[The research of establishing discriminant function for patients with angina pectoris by stepwise analysis based on serum inflammatory factors].

PubMed

Chen, Zhi-bin; Liang, Yan-bing; Tang, Hao; Wang, Zhong-hua; Zeng, Li-jin; Wu, Jing-guo; Li, Zhen-yu; Ma, Zhong-fu

2012-12-01

To improve cost-efficiency, discriminant functions in stepwise method was founded for the differential diagnosis of angina pectoris by detecting the serum level of high-sensitivity C-reactive protein (hs-CRP), macrophage migration inhibitory factor (MIF), interleukin-4 (IL-4) and interleukin-10 (IL-10) in patients with stable angina pectoris (SAP) and unstable angina pectoris (UAP). Thirty-nine SAP patients and 47 UAP patients were enrolled into the study, while 39 healthy volunteers were enrolled into the controlled group forming the entire set of training samples. The serum levels of hs-CRP, MIF, IL-4 and IL-10 were measured by enzyme linked immunosorbent assay (ELISA). Data was analyzed by software to define discriminant functions in the ways of "entering" and "stepwise". Both functions were evaluated by the results of validation. By the way of "enter independent together", the following discriminant functions were defined based on the data of training samples' age, hs-CRP, MIF, IL-4, IL-10: healthy control group =-129.858 + 2.869×age -2.451×hs-CRP + 1.393×MIF + 6.001×IL-4 + 4.848×IL-10; SAP group=-161.037 + 2.896×age-2.022×hs-CRP + 1.662×MIF + 6.703×IL-4 + 6.287×IL-10; UAP group=-199.087 + 2.468×age-1.440×hs-CRP + 3.404×MIF-13.875×IL-4 + 7.752×IL-10. Retrospective validation showed 4.8% of total miss-grouping, while cross-validation showed 5.6% of total miss-grouping. By the way of "stepwise", the above data was screened by software and training samples' age, MIF and IL-10 were suggested to define the following functions: healthy control group = - 125.218 + 2.659 × age + 0.599×MIF + 5.040 × IL-10; SAP group=-157.864 + 2.721×age + 1.008×MIF + 6.468×IL-10; UAP group=- 197.327 + 2.360×age + 2.932×MIF + 7.640×IL-10. Both retrospective and cross validation showed 6.4% of total miss-grouping. Both sets of discriminant functions had the same efficiency (100%) for differential diagnosis of SAP and UAP. The discriminant functions based on samples' age, MIF and IL-10, which were screened and suggested by stepwise method, may contribute to the differential diagnosis of atypical SAP and UAP, and therefore demonstrate better cost-efficiency.

Sex determination based on a thoracic vertebra and ribs evaluation using clinical chest radiography.

PubMed

Tsubaki, Shun; Morishita, Junji; Usumoto, Yosuke; Sakaguchi, Kyoko; Matsunobu, Yusuke; Kawazoe, Yusuke; Okumura, Miki; Ikeda, Noriaki

2017-07-01

Our aim was to investigate whether sex can be determined from a combination of geometric features obtained from the 10th thoracic vertebra, 6th rib, and 7th rib. Six hundred chest radiographs (300 males and 300 females) were randomly selected to include patients of six age groups (20s, 30s, 40s, 50s, 60s, and 70s). Each group included 100 images (50 males and 50 females). A total of 14 features, including 7 lengths, 5 indices for the vertebra, and 2 types of widths for ribs, were utilized and analyzed for sex determination. Dominant features contributing to sex determination were selected by stepwise discriminant analysis after checking the variance inflation factors for multicollinearity. The accuracy of sex determination using a combination of the vertebra and ribs was evaluated from the selected features by the stepwise discriminant analysis. The accuracies in each age group were also evaluated in this study. The accuracy of sex determination based on a combination of features of the vertebra and ribs was 88.8% (533/600). This performance was superior to that of the vertebra or ribs only. Moreover, sex determination of subjects in their 20s demonstrated the highest accuracy (96.0%, 96/100). The features selected in the stepwise discriminant analysis included some features in both the vertebra and ribs. These results indicate the usefulness of combined information obtained from the vertebra and ribs for sex determination. We conclude that a combination of geometric characteristics obtained from the vertebra and ribs could be useful for determining sex. Copyright © 2017 Elsevier B.V. All rights reserved.

Classification of lung cancer patients and controls by chromatography of modified nucleosides in serum

USGS Publications Warehouse

McEntire, John E.; Kuo, Kenneth C.; Smith, Mark E.; Stalling, David L.; Richens, Jack W.; Zumwalt, Robert W.; Gehrke, Charles W.; Papermaster, Ben W.

1989-01-01

A wide spectrum of modified nucleosides has been quantified by high-performance liquid chromatography in serum of 49 male lung cancer patients, 35 patients with other cancers, and 48 patients hospitalized for nonneoplastic diseases. Data for 29 modified nucleoside peaks were normalized to an internal standard and analyzed by discriminant analysis and stepwise discriminant analysis. A model based on peaks selected by a stepwise discriminant procedure correctly classified 79% of the cancer and 75% of the noncancer subjects. It also demonstrated 84% sensitivity and 79% specificity when comparing lung cancer to noncancer subjects, and 80% sensitivity and 55% specificity in comparing lung cancer to other cancers. The nucleoside peaks having the greatest influence on the models varied dependent on the subgroups compared, confirming the importance of quantifying a wide array of nucleosides. These data support and expand previous studies which reported the utility of measuring modified nucleoside levels in serum and show that precise measurement of an array of 29 modified nucleosides in serum by high-performance liquid chromatography with UV scanning with subsequent data modeling may provide a clinically useful approach to patient classification in diagnosis and subsequent therapeutic monitoring.

Reproductive Status of Females in the Eusocial Wasp Polistes ferreri Saussure (Hymenoptera: Vespidae).

PubMed

Soares, E R P; Torres, V O; Antonialli-Junior, W F

2014-12-01

In the subfamily Polistinae, caste dimorphism is not pronounced and differences among females are primarily physiological and behavioral. We investigated factors that indicate the reproductive status in females of Polistes ferreri Saussure. We analyzed females from nine colonies and evaluated morphometric parameters, ovarian development, occurrence of insemination, relative age, and cuticular chemical profile. The colony females showed three kinds of ovarian development: type A, filamentous ovarioles; type B, ovarioles containing partially developed oocytes; and type C, long and well-developed ovarioles containing two or more mature oocytes. The stepwise discriminant analysis of the cuticular chemical profile showed that it was possible to distinguish the three groups of females: workers 1, workers 2, and queens. However, the stepwise discriminant analysis of the morphological differences did not show significant differences among these groups. The queens were among the older females in the colony and were always inseminated, while the age of the workers varied according to the stage of colony development.

Linear discriminant analysis of dermoscopic parameters for the differentiation of early melanomas from Clark naevi.

PubMed

Oka, Hiroshi; Tanaka, Masaru; Kobayashi, Seiichiro; Argenziano, Giuseppe; Soyer, H Peter; Nishikawa, Takeji

2004-04-01

As a first step to develop a screening system for pigmented skin lesions, we performed digital discriminant analyses between early melanomas and Clark naevi. A total of 59 cases of melanoma, including 23 melanoma in situ and 36 thin invasive melanomas (Breslow thickness < or =0.75 mm), and 188 clinically equivocal, histopathologically diagnosed Clark naevi were used in our study. After calculating 62 mathematical variables related to the colour, texture, asymmetry and circularity based on the dermoscopic findings of the pigmented skin lesions, we performed multivariate stepwise discriminant analysis using these variables to differentiate melanomas from naevi. The sensitivities and specificities of our model were 94.4 and 98.4%, respectively, for discriminating between melanomas (Breslow thickness < or =0.75 mm) and Clark naevi, and 73.9 and 85.6%, respectively, for discriminating between melanoma in situ and Clark naevi. Our algorithm accurately discriminated invasive melanomas from Clark naevi, but not melanomas in situ from Clark naevi.

Multi-class ERP-based BCI data analysis using a discriminant space self-organizing map.

PubMed

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

Emotional or non-emotional image stimulus is recently applied to event-related potential (ERP) based brain computer interfaces (BCI). Though the classification performance is over 80% in a single trial, a discrimination between those ERPs has not been considered. In this research we tried to clarify the discriminability of four-class ERP-based BCI target data elicited by desk, seal, spider images and letter intensifications. A conventional self organizing map (SOM) and newly proposed discriminant space SOM (ds-SOM) were applied, then the discriminabilites were visualized. We also classify all pairs of those ERPs by stepwise linear discriminant analysis (SWLDA) and verify the visualization of discriminabilities. As a result, the ds-SOM showed understandable visualization of the data with a shorter computational time than the traditional SOM. We also confirmed the clear boundary between the letter cluster and the other clusters. The result was coherent with the classification performances by SWLDA. The method might be helpful not only for developing a new BCI paradigm, but also for the big data analysis.

Plant community variability on a small area in southeastern Montana

Treesearch

James G. MacCracken; Daniel W. Uresk; Richard M. Hansen

1984-01-01

Plant communities are inherently variable due to a number of environmental and biological forces. Canopy cover and aboveground biomass were determined for understory vegetation in plant communities of a prairie grassland-forest ecotone in southeastern Montana. Vegetation units were described using polar ordination and stepwise discriminant analysis. Nine of a total of...

Otolith shape analysis for stock discrimination of two Collichthys genus croaker (Pieces: Sciaenidae,) from the northern Chinese coast

NASA Astrophysics Data System (ADS)

Zhao, Bo; Liu, Jinhu; Song, Junjie; Cao, Liang; Dou, Shuozeng

2017-08-01

The otolith morphology of two croaker species (Collichthys lucidus and Collichthys niveatus) from three areas (Liaodong Bay, LD; Huanghe (Yellow) River estuary, HRE; Jiaozhou Bay, JZ) along the northern Chinese coast were investigated for species identification and stock discrimination. The otolith contour shape described by elliptic Fourier coefficients (EFC) were analysed using principal components analysis (PCA) and stepwise canonical discriminant analysis (CDA) to identify species and stocks. The two species were well differentiated, with an overall classification success rate of 97.8%. And variations in the otolith shapes were significant enough to discriminate among the three geographical samples of C. lucidus (67.7%) or C. niveatus (65.2%). Relatively high mis-assignment occurred between the geographically adjacent LD and HRE samples, which implied that individual mixing may exist between the two samples. This study yielded information complementary to that derived from genetic studies and provided information for assessing the stock structure of C. lucidus and C. niveatus in the Bohai Sea and the Yellow Sea.

Discrimination of the rare medicinal plant Dendrobium officinale based on naringenin, bibenzyl, and polysaccharides.

PubMed

Chen, Xiaomei; Wang, Fangfei; Wang, Yunqiang; Li, Xuelan; Wang, Airong; Wang, Chunlan; Guo, Shunxing

2012-12-01

The aim of this study was to establish a method for discriminating Dendrobium officinale from four of its close relatives Dendrobium chrysanthum, Dendrobium crystallinum, Dendrobium aphyllum and Dendrobium devonianum based on chemical composition analysis. We analyzed 62 samples of 24 Dendrobium species. High performance liquid chromatography analysis confirmed that the four low molecular weight compounds 4',5,7-trihydroxyflavanone (naringenin), 3,4-dihydroxy-4',5-dime-thoxybibenzyl (DDB-2), 3',4-dihydroxy-3,5'-dimethoxybibenzyl (gigantol), and 4,4'-dihydroxy-3,3',5-trimethoxybibenzy (moscatilin), were common in the genus. The phenol-sulfuric acid method was used to quantify polysaccharides, and the monosaccharide composition of the polysaccharides was determined by gas chromatography. Stepwise discriminant analysis was used to differentiate among the five closely related species based on the chemical composition analysis. This proved to be a simple and accurate approach for discriminating among these species. The results also showed that the polysaccharide content, the amounts of the four low molecular weight compounds, and the mannose to glucose ratio, were important factors for species discriminant. Therefore, we propose that a chemical analysis based on quantification of naringenin, bibenzyl, and polysaccharides is effective for identifying D. officinale.

Differentiation of Chinese rice wines from different wineries based on mineral elemental fingerprinting.

PubMed

Shen, Fei; Wu, Jian; Ying, Yibin; Li, Bobin; Jiang, Tao

2013-12-15

Discrimination of Chinese rice wines from three well-known wineries ("Guyuelongshan", "Kuaijishan", and "Pagoda") in China has been carried out according to mineral element contents in this study. Nineteen macro and trace mineral elements (Na, Mg, Al, K, Ca, Mn, Fe, Cu, Zn, V, Cr, Co, Ni, As, Se, Mo, Cd, Ba and Pb) were determined by inductively coupled plasma mass spectrometry (ICP-MS) in 117 samples. Then the experimental data were subjected to analysis of variance (ANOVA) and principal component analysis (PCA) to reveal significant differences and potential patterns between samples. Stepwise linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA) were applied to develop classification models and achieved correct classified rates of 100% and 97.4% for the prediction sample set, respectively. The discrimination could be attributed to different raw materials (mainly water) and elaboration processes employed. The results indicate that the element compositions combined with multivariate analysis can be used as fingerprinting techniques to protect prestigious wineries and enable the authenticity of Chinese rice wine. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Discrimination of varieties of brake fluid using visual-near infrared spectra].

PubMed

Jiang, Lu-lu; Tan, Li-hong; Qiu, Zheng-jun; Lu, Jiang-feng; He, Yong

2008-06-01

A new method was developed to fast discriminate brands of brake fluid by means of visual-near infrared spectroscopy. Five different brands of brake fluid were analyzed using a handheld near infrared spectrograph, manufactured by ASD Company, and 60 samples were gotten from each brand of brake fluid. The samples data were pretreated using average smoothing and standard normal variable method, and then analyzed using principal component analysis (PCA). A 2-dimensional plot was drawn based on the first and the second principal components, and the plot indicated that the clustering characteristic of different brake fluid is distinct. The foregoing 6 principal components were taken as input variable, and the band of brake fluid as output variable to build the discriminate model by stepwise discriminant analysis method. Two hundred twenty five samples selected randomly were used to create the model, and the rest 75 samples to verify the model. The result showed that the distinguishing rate was 94.67%, indicating that the method proposed in this paper has good performance in classification and discrimination. It provides a new way to fast discriminate different brands of brake fluid.

[Correlation between physical characteristics of sticks and quality of traditional Chinese medicine pills prepared by plastic molded method].

PubMed

Wang, Ling; Xian, Jiechen; Hong, Yanlong; Lin, Xiao; Feng, Yi

2012-05-01

To quantify the physical characteristics of sticks of traditional Chinese medicine (TCM) honeyed pills prepared by the plastic molded method and the correlation of adhesiveness and plasticity-related parameters of sticks and quality of pills, in order to find major parameters and the appropriate range impacting pill quality. Sticks were detected by texture analyzer for their physical characteristic parameters such as hardness and compression action, and pills were observed by visual evaluation for their quality. The correlation of both data was determined by the stepwise discriminant analysis. Stick physical characteristic parameter l(CD) can exactly depict the adhesiveness, with the discriminant equation of Y0 - Y1 = 6.415 - 41.594l(CD). When Y0 < Y1, pills were scattered well; when Y0 > Y1, pills were adhesive with each other. Pills' physical characteristic parameters l(CD) and l(AC), Ar, Tr can exactly depict smoothness of pills, with the discriminant equation of Z0 - Z1 = -195.318 + 78.79l(AC) - 3 258. 982Ar + 3437.935Tr. When Z0 < Z1, pills were smooth on surface. When Z0 > Z1, pills were rough on surface. The stepwise discriminant analysis is made to show the obvious correlation between key physical characteristic parameters l(CD) and l(AC), Ar, Tr of sticks and appearance quality of pills, defining the molding process for preparing pills by the plastic molded and qualifying ranges of key physical characteristic parameters characterizing intermediate sticks, in order to provide theoretical basis for prescription screening and technical parameter adjustment for pills.

Classification of typical and atypical antipsychotic drugs on the basis of dopamine D-1, D-2 and serotonin2 pKi values.

PubMed

Meltzer, H Y; Matsubara, S; Lee, J C

1989-10-01

The pKi values of 13 reference typical and 7 reference atypical antipsychotic drugs (APDs) for rat striatal dopamine D-1 and D-2 receptor binding sites and cortical serotonin (5-HT2) receptor binding sites were determined. The atypical antipsychotics had significantly lower pKi values for the D-2 but not 5-HT2 binding sites. There was a trend for a lower pKi value for the D-1 binding site for the atypical APD. The 5-HT2 and D-1 pKi values were correlated for the typical APD whereas the 5-HT2 and D-2 pKi values were correlated for the atypical APD. A stepwise discriminant function analysis to determine the independent contribution of each pKi value for a given binding site to the classification as a typical or atypical APD entered the D-2 pKi value first, followed by the 5-HT2 pKi value. The D-1 pKi value was not entered. A discriminant function analysis correctly classified 19 of 20 of these compounds plus 14 of 17 additional test compounds as typical or atypical APD for an overall correct classification rate of 89.2%. The major contributors to the discriminant function were the D-2 and 5-HT2 pKi values. A cluster analysis based only on the 5-HT2/D2 ratio grouped 15 of 17 atypical + one typical APD in one cluster and 19 of 20 typical + two atypical APDs in a second cluster, for an overall correct classification rate of 91.9%. When the stepwise discriminant function was repeated for all 37 compounds, only the D-2 and 5-HT2 pKi values were entered into the discriminant function.(ABSTRACT TRUNCATED AT 250 WORDS)

Classification of debtor credit status and determination amount of credit risk by using linier discriminant function

NASA Astrophysics Data System (ADS)

Aidi, Muhammad Nur; Sari, Resty Indah

2012-05-01

A decision of credit that given by bank or another creditur must have a risk and it called credit risk. Credit risk is an investor's risk of loss arising from a borrower who does not make payments as promised. The substantial of credit risk can lead to losses for the banks and the debtor. To minimize this problem need a further study to identify a potential new customer before the decision given. Identification of debtor can using various approaches analysis, one of them is by using discriminant analysis. Discriminant analysis in this study are used to classify whether belonging to the debtor's good credit or bad credit. The result of this study are two discriminant functions that can identify new debtor. Before step built the discriminant function, selection of explanatory variables should be done. Purpose of selection independent variable is to choose the variable that can discriminate the group maximally. Selection variables in this study using different test, for categoric variable selection of variable using proportion chi-square test, and stepwise discriminant for numeric variable. The result of this study are two discriminant functions that can identify new debtor. The selected variables that can discriminating two groups of debtor maximally are status of existing checking account, credit history, credit amount, installment rate in percentage of disposable income, sex, age in year, other installment plans, and number of people being liable to provide maintenance. This classification produce a classification accuracy rate is good enough, that is equal to 74,70%. Debtor classification using discriminant analysis has risk level that is small enough, and it ranged beetwen 14,992% and 17,608%. Based on that credit risk rate, using discriminant analysis on the classification of credit status can be used effectively.

Field hyperspectral data analysis for discriminating spectral behavior of tea plantations under various management practices

NASA Astrophysics Data System (ADS)

Kumar, Amit; Manjunath, K. R.; Meenakshi; Bala, Renu; Sud, R. K.; Singh, R. D.; Panigrahy, Sushma

2013-08-01

The quality and yield of tea depends upon management of tea plantations, which takes into account the factors like type, age of plantation, growth stage, pruning status, light conditions, and disease incidence. Recognizing the importance of hyperspectral data in detecting minute spectral variations in vegetation, the present study was conducted to explore applicability of such data in evaluating these factors. Also stepwise discriminant analysis and principal component analysis were conducted to identify the appropriate bands for accessing the above mentioned factors. The Green region followed by NIR region was found as most appropriate best band for discriminating different types of tea plants, and the tea in sunlit and shade condition. For discriminating age of plantation, growth stage of tea, and diseased and healthy bush, Blue region was most appropriate. The Red and NIR regions were best bands to discriminate pruned and unpruned tea. The study concluded that field hyperspectral data can be efficiently used to know the plantation that need special care and may be an indicator of tea productivity. The spectral signature of these characteristics of tea plantations may also be used to classify the hyperspectral satellite data to derive these parameters at regional scale.

Intractable Ménière's disease. Modelling of the treatment by means of statistical analysis.

PubMed

Sanchez-Ferrandiz, Noelia; Fernandez-Gonzalez, Secundino; Guillen-Grima, Francisco; Perez-Fernandez, Nicolas

2010-08-01

To evaluate the value of different variables of the clinical history, auditory and vestibular tests and handicap measurements to define intractable or disabling Ménière's disease. This is a prospective study with 212 patients of which 155 were treated with intratympanic gentamicin and considered to be suffering a medically intractable Ménière's disease. Age and sex adjustments were performed with the 11 variables selected. Discriminant analysis was performed either using the aforementioned variables or following the stepwise method. Different variables needed to be sex and/or age adjusted and both data were included in the discriminant function. Two different mathematical formulas were obtained and four models were analyzed. With the model selected, diagnostic accuracy is 77.7%, sensitivity is 94.9% and specificity is 52.8%. After discriminant analysis we found that the most informative variables were the number of vertigo spells, the speech discrimination score, the time constant of the VOR and a measure of handicap, the "dizziness index". Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

The Relationship of Selected Supply- and Demand-Side Factors to Forms of Perceived Discrimination among Adults with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Neath, Jeanne; McMahon, Brian T.; Rumrill, Phillip D.

2007-01-01

Single-predictor and stepwise multinomial logistic regression analyses and an external validation were completed on 3,082 allegations of employment discrimination by adults with multiple sclerosis. Women filed two thirds of the allegations, and individuals between 31 and 50 made the vast majority of discrimination charges (73%). Allegations…

[Study on the classification of dominant pathogens related to febrile respiratory syndrome, based on the method of Bayes discriminant analysis].

PubMed

Li, X C; Li, J S; Meng, L; Bai, Y N; Yu, D S; Liu, X N; Liu, X F; Jiang, X J; Ren, X W; Yang, X T; Shen, X P; Zhang, J W

2017-08-10

Objective: To understand the dominant pathogens of febrile respiratory syndrome (FRS) patients in Gansu province and to establish the Bayes discriminant function in order to identify the patients infected with the dominant pathogens. Methods: FRS patients were collected in various sentinel hospitals of Gansu province from 2009 to 2015 and the dominant pathogens were determined by describing the composition of pathogenic profile. Significant clinical variables were selected by stepwise discriminant analysis to establish the Bayes discriminant function. Results: In the detection of pathogens for FRS, both influenza virus and rhinovirus showed higher positive rates than those caused by other viruses (13.79%, 8.63%), that accounting for 54.38%, 13.73% of total viral positive patients. Most frequently detected bacteria would include Streptococcus pneumoniae , and haemophilus influenza (44.41%, 18.07%) that accounting for 66.21% and 24.55% among the bacterial positive patients. The original-validated rate of discriminant function, established by 11 clinical variables, was 73.1%, with the cross-validated rate as 70.6%. Conclusion: Influenza virus, Rhinovirus, Streptococcus pneumoniae and Haemophilus influenzae were the dominant pathogens of FRS in Gansu province. Results from the Bayes discriminant analysis showed both higher accuracy in the classification of dominant pathogens, and applicative value for FRS.

The Profile of Memory Function in Children With Autism

PubMed Central

Williams, Diane L.; Goldstein, Gerald; Minshew, Nancy J.

2007-01-01

A clinical memory test was administered to 38 high-functioning children with autism and 38 individually matched normal controls, 8–16 years of age. The resulting profile of memory abilities in the children with autism was characterized by relatively poor memory for complex visual and verbal information and spatial working memory with relatively intact associative learning ability, verbal working memory, and recognition memory. A stepwise discriminant function analysis of the subtests found that the Finger Windows subtest, a measure of spatial working memory, discriminated most accurately between the autism and normal control groups. A principal components analysis indicated that the factor structure of the subtests differed substantially between the children with autism and controls, suggesting differing organizations of memory ability. PMID:16460219

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

Risk factors for eating disorders in Greek- and Anglo-Australian adolescent girls.

PubMed

Mildred, H; Paxton, S J; Wertheim, E H

1995-01-01

Past research indicates ethnicity may be related to eating disorder and related risk factors. The present study examines risk factors for eating disorders in 50 Anglo- and 50 Greek-Australian girls (mean age = 13.5 years). The variables assessed included bulimic tendencies, body dissatisfaction, use of extreme weight loss behaviors (EWLBs), self-esteem, depression and family cohesion and adaptability. Cultural eating patterns were also explored. A stepwise discriminant function analysis to examine whether the two groups could be discriminated on these variables was significant and correctly classified 73.9% of the sample, the chief discriminating variables being Pressure to Eat, EWLBs, and Family Adaptability. Univariate analyses indicated differences between the groups on Pressure to Eat, Family Adaptability, and Mother's Shape. Although the groups were discriminable, a number of variables generally associated with eating disorder did not contribute to the function. These data are discussed in terms of cultural assimilation.

The prediction of swimming performance in competition from behavioral information.

PubMed

Rushall, B S; Leet, D

1979-06-01

The swimming performances of the Canadian Team at the 1976 Olympic Games were categorized as being improved or worse than previous best times in the events contested. The two groups had been previously assessed on the Psychological Inventories for Competitive Swimmers. A stepwise multiple-discriminant analysis of the inventory responses revealed that 13 test questions produced a perfect discrimination of group membership. The resultant discriminant functions for predicting performance classification were applied to the test responses of 157 swimmers at the 1977 Canadian Winter National Swimming Championships. Using the same performance classification criteria the accuracy of prediction was not better than chance in three of four sex by performance classifications. This yielded a failure to locate a set of behavioral factors which determine swimming performance improvements in elite competitive circumstances. The possibility of sets of factors which do not discriminate between performances in similar environments or between similar groups of swimmers was raised.

Effects of Cerebral Blood Flow and Vessel Conditions on Speech Recognition in Patients With Postlingual Adult Cochlear Implant: Predictable Factors for the Efficacy of Cochlear Implant.

PubMed

Ishino, Takashi; Ragaee, Mahmoud Ali; Maruhashi, Tatsuya; Kajikawa, Masato; Higashi, Yukihito; Sonoyama, Toru; Takeno, Sachio; Hirakawa, Katsuhiro

Cochlear implantation (CI) has been the most successful procedure for restoring hearing in a patient with severe and profound hearing loss. However, possibly owing to the variable brain functions of each patient, its performance and the associated patient satisfaction are widely variable. The authors hypothesize that peripheral and cerebral circulation can be assessed by noninvasive and globally available methods, yielding superior presurgical predictive factors of the performance of CI in adult patients with postlingual hearing loss who are scheduled to undergo CI. Twenty-two adult patients with cochlear implants for postlingual hearing loss were evaluated using Doppler sonography measurement of the cervical arteries (reflecting cerebral blood flow), flow-mediated dilation (FMD; reflecting the condition of cerebral arteries), and their pre-/post-CI best score on a monosyllabic discrimination test (pre-/post-CI best monosyllabic discrimination [BMD] score). Correlations between post-CI BMD score and the other factors were examined using univariate analysis and stepwise multiple linear regression analysis. The prediction factors were calculated by examining the receiver-operating characteristic curve between post-CI BMD score and the significantly positively correlated factors. Age and duration of deafness had a moderately negative correlation. The mean velocity of the internal carotid arteries and FMD had a moderate-to-strong positive correlation with the post-CI BMD score in univariate analysis. Stepwise multiple linear regression analysis revealed that only FMD was significantly positively correlated with post-CI BMD score. Analysis of the receiver-operating characteristic curve showed that a FMD cutoff score of 1.8 significantly predicted post-CI BMD score. These data suggest that FMD is a convenient, noninvasive, and widely available tool for predicting the efficacy of cochlear implants. An FMD cutoff score of 1.8 could be a good index for determining whether patients will hear well with cochlear implants. It could also be used to predict whether cochlear implants will provide good speech recognition benefits to candidates, even if their speech discrimination is poor. This FMD index could become a useful predictive tool for candidates with poor speech discrimination to determine the efficacy of CI before surgery.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions.

PubMed

Jo, Javier A; Fang, Qiyin; Papaioannou, Thanassis; Baker, J Dennis; Dorafshar, Amir H; Reil, Todd; Qiao, Jian-Hua; Fishbein, Michael C; Freischlag, Julie A; Marcu, Laura

2006-01-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions

NASA Astrophysics Data System (ADS)

Jo, Javier A.; Fang, Qiyin; Papaioannou, Thanassis; Baker, J. Dennis; Dorafshar, Amir; Reil, Todd; Qiao, Jianhua; Fishbein, Michael C.; Freischlag, Julie A.; Marcu, Laura

2006-03-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability.

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions

PubMed Central

Jo, Javier A.; Fang, Qiyin; Papaioannou, Thanassis; Baker, J. Dennis; Dorafshar, Amir H.; Reil, Todd; Qiao, Jian-Hua; Fishbein, Michael C.; Freischlag, Julie A.; Marcu, Laura

2007-01-01

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability. PMID:16674179

Simultaneous use of geological, geophysical, and LANDSAT digital data in uranium exploration. [Libya

DOE Office of Scientific and Technical Information (OSTI.GOV)

Missallati, A.; Prelat, A.E.; Lyon, R.J.P.

1979-08-01

The simultaneous use of geological, geophysical and Landsat data in uranium exploration in southern Libya is reported. The values of 43 geological, geophysical and digital data variables, including age and type of rock, geological contacts, aeroradio-metric and aeromagnetic values and brightness ratios, were used as input into a geomathematical model. Stepwise discriminant analysis was used to select grid cells most favorable for detailed mineral exploration and to evaluate the significance of each variable in discriminating between the anomalous (radioactive) and nonanomalous (nonradioactive) areas. It is found that the geological contact relationships, Landsat Bands 6 and Band 7/4 ratio values weremore » most useful in the discrimination. The procedure was found to be statistically and geologically reliable, and applicable to similar regions using only the most important geological and Landsat data.« less

Fingerprint Ridge Density as a Potential Forensic Anthropological Tool for Sex Identification.

PubMed

Dhall, Jasmine Kaur; Kapoor, Anup Kumar

2016-03-01

In cases of partial or poor print recovery and lack of database/suspect print, fingerprint evidence is generally neglected. In light of such constraints, this study was designed to examine whether ridge density can aid in narrowing down the investigation for sex identification. The study was conducted on the right-hand index digit of 245 males and 246 females belonging to the Punjabis of Delhi region. Five ridge density count areas, namely upper radial, radial, ulnar, upper ulnar, and proximal, were selected and designated. Probability of sex origin was calculated, and stepwise discriminant function analysis was performed to determine the discriminating ability of the selected areas. Females were observed with a significantly higher ridge density than males in all the five areas. Discriminant function analysis and logistic regression exhibited 96.8% and 97.4% accuracy, respectively, in sex identification. Hence, fingerprint ridge density is a potential tool for sex identification, even from partial prints. © 2015 American Academy of Forensic Sciences.

Chemometric classification of apple juices according to variety and geographical origin based on polyphenolic profiles.

PubMed

Guo, Jing; Yue, Tianli; Yuan, Yahong; Wang, Yutang

2013-07-17

To characterize and classify apple juices according to apple variety and geographical origin on the basis of their polyphenol composition, the polyphenolic profiles of 58 apple juice samples belonging to 5 apple varieties and from 6 regions in Shaanxi province of China were assessed. Fifty-one of the samples were from protected designation of origin (PDO) districts. Polyphenols were determined by high-performance liquid chromatography coupled to photodiode array detection (HPLC-PDA) and to a Q Exactive quadrupole-Orbitrap mass spectrometer. Chemometric techniques including principal component analysis (PCA) and stepwise linear discriminant analysis (SLDA) were carried out on polyphenolic profiles of the samples to develop discrimination models. SLDA achieved satisfactory discriminations of apple juices according to variety and geographical origin, providing respectively 98.3 and 91.2% success rate in terms of prediction ability. This result demonstrated that polyphenols could served as characteristic indices to verify the variety and geographical origin of apple juices.

Novel methods of time-resolved fluorescence data analysis for in-vivo tissue characterization: application to atherosclerosis.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Dorafshar, A; Reil, T; Baker, D; Freischlag, J; Marcu, L

2004-01-01

This study investigates the ability of new analytical methods of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data to characterize tissue in-vivo, such as the composition of atherosclerotic vulnerable plaques. A total of 73 TR-LIFS measurements were taken in-vivo from the aorta of 8 rabbits, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as normal aorta, thin or thick lesions, and lesions rich in either collagen or macrophages/foam-cells. Different linear and nonlinear classification algorithms (linear discriminant analysis, stepwise linear discriminant analysis, principal component analysis, and feedforward neural networks) were developed using spectral and TR features (ratios of intensity values and Laguerre expansion coefficients, respectively). Normal intima and thin lesions were discriminated from thick lesions (sensitivity >90%, specificity 100%) using only spectral features. However, both spectral and time-resolved features were necessary to discriminate thick lesions rich in collagen from thick lesions rich in foam cells (sensitivity >85%, specificity >93%), and thin lesions rich in foam cells from normal aorta and thin lesions rich in collagen (sensitivity >85%, specificity >94%). Based on these findings, we believe that TR-LIFS information derived from the Laguerre expansion coefficients can provide a valuable additional dimension for in-vivo tissue characterization.

Benign-malignant mass classification in mammogram using edge weighted local texture features

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Sadhu, Anup; Chakraborty, Jayasree

2016-03-01

This paper introduces novel Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for the classification of mammographic masses as benign or malignant. Mass is one of the common, however, challenging evidence of breast cancer in mammography and diagnosis of masses is a difficult task. Since DRLBP and DRLTP overcome the drawbacks of Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) by discriminating a brighter object against the dark background and vice-versa, in addition to the preservation of the edge information along with the texture information, several edge-preserving texture features are extracted, in this study, from DRLBP and DRLTP. Finally, a Fisher Linear Discriminant Analysis method is incorporated with discriminating features, selected by stepwise logistic regression method, for the classification of benign and malignant masses. The performance characteristics of DRLBP and DRLTP features are evaluated using a ten-fold cross-validation technique with 58 masses from the mini-MIAS database, and the best result is observed with DRLBP having an area under the receiver operating characteristic curve of 0.982.

Variation of facial features among three African populations: Body height match analyses.

PubMed

Taura, M G; Adamu, L H; Gudaji, A

2017-01-01

Body height is one of the variables that show a correlation with facial craniometry. Here we seek to discriminate the three populations (Nigerians, Ugandans and Kenyans) using facial craniometry based on different categories of body height of adult males. A total of 513 individuals comprising 234 Nigerians, 169 Ugandans and 110 Kenyans with mean age of 25.27, s=5.13 (18-40 years) participated. Paired and unpaired facial features were measured using direct craniometry. Multivariate and stepwise discriminate function analyses were used for differentiation of the three populations. The result showed significant overall facial differences among the three populations in all the body height categories. Skull height, total facial height, outer canthal distance, exophthalmometry, right ear width and nasal length were significantly different among the three different populations irrespective of body height categories. Other variables were sensitive to body height. Stepwise discriminant function analyses included maximum of six variables for better discrimination between the three populations. The single best discriminator of the groups was total facial height, however, for body height >1.70m the single best discriminator was nasal length. Most of the variables were better used with function 1, hence, better discrimination than function 2. In conclusion, adult body height in addition to other factors such as age, sex, and ethnicity should be considered in making decision on facial craniometry. However, not all the facial linear dimensions were sensitive to body height. Copyright © 2016 Elsevier GmbH. All rights reserved.

Development and Validation of a Disease Severity Scoring Model for Pediatric Sepsis.

PubMed

Hu, Li; Zhu, Yimin; Chen, Mengshi; Li, Xun; Lu, Xiulan; Liang, Ying; Tan, Hongzhuan

2016-07-01

Multiple severity scoring systems have been devised and evaluated in adult sepsis, but a simplified scoring model for pediatric sepsis has not yet been developed. This study aimed to develop and validate a new scoring model to stratify the severity of pediatric sepsis, thus assisting the treatment of sepsis in children. Data from 634 consecutive patients who presented with sepsis at Children's hospital of Hunan province in China in 2011-2013 were analyzed, with 476 patients placed in training group and 158 patients in validation group. Stepwise discriminant analysis was used to develop the accurate discriminate model. A simplified scoring model was generated using weightings defined by the discriminate coefficients. The discriminant ability of the model was tested by receiver operating characteristic curves (ROC). The discriminant analysis showed that prothrombin time, D-dimer, total bilirubin, serum total protein, uric acid, PaO2/FiO2 ratio, myoglobin were associated with severity of sepsis. These seven variables were assigned with values of 4, 3, 3, 4, 3, 3, 3 respectively based on the standardized discriminant coefficients. Patients with higher scores had higher risk of severe sepsis. The areas under ROC (AROC) were 0.836 for accurate discriminate model, and 0.825 for simplified scoring model in validation group. The proposed disease severity scoring model for pediatric sepsis showed adequate discriminatory capacity and sufficient accuracy, which has important clinical significance in evaluating the severity of pediatric sepsis and predicting its progress.

Local connected fractal dimension analysis in gill of fish experimentally exposed to toxicants.

PubMed

Manera, Maurizio; Giari, Luisa; De Pasquale, Joseph A; Sayyaf Dezfuli, Bahram

2016-06-01

An operator-neutral method was implemented to objectively assess European seabass, Dicentrarchus labrax (Linnaeus, 1758) gill pathology after experimental exposure to cadmium (Cd) and terbuthylazine (TBA) for 24 and 48h. An algorithm-derived local connected fractal dimension (LCFD) frequency measure was used in this comparative analysis. Canonical variates (CVA) and linear discriminant analysis (LDA) were used to evaluate the discrimination power of the method among exposure classes (unexposed, Cd exposed, TBA exposed). Misclassification, sensitivity and specificity, both with original and cross-validated cases, were determined. LCFDs frequencies enhanced the differences among classes which were visually selected after their means, respective variances and the differences between Cd and TBA exposed means, with respect to unexposed mean, were analyzed by scatter plots. Selected frequencies were then scanned by means of LDA, stepwise analysis, and Mahalanobis distance to detect the most discriminative frequencies out of ten originally selected. Discrimination resulted in 91.7% of cross-validated cases correctly classified (22 out of 24 total cases), with sensitivity and specificity, respectively, of 95.5% (1 false negative with respect to 21 really positive cases) and 75% (1 false positive with respect to 3 really negative cases). CVA with convex hull polygons ensured prompt, visually intuitive discrimination among exposure classes and graphically supported the false positive case. The combined use of semithin sections, which enhanced the visual evaluation of the overall lamellar structure; of LCFD analysis, which objectively detected local variation in complexity, without the possible bias connected to human personnel; and of CVA/LDA, could be an objective, sensitive and specific approach to study fish gill lamellar pathology. Furthermore this approach enabled discrimination with sufficient confidence between exposure classes or pathological states and avoided misdiagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Children's attitudes toward violence on television.

PubMed

Hough, K J; Erwin, P G

1997-07-01

Children's attitudes toward television violence were studied. A 47-item questionnaire collecting attitudinal and personal information was administered to 316 children aged 11 to 16 years. Cluster analysis was used to split the participants into two groups based on their attitudes toward television violence. A stepwise discriminant function analysis was performed to determine which personal characteristics would predict group membership. The only significant predictor of attitudes toward violence on television was the amount of television watched on school days (p < .05), but we also found that the impact of other predictor variables may have been mediated by this factor.

A 4-gene panel as a marker at chromosome 8q in Asian gastric cancer patients.

PubMed

Cheng, Lei; Zhang, Qing; Yang, Sheng; Yang, Yanqing; Zhang, Wen; Gao, Hengjun; Deng, Xiaxing; Zhang, Qinghua

2013-10-01

A widely held viewpoint is that the use of multiple markers, combined in some type of algorithm, will be necessary to provide high enough discrimination between diseased cases and non-diseased. We applied stepwise logistic regression analysis to identify the best combination of the 32 biomarkers at chromosome 8q on an independent public microarray test set of 80 paired gastric samples. A combination of SULF1, INTS8, ATP6V1C1, and GPR172A was identified with a prediction accuracy of 98.0% for discriminating carcinomas from adjacent noncancerous tissues in our previous 25 paired samples. Interestingly, the overexpression of SULF1 was associated with tumor invasion and metastasis. Function prediction analysis revealed that the 4-marker panel was mainly associated with acidification of intracellular compartments. Taken together, we found a 4-gene panel that accurately discriminated gastric carcinomas from adjacent noncancerous tissues and these results had potential clinical significance in the early diagnosis and targeted treatment of gastric cancer. Copyright © 2013 Elsevier Inc. All rights reserved.

Sex assessment using measurements of the first lumbar vertebra.

PubMed

Zheng, Wen Xu; Cheng, Fu Bo; Cheng, Kai Liang; Tian, Yong; Lai, Ying; Zhang, Wen Song; Zheng, Ya Juan; Li, You Qiong

2012-06-10

Sex determination is a vital part of the medico-legal system but can be difficult in cases where the integrity of the body has been compromised. The purpose of this study was to develop a technique for sex assessment from measurements of the first lumber vertebrate. Twenty-nine linear measurements and five ratios were collected from 113 Chinese adult males and 97 Chinese adult females using digital three-dimensional anthropometry methods. By using discriminant analysis, we found that 23 linear measurements and two ratios identified sexual dimorphism (P<0.01), with predictive accuracy ranging from 57.1% to 86.6%. Using a stepwise method of discriminant function analysis, we found three dimensions predicted sex with 88.6% accuracy: (a) upper end-plate width (EPWu), (b) left pedicle height (PHl), and (c) middle end-plate depth (EPDm). This study shows that a single first lumber vertebra can be used for this purpose, and that the discriminant equation will help forensic determination of sex in the Chinese population. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Artificial nose, NIR and UV-visible spectroscopy for the characterisation of the PDO Chianti Classico olive oil.

PubMed

Forina, M; Oliveri, P; Bagnasco, L; Simonetti, R; Casolino, M C; Nizzi Grifi, F; Casale, M

2015-11-01

An authentication study of the Italian PDO (Protected Designation of Origin) olive oil Chianti Classico, based on artificial nose, near-infrared and UV-visible spectroscopy, with a set of samples representative of the whole Chianti Classico production area and a considerable number of samples from other Italian PDO regions was performed. The signals provided by the three analytical techniques were used both individually and jointly, after fusion of the respective variables, in order to build a model for the Chianti Classico PDO olive oil. Different signal pre-treatments were performed in order to investigate their importance and their effects in enhancing and extracting information from experimental data, correcting backgrounds or removing baseline variations. Stepwise-Linear Discriminant Analysis (STEP-LDA) was used as a feature selection technique and, afterward, Linear Discriminant Analysis (LDA) and the class-modelling technique Quadratic Discriminant Analysis-UNEQual dispersed classes (QDA-UNEQ) were applied to sub-sets of selected variables, in order to obtain efficient models capable of characterising the extra virgin olive oils produced in the Chianti Classico PDO area. Copyright © 2015 Elsevier B.V. All rights reserved.

Discrimination among spawning aggregations of lake herring from Lake Superior using whole-body morphometric characters

USGS Publications Warehouse

Hoff, Michael H.

2004-01-01

The lake herring (Coregonus artedi) was one of the most commercially and ecologically valuable Lake Superior fishes, but declined in the second half of the 20th century as the result of overharvest of putatively discrete stocks. No tools were previously available that described lake herring stock structure and accurately classified lake herring to their spawning stocks. The accuracy of discriminating among spawning aggregations was evaluated using whole-body morphometrics based on a truss network. Lake herring were collected from 11 spawning aggregations in Lake Superior and two inland Wisconsin lakes to evaluate morphometrics as a stock discrimination tool. Discriminant function analysis correctly classified 53% of all fish from all spawning aggregations, and fish from all but one aggregation were classified at greater rates than were possible by chance. Discriminant analysis also correctly classified 66% of fish to nearest neighbor groups, which were groups that accounted for the possibility of mixing among the aggregations. Stepwise discriminant analysis showed that posterior body length and depth measurements were among the best discriminators of spawning aggregations. These findings support other evidence that discrete stocks of lake herring exist in Lake Superior, and fishery managers should consider all but one of the spawning aggregations as discrete stocks. Abundance, annual harvest, total annual mortality rate, and exploitation data should be collected from each stock, and surplus production of each stock should be estimated. Prudent management of stock surplus production and exploitation rates will aid in restoration of stocks and will prevent a repeat of the stock collapses that occurred in the middle of the 20th century, when the species was nearly extirpated from the lake.

Remote Sensing as a Landscape Epidemiologic Tool to Identify Villages at High Risk for Malaria Transmission

NASA Technical Reports Server (NTRS)

Beck, Louisa R.; Rodriquez, Mario H.; Dister, Sheri W.; Rodriquez, Americo D.; Rejmankova, Eliska; Ulloa, Armando; Meza, Rosa A.; Roberts, Donald R.; Paris, Jack F.; Spanner, Michael A.;

Inter- and intraspecific diversity in Cistus L. (Cistaceae) seeds, analysed with computer vision techniques.

PubMed

Lo Bianco, M; Grillo, O; Cañadas, E; Venora, G; Bacchetta, G

2017-03-01

This work aims to discriminate among different species of the genus Cistus, using seed parameters and following the scientific plant names included as accepted in The Plant List. Also, the intraspecific phenotypic differentiation of C. creticus, through comparison with three subspecies (C. creticus subsp. creticus, C. c. subsp. eriocephalus and C. c. subsp. corsicus), as well as the interpopulation variability among five C. creticus subsp. eriocephalus populations was evaluated. Seed mean weight and 137 morphocolorimetric quantitative variables, describing shape, size, colour and textural seed traits, were measured using image analysis techniques. Measured data were analysed applying step-wise linear discriminant analysis. An overall cross-validated classification performance of 80.6% was recorded at species level. With regard to C. creticus, as case study, percentages of correct discrimination of 96.7% and 99.6% were achieved at intraspecific and interpopulation levels, respectively. In this classification model, the relevance of the colorimetric and textural descriptive features was highlighted, as well as the seed mean weight, which was the most discriminant feature at specific and intraspecific level. These achievements proved the ability of the image analysis system as highly diagnostic for systematic purposes and confirm that seeds in the genus Cistus have important diagnostic value. © 2016 German Botanical Society and The Royal Botanical Society of the Netherlands.

Virtual Assessment of Sex: Linear and Angular Traits of the Mandibular Ramus Using Three-Dimensional Computed Tomography.

PubMed

Inci, Ercan; Ekizoglu, Oguzhan; Turkay, Rustu; Aksoy, Sema; Can, Ismail Ozgur; Solmaz, Dilek; Sayin, Ibrahim

2016-10-01

Morphometric analysis of the mandibular ramus (MR) provides highly accurate data to discriminate sex. The objective of this study was to demonstrate the utility and accuracy of MR morphometric analysis for sex identification in a Turkish population.Four hundred fifteen Turkish patients (18-60 y; 201 male and 214 female) who had previously had multidetector computed tomography scans of the cranium were included in the study. Multidetector computed tomography images were obtained using three-dimensional reconstructions and a volume-rendering technique, and 8 linear and 3 angular values were measured. Univariate, bivariate, and multivariate discriminant analyses were performed, and the accuracy rates for determining sex were calculated.Mandibular ramus values produced high accuracy rates of 51% to 95.6%. Upper ramus vertical height had the highest rate at 95.6%, and bivariate analysis showed 89.7% to 98.6% accuracy rates with the highest ratios of mandibular flexure upper border and maximum ramus breadth. Stepwise discrimination analysis gave a 99% accuracy rate for all MR variables.Our study showed that the MR, in particular morphometric measures of the upper part of the ramus, can provide valuable data to determine sex in a Turkish population. The method combines both anthropological and radiologic studies.

Cloud field classification based upon high spatial resolution textural features. I - Gray level co-occurrence matrix approach

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1988-01-01

Stratocumulus, cumulus, and cirrus clouds were identified on the basis of cloud textural features which were derived from a single high-resolution Landsat MSS NIR channel using a stepwise linear discriminant analysis. It is shown that, using this method, it is possible to distinguish high cirrus clouds from low clouds with high accuracy on the basis of spatial brightness patterns. The largest probability of misclassification is associated with confusion between the stratocumulus breakup regions and the fair-weather cumulus.

Computer-assisted sperm morphometry fluorescence-based analysis has potential to determine progeny sex.

PubMed

Santolaria, Pilar; Pauciullo, Alfredo; Silvestre, Miguel A; Vicente-Fiel, Sandra; Villanova, Leyre; Pinton, Alain; Viruel, Juan; Sales, Ester; Yániz, Jesús L

2016-01-01

This study was designed to determine the ability of computer-assisted sperm morphometry analysis (CASA-Morph) with fluorescence to discriminate between spermatozoa carrying different sex chromosomes from the nuclear morphometrics generated and different statistical procedures in the bovine species. The study was divided into two experiments. The first was to study the morphometric differences between X- and Y-chromosome-bearing spermatozoa (SX and SY, respectively). Spermatozoa from eight bulls were processed to assess simultaneously the sex chromosome by FISH and sperm morphometry by fluorescence-based CASA-Morph. SX cells were larger than SY cells on average (P < 0.001) although with important differences between bulls. A simultaneous evaluation of all the measured features by discriminant analysis revealed that nuclear area and average fluorescence intensity were the variables selected by stepwise discriminant function analysis as the best discriminators between SX and SY. In the second experiment, the sperm nuclear morphometric results from CASA-Morph in nonsexed (mixed SX and SY) and sexed (SX) semen samples from four bulls were compared. FISH allowed a successful classification of spermatozoa according to their sex chromosome content. X-sexed spermatozoa displayed a larger size and fluorescence intensity than nonsexed spermatozoa (P < 0.05). We conclude that the CASA-Morph fluorescence-based method has the potential to find differences between X- and Y-chromosome-bearing spermatozoa in bovine species although more studies are needed to increase the precision of sex determination by this technique.

Optical system for tablet variety discrimination using visible/near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Shao, Yongni; He, Yong; Hu, Xingyue

2007-12-01

An optical system based on visible/near-infrared spectroscopy (Vis/NIRS) for variety discrimination of ginkgo (Ginkgo biloba L.) tablets was developed. This system consisted of a light source, beam splitter system, sample chamber, optical detector (diffuse reflection detector), and data collection. The tablet varieties used in the research include Da na kang, Xin bang, Tian bao ning, Yi kang, Hua na xing, Dou le, Lv yuan, Hai wang, and Ji yao. All samples (n=270) were scanned in the Vis/NIR region between 325 and 1075 nm using a spectrograph. The chemometrics method of principal component artificial neural network (PC-ANN) was used to establish discrimination models of them. In PC-ANN models, the scores of the principal components were chosen as the input nodes for the input layer of ANN, and the best discrimination rate of 91.1% was reached. Principal component analysis was also executed to select several optimal wavelengths based on loading values. Wavelengths at 481, 458, 466, 570, 1000, 662, and 400 nm were then used as the input data of stepwise multiple linear regression, the regression equation of ginkgo tablets was obtained, and the discrimination rate was researched 84.4%. The results indicated that this optical system could be applied to discriminating ginkgo (Ginkgo biloba L.) tablets, and it supplied a new method for fast ginkgo tablet variety discrimination.

An electroglottographical analysis-based discriminant function model differentiating multiple sclerosis patients from healthy controls.

PubMed

Vavougios, George D; Doskas, Triantafyllos; Konstantopoulos, Kostas

2018-05-01

Dysarthrophonia is a predominant symptom in many neurological diseases, affecting the quality of life of the patients. In this study, we produced a discriminant function equation that can differentiate MS patients from healthy controls, using electroglottographic variables not analyzed in a previous study. We applied stepwise linear discriminant function analysis in order to produce a function and score derived from electroglottographic variables extracted from a previous study. The derived discriminant function's statistical significance was determined via Wilk's λ test (and the associated p value). Finally, a 2 × 2 confusion matrix was used to determine the function's predictive accuracy, whereas the cross-validated predictive accuracy is estimated via the "leave-one-out" classification process. Discriminant function analysis (DFA) was used to create a linear function of continuous predictors. DFA produced the following model (Wilk's λ = 0.043, χ2 = 388.588, p < 0.0001, Tables 3 and 4): D (MS vs controls) = 0.728*DQx1 mean monologue + 0.325*CQx monologue + 0.298*DFx1 90% range monologue + 0.443*DQx1 90% range reading - 1.490*DQx1 90% range monologue. The derived discriminant score (S1) was used subsequently in order to form the coordinates of a ROC curve. Thus, a cutoff score of - 0.788 for S1 corresponded to a perfect classification (100% sensitivity and 100% specificity, p = 1.67e -22 ). Consistent with previous findings, electroglottographic evaluation represents an easy to implement and potentially important assessment in MS patients, achieving adequate classification accuracy. Further evaluation is needed to determine its use as a biomarker.

Multivariate calibration on NIR data: development of a model for the rapid evaluation of ethanol content in bakery products.

PubMed

Bello, Alessandra; Bianchi, Federica; Careri, Maria; Giannetto, Marco; Mori, Giovanni; Musci, Marilena

2007-11-05

A new NIR method based on multivariate calibration for determination of ethanol in industrially packed wholemeal bread was developed and validated. GC-FID was used as reference method for the determination of actual ethanol concentration of different samples of wholemeal bread with proper content of added ethanol, ranging from 0 to 3.5% (w/w). Stepwise discriminant analysis was carried out on the NIR dataset, in order to reduce the number of original variables by selecting those that were able to discriminate between the samples of different ethanol concentrations. With the so selected variables a multivariate calibration model was then obtained by multiple linear regression. The prediction power of the linear model was optimized by a new "leave one out" method, so that the number of original variables resulted further reduced.

Factors associated with cane use among community dwelling older adults.

PubMed

Aminzadeh, F; Edwards, N

2000-01-01

Guided by the Theory of Planned Behavior (TPB), this study examined factors associated with cane use among community dwelling older adults. Data were collected in a cross-sectional survey of a convenience sample of 106 community residing older adults in Ottawa, Canada. Using a stepwise discriminant analysis, subjective norms, attitudes, and age surfaced as the key variables associated with cane use in this sample. The discriminant function accounted for 67% of the variance in cane use and correctly classified 91% of cases (Wilks's lambda = 0.33, lambda2 = 110.12, df = 3, p < 0.0001). The findings provide evidence for the utility of the TPB in its application to understanding cane use behaviors of older persons and have important implications for the design of theory-based fall prevention interventions to enhance the acceptance and effective use of mobility aids.

The relationship between hemoglobin level and the type 1 diabetic nephropathy in Anhui Han's patients.

PubMed

Jiang, Jun; Lei, Lan; Zhou, Xiaowan; Li, Peng; Wei, Ren

2018-02-20

Recent studies have shown that low hemoglobin (Hb) level promote the progression of chronic kidney disease. This study assessed the relationship between Hb level and type 1 diabetic nephropathy (DN) in Anhui Han's patients. There were a total of 236 patients diagnosed with type 1 diabetes mellitus and (T1DM) seen between January 2014 and December 2016 in our centre. Hemoglobin levels in patients with DN were compared with those without DN. The relationship between Hb level and the urinary albumin-creatinine ratio (ACR) was examined by Spearman's correlational analysis and multiple stepwise regression analysis. The binary logistic multivariate regression analysis was performed to analyze the correlated factors for type 1 DN, calculate the Odds Ratio (OR) and 95%confidence interval (CI). The predicting value of Hb level for DN was evaluated by area under receiver operation characteristic curve (AUROC) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration. The average Hb levels in the DN group (116.1 ± 20.8 g/L) were significantly lower than the non-DN group (131.9 ± 14.4 g/L) , P < 0.001. Hb levels were independently correlated with the urinary ACR in multiple stepwise regression analysis. The logistic multivariate regression analysis showed that the Hb level (OR: 0.936, 95% CI: 0.910 to 0.963, P < 0.001) was inversely correlated with DN in patients with T1DM. In sub-analysis, low Hb level (Hb < 120g/L in female, Hb < 130g/L in male) was still negatively associated with DN in patients with T1DM. The AUROC was 0.721 (95% CI: 0.655 to 0.787) in assessing the discrimination of the Hb level for DN. The value of P was 0.593 in Hosmer-Lemeshow goodness-of-fit test. In Anhui Han's patients with T1DM, the Hb level is inversely correlated with urinary ACR and DN. This article is protected by copyright. All rights reserved.

Discrimination and chemical characterization of different Paeonia lactifloras (Radix Paeoniae Alba and Radix Paeoniae Rubra) by infrared macro-fingerprint analysis-through-separation

NASA Astrophysics Data System (ADS)

Wang, Yang; Wang, Ping; Xu, Changhua; Sun, Suqin; Zhou, Qun; Shi, Zhe; Li, Jin; Chen, Tao; Li, Zheng; Cui, Weili

2015-11-01

Paeonia lactiflora, a commonly used herbal medicine (HM) in Traditional Chinese Medicine (TCM), mainly has two species, Radix Paeoniae Alba (RPA) and Radix Paeoniae Rubra (RPR), for different clinical applications in TCM. For expounding the chemical profile of RPA and RPR and ensuring the clinical efficacy and safety, an infrared macro-fingerprint analysis-through-separation method integrated with statistical pattern recognition was developed to analyze and discriminate the two Paeonia lactifloras. In IR spectra, the major difference between the two was in the range of 1200-900 cm-1: the strongest peak of RPA was at 1024 cm-1, while that of RPR was 1049 cm-1. The difference was magnified in second derivative spectra. The findings were further verified by investigating the separation process of total glucosides, stepwisely monitored by both of IR and UPLC-MS/MS. Simultaneously, the aqueous extracts of RPA and RPR had been separated continuously to acquire the comprehensively hierarchical chemical characteristics for undoubtedly identification and subsequently discrimination of the two herbs. Moreover, 60 batches of the two HMs (30 for each) were objectively classified by principal component regression (PCR) model based on IR macro-fingerprints.

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

PubMed Central

Ferrand, Claude; Audiffren, Michel

2018-01-01

Background Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. Results A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging. PMID:29850247

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis.

PubMed

André, Nathalie; Ferrand, Claude; Albinet, Cédric; Audiffren, Michel

2018-01-01

Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging.

Use of handheld X-ray fluorescence as a non-invasive method to distinguish between Asian and African elephant tusks

PubMed Central

Buddhachat, Kittisak; Thitaram, Chatchote; Brown, Janine L.; Klinhom, Sarisa; Bansiddhi, Pakkanut; Penchart, Kitichaya; Ouitavon, Kanita; Sriaksorn, Khanittha; Pa-in, Chalermpol; Kanchanasaka, Budsabong; Somgird, Chaleamchat; Nganvongpanit, Korakot

2016-01-01

We describe the use of handheld X-ray fluorescence, for elephant tusk species identification. Asian (n = 72) and African (n = 85) elephant tusks were scanned and we utilized the species differences in elemental composition to develop a functional model differentiating between species with high precision. Spatially, the majority of measured elements (n = 26) exhibited a homogeneous distribution in cross-section, but a more heterologous pattern in the longitudinal direction. Twenty-one of twenty four elements differed between Asian and African samples. Data were subjected to hierarchical cluster analysis followed by a stepwise discriminant analysis, which identified elements for the functional equation. The best equation consisted of ratios of Si, S, Cl, Ti, Mn, Ag, Sb and W, with Zr as the denominator. Next, Bayesian binary regression model analysis was conducted to predict the probability that a tusk would be of African origin. A cut-off value was established to improve discrimination. This Bayesian hybrid classification model was then validated by scanning an additional 30 Asian and 41 African tusks, which showed high accuracy (94%) and precision (95%) rates. We conclude that handheld XRF is an accurate, non-invasive method to discriminate origin of elephant tusks provides rapid results applicable to use in the field. PMID:27097717

Use of handheld X-ray fluorescence as a non-invasive method to distinguish between Asian and African elephant tusks

NASA Astrophysics Data System (ADS)

Buddhachat, Kittisak; Thitaram, Chatchote; Brown, Janine L.; Klinhom, Sarisa; Bansiddhi, Pakkanut; Penchart, Kitichaya; Ouitavon, Kanita; Sriaksorn, Khanittha; Pa-in, Chalermpol; Kanchanasaka, Budsabong; Somgird, Chaleamchat; Nganvongpanit, Korakot

2016-04-01

We describe the use of handheld X-ray fluorescence, for elephant tusk species identification. Asian (n = 72) and African (n = 85) elephant tusks were scanned and we utilized the species differences in elemental composition to develop a functional model differentiating between species with high precision. Spatially, the majority of measured elements (n = 26) exhibited a homogeneous distribution in cross-section, but a more heterologous pattern in the longitudinal direction. Twenty-one of twenty four elements differed between Asian and African samples. Data were subjected to hierarchical cluster analysis followed by a stepwise discriminant analysis, which identified elements for the functional equation. The best equation consisted of ratios of Si, S, Cl, Ti, Mn, Ag, Sb and W, with Zr as the denominator. Next, Bayesian binary regression model analysis was conducted to predict the probability that a tusk would be of African origin. A cut-off value was established to improve discrimination. This Bayesian hybrid classification model was then validated by scanning an additional 30 Asian and 41 African tusks, which showed high accuracy (94%) and precision (95%) rates. We conclude that handheld XRF is an accurate, non-invasive method to discriminate origin of elephant tusks provides rapid results applicable to use in the field.

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

Feature extraction and selection from volatile compounds for analytical classification of Chinese red wines from different varieties.

PubMed

Zhang, Jian; Li, Li; Gao, Nianfa; Wang, Depei; Gao, Qiang; Jiang, Shengping

2010-03-10

This work was undertaken to evaluate whether it is possible to determine the variety of a Chinese wine on the basis of its volatile compounds, and to investigate if discrimination models could be developed with the experimental wines that could be used for the commercial ones. A headspace solid-phase microextraction gas chromatographic (HS-SPME-GC) procedure was used to determine the volatile compounds and a blind analysis based on Ac/Ais (peak area of volatile compound/peak area of internal standard) was carried out for statistical purposes. One way analysis of variance (ANOVA), principal component analysis (PCA) and stepwise linear discriminant analysis (SLDA) were used to process data and to develop discriminant models. Only 11 peaks enabled to differentiate and classify the experimental wines. SLDA allowed 100% recognition ability for three grape varieties, 100% prediction ability for Cabernet Sauvignon and Cabernet Gernischt wines, but only 92.31% for Merlot wines. A more valid and robust way was to use the PCA scores to do the discriminant analysis. When we performed SLDA this way, 100% recognition ability and 100% prediction ability were obtained. At last, 11 peaks which selected by SLDA from raw analysis set had been identified. When we demonstrated the models using commercial wines, the models showed 100% recognition ability for the wines collected directly from winery and without ageing, but only 65% for the others. Therefore, the varietal factor was currently discredited as a differentiating parameter for commercial wines in China. Nevertheless, this method could be applied as a screening tool and as a complement to other methods for grape base liquors which do not need ageing and blending procedures. 2010 Elsevier B.V. All rights reserved.

Application of remote sensing for fishery resources assessment and monitoring. [Gulf of Mexico

NASA Technical Reports Server (NTRS)

Savastano, K. J. (Principal Investigator)

1975-01-01

The author has identified the following significant results. The distribution and abundance of white marlin correlated with the chlorophyll, water temperature, and Secchi depth sea truth measurements. Results of correlation analyses for dolphin were inconclusive. Predicition models for white marlin were developed using stepwise multiple regression and discriminant function analysis techniques which demonstrated a potential for increasing the probability of game fishing success. The S190A and B imagery was density sliced/color enhanced with white marlin location superimposed on the image, but no density/white marlin relationship could be established.

Feasibility of detecting aflatoxin B1 on inoculated maize kernels surface using Vis/NIR hyperspectral imaging.

PubMed

Wang, Wei; Heitschmidt, Gerald W; Windham, William R; Feldner, Peggy; Ni, Xinzhi; Chu, Xuan

2015-01-01

The feasibility of using a visible/near-infrared hyperspectral imaging system with a wavelength range between 400 and 1000 nm to detect and differentiate different levels of aflatoxin B1 (AFB1 ) artificially titrated on maize kernel surface was examined. To reduce the color effects of maize kernels, image analysis was limited to a subset of original spectra (600 to 1000 nm). Residual staining from the AFB1 on the kernels surface was selected as regions of interest for analysis. Principal components analysis (PCA) was applied to reduce the dimensionality of hyperspectral image data, and then a stepwise factorial discriminant analysis (FDA) was performed on latent PCA variables. The results indicated that discriminant factors F2 can be used to separate control samples from all of the other groups of kernels with AFB1 inoculated, whereas the discriminant factors F1 can be used to identify maize kernels with levels of AFB1 as low as 10 ppb. An overall classification accuracy of 98% was achieved. Finally, the peaks of β coefficients of the discrimination factors F1 and F2 were analyzed and several key wavelengths identified for differentiating maize kernels with and without AFB1 , as well as those with differing levels of AFB1 inoculation. Results indicated that Vis/NIR hyperspectral imaging technology combined with the PCA-FDA was a practical method to detect and differentiate different levels of AFB1 artificially inoculated on the maize kernels surface. However, indicated the potential to detect and differentiate naturally occurring toxins in maize kernel. © 2014 Institute of Food Technologists®

Differentiating major depressive disorder in youths with attention deficit hyperactivity disorder.

PubMed

Diler, Rasim Somer; Daviss, W Burleson; Lopez, Adriana; Axelson, David; Iyengar, Satish; Birmaher, Boris

2007-09-01

Youths with attention deficit hyperactivity disorders (ADHD) frequently have comorbid major depressive disorders (MDD) sharing overlapping symptoms. Our objective was to examine which depressive symptoms best discriminate MDD among youths with ADHD. One-hundred-eleven youths with ADHD (5.2-17.8 years old) and their parents completed interviews with the K-SADS-PL and respective versions of the child or the parent Mood and Feelings Questionnaire (MFQ-C, MFQ-P). Controlling for group differences, logistic regression was used to calculate odds ratios reflecting the accuracy with which various depressive symptoms on the MFQ-C or MFQ-P discriminated MDD. Stepwise logistic regression then identified depressive symptoms that best discriminated the groups with and without MDD, using cross-validated misclassification rate as the criterion. Symptoms that discriminated youths with MDD (n=18) from those without MDD (n=93) were 4 of 6 mood/anhedonia symptoms, all 14 depressed cognition symptoms, and only 3 of 11 physical/vegetative symptoms. Mild irritability, miserable/unhappy moods, and symptoms related to sleep, appetite, energy levels and concentration did not discriminate MDD. A stepwise logistic regression correctly classified 89% of the comorbid MDD subjects, with only age, anhedonia at school, thoughts about killing self, thoughts that bad things would happen, and talking more slowly remaining in the final model. Results of this study may not generalize to community samples because subjects were drawn largely from a university-based outpatient psychiatric clinic. These findings stress the importance of social withdrawal, anhedonia, depressive cognitions, suicidal thoughts, and psychomotor retardation when trying to identify MDD among ADHD youths.

Overlapped Partitioning for Ensemble Classifiers of P300-Based Brain-Computer Interfaces

PubMed Central

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance. PMID:24695550

Overlapped partitioning for ensemble classifiers of P300-based brain-computer interfaces.

PubMed

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance.

Application of the laguerre deconvolution method for time-resolved fluorescence spectroscopy to the characterization of atherosclerotic plaques.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Beseth, B; Dorafshar, A H; Reil, T; Baker, D; Freischlag, J; Marcu, L

2005-01-01

This study investigates the ability of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) to detect inflammation in atherosclerotic lesion, a key feature of plaque vulnerability. A total of 348 TR-LIFS measurements were taken from carotid plaques of 30 patients, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as Early, Fibrotic/Calcified or Inflamed lesions. A stepwise linear discriminant analysis algorithm was developed using spectral and TR features (normalized intensity values and Laguerre expansion coefficients at discrete emission wavelengths, respectively). Features from only three emission wavelengths (390, 450 and 500 nm) were used in the classifier. The Inflamed lesions were discriminated with sensitivity > 80% and specificity > 90 %, when the Laguerre expansion coefficients were included in the feature space. These results indicate that TR-LIFS information derived from the Laguerre expansion coefficients at few selected emission wavelengths can discriminate inflammation in atherosclerotic plaques. We believe that TR-LIFS derived Laguerre expansion coefficients can provide a valuable additional dimension for the detection of vulnerable plaques.

Discrimination of nuclear explosions and earthquakes from teleseismic distances with a local network of short period seismic stations using artificial neural networks

NASA Astrophysics Data System (ADS)

Tiira, Timo

1996-10-01

Seismic discrimination capability of artificial neural networks (ANNs) was studied using earthquakes and nuclear explosions from teleseismic distances. The events were selected from two areas, which were analyzed separately. First, 23 nuclear explosions from Semipalatinsk and Lop Nor test sites were compared with 46 earthquakes from adjacent areas. Second, 39 explosions from Nevada test site were compared with 27 earthquakes from close-by areas. The basic discriminants were complexity, spectral ratio and third moment of frequency. The spectral discriminants were computed in five different ways to obtain all the information embedded in the signals, some of which were relatively weak. The discriminants were computed using data from six short period stations in Central and southern Finland. The spectral contents of the signals of both classes varied considerably between the stations. The 66 discriminants were formed into 65 optimum subsets of different sizes by using stepwise linear regression. A type of ANN called multilayer perceptron (MLP) was applied to each of the subsets. As a comparison the classification was repeated using linear discrimination analysis (LDA). Since the number of events was small the testing was made with the leave-one-out method. The ANN gave significantly better results than LDA. As a final tool for discrimination a combination of the ten neural nets with the best performance were used. All events from Central Asia were clearly discriminated and over 90% of the events from Nevada region were confidently discriminated. The better performance of ANNs was attributed to its ability to form complex decision regions between the groups and to its highly non-linear nature.

A discriminant function model as an alternative method to spirometry for COPD screening in primary care settings in China.

PubMed

Cui, Jiangyu; Zhou, Yumin; Tian, Jia; Wang, Xinwang; Zheng, Jingping; Zhong, Nanshan; Ran, Pixin

2012-12-01

COPD is often underdiagnosed in a primary care setting where the spirometry is unavailable. This study was aimed to develop a simple, economical and applicable model for COPD screening in those settings. First we established a discriminant function model based on Bayes' Rule by stepwise discriminant analysis, using the data from 243 COPD patients and 112 non-COPD subjects from our COPD survey in urban and rural communities and local primary care settings in Guangdong Province, China. We then used this model to discriminate COPD in additional 150 subjects (50 non-COPD and 100 COPD ones) who had been recruited by the same methods as used to have established the model. All participants completed pre- and post-bronchodilator spirometry and questionnaires. COPD was diagnosed according to the Global Initiative for Chronic Obstructive Lung Disease criteria. The sensitivity and specificity of the discriminant function model was assessed. THE ESTABLISHED DISCRIMINANT FUNCTION MODEL INCLUDED NINE VARIABLES: age, gender, smoking index, body mass index, occupational exposure, living environment, wheezing, cough and dyspnoea. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, accuracy and error rate of the function model to discriminate COPD were 89.00%, 82.00%, 4.94, 0.13, 86.66% and 13.34%, respectively. The accuracy and Kappa value of the function model to predict COPD stages were 70% and 0.61 (95% CI, 0.50 to 0.71). This discriminant function model may be used for COPD screening in primary care settings in China as an alternative option instead of spirometry.

