SU-F-P-64: The Impact of Plan Complexity Parameters On the Plan Quality and Deliverability of Volumetric Modulated Arc Therapy with Canonical Correlation Analysis

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

Jin, X; Yi, J; Xie, C

Purpose: To evaluate the impact of complexity indices on the plan quality and deliverability of volumetric modulated arc therapy (VMAT), and to determine the most significant parameters in the generation of an ideal VMAT plan. Methods: A multi-dimensional exploratory statistical method, canonical correlation analysis (CCA) was adopted to study the correlations between VMAT parameters of complexity, quality and deliverability, as well as their contribution weights with 32 two-arc VMAT nasopharyngeal cancer (NPC) patients and 31 one-arc VMAT prostate cancer patients. Results: The MU per arc (MU/Arc) and MU per control point (MU/CP) of NPC were 337.8±25.2 and 3.7±0.3, respectively, whichmore » were significantly lower than those of prostate cancer patients (MU/Arc : 506.9±95.4, MU/CP : 5.6±1.1). The plan complexity indices indicated that two-arc VMAT plans were more complex than one-arc VMAT plans. Plan quality comparison confirmed that one-arc VMAT plans had a high quality than two-arc VMAT plans. CCA results implied that plan complexity parameters were highly correlated with plan quality with the first two canonical correlations of 0.96, 0.88 (both p<0.001) and significantly correlated with deliverability with the first canonical correlation of 0.79 (p<0.001), plan quality and deliverability was also correlated with the first canonical correlation of 0.71 (p=0.02). Complexity parameters of MU/CP, segment area (SA) per CP, percent of MU/CP less 3 and planning target volume (PTV) were weighted heavily in correlation with plan quality and deliveability . Similar results obtained from individual NPC and prostate CCA analysis. Conclusion: Relationship between complexity, quality, and deliverability parameters were investigated with CCA. MU, SA related parameters and PTV volume were found to have strong effect on the plan quality and deliverability. The presented correlation among different quantified parameters could be used to improve the plan quality and the efficiency of the radiotherapy process when creating a complex VMAT plan.« less

Canonical correlation analysis of infant's size at birth and maternal factors: a study in rural northwest Bangladesh.

PubMed

Kabir, Alamgir; Merrill, Rebecca D; Shamim, Abu Ahmed; Klemn, Rolf D W; Labrique, Alain B; Christian, Parul; West, Keith P; Nasser, Mohammed

2014-01-01

This analysis was conducted to explore the association between 5 birth size measurements (weight, length and head, chest and mid-upper arm [MUAC] circumferences) as dependent variables and 10 maternal factors as independent variables using canonical correlation analysis (CCA). CCA considers simultaneously sets of dependent and independent variables and, thus, generates a substantially reduced type 1 error. Data were from women delivering a singleton live birth (n = 14,506) while participating in a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural Bangladesh. The first canonical correlation was 0.42 (P<0.001), demonstrating a moderate positive correlation mainly between the 5 birth size measurements and 5 maternal factors (preterm delivery, early pregnancy MUAC, infant sex, age and parity). A significant interaction between infant sex and preterm delivery on birth size was also revealed from the score plot. Thirteen percent of birth size variability was explained by the composite score of the maternal factors (Redundancy, RY/X = 0.131). Given an ability to accommodate numerous relationships and reduce complexities of multiple comparisons, CCA identified the 5 maternal variables able to predict birth size in this rural Bangladesh setting. CCA may offer an efficient, practical and inclusive approach to assessing the association between two sets of variables, addressing the innate complexity of interactions.

Allozyme markers in breeding zone designation

Treesearch

R. D. Westfall; M. T. Conkle

1992-01-01

Early studies of allozyme variation in plant populations suggested that allelic frequencies in some loci vary by geography. Since then, the expectation that allozymes might be useful in describing geographic patterns has generally not been borne out by single locus analyses, except on the broadest scale. Multi-locus analyses reveal the converse: canonical correlation...

Life skills and subjective well-being of people with disabilities: a canonical correlation analysis.

PubMed

da Silva Cardoso, Elizabeth; Blalock, Kacie; Allen, Chase A; Chan, Fong; Rubin, Stanford E

2004-12-01

This study examined the canonical relationships between a set of life skill variables and a set of subjective well-being variables among a national sample of vocational rehabilitation clients in the USA. Self-direction, work tolerance, general employability, and self-care were related to physical, family and social, and financial well-being. This analysis also found that communication skill is related to family and social well-being, while psychological well-being is not related to any life skills in the set. The results showed that vocational rehabilitation services aimed to improve life functioning will lead to an improvement in subjective quality of life.

The Mochi project: a field theory approach to plasma dynamics and self-organization

NASA Astrophysics Data System (ADS)

You, Setthivoine; von der Linden, Jens; Lavine, Eric Sander; Card, Alexander; Carroll, Evan

2016-10-01

The Mochi project is designed to study the interaction between plasma flows and magnetic fields from the point-of-view of canonical flux tubes. The Mochi Labjet experiment is being commissioned after achieving first plasma. Analytical and numerical tools are being developed to visualize canonical flux tubes. One analytical tool described here is a field theory approach to plasma dynamics and self-organization. A redefinition of the Lagrangian of a multi-particle system in fields reformulates the single-particle, kinetic, and fluid equations governing fluid and plasma dynamics as a single set of generalized Maxwell's equations and Ohm's law for canonical force-fields. The Lagrangian includes new terms representing the coupling between the motion of particle distributions, between distributions and electromagnetic fields, with relativistic contributions. The formulation shows that the concepts of self-organization and canonical helicity transport are applicable across single-particle, kinetic, and fluid regimes, at classical and relativistic scales. The theory gives the basis for comparing canonical helicity change to energy change in general systems. This work is supported by by US DOE Grant DE-SC0010340.

Long-term forecasting of meteorological time series using Nonlinear Canonical Correlation Analysis (NLCCA)

NASA Astrophysics Data System (ADS)

Woldesellasse, H. T.; Marpu, P. R.; Ouarda, T.

2016-12-01

Wind is one of the crucial renewable energy sources which is expected to bring solutions to the challenges of clean energy and the global issue of climate change. A number of linear and nonlinear multivariate techniques has been used to predict the stochastic character of wind speed. A wind forecast with good accuracy has a positive impact on the reduction of electricity system cost and is essential for the effective grid management. Over the past years, few studies have been done on the assessment of teleconnections and its possible effects on the long-term wind speed variability in the UAE region. In this study Nonlinear Canonical Correlation Analysis (NLCCA) method is applied to study the relationship between global climate oscillation indices and meteorological variables, with a major emphasis on wind speed and wind direction, of Abu Dhabi, UAE. The wind dataset was obtained from six ground stations. The first mode of NLCCA is capable of capturing the nonlinear mode of the climate indices at different seasons, showing the symmetry between the warm states and the cool states. The strength of the nonlinear canonical correlation between the two sets of variables varies with the lead/lag time. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE) and Mean absolute error (MAE). The results indicated that NLCCA models provide more accurate information about the nonlinear intrinsic behaviour of the dataset of variables than linear CCA model in terms of the correlation and root mean square error. Key words: Nonlinear Canonical Correlation Analysis (NLCCA), Canonical Correlation Analysis, Neural Network, Climate Indices, wind speed, wind direction

Computation of canonical correlation and best predictable aspect of future for time series

NASA Technical Reports Server (NTRS)

Pourahmadi, Mohsen; Miamee, A. G.

1989-01-01

The canonical correlation between the (infinite) past and future of a stationary time series is shown to be the limit of the canonical correlation between the (infinite) past and (finite) future, and computation of the latter is reduced to a (generalized) eigenvalue problem involving (finite) matrices. This provides a convenient and essentially, finite-dimensional algorithm for computing canonical correlations and components of a time series. An upper bound is conjectured for the largest canonical correlation.

Is the technical performance of young soccer players influenced by hormonal status, sexual maturity, anthropometric profile, and physical performance?

PubMed

Moreira, Alexandre; Massa, Marcelo; Thiengo, Carlos R; Rodrigues Lopes, Rafael Alan; Lima, Marcelo R; Vaeyens, Roel; Barbosa, Wesley P; Aoki, Marcelo S

2017-12-01

The aim of this study was to examine the influence of hormonal status, anthropometric profile, sexual maturity level, and physical performance on the technical abilities of 40 young male soccer players during small-sided games (SSGs). Anthropometric profiling, saliva sampling, sexual maturity assessment (Tanner scale), and physical performance tests (Yo-Yo and vertical jumps) were conducted two weeks prior to the SSGs. Salivary testosterone was determined by the enzyme-linked immunosorbent assay method. Technical performance was determined by the frequency of actions during SSGs. Principal component analyses identified four technical actions of importance: total number of passes, effectiveness, goal attempts, and total tackles. A multivariate canonical correlation analysis was then employed to verify the prediction of a multiple dependent variables set (composed of four technical actions) from an independent set of variables, composed of testosterone concentration, stage of pubic hair and genitalia development, vertical jumps and Yo-Yo performance. A moderate-to-large relationship between the technical performance set and the independent set was observed. The canonical correlation was 0.75 with a canonical R 2 of 0.45. The highest structure coefficient in the technical performance set was observed for tackles (0.77), while testosterone presented the highest structure coefficient (0.75) for the variables of the independent set. The current data suggest that the selected independent set of variables might be useful in predicting SSG performance in young soccer players. Coaches should be aware that physical development plays a key role in technical performance to avoid decision-making mistakes during the selection of young players.

Canonical Correlation: Terms and Descriptions.

ERIC Educational Resources Information Center

Pugh, Richard C.; Hu, Yuehluen

The use of terms to describe and interpret results from canonical correlation analysis has been inconsistent across research studies. This study assembled the terminology related to the use and interpretation of canonical correlation analysis from research articles, textbooks, and computer manuals. Research articles using canonical correlation…

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

PubMed

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

Science laboratory behavior strategies of students relative to performance in and attitude to laboratory work

NASA Astrophysics Data System (ADS)

Okebukola, Peter Akinsola

The relationship between science laboratory behavior strategies of students and performance in and attitude to laboratory work was investigated in an observational study of 160 laboratory sessions involving 600 class five (eleventh grade) biology students. Zero-order correlations between the behavior strategies and outcome measures reveal a set of low to strong relationships. Transmitting information, listening and nonlesson related behaviors exhibited low correlations with practical skills and the attitude measure. The correlations between manipulating apparatus and observation with practical skills measures were found to be strong. Multiple correlation analysis revealed that the behaviors of students in the laboratories observed accounted for a large percentage of the variance in the scores on manipulative skills and a low percentage on interpretation of data, responsibility, initiative, and work habits. One significant canonical correlation emerged. The loadings on this canonical variate indicate that the practical skills measures, i.e., planning and design, manipulative skills and conduct of experiments, observation and recording of data, and attitude to laboratory work made primary contributions to the canonical relationship. Suggestions as to how students can be encouraged to go beyond cookbook-like laboratories and develop a more favorable attitude to laboratory work are made.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome.

PubMed

Morine, Melissa J; McMonagle, Jolene; Toomey, Sinead; Reynolds, Clare M; Moloney, Aidan P; Gormley, Isobel C; Gaora, Peadar O; Roche, Helen M

2010-10-07

Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways--selenoamino acid metabolism and steroid biosynthesis--illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

PubMed Central

2010-01-01

Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways - selenoamino acid metabolism and steroid biosynthesis - illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease. PMID:20929581

Motivators and barriers to participating in health promotion behaviors in Black men.

PubMed

Calvert, Wilma J; Isaac-Savage, E Paulette

2013-08-01

There is limited research examining the health promotion behaviors (HPBs) of low-income Black men. This study examined the relationship between HPBs, and motivators and barriers to participating in these behaviors in Black men (N = 107), aged 21 to 56. Using descriptive statistics, more than 96% of the participants reported they were motivated because of the desire to be healthy. Canonical correlation analysis and conditional random forest were used to determine the importance of individual motivators and barriers. Canonical correlation analysis yielded one interpretable canonical variate that explained 39.5% of the variance in sets of motivators and barriers, and health promotion lifestyle variables. Men with fewer motivators and more barriers took less responsibility for their health, participated in less physical activity, and reported less spiritual growth. Having too many things to do and not knowing what to do best predicted participation in HPBs.

The relationship between procrastination, learning strategies and statistics anxiety among Iranian college students: a canonical correlation analysis.

PubMed

Vahedi, Shahrum; Farrokhi, Farahman; Gahramani, Farahnaz; Issazadegan, Ali

2012-01-01

Approximately 66-80%of graduate students experience statistics anxiety and some researchers propose that many students identify statistics courses as the most anxiety-inducing courses in their academic curriculums. As such, it is likely that statistics anxiety is, in part, responsible for many students delaying enrollment in these courses for as long as possible. This paper proposes a canonical model by treating academic procrastination (AP), learning strategies (LS) as predictor variables and statistics anxiety (SA) as explained variables. A questionnaire survey was used for data collection and 246-college female student participated in this study. To examine the mutually independent relations between procrastination, learning strategies and statistics anxiety variables, a canonical correlation analysis was computed. Findings show that two canonical functions were statistically significant. The set of variables (metacognitive self-regulation, source management, preparing homework, preparing for test and preparing term papers) helped predict changes of statistics anxiety with respect to fearful behavior, Attitude towards math and class, Performance, but not Anxiety. These findings could be used in educational and psychological interventions in the context of statistics anxiety reduction.

Relationship between organisational commitment and burnout syndrome: a canonical correlation approach.

PubMed

Enginyurt, Ozgur; Cankaya, Soner; Aksay, Kadir; Tunc, Taner; Koc, Bozkurt; Bas, Orhan; Ozer, Erdal

2016-04-01

Objective Burnout syndrome can significantly reduce the performance of health workers. Although many factors have been identified as antecedents of burnout, few studies have investigated the role of organisational commitment in its development. The purpose of the present study was to examine the relationships between subdimensions of burnout syndrome (emotional exhaustion, depersonalisation and personal accomplishment) and subdimensions of organisational commitment (affective commitment, continuance commitment and normative commitment). Methods The present study was a cross-sectional survey of physicians and other healthcare employees working in the Ministry of Health Ordu University Education and Research Hospital. The sample consisted of 486 healthcare workers. Data were collected using the Maslach Burnout Inventory and the Organisation Commitment Scale, and were analysed using the canonical correlation approach. Results The first of three canonical correlation coefficients between pairs of canonical variables (Ui , burnout syndrome and Vi, organisational commitment) was found to be statistically significant. Emotional exhaustion was found to contribute most towards the explanatory capacity of canonical variables estimated from the subdimensions of burnout syndrome, whereas affective commitment provided the largest contribution towards the explanatory capacity of canonical variables estimated from the subdimensions of organisational commitment. Conclusions The results of the present study indicate that affective commitment is the primary determinant of burnout syndrome in healthcare professionals. What is known about the topic? Organisational commitment and burnout syndrome are the most important criteria in predicting health workforce performance. An increasing number of studies in recent years have clearly indicated the field's continued relevance and importance. Conversely, canonical correlation analysis (CCA) is a technique for describing the relationship between two variable sets simultaneously to produce both structural and spatial meaning. What does this paper add? To our knowledge, CCA has not been used to determine the relationships between burnout and organisational commitment of physicians and other healthcare staff. Accordingly, the present study adds information regarding the relationship between burnout and organisational commitment variables determined using CCA. This analysis is used to describe the relationship between two variable sets simultaneously and allows for an easy method of interpretation. What are the implications for practitioners? Burnout syndrome is a major threat to both the health workforce and its organisations. In addition, it affects the quality and effectiveness of health care. Thus, the findings of the present study offer a solid foundation from which actions to decrease burnout levels in healthcare professionals can be implemented by successfully increasing levels of organisational commitment.

The Quality of Life of Hemodialysis Patients Is Affected Not Only by Medical but also Psychosocial Factors: a Canonical Correlation Study.

PubMed

Kim, Kyungmin; Kang, Gun Woo; Woo, Jungmin

2018-04-02

The quality of life (QoL) of patients with end-stage renal disease (ESRD) is very poor, plausibly due to both psychosocial and medical factors. This study aimed to determine the relationship among psychosocial factors, medical factors, and QoL in patients with ESRD undergoing hemodialysis (HD). In total, 55 male and 47 female patients were evaluated (mean age, 57.1 ± 12.0 years). The QoL was evaluated using the Korean version of World Health Organization Quality of Life Scale-Abbreviated Version. The psychosocial factors were evaluated using the Hospital Anxiety and Depression Scale, Multidimensional Scale of Perceived Social Support, Montreal Cognitive Assessment, Pittsburgh Sleep Quality Index, and Zarit Burden Interview. The medical factors were assessed using laboratory examinations. Correlation and canonical correlation analyses were performed to investigate the association patterns. The QoL was significantly correlated with the psychosocial factors, and to a lesser extent with the medical factors. The medical and psychosocial factors were also correlated. The canonical correlation analysis indicated a correlation between QoL and psychosocial factors (1st canonical correlation = 0.696, P < 0.001; 2nd canonical correlation = 0.421, P = 0.191), but not medical factors (1st canonical correlation = 0.478, P = 0.475; 2nd canonical correlation = 0.419, P = 0.751). The medical and psychosocial factors were also correlated (1st canonical correlation = 0.689, P < 0.001; 2nd canonical correlation = 0.603, P = 0.009). Psychosocial factors influence QoL in patients with ESRD, and should thus be carefully considered when caring for these patients in clinical practice. © 2018 The Korean Academy of Medical Sciences.

A Wearable EEG-HEG-HRV Multimodal System With Simultaneous Monitoring of tES for Mental Health Management.

PubMed

Ha, Unsoo; Lee, Yongsu; Kim, Hyunki; Roh, Taehwan; Bae, Joonsung; Kim, Changhyeon; Yoo, Hoi-Jun

2015-12-01

A multimodal mental management system in the shape of the wearable headband and earplugs is proposed to monitor electroencephalography (EEG), hemoencephalography (HEG) and heart rate variability (HRV) for accurate mental health monitoring. It enables simultaneous transcranial electrical stimulation (tES) together with real-time monitoring. The total weight of the proposed system is less than 200 g. The multi-loop low-noise amplifier (MLLNA) achieves over 130 dB CMRR for EEG sensing and the capacitive correlated-double sampling transimpedance amplifier (CCTIA) has low-noise characteristics for HEG and HRV sensing. Measured three-physiology domains such as neural, vascular and autonomic domain signals are combined with canonical correlation analysis (CCA) and temporal kernel canonical correlation analysis (tkCCA) algorithm to find the neural-vascular-autonomic coupling. It supports highly accurate classification with the 19% maximum improvement with multimodal monitoring. For the multi-channel stimulation functionality, after-effects maximization monitoring and sympathetic nerve disorder monitoring, the stimulator is designed as reconfigurable. The 3.37 × 2.25 mm(2) chip has 2-channel EEG sensor front-end, 2-channel NIRS sensor front-end, NIRS current driver to drive dual-wavelength VCSEL and 6-b DAC current source for tES mode. It dissipates 24 mW with 2 mA stimulation current and 5 mA NIRS driver current.

Revisiting Interpretation of Canonical Correlation Analysis: A Tutorial and Demonstration of Canonical Commonality Analysis

ERIC Educational Resources Information Center

Nimon, Kim; Henson, Robin K.; Gates, Michael S.

2010-01-01

In the face of multicollinearity, researchers face challenges interpreting canonical correlation analysis (CCA) results. Although standardized function and structure coefficients provide insight into the canonical variates produced, they fall short when researchers want to fully report canonical effects. This article revisits the interpretation of…

Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging.

PubMed

Bilenko, Natalia Y; Gallant, Jack L

2016-01-01

In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.

Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging

PubMed Central

Bilenko, Natalia Y.; Gallant, Jack L.

2016-01-01

In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model. PMID:27920675

The association between indicators of health and housing in people with Parkinson's disease.

PubMed

Nilsson, Maria H; Ullén, Susann; Ekström, Henrik; Iwarsson, Susanne

2016-07-27

There are knowledge gaps about the life situation for people ageing with Parkinson's disease (PD), with virtually no understanding of home and health dynamics. Therefore, the aim of the present study was to explore the association between aspects of health and objective as well as perceived housing in people with PD. Participants were recruited from three hospitals in the region of Skåne in southern Sweden. The sample for the present study included 231 (62 % men) participants with PD, with a mean age of 75 (min-max, 45-93) years. The data collection procedure included a self-administered postal survey and a subsequent home visit where structured interviews, observations and clinical assessments were administered. To study the association between aspects of health and housing canonical correlation was applied. Twelve variables (6 in the health and 6 in the housing set) were included. This corresponds to about 20 individuals per variable and is considered sufficient to accurately interpret the largest (i.e., first) canonical correlation. The analysis between the health variables and housing variables set yielded two significant pairs of variates with the canonical correlations 0.68 (p < 0.0001) and 0.33 (p = 0.0112), respectively. For the first pair of variates the canonical R(2) was 0.46. The results showed that external control beliefs and behavioral aspects of meaning of home contributed the most to the housing variate, whereas difficulties/dependence in activities of daily living (ADL) and functional limitations contributed the most to the health variate. Although a significant relationship was found for the second canonical correlation, the shared variance between the two variates was considerably lower; R(2) = 0.11. This study suggests that people with PD who have more functional limitations, difficulties in ADL and are more dependent perceive their homes as less meaningful from a behavioral perspective. Moreover, they tend to rely on external influences managing their housing situation. With this kind of knowledge at hand, health care and social services professionals are in a better position to observe and efficiently address problems related to health and housing among people with PD.

Statistics Anxiety and Worry: The Roles of Worry Beliefs, Negative Problem Orientation, and Cognitive Avoidance

ERIC Educational Resources Information Center

Williams, Amanda S.

2015-01-01

Statistics anxiety is a common problem for graduate students. This study explores the multivariate relationship between a set of worry-related variables and six types of statistics anxiety. Canonical correlation analysis indicates a significant relationship between the two sets of variables. Findings suggest that students who are more intolerant…

The Relationship Between Procrastination, Learning Strategies and Statistics Anxiety Among Iranian College Students: A Canonical Correlation Analysis

PubMed Central

Vahedi, Shahrum; Farrokhi, Farahman; Gahramani, Farahnaz; Issazadegan, Ali

2012-01-01

Objective: Approximately 66-80%of graduate students experience statistics anxiety and some researchers propose that many students identify statistics courses as the most anxiety-inducing courses in their academic curriculums. As such, it is likely that statistics anxiety is, in part, responsible for many students delaying enrollment in these courses for as long as possible. This paper proposes a canonical model by treating academic procrastination (AP), learning strategies (LS) as predictor variables and statistics anxiety (SA) as explained variables. Methods: A questionnaire survey was used for data collection and 246-college female student participated in this study. To examine the mutually independent relations between procrastination, learning strategies and statistics anxiety variables, a canonical correlation analysis was computed. Results: Findings show that two canonical functions were statistically significant. The set of variables (metacognitive self-regulation, source management, preparing homework, preparing for test and preparing term papers) helped predict changes of statistics anxiety with respect to fearful behavior, Attitude towards math and class, Performance, but not Anxiety. Conclusion: These findings could be used in educational and psychological interventions in the context of statistics anxiety reduction. PMID:24644468

Influence in Canonical Correlation Analysis.

ERIC Educational Resources Information Center

Romanazzi, Mario

1992-01-01

The perturbation theory of the generalized eigenproblem is used to derive influence functions of each squared canonical correlation coefficient and the corresponding canonical vector pair. Three sample versions of these functions are described, and some properties are noted. Two obvious applications, multiple correlation and correspondence…

Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties

PubMed Central

Adali, Tülay; Levin-Schwartz, Yuri; Calhoun, Vince D.

2015-01-01

Fusion of information from multiple sets of data in order to extract a set of features that are most useful and relevant for the given task is inherent to many problems we deal with today. Since, usually, very little is known about the actual interaction among the datasets, it is highly desirable to minimize the underlying assumptions. This has been the main reason for the growing importance of data-driven methods, and in particular of independent component analysis (ICA) as it provides useful decompositions with a simple generative model and using only the assumption of statistical independence. A recent extension of ICA, independent vector analysis (IVA) generalizes ICA to multiple datasets by exploiting the statistical dependence across the datasets, and hence, as we discuss in this paper, provides an attractive solution to fusion of data from multiple datasets along with ICA. In this paper, we focus on two multivariate solutions for multi-modal data fusion that let multiple modalities fully interact for the estimation of underlying features that jointly report on all modalities. One solution is the Joint ICA model that has found wide application in medical imaging, and the second one is the the Transposed IVA model introduced here as a generalization of an approach based on multi-set canonical correlation analysis. In the discussion, we emphasize the role of diversity in the decompositions achieved by these two models, present their properties and implementation details to enable the user make informed decisions on the selection of a model along with its associated parameters. Discussions are supported by simulation results to help highlight the main issues in the implementation of these methods. PMID:26525830

Role of Frontotemporal Fiber Tract Integrity in Task-Switching Performance of Healthy Controls and Patients with Temporal Lobe Epilepsy

PubMed Central

Kucukboyaci, N. Erkut; Girard, H.M.; Hagler, D.J.; Kuperman, J.; Tecoma, E.S.; Iragui, V.J.; Halgren, E.; McDonald, C.R.

2012-01-01

The objective of this study is to investigate the relationships among frontotemporal fiber tract compromise and task-switching performance in healthy controls and patients with temporal lobe epilepsy (TLE). We performed diffusion tensor imaging (DTI) on 30 controls and 32 patients with TLE (15 left TLE). Fractional anisotropy (FA) was calculated for four fiber tracts [uncinate fasciculus (UncF), arcuate fasciculus (ArcF), dorsal cingulum (CING), and inferior fronto-occipital fasciculus (IFOF)]. Participants completed the Trail Making Test-B (TMT-B) and Verbal Fluency Category Switching (VFCS) test. Multivariate analyses of variances (MANOVAs) were performed to investigate group differences in fiber FA and set-shifting performances. Canonical correlations were used to examine the overall patterns of structural-cognitive relationships and were followed by within-group bivariate correlations. We found a significant canonical correlation between fiber FA and task-switching performance. In controls, TMT-B correlated with left IFOF, whereas VFCS correlated with FA of left ArcF and left UncF. These correlations were not significant in patients with TLE. We report significant correlations between frontotemporal fiber tract integrity and set-shifting performance in healthy controls that appear to be absent or attenuated in patients with TLE. These findings suggest a breakdown of typical structure-function relationships in TLE that may reflect aberrant developmental or degenerative processes. PMID:22014246

Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

PubMed Central

Wang, Shijun; Yao, Jianhua; Liu, Jiamin; Petrick, Nicholas; Van Uitert, Robert L.; Periaswamy, Senthil; Summers, Ronald M.

2009-01-01

Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice—Once supine and once prone—to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27±52.97 to 14.98 mm±11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline. PMID:20095272

Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

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

Wang Shijun; Yao Jianhua; Liu Jiamin

Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice--Once supine and once prone--to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined bymore » the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27{+-}52.97 to 14.98 mm{+-}11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.« less

From grand-canonical density functional theory towards rational compound design

NASA Astrophysics Data System (ADS)

von Lilienfeld, Anatole

2008-03-01

The fundamental challenge of rational compound design, ie the reverse engineering of chemical compounds with predefined specific properties, originates in the high-dimensional combinatorial nature of chemical space. Chemical space is the hyper-space of a given set of molecular observables that is spanned by the grand-canonical variables (particle densities of electrons and nuclei) which define chemical composition. A brief but rigorous description of chemical space within the molecular grand-canonical ensemble multi-component density functional theory framework will be given [1]. Numerical results will be presented for intermolecular energies as a continuous function of alchemical variations within a neutral and isoelectronic 10 proton system, including CH4, NH3, H2O, and HF, interacting with formic acid [2]. Furthermore, engineering the Fermi level through alchemical generation of boron-nitrogen doped mutants of benzene shall be discussed [3].[1] von Lilienfeld and Tuckerman JCP 125 154104 (2006)[2] von Lilienfeld and Tuckerman JCTC 3 1083 (2007)[3] Marcon et al. JCP 127 064305 (2007)

Using canonical correlation analysis to identify environmental attitude groups: considerations for national forest planning in the southwestern U.S.

PubMed

Prera, Alejandro J; Grimsrud, Kristine M; Thacher, Jennifer A; McCollum, Dan W; Berrens, Robert P

2014-10-01

As public land management agencies pursue region-specific resource management plans, with meaningful consideration of public attitudes and values, there is a need to characterize the complex mix of environmental attitudes in a diverse population. The contribution of this investigation is to make use of a unique household, mail/internet survey data set collected in 2007 in the Southwestern United States (Region 3 of the U.S. Forest Service). With over 5,800 survey responses to a set of 25 Public Land Value statements, canonical correlation analysis is able to identify 7 statistically distinct environmental attitudinal groups. We also examine the effect of expected changes in regional demographics on overall environmental attitudes, which may help guide in the development of socially acceptable long-term forest management policies. Results show significant support for conservationist management policies and passive environmental values, as well as a greater role for stakeholder groups in generating consensus for current and future forest management policies.

Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

ERIC Educational Resources Information Center

Wilson, Celia M.

2010-01-01

Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…

Canonical Measure of Correlation (CMC) and Canonical Measure of Distance (CMD) between sets of data. Part 3. Variable selection in classification.

PubMed

Ballabio, Davide; Consonni, Viviana; Mauri, Andrea; Todeschini, Roberto

2010-01-11

In multivariate regression and classification issues variable selection is an important procedure used to select an optimal subset of variables with the aim of producing more parsimonious and eventually more predictive models. Variable selection is often necessary when dealing with methodologies that produce thousands of variables, such as Quantitative Structure-Activity Relationships (QSARs) and highly dimensional analytical procedures. In this paper a novel method for variable selection for classification purposes is introduced. This method exploits the recently proposed Canonical Measure of Correlation between two sets of variables (CMC index). The CMC index is in this case calculated for two specific sets of variables, the former being comprised of the independent variables and the latter of the unfolded class matrix. The CMC values, calculated by considering one variable at a time, can be sorted and a ranking of the variables on the basis of their class discrimination capabilities results. Alternatively, CMC index can be calculated for all the possible combinations of variables and the variable subset with the maximal CMC can be selected, but this procedure is computationally more demanding and classification performance of the selected subset is not always the best one. The effectiveness of the CMC index in selecting variables with discriminative ability was compared with that of other well-known strategies for variable selection, such as the Wilks' Lambda, the VIP index based on the Partial Least Squares-Discriminant Analysis, and the selection provided by classification trees. A variable Forward Selection based on the CMC index was finally used in conjunction of Linear Discriminant Analysis. This approach was tested on several chemical data sets. Obtained results were encouraging.

