of clutter
Canaud, Matthieu; MIHAYLOVA, Lyudmila; EL FAOUZI, Nour-Eddin; BILLOT, Romain; Sau, Jacques
2012-01-01
Prediction of traffic flow variables such as traffic volume, travel speed or travel time for a short time horizon is of paramount importance in traffic control. Hence, the data assimilation process in traffic modeling for estimation and prediction plays a key role. However, the increasing complexity, non-linearity and presence of various uncertainties (both in the measured data and models) are important factors affecting the traffic state prediction. To overcome this problem, new methodologie...
Bayesian Prediction Model Based on Attribute Weighting and Kernel Density Estimations
Directory of Open Access Journals (Sweden)
Zhong-Liang Xiang
2015-01-01
Full Text Available Although naïve Bayes learner has been proven to show reasonable performance in machine learning, it often suffers from a few problems with handling real world data. First problem is conditional independence; the second problem is the usage of frequency estimator. Therefore, we have proposed methods to solve these two problems revolving around naïve Bayes algorithms. By using an attribute weighting method, we have been able to handle conditional independence assumption issue, whereas, for the case of the frequency estimators, we have found a way to weaken the negative effects through our proposed smooth kernel method. In this paper, we have proposed a compact Bayes model, in which a smooth kernel augments weights on likelihood estimation. We have also chosen an attribute weighting method which employs mutual information metric to cooperate with the framework. Experiments have been conducted on UCI benchmark datasets and the accuracy of our proposed learner has been compared with that of standard naïve Bayes. The experimental results have demonstrated the effectiveness and efficiency of our proposed learning algorithm.
Hammou Elotmany; M'Hamed Eddahbi
2015-01-01
Hammou El-otmany, M'hamed Eddahbi Facult{\\'e} des Sciences et Techniques Marrakech-Maroc Laboratoire de m{\\'e}thodes stochastiques appliqu{\\'e}e a la finance et actuariat (LaMsaFA) Abstract. In the present paper we propose a new stochastic diffusion process with drift proportional to the Weibull density function defined as X $\\epsilon$ = x, dX t = $\\gamma$ t (1 -- t $\\gamma$+1) -- t $\\gamma$ X t dt + $\\sigma$X t dB t , t \\textgreater{} 0, with parameters $\\gamma$ \\textgreater{} 0 and $\\sigma$...
Institute of Scientific and Technical Information of China (English)
LIU Dan; WEI Guo; SUN Jin-wei; LIU Xin
2009-01-01
In the osmotic dehydration process of food, on-line estimation of concentrations of two components in ternary solution with NaCI and sucrose was performed based on multi-functional sensing technique.Moving Least Squares were adopted in approximation procedure to estimate the viscosity of such interested ternary solu-tion with the given data set.As a result, in one mode of using total experimental data as calibration data andvalidation data, the relative deviations of estimated viscosities are less than ～ 1.24%.In the other mode, by taking total experimental data except the ones for estimation as calibration data, the relative deviations are less than±3.47%.In the same way, the density of ternary solution can be also estimated with deviations less than ± 0.11% and ± 0.30% respectively in these two models.The satisfactory and accurate results show the ex-traordinary efficiency of Moving Least Squares behaved in signal approximation for multi-functional sensors.
Putku, Elsa; Astover, Alar; Ritz, Christian
2016-04-01
Soil monitoring networks provide a powerful base for estimating and predicting nation's soil status in many aspects. The datasets of soil monitoring are often hierarchically structured demanding sophisticated data analyzing methods. The National Soil Monitoring of Estonia was based on a hierarchical data sampling scheme as each of the monitoring site was divided into four transects with 10 sampling points on each transect. We hypothesized that the hierarchical structure in Estonian Soil Monitoring network data requires a multi-level mixed model approach to achieve good prediction accuracy of soil properties. We used this database to predict soil bulk density and soil organic carbon concentration of mineral soils in arable land using different statistical methods: median approach, linear regression and mixed model; additionally, random forests for SOC concentration. We compared the prediction results and selected the model with the best prediction accuracy to estimate soil organic carbon stock. The mixed model approach achieved the best prediction accuracy in both soil organic carbon (RMSE 0.22%) and bulk density (RMSE 0.09 g cm-3) prediction. Other considered methods under- or overestimated higher and lower values of soil parameters. Thus, using these predictions we calculated the soil organic carbon stock of mineral arable soils and applied the model to a specific case of Tartu County in Estonia. Average estimated SOC stock of Tartu County is 54.8 t C ha-1 and total topsoil SOC stock 1.8 Tg in humus horizon.