Authentication of animal fats using direct analysis in real time (DART) ionization-mass spectrometry and chemometric tools.

PubMed

Vaclavik, Lukas; Hrbek, Vojtech; Cajka, Tomas; Rohlik, Bo-Anne; Pipek, Petr; Hajslova, Jana

2011-06-08

A combination of direct analysis in real time (DART) ionization coupled to time-of-flight mass spectrometry (TOFMS) and chemometrics was used for animal fat (lard and beef tallow) authentication. This novel instrumentation was employed for rapid profiling of triacylglycerols (TAGs) and polar compounds present in fat samples and their mixtures. Additionally, fat isolated from pork, beef, and pork/beef admixtures was analyzed. Mass spectral records were processed by principal component analysis (PCA) and stepwise linear discriminant analysis (LDA). DART-TOFMS profiles of TAGs were found to be more suitable for the purpose of discrimination among the examined fat types as compared to profiles of polar compounds. The LDA model developed using TAG data enabled not only reliable classification of samples representing neat fats but also detection of admixed lard and tallow at adulteration levels of 5 and 10% (w/w), respectively. The presented approach was also successfully applied to minced meat prepared from pork and beef with comparable fat content. Using the DART-TOFMS TAG profiles of fat isolated from meat mixtures, detection of 10% pork added to beef and vice versa was possible.

Transthyretin familial amyloid polyneuropathy (TTR-FAP): Parameters for early diagnosis.

PubMed

Escolano-Lozano, Fabiola; Barreiros, Ana Paula; Birklein, Frank; Geber, Christian

2018-01-01

Familial transthyretin amyloidosis is a life-threatening disease presenting with sensorimotor and autonomic polyneuropathy. Delayed diagnosis has a detrimental effect on treatment and prognosis. To facilitate diagnosis, we analyzed data patterns of patients with transthyretin familial amyloid polyneuropathy (TTR-FAP) and compared them to polyneuropathies of different etiology for clinical and electrophysiological discriminators. Twenty-four patients with TTR-FAP and 48 patients with diabetic polyneuropathy (dPNP) were investigated (neurological impairment score NIS; neurological disability score NDS) in a cross-sectional design. Both groups were matched for gender and presence of pain. Quantitative sensory testing (QST), sympathetic skin response (SSR), heart rate variability (HRV), and nerve conduction studies (NCV) were performed. Both groups were compared using univariate analysis. In a stepwise discriminant analysis, discriminators between both neuropathies were identified. These discriminators were validated comparing TTR-FAP patients with a cohort of patients with chemotherapy-induced polyneuropathy (CIN) and chronic inflammatory demyelinating neuropathy (CIDP). TTR-FAP patients scored higher in NDS and NIS and had impaired cold detection (CDT, p  = .024), cold-warm discrimination (TSL, p  = .019) and mechanical hyperalgesia (MPT, p  = .029) at the hands, SSR (upper limb, p  = .022) HRV and ulnar and sural NCS (all p  < .05) were more affected in TTR-FAP. Ulnar nerve sensory NCV, CDT, and the MPT but not the other parameters discriminated TTR-FAP from dPNP (82% of cases), from CIN (86.7%) and from CIDP (68%; only ulnar sNCV). Low ulnar SNCV, impaired cold perception, and mechanical hyperalgesia at the hands seem to characterize TTR-FAP and might help to differentiate from other polyneuropathies.

[Study on the genuineness and producing area of Panax notoginseng based on infrared spectroscopy combined with discriminant analysis].

PubMed

Liu, Fei; Wang, Yuan-zhong; Yang, Chun-yan; Jin, Hang

2015-01-01

The genuineness and producing area of Panax notoginseng were studied based on infrared spectroscopy combined with discriminant analysis. The infrared spectra of 136 taproots of P. notoginseng from 13 planting point in 11 counties were collected and the second derivate spectra were calculated by Omnic 8. 0 software. The infrared spectra and their second derivate spectra in the range 1 800 - 700 cm-1 were used to build model by stepwise discriminant analysis, which was in order to distinguish study on the genuineness of P. notoginseng. The model built based on the second derivate spectra showed the better recognition effect for the genuineness of P. notoginseng. The correct rate of returned classification reached to 100%, and the prediction accuracy was 93. 4%. The stability of model was tested by cross validation and the method was performed extrapolation validation. The second derivate spectra combined with the same discriminant analysis method were used to distinguish the producing area of P. notoginseng. The recognition effect of models built based on different range of spectrum and different numbers of samples were compared and found that when the model was built by collecting 8 samples from each planting point as training sample and the spectrum in the range 1 500 - 1 200 cm-1 , the recognition effect was better, with the correct rate of returned classification reached to 99. 0%, and the prediction accuracy was 76. 5%. The results indicated that infrared spectroscopy combined with discriminant analysis showed good recognition effect for the genuineness of P. notoginseng. The method might be a hopeful new method for identification of genuineness of P. notoginseng in practice. The method could recognize the producing area of P. notoginseng to some extent and could be a new thought for identification of the producing area of P. natoginseng.

Distinguishing fibromyalgia from rheumatoid arthritis and systemic lupus in clinical questionnaires: an analysis of the revised Fibromyalgia Impact Questionnaire (FIQR) and its variant, the Symptom Impact Questionnaire (SIQR), along with pain locations

PubMed Central

2011-01-01

Introduction The purpose of this study was to explore a data set of patients with fibromyalgia (FM), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) who completed the Revised Fibromyalgia Impact Questionnaire (FIQR) and its variant, the Symptom Impact Questionnaire (SIQR), for discriminating features that could be used to differentiate FM from RA and SLE in clinical surveys. Methods The frequency and means of comparing FM, RA and SLE patients on all pain sites and SIQR variables were calculated. Multiple regression analysis was then conducted to identify the significant pain sites and SIQR predictors of group membership. Thereafter stepwise multiple regression analysis was performed to identify the order of variables in predicting their maximal statistical contribution to group membership. Partial correlations assessed their unique contribution, and, last, two-group discriminant analysis provided a classification table. Results The data set contained information on the SIQR and also pain locations in 202 FM, 31 RA and 20 SLE patients. As the SIQR and pain locations did not differ much between the RA and SLE patients, they were grouped together (RA/SLE) to provide a more robust analysis. The combination of eight SIQR items and seven pain sites correctly classified 99% of FM and 90% of RA/SLE patients in a two-group discriminant analysis. The largest reported SIQR differences (FM minus RA/SLE) were seen for the parameters "tenderness to touch," "difficulty cleaning floors" and "discomfort on sitting for 45 minutes." Combining the SIQR and pain locations in a stepwise multiple regression analysis revealed that the seven most important predictors of group membership were mid-lower back pain (29%; 79% vs. 16%), tenderness to touch (11.5%; 6.86 vs. 3.02), neck pain (6.8%; 91% vs. 39%), hand pain (5%; 64% vs. 77%), arm pain (3%; 69% vs. 18%), outer lower back pain (1.7%; 80% vs. 22%) and sitting for 45 minutes (1.4%; 5.56 vs. 1.49). Conclusions A combination of two SIQR questions ("tenderness to touch" and "difficulty sitting for 45 minutes") plus pain in the lower back, neck, hands and arms may be useful in the construction of clinical questionnaires designed for patients with musculoskeletal pain. This combination provided the correct diagnosis in 97% of patients, with only 7 of 253 patients misclassified. PMID:21477308

Sex determination from the talus in a contemporary Greek population using discriminant function analysis.

PubMed

Peckmann, Tanya R; Orr, Kayla; Meek, Susan; Manolis, Sotiris K

2015-07-01

The determination of sex is an important part of building the biological profile for unknown human remains. Many of the bones traditionally used for the determination of sex are often found fragmented or incomplete in forensic and archaeological cases. The goal of the present research was to derive discriminant function equations from the talus, a preservationally favoured bone, for sexing skeletons from a contemporary Greek population. Nine parameters were measured on 182 individuals (96 males and 86 females) from the University of Athens Human Skeletal Reference Collection. The individuals ranged in age from 20 to 99 years old. The statistical analyses showed that all measured parameters were sexually dimorphic. Discriminant function score equations were generated for use in sex determination. The average accuracy of sex classification ranged from 65.2% to 93.4% for the univariate analysis, 90%-96.5% for the direct method and 86.7% for the stepwise method. Comparisons to other populations were made. Overall, the cross-validated accuracies ranged from 65.5% to 83.2% and males were most often correctly identified. The talus was shown to be useful for sex determination in the modern Greek population. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops

PubMed Central

de Castro, Ana-Isabel; Jurado-Expósito, Montserrat; Gómez-Casero, María-Teresa; López-Granados, Francisca

2012-01-01

In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance between cruciferous weeds, we applied three classification methods: stepwise discriminant (STEPDISC) analysis and two neural networks, specifically, multilayer perceptron (MLP) and radial basis function (RBF). Hyperspectral and multispectral signatures of cruciferous weeds, and wheat and broad bean crops can be classified using STEPDISC analysis, and MLP and RBF neural networks with different success, being the MLP model the most accurate with 100%, or higher than 98.1%, of classification performance for all the years. Classification accuracy from hyperspectral signatures was similar to that from multispectral and spectral indices, suggesting that little advantage would be obtained by using more expensive airborne hyperspectral imagery. Therefore, for next investigations, we recommend using multispectral remote imagery to explore whether they can potentially discriminate these weeds and crops. PMID:22629171

Applying neural networks to hyperspectral and multispectral field data for discrimination of cruciferous weeds in winter crops.

PubMed

de Castro, Ana-Isabel; Jurado-Expósito, Montserrat; Gómez-Casero, María-Teresa; López-Granados, Francisca

2012-01-01

In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance between cruciferous weeds, we applied three classification methods: stepwise discriminant (STEPDISC) analysis and two neural networks, specifically, multilayer perceptron (MLP) and radial basis function (RBF). Hyperspectral and multispectral signatures of cruciferous weeds, and wheat and broad bean crops can be classified using STEPDISC analysis, and MLP and RBF neural networks with different success, being the MLP model the most accurate with 100%, or higher than 98.1%, of classification performance for all the years. Classification accuracy from hyperspectral signatures was similar to that from multispectral and spectral indices, suggesting that little advantage would be obtained by using more expensive airborne hyperspectral imagery. Therefore, for next investigations, we recommend using multispectral remote imagery to explore whether they can potentially discriminate these weeds and crops.

Fast characterization of cheeses by dynamic headspace-mass spectrometry.

PubMed

Pérès, Christophe; Denoyer, Christian; Tournayre, Pascal; Berdagué, Jean-Louis

2002-03-15

This study describes a rapid method to characterize cheeses by analysis of their volatile fraction using dynamic headspace-mass spectrometry. Major factors governing the extraction and concentration of the volatile components were first studied. These components were extracted from the headspace of the cheeses in a stream of helium and concentrated on a Tenax TA trap. They were then desorbed by heating and injected directly into the source of a mass spectrometer via a short deactivated silica transfer line. The mass spectra of the mixture of volatile components were considered as fingerprints of the analyzed substances. Forward stepwise factorial discriminant analysis afforded a limited number of characteristic mass fragments that allowed a good classification of the batches of cheeses studied.

A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

PubMed

Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

2016-11-23

A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P < 0.001). Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

Measurements of the talus in the assessment of population affinity.

PubMed

Bidmos, Mubarak A; Dayal, Manisha R; Adegboye, Oyelola A

2018-06-01

As part of their routine work, forensic anthropologists are expected to report population affinity as part of the biological profile of an individual. The skull is the most widely used bone for the estimation of population affinity but it is not always present in a forensic case. Thus, other bones that preserve well have been shown to give a good indication of either the sex or population affinity of an individual. In this study, the potential of measurements of the talus was investigated for the purpose of estimating population affinity in South Africans. Nine measurements from two hundred and twenty tali of South African Africans (SAA) and South African Whites (SAW) from the Raymond A. Dart Collection of Human Skeletons were used. Direct and step-wise discriminant function and logistic regression analyses were carried out using SPSS and SAS. Talar length was the best single variable for discriminating between these two groups for males while in females the head height was the best single predictor. Average accuracies for correct population affinity classification using logistic regression analysis were higher than those obtained from discriminant function analysis. This study was the first of its type to employ discriminant function analyses and logistic regression analyses to estimate the population affinity of an individual from the talus. Thus these equations can now be used by South African anthropologists when estimating the population affinity of dismembered or damaged or incomplete skeletal remains of SAA and SAW. Copyright © 2018 Elsevier B.V. All rights reserved.

Sex determination from the radius and ulna in a modern South African sample.

PubMed

Barrier, I L O; L'Abbé, E N

2008-07-18

With a large number of unidentified skeletal remains found in South Africa, the development of population specific osteometric standards is imperative. Forensic anthropologists need to have access to a variety of techniques to establish accurate demographic profiles from complete, fragmentary and/or commingled remains. No research has been done on the forearm of African samples, even though these bones have been shown to exhibit sexual dimorphism. The purpose of this paper is to develop discriminant function formulae to determine sex from the radius and ulna in a South African population. The sample consisted of 200 male and 200 female skeletons from the Pretoria Bone (University of Pretoria) and Raymond A. Dart (Witwatersrand University) collections. Sixteen standard anthropometric measurements were taken from the radius (9) and ulna (7) and subjected to stepwise and direct discriminant function analysis. Distal breadth, minimum mid-shaft diameter and maximum head diameter were the best discriminators of sex for the radius, while minimum mid-shaft diameter and olecranon breadth were selected for the ulna. Classification accuracy for the forearm ranged from 76 to 86%. The radius and ulna can be considered moderate discriminators for determining sex in a South African group. However, it is advised that these formulae are used in conjunction with additional methods to determine sex.

determination of sex in south african blacks by discriminant function analysis of mandibular linear dimensions : A preliminary investigation using the zulu local population.

PubMed

Franklin, Daniel; O'Higgins, Paul; Oxnard, Charles E; Dadour, Ian

2006-12-01

The determination of sex is a critical component in forensic anthropological investigation. The literature attests to numerous metrical standards, each utilizing diffetent skeletal elements, for sex determination in South A frican Blacks. Metrical standards are popular because they provide a high degree of expected accuracy and are less error-prone than subjective nonmetric visual techniques. We note, however, that there appears to be no established metric mandible discriminant function standards for sex determination in this population.We report here on a preliminary investigation designed to evaluate whether the mandible is a practical element for sex determination in South African Blacks. The sample analyzed comprises 40 nonpathological Zulu individuals drawn from the R.A. Dart Collection. Ten linear measurements, obtained from mathematically trans-formed three-dimensional landmark data, are analyzed using basic univariate statistics and discriminant function analyses. Seven of the 10 measurements examined are found to be sexually dimorphic; the dimensions of the ramus are most dimorphic. The sex classification accuracy of the discriminant functions ranged from 72.5 to 87.5% for the univariate method, 92.5% for the stepwise method, and 57.5 to 95% for the direct method. We conclude that the mandible is an extremely useful element for sex determination in this population.

Snow mapping and land use studies in Switzerland

NASA Technical Reports Server (NTRS)

Haefner, H. (Principal Investigator)

1977-01-01

The author has identified the following significant results. A system was developed for operational snow and land use mapping, based on a supervised classification method using various classification algorithms and representation of the results in maplike form on color film with a photomation system. Land use mapping, under European conditions, was achieved with a stepwise linear discriminant analysis by using additional ratio variables. On fall images, signatures of built-up areas were often not separable from wetlands. Two different methods were tested to correlate the size of settlements and the population with an accuracy for the densely populated Swiss Plateau between +2 or -12%.

Polar cloud and surface classification using AVHRR imagery - An intercomparison of methods

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Goroch, A. K.; Rabindra, P.; Rangaraj, N.; Navar, M. S.

1992-01-01

Six Advanced Very High-Resolution Radiometer local area coverage (AVHRR LAC) arctic scenes are classified into ten classes. Three different classifiers are examined: (1) the traditional stepwise discriminant analysis (SDA) method; (2) the feed-forward back-propagation (FFBP) neural network; and (3) the probabilistic neural network (PNN). More than 200 spectral and textural measures are computed. These are reduced to 20 features using sequential forward selection. Theoretical accuracy of the classifiers is determined using the bootstrap approach. Overall accuracy is 85.6 percent, 87.6 percent, and 87.0 percent for the SDA, FFBP, and PNN classifiers, respectively, with standard deviations of approximately 1 percent.

Natural Resources Inventory and Land Evaluation in Switzerland

NASA Technical Reports Server (NTRS)

Haefner, H. (Principal Investigator)

1975-01-01

The author has identified the following significant results. A system was developed to operationally map and measure the areal extent of various land use categories for updating existing and producing new and actual thematic maps showing the latest state of rural and urban landscapes and its changes. The processing system includes: (1) preprocessing steps for radiometric and geometric corrections; (2) classification of the data by a multivariate procedure, using a stepwise linear discriminant analysis based on carefully selected training cells; and (3) output in form of color maps by printing black and white theme overlays of a selected scale with photomation system and its coloring and combination into a color composite.

Delineation of sympatric morphotypes of lake trout in Lake Superior

USGS Publications Warehouse

Moore, Seth A.; Bronte, Charles R.

2001-01-01

Three morphotypes of lake trout Salvelinus namaycush are recognized in Lake Superior: lean, siscowet, and humper. Absolute morphotype assignment can be difficult. We used a size-free, whole-body morphometric analysis (truss protocol) to determine whether differences in body shape existed among lake trout morphotypes. Our results showed discrimination where traditional morphometric characters and meristic measurements failed to detect differences. Principal components analysis revealed some separation of all three morphotypes based on head and caudal peduncle shape, but it also indicated considerable overlap in score values. Humper lake trout have smaller caudal peduncle widths to head length and depth characters than do lean or siscowet lake trout. Lean lake trout had larger head measures to caudal widths, whereas siscowet had higher caudal peduncle to head measures. Backward stepwise discriminant function analysis retained two head measures, three midbody measures, and four caudal peduncle measures; correct classification rates when using these variables were 83% for leans, 80% for siscowets, and 83% for humpers, which suggests the measures we used for initial classification were consistent. Although clear ecological reasons for these differences are not readily apparent, patterns in misclassification rates may be consistent with evolutionary hypotheses for lake trout within the Laurentian Great Lakes.

A Java-based tool for the design of classification microarrays.

PubMed

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

An analysis of the relationship of seven selected variables to State Board Test Pool Examination performance of the University of Tennessee, Knoxville, College of Nursing.

PubMed

Sharp, T G

1984-02-01

The study was designed to determine whether any one of seven selected variables or a combination of the variables is predictive of performance on the State Board Test Pool Examination. The selected variables studied were: high school grade point average (HSGPA), The University of Tennessee, Knoxville, College of Nursing grade point average (GPA), and American College Test Assessment (ACT) standard scores (English, ENG; mathematics, MA; social studies, SS; natural sciences, NSC; composite, COMP). Data utilized were from graduates of the baccalaureate program of The University of Tennessee, Knoxville, College of Nursing from 1974 through 1979. The sample of 322 was selected from a total population of 572. The Statistical Analysis System (SAS) was designed to accomplish analysis of the predictive relationship of each of the seven selected variables to State Board Test Pool Examination performance (result of pass or fail), a stepwise discriminant analysis was designed for determining the predictive relationship of the strongest combination of the independent variables to overall State Board Test Pool Examination performance (result of pass or fail), and stepwise multiple regression analysis was designed to determine the strongest predictive combination of selected variables for each of the five subexams of the State Board Test Pool Examination. The selected variables were each found to be predictive of SBTPE performance (result of pass or fail). The strongest combination for predicting SBTPE performance (result of pass or fail) was found to be GPA, MA, and NSC.

Characterization of Armillaria spp. from peach orchards in the southeastern United States using fatty acid methyl ester profiling.

PubMed

Cox, K D; Scherm, H; Riley, M B

2006-04-01

Limited information is available regarding the composition of cellular fatty acids in Armillaria and the extent to which fatty acid profiles can be used to characterize species in this genus. Fatty acid methyl ester (FAME) profiles generated from cultures of A. tabescens, A. mellea, and A. gallica consisted of 16-18 fatty acids ranging from 12-24 carbons in length, although some of these were present only in trace amounts. Across the three species, 9-cis,12-cis-octadecadienoic acid (9,12-C18:2), hexadecanoic acid (16:0), heneicosanoic acid (21:0), 9-cis-octadecenoic acid (9-C18:1), and 2-hydroxy-docosanoic acid (OH-22:0) were the most abundant fatty acids. FAME profiles from different thallus morphologies (mycelium, sclerotial crust, or rhizomorphs) displayed by cultures of A. gallica showed that thallus type had no significant effect on cellular fatty acid composition (P > 0.05), suggesting that FAME profiling is sufficiently robust for species differentiation despite potential differences in thallus morphology within and among species. The three Armillaria species included in this study could be distinguished from other lignicolous basidiomycete species commonly occurring on peach (Schizophyllum commune, Ganoderma lucidum, Stereum hirsutum, and Trametes versicolor) on the basis of FAME profiles using stepwise discriminant analysis (average squared canonical correlation = 0.953), whereby 9-C18:1, 9,12-C18:2, and 10-cis-hexadecenoic acid (10-C16:1) were the three strongest contributors. In a separate stepwise discriminant analysis, A. tabescens, A. mellea, and A. gallica were separated from one another based on their fatty acid profiles (average squared canonical correlation = 0.924), with 11-cis-octadecenoic acid (11-C18:1), 9-C18:1, and 2-hydroxy-hexadecanoic acid (OH-16:0) being most important for species separation. When fatty acids were extracted directly from mycelium dissected from naturally infected host tissue, the FAME-based discriminant functions developed in the preceding experiments classified all samples (n = 16) as A. tabescens; when applied to cultures derived from the same naturally infected samples, all unknowns were similarly classified as A. tabescens. Thus, FAME species classification of Armillaria unknowns directly from infected tissues may be feasible. Species designation of unknown Armillaria cultures by FAME analysis was identical to that indicated by IGS-RFLP classification with AluI.

Talent identification and selection in elite youth football: An Australian context.

PubMed

O'Connor, Donna; Larkin, Paul; Mark Williams, A

2016-10-01

We identified the perceptual-cognitive skills and player history variables that differentiate players selected or not selected into an elite youth football (i.e. soccer) programme in Australia. A sample of elite youth male football players (n = 127) completed an adapted participation history questionnaire and video-based assessments of perceptual-cognitive skills. Following data collection, 22 of these players were offered a full-time scholarship for enrolment at an elite player residential programme. Participants selected for the scholarship programme recorded superior performance on the combined perceptual-cognitive skills tests compared to the non-selected group. There were no significant between group differences on the player history variables. Stepwise discriminant function analysis identified four predictor variables that resulted in the best categorization of selected and non-selected players (i.e. recent match-play performance, region, number of other sports participated, combined perceptual-cognitive performance). The effectiveness of the discriminant function is reflected by 93.7% of players being correctly classified, with the four variables accounting for 57.6% of the variance. Our discriminating model for selection may provide a greater understanding of the factors that influence elite youth talent selection and identification.

[Application of ICP-MS to Identify the Botanic Source of Characteristic Honey in South Yunnan].

PubMed

Wei, Yue; Chen, Fang; Wang, Yong; Chen, Lan-zhen; Zhang, Xue-wen; Wang, Yan-hui; Wu, Li-ming; Zhou, Qun

2016-01-01

By adopting inductively coupled plasma mass spectrometry (ICP-MS) combined with chemometric analysis technology, 23 kinds of minerals in four kinds of characteristic honey derived from Yunnan province were analyzed. The result showed that 21 kinds of mineral elements, namely Na, Mg, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Cd, Sb, Ba, Tl and Pb, have significant differences among different varieties of honey. The results of principal component analysis (PCA) showed that the cumulative variance contribution rate of the first four main components reached 77.74%, seven kinds of elements (Mg, Ca, Mn, Co, Sr, Cd, Ba) from the first main component contained most of the honey information. Through the stepwise discriminant analysis, seven kinds of elements (Mg, K, Ca, Cr, Mn, Sr, Pb) were filtered. out and used to establish the discriminant function model, and the correct classification rates of the proposed model reached 90% and 86.7%, respectively, which showed elements contents could be effectively indicators to discriminate the four kinds characteristic honey in southern Yunnan Province. In view of all the honey samples were harvested from apiaries located at south Yunnan Province where have similar climate, soil and other environment conditions, the differences of the mineral elements contents for the honey samples mainly due to their corresponding nectariferous plant. Therefore, it is feasible to identify honey botanical source through the differences of mineral elements.

Behavioral phenomenology in Alzheimer's disease, frontotemporal dementia, and late-life depression: a retrospective analysis.

PubMed

Swartz, J R; Miller, B L; Lesser, I M; Booth, R; Darby, A; Wohl, M; Benson, D F

1997-04-01

Often patients in the early stages of Alzheimer's disease (AD), frontotemporal dementia (FTD), and late-life depression can be difficult to differentiate clinically. Although subtle cognitive distinctions exist between these disorders, noncognitive behavioral phenomenology may provide additional discriminating power. In 19 subjects with AD, 19 with FTD, 16 with late-life psychotic depression (LLPD), and 19 with late-life nonpsychotic depression (LLNPD), noncognitive behavioral symptoms were quantified retrospectively using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) and compared using both a one-way ANOVA and a multivariate stepwise discriminant analysis, which utilized a jackknife procedure. The FTD group showed the highest mean total SCAN score, while the AD group showed the lowest. ANOVA showed significant differences in the mean total SCAN scores between the four diagnostic groups (P < .0001). With the discriminant analysis, the four disorders demonstrated different clusters of behavioral abnormalities and were differentiated by these symptoms (P < .0001). A subset of 14 SCAN item group symptoms was identified that collectively classified the following percentages of subjects in each diagnostic category: AD 94.7%, FTD 100%, LLPD 87.5%, and LLNPD 100%. These results indicate that AD, FTD, LLPD, and LLNPD were distinguished retrospectively by the SCAN without using cognitive data. Better definition of the longitudinal course of noncognitive behavioral symptoms in different dementias and psychiatric disorders will be valuable both for diagnosis and to help define behavioral syndromes that are associated with selective neuroanatomic and neurochemical brain pathology.

Diagnostic features of Alzheimer's disease extracted from PET sinograms

NASA Astrophysics Data System (ADS)

Sayeed, A.; Petrou, M.; Spyrou, N.; Kadyrov, A.; Spinks, T.

2002-01-01

Texture analysis of positron emission tomography (PET) images of the brain is a very difficult task, due to the poor signal to noise ratio. As a consequence, very few techniques can be implemented successfully. We use a new global analysis technique known as the Trace transform triple features. This technique can be applied directly to the raw sinograms to distinguish patients with Alzheimer's disease (AD) from normal volunteers. FDG-PET images of 18 AD and 10 normal controls obtained from the same CTI ECAT-953 scanner were used in this study. The Trace transform triple feature technique was used to extract features that were invariant to scaling, translation and rotation, referred to as invariant features, as well as features that were sensitive to rotation but invariant to scaling and translation, referred to as sensitive features in this study. The features were used to classify the groups using discriminant function analysis. Cross-validation tests using stepwise discriminant function analysis showed that combining both sensitive and invariant features produced the best results, when compared with the clinical diagnosis. Selecting the five best features produces an overall accuracy of 93% with sensitivity of 94% and specificity of 90%. This is comparable with the classification accuracy achieved by Kippenhan et al (1992), using regional metabolic activity.

Multivariate statistical analysis of the polyphenolic constituents in kiwifruit juices to trace fruit varieties and geographical origins.

PubMed

Guo, Jing; Yuan, Yahong; Dou, Pei; Yue, Tianli

2017-10-01

Fifty-one kiwifruit juice samples of seven kiwifruit varieties from five regions in China were analyzed to determine their polyphenols contents and to trace fruit varieties and geographical origins by multivariate statistical analysis. Twenty-one polyphenols belonging to four compound classes were determined by ultra-high-performance liquid chromatography coupled with ultra-high-resolution TOF mass spectrometry. (-)-Epicatechin, (+)-catechin, procyanidin B1 and caffeic acid derivatives were the predominant phenolic compounds in the juices. Principal component analysis (PCA) allowed a clear separation of the juices according to kiwifruit varieties. Stepwise linear discriminant analysis (SLDA) yielded satisfactory categorization of samples, provided 100% success rate according to kiwifruit varieties and 92.2% success rate according to geographical origins. The result showed that polyphenolic profiles of kiwifruit juices contain enough information to trace fruit varieties and geographical origins. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sex determination from the calcaneus in a 20th century Greek population using discriminant function analysis.

PubMed

Peckmann, Tanya R; Orr, Kayla; Meek, Susan; Manolis, Sotiris K

2015-12-01

The skull and post-cranium have been used for the determination of sex for unknown human remains. However, in forensic cases where skeletal remains often exhibit postmortem damage and taphonomic changes the calcaneus may be used for the determination of sex as it is a preservationally favored bone. The goal of the present research was to derive discriminant function equations from the calcaneus for estimation of sex from a contemporary Greek population. Nine parameters were measured on 198 individuals (103 males and 95 females), ranging in age from 20 to 99 years old, from the University of Athens Human Skeletal Reference Collection. The statistical analyses showed that all variables were sexually dimorphic. Discriminant function score equations were generated for use in sex determination. The average accuracy of sex classification ranged from 70% to 90% for the univariate analysis, 82.9% to 87.5% for the direct method, and 86.2% for the stepwise method. Comparisons to other populations were made. Overall, the cross-validated accuracies ranged from 48.6% to 56.1% with males most often identified correctly and females most often misidentified. The calcaneus was shown to be useful for sex determination in the twentieth century Greek population. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Discriminative and predictive validity of the scoliosis research society-22 questionnaire in management and curve-severity subgroups of adolescents with idiopathic scoliosis.

PubMed

Parent, Eric C; Hill, Doug; Mahood, Jim; Moreau, Marc; Raso, Jim; Lou, Edmond

2009-10-15

Prospective cross-sectional measurement study. To determine the ability of the Scoliosis Research Society (SRS)-22 questionnaire to discriminate among management and scoliosis severity subgroups and to correlate with internal and external measures of curve severity. In earlier studies of the SRS-22 discriminative ability, age was not a controlled factor. The ability of the SRS-22 to predict curve severity has not been thoroughly examined. The SRS-22 was completed by 227 females with adolescent idiopathic scoliosis. Using Analysis of covariance analyses controlling for age, the SRS-22 scores were compared among management subgroups (observation, brace, presurgery, and postsurgery) and curve-severity subgroups (in nonoperated subjects: Cobb angles of <30 degrees, 30 degrees -50 degrees, and >50 degrees). A stepwise discriminant analysis was used to identify the SRS-22 domains most discriminative for curve-severity categories. Correlation between SRS-22 scores and radiographic or surface topography measurements was used to determine the predictive ability of the questionnaire. Pain was better for subjects treated with braces than for those planning surgery. Self-image was better for subjects under observation or postsurgery than for those planning surgery. Satisfaction was better for the brace and postsurgery subgroups than for the observation or presurgery subgroups. Statistically significant mean differences between subgroups were all larger than 0.5, which is within the range of minimal clinically important differences recommended for each of the 5-point SRS-22 domain scoring scales. Pain and mental health were worse for those with Cobb angles of >50 degrees than with Cobb angles of 30 degrees to 50 degrees. Self-image and total scores were worse for those with Cobb angles of >50 degrees than both other subgroups. Using discriminant analysis, self-image was the only SRS-22 domain score selected to classify subjects within curve severity subgroups. The percentage of patients accurately classified was 54% when trying to classify within 3 curve severity subgroups. The percentage of patients accurately classified was 73% when classifying simply as those with curves larger or smaller than 50 degrees . Pain, self-image, and satisfaction scores could discriminate among management subgroups, but function, mental health and total scores could not. The total score and all domain scores except satisfaction discriminated among curve-severity subgroups. Using discriminant analysis, self-image was the only domain retained in a model predicting curve-severity categories.

Oak decline risk rating for the southeastern United States

Treesearch

S. Oak; F. Tainter; J. Williams; D. Starkey

1996-01-01

Oak decline risk rating models were developed for upland hardwood forests in the southeastern United States using data gathered during regional oak decline surveys. Stepwise discriminant analyses were used to relate 12 stand and site variables with major oak decline incidence for each of three subregions plus one incorporating all subregions. The best model for the...

Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis.

PubMed

Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X

2016-09-01

The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

Multi-resolution analysis using integrated microscopic configuration with local patterns for benign-malignant mass classification

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree; Sadhu, Anup; Arif, Wasim

2018-02-01

In this paper, Curvelet based local attributes, Curvelet-Local configuration pattern (C-LCP), is introduced for the characterization of mammographic masses as benign or malignant. Amid different anomalies such as micro- calcification, bilateral asymmetry, architectural distortion, and masses, the reason for targeting the mass lesions is due to their variation in shape, size, and margin which makes the diagnosis a challenging task. Being efficient in classification, multi-resolution property of the Curvelet transform is exploited and local information is extracted from the coefficients of each subband using Local configuration pattern (LCP). The microscopic measures in concatenation with the local textural information provide more discriminating capability than individual. The measures embody the magnitude information along with the pixel-wise relationships among the neighboring pixels. The performance analysis is conducted with 200 mammograms of the DDSM database containing 100 mass cases of each benign and malignant. The optimal set of features is acquired via stepwise logistic regression method and the classification is carried out with Fisher linear discriminant analysis. The best area under the receiver operating characteristic curve and accuracy of 0.95 and 87.55% are achieved with the proposed method, which is further compared with some of the state-of-the-art competing methods.

Understanding college students' fruit consumption. Integrating habit strength in the theory of planned behaviour.

PubMed

de Bruijn, Gert-Jan

2010-02-01

The additive and interactive effect of habit strength in the explanation of young adults' fruit consumption was studied within the context of the theory of planned behaviour (TPB). Additionally, behavioural and control beliefs were modelled as predictors of profile membership based on current fruit consumption, motivation and habit strength towards fruit consumption. Cross-sectional data were available from undergraduate students (n=538; mean age=21.19; S.D.=2.57) who completed measures of fruit consumption, habit strength, TPB-concepts, and behavioural and control beliefs. Data were analyzed using stepwise regression analysis, simple slope analysis, and discriminant function analysis. Results showed that, based on a significant intention x habit interaction (beta=.13), the intention-fruit consumption relationship was more than twice as strong at low levels of habit strength (beta=.39) than at high levels of habit strength (beta=.16). Furthermore, beliefs regarding health and weight management were relatively unable to distinguish profiles created from motivation, habit strength and current fruit consumption. Rather, beliefs about controllability of fruit consumption were amongst the most consistent discriminating beliefs. Findings suggest that stronger fruit consumption habits make fruit consumption less intentional and that interventions aiming to increase fruit consumption may need to develop persuasive messages focusing on situational beliefs, rather than emphasizing health outcomes. 2009 Elsevier Ltd. All rights reserved.

Consumption value theory and the marketing of public health: an effective formative research tool.

PubMed

Nelson, Douglas G; Byus, Kent

2002-01-01

Contemporary public health requires the support and participation of its constituency. This study assesses the capacity of consumption value theory to identify the basis of this support. A telephone survey design used simple random sampling of adult residents of Cherokee County, Oklahoma. Factor analysis and stepwise discriminant analysis was used to identify and classify personal and societal level support variables. Most residents base societal level support on epistemic values. Direct services clientele base their support on positive emotional values derived from personal contact and attractive programs. Residents are curious about public health and want to know more about the health department. Where marketing the effectiveness of public health programs would yield relatively little support, marketing health promotion activities may attract public opposition. This formative research tool suggests a marketing strategy for public health practitioners.

Multivariate analysis of sexual size dimorphism in local turkeys (Meleagris gallopavo) in Nigeria.

PubMed

Ajayi, Oyeyemi O; Yakubu, Abdulmojeed; Jayeola, Oluwaseun O; Imumorin, Ikhide G; Takeet, Michael I; Ozoje, Michael O; Ikeobi, Christian O N; Peters, Sunday O

2012-06-01

Sexual size dimorphism is a key evolutionary feature that can lead to important biological insights. To improve methods of sexing live birds in the field, we assessed sexual size dimorphism in Nigerian local turkeys (Meleagris gallopavo) using multivariate techniques. Measurements were taken on 125 twenty-week-old birds reared under the intensive management system. The body parameters measured were body weight, body length, breast girth, thigh length, shank length, keel length, wing length and wing span. Univariate analysis revealed that toms (males) had significantly (P < 0.05) higher mean values than hens (females) in all the measured traits. Positive phenotypic correlations between body weight and body measurements ranged from 0.445 to 0.821 in toms and 0.053-0.660 in hens, respectively. Three principal components (PC1, PC2 and PC3) were extracted in toms, each accounting for 63.70%, 19.42% and 5.72% of the total variance, respectively. However, four principal components (PC1, PC2, PC3 and PC4) were extracted in hens, which explained 54.03%, 15.29%, 11.68% and 6.95%, respectively of the generalised variance. A stepwise discriminant function analysis of the eight morphological traits indicated that body weight, body length, tail length and wing span were the most discriminating variables in separating the sexes. The single discriminant function obtained was able to correctly classify 100% of the birds into their source population. The results obtained from the present study could aid future management decisions, ecological studies and conservation of local turkeys in a developing economy.

Accurate discrimination of Alzheimer's disease from other dementia and/or normal subjects using SPECT specific volume analysis

NASA Astrophysics Data System (ADS)

Iyatomi, Hitoshi; Hashimoto, Jun; Yoshii, Fumuhito; Kazama, Toshiki; Kawada, Shuichi; Imai, Yutaka

2014-03-01

Discrimination between Alzheimer's disease and other dementia is clinically significant, however it is often difficult. In this study, we developed classification models among Alzheimer's disease (AD), other dementia (OD) and/or normal subjects (NC) using patient factors and indices obtained by brain perfusion SPECT. SPECT is commonly used to assess cerebral blood flow (CBF) and allows the evaluation of the severity of hypoperfusion by introducing statistical parametric mapping (SPM). We investigated a total of 150 cases (50 cases each for AD, OD, and NC) from Tokai University Hospital, Japan. In each case, we obtained a total of 127 candidate parameters from: (A) 2 patient factors (age and sex), (B) 12 CBF parameters and 113 SPM parameters including (C) 3 from specific volume analysis (SVA), and (D) 110 from voxel-based analysis stereotactic extraction estimation (vbSEE). We built linear classifiers with a statistical stepwise feature selection and evaluated the performance with the leave-one-out cross validation strategy. Our classifiers achieved very high classification performances with reasonable number of selected parameters. In the most significant discrimination in clinical, namely those of AD from OD, our classifier achieved both sensitivity (SE) and specificity (SP) of 96%. In a similar way, our classifiers achieved a SE of 90% and a SP of 98% in AD from NC, as well as a SE of 88% and a SP of 86% in AD from OD and NC cases. Introducing SPM indices such as SVA and vbSEE, classification performances improved around 7-15%. We confirmed that these SPM factors are quite important for diagnosing Alzheimer's disease.

Assessing size and strength of the clavicle for its usefulness for sex estimation in a British medieval sample.

PubMed

Atterton, Thomas; De Groote, Isabelle; Eliopoulos, Constantine

2016-10-01

The construction of the biological profile from human skeletal remains is the foundation of anthropological examination. However, remains may be fragmentary and the elements usually employed, such as the pelvis and skull, are not available. The clavicle has been successfully used for sex estimation in samples from Iran and Greece. In the present study, the aim was to test the suitability of the measurements used in those previous studies on a British Medieval population. In addition, the project tested whether discrimination between sexes was due to size or clavicular strength. The sample consisted of 23 females and 25 males of pre-determined sex from two medieval collections: Poulton and Gloucester. Six measurements were taken using an osteometric board, sliding calipers and graduated tape. In addition, putty rings and bi-planar radiographs were made and robusticity measures calculated. The resulting variables were used in stepwise discriminant analyses. The linear measurements allowed correct sex classification in 89.6% of all individuals. This demonstrates the applicability of the clavicle for sex estimation in British populations. The most powerful discriminant factor was maximum clavicular length and the best combination of factors was maximum clavicular length and circumference. This result is similar to that obtained by other studies. To further investigate the extent of sexual dimorphism of the clavicle, the biomechanical properties of the polar second moment of area J and the ratio of maximum to minimum bending rigidity are included in the analysis. These were found to have little influence when entered into the discriminant function analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

ERIC Educational Resources Information Center

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

Commercial sheep flocks--fatty acid and fat-soluble antioxidant composition of milk and cheese related to changes in feeding management throughout lactation.

PubMed

Valdivielso, Izaskun; Bustamante, María Ángeles; Buccioni, Arianna; Franci, Oreste; Ruiz de Gordoa, Juan Carlos; de Renobales, Mertxe; Barron, Luis Javier R

2015-08-01

Fatty acids (FAs), tocopherols and retinoids were analysed in raw milk and cheese from six commercial sheep flocks monitored from early lactation in winter to late lactation in summer. In winter, animals received concentrate and forage indoors; in early spring, animals grazed part-time on cultivated or natural valley grasslands; and from mid spring on, animals were kept outdoors constantly on mountain natural pastures. Mountain grazing in late lactation significantly increased the amount of healthy desirable unsaturated FAs such as C18:1t11 (VA), C18:2c9t11 (RA), C18:2t11c13, C18:3c9c12c15 (ALA) and C20:5c5c8c11c14c17 (EPA), and those of α-tocopherol and α-tocotrienol of milk and cheese. Stepwise discriminant analysis was applied to classify cheese samples according to seasonal feeding management. The multivariate approach was able to discriminate beyond doubt mountain cheeses from those of indoor feeding and part-time valley grazing.

Discriminating between the vocalizations of Indo-Pacific humpback and Australian snubfin dolphins in Queensland, Australia.

PubMed

Berg Soto, Alvaro; Marsh, Helene; Everingham, Yvette; Smith, Joshua N; Parra, Guido J; Noad, Michael

2014-08-01

Australian snubfin and Indo-Pacific humpback dolphins co-occur throughout most of their range in coastal waters of tropical Australia. Little is known of their ecology or acoustic repertoires. Vocalizations from humpback and snubfin dolphins were recorded in two locations along the Queensland coast during 2008 and 2010 to describe their vocalizations and evaluate the acoustic differences between these two species. Broad vocalization types were categorized qualitatively. Both species produced click trains burst pulses and whistles. Principal component analysis of the nine acoustic variables extracted from the whistles produced nine principal components that were input into discriminant function analyses to classify 96% of humpback dolphin whistles and about 78% of snubfin dolphin calls correctly. Results indicate clear acoustic differences between the vocal whistle repertoires of these two species. A stepwise routine identified two principal components as significantly distinguishable between whistles of each species: frequency parameters and frequency trend ratio. The capacity to identify these species using acoustic monitoring techniques has the potential to provide information on presence/absence, habitat use and relative abundance for each species.

IGFBP-1: a metabolic signal associated with exercise-induced amenorrhoea.

PubMed

Jenkins, P J; Ibanez-Santos, X; Holly, J; Cotterill, A; Perry, L; Wolman, R; Harries, M; Grossman, A

1993-04-01

Severe exercise in young females is a potent cause of menstrual irregularity, although the exact pathogenesis is currently unknown. We performed a cross-sectional endocrine and metabolic analysis of a group of elite athletes and dancers in order to establish which variable, if any, was specifically associated with changes in menstruation. By using a step-wise discriminant analysis, two independent predictors, elevated serum cortisol and insulin-like growth factor binding protein 1 (IGFBP-1) levels, were found to account for the majority (67%) of the variance. IGFBP-1 is a hepatic protein which is acutely and inversely regulated by insulin, and is thought to modulate the peripheral actions of IGF-1. While the change in serum cortisol may reflect activation of central stress pathways, these findings suggest for the first time that there is a second peripheral signal, IGFBP-1, which may relate the availability of metabolic fuels to the control of reproduction.

Differentiation of Commercial PDO Wines Produced in Istria (Croatia) According to Variety and Harvest Year Based on HS-SPME-GC/MS Volatile Aroma Compound Profiling.

PubMed

Lukić, Igor; Horvat, Ivana

2017-03-01

To differentiate monovarietal wines made from native and introduced varieties in Istria (Croatia), samples of Malvazija istarska, Chardonnay and Muscat yellow from two harvest years (2013 and 2014) were subjected to headspace solid-phase microextraction and gas chromatographic/mass spectrometric analysis (HS-SPME-GC/MS) of volatile aroma compounds. Significant effects of variety and harvest year were determined, but their interaction complicated the differentiation. Particular compounds were consistent as markers of variety in both years: nerol for Malvazija, ethyl cinnamate and a tentatively identified isomer of dimethylbenzaldehyde for Chardonnay, and terpenes for Muscat yellow. Wines from 2013 contained higher concentrations of the majority of important volatiles. A 100% correct differentiation of Malvazija istarska and Chardonnay wines according to both variety and harvest year was achieved by stepwise linear discriminant analysis.

Odontological approach to sexual dimorphism in southeastern France.

PubMed

Lladeres, Emilie; Saliba-Serre, Bérengère; Sastre, Julien; Foti, Bruno; Tardivo, Delphine; Adalian, Pascal

2013-01-01

The aim of this study was to establish a prediction formula to allow for the determination of sex among the southeastern French population using dental measurements. The sample consisted of 105 individuals (57 males and 48 females, aged between 18 and 25 years). Dental measurements were calculated using Euclidean distances, in three-dimensional space, from point coordinates obtained by a Microscribe. A multiple logistic regression analysis was performed to establish the prediction formula. Among 12 selected dental distances, a stepwise logistic regression analysis highlighted the two most significant discriminate predictors of sex: one located at the mandible and the other at the maxilla. A cutpoint was proposed to prediction of true sex. The prediction formula was then tested on a validation sample (20 males and 34 females, aged between 18 and 62 years and with a history of orthodontics or restorative care) to evaluate the accuracy of the method. © 2012 American Academy of Forensic Sciences.

Discrimination of Active and Weakly Active Human BACE1 Inhibitors Using Self-Organizing Map and Support Vector Machine.

PubMed

Li, Hang; Wang, Maolin; Gong, Ya-Nan; Yan, Aixia

2016-01-01

β-secretase (BACE1) is an aspartyl protease, which is considered as a novel vital target in Alzheimer`s disease therapy. We collected a data set of 294 BACE1 inhibitors, and built six classification models to discriminate active and weakly active inhibitors using Kohonen's Self-Organizing Map (SOM) method and Support Vector Machine (SVM) method. Each molecular descriptor was calculated using the program ADRIANA.Code. We adopted two different methods: random method and Self-Organizing Map method, for training/test set split. The descriptors were selected by F-score and stepwise linear regression analysis. The best SVM model Model2C has a good prediction performance on test set with prediction accuracy, sensitivity (SE), specificity (SP) and Matthews correlation coefficient (MCC) of 89.02%, 90%, 88%, 0.78, respectively. Model 1A is the best SOM model, whose accuracy and MCC of the test set were 94.57% and 0.98, respectively. The lone pair electronegativity and polarizability related descriptors importantly contributed to bioactivity of BACE1 inhibitor. The Extended-Connectivity Finger-Prints_4 (ECFP_4) analysis found some vitally key substructural features, which could be helpful for further drug design research. The SOM and SVM models built in this study can be obtained from the authors by email or other contacts.

Non-targeted 1H NMR fingerprinting and multivariate statistical analyses for the characterisation of the geographical origin of Italian sweet cherries.

PubMed

Longobardi, F; Ventrella, A; Bianco, A; Catucci, L; Cafagna, I; Gallo, V; Mastrorilli, P; Agostiano, A

2013-12-01

In this study, non-targeted (1)H NMR fingerprinting was used in combination with multivariate statistical techniques for the classification of Italian sweet cherries based on their different geographical origins (Emilia Romagna and Puglia). As classification techniques, Soft Independent Modelling of Class Analogy (SIMCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Linear Discriminant Analysis (LDA) were carried out and the results were compared. For LDA, before performing a refined selection of the number/combination of variables, two different strategies for a preliminary reduction of the variable number were tested. The best average recognition and CV prediction abilities (both 100.0%) were obtained for all the LDA models, although PLS-DA also showed remarkable performances (94.6%). All the statistical models were validated by observing the prediction abilities with respect to an external set of cherry samples. The best result (94.9%) was obtained with LDA by performing a best subset selection procedure on a set of 30 principal components previously selected by a stepwise decorrelation. The metabolites that mostly contributed to the classification performances of such LDA model, were found to be malate, glucose, fructose, glutamine and succinate. Copyright © 2013 Elsevier Ltd. All rights reserved.

Differential characteristics in the chemical composition of bananas from Tenerife (Canary Islands) and Ecuador.

PubMed

Forster, Markus Paul; Rodríguez Rodríguez, Elena; Díaz Romero, Carlos

2002-12-18

The contents of moisture, protein, ash, ascorbic acid, glucose, fructose, total sugars, and total and insoluble fiber were determined in cultivars of bananas (Gran Enana and Pequeña Enana) harvested in Tenerife and in bananas (Gran Enana) from Ecuador. The chemical compositions in the bananas from Tenerife and from Ecuador were clearly different. The cultivar did not influence the chemical composition, except for insoluble fiber content. Variations of the chemical composition were observed in the bananas from Tenerife according to cultivation method (greenhouse and outdoors), farming style (conventional and organic), and region of production (north and south). A highly significant (r = 0.995) correlation between glucose and fructose was observed. Correlations of ash and protein contents tend to separate the banana samples according to origin. A higher content of protein, ash, and ascorbic acid was observed as the length of the banana decreased. Applying factor analysis, the bananas from Ecuador were well separated from the bananas produced in Tenerife. An almost total differentiation (91.7%) between bananas from Tenerife and bananas from Ecuador was obtained by selecting protein, ash, and ascorbic acid content and applying stepwise discriminant analysis. By selecting the bananas Pequeña Enana and using discriminant analysis, a clear separation of the samples according to the region of production and farming style was observed.

Multielement fingerprinting as a tool in origin authentication of PGI food products: Tropea red onion.

PubMed

Furia, Emilia; Naccarato, Attilio; Sindona, Giovanni; Stabile, Gaetano; Tagarelli, Antonio

2011-08-10

Tropea red onion ( Allium cepa L. var. Tropea) is among the most highly appreciated Italian products. It is cultivated in specific areas of Calabria and, due to its characteristics, was recently awarded with the protected geographical indications (PGI) certification from the European Union. A reliable classification of onion samples in groups corresponding to "Tropea" and "non-Tropea" categories is now available to the producers. This important goal has been achieved through the evaluation of three supervised chemometric approaches. Onion samples with PGI brand (120) and onion samples not cultivated following the production regulations (80) were digested by a closed-vessel microwave oven system. ICP-MS equipped with a dynamic reaction cell was used to determine the concentrations of 25 elements (Al, Ba, Ca, Cd, Ce, Cr, Dy, Eu, Fe, Ga, Gd, Ho, La, Mg, Mn, Na, Nd, Ni, Pr, Rb, Sm, Sr, Tl, Y, and Zn). The multielement fingerprint was processed using linear discriminant analysis (LDA) (standard and stepwise), soft independent modeling of class analogy (SIMCA), and back-propagation artificial neural network (BP-ANN). The cross-validation procedure has shown good results in terms of the prediction ability for all of the chemometric models: standard LDA, 94.0%; stepwise LDA, 94.5%; SIMCA, 95.5%; and BP-ANN, 91.5%.

1H nuclear magnetic resonance spectroscopy-based metabonomic study in patients with cirrhosis and hepatic encephalopathy

PubMed Central

Dabos, Konstantinos John; Parkinson, John Andrew; Sadler, Ian Howard; Plevris, John Nicholas; Hayes, Peter Clive

2015-01-01

AIM: To identify plasma metabolites used as biomarkers in order to distinguish cirrhotics from controls and encephalopathics. METHODS: A clinical study involving stable cirrhotic patients with and without overt hepatic encephalopathy was designed. A control group of healthy volunteers was used. Plasma from those patients was analysed using 1H - nuclear magnetic resonance spectroscopy. We used the Carr Purcell Meiboom Gill sequence to process the sample spectra at ambient probe temperature. We used a gated secondary irradiation field for water signal suppression. Samples were calibrated and referenced using the sodium trimethyl silyl propionate peak at 0.00 ppm. For each sample 128 transients (FID’s) were acquired into 32 K complex data points over a spectral width of 6 KHz. 30 degree pulses were applied with an acquisition time of 4.0 s in order to achieve better resolution, followed by a recovery delay of 12 s, to allow for complete relaxation and recovery of the magnetisation. A metabolic profile was created for stable cirrhotic patients without signs of overt hepatic encephalopathy and encephalopathic patients as well as healthy controls. Stepwise discriminant analysis was then used and discriminant factors were created to differentiate between the three groups. RESULTS: Eighteen stabled cirrhotic patients, eighteen patients with overt hepatic encephalopathy and seventeen healthy volunteers were recruited. Patients with cirrhosis had significantly impaired ketone body metabolism, urea synthesis and gluconeogenesis. This was demonstrated by higher concentrations of acetoacetate (0.23 ± 0.02 vs 0.05 ± 0.00, P < 0.01), and b-hydroxybutarate (0.58 ± 0.14 vs 0.08 ± 0.00, P < 0.01), lower concentrations of glutamine (0.44 ± 0.08 vs 0.63 ± 0.03, P < 0.05), histidine (0.16 ± 0.01 vs 0.36 ± 0.04, P < 0.01) and arginine (0.08 ± 0.01 vs 0.14 ± 0.02, P < 0.03) and higher concentrations of glutamate (1.36 ± 0.25 vs 0.58 ± 0.04, P < 0.01), lactate (1.53 ± 0.11 vs 0.42 ± 0.05, P < 0.01), pyruvate (0.11 ± 0.02 vs 0.03 ± 0.00, P < 0.01) threonine (0.39 ± 0.02 vs 0.08 ± 0.01, P < 0.01) and aspartate (0.37 ± 0.03 vs 0.03 ± 0.01). A five metabolite signature by stepwise discriminant analysis could separate between controls and cirrhotic patients with an accuracy of 98%. In patients with encephalopathy we observed further derangement of ketone body metabolism, impaired production of glycerol and myoinositol, reversal of Fischer’s ratio and impaired glutamine production as demonstrated by lower b-hydroxybutyrate (0.58 ± 0.14 vs 0.16 ± 0.02, P < 0.0002), higher acetoacetate (0.23 ± 0.02 vs 0.41 ± 0.16, P < 0.05), leucine (0.33 ± 0.02 vs 0.49 ± 0.05, P < 0.005) and isoleucine (0.12 ± 0.02 vs 0.27 ± 0.02, P < 0.0004) and lower glutamine (0.44 ± 0.08 vs 0.36 ± 0.04, P < 0.013), glycerol (0.53 ± 0.03 vs 0.19 ± 0.02, P < 0.000) and myoinositol (0.36 ± 0.04 vs 0.18 ± 0.02, P < 0.010) concentrations. A four metabolite signature by stepwise discriminant analysis could separate between encephalopathic and cirrhotic patients with an accuracy of 87%. CONCLUSION: Patients with cirrhosis and patients with hepatic encephalopathy exhibit distinct metabolic abnormalities and the use of metabonomics can select biomarkers for these diseases. PMID:26140090

Expanded image database of pistachio x-ray images and classification by conventional methods

NASA Astrophysics Data System (ADS)

Keagy, Pamela M.; Schatzki, Thomas F.; Le, Lan Chau; Casasent, David P.; Weber, David

1996-12-01

In order to develop sorting methods for insect damaged pistachio nuts, a large data set of pistachio x-ray images (6,759 nuts) was created. Both film and linescan sensor images were acquired, nuts dissected and internal conditions coded using the U.S. Grade standards and definitions for pistachios. A subset of 1199 good and 686 insect damaged nuts was used to calculate and test discriminant functions. Statistical parameters of image histograms were evaluated for inclusion by forward stepwise discrimination. Using three variables in the discriminant function, 89% of test set nuts were correctly identified. Comparable data for 6 human subjects ranged from 67 to 92%. If the loss of good nuts is held to 1% by requiring a high probability to discard a nut as insect damaged, approximately half of the insect damage present in clean pistachio nuts may be detected and removed by x-ray inspection.

Using foreground/background analysis to determine leaf and canopy chemistry

NASA Technical Reports Server (NTRS)

Pinzon, J. E.; Ustin, S. L.; Hart, Q. J.; Jacquemoud, S.; Smith, M. O.

1995-01-01

Spectral Mixture Analysis (SMA) has become a well established procedure for analyzing imaging spectrometry data, however, the technique is relatively insensitive to minor sources of spectral variation (e.g., discriminating stressed from unstressed vegetation and variations in canopy chemistry). Other statistical approaches have been tried e.g., stepwise multiple linear regression analysis to predict canopy chemistry. Grossman et al. reported that SMLR is sensitive to measurement error and that the prediction of minor chemical components are not independent of patterns observed in more dominant spectral components like water. Further, they observed that the relationships were strongly dependent on the mode of expressing reflectance (R, -log R) and whether chemistry was expressed on a weight (g/g) or are basis (g/sq m). Thus, alternative multivariate techniques need to be examined. Smith et al. reported a revised SMA that they termed Foreground/Background Analysis (FBA) that permits directing the analysis along any axis of variance by identifying vectors through the n-dimensional spectral volume orthonormal to each other. Here, we report an application of the FBA technique for the detection of canopy chemistry using a modified form of the analysis.

Active microwave responses - An aid in improved crop classification

NASA Technical Reports Server (NTRS)

Rosenthal, W. D.; Blanchard, B. J.

1984-01-01

A study determined the feasibility of using visible, infrared, and active microwave data to classify agricultural crops such as corn, sorghum, alfalfa, wheat stubble, millet, shortgrass pasture and bare soil. Visible through microwave data were collected by instruments on board the NASA C-130 aircraft over 40 agricultural fields near Guymon, OK in 1978 and Dalhart, TX in 1980. Results from stepwise and discriminant analysis techniques indicated 4.75 GHz, 1.6 GHz, and 0.4 GHz cross-polarized microwave frequencies were the microwave frequencies most sensitive to crop type differences. Inclusion of microwave data in visible and infrared classification models improved classification accuracy from 73 percent to 92 percent. Despite the results, further studies are needed during different growth stages to validate the visible, infrared, and active microwave responses to vegetation.

Single-Trial Classification of Multi-User P300-Based Brain-Computer Interface Using Riemannian Geometry.

PubMed

Korczowski, L; Congedo, M; Jutten, C

2015-08-01

The classification of electroencephalographic (EEG) data recorded from multiple users simultaneously is an important challenge in the field of Brain-Computer Interface (BCI). In this paper we compare different approaches for classification of single-trials Event-Related Potential (ERP) on two subjects playing a collaborative BCI game. The minimum distance to mean (MDM) classifier in a Riemannian framework is extended to use the diversity of the inter-subjects spatio-temporal statistics (MDM-hyper) or to merge multiple classifiers (MDM-multi). We show that both these classifiers outperform significantly the mean performance of the two users and analogous classifiers based on the step-wise linear discriminant analysis. More importantly, the MDM-multi outperforms the performance of the best player within the pair.

Land use/land cover mapping (1:25000) of Taiwan, Republic of China by automated multispectral interpretation of LANDSAT imagery

NASA Technical Reports Server (NTRS)

Sung, Q. C.; Miller, L. D.

1977-01-01

Three methods were tested for collection of the training sets needed to establish the spectral signatures of the land uses/land covers sought due to the difficulties of retrospective collection of representative ground control data. Computer preprocessing techniques applied to the digital images to improve the final classification results were geometric corrections, spectral band or image ratioing and statistical cleaning of the representative training sets. A minimal level of statistical verification was made based upon the comparisons between the airphoto estimates and the classification results. The verifications provided a further support to the selection of MSS band 5 and 7. It also indicated that the maximum likelihood ratioing technique can achieve more agreeable classification results with the airphoto estimates than the stepwise discriminant analysis.

The effect of combining two echo times in automatic brain tumor classification by MRS.

PubMed

García-Gómez, Juan M; Tortajada, Salvador; Vidal, César; Julià-Sapé, Margarida; Luts, Jan; Moreno-Torres, Angel; Van Huffel, Sabine; Arús, Carles; Robles, Montserrat

2008-11-01

(1)H MRS is becoming an accurate, non-invasive technique for initial examination of brain masses. We investigated if the combination of single-voxel (1)H MRS at 1.5 T at two different (TEs), short TE (PRESS or STEAM, 20-32 ms) and long TE (PRESS, 135-136 ms), improves the classification of brain tumors over using only one echo TE. A clinically validated dataset of 50 low-grade meningiomas, 105 aggressive tumors (glioblastoma and metastasis), and 30 low-grade glial tumors (astrocytomas grade II, oligodendrogliomas and oligoastrocytomas) was used to fit predictive models based on the combination of features from short-TEs and long-TE spectra. A new approach that combines the two consecutively was used to produce a single data vector from which relevant features of the two TE spectra could be extracted by means of three algorithms: stepwise, reliefF, and principal components analysis. Least squares support vector machines and linear discriminant analysis were applied to fit the pairwise and multiclass classifiers, respectively. Significant differences in performance were found when short-TE, long-TE or both spectra combined were used as input. In our dataset, to discriminate meningiomas, the combination of the two TE acquisitions produced optimal performance. To discriminate aggressive tumors from low-grade glial tumours, the use of short-TE acquisition alone was preferable. The classifier development strategy used here lends itself to automated learning and test performance processes, which may be of use for future web-based multicentric classifier development studies. Copyright (c) 2008 John Wiley & Sons, Ltd.

A pilot evaluation of a computer-based psychometric test battery designed to detect impairment in patients with cirrhosis.

PubMed

Cook, Nicola A; Kim, Jin Un; Pasha, Yasmin; Crossey, Mary Me; Schembri, Adrian J; Harel, Brian T; Kimhofer, Torben; Taylor-Robinson, Simon D

2017-01-01

Psychometric testing is used to identify patients with cirrhosis who have developed hepatic encephalopathy (HE). Most batteries consist of a series of paper-and-pencil tests, which are cumbersome for most clinicians. A modern, easy-to-use, computer-based battery would be a helpful clinical tool, given that in its minimal form, HE has an impact on both patients' quality of life and the ability to drive and operate machinery (with societal consequences). We compared the Cogstate™ computer battery testing with the Psychometric Hepatic Encephalopathy Score (PHES) tests, with a view to simplify the diagnosis. This was a prospective study of 27 patients with histologically proven cirrhosis. An analysis of psychometric testing was performed using accuracy of task performance and speed of completion as primary variables to create a correlation matrix. A stepwise linear regression analysis was performed with backward elimination, using analysis of variance. Strong correlations were found between the international shopping list, international shopping list delayed recall of Cogstate and the PHES digit symbol test. The Shopping List Tasks were the only tasks that consistently had P values of <0.05 in the linear regression analysis. Subtests of the Cogstate battery correlated very strongly with the digit symbol component of PHES in discriminating severity of HE. These findings would indicate that components of the current PHES battery with the international shopping list tasks of Cogstate would be discriminant and have the potential to be used easily in clinical practice.

Diagnostic value of fibronectin discriminant score for predicting liver fibrosis stages in chronic hepatitis C virus patients.

PubMed

Attallah, Abdelfattah M; Abdallah, Sanaa O; Attallah, Ahmed A; Omran, Mohamed M; Farid, Khaled; Nasif, Wesam A; Shiha, Gamal E; Abdel-Aziz, Abdel-Aziz F; Rasafy, Nancy; Shaker, Yehia M

2013-01-01

Several noninvasive predictive models were developed to substitute liver biopsy for fibrosis assessment. To evaluate the diagnostic value of fibronectin which reflect extracellular matrix metabolism and standard liver functions tests which reflect alterations in hepatic functions. Chronic hepatitis C (CHC) patients (n = 145) were evaluated using ROC curves and stepwise multivariate discriminant analysis (MDA) and was validated in 180 additional patients. Liver biochemical profile including transaminases, bilirubin, alkaline phosphatase, albumin, complete blood count were estimated. Fibronectin concentration was determined using monoclonal antibody and ELISA. A novel index named fibronectin discriminant score (FDS) based on fibronectin, APRI and albumin was developed. FDS produced areas under ROC curves (AUC) of 0.91 for significant fibrosis and 0.81 for advanced fibrosis. The FDS correctly classified 79% of the significant liver fibrosis patients (F2-F4) with 87% sensitivity and 75% specificity. The relative risk [odds ratio (OR)] of having significant liver fibrosis using the cut-off values determined by ROC curve analyses were 6.1 for fibronectin, 4.9 for APRI, and 4.2 for albumin. FDS predicted liver fibrosis with an OR of 16.8 for significant fibrosis and 8.6 for advanced fibrosis. The FDS had similar AUC and OR in the validation group to the estimation group without statistically significant difference. FDS predicted liver fibrosis with high degree of accuracy, potentially decreasing the number of liver biopsy required.

Personality features, dissociation, self-stigma, hope, and the complex treatment of depressive disorder

PubMed Central

Prasko, Jan; Ociskova, Marie; Grambal, Ales; Sigmundova, Zuzana; Kasalova, Petra; Marackova, Marketa; Holubova, Michaela; Vrbova, Kristyna; Latalova, Klara; Slepecky, Milos

2016-01-01

Objective Identifying the predictors of response to psychiatric and psychotherapeutic treatments may be useful for increasing treatment efficacy in pharmacoresistant depressive patients. The goal of this study was to examine the influence of dissociation, hope, personality trait, and selected demographic factors in treatment response of this group of patients. Methods Pharmacoresistant depressive inpatients were enrolled in the study. All patients completed Clinical Global Impression – both objective and subjective form (CGI), Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI) at baseline and after 6 weeks of combined pharmacotherapy and psychotherapy (group cognitive-behavioral or group psychodynamic) treatment as an outcome measures. The Internalized Stigma of Mental Illness Scale (ISMI), Dissociative Experience Scale (DES), Adult Dispositional Hope Scale (ADHS), and Temperament and Character Inventory (TCI-R) were completed at the start of the treatment with the intention to find the predictors of treatment efficacy. Results The study included 72 patients who were hospitalized for the pharmacoresistant major depression; 63 of them completed the study. The mean scores of BDI-II, BAI, subjCGI, and objCGI significantly decreased during the treatment. BDI-II relative change statistically significantly correlated with the total ISMI score, Discrimination Experience (ISMI subscale), and Harm Avoidance (TCI-R personality trait). According to stepwise regression, the strongest factors connected to BDI-II relative change were the duration of the disorder and Discrimination Experience (domain of ISMI). ObjCGI relative change significantly correlated with the level of dissociation (DES), the total ISMI score, hope in ADHS total score, and Self-Directedness (TCI-R). According to stepwise regression, the strongest factor connected to objCGI relative change was Discrimination Experience (domain of ISMI). The existence of comorbid personality disorder did not influence the treatment response. Conclusion According to the results of the present study, patients with pharmacoresistant depressive disorders, who have had more experience with discrimination because of their mental struggles, showed a poorer response to treatment. PMID:27785031

[An examination of the determinants of social withdrawal and affinity for social withdrawal].

PubMed

Watanabe, Asami; Matsui, Yutaka; Takatsuka, Yusuke

2010-12-01

This study examined the determinants of social withdrawal using data from a survey by the Tokyo Metropolitan Government Office for Youth Affairs and Public Safety (2008). In addition, this study identified young people who showed an affinity for social withdrawal although they were not in a state of withdrawal, and examined the determinants of an affinity for social withdrawal. The results of stepwise discriminant analysis showed that factors such as social phobia, depression, violence, and emotional bonds with family differentiated between the general youth group and the social withdrawal group and the "affinity group". Social phobia, violence, and refusal to be interfered in self-decision making differentiated between the social withdrawal group and the "affinity group". This study shows that an "affinity group" should be cared as well as an actual withdrawal group.

Clot formation is associated with fibrinogen and platelet forces in a cohort of severely-injured Emergency Department trauma patients

PubMed Central

White, Nathan J.; Newton, Jason C.; Martin, Erika J.; Mohammed, Bassem M.; Contaifer, Daniel; Bostic, Jessica L.; Brophy, Gretchen M.; Spiess, Bruce D.; Pusateri, Anthony E.; Ward, Kevin R.; Brophy, Donald F.

2015-01-01

Introduction Anticoagulation, fibrinogen consumption, fibrinolytic activation, and platelet dysfunction all interact to produce different clot formation responses after trauma. However, the relative contributions of these coagulation components to overall clot formation remains poorly defined. We examined for sources of heterogeneity in clot formation responses after trauma. Methods Blood was sampled in the Emergency Department from patients meeting trauma team activation criteria at an urban trauma center. Plasma prothrombin time (PT) ≥ 18 sec was used to define traumatic coagulopathy. Mean kaolin-activated thrombelastography (TEG) parameters were calculated and tested for heterogeneity using Analysis of Means (ANOM). Discriminant analysis and forward stepwise variable selection with linear regression were used to determine if PT, fibrinogen, platelet contractile force (PCF), and D-Dimer concentration, representing key mechanistic components of coagulopathy, each contribute to heterogeneous TEG responses after trauma. Results Of 95 subjects, 16% met criteria for coagulopathy. Coagulopathic subjects were more severely injured with greater shock, and received more blood products in the first 8 hours compared to non-coagulopathic subjects. Mean (SD) TEG maximal amplitude (MA) was significantly decreased in the coagulopathic group=57.5 (4.7) mm, vs. 62.7 (4.7), T test p<0.001. The MA also exceeded the ANOM predicted upper decision limit for the non-coagulopathic group and the lower decision limit for the coagulopathic group at alpha=0.05, suggesting significant heterogeneity from the overall cohort mean. Fibrinogen and PCF best discriminated TEG MA using discriminant analysis. Fibrinogen, PCF, and D-Dimer were primary covariates for TEG MA using regression analysis. Conclusion Heterogeneity in TEG-based clot formation in Emergency Department trauma patients was linked to changes in MA. Individual parameters representing fibrin polymerization, platelet contractile forces, and fibrinolysis were primarily associated with TEG MA after trauma and should be the focus of early hemostatic therapies. PMID:25643013

Using tunable diode laser spectroscopy to measure carbon isotope discrimination and mesophyll conductance to CO₂ diffusion dynamically at different CO₂ concentrations.