Perturbative triples correction for local pair natural orbital based explicitly correlated CCSD(F12*) using Laplace transformation techniques.

PubMed

Schmitz, Gunnar; Hättig, Christof

2016-12-21

We present an implementation of pair natural orbital coupled cluster singles and doubles with perturbative triples, PNO-CCSD(T), which avoids the quasi-canonical triples approximation (T0) where couplings due to off-diagonal Fock matrix elements are neglected. A numerical Laplace transformation of the canonical expression for the perturbative (T) triples correction is used to avoid an I/O and storage bottleneck for the triples amplitudes. Results for a test set of reaction energies show that only very few Laplace grid points are needed to obtain converged energy differences and that PNO-CCSD(T) is a more robust approximation than PNO-CCSD(T0) with a reduced mean absolute deviation from canonical CCSD(T) results. We combine the PNO-based (T) triples correction with the explicitly correlated PNO-CCSD(F12*) method and investigate the use of specialized F12-PNOs in the conventional triples correction. We find that no significant additional errors are introduced and that PNO-CCSD(F12*)(T) can be applied in a black box manner.

Integrative analysis of gene expression and copy number alterations using canonical correlation analysis.

PubMed

Soneson, Charlotte; Lilljebjörn, Henrik; Fioretos, Thoas; Fontes, Magnus

2010-04-15

With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia. Using the correlation-maximizing methods, regularized dual CCA and PCA+CCA, we show that without pre-selection of known disease-relevant genes, and without using information about clinical class membership, an exploratory analysis singles out two patient groups, corresponding to well-known leukemia subtypes. Furthermore, the variables showing the highest relevance to the extracted features agree with previous biological knowledge concerning copy number alterations and gene expression changes in these subtypes. Finally, the correlation-maximizing methods are shown to yield results which are more biologically interpretable than those resulting from a covariance-maximizing method, and provide different insight compared to when each variable set is studied separately using PCA. We conclude that regularized dual CCA as well as PCA+CCA are useful methods for exploratory analysis of paired genetic data sets, and can be efficiently implemented also when the number of variables is very large.

Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model

NASA Astrophysics Data System (ADS)

Arumugam, S.; Libera, D.

2017-12-01

Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.

Patient engagement: an investigation at a primary care clinic

PubMed Central

Gill, Preetinder Singh

2013-01-01

Background Engaged employees are an asset to any organization. They are instrumental in ensuring good commercial outcomes through continuous innovation and incremental improvement. A health care facility is similar to a regular work setting in many ways. A health care provider and a patient have roles akin to a team leader and a team member/stakeholder, respectively. Hence it can be argued that the concept of employee engagement can be applied to patients in health care settings in order to improve health outcomes. Methods Patient engagement data were collected using a survey instrument from a primary care clinic in the northern Indian state of Punjab. Canonical correlation equations were formulated to identify combinations which were strongly related to each other. In addition, the cause-effect relationship between patient engagement and patient-perceived health outcomes was described using structural equation modeling. Results Canonical correlation analysis showed that the first set of canonical variables had a fairly strong relationship, ie, a magnitude > 0.80 at the 95% confidence interval, for five dimensions of patient engagement. Structural equation modeling analysis yielded a β ≥ 0.10 and a Student’s t statistic ≥ 2.96 for these five dimensions. The threshold Student’s t statistic was 1.99. Hence it was found the β values were significant at the 95% confidence interval for all census regions. Conclusion A scaled reliable survey instrument was developed to measured patient engagement. Better patient engagement is associated with better patient-perceived health outcomes. This study provides preliminary evidence that patient engagement has a causal relationship with patient-perceived health outcomes. PMID:23515133

The Application of a Technique for Vector Correlation to Problems in Meteorology and Oceanography.

NASA Astrophysics Data System (ADS)

Breaker, L. C.; Gemmill, W. H.; Crosby, D. S.

1994-11-01

In a recent study, Crosby et al. proposed a definition for vector correlation that has not been commonly used in meteorology or oceanography. This definition has both a firm theoretical basis and a rather complete set of desirable statistical properties. In this study, the authors apply the definition to practical problems arising in meteorology and oceanography. In the first of two case studies, vector correlations were calculated between subsurface currents for five locations along the southeastern shore of Lake Erie. Vector correlations for one sample size were calculated for all current meter combinations, first including the seiche frequency and then with the seiche frequency removed. Removal of the seiche frequency, which was easily detected in the current spectra, had only a small effect on the vector correlations. Under reasonable assumptions, the vector correlations were in most cases statistically significant and revealed considerable fine structure in the vector correlation sequences. In some cases, major variations in vector correlation coincided with changes in surface wind. The vector correlations for the various current meter combinations decreased rapidly with increasing spatial separation. For one current meter combination, canonical correlations were also calculated; the first canonical correlation tended to retain the underlying trend, whereas the second canonical correlation retained the peaks in the vector correlations.In the second case study, vector correlations were calculated between marine surface winds derived from the National Meteorological Center's Global Data Assimilation System and observed winds acquired from the network of National Data Buoy Center buoys that are located off the continental United States and in the Gulf of Alaska. Results of this comparison indicated that 1) there was a significant decrease in correlation between the predicted and observed winds with increasing forecast interval out to 72 h, 2) the technique provides a sensitive indicator for detecting bad buoy reports, and 3) there was no obvious seasonal cycle in the monthly vector correlations for the period of observation.

Creativity and Brain-Functioning in Product Development Engineers: A Canonical Correlation Analysis

ERIC Educational Resources Information Center

Travis, Frederick; Lagrosen, Yvonne

2014-01-01

This study used canonical correlation analysis to explore the relation among scores on the Torrance test of figural and verbal creativity and demographic, psychological and physiological measures in Swedish product-development engineers. The first canonical variate included figural and verbal flexibility and originality as dependent measures and…

Improving Magnitude Detection Thresholds Using Multi-Station Multi-Event, and Multi-Phase Methods

DTIC Science & Technology

2008-07-31

applied to different tectonic settings and for what percentage of the seismicity. 111 million correlations were performed on Lg-waves for the events in...x xi Acknowledgments We’d like to thank the operators of the Chinese Digital Seismograph Network, the U.S. Geological Survey, and...applicable correlation methods can be applied to different tectonic settings and for what percentage of the seismicity. 111 million correlations were

Canonical ensemble ground state and correlation entropy of Bose-Einstein condensate

NASA Astrophysics Data System (ADS)

Svidzinsky, Anatoly; Kim, Moochan; Agarwal, Girish; Scully, Marlan O.

2018-01-01

Constraint of a fixed total number of particles yields a correlation between the fluctuation of particles in different states in the canonical ensemble. Here we show that, below the temperature of Bose-Einstein condensation (BEC), the correlation part of the entropy of an ideal Bose gas is cancelled by the ground-state contribution. Thus, in the BEC region, the thermodynamic properties of the gas in the canonical ensemble can be described accurately in a simplified model which excludes the ground state and assumes no correlation between excited levels.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

PubMed

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis

NASA Astrophysics Data System (ADS)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-01

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Multicollinearity in canonical correlation analysis in maize.

PubMed

Alves, B M; Cargnelutti Filho, A; Burin, C

2017-03-30

The objective of this study was to evaluate the effects of multicollinearity under two methods of canonical correlation analysis (with and without elimination of variables) in maize (Zea mays L.) crop. Seventy-six maize genotypes were evaluated in three experiments, conducted in a randomized block design with three replications, during the 2009/2010 crop season. Eleven agronomic variables (number of days from sowing until female flowering, number of days from sowing until male flowering, plant height, ear insertion height, ear placement, number of plants, number of ears, ear index, ear weight, grain yield, and one thousand grain weight), 12 protein-nutritional variables (crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine, and arginine), and 6 energetic-nutritional variables (apparent metabolizable energy, apparent metabolizable energy corrected for nitrogen, ether extract, crude fiber, starch, and amylose) were measured. A phenotypic correlation matrix was first generated among the 29 variables for each of the experiments. A multicollinearity diagnosis was later performed within each group of variables using methodologies such as variance inflation factor and condition number. Canonical correlation analysis was then performed, with and without the elimination of variables, among groups of agronomic and protein-nutritional, and agronomic and energetic-nutritional variables. The canonical correlation analysis in the presence of multicollinearity (without elimination of variables) overestimates the variability of canonical coefficients. The elimination of variables is an efficient method to circumvent multicollinearity in canonical correlation analysis.

Anharmonic vibrational analysis of s-trans and s-cis conformers of acryloyl fluoride using numerical-analytic Van Vleck operator perturbation theory

NASA Astrophysics Data System (ADS)

Krasnoshchekov, Sergey V.; Craig, Norman C.; Koroleva, Lidiya A.; Stepanov, Nikolay F.

2018-01-01

A new gas-phase infrared (IR) spectrum of acryloyl fluoride (ACRF, CH2dbnd CHsbnd CFdbnd O) with a resolution of 0.1 cm- 1 in the range 4000-450 cm- 1 was measured. Theoretical ab initio molecular structures, full quartic potential energy surfaces (PES), and cubic surfaces of dipole moments and polarizability tensor components (electro-optical properties, EOP) of the s-trans and s-cis conformers of the ACRF were calculated by the second-order Møller-Plesset electronic perturbation theory with a correlation consistent Dunning triple-ζ basis set. The numerical-analytic implementation of the second-order operator canonical Van Vleck perturbation theory was employed for predicting anharmonic IR and Raman scattering (RS) spectra of ACRF. To improve the anharmonic predictions, harmonic frequencies were replaced by their counterparts evaluated with the higher-level CCSD(T)/cc-pVTZ model, to form a ;hybrid; PES. The original operator representation of the Hamiltonian is analytically reduced to a quasi-diagonal form, integrated in the harmonic oscillator basis and diagonalized to account for strong resonance couplings. Double canonical transformations of EOP expansions enabled prediction of integral intensities of both fundamental and multi-quanta transitions in IR/RS spectra. Enhanced band shape analysis reinforced the assignments. A thorough interpretation of the new IR experimental spectra and existing matrix-isolation literature data for the mixture of two conformers of ACRF was accomplished, and a number of assignments clarified.

Emotional distress and dysfunctional illness perception are associated with low mental and physical quality of life in Chinese breast cancer patients.

PubMed

Tang, Lili; Fritzsche, Kurt; Leonhart, Rainer; Pang, Ying; Li, Jinjiang; Song, Lili; Fischer, Irmela; Koch, Maike; Wuensch, Alexander; Mewes, Ricarda; Schaefert, Rainer

2017-12-01

To evaluate the relationship between quality of life (QOL) and physical as well as psychological variables in Chinese breast cancer patients. This multicenter cross-sectional study enrolled 254 Chinese breast cancer patients in different stages and treatment phases. They answered standard instruments assessing QOL (EORTC), somatic symptom severity (PHQ-15), depression (PHQ-9), anxiety (GAD-7), health-related anxiety (WI-7), illness perception (BIPQ), and sense of coherence (SOC-9). Canonical correlation was applied to identify the strongest correlates between the physical, emotional and social QOL scales and the physical and psychological variables. In our sample, a low global QOL was significantly associated with the following physical and psychological variables: symptom-related disability (Karnofsky Index) (r = .211, p < .01), somatic symptom severity (r = -.391, p < .001), depression (r = -.488, p < .001), anxiety (r = -.439, p < .001), health-related anxiety (r = -.398, p < .001), dysfunctional illness perception (r = -.411, p < .001), and sense of coherence (r = .371, p < .001). In the canonical correlation analysis, high somatic symptom severity, depression, anxiety, dysfunctional illness perception, and low sense of coherence showed the strongest correlations with low physical, emotional and social functioning. The first three significant canonical correlations between these two sets of variables were .78, .56, and .45. QOL in Chinese breast cancer patients is strongly associated with psychological factors. Our results suggest that Chinese physicians and nurses should incorporate these factors into their care for women with breast cancer to improve patients' QOL.

Algorithmic transformation of multi-loop master integrals to a canonical basis with CANONICA

NASA Astrophysics Data System (ADS)

Meyer, Christoph

2018-01-01

The integration of differential equations of Feynman integrals can be greatly facilitated by using a canonical basis. This paper presents the Mathematica package CANONICA, which implements a recently developed algorithm to automatize the transformation to a canonical basis. This represents the first publicly available implementation suitable for differential equations depending on multiple scales. In addition to the presentation of the package, this paper extends the description of some aspects of the algorithm, including a proof of the uniqueness of canonical forms up to constant transformations.

A multi-criteria evaluation system for marine litter pollution based on statistical analyses of OSPAR beach litter monitoring time series.

PubMed

Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael

2013-12-01

During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Weak Concordance between Fish and Macroinvertebrates in Mediterranean Streams

PubMed Central

Larsen, Stefano; Mancini, Laura; Pace, Giorgio; Scalici, Massimiliano; Tancioni, Lorenzo

2012-01-01

Although anthropogenic degradation of riverine systems stimulated a multi-taxon bioassessment of their ecological integrity in EU countries, specific responses of different taxonomic groups to human pressure are poorly investigated in Mediterranean rivers. Here, we assess if richness and composition of macroinvertebrate and fish assemblages show concordant variation along a gradient of anthropogenic pressure in 31 reaches across 13 wadeable streams in central Italy. Fish and invertebrate taxonomic richness was not correlated across sites. However, Mantel test showed that the two groups were significantly, albeit weakly, correlated even after statistically controlling for the effect of environmental variables and site proximity. Variance partitioning with partial Canonical Correspondence Analysis showed that the assemblages of the two groups were influenced by different set of environmental drivers: invertebrates were influenced by water organic content, channel and substratum features, while fish were related to stream temperature (mirroring elevation) and local land-use. Variance partitioning revealed the importance of biotic interactions between the two groups as a possible mechanisms determining concordance. Although significant, the congruence between the groups was weak, indicating that they should not be used as surrogate of each other for environmental assessments in these Mediterranean catchments. Indeed, both richness and patterns in nestedness (i.e. where depauperate locations host only a subset of taxa found in richer locations) appeared influenced by different environmental drivers suggesting that the observed concordance did not result from a co-loss of taxa along similar environmental gradients. As fish and macroinvertebrates appeared sensitive to different environmental factors, we argue that monitoring programmes should consider a multi-assemblage assessment, as also required by the Water Framework Directive. PMID:23251432

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

Interpreting medium ring canonical conformers by a triangular plane tessellation of the macrocycle

NASA Astrophysics Data System (ADS)

Khalili, Pegah; Barnett, Christopher B.; Naidoo, Kevin J.

2013-05-01

Cyclic conformational coordinates are essential for the distinction of molecular ring conformers as the use of Cremer-Pople coordinates have illustrated for five- and six-membered rings. Here, by tessellating medium rings into triangular planes and using the relative angles made between triangular planes we are able to assign macrocyclic pucker conformations into canonical pucker conformers such as chairs, boats, etc. We show that the definition is straightforward compared with other methods popularly used for small rings and that it is computationally simple to implement for complex macrocyclic rings. These cyclic conformational coordinates directly couple to the motion of individual nodes of a ring. Therefore, they are useful for correlating the physical properties of macrocycles with their ring pucker and measuring the dynamic ring conformational behavior. We illustrate the triangular tessellation, assignment, and pucker analysis on 7- and 8-membered rings. Sets of canonical states are given for cycloheptane and cyclooctane that have been previously experimentally analysed.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Using canonical correlation analysis to identify environmental attitude groups: Considerations for national forest planning in the southwestern U.S

Treesearch

Alejandro J. Prera; Kristine M. Grimsrud; Jennifer A. Thacher; Dan W. McCollum; Robert P. Berrens

2014-01-01

As public land management agencies pursue region-specific resource management plans, with meaningful consideration of public attitudes and values, there is a need to characterize the complex mix of environmental attitudes in a diverse population. The contribution of this investigation is to make use of a unique household, mail/ internet survey data set collected in...

Electronic Structure at Oxide Interfaces

DTIC Science & Technology

2014-06-01

of materials with desired correlated electron properties such as ferromagnetism with a high Curie temperature, high transition temperature...approximation and therefore the canonical Mott picture is unable to account for the insulating behavior of these materials . We resolve this apparent...the two materials . LaTiO3 shows insulating behavior with a small excitation gap set by Ti d-d transitions and a wide energy separation between Ti d

The Problematics of Postmodernism: The Double-Voiced Honors Canon.

ERIC Educational Resources Information Center

McCracken, Tim

Honors education is not immune from the current controversy concerning the role of the literary canon. Indeed, the problem seems especially crucial for honors programs, for their curriculums are often multi-disciplinary in their approaches to culture and history. The solution may lie in what Linda Hutcheon calls the "poetics of the…

Assessment of the APCC Coupled MME Suite in Predicting the Distinctive Climate Impacts of Two Flavors of ENSO during Boreal Winter

NASA Technical Reports Server (NTRS)

Jeong, Hye-In; Lee, Doo Young; Karumuri, Ashok; Ahn, Joong-Bae; Lee, June-Yi; Luo, Jing-Jia; Schemm, Jae-Kyung E.; Hendon, Harry H.; Braganza, Karl; Ham, Yoo-Geun

2012-01-01

Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal forecast system in predicting two main types of El Nino-Southern Oscillation (ENSO), namely canonical (or cold tongue) and Modoki ENSO, and their regional climate impacts is assessed for boreal winter. The APCC MME is constructed by simple composite of ensemble forecasts from five independent coupled ocean-atmosphere climate models. Based on a hindcast set targeting boreal winter prediction for the period 19822004, we show that the MME can predict and discern the important differences in the patterns of tropical Pacific sea surface temperature anomaly between the canonical and Modoki ENSO one and four month ahead. Importantly, the four month lead MME beats the persistent forecast. The MME reasonably predicts the distinct impacts of the canonical ENSO, including the strong winter monsoon rainfall over East Asia, the below normal rainfall and above normal temperature over Australia, the anomalously wet conditions across the south and cold conditions over the whole area of USA, and the anomalously dry conditions over South America. However, there are some limitations in capturing its regional impacts, especially, over Australasia and tropical South America at a lead time of one and four months. Nonetheless, forecast skills for rainfall and temperature over East Asia and North America during ENSO Modoki are comparable to or slightly higher than those during canonical ENSO events.

Treating Subvalence Correlation Effects in Domain Based Pair Natural Orbital Coupled Cluster Calculations: An Out-of-the-Box Approach.

PubMed

Bistoni, Giovanni; Riplinger, Christoph; Minenkov, Yury; Cavallo, Luigi; Auer, Alexander A; Neese, Frank

2017-07-11

The validity of the main approximations used in canonical and domain based pair natural orbital coupled cluster methods (CCSD(T) and DLPNO-CCSD(T), respectively) in standard chemical applications is discussed. In particular, we investigate the dependence of the results on the number of electrons included in the correlation treatment in frozen-core (FC) calculations and on the main threshold governing the accuracy of DLPNO all-electron (AE) calculations. Initially, scalar relativistic orbital energies for the ground state of the atoms from Li to Rn in the periodic table are calculated. An energy criterion is used for determining the orbitals that can be excluded from the correlation treatment in FC coupled cluster calculations without significant loss of accuracy. The heterolytic dissociation energy (HDE) of a series of metal compounds (LiF, NaF, AlF 3 , CaF 2 , CuF, GaF 3 , YF 3 , AgF, InF 3 , HfF 4 , and AuF) is calculated at the canonical CCSD(T) level, and the dependence of the results on the number of correlated electrons is investigated. Although for many of the studied reactions subvalence correlation effects contribute significantly to the HDE, the use of an energy criterion permits a conservative definition of the size of the core, allowing FC calculations to be performed in a black-box fashion while retaining chemical accuracy. A comparison of the CCSD and the DLPNO-CCSD methods in describing the core-core, core-valence, and valence-valence components of the correlation energy is given. It is found that more conservative thresholds must be used for electron pairs containing at least one core electron in order to achieve high accuracy in AE DLPNO-CCSD calculations relative to FC calculations. With the new settings, the DLPNO-CCSD method reproduces canonical CCSD results in both AE and FC calculations with the same accuracy.

The Pathway Coexpression Network: Revealing pathway relationships

PubMed Central

Tanzi, Rudolph E.

2018-01-01

A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/. PMID:29554099

A MUSIC-based method for SSVEP signal processing.

PubMed

Chen, Kun; Liu, Quan; Ai, Qingsong; Zhou, Zude; Xie, Sheng Quan; Meng, Wei

2016-03-01

The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100%. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.

Robust nonlinear canonical correlation analysis: application to seasonal climate forecasting

NASA Astrophysics Data System (ADS)

Cannon, A. J.; Hsieh, W. W.

2008-02-01

Robust variants of nonlinear canonical correlation analysis (NLCCA) are introduced to improve performance on datasets with low signal-to-noise ratios, for example those encountered when making seasonal climate forecasts. The neural network model architecture of standard NLCCA is kept intact, but the cost functions used to set the model parameters are replaced with more robust variants. The Pearson product-moment correlation in the double-barreled network is replaced by the biweight midcorrelation, and the mean squared error (mse) in the inverse mapping networks can be replaced by the mean absolute error (mae). Robust variants of NLCCA are demonstrated on a synthetic dataset and are used to forecast sea surface temperatures in the tropical Pacific Ocean based on the sea level pressure field. Results suggest that adoption of the biweight midcorrelation can lead to improved performance, especially when a strong, common event exists in both predictor/predictand datasets. Replacing the mse by the mae leads to improved performance on the synthetic dataset, but not on the climate dataset except at the longest lead time, which suggests that the appropriate cost function for the inverse mapping networks is more problem dependent.

Predicting phonetic transcription agreement: Insights from research in infant vocalizations

PubMed Central

RAMSDELL, HEATHER L.; OLLER, D. KIMBROUGH; ETHINGTON, CORINNA A.

2010-01-01

The purpose of this study is to provide new perspectives on correlates of phonetic transcription agreement. Our research focuses on phonetic transcription and coding of infant vocalizations. The findings are presumed to be broadly applicable to other difficult cases of transcription, such as found in severe disorders of speech, which similarly result in low reliability for a variety of reasons. We evaluated the predictiveness of two factors not previously documented in the literature as influencing transcription agreement: canonicity and coder confidence. Transcribers coded samples of infant vocalizations, judging both canonicity and confidence. Correlation results showed that canonicity and confidence were strongly related to agreement levels, and regression results showed that canonicity and confidence both contributed significantly to explanation of variance. Specifically, the results suggest that canonicity plays a major role in transcription agreement when utterances involve supraglottal articulation, with coder confidence offering additional power in predicting transcription agreement. PMID:17882695

Polybrominated diphenyl ethers (PBDEs) in soil and outdoor dust from a multi-functional area of Shanghai: levels, compositional profiles and interrelationships.

PubMed

Wu, Ming-Hong; Pei, Jing-Cheng; Zheng, Ming; Tang, Liang; Bao, Yang-Yang; Xu, Ben-Tuo; Sun, Rui; Sun, Yan-Feng; Xu, Gang; Lei, Jian-Qiu

2015-01-01

In this study, 14 polybrominated diphenyl ethers (PBDEs) congeners were investigated in soil and outdoor dust taken from Jiading District, Shanghai City. The concentrations of Σ13PBDEs (BDE-17, BDE-28, BDE-47, BDE-66, BDE-71, BDE-85, BDE-99, BDE-100, BDE-138, BDE-153, BDE-154, BDE-183 and BDE-190) and BDE-209 ranged from 0.37 to 32.9ngg(-1) and 4.31 to 141.8ngg(-1) dry weight (dw) in soil. Concentrations in outdoor dust ranged from 1.03 to 112.5ngg(-1) and 6.71 to 342.1ngg(-1) (dw) for Σ13PBDEs and BDE-209. BDE-209 was the predominant congener both in soil and outdoor dust, but the BDE-209 contribution was much lower in dust compared with that in soil. A significant correlation between PBDEs congeners and specific land use type was observed, and principal component analysis (PCA) revealed that the major source of PBDE in samples was associated with prevalent use of technical Deca-BDE, which also suggested the contributions from Penta-BDE and Octa-BDE mixtures. Canonical correlation analysis suggested the two sets of PBDEs data (soil and outdoor dust) were uncorrelated, and Spearman correlation coefficient matrix implied that the degradation pathways of PBDEs were different between soil and outdoor dust. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Canonical Correlation Analysis of AIDS Restriction Genes and Metabolic Pathways Identifies Purine Metabolism as a Key Cooperator.

PubMed

Ye, Hanhui; Yuan, Jinjin; Wang, Zhengwu; Huang, Aiqiong; Liu, Xiaolong; Han, Xiao; Chen, Yahong

2016-01-01

Human immunodeficiency virus causes a severe disease in humans, referred to as immune deficiency syndrome. Studies on the interaction between host genetic factors and the virus have revealed dozens of genes that impact diverse processes in the AIDS disease. To resolve more genetic factors related to AIDS, a canonical correlation analysis was used to determine the correlation between AIDS restriction and metabolic pathway gene expression. The results show that HIV-1 postentry cellular viral cofactors from AIDS restriction genes are coexpressed in human transcriptome microarray datasets. Further, the purine metabolism pathway comprises novel host factors that are coexpressed with AIDS restriction genes. Using a canonical correlation analysis for expression is a reliable approach to exploring the mechanism underlying AIDS.

The structural, connectomic and network covariance of the human brain.

PubMed

Irimia, Andrei; Van Horn, John D

2013-02-01

Though it is widely appreciated that complex structural, functional and morphological relationships exist between distinct areas of the human cerebral cortex, the extent to which such relationships coincide remains insufficiently appreciated. Here we determine the extent to which correlations between brain regions are modulated by either structural, connectomic or network-theoretic properties using a structural neuroimaging data set of magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) volumes acquired from N=110 healthy human adults. To identify the linear relationships between all available pairs of regions, we use canonical correlation analysis to test whether a statistically significant correlation exists between each pair of cortical parcels as quantified via structural, connectomic or network-theoretic measures. In addition to this, we investigate (1) how each group of canonical variables (whether structural, connectomic or network-theoretic) contributes to the overall correlation and, additionally, (2) whether each individual variable makes a significant contribution to the test of the omnibus null hypothesis according to which no correlation between regions exists across subjects. We find that, although region-to-region correlations are extensively modulated by structural and connectomic measures, there are appreciable differences in how these two groups of measures drive inter-regional correlation patterns. Additionally, our results indicate that the network-theoretic properties of the cortex are strong modulators of region-to-region covariance. Our findings are useful for understanding the structural and connectomic relationship between various parts of the brain, and can inform theoretical and computational models of cortical information processing. Published by Elsevier Inc.

Restoring canonical partition functions from imaginary chemical potential

NASA Astrophysics Data System (ADS)

Bornyakov, V. G.; Boyda, D.; Goy, V.; Molochkov, A.; Nakamura, A.; Nikolaev, A.; Zakharov, V. I.

2018-03-01

Using GPGPU techniques and multi-precision calculation we developed the code to study QCD phase transition line in the canonical approach. The canonical approach is a powerful tool to investigate sign problem in Lattice QCD. The central part of the canonical approach is the fugacity expansion of the grand canonical partition functions. Canonical partition functions Zn(T) are coefficients of this expansion. Using various methods we study properties of Zn(T). At the last step we perform cubic spline for temperature dependence of Zn(T) at fixed n and compute baryon number susceptibility χB/T2 as function of temperature. After that we compute numerically ∂χ/∂T and restore crossover line in QCD phase diagram. We use improved Wilson fermions and Iwasaki gauge action on the 163 × 4 lattice with mπ/mρ = 0.8 as a sandbox to check the canonical approach. In this framework we obtain coefficient in parametrization of crossover line Tc(µ2B) = Tc(C-ĸµ2B/T2c) with ĸ = -0.0453 ± 0.0099.

Canonical Correlational Models of Students' Perceptions of Assessment Tasks, Motivational Orientations, and Learning Strategies

ERIC Educational Resources Information Center

Alkharusi, Hussain

2013-01-01

The present study aims at deriving correlational models of students' perceptions of assessment tasks, motivational orientations, and learning strategies using canonical analyses. Data were collected from 198 Omani tenth grade students. Results showed that high degrees of authenticity and transparency in assessment were associated with positive…

Integral formulae of the canonical correlation functions for the one dimensional transverse Ising model

NASA Astrophysics Data System (ADS)

Inoue, Makoto

2017-12-01

Some new formulae of the canonical correlation functions for the one dimensional quantum transverse Ising model are found by the ST-transformation method using a Morita's sum rule and its extensions for the two dimensional classical Ising model. As a consequence we obtain a time-independent term of the dynamical correlation functions. Differences of quantum version and classical version of these formulae are also discussed.

Pair natural orbital and canonical coupled cluster reaction enthalpies involving light to heavy alkali and alkaline earth metals: the importance of sub-valence correlation.