Institute of Scientific and Technical Information of China (English)
王红磊; 武力; 阙燕
2011-01-01
[Objective] To investigate the correlation between synthesis diagnostic index (SDI) of diffused optical tomography (DOT) with ultrasonography (US) localization and microvessel density (MVD) based on CD 105, as well as their relationship with clinic pathological characteristics of breast cancer. [Method] A new machine of diffused optical tomography (DOT) with ultrasonography (US) was used in diagnosis of 273 cases with breast cancer, in which 131 cases were benign and 142 cases were malignant. The machine generates a synthesis diagnostic index (SDI) as a quantitative measure of the likelihood of a lesion being malignant. The receiver operating characteristic (ROC) curve analysis was used to estimate the optimal diagnostic threshold of breast cancer. The microvessel density (MVD) based on CD105 was detected by immunohistochemistry on all the 142 cases of breast cancer. [Results] The mean SDI values were 109 ± 48 for benign cases and 191 ± 60 for malignant cases. There was significant difference between them (P 0.05). [Conclusion] SDI of diffused optical tomography with ultrasonography is closely related to microvessel density in breast cancer, which can indirectly reflect the angiogenic activity. It also might play a great role of early diagnosis and in distinguishing benign and malignant tumors.%[目的]探讨乳腺癌超声光散射断层成像综合诊断指数(SDI)与微血管密度(MVD)的关系以及它们与临床病理特征的关系.[方法]采用超声光散射断层成像系统,研究131例乳腺良性肿块及142例乳腺癌患者,测量超声光散射断层成像综合诊断指数通过受试者工作特征曲线(ROC)确定乳腺癌的最佳诊断阈值.使用免疫组化法检测乳腺癌CD105标记的微血管密度.[结果]乳腺良性疾病与乳腺癌的SDI值分别:109±48、191±60.两者之间的差异有统计学意义(P＜0.05).经ROC曲线分析可得:SDI值的ROC曲线下面积为0.889,确定SDI值＞141.2作为乳腺癌的最佳诊断阈
Energy Technology Data Exchange (ETDEWEB)
Zurl, Brigitte, E-mail: brigitte.zurl@klinikum-graz.at [Department of Therapeutic Radiology and Oncology, Medical University of Graz (Austria); Stranzl, Heidi; Winkler, Peter; Kapp, Karin Sigrid [Department of Therapeutic Radiology and Oncology, Medical University of Graz (Austria)
2013-02-01
Purpose: Whole breast irradiation with deep-inspiration breath-hold (DIBH) technique among left-sided breast cancer patients significantly reduces cardiac irradiation; however, a potential disadvantage is increased incidental irradiation of the contralateral breast. Methods and Materials: Contralateral breast dose (CBD) was calculated by comparing 400 treatment plans of 200 left-sided breast cancer patients whose tangential fields had been planned on gated and nongated CT data sets. Various anatomic and field parameters were analyzed for their impact on CBD. For a subgroup of patients (aged {<=}45 years) second cancer risk in the contralateral breast (CB) was modeled by applying the linear quadratic model, compound models, and compound models considering dose-volume information (DVH). Results: The mean CBD was significantly higher in DIBH with 0.69 Gy compared with 0.65 Gy in normal breathing (P=.01). The greatest impact on CBD was due to a shift of the inner field margin toward the CB in DIBH (mean 0.4 cm; range, 0-2), followed by field size in magnitude. Calculation with different risk models for CBC revealed values of excess relative risk/Gy ranging from 0.48-0.65 vs 0.46-0.61 for DIBH vs normal breathing, respectively. Conclusion: Contralateral breast dose, although within a low dose range, was mildly but significantly increased in 200 treatment plans generated under gated conditions, predominately due to a shift in the medial field margin. Risk modeling for CBC among women aged {<=}45 years also pointed to a higher risk when comparing DIBH with normal breathing. This risk, however, was substantially lower in the model considering DVH information. We think that clinical decisions should not be affected by this small increase in CBD with DIBH because DIBH is effective in reducing the dose to the heart in all patients.