PubMed

Tazoe, Youshi; VON Caemmerer, Susanne; Estavillo, Gonzalo M; Evans, John R

2011-04-01

In C₃ leaves, the mesophyll conductance to CO₂ diffusion, g(m) , determines the drawdown in CO₂ concentration from intercellular airspace to the chloroplast stroma. Both g(m) and stomatal conductance limit photosynthetic rate and vary in response to the environment. We investigated the response of g(m) to changes in CO₂ in two Arabidopsis genotypes (including a mutant with open stomata, ost1), tobacco and wheat. We combined measurements of gas exchange with carbon isotope discrimination using tunable diode laser absorption spectroscopy with a CO₂ calibration system specially designed for a range of CO₂ and O₂ concentrations. CO₂ was initially increased from 200 to 1000 ppm and then decreased stepwise to 200 ppm and increased stepwise back to 1000 ppm, or the sequence was reversed. In 2% O₂ a step increase from 200 to 1000 ppm significantly decreased g(m) by 26-40% in all three species, whereas following a step decrease from 1000 to 200 ppm, the 26-38% increase in g(m) was not statistically significant. The response of g(m) to CO₂ was less in 21% O₂. Comparing wild type against the ost1 revealed that mesophyll and stomatal conductance varied independently in response to CO₂. We discuss the effects of isotope fractionation factors on estimating g(m) . © 2011 Blackwell Publishing Ltd.

Detection of high-risk atherosclerotic lesions by time-resolved fluorescence spectroscopy based on the Laguerre deconvolution technique

NASA Astrophysics Data System (ADS)

Jo, J. A.; Fang, Q.; Papaioannou, T.; Qiao, J. H.; Fishbein, M. C.; Beseth, B.; Dorafshar, A. H.; Reil, T.; Baker, D.; Freischlag, J.; Marcu, L.

2006-02-01

This study introduces new methods of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data analysis for tissue characterization. These analytical methods were applied for the detection of atherosclerotic vulnerable plaques. Upon pulsed nitrogen laser (337 nm, 1 ns) excitation, TR-LIFS measurements were obtained from carotid atherosclerotic plaque specimens (57 endarteroctomy patients) at 492 distinct areas. The emission was both spectrally- (360-600 nm range at 5 nm interval) and temporally- (0.3 ns resolution) resolved using a prototype clinically compatible fiber-optic catheter TR-LIFS apparatus. The TR-LIFS measurements were subsequently analyzed using a standard multiexponential deconvolution and a recently introduced Laguerre deconvolution technique. Based on their histopathology, the lesions were classified as early (thin intima), fibrotic (collagen-rich intima), and high-risk (thin cap over necrotic core and/or inflamed intima). Stepwise linear discriminant analysis (SLDA) was applied for lesion classification. Normalized spectral intensity values and Laguerre expansion coefficients (LEC) at discrete emission wavelengths (390, 450, 500 and 550 nm) were used as features for classification. The Laguerre based SLDA classifier provided discrimination of high-risk lesions with high sensitivity (SE>81%) and specificity (SP>95%). Based on these findings, we believe that TR-LIFS information derived from the Laguerre expansion coefficients can provide a valuable additional dimension for the diagnosis of high-risk vulnerable atherosclerotic plaques.

Diagnostic power of optic disc morphology, peripapillary retinal nerve fiber layer thickness, and macular inner retinal layer thickness in glaucoma diagnosis with fourier-domain optical coherence tomography.

PubMed

Huang, Jehn-Yu; Pekmezci, Melike; Mesiwala, Nisreen; Kao, Andrew; Lin, Shan

2011-02-01

To evaluate the capability of the optic disc, peripapillary retinal nerve fiber layer (P-RNFL), macular inner retinal layer (M-IRL) parameters, and their combination obtained by Fourier-domain optical coherent tomography (OCT) in differentiating a glaucoma suspect from perimetric glaucoma. Two hundred and twenty eyes from 220 patients were enrolled in this study. The optic disc morphology, P-RNFL, and M-IRL were assessed by the Fourier-domain OCT (RTVue OCT, Model RT100, Optovue, Fremont, CA). A linear discriminant function was generated by stepwise linear discriminant analysis on the basis of OCT parameters and demographic factors. The diagnostic power of these parameters was evaluated with receiver operating characteristic (ROC) curve analysis. The diagnostic power in the clinically relevant range (specificity ≥ 80%) was presented as the partial area under the ROC curve (partial AROC). The individual OCT parameter with the largest AROC and partial AROC in the high specificity (≥ 80%) range were cup/disc vertical ratio (AROC = 0.854 and partial AROC = 0.142) for the optic disc parameters, average thickness (AROC = 0.919 and partial AROC = 0.147) for P-RNFL parameters, inferior hemisphere thickness (AROC = 0.871 and partial AROC = 0.138) for M-IRL parameters, respectively. The linear discriminant function further enhanced the ability in detecting perimetric glaucoma (AROC = 0.970 and partial AROC = 0.172). Average P-RNFL thickness is the optimal individual OCT parameter to detect perimetric glaucoma. Simultaneous evaluation on disc morphology, P-RNFL, and M-IRL thickness can improve the diagnostic accuracy in diagnosing glaucoma.

Halobenzoquinone-mediated assembly of amino acid modified Mn-doped ZnS quantum dots for halobenzoquinones detection in drinking water.

PubMed

Jiao, Zhe; Zhang, Pengfei; Chen, Hongwei; Li, Jingwen; Zhong, Zhengquan; Fan, Hongbo; Cheng, Faliang

2018-10-05

Halobenzoquinones (HBQs) were reported as disinfection byproducts (DBPs) which had potential risk of bladder cancer. In this paper, a highly selective analytical method for HBQs was developed by HBQs-mediated assembly of amino acid modified Mn-doped ZnS/Quantum Dots (Mn: ZnS QDs). In the presence HBQs, a charge-transfer complex (CTC) was formed between aromatic rings of HBQs and the primary amino groups on the surface of the QDs. The formation of CTC led to the aggregation of QDs, as a result fluorescence decreasing occurred. The decrease was correlated with the concentration of HBQs. Then a fluorescence sensor array for discrimination of three kinds of HBQs including 2,6-Dichloro-1,4-benzoquinone (DCBQ), 2,6-Dibromo-1,4-benzoquinone (DBBQ) and 2,3,6-trichloro-1,4-benzoquinone (TCBQ) was developed. Four kinds of amino acids including cysteine, threonine, tyrosine and tryptophan were embellished on the Mn: ZnS QDs. The different extents of aggregation led to different fluorescence decreasing effect, thus distinct fluorescence patterns were created. It showed that three kinds of HBQs could be discriminated successfully by fluorescence sensor array at a range of concentrations through principal component analysis (PCA). The unknown samples were predicted by with a stepwise linear discriminant analysis (SLDA) using Mahalanobis distance as a selection criterion with accuracy of 100%. Remarkably, the practicability of the proposed sensor array was further validated by identification of three kinds of HBQs at different concentrations in real drinking water samples. Compared to LC/MS/MS, this fluorescent sensor array-based method was proved to be more convenient since the nanoparticles can be prepared flexibly according to the property of the target. Copyright © 2018 Elsevier B.V. All rights reserved.

Sexual dimorphism of the mandible in a contemporary Chinese Han population.

PubMed

Dong, Hongmei; Deng, Mohong; Wang, WenPeng; Zhang, Ji; Mu, Jiao; Zhu, Guanghui

2015-10-01

A present limitation of forensic anthropology practice in China is the lack of population-specific criteria on contemporary human skeletons. In this study, a sample of 203 maxillofacial Cone beam computed tomography (CBCT) images, including 96 male and 107 female cases (20-65 years old), was analyzed to explore mandible sexual dimorphism in a population of contemporary adult Han Chinese to investigate the potential use of the mandible as sex indicator. A three-dimensional image from mandible CBCT scans was reconstructed using the SimPlant Pro 11.40 software. Nine linear and two angular parameters were measured. Discriminant function analysis (DFA) and logistic regression analysis (LRA) were used to develop the mathematics models for sex determination. All of the linear measurements studied and one angular measurement were found to be sexually dimorphic, with the maximum mandibular length and bi-condylar breadth being the most dimorphic by univariate DFA and LRA respectively. The cross-validated sex allocation accuracies on multivariate were ranged from 84.2% (direct DFA), 83.5% (direct LRA), 83.3% (stepwise DFA) to 80.5% (stepwise LRA). In general, multivariate DFA yielded a higher accuracy and LRA obtained a lower sex bias, and therefore both DFA and LRA had their own advantages for sex determination by the mandible in this sample. These results suggest that the mandible expresses sexual dimorphism in the contemporary adult Han Chinese population, indicating an excellent sexual discriminatory ability. Cone beam computed tomography scanning can be used as alternative source for contemporary osteometric techniques. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Passive fishing techniques: a cause of turtle mortality in the Mississippi River

USGS Publications Warehouse

Barko, V.A.; Briggler, J.T.; Ostendorf, D.E.

2004-01-01

We investigated variation of incidentally captured turtle mortality in response to environmental factors and passive fishing techniques. We used Long Term Resource Monitoring Program (LTRMP) data collected from 1996 to 2001 in the unimpounded upper Mississippi River (UMR) adjacent to Missouri and Illinois, USA. We used a principle components analysis (PCA) and a stepwise discriminant function analysis to identify factors correlated with mortality of captured turtles. Furthermore, we were interested in what percentage of turtles died from passive fishing techniques and what techniques caused the most turtle mortality. The main factors influencing captured turtle mortality were water temperature and depth at net deployment. Fyke nets captured the most turtles and caused the most turtle mortality. Almost 90% of mortalities occurred in offshore aquatic areas (i.e., side channel or tributary). Our results provide information on causes of turtle mortality (as bycatch) in a riverine system and implications for river turtle conservation by suggesting management strategies to reduce turtle bycatch and decrease mortality of captured turtles.

Nest site characteristics of three coexisting Accipiter hawks in northeastern Oregon

USGS Publications Warehouse

Moore, K.R.; Henny, C.J.

1983-01-01

Habitat data were evaluated at 34 Goshawk (Accipiter gentilis), 31 Cooper's Hawk (A. cooperii), and 15 Sharp-shinned Hawk (A. striatus) nest sites in coniferous forests of northeastern Oregon. Crown volume profiles indicate a strong similarity in vegetative structure at nest sites of cooperii and striatus; both commonly nest in younger successional stands than gentilis. Habitat separation of nest sites among the three species was illustrated using a stepwise discriminant analysis; 88% of all gentilis sites were correctly classified. Interspecific overlap in nest site habitat was further demonstrated using a canonical analysis of habitat variables. Nest site habitat space of gentilis is distinct and is less variable in structure than that of the other species. Cooperii preferred nesting sites with norhern aspects, whereas striatus and gentilis showed no preference. The use of mistletoe (Arceuthobium sp.) growth by cooperii for nest platforms (64% of all nests) may explain its preference for Douglas fir (Pseudotsuga menziesii) as a nesting tree. Douglas fir is most commonly parasitized by mistletoe.

Novel candidate genes of the PARK7 interactome as mediators of apoptosis and acetylation in multiple sclerosis: An in silico analysis.

PubMed

Vavougios, George D; Zarogiannis, Sotirios G; Krogfelt, Karen Angeliki; Gourgoulianis, Konstantinos; Mitsikostas, Dimos Dimitrios; Hadjigeorgiou, Georgios

2018-01-01

currently only 4 studies have explored the potential role of PARK7's dysregulation in MS pathophysiology Currently, no study has evaluated the potential role of the PARK7 interactome in MS. The aim of our study was to assess the differential expression of PARK7 mRNA in peripheral blood mononuclears (PBMCs) donated from MS versus healthy patients using data mining techniques. The PARK7 interactome data from the GDS3920 profile were scrutinized for differentially expressed genes (DEGs); Gene Enrichment Analysis (GEA) was used to detect significantly enriched biological functions. 27 differentially expressed genes in the MS dataset were detected; 12 of these (NDUFA4, UBA2, TDP2, NPM1, NDUFS3, SUMO1, PIAS2, KIAA0101, RBBP4, NONO, RBBP7 AND HSPA4) are reported for the first time in MS. Stepwise Linear Discriminant Function Analysis constructed a predictive model (Wilk's λ = 0.176, χ 2 = 45.204, p = 1.5275e -10 ) with 2 variables (TIDP2, RBBP4) that achieved 96.6% accuracy when discriminating between patients and controls. Gene Enrichment Analysis revealed that induction and regulation of programmed / intrinsic cell death represented the most salient Gene Ontology annotations. Cross-validation on systemic lupus erythematosus and ischemic stroke datasets revealed that these functions are unique to the MS dataset. Based on our results, novel potential target genes are revealed; these differentially expressed genes regulate epigenetic and apoptotic pathways that may further elucidate underlying mechanisms of autorreactivity in MS. Copyright © 2017 Elsevier B.V. All rights reserved.

A pilot evaluation of a computer-based psychometric test battery designed to detect impairment in patients with cirrhosis

PubMed Central

Cook, Nicola A; Kim, Jin Un; Pasha, Yasmin; Crossey, Mary ME; Schembri, Adrian J; Harel, Brian T; Kimhofer, Torben; Taylor-Robinson, Simon D

2017-01-01

Background Psychometric testing is used to identify patients with cirrhosis who have developed hepatic encephalopathy (HE). Most batteries consist of a series of paper-and-pencil tests, which are cumbersome for most clinicians. A modern, easy-to-use, computer-based battery would be a helpful clinical tool, given that in its minimal form, HE has an impact on both patients’ quality of life and the ability to drive and operate machinery (with societal consequences). Aim We compared the Cogstate™ computer battery testing with the Psychometric Hepatic Encephalopathy Score (PHES) tests, with a view to simplify the diagnosis. Methods This was a prospective study of 27 patients with histologically proven cirrhosis. An analysis of psychometric testing was performed using accuracy of task performance and speed of completion as primary variables to create a correlation matrix. A stepwise linear regression analysis was performed with backward elimination, using analysis of variance. Results Strong correlations were found between the international shopping list, international shopping list delayed recall of Cogstate and the PHES digit symbol test. The Shopping List Tasks were the only tasks that consistently had P values of <0.05 in the linear regression analysis. Conclusion Subtests of the Cogstate battery correlated very strongly with the digit symbol component of PHES in discriminating severity of HE. These findings would indicate that components of the current PHES battery with the international shopping list tasks of Cogstate would be discriminant and have the potential to be used easily in clinical practice. PMID:28919805

Assessment of intracranial pressure with ultrasonographic retrobulbar optic nerve sheath diameter measurement.

PubMed

Liu, Dachuan; Li, Zhen; Zhang, Xuxiang; Zhao, Liping; Jia, Jianping; Sun, Fei; Wang, Yaxing; Ma, Daqing; Wei, Wenbin

2017-09-29

Ultrasonograpic retrobulbar optic nerve sheath diameter (ONSD) measurement is considered to be an alternative noninvasive method to estimate intracranial pressure,but the further validation is urgently needed. The aim of the current study was to investigate the association of the ultrasonographic ONSD and intracranial pressure (ICP) in patients. One hundred and ten patients whose intracranial pressure measured via lumbar puncture were enrolled in the study. Their retrobulbar ONSD with B-scan ultrasound was determined just before lumber puncture. The correlation between the ICP and the body mass index (BMI), ONSD or age was established respectively with the Pearson correlation coefficient analysis. The discriminant analysis was used to obtain a discriminant formula for predicting ICP with the ONSD、BMI、gender and age. Another 20 patients were recruited for further validation the efficiency of this discriminant equation. The mean ICP was 215.3 ± 81.2 mmH 2 O. ONSD was 5.70 ± 0.80 mm in the right eye and 5.80 ± 0.77 mm in the left eye. A significant correlation was found between ICP and BMI (r = 0.554, p < 0.001), the mean ONSD (r = 0.61, P < 0.001), but not with age (r = -0.131, p = 0.174) and gender (r = 0.03, p = 0.753). Using receiver operating characteristic (ROC) curve analysis, the critical value for the risk mean-ONSD was 5.6 mm from the ROC curve, with the sensitivity of 86.2% and specificity of 73.1%. With 200 mmH 2 O as the cutoff point for a high or low ICP, stepwise discriminant was applied, the sensitivity and specificity of ONSD predicting ICP was 84.5%-85.7% and 86.5%-92.3%. Ophthalmic ultrasound measurement of ONSD may be a good surrogate of invasive ICP measurement. This non-invasive method may be an alternative approach to predict the ICP value of patients whose ICP measurement via lumbar puncture are in high risk. The discriminant formula, which incorporated the factor of BMI, had similar sensitivity and higher specificity than the ROC curve.

Combined striatal binding and cerebral influx analysis of dynamic 11C-raclopride PET improves early differentiation between multiple-system atrophy and Parkinson disease.

PubMed

Van Laere, Koen; Clerinx, Kristien; D'Hondt, Eduard; de Groot, Tjibbe; Vandenberghe, Wim

2010-04-01

Striatal dopamine D(2) receptor (D2R) PET has been proposed to differentiate between Parkinson disease (PD) and multiple-system atrophy with predominant parkinsonism (MSA-P). However, considerable overlap in striatal D(2) binding may exist between PD and MSA-P. It has been shown that imaging of neuronal activity, as determined by metabolism or perfusion, can also help distinguish PD from MSA-P. We investigated whether the differential diagnostic value of (11)C-raclopride PET could be improved by dynamic scan analysis combining D2R binding and regional tracer influx. (11)C-raclopride PET was performed in 9 MSA-P patients (mean age +/- SD, 56.2 +/- 10.2 y; disease duration, 2.9 +/- 0.8 y; median Hoehn-Yahr score, 3), 10 PD patients (mean age +/- SD, 65.7 +/- 8.1 y; disease duration, 3.3 +/- 1.5 y; median Hoehn-Yahr score, 1.5), and 10 healthy controls (mean age +/- SD, 61.6 +/- 6.5 y). Diagnosis was obtained after prolonged follow-up (MSA-P, 5.5 +/- 2.0 y; PD, 6.0 +/- 2.3 y) using validated clinical criteria. Spatially normalized parametric images of binding potential (BP) and local influx ratio (R(1) = K(1)/K'(1)) of (11)C-raclopride were obtained using a voxelwise reference tissue model with occipital cortex as reference region. Stepwise forward discriminant analysis with cross-validation, with and without the inclusion of regional R(1) values, was performed using a predefined volume-of-interest template. Using conventional BP values, we correctly classified 65.5% (all values given with cross-validation) of 29 cases only. The combination of BP and R(1) information increased discrimination accuracy to 79.3%. When healthy controls were not included and patients only were considered, BP information alone discriminated PD and MSA-P in 84.2% of cases, but the combination with R(1) data increased accuracy to 100%. Discriminant analysis using combined striatal D2R BP and cerebral influx ratio information of a single dynamic (11)C-raclopride PET scan distinguishes MSA-P and PD patients with high accuracy and is superior to conventional methods of striatal D2R binding analysis.

MULGRES: a computer program for stepwise multiple regression analysis

Treesearch

A. Jeff Martin

1971-01-01

MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.

Cognitive and Linguistic Sources of Variance in 2-Year-Olds’ Speech-Sound Discrimination: A Preliminary Investigation

PubMed Central

Lalonde, Kaylah; Holt, Rachael Frush

2017-01-01

Purpose This preliminary investigation explored potential cognitive and linguistic sources of variance in 2-year-olds’ speech-sound discrimination by using the toddler change/no-change procedure and examined whether modifications would result in a procedure that can be used consistently with younger 2-year-olds. Method Twenty typically developing 2-year-olds completed the newly modified toddler change/no-change procedure. Behavioral tests and parent report questionnaires were used to measure several cognitive and linguistic constructs. Stepwise linear regression was used to relate discrimination sensitivity to the cognitive and linguistic measures. In addition, discrimination results from the current experiment were compared with those from 2-year-old children tested in a previous experiment. Results Receptive vocabulary and working memory explained 56.6% of variance in discrimination performance. Performance was not different on the modified toddler change/no-change procedure used in the current experiment from in a previous investigation, which used the original version of the procedure. Conclusions The relationship between speech discrimination and receptive vocabulary and working memory provides further evidence that the procedure is sensitive to the strength of perceptual representations. The role for working memory might also suggest that there are specific subject-related, nonsensory factors limiting the applicability of the procedure to children who have not reached the necessary levels of cognitive and linguistic development. PMID:24023371

Cognitive and linguistic sources of variance in 2-year-olds’ speech-sound discrimination: a preliminary investigation.

PubMed

Lalonde, Kaylah; Holt, Rachael Frush

2014-02-01

This preliminary investigation explored potential cognitive and linguistic sources of variance in 2-year-olds’ speech-sound discrimination by using the toddler change/ no-change procedure and examined whether modifications would result in a procedure that can be used consistently with younger 2-year-olds. Twenty typically developing 2-year-olds completed the newly modified toddler change/no-change procedure. Behavioral tests and parent report questionnaires were used to measure several cognitive and linguistic constructs. Stepwise linear regression was used to relate discrimination sensitivity to the cognitive and linguistic measures. In addition, discrimination results from the current experiment were compared with those from 2-year-old children tested in a previous experiment. Receptive vocabulary and working memory explained 56.6% of variance in discrimination performance. Performance was not different on the modified toddler change/no-change procedure used in the current experiment from in a previous investigation, which used the original version of the procedure. The relationship between speech discrimination and receptive vocabulary and working memory provides further evidence that the procedure is sensitive to the strength of perceptual representations. The role for working memory might also suggest that there are specific subject-related, nonsensory factors limiting the applicability of the procedure to children who have not reached the necessary levels of cognitive and linguistic development.

Discriminating between Graduates and Failure in the USAF Medical Laboratory Specialist School: An Explorative Approach.

DTIC Science & Technology

1981-12-01

occurred on the Introversion Scale of the NMPI. 20 A review of the use of psychological tests on MT’s was accomplished by Driver and Feeley [1974...programs, Gondek [1981] has recommended that the best pro- cedure for variable inclusion when using a stepwise procedure is to use the threshold default...values supplied by the package, since no simple rules exist for determining entry or removal thresholds for partial F’s, tolerance statistics, or any of

Diagnosis of vulnerable atherosclerotic plaques by time-resolved fluorescence spectroscopy and ultrasound imaging.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Beseth, B; Dorafshar, A H; Reil, T; Baker, D; Freischlag, J; Shung, K K; Sun, L; Marcu, L

2006-01-01

In this study, time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) and ultrasonography were applied to detect vulnerable (high-risk) atherosclerotic plaque. A total of 813 TR-LIFS measurements were taken from carotid plaques of 65 patients, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified by histopathology as thin, fibrotic, calcified, low-inflamed, inflamed and necrotic lesions. Spectral and time-resolved parameters (normalized intensity values and Laguerre expansion coefficients) were extracted from the TR-LIFS data. Feature selection for classification was performed by either analysis of variance (ANOVA) or principal component analysis (PCA). A stepwise linear discriminant analysis algorithm was developed for detecting inflamed and necrotic lesion, representing the most vulnerable plaques. These vulnerable plaques were detected with high sensitivity (>80%) and specificity (>90%). Ultrasound (US) imaging was obtained in 4 carotid plaques in addition to TR-LIFS examination. Preliminary results indicate that US provides important structural information of the plaques that could be combined with the compositional information obtained by TR-LIFS, to obtain a more accurate diagnosis of vulnerable atherosclerotic plaque.

Influence of genetic discrimination perceptions and knowledge on cancer genetics referral practice among clinicians.

PubMed

Lowstuter, Katrina J; Sand, Sharon; Blazer, Kathleen R; MacDonald, Deborah J; Banks, Kimberly C; Lee, Carol A; Schwerin, Barbara U; Juarez, Margaret; Uman, Gwen C; Weitzel, Jeffrey N

2008-09-01

To describe nongenetics clinicians' perceptions and knowledge of cancer genetics and laws prohibiting genetic discrimination, attitudes toward the use of cancer genetic testing, and referral practices. Invitations to participate were sent to a random stratified sample of California Medical Association members and to all members of California Association of Nurse Practitioners and California Latino Medical Association. Responders in active practice were eligible and completed a 47-item survey. There were 1181 qualified participants (62% physicians). Although 96% viewed genetic testing as beneficial for their patients, 75% believed fear of genetic discrimination would cause patients to decline testing. More than 60% were not aware of federal or California laws prohibiting health insurance discrimination--concern about genetic discrimination was selected as a reason for nonreferral by 11%. A positive attitude toward genetic testing was the strongest predictor of referral (odds ratio: 3.55 [95% confidence interval: 2.24-5.63], P < 0.001) in stepwise logistic regression analyses. The higher the belief in genetic discrimination, the less likely a participant was to refer (odds ratio: 0.72 [95% confidence interval: 0.518-0.991], P < 0.05), whereas more knowledge of genetic discrimination law was associated with comfort recommending (odds ratio: 1.18 [95% confidence interval: 1.11-1.25], P < 0.001) and actual referral (odds ratio: 3.55 [95% confidence interval: 2.24-5.63], P < 0.001). Concerns about genetic discrimination and knowledge deficits may be barriers to cancer genetics referrals. Clinician education may help promote access to cancer screening and prevention.

Three-dimensionally derived interlandmark distances for sex estimation in intact and fragmentary crania.

PubMed

Small, Candice; Schepartz, Lynne; Hemingway, Jason; Brits, Desiré

2018-06-01

The skull is the element most frequently presented to forensic anthropologists for analysis yet weathering, corpse maiming, and scavenger activity often result in damage and fragmentation. This fragmentation results in a reduction in the number of traditional calliper derived measurements that can be obtained and subjected to discriminant based analyses for sex estimation. In this investigation, we employed three-dimensional geometric morphometric methods to derive novel interlandmark distance measures across six regions of the cranium including the basicranium, basipalate, zygoma, orbits and the cranium globally to create functions to discriminate sex with high efficacy, even in the event of fragmentation. Forty-five homologous landmarks were digitised across each of 227 (114 males and 113 females) South African crania of European descent (white) sampled from the Raymond A Dart Collection of Human Skeletons, housed in the School of Anatomical Sciences, University of the Witwatersrand, South Africa. A total of 990 interlandmark distances (ILDs) were mathematically derived using Pythagorean geometry. These ILDs were then filtered by region and subjected to both direct and stepwise discriminant function analyses. Discriminant equations where derived for each region and achieved the following average cross-validated sex estimation accuracies: basicranium-74%; basipalate-80.2%; zygomatic-82.4; orbits-71.8%; nasomaxilla-83.7%; global cranium-88.2%. A large number of the ILDs used to derive the discriminant functions are novel, demonstrating the efficacy of geometric morphometric methods and illustrating the need to reassess old methods of data collection using modern methods to determine whether they best capture biological differences. The results of this study provide an invaluable contribution to forensic anthropology in South Africa as it provides an accurate, practical means of assessing sex using fragmentary material that may otherwise have been disregarded. These will undeniable aid in accurate sex estimation and ultimately, victim identification. Copyright © 2018 Elsevier B.V. All rights reserved.

Wavelets analysis for differentiating solid, non-macroscopic fat containing, enhancing renal masses: a pilot study

NASA Astrophysics Data System (ADS)

Varghese, Bino; Hwang, Darryl; Mohamed, Passant; Cen, Steven; Deng, Christopher; Chang, Michael; Duddalwar, Vinay

2017-11-01

Purpose: To evaluate potential use of wavelets analysis in discriminating benign and malignant renal masses (RM) Materials and Methods: Regions of interest of the whole lesion were manually segmented and co-registered from multiphase CT acquisitions of 144 patients (98 malignant RM: renal cell carcinoma (RCC) and 46 benign RM: oncocytoma, lipid-poor angiomyolipoma). Here, the Haar wavelet was used to analyze the grayscale images of the largest segmented tumor in the axial direction. Six metrics (energy, entropy, homogeneity, contrast, standard deviation (SD) and variance) derived from 3-levels of image decomposition in 3 directions (horizontal, vertical and diagonal) respectively, were used to quantify tumor texture. Independent t-test or Wilcoxon rank sum test depending on data normality were used as exploratory univariate analysis. Stepwise logistic regression and receiver operator characteristics (ROC) curve analysis were used to select predictors and assess prediction accuracy, respectively. Results: Consistently, 5 out of 6 wavelet-based texture measures (except homogeneity) were higher for malignant tumors compared to benign, when accounting for individual texture direction. Homogeneity was consistently lower in malignant than benign tumors irrespective of direction. SD and variance measured in the diagonal direction on the corticomedullary phase showed significant (p<0.05) difference between benign versus malignant tumors. The multivariate model with variance (3 directions) and SD (vertical direction) extracted from the excretory and pre-contrast phase, respectively showed an area under the ROC curve (AUC) of 0.78 (p < 0.05) in discriminating malignant from benign. Conclusion: Wavelet analysis is a valuable texture evaluation tool to add to a radiomics platforms geared at reliably characterizing and stratifying renal masses.

Bayesian multimodel inference of soil microbial respiration models: Theory, application and future prospective

NASA Astrophysics Data System (ADS)

Elshall, A. S.; Ye, M.; Niu, G. Y.; Barron-Gafford, G.

2015-12-01

Models in biogeoscience involve uncertainties in observation data, model inputs, model structure, model processes and modeling scenarios. To accommodate for different sources of uncertainty, multimodal analysis such as model combination, model selection, model elimination or model discrimination are becoming more popular. To illustrate theoretical and practical challenges of multimodal analysis, we use an example about microbial soil respiration modeling. Global soil respiration releases more than ten times more carbon dioxide to the atmosphere than all anthropogenic emissions. Thus, improving our understanding of microbial soil respiration is essential for improving climate change models. This study focuses on a poorly understood phenomena, which is the soil microbial respiration pulses in response to episodic rainfall pulses (the "Birch effect"). We hypothesize that the "Birch effect" is generated by the following three mechanisms. To test our hypothesis, we developed and assessed five evolving microbial-enzyme models against field measurements from a semiarid Savannah that is characterized by pulsed precipitation. These five model evolve step-wise such that the first model includes none of these three mechanism, while the fifth model includes the three mechanisms. The basic component of Bayesian multimodal analysis is the estimation of marginal likelihood to rank the candidate models based on their overall likelihood with respect to observation data. The first part of the study focuses on using this Bayesian scheme to discriminate between these five candidate models. The second part discusses some theoretical and practical challenges, which are mainly the effect of likelihood function selection and the marginal likelihood estimation methods on both model ranking and Bayesian model averaging. The study shows that making valid inference from scientific data is not a trivial task, since we are not only uncertain about the candidate scientific models, but also about the statistical methods that are used to discriminate between these models.

Age-specific productivity and nest site characteristics of Cooper's hawks (Accipiter cooperii)

USGS Publications Warehouse

Moore, K.R.; Henny, C.J.

1984-01-01

Nesting Cooper's Hawks (Accipiter cooperii) were studied in northeastern Oregon. Second-year (SY) males did not breed, but 22 percent of the breeding females were SY's. Mean clutch size (P = 0.012) and mean number of young fledged per pair that laid eggs (P < 0.10) were lower for SY females than for adult (after second year [ASY}) females; however, an equal percentage of the eggs (excluding a collected sample egg) yielded fledged young for each age class. Stepwise discriminant analysis suggested differences in structural characteristics of the nest site habitat for ASY and SY females, i.e., SY female nest sites were associated with younger successional stages than ASY female nest sites. Nests of both age groups were built in trees with high crown volume, but ASY females utilized mistletoe (Arceuthobium sp.) for nest structures more frequently (P < 0.01) than SY females.

Potential use of ionic species for identifying source land-uses of stormwater runoff.

PubMed

Lee, Dong Hoon; Kim, Jin Hwi; Mendoza, Joseph A; Lee, Chang-Hee; Kang, Joo-Hyon

2017-02-01

Identifying critical land-uses or source areas is important to prioritize resources for cost-effective stormwater management. This study investigated the use of information on ionic composition as a fingerprint to identify the source land-use of stormwater runoff. We used 12 ionic species in stormwater runoff monitored for a total of 20 storm events at five sites with different land-use compositions during the 2012-2014 wet seasons. A stepwise forward discriminant function analysis (DFA) with the jack-knifed cross validation approach was used to select ionic species that better discriminate the land-use of its source. Of the 12 ionic species, 9 species (K + , Mg 2+ , Na + , NH 4 + , Br - , Cl - , F - , NO 2 - , and SO 4 2- ) were selected for better performance of the DFA. The DFA successfully differentiated stormwater samples from urban, rural, and construction sites using concentrations of the ionic species (70%, 95%, and 91% of correct classification, respectively). Over 80% of the new data cases were correctly classified by the trained DFA model. When applied to data cases from a mixed land-use catchment and downstream, the DFA model showed the greater impact of urban areas and rural areas respectively in the earlier and later parts of a storm event.

Young swimmers' classification based on kinematics, hydrodynamics, and anthropometrics.

PubMed

Barbosa, Tiago M; Morais, Jorge E; Costa, Mário J; Goncalves, José; Marinho, Daniel A; Silva, António J

2014-04-01

The aim of this article has been to classify swimmers based on kinematics, hydrodynamics, and anthropometrics. Sixty-seven young swimmers made a maximal 25 m front-crawl to measure with a speedometer the swimming velocity (v), speed-fluctuation (dv) and dv normalized to v (dv/v). Another two 25 m bouts with and without carrying a perturbation device were made to estimate active drag coefficient (CDa). Trunk transverse surface area (S) was measured with photogrammetric technique on land and in the hydrodynamic position. Cluster 1 was related to swimmers with a high speed fluctuation (ie, dv and dv/v), cluster 2 with anthropometrics (ie, S) and cluster 3 with a high hydrodynamic profile (ie, CDa). The variable that seems to discriminate better the clusters was the dv/v (F=53.680; P<.001), followed by the dv (F=28.506; P<.001), CDa (F=21.025; P<.001), S (F=6.297; P<.01) and v (F=5.375; P=.01). Stepwise discriminant analysis extracted 2 functions: Function 1 was mainly defined by dv/v and S (74.3% of variance), whereas function 2 was mainly defined by CDa (25.7% of variance). It can be concluded that kinematics, hydrodynamics and anthropometrics are determinant domains in which to classify and characterize young swimmers' profiles.

Multivariate Profiles of Selected versus Non-Selected Elite Youth Brazilian Soccer Players

PubMed Central

Alves, Isabella S.; Padilha, Maickel B.; Casanova, Filipe; Puggina, Enrico F.; Maia, José

2017-01-01

Abstract This study determined whether a multivariate profile more effectively discriminated selected than non-selected elite youth Brazilian soccer players. This examination was carried out on 66 youth soccer players (selected, n = 28, mean age 16.3 ± 0.1; non-selected, n = 38, mean age 16.7 ± 0.4) using objective instruments. Multivariate profiles were assessed through anthropometric characteristics, biological maturation, tactical-technical skills, and motor performance. The Student’s t-test identified that selected players exhibited significantly higher values for height (t = 2.331, p = 0.02), lean body mass (t = 2.441, p = 0.01), and maturity offset (t = 4.559, p < 0.001), as well as performed better in declarative tactical knowledge (t = 10.484, p < 0.001), shooting (t = 2.188, p = 0.03), dribbling (t = 5.914, p < 0.001), speed – 30 m (t = 8.304, p < 0.001), countermovement jump (t = 2.718, p = 0.008), and peak power tests (t = 2.454, p = 0.01). Forward stepwise discriminant function analysis showed that declarative tactical knowledge, running speed –30 m, maturity offset, dribbling, height, and peak power correctly classified 97% of the selected players. These findings may have implications for a highly efficient selection process with objective measures of youth players in soccer clubs. PMID:29339991

Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B.

PubMed

Chen, Xiao Yu; Ma, Li Zhuang; Chu, Na; Zhou, Min; Hu, Yiyang

2013-01-01

Chronic hepatitis B (CHB) is a serious public health problem, and Traditional Chinese Medicine (TCM) plays an important role in the control and treatment for CHB. In the treatment of TCM, zheng discrimination is the most important step. In this paper, an approach based on CFS-GA (Correlation based Feature Selection and Genetic Algorithm) and C5.0 boost decision tree is used for zheng classification and progression in the TCM treatment of CHB. The CFS-GA performs better than the typical method of CFS. By CFS-GA, the acquired attribute subset is classified by C5.0 boost decision tree for TCM zheng classification of CHB, and C5.0 decision tree outperforms two typical decision trees of NBTree and REPTree on CFS-GA, CFS, and nonselection in comparison. Based on the critical indicators from C5.0 decision tree, important lab indicators in zheng progression are obtained by the method of stepwise discriminant analysis for expressing TCM zhengs in CHB, and alterations of the important indicators are also analyzed in zheng progression. In conclusion, all the three decision trees perform better on CFS-GA than on CFS and nonselection, and C5.0 decision tree outperforms the two typical decision trees both on attribute selection and nonselection.

Novel non-invasive biological predictive index for liver fibrosis in hepatitis C virus genotype 4 patients

PubMed Central

Khattab, Mahmoud; Sakr, Mohamed Amin; Fattah, Mohamed Abdel; Mousa, Youssef; Soliman, Elwy; Breedy, Ashraf; Fathi, Mona; Gaber, Salwa; Altaweil, Ahmed; Osman, Ashraf; Hassouna, Ahmed; Motawea, Ibrahim

2016-01-01

AIM To investigate the diagnostic ability of a non-invasive biological marker to predict liver fibrosis in hepatitis C genotype 4 patients with high accuracy. METHODS A cohort of 332 patients infected with hepatitis C genotype 4 was included in this cross-sectional study. Fasting plasma glucose, insulin, C-peptide, and angiotensin-converting enzyme serum levels were measured. Insulin resistance was mathematically calculated using the homeostasis model of insulin resistance (HOMA-IR). RESULTS Fibrosis stages were distributed based on Metavir score as follows: F0 = 43, F1 = 136, F2 = 64, F3 = 45 and F4 = 44. Statistical analysis relied upon reclassification of fibrosis stages into mild fibrosis (F0-F) = 179, moderate fibrosis (F2) = 64, and advanced fibrosis (F3-F4) = 89. Univariate analysis indicated that age, log aspartate amino transaminase, log HOMA-IR and log platelet count were independent predictors of liver fibrosis stage (P < 0.0001). A stepwise multivariate discriminant functional analysis was used to drive a discriminative model for liver fibrosis. Our index used cut-off values of ≥ 0.86 and ≤ -0.31 to diagnose advanced and mild fibrosis, respectively, with receiving operating characteristics of 0.91 and 0.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio were: 73%, 91%, 75%, 90% and 8.0 respectively for advanced fibrosis, and 67%, 88%, 84%, 70% and 4.9, respectively, for mild fibrosis. CONCLUSION Our predictive model is easily available and reproducible, and predicted liver fibrosis with acceptable accuracy. PMID:27917265

Novel non-invasive biological predictive index for liver fibrosis in hepatitis C virus genotype 4 patients.

PubMed

Khattab, Mahmoud; Sakr, Mohamed Amin; Fattah, Mohamed Abdel; Mousa, Youssef; Soliman, Elwy; Breedy, Ashraf; Fathi, Mona; Gaber, Salwa; Altaweil, Ahmed; Osman, Ashraf; Hassouna, Ahmed; Motawea, Ibrahim

2016-11-18

To investigate the diagnostic ability of a non-invasive biological marker to predict liver fibrosis in hepatitis C genotype 4 patients with high accuracy. A cohort of 332 patients infected with hepatitis C genotype 4 was included in this cross-sectional study. Fasting plasma glucose, insulin, C-peptide, and angiotensin-converting enzyme serum levels were measured. Insulin resistance was mathematically calculated using the homeostasis model of insulin resistance (HOMA-IR). Fibrosis stages were distributed based on Metavir score as follows: F0 = 43, F1 = 136, F2 = 64, F3 = 45 and F4 = 44. Statistical analysis relied upon reclassification of fibrosis stages into mild fibrosis (F0-F) = 179, moderate fibrosis (F2) = 64, and advanced fibrosis (F3-F4) = 89. Univariate analysis indicated that age, log aspartate amino transaminase, log HOMA-IR and log platelet count were independent predictors of liver fibrosis stage ( P < 0.0001). A stepwise multivariate discriminant functional analysis was used to drive a discriminative model for liver fibrosis. Our index used cut-off values of ≥ 0.86 and ≤ -0.31 to diagnose advanced and mild fibrosis, respectively, with receiving operating characteristics of 0.91 and 0.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio were: 73%, 91%, 75%, 90% and 8.0 respectively for advanced fibrosis, and 67%, 88%, 84%, 70% and 4.9, respectively, for mild fibrosis. Our predictive model is easily available and reproducible, and predicted liver fibrosis with acceptable accuracy.

Classifying northern forests using Thematic Mapper Simulator data

NASA Technical Reports Server (NTRS)

Nelson, R. F.; Latty, R. S.; Mott, G.

1984-01-01

Thematic Mapper Simulator data were collected over a 23,200 hectare forested area near Baxter State Park in north-central Maine. Photointerpreted ground reference information was used to drive a stratified random sampling procedure for waveband discriminant analyses and to generate training statistics and test pixel accuracies. Stepwise discriminant analyses indicated that the following bands best differentiated the thirteen level II - III cover types (in order of entry): near infrared (0.77 to 0.90 micron), blue (0.46 0.52 micron), first middle infrared (1.53 to 1.73 microns), second middle infrared (2.06 to 2.33 microsn), red (0.63 to 0.69 micron), thermal (10.32 to 12.33 microns). Classification accuracies peaked at 58 percent for thirteen level II-III land-cover classes and at 65 percent for ten level II classes.

Multifactorial Analysis of a Biomarker Pool for Alzheimer Disease Risk in a North Indian Population.

PubMed

Talwar, Puneet; Grover, Sandeep; Sinha, Juhi; Chandna, Puneet; Agarwal, Rachna; Kushwaha, Suman; Kukreti, Ritushree

2017-01-01

Alzheimer disease (AD) is a progressive neurodegenerative disease with a complex multifactorial etiology. Here, we aim to identify a biomarker pool comprised of genetic variants and blood biomarkers as predictor of AD risk. We performed a case-control study involving 108 cases and 159 non-demented healthy controls to examine the association of multiple biomarkers with AD risk. The APOE genotyping revealed that ε4 allele frequency was significantly high (p value = 0.0001, OR = 2.66, 95% CI 1.58-4.46) in AD as compared to controls, whereas ε2 (p = 0.0430, OR = 0.29, CI 0.07-1.10) was overrepresented in controls. In biochemical assays, significant differences in levels of total copper, free copper, zinc, copper/zinc ratio, iron, epidermal growth factor receptor (EGFR), leptin, and albumin were also observed. The AD risk score (ADRS) as a linear combination of 6 candidate markers involving age, education status, APOE ε4 allele, levels of iron, Cu/Zn ratio, and EGFR was created using stepwise linear discriminant analysis. The area under the ROC curve of the ADRS panel for predicting AD risk was significantly high (AUC = 0.84, p < 0.0001, 95% CI 0.78-0.89, sensitivity = 70.0%, specificity = 83.8%) compared to individual parameters. These findings support the multifactorial etiology of AD and demonstrate the ability of a panel involving 6 biomarkers to discriminate AD cases from non-demented healthy controls. © 2017 S. Karger AG, Basel.

Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques.

PubMed

Nosrati, Kazem

2013-04-01

Soil degradation associated with soil erosion and land use is a critical problem in Iran and there is little or insufficient scientific information in assessing soil quality indicator. In this study, factor analysis (FA) and discriminant analysis (DA) were used to identify the most sensitive indicators of soil quality for evaluating land use and soil erosion within the Hiv catchment in Iran and subsequently compare soil quality assessment using expert opinion based on soil surface factors (SSF) form of Bureau of Land Management (BLM) method. Therefore, 19 soil physical, chemical, and biochemical properties were measured from 56 different sampling sites covering three land use/soil erosion categories (rangeland/surface erosion, orchard/surface erosion, and rangeland/stream bank erosion). FA identified four factors that explained for 82 % of the variation in soil properties. Three factors showed significant differences among the three land use/soil erosion categories. The results indicated that based upon backward-mode DA, dehydrogenase, silt, and manganese allowed more than 80 % of the samples to be correctly assigned to their land use and erosional status. Canonical scores of discriminant functions were significantly correlated to the six soil surface indices derived of BLM method. Stepwise linear regression revealed that soil surface indices: soil movement, surface litter, pedestalling, and sum of SSF were also positively related to the dehydrogenase and silt. This suggests that dehydrogenase and silt are most sensitive to land use and soil erosion.

Determination of Sex from Footprint Dimensions in a Ghanaian Population.

PubMed

Abledu, Jubilant Kwame; Abledu, Godfred Kwame; Offei, Eric Bekoe; Antwi, Emmanuel Mensah

2015-01-01

The present study sought to verify the utility and reliability of footprint dimensions in sex determination in a Ghanaian population. Bilateral footprints were obtained from 126 Ghanaian students (66 males and 60 females) aged 18-30 years at Koforidua Polytechnic using an ink pad and white papers. Seven dimensions-length of each toe (designated T1-T5) from the most anterior point of the toe to the mid-rear heel point, breadth at ball (BAB) and breadth at heel (BAH)--and the heel-ball (HB) index were obtained from each footprint. Some footprint dimensions (i.e. T2, T3, T4 and T5) showed statistically significant bilateral asymmetry in males only. All the footprint dimensions, except HB index, were significantly greater in males than females (p<0.001). Applied singly in discriminant function analysis, the footprint dimensions allowed 69.8%-80.3% of cases to be correctly classified into their sex groups; the accuracy of sex classification was higher using left footprints than right footprints. With all dimensions subjected to stepwise discriminant function analysis 80.3% and 77% of cases could be correctly classified, combining both T5 and BAH for left footprints and T1, BAB and BAH for left footprints respectively. The present study has demonstrated, for the first time among Ghanaian subjects, the utility and reliability of sex determination standards developed from footprint dimensions. The results thus provide the baseline for elaborated studies in the future.

Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.

PubMed

Fortner, Renée T; Hüsing, Anika; Kühn, Tilman; Konar, Meric; Overvad, Kim; Tjønneland, Anne; Hansen, Louise; Boutron-Ruault, Marie-Christine; Severi, Gianluca; Fournier, Agnès; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vasiliki; Orfanos, Philippos; Masala, Giovanna; Agnoli, Claudia; Mattiello, Amalia; Tumino, Rosario; Sacerdote, Carlotta; Bueno-de-Mesquita, H B As; Peeters, Petra H M; Weiderpass, Elisabete; Gram, Inger T; Gavrilyuk, Oxana; Quirós, J Ramón; Maria Huerta, José; Ardanaz, Eva; Larrañaga, Nerea; Lujan-Barroso, Leila; Sánchez-Cantalejo, Emilio; Butt, Salma Tunå; Borgquist, Signe; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Allen, Naomi E; Rinaldi, Sabina; Dossus, Laure; Gunter, Marc; Merritt, Melissa A; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf

2017-03-15

Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination. © 2016 UICC.

A multidisciplinary selection model for youth soccer: the Ghent Youth Soccer Project

PubMed Central

Vaeyens, R; Malina, R M; Janssens, M; Van Renterghem, B; Bourgois, J; Vrijens, J; Philippaerts, R M

2006-01-01

Objectives To determine the relationships between physical and performance characteristics and level of skill in youth soccer players aged 12–16 years. Methods Anthropometry, maturity status, functional and sport‐specific parameters were assessed in elite, sub‐elite, and non‐elite youth players in four age groups: U13 (n = 117), U14 (n = 136), U15 (n = 138) and U16 (n = 99). Results Multivariate analyses of covariance by age group with maturity status as the covariate showed that elite players scored better than the non‐elite players on strength, flexibility, speed, aerobic endurance, anaerobic capacity and several technical skills (p<0.05). Stepwise discriminant analyses showed that running speed and technical skills were the most important characteristics in U13 and U14 players, while cardiorespiratory endurance was more important in U15 and U16 players. The results suggest that discriminating characteristics change with competitive age levels. Conclusions Characteristics that discriminate youth soccer players vary by age group. Talent identification models should thus be dynamic and provide opportunities for changing parameters in a long‐term developmental context. PMID:16980535

An integrated approach utilising chemometrics and GC/MS for classification of chamomile flowers, essential oils and commercial products.

PubMed

Wang, Mei; Avula, Bharathi; Wang, Yan-Hong; Zhao, Jianping; Avonto, Cristina; Parcher, Jon F; Raman, Vijayasankar; Zweigenbaum, Jerry A; Wylie, Philip L; Khan, Ikhlas A

2014-01-01

As part of an ongoing research program on authentication, safety and biological evaluation of phytochemicals and dietary supplements, an in-depth chemical investigation of different types of chamomile was performed. A collection of chamomile samples including authenticated plants, commercial products and essential oils was analysed by GC/MS. Twenty-seven authenticated plant samples representing three types of chamomile, viz. German chamomile, Roman chamomile and Juhua were analysed. This set of data was employed to construct a sample class prediction (SCP) model based on stepwise reduction of data dimensionality followed by principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The model was cross-validated with samples including authenticated plants and commercial products. The model demonstrated 100.0% accuracy for both recognition and prediction abilities. In addition, 35 commercial products and 11 essential oils purported to contain chamomile were subsequently predicted by the validated PLS-DA model. Furthermore, tentative identification of the marker compounds correlated with different types of chamomile was explored. Copyright © 2013 Elsevier Ltd. All rights reserved.

Psychoanalysis, artistic obsession, and artistic motivation: the study of pathography.

PubMed

Kemler, David S

2014-02-01

A modern assessment of Freud's conceptualization of the creative process focusing on drives, ego psychology, and object relation theory is presented. 40 artists and musicians were interviewed employing 13 open-ended questions to provoke responses historically associated with the theoretical conceptualizations of Freud and post-Freudian theory related to the creative process. Creative process was defined as internal object relations that motivate the external connection between artist and the creative work. Measured responses concerning purpose and understanding; motivation before, during, and after performance; obstacles in performance; and needs through the creative process were assessed. Cluster analysis segregated the participants into high, medium, and low agreement groups based on similarity of responses. A multivariate stepwise regression revealed four questions (enlightenment, drives, obstacles, and ought self discrepancies) accounted for 83.9% of the variance. A post hoc discriminant function analysis identified 82.5% of the population to their correct groups. The findings support Spitz's (2005) suggestion that we regard "drives, ego psychology, and object relation theory not as separate approaches but as parts of a whole with varying stresses or accents" (p. 503).

Forest tree species discrimination in western Himalaya using EO-1 Hyperion

NASA Astrophysics Data System (ADS)

George, Rajee; Padalia, Hitendra; Kushwaha, S. P. S.

2014-05-01

The information acquired in the narrow bands of hyperspectral remote sensing data has potential to capture plant species spectral variability, thereby improving forest tree species mapping. This study assessed the utility of spaceborne EO-1 Hyperion data in discrimination and classification of broadleaved evergreen and conifer forest tree species in western Himalaya. The pre-processing of 242 bands of Hyperion data resulted into 160 noise-free and vertical stripe corrected reflectance bands. Of these, 29 bands were selected through step-wise exclusion of bands (Wilk's Lambda). Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) algorithms were applied to the selected bands to assess their effectiveness in classification. SVM was also applied to broadband data (Landsat TM) to compare the variation in classification accuracy. All commonly occurring six gregarious tree species, viz., white oak, brown oak, chir pine, blue pine, cedar and fir in western Himalaya could be effectively discriminated. SVM produced a better species classification (overall accuracy 82.27%, kappa statistic 0.79) than SAM (overall accuracy 74.68%, kappa statistic 0.70). It was noticed that classification accuracy achieved with Hyperion bands was significantly higher than Landsat TM bands (overall accuracy 69.62%, kappa statistic 0.65). Study demonstrated the potential utility of narrow spectral bands of Hyperion data in discriminating tree species in a hilly terrain.

Student Retention in Athletic Training Education Programs

PubMed Central

Dodge, Thomas M; Mitchell, Murray F; Mensch, James M

2009-01-01

Context: The success of any academic program, including athletic training, depends upon attracting and keeping quality students. The nature of persistent students versus students who prematurely leave the athletic training major is not known. Understanding the profiles of athletic training students who persist or leave is important. Objective: To (1) explore the relationships among the following variables: anticipatory factors, academic integration, clinical integration, social integration, and motivation; (2) determine which of the aforementioned variables discriminate between senior athletic training students and major changers; and (3) identify which variable is the strongest predictor of persistence in athletic training education programs. Design: Descriptive study using a qualitative and quantitative mixed-methods approach. Setting: Thirteen athletic training education programs located in District 3 of the National Athletic Trainers' Association. Patients or Other Participants: Ninety-four senior-level athletic training students and 31 college students who changed majors from athletic training to another degree option. Data Collection: Data were collected with the Athletic Training Education Program Student Retention Questionnaire (ATEPSRQ). Analysis: Data from the ATEPSRQ were analyzed via Pearson correlations, multivariate analysis of variance, univariate analysis of variance, and a stepwise discriminant analysis. Open-ended questions were transcribed and analyzed using open, axial, and selective coding procedures. Member checks and peer debriefing techniques ensured trustworthiness of the study. Results: Pearson correlations identified moderate relationships among motivation and clinical integration (r  =  0.515, P < .01) and motivation and academic integration (r  =  0.509, P < .01). Univariate analyses of variance showed that academic integration (F1,122  =  8.483, P < .004), clinical integration (F1,119  =  30.214, P < .001), and motivation (F1,121  =  68.887, P < .001) discriminated between seniors and major changers. Discriminant analysis indicated that motivation was the strongest predictor of persistence in athletic training education, accounting for 37.2% of the variance between groups. The theoretic model accurately classified 95.7% of the seniors and 53.8% of the major changers. A common theme emerging from the qualitative data was the presence of a strong peer-support group that surrounded many of the senior-level students. Conclusions: Understanding student retention in athletic training is important for our profession. Results from this study suggest 3 key factors associated with student persistence in athletic training education programs: (1) student motivation, (2) clinical and academic integration, and (3) the presence of a peer-support system. Educators and program directors must create comprehensive recruitment and retention strategies that address factors influencing students' decisions to stay in the athletic training profession. PMID:19295966

Using Balance Tests to Discriminate Between Participants With a Recent Index Lateral Ankle Sprain and Healthy Control Participants: A Cross-Sectional Study

PubMed Central

Pourkazemi, Fereshteh; Hiller, Claire; Raymond, Jacqueline; Black, Deborah; Nightingale, Elizabeth; Refshauge, Kathryn

2016-01-01

Context:  The first step to identifying factors that increase the risk of recurrent ankle sprains is to identify impairments after a first sprain and compare performance with individuals who have never sustained a sprain. Few researchers have restricted recruitment to a homogeneous group of patients with first sprains, thereby introducing the potential for confounding. Objective:  To identify impairments that differ in participants with a recent index lateral ankle sprain versus participants with no history of ankle sprain. Design:  Cross-sectional study. Patients or Other Participants:  We recruited a sample of convenience from May 2010 to April 2013 that included 70 volunteers (age = 27.4 ± 8.3 years, height = 168.7 ± 9.5 cm, mass = 65.0 ± 12.5 kg) serving as controls and 30 volunteers (age = 31.1 ± 13.3 years, height = 168.3 ± 9.1 cm, mass = 67.3 ± 13.7 kg) with index ankle sprains. Main Outcome Measure(s):  We collected demographic and physical performance variables, including ankle-joint range of motion, balance (time to balance after perturbation, Star Excursion Balance Test, foot lifts during single-legged stance, demi-pointe balance test), proprioception, motor planning, inversion-eversion peak power, and timed stair tests. Discriminant analysis was conducted to determine the relationship between explanatory variables and sprain status. Sequential discriminant analysis was performed to identify the most relevant variables that explained the greatest variance. Results:  The average time since the sprain was 3.5 ± 1.5 months. The model, including all variables, correctly predicted a sprain status of 77% (n = 23) of the sprain group and 80% (n = 56) of the control group and explained 40% of the variance between groups ( = 42.16, P = .03). Backward stepwise discriminant analysis revealed associations between sprain status and only 2 tests: Star Excursion Balance Test in the anterior direction and foot lifts during single-legged stance ( = 15.2, P = .001). These 2 tests explained 15% of the between-groups variance and correctly predicted group membership of 63% (n = 19) of the sprain group and 69% (n = 48) of the control group. Conclusions:  Balance impairments were associated with a recent first ankle sprain, but proprioception, motor control, power, and function were not. PMID:26967374

Using Balance Tests to Discriminate Between Participants With a Recent Index Lateral Ankle Sprain and Healthy Control Participants: A Cross-Sectional Study.

PubMed

Pourkazemi, Fereshteh; Hiller, Claire; Raymond, Jacqueline; Black, Deborah; Nightingale, Elizabeth; Refshauge, Kathryn

2016-03-01

The first step to identifying factors that increase the risk of recurrent ankle sprains is to identify impairments after a first sprain and compare performance with individuals who have never sustained a sprain. Few researchers have restricted recruitment to a homogeneous group of patients with first sprains, thereby introducing the potential for confounding. To identify impairments that differ in participants with a recent index lateral ankle sprain versus participants with no history of ankle sprain. Cross-sectional study. We recruited a sample of convenience from May 2010 to April 2013 that included 70 volunteers (age = 27.4 ± 8.3 years, height = 168.7 ± 9.5 cm, mass = 65.0 ± 12.5 kg) serving as controls and 30 volunteers (age = 31.1 ± 13.3 years, height = 168.3 ± 9.1 cm, mass = 67.3 ± 13.7 kg) with index ankle sprains. We collected demographic and physical performance variables, including ankle-joint range of motion, balance (time to balance after perturbation, Star Excursion Balance Test, foot lifts during single-legged stance, demi-pointe balance test), proprioception, motor planning, inversion-eversion peak power, and timed stair tests. Discriminant analysis was conducted to determine the relationship between explanatory variables and sprain status. Sequential discriminant analysis was performed to identify the most relevant variables that explained the greatest variance. The average time since the sprain was 3.5 ± 1.5 months. The model, including all variables, correctly predicted a sprain status of 77% (n = 23) of the sprain group and 80% (n = 56) of the control group and explained 40% of the variance between groups ([Formula: see text] = 42.16, P = .03). Backward stepwise discriminant analysis revealed associations between sprain status and only 2 tests: Star Excursion Balance Test in the anterior direction and foot lifts during single-legged stance ([Formula: see text] = 15.2, P = .001). These 2 tests explained 15% of the between-groups variance and correctly predicted group membership of 63% (n = 19) of the sprain group and 69% (n = 48) of the control group. Balance impairments were associated with a recent first ankle sprain, but proprioception, motor control, power, and function were not.

Perfusion MR imaging detection of carcinoma arising from preexisting salivary gland pleomorphic adenoma by computer-assisted analysis of time-signal intensity maps

PubMed Central

Katayama, Ikuo; Eida, Sato; Fujita, Shuichi; Hotokezaka, Yuka; Sumi, Misa

2017-01-01

Tumor perfusion can be evaluated by analyzing the time-signal intensity curve (TIC) after dynamic contrast-enhanced (DCE) MR imaging. Accordingly, TIC profiles are characteristic of some benign and malignant salivary gland tumors. A carcinoma ex pleomorphic adenoma (CXPA) arises from a long-standing pleomorphic adenoma (PA) and has a distinctive prognostic risk depending on the tumor growth potential such as invasion beyond the preexisting capsule. Differentiating CXPA from PA can be very challenging. In this study, we have attempted to discriminate CXPA from PA based on a two-dimensional TIC mapping algorithm. TIC mapping analysis was performed on 8 patients with CXPA and 20 patients with PA after dynamic contrast-enhanced (DCE) MR imaging using a 1.5-T MR system. The TIC profiles obtained were automatically categorized into 5 types based on the enhancement ratio, maximum time, and washout ratio (Type 1 TIC with flat profile, Type 2 TIC with slow uptake, Type 3 TIC with rapid uptake and a low washout ratio, Type 4 TIC with rapid uptake and a high washout ratio, and Type 5 TIC not otherwise specific). The percentage tumor areas with each of the 5 TIC types were compared between CXPAs and PAs. Stepwise differentiation and cluster analysis using multiple TIC cut-off thresholds distinguished CXPAs from PAs with 75% sensitivity, 95% specificity, 86% accuracy, and 86% positive and 90% negative predictive values, when tumors with ≤1.1% Type 1 and ≥15% Type 4, or those with ≤1.1% Type 1, ≥78.1% Type 2, ≥16.1% Type 3, and <15% Type 4, or those with >1.1% Type 1, ≥78.1% Type 2, and ≥16.1% Type 3 areas were diagnosed as CXPAs. The overall TIC profiles predicted some aggressive CXPA growth patterns. These results suggest that stepwise differentiation based on TIC mapping is helpful in differentiating CXPAs from PAs. PMID:28531213

Quantitative analysis of professionally trained versus untrained voices.

PubMed

Siupsinskiene, Nora

2003-01-01

The aim of this study was to compare healthy trained and untrained voices as well as healthy and dysphonic trained voices in adults using combined voice range profile and aerodynamic tests, to define the normal range limiting values of quantitative voice parameters and to select the most informative quantitative voice parameters for separation between healthy and dysphonic trained voices. Three groups of persons were evaluated. One hundred eighty six healthy volunteers were divided into two groups according to voice training: non-professional speakers group consisted of 106 untrained voices persons (36 males and 70 females) and professional speakers group--of 80 trained voices persons (21 males and 59 females). Clinical group consisted of 103 dysphonic professional speakers (23 males and 80 females) with various voice disorders. Eighteen quantitative voice parameters from combined voice range profile (VRP) test were analyzed: 8 of voice range profile, 8 of speaking voice, overall vocal dysfunction degree and coefficient of sound, and aerodynamic maximum phonation time. Analysis showed that healthy professional speakers demonstrated expanded vocal abilities in comparison to healthy non-professional speakers. Quantitative voice range profile parameters- pitch range, high frequency limit, area of high frequencies and coefficient of sound differed significantly between healthy professional and non-professional voices, and were more informative than speaking voice or aerodynamic parameters in showing the voice training. Logistic stepwise regression revealed that VRP area in high frequencies was sufficient to discriminate between healthy and dysphonic professional speakers for male subjects (overall discrimination accuracy--81.8%) and combination of three quantitative parameters (VRP high frequency limit, maximum voice intensity and slope of speaking curve) for female subjects (overall model discrimination accuracy--75.4%). We concluded that quantitative voice assessment with selected parameters might be useful for evaluation of voice education for healthy professional speakers as well as for detection of vocal dysfunction and evaluation of rehabilitation effect in dysphonic professionals.

A Machine-Learning Algorithm Toward Color Analysis for Chronic Liver Disease Classification, Employing Ultrasound Shear Wave Elastography.

PubMed

Gatos, Ilias; Tsantis, Stavros; Spiliopoulos, Stavros; Karnabatidis, Dimitris; Theotokas, Ioannis; Zoumpoulis, Pavlos; Loupas, Thanasis; Hazle, John D; Kagadis, George C

2017-09-01

The purpose of the present study was to employ a computer-aided diagnosis system that classifies chronic liver disease (CLD) using ultrasound shear wave elastography (SWE) imaging, with a stiffness value-clustering and machine-learning algorithm. A clinical data set of 126 patients (56 healthy controls, 70 with CLD) was analyzed. First, an RGB-to-stiffness inverse mapping technique was employed. A five-cluster segmentation was then performed associating corresponding different-color regions with certain stiffness value ranges acquired from the SWE manufacturer-provided color bar. Subsequently, 35 features (7 for each cluster), indicative of physical characteristics existing within the SWE image, were extracted. A stepwise regression analysis toward feature reduction was used to derive a reduced feature subset that was fed into the support vector machine classification algorithm to classify CLD from healthy cases. The highest accuracy in classification of healthy to CLD subject discrimination from the support vector machine model was 87.3% with sensitivity and specificity values of 93.5% and 81.2%, respectively. Receiver operating characteristic curve analysis gave an area under the curve value of 0.87 (confidence interval: 0.77-0.92). A machine-learning algorithm that quantifies color information in terms of stiffness values from SWE images and discriminates CLD from healthy cases is introduced. New objective parameters and criteria for CLD diagnosis employing SWE images provided by the present study can be considered an important step toward color-based interpretation, and could assist radiologists' diagnostic performance on a daily basis after being installed in a PC and employed retrospectively, immediately after the examination. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Relationship between COMLEX-USA scores and performance on the American Osteopathic Board of Emergency Medicine Part I certifying examination.

PubMed

Li, Feiming; Gimpel, John R; Arenson, Ethan; Song, Hao; Bates, Bruce P; Ludwin, Fredric

2014-04-01

Few studies have investigated how well scores from the Comprehensive Osteopathic Medical Licensing Examination-USA (COMLEX-USA) series predict resident outcomes, such as performance on board certification examinations. To determine how well COMLEX-USA predicts performance on the American Osteopathic Board of Emergency Medicine (AOBEM) Part I certification examination. The target study population was first-time examinees who took AOBEM Part I in 2011 and 2012 with matched performances on COMLEX-USA Level 1, Level 2-Cognitive Evaluation (CE), and Level 3. Pearson correlations were computed between AOBEM Part I first-attempt scores and COMLEX-USA performances to measure the association between these examinations. Stepwise linear regression analysis was conducted to predict AOBEM Part I scores by the 3 COMLEX-USA scores. An independent t test was conducted to compare mean COMLEX-USA performances between candidates who passed and who failed AOBEM Part I, and a stepwise logistic regression analysis was used to predict the log-odds of passing AOBEM Part I on the basis of COMLEX-USA scores. Scores from AOBEM Part I had the highest correlation with COMLEX-USA Level 3 scores (.57) and slightly lower correlation with COMLEX-USA Level 2-CE scores (.53). The lowest correlation was between AOBEM Part I and COMLEX-USA Level 1 scores (.47). According to the stepwise regression model, COMLEX-USA Level 1 and Level 2-CE scores, which residency programs often use as selection criteria, together explained 30% of variance in AOBEM Part I scores. Adding Level 3 scores explained 37% of variance. The independent t test indicated that the 397 examinees passing AOBEM Part I performed significantly better than the 54 examinees failing AOBEM Part I in all 3 COMLEX-USA levels (P<.001 for all 3 levels). The logistic regression model showed that COMLEX-USA Level 1 and Level 3 scores predicted the log-odds of passing AOBEM Part I (P=.03 and P<.001, respectively). The present study empirically supported the predictive and discriminant validities of the COMLEX-USA series in relation to the AOBEM Part I certification examination. Although residency programs may use COMLEX-USA Level 1 and Level 2-CE scores as partial criteria in selecting residents, Level 3 scores, though typically not available at the time of application, are actually the most statistically related to performances on AOBEM Part I.

Re-evaluation of the interrelationships among the behavioral tests in rats exposed to chronic unpredictable mild stress

PubMed Central

Hu, Congli; Luo, Ying; Wang, Hong; Kuang, Shengnan; Liang, Guojuan; Yang, Yang; Mai, Shaoshan; Yang, Junqing

2017-01-01

The chronic unpredictable mild stress model of depression has been widely used as an experimental tool to investigate human psychopathology. Our objective was to provide an update on the validity and reliability of the chronic unpredictable mild stress model, by analyzing the interrelationships among the indexes using stepwise discriminant analysis and Pearson correlation coefficient to examine the possible combinations. We evaluated the depressive rats in both the presence and the absence of chronic unpredictable mild stress, using weight change, percentage of sucrose preference, coat state, splash test, open-field test, elevated plus-maze test, forced swimming test, and Morris water maze test. The results showed that 6-week-long chronic unpredictable mild stress produces significant depression and anxiety-like behavior. The combination of body weight change, percentage of sucrose preference, coat state score, open-field score, grooming latency of splash test, immobility time in force swimming test, and platform crossing in the Morris water maze test can effectively discriminate between normal and chronic unpredictable mild stress rats. Strong interrelationships were noted among these indexes in both open-field test and elevated plus-maze test. In conclusion, there might be certain criteria for the combination of behavioral endpoints, which is advantageous to more effectively and reliably assess the chronic unpredictable mild stress induced depression model. PMID:28931086

Behavioural Inhibition System (BIS) sensitivity differentiates EEG theta responses during goal conflict in a continuous monitoring task.

PubMed

Moore, Roger A; Mills, Matthew; Marshman, Paul; Corr, Philip J

2012-08-01

Previous research has revealed that EEG theta oscillations are affected during goal conflict processing. This is consistent with the behavioural inhibition system (BIS) theory of anxiety (Gray & McNaughton, 2000). However, studies have not attempted to relate these BIS-related theta effects to BIS personality measures. Confirmation of such an association would provide further support for BIS theory, especially as it relates to trait differences. EEG was measured (32 electrodes) from extreme groups (low/high trait BIS) engaged in a target detection task. Goal conflicts were introduced throughout the task. Results show that the two groups did not differ in behavioural performance. The major EEG result was that a stepwise discriminant analysis indicated discrimination by 6 variables derived from coherence and power, with 5 of the 6 in the theta range as predicted by BIS theory and one in the beta range. Also, across the whole sample, EEG theta coherence increased at a variety of regions during primary goal conflict and showed a general increase during response execution; EEG theta power, in contrast, was primarily reactive to response execution. This is the first study to reveal a three-way relationship between the induction of goal conflict, the induction of theta power and coherence, and differentiation by psychometrically-defined low/high BIS status. Copyright © 2012 Elsevier B.V. All rights reserved.

Assessment of gross motor skills and phenotype profile in children 9-11 years of age in survivors of acute lymphoblastic leukemia.

PubMed

Leone, Mario; Viret, Pierre; Bui, Hung Tien; Laverdière, Caroline; Kalinova, Émilia; Comtois, Alain-Steve

2014-01-01

The purpose of this study was to evaluate the usefulness of a new gross motor skill test battery in acute lymphoblastic leukemia (ALL) children who have been off therapy for at least 1 year and to assess its discriminatory power (discriminant analysis) from healthy children. Twenty children (10 males and 10 females) 9-11 years of age (median age = 10.6 years) were assessed by the UQAC-UQAM test battery and then compared to recent provincial norms. This pilot study was also an opportunity to validate this test battery as a reliable tool for clinical or research purposes in the area of chronic or disabling diseases in children. Eleven motor skill variables grouped into five factors have been measured (speed, agility, balance, coordination, and reaction time). Scores from 10 of the 11 motor skill tests showed significant differences when compared to the control group (P ≤ 0.05). Nearly 50% of patients obtained an average score below the 15th percentile. Furthermore, stepwise discriminant analysis allowed classifying successfully 88.4% of children in the correct group (ALL or Control). The normal development of GMS among children affected by ALL appears to have been compromised. The UQAC-UQAM test battery seems to be sensitive enough to quantify with precision the extent of the motor impairment in these children. The UQAC-UQAM test battery appears to be a useful tool to evaluate the extent to which ALL survivors are affected. Early motor intervention should be considered for those patients even during the treatment periods. © 2013 Wiley Periodicals, Inc.

Origin of fine dust in urban environmental zones--Evidence from element patterns received by dichotomous collection and INAA.

PubMed

Weckwerth, G

2010-10-01

In order to fulfil the EU-limitations of fine dust and traffic-produced gases Cologne installed 2008 one of the first German environmental zones, from which stepwise vehicles with too high emissions will be locked out. Verification of effectiveness and the research on further strategies to reduce fine dust are studied as promising applications of a method on discrimination of aerosol components from different origins (Weckwerth, 2001). New measurements in Cologne gave several implications on supports, especially in connection with traffic abrasion from brakes, tires and rails. Copyright 2010. Published by Elsevier Ltd.