PubMed

Minenkov, Yury; Bistoni, Giovanni; Riplinger, Christoph; Auer, Alexander A; Neese, Frank; Cavallo, Luigi

2017-04-05

In this work, we tested canonical and domain based pair natural orbital coupled cluster methods (CCSD(T) and DLPNO-CCSD(T), respectively) for a set of 32 ligand exchange and association/dissociation reaction enthalpies involving ionic complexes of Li, Be, Na, Mg, Ca, Sr, Ba and Pb(ii). Two strategies were investigated: in the former, only valence electrons were included in the correlation treatment, giving rise to the computationally very efficient FC (frozen core) approach; in the latter, all non-ECP electrons were included in the correlation treatment, giving rise to the AE (all electron) approach. Apart from reactions involving Li and Be, the FC approach resulted in non-homogeneous performance. The FC approach leads to very small errors (<2 kcal mol -1 ) for some reactions of Na, Mg, Ca, Sr, Ba and Pb, while for a few reactions of Ca and Ba deviations up to 40 kcal mol -1 have been obtained. Large errors are both due to artificial mixing of the core (sub-valence) orbitals of metals and the valence orbitals of oxygen and halogens in the molecular orbitals treated as core, and due to neglecting core-core and core-valence correlation effects. These large errors are reduced to a few kcal mol -1 if the AE approach is used or the sub-valence orbitals of metals are included in the correlation treatment. On the technical side, the CCSD(T) and DLPNO-CCSD(T) results differ by a fraction of kcal mol -1 , indicating the latter method as the perfect choice when the CPU efficiency is essential. For completely black-box applications, as requested in catalysis or thermochemical calculations, we recommend the DLPNO-CCSD(T) method with all electrons that are not covered by effective core potentials included in the correlation treatment and correlation-consistent polarized core valence basis sets of cc-pwCVQZ(-PP) quality.

Effects of biomotor structures on performance of competitive gymnastics elements in elementary school male sixth-graders.

PubMed

Delas, Suncica; Zagorac, Nebojsa; Katić, Ratko

2008-06-01

In order to identify the biomotor systems that determine performance of competitive gymnastics elements in elementary school male sixth-graders, factor structures of morphological characteristics and basic motor abilities were determined first, followed by relations of the morphological-motor system factors obtained with a set of criterion variables evaluating specific motor skills in competitive gymnastics in 110 male children aged 12 years +/- 3 months. Factor analysis of 17 morphological measures produced three morphological factors: factor of mesoectoendomorphy (general morphological factor) and factor of pronounced endomorphy, i.e. excessive adipose tissue, along with low skeleton longitudinality. Factor analysis of 16 motor variables yielded four motor factors: factor of general motoricity; factor integrating leg flexibility and arm explosiveness; factor juxtaposing body flexibility and repetitive leg strength; and factor predominantly defining leg movement frequency. Three significant canonical correlations, i.e. linear combinations, explained the association between the set of six latent variables of the morphological and basic motor system, and five variables assessing the knowledge in competitive gymnastics. The first canonical linear combination was based on the favorable and predominant impact of the general motor factor (a system integrating leg explosiveness, whole body coordination, relative arm and trunk strength, and arm movement frequency), along with unfavorable effect of morphological factors on the gymnastics elements performance, squat vault and handstand in particular The relation of the second pair of canonical factors pointed to the effects of leg flexibility and arm explosiveness on the cartwheel and backward pullover mount performance, whereas the relation of the third pair of canonical factors showed a favorable impact of the general morphological factor and leg movement frequency regulator on the forward shoulderkip from increase, cartwheel and handstand performance.

Effects of biomotor structures on performance of competitive gymnastics elements in elementary school female sixth-graders.

PubMed

Delas, Suncica; Babin, Josip; Katić, Ratko

2007-12-01

In order to identify biomotor systems that determine performance of competitive gymnastics elements in elementary school female sixth-graders, factor structures of morphological characteristics and basic motor abilities were determined first, followed by relations of the morphological-motor system factors obtained with a set of criterion variables evaluating specific motor skills in competitive gymnastics in 126 female children aged 12 years +/- 3 months. Factor analysis of 17 morphological measures yielded three morphological factors: factor of mesoendomorphy and/or adipose body voluminosity; factor of longitudinal body dimensionality; and factor of transverse arm dimensionality. Factor analysis of 16 motor variables produced four motor factors: general motoricity factor (motor system); general speed factor; factor of explosive strength of throwing type (arm explosiveness); and factor of arm and leg flexibility. Three significant canonical correlations, i.e. linear combinations, explained the association between the set of seven latent variables of the morphological and basic motor system, and five variables evaluating the knowledge in competitive gymnastics. The first canonical linear combination was based on a favorable and predominant impact of the general motor factor (a system integrating whole body coordination, leg explosiveness, relative arm strength, arm movement frequency and body flexibility) on performance of gymnastics elements, cartwheel, handstand and backward pullover mount in particular, and to a lesser extent front scale and double leg pirouette for 180 degrees. The relation of the second pair of canonical factors additionally explained the role of transverse dimensionality of arm skeleton, arm flexibility and explosiveness in performing cartwheel and squat vault, whereas the relation of the third pair of canonical factors explained the unfavorable impact of adipose voluminosity on the performance of squat vault and backward pullover mount.

Association Study between Lead and Zinc Accumulation at Different Physiological Systems of Cattle by Canonical Correlation and Canonical Correspondence Analyses

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

Karmakar, Partha; Das, Pradip Kumar; Mondal, Seema Sarkar

2010-10-26

Pb pollution from automobile exhausts around highways is a persistent problem in India. Pb intoxication in mammalian body is a complex phenomenon which is influence by agonistic and antagonistic interactions of several other heavy metals and micronutrients. An attempt has been made to study the association between Pb and Zn accumulation in different physiological systems of cattles (n = 200) by application of both canonical correlation and canonical correspondence analyses. Pb was estimated from plasma, liver, bone, muscle, kidney, blood and milk where as Zn was measured from all these systems except bone, blood and milk. Both statistical techniques demonstratedmore » that there was a strong association among blood-Pb, liver-Zn, kidney-Zn and muscle-Zn. From observations, it can be assumed that Zn accumulation in cattles' muscle, liver and kidney directs Pb mobilization from those organs which in turn increases Pb pool in blood. It indicates antagonistic activity of Zn to the accumulation of Pb. Although there were some contradictions between the observations obtained from the two different statistical methods, the overall pattern of Pb accumulation in various organs as influenced by Zn were same. It is mainly due to the fact that canonical correlation is actually a special type of canonical correspondence analyses where linear relationship is followed between two groups of variables instead of Gaussian relationship.« less

Association Study between Lead and Zinc Accumulation at Different Physiological Systems of Cattle by Canonical Correlation and Canonical Correspondence Analyses

NASA Astrophysics Data System (ADS)

Karmakar, Partha; Das, Pradip Kumar; Mondal, Seema Sarkar; Karmakar, Sougata; Mazumdar, Debasis

2010-10-01

Pb pollution from automobile exhausts around highways is a persistent problem in India. Pb intoxication in mammalian body is a complex phenomenon which is influence by agonistic and antagonistic interactions of several other heavy metals and micronutrients. An attempt has been made to study the association between Pb and Zn accumulation in different physiological systems of cattles (n = 200) by application of both canonical correlation and canonical correspondence analyses. Pb was estimated from plasma, liver, bone, muscle, kidney, blood and milk where as Zn was measured from all these systems except bone, blood and milk. Both statistical techniques demonstrated that there was a strong association among blood-Pb, liver-Zn, kidney-Zn and muscle-Zn. From observations, it can be assumed that Zn accumulation in cattles' muscle, liver and kidney directs Pb mobilization from those organs which in turn increases Pb pool in blood. It indicates antagonistic activity of Zn to the accumulation of Pb. Although there were some contradictions between the observations obtained from the two different statistical methods, the overall pattern of Pb accumulation in various organs as influenced by Zn were same. It is mainly due to the fact that canonical correlation is actually a special type of canonical correspondence analyses where linear relationship is followed between two groups of variables instead of Gaussian relationship.

A new randomized Kaczmarz based kernel canonical correlation analysis algorithm with applications to information retrieval.

PubMed

Cai, Jia; Tang, Yi

2018-02-01

Canonical correlation analysis (CCA) is a powerful statistical tool for detecting the linear relationship between two sets of multivariate variables. Kernel generalization of it, namely, kernel CCA is proposed to describe nonlinear relationship between two variables. Although kernel CCA can achieve dimensionality reduction results for high-dimensional data feature selection problem, it also yields the so called over-fitting phenomenon. In this paper, we consider a new kernel CCA algorithm via randomized Kaczmarz method. The main contributions of the paper are: (1) A new kernel CCA algorithm is developed, (2) theoretical convergence of the proposed algorithm is addressed by means of scaled condition number, (3) a lower bound which addresses the minimum number of iterations is presented. We test on both synthetic dataset and several real-world datasets in cross-language document retrieval and content-based image retrieval to demonstrate the effectiveness of the proposed algorithm. Numerical results imply the performance and efficiency of the new algorithm, which is competitive with several state-of-the-art kernel CCA methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inverse eigenproblem for R-symmetric matrices and their approximation

NASA Astrophysics Data System (ADS)

Yuan, Yongxin

2009-11-01

Let be a nontrivial involution, i.e., R=R-1[not equal to]±In. We say that is R-symmetric if RGR=G. The set of all -symmetric matrices is denoted by . In this paper, we first give the solvability condition for the following inverse eigenproblem (IEP): given a set of vectors in and a set of complex numbers , find a matrix such that and are, respectively, the eigenvalues and eigenvectors of A. We then consider the following approximation problem: Given an n×n matrix , find such that , where is the solution set of IEP and ||[dot operator]|| is the Frobenius norm. We provide an explicit formula for the best approximation solution by means of the canonical correlation decomposition.

Hydrogen adsorption capacities of multi-walled boron nitride nanotubes and nanotube arrays: a grand canonical Monte Carlo study.

PubMed

Ahadi, Zohreh; Shadman, Muhammad; Yeganegi, Saeed; Asgari, Farid

2012-07-01

Hydrogen adsorption in multi-walled boron nitride nanotubes and their arrays was studied using grand canonical Monte Carlo simulation. The results show that hydrogen storage increases with tube diameter and the distance between the tubes in multi-walled boron nitride nanotube arrays. Also, triple-walled boron nitride nanotubes present the lowest level of hydrogen physisorption, double-walled boron nitride nanotubes adsorb hydrogen better when the diameter of the inner tube diameter is sufficiently large, and single-walled boron nitride nanotubes adsorb hydrogen well when the tube diameter is small enough. Boron nitride nanotube arrays adsorb hydrogen, but the percentage of adsorbed hydrogen (by weight) in boron nitride nanotube arrays is rather similar to that found in multi-walled boron nitride nanotubes. Also, when the Langmuir and Langmuir-Freundlich equations were fitted to the simulated data, it was found that multi-layer adsorptivity occurs more prominently as the number of walls and the tube diameter increase. However, in single-walled boron nitride nanotubes with a small diameter, the dominant mechanism is monolayer adsorptivity.

Relations between basic and specific motor abilities and player quality of young basketball players.

PubMed

Marić, Kristijan; Katić, Ratko; Jelicić, Mario

2013-05-01

Subjects from 5 first league clubs from Herzegovina were tested with the purpose of determining the relations of basic and specific motor abilities, as well as the effect of specific abilities on player efficiency in young basketball players (cadets). A battery of 12 tests assessing basic motor abilities and 5 specific tests assessing basketball efficiency were used on a sample of 83 basketball players. Two significant canonical correlations, i.e. linear combinations explained the relation between the set of twelve variables of basic motor space and five variables of situational motor abilities. Underlying the first canonical linear combination is the positive effect of the general motor factor, predominantly defined by jumping explosive power, movement speed of the arms, static strength of the arms and coordination, on specific basketball abilities: movement efficiency, the power of the overarm throw, shooting and passing precision, and the skill of handling the ball. The impact of basic motor abilities of precision and balance on specific abilities of passing and shooting precision and ball handling is underlying the second linear combination. The results of regression correlation analysis between the variable set of specific motor abilities and game efficiency have shown that the ability of ball handling has the largest impact on player quality in basketball cadets, followed by shooting precision and passing precision, and the power of the overarm throw.

Data analytics using canonical correlation analysis and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles

2017-07-01

A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.

ClaRNA: a classifier of contacts in RNA 3D structures based on a comparative analysis of various classification schemes

PubMed Central

Waleń, Tomasz; Chojnowski, Grzegorz; Gierski, Przemysław; Bujnicki, Janusz M.

2014-01-01

The understanding of folding and function of RNA molecules depends on the identification and classification of interactions between ribonucleotide residues. We developed a new method named ClaRNA for computational classification of contacts in RNA 3D structures. Unique features of the program are the ability to identify imperfect contacts and to process coarse-grained models. Each doublet of spatially close ribonucleotide residues in a query structure is compared to clusters of reference doublets obtained by analysis of a large number of experimentally determined RNA structures, and assigned a score that describes its similarity to one or more known types of contacts, including pairing, stacking, base–phosphate and base–ribose interactions. The accuracy of ClaRNA is 0.997 for canonical base pairs, 0.983 for non-canonical pairs and 0.961 for stacking interactions. The generalized squared correlation coefficient (GC2) for ClaRNA is 0.969 for canonical base pairs, 0.638 for non-canonical pairs and 0.824 for stacking interactions. The classifier can be easily extended to include new types of spatial relationships between pairs or larger assemblies of nucleotide residues. ClaRNA is freely available via a web server that includes an extensive set of tools for processing and visualizing structural information about RNA molecules. PMID:25159614

A Study on the Oral Disfluencies Developmental Traits of EFL Students--A Report Based on Canonical Correlation Analysis

ERIC Educational Resources Information Center

Gao, Ying; Du, Wanyi

2013-01-01

This paper traces 9 non-English major EFL students and collects their oral productions in 4 successive oral exams in 2 years. The canonical correlation analysis approach of SPSS is adopted to study the disfluencies developmental traits under the influence of language acquisition development. We find that as language acquisition develops, the total…

Uncertainty relations, zero point energy and the linear canonical group

NASA Technical Reports Server (NTRS)

Sudarshan, E. C. G.

1993-01-01

The close relationship between the zero point energy, the uncertainty relations, coherent states, squeezed states, and correlated states for one mode is investigated. This group-theoretic perspective enables the parametrization and identification of their multimode generalization. In particular the generalized Schroedinger-Robertson uncertainty relations are analyzed. An elementary method of determining the canonical structure of the generalized correlated states is presented.

Integrating Multiple Criteria in Selection Procedures for Improving Student Quality and Reducing Cost Per Graduate. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Jones, Gerald L.; Westen, Risdon J.

The multivariate approach of canonical correlation was used to assess selection procedures of the Air Force Academy. It was felt that improved student selection methods might reduce the number of dropouts while maintaining or improving the quality of graduates. The method of canonical correlation was designed to maximize prediction of academic…

A review of multivariate methods in brain imaging data fusion

NASA Astrophysics Data System (ADS)

Sui, Jing; Adali, Tülay; Li, Yi-Ou; Yang, Honghui; Calhoun, Vince D.

2010-03-01

On joint analysis of multi-task brain imaging data sets, a variety of multivariate methods have shown their strengths and been applied to achieve different purposes based on their respective assumptions. In this paper, we provide a comprehensive review on optimization assumptions of six data fusion models, including 1) four blind methods: joint independent component analysis (jICA), multimodal canonical correlation analysis (mCCA), CCA on blind source separation (sCCA) and partial least squares (PLS); 2) two semi-blind methods: parallel ICA and coefficient-constrained ICA (CC-ICA). We also propose a novel model for joint blind source separation (BSS) of two datasets using a combination of sCCA and jICA, i.e., 'CCA+ICA', which, compared with other joint BSS methods, can achieve higher decomposition accuracy as well as the correct automatic source link. Applications of the proposed model to real multitask fMRI data are compared to joint ICA and mCCA; CCA+ICA further shows its advantages in capturing both shared and distinct information, differentiating groups, and interpreting duration of illness in schizophrenia patients, hence promising applicability to a wide variety of medical imaging problems.

Thermodynamics of pairing in mesoscopic systems

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

Sumaryada, Tony; Volya, Alexander

Using numerical and analytical methods implemented for different models, we conduct a systematic study of the thermodynamic properties of pairing correlations in mesoscopic nuclear systems. Various quantities are calculated and analyzed using the exact solution of pairing. An in-depth comparison of canonical, grand canonical, and microcanonical ensembles is conducted. The nature of the pairing phase transition in a small system is of a particular interest. We discuss the onset of discontinuity in the thermodynamic variables, fluctuations, and evolution of zeros of the canonical and grand canonical partition functions in the complex plane. The behavior of the invariant correlational entropy ismore » also studied in the transitional region of interest. The change in the character of the phase transition due to the presence of a magnetic field is discussed along with studies of superconducting thermodynamics.« less

Expanded all-optical programmable logic array based on multi-input/output canonical logic units.

PubMed

Lei, Lei; Dong, Jianji; Zou, Bingrong; Wu, Zhao; Dong, Wenchan; Zhang, Xinliang

2014-04-21

We present an expanded all-optical programmable logic array (O-PLA) using multi-input and multi-output canonical logic units (CLUs) generation. Based on four-wave mixing (FWM) in highly nonlinear fiber (HNLF), two-input and three-input CLUs are simultaneously achieved in five different channels with an operation speed of 40 Gb/s. Clear temporal waveforms and wide open eye diagrams are successfully observed. The effectiveness of the scheme is validated by extinction ratio and optical signal-to-noise ratio measurements. The computing capacity, defined as the total amount of logic functions achieved by the O-PLA, is discussed in detail. For a three-input O-PLA, the computing capacity of the expanded CLUs-PLA is more than two times as large as that of the standard CLUs-PLA, and this multiple will increase to more than three and a half as the idlers are individually independent.

Zombie states for description of structure and dynamics of multi-electron systems

NASA Astrophysics Data System (ADS)

Shalashilin, Dmitrii V.

2018-05-01

Canonical Coherent States (CSs) of Harmonic Oscillator have been extensively used as a basis in a number of computational methods of quantum dynamics. However, generalising such techniques for fermionic systems is difficult because Fermionic Coherent States (FCSs) require complicated algebra of Grassmann numbers not well suited for numerical calculations. This paper introduces a coherent antisymmetrised superposition of "dead" and "alive" electronic states called here Zombie State (ZS), which can be used in a manner of FCSs but without Grassmann algebra. Instead, for Zombie States, a very simple sign-changing rule is used in the definition of creation and annihilation operators. Then, calculation of electronic structure Hamiltonian matrix elements between two ZSs becomes very simple and a straightforward technique for time propagation of fermionic wave functions can be developed. By analogy with the existing methods based on Canonical Coherent States of Harmonic Oscillator, fermionic wave functions can be propagated using a set of randomly selected Zombie States as a basis. As a proof of principles, the proposed Coupled Zombie States approach is tested on a simple example showing that the technique is exact.

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

Efficient construction of exchange and correlation potentials by inverting the Kohn-Sham equations.

PubMed

Kananenka, Alexei A; Kohut, Sviataslau V; Gaiduk, Alex P; Ryabinkin, Ilya G; Staroverov, Viktor N

2013-08-21

Given a set of canonical Kohn-Sham orbitals, orbital energies, and an external potential for a many-electron system, one can invert the Kohn-Sham equations in a single step to obtain the corresponding exchange-correlation potential, vXC(r). For orbitals and orbital energies that are solutions of the Kohn-Sham equations with a multiplicative vXC(r) this procedure recovers vXC(r) (in the basis set limit), but for eigenfunctions of a non-multiplicative one-electron operator it produces an orbital-averaged potential. In particular, substitution of Hartree-Fock orbitals and eigenvalues into the Kohn-Sham inversion formula is a fast way to compute the Slater potential. In the same way, we efficiently construct orbital-averaged exchange and correlation potentials for hybrid and kinetic-energy-density-dependent functionals. We also show how the Kohn-Sham inversion approach can be used to compute functional derivatives of explicit density functionals and to approximate functional derivatives of orbital-dependent functionals.

Investigation of priorities in water quality management based on correlations and variations.

PubMed

Boyacıoğlu, Hülya; Gündogdu, Vildan; Boyacıoğlu, Hayal

2013-04-15

The development of water quality assessment strategies investigating spatial and temporal changes caused by natural and anthropogenic phenomena is an important tool in management practices. This paper used cluster analysis, water quality index method, sensitivity analysis and canonical correlation analysis to investigate priorities in pollution control activities. Data sets representing 22 surface water quality parameters were subject to analysis. Results revealed that organic pollution was serious threat for overall water quality in the region. Besides, oil and grease, lead and mercury were the critical variables violating the standard. In contrast to inorganic variables, organic and physical-inorganic chemical parameters were influenced by variations in physical conditions (discharge, temperature). This study showed that information produced based on the variations and correlations in water quality data sets can be helpful to investigate priorities in water management activities. Moreover statistical techniques and index methods are useful tools in data - information transformation process. Copyright © 2013 Elsevier Ltd. All rights reserved.

Emotional intelligence and the relationship to resident performance: a multi-institutional study.

PubMed

Talarico, Joseph F; Varon, Albert J; Banks, Shawn E; Berger, Jeffrey S; Pivalizza, Evan G; Medina-Rivera, Glorimar; Rimal, Jyotsna; Davidson, Melissa; Dai, Feng; Qin, Li; Ball, Ryan D; Loudd, Cheryl; Schoenberg, Catherine; Wetmore, Amy L; Metro, David G

2013-05-01

To test the hypothesis that emotional intelligence, as measured by a BarOn Emotional Quotient Inventory (EQ-i), the 125-item version personal inventory (EQ-i:125), correlates with resident performance. Survey (personal inventory) instrument. Five U.S. academic anesthesiology residency programs. Postgraduate year (PGY) 2, 3, and 4 residents enrolled in university-based anesthesiology residency programs. Residents confidentially completed the BarOn EQ-i:125 personal inventory. The deidentified resident evaluations were sent to the principal investigator of a separate data collection study for data analysis. Data collected from the inventory were correlated with daily evaluations of the residents by residency program faculty. Results of the individual BarOn EQ-i:125 and daily faculty evaluations of the residents were compiled and analyzed. Univariate correlation analysis and multivariate canonical analysis showed that some aspects of the BarOn EQ-i:125 were significantly correlated with, and likely to be predictors of, resident performance. Emotional intelligence, as measured by the BarOn EQ-i personal inventory, has considerable promise as an independent indicator of performance as an anesthesiology resident. Copyright © 2013 Elsevier Inc. All rights reserved.

Multi-Object Filtering for Space Situational Awareness

DTIC Science & Technology

2014-06-01

labelling such as the labelled multi- Bernoulli filter [27]. 3.2 Filter derivation: key modelling assumptions Ouf of the general filtering framework [14...radiation pressure in the canon- ball model has been taken into account, leading to the following acceleration: arad = −Fp · C A m E c AEarth |r− rSun| esatSun

A CCA+ICA based model for multi-task brain imaging data fusion and its application to schizophrenia.

PubMed

Sui, Jing; Adali, Tülay; Pearlson, Godfrey; Yang, Honghui; Sponheim, Scott R; White, Tonya; Calhoun, Vince D

2010-05-15

Collection of multiple-task brain imaging data from the same subject has now become common practice in medical imaging studies. In this paper, we propose a simple yet effective model, "CCA+ICA", as a powerful tool for multi-task data fusion. This joint blind source separation (BSS) model takes advantage of two multivariate methods: canonical correlation analysis and independent component analysis, to achieve both high estimation accuracy and to provide the correct connection between two datasets in which sources can have either common or distinct between-dataset correlation. In both simulated and real fMRI applications, we compare the proposed scheme with other joint BSS models and examine the different modeling assumptions. The contrast images of two tasks: sensorimotor (SM) and Sternberg working memory (SB), derived from a general linear model (GLM), were chosen to contribute real multi-task fMRI data, both of which were collected from 50 schizophrenia patients and 50 healthy controls. When examining the relationship with duration of illness, CCA+ICA revealed a significant negative correlation with temporal lobe activation. Furthermore, CCA+ICA located sensorimotor cortex as the group-discriminative regions for both tasks and identified the superior temporal gyrus in SM and prefrontal cortex in SB as task-specific group-discriminative brain networks. In summary, we compared the new approach to some competitive methods with different assumptions, and found consistent results regarding each of their hypotheses on connecting the two tasks. Such an approach fills a gap in existing multivariate methods for identifying biomarkers from brain imaging data.

The canonical semantic network supports residual language function in chronic post-stroke aphasia

PubMed Central

Griffis, Joseph C.; Nenert, Rodolphe; Allendorfer, Jane B.; Vannest, Jennifer; Holland, Scott; Dietz, Aimee; Szaflarski, Jerzy P.

2016-01-01

Current theories of language recovery after stroke are limited by a reliance on small studies. Here, we aimed to test predictions of current theory and resolve inconsistencies regarding right hemispheric contributions to long-term recovery. We first defined the canonical semantic network in 43 healthy controls. Then, in a group of 43 patients with chronic post-stroke aphasia, we tested whether activity in this network predicted performance on measures of semantic comprehension, naming, and fluency while controlling for lesion volume effects. Canonical network activation accounted for 22–33% of the variance in language test scores. Whole-brain analyses corroborated these findings, and revealed a core set of regions showing positive relationships to all language measures. We next evaluated the relationship between activation magnitudes in left and right hemispheric portions of the network, and characterized how right hemispheric activation related to the extent of left hemispheric damage. Activation magnitudes in each hemispheric network were strongly correlated, but four right frontal regions showed heightened activity in patients with large lesions. Activity in two of these regions (inferior frontal gyrus pars opercularis and supplementary motor area) was associated with better language abilities in patients with larger lesions, but poorer language abilities in patients with smaller lesions. Our results indicate that bilateral language networks support language processing after stroke, and that right hemispheric activations related to extensive left hemisphere damage occur outside of the canonical semantic network and differentially relate to behavior depending on the extent of left hemispheric damage. PMID:27981674

A Technology Integration Education (TIE) Model for Millennial Preservice Teachers: Exploring the Canonical Correlation Relationships among Attitudes, Subjective Norms, Perceived Behavioral Controls, Motivation, and Technological, Pedagogical, and Content Knowledge (TPACK) Competencies

ERIC Educational Resources Information Center

Holland, Denise D.; Piper, Randy T.

2016-01-01

Intellectual goods can follow the same pattern as physical goods with the product life cycle of birth, growth, maturity, and decline. For the intellectual good of technological, pedagogical, and content knowledge (TPACK), its birth began with Shulman (1986, 1987). Canonical correlation analysis (CCA) was used to test the relationships among five…

Sub-seasonal-to-seasonal Reservoir Inflow Forecast using Bayesian Hierarchical Hidden Markov Model

NASA Astrophysics Data System (ADS)

Mukhopadhyay, S.; Arumugam, S.

2017-12-01

Sub-seasonal-to-seasonal (S2S) (15-90 days) streamflow forecasting is an emerging area of research that provides seamless information for reservoir operation from weather time scales to seasonal time scales. From an operational perspective, sub-seasonal inflow forecasts are highly valuable as these enable water managers to decide short-term releases (15-30 days), while holding water for seasonal needs (e.g., irrigation and municipal supply) and to meet end-of-the-season target storage at a desired level. We propose a Bayesian Hierarchical Hidden Markov Model (BHHMM) to develop S2S inflow forecasts for the Tennessee Valley Area (TVA) reservoir system. Here, the hidden states are predicted by relevant indices that influence the inflows at S2S time scale. The hidden Markov model also captures the both spatial and temporal hierarchy in predictors that operate at S2S time scale with model parameters being estimated as a posterior distribution using a Bayesian framework. We present our work in two steps, namely single site model and multi-site model. For proof of concept, we consider inflows to Douglas Dam, Tennessee, in the single site model. For multisite model we consider reservoirs in the upper Tennessee valley. Streamflow forecasts are issued and updated continuously every day at S2S time scale. We considered precipitation forecasts obtained from NOAA Climate Forecast System (CFSv2) GCM as predictors for developing S2S streamflow forecasts along with relevant indices for predicting hidden states. Spatial dependence of the inflow series of reservoirs are also preserved in the multi-site model. To circumvent the non-normality of the data, we consider the HMM in a Generalized Linear Model setting. Skill of the proposed approach is tested using split sample validation against a traditional multi-site canonical correlation model developed using the same set of predictors. From the posterior distribution of the inflow forecasts, we also highlight different system behavior under varied global and local scale climatic influences from the developed BHMM.

Determination of priority among air pollution factors in preventing COPD in residents of Shanghai City proper

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

Xuguang, Tao; Chuan-jie, Hong; Shun-zhang, Yu

The purpose of our study is to determine the priority among ambient sulphur dioxide (SO{sub 2}), inhalable particulates (IP), and indoor use of coal for cooking or heating to prevent COPD in residents of Shanghai city proper. We describe spatial and temporal distribution of the concentration of ambient SO{sub 2}, IP, and the proportion of families who use coal (1980-1985) by the trend surface simulating method and other statistics. Stratified by two sets of extreme levels of ambient SO{sub 2}, IP, and the proportion of coal-using families, we selected eight groups with different combinations of exposure levels. We analyzed themore » relationship between air pollution factors and their health effects at levels of mortality (1978-1987, 232,459 person years), prevalence (1987, 12,037 persons), lung function and local immunologic function (1987, 514 women) with logistic and stepwise regression, and ridit analysis. After controlling for possible confounders, e.g., tobacco smoking and occupational exposure, we found that indoor use of coal is a more important risk factor than ambient SO{sub 2} and IP. We then used canonical correlation analysis to evaluate the overall exposure-effect relationship between one set of air pollution and confounding factors and the other set of health effect indices. High correlation is found between the two. The indoor use of coal is more important for the overall health effects than the ambient SO{sub 2} and IP, to change from coal to gas could reduce the environmental exposure canonical variable more readily, with an effect equivalent to a reduction of 0.1839 mg/m{sup 3} for ambient SO{sub 2}, or 0.2806 mg/m{sup 3} for ambient IP in concentration.« less

A novel structure-aware sparse learning algorithm for brain imaging genetics.

PubMed

Du, Lei; Jingwen, Yan; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-01-01

Brain imaging genetics is an emergent research field where the association between genetic variations such as single nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is evaluated. Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. Most existing SCCA algorithms are designed using the soft threshold strategy, which assumes that the features in the data are independent from each other. This independence assumption usually does not hold in imaging genetic data, and thus inevitably limits the capability of yielding optimal solutions. We propose a novel structure-aware SCCA (denoted as S2CCA) algorithm to not only eliminate the independence assumption for the input data, but also incorporate group-like structure in the model. Empirical comparison with a widely used SCCA implementation, on both simulated and real imaging genetic data, demonstrated that S2CCA could yield improved prediction performance and biologically meaningful findings.