Ashihara, Y.; Miyake, T.; Ishisaka, K.; Murayama, Y.; Kawamura, S.; Nagano, I.; Okada, T.
2006-12-01
MF radar estimates the electron density in lower ionospheric D and E regions at the altitude from 60km to 100km by using the partial reflection information of MF radar transmission wave. Though, the electron density in ionospheric D region is very small, about 10-1000 /cc, electrons are closely related to neutral dynamic meteorology and chemistry including such as hydrated ion and NOx in the region. Therefore, it has the possibility to find a new physical knowledge in mesosphere and lower ionosphere. MF Rader transmits the burst pulse radio wave toward vertically direction. This pulse has 48μsec. width and modulated by 1.995MHz. Differential Absorption Experiment (DAE) is one of the methods to estimate the electron density by MF radar. DAE needs three information, which are ratio of received intensity, reflection coefficient and attenuate coefficient. Ratio of received intensity is found by the differential amount of between the left and the right polarized wave reflected by ionosphere. Though, reflection and attenuation coefficient are given as constant which is only depended on altitude, and is not depended on electron or atmospheric density. The validity of DAE has not been examined for more than 30 years. So we examine the validity of treatment both refection and attenuation coefficient as constant. Full wave analysis is a simulation method to calculate the radio wave propagation characteristics in ionosphere. Though, MF radar transmitted pulse must be treated in the time-domain. In this study, we obtain the time development of MF radar transmitted pulse by applying Fourier transformation to Full wave analysis on simulation. It is required some parameters, electron density profile, neutral-electron collision frequency profile, etc., to execute Full wave analysis. This time development data of MF radar transmitted pulse includes the reflection pulse, i.e. ratio of received intensity, at the ionosphere. We can calculate electron density profile by DAE method
Inverse Bayesian Estimation of Gravitational Mass Density in Galaxies from Missing Kinematic Data
Chakrabarty, Dalia
2014-01-01
In this paper we focus on a type of inverse problem in which the data is expressed as an unknown function of the sought and unknown model function (or its discretised representation as a model parameter vector). In particular, we deal with situations in which training data is not available. Then we cannot model the unknown functional relationship between data and the unknown model function (or parameter vector) with a Gaussian Process of appropriate dimensionality. A Bayesian method based on state space modelling is advanced instead. Within this framework, the likelihood is expressed in terms of the probability density function ($pdf$) of the state space variable and the sought model parameter vector is embedded within the domain of this $pdf$. As the measurable vector lives only inside an identified sub-volume of the system state space, the $pdf$ of the state space variable is projected onto the space of the measurables, and it is in terms of the projected state space density that the likelihood is written; ...
Xing, Ye; Xue, Zhong; Englander, Sarah; Schnall, Mitchell; Shen, Dinggang
2008-01-01
The parenchyma tissue in the breast has a strong relation with predictive biomarkers of breast cancer. To better segment parenchyma, we perform segmentation on estimated tissue property T1 map. To improve the estimation of tissue property (T1) which is the basis for parenchyma segmentation, we present an integrated algorithm for simultaneous T1 map estimation, T1 map based parenchyma segmentation and group-wise registration on series of inversion recovery magnetic resonance (MR) breast images. The advantage of using this integrated algorithm is that the simultaneous T1 map estimation (E-step) and group-wise registration (R-step) could benefit each other and jointly improve parenchyma segmentation. In particular, in E-step, T1 map based segmentation could help perform an edge-preserving smoothing on the tentatively estimated noisy T1 map, and could also help provide tissue probability maps to be robustly registered in R-step. Meanwhile, the improved estimation of T1 map could help segment parenchyma in a more accurate way. In R-step, for robust registration, the group-wise registration is performed on the tissue probability maps produced in E-step, rather than the original inversion recovery MR images, since tissue probability maps are the intrinsic tissue property which is invariant to the use of different imaging parameters. The better alignment of images achieved in R-step can help improve T1 map estimation and indirectly the T1 map based parenchyma segmentation. By iteratively performing E-step and R-step, we can simultaneously obtain better results for T1 map estimation, T1 map based segmentation, group-wise registration, and finally parenchyma segmentation.