Prediction of health levels by remote sensing

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

Measures of the environment derived from remote sensing were compared to census population/housing measures in their ability to discriminate among health status areas in two urban communities. Three hypotheses were developed to explore the relationships between environmental and health data. Univariate and multiple step-wise linear regression analyses were performed on data from two sample areas in Houston and Galveston, Texas. Environmental data gathered by remote sensing were found to equal or surpass census data in predicting rates of health outcomes. Remote sensing offers the advantages of data collection for any chosen area or time interval, flexibilities not allowed by the decennial census.

Predictive Method for Correct Identification of Archaeological Charred Grape Seeds: Support for Advances in Knowledge of Grape Domestication Process

PubMed Central

Ucchesu, Mariano; Orrù, Martino; Grillo, Oscar; Venora, Gianfranco; Paglietti, Giacomo; Ardu, Andrea; Bacchetta, Gianluigi

2016-01-01

The identification of archaeological charred grape seeds is a difficult task due to the alteration of the morphological seeds shape. In archaeobotanical studies, for the correct discrimination between Vitis vinifera subsp. sylvestris and Vitis vinifera subsp. vinifera grape seeds it is very important to understand the history and origin of the domesticated grapevine. In this work, different carbonisation experiments were carried out using a hearth to reproduce the same burning conditions that occurred in archaeological contexts. In addition, several carbonisation trials on modern wild and cultivated grape seeds were performed using a muffle furnace. For comparison with archaeological materials, modern grape seed samples were obtained using seven different temperatures of carbonisation ranging between 180 and 340ºC for 120 min. Analysing the grape seed size and shape by computer vision techniques, and applying the stepwise linear discriminant analysis (LDA) method, discrimination of the wild from the cultivated charred grape seeds was possible. An overall correct classification of 93.3% was achieved. Applying the same statistical procedure to compare modern charred with archaeological grape seeds, found in Sardinia and dating back to the Early Bronze Age (2017–1751 2σ cal. BC), allowed 75.0% of the cases to be identified as wild grape. The proposed method proved to be a useful and effective procedure in identifying, with high accuracy, the charred grape seeds found in archaeological sites. Moreover, it may be considered valid support for advances in the knowledge and comprehension of viticulture adoption and the grape domestication process. The same methodology may also be successful when applied to other plant remains, and provide important information about the history of domesticated plants. PMID:26901361

Predictive Method for Correct Identification of Archaeological Charred Grape Seeds: Support for Advances in Knowledge of Grape Domestication Process.

PubMed

Ucchesu, Mariano; Orrù, Martino; Grillo, Oscar; Venora, Gianfranco; Paglietti, Giacomo; Ardu, Andrea; Bacchetta, Gianluigi

2016-01-01

The identification of archaeological charred grape seeds is a difficult task due to the alteration of the morphological seeds shape. In archaeobotanical studies, for the correct discrimination between Vitis vinifera subsp. sylvestris and Vitis vinifera subsp. vinifera grape seeds it is very important to understand the history and origin of the domesticated grapevine. In this work, different carbonisation experiments were carried out using a hearth to reproduce the same burning conditions that occurred in archaeological contexts. In addition, several carbonisation trials on modern wild and cultivated grape seeds were performed using a muffle furnace. For comparison with archaeological materials, modern grape seed samples were obtained using seven different temperatures of carbonisation ranging between 180 and 340ºC for 120 min. Analysing the grape seed size and shape by computer vision techniques, and applying the stepwise linear discriminant analysis (LDA) method, discrimination of the wild from the cultivated charred grape seeds was possible. An overall correct classification of 93.3% was achieved. Applying the same statistical procedure to compare modern charred with archaeological grape seeds, found in Sardinia and dating back to the Early Bronze Age (2017-1751 2σ cal. BC), allowed 75.0% of the cases to be identified as wild grape. The proposed method proved to be a useful and effective procedure in identifying, with high accuracy, the charred grape seeds found in archaeological sites. Moreover, it may be considered valid support for advances in the knowledge and comprehension of viticulture adoption and the grape domestication process. The same methodology may also be successful when applied to other plant remains, and provide important information about the history of domesticated plants.

[Response characteristics of the field-measured spectrum for the four general types of halophyte and species recognition in the northern slope area of Tianshan Mountain in Xinjiang].

PubMed

Zhang, Fang; Xiong, Hei-gang; Nurbay, Abdusalih; Luan, Fu-ming

2011-12-01

Based on the field-measured Vis-NIR reflectance of four common types of halophyte (Achnatherum splendens(Trin.) Nevski, Sophora alopecuroides L., Camphorosma monspeliaca L. subsp. lessingii(L.)Aellen, Alhagi sparsifolia shap) within given spots in the Northern Slope Area of Tianshan Mountain in Xinjiang, the spectral response characteristics and species recognition of these types of halophyte were analyzed. The results showed that (Alhagi sparsifolia shap) had higher chlorophyll and carotenoid by CARI and SIPI index. (Sophora alopecuroides L. was at a vigorously growing state and had a higher NDVI compared with the other three types of halophyte because of its greater canopy density. But its CARI and SIPI values were lower due to the influence of its flowers. (Sophora alopecuroides L.) and (Camphorosma monspeliaca L. subsp. lessingii(L.)) had stable REPs and BEPs, but REPs and BEPs of (Achnatherum splendens(Trin.)Nevski, Aellen, Alhagi sparsifolia shap) whose spectra red shift and spectra blue shift occurred concurrently obviously changed. There was little difference in spectral curves among the four types of halophyte, so the spectrum mixing phenomenon was severe. (Camphorosma monspeliaca L. subsp. lessingii (L.)Aellen) and (Alhagi sparsifolia shap) could not be separated exactly in a usual R/NIR feature space in remote sensing. Using the stepwise discriminant analysis, five indices were selected to establish the discriminant model, and the model accuracy was discussed using the validated sample group. The total accuracy of the discriminant model was above 92% and (Achnatherum splendens(Trin.)Nevski) and (Camphorosma monspeliaca L. subsp. lessingii(L.)Aellen) could be respectively recognized 100% correctly.

A Latent-Variable Causal Model of Faculty Reputational Ratings.

ERIC Educational Resources Information Center

King, Suzanne; Wolfle, Lee M.

A reanalysis was conducted of Saunier's research (1985) on sources of variation in the National Research Council (NRC) reputational ratings of university faculty. Saunier conducted a stepwise regression analysis using 12 predictor variables. Due to problems with multicollinearity and because of the atheoretical nature of stepwise regression,…

Testing Different Model Building Procedures Using Multiple Regression.

ERIC Educational Resources Information Center

Thayer, Jerome D.

The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…

Lithium might be associated with better decision-making performance in euthymic bipolar patients.

PubMed

Adida, Marc; Jollant, Fabrice; Clark, Luke; Guillaume, Sebastien; Goodwin, Guy M; Azorin, Jean-Michel; Courtet, Philippe

2015-06-01

Bipolar disorder is associated with impaired decision-making. Little is known about how treatment, especially lithium, influences decision-making abilities in bipolar patients when euthymic. We aimed at testing for an association between lithium medication and decision-making performance in remitted bipolar patients. Decision-making was measured using the Iowa Gambling Task in 3 groups of subjects: 34 and 56 euthymic outpatients with bipolar disorder, treated with lithium (monotherapy and lithium combined with anticonvulsant or antipsychotic) and without lithium (anticonvulsant, antipsychotic and combination treatment), respectively, and 152 matched healthy controls. Performance was compared between the 3 groups. In the 90 euthymic patients, the relationship between different sociodemographic and clinical variables and decision-making was assessed by stepwise multivariate regression analysis. Euthymic patients with lithium (p=0.007) and healthy controls (p=0.001) selected significantly more cards from the safe decks than euthymic patients without lithium, with no significant difference between euthymic patients with lithium and healthy controls (p=0.9). In the 90 euthymic patients, the stepwise linear multivariate regression revealed that decision-making was significantly predicted (p<0.001) by lithium dose, level of education and no family history of bipolar disorder (all p≤0.01). Because medication was not randomized, it was not possible to discriminate the effect of different medications. Lithium medication might be associated with better decision-making in remitted bipolar patients. A randomized trial is required to test for the hypothesis that lithium, but not other mood stabilizers, may specifically improve decision-making abilities in bipolar disorder. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

Verifying the botanical authenticity of commercial tannins through sugars and simple phenols profiles.

PubMed

Malacarne, Mario; Nardin, Tiziana; Bertoldi, Daniela; Nicolini, Giorgio; Larcher, Roberto

2016-09-01

Commercial tannins from several botanical sources and with different chemical and technological characteristics are used in the food and winemaking industries. Different ways to check their botanical authenticity have been studied in the last few years, through investigation of different analytical parameters. This work proposes a new, effective approach based on the quantification of 6 carbohydrates, 7 polyalcohols, and 55 phenols. 87 tannins from 12 different botanical sources were analysed following a very simple sample preparation procedure. Using Forward Stepwise Discriminant Analysis, 3 statistical models were created based on sugars content, phenols concentration and combination of the two classes of compounds for the 8 most abundant categories (i.e. oak, grape seed, grape skin, gall, chestnut, quebracho, tea and acacia). The last approach provided good results in attributing tannins to the correct botanical origin. Validation, repeated 3 times on subsets of 10% of samples, confirmed the reliability of this model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Treatment of skeletal Class III malocclusions: orthognathic surgery or orthodontic camouflage? How to decide.

PubMed

Benyahia, Hicham; Azaroual, Mohamed Faouzi; Garcia, Claude; Hamou, Edith; Abouqal, Redouane; Zaoui, Fatima

2011-06-01

The choice of treatment in adult skeletal Class III occlusions often poses a particularly tricky problem for the orthodontist. Faced with the option of either orthodontic camouflage or orthognathic surgery, the clinician's clinical experience is of paramount importance, especially in borderline cases. The aim of our study was to uncover a guide model enabling the practitioner to distinguish between skeletal Class III cases which can be suitably treated with orthodontics and those requiring orthognathic surgery. The lateral headfilms of 47 adult patients exhibiting skeletal Class III occlusions were analyzed. The orthodontic group comprised 22 patients and the surgical group 25. Twenty-seven linear, proportional and angular measurements were scrutinized. Stepwise discriminant analysis was used to identify the dentoskeletal and esthetic variables which most distinguished the two groups. The Holdaway angle was chosen to differentiate between patients prior to treatment. This model enables us to classify 87.2% of patients correctly. Copyright © 2011 CEO. Published by Elsevier Masson SAS. All rights reserved.

Student retention in athletic training education programs.

PubMed

Dodge, Thomas M; Mitchell, Murray F; Mensch, James M

2009-01-01

The success of any academic program, including athletic training, depends upon attracting and keeping quality students. The nature of persistent students versus students who prematurely leave the athletic training major is not known. Understanding the profiles of athletic training students who persist or leave is important. To (1) explore the relationships among the following variables: anticipatory factors, academic integration, clinical integration, social integration, and motivation; (2) determine which of the aforementioned variables discriminate between senior athletic training students and major changers; and (3) identify which variable is the strongest predictor of persistence in athletic training education programs. Descriptive study using a qualitative and quantitative mixed-methods approach. Thirteen athletic training education programs located in District 3 of the National Athletic Trainers' Association. Ninety-four senior-level athletic training students and 31 college students who changed majors from athletic training to another degree option. Data were collected with the Athletic Training Education Program Student Retention Questionnaire (ATEPSRQ). Data from the ATEPSRQ were analyzed via Pearson correlations, multivariate analysis of variance, univariate analysis of variance, and a stepwise discriminant analysis. Open-ended questions were transcribed and analyzed using open, axial, and selective coding procedures. Member checks and peer debriefing techniques ensured trustworthiness of the study. Pearson correlations identified moderate relationships among motivation and clinical integration (r = 0.515, P < .01) and motivation and academic integration (r = 0.509, P < .01). Univariate analyses of variance showed that academic integration (F(1,122) = 8.483, P < .004), clinical integration (F(1,119) = 30.214, P < .001), and motivation (F(1,121) = 68.887, P < .001) discriminated between seniors and major changers. Discriminant analysis indicated that motivation was the strongest predictor of persistence in athletic training education, accounting for 37.2% of the variance between groups. The theoretic model accurately classified 95.7% of the seniors and 53.8% of the major changers. A common theme emerging from the qualitative data was the presence of a strong peer-support group that surrounded many of the senior-level students. Understanding student retention in athletic training is important for our profession. Results from this study suggest 3 key factors associated with student persistence in athletic training education programs: (1) student motivation, (2) clinical and academic integration, and (3) the presence of a peer-support system. Educators and program directors must create comprehensive recruitment and retention strategies that address factors influencing students' decisions to stay in the athletic training profession.

Mapping Robinia pseudoacacia forest health in the Yellow River delta by using high-resolution IKONOS imagery and object-based image analysis

NASA Astrophysics Data System (ADS)

Wang, Hong; Lu, Kaiyu; Pu, Ruiliang

2016-10-01

The Robinia pseudoacacia forest in the Yellow River delta of China has been planted since the 1970s, and a large area of dieback of the forest has occurred since the 1990s. To assess the condition of the R. pseudoacacia forest in three forest areas (i.e., Gudao, Machang, and Abandoned Yellow River) in the delta, we combined an estimation of scale parameters tool and geometry/topology assessment criteria to determine the optimal scale parameters, selected optimal predictive variables determined by stepwise discriminant analysis, and compared object-based image analysis (OBIA) and pixel-based approaches using IKONOS data. The experimental results showed that the optimal segmentation scale is 5 for both the Gudao and Machang forest areas, and 12 for the Abandoned Yellow River forest area. The results produced by the OBIA method were much better than those created by the pixel-based method. The overall accuracy of the OBIA method was 93.7% (versus 85.4% by the pixel-based) for Gudao, 89.0% (versus 72.7%) for Abandoned Yellow River, and 91.7% (versus 84.4%) for Machang. Our analysis results demonstrated that the OBIA method was an effective tool for rapidly mapping and assessing the health levels of forest.

Automated classification of maxillofacial cysts in cone beam CT images using contourlet transformation and Spherical Harmonics.

PubMed

Abdolali, Fatemeh; Zoroofi, Reza Aghaeizadeh; Otake, Yoshito; Sato, Yoshinobu

2017-02-01

Accurate detection of maxillofacial cysts is an essential step for diagnosis, monitoring and planning therapeutic intervention. Cysts can be of various sizes and shapes and existing detection methods lead to poor results. Customizing automatic detection systems to gain sufficient accuracy in clinical practice is highly challenging. For this purpose, integrating the engineering knowledge in efficient feature extraction is essential. This paper presents a novel framework for maxillofacial cysts detection. A hybrid methodology based on surface and texture information is introduced. The proposed approach consists of three main steps as follows: At first, each cystic lesion is segmented with high accuracy. Then, in the second and third steps, feature extraction and classification are performed. Contourlet and SPHARM coefficients are utilized as texture and shape features which are fed into the classifier. Two different classifiers are used in this study, i.e. support vector machine and sparse discriminant analysis. Generally SPHARM coefficients are estimated by the iterative residual fitting (IRF) algorithm which is based on stepwise regression method. In order to improve the accuracy of IRF estimation, a method based on extra orthogonalization is employed to reduce linear dependency. We have utilized a ground-truth dataset consisting of cone beam CT images of 96 patients, belonging to three maxillofacial cyst categories: radicular cyst, dentigerous cyst and keratocystic odontogenic tumor. Using orthogonalized SPHARM, residual sum of squares is decreased which leads to a more accurate estimation. Analysis of the results based on statistical measures such as specificity, sensitivity, positive predictive value and negative predictive value is reported. The classification rate of 96.48% is achieved using sparse discriminant analysis and orthogonalized SPHARM features. Classification accuracy at least improved by 8.94% with respect to conventional features. This study demonstrated that our proposed methodology can improve the computer assisted diagnosis (CAD) performance by incorporating more discriminative features. Using orthogonalized SPHARM is promising in computerized cyst detection and may have a significant impact in future CAD systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Sex estimation from the patella in an African American population.

PubMed

Peckmann, Tanya R; Fisher, Brooke

2018-02-01

The skull and pelvis have been used for the estimation of sex for unknown human remains. However, in forensic cases where skeletal remains often exhibit postmortem damage and taphonomic changes the patella may be used for the estimation of sex as it is a preservationally favoured bone. The goal of the present research was to derive discriminant function equations from the patella for estimation of sex from an historic African American population. Six parameters were measured on 200 individuals (100 males and 100 females), ranging in age from 20 to 80 years old, from the Robert J. Terry Anatomical Skeleton Collection. The statistical analyses showed that all variables were sexually dimorphic. Discriminant function score equations were generated for use in sex estimation. The overall accuracy of sex classification ranged from 80.0% to 85.0% for the direct method and 80.0%-84.5% for the stepwise method. Overall, when the Spanish and Black South African discriminant functions were applied to the African American population they showed low accuracy rates for sexing the African American sample. However, when the White South African discriminant functions were applied to the African American sample they displayed high accuracy rates for sexing the African American population. The patella was shown to be accurate for sex estimation in the historic African American population. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Effects of Sublethal Fungicides on Mutation Rates and Genomic Variation in Fungal Plant Pathogen, Sclerotinia sclerotiorum.

PubMed

Amaradasa, B Sajeewa; Everhart, Sydney E

2016-01-01

Pathogen exposure to sublethal doses of fungicides may result in mutations that may represent an important and largely overlooked mechanism of introducing new genetic variation into strictly clonal populations, including acquisition of fungicide resistance. We tested this hypothesis using the clonal plant pathogen, Sclerotinia sclerotiorum. Nine susceptible isolates were exposed independently to five commercial fungicides with different modes of action: boscalid (respiration inhibitor), iprodione (unclear mode of action), thiophanate methyl (inhibition of microtubulin synthesis) and azoxystrobin and pyraclostrobin (quinone outside inhibitors). Mycelium of each isolate was inoculated onto a fungicide gradient and sub-cultured from the 50-100% inhibition zone for 12 generations and experiment repeated. Mutational changes were assessed for all isolates at six neutral microsatellite (SSR) loci and for a subset of isolates using amplified fragment length polymorphisms (AFLPs). SSR analysis showed 12 of 85 fungicide-exposed isolates had a total of 127 stepwise mutations with 42 insertions and 85 deletions. Most stepwise deletions were in iprodione- and azoxystrobin-exposed isolates (n = 40/85 each). Estimated mutation rates were 1.7 to 60-fold higher for mutated loci compared to that expected under neutral conditions. AFLP genotyping of 33 isolates (16 non-exposed control and 17 fungicide exposed) generated 602 polymorphic alleles. Cluster analysis with principal coordinate analysis (PCoA) and discriminant analysis of principal components (DAPC) identified fungicide-exposed isolates as a distinct group from non-exposed control isolates (PhiPT = 0.15, P = 0.001). Dendrograms based on neighbor-joining also supported allelic variation associated with fungicide-exposure. Fungicide sensitivity of isolates measured throughout both experiments did not show consistent trends. For example, eight isolates exposed to boscalid had higher EC50 values at the end of the experiment, and when repeated, only one isolate had higher EC50 while most isolates showed no difference. Results of this support the hypothesis that sublethal fungicide stress increases mutation rates in a largely clonal plant pathogen under in vitro conditions. Collectively, this work will aid our understanding how non-lethal fungicide exposure may affect genomic variation, which may be an important mechanism of novel trait emergence, adaptation, and evolution for clonal organisms.

Effects of Sublethal Fungicides on Mutation Rates and Genomic Variation in Fungal Plant Pathogen, Sclerotinia sclerotiorum

PubMed Central

Amaradasa, B. Sajeewa

2016-01-01

Pathogen exposure to sublethal doses of fungicides may result in mutations that may represent an important and largely overlooked mechanism of introducing new genetic variation into strictly clonal populations, including acquisition of fungicide resistance. We tested this hypothesis using the clonal plant pathogen, Sclerotinia sclerotiorum. Nine susceptible isolates were exposed independently to five commercial fungicides with different modes of action: boscalid (respiration inhibitor), iprodione (unclear mode of action), thiophanate methyl (inhibition of microtubulin synthesis) and azoxystrobin and pyraclostrobin (quinone outside inhibitors). Mycelium of each isolate was inoculated onto a fungicide gradient and sub-cultured from the 50–100% inhibition zone for 12 generations and experiment repeated. Mutational changes were assessed for all isolates at six neutral microsatellite (SSR) loci and for a subset of isolates using amplified fragment length polymorphisms (AFLPs). SSR analysis showed 12 of 85 fungicide-exposed isolates had a total of 127 stepwise mutations with 42 insertions and 85 deletions. Most stepwise deletions were in iprodione- and azoxystrobin-exposed isolates (n = 40/85 each). Estimated mutation rates were 1.7 to 60-fold higher for mutated loci compared to that expected under neutral conditions. AFLP genotyping of 33 isolates (16 non-exposed control and 17 fungicide exposed) generated 602 polymorphic alleles. Cluster analysis with principal coordinate analysis (PCoA) and discriminant analysis of principal components (DAPC) identified fungicide-exposed isolates as a distinct group from non-exposed control isolates (PhiPT = 0.15, P = 0.001). Dendrograms based on neighbor-joining also supported allelic variation associated with fungicide-exposure. Fungicide sensitivity of isolates measured throughout both experiments did not show consistent trends. For example, eight isolates exposed to boscalid had higher EC50 values at the end of the experiment, and when repeated, only one isolate had higher EC50 while most isolates showed no difference. Results of this support the hypothesis that sublethal fungicide stress increases mutation rates in a largely clonal plant pathogen under in vitro conditions. Collectively, this work will aid our understanding how non-lethal fungicide exposure may affect genomic variation, which may be an important mechanism of novel trait emergence, adaptation, and evolution for clonal organisms. PMID:27959950

Perception of Small Frequency Differences in Children with Auditory Processing Disorder or Specific Language Impairment

PubMed Central

Rota-Donahue, Christine; Schwartz, Richard G.; Shafer, Valerie; Sussman, Elyse S.

2016-01-01

Background Frequency discrimination is often impaired in children developing language atypically. However, findings in the detection of small frequency changes in these children are conflicting. Previous studies on children’s auditory perceptual abilities usually involved establishing differential sensitivity thresholds in sample populations who were not tested for auditory deficits. To date, there are no data comparing suprathreshold frequency discrimination ability in children tested for both auditory processing and language skills. Purpose This study examined the perception of small frequency differences (Δf) in children with auditory processing disorder (APD) and/or specific language impairment (SLI). The aim was to determine whether children with APD and children with SLI showed differences in their behavioral responses to frequency changes. Results were expected to identify different degrees of impairment and shed some light on the auditory perceptual overlap between pediatric APD and SLI. Research Design An experimental group design using a two-alternative forced-choice procedure was used to determine frequency discrimination ability for three magnitudes of Δf from the 1000-Hz base frequency. Study Sample Thirty children between 10 years of age and 12 years, 11 months of age: 17 children with APD and/or SLI, and 13 typically developing (TD) peers participated. The clinical groups included four children with APD only, four children with SLI only, and nine children with both APD and SLI. Data Collection and Analysis Behavioral data collected using headphone delivery were analyzed using the sensitivity index d′, calculated for three Δf was 2%, 5%, and 15% of the base frequency or 20, 50, and 150 Hz. Correlations between the dependent variable d′ and the independent variables measuring auditory processing and language skills were also obtained. A stepwise regression analysis was then performed. Results TD children and children with APD and/or SLI differed in the detection of small-tone Δf. In addition, APD or SLI status affected behavioral results differently. Comparisons between auditory processing test scores or language test scores and the sensitivity index d′ showed different strengths of correlation based on the magnitudes of the Δf. Auditory processing scores showed stronger correlation to the sensitivity index d′ for the small Δf, while language scores showed stronger correlation to the sensitivity index d′ for the large Δf. Conclusion Although children with APD and/or SLI have difficulty with behavioral frequency discrimination, this difficulty may stem from two different levels: a basic auditory level for children with APD and a higher language processing level for children with SLI; the frequency discrimination performance seemed to be affected by the labeling demands of the same versus different frequency discrimination task for the children with SLI. PMID:27310407

Differences in temperament, character and psychopathology among subjects with different patterns of cannabis use.

PubMed

Spalletta, Gianfranco; Bria, Pietro; Caltagirone, Carlo

2007-01-01

Patients who use illicit drugs and suffer from comorbid psychiatric illnesses have worse outcomes than drug users without a dual diagnosis. For this reason we aimed at identifying predictors of cannabis use severity using a multivariate model in which different clinical and socio-demographic variables were included. We administered the Temperament and Character Inventory, SCID-P, SCID-II, the Beck Depression Inventory and the State-Trait Anxiety Inventory. Of the 84 subjects included, 25 were occasional users, 37 were abusers, and 22 were dependent on cannabis. A stepwise multiple regression analysis identified increased self-transcendence scores and state anxiety severity as the only predictors of a increased cannabis use severity (F = 6.635; d.f. = 2, 81; p = 0.0021). In particular, in a further multivariate analysis of variance, the transpersonal identification issue of self-transcendence was associated significantly (F = 4.267; d.f. = 2, 81; p = 0.017) with greater severity of cannabis use. Character dimension of self-transcendence and symptoms of state anxiety should be taken into consideration during the assessment procedure of patients with cannabis use as they may be helpful in the discrimination of cannabis use severity.

Automated texture-based identification of ovarian cancer in confocal microendoscope images

NASA Astrophysics Data System (ADS)

Srivastava, Saurabh; Rodriguez, Jeffrey J.; Rouse, Andrew R.; Brewer, Molly A.; Gmitro, Arthur F.

2005-03-01

The fluorescence confocal microendoscope provides high-resolution, in-vivo imaging of cellular pathology during optical biopsy. There are indications that the examination of human ovaries with this instrument has diagnostic implications for the early detection of ovarian cancer. The purpose of this study was to develop a computer-aided system to facilitate the identification of ovarian cancer from digital images captured with the confocal microendoscope system. To achieve this goal, we modeled the cellular-level structure present in these images as texture and extracted features based on first-order statistics, spatial gray-level dependence matrices, and spatial-frequency content. Selection of the best features for classification was performed using traditional feature selection techniques including stepwise discriminant analysis, forward sequential search, a non-parametric method, principal component analysis, and a heuristic technique that combines the results of these methods. The best set of features selected was used for classification, and performance of various machine classifiers was compared by analyzing the areas under their receiver operating characteristic curves. The results show that it is possible to automatically identify patients with ovarian cancer based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of the human observer.

Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms.

PubMed

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

2018-05-01

In this paper, two novel feature extraction methods, using neighborhood structural similarity (NSS), are proposed for the characterization of mammographic masses as benign or malignant. Since gray-level distribution of pixels is different in benign and malignant masses, more regular and homogeneous patterns are visible in benign masses compared to malignant masses; the proposed method exploits the similarity between neighboring regions of masses by designing two new features, namely, NSS-I and NSS-II, which capture global similarity at different scales. Complementary to these global features, uniform local binary patterns are computed to enhance the classification efficiency by combining with the proposed features. The performance of the features are evaluated using the images from the mini-mammographic image analysis society (mini-MIAS) and digital database for screening mammography (DDSM) databases, where a tenfold cross-validation technique is incorporated with Fisher linear discriminant analysis, after selecting the optimal set of features using stepwise logistic regression method. The best area under the receiver operating characteristic curve of 0.98 with an accuracy of is achieved with the mini-MIAS database, while the same for the DDSM database is 0.93 with accuracy .

A comparison of the validity of GHQ-12 and CHQ-12 in Chinese primary care patients in Manchester.

PubMed

Pan, P C; Goldberg, D P

1990-11-01

The present study compares the efficacy of the GHQ-12 and the Chinese Health Questionnaire (CHQ-12) in Cantonese speaking Chinese primary-care patients living in Greater Manchester, using relative operating characteristic (ROC) analysis. We did not find that the Chinese version offered any advantage over the conventional version of the GHQ in this population. Stepwise discriminant analysis however confirmed the value of individual items in the former pertaining to specific somatic symptoms and interpersonal relationships in differentiating cases from non-cases. Information biases, arising from the lack of a reliability study on the second-stage case identifying interview and the unique linguistic characteristics of the Chinese language may have affected the overall validity indices of the questionnaires. The study also examines the effects of using different criteria to define a case, and shows that with increasing levels of severity, there is an improvement in the diagnostic performance of the two questionnaires as reflected by areas under ROC curves and traditional validity indices. Possible explanations of these findings are discussed. The scoring method proposed by Goodchild & Duncan-Jones (1985) when used on these questionnaires had no demonstrable advantage over the conventional scoring method.

Generation of high-yield insulin producing cells from human bone marrow mesenchymal stem cells.

PubMed

Jafarian, Arefeh; Taghikhani, Mohammad; Abroun, Saeid; Pourpak, Zahra; Allahverdi, Amir; Soleimani, Masoud

2014-07-01

Allogenic islet transplantation is a most efficient approach for treatment of diabetes mellitus. However, the scarcity of islets and long term need for an immunosuppressant limits its application. Recently, cell replacement therapies that generate of unlimited sources of β cells have been developed to overcome these limitations. In this study we have described a stage specific differentiation protocol for the generation of insulin producing islet-like clusters from human bone marrow mesenchymal stem cells (hBM-MSCs). This specific stepwise protocol induced differentiation of hMSCs into definitive endoderm, pancreatic endoderm and pancreatic endocrine cells that expressed of sox17, foxa2, pdx1, ngn3, nkx2.2, insulin, glucagon, somatostatin, pancreatic polypeptide, and glut2 transcripts respectively. In addition, immunocytochemical analysis confirmed protein expression of the above mentioned genes. Western blot analysis discriminated insulin from proinsulin in the final differentiated cells. In derived insulin producing cells (IPCs), secreted insulin and C-peptide was in a glucose dependent manner. We have developed a protocol that generates effective high-yield human IPCs from hBM-MSCs in vitro. These finding suggest that functional IPCs generated by this procedure can be used as a cell-based approach for insulin dependent diabetes mellitus.

A visual parallel-BCI speller based on the time-frequency coding strategy.

PubMed

Xu, Minpeng; Chen, Long; Zhang, Lixin; Qi, Hongzhi; Ma, Lan; Tang, Jiabei; Wan, Baikun; Ming, Dong

2014-04-01

Spelling is one of the most important issues in brain-computer interface (BCI) research. This paper is to develop a visual parallel-BCI speller system based on the time-frequency coding strategy in which the sub-speller switching among four simultaneously presented sub-spellers and the character selection are identified in a parallel mode. The parallel-BCI speller was constituted by four independent P300+SSVEP-B (P300 plus SSVEP blocking) spellers with different flicker frequencies, thereby all characters had a specific time-frequency code. To verify its effectiveness, 11 subjects were involved in the offline and online spellings. A classification strategy was designed to recognize the target character through jointly using the canonical correlation analysis and stepwise linear discriminant analysis. Online spellings showed that the proposed parallel-BCI speller had a high performance, reaching the highest information transfer rate of 67.4 bit min(-1), with an average of 54.0 bit min(-1) and 43.0 bit min(-1) in the three rounds and five rounds, respectively. The results indicated that the proposed parallel-BCI could be effectively controlled by users with attention shifting fluently among the sub-spellers, and highly improved the BCI spelling performance.

A hybrid sensing approach for pure and adulterated honey classification.

PubMed

Subari, Norazian; Mohamad Saleh, Junita; Md Shakaff, Ali Yeon; Zakaria, Ammar

2012-10-17

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.

Predictors of Long-Term School-Based Behavioral Outcomes in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder

PubMed Central

Reed, Margot O.; Jakubovski, Ewgeni; Johnson, Jessica A.

2017-01-01

Abstract Objective: To explore predictors of 8-year school-based behavioral outcomes in attention-deficit/hyperactivity disorder (ADHD). Methods: We examined potential baseline predictors of school-based behavioral outcomes in children who completed the 8-year follow-up in the multimodal treatment study of children with ADHD. Stepwise logistic regression and receiver operating characteristic (ROC) analysis identified baseline predictors that were associated with a higher risk of truancy, school discipline, and in-school fights. Results: Stepwise regression analysis explained between 8.1% (in-school fights) and 12.0% (school discipline) of the total variance in school-based behavioral outcomes. Logistic regression identified several baseline characteristics that were associated with school-based behavioral difficulties 8 years later, including being male (associated with truancy and school discipline), African American (school discipline, in-school fights), increased conduct disorder (CD) symptoms (truancy), decreased affection from parents (school discipline), ADHD severity (in-school fights), and study site (truancy and school discipline). ROC analyses identified the most discriminative predictors of truancy, school discipline, and in-school fights, which were Aggression and Conduct Problem Scale Total score, family income, and race, respectively. Conclusions: A modest, but nontrivial portion of school-based behavioral outcomes, was predicted by baseline childhood characteristics. Exploratory analyses identified modifiable (lack of paternal involvement, lower parental knowledge of behavioral principles, and parental use of physical punishment), somewhat modifiable (income and having comorbid CD), and nonmodifiable (African American and male) factors that were associated with school-based behavioral difficulties. Future research should confirm that the associations between earlier specific parenting behaviors and poor subsequent school-based behavioral outcomes are, indeed, causally related and independent cooccurring childhood psychopathology. Future research might target increasing paternal involvement and parental knowledge of behavioral principles and reducing use of physical punishment to improve school-based behavioral outcomes in children with ADHD. PMID:28253029

Predictors of Long-Term School-Based Behavioral Outcomes in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder.

PubMed

Reed, Margot O; Jakubovski, Ewgeni; Johnson, Jessica A; Bloch, Michael H

2017-05-01

To explore predictors of 8-year school-based behavioral outcomes in attention-deficit/hyperactivity disorder (ADHD). We examined potential baseline predictors of school-based behavioral outcomes in children who completed the 8-year follow-up in the multimodal treatment study of children with ADHD. Stepwise logistic regression and receiver operating characteristic (ROC) analysis identified baseline predictors that were associated with a higher risk of truancy, school discipline, and in-school fights. Stepwise regression analysis explained between 8.1% (in-school fights) and 12.0% (school discipline) of the total variance in school-based behavioral outcomes. Logistic regression identified several baseline characteristics that were associated with school-based behavioral difficulties 8 years later, including being male (associated with truancy and school discipline), African American (school discipline, in-school fights), increased conduct disorder (CD) symptoms (truancy), decreased affection from parents (school discipline), ADHD severity (in-school fights), and study site (truancy and school discipline). ROC analyses identified the most discriminative predictors of truancy, school discipline, and in-school fights, which were Aggression and Conduct Problem Scale Total score, family income, and race, respectively. A modest, but nontrivial portion of school-based behavioral outcomes, was predicted by baseline childhood characteristics. Exploratory analyses identified modifiable (lack of paternal involvement, lower parental knowledge of behavioral principles, and parental use of physical punishment), somewhat modifiable (income and having comorbid CD), and nonmodifiable (African American and male) factors that were associated with school-based behavioral difficulties. Future research should confirm that the associations between earlier specific parenting behaviors and poor subsequent school-based behavioral outcomes are, indeed, causally related and independent cooccurring childhood psychopathology. Future research might target increasing paternal involvement and parental knowledge of behavioral principles and reducing use of physical punishment to improve school-based behavioral outcomes in children with ADHD.

Analysis of intraspecific seed diversity in Astragalus aquilanus (Fabaceae), an endemic species of Central Apennine.

PubMed

Di Cecco, V; Di Musciano, M; D'Archivio, A A; Frattaroli, A R; Di Martino, L

2018-05-20

This work aims to study seeds of the endemic species Astragalus aquilanus from four different populations of central Italy. We investigated seed morpho-colorimetric features (shape and size) and chemical differences (through infrared spectroscopy) among populations and between dark and light seeds. Seed morpho-colorimetric quantitative variables, describing shape, size and colour traits, were measured using image analysis techniques. Fourier transform infrared (FT-IR) spectroscopy was used to attempt seed chemical characterisation. The measured data were analysed by step-wise linear discriminant analysis (LDA). Moreover, we analysed the correlation between the four most important traits and six climatic variables extracted from WorldClim 2.0. The LDA on seeds traits shows clear differentiation of the four populations, which can be attributed to different chemical composition, as confirmed by Wilk's lambda test (P < 0.001). A strong correlation between morphometric traits and temperature (annual mean temperature, mean temperature of the warmest and coolest quarter), colorimetric traits and precipitation (annual precipitation, precipitation of wettest and driest quarter) was observed. The characterisation of A. aquilanus seeds shows large intraspecific plasticity both in morpho-colorimetric and chemical composition. These results confirm the strong relationship between the type of seed produced and the climatic variables. © 2018 German Society for Plant Sciences and The Royal Botanical Society of the Netherlands.

Metallic content of wines from the Canary Islands (Spain). Application of artificial neural networks to the data analysis.

PubMed

Frías, Sergio; Conde, José E; Rodríguez, Miguel A; Dohnal, Vlasta; Pérez-Trujillo, Juan P

2002-10-01

Eleven elements, K, Na, Ca, Mg, Fe, Cu, Zn, Mn, Sr, Li and Rb, were determined in dry and sweet wines bearing the denominations of origin of El Hierro, La Palma and Lanzarote islands (Canary Islands, Spain). Analyses were performed by flame atomic absorption spectrophotometry, with the exceptions of Li and Rb for which flame atomic emission spectrophotometry was used. The content in copper and iron did not present risks of cases. All samples presented a copper and zinc content below the maximum amount recommended by the Office International de la Vigne et du Vin (OIV) for these elements. Significant differences in the metallic content were found among the different islands. Thus, Lanzarote presented the highest mean content in sodium and lithium and the lowest mean content in rubidium, and La Palma presented the highest mean content in strontium and rubidium. Sweet wines from La Palma, elaborated as naturally sweet with over-ripe grapes, presented mean contents significantly higher with regard to dry wines from the same island in the majority of the analysed elements. Cluster analysis and Kohonen self-organising maps showed differences in wines according to the island of origin and the ripening state of the grapes. Back-propagation artificial neural networks showed better prediction ability than stepwise linear discriminant analysis.

Investigating the sources of sediment in a Canadian agricultural watershed using a colour-based fingerprinting technique

NASA Astrophysics Data System (ADS)

Barthod, Louise; Lobb, David; Owens, Philip; Martinez-Carreras, Nuria; Koiter, Alexander; Petticrew, Ellen; McCullough, Gregory

2014-05-01

The development of beneficial management practises to minimize adverse impacts of agriculture on soil and water quality requires information on the sources of sediment at the watershed scale. Sediment fingerprinting allows for the determination of sediment sources and apportionment of their contribution within a watershed, using unique physical, radiochemical or biogeochemical properties, or fingerprints, of the potential sediment sources. The use of sediment colour as a fingerprint is an emerging technique that can provide a rapid and inexpensive means of investigating sediment sources. This technique is currently being utilized to determine sediment sources within the South Tobacco Creek Watershed, an agricultural watershed located in the Canadian prairies (south-central Manitoba). Suspended sediment and potential source (topsoil, channel bank and shale bedrock material) samples were collected between 2009 and 2011 at six locations along the main stem of the creek. Sample colour was quantified from diffuse reflectance spectrometry measurements over the visible wavelength range using a spectroradiometer (ASD Field Spec Pro, 400-2500 nm). Sixteen colour coefficients were derived from several colour space models (CIE XYZ, CIE xyY, CIE Lab, CIE Luv, CIE Lch, Landsat RGB, Redness Index). The individual discrimination power of the colour coefficients, after passing several prerequisite tests (e.g., linearly additive behaviour), was assessed using discriminant function analysis. A stepwise discriminant analysis, based on the Wilk's lambda criterion, was then performed in order to determine the best-suited colour coefficient fingerprints which maximized the discrimination between the potential sources. The selected fingerprints classified the source samples in the correct category 86% of the time. The misclassification is due to intra-source variability and source overlap which can lead to higher uncertainty in sediment source apportionment. The selected fingerprints were then included in a Bayesian mixing model using Monte-Carlo simulation (Stable Isotope Analysis in R, SIAR) in order to apportion the contribution of the different sources to the sediment collected at each location. A switch in the dominant sediment source between the headwaters and the outlet of the watershed is observed. Sediment is enriched with shale bedrock and depleted of topsoil sources as the stream crosses and down-cuts through the Manitoba Escarpment. The switch in sources highlights the importance of the sampling location in relation to the scale and geomorphic connectivity of the watershed. Although the results include considerable uncertainty, they are consistent with the findings from a classical fingerprinting approach undertaken in the same watershed (i.e., geochemical and radionuclide fingerprints), and confirm the potential of sediment colour parameters as suitable fingerprints.

Botanical traceability of commercial tannins using the mineral profile and stable isotopes.

PubMed

Bertoldi, Daniela; Santato, Alessandro; Paolini, Mauro; Barbero, Alice; Camin, Federica; Nicolini, Giorgio; Larcher, Roberto

2014-09-01

Commercial tannins are natural polyphenolic compounds extracted from different plant tissues such as gall, the wood of different species and fruit. In the food industry they are mainly used as flavourings and food ingredients, whereas in winemaking they are classified as clarification agents for wine protein stabilisation, although colour stabilisation, metal removal, unpleasant thiol removal and rheological correction are also well-known and desired effects. Due to their particular technical properties and very different costs, the possibility of correct identification of the real botanical origin of tannins can be considered a primary target in oenology research and in fulfilling the technical and economic requirements of the wine industry. For some categories of tannins encouraging results have already been achieved by considering sugar or polyphenolic composition. For the first time this work verifies the possibility of determining the botanical origin of tannins on the basis of the mineral element profile and analysis of the (13) C/(12) C isotopic ratio. One hundred two commercial tannins originating from 10 different botanical sources (grapes, oak, gall, chestnut, fruit trees, quebracho, tea, acacia, officinal plants and tara) were analysed to determine 57 elements and the (13) C/(12) C isotopic ratio, using inductively coupled plasma mass spectrometry and isotope-ratio mass spectrometry, respectively. Forward stepwise discriminant analysis provided good discrimination between the 8 most abundant groups, with 100% correct re-classification. The model was then validated five times on subsets of 10% of the overall samples, randomly extracted, achieving satisfactory results. With a similar approach it was also possible to distinguish toasted and untoasted oak tannins as well as tannins from grape skin and grape seeds. Copyright © 2014 John Wiley & Sons, Ltd.

Knowing the operative game plan: a novel tool for the assessment of surgical procedural knowledge.

PubMed

Balayla, Jacques; Bergman, Simon; Ghitulescu, Gabriela; Feldman, Liane S; Fraser, Shannon A

2012-08-01

What is the source of inadequate performance in the operating room? Is it a lack of technical skills, poor judgment or a lack of procedural knowledge? We created a surgical procedural knowledge (SPK) assessment tool and evaluated its use. We interviewed medical students, residents and training program staff on SPK assessment tools developed for 3 different common general surgery procedures: inguinal hernia repair with mesh in men, laparoscopic cholecystectomy and right hemicolectomy. The tools were developed as a step-wise assessment of specific surgical procedures based on techniques described in a current surgical text. We compared novice (medical student to postgraduate year [PGY]-2) and expert group (PGY-3 to program staff) scores using the Mann-Whitney U test. We calculated the total SPK score and defined a cut-off score using receiver operating characteristic analysis. In all, 5 participants in 7 different training groups (n = 35) underwent an interview. Median scores for each procedure and overall SPK scores increased with experience. The median SPK for novices was 54.9 (95% confidence interval [CI] 21.6-58.8) compared with 98.05 (95% CP 94.1-100.0) for experts (p = 0.012). The SPK cut-off score of 93.1 discriminates between novice and expert surgeons. Surgical procedural knowledge can reliably be assessed using our SPK assessment tool. It can discriminate between novice and expert surgeons for common general surgical procedures. Future studies are planned to evaluate its use for more complex procedures.

Near-infrared Raman spectroscopy for assessing biochemical changes of cervical tissue associated with precarcinogenic transformation.

PubMed

Duraipandian, Shiyamala; Mo, Jianhua; Zheng, Wei; Huang, Zhiwei

2014-11-07

Raman spectroscopy measures the inelastically scattered light from tissue that is capable of identifying native tissue biochemical constituents and their changes associated with disease transformation. This study aims to characterize the Raman spectroscopic properties of cervical tissue associated with the multi-stage progression of cervical precarcinogenic sequence. A rapid-acquisition fiber-optic near-infrared (NIR) Raman diagnostic system was employed for tissue Raman spectral measurements at 785 nm excitation. A total of 68 Raman spectra (23 benign, 29 low-grade squamous intraepithelial lesions (LSIL) and 16 high grade squamous intraepithelial lesions (HSIL)) were measured from 25 cervical tissue biopsy specimens, as confirmed by colposcopy-histopathology. The semi-quantitative biochemical modeling based on the major biochemicals (i.e., DNA, proteins (histone, collagen), lipid (triolein) and carbohydrates (glycogen)) in cervical tissue uncovers the stepwise accumulation of biomolecular changes associated with progressive cervical precarcinogenesis. Multi-class partial least squares-discriminant analysis (PLS-DA) together with leave-one tissue site-out, cross-validation yielded the diagnostic sensitivities of 95.7%, 82.8% and 81.3%; specificities of 100.0%, 92.3% and 88.5%,for discrimination among benign, LSIL and HSIL cervical tissues, respectively. This work suggests that the Raman spectral biomarkers have identified the potential to be used for monitoring the multi-stage cervical precarcinogenesis, forming the foundation of applying NIR Raman spectroscopy for the early diagnosis of cervical precancer in vivo at the molecular level.

Prolonged activation EEG differentiates dementia with and without delirium in frail elderly patients.

PubMed

Thomas, C; Hestermann, U; Walther, S; Pfueller, U; Hack, M; Oster, P; Mundt, C; Weisbrod, M

2008-02-01

Delirium in the elderly results in increased morbidity, mortality and functional decline. Delirium is underdiagnosed, particularly in dementia. To increase diagnostic accuracy, we investigated whether maintenance of activation assessed by EEG discriminates delirium in association with dementia (D+D) from dementia without delirium (DP) and cognitively unimpaired elderly subjects (CU). Routine and quantitative EEG (rEEG/qEEG) with additional prolonged activation (3 min eyes open period) were evaluated in hospitalised elderly patients with acute geriatric disease. Patients were assigned post hoc to three comparable groups (D+D/DP/CU) by expert consensus based on DSM-IV criteria. Dementia diagnosis was confirmed using cognitive and functional tests and caregiver rating (IQCODE, Informed Questionnaire of Cognitive Decline in the Elderly). While rEEG at rest showed low accuracy for a diagnosis of delirium, qEEG in DP and CU revealed a specific activation pattern of high significance found to be absent in the D+D group. Stepwise logistic regression confirmed that differentiation of D+D from DP was best resolved using activated upper alpha and delta power density which, compared with rEEG, enabled an 11% increase in diagnostic correctness to 83%, resulting in 67% sensitivity and 91% specificity. Among frail CU and D+D subjects, almost 90% were correctly classified. Dementia associated with delirium can be discriminated reliably from dementia alone in a meaningful clinical setting. Thus EEG evaluation in chronic encephalopathy should be optimised by a simple activation task and spectral analysis, particularly in the elderly with dementia.

Factors associated with enrollment of African Americans into a clinical trial: results from the African American study of kidney disease and hypertension.

PubMed

Gadegbeku, Crystal A; Stillman, Phyllis Kreger; Huffman, Mark D; Jackson, James S; Kusek, John W; Jamerson, Kenneth A

2008-11-01

Recruitment of diverse populations into clinical trials remains challenging but is needed to fully understand disease processes and benefit the general public. Greater knowledge of key factors among ethnic and racial minority populations associated with the decision to participate in clinical research studies may facilitate recruitment and enhance the generalizibility of study results. Therefore, during the recruitment phase of the African American Study of Kidney Disease and Hypertension (AASK) trial, we conducted a telephone survey, using validated questions, to explore potential facilitators and barriers of research participation among eligible candidates residing in seven U.S. locations. Survey responses included a range of characteristics and perceptions among participants and non-participants and were compared using bivariate and step-wise logistic regression analyses. One-hundred forty-one respondents in the one-hundred forty (70 trial participants and 71 non-participants) completed the survey. Trial participants and non-participants were similar in multiple demographic characteristics and shared similar views on discrimination, physician mistrust, and research integrity. Key group differences were related to their perceptions of the impact of their research participation. Participants associated enrollment with personal and societal health benefits, while non-participants were influenced by the health risks. In a step-wise linear regression analysis, the most powerful significant positive predictors of participation were acknowledgement of health status as important in the enrollment decision (OR=4.54, p=0.006), employment (OR=3.12, p = 0.05) and healthcare satisfaction (OR=2.12, p<0.01). Racially-based mistrust did not emerge as a negative predictor and subjects' decisions were not influenced by the race of the research staff. In conclusion, these results suggest that health-related factors, and not psychosocial perceptions, have predominant influence on research participation among African Americans.

Determination of sex from the patella in a contemporary Spanish population.

PubMed

Peckmann, Tanya R; Meek, Susan; Dilkie, Natasha; Rozendaal, Andrew

2016-11-01

The skull and pelvis have been used for the determination of sex for unknown human remains. However, in forensic cases where skeletal remains often exhibit postmortem damage and taphonomic changes the patella may be used for the determination of sex as it is a preservationally favoured bone. The goal of the present research was to derive discriminant function equations from the patella for estimation of sex from a contemporary Spanish population. Six parameters were measured on 106 individuals (55 males and 51 females), ranging in age from 22 to 85 years old, from the Granada Osteological Collection. The statistical analyses showed that all variables were sexually dimorphic. Discriminant function score equations were generated for use in sex determination. The overall accuracy of sex classification ranged from 75.2% to 84.8% for the direct method and 75.5%-83.8% for the stepwise method. When the South African White discriminant functions were applied to the Spanish sample they showed high accuracy rates for sexing female patellae (90%-95.9%) and low accuracy rates for sexing male patellae (52.7%-58.2%). When the South African Black discriminant functions were applied to the Spanish sample they showed high accuracy rates for sexing male patellae (90.9%) and low accuracy rates for sexing female patellae (70%-75.5%). The patella was shown to be useful for sex determination in the contemporary Spanish population. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Differentiation of infiltrative cholangiocarcinoma from benign common bile duct stricture using three-dimensional dynamic contrast-enhanced MRI with MRCP.

PubMed

Yu, X-R; Huang, W-Y; Zhang, B-Y; Li, H-Q; Geng, D-Y

2014-06-01

To retrospectively evaluate the criteria for discriminating infiltrative cholangiocarcinoma from benign common bile duct (CBD) stricture using three-dimensional dynamic contrast-enhanced (3D-DCE) magnetic resonance imaging (MRI) combined with magnetic resonance cholangiopancreatography (MRCP) imaging and to determine the predictors for cholangiocarcinoma versus benign CBD stricture. 3D-DCE MRI and MRCP images in 28 patients with infiltrative cholangiocarcinoma and 23 patients with benign causes of CBD stricture were reviewed retrospectively. The final diagnosis was based on surgical or biopsy records. Two radiologists analysed the MRI images for asymmetry, including the wall thickness, length, and enhancement pattern of the narrowed CBD segment, and upstream CBD dilatation. MRI findings that could be used as predictors were identified by univariate analysis and multivariable stepwise logistic regression analysis. Malignant strictures were significantly thicker (4.4 ± 1.2 mm) and longer (16.7 ± 7.7 mm) than the benign strictures (p < 0.05), and upstream CBD dilatation was larger in the infiltrative cholangiocarcinoma cases (20.7 ± 5.7 mm) than in the benign cases (16.5 ± 5.2 mm; p = 0.018). During both the portal venous and equilibrium phases, hyperenhancement was more frequently observed in malignant cases than in benign cases (p < 0.001). The results of the multivariable stepwise logistic regression analysis showed that both hyperenhancement of the involved CBD during the equilibrium phase and the ductal thickness were significant predictors for malignant strictures. When two diagnostic predictive values were used in combination, almost all patients with malignant strictures (n = 26, 92.9%) and benign strictures (n = 21, 91.3%) were correctly identified; the overall accuracy was 92.2% with correct classifications in 47 of the 51 patients. Infiltrative cholangiocarcinoma and benign CBD strictures could be effectively differentiated using DCE-MRI and MRCP based on hyperenhancement during the equilibrium phase and bile wall thickness of the involved segment. Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Developing and validating a predictive model for stroke progression.

PubMed

Craig, L E; Wu, O; Gilmour, H; Barber, M; Langhorne, P

2011-01-01

Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Two patient cohorts were used for this study - the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p < 0.1) on univariate analysis were included in the multivariate model. Logistic regression was the technique employed using backward stepwise regression to drop the least significant variables (p > 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72-0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50-0.92)]. The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and calibration of the predictive model appear sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice.

Application of stepwise multiple regression techniques to inversion of Nimbus 'IRIS' observations.

NASA Technical Reports Server (NTRS)

Ohring, G.

1972-01-01

Exploratory studies with Nimbus-3 infrared interferometer-spectrometer (IRIS) data indicate that, in addition to temperature, such meteorological parameters as geopotential heights of pressure surfaces, tropopause pressure, and tropopause temperature can be inferred from the observed spectra with the use of simple regression equations. The technique of screening the IRIS spectral data by means of stepwise regression to obtain the best radiation predictors of meteorological parameters is validated. The simplicity of application of the technique and the simplicity of the derived linear regression equations - which contain only a few terms - suggest usefulness for this approach. Based upon the results obtained, suggestions are made for further development and exploitation of the stepwise regression analysis technique.

Characterizing hydrochemical properties of springs in Taiwan based on their geological origins.

PubMed

Jang, Cheng-Shin; Chen, Jui-Sheng; Lin, Yun-Bin; Liu, Chen-Wuing

2012-01-01

This study was performed to characterize hydrochemical properties of springs based on their geological origins in Taiwan. Stepwise discriminant analysis (DA) was used to establish a linear classification model of springs using hydrochemical parameters. Two hydrochemical datasets-ion concentrations and relative proportions of equivalents per liter of major ions-were included to perform prediction of the geological origins of springs. Analyzed results reveal that DA using relative proportions of equivalents per liter of major ions yields a 95.6% right assignation, which is superior to DA using ion concentrations. This result indicates that relative proportions of equivalents of major hydrochemical parameters in spring water are more highly associated with the geological origins than ion concentrations do. Low percentages of Na(+) equivalents are common properties of springs emerging from acid-sulfate and neutral-sulfate igneous rock. Springs emerging from metamorphic rock show low percentages of Cl( - ) equivalents and high percentages of HCO[Formula: see text] equivalents, and springs emerging from sedimentary rock exhibit high Cl( - )/SO(2-)(4) ratios.

Body fat distribution of overweight females with a history of weight cycling.

PubMed

Wallner, S J; Luschnigg, N; Schnedl, W J; Lahousen, T; Sudi, K; Crailsheim, K; Möller, R; Tafeit, E; Horejsi, R

2004-09-01

Weight cycling may cause a redistribution of body fat to the upper body fat compartments. We investigated the distribution of subcutaneous adipose tissue (SAT) in 30 overweight women with a history of weight-cycling and age-matched controls (167 normal weight and 97 overweight subjects). Measurements of SAT were performed using an optical device, the Lipometer. The SAT topography describes the thicknesses of SAT layers at 15 anatomically well-defined body sites from neck to calf. The overweight women with a history of weight cycling had significantly thicker SAT layers on the upper body compared to the overweight controls, but even thinner SAT layers on their legs than the normal weight women. An android fat pattern was attributed to overweight females and, even more pronounced, to the weight cyclers. The majority of normal weight women showed a gynoid fat pattern. Using stepwise discriminant analysis, 89.0% of all weight cyclers and overweight controls could be classified correctly into the two groups. These findings show the importance of normal weight maintenance as a health-promoting factor.

A neural network approach to cloud classification

NASA Technical Reports Server (NTRS)

Lee, Jonathan; Weger, Ronald C.; Sengupta, Sailes K.; Welch, Ronald M.

1990-01-01

It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.

Comparative Study of Phenolic Profile, Antioxidant Capacity, and Color-composition Relation of Roselle Cultivars with Contrasting Pigmentation.

PubMed

Camelo-Méndez, Gustavo A; Jara-Palacios, M José; Escudero-Gilete, M Luisa; Gordillo, Belén; Hernanz, Dolores; Paredes-López, Octavio; Vanegas-Espinoza, Pablo E; Del Villar-Martínez, Alma A; Heredia, Francisco J

2016-03-01

Roselle is a plant that accumulates anthocyanins significantly, hence its importance as food coloring and as a source of antioxidant compounds for human health. This study was aimed to determine phenolic composition and antioxidant capacity of methanolic extracts, and beverages obtained from native roselle cultivars in Mexico (Negra, Sudan, Rosa and Blanca) with different degrees of pigmentation, and to establish the color-composition relationship. Chromatographic methods were used to determine phenolic compounds: flavanols, flavonols, benzoic, hibiscus and phenolic acids as well as two main anthocyanins (cyanidin 3-sambubioside and delphinidin 3-sambubioside). The antioxidant capacity was evaluated by ABTS and FRAP assays. Tristimulus colorimetry showed to be a useful technique to determine the color-composition relationship, leading to equations that allowed to predict anthocyanin content of roselle (R > 0.84). Also, a stepwise linear discriminant analysis (SLDA) was developed in order to classify roselle cultivars. The obtained mathematical model could be an important tool to be used in colorimetric characterization of functional compounds used in food processing.

The relationship of strength and muscle balance to shoulder pain and impingement syndrome in elite quadriplegic wheelchair rugby players.

PubMed

Miyahara, M; Sleivert, G G; Gerrard, D F

1998-04-01

Wheelchair athletes are susceptible to injuries related to overuse of the shoulder, in particular shoulder impingement syndrome. The present study examined the relationship of shoulder pain to demographic details, isokinetic strength and muscle balance in 8 elite quadriplegic rugby players. Demographic data were collected using personal interviews and each subject was clinically examined for signs of impingement syndrome by a physician. In addition each subject underwent bilateral isokinetic strength testing of the shoulder at 60 and 180 deg/s for abduction/adduction and internal/external rotation. A series of step-wise multiple discriminant analysis successfully predicted clinical symptoms from demographic, muscular strength and balance data. In particular, there was a significant deficit in adductor strength and this was related to shoulder pain and wasting of the scapular muscles. This strength deficit may be due to the high level of spinal lesions in the quadriplegic population. The level of spinal lesion may contribute to the aetiology of shoulder pathology in quadriplegia, and differentiate it from that observed in able-bodied athletes who exhibit weak abductors.

Sparse Logistic Regression for Diagnosis of Liver Fibrosis in Rat by Using SCAD-Penalized Likelihood

PubMed Central

Yan, Fang-Rong; Lin, Jin-Guan; Liu, Yu

2011-01-01

The objective of the present study is to find out the quantitative relationship between progression of liver fibrosis and the levels of certain serum markers using mathematic model. We provide the sparse logistic regression by using smoothly clipped absolute deviation (SCAD) penalized function to diagnose the liver fibrosis in rats. Not only does it give a sparse solution with high accuracy, it also provides the users with the precise probabilities of classification with the class information. In the simulative case and the experiment case, the proposed method is comparable to the stepwise linear discriminant analysis (SLDA) and the sparse logistic regression with least absolute shrinkage and selection operator (LASSO) penalty, by using receiver operating characteristic (ROC) with bayesian bootstrap estimating area under the curve (AUC) diagnostic sensitivity for selected variable. Results show that the new approach provides a good correlation between the serum marker levels and the liver fibrosis induced by thioacetamide (TAA) in rats. Meanwhile, this approach might also be used in predicting the development of liver cirrhosis. PMID:21716672

Chemical cues identify gender and individuality in Giant pandas (Ailuropoda melanoleuca).

PubMed

Hagey, Lee; MacDonald, Edith

2003-06-01

The Giant panda communicates with conspecifics by depositing a mixture of volatile compounds (called scent marks) on trees and rocks. Using mass spectrometry, we identified 951 chemical components from scent glands, urine, vaginal secretions, and scent marks made by pandas. The scent marks of the two genders contained a similar array of chemicals but varied in concentration; specifically, males possessed a significantly greater amount of short chain fatty acids (F(1, 29) = 18.4, P = 0.002). Using stepwise discriminate analysis on the relative proportions of a subset of these chemicals, it was possible to classify gender (94% for males and females) and individuality (81% for males and 91% for females) from scent marks. The power to identify individual males was reduced due to the relatedness of two subjects. By cracking the identity code of Giant panda communication, we show insights into how these animals can match individuals with unique chemical profiles. Since radiocollaring is currently banned in China, the techniques described in this paper give field biologists a new means to identify and track pandas in the wild.

Diversity of soil yeasts isolated from South Victoria Land, Antarctica

USGS Publications Warehouse

Connell, L.; Redman, R.; Craig, S.; Scorzetti, G.; Iszard, M.; Rodriguez, R.

2008-01-01

Unicellular fungi, commonly referred to as yeasts, were found to be components of the culturable soil fungal population in Taylor Valley, Mt. Discovery, Wright Valley, and two mountain peaks of South Victoria Land, Antarctica. Samples were taken from sites spanning a diversity of soil habitats that were not directly associated with vertebrate activity. A large proportion of yeasts isolated in this study were basidiomycetous species (89%), of which 43% may represent undescribed species, demonstrating that culturable yeasts remain incompletely described in these polar desert soils. Cryptococcus species represented the most often isolated genus (33%) followed by Leucosporidium (22%). Principle component analysis and multiple linear regression using stepwise selection was used to model the relation between abiotic variables (principle component 1 and principle component 2 scores) and yeast biodiversity (the number of species present at a given site). These analyses identified soil pH and electrical conductivity as significant predictors of yeast biodiversity. Species-specific PCR primers were designed to rapidly discriminate among the Dioszegia and Leucosporidium species collected in this study. ?? 2008 Springer Science+Business Media, LLC.

Genetic predisposition scores associate with muscular strength, size, and trainability.

PubMed

Thomaes, Tom; Thomis, Martine; Onkelinx, Steven; Goetschalckx, Kaatje; Fagard, Robert; Lambrechts, Diether; Vanhees, Luc

2013-08-01

The number of studies trying to identify genetic sequence variation related to muscular phenotypes has increased enormously. The aim of this study was to identify the role of a genetic predisposition score (GPS) based on earlier identified gene variants for different muscular endophenotypes to explain the individual differences in muscular fitness characteristics and the response to training in patients with coronary artery disease. Two hundred and sixty coronary artery disease patients followed a standard ambulatory, 3-month supervised training program for cardiac patients. Maximal knee extension strength (KES) and rectus femoris diameter were measured at baseline and after rehabilitation. Sixty-five single nucleotide polymorphisms (SNP) in 30 genes were selected based on genotype-phenotype association literature. Backward regression analysis revealed subsets of SNP associated with the different phenotypes. GPS were constructed for all sets of SNP by adding up the strength-increasing alleles. General linear models and multiple stepwise regression analysis were used to test the explained variance of the GPS in baseline and strength responses. Receiver operating characteristic curve analyses were performed to discriminate between high- and low-responder status. GPS were significantly associated with the rectus femoris diameter (P < 0.01) and its response (P < 0.0001), the isometric KES (P < 0.05) and its response (P < 0.01), the isokinetic KES at 60° · s (P < 0.05) and 180° · s (P < 0.001) and their responses to training (P < 0.0001), and the isokinetic KES endurance (P < 0.001) and its change after training (P < 0.0001). The GPS was shown as an independent determinant in baseline and response phenotypes with partial explained variance up to 23%. Receiver operating characteristic analysis showed a significant discriminating accuracy of the models, including the GPS for responses to training, with areas under the curve ranging from 0.62 to 0.85. GPS for muscular phenotypes showed to be associated with baseline KES, muscle diameter, and the response to training in cardiac rehabilitation patients.

The Abdominal Aortic Aneurysm Statistically Corrected Operative Risk Evaluation (AAA SCORE) for predicting mortality after open and endovascular interventions.

PubMed

Ambler, Graeme K; Gohel, Manjit S; Mitchell, David C; Loftus, Ian M; Boyle, Jonathan R

2015-01-01

Accurate adjustment of surgical outcome data for risk is vital in an era of surgeon-level reporting. Current risk prediction models for abdominal aortic aneurysm (AAA) repair are suboptimal. We aimed to develop a reliable risk model for in-hospital mortality after intervention for AAA, using rigorous contemporary statistical techniques to handle missing data. Using data collected during a 15-month period in the United Kingdom National Vascular Database, we applied multiple imputation methodology together with stepwise model selection to generate preoperative and perioperative models of in-hospital mortality after AAA repair, using two thirds of the available data. Model performance was then assessed on the remaining third of the data by receiver operating characteristic curve analysis and compared with existing risk prediction models. Model calibration was assessed by Hosmer-Lemeshow analysis. A total of 8088 AAA repair operations were recorded in the National Vascular Database during the study period, of which 5870 (72.6%) were elective procedures. Both preoperative and perioperative models showed excellent discrimination, with areas under the receiver operating characteristic curve of .89 and .92, respectively. This was significantly better than any of the existing models (area under the receiver operating characteristic curve for best comparator model, .84 and .88; P < .001 and P = .001, respectively). Discrimination remained excellent when only elective procedures were considered. There was no evidence of miscalibration by Hosmer-Lemeshow analysis. We have developed accurate models to assess risk of in-hospital mortality after AAA repair. These models were carefully developed with rigorous statistical methodology and significantly outperform existing methods for both elective cases and overall AAA mortality. These models will be invaluable for both preoperative patient counseling and accurate risk adjustment of published outcome data. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

A canonical discriminant analysis to study the association between milk fatty acids of ruminal origin and milk fat depression in dairy cows.

PubMed

Conte, G; Dimauro, C; Serra, A; Macciotta, N P P; Mele, M

2018-04-04

Although milk fat depression (MFD) has been observed and described since the beginning of the last century, all the molecular and biochemical mechanisms involved are still not completely understood. Some fatty acids (FA) originating during rumen biohydrogenation have been proposed as causative elements of MFD. However, contradictory results were obtained when studying the effect of single FA on MFD. An alternative could be the simultaneous evaluation of the effect of many FA using a multivariate approach. The aim of this study was to evaluate the relationship between individual milk FA of ruminal origin and MFD using canonical discriminant analysis, a multivariate technique able to distinguish 2 or more groups on the basis of a pool of variables. In a commercial dairy herd, a diet containing 26% starch on a DM basis induced an unintentional MFD syndrome in 14 cows out of 40. Milk yielded by these 14 animals showed a fat content lower than 50% of the ordinary value, whereas milk production and protein content were normal. The remaining 26 cows secreted typical milk fat content and therefore were considered the control group, even though they ate the same diet. The stepwise discriminant analysis selected 14 milk FA of ruminal origin most able to distinguish the 2 groups. This restricted pool of FA was used, as variables, in a run of the canonical discriminant analysis that was able to significantly discriminate between the 2 groups. Out of the 14 FA, 5 conjugated linoleic acid isomers (C18:2 trans-10,trans-12, C18:2 trans-8,trans-10, C18:2 trans-11,cis-13, C18:2 cis-9,cis-11, C18:2 cis-10,cis-12) and C15:0 iso were more related to the control group, whereas C18:2 trans-10,cis-12, C16:1 trans-6-7, C16:1 trans-9, C18:1 trans-6-8, C18:1 trans-9, C18:1 trans-10, C18:1 cis-11, and C18:3n-3 were positively associated with the MFD group, allowing a complete discrimination. On the basis of these results, we can conclude that (1) the shift of ruminal biohydrogenation from C18:1 trans-11 to C18:1 trans-10 seemed to be strongly associated with MFD; (2) at the same time, other C18:1 trans isomers showed a similar association; (3) on the contrary, conjugated linoleic acid isomers other than C18:2 trans-10,cis-12 seemed to be associated with a normal fat secretion. Results confirmed that MFD is the consequence of a combined effect of the outflow of many ruminal FA, which collectively affect mammary fat synthesis. Because the animals of the 2 groups were fed the same diet, these results suggested that factors other than diet are involved in the MFD syndrome. Feeding behavior (i.e., ability to select dietary ingredients in a total mixed ration), rumen environment and the composition of ruminal bacteria are additional factors able to modify the products of rumen biohydrogenation. Results of the present work confirmed that the multivariate approach can be a useful tool to evaluate a metabolic pathway that involves several parameters, providing interesting suggestions about the role of some FA involved in MFD. However, results about the MFD syndrome obtained in the present research require a deep molecular investigation to be confirmed. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Noninvasive fluorescence excitation spectroscopy for the diagnosis of oral neoplasia in vivo

NASA Astrophysics Data System (ADS)

Ebenezar, Jeyasingh; Ganesan, Singaravelu; Aruna, Prakasarao; Muralinaidu, Radhakrishnan; Renganathan, Kannan; Saraswathy, Thillai Rajasekaran

2012-09-01

Fluorescence excitation spectroscopy (FES) is an emerging approach to cancer detection. The goal of this pilot study is to evaluate the diagnostic potential of FES technique for the detection and characterization of normal and cancerous oral lesions in vivo. Fluorescence excitation (FE) spectra from oral mucosa were recorded in the spectral range of 340 to 600 nm at 635 nm emission using a fiberoptic probe spectrofluorometer to obtain spectra from the buccal mucosa of 30 sites of 15 healthy volunteers and 15 sites of 10 cancerous patients. Significant FE spectral differences were observed between normal and well differentiated squamous cell carcinoma (WDSCC) oral lesions. The FE spectra of healthy volunteers consists of a broad emission band around 440 to 470 nm, whereas in WDSCC lesions, a new primary peak was seen at 410 nm with secondary peaks observed at 505, 540, and 580 nm due to the accumulation of porphyrins in oral lesions. The FE spectral bands of the WDSCC lesions resemble the typical absorption spectra of a porphyrin. Three potential ratios (I410/I505, I410/I540, and I410/I580) were calculated from the FE spectra and used as input variables for a stepwise linear discriminant analysis (SLDA) for normal and WDSCC groups. Leave-one-out (LOO) method of cross-validation was performed to check the reliability on spectral data for tissue characterization. The diagnostic sensitivity and specificity were determined for normal and WDSCC lesions from the scatter plot of the discriminant function scores. It was observed that diagnostic algorithm based on discriminant function scores obtained by SLDA-LOO method was able to distinguish WDSCC from normal lesions with a sensitivity of 100% and specificity of 100%. Results of the pilot study demonstrate that the FE spectral changes due to porphyrin have a good diagnostic potential; therefore, porphyrin can be used as a native tumor marker.