Use of Canonical Analysis in Cropley's "A Five-Year Longitudinal Study of the Validity of Creativity Tests"

ERIC Educational Resources Information Center

Jordan, Lawrence A.

1975-01-01

Calls attention to several errors in a recent application of canonical correlation analysis. The reanalysis contradicts Cropley's conclusion that "creativity tests can be said to possess reasonable and encouraging long-range predictive validity." (Author/SDH)

Non-canonical autophagy: an exception or an underestimated form of autophagy?

PubMed

Scarlatti, Francesca; Maffei, Roberta; Beau, Isabelle; Ghidoni, Riccardo; Codogno, Patrice

2008-11-01

Macroautophagy (hereafter called autophagy) is a dynamic and evolutionarily conserved process used to sequester and degrade cytoplasm and entire organelles in a sequestering vesicle with a double membrane, known as the autophagosome, which ultimately fuses with a lysosome to degrade its autophagic cargo. Recently, we have unraveled two distinct forms of autophagy in cancer cells, which we term canonical and non-canonical autophagy. In contrast to classical or canonical autophagy, non-canonical autophagy is a process that does not require the entire set of autophagy-related (Atg) proteins in particular Beclin 1, to form the autophagosome. Non-canonical autophagy is therefore not blocked by the knockdown of Beclin 1 or of its binding partner hVps34. Moreover overexpression of Bcl-2, which is known to block canonical starvation-induced autophagy by binding to Beclin 1, is unable to reverse the non-canonical autophagy triggered by the polyphenol resveratrol in the breast cancer MCF-7 cell line. In MCF-7 cells, at least, non-canonical autophagy is involved in the caspase-independent cell death induced by resveratrol.

Two-particle correlation function and dihadron correlation approach

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

Vechernin, V. V., E-mail: v.vechernin@spbu.ru; Ivanov, K. O.; Neverov, D. I.

It is shown that, in the case of asymmetric nuclear interactions, the application of the traditional dihadron correlation approach to determining a two-particle correlation function C may lead to a form distorted in relation to the canonical pair correlation function {sub C}{sup 2}. This result was obtained both by means of exact analytic calculations of correlation functions within a simple string model for proton–nucleus and deuteron–nucleus collisions and by means of Monte Carlo simulations based on employing the HIJING event generator. It is also shown that the method based on studying multiplicity correlations in two narrow observation windows separated inmore » rapidity makes it possible to determine correctly the canonical pair correlation function C{sub 2} for all cases, including the case where the rapidity distribution of product particles is not uniform.« less

Kernel PLS-SVC for Linear and Nonlinear Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Trejo, Leonard J.; Matthews, Bryan

2003-01-01

A new methodology for discrimination is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by support vector machines for classification. Close connection of orthonormalized PLS and Fisher's approach to linear discrimination or equivalently with canonical correlation analysis is described. This gives preference to use orthonormalized PLS over principal component analysis. Good behavior of the proposed method is demonstrated on 13 different benchmark data sets and on the real world problem of the classification finger movement periods versus non-movement periods based on electroencephalogram.

A Comparison of Three Multivariate Models for Estimating Test Battery Reliability.

ERIC Educational Resources Information Center

Wood, Terry M.; Safrit, Margaret J.

1987-01-01

A comparison of three multivariate models (canonical reliability model, maximum generalizability model, canonical correlation model) for estimating test battery reliability indicated that the maximum generalizability model showed the least degree of bias, smallest errors in estimation, and the greatest relative efficiency across all experimental…

Spectroscopic accuracy directly from quantum chemistry: application to ground and excited states of beryllium dimer.

PubMed

Sharma, Sandeep; Yanai, Takeshi; Booth, George H; Umrigar, C J; Chan, Garnet Kin-Lic

2014-03-14

We combine explicit correlation via the canonical transcorrelation approach with the density matrix renormalization group and initiator full configuration interaction quantum Monte Carlo methods to compute a near-exact beryllium dimer curve, without the use of composite methods. In particular, our direct density matrix renormalization group calculations produce a well-depth of D(e) = 931.2 cm(-1) which agrees very well with recent experimentally derived estimates D(e) = 929.7±2 cm(-1) [J. M. Merritt, V. E. Bondybey, and M. C. Heaven, Science 324, 1548 (2009)] and D(e) = 934.6 cm(-1) [K. Patkowski, V. Špirko, and K. Szalewicz, Science 326, 1382 (2009)], as well the best composite theoretical estimates, D(e) = 938±15 cm(-1) [K. Patkowski, R. Podeszwa, and K. Szalewicz, J. Phys. Chem. A 111, 12822 (2007)] and D(e) = 935.1±10 cm(-1) [J. Koput, Phys. Chem. Chem. Phys. 13, 20311 (2011)]. Our results suggest possible inaccuracies in the functional form of the potential used at shorter bond lengths to fit the experimental data [J. M. Merritt, V. E. Bondybey, and M. C. Heaven, Science 324, 1548 (2009)]. With the density matrix renormalization group we also compute near-exact vertical excitation energies at the equilibrium geometry. These provide non-trivial benchmarks for quantum chemical methods for excited states, and illustrate the surprisingly large error that remains for 1 ¹Σ(g)⁻ state with approximate multi-reference configuration interaction and equation-of-motion coupled cluster methods. Overall, we demonstrate that explicitly correlated density matrix renormalization group and initiator full configuration interaction quantum Monte Carlo methods allow us to fully converge to the basis set and correlation limit of the non-relativistic Schrödinger equation in small molecules.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

PubMed

Deligianni, Fani; Centeno, Maria; Carmichael, David W; Clayden, Jonathan D

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

PubMed Central

Deligianni, Fani; Centeno, Maria; Carmichael, David W.; Clayden, Jonathan D.

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity. PMID:25221467

A New Ensemble Canonical Correlation Prediction Scheme for Seasonal Precipitation

NASA Technical Reports Server (NTRS)

Kim, Kyu-Myong; Lau, William K. M.; Li, Guilong; Shen, Samuel S. P.; Lau, William K. M. (Technical Monitor)

2001-01-01

Department of Mathematical Sciences, University of Alberta, Edmonton, Canada This paper describes the fundamental theory of the ensemble canonical correlation (ECC) algorithm for the seasonal climate forecasting. The algorithm is a statistical regression sch eme based on maximal correlation between the predictor and predictand. The prediction error is estimated by a spectral method using the basis of empirical orthogonal functions. The ECC algorithm treats the predictors and predictands as continuous fields and is an improvement from the traditional canonical correlation prediction. The improvements include the use of area-factor, estimation of prediction error, and the optimal ensemble of multiple forecasts. The ECC is applied to the seasonal forecasting over various parts of the world. The example presented here is for the North America precipitation. The predictor is the sea surface temperature (SST) from different ocean basins. The Climate Prediction Center's reconstructed SST (1951-1999) is used as the predictor's historical data. The optimally interpolated global monthly precipitation is used as the predictand?s historical data. Our forecast experiments show that the ECC algorithm renders very high skill and the optimal ensemble is very important to the high value.

Correlations of occupation numbers in the canonical ensemble and application to a Bose-Einstein condensate in a one-dimensional harmonic trap

NASA Astrophysics Data System (ADS)

Giraud, Olivier; Grabsch, Aurélien; Texier, Christophe

2018-05-01

We study statistical properties of N noninteracting identical bosons or fermions in the canonical ensemble. We derive several general representations for the p -point correlation function of occupation numbers n1⋯np ¯. We demonstrate that it can be expressed as a ratio of two p ×p determinants involving the (canonical) mean occupations n1¯, ..., np¯, which can themselves be conveniently expressed in terms of the k -body partition functions (with k ≤N ). We draw some connection with the theory of symmetric functions and obtain an expression of the correlation function in terms of Schur functions. Our findings are illustrated by revisiting the problem of Bose-Einstein condensation in a one-dimensional harmonic trap, for which we get analytical results. We get the moments of the occupation numbers and the correlation between ground-state and excited-state occupancies. In the temperature regime dominated by quantum correlations, the distribution of the ground-state occupancy is shown to be a truncated Gumbel law. The Gumbel law, describing extreme-value statistics, is obtained when the temperature is much smaller than the Bose-Einstein temperature.

Hamiltonian formalism for f (T ) gravity

NASA Astrophysics Data System (ADS)

Ferraro, Rafael; Guzmán, María José

2018-05-01

We present the Hamiltonian formalism for f (T ) gravity, and prove that the theory has n/(n -3 ) 2 +1 degrees of freedom (d.o.f.) in n dimensions. We start from a scalar-tensor action for the theory, which represents a scalar field minimally coupled with the torsion scalar T that defines the teleparallel equivalent of general relativity (TEGR) Lagrangian. T is written as a quadratic form of the coefficients of anholonomy of the vierbein. We obtain the primary constraints through the analysis of the structure of the eigenvalues of the multi-index matrix involved in the definition of the canonical momenta. The auxiliary scalar field generates one extra primary constraint when compared with the TEGR case. The secondary constraints are the super-Hamiltonian and supermomenta constraints, that are preserved from the Arnowitt-Deser-Misner formulation of GR. There is a set of n/(n -1 ) 2 primary constraints that represent the local Lorentz transformations of the theory, which can be combined to form a set of n/(n -1 ) 2 -1 first-class constraints, while one of them becomes second class. This result is irrespective of the dimension, due to the structure of the matrix of the brackets between the constraints. The first-class canonical Hamiltonian is modified due to this local Lorentz violation, and the only one local Lorentz transformation that becomes second-class pairs up with the second-class constraint π ≈0 to remove one d.o.f. from the n2+1 pairs of canonical variables. The remaining n/(n -1 ) 2 +2 n -1 primary constraints remove the same number of d.o.f., leaving the theory with n/(n -3 ) 2 +1 d.o.f. This means that f (T ) gravity has only one extra d.o.f., which could be interpreted as a scalar d.o.f.

Building a Multi-Discipline Digital Library Through Extending the Dienst Protocol

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.

1997-01-01

The purpose of this project is to establish multi-discipline capability for a unified, canonical digital library service for scientific and technical information (STI). This is accomplished by extending the Dienst Protocol to be aware of subject classification of a servers holdings. We propose a hierarchical, general, and extendible subject classification that can encapsulate existing classification systems.

Pervasive, Coordinated Protein-Level Changes Driven by Transcript Isoform Switching during Meiosis.

PubMed

Cheng, Ze; Otto, George Maxwell; Powers, Emily Nicole; Keskin, Abdurrahman; Mertins, Philipp; Carr, Steven Alfred; Jovanovic, Marko; Brar, Gloria Ann

2018-02-22

To better understand the gene regulatory mechanisms that program developmental processes, we carried out simultaneous genome-wide measurements of mRNA, translation, and protein through meiotic differentiation in budding yeast. Surprisingly, we observed that the levels of several hundred mRNAs are anti-correlated with their corresponding protein products. We show that rather than arising from canonical forms of gene regulatory control, the regulation of at least 380 such cases, or over 8% of all measured genes, involves temporally regulated switching between production of a canonical, translatable transcript and a 5' extended isoform that is not efficiently translated into protein. By this pervasive mechanism for the modulation of protein levels through a natural developmental program, a single transcription factor can coordinately activate and repress protein synthesis for distinct sets of genes. The distinction is not based on whether or not an mRNA is induced but rather on the type of transcript produced. Copyright © 2018 Elsevier Inc. All rights reserved.

Multivariate analysis of meat production traits in Murciano-Granadina goat kids.

PubMed

Zurita-Herrera, P; Delgado, J V; Argüello, A; Camacho, M E

2011-07-01

Growth, carcass quality, and meat quality data from Murciano-Granadina kids (n=61) raised under three different systems were collected. Canonical discriminatory analysis and cluster analysis of the entire meat production process and its stages were performed using the rearing systems as grouping criteria. All comparisons resulted in significant differences and indicated the existence of three products with different quality characteristics as a result of the three rearing systems. Differences among groups were greater when comparing carcass and meat qualities as compared with growth differences. The paired analyses of canonical correlations among groups of variables integrated in growth, carcass and meat quality, resulted in all being statistically significant, pointing out the canonical correlation coefficient between carcass quality and meat quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessment of multireference approaches to explicitly correlated full configuration interaction quantum Monte Carlo

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

Kersten, J. A. F., E-mail: jennifer.kersten@cantab.net; Alavi, Ali, E-mail: a.alavi@fkf.mpg.de; Max Planck Institute for Solid State Research, Heisenbergstraße 1, 70569 Stuttgart

2016-08-07

The Full Configuration Interaction Quantum Monte Carlo (FCIQMC) method has proved able to provide near-exact solutions to the electronic Schrödinger equation within a finite orbital basis set, without relying on an expansion about a reference state. However, a drawback to the approach is that being based on an expansion of Slater determinants, the FCIQMC method suffers from a basis set incompleteness error that decays very slowly with the size of the employed single particle basis. The FCIQMC results obtained in a small basis set can be improved significantly with explicitly correlated techniques. Here, we present a study that assesses andmore » compares two contrasting “universal” explicitly correlated approaches that fit into the FCIQMC framework: the [2]{sub R12} method of Kong and Valeev [J. Chem. Phys. 135, 214105 (2011)] and the explicitly correlated canonical transcorrelation approach of Yanai and Shiozaki [J. Chem. Phys. 136, 084107 (2012)]. The former is an a posteriori internally contracted perturbative approach, while the latter transforms the Hamiltonian prior to the FCIQMC simulation. These comparisons are made across the 55 molecules of the G1 standard set. We found that both methods consistently reduce the basis set incompleteness, for accurate atomization energies in small basis sets, reducing the error from 28 mE{sub h} to 3-4 mE{sub h}. While many of the conclusions hold in general for any combination of multireference approaches with these methodologies, we also consider FCIQMC-specific advantages of each approach.« less

A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data.

PubMed

Climer, Sharlee; Yang, Wei; de las Fuentes, Lisa; Dávila-Román, Victor G; Gu, C Charles

2014-11-01

Complex diseases are often associated with sets of multiple interacting genetic factors and possibly with unique sets of the genetic factors in different groups of individuals (genetic heterogeneity). We introduce a novel concept of custom correlation coefficient (CCC) between single nucleotide polymorphisms (SNPs) that address genetic heterogeneity by measuring subset correlations autonomously. It is used to develop a 3-step process to identify candidate multi-SNP patterns: (1) pairwise (SNP-SNP) correlations are computed using CCC; (2) clusters of so-correlated SNPs identified; and (3) frequencies of these clusters in disease cases and controls compared to identify disease-associated multi-SNP patterns. This method identified 42 candidate multi-SNP associations with hypertensive heart disease (HHD), among which one cluster of 22 SNPs (six genes) included 13 in SLC8A1 (aka NCX1, an essential component of cardiac excitation-contraction coupling) and another of 32 SNPs had 29 from a different segment of SLC8A1. While allele frequencies show little difference between cases and controls, the cluster of 22 associated alleles were found in 20% of controls but no cases and the other in 3% of controls but 20% of cases. These suggest that both protective and risk effects on HHD could be exerted by combinations of variants in different regions of SLC8A1, modified by variants from other genes. The results demonstrate that this new correlation metric identifies disease-associated multi-SNP patterns overlooked by commonly used correlation measures. Furthermore, computation time using CCC is a small fraction of that required by other methods, thereby enabling the analyses of large GWAS datasets. © 2014 WILEY PERIODICALS, INC.

A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data

PubMed Central

Climer, Sharlee; Yang, Wei; de las Fuentes, Lisa; Dávila-Román, Victor G.; Gu, C. Charles

2014-01-01

Complex diseases are often associated with sets of multiple interacting genetic factors and possibly with unique sets of the genetic factors in different groups of individuals (genetic heterogeneity). We introduce a novel concept of Custom Correlation Coefficient (CCC) between single nucleotide polymorphisms (SNPs) that address genetic heterogeneity by measuring subset correlations autonomously. It is used to develop a 3-step process to identify candidate multi-SNP patterns: (1) pairwise (SNP-SNP) correlations are computed using CCC; (2) clusters of so-correlated SNPs identified; and (3) frequencies of these clusters in disease cases and controls compared to identify disease-associated multi-SNP patterns. This method identified 42 candidate multi-SNP associations with hypertensive heart disease (HHD), among which one cluster of 22 SNPs (6 genes) included 13 in SLC8A1 (aka NCX1, an essential component of cardiac excitation-contraction coupling) and another of 32 SNPs had 29 from a different segment of SLC8A1. While allele frequencies show little difference between cases and controls, the cluster of 22 associated alleles were found in 20% of controls but no cases and the other in 3% of controls but 20% of cases. These suggest that both protective and risk effects on HHD could be exerted by combinations of variants in different regions of SLC8A1, modified by variants from other genes. The results demonstrate that this new correlation metric identifies disease-associated multi-SNP patterns overlooked by commonly used correlation measures. Furthermore, computation time using CCC is a small fraction of that required by other methods, thereby enabling the analyses of large GWAS datasets. PMID:25168954

Technological innovation and its effect on public health in the United States

PubMed Central

Gill, Preetinder Singh

2013-01-01

Background Good public health ensures an efficient work force. Organizations can ensure a prominent position on the global stage by staying on the leading edge of technological development. Public health and technological innovation are vital elements of prosperous economies. It is important to understand how these elements affect each other. This research study explored and described the relationship between these two critical elements/constructs. Methods Indicators representing technological innovation and public health were identified. Indicator data from 2000 to 2009 were collected from various US federal government sources, for the four US Census regions. The four US Census regions were then compared in terms of these indicators. Canonical correlation equations were formulated to identify combinations of the indicators that are strongly related to each other. Additionally, the cause–effect relationship between public health and technological innovation was described using the structural equation modeling technique. Results The four US Census regions ranked differently in terms of both type of indicators in a statistically significant manner. The canonical correlation analysis showed that the first set of canonical variables had a fairly strong relationship, with a magnitude > 0.65 at the 95% confidence interval, for all census regions. Structural equation modeling analysis provided β < −0.69 and Student’s t statistic > 12.98, for all census regions. The threshold Student’s t statistic was 1.98. Hence, it was found that the β values were significant at the 95% confidence interval, for all census regions. Discussion The results of the study showed that better technological innovation indicator scores were associated with better public health indicator scores. Furthermore, the study provided preliminary evidence that technological innovation shares causal relation with public health. PMID:23378771

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging.

PubMed

Rosa, Maria J; Mehta, Mitul A; Pich, Emilio M; Risterucci, Celine; Zelaya, Fernando; Reinders, Antje A T S; Williams, Steve C R; Dazzan, Paola; Doyle, Orla M; Marquand, Andre F

2015-01-01

An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labeling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow.

Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information.

PubMed

Safo, Sandra E; Li, Shuzhao; Long, Qi

2018-03-01

Integrative analysis of high dimensional omics data is becoming increasingly popular. At the same time, incorporating known functional relationships among variables in analysis of omics data has been shown to help elucidate underlying mechanisms for complex diseases. In this article, our goal is to assess association between transcriptomic and metabolomic data from a Predictive Health Institute (PHI) study that includes healthy adults at a high risk of developing cardiovascular diseases. Adopting a strategy that is both data-driven and knowledge-based, we develop statistical methods for sparse canonical correlation analysis (CCA) with incorporation of known biological information. Our proposed methods use prior network structural information among genes and among metabolites to guide selection of relevant genes and metabolites in sparse CCA, providing insight on the molecular underpinning of cardiovascular disease. Our simulations demonstrate that the structured sparse CCA methods outperform several existing sparse CCA methods in selecting relevant genes and metabolites when structural information is informative and are robust to mis-specified structural information. Our analysis of the PHI study reveals that a number of gene and metabolic pathways including some known to be associated with cardiovascular diseases are enriched in the set of genes and metabolites selected by our proposed approach. © 2017, The International Biometric Society.

Coupled-cluster and explicitly correlated perturbation-theory calculations of the uracil anion.

PubMed

Bachorz, Rafał A; Klopper, Wim; Gutowski, Maciej

2007-02-28

A valence-type anion of the canonical tautomer of uracil has been characterized using explicitly correlated second-order Moller-Plesset perturbation theory (RI-MP2-R12) in conjunction with conventional coupled-cluster theory with single, double, and perturbative triple excitations. At this level of electron-correlation treatment and after inclusion of a zero-point vibrational energy correction, determined in the harmonic approximation at the RI-MP2 level of theory, the valence anion is adiabatically stable with respect to the neutral molecule by 40 meV. The anion is characterized by a vertical detachment energy of 0.60 eV. To obtain accurate estimates of the vertical and adiabatic electron binding energies, a scheme was applied in which electronic energy contributions from various levels of theory were added, each of them extrapolated to the corresponding basis-set limit. The MP2 basis-set limits were also evaluated using an explicitly correlated approach, and the results of these calculations are in agreement with the extrapolated values. A remarkable feature of the valence anionic state is that the adiabatic electron binding energy is positive but smaller than the adiabatic electron binding energy of the dipole-bound state.

A Novel Multilayer Correlation Maximization Model for Improving CCA-Based Frequency Recognition in SSVEP Brain-Computer Interface.

PubMed

Jiao, Yong; Zhang, Yu; Wang, Yu; Wang, Bei; Jin, Jing; Wang, Xingyu

2018-05-01

Multiset canonical correlation analysis (MsetCCA) has been successfully applied to optimize the reference signals by extracting common features from multiple sets of electroencephalogram (EEG) for steady-state visual evoked potential (SSVEP) recognition in brain-computer interface application. To avoid extracting the possible noise components as common features, this study proposes a sophisticated extension of MsetCCA, called multilayer correlation maximization (MCM) model for further improving SSVEP recognition accuracy. MCM combines advantages of both CCA and MsetCCA by carrying out three layers of correlation maximization processes. The first layer is to extract the stimulus frequency-related information in using CCA between EEG samples and sine-cosine reference signals. The second layer is to learn reference signals by extracting the common features with MsetCCA. The third layer is to re-optimize the reference signals set in using CCA with sine-cosine reference signals again. Experimental study is implemented to validate effectiveness of the proposed MCM model in comparison with the standard CCA and MsetCCA algorithms. Superior performance of MCM demonstrates its promising potential for the development of an improved SSVEP-based brain-computer interface.

LU Factorization with Partial Pivoting for a Multi-CPU, Multi-GPU Shared Memory System

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

Kurzak, Jakub; Luszczek, Pitior; Faverge, Mathieu

2012-03-01

LU factorization with partial pivoting is a canonical numerical procedure and the main component of the High Performance LINPACK benchmark. This article presents an implementation of the algorithm for a hybrid, shared memory, system with standard CPU cores and GPU accelerators. Performance in excess of one TeraFLOPS is achieved using four AMD Magny Cours CPUs and four NVIDIA Fermi GPUs.

Simulations & Measurements of Airframe Noise: A BANC Workshops Perspective

NASA Technical Reports Server (NTRS)

Choudhari, Meelan; Lockard, David

2016-01-01

Airframe noise corresponds to the acoustic radiation due to turbulent flow in the vicinity of airframe components such as high-lift devices and landing gears. Since 2010, the American Institute of Aeronautics and Astronautics has organized an ongoing series of workshops devoted to Benchmark Problems for Airframe Noise Computations (BANC). The BANC workshops are aimed at enabling a systematic progress in the understanding and high-fidelity predictions of airframe noise via collaborative investigations that integrate computational fluid dynamics, computational aeroacoustics, and in depth measurements targeting a selected set of canonical yet realistic configurations that advance the current state-of-the-art in multiple respects. Unique features of the BANC Workshops include: intrinsically multi-disciplinary focus involving both fluid dynamics and aeroacoustics, holistic rather than predictive emphasis, concurrent, long term evolution of experiments and simulations with a powerful interplay between the two, and strongly integrative nature by virtue of multi-team, multi-facility, multiple-entry measurements. This paper illustrates these features in the context of the BANC problem categories and outlines some of the challenges involved and how they were addressed. A brief summary of the BANC effort, including its technical objectives, strategy, and selective outcomes thus far is also included.

[The physiological classification of human thermal states under high environmental temperatures].

PubMed

Bobrov, A F; Kuznets, E I

1995-01-01

The paper deals with the physiological classification of human thermal states in a hot environment. A review of the basic systems of classifications of thermal states is given, their main drawbacks are discussed. On the basis of human functional state research in a broad range of environmental temperatures the system of evaluation and classification of human thermal states is proposed. New integral one-dimensional multi-parametric criteria for evaluation are used. For the development of these criteria methods of factor, cluster and canonical correlation analyses are applied. Stochastic nomograms capable of identification of human thermal state for different intensity of influence are given. In this case evaluation of intensity is estimated according to one-dimensional criteria taking into account environmental temperature, physical load and time of man's staying in overheating conditions.

Influence of Environmental Factors on Essential Oil Variability in Origanum compactum Benth. Growing Wild in Morocco.

PubMed

Aboukhalid, Kaoutar; Al Faiz, Chaouki; Douaik, Ahmed; Bakha, Mohamed; Kursa, Karolina; Agacka-Mołdoch, Monika; Machon, Nathalie; Tomi, Félix; Lamiri, Abdeslam

2017-09-01

The present study aimed to evaluate the influence of environmental factors on essential oils (EOs) composition of Origanum compactum populations sampled all over the distribution area of the species in Morocco, and to determine the extent of the chemical profiles throughout the geographical distribution of the species. The chemical compositions were submitted to canonical correlation analysis and canonical discriminant analysis that indicated a significant relationship between oil components and some environmental factors. According to their chemical composition and edapho-climatic characteristics, two major groups of populations were differentiated. The first group was composed of samples growing in regions with humid climate, clayey, sandy, and alkaline soils. These samples showed high thymol, α-terpineol, linalool, and carvacryl methyl oxide content. The second group consisted of plants belonging to semi-arid climate, and growing at high altitudes and silty soils. These samples were characterized by high carvacrol, α-thujene, α-terpinene, and myrcene content. However, populations exposed to sub-humid climate, appeared less homogeneous and belong mainly either to the first or second group. A significant correlation between some edaphic factors (pH, K 2 O content, soil texture) and the EOs yield of O. compactum plants was evidenced. In spite of the correlation obtained for the oil composition with edapho-climatic factors and the variance explained by the environmental data set, the observed EO diversity might be also genetically determined. © 2017 Wiley-VHCA AG, Zurich, Switzerland.

Recovery of Areas Degraded by Mining Within the Amazon Forest: Interaction of the Physical Condition of Soil and Biological Activity

NASA Astrophysics Data System (ADS)

Ribeiro, A. I.; Mello, G. F.; Longo, R. M.; Fengler, F. H.; Peche Filho, A., Sr.

2017-12-01

One of the greatest natural riches of Brazil is the Amazon rainforest. The Amazon region is known for its abundance of mineral resources, and may include topaz, oil, and especially cassiterite. In this scope, the mining sector in Brazil has great strategic importance because it accounts for approximately 30% of the country's exports with a mineral production of 40 billion dollars (Brazilian Mining Institute, 2015). In this scenario, as a consequence of mining, the Amazonian ecosystem has been undergoing a constant process of degradation. An important artifice in the exploitation of mineral resources is the rehabilitation and/or recovery of degraded areas. This recovery requires the establishment of degradation indicators and also the quality of the soil associated with its biota, since the Amazonian environment is dynamic, heterogeneous and complex in its physical, chemical and biological characteristics. In this way, this work presupposes that it is possible to characterize the different stages of recovery of tillage floor areas in deactivated cassiterite mines, within the Amazonian forest, in order to evaluate the interactions between the level of biological activity (Serrapilheira Height, Coefficient Metabolic, Basal Breath) and physical soil characteristics (aggregate DMG, Porosity, Total Soil Density, Moisture Content), through canonical correlation analysis. The results present correlations between the groups of indicators. Thus, from the use of the groups defined by canonical correlations, it was possible to identify the response of the set of physical and biological variables to the areas at different stages of recovery.

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

NASA Astrophysics Data System (ADS)

Guo, Yang; Sivalingam, Kantharuban; Valeev, Edward F.; Neese, Frank

2016-03-01

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still two important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling "partially contracted" NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient "electron pair prescreening" that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.

Canonical multi-valued input Reed-Muller trees and forms

NASA Technical Reports Server (NTRS)

Perkowski, M. A.; Johnson, P. D.

1991-01-01

There is recently an increased interest in logic synthesis using EXOR gates. The paper introduces the fundamental concept of Orthogonal Expansion, which generalizes the ring form of the Shannon expansion to the logic with multiple-valued (mv) inputs. Based on this concept we are able to define a family of canonical tree circuits. Such circuits can be considered for binary and multiple-valued input cases. They can be multi-level (trees and DAG's) or flattened to two-level AND-EXOR circuits. Input decoders similar to those used in Sum of Products (SOP) PLA's are used in realizations of multiple-valued input functions. In the case of the binary logic the family of flattened AND-EXOR circuits includes several forms discussed by Davio and Green. For the case of the logic with multiple-valued inputs, the family of the flattened mv AND-EXOR circuits includes three expansions known from literature and two new expansions.

Multimodal neural correlates of cognitive control in the Human Connectome Project.

PubMed

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions hypothesized to be modulated by cognitive control signaling, such as visual cortex. Taken together, these results illustrate the potential utility of multi-modal analyses in identifying the neural correlates of cognitive control across different indicators of brain structure and function. Copyright © 2017 Elsevier Inc. All rights reserved.

A canonical correlation analysis on the relationship between functional fitness and health-related quality of life in older adults.