Pande, Vikram
2016-01-01
Graphite is the most widely used and among the most widely-studied anode materials for lithium-ion batteries. Lithium intercalation into graphite has been extensively studied theoretically using density functional theory (DFT) calculations, complemented by experimental studies through X-ray diffraction, spectroscopy, optical imaging and other techniques. However, previous theoretical studies have not directly included van der Waals (vdW) interactions in their density functional theory calculations and vdW interactions play a crucial role in determining the stable phases. In this work, we present a first principles based model using DFT calculations, employing Bayesian Error Estimation Functional with van der Waals (BEEF-vdW) as the exchange correlation functional, and statistical thermodynamics to determine the phase transformations and subsequently, the thermodynamic intercalation potential diagram. We explore the entire configurational phase space by determining the important interactions and applying clust...
Individual movements and population density estimates for moray eels on a Caribbean coral reef
Abrams, R. W.; Schein, M. W.
1986-12-01
Observations of moray eel (Muraenidae) distribution made on a Caribbean coral reef are discussed in the context of long term population trends. Observations of eel distribution made using SCUBA during 1978, 1979 1980, and 1984 are compared and related to the occurrence of a hurricane in 1979. An estimate of the mean standing stock of moray eels is presented. The degree of site attachment is discussed for spotted morays ( Gymnothorax moringa) and goldentail morays ( Muraena miliaris). The repeated non-aggressive association of moray eels with large aggregations of potential prey fishes is detailed.
Sperling, Or; Shapira, Or; Cohen, Shabtai; Tripler, Effi; Schwartz, Amnon; Lazarovitch, Naftali
2012-09-01
In a world of diminishing water reservoirs and a rising demand for food, the practice and development of water stress indicators and sensors are in rapid progress. The heat dissipation method, originally established by Granier, is herein applied and modified to enable sap flow measurements in date palm trees in the southern Arava desert of Israel. A long and tough sensor was constructed to withstand insertion into the date palm's hard exterior stem. This stem is wide and fibrous, surrounded by an even tougher external non-conducting layer of dead leaf bases. Furthermore, being a monocot species, water flow does not necessarily occur through the outer part of the palm's stem, as in most trees. Therefore, it is highly important to investigate the variations of the sap flux densities and determine the preferable location for sap flow sensing within the stem. Once installed into fully grown date palm trees stationed on weighing lysimeters, sap flow as measured by the modified sensors was compared with the actual transpiration. Sap flow was found to be well correlated with transpiration, especially when using a recent calibration equation rather than the original Granier equation. Furthermore, inducing the axial variability of the sap flux densities was found to be highly important for accurate assessments of transpiration by sap flow measurements. The sensors indicated no transpiration at night, a high increase of transpiration from 06:00 to 09:00, maximum transpiration at 12:00, followed by a moderate reduction until 08:00; when transpiration ceased. These results were reinforced by the lysimeters' output. Reduced sap flux densities were detected at the stem's mantle when compared with its center. These results were reinforced by mechanistic measurements of the stem's specific hydraulic conductivity. Variance on the vertical axis was also observed, indicating an accelerated flow towards the upper parts of the tree and raising a hypothesis concerning dehydrating
2015-12-01
11: Control enrollment (months 8-24) HARVEY Completed. After building the dataset, iPads were programmed for survey data acquisition by the...Density Notification Laws have been passed in 23 states since this grant was awarded in 2011. Virginia was the third state to have a density notification...the right language for enrollment materials, obtain their perception of the importance of the study, and understand their views regarding a new model
Kaesmacher, Johannes; Liebl, Hans; Baum, Thomas; Kirschke, Jan Stefan
2017-01-01