Associations of multiple domains of self-esteem with four dimensions of stigma in schizophrenia

PubMed Central

Lysaker, Paul H.; Tsai, Jack; Yanos, Philip; Roe, David

2011-01-01

Research suggests global self-esteem among persons with schizophrenia may be negatively affected by stigma or stereotyped beliefs about persons with severe mental illness. Less clear however, is whether particular dimensions of self-esteem are linked to particular domains of stigma. To examine this we surveyed a range of self-esteem dimensions including lovability, personal power, competence and moral self-approval and four domains of stigma: Stereotype endorsement, Discrimination experience, Social withdrawal and Stigma rejection. Participants were 133 adults with diagnoses of schizophrenia or schizoaffective disorder. Stepwise multiple regressions controlling for a possible defensive response bias suggested that aspects of self-esteem related to lovability by others were more closely linked with lesser feelings of being alienated from others due to mental illness. Aspects of self-esteem related to the ability to manage one’s own affairs were more closely associated with the rejection of stereotypes of mental illness. A sense of being able to influence others was linked to both the absence of discrimination experiences and the ability to ward off stigma. Implications for treatment are discussed. PMID:18029145

Sex discrimination potential of buccolingual and mesiodistal tooth dimensions.

PubMed

Acharya, Ashith B; Mainali, Sneedha

2008-07-01

Tooth crown dimensions are reasonably accurate predictors of sex and are useful adjuncts in sex assessment. This study explores the utility of buccolingual (BL) and mesiodistal (MD) measurements in sex differentiation when used independently. BL and MD measurements of 28 teeth (third molars excluded) were obtained from a group of 53 Nepalese subjects (22 women and 31 men) aged 19-28 years. Stepwise discriminant analyses were undertaken separately for both types of tooth crown variables and their accuracy in sex classification compared with one another. MD dimensions had recognizably greater accuracy (77.4-83%) in sex identification than BL measurements (62.3-64.2%)--results that are consistent with previous reports. However, the accuracy of MD variables is not high enough to warrant their exclusive use in odontometric sex assessment--higher accuracy levels have been obtained when both types of dimensions were used concurrently, implying that BL variables contribute to sex assessment to some extent. Hence, it is inferred that optimal results in dental sex assessment are obtained when both MD and BL variables are used together.

Stepwise Iterative Fourier Transform: The SIFT

NASA Technical Reports Server (NTRS)

Benignus, V. A.; Benignus, G.

1975-01-01

A program, designed specifically to study the respective effects of some common data problems on results obtained through stepwise iterative Fourier transformation of synthetic data with known waveform composition, was outlined. Included in this group were the problems of gaps in the data, different time-series lengths, periodic but nonsinusoidal waveforms, and noisy (low signal-to-noise) data. Results on sinusoidal data were also compared with results obtained on narrow band noise with similar characteristics. The findings showed that the analytic procedure under study can reliably reduce data in the nature of (1) sinusoids in noise, (2) asymmetric but periodic waves in noise, and (3) sinusoids in noise with substantial gaps in the data. The program was also able to analyze narrow-band noise well, but with increased interpretational problems. The procedure was shown to be a powerful technique for analysis of periodicities, in comparison with classical spectrum analysis techniques. However, informed use of the stepwise procedure nevertheless requires some background of knowledge concerning characteristics of the biological processes under study.

Association between ICP pulse waveform morphology and ICP B waves.

PubMed

Kasprowicz, Magdalena; Bergsneider, Marvin; Czosnyka, Marek; Hu, Xiao

2012-01-01

The study aimed to investigate changes in the shape of ICP pulses associated with different patterns of the ICP slow waves (0.5-2.0 cycles/min) during ICP overnight monitoring in hydrocephalus. Four patterns of ICP slow waves were characterized in 44 overnight ICP recordings (no waves - NW, slow symmetrical waves - SW, slow asymmetrical waves - AS, slow waves with plateau phase - PW). The morphological clustering and analysis of ICP pulse (MOCAIP) algorithm was utilized to calculate a set of metrics describing ICP pulse morphology based on the location of three sub-peaks in an ICP pulse: systolic peak (P(1)), tidal peak (P(2)) and dicrotic peak (P(3)). Step-wise discriminant analysis was applied to select the most characteristic morphological features to distinguish between different ICP slow waves. Based on relative changes in variability of amplitudes of P(2) and P(3) we were able to distinguish between the combined groups NW + SW and AS + PW (p < 0.000001). The AS pattern can be differentiated from PW based on respective changes in the mean curvature of P(2) and P(3) (p < 0.000001); however, none of the MOCAIP feature separates between NW and SW. The investigation of ICP pulse morphology associated with different ICP B waves may provide additional information for analysing recordings of overnight ICP.

Coronary risk factors of angiographically assessed patients from Syria.

PubMed

al-Kateb, H; Zarzzour, W; Shameah, M; Juoma, M

1998-02-01

Predictors of coronary artery disease in an Arab population had not been defined well. We studied 192 male patients with suspected coronary artery disease, who underwent catheterization. We defined definite coronary artery disease as > 50% stenosis in any of three vessels. The effects of age, obesity, smoking, hypertension, diabetes, and lipid fractions were assessed by means of univariate and multivariate regression analysis. Coronary artery disease was present in 153 men (80%) and absent from 39 men. Patients without coronary artery disease were slightly younger, thinner, smoked less, and had lower cholesterol, low-density lipoprotein cholesterol, and apolipoprotein B levels than did those who had coronary artery disease. By stepwise regression analysis, the best discriminators were body mass index (P = 0.0004), age (P = 0.0005), smoking (P = 0.014) and the apolipoprotein B:A-I ratio (P = 0.041). The strongest Pearson correlation coefficients for coronary artery disease were the ratio of total: high-density lipoprotein cholesterol levels (r = 0.26), the apolipoprotein B:A-I ratio (r = 0.26), and age (r = 0.25), all P < 0.0005. In this angiographically evaluated Syrian population, previously recognized, well-known risk factors appeared. Obesity, smoking, hypertension, diabetes, and elevated lipid levels are all amenable to correction. Syria should adopt the same secondary prevention strategies as those currently being practiced by non-Arab countries.

Multivariate class modeling techniques applied to multielement analysis for the verification of the geographical origin of chili pepper.

PubMed

Naccarato, Attilio; Furia, Emilia; Sindona, Giovanni; Tagarelli, Antonio

2016-09-01

Four class-modeling techniques (soft independent modeling of class analogy (SIMCA), unequal dispersed classes (UNEQ), potential functions (PF), and multivariate range modeling (MRM)) were applied to multielement distribution to build chemometric models able to authenticate chili pepper samples grown in Calabria respect to those grown outside of Calabria. The multivariate techniques were applied by considering both all the variables (32 elements, Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Fe, Ga, La, Li, Mg, Mn, Na, Nd, Ni, Pb, Pr, Rb, Sc, Se, Sr, Tl, Tm, V, Y, Yb, Zn) and variables selected by means of stepwise linear discriminant analysis (S-LDA). In the first case, satisfactory and comparable results in terms of CV efficiency are obtained with the use of SIMCA and MRM (82.3 and 83.2% respectively), whereas MRM performs better than SIMCA in terms of forced model efficiency (96.5%). The selection of variables by S-LDA permitted to build models characterized, in general, by a higher efficiency. MRM provided again the best results for CV efficiency (87.7% with an effective balance of sensitivity and specificity) as well as forced model efficiency (96.5%). Copyright © 2016 Elsevier Ltd. All rights reserved.

A visual parallel-BCI speller based on the time-frequency coding strategy

NASA Astrophysics Data System (ADS)

Xu, Minpeng; Chen, Long; Zhang, Lixin; Qi, Hongzhi; Ma, Lan; Tang, Jiabei; Wan, Baikun; Ming, Dong

2014-04-01

Objective. Spelling is one of the most important issues in brain-computer interface (BCI) research. This paper is to develop a visual parallel-BCI speller system based on the time-frequency coding strategy in which the sub-speller switching among four simultaneously presented sub-spellers and the character selection are identified in a parallel mode. Approach. The parallel-BCI speller was constituted by four independent P300+SSVEP-B (P300 plus SSVEP blocking) spellers with different flicker frequencies, thereby all characters had a specific time-frequency code. To verify its effectiveness, 11 subjects were involved in the offline and online spellings. A classification strategy was designed to recognize the target character through jointly using the canonical correlation analysis and stepwise linear discriminant analysis. Main results. Online spellings showed that the proposed parallel-BCI speller had a high performance, reaching the highest information transfer rate of 67.4 bit min-1, with an average of 54.0 bit min-1 and 43.0 bit min-1 in the three rounds and five rounds, respectively. Significance. The results indicated that the proposed parallel-BCI could be effectively controlled by users with attention shifting fluently among the sub-spellers, and highly improved the BCI spelling performance.

Towards a truly mobile auditory brain-computer interface: exploring the P300 to take away.

PubMed

De Vos, Maarten; Gandras, Katharina; Debener, Stefan

2014-01-01

In a previous study we presented a low-cost, small, and wireless 14-channel EEG system suitable for field recordings (Debener et al., 2012, psychophysiology). In the present follow-up study we investigated whether a single-trial P300 response can be reliably measured with this system, while subjects freely walk outdoors. Twenty healthy participants performed a three-class auditory oddball task, which included rare target and non-target distractor stimuli presented with equal probabilities of 16%. Data were recorded in a seated (control condition) and in a walking condition, both of which were realized outdoors. A significantly larger P300 event-related potential amplitude was evident for targets compared to distractors (p<.001), but no significant interaction with recording condition emerged. P300 single-trial analysis was performed with regularized stepwise linear discriminant analysis and revealed above chance-level classification accuracies for most participants (19 out of 20 for the seated, 16 out of 20 for the walking condition), with mean classification accuracies of 71% (seated) and 64% (walking). Moreover, the resulting information transfer rates for the seated and walking conditions were comparable to a recently published laboratory auditory brain-computer interface (BCI) study. This leads us to conclude that a truly mobile auditory BCI system is feasible. © 2013.

A Hybrid Sensing Approach for Pure and Adulterated Honey Classification

PubMed Central

Subari, Norazian; Saleh, Junita Mohamad; Shakaff, Ali Yeon Md; Zakaria, Ammar

2012-01-01

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data. PMID:23202033

Stock structure of Lake Baikal omul as determined by whole-body morphology

USGS Publications Warehouse

Bronte, Charles R.; Fleischer, G.W.; Maistrenko, S.G.; Pronin, N.M.

1999-01-01

In Lake Baikal, three morphotypes of omul Coregonus autumnalis migratorius are recognized; the littoral, pelagic, and deep-water forms. Morphotype assignment is difficult, and similar to that encountered in pelagic and deep-water coregonines in the Laurentian Great Lakes. Principal component analysis revealed separation of all three morphotypes based on caudal peduncle length and depth, length and depth of the body between the dorsal and anal fin, and distance between the pectoral and the pelvic fins. Strong negative loadings were associated with head measurements. Omul of the same morphotype captured at different locations were classified to location of capture using step-wise discriminant function analysis. Jackknife correct classifications ranged from 43 to 78% for littoral omul from five locations, and 45–86% for pelagic omul from four locations. Patterns of location misclassification of littoral omul suggested that the sub-population structure, hence stock affinity, may be influenced by movements and intermixing of individuals among areas that are joined bathymetrically. Pelagic omul were more distinguishable by site and may support a previous hypothesis of a spawning-based rather than a foraging-based sub-population structure. Omul morphotypes may reflect adaptations to both ecological and local environmental conditions, and may have a genetic basis.

Analysis of brief language tests in the detection of cognitive decline and dementia

PubMed Central

Radanovic, Marcia; Carthery-Goulart, Maria Teresa; Charchat-Fichman, Helenice; Herrera Jr., Emílio; Lima, Edson Erasmo Pereira; Smid, Jerusa; Porto, Cláudia Sellitto; Nitrini, Ricardo

2007-01-01

Lexical access difficulties are frequent in normal aging and initial stages of dementia.Verbal fluency tests are valuable to detect cognitive decline, evidencing lexico-semantic and executive dysfunction. Objectives To establish which language tests can contribute in detecting dementia and to verify schooling influence on subject performance. Method 74 subjects: 33 controls, 17 Clinical Dementia Rating (CDR) 0.5 and 24 (Brief Cognitive Battery - BCB e Boston Naming Test - BNT) 1 were compared in tests of semantic verbal fluency (animal and fruit), picture naming (BCB and BNT) and the language items of Mini Mental State Examination (MMSE). Results There were significant differences between the control group and both CDR 0.5 and CDR 1 in all tests. Cut-off scores were: 11 and 10 for animal fluency, 8 for fruit fluency (in both), 8 and 9 for BCB naming. The CDR 0.5 group performed better than the CDR 1 group only in animal fluency. Stepwise multiple regression revealed fruit fluency, animal fluency and BCB naming as the best discriminators between patients and controls (specificity: 93.8%; sensitivity: 91.3%). In controls, comparison between illiterates and literates evidenced schooling influence in all tests, except for fruit fluency and BCB naming. In patients with dementia, only fruit fluency was uninfluenced by schooling. Conclusion The combination of verbal fluency tests in two semantic categories along with a simple picture naming test is highly sensitive in detecting cognitive decline. Comparison between literate and illiterate subjects shows a lesser degree of influence of schooling on the selected tests, thus improving discrimination between low performance and incipient cognitive decline. PMID:29213366

Uncovering of melanin fluorescence in human skin tissue

NASA Astrophysics Data System (ADS)

Scholz, Matthias; Stankovic, Goran; Seewald, Gunter; Leupold, Dieter

2007-07-01

Due to its extremely low fluorescence quantum yield, in the conventionally (one-photon) excited autofluorescence of skin tissue, melanin fluorescence is masked by several other endogenous and possibly also exogenous fluorophores (e.g. NADH, FAD, Porphyrins). A first step to enhance the melanin contribution had been realized by two-photon fs-pulse excitation in the red/near IR, based on the fact that melanin can be excited by stepwise two-photon absorption, whereas all other fluorophores in this spectral region allow only simultaneous two-photon excitation. Now, the next and decisive step has been realized: Using an extremely sensitive detection system, for the first time twophoton fluorescence of skin tissue excited with pulses in the ns-range could be measured. The motivation for this step was based on the fact that the population density of the fluorescent level resulting from a stepwise excitation has a different dependence of the pulse duration than that from a simultaneous excitation (Δt2 vs. Δt). Due to this strong discrimination between the fluorophores, practically pure melanin fluorescence can be obtained. Examples for in-vivo, ex-vivo as well as paraffin embedded skin tissue will be shown. The content of information with respect to early diagnosis of skin deseases will be discussed.

A survey of variable selection methods in two Chinese epidemiology journals

PubMed Central

2010-01-01

Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals. PMID:20920252

Identification of molecular markers associated with mite resistance in coconut (Cocos nucifera L.).

PubMed

Shalini, K V; Manjunatha, S; Lebrun, P; Berger, A; Baudouin, L; Pirany, N; Ranganath, R M; Prasad, D Theertha

2007-01-01

Coconut mite (Aceria guerreronis 'Keifer') has become a major threat to Indian coconut (Coçcos nucifera L.) cultivators and the processing industry. Chemical and biological control measures have proved to be costly, ineffective, and ecologically undesirable. Planting mite-resistant coconut cultivars is the most effective method of preventing yield loss and should form a major component of any integrated pest management stratagem. Coconut genotypes, and mite-resistant and -susceptible accessions were collected from different parts of South India. Thirty-two simple sequence repeat (SSR) and 7 RAPD primers were used for molecular analyses. In single-marker analysis, 9 SSR and 4 RAPD markers associated with mite resistance were identified. In stepwise multiple regression analysis of SSRs, a combination of 6 markers showed 100% association with mite infestation. Stepwise multiple regression analysis for RAPD data revealed that a combination of 3 markers accounted for 83.86% of mite resistance in the selected materials. Combined stepwise multiple regression analysis of RAPD and SSR data showed that a combination of 5 markers explained 100% of the association with mite resistance in coconut. Markers associated with mite resistance are important in coconut breeding programs and will facilitate the selection of mite-resistant plants at an early stage as well as mother plants for breeding programs.

An investigation of correlation between pilot scanning behavior and workload using stepwise regression analysis

NASA Technical Reports Server (NTRS)

Waller, M. C.

1976-01-01

An electro-optical device called an oculometer which tracks a subject's lookpoint as a time function has been used to collect data in a real-time simulation study of instrument landing system (ILS) approaches. The data describing the scanning behavior of a pilot during the instrument approaches have been analyzed by use of a stepwise regression analysis technique. A statistically significant correlation between pilot workload, as indicated by pilot ratings, and scanning behavior has been established. In addition, it was demonstrated that parameters derived from the scanning behavior data can be combined in a mathematical equation to provide a good representation of pilot workload.

Perception of Small Frequency Differences in Children with Auditory Processing Disorder or Specific Language Impairment.

PubMed

Rota-Donahue, Christine; Schwartz, Richard G; Shafer, Valerie; Sussman, Elyse S

2016-06-01

Frequency discrimination is often impaired in children developing language atypically. However, findings in the detection of small frequency changes in these children are conflicting. Previous studies on children's auditory perceptual abilities usually involved establishing differential sensitivity thresholds in sample populations who were not tested for auditory deficits. To date, there are no data comparing suprathreshold frequency discrimination ability in children tested for both auditory processing and language skills. : This study examined the perception of small frequency differences (∆ƒ) in children with auditory processing disorder (APD) and/or specific language impairment (SLI). The aim was to determine whether children with APD and children with SLI showed differences in their behavioral responses to frequency changes. Results were expected to identify different degrees of impairment and shed some light on the auditory perceptual overlap between pediatric APD and SLI. An experimental group design using a two-alternative forced-choice procedure was used to determine frequency discrimination ability for three magnitudes of ∆ƒ from the 1000-Hz base frequency. Thirty children between 10 years of age and 12 years, 11 months of age: 17 children with APD and/or SLI, and 13 typically developing (TD) peers participated. The clinical groups included four children with APD only, four children with SLI only, and nine children with both APD and SLI. Behavioral data collected using headphone delivery were analyzed using the sensitivity index d', calculated for three ∆ƒ was 2%, 5%, and 15% of the base frequency or 20, 50, and 150 Hz. Correlations between the dependent variable d' and the independent variables measuring auditory processing and language skills were also obtained. A stepwise regression analysis was then performed. TD children and children with APD and/or SLI differed in the detection of small-tone ∆ƒ. In addition, APD or SLI status affected behavioral results differently. Comparisons between auditory processing test scores or language test scores and the sensitivity index d' showed different strengths of correlation based on the magnitudes of the ∆ƒ. Auditory processing scores showed stronger correlation to the sensitivity index d' for the small ∆ƒ, while language scores showed stronger correlation to the sensitivity index d' for the large ∆ƒ. Although children with APD and/or SLI have difficulty with behavioral frequency discrimination, this difficulty may stem from two different levels: a basic auditory level for children with APD and a higher language processing level for children with SLI; the frequency discrimination performance seemed to be affected by the labeling demands of the same versus different frequency discrimination task for the children with SLI. American Academy of Audiology.

One-Step and Stepwise Magnification of a BOBBED LETHAL Chromosome in DROSOPHILA MELANOGASTER

PubMed Central

Endow, Sharyn A.; Komma, Donald J.

1986-01-01

Bobbed lethal (bbl) chromosomes carry too few ribosomal genes for homozygous flies to be viable. Reversion of bbl chromosomes to bb or nearly bb + occurs under magnifying conditions at a low frequency in a single generation. These reversions occur too rapidly to be accounted for by single unequal sister chromatid exchanges and seem unlikely to be due to multiple sister strand exchanges within a given cell lineage. Analysis of several one-step revertants indicates that they are X-Y recombinant chromosomes which probably arise from X-Y recombination at bb. The addition of ribosomal genes from the Y chromosome to the bbl chromosome explains the more rapid reversion of the bbl chromosome than is permitted by single events of unequal sister chromatid exchange. Analysis of stepwise bbl magnified chromosomes, which were selected over a period of 4–9 magnifying generations, shows ribosomal gene patterns that are closely similar to each other. Similarity in rDNA pattern among stepwise magnified products of the same parental chromosome is consistent with reversion by a mechanism of unequal sister strand exchange. PMID:3095184

Short Personality and Life Event scale for detection of suicide attempters.

PubMed

Artieda-Urrutia, Paula; Delgado-Gómez, David; Ruiz-Hernández, Diego; García-Vega, Juan Manuel; Berenguer, Nuria; Oquendo, Maria A; Blasco-Fontecilla, Hilario

2015-01-01

To develop a brief and reliable psychometric scale to identify individuals at risk for suicidal behaviour. Case-control study. 182 individuals (61 suicide attempters, 57 psychiatric controls, and 64 psychiatrically healthy controls) aged 18 or older, admitted to the Emergency Department at Puerta de Hierro University Hospital in Madrid, Spain. All participants completed a form including their socio-demographic and clinical characteristics, and the Personality and Life Events scale (27 items). To assess Axis I diagnoses, all psychiatric patients (including suicide attempters) were administered the Mini International Neuropsychiatric Interview. Descriptive statistics were computed for the socio-demographic factors. Additionally, χ(2) independence tests were applied to evaluate differences in socio-demographic and clinical variables, and the Personality and Life Events scale between groups. A stepwise linear regression with backward variable selection was conducted to build the Short Personality Life Event (S-PLE) scale. In order to evaluate the accuracy, a ROC analysis was conducted. The internal reliability was assessed using Cronbach's α, and the external reliability was evaluated using a test-retest procedure. The S-PLE scale, composed of just 6 items, showed good performance in discriminating between medical controls, psychiatric controls and suicide attempters in an independent sample. For instance, the S-PLE scale discriminated between past suicide and past non-suicide attempters with sensitivity of 80% and specificity of 75%. The area under the ROC curve was 88%. A factor analysis extracted only one factor, revealing a single dimension of the S-PLE scale. Furthermore, the S-PLE scale provides values of internal and external reliability between poor (test-retest: 0.55) and acceptable (Cronbach's α: 0.65) ranges. Administration time is about one minute. The S-PLE scale is a useful and accurate instrument for estimating the risk of suicidal behaviour in settings where the time is scarce. Copyright © 2015 SEP y SEPB. Published by Elsevier España. All rights reserved.

Gender differences in autism spectrum disorders: Divergence among specific core symptoms.

PubMed

Beggiato, Anita; Peyre, Hugo; Maruani, Anna; Scheid, Isabelle; Rastam, Maria; Amsellem, Frederique; Gillberg, Carina I; Leboyer, Marion; Bourgeron, Thomas; Gillberg, Christopher; Delorme, Richard

2017-04-01

Community-based studies have consistently shown a sex ratio heavily skewed towards males in autism spectrum disorders (ASD). The factors underlying this predominance of males are largely unknown, but the way girls score on standardized categorical diagnostic tools might account for the underrecognition of ASD in girls. Despite the existence of different norms for boys and girls with ASD on several major screening tests, the algorithm of the Autism Diagnosis Interview-Revised (ADI-R) has not been reformulated. The aim of our study was to investigate which ADI-R items discriminate between males and females, and to evaluate their weighting in the final diagnosis of autism. We then conducted discriminant analysis (DA) on a sample of 594 probands including 129 females with ASD, recruited by the Paris Autism Research International Sibpair (PARIS) Study. A replication analysis was run on an independent sample of 1716 probands including 338 females with ASD, recruited through the Autism Genetics Resource Exchange (AGRE) program. Entering the raw scores for all ADI-R items as independent variables, the DA correctly classified 78.9% of males and 72.9% of females (P < 0.001) in the PARIS cohort, and 72.2% of males and 68.3% of females (P < 0.0001) in the AGRE cohort. Among the items extracted by the stepwise DA, four belonged to the ADI-R algorithm used for the final diagnosis of ASD. In conclusion, several items of the ADI-R that are taken into account in the diagnosis of autism significantly differentiates between males and females. The potential gender bias thus induced may participate in the underestimation of the prevalence of ASD in females. Autism Res 2016,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 680-689. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

NASA Astrophysics Data System (ADS)

Prasad, S.; Bruce, L. M.

2007-04-01

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target recognition accuracies.

Suicidal ideation in outpatients with chronic musculoskeletal pain: an exploratory study of the role of sleep onset insomnia and pain intensity.

PubMed

Smith, Michael T; Perlis, Michael L; Haythornthwaite, Jennifer A

2004-01-01

Sleep disturbance, depression, and heightened risk of suicide are among the most clinically significant sequelae of chronic pain. While sleep disturbance is associated with suicidality in patients with major depression and is a significant independent predictor of completed suicide in psychiatric patients, it is not known whether sleep disturbance is associated with suicidal behavior in chronic pain. This exploratory study evaluates the importance of insomnia in discriminating suicidal ideation in chronic pain relative to depression severity and other pain-related factors. Fifty-one outpatients with non-cancer chronic pain were recruited. Subjects completed a pain and sleep survey, the Pittsburgh Sleep Quality Index, the Beck Depression Inventory, and the Multidimensional Pain Inventory. Subjects were classified as "suicidal ideators" or "non-ideators" based on their responses to BDI-Item 9 (Suicide). Bivariate analyses and multivariate discriminant function analyses were conducted. Twenty-four percent reported suicidal ideation (without intent). Suicidal ideators endorsed higher levels of: sleep onset insomnia, pain intensity, medication usage, pain-related interference, affective distress, and depressive symptoms (P < 0.03). These 6 variables were entered into stepwise discriminant function analyses. Two variables predicted group membership: Sleep Onset Insomnia Severity and Pain Intensity, respectively. The discriminant function correctly classified 84.3% of the cases (P < 0.0001). Chronic pain patients who self-reported severe and frequent initial insomnia with concomitant daytime dysfunction and high pain intensity were more likely to report passive suicidal ideation, independent from the effects of depression severity. Future research aimed at determining whether sleep disturbance is a modifiable risk factor for suicidal ideation in chronic pain is warranted.

Quantification of Cannabinoid Content in Cannabis

NASA Astrophysics Data System (ADS)

Tian, Y.; Zhang, F.; Jia, K.; Wen, M.; Yuan, Ch.

2015-09-01

Cannabis is an economically important plant that is used in many fields, in addition to being the most commonly consumed illicit drug worldwide. Monitoring the spatial distribution of cannabis cultivation and judging whether it is drug- or fiber-type cannabis is critical for governments and international communities to understand the scale of the illegal drug trade. The aim of this study was to investigate whether the cannabinoids content in cannabis could be spectrally quantified using a spectrometer and to identify the optimal wavebands for quantifying the cannabinoid content. Spectral reflectance data of dried cannabis leaf samples and the cannabis canopy were measured in the laboratory and in the field, respectively. Correlation analysis and the stepwise multivariate regression method were used to select the optimal wavebands for cannabinoid content quantification based on the laboratory-measured spectral data. The results indicated that the delta-9-tetrahydrocannabinol (THC) content in cannabis leaves could be quantified using laboratory-measured spectral reflectance data and that the 695 nm band is the optimal band for THC content quantification. This study provides prerequisite information for designing spectral equipment to enable immediate quantification of THC content in cannabis and to discriminate drug- from fiber-type cannabis based on THC content quantification in the field.

Changes in the free amino acid contents of honeys during storage at ambient temperature.

PubMed

Iglesias, M Teresa; Martín-Alvarez, Pedro J; Polo, M Carmen; de Lorenzo, Cristina; Gonzalez, Montserrat; Pueyo, Encarnación

2006-11-29

This study was carried out to establish the changes in the free amino acid contents of floral honeys, honeydew honeys, and blend honeys during storage at room temperature and to test the capacity of the amino acids to distinguish the origin of the honeys after storage. For this purpose, 54 artisanal honeys (39 floral, 5 honeydew, and 10 blend) were studied. Samples were taken from recently collected honeys and at 3, 6, 9, 12, 16, 20, and 24 months after harvesting. The contents of most of the free amino acids were found to decrease with storage time, with the greatest reduction observed in the first 9 months. The contents of the amino acids aspartic acid, beta-alanine, and proline increased in the first few months after storage, reaching maximum values at 6 months, suggesting the possible existence of enzymatic activities. The application of stepwise discriminant analysis to the free amino acid content data demonstrated that the contents of the amino acids valine, beta-alanine, gamma-aminobutyric acid, serine, isoleucine, alpha-alanine, ornithine, and glutamine correctly assigned 87% of honeys to their group of origin: floral, honeydew, or blend.

Heuristics to Facilitate Understanding of Discriminant Analysis.

ERIC Educational Resources Information Center

Van Epps, Pamela D.

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

Improving prediction of metal uptake by Chinese cabbage (Brassica pekinensis L.) based on a soil-plant stepwise analysis.

PubMed

Zhang, Sha; Song, Jing; Gao, Hui; Zhang, Qiang; Lv, Ming-Chao; Wang, Shuang; Liu, Gan; Pan, Yun-Yu; Christie, Peter; Sun, Wenjie

2016-11-01

It is crucial to develop predictive soil-plant transfer (SPT) models to derive the threshold values of toxic metals in contaminated arable soils. The present study was designed to examine the heavy metal uptake pattern and to improve the prediction of metal uptake by Chinese cabbage grown in agricultural soils with multiple contamination by Cd, Cu, Ni, Pb, and Zn. Pot experiments were performed with 25 historically contaminated soils to determine metal accumulation in different parts of Chinese cabbage. Different soil bioavailable metal fractions were determined using different extractants (0.43M HNO3, 0.01M CaCl2, 0.005M DTPA, and 0.01M LWMOAs), soil moisture samplers, and diffusive gradients in thin films (DGT), and the fractions were compared with shoot metal uptake using both direct and stepwise multiple regression analysis. The stepwise approach significantly improved the prediction of metal uptake by cabbage over the direct approach. Strongly pH dependent or nonlinear relationships were found for the adsorption of root surfaces and in root-shoot uptake processes. Metals were linearly translocated from the root surface to the root. Therefore, the nonlinearity of uptake pattern is an important explanation for the inadequacy of the direct approach in some cases. The stepwise approach offers an alternative and robust method to study the pattern of metal uptake by Chinese cabbage (Brassica pekinensis L.). Copyright © 2016. Published by Elsevier B.V.

Developing and Validating a Predictive Model for Stroke Progression

PubMed Central

Craig, L.E.; Wu, O.; Gilmour, H.; Barber, M.; Langhorne, P.

2011-01-01

Background Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Methods Two patient cohorts were used for this study – the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p < 0.1) on univariate analysis were included in the multivariate model. Logistic regression was the technique employed using backward stepwise regression to drop the least significant variables (p > 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Results Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72–0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50–0.92)]. Conclusion The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and calibration of the predictive model appear sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice. PMID:22566988

A modified GFP facilitates counting membrane protein subunits by step-wise photobleaching in Arabidopsis.

PubMed

Song, Kai; Xue, Yiqun; Wang, Xiaohua; Wan, Yinglang; Deng, Xin; Lin, Jinxing

2017-06-01

Membrane proteins exert functions by forming oligomers or molecular complexes. Currently, step-wise photobleaching has been applied to count the fluorescently labelled subunits in plant cells, for which an accurate and reliable control is required to distinguish individual subunits and define the basal fluorescence. However, the common procedure using immobilized GFP molecules is obviously not applicable for analysis in living plant cells. Using the spatial intensity distribution analysis (SpIDA), we found that the A206K mutation reduced the dimerization of GFP molecules. Further ectopic expression of Myristoyl-GFP A206K driven by the endogenous AtCLC2 promoter allowed imaging of individual molecules at a low expression level. As a result, the percentage of dimers in the transgenic pCLC2::Myristoyl-mGFP A206K line was significantly reduced in comparison to that of the pCLC2::Myristoyl-GFP line, confirming its application in defining the basal fluorescence intensity of GFP. Taken together, our results demonstrated that pCLC2::Myristoyl-mGFP A206K can be used as a standard control for monomer GFP, facilitating the analysis of the step-wise photobleaching of membrane proteins in Arabidopsis thaliana. Copyright © 2017 Elsevier GmbH. All rights reserved.

A Critical Analysis of Anti-Discrimination Law and Microaggressions in Academia

ERIC Educational Resources Information Center

Lukes, Robin; Bangs, Joann

2014-01-01

This article provides a critical analysis of microaggressions and anti-discrimination law in academia. There are many challenges for faculty claiming discrimination under current civil rights laws. Examples of microaggressions that fall outside of anti-discrimination law will be provided. Traditional legal analysis of discrimination will not end…

Performance of an attention-demanding task during treadmill walking shifts the noise qualities of step-to-step variation in step width.

PubMed

Grabiner, Mark D; Marone, Jane R; Wyatt, Marilynn; Sessoms, Pinata; Kaufman, Kenton R

2018-06-01

The fractal scaling evident in the step-to-step fluctuations of stepping-related time series reflects, to some degree, neuromotor noise. The primary purpose of this study was to determine the extent to which the fractal scaling of step width, step width and step width variability are affected by performance of an attention-demanding task. We hypothesized that the attention-demanding task would shift the structure of the step width time series toward white, uncorrelated noise. Subjects performed two 10-min treadmill walking trials, a control trial of undisturbed walking and a trial during which they performed a mental arithmetic/texting task. Motion capture data was converted to step width time series, the fractal scaling of which were determined from their power spectra. Fractal scaling decreased by 22% during the texting condition (p < 0.001) supporting the hypothesized shift toward white uncorrelated noise. Step width and step width variability increased 19% and five percent, respectively (p < 0.001). However, a stepwise discriminant analysis to which all three variables were input revealed that the control and dual task conditions were discriminated only by step width fractal scaling. The change of the fractal scaling of step width is consistent with increased cognitive demand and suggests a transition in the characteristics of the signal noise. This may reflect an important advance toward the understanding of the manner in which neuromotor noise contributes to some types of falls. However, further investigation of the repeatability of the results, the sensitivity of the results to progressive increases in cognitive load imposed by attention-demanding tasks, and the extent to which the results can be generalized to the gait of older adults seems warranted. Copyright © 2018 Elsevier B.V. All rights reserved.

Predicting the duration of sickness absence for patients with common mental disorders in occupational health care.

PubMed

Nieuwenhuijsen, Karen; Verbeek, Jos H A M; de Boer, Angela G E M; Blonk, Roland W B; van Dijk, Frank J H

2006-02-01

This study attempted to determine the factors that best predict the duration of absence from work among employees with common mental disorders. A cohort of 188 employees, of whom 102 were teachers, on sick leave with common mental disorders was followed for 1 year. Only information potentially available to the occupational physician during a first consultation was included in the predictive model. The predictive power of the variables was tested using Cox's regression analysis with a stepwise backward selection procedure. The hazard ratios (HR) from the final model were used to deduce a simple prediction rule. The resulting prognostic scores were then used to predict the probability of not returning to work after 3, 6, and 12 months. Calculating the area under the curve from the ROC (receiver operating characteristic) curve tested the discriminative ability of the prediction rule. The final Cox's regression model produced the following four predictors of a longer time until return to work: age older than 50 years [HR 0.5, 95% confidence interval (95% CI) 0.3-0.8], expectation of duration absence longer than 3 months (HR 0.5, 95% CI 0.3-0.8), higher educational level (HR 0.5, 95% CI 0.3-0.8), and diagnosis depression or anxiety disorder (HR 0.7, 95% CI 0.4-0.9). The resulting prognostic score yielded areas under the curves ranging from 0.68 to 0.73, which represent acceptable discrimination of the rule. A prediction rule based on four simple variables can be used by occupational physicians to identify unfavorable cases and to predict the duration of sickness absence.

Presurgical levels of circulating cell-derived microparticles discriminate between patients with and without transfusion in coronary artery bypass graft surgery.

PubMed

Jy, Wenche; Gómez-Marín, Orlando; Salerno, Tomas A; Panos, Anthony L; Williams, Donald; Horstman, Lawrence L; Ahn, Yeon S

2015-01-01

Improved understanding of presurgical risk factors for transfusions will lead to reduction in their number and related complications. The goal of this study is to identify these factors in coronary artery bypass graft (CABG) surgery. Presented herein are results of analyses of data from an ongoing study of transfusion in CABG surgery. Of 122 patients, 81 received transfusion (Tx) and 41 did not (NoTx). In addition to routine tests, presurgical levels of microparticles from platelets (PMPs), red cells (RMPs), and other lineages were assayed. The Tx and NoTx groups were similar with respect to most presurgical variables but differed in distribution of gender, blood type, diabetes prevalence, activated partial thromboplastin time (aPTT), hemoglobin (HGB), and microparticle levels. Stepwise multiple logistic regression was used to evaluate presurgical variables and to develop a model to assess risk factors for transfusion. CD41(+) PMP and CD235(+) RMP levels were found to be the main risk factors for transfusion. The Model's discriminating ability was assessed using receiver operating characteristic curve analysis, which showed that the area under the model curve (± standard error) was 0.86 ± 0.04 (95% confidence interval, 0.77-0.94). According to the model, patients with higher presurgical levels of circulating CD41(+) PMP, CD235a(+) RMP, and HGB, as well as a shorter aPTT, are less likely to receive transfusion(s). Presurgical levels of CD41(+) PMPs and CD235a(+) RMPs are the main risk factors for transfusion in CABG, followed by HGB and aPTT. Copyright © 2015 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Quantifying prognosis with risk predictions.

PubMed

Pace, Nathan L; Eberhart, Leopold H J; Kranke, Peter R

2012-01-01

Prognosis is a forecast, based on present observations in a patient, of their probable outcome from disease, surgery and so on. Research methods for the development of risk probabilities may not be familiar to some anaesthesiologists. We briefly describe methods for identifying risk factors and risk scores. A probability prediction rule assigns a risk probability to a patient for the occurrence of a specific event. Probability reflects the continuum between absolute certainty (Pi = 1) and certified impossibility (Pi = 0). Biomarkers and clinical covariates that modify risk are known as risk factors. The Pi as modified by risk factors can be estimated by identifying the risk factors and their weighting; these are usually obtained by stepwise logistic regression. The accuracy of probabilistic predictors can be separated into the concepts of 'overall performance', 'discrimination' and 'calibration'. Overall performance is the mathematical distance between predictions and outcomes. Discrimination is the ability of the predictor to rank order observations with different outcomes. Calibration is the correctness of prediction probabilities on an absolute scale. Statistical methods include the Brier score, coefficient of determination (Nagelkerke R2), C-statistic and regression calibration. External validation is the comparison of the actual outcomes to the predicted outcomes in a new and independent patient sample. External validation uses the statistical methods of overall performance, discrimination and calibration and is uniformly recommended before acceptance of the prediction model. Evidence from randomised controlled clinical trials should be obtained to show the effectiveness of risk scores for altering patient management and patient outcomes.

Normative data and discriminant validity of Rey's Verbal Learning Test for the Greek adult population.

PubMed

Messinis, Lambros; Tsakona, Ioanna; Malefaki, Sonia; Papathanasopoulos, Panagiotis

2007-08-01

The present study sought to establish normative and discriminant validity data for Rey's Auditory Verbal Learning Test [Rey, A. (1964). L 'examen clinique en psychologie [Clinical tests in psychology]. Paris: Presses Universitaires de France; Schmidt, M. (1996). Rey auditory verbal learning test: A handbook. Los Angeles, CA: Western Psychological Services] using newly adapted learning lists for the Greek adult population. Applying the procedure suggested by Geffen et al. [Geffen, G., Moar, K. J., O'Hanlon, A. P., Clark, C. R., & Geffen, L. N. (1990). Performance measures of 16-86-year-old males and females on the auditory verbal learning test. The Clinical Neuropsychologist, 4, 45-63] we administered the test to 205 healthy participants, aged 18-78 years and two adult patient groups (long-term cannabis users and HIV symptomatic patients). Stepwise linear regression analyses showed that the variables age, education and gender contributed significantly to most trials of the RAVLT. Performance decreased in an age-dependent manner from young adulthood. Women, young adults and higher educated participants outperformed men, older adults and less educated individuals. The test appears to discriminate adequately between the performance of long-term heavy cannabis users and HIV seropositive symptomatic patients and matched healthy controls, as both patient groups performed more poorly than their respective control group. Normative data stratified by age, gender and education for the Greek adult population is presented for use in research and clinical settings.

Volatile fraction composition and physicochemical parameters as tools for the differentiation of lemon blossom honey and orange blossom honey.

PubMed

Kadar, Melinda; Juan-Borrás, Marisol; Carot, Jose M; Domenech, Eva; Escriche, Isabel

2011-12-01

Volatile fraction profile and physicochemical parameters were studied with the aim of evaluating their effectiveness for the differentiation between lemon blossom honey (Citrus limon L.) and orange blossom honey (Citrus spp.). They would be useful complementary tools to the traditional analysis based on the percentage of pollen. A stepwise discriminant analysis constructed using 37 volatile compounds (extracted by purge and trap and analysed by gas chromatography-mass spectrometry), and physicochemical and colour parameters (diastase, conductivity, Pfund colour and CIE L a b) together provided a model that permitted the correct classification of 98.3% of the original and 96.6% of the cross-validated cases, indicating its efficiency and robustness. This model proved its effectiveness in the differentiation of both types of honey with another set of batches from the following year. This model, developed from the volatile compounds, physicochemical and colour parameters, has been useful for the differentiation of lemon and orange blossom honeys. Furthermore, it may be of particular interest for the attainment of a suitable classification of orange honey in which the pollen count is very low. These capabilities imply an evident marketing advantage for the beekeeping sector, since lemon blossom honey could be commercialized as unifloral honey and not as generic citrus honey and orange blossom honey could be correctly characterized. Copyright © 2011 Society of Chemical Industry.

Determinants of the half-turn with the ball in sub-elite youth soccer players.

PubMed

Zago, Matteo; Codari, Marina; Grilli, Massimo; Bellistri, Giuseppe; Lovecchio, Nicola; Sforza, Chiarella

2016-06-01

We explored the biomechanics of the 180° change-of-direction with the ball (half-turn) in soccer. We aimed at identifying movement strategies which enhance the players' half-turning performance, by characterising technique kinematics and understanding the structure of biomechanical and anthropometrics variables. Ten Under-13 sub-elite male players were recorded with an optoelectronic motion analyser while performing a 5-m straight dribbling followed by a half-turn with the sole. Joints kinematics differences between faster and slower trials were found in support-side hip rotation, driving-side hip adduction, trunk flexion and rotation, and arms abduction. To unveil the data-set structure, a principal component (PC) analysis and a stepwise linear discriminant analysis were performed using 30 biomechanical parameters and four anthropometric variables for each trial. Seven retained PCs explained 79% of the overall variability, featuring combinations of original variables that help in understanding the factors facilitating fast half-turns: keeping short steps, minimising lateral and forward body movements, and centre-of-mass lowering, even with ample lower limbs ranges of motion (RoM); abducting the upper limbs while limiting trunk flexion and pelvic inclination RoM. Balance and task-constrained exercises may be proposed to improve this technique. Moreover, a quantitative knowledge of the movement structure could give coaches objective insights to better instruct young players.

Potential use of stable isotope and fatty acid analyses for traceability of geographic origins of jumbo squid (Dosidicus gigas).

PubMed

Gong, Yi; Li, Yunkai; Chen, Xinjun; Chen, Ling

2018-04-15

Squid is an important seafood resource for Asian and European countries. With the continuous development of processed squid products, an effective traceability system has become increasingly prominent. Here, we attempt to trace the fishery products of the main target species, jumbo squid (Dosidicus gigas), by using biochemical tracers. Carbon and nitrogen isotope ratios (δ 13 C and δ 15 N values) and fatty acid profiles were identified in squid from three harvest locations in the eastern Pacific Ocean by isotope ratio mass spectrometry and gas chromatography/mass spectrometry, respectively. Comparative analysis was used to evaluate the geographic variations in tracers and to identify the suitable discriminatory variables among origins. Significant spatial variations were found in isotopic values and fatty acid profiles in squid muscle tissues, possibly because of different food availability and/or oceanographic conditions that each group experiences at a given location. The stepwise discriminant analysis indicated that δ 15 N, C16:1n7, C17:1n7, C18:2n6, C20:1 and C20:4n6 were effective variables at differentiating origin. Combined use of stable isotope ratios and fatty acid analyses could trace geographic origins of jumbo squid. This study provides an alternative approach for improving authenticity evaluation of commercial squid products. Copyright © 2018 John Wiley & Sons, Ltd.

Resource partitioning among forest owls in the River of No Return Wilderness, Idaho.

PubMed

Hayward, G D; Garton, E O

1988-03-01

We studied resource partitioning among the forest owls in the River of No Return Wilderness, Idaho, during the winter and spring of 1980 and 1981. The owl assemblage consisted of five abundant species: pygmy (Glaucidium gnoma), saw-whet (Aegolius acadicus), boreal (A. funereus), western screech (Otus kennicottii), and great-horned (Bubo virginianus). Long-eared (Asio otus) and flammulated (O. flammeolus) owls were rarely observed. Information from the literature supplemented our data to describe the pattern of resource partitioning. Stepwise discriminant function analysis and multivariate analysis of variance revealed differences in macrohabitat and microhabitat. The saw-whet, boreal, western screech, and great-horned owls all preferred mammalian prey but exhibited habitat differences. They also differed in activity periods and food habits. The pygmy owl, a food and habitat generalist, foraged diurnally more than the other species and took a higher proportion of brids. The flammulated owl used areas within the territories of other owl species but specialized on forest insects. The observed pattern of resource use was interpreted to result from environmental factors, morphological limitations and interspecific competition. Differences in food and activity time, we suggest, result from environmental factors and differences in owl morphology, while present-day interspecific competition may be important in shaping habitat use. Experiments will be necessary to determine the causal factors responsible for segregation among the forest owls.

Formation of intermediate products during the resonance stepwise polarization of dibenzyl ketone and benzil molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Polevoi, A.V.; Matyuk, V.M.; Grigor'eva, G.A.

1987-07-01

The processes resulting in the intramolecular redistribution of energy in electronically excited S/sub ..pi pi..*/ states of dibenzyl ketone and benzil molecules have been investigated by laser mass spectrometry. The decisive role of dissociation under the conditions of the resonance stepwise photoionization of these molecules upon excitation by radiation with lambda = 266 nm has been demonstrated. The ionization potentials of the molecules and the appearance potentials of fragment ions from dibenzyl ketone and benzil have been determined on the basis of an analysis of photoionization efficiency curves.

Characterization of bovine cartilage by fiber Bragg grating-based stress relaxation measurements

NASA Astrophysics Data System (ADS)

Baier, V.; Marchi, G.; Foehr, P.; Burgkart, R.; Roths, J.

2017-04-01

A fiber-based device for testing mechanical properties of cartilage is presented within this study. The measurement principle is based on stepwise indentation into the tissue and observing of corresponding relaxation of the stress. The indenter tip is constituted of a cleaved optical fiber that includes a fiber Bragg grating which is used as the force sensor. Stress relaxation measurements at 25 different positions on a healthy bovine cartilage sample were performed to assess the behavior of healthy cartilage. For each indentation step a good agreement was found with a viscoelastic model that included two time constants. The model parameters showed low variability and a clear dependence with indentation depth. The parameters can be used as reference values for discriminating healthy and degenerated cartilage.

Risk stratification personalised model for prediction of life-threatening ventricular tachyarrhythmias in patients with chronic heart failure.

PubMed

Frolov, Alexander Vladimirovich; Vaikhanskaya, Tatjana Gennadjevna; Melnikova, Olga Petrovna; Vorobiev, Anatoly Pavlovich; Guel, Ludmila Michajlovna

2017-01-01

The development of prognostic factors of life-threatening ventricular tachyarrhythmias (VTA) and sudden cardiac death (SCD) continues to maintain its priority and relevance in cardiology. The development of a method of personalised prognosis based on multifactorial analysis of the risk factors associated with life-threatening heart rhythm disturbances is considered a key research and clinical task. To design a prognostic and mathematical model to define personalised risk for life-threatening VTA in patients with chronic heart failure (CHF). The study included 240 patients with CHF (mean-age of 50.5 ± 12.1 years; left ventricular ejection fraction 32.8 ± 10.9%; follow-up period 36.8 ± 5.7 months). The participants received basic therapy for heart failure. The elec-trocardiogram (ECG) markers of myocardial electrical instability were assessed including microvolt T-wave alternans, heart rate turbulence, heart rate deceleration, and QT dispersion. Additionally, echocardiography and Holter monitoring (HM) were performed. The cardiovascular events were considered as primary endpoints, including SCD, paroxysmal ventricular tachycardia/ventricular fibrillation (VT/VF) based on HM-ECG data, and data obtained from implantable device interrogation (CRT-D, ICD) as well as appropriated shocks. During the follow-up period, 66 (27.5%) subjects with CHF showed adverse arrhythmic events, including nine SCD events and 57 VTAs. Data from a stepwise discriminant analysis of cumulative ECG-markers of myocardial electrical instability were used to make a mathematical model of preliminary VTA risk stratification. Uni- and multivariate Cox logistic regression analysis were performed to define an individualised risk stratification model of SCD/VTA. A binary logistic regression model demonstrated a high prognostic significance of discriminant function with a classification sensitivity of 80.8% and specificity of 99.1% (F = 31.2; c2 = 143.2; p < 0.0001). The method of personalised risk stratification using Cox logistic regression allows correct classification of more than 93.9% of CHF cases. A robust body of evidence concerning logistic regression prognostic significance to define VTA risk allows inclusion of this method into the algorithm of subsequent control and selection of the optimal treatment modality to treat patients with CHF.

Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Xu, Fuyun; Zhuang, Shidong; He, Changwei

2016-10-01

Heavy metal pollution in soils is one of the most critical problems in the global ecology and environment safety nowadays. Hyperspectral remote sensing and its application is capable of high speed, low cost, less risk and less damage, and provides a good method for detecting heavy metals in soil. This paper proposed a new idea of applying regression analysis of stepwise multiple regression between the spectral data and monitoring the amount of heavy metal Cr by sample points in soil for environmental protection. In the measurement, a FieldSpec HandHeld spectroradiometer is used to collect reflectance spectra of sample points over the wavelength range of 325-1075 nm. Then the spectral data measured by the spectroradiometer is preprocessed to reduced the influence of the external factors, and the preprocessed methods include first-order differential equation, second-order differential equation and continuum removal method. The algorithms of stepwise multiple regression are established accordingly, and the accuracy of each equation is tested. The results showed that the accuracy of first-order differential equation works best, which makes it feasible to predict the content of heavy metal Cr by using stepwise multiple regression.

Vapor permeation-stepwise injection simultaneous determination of methanol and ethanol in biodiesel with voltammetric detection.

PubMed

Shishov, Andrey; Penkova, Anastasia; Zabrodin, Andrey; Nikolaev, Konstantin; Dmitrenko, Maria; Ermakov, Sergey; Bulatov, Andrey

2016-02-01

A novel vapor permeation-stepwise injection (VP-SWI) method for the determination of methanol and ethanol in biodiesel samples is discussed. In the current study, stepwise injection analysis was successfully combined with voltammetric detection and vapor permeation. This method is based on the separation of methanol and ethanol from a sample using a vapor permeation module (VPM) with a selective polymer membrane based on poly(phenylene isophtalamide) (PA) containing high amounts of a residual solvent. After the evaporation into the headspace of the VPM, methanol and ethanol were transported, by gas bubbling, through a PA membrane to a mixing chamber equipped with a voltammetric detector. Ethanol was selectively detected at +0.19 V, and both compounds were detected at +1.20 V. Current subtractions (using a correction factor) were used for the selective determination of methanol. A linear range between 0.05 and 0.5% (m/m) was established for each analyte. The limits of detection were estimated at 0.02% (m/m) for ethanol and methanol. The sample throughput was 5 samples h(-1). The method was successfully applied to the analysis of biodiesel samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Predicting rheological behavior and baking quality of wheat flour using a GlutoPeak test.

PubMed

Rakita, Slađana; Dokić, Ljubica; Dapčević Hadnađev, Tamara; Hadnađev, Miroslav; Torbica, Aleksandra

2018-06-01

The purpose of this research was to gain an insight into the ability of the GlutoPeak instrument to predict flour functionality for bread making, as well as to determine which of the GlutoPeak parameters show the best potential in predicting dough rheological behavior and baking performance. Obtained results showed that GlutoPeak parameters correlated better with the indices of extensional rheological tests which consider constant dough hydration than with those which were performed at constant dough consistency. The GlutoPeak test showed that it is suitable for discriminating wheat varieties of good quality from those of poor quality, while the most discriminating index was maximum torque (MT). Moreover, MT value of 50 BU and aggregation energy value of 1,300 GPU were set as limits of wheat flour quality. The backward stepwise regression analysis revealed that a high-level prediction of indices which are highly affected by protein content (gluten content, flour water absorption, and dough tenacity) was achieved by using the GlutoPeak indices. Concerning bread quality, a moderate prediction of specific loaf volume and an intense level prediction of breadcrumb textural properties were accomplished by using the GlutoPeak parameters. The presented results indicated that the application of this quick test in wheat transformation chain for the assessment of baking quality would be useful. Baking test is considered as the most reliable method for assessing wheat-baking quality. However, baking test requires trained stuff, time, and large sample amount. These disadvantages have led to a growing demand to develop new rapid tests which would enable prediction of baked product quality with a limited flour size. Therefore, we tested the possibility of using a GlutoPeak tester to predict loaf volume and breadcrumb textural properties. Discrimination of wheat varieties according to quality with a restricted flour amount was also examined. Furthermore, we proposed the limit values of GlutoPeak parameters which would be highly beneficial for millers and bakers when determine suitability of flour for end-use. © 2017 Wiley Periodicals, Inc.

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery - part II: an illustrative example.

PubMed

Cevenini, Gabriele; Barbini, Emanuela; Scolletta, Sabino; Biagioli, Bonizella; Giomarelli, Pierpaolo; Barbini, Paolo

2007-11-22

Popular predictive models for estimating morbidity probability after heart surgery are compared critically in a unitary framework. The study is divided into two parts. In the first part modelling techniques and intrinsic strengths and weaknesses of different approaches were discussed from a theoretical point of view. In this second part the performances of the same models are evaluated in an illustrative example. Eight models were developed: Bayes linear and quadratic models, k-nearest neighbour model, logistic regression model, Higgins and direct scoring systems and two feed-forward artificial neural networks with one and two layers. Cardiovascular, respiratory, neurological, renal, infectious and hemorrhagic complications were defined as morbidity. Training and testing sets each of 545 cases were used. The optimal set of predictors was chosen among a collection of 78 preoperative, intraoperative and postoperative variables by a stepwise procedure. Discrimination and calibration were evaluated by the area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness-of-fit test, respectively. Scoring systems and the logistic regression model required the largest set of predictors, while Bayesian and k-nearest neighbour models were much more parsimonious. In testing data, all models showed acceptable discrimination capacities, however the Bayes quadratic model, using only three predictors, provided the best performance. All models showed satisfactory generalization ability: again the Bayes quadratic model exhibited the best generalization, while artificial neural networks and scoring systems gave the worst results. Finally, poor calibration was obtained when using scoring systems, k-nearest neighbour model and artificial neural networks, while Bayes (after recalibration) and logistic regression models gave adequate results. Although all the predictive models showed acceptable discrimination performance in the example considered, the Bayes and logistic regression models seemed better than the others, because they also had good generalization and calibration. The Bayes quadratic model seemed to be a convincing alternative to the much more usual Bayes linear and logistic regression models. It showed its capacity to identify a minimum core of predictors generally recognized as essential to pragmatically evaluate the risk of developing morbidity after heart surgery.

The National Early Warning Score (NEWS) for outcome prediction in emergency department patients with community-acquired pneumonia: results from a 6-year prospective cohort study

PubMed Central

Sbiti-Rohr, Diana; Kutz, Alexander; Christ-Crain, Mirjam; Thomann, Robert; Zimmerli, Werner; Hoess, Claus; Henzen, Christoph; Mueller, Beat; Schuetz, Philipp

2016-01-01

Objective To investigate the accuracy of the National Early Warning Score (NEWS) to predict mortality and adverse clinical outcomes for patients with community-acquired pneumonia (CAP) compared to standard risk scores such as the pneumonia severity index (PSI) and CURB-65. Design Secondary analysis of patients included in a previous randomised-controlled trial with a median follow-up of 6.1 years. Settings Patients with CAP included on admission to the emergency departments (ED) of 6 tertiary care hospitals in Switzerland. Participants A total of 925 patients with confirmed CAP were included. NEWS, PSI and CURB-65 scores were calculated on admission to the ED based on admission data. Main outcome measure Our primary outcome was all-cause mortality within 6 years of follow-up. Secondary outcomes were adverse clinical outcome defined as intensive care unit (ICU) admission, empyema and unplanned hospital readmission all occurring within 30 days after admission. We used regression models to study associations of baseline risk scores and outcomes with the area under the receiver operating curve (AUC) as a measure of discrimination. Results 6-year overall mortality was 45.1% (n=417) with a stepwise increase with higher NEWS categories. For 30 day and 6-year mortality prediction, NEWS showed only low discrimination (AUC 0.65 and 0.60) inferior compared to PSI and CURB-65. For prediction of ICU admission, NEWS showed moderate discrimination (AUC 0.73) and improved the prognostic accuracy of a regression model, including PSI (AUC from 0.66 to 0.74, p=0.001) and CURB-65 (AUC from 0.64 to 0.73, p=0.015). NEWS was also superior to PSI and CURB-65 for prediction of empyema, but did not well predict rehospitalisation. Conclusions NEWS provides additional prognostic information with regard to risk of ICU admission and complications and thereby improves traditional clinical-risk scores in the management of patients with CAP in the ED setting. Trial registration number ISRCTN95122877; Post-results. PMID:27683509

The National Early Warning Score (NEWS) for outcome prediction in emergency department patients with community-acquired pneumonia: results from a 6-year prospective cohort study.

PubMed

Sbiti-Rohr, Diana; Kutz, Alexander; Christ-Crain, Mirjam; Thomann, Robert; Zimmerli, Werner; Hoess, Claus; Henzen, Christoph; Mueller, Beat; Schuetz, Philipp

2016-09-28

To investigate the accuracy of the National Early Warning Score (NEWS) to predict mortality and adverse clinical outcomes for patients with community-acquired pneumonia (CAP) compared to standard risk scores such as the pneumonia severity index (PSI) and CURB-65. Secondary analysis of patients included in a previous randomised-controlled trial with a median follow-up of 6.1 years. Patients with CAP included on admission to the emergency departments (ED) of 6 tertiary care hospitals in Switzerland. A total of 925 patients with confirmed CAP were included. NEWS, PSI and CURB-65 scores were calculated on admission to the ED based on admission data. Our primary outcome was all-cause mortality within 6 years of follow-up. Secondary outcomes were adverse clinical outcome defined as intensive care unit (ICU) admission, empyema and unplanned hospital readmission all occurring within 30 days after admission. We used regression models to study associations of baseline risk scores and outcomes with the area under the receiver operating curve (AUC) as a measure of discrimination. 6-year overall mortality was 45.1% (n=417) with a stepwise increase with higher NEWS categories. For 30 day and 6-year mortality prediction, NEWS showed only low discrimination (AUC 0.65 and 0.60) inferior compared to PSI and CURB-65. For prediction of ICU admission, NEWS showed moderate discrimination (AUC 0.73) and improved the prognostic accuracy of a regression model, including PSI (AUC from 0.66 to 0.74, p=0.001) and CURB-65 (AUC from 0.64 to 0.73, p=0.015). NEWS was also superior to PSI and CURB-65 for prediction of empyema, but did not well predict rehospitalisation. NEWS provides additional prognostic information with regard to risk of ICU admission and complications and thereby improves traditional clinical-risk scores in the management of patients with CAP in the ED setting. ISRCTN95122877; Post-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Acquisition of thermotolerant yeast Saccharomyces cerevisiae by breeding via stepwise adaptation.

PubMed

Satomura, Atsushi; Katsuyama, Yoshiaki; Miura, Natsuko; Kuroda, Kouichi; Tomio, Ayako; Bamba, Takeshi; Fukusaki, Eiichiro; Ueda, Mitsuyoshi

2013-01-01

A thermotolerant Saccharomyces cerevisiae yeast strain, YK60-1, was bred from a parental strain, MT8-1, via stepwise adaptation. YK60-1 grew at 40°C, a temperature at which MT8-1 could not grow at all. YK60-1 exhibited faster growth than MT8-1 at 30°C. To investigate the mechanisms how MT8-1 acquired thermotolerance, DNA microarray analysis was performed. The analysis revealed the induction of stress-responsive genes such as those encoding heat shock proteins and trehalose biosynthetic enzymes in YK60-1. Furthermore, nontargeting metabolome analysis showed that YK60-1 accumulated more trehalose, a metabolite that contributes to stress tolerance in yeast, than MT8-1. In conclusion, S. cerevisiae MT8-1 acquired thermotolerance by induction of specific stress-responsive genes and enhanced intracellular trehalose levels. © 2013 American Institute of Chemical Engineers.

Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhao, Jianhua; Zeng, Haishan; Kalia, Sunil; Lui, Harvey

2017-02-01

Background: Raman spectroscopy is a non-invasive optical technique which can measure molecular vibrational modes within tissue. A large-scale clinical study (n = 518) has demonstrated that real-time Raman spectroscopy could distinguish malignant from benign skin lesions with good diagnostic accuracy; this was validated by a follow-up independent study (n = 127). Objective: Most of the previous diagnostic algorithms have typically been based on analyzing the full band of the Raman spectra, either in the fingerprint or high wavenumber regions. Our objective in this presentation is to explore wavenumber selection based analysis in Raman spectroscopy for skin cancer diagnosis. Methods: A wavenumber selection algorithm was implemented using variably-sized wavenumber windows, which were determined by the correlation coefficient between wavenumbers. Wavenumber windows were chosen based on accumulated frequency from leave-one-out cross-validated stepwise regression or least and shrinkage selection operator (LASSO). The diagnostic algorithms were then generated from the selected wavenumber windows using multivariate statistical analyses, including principal component and general discriminant analysis (PC-GDA) and partial least squares (PLS). A total cohort of 645 confirmed lesions from 573 patients encompassing skin cancers, precancers and benign skin lesions were included. Lesion measurements were divided into training cohort (n = 518) and testing cohort (n = 127) according to the measurement time. Result: The area under the receiver operating characteristic curve (ROC) improved from 0.861-0.891 to 0.891-0.911 and the diagnostic specificity for sensitivity levels of 0.99-0.90 increased respectively from 0.17-0.65 to 0.20-0.75 by selecting specific wavenumber windows for analysis. Conclusion: Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels.

Influence of storage conditions on the stability of monomeric anthocyanins studied by reversed-phase high-performance liquid chromatography.

PubMed

Morais, Helena; Ramos, Cristina; Forgács, Esther; Cserháti, Tibor; Oliviera, José

2002-04-25

The effect of light, storage time and temperature on the decomposition rate of monomeric anthocyanin pigments extracted from skins of grape (Vitis vinifera var. Red globe) was determined by reversed-phase high-performance liquid chromatography (RP-HPLC). The impact of various storage conditions on the pigment stability was assessed by stepwise regression analysis. RP-HPLC separated well the five anthocyanins identified and proved the presence of other unidentified pigments at lower concentrations. Stepwise regression analysis confirmed that the overall decomposition rate of monomeric anthocyanins, peonidin-3-glucoside and malvidin-3-glucoside significantly depended on the time and temperature of storage, the effect of storage time being the most important. The presence or absence of light exerted a negligible impact on the decomposition rate.

Molecular Analysis of Primary Vapor and Char Products during Stepwise Pyrolysis of Poplar Biomass

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, Roger W.; Reinot, Tonu; McClelland, John F.

2010-08-03

Pyrolysis of biomass produces both pyrolysis oil and solid char. In this study, poplar has been pyrolyzed in a stepwise fashion over a series of temperatures from 200 to 500°C, and both the primary products contributing to pyrolysis oil and the changes in the pyrolyzing poplar surface leading toward char have been characterized at each step. The primary products were identified by direct analysis in real time (DART) mass spectrometry, and the changes in the poplar surface were monitored using Fourier transform infrared (FTIR) photoacoustic spectroscopy, with a sampling depth of a few micrometers. The primary products from pyrolyzing cellulose,more » xylan, and lignin under similar conditions were also characterized to identify the sources of the poplar products.« less

Molecular Analysis of Primary Vapor and Char Products during Stepwise Pyrolysis of Poplar Biomass

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, Roger W.; Reinot, Tonu; McClelland, John F.

2010-08-30

Pyrolysis of biomass produces both pyrolysis oil and solid char. In this study, poplar has been pyrolyzed in a stepwise fashion over a series of temperatures from 200 to 500 C, and both the primary products contributing to pyrolysis oil and the changes in the pyrolyzing poplar surface leading toward char have been characterized at each step. The primary products were identified by direct analysis in real time (DART) mass spectrometry, and the changes in the poplar surface were monitored using Fourier transform infrared (FTIR) photoacoustic spectroscopy, with a sampling depth of a few micrometers. The primary products from pyrolyzingmore » cellulose, xylan, and lignin under similar conditions were also characterized to identify the sources of the poplar products.« less

Legitimating Racial Discrimination: Emotions, Not Beliefs, Best Predict Discrimination in a Meta-Analysis

PubMed Central

Talaska, Cara A.; Chaiken, Shelly

2013-01-01

Investigations of racial bias have emphasized stereotypes and other beliefs as central explanatory mechanisms and as legitimating discrimination. In recent theory and research, emotional prejudices have emerged as another, more direct predictor of discrimination. A new comprehensive meta-analysis of 57 racial attitude-discrimination studies finds a moderate relationship between overall attitudes and discrimination. Emotional prejudices are twices as closely related to racial discrimination as stereotypes and beliefs are. Moreover, emotional prejudices are closely related to both observed and self-reported discrimination, whereas stereotypes and beliefs are related only to self-reported discrimination. Implications for justifying discrimination are discussed. PMID:24052687

School-age effects of the newborn individualized developmental care and assessment program for preterm infants with intrauterine growth restriction: preliminary findings

PubMed Central

2013-01-01

Background The experience in the newborn intensive care nursery results in premature infants’ neurobehavioral and neurophysiological dysfunction and poorer brain structure. Preterms with severe intrauterine growth restriction are doubly jeopardized given their compromised brains. The Newborn Individualized Developmental Care and Assessment Program improved outcome at early school-age for preterms with appropriate intrauterine growth. It also showed effectiveness to nine months for preterms with intrauterine growth restriction. The current study tested effectiveness into school-age for preterms with intrauterine growth restriction regarding executive function (EF), electrophysiology (EEG) and neurostructure (MRI). Methods Twenty-three 9-year-old former growth-restricted preterms, randomized at birth to standard care (14 controls) or to the Newborn Individualized Developmental Care and Assessment Program (9 experimentals) were assessed with standardized measures of cognition, achievement, executive function, electroencephalography, and magnetic resonance imaging. The participating children were comparable to those lost to follow-up, and the controls to the experimentals, in terms of newborn background health and demographics. All outcome measures were corrected for mother’s intelligence. Analysis techniques included two-group analysis of variance and stepwise discriminate analysis for the outcome measures, Wilks’ lambda and jackknifed classification to ascertain two-group classification success per and across domains; canonical correlation analysis to explore relationships among neuropsychological, electrophysiological and neurostructural domains at school-age, and from the newborn period to school-age. Results Controls and experimentals were comparable in age at testing, anthropometric and health parameters, and in cognitive and achievement scores. Experimentals scored better in executive function, spectral coherence, and cerebellar volumes. Furthermore, executive function, spectral coherence and brain structural measures discriminated controls from experimentals. Executive function correlated with coherence and brain structure measures, and with newborn-period neurobehavioral assessment. Conclusion The intervention in the intensive care nursery improved executive function as well as spectral coherence between occipital and frontal as well as parietal regions. The experimentals’ cerebella were significantly larger than the controls’. These results, while preliminary, point to the possibility of long-term brain improvement even of intrauterine growth compromised preterms if individualized intervention begins with admission to the NICU and extends throughout transition home. Larger sample replications are required in order to confirm these results. Clinical trial registration The study is registered as a clinical trial. The trial registration number is NCT00914108. PMID:23421857

School-age effects of the newborn individualized developmental care and assessment program for preterm infants with intrauterine growth restriction: preliminary findings.

PubMed

McAnulty, Gloria; Duffy, Frank H; Kosta, Sandra; Weisenfeld, Neil I; Warfield, Simon K; Butler, Samantha C; Alidoost, Moona; Bernstein, Jane Holmes; Robertson, Richard; Zurakowski, David; Als, Heidelise

2013-02-19

The experience in the newborn intensive care nursery results in premature infants' neurobehavioral and neurophysiological dysfunction and poorer brain structure. Preterms with severe intrauterine growth restriction are doubly jeopardized given their compromised brains. The Newborn Individualized Developmental Care and Assessment Program improved outcome at early school-age for preterms with appropriate intrauterine growth. It also showed effectiveness to nine months for preterms with intrauterine growth restriction. The current study tested effectiveness into school-age for preterms with intrauterine growth restriction regarding executive function (EF), electrophysiology (EEG) and neurostructure (MRI). Twenty-three 9-year-old former growth-restricted preterms, randomized at birth to standard care (14 controls) or to the Newborn Individualized Developmental Care and Assessment Program (9 experimentals) were assessed with standardized measures of cognition, achievement, executive function, electroencephalography, and magnetic resonance imaging. The participating children were comparable to those lost to follow-up, and the controls to the experimentals, in terms of newborn background health and demographics. All outcome measures were corrected for mother's intelligence. Analysis techniques included two-group analysis of variance and stepwise discriminate analysis for the outcome measures, Wilks' lambda and jackknifed classification to ascertain two-group classification success per and across domains; canonical correlation analysis to explore relationships among neuropsychological, electrophysiological and neurostructural domains at school-age, and from the newborn period to school-age. Controls and experimentals were comparable in age at testing, anthropometric and health parameters, and in cognitive and achievement scores. Experimentals scored better in executive function, spectral coherence, and cerebellar volumes. Furthermore, executive function, spectral coherence and brain structural measures discriminated controls from experimentals. Executive function correlated with coherence and brain structure measures, and with newborn-period neurobehavioral assessment. The intervention in the intensive care nursery improved executive function as well as spectral coherence between occipital and frontal as well as parietal regions. The experimentals' cerebella were significantly larger than the controls'. These results, while preliminary, point to the possibility of long-term brain improvement even of intrauterine growth compromised preterms if individualized intervention begins with admission to the NICU and extends throughout transition home. Larger sample replications are required in order to confirm these results. The study is registered as a clinical trial. The trial registration number is NCT00914108.

Predicting death from kala-azar: construction, development, and validation of a score set and accompanying software.

PubMed

Costa, Dorcas Lamounier; Rocha, Regina Lunardi; Chaves, Eldo de Brito Ferreira; Batista, Vivianny Gonçalves de Vasconcelos; Costa, Henrique Lamounier; Costa, Carlos Henrique Nery

2016-01-01

Early identification of patients at higher risk of progressing to severe disease and death is crucial for implementing therapeutic and preventive measures; this could reduce the morbidity and mortality from kala-azar. We describe a score set composed of four scales in addition to software for quick assessment of the probability of death from kala-azar at the point of care. Data from 883 patients diagnosed between September 2005 and August 2008 were used to derive the score set, and data from 1,031 patients diagnosed between September 2008 and November 2013 were used to validate the models. Stepwise logistic regression analyses were used to derive the optimal multivariate prediction models. Model performance was assessed by its discriminatory accuracy. A computational specialist system (Kala-Cal(r)) was developed to speed up the calculation of the probability of death based on clinical scores. The clinical prediction score showed high discrimination (area under the curve [AUC] 0.90) for distinguishing death from survival for children ≤2 years old. Performance improved after adding laboratory variables (AUC 0.93). The clinical score showed equivalent discrimination (AUC 0.89) for older children and adults, which also improved after including laboratory data (AUC 0.92). The score set also showed a high, although lower, discrimination when applied to the validation cohort. This score set and Kala-Cal(r) software may help identify individuals with the greatest probability of death. The associated software may speed up the calculation of the probability of death based on clinical scores and assist physicians in decision-making.