PubMed

Chung, Pak-Kwong; Zhao, Yanan; Liu, Jing-Dong; Quach, Binh

This study aimed to explore the relationship between the functional fitness (FF) and health-related quality of life (HRQoL) in older adults, and to identify the key subdimensions of FF and HRQoL influencing their overall relationship. This cross-sectional study was performed among 851 independent community members (65-84 years; men=402). The Senior Fitness Test and the Short Form 36 Health Survey were used to measure FF and HRQoL, respectively. A canonical correlation analysis was conducted using seven fitness variables as predictors of eight HRQoL variables to examine the relationship between FF and HRQoL. The overall FF was positively correlated with the overall HRQoL in both men (canonical correlation=0.350) and women (canonical correlation=0.456). The up-and-go and 2-min step contributed the most to FF, and physical functioning contributed the most to HRQOL among men. Conversely, the up-and-go and 30-s chair stand contributed the most to FF, and physical functioning contributed the most to HRQoL in women. There were positive and moderate relationships between overall FF and overall HRQOL in older adults. The FF has a significant influence on HRQoL, particularly physical functioning. The main FF components influencing the relationship between FF and HRQoL in men are balance and agility and aerobic endurance, whereas in women they are balance and agility and lower extremity muscle strength. Results from this study facilitate comprehensively understanding the relationship between FF and HRQoL, and generating critical insight into HRQoL improvement from the perspective of FF enhancement. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Relating drug–protein interaction network with drug side effects

PubMed Central

Mizutani, Sayaka; Pauwels, Edouard; Stoven, Véronique; Goto, Susumu; Yamanishi, Yoshihiro

2012-01-01

Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system–wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs. Results: We performed a large-scale analysis to extract correlated sets of targeted proteins and side effects, based on the co-occurrence of drugs in protein-binding profiles and side effect profiles, using sparse canonical correlation analysis. The analysis of 658 drugs with the two profiles for 1368 proteins and 1339 side effects led to the extraction of 80 correlated sets. Enrichment analyses using KEGG and Gene Ontology showed that most of the correlated sets were significantly enriched with proteins that are involved in the same biological pathways, even if their molecular functions are different. This allowed for a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. The extracted side effects can be regarded as possible phenotypic outcomes by drugs targeting the proteins that appear in the same correlated set. The proposed method is expected to be useful for predicting potential side effects of new drug candidate compounds based on their protein-binding profiles. Supplementary information: Datasets and all results are available at http://web.kuicr.kyoto-u.ac.jp/supp/smizutan/target-effect/. Availability: Software is available at the above supplementary website. Contact: yamanishi@bioreg.kyushu-u.ac.jp, or goto@kuicr.kyoto-u.ac.jp PMID:22962476

Social inequality, lifestyles and health - a non-linear canonical correlation analysis based on the approach of Pierre Bourdieu.

PubMed

Grosse Frie, Kirstin; Janssen, Christian

2009-01-01

Based on the theoretical and empirical approach of Pierre Bourdieu, a multivariate non-linear method is introduced as an alternative way to analyse the complex relationships between social determinants and health. The analysis is based on face-to-face interviews with 695 randomly selected respondents aged 30 to 59. Variables regarding socio-economic status, life circumstances, lifestyles, health-related behaviour and health were chosen for the analysis. In order to determine whether the respondents can be differentiated and described based on these variables, a non-linear canonical correlation analysis (OVERALS) was performed. The results can be described on three dimensions; Eigenvalues add up to the fit of 1.444, which can be interpreted as approximately 50 % of explained variance. The three-dimensional space illustrates correspondences between variables and provides a framework for interpretation based on latent dimensions, which can be described by age, education, income and gender. Using non-linear canonical correlation analysis, health characteristics can be analysed in conjunction with socio-economic conditions and lifestyles. Based on Bourdieus theoretical approach, the complex correlations between these variables can be more substantially interpreted and presented.

Automated Change Detection for Synthetic Aperture Sonar

DTIC Science & Technology

2014-01-01

channels, respectively. The canonical coordinates of x and y are defined as u = FHR−1/2xx x v = GHR−1/2yy y where F and G are the mapping matrices...containing the left and right singular vectors of the coherence matrix C, respectively. The canonical coordinate vectors u and v share the diagonal cross...feature set. The coherent change information between canonical coordinates v and u can be calculated using the residual, v −Ku, owing to the fact that

Onset of Speech-Like Vocalizations in Infants with Down Syndrome.

ERIC Educational Resources Information Center

Lynch, Michael P.; And Others

1995-01-01

Evaluation of canonical babbling of 13 infants with Down syndrome found that age of onset of babbling was approximately 2 months later and less stable than that of 27 typically developing infants. Age at onset of canonical babbling for Down syndrome infants was correlated with scores at 27 months on the Early Social-Communication Scales.…

Efficient measurement of point-to-set correlations and overlap fluctuations in glass-forming liquids

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

Berthier, Ludovic; Charbonneau, Patrick; Department of Physics, Duke University, Durham, North Carolina 27708

Cavity point-to-set correlations are real-space tools to detect the roughening of the free-energy landscape that accompanies the dynamical slowdown of glass-forming liquids. Measuring these correlations in model glass formers remains, however, a major computational challenge. Here, we develop a general parallel-tempering method that provides orders-of-magnitude improvement for sampling and equilibrating configurations within cavities. We apply this improved scheme to the canonical Kob-Andersen binary Lennard-Jones model for temperatures down to the mode-coupling theory crossover. Most significant improvements are noted for small cavities, which have thus far been the most difficult to study. This methodological advance also enables us to study amore » broader range of physical observables associated with thermodynamic fluctuations. We measure the probability distribution of overlap fluctuations in cavities, which displays a non-trivial temperature evolution. The corresponding overlap susceptibility is found to provide a robust quantitative estimate of the point-to-set length scale requiring no fitting. By resolving spatial fluctuations of the overlap in the cavity, we also obtain quantitative information about the geometry of overlap fluctuations. We can thus examine in detail how the penetration length as well as its fluctuations evolve with temperature and cavity size.« less

Positive geometries and canonical forms

NASA Astrophysics Data System (ADS)

Arkani-Hamed, Nima; Bai, Yuntao; Lam, Thomas

2017-11-01

Recent years have seen a surprising connection between the physics of scattering amplitudes and a class of mathematical objects — the positive Grassmannian, positive loop Grassmannians, tree and loop Amplituhedra — which have been loosely referred to as "positive geometries". The connection between the geometry and physics is provided by a unique differential form canonically determined by the property of having logarithmic singularities (only) on all the boundaries of the space, with residues on each boundary given by the canonical form on that boundary. The structures seen in the physical setting of the Amplituhedron are both rigid and rich enough to motivate an investigation of the notions of "positive geometries" and their associated "canonical forms" as objects of study in their own right, in a more general mathematical setting. In this paper we take the first steps in this direction. We begin by giving a precise definition of positive geometries and canonical forms, and introduce two general methods for finding forms for more complicated positive geometries from simpler ones — via "triangulation" on the one hand, and "push-forward" maps between geometries on the other. We present numerous examples of positive geometries in projective spaces, Grassmannians, and toric, cluster and flag varieties, both for the simplest "simplex-like" geometries and the richer "polytope-like" ones. We also illustrate a number of strategies for computing canonical forms for large classes of positive geometries, ranging from a direct determination exploiting knowledge of zeros and poles, to the use of the general triangulation and push-forward methods, to the representation of the form as volume integrals over dual geometries and contour integrals over auxiliary spaces. These methods yield interesting representations for the canonical forms of wide classes of positive geometries, ranging from the simplest Amplituhedra to new expressions for the volume of arbitrary convex polytopes.

Correlated Observations, the Law of Small Numbers and Bank Runs

PubMed Central

2016-01-01

Empirical descriptions and studies suggest that generally depositors observe a sample of previous decisions before deciding if to keep their funds deposited or to withdraw them. These observed decisions may exhibit different degrees of correlation across depositors. In our model depositors decide sequentially and are assumed to follow the law of small numbers in the sense that they believe that a bank run is underway if the number of observed withdrawals in their sample is large. Theoretically, with highly correlated samples and infinite depositors runs occur with certainty, while with random samples it needs not be the case, as for many parameter settings the likelihood of bank runs is zero. We investigate the intermediate cases and find that i) decreasing the correlation and ii) increasing the sample size reduces the likelihood of bank runs, ceteris paribus. Interestingly, the multiplicity of equilibria, a feature of the canonical Diamond-Dybvig model that we use also, disappears almost completely in our setup. Our results have relevant policy implications. PMID:27035435

Correlated Observations, the Law of Small Numbers and Bank Runs.

PubMed

Horváth, Gergely; Kiss, Hubert János

2016-01-01

Empirical descriptions and studies suggest that generally depositors observe a sample of previous decisions before deciding if to keep their funds deposited or to withdraw them. These observed decisions may exhibit different degrees of correlation across depositors. In our model depositors decide sequentially and are assumed to follow the law of small numbers in the sense that they believe that a bank run is underway if the number of observed withdrawals in their sample is large. Theoretically, with highly correlated samples and infinite depositors runs occur with certainty, while with random samples it needs not be the case, as for many parameter settings the likelihood of bank runs is zero. We investigate the intermediate cases and find that i) decreasing the correlation and ii) increasing the sample size reduces the likelihood of bank runs, ceteris paribus. Interestingly, the multiplicity of equilibria, a feature of the canonical Diamond-Dybvig model that we use also, disappears almost completely in our setup. Our results have relevant policy implications.

Biomotor structures in elite female handball players.

PubMed

Katić, Ratko; Cavala, Marijana; Srhoj, Vatromir

2007-09-01

In order to identify biomotor structures in elite female handball players, factor structures of morphological characteristics and basic motor abilities of elite female handball players (N = 53) were determined first, followed by determination of relations between the morphological-motor space factors obtained and the set of criterion variables evaluating situation motor abilities in handball. Factor analysis of 14 morphological measures produced three morphological factors, i.e. factor of absolute voluminosity (mesoendomorph), factor of longitudinal skeleton dimensionality, and factor of transverse hand dimensionality. Factor analysis of 15 motor variables yielded five basic motor dimensions, i.e. factor of agility, factor of jumping explosive strength, factor of throwing explosive strength, factor of movement frequency rate, and factor of running explosive strength (sprint). Four significant canonic correlations, i.e. linear combinations, explained the correlation between the set of eight latent variables of the morphological and basic motor space and five variables of situation motoricity. First canonic linear combination is based on the positive effect of the factors of agility/coordination on the ability of fast movement without ball. Second linear combination is based on the effect of jumping explosive strength and transverse hand dimensionality on ball manipulation, throw precision, and speed of movement with ball. Third linear combination is based on the running explosive strength determination by the speed of movement with ball, whereas fourth combination is determined by throwing and jumping explosive strength, and agility on ball pass. The results obtained were consistent with the model of selection in female handball proposed (Srhoj et al., 2006), showing the speed of movement without ball and the ability of ball manipulation to be the predominant specific abilities, as indicated by the first and second linear combination.

Exploration of Acoustic Features for Automatic Vowel Discrimination in Spontaneous Speech

ERIC Educational Resources Information Center

Tyson, Na'im R.

2012-01-01

In an attempt to understand what acoustic/auditory feature sets motivated transcribers towards certain labeling decisions, I built machine learning models that were capable of discriminating between canonical and non-canonical vowels excised from the Buckeye Corpus. Specifically, I wanted to model when the dictionary form and the transcribed-form…

Astronaut Preflight Cardiovascular Variables Associated with Vascular Compliance are Highly Correlated with Post-Flight Eye Outcome Measures in the Visual Impairment Intracranial Pressure (VIIP) Syndrome Following Long Duration Spaceflight

NASA Technical Reports Server (NTRS)

Otto, Christian; Ploutz-Snyder, R.

2015-01-01

The detection of the first VIIP case occurred in 2005, and adequate eye outcome measures were available for 31 (67.4%) of the 46 long duration US crewmembers who had flown on the ISS since its first crewed mission in 2000. Therefore, this analysis is limited to a subgroup (22 males and 9 females). A "cardiovascular profile" for each astronaut was compiled by examining twelve individual parameters; eleven of these were preflight variables: systolic blood pressure, pulse pressure, body mass index, percentage body fat, LDL, HDL, triglycerides, use of anti-lipid medication, fasting serum glucose, and maximal oxygen uptake in ml/kg. Each of these variables was averaged across three preflight annual physical exams. Astronaut age prior to the long duration mission, and inflight salt intake was also included in the analysis. The group of cardiovascular variables for each crew member was compared with seven VIIP eye outcome variables collected during the immediate post-flight period: anterior-posterior axial length of the globe measured by ultrasound and optical biometry; optic nerve sheath diameter, optic nerve diameter, and optic nerve to sheath ratio- each measured by ultrasound and magnetic resonance imaging (MRI), intraocular pressure (IOP), change in manifest refraction, mean retinal nerve fiber layer (RNFL) on optical coherence tomography (OCT), and RNFL of the inferior and superior retinal quadrants. Since most of the VIIP eye outcome measures were added sequentially beginning in 2005, as knowledge of the syndrome improved, data were unavailable for 22.0% of the outcome measurements. To address the missing data, we employed multivariate multiple imputation techniques with predictive mean matching methods to accumulate 200 separate imputed datasets for analysis. We were able to impute data for the 22.0% of missing VIIP eye outcomes. We then applied Rubin's rules for collapsing the statistical results across our 200 multiply imputed data sets to assess the canonical correlation between the eye outcomes and the twelve astronaut cardiovascular variables available for all 31 subjects. Results: A highly significant canonical correlation was observed among the canonical solutions (p<.00001), with an average best canonical correlation of.97. The results suggest a strong association between astronauts' measures of cardiovascular health and the seven eye outcomes of the VIIP syndrome used in this analysis. Furthermore, the "joint test" revealed a significant difference in cardiovascular profile between male and female astronauts (Prob > F = 0.00001). Overall, female astronauts demonstrated a significantly healthier cardiovascular status. Individually, the female astronauts had significantly healthier profiles on seven of twelve cardiovascular variables than the men (p values ranging from <0.0001 to <0.05). Male astronauts did not demonstrate significantly healthier values on any of the twelve cardiovascular variables measured

Examination of the relationships between environmental exposures to volatile organic compounds and biochemical liver tests: application of canonical correlation analysis

PubMed Central

Liu, Jing; Drane, Wanzer; Liu, Xuefeng; Wu, Tiejian

2009-01-01

This study was to explore the relationships between personal exposure to ten volatile organic compounds (VOCs) and biochemical liver tests with the application of canonical correlation analysis. Data from a subsample of the 1999–2000 National Health and Nutrition Examination Survey were used. Serum albumin, total bilirubin (TB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and γ-glutamyl transferase (GGT) served as the outcome variables. Personal exposures to benzene, chloroform, ethylbenzene, tetrachloroethene, toluene, trichloroethene, o-xylene, m-, p-xylene, 1,4-dichlorobenzene, and methyl tert-butyl ether (MTBE) were assessed through the use of passive exposure monitors worn by study participants. The first two canonical correlations were 0.3218 and 0.2575, suggesting a positive correlation mainly between the six VOCs (benzene, ethylbenzene, toluene, o-xylene, m-, p-xylene, and MTBE) and the three biochemical liver tests (albumin, ALP, and GGT) and a positive correlation mainly between the two VOCs (1,4-dichlorobenzene and tetrachloroethene) and the two biochemical liver tests (LDH and TB). Subsequent multiple linear regressions show that exposure to benzene, toluene, or MTBE was associated with serum albumin, while exposure to tetrachloroethene was associated with LDH and total bilirubin. In conclusion, exposure to certain VOCs as a group or individually may influence certain biochemical liver test results in the general population. PMID:19117555

Examination of the relationships between environmental exposures to volatile organic compounds and biochemical liver tests: application of canonical correlation analysis.

PubMed

Liu, Jing; Drane, Wanzer; Liu, Xuefeng; Wu, Tiejian

2009-02-01

This study was to explore the relationships between personal exposure to 10 volatile organic compounds (VOCs) and biochemical liver tests with the application of canonical correlation analysis. Data from a subsample of the 1999-2000 National Health and Nutrition Examination Survey were used. Serum albumin, total bilirubin (TB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and gamma-glutamyl transferase (GGT) served as the outcome variables. Personal exposures to benzene, chloroform, ethylbenzene, tetrachloroethene, toluene, trichloroethene, o-xylene, m-,p-xylene, 1,4-dichlorobenzene, and methyl tert-butyl ether (MTBE) were assessed through the use of passive exposure monitors worn by study participants. The first two canonical correlations were 0.3218 and 0.2575, suggesting a positive correlation mainly between the six VOCs (benzene, ethylbenzene, toluene, o-xylene, m-,p-xylene, and MTBE) and the three biochemical liver tests (albumin, ALP, and GGT) and a positive correlation mainly between the two VOCs (1,4-dichlorobenzene and tetrachloroethene) and the two biochemical liver tests (LDH and TB). Subsequent multiple linear regressions show that exposure to benzene, toluene, or MTBE was associated with serum albumin, while exposure to tetrachloroethene was associated with LDH and total bilirubin. In conclusion, exposure to certain VOCs as a group or individually may influence certain biochemical liver test results in the general population.

Infant vocalizations and the early diagnosis of severe hearing impairment.

PubMed

Eilers, R E; Oller, D K

1994-02-01

To determine whether late onset of canonical babbling could be used as a criterion to determine risk of hearing impairment, we obtained vocalization samples longitudinally from 94 infants with normal hearing and 37 infants with severe to profound hearing impairment. Parents were instructed to report the onset of canonical babbling (the production of well-formed syllables such as "da," "na," "bee," "yaya"). Verification that the infants were producing canonical syllables was collected in laboratory audio recordings. Infants with normal hearing produced canonical vocalizations before 11 months of age (range, 3 to 10 months; mode, 7 months); infants who were deaf failed to produce canonical syllables until 11 months of age or older, often well into the third year of life (range, 11 to 49 months; mode, 24 months). The correlation between age at onset of the canonical stage and age at auditory amplification was 0.68, indicating that early identification and fitting of hearing aids is of significant benefit to infants learning language. The fact that there is no overlap in the distribution of the onset of canonical babbling between infants with normal hearing and infants with hearing impairment means that the failure of otherwise healthy infants to produce canonical syllables before 11 months of age should be considered a serious risk factor for hearing impairment and, when observed, should result in immediate referral for audiologic evaluation.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

PubMed

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-07-01

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

PubMed Central

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T.; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-01-01

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153689

Correlation between Gini index and mobility in a stochastic kinetic model of economic exchange

NASA Astrophysics Data System (ADS)

Bertotti, Maria Letizia; Chattopadhyay, Amit K.; Modanese, Giovanni

Starting from a class of stochastically driven kinetic models of economic exchange, here we present results highlighting the correlation of the Gini inequality index with the social mobility rate, close to dynamical equilibrium. Except for the "canonical-additive case", our numerical results consistently indicate negative values of the correlation coefficient, in agreement with empirical evidence. This confirms that growing inequality is not conducive to social mobility which then requires an "external source" to sustain its dynamics. On the other hand, the sign of the correlation between inequality and total income in the canonical ensemble depends on the way wealth enters or leaves the system. At a technical level, the approach involves a generalization of a stochastic dynamical system formulation, that further paves the way for a probabilistic formulation of perturbed economic exchange models.

Canonical correlation analysis to identify the semen characteristics used to forecast the freeze survival of Curimba (Prochilodus lineatus) spermatozoa.

PubMed

Carvalho, A F S; Murgas, L D S; Ferreira-Machad, M R; Andrade, E S; Felizardo, V O; Allaman, I B; de Paula, F G

　　OBJECTIVE: To identify which sperm characteristics were able to predict more accurately the quality of curimba (Prochilodus lineatus) semen upon freezing using canonical correlation analysis. Eleven fish breeders with initial mean weight of 705.21 ± 111 g were used. For cryopreservation, 200 µL of semen were taken from each animal and diluted in the cryoprotectant solution (10% dimethyl sulfoxide and 5% Beltsville Thawing Solution Minitub) in a 1:4 ratio and placed into 0.5-mL straws. Sperm characteristics (motility, sperm abnormalities, total antioxidant activity and lipid peroxidation) were evaluated. A randomized block design with duplicate samples per treatment (fresh and frozen semen) was used. The block factor was the animals, and the experimental unit the ejaculates. Canonical correlation was used to evaluate the association between sperm characteristics of fresh semen and thawed semen. There was a significant association (P = 0.10) among the variables measured in fresh semen with the variables measured in thawed semen, and 78.6% of the difference observed in the thawed semen can be attributed to variation of variables measured in fresh semen. Sperm motility, motility duration and antioxidant activity of the thawed semen showed an inverse relationship with those of the fresh semen; whereas the minor sperm abnormalities, major sperm abnormalities and lipid peroxidation showed a direct relationship with those of the fresh semen. Only the rate and motility duration of the thawed semen presented high correlation (-0.63 and -0.73, respectively) with the canonical variable represented by the sperm characteristics of fresh semen. The rate and motility duration of fresh semen may be used to predict the quality of the thawed sperm in Prochilodus lineatus.

Gender and the Contemporary Educational Canon in the UK

ERIC Educational Resources Information Center

Elliott, Victoria

2017-01-01

This paper presents an analysis of the gender of the authors and the main characters of the set texts for English examinations taken at age 16 in England, Northern Ireland, Scotland and Wales. It presents an argument for why representation within the canon is important and places this within the context of recent educational reform in England and…

A data-driven investigation of relationships between bipolar psychotic symptoms and schizophrenia genome-wide significant genetic loci.

PubMed

Leonenko, Ganna; Di Florio, Arianna; Allardyce, Judith; Forty, Liz; Knott, Sarah; Jones, Lisa; Gordon-Smith, Katherine; Owen, Michael J; Jones, Ian; Walters, James; Craddock, Nick; O'Donovan, Michael C; Escott-Price, Valentina

2018-06-01

The etiologies of bipolar disorder (BD) and schizophrenia include a large number of common risk alleles, many of which are shared across the disorders. BD is clinically heterogeneous and it has been postulated that the pattern of symptoms is in part determined by the particular risk alleles carried, and in particular, that risk alleles also confer liability to schizophrenia influence psychotic symptoms in those with BD. To investigate links between psychotic symptoms in BD and schizophrenia risk alleles we employed a data-driven approach in a genotyped and deeply phenotyped sample of subjects with BD. We used sparse canonical correlation analysis (sCCA) (Witten, Tibshirani, & Hastie, ) to analyze 30 psychotic symptoms, assessed with the OPerational CRITeria checklist, and 82 independent genome-wide significant single nucleotide polymorphisms (SNPs) identified by the Schizophrenia Working group of the Psychiatric Genomics Consortium for which we had data in our BD sample (3,903 subjects). As a secondary analysis, we applied sCCA to larger groups of SNPs, and also to groups of symptoms defined according to a published factor analyses of schizophrenia. sCCA analysis based on individual psychotic symptoms revealed a significant association (p = .033), with the largest weights attributed to a variant on chromosome 3 (rs11411529), chr3:180594593, build 37) and delusions of influence, bizarre behavior and grandiose delusions. sCCA analysis using the same set of SNPs supported association with the same SNP and the group of symptoms defined "factor 3" (p = .012). A significant association was also observed to the "factor 3" phenotype group when we included a greater number of SNPs that were less stringently associated with schizophrenia; although other SNPs contributed to the significant multivariate association result, the greatest weight remained assigned to rs11411529. Our results suggest that the canonical correlation is a useful tool to explore phenotype-genotype relationships. To the best of our knowledge, this is the first study to apply this approach to complex, polygenic psychiatric traits. The sparse canonical correlation approach offers the potential to include a larger number of fine-grained systematic descriptors, and to include genetic markers associated with other disorders that are genetically correlated with BD. © 2018 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Statistical hadronization and microcanonical ensemble

DOE PAGES

Becattini, F.; Ferroni, L.

2004-01-01

We present a Monte Carlo calculation of the microcanonical ensemble of the of the ideal hadron-resonance gas including all known states up to a mass of 1. 8 GeV, taking into account quantum statistics. The computing method is a development of a previous one based on a Metropolis Monte Carlo algorithm, with a the grand-canonical limit of the multi-species multiplicity distribution as proposal matrix. The microcanonical average multiplicities of the various hadron species are found to converge to the canonical ones for moderately low values of the total energy. This algorithm opens the way for event generators based for themore » statistical hadronization model.« less

Characterizing chaotic melodies in automatic music composition

NASA Astrophysics Data System (ADS)

Coca, Andrés E.; Tost, Gerard O.; Zhao, Liang

2010-09-01

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests.

Corticospinal signals recorded with MEAs can predict the volitional forearm forces in rats.

PubMed

Guo, Yi; Mesut, Sahin; Foulds, Richard A; Adamovich, Sergei V

2013-01-01

We set out to investigate if volitional components in the descending tracts of the spinal cord white matter can be accessed with multi-electrode array (MEA) recording technique. Rats were trained to press a lever connected to a haptic device with force feedback to receive sugar pellets. A flexible-substrate multi-electrode array was chronically implanted into the dorsal column of the cervical spinal cord. Field potentials and multi-unit activities were recorded from the descending axons of the corticospinal tract while the rat performed a lever pressing task. Forelimb forces, recorded with the sensor attached to the lever, were reconstructed using the hand position data and the neural signals through multiple trials over three weeks. The regression coefficients found from the trial set were cross-validated on the other trials recorded on same day. Approximately 30 trials of at least 2 seconds were required for accurate model estimation. The maximum correlation coefficient between the actual and predicted force was 0.7 in the test set. Positional information and its interaction with neural signals improved the correlation coefficient by 0.1 to 0.15. These results suggest that the volitional information contained in the corticospinal tract can be extracted with multi-channel neural recordings made with parenchymal electrodes.

Quantitative EEG and its Correlation with Cardiovascular, Cognition and mood State: an Integrated Study in Simulated Microgravity

NASA Astrophysics Data System (ADS)

Zhang, Jianyuan; Hu, Bin; Chen, Wenjuan; Moore, Philip; Xu, Tingting; Dong, Qunxi; Liu, Zhenyu; Luo, Yuejia; Chen, Shanguang

2014-12-01

The focus of the study is the estimation of the effects of microgravity on the central nervous activity and its underlying influencing mechanisms. To validate the microgravity-induced physiological and psychological effects on EEG, quantitative EEG features, cardiovascular indicators, mood state, and cognitive performances data collection was achieved during a 45 day period using a -6°head-down bed rest (HDBR) integrated approach. The results demonstrated significant differences in EEG data, as an increased Theta wave, a decreased Beta wave and a reduced complexity of brain, accompanied with an increased heart rate and pulse rate, decreased positive emotion, and degraded emotion conflict monitoring performance. The canonical correlation analysis (CCA) based cardiovascular and cognitive related EEG model showed the cardiovascular effect on EEG mainly affected bilateral temporal region and the cognitive effect impacted parietal-occipital and frontal regions. The results obtained in the study support the use of an approach which combines a multi-factor influential mechanism hypothesis. The changes in the EEG data may be influenced by both cardiovascular and cognitive effects.

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

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

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

DOE PAGES

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu; ...

2016-11-09

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

PubMed

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

PubMed

Madrigal, Pedro

2017-03-01

Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Electronic and spectroscopic characterizations of SNP isomers

NASA Astrophysics Data System (ADS)

Trabelsi, Tarek; Al Mogren, Muneerah Mogren; Hochlaf, Majdi; Francisco, Joseph S.

2018-02-01

High-level ab initio electronic structure calculations were performed to characterize SNP isomers. In addition to the known linear SNP, cyc-PSN, and linear SPN isomers, we identified a fourth isomer, linear PSN, which is located ˜2.4 eV above the linear SNP isomer. The low-lying singlet and triplet electronic states of the linear SNP and SPN isomers were investigated using a multi-reference configuration interaction method and large basis set. Several bound electronic states were identified. However, their upper rovibrational levels were predicted to pre-dissociate, leading to S + PN, P + NS products, and multi-step pathways were discovered. For the ground states, a set of spectroscopic parameters were derived using standard and explicitly correlated coupled-cluster methods in conjunction with augmented correlation-consistent basis sets extrapolated to the complete basis set limit. We also considered scalar and core-valence effects. For linear isomers, the rovibrational spectra were deduced after generation of their 3D-potential energy surfaces along the stretching and bending coordinates and variational treatments of the nuclear motions.

Patterns of metal composition and biological condition and their association in male common carp across an environmental contaminant gradient in Lake Mead National Recreation Area, Nevada and Arizona, USA

USGS Publications Warehouse

Patino, R.; Rosen, Michael R.; Orsak, E.L.; Goodbred, S.L.; May, T.W.; Alvarez, David; Echols, K.R.; Wieser, C.M.; Ruessler, S.; Torres, L.

2012-01-01

There is a contaminant gradient in Lake Mead National Recreation Area (LMNRA) that is partly driven by municipal and industrial runoff and wastewater inputs via Las Vegas Wash (LVW). Adult male common carp (Cyprinus carpio; 10 fish/site) were collected from LVW, Las Vegas Bay (receiving LVW flow), Overton Arm (OA, upstream reference), and Willow Beach (WB, downstream) in March 2008. Discriminant function analysis was used to describe differences in metal concentrations and biological condition of fish collected from the four study sites, and canonical correlation analysis was used to evaluate the association between metal and biological traits. Metal concentrations were determined in whole-body extracts. Of 63 metals screened, those initially used in the statistical analysis were Ag, As, Ba, Cd, Co, Fe, Hg, Pb, Se, Zn. Biological variables analyzed included total length (TL), Fulton's condition factor, gonadosomatic index (GSI), hematocrit (Hct), and plasma estradiol-17?? and 11-ketotestosterone (11kt) concentrations. Analysis of metal composition and biological condition both yielded strong discrimination of fish by site (respective canonical model, p< 0.0001). Compared to OA, pairwise Mahalanobis distances between group means were WB < LVB < LVW for metal concentrations and LVB < WB < LVW for biological traits. Respective primary drivers for these separations were Ag, As, Ba, Hg, Pb, Se and Zn; and TL, GSI, 11kt, and Hct. Canonical correlation analysis using the latter variable sets showed they are significantly associated (p<0.0003); with As, Ba, Hg, and Zn, and TL, 11kt, and Hct being the primary contributors to the association. In conclusion, male carp collected along a contaminant gradient in LMNRA have distinct, collection site-dependent metal and morpho-physiological profiles that are significantly associated with each other. These associations suggest that fish health and reproductive condition (as measured by the biological variables evaluated in this study) are influenced by levels of certain metals in the Lake Mead environment. ?? 2011.