Introduction Phantom-based (synchronous and asynchronous) and phantomless (internal tissue calibration based) assessment of bone mineral density (BMD) in routine MDCT (multidetector computed tomography) examinations potentially allows for diagnosis of osteoporosis. Although recent studies investigated the effects of contrast-medium application on phantom-calibrated BMD measurements, it remains uncertain to what extent internal tissue-calibrated BMD measurements are also susceptible to contrast-medium associated density variation. The present study is the first to systemically evaluate BMD variations related to contrast application comparing different calibration techniques. Purpose To compare predicative performance of different calibration techniques for BMD measurements obtained from triphasic contrast-enhanced MDCT. Materials and Methods Bone mineral density was measured on nonenhanced (NE), arterial (AR) and portal-venous (PV) contrast phase MDCT images of 46 patients using synchronous (SYNC) and asynchronous (ASYNC) phantom calibration as well as internal calibration (IC). Quantitative computed tomography (QCT) served as criterion standard. Density variations were analyzed for each contrast phase and calibration technique, and respective linear fitting was performed. Results Both asynchronous calibration-derived BMD values (NE-ASYNC) and values estimated using IC (NE-IC) on NE MDCT images did reasonably well in predicting QCT BMD (root-mean-square deviation, 8.0% and 7.8%, respectively). Average NE-IC BMD was 2.7% lower when compared with QCT (P = 0.017), whereas no difference could be found for NE-ASYNC (P = 0.957). All average BMD estimates derived from contrast-enhanced scans differed significantly from QCT BMD (all P 6.0 mg/mL). All regression fits revealed a consistent linear dependency (R2 range, 0.861–0.963). Overall accuracy and goodness of fit tended to decrease from AR to PV contrast phase. Highest precision and best linear fit could be reached
Kokado, Satoshi; Sakuraba, Yuya; Tsunoda, Masakiyo
2016-10-01
We derive a simple relational expression between the spin polarization ratio of resistivity, Pρ, and the anisotropic magnetoresistance ratio Δρ/ρ, and that between the spin polarization ratio of the density of states at the Fermi energy, PDOS, and Δρ/ρ for nearly half-metallic ferromagnets. We find that Pρ and PDOS increase with increasing |Δρ/ρ| from 0 to a maximum value. In addition, we roughly estimate Pρ and PDOS for a Co2FeGa0.5Ge0.5 Heusler alloy by substituting its experimentally observed Δρ/ρ into the respective expressions.
Bell, David M; Ward, Eric J; Oishi, A Christopher; Oren, Ram; Flikkema, Paul G; Clark, James S
2015-07-01
Uncertainties in ecophysiological responses to environment, such as the impact of atmospheric and soil moisture conditions on plant water regulation, limit our ability to estimate key inputs for ecosystem models. Advanced statistical frameworks provide coherent methodologies for relating observed data, such as stem sap flux density, to unobserved processes, such as canopy conductance and transpiration. To address this need, we developed a hierarchical Bayesian State-Space Canopy Conductance (StaCC) model linking canopy conductance and transpiration to tree sap flux density from a 4-year experiment in the North Carolina Piedmont, USA. Our model builds on existing ecophysiological knowledge, but explicitly incorporates uncertainty in canopy conductance, internal tree hydraulics and observation error to improve estimation of canopy conductance responses to atmospheric drought (i.e., vapor pressure deficit), soil drought (i.e., soil moisture) and above canopy light. Our statistical framework not only predicted sap flux observations well, but it also allowed us to simultaneously gap-fill missing data as we made inference on canopy processes, marking a substantial advance over traditional methods. The predicted and observed sap flux data were highly correlated (mean sensor-level Pearson correlation coefficient = 0.88). Variations in canopy conductance and transpiration associated with environmental variation across days to years were many times greater than the variation associated with model uncertainties. Because some variables, such as vapor pressure deficit and soil moisture, were correlated at the scale of days to weeks, canopy conductance responses to individual environmental variables were difficult to interpret in isolation. Still, our results highlight the importance of accounting for uncertainty in models of ecophysiological and ecosystem function where the process of interest, canopy conductance in this case, is not observed directly. The StaCC modeling
Tolaney, Sara M.; Boucher, Yves; Duda, Dan G.; Martin, John D.; Seano, Giorgio; Ancukiewicz, Marek; Barry, William T.; Goel, Shom; Lahdenrata, Johanna; Isakoff, Steven J.; Yeh, Eren D.; Jain, Saloni R.; Golshan, Mehra; Brock, Jane; Snuderl, Matija
2015-01-01
Emerging evidence indicates patients who benefit from antiangiogenic therapies have improved vessel function. To determine how bevacizumab modulates vessel morphology to improve vessel function we conducted a phase II trial of preoperative bevacizumab followed by bevacizumab combined with chemotherapy in HER2-negative breast cancer patients. Our results suggest that the clinical response to bevacizumab may occur through an increase in the extent of vascular normalization primarily in patients...