Hormonally active agents in the environment and children's behavior: assessing effects on children's gender-dimorphic outcomes.

PubMed

Sandberg, David E; Vena, John E; Weiner, John; Beehler, Gregory P; Swanson, Mya; Meyer-Bahlburg, Heino F L

2003-03-01

Early sex hormone exposure contributes to gender-dimorphic behavioral development in mammals, including humans. Environmental toxicants concentrated in contaminated sport fish can interfere with the actions of sex steroids. This study developed an outcome variable by combining gender-dimorphic behaviors that differentiates boys and girls. Offspring of participants in the New York State Angler Cohort Study (NYSACS) were targeted in a parent-report postal survey. Instruments were selected based on findings of gender differences in the general population. A linear discriminant function model incorporating three gender behavior scales correctly classified the sex of 97.7% of children (252 boys and 234 girls) from a random NYSACS sample. The discriminant function was cross-validated by correctly classifying the sex of 98.4% of children (457 boys and 425 girls) from the remaining NYSACS cases and 97.6% of children (154 boys and 142 girls) from an independent school sample. Within-sex stepwise multiple regression analyses revealed that masculine behavior increased among boys with age and with the number of years of maternal sport fish consumption. In girls, older age and previous live-born siblings were associated with more masculine behavior, whereas feminine behavior increased with the duration of breast feeding. These associations were replicated in an independent sample. A linear discriminant function effectively transformed the binary classification of sex (male-female) to a bipolar continuum of gender (masculinity-femininity). Findings from this study are consistent with the hypothesis that environmental contaminants contribute to shifts in gender-role behavior. Future investigations will need to account for competing explanations of this effect.

Color Trails Test: normative data and criterion validity for the greek adult population.

PubMed

Messinis, Lambros; Malegiannaki, Amaryllis-Chryssi; Christodoulou, Tessa; Panagiotopoulos, Vassillis; Papathanasopoulos, Panagiotis

2011-06-01

The Color Trails Test (CTT) was developed as a culturally fair analog of the Trail Making Test. In the present study, normative data for the CTT were developed for the Greek adult population and further the criterion validity of the CTT was examined in two clinical groups (29 Parkinson's disease [PD] and 25 acute stroke patients). The instrument was applied to 163 healthy participants, aged 19-75. Stepwise linear regression analyses revealed a significant influence of age and education level on completion time in both parts of the CTT (increased age and decreased educational level contributed to slower completion times for both parts), whereas gender did not influence time to completion of part B. Further, the CTT appears to discriminate adequately between the performance of PD and acute stroke patients and matched healthy controls.

Physical disability, life stress, and psychosocial adjustment in multiple sclerosis.

PubMed

Zeldow, P B; Pavlou, M

1984-02-01

Eighty-one outpatients with diagnosed multiple sclerosis were studied in an effort to examine the relative contributions of physical health status, life stress, duration of illness, age, sex, marital status, and social class on various aspects of personal and interpersonal functioning. Stepwise multiple regression analyses were performed to identify the most significant discriminators of the seven psychosocial measures. Physical health status exerted the broadest influence, affecting personal efficiency and well-being, capacity for independent thought and action, self-confidence, self-reliance, and number of meaningful social contacts. Life stress was associated with lowered personal efficiency and sense of well-being. Duration of illness and the demographic variables had few or no effects on psychosocial adjustment. Discussion contrasts the present findings with others in the rehabilitation literature and specifies certain limitations of the study's design.

Stepwise pumping approach to improve free phase light hydrocarbon recovery from unconfined aquifers

NASA Astrophysics Data System (ADS)

Cooper, Grant S.; Peralta, Richard C.; Kaluarachchi, Jagath J.

1995-04-01

A stepwise, time-varying pumping approach is developed to improve free phase oil recovery of light non-aqueous phase liquids (LNAPL) from a homogeneous, unconfined aquifer. Stepwise pumping is used to contain the floating oil plume and obtain efficient free oil recovery. The graphical plots. The approach uses ARMOS ©, an areal two-dimensional multiphase flow, finite-element simulation model. Systematic simulations of free oil area changes to pumping rates are analyzed. Pumping rates are determined that achieve LNAPL plume containment at different times (i.e. 90, 180 and 360 days) for a planning period of 360 days. These pumping rates are used in reverse order as a stepwise (monotonically increasing) pumping strategy. This stepwise pumping strategy is analyzed further by performing additional simulations at different pumping rates for the last pumping period. The final stepwise pumping strategy is varied by factors of -25% and +30% to evaluate sensitivity in the free oil recovery process. Stepwise pumping is compared to steady pumping rates to determine the best free oil recovery strategy. Stepwise pumping is shown to improve oil recovery by increasing recoveredoil volume (11%) and decreasing residual oil (15%) when compared with traditional steady pumping strategies. The best stepwise pumping strategy recovers more free oil by reducing the amount of residual oil left in the system due to pumping drawdown. This stepwise pumping pproach can be used to enhance free oil recovery and provide for cost-effective design and management of LNAPL cleanup.

Biometric parameters in different stages of primary angle closure using low-coherence interferometry.

PubMed

Yazdani, Shahin; Akbarian, Shadi; Pakravan, Mohammad; Doozandeh, Azadeh; Afrouzifar, Mohsen

2015-03-01

To compare ocular biometric parameters using low-coherence interferometry among siblings affected with different degrees of primary angle closure (PAC). In this cross-sectional comparative study, a total of 170 eyes of 86 siblings from 47 families underwent low-coherence interferometry (LenStar 900; Haag-Streit, Koeniz, Switzerland) to determine central corneal thickness, anterior chamber depth (ACD), aqueous depth (AD), lens thickness (LT), vitreous depth, and axial length (AL). Regression coefficients were applied to show the trend of the measured variables in different stages of angle closure. To evaluate the discriminative power of the parameters, receiver operating characteristic curves were used. Best cutoff points were selected based on the Youden index. Sensitivity, specificity, positive and negative predicative values, positive and negative likelihood ratios, and diagnostic accuracy were determined for each variable. All biometric parameters changed significantly from normal eyes to PAC suspects, PAC, and PAC glaucoma; there was a significant stepwise decrease in central corneal thickness, ACD, AD, vitreous depth, and AL, and an increase in LT and LT/AL. Anterior chamber depth and AD had the best diagnostic power for detecting angle closure; best levels of sensitivity and specificity were obtained with cutoff values of 3.11 mm for ACD and 2.57 mm for AD. Biometric parameters measured by low-coherence interferometry demonstrated a significant and stepwise change among eyes affected with various degrees of angle closure. Although the current classification scheme for angle closure is based on anatomical features, it has excellent correlation with biometric parameters.

Response kinetics of tethered bacteria to stepwise changes in nutrient concentration.

PubMed

Chernova, Anna A; Armitage, Judith P; Packer, Helen L; Maini, Philip K

2003-09-01

We examined the changes in swimming behaviour of the bacterium Rhodobacter sphaeroides in response to stepwise changes in a nutrient (propionate), following the pre-stimulus motion, the initial response and the adaptation to the sustained concentration of the chemical. This was carried out by tethering motile cells by their flagella to glass slides and following the rotational behaviour of their cell bodies in response to the nutrient change. Computerised motion analysis was used to analyse the behaviour. Distributions of run and stop times were obtained from rotation data for tethered cells. Exponential and Weibull fits for these distributions, and variability in individual responses are discussed. In terms of parameters derived from the run and stop time distributions, we compare the responses to stepwise changes in the nutrient concentration and the long-term behaviour of 84 cells under 12 propionate concentration levels from 1 nM to 25 mM. We discuss traditional assumptions for the random walk approximation to bacterial swimming and compare them with the observed R. sphaeroides motile behaviour.

Prediction of troponin-T degradation using color image texture features in 10d aged beef longissimus steaks.

PubMed

Sun, X; Chen, K J; Berg, E P; Newman, D J; Schwartz, C A; Keller, W L; Maddock Carlin, K R

2014-02-01

The objective was to use digital color image texture features to predict troponin-T degradation in beef. Image texture features, including 88 gray level co-occurrence texture features, 81 two-dimension fast Fourier transformation texture features, and 48 Gabor wavelet filter texture features, were extracted from color images of beef strip steaks (longissimus dorsi, n = 102) aged for 10d obtained using a digital camera and additional lighting. Steaks were designated degraded or not-degraded based on troponin-T degradation determined on d 3 and d 10 postmortem by immunoblotting. Statistical analysis (STEPWISE regression model) and artificial neural network (support vector machine model, SVM) methods were designed to classify protein degradation. The d 3 and d 10 STEPWISE models were 94% and 86% accurate, respectively, while the d 3 and d 10 SVM models were 63% and 71%, respectively, in predicting protein degradation in aged meat. STEPWISE and SVM models based on image texture features show potential to predict troponin-T degradation in meat. © 2013.

Characterization of subarctic vegetation using ground based remote sensing methods

NASA Astrophysics Data System (ADS)

Finnell, D.; Garnello, A.; Palace, M. W.; Sullivan, F.; Herrick, C.; Anderson, S. M.; Crill, P. M.; Varner, R. K.

2014-12-01

Stordalen mire is located at 68°21'N and 19°02'E in the Swedish subarctic. Climate monitoring has revealed a warming trend spanning the past 150 years affecting the mires ability to hold stable palsa/hummock mounds. The micro-topography of the landscape has begun to degrade into thaw ponds changing the vegetation cover from ombrothrophic to minerotrophic. Hummocks are ecologically important due to their ability to act as a carbon sinks. Thaw ponds and sphagnum rich transitional zones have been documented as sources of atmospheric CH4. An objective of this project is to determine if a high resolution three band camera (RGB) and a RGNIR camera could detect differences in vegetation over five different site types. Species composition was collected for 50 plots with ten repetitions for each site type: palsa/hummock, tall shrub, semi-wet, tall graminoid, and wet. Sites were differentiated based on dominating species and features consisting of open water presence, sphagnum spp. cover, graminoid spp. cover, or the presence of dry raised plateaus/mounds. A pole based camera mount was used to collect images at a height of ~2.44m from the ground. The images were cropped in post-processing to fit a one-square meter quadrat. Texture analysis was performed on all images, including entropy, lacunarity, and angular second momentum. Preliminary results suggested that site type influences the number of species present. The p-values for the ability to predict site type using a t-test range from <0.0001 to 0.0461. A stepwise discriminant analysis on site type vs. texture yielded a 10% misclassification rate. Through the use of a stepwise regression of texture variables, actual vs. predicted percent of vegetation coverage provided R squared values of 0.73, 0.71, 0.67, and 0.89 for C. bigelowii, R. chamaemorus, Sphagnum spp., and open water respectively. These data have provided some support to the notion that texture analyses can be used for classification of mire site types. Future work will involve scaling up from the 50 plots through the use of data collected from two unmanned aerial systems (UAS), as well as WorldView-2 satellite imagery collected during the years 2012-2014. Identification of methane flux regions will later be analyzed based on vegetation coverage to aid classification of increased emission zones within the mire.

Can the FIGO 2000 scoring system for gestational trophoblastic neoplasia be simplified? A new retrospective analysis from a nationwide dataset.

PubMed

Eysbouts, Y K; Ottevanger, P B; Massuger, L F A G; IntHout, J; Short, D; Harvey, R; Kaur, B; Sebire, N J; Sarwar, N; Sweep, F C G J; Seckl, M J

2017-08-01

Worldwide introduction of the International Fedaration of Gynaecology and Obstetrics (FIGO) 2000 scoring system has provided an effective means to stratify patients with gestational trophoblastic neoplasia to single- or multi-agent chemotherapy. However, the system is quite elaborate with an extensive set of risk factors. In this study, we re-evaluate all prognostic risk factors involved in the FIGO 2000 scoring system and examine if simplification is feasible. Between January 2003 and December 2012, 813 patients diagnosed with gestational trophoblastic neoplasia were identified at the Trophoblastic Disease Centre in London and scored using the FIGO 2000. Multivariable analysis and stepwise logistic regression were carried out to evaluate whether the FIGO 2000 scoring system could be simplified. Of the eight FIGO risk factors only pre-treatment serum human chorionic gonadotropin (hCG) levels exceeding 10 000 IU/l (OR = 5.0; 95% CI 2.5-10.4) and 100 000 IU/l (OR = 14.3; 95% CI 4.7-44.1), interval exceeding 7 months since antecedent pregnancy (OR = 4.1; 95% CI 1.0-16.2), and tumor size of over 5 cm (OR = 2.2; 95% CI 1.3-3.6) were identified as independently predictive for single-agent resistance. In addition, increased risk was apparent for antecedent term pregnancy (OR = 3.4; 95% CI 0.9-12.7) and the presence of five or more metastases (OR = 3.5; 95% CI 0.4-30.4), but patient numbers in these categories were relatively small. Stepwise logistic regression identified a simplified risk scoring model comprising age, pretreatment serum hCG, number of metastases, antecedent pregnancy, and interval but omitting tumor size, previous failed chemotherapy, and site of metastases. With this model only 1 out 725 patients was classified different from the FIGO 2000 system. Our simplified alternative using only five of the FIGO prognostic factors appears to be an accurate system for discriminating patients requiring single as opposed to multi-agent chemotherapy. Further work is urgently needed to validate these findings. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

[Discrimination of Rice Syrup Adulterant of Acacia Honey Based Using Near-Infrared Spectroscopy].

PubMed

Zhang, Yan-nan; Chen, Lan-zhen; Xue, Xiao-feng; Wu, Li-ming; Li, Yi; Yang, Juan

2015-09-01

At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.

Evaluation of carbohydrates in natural and cultured Cordyceps by pressurized liquid extraction and gas chromatography coupled with mass spectrometry.

PubMed

Guan, Jia; Yang, Feng-Qing; Li, Shao-Ping

2010-06-11

Free and polymeric carbohydrates in Cordyceps, a valued edible mushroom and well-known traditional Chinese medicine, were determined using stepwise pressurized liquid extraction (PLE) extraction and GC-MS. Based on the optimized PLE conditions, acid hydrolysis and derivatization, ten monosaccharides, namely rhamnose, ribose, arabinose, xylose, mannose, glucose, galactose, mannitol, fructose and sorbose in 13 samples of natural and cultured Cordyceps were qualitatively and quantitatively analyzed and compared with myo-inositol hexaacetate as internal standard. The results showed that natural C. sinensis contained more than 7.99% free mannitol and a small amount of glucose, while its polysaccharides were usually composed of mannose, glucose and galactose with a molar ratio of 1.00:16.61-3.82:1.60-1.28. However, mannitol in cultured C. sinensis and cultured C. militaris were less than 5.83%, and free glucose was only detected in a few samples, while their polysaccharides were mainly composed of mannose, glucose and galactose with molar ratios of 1.00:3.01-1.09:3.30-1.05 and 1.00:2.86-1.28:1.07-0.78, respectively. Natural and cultured Cordyceps could be discriminated by hierarchical clustering analysis based on its free carbohydrate contents.

Manipulating attention via mindfulness induction improves P300-based brain-computer interface performance

NASA Astrophysics Data System (ADS)

Lakey, Chad E.; Berry, Daniel R.; Sellers, Eric W.

2011-04-01

In this study, we examined the effects of a short mindfulness meditation induction (MMI) on the performance of a P300-based brain-computer interface (BCI) task. We expected that MMI would harness present-moment attentional resources, resulting in two positive consequences for P300-based BCI use. Specifically, we believed that MMI would facilitate increases in task accuracy and promote the production of robust P300 amplitudes. Sixteen-channel electroencephalographic data were recorded from 18 subjects using a row/column speller task paradigm. Nine subjects participated in a 6 min MMI and an additional nine subjects served as a control group. Subjects were presented with a 6 × 6 matrix of alphanumeric characters on a computer monitor. Stimuli were flashed at a stimulus onset asynchrony (SOA) of 125 ms. Calibration data were collected on 21 items without providing feedback. These data were used to derive a stepwise linear discriminate analysis classifier that was applied to an additional 14 items to evaluate accuracy. Offline performance analyses revealed that MMI subjects were significantly more accurate than control subjects. Likewise, MMI subjects produced significantly larger P300 amplitudes than control subjects at Cz and PO7. The discussion focuses on the potential attentional benefits of MMI for P300-based BCI performance.

Discrimination in Degradability of Soil Pyrogenic Organic Matter Follows a Return-On-Energy-Investment Principle.

PubMed

Harvey, Omar R; Myers-Pigg, Allison N; Kuo, Li-Jung; Singh, Bhupinder Pal; Kuehn, Kevin A; Louchouarn, Patrick

2016-08-16

A fundamental understanding of biodegradability is central to elucidating the role(s) of pyrogenic organic matter (PyOM) in biogeochemical cycles. Since microbial community and ecosystem dynamics are driven by net energy flows, then a quantitative assessment of energy value versus energy requirement for oxidation of PyOM should yield important insights into their biodegradability. We used bomb calorimetry, stepwise isothermal thermogravimetric analysis (isoTGA), and 5-year in situ bidegradation data to develop energy-biodegradability relationships for a suite of plant- and manure-derived PyOM (n = 10). The net energy value (ΔE) for PyOM was between 4.0 and 175 kJ mol(-1); with manure-derived PyOM having the highest ΔE. Thermal-oxidation activation energy (Ea) requirements ranged from 51 to 125 kJ mol(-1), with wood-derived PyOM having the highest Ea requirements. We propose a return-on-investment (ROI) parameter (ΔE/Ea) for differentiating short-to-medium term biodegradability of PyOM and deciphering if biodegradation will most likely proceed via cometabolism (ROI < 1) or direct metabolism (ROI ≥ 1). The ROI-biodegradability relationship was sigmoidal with higher biodegradability associated with PyOM of higher ROI; indicating that microbes exhibit a higher preference for "high investment value" PyOM.

Relationship between self-reported upper limb disability and quantitative tests in hand-arm vibration syndrome.

PubMed

Poole, Kerry; Mason, Howard

2007-03-15

To establish the relationship between quantitative tests of hand function and upper limb disability, as measured by the Disability of the Arm, Shoulder and Hand (DASH) questionnaire, in hand-arm vibration syndrome (HAVS). A total of 228 individuals with HAVS were included in this study. Each had undergone a full HAVS assessment by an experienced physician, including quantitative tests of vibrotactile and thermal perception thresholds, maximal hand-grip strength (HG) and the Purdue pegboard (PP) test. Individuals were also asked to complete a DASH questionnaire. PP and HG of the quantitative tests gave the best and statistically significant individual correlations with the DASH disability score (r2 = 0.168 and 0.096). Stepwise linear regression analysis revealed that only PP and HG measurements were statistically significant predictors of upper limb disability (r2 = 0.178). Overall a combination of the PP and HG measurements, rather than each alone, gave slightly better discrimination, although not statistically significant, between normal and abnormal DASH scores with a sensitivity of 73.1% and specificity of 64.3%. Measurements of manual dexterity and hand-grip strength using PP and HG may be useful in helping to confirm lack of upper limb function and 'perceived' disability in HAVS.

Vocal individuality cues in the African penguin (Spheniscus demersus): a source-filter theory approach.

PubMed

Favaro, Livio; Gamba, Marco; Alfieri, Chiara; Pessani, Daniela; McElligott, Alan G

2015-11-25

The African penguin is a nesting seabird endemic to southern Africa. In penguins of the genus Spheniscus vocalisations are important for social recognition. However, it is not clear which acoustic features of calls can encode individual identity information. We recorded contact calls and ecstatic display songs of 12 adult birds from a captive colony. For each vocalisation, we measured 31 spectral and temporal acoustic parameters related to both source and filter components of calls. For each parameter, we calculated the Potential of Individual Coding (PIC). The acoustic parameters showing PIC ≥ 1.1 were used to perform a stepwise cross-validated discriminant function analysis (DFA). The DFA correctly classified 66.1% of the contact calls and 62.5% of display songs to the correct individual. The DFA also resulted in the further selection of 10 acoustic features for contact calls and 9 for display songs that were important for vocal individuality. Our results suggest that studying the anatomical constraints that influence nesting penguin vocalisations from a source-filter perspective, can lead to a much better understanding of the acoustic cues of individuality contained in their calls. This approach could be further extended to study and understand vocal communication in other bird species.

Vocal individuality cues in the African penguin (Spheniscus demersus): a source-filter theory approach

PubMed Central

Favaro, Livio; Gamba, Marco; Alfieri, Chiara; Pessani, Daniela; McElligott, Alan G.

2015-01-01

The African penguin is a nesting seabird endemic to southern Africa. In penguins of the genus Spheniscus vocalisations are important for social recognition. However, it is not clear which acoustic features of calls can encode individual identity information. We recorded contact calls and ecstatic display songs of 12 adult birds from a captive colony. For each vocalisation, we measured 31 spectral and temporal acoustic parameters related to both source and filter components of calls. For each parameter, we calculated the Potential of Individual Coding (PIC). The acoustic parameters showing PIC ≥ 1.1 were used to perform a stepwise cross-validated discriminant function analysis (DFA). The DFA correctly classified 66.1% of the contact calls and 62.5% of display songs to the correct individual. The DFA also resulted in the further selection of 10 acoustic features for contact calls and 9 for display songs that were important for vocal individuality. Our results suggest that studying the anatomical constraints that influence nesting penguin vocalisations from a source-filter perspective, can lead to a much better understanding of the acoustic cues of individuality contained in their calls. This approach could be further extended to study and understand vocal communication in other bird species. PMID:26602001

Characterizing Walk Trips in communities by Using Data from 2009 National Household Travel Survey, American Community Survey, and Other Sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hwang, Ho-Ling; Reuscher, Tim; Wilson, Daniel W

Non-motorized travel (i.e. walking and bicycling) are of increasing interest to the transportation profession, especially in context with energy consumption, reducing vehicular congestion, urban development patterns, and promotion of healthier life styles. This research project aimed to identify factors impacting the amount of travel for both walk and bike trips at the Census block group or tract level, using several public and private data sources. The key survey of travel behavior is the 2009 National Household Travel Survey (NHTS) which had over 87,000 walk trips for persons 16 and over, and over 6000 bike trips for persons 16 and over.more » The NHTS, in conjunction with the Census Bureau s American Community Survey, street density measures using Census Bureau TIGER, WalkScore , Nielsen Claritas employment estimates, and several other sources were used for this study. Stepwise Logistic Regression modeling techniques as well as Discriminant Analysis were applied using the integrated data set. While the models performed reasonably well for walk trips, travel by bike was abandoned due to sparseness of data. This paper discusses data sources utilized and modeling processes conducted under this study. It also presents a summary of findings and addresses data challenges and lesson-learned from this research effort.« less

A case definition and photographic screening tool for the facial phenotype of fetal alcohol syndrome.

PubMed

Astley, S J; Clarren, S K

1996-07-01

The purpose of this study was to demonstrate that a quantitative, multivariate case definition of the fetal alcohol syndrome (FAS) facial phenotype could be derived from photographs of individuals with FAS and to demonstrate how this case definition and photographic approach could be used to develop efficient, accurate, and precise screening tools, diagnostic aids, and possibly surveillance tools. Frontal facial photographs of 42 subjects (from birth to 27 years of age) with FAS were matched to 84 subjects without FAS. The study population was randomly divided in half. Group 1 was used to identify the facial features that best differentiated individuals with and without FAS. Group 2 was used for cross validation. In group 1, stepwise discriminant analysis identified three facial features (reduced palpebral fissure length/inner canthal distance ratio, smooth philtrum, and thin upper lip) as the cluster of features that differentiated individuals with and without FAS in groups 1 and 2 with 100% accuracy. Sensitivity and specificity were unaffected by race, gender, and age. The phenotypic case definition derived from photographs accurately distinguished between individuals with and without FAS, demonstrating the potential of this approach for developing screening, diagnostic, and surveillance tools. Further evaluation of the validity and generalizability of this method will be needed.

Sex determination using humeral dimensions in a sample from KwaZulu-Natal: an osteometric study

PubMed Central

Ogedengbe, Oluwatosin Olalekan; Ajayi, Sunday Adelaja; Komolafe, Omobola Aderibigbe; Zaw, Aung Khaing; Naidu, Edwin Coleridge Stephen

2017-01-01

The morphological characteristics of the humeral bone has been investigated in recent times with studies showing varying degrees of sexual dimorphism. Osteologists and forensic scientists have shown that sex determination methods based on skeletal measurements are population specific, and these population-specific variations are present in many body dimensions. The present study aims to establish sex identification using osteometric standards for the humerus in a contemporary KwaZulu-Natal population. A total of 11 parameters were measured in a sample of n=211 humeri (males, 113; females, 98) from the osteological collection in the Discipline of Clinical Anatomy, Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa. The difference in means for nearly all variables were found to be significantly higher in males compared to females (P<0.01) with the most effective single parameter for predicting sex being the vertical head diameter having an accuracy of 82.5%. Stepwise discriminant analysis increased the overall accuracy rate to 87.7% when all measurements were jointly applied. We conclude that the humerus is an important bone which can be reliably used for sex determination based on standard metric methods despite minor tribal or ancestral differences amongst an otherwise homogenous population. PMID:29043096

Sex determination using humeral dimensions in a sample from KwaZulu-Natal: an osteometric study.

PubMed

Ogedengbe, Oluwatosin Olalekan; Ajayi, Sunday Adelaja; Komolafe, Omobola Aderibigbe; Zaw, Aung Khaing; Naidu, Edwin Coleridge Stephen; Okpara Azu, Onyemaechi

2017-09-01

The morphological characteristics of the humeral bone has been investigated in recent times with studies showing varying degrees of sexual dimorphism. Osteologists and forensic scientists have shown that sex determination methods based on skeletal measurements are population specific, and these population-specific variations are present in many body dimensions. The present study aims to establish sex identification using osteometric standards for the humerus in a contemporary KwaZulu-Natal population. A total of 11 parameters were measured in a sample of n=211 humeri (males, 113; females, 98) from the osteological collection in the Discipline of Clinical Anatomy, Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa. The difference in means for nearly all variables were found to be significantly higher in males compared to females ( P <0.01) with the most effective single parameter for predicting sex being the vertical head diameter having an accuracy of 82.5%. Stepwise discriminant analysis increased the overall accuracy rate to 87.7% when all measurements were jointly applied. We conclude that the humerus is an important bone which can be reliably used for sex determination based on standard metric methods despite minor tribal or ancestral differences amongst an otherwise homogenous population.

Thrombomodulin, von Willebrand factor and E-selectin as plasma markers of endothelial damage/dysfunction and activation in pregnancy induced hypertension.

PubMed

Nadar, Sunil K; Al Yemeni, Eman; Blann, Andrew D; Lip, Gregory Y H

2004-01-01

Endothelial disturbance (whether activation, dysfunction or damage) is a likely pathogenic mechanism in pre-eclampsia and pregnancy-induced hypertension (PIH). We set out to determine which of three plasma markers of endothelial disturbance, indicating endothelial activation (E-selectin) or damage/dysfunction (von Willebrand factor (vWf), soluble thrombomodulin), would provide the best discriminator of PIH compared to normotensive pregnancy. Cross-sectional study of 36 consecutive women with PIH (age 31+/-6 years) and 36 consecutive women with normotensive pregnancies (age 29+/-5 years) of similar parity. Plasma levels of vWf, E-selectin and thrombomodulin were measured using ELISA. As expected, women with PIH had significantly higher levels of plasma vWf (by 19%, p=0.003), E-selectin (by 40%, p<0.001) and thrombomodulin (by 61%, p=0.01) than normotensive women. However, on stepwise multiple regression analysis, only thrombomodulin was an independent significant predictor of the presence of PIH (p=0.023). We conclude that although vWf, E-selectin and thrombomodulin are all raised in PIH, only thrombomodulin was independently associated with PIH. This molecule could potentially be useful in monitoring and in providing clues in aetiology and pathophysiology, and may have implications for the clinical complications associated with PIH.

Estimation of maximal oxygen uptake by bioelectrical impedance analysis.

PubMed

Stahn, Alexander; Terblanche, Elmarie; Grunert, Sven; Strobel, Günther

2006-02-01

Previous non-exercise models for the prediction of maximal oxygen uptake VO(2max) have failed to accurately discriminate cardiorespiratory fitness within large cohorts. The aim of the present study was to evaluate the feasibility of a completely indirect method for predicting VO(2max) that was based on bioelectrical impedance analysis (BIA) in 66 young, healthy fit men and women. Multiple, stepwise regression analysis was used to determine the usefulness of BIA and additional covariates to estimate VO(2max) (ml min(-1)). BIA was highly correlated to VO(2max) (r = 0.914; P < 0.001) and entered the regression equation first. The inclusion of gender and a physical activity rating further improved the model which accounted for 88% of the variance in VO(2max) and resulted in a relative standard error of the estimate (SEE) of 7.2%. Substantial agreement between the methods was confirmed by the fact that nearly all the differences were within +/-2 SD. Furthermore, in contrast to previously published non-exercise models, no trend of a reduction in prediction accuracy with increasing VO(2max) values was apparent. It was concluded that a non-exercise model based on BIA might be a rapid and useful technique to estimate VO(2max), when a direct test does not seem feasible. However, though the present results are useful to determine the viability of the method, further refinement of the BIA approach and its validation in a large, diverse population is needed before it can be applied to the clinical and epidemiological settings.

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearinga)

PubMed Central

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-01-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes. PMID:26233047

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearing.

PubMed

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-07-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes.

Design and implementation of a novel mechanical testing system for cellular solids.

PubMed

Nazarian, Ara; Stauber, Martin; Müller, Ralph

2005-05-01

Cellular solids constitute an important class of engineering materials encompassing both man-made and natural constructs. Materials such as wood, cork, coral, and cancellous bone are examples of cellular solids. The structural analysis of cellular solid failure has been limited to 2D sections to illustrate global fracture patterns. Due to the inherent destructiveness of 2D methods, dynamic assessment of fracture progression has not been possible. Image-guided failure assessment (IGFA), a noninvasive technique to analyze 3D progressive bone failure, has been developed utilizing stepwise microcompression in combination with time-lapsed microcomputed tomographic imaging (microCT). This method allows for the assessment of fracture progression in the plastic region, where much of the structural deformation/energy absorption is encountered in a cellular solid. Therefore, the goal of this project was to design and fabricate a novel micromechanical testing system to validate the effectiveness of the stepwise IGFA technique compared to classical continuous mechanical testing, using a variety of engineered and natural cellular solids. In our analysis, we found stepwise compression to be a valid approach for IGFA with high precision and accuracy comparable to classical continuous testing. Therefore, this approach complements the conventional mechanical testing methods by providing visual insight into the failure propagation mechanisms of cellular solids. (c) 2005 Wiley Periodicals, Inc.

Solid-phase extraction versus matrix solid-phase dispersion: Application to white grapes.

PubMed

Dopico-García, M S; Valentão, P; Jagodziñska, A; Klepczyñska, J; Guerra, L; Andrade, P B; Seabra, R M

2007-11-15

The use of matrix solid-phase dispersion (MSPD) was tested to, separately, extract phenolic compounds and organic acids from white grapes. This method was compared with a more conventional analytical method previously developed that combines solid liquid extraction (SL) to simultaneously extract phenolic compounds and organic acids followed by a solid-phase extraction (SPE) to separate the two types of compounds. Although the results were qualitatively similar for both techniques, the levels of extracted compounds were in general quite lower on using MSPD, especially for organic acids. Therefore, SL-SPE method was preferred to analyse white "Vinho Verde" grapes. Twenty samples of 10 different varieties (Alvarinho, Avesso, Asal-Branco, Batoca, Douradinha, Esganoso de Castelo Paiva, Loureiro, Pedernã, Rabigato and Trajadura) from four different locations in Minho (Portugal) were analysed in order to study the effects of variety and origin on the profile of the above mentioned compounds. Principal component analysis (PCA) was applied separately to establish the main sources of variability present in the data sets for phenolic compounds, organic acids and for the global data. PCA of phenolic compounds accounted for the highest variability (77.9%) with two PCs, enabling characterization of the varieties of samples according to their higher content in flavonol derivatives or epicatechin. Additionally, a strong effect of sample origin was observed. Stepwise linear discriminant analysis (SLDA) was used for differentiation of grapes according to the origin and variety, resulting in a correct classification of 100 and 70%, respectively.

Neural network classification of sweet potato embryos

NASA Astrophysics Data System (ADS)

Molto, Enrique; Harrell, Roy C.

1993-05-01

Somatic embryogenesis is a process that allows for the in vitro propagation of thousands of plants in sub-liter size vessels and has been successfully applied to many significant species. The heterogeneity of maturity and quality of embryos produced with this technique requires sorting to obtain a uniform product. An automated harvester is being developed at the University of Florida to sort embryos in vitro at different stages of maturation in a suspension culture. The system utilizes machine vision to characterize embryo morphology and a fluidic based separation device to isolate embryos associated with a pre-defined, targeted morphology. Two different backpropagation neural networks (BNN) were used to classify embryos based on information extracted from the vision system. One network utilized geometric features such as embryo area, length, and symmetry as inputs. The alternative network utilized polar coordinates of an embryo's perimeter with respect to its centroid as inputs. The performances of both techniques were compared with each other and with an embryo classification method based on linear discriminant analysis (LDA). Similar results were obtained with all three techniques. Classification efficiency was improved by reducing the dimension of the feature vector trough a forward stepwise analysis by LDA. In order to enhance the purity of the sample selected as harvestable, a reject to classify option was introduced in the model and analyzed. The best classifier performances (76% overall correct classifications, 75% harvestable objects properly classified, homogeneity improvement ratio 1.5) were obtained using 8 features in a BNN.

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

[Discriminant analysis to predict the clinical diagnosis of primary immunodeficiencies: a preliminary report].

PubMed

Murata, Chiharu; Ramírez, Ana Belén; Ramírez, Guadalupe; Cruz, Alonso; Morales, José Luis; Lugo-Reyes, Saul Oswaldo

2015-01-01

The features in a clinical history from a patient with suspected primary immunodeficiency (PID) direct the differential diagnosis through pattern recognition. PIDs are a heterogeneous group of more than 250 congenital diseases with increased susceptibility to infection, inflammation, autoimmunity, allergy and malignancy. Linear discriminant analysis (LDA) is a multivariate supervised classification method to sort objects of study into groups by finding linear combinations of a number of variables. To identify the features that best explain membership of pediatric PID patients to a group of defect or disease. An analytic cross-sectional study was done with a pre-existing database with clinical and laboratory records from 168 patients with PID, followed at the National Institute of Pediatrics during 1991-2012, it was used to build linear discriminant models that would explain membership of each patient to the different group defects and to the most prevalent PIDs in our registry. After a preliminary run only 30 features were included (4 demographic, 10 clinical, 10 laboratory, 6 germs), with which the training models were developed through a stepwise regression algorithm. We compared the automatic feature selection with a selection made by a human expert, and then assessed the diagnostic usefulness of the resulting models (sensitivity, specificity, prediction accuracy and kappa coefficient), with 95% confidence intervals. The models incorporated 6 to 14 features to explain membership of PID patients to the five most abundant defect groups (combined, antibody, well-defined, dysregulation and phagocytosis), and to the four most prevalent PID diseases (X-linked agammaglobulinemia, chronic granulomatous disease, common variable immunodeficiency and ataxiatelangiectasia). In practically all cases of feature selection the machine outperformed the human expert. Diagnosis prediction using the equations created had a global accuracy of 83 to 94%, with sensitivity of 60 to 100%, specificity of 83 to 95% and kappa coefficient of 0.37 to 0.76. In general, the selection of features has clinical plausibility, and the practical advantage of utilizing only clinical attributes, infecting germs and routine lab results (blood cell counts and serum immunoglobulins). The performance of the model as a diagnostic tool was acceptable. The study's main limitations are a limited sample size and a lack of cross validation. This is only the first step in the construction of a machine learning system, with a wider approach that includes a larger database and different methodologies, to assist the clinical diagnosis of primary immunodeficiencies.

Tumor necrosis factor inhibitor therapy but not standard therapy is associated with resolution of erosion in the sacroiliac joints of patients with axial spondyloarthritis

PubMed Central

2014-01-01

Introduction Radiography is an unreliable and insensitive tool for the assessment of structural lesions in the sacroiliac joints (SIJ). Magnetic resonance imaging (MRI) detects a wider spectrum of structural lesions but has undergone minimal validation in prospective studies. The Spondyloarthritis Research Consortium of Canada (SPARCC) MRI Sacroiliac Joint (SIJ) Structural Score (SSS) assesses a spectrum of structural lesions (erosion, fat metaplasia, backfill, ankylosis) and its potential to discriminate between therapies requires evaluation. Methods The SSS score assesses five consecutive coronal slices through the cartilaginous portion of the joint on T1-weighted sequences starting from the transitional slice between cartilaginous and ligamentous portions of the joint. Lesions are scored dichotomously (present/absent) in SIJ quadrants (fat metaplasia, erosion) or halves (backfill, ankylosis). Two readers independently scored 147 pairs (baseline, 2 years) of scans from a prospective cohort of patients with SpA who received either standard (n = 69) or tumor necrosis factor alpha (TNFα) inhibitor (n = 78) therapy. Smallest detectable change (SDC) was calculated using analysis of variance (ANOVA), discrimination was assessed using Guyatt’s effect size, and treatment group differences were assessed using t-tests and the Mann–Whitney test. We identified baseline demographic and structural damage variables associated with change in SSS score by univariate analysis and analyzed the effect of treatment by multivariate stepwise regression adjusted for severity of baseline structural damage and demographic variables. Results A significant increase in mean SSS score for fat metaplasia (P = 0.017) and decrease in mean SSS score for erosion (P = 0.017) was noted in anti-TNFα treated patients compared to those on standard therapy. Effect size for this change in SSS fat metaplasia and erosion score was moderate (0.5 and 0.6, respectively). Treatment and baseline SSS score for erosion were independently associated with change in SSS erosion score (β = 1.75, P = 0.003 and β = 0.40, P < 0.0001, respectively). Change in ASDAS (β = −0.46, P = 0.006), SPARCC MRI SIJ inflammation (β = −0.077, P = 0.019), and baseline SSS score for fat metaplasia (β = 0.085, P = 0.034) were independently associated with new fat metaplasia. Conclusion The SPARCC SSS method for assessment of structural lesions has discriminative capacity in demonstrating significantly greater reduction in erosion and new fat metaplasia in patients receiving anti-TNFα therapy. PMID:24755322

Perceived Discrimination and Health: A Meta-Analytic Review

PubMed Central

Pascoe, Elizabeth A.; Richman, Laura Smart

2009-01-01

Perceived discrimination has been studied with regard to its impact on several types of health effects. This meta-analysis provides a comprehensive account of the relationships between multiple forms of perceived discrimination and both mental and physical health outcomes. In addition, this meta-analysis examines potential mechanisms by which perceiving discrimination may affect health, including through psychological and physiological stress responses and health behaviors. Analysis of 134 samples suggests that when weighting each study’s contribution by sample size, perceived discrimination has a significant negative effect on both mental and physical health. Perceived discrimination also produces significantly heightened stress responses and is related to participation in unhealthy and nonparticipation in healthy behaviors. These findings suggest potential pathways linking perceived discrimination to negative health outcomes. PMID:19586161

Stepwise versus Hierarchical Regression: Pros and Cons

ERIC Educational Resources Information Center

Lewis, Mitzi

2007-01-01

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

A Graph Oriented Approach for Network Forensic Analysis

ERIC Educational Resources Information Center

Wang, Wei

2010-01-01

Network forensic analysis is a process that analyzes intrusion evidence captured from networked environment to identify suspicious entities and stepwise actions in an attack scenario. Unfortunately, the overwhelming amount and low quality of output from security sensors make it difficult for analysts to obtain a succinct high-level view of complex…

Technological Literacy Learning with Cumulative and Stepwise Integration of Equations into Electrical Circuit Diagrams

ERIC Educational Resources Information Center

Ozogul, G.; Johnson, A. M.; Moreno, R.; Reisslein, M.

2012-01-01

Technological literacy education involves the teaching of basic engineering principles and problem solving, including elementary electrical circuit analysis, to non-engineering students. Learning materials on circuit analysis typically rely on equations and schematic diagrams, which are often unfamiliar to non-engineering students. The goal of…

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

A stepwise composite echocardiographic score predicts severe pulmonary hypertension in patients with interstitial lung disease.

PubMed

Bax, Simon; Bredy, Charlene; Kempny, Aleksander; Dimopoulos, Konstantinos; Devaraj, Anand; Walsh, Simon; Jacob, Joseph; Nair, Arjun; Kokosi, Maria; Keir, Gregory; Kouranos, Vasileios; George, Peter M; McCabe, Colm; Wilde, Michael; Wells, Athol; Li, Wei; Wort, Stephen John; Price, Laura C

2018-04-01

European Respiratory Society (ERS) guidelines recommend the assessment of patients with interstitial lung disease (ILD) and severe pulmonary hypertension (PH), as defined by a mean pulmonary artery pressure (mPAP) ≥35 mmHg at right heart catheterisation (RHC). We developed and validated a stepwise echocardiographic score to detect severe PH using the tricuspid regurgitant velocity and right atrial pressure (right ventricular systolic pressure (RVSP)) and additional echocardiographic signs. Consecutive ILD patients with suspected PH underwent RHC between 2005 and 2015. Receiver operating curve analysis tested the ability of components of the score to predict mPAP ≥35 mmHg, and a score devised using a stepwise approach. The score was tested in a contemporaneous validation cohort. The score used "additional PH signs" where RVSP was unavailable, using a bootstrapping technique. Within the derivation cohort (n=210), a score ≥7 predicted severe PH with 89% sensitivity, 71% specificity, positive predictive value 68% and negative predictive value 90%, with similar performance in the validation cohort (n=61) (area under the curve (AUC) 84.8% versus 83.1%, p=0.8). Although RVSP could be estimated in 92% of studies, reducing this to 60% maintained a fair accuracy (AUC 74.4%). This simple stepwise echocardiographic PH score can predict severe PH in patients with ILD.

A stepwise composite echocardiographic score predicts severe pulmonary hypertension in patients with interstitial lung disease

PubMed Central

Bax, Simon; Bredy, Charlene; Kempny, Aleksander; Dimopoulos, Konstantinos; Devaraj, Anand; Walsh, Simon; Jacob, Joseph; Nair, Arjun; Kokosi, Maria; Keir, Gregory; Kouranos, Vasileios; George, Peter M.; McCabe, Colm; Wilde, Michael; Wells, Athol; Li, Wei; Wort, Stephen John; Price, Laura C.

2018-01-01

European Respiratory Society (ERS) guidelines recommend the assessment of patients with interstitial lung disease (ILD) and severe pulmonary hypertension (PH), as defined by a mean pulmonary artery pressure (mPAP) ≥35 mmHg at right heart catheterisation (RHC). We developed and validated a stepwise echocardiographic score to detect severe PH using the tricuspid regurgitant velocity and right atrial pressure (right ventricular systolic pressure (RVSP)) and additional echocardiographic signs. Consecutive ILD patients with suspected PH underwent RHC between 2005 and 2015. Receiver operating curve analysis tested the ability of components of the score to predict mPAP ≥35 mmHg, and a score devised using a stepwise approach. The score was tested in a contemporaneous validation cohort. The score used “additional PH signs” where RVSP was unavailable, using a bootstrapping technique. Within the derivation cohort (n=210), a score ≥7 predicted severe PH with 89% sensitivity, 71% specificity, positive predictive value 68% and negative predictive value 90%, with similar performance in the validation cohort (n=61) (area under the curve (AUC) 84.8% versus 83.1%, p=0.8). Although RVSP could be estimated in 92% of studies, reducing this to 60% maintained a fair accuracy (AUC 74.4%). This simple stepwise echocardiographic PH score can predict severe PH in patients with ILD. PMID:29750141

Study on bayes discriminant analysis of EEG data.

PubMed

Shi, Yuan; He, DanDan; Qin, Fang

2014-01-01

In this paper, we have done Bayes Discriminant analysis to EEG data of experiment objects which are recorded impersonally come up with a relatively accurate method used in feature extraction and classification decisions. In accordance with the strength of α wave, the head electrodes are divided into four species. In use of part of 21 electrodes EEG data of 63 people, we have done Bayes Discriminant analysis to EEG data of six objects. Results In use of part of EEG data of 63 people, we have done Bayes Discriminant analysis, the electrode classification accuracy rates is 64.4%. Bayes Discriminant has higher prediction accuracy, EEG features (mainly αwave) extract more accurate. Bayes Discriminant would be better applied to the feature extraction and classification decisions of EEG data.

Regional Famine Patterns of The Last Millennium as Influenced by Aggregated Climate Teleconnections

NASA Astrophysics Data System (ADS)

Santoro, Michael Melton

Famine is the result of a complex set of environmental and social factors. Climate conditions are established as environmental factors contributing to famine occurrence, often through teleconnective patterns. This dissertation is designed to investigate the combined influence on world famine patterns of teleconnections, specifically the North Atlantic Oscillation (NAO), Southern Oscillation (SO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), or regional climate variations such as the South Asian Summer Monsoon (SASM). The investigation is three regional case studies of famine patterns specifically, Egypt, the British Isles, and India. The first study (published in Holocene) employs the results of a Principal Component Analysis (PCA) yielding a SO-NAO eigenvector to predict major Egyptian famines between AD 1049-1921. The SO-NAO eigenvector (1) successfully discriminates between the 5-10 years preceding a famine and the other years, (2) predicts eight of ten major famines, and (3) correctly identifies fifty out of eighty events (63%) of food availability decline leading up to major famines. The second study investigates the impact of the NAO, PDO, SO, and AMO on 63 British Isle famines between AD 1049 and 1914 attributed to climate causes in historical texts. Stepwise Regression Analysis demonstrates that the 5-year lagged NAO is the primary teleconnective influence on famine patterns; it successfully discriminates 73.8% of weather-related famines in the British Isles from 1049 to 1914. The final study identifies the aggregated influence of the NAO, SO, PDO, and SASM on 70 Indian famines from AD 1049 to 1955. PCA results in a NAO-SOI vector and SASM vector that predicts famine conditions with a positive NAO and negative SO, distinct from the secondary SASM influence. The NAO-famine relationship is consistently the strongest; 181 of 220 (82%) of all famines occurred during positive NAO years. Ultimately, the causes of famine are complex and involve many factors including societal and climatic. This dissertation demonstrates that climate teleconnections impact famine patterns and often the aggregates of multiple climate variables hold the most significant climatic impact. These results will increase the understanding of famine patterns and will help to better allocate resources to alleviate future famines.

Social status correlates of reporting gender discrimination and racial discrimination among racially diverse women.

PubMed

Ro, Annie E; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in North California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design.

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES

PubMed Central

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D.

2009-01-01

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component’s discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies. PMID:20582334

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES.

PubMed

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D

2008-05-12

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component's discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies.

Integrated, Step-Wise, Mass-Isotopomeric Flux Analysis of the TCA Cycle.

PubMed

Alves, Tiago C; Pongratz, Rebecca L; Zhao, Xiaojian; Yarborough, Orlando; Sereda, Sam; Shirihai, Orian; Cline, Gary W; Mason, Graeme; Kibbey, Richard G

2015-11-03

Mass isotopomer multi-ordinate spectral analysis (MIMOSA) is a step-wise flux analysis platform to measure discrete glycolytic and mitochondrial metabolic rates. Importantly, direct citrate synthesis rates were obtained by deconvolving the mass spectra generated from [U-(13)C6]-D-glucose labeling for position-specific enrichments of mitochondrial acetyl-CoA, oxaloacetate, and citrate. Comprehensive steady-state and dynamic analyses of key metabolic rates (pyruvate dehydrogenase, β-oxidation, pyruvate carboxylase, isocitrate dehydrogenase, and PEP/pyruvate cycling) were calculated from the position-specific transfer of (13)C from sequential precursors to their products. Important limitations of previous techniques were identified. In INS-1 cells, citrate synthase rates correlated with both insulin secretion and oxygen consumption. Pyruvate carboxylase rates were substantially lower than previously reported but showed the highest fold change in response to glucose stimulation. In conclusion, MIMOSA measures key metabolic rates from the precursor/product position-specific transfer of (13)C-label between metabolites and has broad applicability to any glucose-oxidizing cell. Copyright © 2015 Elsevier Inc. All rights reserved.

Discrimination against Latina/os: A Meta-Analysis of Individual-Level Resources and Outcomes

ERIC Educational Resources Information Center

Lee, Debbiesiu L.; Ahn, Soyeon

2012-01-01

This meta-analysis synthesizes the findings of 60 independent samples from 51 studies examining racial/ethnic discrimination against Latina/os in the United States. The purpose was to identify individual-level resources and outcomes that most strongly relate to discrimination. Discrimination against Latina/os significantly results in outcomes…

Differentiation of depression and anxiety groups using defense mechanisms.

PubMed

Olson, Trevor R; Presniak, Michelle D; MacGregor, Michael Wm

2009-11-01

We examined whether participants in depressed and anxious groups could be classified correctly using observer and self-report measures of defense mechanisms. A sample of 1182 university students completed the Personality Assessment Inventory and those scoring in the clinical range on either depression or anxiety indices were selected for participation. In total, 25 participants met criteria for the depressed group and 94 met criteria for the anxious group. Individual defense scores from the Defense-Q and the Defense Style Questionnaire were separately entered into 2 stepwise discriminant analyses. After cross-validation, the Defense-Q and Defense Style Questionnaire analyses classified participants with 75.0% and 71.3% accuracy, respectively. The results indicated that depression and anxiety groups can be significantly differentiated by defense use alone. Important differences in defensive functioning between these groups were confirmed and differences between observer and self-report measures of defenses mechanisms and current challenges in defense research were highlighted.

A model for predicting sulcus-to-sulcus diameter in posterior chamber phakic intraocular lens candidates: correlation between ocular biometric parameters.

PubMed

Ghoreishi, Mohammad; Abdi-Shahshahani, Mehdi; Peyman, Alireza; Pourazizi, Mohsen

2018-02-21

The aim of this study was to determine the correlation between ocular biometric parameters and sulcus-to-sulcus (STS) diameter. This was a cross-sectional study of preoperative ocular biometry data of patients who were candidates for phakic intraocular lens (IOL) surgery. Subjects underwent ocular biometry analysis, including refraction error evaluation using an autorefractor and Orbscan topography for white-to-white (WTW) corneal diameter and measurement. Pentacam was used to perform WTW corneal diameter and measurements of minimum and maximum keratometry (K). Measurements of STS and angle-to-angle (ATA) were obtained using a 50-MHz B-mode ultrasound device. Anterior optical coherence tomography was performed for anterior chamber depth measurement. Pearson's correlation test and stepwise linear regression analysis were used to find a model to predict STS. Fifty-eight eyes of 58 patients were enrolled. Mean age ± standard deviation of sample was 28.95 ± 6.04 years. The Pearson's correlation coefficient between STS with WTW, ATA, mean K was 0.383, 0.492, and - 0.353, respectively, which was statistically significant (all P < 0.001). Using stepwise linear regression analysis, there is a statistically significant association between STS with WTW (P = 0.011) and mean K (P = 0.025). The standardized coefficient was 0.323 and - 0.284 for WTW and mean K, respectively. The stepwise linear regression analysis equation was: (STS = 9.549 + 0.518 WTW - 0.083 mean K). Based on our result, given the correlation of STS with WTW and mean K and potential of direct and essay measurement of WTW and mean K, it seems that current IOL sizing protocols could be estimating with WTW and mean K.

Cytopathologic differential diagnosis of low-grade urothelial carcinoma and reactive urothelial proliferation in bladder washings: a logistic regression analysis.

PubMed

Cakir, Ebru; Kucuk, Ulku; Pala, Emel Ebru; Sezer, Ozlem; Ekin, Rahmi Gokhan; Cakmak, Ozgur

2017-05-01

Conventional cytomorphologic assessment is the first step to establish an accurate diagnosis in urinary cytology. In cytologic preparations, the separation of low-grade urothelial carcinoma (LGUC) from reactive urothelial proliferation (RUP) can be exceedingly difficult. The bladder washing cytologies of 32 LGUC and 29 RUP were reviewed. The cytologic slides were examined for the presence or absence of the 28 cytologic features. The cytologic criteria showing statistical significance in LGUC were increased numbers of monotonous single (non-umbrella) cells, three-dimensional cellular papillary clusters without fibrovascular cores, irregular bordered clusters, atypical single cells, irregular nuclear overlap, cytoplasmic homogeneity, increased N/C ratio, pleomorphism, nuclear border irregularity, nuclear eccentricity, elongated nuclei, and hyperchromasia (p ˂ 0.05), and the cytologic criteria showing statistical significance in RUP were inflammatory background, mixture of small and large urothelial cells, loose monolayer aggregates, and vacuolated cytoplasm (p ˂ 0.05). When these variables were subjected to a stepwise logistic regression analysis, four features were selected to distinguish LGUC from RUP: increased numbers of monotonous single (non-umbrella) cells, increased nuclear cytoplasmic ratio, hyperchromasia, and presence of small and large urothelial cells (p = 0.0001). By this logistic model of the 32 cases with proven LGUC, the stepwise logistic regression analysis correctly predicted 31 (96.9%) patients with this diagnosis, and of the 29 patients with RUP, the logistic model correctly predicted 26 (89.7%) patients as having this disease. There are several cytologic features to separate LGUC from RUP. Stepwise logistic regression analysis is a valuable tool for determining the most useful cytologic criteria to distinguish these entities. © 2017 APMIS. Published by John Wiley & Sons Ltd.

Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

PubMed Central

Lim, Jongguk; Kim, Giyoung; Mo, Changyeun; Oh, Kyoungmin; Yoo, Hyeonchae; Ham, Hyeonheui; Kim, Moon S.

2017-01-01

The purpose of this study is to use near-infrared reflectance (NIR) spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA) was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method. PMID:28974012

Discrimination of red and white rice bran from Indonesia using HPLC fingerprint analysis combined with chemometrics.

PubMed

Sabir, Aryani; Rafi, Mohamad; Darusman, Latifah K

2017-04-15

HPLC fingerprint analysis combined with chemometrics was developed to discriminate between the red and the white rice bran grown in Indonesia. The major component in rice bran is γ-oryzanol which consisted of 4 main compounds, namely cycloartenol ferulate, cyclobranol ferulate, campesterol ferulate and β-sitosterol ferulate. Separation of these four compounds along with other compounds was performed using C18 and methanol-acetonitrile with gradient elution system. By using these intensity variations, principal component and discriminant analysis were performed to discriminate the two samples. Discriminant analysis was successfully discriminated the red from the white rice bran with predictive ability of the model showed a satisfactory classification for the test samples. The results of this study indicated that the developed method was suitable as quality control method for rice bran in terms of identification and discrimination of the red and the white rice bran. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.

PubMed

Morote, Juan; Del Amo, Jokin; Borque, Angel; Ars, Elisabet; Hernández, Carlos; Herranz, Felipe; Arruza, Antonio; Llarena, Roberto; Planas, Jacques; Viso, María J; Palou, Joan; Raventós, Carles X; Tejedor, Diego; Artieda, Marta; Simón, Laureano; Martínez, Antonio; Rioja, Luis A

2010-08-01

Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information. Copyright (c) 2010 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

On the Challenge of Observing Pelagic Sargassum in Coastal Oceans: A Multi-sensor Assessment

NASA Astrophysics Data System (ADS)

Hu, C.; Feng, L.; Hardy, R.; Hochberg, E. J.

2016-02-01

Remote detection of pelagic Sargassum is often hindered by its spectral similarity to other floating materials and by the inadequate spatial resolution. Using measurements from multi-spectral satellite sensors (Moderate Resolution Imaging Spectroradiometer or MODIS), Landsat, WorldView-2 (or WV-2) as well as hyperspectral sensors (Hyperspectral Imager for the Coastal Ocean or HICO, Airborne Visible-InfraRed Imaging Spectrometer or AVIRIS) and airborne digital photos, we analyze and compare their ability (in terms of spectral and spatial resolutions) to detect Sargassum and to differentiate from other floating materials such as Trichodesmium, Syringodium, Ulva, garbage, and emulsified oil. Field measurements suggest that Sargassum has a distinctive reflectance curvature around 630 nm due to its chlorophyll c pigments, which provides a unique spectral signature when combined with the reflectance ratio between brown ( 650 nm) and green ( 555 nm) wavelengths. For a 10-nm resolution sensor on the hyperspectral HyspIRI mission currently being planned by NASA, a stepwise rule to examine several indexes established from 6 bands (centered at 555, 605, 625, 645, 685, 755 nm) is shown to be effective to unambiguously differentiate Sargassum from all other floating materials Numerical simulations using spectral endmembers and noise in the satellite-derived reflectance suggest that spectral discrimination is degraded when a pixel is mixed between Sargassum and water. A minimum of 20-30% Sargassum coverage within a pixel is required to retain such ability, while the partial coverage can be as low as 1-2% when detecting floating materials without spectral discrimination. With its expected signal-to-noise ratios (SNRs 200:1), the hyperspectral HyspIRI mission may provide a compromise between spatial resolution and spatial coverage to improve our capacity to detect, discriminate, and quantify Sargassum.

Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization.

PubMed

Yuan, Yuan; Lin, Jianzhe; Wang, Qi

2016-12-01

Hyperspectral image (HSI) classification is a crucial issue in remote sensing. Accurate classification benefits a large number of applications such as land use analysis and marine resource utilization. But high data correlation brings difficulty to reliable classification, especially for HSI with abundant spectral information. Furthermore, the traditional methods often fail to well consider the spatial coherency of HSI that also limits the classification performance. To address these inherent obstacles, a novel spectral-spatial classification scheme is proposed in this paper. The proposed method mainly focuses on multitask joint sparse representation (MJSR) and a stepwise Markov random filed framework, which are claimed to be two main contributions in this procedure. First, the MJSR not only reduces the spectral redundancy, but also retains necessary correlation in spectral field during classification. Second, the stepwise optimization further explores the spatial correlation that significantly enhances the classification accuracy and robustness. As far as several universal quality evaluation indexes are concerned, the experimental results on Indian Pines and Pavia University demonstrate the superiority of our method compared with the state-of-the-art competitors.

ISECG Global Exploration Roadmap: A Stepwise Approach to Deep Space Exploration

NASA Technical Reports Server (NTRS)

Martinez, Roland; Goodliff, Kandyce; Whitley, Ryan

2013-01-01

In 2011, ISECG released the Global Exploration Roadmap (GER), advancing the "Global Exploration Strategy: The Framework for Coordination" by articulating the perspectives of participating agencies on exploration goals and objectives, mission scenarios, and coordination of exploration preparatory activities. The GER featured a stepwise development and demonstration of capabilities ultimately required for human exploration of Mars. In 2013 the GER was updated to reflect the ongoing evolution of agency's exploration policies and plans, informed by individual agency and coordinated analysis activities that are relevant to various elements of the GER framework as well as coordinated stakeholder engagement activities. For this release of version 2 of the GER in the mid 2013 timeframe, a modified mission scenario is presented, more firmly reflecting the importance of a stepwise evolution of critical capabilities provided by multiple partners necessary for executing increasingly complex missions to multiple destinations and leading to human exploration of Mars. This paper will describe the updated mission scenario, the changes since the release of version 1, the mission themes incorporated into the scenario, and risk reduction for Mars missions provided by exploration at various destinations.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies.

PubMed

Zhang, Xiaoshuai; Xue, Fuzhong; Liu, Hong; Zhu, Dianwen; Peng, Bin; Wiemels, Joseph L; Yang, Xiaowei

2014-12-10

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this "missing heritability" problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets. Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case-control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies. The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

Discrimination of Aurantii Fructus Immaturus and Fructus Poniciri Trifoliatae Immaturus by Flow Injection UV Spectroscopy (FIUV) and 1H NMR using Partial Least-squares Discriminant Analysis (PLS-DA)

USDA-ARS?s Scientific Manuscript database

Two simple fingerprinting methods, flow-injection UV spectroscopy (FIUV) and 1H nuclear magnetic resonance (NMR), for discrimination of Aurantii FructusImmaturus and Fructus Poniciri TrifoliataeImmaturususing were described. Both methods were combined with partial least-squares discriminant analysis...

[Associated factors in newborns with intrauterine growth retardation].

PubMed

Thompson-Chagoyán, Oscar C; Vega-Franco, Leopoldo

2008-01-01

To identify the risk factors implicated in the intrauterine growth retardation (IUGR) of neonates born in a social security institution. Case controls design study in 376 neonates: 188 with IUGR (weight < 10 percentile) and 188 without IUGR. When they born, information about 30 variables of risk for IUGR were obtained from mothers. Risk analysis and logistical regression (stepwise) were used. Odds ratios were significant for 12 of the variables. The model obtains by stepwise regression included: weight gain at pregnancy, prenatal care attendance, toxemia, chocolate ingestion, father's weight, and the environmental house. Must of the variables included in the model are related to socioeconomic disadvantages related to the risk of RCIU in the population.

Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

PubMed Central

Ro, Annie E.; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in Northern California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design. PMID:19485231

Apolipoprotein E4 serum concentration for increased sensitivity and specificity of diagnosis of drug treated Alzheimer's disease patients vs. drug treated parkinson's disease patients vs. age-matched normal controls.

PubMed

Goldknopf, Ira L; Park, Helen R; Sabbagh, Marwan

2012-12-01

Inasmuch as Alzheimer's disease (AD) is difficult to diagnose, patients with suspected dementias are often given FDA approved medications, including donepezil, rivastigmine, memantine HCl, or a combination, prior to diagnosis, and some respond with improved cognition. The present study demonstrates how concentrations of a select group of serum protein biomarkers can provide the basis for sensitive and specific differential diagnosis of AD in drug treated patients. Optimization is addressed by taking into account whether the patients and controls have or do not have increased risk of AD die to the presence or absence of Apolipoprotein E4. For differential diagnosis of AD, prospectively collected newly drawn blood serum samples were obtained from drug treated Alzheimer's disease and Parkinson's disease patients from a first (39 drug treated DTAD, and 31 age matched normal controls) and second medical center (56 drug treated DTPD, 47 age-matched normal controls). Analytically validated quantitative 2D gel electrophoresis (%CV ≤ 20%; LOD ≥ 0.5 ng/spot, 300 μg/ml of blood serum) was employed with patient and control sera for differential diagnosis of AD. Protein quantitation was subjected to statistical analysis by single variable Dot, Box and Whiskers and Receiver Operator Characteristics (ROC) plots for individual biomarker performance, and multivariate linear discriminant analysis for joint performance of groups of biomarkers. Protein spots were identified and characterized by LC MS/MS of in-gel trypsin digests, amino acid sequence spans of the identified peptides, and the protein spot molecular weights and isoelectric points. The single variable statistical profiles of 58 individual protein biomarker concentrations of the DTAD patient group differed from those of the normal and/or the disease control groups. Multivariate linear discriminant analysis of blood serum concentrations of the 58 proteins distinguished drug treated Alzheimer's disease (DTAD) patients from drug treated Parkinson's disease (DTPD) patients and age matched normal controls (collectively not-DTAD, DTAD Sensitivity 87.2%, Not-DTAD Specificity 87.2). Moreover, when the patients and controls were stratified into carriers or non-carriers of Alzheimer's high risk Apolipoprotein E 4 allele and/or the Apolipoprotein E4 protein, the DTAD, DTPD and control Apo E4 (+) profiles were more divergent from one another than the corresponding Apo E4 (-) profiles. Multivariate stepwise linear discriminant analysis selected 17 of the 58 biomarkers as optimal and complimentary for distinguishing Apo E4 (+) DTAD patients from Apo E4 (+) DTPD and Apo E4 (+) controls (collectively Apo E4 (+) not-DTAD, DTAD Sensitivity 100%, not-DTAD Specificity 100%) and 22 of the 58 biomarkers for distinguishing Apo E4 (-) DTAD patients from Apo E4 (-) DTPD and Apo E4 (-) controls (collectively Apo E4 (-) not-DTAD, DTAD Sensitivity 94.4%, not- DTAD Specificity 94.4%). Only 6 of the selected proteins were common to both the Apo E4 (+) and the Apo E4 (-) discriminant functions. Recombining of the results of Apo E4 (+) and Apo E4 (-) discriminations provided overall sensitivity for total DTAD of 97.4% and specificity for total not-DTAD of 95.7%. These results can form the basis of a blood test for differential diagnosis of Alzheimer's disease patients already under treatment (DTAD) by anti dementia drugs, including donepezil, rivastigmine, memantine HCl, or a combination thereof. Also, the profile differences and the rise in specificity and sensitivity obtained by handling the Apo E4 (+) and Apo E4 (-) groups separately supports the concept that they are different patient and control populations in terms of the "normal" physiology, the pathophysiology of disease, and the response to drug treatment. Taking that into account enables increased sensitivity and specificity of differential diagnosis of Alzheimer's disease.

Landslide Hazard Map of The Upper Tiber River Basin, Central Italy

NASA Astrophysics Data System (ADS)

Cardinali, M.; Carrara, A.; Guzzetti, F.; Reichenbach, P.

For the Upper Tiber River basin, which extends over 4000 km2 in Central Italy, a landslide hazard map was derived from a statistical model based on a mix of morpho- logical, lithological, structural and land use data. All these data were obtained from the analysis of different sets of aerial photographs, ranging in scale from 1:33,000 to 1:13,000, systematic field surveys and bibliographical information. Rock types were grouped in 37 units on the basis of the hard vs. soft rock percentage, as as- certained from photo-geological interpretation and field surveys. During the photo- interpretation, the spatial relations between bedding plane attitude and slope aspect were also systematically determined. The landslide inventory map recognised 17,600 slope-failures that cover nearly 12.5% of the basin area. Landslides, which are mainly slide flow slide earth-flow and compound or complex movements, were classified and mapped as shallow or deep seated. A DTM, with a grid resolution of 25x25 m, was derived from digitised contour lines of base topographic maps, 1:25,000.in scale. The basin was then automatically partitioned into nearly 16,000 main slope-units through a specifically-designed software module that, starting from a high quality DTM gen- erates fully connected and complementary drainage and divide networks and a wide spectrum of morphometric parameters. Main slope-units were then subdivided accord- ing to the major rock types cropping out in the basin generating over 28,700 hydro- morphological-lithological terrain-units. Using the presence/absence of landslide in each terrain unit, as the grouping variable, a stepwise discriminant function was ap- plied to the terrain units. of the 50 variables entered into the discriminant function, 15 are lithological, 15 morphological, 11 express the structural setting or bedding plane attitude, 7 refer to land use and the last 2 reflect local climatic conditions. The model proved to be capable of correctly classifying as stable or unstable over 75% of the terrain units.

Can cognitive assessment really discriminate early stages of Alzheimer's and behavioural variant frontotemporal dementia at initial clinical presentation?

PubMed

Reul, Sophia; Lohmann, Hubertus; Wiendl, Heinz; Duning, Thomas; Johnen, Andreas

2017-08-09

Neuropsychological testing is considered crucial for differential diagnosis of Alzheimer's disease (AD) and behavioural variant frontotemporal dementia (bvFTD). In-depth neuropsychological assessment revealed specific dysfunctions in the two dementia syndromes. However, a significant overlap of cognitive impairments exists in early disease stages. We questioned whether a standard neuropsychological assessment at initial clinical presentation can delineate patients with AD versus bvFTD. In a retrospective approach, we evaluated and compared how cognitive profiles assessed at initial clinical presentation predicted the diagnosis of later verified AD (n = 43) and bvFTD (n = 26). Additionally, the neuropsychological standard domains memory, language, visuospatial skills, executive functions, praxis and social cognition were subjected to stepwise discriminant analysis to compare their differential contribution to diagnosis. Regardless of diagnosis, a percentage of patients presented with major deterioration in a wide range of cognitive domains when compared with age-matched normative data. Only few significant differences were detected on the group level: Patients with AD were relatively more impaired in the verbal recall, verbal recognition, figure copy, and surprisingly in the executive subdomains, set shifting and processing speed whereas bvFTD was characterised by more deficits in imitation of face postures. A combination of tests for verbal recall, imitation of limb and face postures, and figure copy showed the greatest discriminatory power. Our results imply that the contribution of a standard neuropsychological assessment is limited for differential diagnosis of AD and bvFTD at initial presentation. In contrast to current clinical guidelines, executive functions are neither particularly nor exclusively impaired in patients with bvFTD when assessed within a standard clinical neuropsychological test battery. The significant overlap of bvFTD and AD concerning the profile of cognitive impairments questions current neuropsychological diagnostic criteria and calls for revision, regarding both the degree and the profile of cognitive deficits.

Attitudes Toward Obese Persons and Weight Locus of Control in Chinese Nurses: A Cross-sectional Survey.

PubMed

Wang, Yan; Ding, Ye; Song, Daoping; Zhu, Daqiao; Wang, Jianrong

2016-01-01

Obese individuals frequently experience weight-related bias or discrimination-even in healthcare settings. Although obesity bias has been associated with several demographic factors, little is known about the association of weight locus of control with bias against overweight persons or about weight bias among Chinese health professionals. The aim of the study was to examine attitudes toward obese patients in a sample of Chinese registered nurses (RNs) and the relationship between weight bias and nurses' weight locus of control. RNs working in nine community health service centers across Shanghai, China, answered three self-report questionnaires: The Attitudes Toward Obese Persons Scale (ATOP), the External Weight Locus of Control Subscale (eWLOC) from the Dieting Belief Scale, and a sociodemographic profile. Hierarchical, stepwise, multiple regression was used to predict ATOP scores. From among 385 invited, a total of 297 RNs took part in the study (77.1% response rate). Participants scored an average of 71.04 on the ATOP, indicating slightly positive attitudes toward obese persons, and 30.08 on the eWLOC, indicating a belief in the uncontrollability of body weight. Using hierarchical, stepwise, multiple regression, two predictors of ATOP scores were statistically significant (eWLOC scores and status as a specialist rather than generalist nurse), but explained variance was low. Chinese RNs seemed to have relatively neutral or even slightly positive attitudes toward obese persons. Those nurses who believed that obesity was beyond the individual's control or worked in specialties were more likely to have positive attitudes toward obese people. Improved understanding of the comprehensive etiology of obesity is needed.

[Relationships between electrophysiological characteristic of speech evoked auditory brainstem response and Mandarin monosyllable discriminative ability at different hearing impairment].