Unsupervised detection and removal of muscle artifacts from scalp EEG recordings using canonical correlation analysis, wavelets and random forests.

PubMed

Anastasiadou, Maria N; Christodoulakis, Manolis; Papathanasiou, Eleftherios S; Papacostas, Savvas S; Mitsis, Georgios D

2017-09-01

This paper proposes supervised and unsupervised algorithms for automatic muscle artifact detection and removal from long-term EEG recordings, which combine canonical correlation analysis (CCA) and wavelets with random forests (RF). The proposed algorithms first perform CCA and continuous wavelet transform of the canonical components to generate a number of features which include component autocorrelation values and wavelet coefficient magnitude values. A subset of the most important features is subsequently selected using RF and labelled observations (supervised case) or synthetic data constructed from the original observations (unsupervised case). The proposed algorithms are evaluated using realistic simulation data as well as 30min epochs of non-invasive EEG recordings obtained from ten patients with epilepsy. We assessed the performance of the proposed algorithms using classification performance and goodness-of-fit values for noisy and noise-free signal windows. In the simulation study, where the ground truth was known, the proposed algorithms yielded almost perfect performance. In the case of experimental data, where expert marking was performed, the results suggest that both the supervised and unsupervised algorithm versions were able to remove artifacts without affecting noise-free channels considerably, outperforming standard CCA, independent component analysis (ICA) and Lagged Auto-Mutual Information Clustering (LAMIC). The proposed algorithms achieved excellent performance for both simulation and experimental data. Importantly, for the first time to our knowledge, we were able to perform entirely unsupervised artifact removal, i.e. without using already marked noisy data segments, achieving performance that is comparable to the supervised case. Overall, the results suggest that the proposed algorithms yield significant future potential for improving EEG signal quality in research or clinical settings without the need for marking by expert neurophysiologists, EMG signal recording and user visual inspection. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Path integral approach to the Wigner representation of canonical density operators for discrete systems coupled to harmonic baths.

PubMed

Montoya-Castillo, Andrés; Reichman, David R

2017-01-14

We derive a semi-analytical form for the Wigner transform for the canonical density operator of a discrete system coupled to a harmonic bath based on the path integral expansion of the Boltzmann factor. The introduction of this simple and controllable approach allows for the exact rendering of the canonical distribution and permits systematic convergence of static properties with respect to the number of path integral steps. In addition, the expressions derived here provide an exact and facile interface with quasi- and semi-classical dynamical methods, which enables the direct calculation of equilibrium time correlation functions within a wide array of approaches. We demonstrate that the present method represents a practical path for the calculation of thermodynamic data for the spin-boson and related systems. We illustrate the power of the present approach by detailing the improvement of the quality of Ehrenfest theory for the correlation function C zz (t)=Re⟨σ z (0)σ z (t)⟩ for the spin-boson model with systematic convergence to the exact sampling function. Importantly, the numerically exact nature of the scheme presented here and its compatibility with semiclassical methods allows for the systematic testing of commonly used approximations for the Wigner-transformed canonical density.

Refining inflation using non-canonical scalars

NASA Astrophysics Data System (ADS)

Unnikrishnan, Sanil; Sahni, Varun; Toporensky, Aleksey

2012-08-01

This paper revisits the Inflationary scenario within the framework of scalar field models possessing a non-canonical kinetic term. We obtain closed form solutions for all essential quantities associated with chaotic inflation including slow roll parameters, scalar and tensor power spectra, spectral indices, the tensor-to-scalar ratio, etc. We also examine the Hamilton-Jacobi equation and demonstrate the existence of an inflationary attractor. Our results highlight the fact that non-canonical scalars can significantly improve the viability of inflationary models. They accomplish this by decreasing the tensor-to-scalar ratio while simultaneously increasing the value of the scalar spectral index, thereby redeeming models which are incompatible with the cosmic microwave background (CMB) in their canonical version. For instance, the non-canonical version of the chaotic inflationary potential, V(phi) ~ λphi4, is found to agree with observations for values of λ as large as unity! The exponential potential can also provide a reasonable fit to CMB observations. A central result of this paper is that steep potentials (such as Vproptophi-n) usually associated with dark energy, can drive inflation in the non-canonical setting. Interestingly, non-canonical scalars violate the consistency relation r = -8nT, which emerges as a smoking gun test for this class of models.

On unified modeling, theory, and method for solving multi-scale global optimization problems

NASA Astrophysics Data System (ADS)

Gao, David Yang

2016-10-01

A unified model is proposed for general optimization problems in multi-scale complex systems. Based on this model and necessary assumptions in physics, the canonical duality theory is presented in a precise way to include traditional duality theories and popular methods as special applications. Two conjectures on NP-hardness are proposed, which should play important roles for correctly understanding and efficiently solving challenging real-world problems. Applications are illustrated for both nonconvex continuous optimization and mixed integer nonlinear programming.

X-ray spectral analysis of the steady states of GRS 1915+105

NASA Astrophysics Data System (ADS)

Peris, Charith; Remillard, Ronald A.; Steiner, James F.; Vrtilek, Saeqa Dil; Varniere, Peggy; Rodriguez, Jerome; Pooley, Guy G.

2016-04-01

Of the black hole binaries (BHBs) discovered thus far, GRS 1915+105 stands out as an exceptional source primarily due to its wild X-ray variability, the diversity of which has not been replicated in any other stellar-mass black hole. Although extreme variability is commonplace in its light-curve, about half of the observations of GRS1915+105 show fairly steady X-ray intensity. We report on the X-ray spectral behavior within these steady observations. Our work is based on a vast RXTE/PCA data set obtained on GRS 1915+105 during the course of its entire mission and 10 years of radio data from the Ryle Telescope, which overlap the X-ray data. We find that the steady observations within the X-ray data set naturally separate into two regions in a color-color diagram, which we refer to as steady-soft and steady-hard. GRS 1915+105 displays significant curvature in the Comptonization component within the PCA band pass suggesting significantly heating from a hot disk present in all states. A new Comptonization model 'simplcut' was developed in order to model this curvature to best effect. A majority of the steady-soft observations display a roughly constant inner disk radius, remarkably reminiscent of canonical soft state black hole binaries. In contrast, the steady-hard observations display a growing disk truncation that is correlated to the mass accretion rate through the disk, which suggests a magnetically truncated disk. A comparison of X-ray model parameters to the canonical state definitions show that almost all steady-soft observations match the criteria of either thermal or steep power law state, while the thermal state observations dominate the constant radius branch. A large portion 80 % of the steady-hard observations matches the hard state criteria when the disk fraction constraint is neglected. These results combine to suggest that within the complexity of this source is a simpler underlying basis of states, which map to those observed in canonical BHBs.

Logarithmic violation of scaling in anisotropic kinematic dynamo model

NASA Astrophysics Data System (ADS)

Antonov, N. V.; Gulitskiy, N. M.

2016-01-01

Inertial-range asymptotic behavior of a vector (e.g., magnetic) field, passively advected by a strongly anisotropic turbulent flow, is studied by means of the field theoretic renormalization group and the operator product expansion. The advecting velocity field is Gaussian, not correlated in time, with the pair correlation function of the form ∝δ (t -t')/k⊥d-1 +ξ , where k⊥ = |k⊥| and k⊥ is the component of the wave vector, perpendicular to the distinguished direction. The stochastic advection-diffusion equation for the transverse (divergence-free) vector field includes, as special cases, the kinematic dynamo model for magnetohydrodynamic turbulence and the linearized Navier-Stokes equation. In contrast to the well known isotropic Kraichnan's model, where various correlation functions exhibit anomalous scaling behavior with infinite sets of anomalous exponents, here the dependence on the integral turbulence scale L has a logarithmic behavior: instead of power-like corrections to ordinary scaling, determined by naive (canonical) dimensions, the anomalies manifest themselves as polynomials of logarithms of L.

Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

NASA Astrophysics Data System (ADS)

Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

2017-05-01

WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

Density Effects on Post-shock Turbulence Structure

NASA Astrophysics Data System (ADS)

Tian, Yifeng; Jaberi, Farhad; Livescu, Daniel; Li, Zhaorui; Michigan State University Collaboration; Los Alamos National Laboratory Collaboration; Texas A&M University-Corpus Christi Collaboration

2017-11-01

The effects of density variations due to mixture composition on post-shock turbulence structure are studied using turbulence-resolving shock-capturing simulations. This work extends the canonical Shock-Turbulence Interaction (STI) problem to involve significant variable density effects. The numerical method has been verified using a series of grid and LIA convergence tests, and is used to generate accurate post-shock turbulence data for a detailed flow study. Density effects on post-shock turbulent statistics are shown to be significant, leading to an increased amplification of turbulent kinetic energy (TKE). Eulerian and Lagrangian analyses show that the increase in the post-shock correlation between rotation and strain is weakened in the case with significant density variations (referred to as the ``multi-fluid'' case). Similar to previous single-fluid results and LIA predictions, the shock wave significantly changes the topology of the turbulent structures, exhibiting a symmetrization of the joint PDF of second and third invariant of the deviatoric part of velocity gradient tensor. In the multi-fluid case, this trend is more significant and mainly manifested in the heavy fluid regions. Lagrangian data are also used to study the evolution of turbulence structure away from the shock wave and assess the accuracy of Lagrangian dynamical models.

A scalable correlator for multichannel diffuse correlation spectroscopy.

PubMed

Stapels, Christopher J; Kolodziejski, Noah J; McAdams, Daniel; Podolsky, Matthew J; Fernandez, Daniel E; Farkas, Dana; Christian, James F

2016-02-01

Diffuse correlation spectroscopy (DCS) is a technique which enables powerful and robust non-invasive optical studies of tissue micro-circulation and vascular blood flow. The technique amounts to autocorrelation analysis of coherent photons after their migration through moving scatterers and subsequent collection by single-mode optical fibers. A primary cost driver of DCS instruments are the commercial hardware-based correlators, limiting the proliferation of multi-channel instruments for validation of perfusion analysis as a clinical diagnostic metric. We present the development of a low-cost scalable correlator enabled by microchip-based time-tagging, and a software-based multi-tau data analysis method. We will discuss the capabilities of the instrument as well as the implementation and validation of 2- and 8-channel systems built for live animal and pre-clinical settings.

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

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

Guo, Yang; Sivalingam, Kantharuban; Neese, Frank, E-mail: Frank.Neese@cec.mpg.de

2016-03-07

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still twomore » important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling “partially contracted” NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient “electron pair prescreening” that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.« less

Teaching the Principles of Economics: Reconciling the Canon of the American Economics Association to Catholic Social Thought

ERIC Educational Resources Information Center

Meador, Douglas

2013-01-01

The American Economics Association, through its Committee on Economic Education, has worked since 1950 to develop a set of standards for what is taught in introductory economics courses. The result is the Test for Understanding in College Economics. The TUCE has come to define a canon of expectations for students in college business schools. Some…

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials.

PubMed

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A; Burgueño, Juan; Bandeira E Sousa, Massaine; Crossa, José

2018-03-28

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines ([Formula: see text]) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. Copyright © 2018 Cuevas et al.

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

PubMed Central

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA.

PubMed

Rabiul Islam, Md; Khademul Islam Molla, Md; Nakanishi, Masaki; Tanaka, Toshihisa

2017-04-01

Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, as the number of commands increases. This paper develops a novel unsupervised method based on canonical correlation analysis (CCA) for accurate detection of stimulus frequency. A novel unsupervised technique termed as binary subband CCA (BsCCA) is implemented in a multiband approach to enhance the frequency recognition performance of SSVEP. In BsCCA, two subbands are used and a CCA-based correlation coefficient is computed for the individual subbands. In addition, a reduced set of artificial reference signals is used to calculate CCA for the second subband. The analyzing SSVEP is decomposed into multiple subband and the BsCCA is implemented for each one. Then, the overall recognition score is determined by a weighted sum of the canonical correlation coefficients obtained from each band. A 12-class SSVEP dataset (frequency range: 9.25-14.75 Hz with an interval of 0.5 Hz) for ten healthy subjects are used to evaluate the performance of the proposed method. The results suggest that BsCCA significantly improves the performance of SSVEP-based BCI compared to the state-of-the-art methods. The proposed method is an unsupervised approach with averaged information transfer rate (ITR) of 77.04 bits min -1 across 10 subjects. The maximum individual ITR is 107.55 bits min -1 for 12-class SSVEP dataset, whereas, the ITR of 69.29 and 69.44 bits min -1 are achieved with CCA and NCCA respectively. The statistical test shows that the proposed unsupervised method significantly improves the performance of the SSVEP-based BCI. It can be usable in real world applications.

Coherent population transfer in multi-level Allen-Eberly models

NASA Astrophysics Data System (ADS)

Li, Wei; Cen, Li-Xiang

2018-04-01

We investigate the solvability of multi-level extensions of the Allen-Eberly model and the population transfer yielded by the corresponding dynamical evolution. We demonstrate that, under a matching condition of the frequency, the driven two-level system and its multi-level extensions possess a stationary-state solution in a canonical representation associated with a unitary transformation. As a consequence, we show that the resulting protocol is able to realize complete population transfer in a nonadiabatic manner. Moreover, we explore the imperfect pulsing process with truncation and display that the nonadiabatic effect in the evolution can lead to suppression to the cutoff error of the protocol.

Thermodynamics of Computational Copying in Biochemical Systems

NASA Astrophysics Data System (ADS)

Ouldridge, Thomas E.; Govern, Christopher C.; ten Wolde, Pieter Rein

2017-04-01

Living cells use readout molecules to record the state of receptor proteins, similar to measurements or copies in typical computational devices. But is this analogy rigorous? Can cells be optimally efficient, and if not, why? We show that, as in computation, a canonical biochemical readout network generates correlations; extracting no work from these correlations sets a lower bound on dissipation. For general input, the biochemical network cannot reach this bound, even with arbitrarily slow reactions or weak thermodynamic driving. It faces an accuracy-dissipation trade-off that is qualitatively distinct from and worse than implied by the bound, and more complex steady-state copy processes cannot perform better. Nonetheless, the cost remains close to the thermodynamic bound unless accuracy is extremely high. Additionally, we show that biomolecular reactions could be used in thermodynamically optimal devices under exogenous manipulation of chemical fuels, suggesting an experimental system for testing computational thermodynamics.

Lymphotoxin β receptor activation promotes bladder cancer in a nuclear factor-κB-dependent manner.

PubMed

Shen, Mo; Duan, Xiuzhi; Zhou, Ping; Zhou, Wu; Wu, Xiuling; Xu, Siqi; Chen, Yuhua; Tao, Zhihua

2015-02-01

Bladder cancer (BCa) is the most common tumor of the urinary system. Chronic inflammation in the papillary urothelial neoplasm of low malignant potential (PUNLMP)may contribute to carcinogenesis, including that of BCa, via poorly understood mechanisms. In this study, we show that the lymphotoxin β receptor (LTβR) is upregulated in BCa via activation of the canonical and non-canonical nuclear factor-κB (NF-κB) pathways. The mRNA expression of LTβR in 81 BCa, 10 chronic cystitis and 23 healthy bladder mucosa tissues was investigated by reverse transcription-fluorescent quantitative polymerase chain reaction (RT-FQ-PCR), and protein expression was studied in 73 BCa, 30 cystitis and 15 healthy paraffin-embedded tissue sections by immunohistochemistry. Both LTβR mRNA and protein were upregulated in BCa and cystitis compared to the healthy group (P<0.05). The mRNA level of the downstream NF-κB canonical pathway p65 gene and of the non-canonical pathway RelB gene were higher in the BCa and cystitis groups compared to the healthy one. The level of phosphorylated p65 (p-p65) protein of the canonical NF-κB pathway and that of p52, a protein of the non-canonical NF-κB pathway, were also higher in the BCa and cystitis group compared to the healthy group. The levels of these proteins significantly correlated to the pathological grade, clinical stage and lymph node metastasis of BCa patients (P<0.05). In addition, there was a positive correlation between LTβR and NF-κB pathway proteins. Thus, LTβR signaling may be involved in promoting BCa through the NF-κB pathway, and which may represent the molecular link between inflammation and BCa.

Factor Analysis and Counseling Research

ERIC Educational Resources Information Center

Weiss, David J.

1970-01-01

Topics discussed include factor analysis versus cluster analysis, analysis of Q correlation matrices, ipsativity and factor analysis, and tests for the significance of a correlation matrix prior to application of factor analytic techniques. Techniques for factor extraction discussed include principal components, canonical factor analysis, alpha…

Dimensions of Intuition: First-Round Validation Studies

ERIC Educational Resources Information Center

Vrugtman, Rosanne

2009-01-01

This study utilized confirmatory factor analysis (CFA), canonical correlation analysis (CCA), regression analysis (RA), and correlation analysis (CA) for first-round validation of the researcher's Dimensions of Intuition (DOI) instrument. The DOI examined 25 personal characteristics and situations purportedly predictive of intuition. Data was…

Motivation and Burnout in Professional Rugby Players

ERIC Educational Resources Information Center

Cresswell, Scott L.; Eklund, Robert C.

2005-01-01

The authors examined relationships among burnout and motivational types differing in self-determination, using simple correlational analyses as well as more sophisticated canonical correlation analyses allowing for the simultaneous examination of multiple independent and dependent variables. The authors hypothesized that: (a) motivation low in…

Patterns of Student Growth in Reasoning about Multivariate Correlational Problems.

ERIC Educational Resources Information Center

Ross, John A.; Cousins, J. Bradley

Previous studies of the development of correlational reasoning have focused on the interpretation of relatively simple data sets contained in 2 X 2 tables. In contrast, this study examined age trends in subjects' responses to problems involving more than two continuous variables. The research is part of a multi-year project to conceptualize…

Facial Phenotyping by Quantitative Photography Reflects Craniofacial Morphology Measured on Magnetic Resonance Imaging in Icelandic Sleep Apnea Patients

PubMed Central

Sutherland, Kate; Schwab, Richard J.; Maislin, Greg; Lee, Richard W.W.; Benedikstdsottir, Bryndis; Pack, Allan I.; Gislason, Thorarinn; Juliusson, Sigurdur; Cistulli, Peter A.

2014-01-01

Study Objectives: (1) To determine whether facial phenotype, measured by quantitative photography, relates to underlying craniofacial obstructive sleep apnea (OSA) risk factors, measured with magnetic resonance imaging (MRI); (2) To assess whether these associations are independent of body size and obesity. Design: Cross-sectional cohort. Setting: Landspitali, The National University Hospital, Iceland. Participants: One hundred forty patients (87.1% male) from the Icelandic Sleep Apnea Cohort who had both calibrated frontal and profile craniofacial photographs and upper airway MRI. Mean ± standard deviation age 56.1 ± 10.4 y, body mass index 33.5 ± 5.05 kg/m2, with on-average severe OSA (apnea-hypopnea index 45.4 ± 19.7 h-1). Interventions: N/A. Measurements and Results: Relationships between surface facial dimensions (photos) and facial bony dimensions and upper airway soft-tissue volumes (MRI) was assessed using canonical correlation analysis. Photo and MRI craniofacial datasets related in four significant canonical correlations, primarily driven by measurements of (1) maxillary-mandibular relationship (r = 0.8, P < 0.0001), (2) lower face height (r = 0.76, P < 0.0001), (3) mandibular length (r = 0.67, P < 0.0001), and (4) tongue volume (r = 0.52, P = 0.01). Correlations 1, 2, and 3 were unchanged when controlled for weight and neck and waist circumference. However, tongue volume was no longer significant, suggesting facial dimensions relate to tongue volume as a result of obesity. Conclusions: Significant associations were found between craniofacial variable sets from facial photography and MRI. This study confirms that facial photographic phenotype reflects underlying aspects of craniofacial skeletal abnormalities associated with OSA. Therefore, facial photographic phenotyping may be a useful tool to assess intermediate phenotypes for OSA, particularly in large-scale studies. Citation: Sutherland K, Schwab RJ, Maislin G, Lee RW, Benedikstdsottir B, Pack AI, Gislason T, Juliusson S, Cistulli PA. Facial phenotyping by quantitative photography reflects craniofacial morphology measured on magnetic resonance imaging in icelandic sleep apnea patients. SLEEP 2014;37(5):959-968. PMID:24790275

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Gui-Long

2001-01-01

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses

PubMed Central

Stephen, Emily P.; Lepage, Kyle Q.; Eden, Uri T.; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S.; Guenther, Frank H.; Kramer, Mark A.

2014-01-01

The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty—both in the functional network edges and the corresponding aggregate measures of network topology—are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here—appropriate for static and dynamic network inference and different statistical measures of coupling—permits the evaluation of confidence in network measures in a variety of settings common to neuroscience. PMID:24678295

Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses.

PubMed

Stephen, Emily P; Lepage, Kyle Q; Eden, Uri T; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S; Guenther, Frank H; Kramer, Mark A

2014-01-01

The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty-both in the functional network edges and the corresponding aggregate measures of network topology-are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here-appropriate for static and dynamic network inference and different statistical measures of coupling-permits the evaluation of confidence in network measures in a variety of settings common to neuroscience.

Structural and evolutionary relationships of "AT-less" type I polyketide synthase ketosynthases.

PubMed

Lohman, Jeremy R; Ma, Ming; Osipiuk, Jerzy; Nocek, Boguslaw; Kim, Youngchang; Chang, Changsoo; Cuff, Marianne; Mack, Jamey; Bigelow, Lance; Li, Hui; Endres, Michael; Babnigg, Gyorgy; Joachimiak, Andrzej; Phillips, George N; Shen, Ben

2015-10-13

Acyltransferase (AT)-less type I polyketide synthases (PKSs) break the type I PKS paradigm. They lack the integrated AT domains within their modules and instead use a discrete AT that acts in trans, whereas a type I PKS module minimally contains AT, acyl carrier protein (ACP), and ketosynthase (KS) domains. Structures of canonical type I PKS KS-AT didomains reveal structured linkers that connect the two domains. AT-less type I PKS KSs have remnants of these linkers, which have been hypothesized to be AT docking domains. Natural products produced by AT-less type I PKSs are very complex because of an increased representation of unique modifying domains. AT-less type I PKS KSs possess substrate specificity and fall into phylogenetic clades that correlate with their substrates, whereas canonical type I PKS KSs are monophyletic. We have solved crystal structures of seven AT-less type I PKS KS domains that represent various sequence clusters, revealing insight into the large structural and subtle amino acid residue differences that lead to unique active site topologies and substrate specificities. One set of structures represents a larger group of KS domains from both canonical and AT-less type I PKSs that accept amino acid-containing substrates. One structure has a partial AT-domain, revealing the structural consequences of a type I PKS KS evolving into an AT-less type I PKS KS. These structures highlight the structural diversity within the AT-less type I PKS KS family, and most important, provide a unique opportunity to study the molecular evolution of substrate specificity within the type I PKSs.

Structural and evolutionary relationships of “AT-less” type I polyketide synthase ketosynthases

PubMed Central

Lohman, Jeremy R.; Ma, Ming; Osipiuk, Jerzy; Nocek, Boguslaw; Kim, Youngchang; Chang, Changsoo; Cuff, Marianne; Mack, Jamey; Bigelow, Lance; Li, Hui; Endres, Michael; Babnigg, Gyorgy; Joachimiak, Andrzej; Phillips, George N.; Shen, Ben

2015-01-01

Acyltransferase (AT)-less type I polyketide synthases (PKSs) break the type I PKS paradigm. They lack the integrated AT domains within their modules and instead use a discrete AT that acts in trans, whereas a type I PKS module minimally contains AT, acyl carrier protein (ACP), and ketosynthase (KS) domains. Structures of canonical type I PKS KS-AT didomains reveal structured linkers that connect the two domains. AT-less type I PKS KSs have remnants of these linkers, which have been hypothesized to be AT docking domains. Natural products produced by AT-less type I PKSs are very complex because of an increased representation of unique modifying domains. AT-less type I PKS KSs possess substrate specificity and fall into phylogenetic clades that correlate with their substrates, whereas canonical type I PKS KSs are monophyletic. We have solved crystal structures of seven AT-less type I PKS KS domains that represent various sequence clusters, revealing insight into the large structural and subtle amino acid residue differences that lead to unique active site topologies and substrate specificities. One set of structures represents a larger group of KS domains from both canonical and AT-less type I PKSs that accept amino acid-containing substrates. One structure has a partial AT-domain, revealing the structural consequences of a type I PKS KS evolving into an AT-less type I PKS KS. These structures highlight the structural diversity within the AT-less type I PKS KS family, and most important, provide a unique opportunity to study the molecular evolution of substrate specificity within the type I PKSs. PMID:26420866

Relationships between self-determination theory and theory of planned behavior applied to physical activity and exercise behavior in chronic pain.

PubMed

Brooks, Jessica M; Iwanaga, Kanako; Chiu, Chung-Yi; Cotton, Brandi Parker; Deiches, Jon; Morrison, Blaise; Moser, Erin; Chan, Fong

2017-08-01

This study examined the relationships between self-determination theory (SDT) and theory of planned behavior (TpB) applied to physical activity and exercise behavior (PA&E) in people with chronic pain. Two hundred and eleven adults with chronic musculoskeletal pain (28 males and 183 females, age range 18 to 82 years, mean age 43 years) were recruited from online support groups and clinic networks in the United States. Participants completed SDT measures relevant to PA&E on perceived autonomy support, autonomy, competence, and relatedness, as well as TpB measures relevant to PA&E on intention, attitudes, subjective norms, and perceived behavioral control. Correlational techniques and canonical correlation analysis were performed to examine the relationships and variance within and between theoretical dimensions. Overall, the SDT set accounted for 37% of the TpB variance and the TpB set accounted for 32% of the SDT set variance. The results indicate there are statistical similarities and differences between concepts in SDT and TpB models for PA&E. Using both empirical guidance and clinical expertise, researchers and practitioners should attempt to select and integrate non-redundant and complementary components from SDT, TpB, and other related health behavior theories.

A multi-time-step noise reduction method for measuring velocity statistics from particle tracking velocimetry

NASA Astrophysics Data System (ADS)

Machicoane, Nathanaël; López-Caballero, Miguel; Bourgoin, Mickael; Aliseda, Alberto; Volk, Romain

2017-10-01

We present a method to improve the accuracy of velocity measurements for fluid flow or particles immersed in it, based on a multi-time-step approach that allows for cancellation of noise in the velocity measurements. Improved velocity statistics, a critical element in turbulent flow measurements, can be computed from the combination of the velocity moments computed using standard particle tracking velocimetry (PTV) or particle image velocimetry (PIV) techniques for data sets that have been collected over different values of time intervals between images. This method produces Eulerian velocity fields and Lagrangian velocity statistics with much lower noise levels compared to standard PIV or PTV measurements, without the need of filtering and/or windowing. Particle displacement between two frames is computed for multiple different time-step values between frames in a canonical experiment of homogeneous isotropic turbulence. The second order velocity structure function of the flow is computed with the new method and compared to results from traditional measurement techniques in the literature. Increased accuracy is also demonstrated by comparing the dissipation rate of turbulent kinetic energy measured from this function against previously validated measurements.

Analytic energy derivatives for the calculation of the first-order molecular properties using the domain-based local pair-natural orbital coupled-cluster theory

NASA Astrophysics Data System (ADS)

Datta, Dipayan; Kossmann, Simone; Neese, Frank

2016-09-01

The domain-based local pair-natural orbital coupled-cluster (DLPNO-CC) theory has recently emerged as an efficient and powerful quantum-chemical method for the calculation of energies of molecules comprised of several hundred atoms. It has been demonstrated that the DLPNO-CC approach attains the accuracy of a standard canonical coupled-cluster calculation to about 99.9% of the basis set correlation energy while realizing linear scaling of the computational cost with respect to system size. This is achieved by combining (a) localized occupied orbitals, (b) large virtual orbital correlation domains spanned by the projected atomic orbitals (PAOs), and (c) compaction of the virtual space through a truncated pair natural orbital (PNO) basis. In this paper, we report on the implementation of an analytic scheme for the calculation of the first derivatives of the DLPNO-CC energy for basis set independent perturbations within the singles and doubles approximation (DLPNO-CCSD) for closed-shell molecules. Perturbation-independent one-particle density matrices have been implemented in order to account for the response of the CC wave function to the external perturbation. Orbital-relaxation effects due to external perturbation are not taken into account in the current implementation. We investigate in detail the dependence of the computed first-order electrical properties (e.g., dipole moment) on the three major truncation parameters used in a DLPNO-CC calculation, namely, the natural orbital occupation number cutoff used for the construction of the PNOs, the weak electron-pair cutoff, and the domain size cutoff. No additional truncation parameter has been introduced for property calculation. We present benchmark calculations on dipole moments for a set of 10 molecules consisting of 20-40 atoms. We demonstrate that 98%-99% accuracy relative to the canonical CCSD results can be consistently achieved in these calculations. However, this comes with the price of tightening the threshold for the natural orbital occupation number cutoff by an order of magnitude compared to the DLPNO-CCSD energy calculations.

Recent applications of THERMUS

NASA Astrophysics Data System (ADS)

Wheaton, S.; Hauer, M.

2011-12-01

Some of the most recent applications of the statistical-thermal model package, THERMUS, are reviewed. These applications focus on fluctuation and correlation observables in an ideal particle and anti-particle gas in limited momentum space segments, as well as in a hadron resonance gas. In the case of the latter, a Monte Carlo event generator, utilising THERMUS functionality and assuming thermal production of hadrons, is discussed. The system under consideration is sampled grand canonically in the Boltzmann approximation. A re-weighting scheme is then introduced to account for conservation of charges (baryon number, strangeness, electric charge) and energy and momentum, effectively allowing for extrapolation of grand canonical results to the micro canonical limit. The approach utilised in this and other applications suggests improvements to existing THERMUS calculations.

What can nuclear collisions teach us about the boiling of water or the formation of multi-star systems

NASA Astrophysics Data System (ADS)

Gross, D. H. E.