Levels and profiles of PCDDs, PCDFs and cPCBs in Belgian breast milk. Estimation of infant intake.
Focant, J F; Pirard, C; Thielen, C; De Pauw, E
2002-09-01
Congener-specific analyses of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and non-ortho (coplanar) polychlorinated biphenyls (cPCBs) were performed on 20 non-pooled breast milk samples collected in or close to an industrial area of Wallonia (Belgium). PCDD/F concentrations ranged between 16.0 and 52.1 pg TEQ/g fat, with a mean value of 29.4 pg TEQ/g fat. If coplanar PCBs (77, 126, 169) are included in TEQ calculations, levels ranged between 22.2 and 100.2 pg TEQ/g fat, with a mean value of 40.8 pg TEQ/g fat. It appears that 2,3,7,8-TCDD, 1,2,3,7,8-PeCDD, 2,3,4,7,8-PeCDF and PCB-126 account for more than 90% of the TEQ. Estimated PCDD/F dietary intake is 76 pg TEQ/kg body weight (bw)/day. This value is almost 20 times higher than the World Health Organization tolerable daily intake. A value of 103 pg TEQ/kg bw/day represents the intake of PCDDs, PCDFs and cPCBs (no mono-ortho PCBs included).
Vieira, Vasco M. N. C. S.; Engelen, Aschwin H.; Huanel, Oscar R.; Guillemin, Marie-Laure
2016-01-01
Survival is a fundamental demographic component and the importance of its accurate estimation goes beyond the traditional estimation of life expectancy. The evolutionary stability of isomorphic biphasic life-cycles and the occurrence of its different ploidy phases at uneven abundances are hypothesized to be driven by differences in survival rates between haploids and diploids. We monitored Gracilaria chilensis, a commercially exploited red alga with an isomorphic biphasic life-cycle, having found density-dependent survival with competition and Allee effects. While estimating the linear-in-the-parameters survival function, all model I regression methods (i.e, vertical least squares) provided biased line-fits rendering them inappropriate for studies about ecology, evolution or population management. Hence, we developed an iterative two-step non-linear model II regression (i.e, oblique least squares), which provided improved line-fits and estimates of survival function parameters, while robust to the data aspects that usually turn the regression methods numerically unstable. PMID:27936048
Energy Technology Data Exchange (ETDEWEB)
Lee, Jong Kyeom; Kim, Tae Yun; Kim, Hyun Su; Chai, Jang Bom; Lee, Jin Woo [Div. of Mechanical Engineering, Ajou University, Suwon (Korea, Republic of)
2016-10-15
This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.
Energy Technology Data Exchange (ETDEWEB)
Ansarifar, G.R., E-mail: ghr.ansarifar@ast.ui.ac.ir; Nasrabadi, M.N.; Hassanvand, R.
2016-01-15
Highlights: • We present a S.M.C. system based on the S.M.O for control of a fast reactor power. • A S.M.O has been developed to estimate the density of delayed neutron precursor. • The stability analysis has been given by means Lyapunov approach. • The control system is guaranteed to be stable within a large range. • Th