PubMed

Fu, Q Y; Liang, Y; Zou, A; Wang, T; Zhao, X D; Wan, J

2016-04-07

To investigate the relationships between electrophysiological characteristic of speech evoked auditory brainstem response(s-ABR) and Mandarin phonetically balanced maximum(PBmax) at different hearing impairment, so as to provide more clues for the mechanism of speech cognitive behavior. Forty-one ears in 41 normal hearing adults(NH), thirty ears in 30 conductive hearing loss patients(CHL) and twenty-seven ears in 27 sensorineural hearing loss patients(SNHL) were included in present study. The speech discrimination scores were obtained by Mandarin phonemic-balanced monosyllable lists via speech audiometric software. Their s-ABRs were recorded with speech syllables /da/ with the intensity of phonetically balanced maximum(PBmax). The electrophysiological characteristic of s-ABR, as well as the relationships between PBmax and s-ABR parameters including latency in time domain, fundamental frequency(F0) and first formant(F1) in frequency domain were analyzed statistically. All subjects completed good speech perception tests and PBmax of CHL and SNHL had no significant difference (P>0.05), but both significantly less than that of NH (P<0.05). While divided the subjects into three groups by 90%

Neural networks using broadband spectral discriminators reduces illumination required for broccoli identification in weedy fields

NASA Astrophysics Data System (ADS)

Hahn, Federico

1996-03-01

Statistical discriminative analysis and neural networks were used to prove that crop/weed/soil discrimination by optical reflectance was feasible. The wavelengths selected as inputs on those neural networks were ten nanometers width, reducing the total collected radiation for the sensor. Spectral data collected from several farms having different weed populations were introduced to discriminant analysis. The best discriminant wavelengths were used to build a wavelength histogram which selected the three best spectral broadbands for broccoli/weed/soil discrimination. The broadbands were analyzed using a new single broadband discriminator index named the discriminative integration index, DII, and the DII values obtained were used to train a neural network. This paper introduces the index concept, its results and its use for minimizing artificial lightning requirements with broadband spectral measurements for broccoli/weed/soil discrimination.

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images

PubMed Central

Khansari, Maziyar M; O’Neill, William; Penn, Richard; Chau, Felix; Blair, Norman P; Shahidi, Mahnaz

2016-01-01

The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method’s discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring. PMID:27446692

The Effect of Aging and Severity of Sleep Apnea on Heart Rate Variability Indices in Obstructive Sleep Apnea Syndrome

PubMed Central

Song, Man-Kyu; Ha, Jee Hyun; Ryu, Seung-Ho; Yu, Jaehak

2012-01-01

Objective This study aims to analyze how much heart rate variability (HRV) indices discriminatively respond to age and severity of sleep apnea in the obstructive sleep apnea syndrome (OSAS). Methods 176 male OSAS patients were classified into four groups according to their age and apnea-hypopnea index (AHI). The HRV indices were compared via analysis of covariance (ANCOVA). In particular, the partial correlation method was performed to identify the most statistically significant HRV indices in the time and frequency domains. Stepwise multiple linear regressions were further executed to examine the effects of age, AHI, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and sleep parameters on the significant HRV indices. Results The partial correlation analysis yielded the NN50 count (defined as the number of adjacent R-wave to R-wave intervals differing by more than 50 ms) and low frequency/high frequency (LF/HF) ratio to be two most statistically significant HRV indices in both time and frequency domains. The two indices showed significant differences between the groups. The NN50 count was affected by age (p<0.001) and DBP (p=0.039), while the LF/HF ratio was affected by AHI (p<0.001), the amount of Stage 2 sleep (p=0.005), and age (p=0.021) in the order named in the regression analysis. Conclusion The NN50 count more sensitively responded to age than to AHI, suggesting that the index is mainly associated with an age-related parasympathetic system. On the contrary, the LF/HF ratio responded to AHI more sensitively than to age, suggesting that it is mainly associated with a sympathetic tone likely reflecting the severity of sleep apnea. PMID:22396687

Exhaled gases online measurements for esophageal cancer patients and healthy people by proton transfer reaction mass spectrometry.

PubMed

Zou, Xue; Zhou, Wenzhao; Lu, Yan; Shen, Chengyin; Hu, Zongtao; Wang, Hongzhi; Jiang, Haihe; Chu, Yannan

2016-11-01

Esophageal cancer is a prevalent malignancy. There is a considerable demand for developing a fast and noninvasive method to screen out the suspect esophageal cancer patients who may undergo further clinical diagnosis. The exhaled breathes from 29 esophageal cancer patients and 57 healthy people were directly measured using our home-made proton transfer reaction mass spectrometer (PTR-MS). Mann-Whitney U test and stepwise discriminant analysis were applied to identify the ions in the breath mass spectral data which can distinguish cancer cohort from healthy group. Receiver operating characteristics (ROC) analysis was also performed. Seven kinds of ions in the breath mass spectrum, viz., m/z 136, m/z 34, m/z 63, m/z 27, m/z 95, m/z 107 and m/z 45, have been found to distinguish between the esophageal cancer patients and healthy people with a sensitivity of 86.2% and a specificity of 89.5%, respectively. Compared with that from the healthy people, the breath mass spectra from esophageal cancer patients show that the mediant intensities of five kinds of ions were decrease and the rest two kinds of ions were increase. ROC analysis gave the area under the curve (AUC) of 0.943. This pilot study shows that the ionic characteristics of exhaled VOCs detected by PTR-MS may be used to differentiate between the esophageal cancer patients and the healthy people. Although the breath tests for more patients are needed to confirm such results, the present work indicates that the PTR-MS may be a promising method in the esophageal cancer screening. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Return to work after a myocardial infarction: the influence of background factors, work characteristics and illness severity.

PubMed

Maeland, J G; Havik, O E

1986-01-01

The relationship between return to work (RTW) within 6 months after a myocardial infarction (MI) and selected demographic factors, characteristics of prior work situation, pre-MI health status, and clinical severity of the MI has been studied in 249 patients below 67 years of age living in urban and rural areas of Western Norway. At the follow-up 8 out of 10 urban patients and 6 out of 10 rural patients were back at work. The RTW rate for the total sample was 73%. Age below 51 years, high educational and income level, working in tertiary industries, and in a job characterized by low physical activity and little psychosocial stress were all factors associated with a favourable work resumption. Multivariate analyses showed that socioeconomic or work-related factors could not fully explain the urban-rural differences in RTW. Stepwise discriminant analysis identified the following factors as important and independent predictors for RTW: Place of residence, age, education, perceived job stress, and clinical complications during hospitalization. Failure to return to work after a MI can be explained by a number of individual and social factors and only to a limited degree by the medical status of the patient. More knowledge is needed concerning the socio-cultural differences among both patients and attending physicians in attitudes towards work resumption after a MI.

In-Vivo Fluorescence Spectroscopy Of Normal And Atherosclerotic Arteries

NASA Astrophysics Data System (ADS)

Deckelbaum, Lawrence I.; Sarembock, Ian J.; Stetz, Mark L.; O'Brien, Kenneth M.; Cutruzzola, Francis W.; Gmitro, Arthur F.; Ezekowitz, Michael D.

1988-06-01

Laser-induced fluorescence spectroscopy can discriminate atherosclerotic from normal arteries in-vitro and may thus potentially guide laser angioplasty. To evaluate the feasibility of laser-induced fluorescence spectroscopy in a living blood-filled arterial system we performed fiberoptic laser-induced fluorescence spectroscopy in a rabbit model of focal femoral atherosclerosis. A laser-induced fluorescence spectroscopy score was derived from stepwise linear regression analysis of in-vitro spectra to distinguish normal aorta (score>0) from atherosclerotic femoral artery (score<0). A 400 u silica fiber, coupled to a helium cadmium laser and optical multichannel analyzer, was inserted through a 5F catheter to induce and record in-vivo fluorescence from femoral and aortoiliac arteries. Arterial spectra could be recorded in all animals (n=10: 5 occlusions, 5 stenoses). Blood spectra were of low intensity and were easily distinguished from arterial spectra. The scores (mean ± SEM) for the in-vivo spectra were -0.69 +/- 0.29 for artherosclerotic femoral, and +0.54 ±. 0.15 for normal aorta (p<.01 p=NS compared to in-vitro spectra). In-vitro, a fiber tip to tissue distance <50 u was necessary for adequate arterial LIFS in blood. At larger distances low intensity blood spectra were recorded (1/20 the intensity of tissue spectra). Thus, fiberoptic laser-induced fluorescence spectroscopy can be sucessfully performed in a blood filled artery provided the fiber tip is approximated to the tissue.

Prediction of in vivo developmental toxicity by combination of Hand1-Luc embryonic stem cell test and metabolic stability test with clarification of metabolically inapplicable candidates.

PubMed

Nagahori, Hirohisa; Suzuki, Noriyuki; Le Coz, Florian; Omori, Takashi; Saito, Koichi

2016-09-30

Hand1-Luc Embryonic Stem Cell Test (Hand1-Luc EST) is a promising alternative method for evaluation of developmental toxicity. However, the problems of predictivity have remained due to appropriateness of the solubility, metabolic system, and prediction model. Therefore, we assessed the usefulness of rat liver S9 metabolic stability test using LC-MS/MS to develop new prediction model. A total of 71 chemicals were analyzed by measuring cytotoxicity and differentiation toxicity, and highly reproducible (CV=20%) results were obtained. The first prediction model was developed by discriminant analysis performed on a full dataset using Hand1-Luc EST, and 66.2% of the chemicals were correctly classified by the cross-validated classification. A second model was developed with additional descriptors obtained from the metabolic stability test to calculate hepatic availability, and an accuracy of 83.3% was obtained with applicability domain of 50.7% (=36/71) after exclusion of 22 metabolically inapplicable candidates, which potentially have a metabolic activation property. A step-wise prediction scheme with combination of Hand1-Luc EST and metabolic stability test was therefore proposed. The current results provide a promising in vitro test method for accurately predicting in vivo developmental toxicity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Discrimination in Degradability of Soil Pyrogenic Organic Matter Follows a Return-On-Energy-Investment Principle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harvey, Omar R.; Myers-Pigg, Allison N.; Kuo, Li-Jung

A fundamental understanding of biodegradability is central to elucidating the role(s) of pyrogenic organic matter (PyOM) in biogeochemical cycles. Since microbial community and ecosystem dynamics are driven by net energy flows, then a quantitative assessment of energy value versus energy requirement for oxidation of PyOM should yield important insights into their biodegradability. We used bomb calorimetry, step-wise isothermal thermogravimetric analysis (isoTGA) and 5-year in-situ bidegradation data, to develop energy-biodegradability relationships for a suite of plant- and manure-derived PyOM (n = 10). The net energy value (ΔE) for PyOM was between 4.0 and 175 kJ mol-1; with manure-derived PyOM having themore » highest ΔE. Thermal-oxidation activation energy (Ea) requirements ranged from 51 to 125 kJ mol-1, with wood-derived PyOM having the highest Ea requirements. We propose a return-on-investment (ROI) parameter (ΔE/Ea) for differentiating short-to-medium term biodegradability of PyOM and deciphering if biodegradation will most likely proceed via co-metabolism (ROI < 1) or direct metabolism (ROI ≥ 1). The ROI-biodegradability relationship was sigmoidal with higher biodegradability associated with PyOM of higher ROI; indicating that microbes exhibit a higher preference for “high investment value” PyOM.« less

A novel P300-based brain-computer interface stimulus presentation paradigm: moving beyond rows and columns

PubMed Central

Townsend, G.; LaPallo, B.K.; Boulay, C.B.; Krusienski, D.J.; Frye, G.E.; Hauser, C.K.; Schwartz, N.E.; Vaughan, T.M.; Wolpaw, J.R.; Sellers, E.W.

2010-01-01

Objective An electroencephalographic brain-computer interface (BCI) can provide a non-muscular means of communication for people with amyotrophic lateral sclerosis (ALS) or other neuromuscular disorders. We present a novel P300-based BCI stimulus presentation – the checkerboard paradigm (CBP). CBP performance is compared to that of the standard row/column paradigm (RCP) introduced by Farwell and Donchin (1988). Methods Using an 8×9 matrix of alphanumeric characters and keyboard commands, 18 participants used the CBP and RCP in counter-balanced fashion. With approximately 9 – 12 minutes of calibration data, we used a stepwise linear discriminant analysis for online classification of subsequent data. Results Mean online accuracy was significantly higher for the CBP, 92%, than for the RCP, 77%. Correcting for extra selections due to errors, mean bit rate was also significantly higher for the CBP, 23 bits/min, than for the RCP, 17 bits/min. Moreover, the two paradigms produced significantly different waveforms. Initial tests with three advanced ALS participants produced similar results. Furthermore, these individuals preferred the CBP to the RCP. Conclusions These results suggest that the CBP is markedly superior to the RCP in performance and user acceptability. Significance The CBP has the potential to provide a substantially more effective BCI than the RCP. This is especially important for people with severe neuromuscular disabilities. PMID:20347387

Difference in symptom profile between generalized anxiety disorder and anxiety secondary to hyperthyroidism.

PubMed

Iacovides, A; Fountoulakis, K N; Grammaticos, P; Ierodiakonou, C

2000-01-01

The differential diagnosis between subclinical hyperthyroidism and Generalized Anxiety Disorder (GAD) is often a difficult problem to solve without laboratory examination. The aim of this pilot study was to assess whether there are differences in the symptom profile between these two disorders. Fifty patients took part in the study: Twenty-five were hyperthyroid patients, and twenty-five were GAD patients. The diagnosis was based on the TSH values and the DSM-IV criteria, respectively. The Hamilton Anxiety Scale (HAS) and the list of fifty-one symptoms produced by the detailed expansion of HAS items were used to quantify the anxiety symptomatology. The differences in the frequencies between the two diagnostic groups were calculated at each categorical response for every item of both scales. Forward Stepwise Discriminant Function Analysis was performed twice using HAS items and the fifty-one-list items. The symptoms of anxiety in subclinical hyperthyroidism were not identical to those of GAD. Four Hyperthyroid/Anxiety Indices (HAI I-IV) were developed. These indices reach optimum classification of patients (3 of them reach 100% sensitivity and specificity). The results of the current study suggest that it is possible to differentiate between GAD and subclinical cases of hyperthyroidism by the careful study of clinical symptomatology. This may be of particular help in isolated areas without laboratory support, but replication of the indices in other samples is indicated.

Dietary relationships among shrumsteppe passerine birds: competition or opportunism in a variable environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rotenberry, J.T.

1980-03-01

The suggestion that in less stable environments resource limitation and subsequent interspecific competition may be relatively unimportant in determining bird community structure is explored by examining the dietary relationships within a guild of three ground-foraging passerine birds (Horned Lark, Sage Sparrow, and Western Meadowlark) in the shrubsteppe of southeastern Washington, USA, an area of severe, arid, unstable climate. General dietary analyses indicated a strong temporal component to the organization of bird diets: different species collected at the same time ate much the same things while the same species collected at different times ate different things. This pattern is reinforced bymore » cluster analysis and stepwise discriminant analysis. Similarities in diet extended to other components as well. Dietary diversities tended to be the same for contemporaneous collections of birds, as did averge prey sizes, although the latter evidenced a few statistically significant exceptions. Theoretically predicted relationships between diet and trophic structure morphology emerged only at the most general level, and even then were not always observed. In general, differences in body size or bill length were insufficient to account for variations in prey sizes, although meadowlarks did on occasion take significantly larger items than the other, smaller species. Average prey size was significantly correlated with the proportion of seeds in the diet and varied seasonally as seed consumption varied. Several aspects of this study indicate that shrubsteppe passerines are largely opportunistic in their foraging and diet selection, and that the apparent absence of fine tuning to their competitive milieu is most likely a function of the variable environment in which they coexist.« less

Vocalizations of adult male Asian koels (Eudynamys scolopacea) in the breeding season.

PubMed

Khan, Abdul Aziz; Qureshi, Irfan Zia

2017-01-01

Defining the vocal repertoire provides a basis for understanding the role of acoustic signals in sexual and social interactions of an animal. The Asian koel (Eudynamys scolopacea) is a migratory bird which spends its summer breeding season in the plains of Pakistan. The bird is typically wary and secretive but produces loud and distinct calls, making it easily detected when unseen. Like the other birds in the wild, presumably Asian koels use their calls for social cohesion and coordination of different behaviors. To date, the description of vocal repertoire of the male Asian koel has been lacking. Presently we analyzed and described for the first time the vocalizations of the adult male Asian koel, recorded in two consecutive breeding seasons. Using 10 call parameters, we categorized the vocalization type into six different categories on the basis of spectrogram and statistical analyses, namely the; "type 1 cooee call", "type 2 cooee call", "type 1 coegh call", "type 2 coegh call", "wurroo call" and "coe call". These names were assigned not on the basis of functional analysis and were therefore onomatopoeic. Stepwise cross validated discriminant function analysis classified the vocalization correctly (100%) into the predicted vocal categories that we initially classified on the basis of spectrographic examination. Our findings enrich the biological knowledge about vocalizations of the adult male Asian koel and provide a foundation for future acoustic monitoring of the species, as well as for comparative studies with vocalizations of other bird species of the cuckoo family. Further studies on the vocalizations of the Asian koel are required to unravel their functions in sexual selection and individual recognition.

Development and Psychometric Evaluation of the Brief Adolescent Gambling Screen (BAGS)

PubMed Central

Stinchfield, Randy; Wynne, Harold; Wiebe, Jamie; Tremblay, Joel

2017-01-01

The purpose of this study was to develop and evaluate the initial reliability, validity and classification accuracy of a new brief screen for adolescent problem gambling. The three-item Brief Adolescent Gambling Screen (BAGS) was derived from the nine-item Gambling Problem Severity Subscale (GPSS) of the Canadian Adolescent Gambling Inventory (CAGI) using a secondary analysis of existing CAGI data. The sample of 105 adolescents included 49 females and 56 males from Canada who completed the CAGI, a self-administered measure of DSM-IV diagnostic criteria for Pathological Gambling, and a clinician-administered diagnostic interview including the DSM-IV diagnostic criteria for Pathological Gambling (both of which were adapted to yield DSM-5 Gambling Disorder diagnosis). A stepwise multivariate discriminant function analysis selected three GPSS items as the best predictors of a diagnosis of Gambling Disorder. The BAGS demonstrated satisfactory estimates of reliability, validity and classification accuracy and was equivalent to the nine-item GPSS of the CAGI and the BAGS was more accurate than the SOGS-RA. The BAGS estimates of classification accuracy include hit rate = 0.95, sensitivity = 0.88, specificity = 0.98, false positive rate = 0.02, and false negative rate = 0.12. Since these classification estimates are preliminary, derived from a relatively small sample size, and based upon the same sample from which the items were selected, it will be important to cross-validate the BAGS with larger and more diverse samples. The BAGS should be evaluated for use as a screening tool in both clinical and school settings as well as epidemiological surveys. PMID:29312064

Discrimination Enhancement with Transient Feature Analysis of a Graphene Chemical Sensor.

PubMed

Nallon, Eric C; Schnee, Vincent P; Bright, Collin J; Polcha, Michael P; Li, Qiliang

2016-01-19

A graphene chemical sensor is subjected to a set of structurally and chemically similar hydrocarbon compounds consisting of toluene, o-xylene, p-xylene, and mesitylene. The fractional change in resistance of the sensor upon exposure to these compounds exhibits a similar response magnitude among compounds, whereas large variation is observed within repetitions for each compound, causing a response overlap. Therefore, traditional features depending on maximum response change will cause confusion during further discrimination and classification analysis. More robust features that are less sensitive to concentration, sampling, and drift variability would provide higher quality information. In this work, we have explored the advantage of using transient-based exponential fitting coefficients to enhance the discrimination of similar compounds. The advantages of such feature analysis to discriminate each compound is evaluated using principle component analysis (PCA). In addition, machine learning-based classification algorithms were used to compare the prediction accuracies when using fitting coefficients as features. The additional features greatly enhanced the discrimination between compounds while performing PCA and also improved the prediction accuracy by 34% when using linear discrimination analysis.

Step-wise refolding of recombinant proteins.

PubMed

Tsumoto, Kouhei; Arakawa, Tsutomu; Chen, Linda

2010-04-01

Protein refolding is still on trial-and-error basis. Here we describe step-wise dialysis refolding, in which denaturant concentration is altered in step-wise fashion. This technology controls the folding pathway by adjusting the concentrations of the denaturant and other solvent additives to induce sequential folding or disulfide formation.

Discrimination between smiling faces: Human observers vs. automated face analysis.

PubMed

Del Líbano, Mario; Calvo, Manuel G; Fernández-Martín, Andrés; Recio, Guillermo

2018-05-11

This study investigated (a) how prototypical happy faces (with happy eyes and a smile) can be discriminated from blended expressions with a smile but non-happy eyes, depending on type and intensity of the eye expression; and (b) how smile discrimination differs for human perceivers versus automated face analysis, depending on affective valence and morphological facial features. Human observers categorized faces as happy or non-happy, or rated their valence. Automated analysis (FACET software) computed seven expressions (including joy/happiness) and 20 facial action units (AUs). Physical properties (low-level image statistics and visual saliency) of the face stimuli were controlled. Results revealed, first, that some blended expressions (especially, with angry eyes) had lower discrimination thresholds (i.e., they were identified as "non-happy" at lower non-happy eye intensities) than others (especially, with neutral eyes). Second, discrimination sensitivity was better for human perceivers than for automated FACET analysis. As an additional finding, affective valence predicted human discrimination performance, whereas morphological AUs predicted FACET discrimination. FACET can be a valid tool for categorizing prototypical expressions, but is currently more limited than human observers for discrimination of blended expressions. Configural processing facilitates detection of in/congruence(s) across regions, and thus detection of non-genuine smiling faces (due to non-happy eyes). Copyright © 2018 Elsevier B.V. All rights reserved.

DIFFERENTIATION OF AURANTII FRUCTUS IMMATURUS AND FRUCTUS PONICIRI TRIFOLIATAE IMMATURUS BY FLOW-INJECTION WITH ULTRAVIOLET SPECTROSCOPIC DETECTION AND PROTON NUCLEAR MAGNETIC RESONANCE USING PARTIAL LEAST-SQUARES DISCRIMINANT ANALYSIS.

PubMed

Zhang, Mengliang; Zhao, Yang; Harrington, Peter de B; Chen, Pei

2016-03-01

Two simple fingerprinting methods, flow-injection coupled to ultraviolet spectroscopy and proton nuclear magnetic resonance, were used for discriminating between Aurantii fructus immaturus and Fructus poniciri trifoliatae immaturus . Both methods were combined with partial least-squares discriminant analysis. In the flow-injection method, four data representations were evaluated: total ultraviolet absorbance chromatograms, averaged ultraviolet spectra, absorbance at 193, 205, 225, and 283 nm, and absorbance at 225 and 283 nm. Prediction rates of 100% were achieved for all data representations by partial least-squares discriminant analysis using leave-one-sample-out cross-validation. The prediction rate for the proton nuclear magnetic resonance data by partial least-squares discriminant analysis with leave-one-sample-out cross-validation was also 100%. A new validation set of data was collected by flow-injection with ultraviolet spectroscopic detection two weeks later and predicted by partial least-squares discriminant analysis models constructed by the initial data representations with no parameter changes. The classification rates were 95% with the total ultraviolet absorbance chromatograms datasets and 100% with the other three datasets. Flow-injection with ultraviolet detection and proton nuclear magnetic resonance are simple, high throughput, and low-cost methods for discrimination studies.

Advanced Signal Processing Analysis of Laser-Induced Breakdown Spectroscopy Data for the Discrimination of Obsidian Sources

DTIC Science & Technology

2012-02-09

different sources [12,13], but the analytical techniques needed for such analysis (XRD, INAA , & ICP-MS) are time consuming and require expensive...partial least-squares discriminant analysis (PLSDA) that used the SIMPLS solving method [33]. In the experi- ment design, a leave-one-sample-out (LOSO) para...REPORT Advanced signal processing analysis of laser-induced breakdown spectroscopy data for the discrimination of obsidian sources 14. ABSTRACT 16

Layer moduli of Nebraska pavements for the new Mechanistic-Empirical Pavement Design Guide (MEPDG).

DOT National Transportation Integrated Search

2010-12-01

As a step-wise implementation effort of the Mechanistic-Empirical Pavement Design Guide (MEPDG) for the design : and analysis of Nebraska flexible pavement systems, this research developed a database of layer moduli dynamic : modulus, creep compl...

Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine.

PubMed

Monakhova, Yulia B; Godelmann, Rolf; Kuballa, Thomas; Mushtakova, Svetlana P; Rutledge, Douglas N

2015-08-15

Discriminant analysis (DA) methods, such as linear discriminant analysis (LDA) or factorial discriminant analysis (FDA), are well-known chemometric approaches for solving classification problems in chemistry. In most applications, principle components analysis (PCA) is used as the first step to generate orthogonal eigenvectors and the corresponding sample scores are utilized to generate discriminant features for the discrimination. Independent components analysis (ICA) based on the minimization of mutual information can be used as an alternative to PCA as a preprocessing tool for LDA and FDA classification. To illustrate the performance of this ICA/DA methodology, four representative nuclear magnetic resonance (NMR) data sets of wine samples were used. The classification was performed regarding grape variety, year of vintage and geographical origin. The average increase for ICA/DA in comparison with PCA/DA in the percentage of correct classification varied between 6±1% and 8±2%. The maximum increase in classification efficiency of 11±2% was observed for discrimination of the year of vintage (ICA/FDA) and geographical origin (ICA/LDA). The procedure to determine the number of extracted features (PCs, ICs) for the optimum DA models was discussed. The use of independent components (ICs) instead of principle components (PCs) resulted in improved classification performance of DA methods. The ICA/LDA method is preferable to ICA/FDA for recognition tasks based on NMR spectroscopic measurements. Copyright © 2015 Elsevier B.V. All rights reserved.

Links between patterns of racial socialization and discrimination experiences and psychological adjustment: a cluster analysis.

PubMed

Ajayi, Alex A; Syed, Moin

2014-10-01

This study used a person-oriented analytic approach to identify meaningful patterns of barriers-focused racial socialization and perceived racial discrimination experiences in a sample of 295 late adolescents. Using cluster analysis, three distinct groups were identified: Low Barrier Socialization-Low Discrimination, High Barrier Socialization-Low Discrimination, and High Barrier Socialization-High Discrimination clusters. These groups were substantively unique in terms of the frequency of racial socialization messages about bias preparation and out-group mistrust its members received and their actual perceived discrimination experiences. Further, individuals in the High Barrier Socialization-High Discrimination cluster reported significantly higher depressive symptoms than those in the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. However, no differences in adjustment were observed between the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. Overall, the findings highlight important individual differences in how young people of color experience their race and how these differences have significant implications on psychological adjustment. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Plausibility assessment of a 2-state self-paced mental task-based BCI using the no-control performance analysis.

PubMed

Faradji, Farhad; Ward, Rabab K; Birch, Gary E

2009-06-15

The feasibility of having a self-paced brain-computer interface (BCI) based on mental tasks is investigated. The EEG signals of four subjects performing five mental tasks each are used in the design of a 2-state self-paced BCI. The output of the BCI should only be activated when the subject performs a specific mental task and should remain inactive otherwise. For each subject and each task, the feature coefficient and the classifier that yield the best performance are selected, using the autoregressive coefficients as the features. The classifier with a zero false positive rate and the highest true positive rate is selected as the best classifier. The classifiers tested include: linear discriminant analysis, quadratic discriminant analysis, Mahalanobis discriminant analysis, support vector machine, and radial basis function neural network. The results show that: (1) some classifiers obtained the desired zero false positive rate; (2) the linear discriminant analysis classifier does not yield acceptable performance; (3) the quadratic discriminant analysis classifier outperforms the Mahalanobis discriminant analysis classifier and performs almost as well as the radial basis function neural network; and (4) the support vector machine classifier has the highest true positive rates but unfortunately has nonzero false positive rates in most cases.

Texture analysis of tissues in Gleason grading of prostate cancer

NASA Astrophysics Data System (ADS)

Alexandratou, Eleni; Yova, Dido; Gorpas, Dimitris; Maragos, Petros; Agrogiannis, George; Kavantzas, Nikolaos

2008-02-01

Prostate cancer is a common malignancy among maturing men and the second leading cause of cancer death in USA. Histopathological grading of prostate cancer is based on tissue structural abnormalities. Gleason grading system is the gold standard and is based on the organization features of prostatic glands. Although Gleason score has contributed on cancer prognosis and on treatment planning, its accuracy is about 58%, with this percentage to be lower in GG2, GG3 and GG5 grading. On the other hand it is strongly affected by "inter- and intra observer variations", making the whole process very subjective. Therefore, there is need for the development of grading tools based on imaging and computer vision techniques for a more accurate prostate cancer prognosis. The aim of this paper is the development of a novel method for objective grading of biopsy specimen in order to support histopathological prognosis of the tumor. This new method is based on texture analysis techniques, and particularly on Gray Level Co-occurrence Matrix (GLCM) that estimates image properties related to second order statistics. Histopathological images of prostate cancer, from Gleason grade2 to Gleason grade 5, were acquired and subjected to image texture analysis. Thirteen texture characteristics were calculated from this matrix as they were proposed by Haralick. Using stepwise variable selection, a subset of four characteristics were selected and used for the description and classification of each image field. The selected characteristics profile was used for grading the specimen with the multiparameter statistical method of multiple logistic discrimination analysis. The subset of these characteristics provided 87% correct grading of the specimens. The addition of any of the remaining characteristics did not improve significantly the diagnostic ability of the method. This study demonstrated that texture analysis techniques could provide valuable grading decision support to the pathologists, concerning prostate cancer prognosis.

Application of otolith shape analysis for stock discrimination and species identification of five goby species (Perciformes: Gobiidae) in the northern Chinese coastal waters

NASA Astrophysics Data System (ADS)

Yu, Xin; Cao, Liang; Liu, Jinhu; Zhao, Bo; Shan, Xiujuan; Dou, Shuozeng

2014-09-01

We tested the use of otolith shape analysis to discriminate between species and stocks of five goby species ( Ctenotrypauchen chinensis, Odontamblyopus lacepedii, Amblychaeturichthys hexanema, Chaeturichthys stigmatias, and Acanthogobius hasta) found in northern Chinese coastal waters. The five species were well differentiated with high overall classification success using shape indices (83.7%), elliptic Fourier coefficients (98.6%), or the combination of both methods (94.9%). However, shape analysis alone was only moderately successful at discriminating among the four stocks (Liaodong Bay, LD; Bohai Bay, BH; Huanghe (Yellow) River estuary HRE, and Jiaozhou Bay, JZ stocks) of A. hasta (50%-54%) and C. stigmatias (65.7%-75.8%). For these two species, shape analysis was moderately successful at discriminating the HRE or JZ stocks from other stocks, but failed to effectively identify the LD and BH stocks. A large number of otoliths were misclassified between the HRE and JZ stocks, which are geographically well separated. The classification success for stock discrimination was higher using elliptic Fourier coefficients alone (70.2%) or in combination with shape indices (75.8%) than using only shape indices (65.7%) in C. stigmatias whereas there was little difference among the three methods for A. hasta. Our results supported the common belief that otolith shape analysis is generally more effective for interspecific identification than intraspecific discrimination. Moreover, compared with shape indices analysis, Fourier analysis improves classification success during inter- and intra-species discrimination by otolith shape analysis, although this did not necessarily always occur in all fish species.

[Discrimination of Red Tide algae by fluorescence spectra and principle component analysis].

PubMed

Su, Rong-guo; Hu, Xu-peng; Zhang, Chuan-song; Wang, Xiu-lin

2007-07-01

Fluorescence discrimination technology for 11 species of the Red Tide algae at genus level was constructed by principle component analysis and non-negative least squares. Rayleigh and Raman scattering peaks of 3D fluorescence spectra were eliminated by Delaunay triangulation method. According to the results of Fisher linear discrimination, the first principle component score and the second component score of 3D fluorescence spectra were chosen as discriminant feature and the feature base was established. The 11 algae species were tested, and more than 85% samples were accurately determinated, especially for Prorocentrum donghaiense, Skeletonema costatum, Gymnodinium sp., which have frequently brought Red tide in the East China Sea. More than 95% samples were right discriminated. The results showed that the genus discriminant feature of 3D fluorescence spectra of Red Tide algae given by principle component analysis could work well.

Fast discrimination of hydroxypropyl methyl cellulose using portable Raman spectrometer and multivariate methods

NASA Astrophysics Data System (ADS)

Song, Biao; Lu, Dan; Peng, Ming; Li, Xia; Zou, Ye; Huang, Meizhen; Lu, Feng

2017-02-01

Raman spectroscopy is developed as a fast and non-destructive method for the discrimination and classification of hydroxypropyl methyl cellulose (HPMC) samples. 44 E series and 41 K series of HPMC samples are measured by a self-developed portable Raman spectrometer (Hx-Raman) which is excited by a 785 nm diode laser and the spectrum range is 200-2700 cm-1 with a resolution (FWHM) of 6 cm-1. Multivariate analysis is applied for discrimination of E series from K series. By methods of principal components analysis (PCA) and Fisher discriminant analysis (FDA), a discrimination result with sensitivity of 90.91% and specificity of 95.12% is achieved. The corresponding receiver operating characteristic (ROC) is 0.99, indicting the accuracy of the predictive model. This result demonstrates the prospect of portable Raman spectrometer for rapid, non-destructive classification and discrimination of E series and K series samples of HPMC.

Declining Bias and Gender Wage Discrimination? A Meta-Regression Analysis

ERIC Educational Resources Information Center

Jarrell, Stephen B.; Stanley, T. D.

2004-01-01

The meta-regression analysis reveals that there is a strong tendency for discrimination estimates to fall and wage discrimination exist against the woman. The biasing effect of researchers' gender of not correcting for selection bias has weakened and changes in labor market have made it less important.

From Equal to Equivalent Pay: Salary Discrimination in Academia

ERIC Educational Resources Information Center

Greenfield, Ester

1977-01-01

Examines the federal statutes barring sex discrimination in employment and argues that the work of any two professors is comparable but not equal. Suggests using regression analysis to prove salary discrimination and discusses the legal justification for adopting regression analysis and the standard of comparable pay for comparable work.…

Perceived Discrimination and Health: A Meta-Analytic Review

ERIC Educational Resources Information Center

Pascoe, Elizabeth A.; Richman, Laura Smart

2009-01-01

Perceived discrimination has been studied with regard to its impact on several types of health effects. This meta-analysis provides a comprehensive account of the relationships between multiple forms of perceived discrimination and both mental and physical health outcomes. In addition, this meta-analysis examines potential mechanisms by which…

Auditory Proprioceptive Integration: Effects of Real-Time Kinematic Auditory Feedback on Knee Proprioception

PubMed Central

Ghai, Shashank; Schmitz, Gerd; Hwang, Tong-Hun; Effenberg, Alfred O.

2018-01-01

The purpose of the study was to assess the influence of real-time auditory feedback on knee proprioception. Thirty healthy participants were randomly allocated to control (n = 15), and experimental group I (15). The participants performed an active knee-repositioning task using their dominant leg, with/without additional real-time auditory feedback where the frequency was mapped in a convergent manner to two different target angles (40 and 75°). Statistical analysis revealed significant enhancement in knee re-positioning accuracy for the constant and absolute error with real-time auditory feedback, within and across the groups. Besides this convergent condition, we established a second divergent condition. Here, a step-wise transposition of frequency was performed to explore whether a systematic tuning between auditory-proprioceptive repositioning exists. No significant effects were identified in this divergent auditory feedback condition. An additional experimental group II (n = 20) was further included. Here, we investigated the influence of a larger magnitude and directional change of step-wise transposition of the frequency. In a first step, results confirm the findings of experiment I. Moreover, significant effects on knee auditory-proprioception repositioning were evident when divergent auditory feedback was applied. During the step-wise transposition participants showed systematic modulation of knee movements in the opposite direction of transposition. We confirm that knee re-positioning accuracy can be enhanced with concurrent application of real-time auditory feedback and that knee re-positioning can modulated in a goal-directed manner with step-wise transposition of frequency. Clinical implications are discussed with respect to joint position sense in rehabilitation settings. PMID:29568259

Diels–Alder Reactions of Allene with Benzene and Butadiene: Concerted, Stepwise, and Ambimodal Transition States

PubMed Central

2015-01-01

Multiconfigurational complete active space methods (CASSCF and CASPT2) have been used to investigate the (4 + 2) cycloadditions of allene with butadiene and with benzene. Both concerted and stepwise radical pathways were examined to determine the mechanism of the Diels–Alder reactions with an allene dienophile. Reaction with butadiene occurs via a single ambimodal transition state that can lead to either the concerted or stepwise trajectories along the potential energy surface, while reaction with benzene involves two separate transition states and favors the concerted mechanism relative to the stepwise mechanism via a diradical intermediate. PMID:25216056

DEVELOPMENT AND PSYCHOMETRIC TESTING OF A MULTIDIMENSIONAL INSTRUMENT OF PERCEIVED DISCRIMINATION AMONG AFRICAN AMERICANS IN THE JACKSON HEART STUDY

PubMed Central

Sims, Mario; Wyatt, Sharon B.; Gutierrez, Mary Lou; Taylor, Herman A.; Williams, David R.

2009-01-01

Objective Assessing the discrimination-health disparities hypothesis requires psychometrically sound, multidimensional measures of discrimination. Among the available discrimination measures, few are multidimensional and none have adequate psychometric testing in a large, African American sample. We report the development and psychometric testing of the multidimensional Jackson Heart Study Discrimination (JHSDIS) Instrument. Methods A multidimensional measure assessing the occurrence, frequency, attribution, and coping responses to perceived everyday and lifetime discrimination; lifetime burden of discrimination; and effect of skin color was developed and tested in the 5302-member cohort of the Jackson Heart Study. Internal consistency was calculated by using Cronbach α. coefficient. Confirmatory factor analysis established the dimensions, and intercorrelation coefficients assessed the discriminant validity of the instrument. Setting Tri-county area of the Jackson, MS metropolitan statistical area. Results The JHSDIS was psychometrically sound (overall α=.78, .84 and .77, respectively, for the everyday and lifetime subscales). Confirmatory factor analysis yielded 11 factors, which confirmed the a priori dimensions represented. Conclusions The JHSDIS combined three scales into a single multidimensional instrument with good psychometric properties in a large sample of African Americans. This analysis lays the foundation for using this instrument in research that will examine the association between perceived discrimination and CVD among African Americans. PMID:19341164

Neural mechanisms of coarse-to-fine discrimination in the visual cortex.

PubMed

Purushothaman, Gopathy; Chen, Xin; Yampolsky, Dmitry; Casagrande, Vivien A

2014-12-01

Vision is a dynamic process that refines the spatial scale of analysis over time, as evidenced by a progressive improvement in the ability to detect and discriminate finer details. To understand coarse-to-fine discrimination, we studied the dynamics of spatial frequency (SF) response using reverse correlation in the primary visual cortex (V1) of the primate. In a majority of V1 cells studied, preferred SF either increased monotonically with time (group 1) or changed nonmonotonically, with an initial increase followed by a decrease (group 2). Monotonic shift in preferred SF occurred with or without an early suppression at low SFs. Late suppression at high SFs always accompanied nonmonotonic SF dynamics. Bayesian analysis showed that SF discrimination performance and best discriminable SF frequencies changed with time in different ways in the two groups of neurons. In group 1 neurons, SF discrimination performance peaked on both left and right flanks of the SF tuning curve at about the same time. In group 2 neurons, peak discrimination occurred on the right flank (high SFs) later than on the left flank (low SFs). Group 2 neurons were also better discriminators of high SFs. We examined the relationship between the time at which SF discrimination performance peaked on either flank of the SF tuning curve and the corresponding best discriminable SFs in both neuronal groups. This analysis showed that the population best discriminable SF increased with time in V1. These results suggest neural mechanisms for coarse-to-fine discrimination behavior and that this process originates in V1 or earlier. Copyright © 2014 the American Physiological Society.

Discrimination surfaces with application to region-specific brain asymmetry analysis.

PubMed

Martos, Gabriel; de Carvalho, Miguel

2018-05-20

Discrimination surfaces are here introduced as a diagnostic tool for localizing brain regions where discrimination between diseased and nondiseased participants is higher. To estimate discrimination surfaces, we introduce a Mann-Whitney type of statistic for random fields and present large-sample results characterizing its asymptotic behavior. Simulation results demonstrate that our estimator accurately recovers the true surface and corresponding interval of maximal discrimination. The empirical analysis suggests that in the anterior region of the brain, schizophrenic patients tend to present lower local asymmetry scores in comparison with participants in the control group. Copyright © 2018 John Wiley & Sons, Ltd.

Simple models for estimating local removals of timber in the northeast

Treesearch

David N. Larsen; David A. Gansner

1975-01-01

Provides a practical method of estimating subregional removals of timber and demonstrates its application to a typical problem. Stepwise multiple regression analysis is used to develop equations for estimating removals of softwood, hardwood, and all timber from selected characteristics of socioeconomic structure.

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

Comparison of cranial sex determination by discriminant analysis and logistic regression.

PubMed

Amores-Ampuero, Anabel; Alemán, Inmaculada

2016-04-05

Various methods have been proposed for estimating dimorphism. The objective of this study was to compare sex determination results from cranial measurements using discriminant analysis or logistic regression. The study sample comprised 130 individuals (70 males) of known sex, age, and cause of death from San José cemetery in Granada (Spain). Measurements of 19 neurocranial dimensions and 11 splanchnocranial dimensions were subjected to discriminant analysis and logistic regression, and the percentages of correct classification were compared between the sex functions obtained with each method. The discriminant capacity of the selected variables was evaluated with a cross-validation procedure. The percentage accuracy with discriminant analysis was 78.2% for the neurocranium (82.4% in females and 74.6% in males) and 73.7% for the splanchnocranium (79.6% in females and 68.8% in males). These percentages were higher with logistic regression analysis: 85.7% for the neurocranium (in both sexes) and 94.1% for the splanchnocranium (100% in females and 91.7% in males).

Classification accuracy on the family planning participation status using kernel discriminant analysis

NASA Astrophysics Data System (ADS)

Kurniawan, Dian; Suparti; Sugito

2018-05-01

Population growth in Indonesia has increased every year. According to the population census conducted by the Central Bureau of Statistics (BPS) in 2010, the population of Indonesia has reached 237.6 million people. Therefore, to control the population growth rate, the government hold Family Planning or Keluarga Berencana (KB) program for couples of childbearing age. The purpose of this program is to improve the health of mothers and children in order to manifest prosperous society by controlling births while ensuring control of population growth. The data used in this study is the updated family data of Semarang city in 2016 that conducted by National Family Planning Coordinating Board (BKKBN). From these data, classifiers with kernel discriminant analysis will be obtained, and also classification accuracy will be obtained from that method. The result of the analysis showed that normal kernel discriminant analysis gives 71.05 % classification accuracy with 28.95 % classification error. Whereas triweight kernel discriminant analysis gives 73.68 % classification accuracy with 26.32 % classification error. Using triweight kernel discriminant for data preprocessing of family planning participation of childbearing age couples in Semarang City of 2016 can be stated better than with normal kernel discriminant.

Varietal discrimination of hop pellets by near and mid infrared spectroscopy.

PubMed

Machado, Julio C; Faria, Miguel A; Ferreira, Isabel M P L V O; Páscoa, Ricardo N M J; Lopes, João A

2018-04-01

Hop is one of the most important ingredients of beer production and several varieties are commercialized. Therefore, it is important to find an eco-real-time-friendly-low-cost technique to distinguish and discriminate hop varieties. This paper describes the development of a method based on vibrational spectroscopy techniques, namely near- and mid-infrared spectroscopy, for the discrimination of 33 commercial hop varieties. A total of 165 samples (five for each hop variety) were analysed by both techniques. Principal component analysis, hierarchical cluster analysis and partial least squares discrimination analysis were the chemometric tools used to discriminate positively the hop varieties. After optimizing the spectral regions and pre-processing methods a total of 94.2% and 96.6% correct hop varieties discrimination were obtained for near- and mid-infrared spectroscopy, respectively. The results obtained demonstrate the suitability of these vibrational spectroscopy techniques to discriminate different hop varieties and consequently their potential to be used as an authenticity tool. Compared with the reference procedures normally used for hops variety discrimination these techniques are quicker, cost-effective, non-destructive and eco-friendly. Copyright © 2017 Elsevier B.V. All rights reserved.

[Comparison of Discriminant Analysis and Decision Trees for the Detection of Subclinical Keratoconus].

PubMed

Kleinhans, Sonja; Herrmann, Eva; Kohnen, Thomas; Bühren, Jens

2017-08-15

Background Iatrogenic keratectasia is one of the most dreaded complications of refractive surgery. In most cases, keratectasia develops after refractive surgery of eyes suffering from subclinical stages of keratoconus with few or no signs. Unfortunately, there has been no reliable procedure for the early detection of keratoconus. In this study, we used binary decision trees (recursive partitioning) to assess their suitability for discrimination between normal eyes and eyes with subclinical keratoconus. Patients and Methods The method of decision tree analysis was compared with discriminant analysis which has shown good results in previous studies. Input data were 32 eyes of 32 patients with newly diagnosed keratoconus in the contralateral eye and preoperative data of 10 eyes of 5 patients with keratectasia after laser in-situ keratomileusis (LASIK). The control group was made up of 245 normal eyes after LASIK and 12-month follow-up without any signs of iatrogenic keratectasia. Results Decision trees gave better accuracy and specificity than did discriminant analysis. The sensitivity of decision trees was lower than the sensitivity of discriminant analysis. Conclusion On the basis of the patient population of this study, decision trees did not prove to be superior to linear discriminant analysis for the detection of subclinical keratoconus. Georg Thieme Verlag KG Stuttgart · New York.

Multivariate geomorphic analysis of forest streams: Implications for assessment of land use impacts on channel condition

Treesearch

Richard. D. Wood-Smith; John M. Buffington

1996-01-01

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10...

Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes.

PubMed

De Luca, Michele; Restuccia, Donatella; Clodoveo, Maria Lisa; Puoci, Francesco; Ragno, Gaetano

2016-07-01

Chemometric discrimination of extra virgin olive oils (EVOO) from whole and stoned olive pastes was carried out by using Fourier transform infrared (FTIR) data and partial least squares-discriminant analysis (PLS1-DA) approach. Four Italian commercial EVOO brands, all in both whole and stoned version, were considered in this study. The adopted chemometric methodologies were able to describe the different chemical features in phenolic and volatile compounds contained in the two types of oil by using unspecific IR spectral information. Principal component analysis (PCA) was employed in cluster analysis to capture data patterns and to highlight differences between technological processes and EVOO brands. The PLS1-DA algorithm was used as supervised discriminant analysis to identify the different oil extraction procedures. Discriminant analysis was extended to the evaluation of possible adulteration by addition of aliquots of oil from whole paste to the most valuable oil from stoned olives. The statistical parameters from external validation of all the PLS models were very satisfactory, with low root mean square error of prediction (RMSEP) and relative error (RE%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Tropical Cyclone Intensity and Position Analysis Using Passive Microwave Imager and Sounder Data

DTIC Science & Technology

2015-03-26

NPP) Advanced Technology Microwave Sounder (ATMS) for a sample of 28 North Atlantic storms from the 2011 through 2013 TC seasons . Using a stepwise...58 27. NOAA NHC 2011 TC Season Tracks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 28...per Season and TCs with Aircraft Reconnaissance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Fair lineups are better than biased lineups and showups, but not because they increase underlying discriminability.

PubMed

Smith, Andrew M; Wells, Gary L; Lindsay, R C L; Penrod, Steven D

2017-04-01

Receiver Operating Characteristic (ROC) analysis has recently come in vogue for assessing the underlying discriminability and the applied utility of lineup procedures. Two primary assumptions underlie recommendations that ROC analysis be used to assess the applied utility of lineup procedures: (a) ROC analysis of lineups measures underlying discriminability, and (b) the procedure that produces superior underlying discriminability produces superior applied utility. These same assumptions underlie a recently derived diagnostic-feature detection theory, a theory of discriminability, intended to explain recent patterns observed in ROC comparisons of lineups. We demonstrate, however, that these assumptions are incorrect when ROC analysis is applied to lineups. We also demonstrate that a structural phenomenon of lineups, differential filler siphoning, and not the psychological phenomenon of diagnostic-feature detection, explains why lineups are superior to showups and why fair lineups are superior to biased lineups. In the process of our proofs, we show that computational simulations have assumed, unrealistically, that all witnesses share exactly the same decision criteria. When criterial variance is included in computational models, differential filler siphoning emerges. The result proves dissociation between ROC curves and underlying discriminability: Higher ROC curves for lineups than for showups and for fair than for biased lineups despite no increase in underlying discriminability. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Is there a step-wise migration in Nigeria? A case study of the migrational histories of migrants in Lagos.

PubMed

Afolayan, A A

1985-09-01

"The paper sets out to test whether or not the movement pattern of people in Nigeria is step-wise. It examines the spatial order in the country and the movement pattern of people. It then analyzes the survey data and tests for the validity of step-wise migration in the country. The findings show that step-wise migration cannot adequately describe all the patterns observed." The presence of large-scale circulatory migration between rural and urban areas is noted. Ways to decrease the pressure on Lagos by developing intermediate urban areas are considered. excerpt

The intersectionality of discrimination attributes and bullying among youth: an applied latent class analysis.

PubMed

Garnett, Bernice Raveche; Masyn, Katherine E; Austin, S Bryn; Miller, Matthew; Williams, David R; Viswanath, Kasisomayajula

2014-08-01

Discrimination is commonly experienced among adolescents. However, little is known about the intersection of multiple attributes of discrimination and bullying. We used a latent class analysis (LCA) to illustrate the intersections of discrimination attributes and bullying, and to assess the associations of LCA membership to depressive symptoms, deliberate self harm and suicidal ideation among a sample of ethnically diverse adolescents. The data come from the 2006 Boston Youth Survey where students were asked whether they had experienced discrimination based on four attributes: race/ethnicity, immigration status, perceived sexual orientation and weight. They were also asked whether they had been bullied or assaulted for these attributes. A total of 965 (78%) students contributed to the LCA analytic sample (45% Non-Hispanic Black, 29% Hispanic, 58% Female). The LCA revealed that a 4-class solution had adequate relative and absolute fit. The 4-classes were characterized as: low discrimination (51%); racial discrimination (33%); sexual orientation discrimination (7%); racial and weight discrimination with high bullying (intersectional class) (7%). In multivariate models, compared to the low discrimination class, individuals in the sexual orientation discrimination class and the intersectional class had higher odds of engaging in deliberate self-harm. Students in the intersectional class also had higher odds of suicidal ideation. All three discrimination latent classes had significantly higher depressive symptoms compared to the low discrimination class. Multiple attributes of discrimination and bullying co-occur among adolescents. Research should consider the co-occurrence of bullying and discrimination.

Discriminant forest classification method and system

DOEpatents

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

2012-11-06

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

Item validity vs. item discrimination index: a redundancy?

NASA Astrophysics Data System (ADS)

Panjaitan, R. L.; Irawati, R.; Sujana, A.; Hanifah, N.; Djuanda, D.

2018-03-01

In several literatures about evaluation and test analysis, it is common to find that there are calculations of item validity as well as item discrimination index (D) with different formula for each. Meanwhile, other resources said that item discrimination index could be obtained by calculating the correlation between the testee’s score in a particular item and the testee’s score on the overall test, which is actually the same concept as item validity. Some research reports, especially undergraduate theses tend to include both item validity and item discrimination index in the instrument analysis. It seems that these concepts might overlap for both reflect the test quality on measuring the examinees’ ability. In this paper, examples of some results of data processing on item validity and item discrimination index were compared. It would be discussed whether item validity and item discrimination index can be represented by one of them only or it should be better to present both calculations for simple test analysis, especially in undergraduate theses where test analyses were included.

Orthogonal sparse linear discriminant analysis

NASA Astrophysics Data System (ADS)

Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun

2018-03-01

Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.

Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Manfredi, Marcello; Robotti, Elisa; Quasso, Fabio; Mazzucco, Eleonora; Calabrese, Giorgio; Marengo, Emilio

2018-01-01

The authentication and traceability of hazelnuts is very important for both the consumer and the food industry, to safeguard the protected varieties and the food quality. This study investigates the use of a portable FTIR spectrometer coupled to multivariate statistical analysis for the classification of raw hazelnuts. The method discriminates hazelnuts from different origins/cultivars based on differences of the signal intensities of their IR spectra. The multivariate classification methods, namely principal component analysis (PCA) followed by linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA), with or without variable selection, allowed a very good discrimination among the groups, with PLS-DA coupled to variable selection providing the best results. Due to the fast analysis, high sensitivity, simplicity and no sample preparation, the proposed analytical methodology could be successfully used to verify the cultivar of hazelnuts, and the analysis can be performed quickly and directly on site.

Analysis of laser printer and photocopier toners by spectral properties and chemometrics

NASA Astrophysics Data System (ADS)

Verma, Neha; Kumar, Raj; Sharma, Vishal

2018-05-01

The use of printers to generate falsified documents has become a common practice in today's world. The examination and identification of the printed matter in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the document. In the present study, a total number of 100 black toner samples both from laser printers and photocopiers were examined using diffuse reflectance UV-Vis Spectroscopy. The present research is divided into two parts; visual discrimination and discrimination by using multivariate analysis. A comparison between qualitative and quantitative analysis showed that multivariate analysis (Principal component analysis) provides 99.59%pair-wise discriminating power for laser printer toners while 99.84% pair-wise discriminating power for photocopier toners. The overall results obtained confirm the applicability of UV-Vis spectroscopy and chemometrics, in the nondestructive analysis of toner printed documents while enhancing their evidential value for forensic applications.

Stigma in the mental health workplace: perceptions of peer employees and clinicians.

PubMed

Stromwall, Layne K; Holley, Lynn C; Bashor, Kathy E

2011-08-01

Informed by a structural theory of workplace discrimination, mental health system employees' perceptions of mental health workplace stigma and discrimination against service recipients and peer employees were investigated. Fifty-one peer employees and 52 licensed behavioral health clinicians participated in an online survey. Independent variables were employee status (peer or clinician), gender, ethnicity, years of mental health employment, age, and workplace social inclusion of peer employees. Analysis of covariance on workplace discrimination against service recipients revealed that peer employees perceived more discrimination than clinicians and whites perceived more discrimination than employees of color (corrected model F = 9.743 [16, 87], P = .000, partial ŋ (2) = .644). Analysis of covariance on workplace discrimination against peer employees revealed that peer employees perceived more discrimination than clinicians (F = 4.593, [6, 97], P = .000, partial ŋ (2) = .223).

Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI.

PubMed

Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M

2017-05-01

Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.

Prediction of IOI-HA scores using speech reception thresholds and speech discrimination scores in quiet.

PubMed

Brännström, K Jonas; Lantz, Johannes; Nielsen, Lars Holme; Olsen, Steen Østergaard

2014-02-01

Outcome measures can be used to improve the quality of the rehabilitation by identifying and understanding which variables influence the outcome. This information can be used to improve outcomes for clients. In clinical practice, pure-tone audiometry, speech reception thresholds (SRTs), and speech discrimination scores (SDSs) in quiet or in noise are common assessments made prior to hearing aid (HA) fittings. It is not known whether SRT and SDS in quiet relate to HA outcome measured with the International Outcome Inventory for Hearing Aids (IOI-HA). The aim of the present study was to investigate the relationship between pure-tone average (PTA), SRT, and SDS in quiet and IOI-HA in both first-time and experienced HA users. SRT and SDS were measured in a sample of HA users who also responded to the IOI-HA. Fifty-eight Danish-speaking adult HA users. The psychometric properties were evaluated and compared to previous studies using the IOI-HA. The associations and differences between the outcome scores and a number of descriptive variables (age, gender, fitted monaurally/binaurally with HA, first-time/experienced HA users, years of HA use, time since last HA fitting, best ear PTA, best ear SRT, or best ear SDS) were examined. A multiple forward stepwise regression analysis was conducted using scores on the separate IOI-HA items, the global score, and scores on the introspection and interaction subscales as dependent variables to examine whether the descriptive variables could predict these outcome measures. Scores on single IOI-HA items, the global score, and scores on the introspection (items 1, 2, 4, and 7) and interaction (items 3, 5, and 6) subscales closely resemble those previously reported. Multiple regression analysis showed that the best ear SDS predicts about 18-19% of the outcome on items 3 and 5 separately, and about 16% on the interaction subscale (sum of items 3, 5, and 6) CONCLUSIONS: The best ears SDS explains some of the variance displayed in the IOI-HA global score and the interaction subscale. The relation between SDS and IOI-HA suggests that a poor unaided SDS might in itself be a limiting factor for the HA rehabilitation efficacy and hence the IOI-HA outcome. The clinician could use this information to align the user's HA expectations to what is within possible reach. American Academy of Audiology.

Testing inferences in developmental evolution: the forensic evidence principle.

PubMed

Larsson, Hans C E; Wagner, Günter P

2012-09-01

Developmental evolution (DE) examines the influence of developmental mechanisms on biological evolution. Here we consider the question: "what is the evidence that allows us to decide whether a certain developmental scenario for an evolutionary change is in fact "correct" or at least falsifiable?" We argue that the comparative method linked with what we call the "forensic evidence principle" (FEP) is sufficient to conduct rigorous tests of DE scenarios. The FEP states that different genetically mediated developmental causes of an evolutionary transformation will leave different signatures in the development of the derived character. Although similar inference rules have been used in practically every empirical science, we expand this approach here in two ways: (1) we justify the validity of this principle with reference to a well-known result from mathematical physics, known as the symmetry principle, and (2) propose a specific form of the FEP for DE: given two or more developmental explanations for a certain evolutionary event, say an evolutionary novelty, then the evidence discriminating between these hypotheses will be found in the most proximal internal drivers of the derived character. Hence, a detailed description of the ancestral and derived states, and their most proximal developmental drivers are necessary to discriminate between various evolutionary developmental hypotheses. We discuss how this stepwise order of testing is necessary, establishes a formal test, and how skipping this order of examination may violate a more accurate examination of DE. We illustrate the approach with an example from avian digit evolution. © 2012 Wiley Periodicals, Inc.

Body size and physique among Canadians of First Nation and European ancestry.

PubMed

Katzmarzyk, P T; Malina, R M

1999-02-01

The purpose of this study was to compare body size and physique among Canadians of Aboriginal (First Nation [FN]) and European ancestry (EA) from the northern Ontario communities of Temagami and Bear Island. The sample consisted of 130 FN and 494 EA participants including adults (20-75 years: 214 men, 234 women) and youth (5-19 years: 97 boys, 79 girls). Indicators of body size and physique included stature, the sitting height-to-stature ratio (SSR), body mass, BMI, estimated upper-arm muscle area, biacromial, bicristal, biepicondylar, and bicondylar breadths, and the Heath-Carter anthropometric somatotype (endomorphy, mesomorphy, and ectomorphy). There were few differences in body size between FN and EA, with the exception of adult females. Adult FN females were significantly heavier and had greater bone breadths than EA women (P < 0.001). On the other hand, somatotype differed significantly between EA and FN by age and sex, except for 5-19-year-old females. Among boys and men, FN had greater endomorphy (P < 0.03), whereas FN men also had lower ectomorphy (P < 0.01). Among women, FN were significantly more endomorphic and mesomorphic and less ectomorphic (P < 0.001). Although results for 5-19-year-old females were not significant, they were in the same direction as the other groups (greater endomorphy). Forward stepwise discriminant function analyses indicated that endomorphy was the most important discriminator between FN and EA by age and sex.

Vocational outcome following spinal cord injury.

PubMed

Conroy, L; McKenna, K

1999-09-01

Non-experimental (ex post facto) survey research design involving the use of a fixed alternative format questionnaire. To investigate variables influencing vocational outcome, to identify barriers to gaining and sustaining employment and to identify the effects of variables on the type of work engaged in following spinal cord injury. The two sets of independent variables considered were, individual and injury-related factors (age at onset of injury, time since injury, extent/level of injury, highest educational qualification achieved pre-injury, and pre-injury occupation) and circumstantial factors (means of transport, access difficulties, perceived workplace discrimination, financial disincentives to work and perceived level of skill). The Princess Alexandra Hospital Spinal Injuries Unit, Queensland, Australia. Data on the variables and the vocational outcomes of having ever worked or studied post-injury, current employment status and post-injury occupation were obtained from survey responses. Demographical and medical data were gathered from medical records. Forward stepwise logistic regression revealed that having ever worked or studied post-injury was associated with all individual and injury-related factors except pre-injury occupation, and two circumstantial factors, namely means of transport and access difficulties. Current employment was associated with all circumstantial factors as well as age at injury and pre-injury occupation. Standard multiple regression analyses revealed that post-injury occupation was correlated with all individual and injury-related factors as well as means of transport and perceived workplace discrimination. Tailored rehabilitation programs for individuals with characteristics associated with less successful vocational outcomes may facilitate their employment status after injury.

An item response theory evaluation of three depression assessment instruments in a clinical sample.

PubMed

Adler, Mats; Hetta, Jerker; Isacsson, Göran; Brodin, Ulf

2012-06-21

This study investigates whether an analysis, based on Item Response Theory (IRT), can be used for initial evaluations of depression assessment instruments in a limited patient sample from an affective disorder outpatient clinic, with the aim to finding major advantages and deficiencies of the instruments. Three depression assessment instruments, the depression module from the Patient Health Questionnaire (PHQ9), the depression subscale of Affective Self Rating Scale (AS-18-D) and the Montgomery-Åsberg Depression Rating Scale (MADRS) were evaluated in a sample of 61 patients with affective disorder diagnoses, mainly bipolar disorder. A '3- step IRT strategy' was used. In a first step, the Mokken non-parametric analysis showed that PHQ9 and AS-18-D had strong overall scalabilities of 0.510 [C.I. 0.42, 0.61] and 0,513 [C.I. 0.41, 0.63] respectively, while MADRS had a weak scalability of 0.339 [C.I. 0.25, 0.43]. In a second step, a Rasch model analysis indicated large differences concerning the item discriminating capacity and was therefore considered not suitable for the data. In third step, applying a more flexible two parameter model, all three instruments showed large differences in item information and items had a low capacity to reliably measure respondents at low levels of depression severity. We conclude that a stepwise IRT-approach, as performed in this study, is a suitable tool for studying assessment instruments at early stages of development. Such an analysis can give useful information, even in small samples, in order to construct more precise measurements or to evaluate existing assessment instruments. The study suggests that the PHQ9 and AS-18-D can be useful for measurement of depression severity in an outpatient clinic for affective disorder, while the MADRS shows weak measurement properties for this type of patients.

Experimental and Theoretical Studies of Long-Period Tilt of Earth’s Crust: Part I. Experimental.

DTIC Science & Technology

A three-element borehole tiltmeter system was developed and installed at Bedford, Massachusetts for the purpose of measurement and analysis of...crustal tilts. Each borehole unit contains two single-axis tiltmeters with diamagnetically suspended masses and leveling motors adapted for stepwise

Working with Evaluation Stakeholders: A Rationale, Step-Wise Approach and Toolkit

ERIC Educational Resources Information Center

Bryson, John M.; Patton, Michael Quinn; Bowman, Ruth A.

2011-01-01

In the broad field of evaluation, the importance of stakeholders is often acknowledged and different categories of stakeholders are identified. Far less frequent is careful attention to analysis of stakeholders' interests, needs, concerns, power, priorities, and perspectives and subsequent application of that knowledge to the design of…

Personality Factors and Instructional Methods

ERIC Educational Resources Information Center

Hunt, Dennis; Randhawa, Bikkar S.

The Children's Personality Questionnaire (CPQ) was administered to 23 academically handicapped children (mean IQ, 79) and 35 academically gifted students (mean IQ, 147). The CPQ measures 14 distinct personality factors; data on these variables were analyzed using a 2 x 2 (academic ability x sex) analysis of variance design. A stepwise discriminant…

Knowing When to Retire: The First Step towards Financial Planning in Malaysia

ERIC Educational Resources Information Center

Kock, Tan Hoe; Yoong, Folk Jee

2011-01-01

This article draws upon expected retirement age cohorts as a main determinant to financial planning preparation in Malaysia. The return rate was 55% from 600 questionnaires distributed. Five hypotheses were analyzed using hierarchical and stepwise regression analysis. The results revealed that expected retirement age cohort variables made…

Everyday Discrimination and Mood and Substance Use Disorders: A Latent Profile Analysis with African Americans and Caribbean Blacks

PubMed Central

Clark, Trenette T.; Salas-Wright, Christopher P.; Vaughn, Michael G.; Whitfield, Keith E.

2016-01-01

Perceived discrimination is a major source of health-related stress. The purpose of this study was to model the heterogeneity of everyday-discrimination experiences among African American and Caribbean Blacks and to identify differences in the prevalence of mood and substance use outcomes, including generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder among the identified subgroups. The study uses data from the National Survey of American Life obtained from a sample of African American and Caribbean Black respondents (N = 4,462) between 18 and 65 years. We used latent profile analysis and multinomial regression analyses to identify and validate latent subgroups and test hypotheses, yielding 4 classes of perceived everyday discrimination: Low Discrimination, Disrespect and Condescension, General Discrimination, and Chronic Discrimination. Findings show significant differences exist between the Low Discrimination and General Discrimination classes for major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Moreover, we find significant differences exist between the Low Discrimination and Chronic Discrimination classes for the four disorders examined. Compared with the Chronic Discrimination class, members of the other classes were significantly less likely to meet criteria for generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Findings suggest elevated levels of discrimination increase risk for mood and substance-use disorders. Importantly, results suggest the prevalence of mood and substance-use disorders is a function of the type and frequency of discrimination that individuals experience. PMID:25254321

Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhu, Ying; Tan, Tuck Lee

2016-04-01

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.

The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis.

PubMed

Corvucci, Francesca; Nobili, Lara; Melucci, Dora; Grillenzoni, Francesca-Vittoria

2015-02-15

Honey traceability to food quality is required by consumers and food control institutions. Melissopalynologists traditionally use percentages of nectariferous pollens to discriminate the botanical origin and the entire pollen spectrum (presence/absence, type and quantities and association of some pollen types) to determinate the geographical origin of honeys. To improve melissopalynological routine analysis, principal components analysis (PCA) was used. A remarkable and innovative result was that the most significant pollens for the traditional discrimination of the botanical and geographical origin of honeys were the same as those individuated with the chemometric model. The reliability of assignments of samples to honey classes was estimated through explained variance (85%). This confirms that the chemometric model properly describes the melissopalynological data. With the aim to improve honey discrimination, FT-microRaman spectrography and multivariate analysis were also applied. Well performing PCA models and good agreement with known classes were achieved. Encouraging results were obtained for botanical discrimination. Copyright © 2014 Elsevier Ltd. All rights reserved.

Local kernel nonparametric discriminant analysis for adaptive extraction of complex structures

NASA Astrophysics Data System (ADS)

Li, Quanbao; Wei, Fajie; Zhou, Shenghan

2017-05-01

The linear discriminant analysis (LDA) is one of popular means for linear feature extraction. It usually performs well when the global data structure is consistent with the local data structure. Other frequently-used approaches of feature extraction usually require linear, independence, or large sample condition. However, in real world applications, these assumptions are not always satisfied or cannot be tested. In this paper, we introduce an adaptive method, local kernel nonparametric discriminant analysis (LKNDA), which integrates conventional discriminant analysis with nonparametric statistics. LKNDA is adept in identifying both complex nonlinear structures and the ad hoc rule. Six simulation cases demonstrate that LKNDA have both parametric and nonparametric algorithm advantages and higher classification accuracy. Quartic unilateral kernel function may provide better robustness of prediction than other functions. LKNDA gives an alternative solution for discriminant cases of complex nonlinear feature extraction or unknown feature extraction. At last, the application of LKNDA in the complex feature extraction of financial market activities is proposed.

L1-norm kernel discriminant analysis via Bayes error bound optimization for robust feature extraction.

PubMed

Zheng, Wenming; Lin, Zhouchen; Wang, Haixian

2014-04-01

A novel discriminant analysis criterion is derived in this paper under the theoretical framework of Bayes optimality. In contrast to the conventional Fisher's discriminant criterion, the major novelty of the proposed one is the use of L1 norm rather than L2 norm, which makes it less sensitive to the outliers. With the L1-norm discriminant criterion, we propose a new linear discriminant analysis (L1-LDA) method for linear feature extraction problem. To solve the L1-LDA optimization problem, we propose an efficient iterative algorithm, in which a novel surrogate convex function is introduced such that the optimization problem in each iteration is to simply solve a convex programming problem and a close-form solution is guaranteed to this problem. Moreover, we also generalize the L1-LDA method to deal with the nonlinear robust feature extraction problems via the use of kernel trick, and hereafter proposed the L1-norm kernel discriminant analysis (L1-KDA) method. Extensive experiments on simulated and real data sets are conducted to evaluate the effectiveness of the proposed method in comparing with the state-of-the-art methods.

Discrimination among populations of sockeye salmon fry with Fourier analysis of otolith banding patterns formed during incubation

USGS Publications Warehouse

Finn, James E.; Burger, Carl V.; Holland-Bartels, Leslie E.

1997-01-01

We used otolith banding patterns formed during incubation to discriminate among hatchery- and wild-incubated fry of sockeye salmon Oncorhynchus nerka from Tustumena Lake, Alaska. Fourier analysis of otolith luminance profiles was used to describe banding patterns: the amplitudes of individual Fourier harmonics were discriminant variables. Correct classification of otoliths to either hatchery or wild origin was 83.1% (cross-validation) and 72.7% (test data) with the use of quadratic discriminant function analysts on 10 Fourier amplitudes. Overall classification rates among the six test groups (one hatchery and five wild groups) were 46.5% (cross-validation) and 39.3% (test data) with the use of linear discriminant function analysis on 16 Fourier amplitudes. Although classification rates for wild-incubated fry from any one site never exceeded 67% (cross-validation) or 60% (test data), location-specific information was evident for all groups because the probability of classifying an individual to its true incubation location was significantly greater than chance. Results indicate phenotypic differences in otolith microstructure among incubation sites separated by less than 10 km. Analysis of otolith luminance profiles is a potentially useful technique for discriminating among and between various populations of hatchery and wild fish.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of LANDSAT digital data

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

Causal correlation of foliar biochemical concentrations with AVIRIS spectra using forced entry linear regression

NASA Technical Reports Server (NTRS)

Dawson, Terence P.; Curran, Paul J.; Kupiec, John A.