2001-11-01

Phase transitions in nuclei, small atomic clusters and self-gravitating systems demand the extension of thermo-statistics to "Small" systems. The main obstacle is the thermodynamic limit. It is shown how the original definition of the entropy by Boltzmann as the volume of the energy-manifold of the N-body phase space allows a geometrical definition of the entropy as function of the conserved quantities. Without invoking the thermodynamic limit the whole "zoo" of phase transitions and critical points/lines can be unambiguously defined. The relation to the Yang-Lee singularities of the grand-canonical partition sum is pointed out. It is shown that just phase transitions in non-extensive systems give the complete set of characteristic parameters of the transition including the surface tension. Nuclear heavy-ion collisions are an experimental playground to explore this extension of thermo-statistics

An approach for generating trajectory-based dynamics which conserves the canonical distribution in the phase space formulation of quantum mechanics. II. Thermal correlation functions.

PubMed

Liu, Jian; Miller, William H

2011-03-14

We show the exact expression of the quantum mechanical time correlation function in the phase space formulation of quantum mechanics. The trajectory-based dynamics that conserves the quantum canonical distribution-equilibrium Liouville dynamics (ELD) proposed in Paper I is then used to approximately evaluate the exact expression. It gives exact thermal correlation functions (of even nonlinear operators, i.e., nonlinear functions of position or momentum operators) in the classical, high temperature, and harmonic limits. Various methods have been presented for the implementation of ELD. Numerical tests of the ELD approach in the Wigner or Husimi phase space have been made for a harmonic oscillator and two strongly anharmonic model problems, for each potential autocorrelation functions of both linear and nonlinear operators have been calculated. It suggests ELD can be a potentially useful approach for describing quantum effects for complex systems in condense phase.

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

Predicting drug side-effect profiles: a chemical fragment-based approach

PubMed Central

2011-01-01

Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169

An integrated brain-behavior model for working memory.

PubMed

Moser, D A; Doucet, G E; Ing, A; Dima, D; Schumann, G; Bilder, R M; Frangou, S

2017-12-05

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral-health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network.Molecular Psychiatry advance online publication, 5 December 2017; doi:10.1038/mp.2017.247.

Protein linear indices of the 'macromolecular pseudograph alpha-carbon atom adjacency matrix' in bioinformatics. Part 1: prediction of protein stability effects of a complete set of alanine substitutions in Arc repressor.

PubMed

Marrero-Ponce, Yovani; Medina-Marrero, Ricardo; Castillo-Garit, Juan A; Romero-Zaldivar, Vicente; Torrens, Francisco; Castro, Eduardo A

2005-04-15

A novel approach to bio-macromolecular design from a linear algebra point of view is introduced. A protein's total (whole protein) and local (one or more amino acid) linear indices are a new set of bio-macromolecular descriptors of relevance to protein QSAR/QSPR studies. These amino-acid level biochemical descriptors are based on the calculation of linear maps on Rn[f k(xmi):Rn-->Rn] in canonical basis. These bio-macromolecular indices are calculated from the kth power of the macromolecular pseudograph alpha-carbon atom adjacency matrix. Total linear indices are linear functional on Rn. That is, the kth total linear indices are linear maps from Rn to the scalar R[f k(xm):Rn-->R]. Thus, the kth total linear indices are calculated by summing the amino-acid linear indices of all amino acids in the protein molecule. A study of the protein stability effects for a complete set of alanine substitutions in the Arc repressor illustrates this approach. A quantitative model that discriminates near wild-type stability alanine mutants from the reduced-stability ones in a training series was obtained. This model permitted the correct classification of 97.56% (40/41) and 91.67% (11/12) of proteins in the training and test set, respectively. It shows a high Matthews correlation coefficient (MCC=0.952) for the training set and an MCC=0.837 for the external prediction set. Additionally, canonical regression analysis corroborated the statistical quality of the classification model (Rcanc=0.824). This analysis was also used to compute biological stability canonical scores for each Arc alanine mutant. On the other hand, the linear piecewise regression model compared favorably with respect to the linear regression one on predicting the melting temperature (tm) of the Arc alanine mutants. The linear model explains almost 81% of the variance of the experimental tm (R=0.90 and s=4.29) and the LOO press statistics evidenced its predictive ability (q2=0.72 and scv=4.79). Moreover, the TOMOCOMD-CAMPS method produced a linear piecewise regression (R=0.97) between protein backbone descriptors and tm values for alanine mutants of the Arc repressor. A break-point value of 51.87 degrees C characterized two mutant clusters and coincided perfectly with the experimental scale. For this reason, we can use the linear discriminant analysis and piecewise models in combination to classify and predict the stability of the mutant Arc homodimers. These models also permitted the interpretation of the driving forces of such folding process, indicating that topologic/topographic protein backbone interactions control the stability profile of wild-type Arc and its alanine mutants.

Correlated Hopping in the 1D Falicov--Kimball Model

NASA Astrophysics Data System (ADS)

Gajek, Z.; Lemanski, R.

2001-10-01

Ground state phase diagrams in the canonical ensemble of the one-dimensional Falicov-Kimball Model (FKM) with the correlated hopping are presented for several values of the model parameters. As compare to the conventional FKM, the diagrams exhibit a loss of the particle--hole symmetry.

Multi-way chemometric methodologies and applications: a central summary of our research work.

PubMed

Wu, Hai-Long; Nie, Jin-Fang; Yu, Yong-Jie; Yu, Ru-Qin

2009-09-14

Multi-way data analysis and tensorial calibration are gaining widespread acceptance with the rapid development of modern analytical instruments. In recent years, our group working in State Key Laboratory of Chemo/Biosensing and Chemometrics in Hunan University has carried out exhaustive scientific research work in this area, such as building more canonical symbol systems, seeking the inner mathematical cyclic symmetry property for trilinear or multilinear decomposition, suggesting a series of multi-way calibration algorithms, exploring the rank estimation of three-way trilinear data array and analyzing different application systems. In this present paper, an overview from second-order data to third-order data covering about theories and applications in analytical chemistry has been presented.

A Hierarchical Model for Simultaneous Detection and Estimation in Multi-subject fMRI Studies

PubMed Central

Degras, David; Lindquist, Martin A.

2014-01-01

In this paper we introduce a new hierarchical model for the simultaneous detection of brain activation and estimation of the shape of the hemodynamic response in multi-subject fMRI studies. The proposed approach circumvents a major stumbling block in standard multi-subject fMRI data analysis, in that it both allows the shape of the hemodynamic response function to vary across region and subjects, while still providing a straightforward way to estimate population-level activation. An e cient estimation algorithm is presented, as is an inferential framework that not only allows for tests of activation, but also for tests for deviations from some canonical shape. The model is validated through simulations and application to a multi-subject fMRI study of thermal pain. PMID:24793829

The any particle molecular orbital grid-based Hartree-Fock (APMO-GBHF) approach

NASA Astrophysics Data System (ADS)

Posada, Edwin; Moncada, Félix; Reyes, Andrés

2018-02-01

The any particle molecular orbital grid-based Hartree-Fock approach (APMO-GBHF) is proposed as an initial step to perform multi-component post-Hartree-Fock, explicitly correlated, and density functional theory methods without basis set errors. The method has been applied to a number of electronic and multi-species molecular systems. Results of these calculations show that the APMO-GBHF total energies are comparable with those obtained at the APMO-HF complete basis set limit. In addition, results reveal a considerable improvement in the description of the nuclear cusps of electronic and non-electronic densities.

Adolescents' Faith Commitments as Correlates of Their Involvement in Christian Service

ERIC Educational Resources Information Center

Nagy, Andrea; Ostrander, Raymond; Kijai, Jimmy; Matthews, John

2017-01-01

This study sought to determine the relationship between adolescents' involvement in service to others and their commitment to religious values and Seventh-day Adventist beliefs. Canonical correlation indicated that adolescents' involvement in service to others is significantly related to their commitment to religious values and beliefs. Results…

Recursive analytical solution describing artificial satellite motion perturbed by an arbitrary number of zonal terms

NASA Technical Reports Server (NTRS)

Mueller, A. C.

1977-01-01

An analytical first order solution has been developed which describes the motion of an artificial satellite perturbed by an arbitrary number of zonal harmonics of the geopotential. A set of recursive relations for the solution, which was deduced from recursive relations of the geopotential, was derived. The method of solution is based on Von-Zeipel's technique applied to a canonical set of two-body elements in the extended phase space which incorporates the true anomaly as a canonical element. The elements are of Poincare type, that is, they are regular for vanishing eccentricities and inclinations. Numerical results show that this solution is accurate to within a few meters after 500 revolutions.

The Ecology of Early Childhood Risk: A Canonical Correlation Analysis of Children’s Adjustment, Family, and Community Context in a High-Risk Sample

PubMed Central

Aiyer, Sophie M.; Wilson, Melvin N.; Shaw, Daniel S.; Dishion, Thomas J.

2013-01-01

The ecology of the emergence of psycho-pathology in early childhood is often approached by the analysis of a limited number of contextual risk factors. In the present study, we provide a comprehensive analysis of ecological risk by conducting a canonical correlation analysis of 13 risk factors at child age 2 and seven narrow-band scales of internalizing and externalizing problem behaviors at child age 4, using a sample of 364 geographically and ethnically diverse, disadvantaged primary caregivers, alternative caregivers, and preschool-age children. Participants were recruited from Special Supplemental Nutrition Program for Women, Infants, and Children sites and were screened for family risk. Canonical correlation analysis revealed that (1) a first latent combination of family and individual risks of caregivers predicted combinations of child emotional and behavioral problems, and that (2) a second latent combination of contextual and structural risks predicted child somatic complaints. Specifically, (1) the combination of chaotic home, conflict with child, parental depression, and parenting hassles predicted a co-occurrence of internalizing and externalizing behaviors, and (2) the combination of father absence, perceived discrimination, neighborhood danger, and fewer children living in the home predicted child somatic complaints. The research findings are discussed in terms of the development of psychopathology, as well as the potential prevention needs of families in high-risk contexts. PMID:23700232

Multidimensional correlation among plan complexity, quality and deliverability parameters for volumetric-modulated arc therapy using canonical correlation analysis.

PubMed

Shen, Lanxiao; Chen, Shan; Zhu, Xiaoyang; Han, Ce; Zheng, Xiaomin; Deng, Zhenxiang; Zhou, Yongqiang; Gong, Changfei; Xie, Congying; Jin, Xiance

2018-03-01

A multidimensional exploratory statistical method, canonical correlation analysis (CCA), was applied to evaluate the impact of complexity parameters on the plan quality and deliverability of volumetric-modulated arc therapy (VMAT) and to determine parameters in the generation of an ideal VMAT plan. Canonical correlations among complexity, quality and deliverability parameters of VMAT, as well as the contribution weights of different parameters were investigated with 71 two-arc VMAT nasopharyngeal cancer (NPC) patients, and further verified with 28 one-arc VMAT prostate cancer patients. The average MU and MU per control point (MU/CP) for two-arc VMAT plans were 702.6 ± 55.7 and 3.9 ± 0.3 versus 504.6 ± 99.2 and 5.6 ± 1.1 for one-arc VMAT plans, respectively. The individual volume-based 3D gamma passing rates of clinical target volume (γCTV) and planning target volume (γPTV) for NPC and prostate cancer patients were 85.7% ± 9.0% vs 92.6% ± 7.8%, and 88.0% ± 7.6% vs 91.2% ± 7.7%, respectively. Plan complexity parameters of NPC patients were correlated with plan quality (P = 0.047) and individual volume-based 3D gamma indices γ(IV) (P = 0.01), in which, MU/CP and segment area (SA) per control point (SA/CP) were weighted highly in correlation with γ(IV) , and SA/CP, percentage of CPs with SA < 5 × 5 cm2 (%SA < 5 × 5 cm2) and PTV volume were weighted highly in correlation with plan quality with coefficients of 0.98, 0.68 and -0.99, respectively. Further verification with one-arc VMAT plans demonstrated similar results. In conclusion, MU, SA-related parameters and PTV volume were found to have strong effects on the plan quality and deliverability.

Multidimensional correlation among plan complexity, quality and deliverability parameters for volumetric-modulated arc therapy using canonical correlation analysis

PubMed Central

Shen, Lanxiao; Chen, Shan; Zhu, Xiaoyang; Han, Ce; Zheng, Xiaomin; Deng, Zhenxiang; Zhou, Yongqiang; Gong, Changfei; Jin, Xiance

2018-01-01

Abstract A multidimensional exploratory statistical method, canonical correlation analysis (CCA), was applied to evaluate the impact of complexity parameters on the plan quality and deliverability of volumetric-modulated arc therapy (VMAT) and to determine parameters in the generation of an ideal VMAT plan. Canonical correlations among complexity, quality and deliverability parameters of VMAT, as well as the contribution weights of different parameters were investigated with 71 two-arc VMAT nasopharyngeal cancer (NPC) patients, and further verified with 28 one-arc VMAT prostate cancer patients. The average MU and MU per control point (MU/CP) for two-arc VMAT plans were 702.6 ± 55.7 and 3.9 ± 0.3 versus 504.6 ± 99.2 and 5.6 ± 1.1 for one-arc VMAT plans, respectively. The individual volume-based 3D gamma passing rates of clinical target volume (γCTV) and planning target volume (γPTV) for NPC and prostate cancer patients were 85.7% ± 9.0% vs 92.6% ± 7.8%, and 88.0% ± 7.6% vs 91.2% ± 7.7%, respectively. Plan complexity parameters of NPC patients were correlated with plan quality (P = 0.047) and individual volume-based 3D gamma indices γ(IV) (P = 0.01), in which, MU/CP and segment area (SA) per control point (SA/CP) were weighted highly in correlation with γ(IV) , and SA/CP, percentage of CPs with SA < 5 × 5 cm2 (%SA < 5 × 5 cm2) and PTV volume were weighted highly in correlation with plan quality with coefficients of 0.98, 0.68 and −0.99, respectively. Further verification with one-arc VMAT plans demonstrated similar results. In conclusion, MU, SA-related parameters and PTV volume were found to have strong effects on the plan quality and deliverability. PMID:29415196

Molecular dynamics of liquid crystals

NASA Astrophysics Data System (ADS)

Sarman, Sten

1997-02-01

We derive Green-Kubo relations for the viscosities of a nematic liquid crystal. The derivation is based on the application of a Gaussian constraint algorithm that makes the director angular velocity of a liquid crystal a constant of motion. Setting this velocity equal to zero means that a director-based coordinate system becomes an inertial frame and that the constraint torques do not do any work on the system. The system consequently remains in equilibrium. However, one generates a different equilibrium ensemble. The great advantage of this ensemble is that the Green-Kubo relations for the viscosities become linear combinations of time correlation function integrals, whereas they are complicated rational functions in the conventional canonical ensemble. This facilitates the numerical evaluation of the viscosities by molecular dynamics simulations.

The Eye of a Mathematical Physicist

NASA Astrophysics Data System (ADS)

Hepp, Klaus

2009-03-01

In this essay we are searching for neural correlates of `doing mathematical physics'. We introduce a toy model of a mathematical physicist, a brain connected with the outside world only by vision and saccadic eye movements and interacting with a computer screen. First, we describe the neuroanatomy of the visuo-saccadic system and Listing's law, which binds saccades and the optics of the eye. Then we explain space-time transformations in the superior colliculus, the performance of a canonical cortical circuit in the frontal eye field and finally the recurrent interaction of both areas, which leads to a coherent percept of space in spite of saccades. This sets the stage in the brain for doing mathematical physics, which is analyzed in simple examples.

The linkage between geopotential height and monthly precipitation in Iran

NASA Astrophysics Data System (ADS)

Shirvani, Amin; Fadaei, Amir Sabetan; Landman, Willem A.

2018-04-01

This paper investigates the linkage between large-scale atmospheric circulation and monthly precipitation during November to April over Iran. Canonical correlation analysis (CCA) is used to set up the statistical linkage between the 850 hPa geopotential height large-scale circulation and monthly precipitation over Iran for the period 1968-2010. The monthly precipitation dataset for 50 synoptic stations distributed in different climate regions of Iran is considered as the response variable in the CCA. The monthly geopotential height reanalysis dataset over an area between 10° N and 60° N and from 20° E to 80° E is utilized as the explanatory variable in the CCA. Principal component analysis (PCA) as a pre-filter is used for data reduction for both explanatory and response variables before applying CCA. The optimal number of principal components and canonical variables to be retained in the CCA equations is determined using the highest average cross-validated Kendall's tau value. The 850 hPa geopotential height pattern over the Red Sea, Saudi Arabia, and Persian Gulf is found to be the major pattern related to Iranian monthly precipitation. The Pearson correlation between the area averaged of the observed and predicted precipitation over the study area for Jan, Feb, March, April, November, and December months are statistically significant at the 5% significance level and are 0.78, 0.80, 0.82, 0.74, 0.79, and 0.61, respectively. The relative operating characteristic (ROC) indicates that the highest scores for the above- and below-normal precipitation categories are, respectively, for February and April and the lowest scores found for December.

Clustering of local group distances: publication bias or correlated measurements? I. The large Magellanic cloud

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

De Grijs, Richard; Wicker, James E.; Bono, Giuseppe

2014-05-01

The distance to the Large Magellanic Cloud (LMC) represents a key local rung of the extragalactic distance ladder yet the galaxy's distance modulus has long been an issue of contention, in particular in view of claims that most newly determined distance moduli cluster tightly—and with a small spread—around the 'canonical' distance modulus, (m – M){sub 0} = 18.50 mag. We compiled 233 separate LMC distance determinations published between 1990 and 2013. Our analysis of the individual distance moduli, as well as of their two-year means and standard deviations resulting from this largest data set of LMC distance moduli available tomore » date, focuses specifically on Cepheid and RR Lyrae variable-star tracer populations, as well as on distance estimates based on features in the observational Hertzsprung-Russell diagram. We conclude that strong publication bias is unlikely to have been the main driver of the majority of published LMC distance moduli. However, for a given distance tracer, the body of publications leading to the tightly clustered distances is based on highly non-independent tracer samples and analysis methods, hence leading to significant correlations among the LMC distances reported in subsequent articles. Based on a careful, weighted combination, in a statistical sense, of the main stellar population tracers, we recommend that a slightly adjusted canonical distance modulus of (m – M){sub 0} = 18.49 ± 0.09 mag be used for all practical purposes that require a general distance scale without the need for accuracies of better than a few percent.« less

Correlation of soil microbes and soil micro-environment under long-term safflower (Carthamus tinctorius L.) plantation in China.

PubMed

Lu, Shuang; Quan, Wang; Wang, Shao-Ming; Liu, Hong-Ling; Tan, Yong; Zeng, Guang-Ping; Zhang, Xia

2013-04-01

Microbial community structure and ecological functions are influenced by interactions between above and belowground biota. There is an urgent need for intensive monitoring of microbes feedback of soil micro-ecosystem for setting up a good agricultural practice. Recent researches have revealed that many soils characteristic can effect microbial community structure. In the present study factors affecting microbial community structure and soil in Carthamus tinctorius plantations in arid agricultural ecosystem of northern Xinjiang, China were identified. The result of the study revealed that soil type was the key factor in safflower yield; Unscientific field management resulted high fertility level (bacteria dominant) of soil to turn to low fertility level (fungi dominant), and Detruded Canonical Correspondence Analysis (DCCA) showed that soil water content, organic matter, available N, P and K were the dominant factors affecting distribution of microbial community. Soil water content showed a significant positive correlation with soil microbes quantity (P < 0.01), while others showed a significant quantity correlation with soil microbe quantity (P < 0.05).

Freezing behavior as a response to sexual visual stimuli as demonstrated by posturography.

PubMed

Mouras, Harold; Lelard, Thierry; Ahmaidi, Said; Godefroy, Olivier; Krystkowiak, Pierre

2015-01-01

Posturographic changes in motivational conditions remain largely unexplored in the context of embodied cognition. Over the last decade, sexual motivation has been used as a good canonical working model to study motivated social interactions. The objective of this study was to explore posturographic variations in response to visual sexual videos as compared to neutral videos. Our results support demonstration of a freezing-type response in response to sexually explicit stimuli compared to other conditions, as demonstrated by significantly decreased standard deviations for (i) the center of pressure displacement along the mediolateral and anteroposterior axes and (ii) center of pressure's displacement surface. These results support the complexity of the motor correlates of sexual motivation considered to be a canonical functional context to study the motor correlates of motivated social interactions.

Building Background Knowledge through Reading: Rethinking Text Sets

ERIC Educational Resources Information Center

Lupo, Sarah M.; Strong, John Z.; Lewis, William; Walpole, Sharon; McKenna, Michael C.

2018-01-01

To increase reading volume and help students access challenging texts, the authors propose a four-dimensional framework for text sets. The quad text set framework is designed around a target text: a challenging content area text, such as a canonical literary work, research article, or historical primary source document. The three remaining…

Environmental factors influence on chemical polymorphism of the essential oils of Lychnophora ericoides.

PubMed

Curado, Marco A; Oliveira, Carolina B A; Jesus, José G; Santos, Suzana C; Seraphin, José C; Ferri, Pedro H

2006-11-01

Lychnophora ericoides is a Brazilian medicinal plant used in folk medicine as an anti-inflammatory and analgesic agent. The essential oils from leaves of two populations with and without scent, collected at 2-month intervals during an 1-year period, were analysed by GC-MS. The results were submitted to principal component and cluster analysis which allowed two groups of essential oils to be distinguished with respect to sampling site and scent: cluster I (Vianópolis site, with specimens exhibiting an aromatic scent) containing a high percentage of alpha-bisabolol (44.7-76.4%) and alpha-cadinol (10.9-23.5%), and cluster II (Cristalina site, with specimens without scent) characterised by a high content of (E)-nerolidol (31.3-47.1%) and ar-dihydro-turmerone (4.8-15.4%). The canonical discriminant analysis showed that using the data set of the seven sampling months and (E)-nerolidol and alpha-bisabolol as predictable variables, it was possible to distinguish between the samples harvested according to Cerrado seasons, dry winter (May-September) and humid summer (November-March). In addition, canonical correlation analysis between the soil sampling sites and the populations revealed a significant relationship between oil components and edaphic factors. Oxygenated sesquiterpenes and potential acidity, Al saturation, cationic exchange capacity, silt, and sand load as the first canonical variate were fairly strongly related to samples collected in Vianópolis site. On the other hand, monoterpenes and sesquiterpene hydrocarbons were strongly related to chemical balance in soils (organic matter, P and base saturation), which is related to samples at the Cristalina site. The chemovariation observed appears to be environmentally determined.

Structural and evolutionary relationships of "AT-less" type I polyketide synthase ketosynthases

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

Lohman, Jeremy; Ma, Ming; Osipiuk, Jerzy

2015-10-13

Acyltransferase (AT)-less type I polyketide synthases (PKSs) break the type I PKS paradigm. They lack the integrated AT domains within their modules and instead use a discrete AT that acts in trans, whereas a type I PKS module minimally contains AT, acyl carrier protein (ACP), and ketosynthase (KS) domains. Structures of canonical type I PKS KS-AT didomains reveal structured linkers that connect the two domains. AT-less type I PKS KSs have remnants of these linkers, which have been hypothesized to be AT docking domains. Natural products produced by AT-less type I PKSs are very complex because of an increased representationmore » of unique modifying domains. AT-less type I PKS KSs possess substrate specificity and fall into phylogenetic clades that correlate with their substrates, whereas canonical type I PKS KSs are monophyletic. We have solved crystal structures of seven AT-less type I PKS KS domains that represent various sequence clusters, revealing insight into the large structural and subtle amino acid residue differences that lead to unique active site topologies and substrate specificities. One set of structures represents a larger group of KS domains from both canonical and AT-less type I PKSs that accept amino acid-containing substrates. One structure has a partial AT-domain, revealing the structural consequences of a type I PKS KS evolving into an AT-less type I PKS KS. These structures highlight the structural diversity within the AT-less type I PKS KS family, and most important, provide a unique opportunity to study the molecular evolution of substrate specificity within the type I PKSs.« less

The limitations of simple gene set enrichment analysis assuming gene independence.

PubMed

Tamayo, Pablo; Steinhardt, George; Liberzon, Arthur; Mesirov, Jill P

2016-02-01

Since its first publication in 2003, the Gene Set Enrichment Analysis method, based on the Kolmogorov-Smirnov statistic, has been heavily used, modified, and also questioned. Recently a simplified approach using a one-sample t-test score to assess enrichment and ignoring gene-gene correlations was proposed by Irizarry et al. 2009 as a serious contender. The argument criticizes Gene Set Enrichment Analysis's nonparametric nature and its use of an empirical null distribution as unnecessary and hard to compute. We refute these claims by careful consideration of the assumptions of the simplified method and its results, including a comparison with Gene Set Enrichment Analysis's on a large benchmark set of 50 datasets. Our results provide strong empirical evidence that gene-gene correlations cannot be ignored due to the significant variance inflation they produced on the enrichment scores and should be taken into account when estimating gene set enrichment significance. In addition, we discuss the challenges that the complex correlation structure and multi-modality of gene sets pose more generally for gene set enrichment methods. © The Author(s) 2012.

Visualising associations between paired ‘omics’ data sets

PubMed Central

2012-01-01

Background Each omics platform is now able to generate a large amount of data. Genomics, proteomics, metabolomics, interactomics are compiled at an ever increasing pace and now form a core part of the fundamental systems biology framework. Recently, several integrative approaches have been proposed to extract meaningful information. However, these approaches lack of visualisation outputs to fully unravel the complex associations between different biological entities. Results The multivariate statistical approaches ‘regularized Canonical Correlation Analysis’ and ‘sparse Partial Least Squares regression’ were recently developed to integrate two types of highly dimensional ‘omics’ data and to select relevant information. Using the results of these methods, we propose to revisit few graphical outputs to better understand the relationships between two ‘omics’ data and to better visualise the correlation structure between the different biological entities. These graphical outputs include Correlation Circle plots, Relevance Networks and Clustered Image Maps. We demonstrate the usefulness of such graphical outputs on several biological data sets and further assess their biological relevance using gene ontology analysis. Conclusions Such graphical outputs are undoubtedly useful to aid the interpretation of these promising integrative analysis tools and will certainly help in addressing fundamental biological questions and understanding systems as a whole. Availability The graphical tools described in this paper are implemented in the freely available R package mixOmics and in its associated web application. PMID:23148523

Parallel Grand Canonical Monte Carlo (ParaGrandMC) Simulation Code

NASA Technical Reports Server (NTRS)

Yamakov, Vesselin I.

2016-01-01

This report provides an overview of the Parallel Grand Canonical Monte Carlo (ParaGrandMC) simulation code. This is a highly scalable parallel FORTRAN code for simulating the thermodynamic evolution of metal alloy systems at the atomic level, and predicting the thermodynamic state, phase diagram, chemical composition and mechanical properties. The code is designed to simulate multi-component alloy systems, predict solid-state phase transformations such as austenite-martensite transformations, precipitate formation, recrystallization, capillary effects at interfaces, surface absorption, etc., which can aid the design of novel metallic alloys. While the software is mainly tailored for modeling metal alloys, it can also be used for other types of solid-state systems, and to some degree for liquid or gaseous systems, including multiphase systems forming solid-liquid-gas interfaces.

Pressures, Stresses, Anxieties, and On-Job Safety of the School Superintendent.

ERIC Educational Resources Information Center

Chand, Krishan

Identification of the causes of job stress for public school superintendents, with a focus on personal-experiential and task variables, is the purpose of this study. Methodology involved a mail survey of 1,531 randomly selected superintendents. Canonical correlation analysis (CCA) and multiple regression correlation (MCR) analysis were used to…

Patterns of internet use and mental health of high school students in Istria County Croatia: cross-sectional study.

PubMed

Bezinović, Petar; Roviš, Darko; Rončević, Nena; Bilajac, Lovorka

2015-06-01

To examine associations between different forms of internet use and a number of psychological variables related to mental health in adolescents. A cross-sectional survey was carried out on a representative sample of students (N=1539) from all high schools in the region of Istria in Croatia (14-19 years). The associations between four factors of internet use and nine mental health indicators were analyzed using canonical correlation analysis. The four canonical functions suggested a significant association between different types of internet use and specific indicators of mental health (P<0.001). Problematic internet use, more typical among boys, was associated with general aggressive behavior and substance abuse (P<0.001). Experiences of harassment, more typical among girls, were associated with health complaints, symptoms of depression, loneliness, and fear of negative evaluation (P<0.001). Using the internet for communication and entertainment was associated with better relationships with peers (P<0.001), while use of the internet for academic purposes was associated with conscientiousness (P<0.001). The results suggest that different patterns of internet use are significantly associated with specific sets of positive and negative mental health indicators. The data support the assumption that internet use can have both positive and adverse effects on the mental health of youth.

New insights into transcription fidelity: thermal stability of non-canonical structures in template DNA regulates transcriptional arrest, pause, and slippage.

PubMed

Tateishi-Karimata, Hisae; Isono, Noburu; Sugimoto, Naoki

2014-01-01

The thermal stability and topology of non-canonical structures of G-quadruplexes and hairpins in template DNA were investigated, and the effect of non-canonical structures on transcription fidelity was evaluated quantitatively. We designed ten template DNAs: A linear sequence that does not have significant higher-order structure, three sequences that form hairpin structures, and six sequences that form G-quadruplex structures with different stabilities. Templates with non-canonical structures induced the production of an arrested, a slipped, and a full-length transcript, whereas the linear sequence produced only a full-length transcript. The efficiency of production for run-off transcripts (full-length and slipped transcripts) from templates that formed the non-canonical structures was lower than that from the linear. G-quadruplex structures were more effective inhibitors of full-length product formation than were hairpin structure even when the stability of the G-quadruplex in an aqueous solution was the same as that of the hairpin. We considered that intra-polymerase conditions may differentially affect the stability of non-canonical structures. The values of transcription efficiencies of run-off or arrest transcripts were correlated with stabilities of non-canonical structures in the intra-polymerase condition mimicked by 20 wt% polyethylene glycol (PEG). Transcriptional arrest was induced when the stability of the G-quadruplex structure (-ΔG°37) in the presence of 20 wt% PEG was more than 8.2 kcal mol(-1). Thus, values of stability in the presence of 20 wt% PEG are an important indicator of transcription perturbation. Our results further our understanding of the impact of template structure on the transcription process and may guide logical design of transcription-regulating drugs.