1995-01-01

A major goal of airborne imaging spectrometry is to estimate the biochemical composition of vegetation canopies from reflectance spectra. Remotely-sensed estimates of foliar biochemical concentrations of forests would provide valuable indicators of ecosystem function at regional and eventually global scales. Empirical research has shown a relationship exists between the amount of radiation reflected from absorption features and the concentration of given biochemicals in leaves and canopies (Matson et al., 1994, Johnson et al., 1994). A technique commonly used to determine which wavelengths have the strongest correlation with the biochemical of interest is unguided (stepwise) multiple regression. Wavelengths are entered into a multivariate regression equation, in their order of importance, each contributing to the reduction of the variance in the measured biochemical concentration. A significant problem with the use of stepwise regression for determining the correlation between biochemical concentration and spectra is that of 'overfitting' as there are significantly more wavebands than biochemical measurements. This could result in the selection of wavebands which may be more accurately attributable to noise or canopy effects. In addition, there is a real problem of collinearity in that the individual biochemical concentrations may covary. A strong correlation between the reflectance at a given wavelength and the concentration of a biochemical of interest, therefore, may be due to the effect of another biochemical which is closely related. Furthermore, it is not always possible to account for potentially suitable waveband omissions in the stepwise selection procedure. This concern about the suitability of stepwise regression has been identified and acknowledged in a number of recent studies (Wessman et al., 1988, Curran, 1989, Curran et al., 1992, Peterson and Hubbard, 1992, Martine and Aber, 1994, Kupiec, 1994). These studies have pointed to the lack of a physical link between wavelengths chosen by stepwise regression and the biochemical of interest, and this in turn has cast doubts on the use of imaging spectrometry for the estimation of foliar biochemical concentrations at sites distant from the training sites. To investigate this problem, an analysis was conducted on the variation in canopy biochemical concentrations and reflectance spectra using forced entry linear regression.

Orientation-free and differentially pumped addition of a low-flux reactive gas beam to a surface analysis system.

PubMed

Harthcock, Colin; Jahanbekam, Abdolreza; Eskelsen, Jeremy R; Lee, David Y

2016-11-01

We describe an example of a piecewise gas chamber that can be customized to incorporate a low flux of gas-phase radicals with an existing surface analysis chamber for in situ and stepwise gas-surface interaction experiments without any constraint in orientation. The piecewise nature of this gas chamber provides complete angular freedom and easy alignment and does not require any modification of the existing surface analysis chamber. In addition, the entire gas-surface system is readily differentially pumped with the surface chamber kept under ultra-high-vacuum during the gas-surface measurements. This new design also allows not only straightforward reconstruction to accommodate the orientation of different surface chambers but also for the addition of other desired features, such as an additional pump to the current configuration. Stepwise interaction between atomic oxygen and a highly ordered pyrolytic graphite surface was chosen to test the effectiveness of this design, and the site-dependent O-atom chemisorption and clustering on the graphite surface were resolved by a scanning tunneling microscope in the nm-scale. X-ray photoelectron spectroscopy was used to further confirm the identity of the chemisorbed species on the graphite surface as oxygen.

Religious Discrimination Discourse in the Mono-Cultural School: The Case of Poland

ERIC Educational Resources Information Center

Anczyk, Adam; Grzymala-Moszczynska, Joanna

2018-01-01

The article forms an analysis of the religious discrimination discourse in Polish public schools, with special attention paid to the culturally specific, Polish understanding of the notion of religious discrimination. The introductory part presents the concept of religious discrimination as present in anti-discriminatory policies. The following…

Discrimination of surface wear on obsidian tools using LSCM and RelA: pilot study results (area-scale analysis of obsidian tool surfaces).

PubMed

Stemp, W James; Chung, Steven

2011-01-01

This pilot study tests the reliability of laser scanning confocal microscopy (LSCM) to quantitatively measure wear on experimental obsidian tools. To our knowledge, this is the first use of confocal microscopy to study wear on stone flakes made from an amorphous silicate like obsidian. Three-dimensional surface roughness or texture area scans on three obsidian flakes used on different contact materials (hide, shell, wood) were documented using the LSCM to determine whether the worn surfaces could be discriminated using area-scale analysis, specifically relative area (RelA). When coupled with the F-test, this scale-sensitive fractal analysis could not only discriminate the used from unused surfaces on individual tools, but was also capable of discriminating the wear histories of tools used on different contact materials. Results indicate that such discriminations occur at different scales. Confidence levels for the discriminations at different scales were established using the F-test (mean square ratios or MSRs). In instances where discrimination of surface roughness or texture was not possible above the established confidence level based on MSRs, photomicrographs and RelA assisted in hypothesizing why this was so. Copyright © 2011 Wiley Periodicals, Inc.

Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar

NASA Astrophysics Data System (ADS)

Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

2015-02-01

Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm-1). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species.

The effect of thermal history on crystalline structure and mechanical properties of β-nucleated isotactic polypropylene

NASA Astrophysics Data System (ADS)

Tian, Yefei; Zhou, Jian; Feng, Jiachun

2018-04-01

The effect of thermal history on β-nucleated iPP was systematically investigated by comparing the variance of crystalline microstructures and mechanical property of stepwise crystallized sample and annealed sample, which experienced different thermal history. The mechanical property tests exhibit that that the toughness of stepwise crystallized sample and annealed sample were both decreased compared to control sample, while the tensile strength of the stepwise crystallized sample increased slightly. Structure investigation showed that the α-relaxation peak, which is related to the assignment of chains in rigid amorphous phase, moved to the high temperature region for stepwise crystallized sample, while it moved to the low temperature region for annealed sample. The results indicated the weakening in rigid amorphous fraction (RAF) and the increase in lamellar thickness of β-iPP after stepwise crystallization treatment. For annealed sample, the RAF strengthened and lamellar thickness decreased slightly after thermal treatment. A mechanism of crystalline microstructures evolution of restricted area between the main lamellar under different treatments was proposed.

Improving meat quality of organic pork through post mortem handling of carcasses: an innovative approach.

PubMed

Therkildsen, Margrethe; Kristensen, Lars; Kyed, Sybille; Oksbjerg, Niels

2012-06-01

This study was conducted to examine the best combination of post mortem chilling, suspension and ageing in order to optimize tenderness of organic pork at slaughter, which may be tougher than conventionally produced pork, because of lower daily gain. Combinations of stepwise chilling with a holding period of 6h at 10°C or traditional blast tunnel chilling, suspension in the pelvic bone or Achilles Tendon and ageing 2 or 4 days post mortem were tested. Stepwise chilling and ageing improved tenderness of the loin, and the effects were additive, whereas pelvic suspension was less effective in texture improvements, and non-additive to stepwise chilling. Stepwise chilling improved tenderness to a similar degree as can be obtained within 2-4 days of extended ageing, however, the minimum temperature during the holding period seems to be crucial in order to obtain a positive effect of stepwise chilling, and it should be above 7.5°C. Copyright © 2011 Elsevier Ltd. All rights reserved.

Stepwise introduction of laparoscopic liver surgery: validation of guideline recommendations.

PubMed

van der Poel, Marcel J; Huisman, Floor; Busch, Olivier R; Abu Hilal, Mohammad; van Gulik, Thomas M; Tanis, Pieter J; Besselink, Marc G

2017-10-01

Uncontrolled introduction of laparoscopic liver surgery (LLS) could compromise postoperative outcomes. A stepwise introduction of LLS combined with structured training is advised. This study aimed to evaluate the impact of such a stepwise introduction. A retrospective, single-center case series assessing short term outcomes of all consecutive LLS in the period November 2006-January 2017. The technique was implemented in a stepwise fashion. To evaluate the impact of this stepwise approach combined with structured training, outcomes of LLS before and after a laparoscopic HPB fellowship were compared. A total of 135 laparoscopic resections were performed. Overall conversion rate was 4% (n = 5), clinically relevant complication rate 13% (n = 18) and mortality 0.7% (n = 1). A significant increase in patients with major LLS, multiple liver resections, previous abdominal surgery, malignancies and lesions located in posterior segments was observed after the fellowship as well as a decrease in the use of hand-assistance. Increasing complexity in the post fellowship period was reflected by an increase in operating times, but without comprising other surgical outcomes. A stepwise introduction of LLS combined with structured training reduced the clinical impact of the learning curve, thereby confirming guideline recommendations. Copyright © 2017 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

The role of multicollinearity in landslide susceptibility assessment by means of Binary Logistic Regression: comparison between VIF and AIC stepwise selection

NASA Astrophysics Data System (ADS)

Cama, Mariaelena; Cristi Nicu, Ionut; Conoscenti, Christian; Quénéhervé, Geraldine; Maerker, Michael

2016-04-01

Landslide susceptibility can be defined as the likelihood of a landslide occurring in a given area on the basis of local terrain conditions. In the last decades many research focused on its evaluation by means of stochastic approaches under the assumption that 'the past is the key to the future' which means that if a model is able to reproduce a known landslide spatial distribution, it will be able to predict the future locations of new (i.e. unknown) slope failures. Among the various stochastic approaches, Binary Logistic Regression (BLR) is one of the most used because it calculates the susceptibility in probabilistic terms and its results are easily interpretable from a geomorphological point of view. However, very often not much importance is given to multicollinearity assessment whose effect is that the coefficient estimates are unstable, with opposite sign and therefore difficult to interpret. Therefore, it should be evaluated every time in order to make a model whose results are geomorphologically correct. In this study the effects of multicollinearity in the predictive performance and robustness of landslide susceptibility models are analyzed. In particular, the multicollinearity is estimated by means of Variation Inflation Index (VIF) which is also used as selection criterion for the independent variables (VIF Stepwise Selection) and compared to the more commonly used AIC Stepwise Selection. The robustness of the results is evaluated through 100 replicates of the dataset. The study area selected to perform this analysis is the Moldavian Plateau where landslides are among the most frequent geomorphological processes. This area has an increasing trend of urbanization and a very high potential regarding the cultural heritage, being the place of discovery of the largest settlement belonging to the Cucuteni Culture from Eastern Europe (that led to the development of the great complex Cucuteni-Tripyllia). Therefore, identifying the areas susceptible to landslides may lead to a better understanding and mitigation for government, local authorities and stakeholders to plan the economic activities, minimize the damages costs, environmental and cultural heritage protection. The results show that although the VIF Stepwise selection allows a more stable selection of the controlling factors, the AIC Stepwise selection produces better predictive performance. Moreover, when working with replicates the effect of multicollinearity are statistically reduced by the application of the AIC stepwise selection and the results are easily interpretable in geomorphologic terms.

Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

PubMed

Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

2017-12-01

Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Habitat characterization of western hoolock gibbons Hoolock hoolock by examining home range microhabitat use.

PubMed

Akers, Alice A; Anwarul Islam, Md; Nijman, Vincent

2013-10-01

Conserving a species depends on an understanding of its habitat requirements. Primatologists often characterize the habitat requirements of primates using macroscale population-based approaches relying on correlations between habitat attributes and population abundances between sites with varying levels of disturbance. This approach only works for species spread between several populations. The populations of some primates do not fulfill these criteria, forcing researchers to rely on individual-based (microscale) rather than population-based approaches for habitat characterization. We examined the reliability of using micro-scale habitat characterizations by studying the microhabitat preferences of a group of wild western hoolock gibbons (Hoolock hoolock) in order to compare our results to the habitat preferences of western hoolock gibbons identified during a macroscale study of populations across Bangladesh. We used stepwise discriminant analysis to differentiate between the areas of low, medium, and high usage based on microhabitat characteristics (tree species availability, altitude, canopy connection, distance from forest edge, and levels of human disturbance). The gibbons used interior forest habitat with low food tree availability most frequently for sleeping and socializing, and used edge habitat containing high food tree availability for medium periods for feeding. These results indicate that the gibbons prefer interior forest but are frequently forced to visit the forest edge to feed. Therefore, the optimal habitat would be interior forest away from human disturbance with high sleeping-tree and feeding-tree availability. These habitat preferences are consistent with the habitat attributes of Bangladesh's largest remaining western hoolock gibbon populations, which live in areas containing low agricultural encroachment and high food-tree availability. Microhabitat use studies can be used to characterize the habitat requirements of a species, but should include multiple scales of analysis wherever possible.

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

NASA Astrophysics Data System (ADS)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

A fingerprinting mixing model approach to generate uniformly representative solutions for distributed contributions of sediment sources in a Pyrenean drainage basin

NASA Astrophysics Data System (ADS)

Palazón, Leticia; Gaspar, Leticia; Latorre, Borja; Blake, Will; Navas, Ana

2014-05-01

Spanish Pyrenean reservoirs are under pressure from high sediment yields in contributing catchments. Sediment fingerprinting approaches offer potential to quantify the contribution of different sediment sources, evaluate catchment erosion dynamics and develop management plans to tackle the reservoir siltation problems. The drainage basin of the Barasona reservoir (1509 km2), located in the Central Spanish Pyrenees, is an alpine-prealpine agroforest basin supplying sediments to the reservoir at an annual rate of around 350 t km-2 with implications for reservoir longevity. The climate is mountain type, wet and cold, with both Atlantic and Mediterranean influences. Steep slopes and the presence of deep and narrow gorges favour rapid runoff and large floods. The ability of geochemical fingerprint properties to discriminate between the sediment sources was investigated by conducting the nonparametric Kruskal-Wallis H-test and a stepwise discriminant function analysis (minimization of Wilk's lambda). This standard procedure selects potential fingerprinting properties as optimum composite fingerprint to characterize and discriminate between sediment sources to the reservoir. Then the contribution of each potential sediment source was assessed by applying a Monte Carlo mixing model to obtain source proportions for the Barasona reservoir sediment samples. The Monte Carlo mixing model was written in C programming language and designed to deliver a user-defined number possible solutions. A Combinatorial Principals method was used to identify the most probable solution with associated uncertainty based on source variability. The unique solution for each sample was characterized by the mean value and the standard deviation of the generated solutions and the lower goodness of fit value applied. This method is argued to guarantee a similar set of representative solutions in all unmixing cases based on likelihood of occurrence. Soil samples for the different potential sediment sources of the drainage basin were compared with samples from the reservoir using a range of different fingerprinting properties (i.e. mass activities of environmental radionuclides, elemental composition and magnetic susceptibility) analyzed in the < 63 μm sediment fraction. In this case, the 100 best results from 106 generated iterations were selected obtaining a goodness of fit higher than 0.76. The preliminary results using this new data processing methodology for samples collected in the reservoir allowed us to identify cultivated fields and badlands as main potential sources of sediments to the reservoir. These findings support the appropriate use of the fingerprinting methodology in a Spanish Pyrenees basin, which will enable us to better understand the basin sediment production of the Barasona reservoir.

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

PubMed

Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

2012-08-01

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

Classifying Failing States

DTIC Science & Technology

2007-03-01

state failure, and Discriminant Analysis to classify states as Stable, Borderline, or Failing based on these indicators. Furthermore, each...nation’s discriminant function scores are used to determine their degree of instability. The methodology is applied to 200 countries for which open source...and go for a long walk. Finally, to my wonderful wife, who now knows more about Discriminant Analysis than any Legal Assistant on the planet, thank

Metazoan parasite infection in the swordfish, Xiphias gladius, from the Mediterranean Sea and comparison with Atlantic populations: implications for its stock characterization

PubMed Central

Mattiucci, Simonetta; Garcia, Alexandra; Cipriani, Paolo; Santos, Miguel Neves; Nascetti, Giuseppe; Cimmaruta, Roberta

2014-01-01

Thirteen parasite taxa were identified in the Mediterranean swordfish by morphological and genetic/molecular methods. The comparison of the identified parasite taxa and parasitic infection values observed in the Mediterranean swordfish showed statistically significant differences with respect to those reported for its Atlantic populations. A stepwise Linear Discriminant Analysis of the individual fish examined showed a separation among three groups: one including fish from the Mediterranean Sea (CTS, STS, and IOS); one consisting of fish from the Central South (CS), Eastern Tropical (ET), and Equatorial (TEQ) Atlantic; and a third comprising the fish sampled from the North-West Atlantic (NW); the CN Atlantic sample was more similar to the first group rather than to the other Atlantic ones. The nematodes Hysterothylacium petteri and Anisakis pegreffii were the species that contributed most to the characterization of the Mediterranean swordfish samples with respect to these Atlantic ones. Anisakis brevispiculata, A. physeteris, A. paggiae, Anisakis sp. 2, Hysterothylacium incurvum, Hepatoxylon trichiuri, Sphyriocephalus viridis, and their high infection levels were associated with the swordfish from the Central and the Southern Atlantic areas. Finally, H. corrugatum, A. simplex (s.s.), Rhadinorhynchus pristis, and Bolbosoma vasculosum were related to the fish from the North-West (NW) Atlantic area. These results indicate that some parasites, particularly Anisakis spp. larvae identified by genetic markers, could be used as “biological tags” and support the existence of a Mediterranean swordfish stock. PMID:25057787

A Web-based nomogram predicting para-aortic nodal metastasis in incompletely staged patients with endometrial cancer: a Korean Multicenter Study.

PubMed

Kang, Sokbom; Lee, Jong-Min; Lee, Jae-Kwan; Kim, Jae-Weon; Cho, Chi-Heum; Kim, Seok-Mo; Park, Sang-Yoon; Park, Chan-Yong; Kim, Ki-Tae

2014-03-01

The purpose of this study is to develop a Web-based nomogram for predicting the individualized risk of para-aortic nodal metastasis in incompletely staged patients with endometrial cancer. From 8 institutions, the medical records of 397 patients who underwent pelvic and para-aortic lymphadenectomy as a surgical staging procedure were retrospectively reviewed. A multivariate logistic regression model was created and internally validated by rigorous bootstrap resampling methods. Finally, the model was transformed into a user-friendly Web-based nomogram (http://http://www.kgog.org/nomogram/empa001.html). The rate of para-aortic nodal metastasis was 14.4% (57/397 patients). Using a stepwise variable selection, 4 variables including deep myometrial invasion, non-endometrioid subtype, lymphovascular space invasion, and log-transformed CA-125 levels were finally adopted. After 1000 repetitions of bootstrapping, all of these 4 variables retained a significant association with para-aortic nodal metastasis in the multivariate analysis-deep myometrial invasion (P = 0.001), non-endometrioid histologic subtype (P = 0.034), lymphovascular space invasion (P = 0.003), and log-transformed serum CA-125 levels (P = 0.004). The model showed good discrimination (C statistics = 0.87; 95% confidence interval, 0.82-0.92) and accurate calibration (Hosmer-Lemeshow P = 0.74). This nomogram showed good performance in predicting para-aortic metastasis in patients with endometrial cancer. The tool may be useful in determining the extent of lymphadenectomy after incomplete surgery.

NCLscan: accurate identification of non-co-linear transcripts (fusion, trans-splicing and circular RNA) with a good balance between sensitivity and precision.

PubMed

Chuang, Trees-Juen; Wu, Chan-Shuo; Chen, Chia-Ying; Hung, Li-Yuan; Chiang, Tai-Wei; Yang, Min-Yu

2016-02-18

Analysis of RNA-seq data often detects numerous 'non-co-linear' (NCL) transcripts, which comprised sequence segments that are topologically inconsistent with their corresponding DNA sequences in the reference genome. However, detection of NCL transcripts involves two major challenges: removal of false positives arising from alignment artifacts and discrimination between different types of NCL transcripts (trans-spliced, circular or fusion transcripts). Here, we developed a new NCL-transcript-detecting method ('NCLscan'), which utilized a stepwise alignment strategy to almost completely eliminate false calls (>98% precision) without sacrificing true positives, enabling NCLscan outperform 18 other publicly-available tools (including fusion- and circular-RNA-detecting tools) in terms of sensitivity and precision, regardless of the generation strategy of simulated dataset, type of intragenic or intergenic NCL event, read depth of coverage, read length or expression level of NCL transcript. With the high accuracy, NCLscan was applied to distinguishing between trans-spliced, circular and fusion transcripts on the basis of poly(A)- and nonpoly(A)-selected RNA-seq data. We showed that circular RNAs were expressed more ubiquitously, more abundantly and less cell type-specifically than trans-spliced and fusion transcripts. Our study thus describes a robust pipeline for the discovery of NCL transcripts, and sheds light on the fundamental biology of these non-canonical RNA events in human transcriptome. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A genomic copy number signature predicts radiation exposure in post-Chernobyl breast cancer.

PubMed

Wilke, Christina M; Braselmann, Herbert; Hess, Julia; Klymenko, Sergiy V; Chumak, Vadim V; Zakhartseva, Liubov M; Bakhanova, Elena V; Walch, Axel K; Selmansberger, Martin; Samaga, Daniel; Weber, Peter; Schneider, Ludmila; Fend, Falko; Bösmüller, Hans C; Zitzelsberger, Horst; Unger, Kristian

2018-04-16

Breast cancer is the second leading cause of cancer death among women worldwide and besides life style, age and genetic risk factors, exposure to ionizing radiation is known to increase the risk for breast cancer. Further, DNA copy number alterations (CNAs), which can result from radiation-induced double-strand breaks, are frequently occurring in breast cancer cells. We set out to identify a signature of CNAs discriminating breast cancers from radiation-exposed and non-exposed female patients. We analyzed resected breast cancer tissues from 68 exposed female Chernobyl clean-up workers and evacuees and 68 matched non-exposed control patients for CNAs by array comparative genomic hybridization analysis (aCGH). Using a stepwise forward-backward selection approach a non-complex CNA signature, that is, less than ten features, was identified in the training data set, which could be subsequently validated in the validation data set (p value < 0.05). The signature consisted of nine copy number regions located on chromosomal bands 7q11.22-11.23, 7q21.3, 16q24.3, 17q21.31, 20p11.23-11.21, 1p21.1, 2q35, 2q35, 6p22.2. The signature was independent of any clinical characteristics of the patients. In all, we identified a CNA signature that has the potential to allow identification of radiation-associated breast cancer at the individual level. © 2018 UICC.

Influence of chronic back pain on kinematic reactions to unpredictable arm pulls.

PubMed

Götze, Martin; Ernst, Michael; Koch, Markus; Blickhan, Reinhard

2015-03-01

There is evidence that muscle reflexes are delayed in patients with chronic low back pain in response to perturbations. It is still unrevealed whether these delays accompanied by an altered kinematic or compensated by adaption of other muscle parameters. The aim of this study was to investigate whether chronic low back pain patients show an altered kinematic reaction and if such data are reliable for the classification of chronic low back pain. In an experiment involving 30 females, sudden lateral perturbations were applied to the arm of a subject in an upright, standing position. Kinematics was used to distinguish between chronic low back pain patients and healthy controls. A calculated model of a stepwise discriminant function analysis correctly predicted 100% of patients and 80% of healthy controls. The estimation of the classification error revealed a constant rate for the classification of the healthy controls and a slightly decreased rate for the patients. Observed reflex delays and identified kinematic differences inside and outside the region of pain during impaired movement indicated that chronic low back pain patients have an altered motor control that is not restricted to the lumbo-pelvic region. This applied paradigm of external perturbations can be used to detect chronic low back pain patients and also persons without chronic low back pain but with an altered motor control. Further investigations are essential to reveal whether healthy persons with changes in motor function have an increased potential to develop chronic back pain. Copyright © 2015 Elsevier Ltd. All rights reserved.

In-Line Sorting of Harumanis Mango Based on External Quality Using Visible Imaging

PubMed Central

Ibrahim, Mohd Firdaus; Ahmad Sa’ad, Fathinul Syahir; Zakaria, Ammar; Md Shakaff, Ali Yeon

2016-01-01

The conventional method of grading Harumanis mango is time-consuming, costly and affected by human bias. In this research, an in-line system was developed to classify Harumanis mango using computer vision. The system was able to identify the irregularity of mango shape and its estimated mass. A group of images of mangoes of different size and shape was used as database set. Some important features such as length, height, centroid and parameter were extracted from each image. Fourier descriptor and size-shape parameters were used to describe the mango shape while the disk method was used to estimate the mass of the mango. Four features have been selected by stepwise discriminant analysis which was effective in sorting regular and misshapen mango. The volume from water displacement method was compared with the volume estimated by image processing using paired t-test and Bland-Altman method. The result between both measurements was not significantly different (P > 0.05). The average correct classification for shape classification was 98% for a training set composed of 180 mangoes. The data was validated with another testing set consist of 140 mangoes which have the success rate of 92%. The same set was used for evaluating the performance of mass estimation. The average success rate of the classification for grading based on its mass was 94%. The results indicate that the in-line sorting system using machine vision has a great potential in automatic fruit sorting according to its shape and mass. PMID:27801799

In-Line Sorting of Harumanis Mango Based on External Quality Using Visible Imaging.

PubMed

Ibrahim, Mohd Firdaus; Ahmad Sa'ad, Fathinul Syahir; Zakaria, Ammar; Md Shakaff, Ali Yeon

2016-10-27

The conventional method of grading Harumanis mango is time-consuming, costly and affected by human bias. In this research, an in-line system was developed to classify Harumanis mango using computer vision. The system was able to identify the irregularity of mango shape and its estimated mass. A group of images of mangoes of different size and shape was used as database set. Some important features such as length, height, centroid and parameter were extracted from each image. Fourier descriptor and size-shape parameters were used to describe the mango shape while the disk method was used to estimate the mass of the mango. Four features have been selected by stepwise discriminant analysis which was effective in sorting regular and misshapen mango. The volume from water displacement method was compared with the volume estimated by image processing using paired t -test and Bland-Altman method. The result between both measurements was not significantly different (P > 0.05). The average correct classification for shape classification was 98% for a training set composed of 180 mangoes. The data was validated with another testing set consist of 140 mangoes which have the success rate of 92%. The same set was used for evaluating the performance of mass estimation. The average success rate of the classification for grading based on its mass was 94%. The results indicate that the in-line sorting system using machine vision has a great potential in automatic fruit sorting according to its shape and mass.

A pilot study on predictors of brainstem raphe abnormality in patients with major depressive disorder.

PubMed

Kostić, Milutin; Munjiza, Ana; Pesic, Danilo; Peljto, Amir; Novakovic, Ivana; Dobricic, Valerija; Tosevski, Dusica Lecic; Mijajlovic, Milija

2017-02-01

Hypo/anechogenicity of the brainstem raphe (BR) structures has been suggested as a possible transcranial parenchymal sonography (TCS) marker associated with depression. The aim of this study was to analyze possible association of the abnormal BR echogenicity in patients with major depression when compared to healthy controls, and to evaluate its clinical and genetic correlates. TCS was performed in 53 patients diagnosed as major depressive disorder (MDD) without psychotic symptoms and in 54 healthy matched controls. The TCS detected BR abnormalities were significantly more frequent in MDD patients (35 out of 53; 66%) in comparison to matched controls (5 out of 56; 9%). The prevalence of short allele (s) homozygocity in the length polymorphism of the promoter region of the serotonin transporter gene (5-HTTLPR) was significantly higher in MDD patients relative to those with normal BR echogenicity. A stepwise statistical discriminant analysis revealed statistically significant separation between MDD patients with and without BR abnormalities groups based on the four predictors combined: the Hamilton Anxiety Rating Scale item 5 ("difficulty in concentration, poor memory"), presence of social phobia, s allele homozygocity of the 5-HTTLPR polymorphism, and presence of generalized anxiety disorder. Cross-sectional design and heterogenous treatment of depressed patients. Reduced BR echogenicity in at least a subgroup of MDD patients may reflect a particular phenotype, characterized by more prevalent comorbid anxiety disorders, associated with particular genetic polymorphisms and neurotransmitter(s) deficits, most probably altered serotonergic mechanisms. Copyright © 2016 Elsevier B.V. All rights reserved.

Everyday discrimination and mood and substance use disorders: a latent profile analysis with African Americans and Caribbean Blacks.

PubMed

Clark, Trenette T; Salas-Wright, Christopher P; Vaughn, Michael G; Whitfield, Keith E

2015-01-01

Perceived discrimination is a major source of health-related stress. The purpose of this study was to model the heterogeneity of everyday-discrimination experiences among African American and Caribbean Blacks and to identify differences in the prevalence of mood and substance use outcomes, including generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder among the identified subgroups. The study uses data from the National Survey of American Life obtained from a sample of African American and Caribbean Black respondents (N=4,462) between 18 and 65 years. We used latent profile analysis and multinomial regression analyses to identify and validate latent subgroups and test hypotheses, yielding 4 classes of perceived everyday discrimination: Low Discrimination, Disrespect and Condescension, General Discrimination, and Chronic Discrimination. Findings show significant differences exist between the Low Discrimination and General Discrimination classes for major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Moreover, we find significant differences exist between the Low Discrimination and Chronic Discrimination classes for the four disorders examined. Compared with the Chronic Discrimination class, members of the other classes were significantly less likely to meet criteria for generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Findings suggest elevated levels of discrimination increase risk for mood and substance-use disorders. Importantly, results suggest the prevalence of mood and substance-use disorders is a function of the type and frequency of discrimination that individuals experience. Copyright © 2014 Elsevier Ltd. All rights reserved.

Kin discrimination within honey bee (Apis mellifera) colonies: An analysis of the evidence.

PubMed

Breed, M D; Welch, C K; Cruz, R

1994-12-01

Compelling evolutionary arguments lead to the prediction that honey bee workers should discriminate between supersisters and half-sisters within colonies. We review the theoretical support for discrimination during swarming, queen rearing, feeding, and grooming. A survey of the data that tests whether such discrimination takes place shows that, despite substantial effort in a number of laboratories, there is no conclusive evidence for intracolony discrimination in any of the postulated contexts. The strongest suggestive data is in the critical context of queen rearing, but flaws in experimental design or analysis make the best available tests inconclusive. We present new data that shows that cues exist on which discriminations can be made among adult workers in nestmate recognition interactions and in feeding interactions, but our data does not differentiate between subfamily recognition and recognition associated with color phenotypes. We conclude that while selection may favor discrimination between supersisters and half-sisters, as a practical matter such discriminations play no role, or only a minor role, in the biology of the honey bee. Copyright © 1994. Published by Elsevier B.V.

Feature extraction with deep neural networks by a generalized discriminant analysis.

PubMed

Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

2012-04-01

We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.

Differential experiences of discrimination among ethnoracially diverse persons experiencing mental illness and homelessness.

PubMed

Zerger, Suzanne; Bacon, Sarah; Corneau, Simon; Skosireva, Anna; McKenzie, Kwame; Gapka, Susan; O'Campo, Patricia; Sarang, Aseefa; Stergiopoulos, Vicky

2014-12-14

This mixed methods study explored the characteristics of and experiences with perceived discrimination in an ethnically diverse urban sample of adults experiencing homelessness and mental illness. Data were collected in Toronto, Ontario, as part of a 4-year national randomized field trial of the Housing First treatment model. Rates of perceived discrimination were captured from survey questions regarding perceived discrimination among 231 ethnoracially diverse participants with moderate mental health needs. The qualitative component included thirty six in-depth interviews which explored how individuals who bear these multiple identities of oppression navigate stigma and discrimination, and what affects their capacity to do so. Quantitative analysis revealed very high rates of perceived discrimination related to: homelessness/poverty (61.5%), race/ethnicity/skin colour (50.6%) and mental illness/substance use (43.7%). Immigrants and those who had been homeless three or more years reported higher perceived discrimination on all three domains. Analysis of qualitative interviews revealed three common themes related to navigating these experiences of discrimination among participants: 1) social distancing; 2) old and new labels/identities; and, 3) 'homeland' cultures. These study findings underscore poverty and homelessness as major sources of perceived discrimination, and expose underlying complexities in the navigation of multiple identities in responding to stigma and discrimination. Current Controlled Trials ISRCTN42520374 . Registered 18 August 2009.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy.

PubMed

Zhu, Ying; Tan, Tuck Lee

2016-04-15

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects. Copyright © 2016 Elsevier B.V. All rights reserved.

Variable selection with stepwise and best subset approaches

PubMed Central

2016-01-01

While purposeful selection is performed partly by software and partly by hand, the stepwise and best subset approaches are automatically performed by software. Two R functions stepAIC() and bestglm() are well designed for stepwise and best subset regression, respectively. The stepAIC() function begins with a full or null model, and methods for stepwise regression can be specified in the direction argument with character values “forward”, “backward” and “both”. The bestglm() function begins with a data frame containing explanatory variables and response variables. The response variable should be in the last column. Varieties of goodness-of-fit criteria can be specified in the IC argument. The Bayesian information criterion (BIC) usually results in more parsimonious model than the Akaike information criterion. PMID:27162786

Melanin fluorescence spectra by step-wise three photon excitation

NASA Astrophysics Data System (ADS)

Lai, Zhenhua; Kerimo, Josef; DiMarzio, Charles A.

2012-03-01

Melanin is the characteristic chromophore of human skin with various potential biological functions. Kerimo discovered enhanced melanin fluorescence by stepwise three-photon excitation in 2011. In this article, step-wise three-photon excited fluorescence (STPEF) spectrum between 450 nm -700 nm of melanin is reported. The melanin STPEF spectrum exhibited an exponential increase with wavelength. However, there was a probability of about 33% that another kind of step-wise multi-photon excited fluorescence (SMPEF) that peaks at 525 nm, shown by previous research, could also be generated using the same process. Using an excitation source at 920 nm as opposed to 830 nm increased the potential for generating SMPEF peaks at 525 nm. The SMPEF spectrum peaks at 525 nm photo-bleached faster than STPEF spectrum.

Discriminant Analysis of Student Loan Applications

ERIC Educational Resources Information Center

Dyl, Edward A.; McGann, Anthony F.

1977-01-01

The use of discriminant analysis in identifying potentially "good" versus potentially "bad" student loans is explained. The technique is applied to a sample of 200 student loan applications at the University of Wyoming. (LBH)

Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

NASA Astrophysics Data System (ADS)

Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan

2010-12-01

This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.

Determination of five active compounds in Artemisia princeps and A. capillaris based on UPLC-DAD and discrimination of two species with multivariate analysis.

PubMed

Yang, Heejung; Lee, Dong Young; Jeon, Minji; Suh, Youngbae; Sung, Sang Hyun

2014-05-01

Five active compounds, chlorogenic acid, 3,5-di-O-caffeoylquinic acid, 4,5-di-O-caffeoylquinic acid, jaceosidin, and eupatilin, in Artemisia princeps (Compositae) were simultaneously determined by ultra-performance liquid chromatography connected to diode array detector. The morphological resemblance between A. princeps and A. capillaris makes it difficult to properly identify species properly. It occasionally leads to misuse or misapplication in Korean traditional medicine. In the study, the discrimination between A. princeps and A. capillaris was optimally performed by the developed validation method, which resulted in definitely a difference between two species. Also, it was developed the most reliable markers contributing to the discrimination of two species by the multivariate analysis methods, such as a principal component analysis and a partial least squares discrimination analysis.

An automated image processing method for classification of diabetic retinopathy stages from conjunctival microvasculature images

NASA Astrophysics Data System (ADS)

Khansari, Maziyar M.; O'Neill, William; Penn, Richard; Blair, Norman P.; Chau, Felix; Shahidi, Mahnaz

2017-03-01

The conjunctiva is a densely vascularized tissue of the eye that provides an opportunity for imaging of human microcirculation. In the current study, automated fine structure analysis of conjunctival microvasculature images was performed to discriminate stages of diabetic retinopathy (DR). The study population consisted of one group of nondiabetic control subjects (NC) and 3 groups of diabetic subjects, with no clinical DR (NDR), non-proliferative DR (NPDR), or proliferative DR (PDR). Ordinary least square regression and Fisher linear discriminant analyses were performed to automatically discriminate images between group pairs of subjects. Human observers who were masked to the grouping of subjects performed image discrimination between group pairs. Over 80% and 70% of images of subjects with clinical and non-clinical DR were correctly discriminated by the automated method, respectively. The discrimination rates of the automated method were higher than human observers. The fine structure analysis of conjunctival microvasculature images provided discrimination of DR stages and can be potentially useful for DR screening and monitoring.

Meta-analysis of field experiments shows no change in racial discrimination in hiring over time.

PubMed

Quillian, Lincoln; Pager, Devah; Hexel, Ole; Midtbøen, Arnfinn H

2017-10-10

This study investigates change over time in the level of hiring discrimination in US labor markets. We perform a meta-analysis of every available field experiment of hiring discrimination against African Americans or Latinos ( n = 28). Together, these studies represent 55,842 applications submitted for 26,326 positions. We focus on trends since 1989 ( n = 24 studies), when field experiments became more common and improved methodologically. Since 1989, whites receive on average 36% more callbacks than African Americans, and 24% more callbacks than Latinos. We observe no change in the level of hiring discrimination against African Americans over the past 25 years, although we find modest evidence of a decline in discrimination against Latinos. Accounting for applicant education, applicant gender, study method, occupational groups, and local labor market conditions does little to alter this result. Contrary to claims of declining discrimination in American society, our estimates suggest that levels of discrimination remain largely unchanged, at least at the point of hire.

Is it really organic?--multi-isotopic analysis as a tool to discriminate between organic and conventional plants.

PubMed

Laursen, K H; Mihailova, A; Kelly, S D; Epov, V N; Bérail, S; Schjoerring, J K; Donard, O F X; Larsen, E H; Pedentchouk, N; Marca-Bell, A D; Halekoh, U; Olesen, J E; Husted, S

2013-12-01

Novel procedures for analytical authentication of organic plant products are urgently needed. Here we present the first study encompassing stable isotopes of hydrogen, carbon, nitrogen, oxygen, magnesium and sulphur as well as compound-specific nitrogen and oxygen isotope analysis of nitrate for discrimination of organically and conventionally grown plants. The study was based on wheat, barley, faba bean and potato produced in rigorously controlled long-term field trials comprising 144 experimental plots. Nitrogen isotope analysis revealed the use of animal manure, but was unable to discriminate between plants that were fertilised with synthetic nitrogen fertilisers or green manures from atmospheric nitrogen fixing legumes. This limitation was bypassed using oxygen isotope analysis of nitrate in potato tubers, while hydrogen isotope analysis allowed complete discrimination of organic and conventional wheat and barley grains. It is concluded, that multi-isotopic analysis has the potential to disclose fraudulent substitutions of organic with conventionally cultivated plants. Copyright © 2013 Elsevier Ltd. All rights reserved.

Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics.

PubMed

Melucci, Dora; Bendini, Alessandra; Tesini, Federica; Barbieri, Sara; Zappi, Alessandro; Vichi, Stefania; Conte, Lanfranco; Gallina Toschi, Tullia

2016-08-01

At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between "100% Italian" and "non-100% Italian" oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined. Copyright © 2016. Published by Elsevier Ltd.

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

An Educational Model for Disruption of Bacteria for Protein Studies.

ERIC Educational Resources Information Center

Bhaduri, Saumya; Demchick, Paul H.

1984-01-01

A simple, rapid, and safe method has been developed for disrupting bacterial cells for protein studies. The method involved stepwise treatment of cells with acetone and with sodium dodecyl sulfate solution to allow extraction of cellular proteins for analysis by polyacrylamide gel electrophoresis. Applications for instructional purposes are noted.…

Student Physical Education Teachers' Well-Being: Contribution of Basic Psychological Needs

ERIC Educational Resources Information Center

Ciyin, Gülten; Erturan-Ilker, Gökçe

2014-01-01

This study adopted Self-Determination Theory tenets and aimed to explore whether student physical education (PE) teachers' satisfaction of the three basic psychological needs independently predicts well-being. 267 Turkish student PE teachers were recruited for the study. Two stepwise multiple regression analysis was performed in which each outcome…

Quality Curriculum for Under-Threes: The Impact of Structural Standards

ERIC Educational Resources Information Center

Wertfein, Monika; Spies-Kofler, Anita; Becker-Stoll, Fabienne

2009-01-01

The purpose of this study conducted in 36 infant-toddler centres ("Kinderkrippen") in the city of Munich in Bavaria/Germany was to explore structural characteristics of early child care and education and their effects on child care quality. Stepwise regressions and variance analysis (Manova) examined the relation between quality of care…

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Quantitative laser-induced breakdown spectroscopy data using peak area step-wise regression analysis: an alternative method for interpretation of Mars science laboratory results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clegg, Samuel M; Barefield, James E; Wiens, Roger C

2008-01-01

The ChemCam instrument on the Mars Science Laboratory (MSL) will include a laser-induced breakdown spectrometer (LIBS) to quantify major and minor elemental compositions. The traditional analytical chemistry approach to calibration curves for these data regresses a single diagnostic peak area against concentration for each element. This approach contrasts with a new multivariate method in which elemental concentrations are predicted by step-wise multiple regression analysis based on areas of a specific set of diagnostic peaks for each element. The method is tested on LIBS data from igneous and metamorphosed rocks. Between 4 and 13 partial regression coefficients are needed to describemore » each elemental abundance accurately (i.e., with a regression line of R{sup 2} > 0.9995 for the relationship between predicted and measured elemental concentration) for all major and minor elements studied. Validation plots suggest that the method is limited at present by the small data set, and will work best for prediction of concentration when a wide variety of compositions and rock types has been analyzed.« less

Nucleated red blood cells in growth-restricted fetuses: associations with short-term neonatal outcome.

PubMed

Minior, V K; Bernstein, P S; Divon, M Y

2000-01-01

To determine the utility of the neonatal nucleated red blood cell (NRBC) count as an independent predictor of short-term perinatal outcome in growth-restricted fetuses. Hospital charts of neonates with a discharge diagnosis indicating a birth weight <10th percentile were reviewed for perinatal outcome. We studied all eligible neonates who had a complete blood count on the first day of life. After multiple gestations, anomalous fetuses and diabetic pregnancies were excluded; 73 neonates comprised the study group. Statistical analysis included ANOVA, simple and stepwise regression. Elevated NRBC counts were significantly associated with cesarean section for non-reassuring fetal status, neonatal intensive care unit admission and duration of neonatal intensive care unit stay, respiratory distress and intubation, thrombocytopenia, hyperbilirubinemia, intraventricular hemorrhage and neonatal death. Stepwise regression analysis including gestational age at birth, birth weight and NRBC count demonstrated that in growth-restricted fetuses, NRBC count was the strongest predictor of neonatal intraventricular hemorrhage, neonatal respiratory distress and neonatal death. An elevated NRBC count independently predicts adverse perinatal outcome in growth-restricted fetuses. Copyright 2000 S. Karger AG, Basel.

Escherichia coli identification and strain discrimination using nanosecond laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Diedrich, Jonathan; Rehse, Steven J.; Palchaudhuri, Sunil

2007-04-01

Three strains of Escherichia coli, one strain of environmental mold, and one strain of Candida albicans yeast have been analyzed by laser-induced breakdown spectroscopy using nanosecond laser pulses. All microorganisms were analyzed while still alive and with no sample preparation. Nineteen atomic and ionic emission lines have been identified in the spectrum, which is dominated by calcium, magnesium, and sodium. A discriminant function analysis has been used to discriminate between the biotypes and E. coli strains. This analysis showed efficient discrimination between laser-induced breakdown spectroscopy spectra from different strains of a single bacteria species.

Gender Wage Inequality and Economic Growth: Is There Really a Puzzle?-A Comment.

PubMed

Schober, Thomas; Winter-Ebmer, Rudolf

2011-08-01

Seguino (2000) shows that gender wage discrimination in export-oriented semi-industrialized countries might be fostering investment and growth in general. While the original analysis does not have internationally comparable wage discrimination data, we replicate the analysis using data from a meta-study on gender wage discrimination and do not find any evidence that more discrimination might further economic growth-on the contrary: if anything the impact of gender inequality is negative for growth. Standing up for more gender equality-also in terms of wages-is good for equity considerations and at least not negative for growth.

Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability.

PubMed

Krafty, Robert T

2016-07-01

Many studies record replicated time series epochs from different groups with the goal of using frequency domain properties to discriminate between the groups. In many applications, there exists variation in cyclical patterns from time series in the same group. Although a number of frequency domain methods for the discriminant analysis of time series have been explored, there is a dearth of models and methods that account for within-group spectral variability. This article proposes a model for groups of time series in which transfer functions are modeled as stochastic variables that can account for both between-group and within-group differences in spectra that are identified from individual replicates. An ensuing discriminant analysis of stochastic cepstra under this model is developed to obtain parsimonious measures of relative power that optimally separate groups in the presence of within-group spectral variability. The approach possess favorable properties in classifying new observations and can be consistently estimated through a simple discriminant analysis of a finite number of estimated cepstral coefficients. Benefits in accounting for within-group spectral variability are empirically illustrated in a simulation study and through an analysis of gait variability.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of Landsat digital data. [mapping of hydrothermally altered volcanic rocks

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed using Johnson's HICLUS program. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

MATRIX DISCRIMINANT ANALYSIS WITH APPLICATION TO COLORIMETRIC SENSOR ARRAY DATA

PubMed Central

Suslick, Kenneth S.

2014-01-01

With the rapid development of nano-technology, a “colorimetric sensor array” (CSA) which is referred to as an optical electronic nose has been developed for the identification of toxicants. Unlike traditional sensors which rely on a single chemical interaction, CSA can measure multiple chemical interactions by using chemo-responsive dyes. The color changes of the chemo-responsive dyes are recorded before and after exposure to toxicants and serve as a template for classification. The color changes are digitalized in the form of a matrix with rows representing dye effects and columns representing the spectrum of colors. Thus, matrix-classification methods are highly desirable. In this article, we develop a novel classification method, matrix discriminant analysis (MDA), which is a generalization of linear discriminant analysis (LDA) for the data in matrix form. By incorporating the intrinsic matrix-structure of the data in discriminant analysis, the proposed method can improve CSA’s sensitivity and more importantly, specificity. A penalized MDA method, PMDA, is also introduced to further incorporate sparsity structure in discriminant function. Numerical studies suggest that the proposed MDA and PMDA methods outperform LDA and other competing discriminant methods for matrix predictors. The asymptotic consistency of MDA is also established. R code and data are available online as supplementary material. PMID:26783371

Proof of Principle for a Real-Time Pathogen Isolation Media Diagnostic: The Use of Laser-Induced Breakdown Spectroscopy to Discriminate Bacterial Pathogens and Antimicrobial-Resistant Staphylococcus aureus Strains Grown on Blood Agar

PubMed Central

Multari, Rosalie A.; Cremers, David A.; Bostian, Melissa L.; Dupre, Joanne M.

2013-01-01

Laser-Induced Breakdown Spectroscopy (LIBS) is a rapid, in situ, diagnostic technique in which light emissions from a laser plasma formed on the sample are used for analysis allowing automated analysis results to be available in seconds to minutes. This speed of analysis coupled with little or no sample preparation makes LIBS an attractive detection tool. In this study, it is demonstrated that LIBS can be utilized to discriminate both the bacterial species and strains of bacterial colonies grown on blood agar. A discrimination algorithm was created based on multivariate regression analysis of spectral data. The algorithm was deployed on a simulated LIBS instrument system to demonstrate discrimination capability using 6 species. Genetically altered Staphylococcus aureus strains grown on BA, including isogenic sets that differed only by the acquisition of mutations that increase fusidic acid or vancomycin resistance, were also discriminated. The algorithm successfully identified all thirteen cultures used in this study in a time period of 2 minutes. This work provides proof of principle for a LIBS instrumentation system that could be developed for the rapid discrimination of bacterial species and strains demonstrating relatively minor genomic alterations using data collected directly from pathogen isolation media. PMID:24109513

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

Credit scoring analysis using kernel discriminant

NASA Astrophysics Data System (ADS)

Widiharih, T.; Mukid, M. A.; Mustafid

2018-05-01

Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Score-moment combined linear discrimination analysis (SMC-LDA) as an improved discrimination method.

PubMed

Han, Jintae; Chung, Hoeil; Han, Sung-Hwan; Yoon, Moon-Young

2007-01-01

A new discrimination method called the score-moment combined linear discrimination analysis (SMC-LDA) has been developed and its performance has been evaluated using three practical spectroscopic datasets. The key concept of SMC-LDA was to use not only the score from principal component analysis (PCA), but also the moment of the spectrum, as inputs for LDA to improve discrimination. Along with conventional score, moment is used in spectroscopic fields as an effective alternative for spectral feature representation. Three different approaches were considered. Initially, the score generated from PCA was projected onto a two-dimensional feature space by maximizing Fisher's criterion function (conventional PCA-LDA). Next, the same procedure was performed using only moment. Finally, both score and moment were utilized simultaneously for LDA. To evaluate discrimination performances, three different spectroscopic datasets were employed: (1) infrared (IR) spectra of normal and malignant stomach tissue, (2) near-infrared (NIR) spectra of diesel and light gas oil (LGO) and (3) Raman spectra of Chinese and Korean ginseng. For each case, the best discrimination results were achieved when both score and moment were used for LDA (SMC-LDA). Since the spectral representation character of moment was different from that of score, inclusion of both score and moment for LDA provided more diversified and descriptive information.

Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar.

PubMed

Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

2015-02-25

Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm(-1)). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparison of discriminant analysis methods: Application to occupational exposure to particulate matter

NASA Astrophysics Data System (ADS)

Ramos, M. Rosário; Carolino, E.; Viegas, Carla; Viegas, Sandra

2016-06-01

Health effects associated with occupational exposure to particulate matter have been studied by several authors. In this study were selected six industries of five different areas: Cork company 1, Cork company 2, poultry, slaughterhouse for cattle, riding arena and production of animal feed. The measurements tool was a portable device for direct reading. This tool provides information on the particle number concentration for six different diameters, namely 0.3 µm, 0.5 µm, 1 µm, 2.5 µm, 5 µm and 10 µm. The focus on these features is because they might be more closely related with adverse health effects. The aim is to identify the particles that better discriminate the industries, with the ultimate goal of classifying industries regarding potential negative effects on workers' health. Several methods of discriminant analysis were applied to data of occupational exposure to particulate matter and compared with respect to classification accuracy. The selected methods were linear discriminant analyses (LDA); linear quadratic discriminant analysis (QDA), robust linear discriminant analysis with selected estimators (MLE (Maximum Likelihood Estimators), MVE (Minimum Volume Elipsoid), "t", MCD (Minimum Covariance Determinant), MCD-A, MCD-B), multinomial logistic regression and artificial neural networks (ANN). The predictive accuracy of the methods was accessed through a simulation study. ANN yielded the highest rate of classification accuracy in the data set under study. Results indicate that the particle number concentration of diameter size 0.5 µm is the parameter that better discriminates industries.

An Analysis of the Association between Perceived Discrimination and Self-Reported Health among University Students in Southwest Florida

ERIC Educational Resources Information Center

McFarland, Renee L.

2013-01-01

The experience of discrimination is a complex phenomenon. At present, there are few studies that have captured the experience of discrimination on a predominately white university campus. This study was designed to investigate the association between perceived discrimination and self-reported health outcomes among university students in Southwest…

Stepwise hydrolysis to improve carbon releasing efficiency from sludge.

PubMed

Liu, Hongbo; Wang, Yuanyuan; Wang, Ling; Yu, Tiantian; Fu, Bo; Liu, He

2017-08-01

Based on thermal alkaline hydrolysis (TAH), a novel strategy of stepwise hydrolysis was developed to improve carbon releasing efficiency from waste activated sludge (WAS). By stepwise increasing hydrolysis intensity, conventional sludge hydrolysis (the control) was divided into four stages for separately recovering sludge carbon sources with different bonding strengths, namely stage 1 (60 °C, pH 6.0-8.0), stage 2 (80 °C, pH 6.0-8.0), stage 3 (80 °C, pH 10.0) and stage 4 (90 °C, pH 12.0). Results indicate stepwise hydrolysis could enhance the amount of released soluble chemical oxygen demand (SCOD) for almost 2 times, from 7200 to 14,693 mg/L, and the released carbon presented better biodegradability, with BOD/COD of 0.47 and volatile fatty acids (VFAs) yield of 0.37 g VFAs/g SCOD via anaerobic fermentation. Moreover, stepwise hydrolysis also improved the dewaterability of hydrolyzed sludge, capillary suction time (CST) reducing from 2500 to 1600 s. Economic assessment indicates stepwise hydrolysis shows less alkali demand and lower thermal energy consumption than those of the control. Furthermore, results of this study help support the concepts of improving carbon recovery in wastewater by manipulating WAS composition and the idea of classifiably recovering the nutrients in WAS. Copyright © 2017 Elsevier Ltd. All rights reserved.

Diagnosis of human malignancies using laser-induced breakdown spectroscopy in combination with chemometric methods

NASA Astrophysics Data System (ADS)

Chen, Xue; Li, Xiaohui; Yu, Xin; Chen, Deying; Liu, Aichun

2018-01-01

Diagnosis of malignancies is a challenging clinical issue. In this work, we present quick and robust diagnosis and discrimination of lymphoma and multiple myeloma (MM) using laser-induced breakdown spectroscopy (LIBS) conducted on human serum samples, in combination with chemometric methods. The serum samples collected from lymphoma and MM cancer patients and healthy controls were deposited on filter papers and ablated with a pulsed 1064 nm Nd:YAG laser. 24 atomic lines of Ca, Na, K, H, O, and N were selected for malignancy diagnosis. Principal component analysis (PCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and k nearest neighbors (kNN) classification were applied to build the malignancy diagnosis and discrimination models. The performances of the models were evaluated using 10-fold cross validation. The discrimination accuracy, confusion matrix and receiver operating characteristic (ROC) curves were obtained. The values of area under the ROC curve (AUC), sensitivity and specificity at the cut-points were determined. The kNN model exhibits the best performances with overall discrimination accuracy of 96.0%. Distinct discrimination between malignancies and healthy controls has been achieved with AUC, sensitivity and specificity for healthy controls all approaching 1. For lymphoma, the best discrimination performance values are AUC = 0.990, sensitivity = 0.970 and specificity = 0.956. For MM, the corresponding values are AUC = 0.986, sensitivity = 0.892 and specificity = 0.994. The results show that the serum-LIBS technique can serve as a quick, less invasive and robust method for diagnosis and discrimination of human malignancies.

Direct 40Ar/39Ar age determination of fluid inclusions using in-vacuo¬ stepwise crushing - Example of garnet from the Cycladic Blueschist Unit on Syros

NASA Astrophysics Data System (ADS)

Uunk, Bertram; Postma, Onno; Wijbrans, Jan; Brouwer, Fraukje

2017-04-01

Metamorphic minerals and veins commonly trap attending hydrous fluids in fluid inclusions, which yield a wealth of information on the history of the hosting metamorphic system. When these fluids are sufficiently saline, the KCl in the inclusions can be used as a K/Ar geochronologic system, potentially dating inclusion incorporation. Whilst primary fluid inclusions (PFIs) can date fluid incorporation during mineral or vein growth, secondary fluid inclusion trails (SFIs) can provide age constraints on later fluid flow events. At VU Amsterdam, a new in-vacuo crushing apparatus has been designed to extract fluid inclusions from minerals for 40Ar/39Ar analysis. Separates are crushed inside a crusher tube connected to a purification line and a quadrupole mass spectrometer. In-vacuo crushing is achieved by lifting and dropping a steel pestle using an externally controlled magnetic field. As the gas can be analyzed between different crushing steps, the setup permits stepwise crushing experiments. Additionally, crushed powder can be heated by inserting the crusher tube in an externally controlled furnace. Dating by 40Ar/39Ar stepwise crushing has the added advantage that, during neutron irradiation to produce 39Ar from 39K, 38Ar and 37Ar are also produced from 38Cl and 40Ca, respectively. Simultaneous analysis of these argon isotopes permits constraining the chemistry of the argon source sampled during the experiment. This allows a distinction between different fluid or crystal lattice sources. Garnet from three samples of the HP metamorphic Cycladic Blueschist Unit on Syros, Greece was stepwise crushed to obtain fluid inclusion ages. Initial steps for all three experiments yield significant components of excess argon, which are interpreted to originate from grain boundary fluids and secondary fluid inclusions trails. During subsequent steps, age results stabilize to a plateau age. One garnet from North Syros yields an unusually old 80 Ma plateau age. However, isochrons indicate the presence of excess argon in the PFIs and isochron ages overlap with other isotopic constraints on the age of garnet growth during eclogite metamorphism (55-50 Ma) in the underlying metabasite. Garnet from two samples from the center of Syros yields younger ages overlapping with greenschist overprinting (25-30 Ma). Further studies will indicate whether these younger ages reflect a young garnet growth age or a young fluid flow event affecting older garnet crystals. The stepwise crushing and heating approach shows to be effective in dating fluid inclusions in natural mineral systems. As many metamorphic processes occur under influence or in the presence of fluids, this method should greatly expand our possibilities to date crustal processes.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

ERIC Educational Resources Information Center

Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

2016-01-01

Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

The Coopersmith Self-Esteem Inventory in an Adult Sample.

ERIC Educational Resources Information Center

Noller, Patricia; Shugm, David

1988-01-01

The reliability and validity of the Self-Esteem Inventory developed by S. C. Coopersmith (1975) were evaluated via item-total correlation, discriminant analysis, factor analysis, and analysis of variance of data for 352 Australian adults. The instrument had high internal consistency and discriminated well between subjects with high and low…

Metabolic fingerprinting of Cannabis sativa L., cannabinoids and terpenoids for chemotaxonomic and drug standardization purposes.

PubMed

Fischedick, Justin Thomas; Hazekamp, Arno; Erkelens, Tjalling; Choi, Young Hae; Verpoorte, Rob

2010-12-01

Cannabis sativa L. is an important medicinal plant. In order to develop cannabis plant material as a medicinal product quality control and clear chemotaxonomic discrimination between varieties is a necessity. Therefore in this study 11 cannabis varieties were grown under the same environmental conditions. Chemical analysis of cannabis plant material used a gas chromatography flame ionization detection method that was validated for quantitative analysis of cannabis monoterpenoids, sesquiterpenoids, and cannabinoids. Quantitative data was analyzed using principal component analysis to determine which compounds are most important in discriminating cannabis varieties. In total 36 compounds were identified and quantified in the 11 varieties. Using principal component analysis each cannabis variety could be chemically discriminated. This methodology is useful for both chemotaxonomic discrimination of cannabis varieties and quality control of plant material. Copyright © 2010 Elsevier Ltd. All rights reserved.

Natural Genetic Variation for Acclimation of Photosynthetic Light Use Efficiency to Growth Irradiance in Arabidopsis1[OPEN

PubMed Central

Harbinson, Jeremy

2015-01-01

Plants are known to be able to acclimate their photosynthesis to the level of irradiance. Here, we present the analysis of natural genetic variation for photosynthetic light use efficiency (ΦPSII) in response to five light environments among 12 genetically diverse Arabidopsis (Arabidopsis thaliana) accessions. We measured the acclimation of ΦPSII to constant growth irradiances of four different levels (100, 200, 400, and 600 µmol m−2 s−1) by imaging chlorophyll fluorescence after 24 d of growth and compared these results with acclimation of ΦPSII to a step-wise change in irradiance where the growth irradiance was increased from 100 to 600 µmol m−2 s−1 after 24 d of growth. Genotypic variation for ΦPSII is shown by calculating heritability for the short-term ΦPSII response to different irradiance levels as well as for the relation of ΦPSII measured at light saturation (a measure of photosynthetic capacity) to growth irradiance level and for the kinetics of the response to a step-wise increase in irradiance from 100 to 600 µmol m−2 s−1. A genome-wide association study for ΦPSII measured 1 h after a step-wise increase in irradiance identified several new candidate genes controlling this trait. In conclusion, the different photosynthetic responses to a changing light environment displayed by different Arabidopsis accessions are due to genetic differences, and we have identified candidate genes for the photosynthetic response to an irradiance change. The genetic variation for photosynthetic acclimation to irradiance found in this study will allow future identification and analysis of the causal genes for the regulation of ΦPSII in plants. PMID:25670817

A step-wise approach for analysis of the mouse embryonic heart using 17.6 Tesla MRI

PubMed Central

Gabbay-Benziv, Rinat; Reece, E. Albert; Wang, Fang; Bar-Shir, Amnon; Harman, Chris; Turan, Ozhan M.; Yang, Peixin; Turan, Sifa

2018-01-01

Background The mouse embryo is ideal for studying human cardiac development. However, laboratory discoveries do not easily translate into clinical findings partially because of histological diagnostic techniques that induce artifacts and lack standardization. Aim To present a step-wise approach using 17.6 T MRI, for evaluation of mice embryonic heart and accurate identification of congenital heart defects. Subjects 17.5-embryonic days embryos from low-risk (non-diabetic) and high-risk (diabetic) model dams. Study design Embryos were imaged using 17.6 Tesla MRI. Three-dimensional volumes were analyzed using ImageJ software. Outcome measures Embryonic hearts were evaluated utilizing anatomic landmarks to locate the four-chamber view, the left- and right-outflow tracts, and the arrangement of the great arteries. Inter- and intra-observer agreement were calculated using kappa scores by comparing two researchers’ evaluations independently analyzing all hearts, blinded to the model, on three different, timed occasions. Each evaluated 16 imaging volumes of 16 embryos: 4 embryos from normal dams, and 12 embryos from diabetic dams. Results Inter-observer agreement and reproducibility were 0.779 (95% CI 0.653–0.905) and 0.763 (95% CI 0.605–0.921), respectively. Embryonic hearts were structurally normal in 4/4 and 7/12 embryos from normal and diabetic dams, respectively. Five embryos from diabetic dams had defects: ventricular septal defects (n = 2), transposition of great arteries (n = 2) and Tetralogy of Fallot (n = 1). Both researchers identified all cardiac lesions. Conclusion A step-wise approach for analysis of MRI-derived 3D imaging provides reproducible detailed cardiac evaluation of normal and abnormal mice embryonic hearts. This approach can accurately reveal cardiac structure and, thus, increases the yield of animal model in congenital heart defect research. PMID:27569369

Development, validation and operating room-transfer of a six-step laparoscopic training program for the vesicourethral anastomosis.

PubMed

Klein, Jan; Teber, Dogu; Frede, Tom; Stock, Christian; Hruza, Marcel; Gözen, Ali; Seemann, Othmar; Schulze, Michael; Rassweiler, Jens

2013-03-01

Development and full validation of a laparoscopic training program for stepwise learning of a reproducible application of a standardized laparoscopic anastomosis technique and integration into the clinical course. The training of vesicourethral anastomosis (VUA) was divided into six simple standardized steps. To fix the objective criteria, four experienced surgeons performed the stepwise training protocol. Thirty-eight participants with no previous laparoscopic experience were investigated in their training performance. The times needed to manage each training step and the total training time were recorded. The integration into the clinical course was investigated. The training results and the corresponding steps during laparoscopic radical prostatectomy (LRP) were analyzed. Data analysis of corresponding operating room (OR) sections of 793 LRP was performed. Based on the validity, criteria were determined. In the laboratory section, a significant reduction of OR time for every step was seen in all participants. Coordination: 62%; longitudinal incision: 52%; inverted U-shape incision: 43%; plexus: 47%. Anastomosis catheter model: 38%. VUA: 38%. The laboratory section required a total time of 29 hours (minimum: 16 hours; maximum: 42 hours). All participants had shorter execution times in the laboratory than under real conditions. The best match was found within the VUA model. To perform an anastomosis under real conditions, 25% more time was needed. By using the training protocol, the performance of the VUA is comparable to that of an surgeon with experience of about 50 laparoscopic VUA. Data analysis proved content, construct, and prognostic validity. The use of stepwise training approaches enables a surgeon to learn and reproduce complex reconstructive surgical tasks: eg, the VUA in a safe environment. The validity of the designed system is given at all levels and should be used as a standard in the clinical surgical training in laparoscopic reconstructive urology.

Dynamic in vivo binding of transcription factors to cis-regulatory modules of cer and gsc in the stepwise formation of the Spemann–Mangold organizer

PubMed Central

Sudou, Norihiro; Yamamoto, Shinji; Ogino, Hajime; Taira, Masanori

2012-01-01

How multiple developmental cues are integrated on cis-regulatory modules (CRMs) for cell fate decisions remains uncertain. The Spemann–Mangold organizer in Xenopus embryos expresses the transcription factors Lim1/Lhx1, Otx2, Mix1, Siamois (Sia) and VegT. Reporter analyses using sperm nuclear transplantation and DNA injection showed that cerberus (cer) and goosecoid (gsc) are activated by the aforementioned transcription factors through CRMs conserved between X. laevis and X. tropicalis. ChIP-qPCR analysis for the five transcription factors revealed that cer and gsc CRMs are initially bound by both Sia and VegT at the late blastula stage, and subsequently bound by all five factors at the gastrula stage. At the neurula stage, only binding of Lim1 and Otx2 to the gsc CRM, among others, persists, which corresponds to their co-expression in the prechordal plate. Based on these data, together with detailed expression pattern analysis, we propose a new model of stepwise formation of the organizer, in which (1) maternal VegT and Wnt-induced Sia first bind to CRMs at the blastula stage; then (2) Nodal-inducible Lim1, Otx2, Mix1 and zygotic VegT are bound to CRMs in the dorsal endodermal and mesodermal regions where all these genes are co-expressed; and (3) these two regions are combined at the gastrula stage to form the organizer. Thus, the in vivo dynamics of multiple transcription factors highlight their roles in the initiation and maintenance of gene expression, and also reveal the stepwise integration of maternal, Nodal and Wnt signaling on CRMs of organizer genes to generate the organizer. PMID:22492356

Dynamic in vivo binding of transcription factors to cis-regulatory modules of cer and gsc in the stepwise formation of the Spemann-Mangold organizer.

PubMed

Sudou, Norihiro; Yamamoto, Shinji; Ogino, Hajime; Taira, Masanori

2012-05-01

How multiple developmental cues are integrated on cis-regulatory modules (CRMs) for cell fate decisions remains uncertain. The Spemann-Mangold organizer in Xenopus embryos expresses the transcription factors Lim1/Lhx1, Otx2, Mix1, Siamois (Sia) and VegT. Reporter analyses using sperm nuclear transplantation and DNA injection showed that cerberus (cer) and goosecoid (gsc) are activated by the aforementioned transcription factors through CRMs conserved between X. laevis and X. tropicalis. ChIP-qPCR analysis for the five transcription factors revealed that cer and gsc CRMs are initially bound by both Sia and VegT at the late blastula stage, and subsequently bound by all five factors at the gastrula stage. At the neurula stage, only binding of Lim1 and Otx2 to the gsc CRM, among others, persists, which corresponds to their co-expression in the prechordal plate. Based on these data, together with detailed expression pattern analysis, we propose a new model of stepwise formation of the organizer, in which (1) maternal VegT and Wnt-induced Sia first bind to CRMs at the blastula stage; then (2) Nodal-inducible Lim1, Otx2, Mix1 and zygotic VegT are bound to CRMs in the dorsal endodermal and mesodermal regions where all these genes are co-expressed; and (3) these two regions are combined at the gastrula stage to form the organizer. Thus, the in vivo dynamics of multiple transcription factors highlight their roles in the initiation and maintenance of gene expression, and also reveal the stepwise integration of maternal, Nodal and Wnt signaling on CRMs of organizer genes to generate the organizer.

Don't ask for fair treatment? A gender analysis of ethnic discrimination, response to discrimination, and self-rated health among marriage migrants in South Korea.

PubMed

Kim, Yugyun; Son, Inseo; Wie, Dainn; Muntaner, Carles; Kim, Hyunwoo; Kim, Seung-Sup

2016-07-19

Ethnic discrimination is increasingly common nowadays in South Korea with the influx of migrants. Despite the growing body of evidences suggests that ethnic discrimination negatively impacts health, only few researches have been conducted on the association between ethnic discrimination and health outcomes among marriage migrants in Korea. This study sought to examine how ethnic discrimination and response to the discrimination are related to self-rated health and whether the association differs by victim's gender. We conducted two-step analysis using cross-sectional dataset from the 'National Survey of Multicultural Families 2012'. First, we examined the association between perceived ethnic discrimination and self-rated health among 14,406 marriage migrants in Korea. Second, among the marriage migrants who experienced ethnic discrimination (n=5,880), we examined how response to discrimination (i.e., whether or not asking for fair treatment) is related to poor self-rated health. All analyses were conducted after being stratified by the migrant's gender. This research found the significant association between ethnic discrimination and poor self-rated health among female marriage migrants (OR: 1.53, 95 % CI: 1.32, 1.76), but not among male marriage migrants (OR: 1.16, 95 % CI: 0.81, 1.66). In the restricted analysis with marriage migrants who experienced ethnic discrimination, compared to the group who did not ask for fair treatment, female marriage migrants who asked for fair treatment were more likely to report poor self-rated health (OR: 1.21, 95 % CI: 0.98, 1.50); however, male marriage migrants who asked for fair treatment were less likely to report poor self-rated health (OR: 0.65, 95 % CI: 0.36, 1.04) although both were not statistically significant. This is the first study to investigate gender difference in the association between response to ethnic discrimination and self-rated health in South Korea. We discussed that gender may play an important role in the association between response to discrimination and self-rated health among marriage migrants in Korea. In order to prevent discrimination which could endanger the health of ethnic minorities including marriage migrants, relevant policies are needed.

Discrimination of cultivation ages and cultivars of ginseng leaves using Fourier transform infrared spectroscopy combined with multivariate analysis

PubMed Central

Kwon, Yong-Kook; Ahn, Myung Suk; Park, Jong Suk; Liu, Jang Ryol; In, Dong Su; Min, Byung Whan; Kim, Suk Weon

2013-01-01

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng. PMID:24558311

Graphical methods for the sensitivity analysis in discriminant analysis

DOE PAGES

Kim, Youngil; Anderson-Cook, Christine M.; Dae-Heung, Jang

2015-09-30

Similar to regression, many measures to detect influential data points in discriminant analysis have been developed. Many follow similar principles as the diagnostic measures used in linear regression in the context of discriminant analysis. Here we focus on the impact on the predicted classification posterior probability when a data point is omitted. The new method is intuitive and easily interpretative compared to existing methods. We also propose a graphical display to show the individual movement of the posterior probability of other data points when a specific data point is omitted. This enables the summaries to capture the overall pattern ofmore » the change.« less

Forensic analysis of printing inks using tandem Laser Induced Breakdown Spectroscopy and Laser Ablation Inductively Coupled Plasma Mass Spectrometry

NASA Astrophysics Data System (ADS)

Subedi, Kiran; Trejos, Tatiana; Almirall, José

2015-01-01

Elemental analysis, using either LA-ICP-MS or LIBS, can be used for the chemical characterization of materials of forensic interest to discriminate between source materials originating from different sources and also for the association of materials known to originate from the same source. In this study, a tandem LIBS/LA-ICP-MS system that combines the benefits of both LIBS and LA-ICP-MS was evaluated for the characterization of samples of printing inks (toners, inkjets, intaglio and offset.). The performance of both laser sampling methods is presented. A subset of 9 black laser toners, 10 colored (CMYK) inkjet samples, 12 colored (CMYK) offset samples and 12 intaglio inks originating from different manufacturing sources were analyzed to evaluate the discrimination capability of the tandem method. These samples were selected because they presented a very similar elemental profile by LA-ICP-MS. Although typical discrimination between different ink sources is found to be > 99% for a variety of inks when only LA-ICP-MS was used for the analysis, additional discrimination was achieved by combining the elemental results from the LIBS analysis to the LA-ICP-MS analysis in the tandem technique, enhancing the overall discrimination capability of the individual laser ablation methods. The LIBS measurements of the Ca, Fe, K and Si signals, in particular, improved the discrimination for this specific set of different ink samples previously shown to exhibit very similar LA-ICP-MS elemental profiles. The combination of these two techniques in a single setup resulted in better discrimination of the printing inks with two distinct fingerprint spectra, providing information from atomic/ionic emissions and isotopic composition (m/z) for each ink sample.