New Insights into Transcription Fidelity: Thermal Stability of Non-Canonical Structures in Template DNA Regulates Transcriptional Arrest, Pause, and Slippage

PubMed Central

Tateishi-Karimata, Hisae; Isono, Noburu; Sugimoto, Naoki

2014-01-01

The thermal stability and topology of non-canonical structures of G-quadruplexes and hairpins in template DNA were investigated, and the effect of non-canonical structures on transcription fidelity was evaluated quantitatively. We designed ten template DNAs: A linear sequence that does not have significant higher-order structure, three sequences that form hairpin structures, and six sequences that form G-quadruplex structures with different stabilities. Templates with non-canonical structures induced the production of an arrested, a slipped, and a full-length transcript, whereas the linear sequence produced only a full-length transcript. The efficiency of production for run-off transcripts (full-length and slipped transcripts) from templates that formed the non-canonical structures was lower than that from the linear. G-quadruplex structures were more effective inhibitors of full-length product formation than were hairpin structure even when the stability of the G-quadruplex in an aqueous solution was the same as that of the hairpin. We considered that intra-polymerase conditions may differentially affect the stability of non-canonical structures. The values of transcription efficiencies of run-off or arrest transcripts were correlated with stabilities of non-canonical structures in the intra-polymerase condition mimicked by 20 wt% polyethylene glycol (PEG). Transcriptional arrest was induced when the stability of the G-quadruplex structure (−ΔGo 37) in the presence of 20 wt% PEG was more than 8.2 kcal mol−1. Thus, values of stability in the presence of 20 wt% PEG are an important indicator of transcription perturbation. Our results further our understanding of the impact of template structure on the transcription process and may guide logical design of transcription-regulating drugs. PMID:24594642

[The correlations of somatic, dermatoglyphic and psychological characteristics in the structure of general human constitution from the standpoint of systemic approach].

PubMed

Negasheva, M A

2008-01-01

669 young men and women aged 16-23 years were examined using a program including the measurements of 40 body, head and face parameters, fingerprinting and determination of personal psychological characteristics. On the basis of the study of the correlations between the different groups of characteristics, the evidence was obtained that supports the concept of a relative autonomy of the morpho-functional systems as an essential condition for the integrity of the organism as a whole. The coefficients of canonical correlation were calculated between the somatic and dermatoglyphic features (R=0.3), somatic sizes and psychological personality characteristics (R=0.4), psychological characteristics and the dermatoglyphic indices (R=0.4). An original model is suggested that describes the correlations of somatic, dermatoglyphic and psychological features in the structure of general human constitution on the basis of statistically significant canonical correlations (revealed by the author) and that takes in consideration the degree of the influence of genetic and social-economic complex of factors (on the basis of the literature data) on the development and formation of the investigated systems of characteristics.

Influence of single particle orbital sets and configuration selection on multideterminant wavefunctions in quantum Monte Carlo

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

Clay, Raymond C.; Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550; Morales, Miguel A., E-mail: moralessilva2@llnl.gov

2015-06-21

Multideterminant wavefunctions, while having a long history in quantum chemistry, are increasingly being used in highly accurate quantum Monte Carlo calculations. Since the accuracy of QMC is ultimately limited by the quality of the trial wavefunction, multi-Slater determinants wavefunctions offer an attractive alternative to Slater-Jastrow and more sophisticated wavefunction ansatz for several reasons. They can be efficiently calculated, straightforwardly optimized, and systematically improved by increasing the number of included determinants. In spite of their potential, however, the convergence properties of multi-Slater determinant wavefunctions with respect to orbital set choice and excited determinant selection are poorly understood, which hinders the applicationmore » of these wavefunctions to large systems and solids. In this paper, by performing QMC calculations on the equilibrium and stretched carbon dimer, we find that convergence of the recovered correlation energy with respect to number of determinants can depend quite strongly on basis set and determinant selection methods, especially where there is strong correlation. We demonstrate that properly chosen orbital sets and determinant selection techniques from quantum chemistry methods can dramatically reduce the required number of determinants (and thus the computational cost) to reach a given accuracy, which we argue shows clear need for an automatic QMC-only method for selecting determinants and generating optimal orbital sets.« less

Coexistence of multiple bifurcation modes in memristive diode-bridge-based canonical Chua's circuit

NASA Astrophysics Data System (ADS)

Bao, Bocheng; Xu, Li; Wu, Zhimin; Chen, Mo; Wu, Huagan

2018-07-01

Based on a memristive diode bridge cascaded with series resistor and inductor filter, a modified memristive canonical Chua's circuit is presented in this paper. With the modelling of the memristive circuit, a normalised system model is built. Stability analyses of the equilibrium points are performed and bifurcation behaviours are investigated by numerical simulations and hardware experiments. Most extraordinary in the memristive circuit is that within a parameter region, coexisting phenomenon of multiple bifurcation modes is emerged under six sets of different initial values, resulting in the coexistence of four sets of topologically different and disconnected attractors. These coexisting attractors are easily captured by repeatedly switching on and off the circuit power supplies, which well verify the numerical simulations.

Androgen receptor (AR) cistrome in prostate differentiation and cancer progression.

PubMed

Wang, Fengtian; Koul, Hari K

2017-01-01

Despite the progress in development of better AR-targeted therapies for prostate cancer (PCa), there is no curative therapy for castration-resistant prostate cancer (CRPC). Therapeutic resistance in PCa can be characterized in two broad categories of AR therapy resistance: the first and most prevalent one involves restoration of AR activity despite AR targeted therapy, and the second one involves tumor progression despite blockade of AR activity. As such AR remains the most attractive drug target for CRPC. Despite its oncogenic role, AR signaling also contributes to the maturation and differentiation of prostate luminal cells during development. Recent evidence suggests that AR cistrome is altered in advanced PCa. Alteration in AR may result from AR amplification, alternative splicing, mutations, post-translational modification of AR, and altered expression of AR co-factors. We reasoned that such alterations would result in the transcription of disparate AR target genes and as such may contribute to the emergence of castration-resistance. In the present study, we evaluated the expression of genes associated with canonical or non-canonical AR cistrome in relationship with PCa progression and prostate development by analyzing publicly available datasets. We discovered a transcription switch from canonical AR cistrome target genes to the non-canonical AR cistrome target genes during PCa progression. Using Gene Set Enrichment Analysis (GSEA), we discovered that canonical AR cistrome target genes are enriched in indolent PCa patients and the loss of canonical AR cistrome is associated with tumor metastasis and poor clinical outcome. Analysis of the datasets involving prostate development, revealed that canonical AR cistrome target genes are significantly enriched in prostate luminal cells and can distinguish luminal cells from basal cells, suggesting a pivotal role for canonical AR cistrome driven genes in prostate development. These data suggest that the expression of canonical AR cistrome related genes play an important role in maintaining the prostate luminal cell identity and might restrict the lineage plasticity observed in lethal PCa. Understanding the molecular mechanisms that dictate AR cistrome may lead to development of new therapeutic strategies aimed at restoring canonical AR cistrome, rewiring the oncogenic AR signaling and overcome resistance to AR targeted therapies.

Nonlinear circuits for naturalistic visual motion estimation

PubMed Central

Fitzgerald, James E; Clark, Damon A

2015-01-01

Many animals use visual signals to estimate motion. Canonical models suppose that animals estimate motion by cross-correlating pairs of spatiotemporally separated visual signals, but recent experiments indicate that humans and flies perceive motion from higher-order correlations that signify motion in natural environments. Here we show how biologically plausible processing motifs in neural circuits could be tuned to extract this information. We emphasize how known aspects of Drosophila's visual circuitry could embody this tuning and predict fly behavior. We find that segregating motion signals into ON/OFF channels can enhance estimation accuracy by accounting for natural light/dark asymmetries. Furthermore, a diversity of inputs to motion detecting neurons can provide access to more complex higher-order correlations. Collectively, these results illustrate how non-canonical computations improve motion estimation with naturalistic inputs. This argues that the complexity of the fly's motion computations, implemented in its elaborate circuits, represents a valuable feature of its visual motion estimator. DOI: http://dx.doi.org/10.7554/eLife.09123.001 PMID:26499494

Population Dynamics of Bulking and Foaming Bacteria in a Full-scale Wastewater Treatment Plant over Five Years.

PubMed

Jiang, Xiao-Tao; Guo, Feng; Zhang, Tong

2016-04-11

Bulking and foaming are two notorious problems in activated sludge wastewater treatment plants (WWTPs), which are mainly associated with the excessive growth of bulking and foaming bacteria (BFB). However, studies on affecting factors of BFB in full-scale WWTPs are still limited. In this study, data sets of high-throughput sequencing (HTS) of 16S V3-V4 amplicons of 58 monthly activated sludge samples from a municipal WWTP was re-analyzed to investigate the BFB dynamics and further to study the determinative factors. The population of BFB occupied 0.6~36% (averagely 8.5% ± 7.3%) of the total bacteria and showed seasonal variations with higher abundance in winter-spring than summer-autumn. Pair-wise correlation analysis and canonical correlation analysis (CCA) showed that Gordonia sp. was positively correlated with NO2-N and negatively correlated with NO3-N, and Nostocodia limicola II Tetraspharea sp. was negatively correlated with temperature and positively correlated with NH3-N in activated sludge. Bacteria species correlated with BFB could be clustered into two negatively related modules. Moreover, with intensive time series sampling, the dominant BFB could be accurately modeled with environmental interaction network, i.e. environmental parameters and biotic interactions between BFB and related bacteria, indicating that abiotic and biotic factors were both crucial to the dynamics of BFB.

Optimizing detection and analysis of slow waves in sleep EEG.

PubMed

Mensen, Armand; Riedner, Brady; Tononi, Giulio

2016-12-01

Analysis of individual slow waves in EEG recording during sleep provides both greater sensitivity and specificity compared to spectral power measures. However, parameters for detection and analysis have not been widely explored and validated. We present a new, open-source, Matlab based, toolbox for the automatic detection and analysis of slow waves; with adjustable parameter settings, as well as manual correction and exploration of the results using a multi-faceted visualization tool. We explore a large search space of parameter settings for slow wave detection and measure their effects on a selection of outcome parameters. Every choice of parameter setting had some effect on at least one outcome parameter. In general, the largest effect sizes were found when choosing the EEG reference, type of canonical waveform, and amplitude thresholding. Previously published methods accurately detect large, global waves but are conservative and miss the detection of smaller amplitude, local slow waves. The toolbox has additional benefits in terms of speed, user-interface, and visualization options to compare and contrast slow waves. The exploration of parameter settings in the toolbox highlights the importance of careful selection of detection METHODS: The sensitivity and specificity of the automated detection can be improved by manually adding or deleting entire waves and or specific channels using the toolbox visualization functions. The toolbox standardizes the detection procedure, sets the stage for reliable results and comparisons and is easy to use without previous programming experience. Copyright © 2016 Elsevier B.V. All rights reserved.

Reconstruction of 7T-Like Images From 3T MRI

PubMed Central

Bahrami, Khosro; Shi, Feng; Zong, Xiaopeng; Shin, Hae Won; An, Hongyu

2016-01-01

In the recent MRI scanning, ultra-high-field (7T) MR imaging provides higher resolution and better tissue contrast compared to routine 3T MRI, which may help in more accurate and early brain diseases diagnosis. However, currently, 7T MRI scanners are more expensive and less available at clinical and research centers. These motivate us to propose a method for the reconstruction of images close to the quality of 7T MRI, called 7T-like images, from 3T MRI, to improve the quality in terms of resolution and contrast. By doing so, the post-processing tasks, such as tissue segmentation, can be done more accurately and brain tissues details can be seen with higher resolution and contrast. To do this, we have acquired a unique dataset which includes paired 3T and 7T images scanned from same subjects, and then propose a hierarchical reconstruction based on group sparsity in a novel multi-level Canonical Correlation Analysis (CCA) space, to improve the quality of 3T MR image to be 7T-like MRI. First, overlapping patches are extracted from the input 3T MR image. Then, by extracting the most similar patches from all the aligned 3T and 7T images in the training set, the paired 3T and 7T dictionaries are constructed for each patch. It is worth noting that, for the training, we use pairs of 3T and 7T MR images from each training subject. Then, we propose multi-level CCA to map the paired 3T and 7T patch sets to a common space to increase their correlations. In such space, each input 3T MRI patch is sparsely represented by the 3T dictionary and then the obtained sparse coefficients are used together with the corresponding 7T dictionary to reconstruct the 7T-like patch. Also, to have the structural consistency between adjacent patches, the group sparsity is employed. This reconstruction is performed with changing patch sizes in a hierarchical framework. Experiments have been done using 13 subjects with both 3T and 7T MR images. The results show that our method outperforms previous methods and is able to recover better structural details. Also, to place our proposed method in a medical application context, we evaluated the influence of post-processing methods such as brain tissue segmentation on the reconstructed 7T-like MR images. Results show that our 7T-like images lead to higher accuracy in segmentation of white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and skull, compared to segmentation of 3T MR images. PMID:27046894

Brain mediators of predictive cue effects on perceived pain

PubMed Central

Atlas, Lauren Y.; Bolger, Niall; Lindquist, Martin A.; Wager, Tor D.

2010-01-01

Information about upcoming pain strongly influences pain experience in experimental and clinical settings, but little is known about the brain mechanisms that link expectation and experience. To identify the pathways by which informational cues influence perception, analyses must jointly consider both the effects of cues on brain responses and the relationship between brain responses and changes in reported experience. Our task and analysis strategy were designed to test these relationships. Auditory cues elicited expectations for low or high painful thermal stimulation, and we assessed how cues influenced human subjects’ pain reports and BOLD fMRI responses to matched levels of noxious heat. We used multi-level mediation analysis to identify brain regions that 1) are modulated by predictive cues, 2) predict trial-to-trial variations in pain reports, and 3) formally mediate the relationship between cues and reported pain. Cues influenced heat-evoked responses in most canonical pain-processing regions, including both medial and lateral pain pathways. Effects on several regions correlated with pre-task expectations, suggesting that expectancy plays a prominent role. A subset of pain-processing regions, including anterior cingulate cortex, anterior insula, and thalamus, formally mediated cue effects on pain. Effects on these regions were in turn mediated by cue-evoked anticipatory activity in the medial orbitofrontal cortex (OFC) and ventral striatum, areas not previously directly implicated in nociception. These results suggest that activity in pain-processing regions reflects a combination of nociceptive input and top-down information related to expectations, and that anticipatory processes in OFC and striatum may play a key role in modulating pain processing. PMID:20881115

Logical qubit fusion

NASA Astrophysics Data System (ADS)

Moussa, Jonathan; Ryan-Anderson, Ciaran

The canonical modern plan for universal quantum computation is a Clifford+T gate set implemented in a topological error-correcting code. This plan has the basic disparity that logical Clifford gates are natural for codes in two spatial dimensions while logical T gates are natural in three. Recent progress has reduced this disparity by proposing logical T gates in two dimensions with doubled, stacked, or gauge color codes, but these proposals lack an error threshold. An alternative universal gate set is Clifford+F, where a fusion (F) gate converts two logical qubits into a logical qudit. We show that logical F gates can be constructed by identifying compatible pairs of qubit and qudit codes that stabilize the same logical subspace, much like the original Bravyi-Kitaev construction of magic state distillation. The simplest example of high-distance compatible codes results in a proposal that is very similar to the stacked color code with the key improvement of retaining an error threshold. Sandia National Labs is a multi-program laboratory managed and operated by Sandia Corp, a wholly owned subsidiary of Lockheed Martin Corp, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling.

PubMed

Perdikaris, P; Raissi, M; Damianou, A; Lawrence, N D; Karniadakis, G E

2017-02-01

Multi-fidelity modelling enables accurate inference of quantities of interest by synergistically combining realizations of low-cost/low-fidelity models with a small set of high-fidelity observations. This is particularly effective when the low- and high-fidelity models exhibit strong correlations, and can lead to significant computational gains over approaches that solely rely on high-fidelity models. However, in many cases of practical interest, low-fidelity models can only be well correlated to their high-fidelity counterparts for a specific range of input parameters, and potentially return wrong trends and erroneous predictions if probed outside of their validity regime. Here we put forth a probabilistic framework based on Gaussian process regression and nonlinear autoregressive schemes that is capable of learning complex nonlinear and space-dependent cross-correlations between models of variable fidelity, and can effectively safeguard against low-fidelity models that provide wrong trends. This introduces a new class of multi-fidelity information fusion algorithms that provide a fundamental extension to the existing linear autoregressive methodologies, while still maintaining the same algorithmic complexity and overall computational cost. The performance of the proposed methods is tested in several benchmark problems involving both synthetic and real multi-fidelity datasets from computational fluid dynamics simulations.

Freezing Behavior as a Response to Sexual Visual Stimuli as Demonstrated by Posturography

PubMed Central

Mouras, Harold; Lelard, Thierry; Ahmaidi, Said; Godefroy, Olivier; Krystkowiak, Pierre

2015-01-01

Posturographic changes in motivational conditions remain largely unexplored in the context of embodied cognition. Over the last decade, sexual motivation has been used as a good canonical working model to study motivated social interactions. The objective of this study was to explore posturographic variations in response to visual sexual videos as compared to neutral videos. Our results support demonstration of a freezing-type response in response to sexually explicit stimuli compared to other conditions, as demonstrated by significantly decreased standard deviations for (i) the center of pressure displacement along the mediolateral and anteroposterior axes and (ii) center of pressure’s displacement surface. These results support the complexity of the motor correlates of sexual motivation considered to be a canonical functional context to study the motor correlates of motivated social interactions. PMID:25992571

Gustave Caillebotte, French impressionism, and mere exposure.

PubMed

Cutting, James E

2003-06-01

Gustave Caillebotte was a painter, a collector of some of his colleagues' most renowned works, and a major force in the creation of the late 19th century French Impressionist canon. Six studies are presented as a naturalistic investigation of the effects of mere exposure to images in his collection and to those matched to them. The probabilities of cultural exposure to the 132 stimulus images were indexed by the frequencies of their separate appearances in Cornell University library books--a total of 4,232 times in 980 different books. Across the studies, adult preferences were correlated with differences in image frequencies, but not with recognition, complexity, or prototypicality judgments; children's preferences were not correlated with frequency. Prior cultural exposure also interacted with experimental exposure in predictable ways. The results suggest that mere exposure helps to maintain an artistic canon.

A third-generation density-functional-theory-based method for calculating canonical molecular orbitals of large molecules.

PubMed

Hirano, Toshiyuki; Sato, Fumitoshi

2014-07-28

We used grid-free modified Cholesky decomposition (CD) to develop a density-functional-theory (DFT)-based method for calculating the canonical molecular orbitals (CMOs) of large molecules. Our method can be used to calculate standard CMOs, analytically compute exchange-correlation terms, and maximise the capacity of next-generation supercomputers. Cholesky vectors were first analytically downscaled using low-rank pivoted CD and CD with adaptive metric (CDAM). The obtained Cholesky vectors were distributed and stored on each computer node in a parallel computer, and the Coulomb, Fock exchange, and pure exchange-correlation terms were calculated by multiplying the Cholesky vectors without evaluating molecular integrals in self-consistent field iterations. Our method enables DFT and massively distributed memory parallel computers to be used in order to very efficiently calculate the CMOs of large molecules.

Paradoxical correlation between signal in functional magnetic resonance imaging and deoxygenated haemoglobin content in capillaries: a new theoretical explanation

NASA Astrophysics Data System (ADS)

Yamamoto, Toru; Kato, Toshinori

2002-04-01

Signal increases in functional magnetic resonance imaging (fMRI) are believed to be a result of decreased paramagnetic deoxygenated haemoglobin (deoxyHb) content in the neural activation area. However, discrepancies in this canonical blood oxygenation level dependent (BOLD) theory have been pointed out in studies using optical techniques, which directly measure haemoglobin changes. To explain the discrepancies, we developed a new theory bridging magnetic resonance (MR) signal and haemoglobin changes. We focused on capillary influences, which have been neglected in most previous fMRI studies and performed a combined fMRI and near-infrared spectroscopy (NIRS) study using a language task. Paradoxically, both the MR signal and deoxyHb content increased in Broca's area. On the other hand, fMRI activation in the auditory area near large veins correlated with a mirror-image decrease in deoxyHb and increase in oxygenated haemoglobin (oxyHb), in agreement with canonical BOLD theory. All fMRI signal changes correlated consistently with changes in oxyHb, the diamagnetism of which is insensitive to MR. We concluded that the discrepancy with the canonical BOLD theory is caused by the fact that the BOLD theory ignores the effect of the capillaries. Our theory explains the paradoxical phenomena of the oxyHb and deoxyHb contributions to the MR signal and gives a new insight into the precise haemodynamics of activation by analysing fMRI and NIRS data.

IQ-domain GTPase-activating protein 1 promotes the malignant phenotype of invasive ductal breast carcinoma via canonical Wnt pathway.

PubMed

Zhao, Huan-Yu; Han, Yang; Wang, Jian; Yang, Lian-He; Zheng, Xiao-Ying; Du, Jiang; Wu, Guang-Ping; Wang, En-Hua

2017-06-01

IQ-domain GTPase-activating protein 1 is a scaffolding protein with multidomain which plays a role in modulating dishevelled (Dvl) nuclear translocation in canonical Wnt pathway. However, the biological function and mechanism of IQ-domain GTPase-activating protein 1 in invasive ductal carcinoma (IDC) remain unknown. In this study, we found that IQ-domain GTPase-activating protein 1 expression was elevated in invasive ductal carcinoma, which was positively correlated with tumor grade, lymphatic metastasis, and poor prognosis. Coexpression of IQ-domain GTPase-activating protein 1 and Dvl in the nucleus and cytoplasm of invasive ductal carcinoma was significantly correlated but not in the membrane. Postoperative survival in the patients with their coexpression in the nucleus and cytoplasm was obviously lower than that without coexpression. The positive expression rates of c-myc and cyclin D1 were significantly higher in the patients with nuclear coexpression of Dvl and IQ-domain GTPase-activating protein 1 than that with cytoplasmic coexpression, correlating with poor prognosis. IQ-domain GTPase-activating protein 1 significantly enhanced cell proliferation and invasion in invasive ductal carcinoma cell lines by interacting with Dvl in cytoplasm to promote Dvl nuclear translocation so as to upregulate the expression of c-myc and cyclin D1. Collectively, our data suggest that IQ-domain GTPase-activating protein 1 may promote the malignant phenotype of invasive ductal carcinoma via canonical Wnt signaling, and it could be used as a potential prognostic biomarker for breast cancer patients.

Remote Sensing of Multiple Cloud Layer Heights Using Multi-Angular Measurements

NASA Technical Reports Server (NTRS)

Sinclair, Kenneth; Van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej; Mcgill, Matthew

2017-01-01

Cloud top height (CTH) affects the radiative properties of clouds. Improved CTH observations will allow for improved parameterizations in large-scale models and accurate information on CTH is also important when studying variations in freezing point and cloud microphysics. NASAs airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. For the determination of CTH, a set of consecutive nadir reflectances is selected and the cross-correlations between this set and co-located sets at other viewing angles are calculated for a range of assumed cloud top heights, yielding a correlation profile. Under the assumption that cloud reflectances are isotropic, local peaks in the correlation profile indicate cloud layers. This technique can be applied to every RSP footprint and we demonstrate that detection of multiple peaks in the correlation profile allow retrieval of heights of multiple cloud layers within single RSP footprints. This paper provides an in-depth description of the architecture and performance of the RSPs CTH retrieval technique using data obtained during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC(exp. 4)RS) campaign. RSP retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar (CPL). The method's accuracy associated with the magnitude of correlation, optical thickness, cloud thickness and cloud height are explored. The technique is applied to measurements at a wavelength of 670 nm and 1880 nm and their combination. The 1880-nm band is virtually insensitive to the lower troposphere due to strong water vapor absorption.

Weight-Loss Expectancies, Relative Weight, and Symptoms of Bulimia in Young Women.

ERIC Educational Resources Information Center

Thombs, Dennis L.; And Others

1996-01-01

A canonical correlation analysis of various weight concerns in a sample of college women revealed that strong expectations of weight loss benefits and a high relative body weight were positively correlated with the four major symptoms of bulimia. Expectations of increased self-worth and social confidence were linked to eating problems. (RJM)

Multi-task feature learning by using trace norm regularization

NASA Astrophysics Data System (ADS)

Jiangmei, Zhang; Binfeng, Yu; Haibo, Ji; Wang, Kunpeng

2017-11-01

Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.

Heavy metals relationship with water and size-fractionated sediments in rivers using canonical correlation analysis (CCA) case study, rivers of south western Caspian Sea.

PubMed

Vosoogh, Ali; Saeedi, Mohsen; Lak, Raziyeh

2016-11-01

Some pollutants can qualitatively affect aquatic freshwater such as rivers, and heavy metals are one of the most important pollutants in aquatic fresh waters. Heavy metals can be found in the form of components dissolved in these waters or in compounds with suspended particles and surface sediments. It can be said that heavy metals are in equilibrium between water and sediment. In this study, the amount of heavy metals is determined in water and different sizes of sediment. To obtain the relationship between heavy metals in water and size-fractionated sediments, a canonical correlation analysis (CCA) was utilized in rivers of the southwestern Caspian Sea. In this research, a case study was carried out on 18 sampling stations in nine rivers. In the first step, the concentrations of heavy metals (Cu, Zn, Cr, Fe, Mn, Pb, Ni, and Cd) were determined in water and size-fractionated sediment samples. Water sampling sites were classified by hierarchical cluster analysis (HCA) utilizing squared Euclidean distance with Ward's method. In addition, for interpreting the obtained results and the relationships between the concentration of heavy metals in the tested river water and sample sediments, canonical correlation analysis (CCA) was utilized. The rivers were grouped into two classes (those having no pollution and those having low pollution) based on the HCA results obtained for river water samples. CCA results found numerous relationships between rivers in Iran's Guilan province and their size-fractionated sediments samples. The heavy metals of sediments with 0.038 to 0.125 mm size in diameter are slightly correlated with those of water samples.

Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA

NASA Astrophysics Data System (ADS)

Rabiul Islam, Md; Khademul Islam Molla, Md; Nakanishi, Masaki; Tanaka, Toshihisa

2017-04-01

Objective. Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, as the number of commands increases. This paper develops a novel unsupervised method based on canonical correlation analysis (CCA) for accurate detection of stimulus frequency. Approach. A novel unsupervised technique termed as binary subband CCA (BsCCA) is implemented in a multiband approach to enhance the frequency recognition performance of SSVEP. In BsCCA, two subbands are used and a CCA-based correlation coefficient is computed for the individual subbands. In addition, a reduced set of artificial reference signals is used to calculate CCA for the second subband. The analyzing SSVEP is decomposed into multiple subband and the BsCCA is implemented for each one. Then, the overall recognition score is determined by a weighted sum of the canonical correlation coefficients obtained from each band. Main results. A 12-class SSVEP dataset (frequency range: 9.25-14.75 Hz with an interval of 0.5 Hz) for ten healthy subjects are used to evaluate the performance of the proposed method. The results suggest that BsCCA significantly improves the performance of SSVEP-based BCI compared to the state-of-the-art methods. The proposed method is an unsupervised approach with averaged information transfer rate (ITR) of 77.04 bits min-1 across 10 subjects. The maximum individual ITR is 107.55 bits min-1 for 12-class SSVEP dataset, whereas, the ITR of 69.29 and 69.44 bits min-1 are achieved with CCA and NCCA respectively. Significance. The statistical test shows that the proposed unsupervised method significantly improves the performance of the SSVEP-based BCI. It can be usable in real world applications.

Stripe order in the underdoped region of the two-dimensional Hubbard model

NASA Astrophysics Data System (ADS)

Zheng, Bo-Xiao; Chung, Chia-Min; Corboz, Philippe; Ehlers, Georg; Qin, Ming-Pu; Noack, Reinhard M.; Shi, Hao; White, Steven R.; Zhang, Shiwei; Chan, Garnet Kin-Lic

2017-12-01

Competing inhomogeneous orders are a central feature of correlated electron materials, including the high-temperature superconductors. The two-dimensional Hubbard model serves as the canonical microscopic physical model for such systems. Multiple orders have been proposed in the underdoped part of the phase diagram, which corresponds to a regime of maximum numerical difficulty. By combining the latest numerical methods in exhaustive simulations, we uncover the ordering in the underdoped ground state. We find a stripe order that has a highly compressible wavelength on an energy scale of a few kelvin, with wavelength fluctuations coupled to pairing order. The favored filled stripe order is different from that seen in real materials. Our results demonstrate the power of modern numerical methods to solve microscopic models, even in challenging settings.

Symplectic approach to calculation of magnetic field line trajectories in physical space with realistic magnetic geometry in divertor tokamaks

NASA Astrophysics Data System (ADS)

Punjabi, Alkesh; Ali, Halima

2008-12-01

A new approach to integration of magnetic field lines in divertor tokamaks is proposed. In this approach, an analytic equilibrium generating function (EGF) is constructed in natural canonical coordinates (ψ,θ) from experimental data from a Grad-Shafranov equilibrium solver for a tokamak. ψ is the toroidal magnetic flux and θ is the poloidal angle. Natural canonical coordinates (ψ,θ,φ) can be transformed to physical position (R,Z,φ) using a canonical transformation. (R,Z,φ) are cylindrical coordinates. Another canonical transformation is used to construct a symplectic map for integration of magnetic field lines. Trajectories of field lines calculated from this symplectic map in natural canonical coordinates can be transformed to trajectories in real physical space. Unlike in magnetic coordinates [O. Kerwin, A. Punjabi, and H. Ali, Phys. Plasmas 15, 072504 (2008)], the symplectic map in natural canonical coordinates can integrate trajectories across the separatrix surface, and at the same time, give trajectories in physical space. Unlike symplectic maps in physical coordinates (x,y) or (R,Z), the continuous analog of a symplectic map in natural canonical coordinates does not distort trajectories in toroidal planes intervening the discrete map. This approach is applied to the DIII-D tokamak [J. L. Luxon and L. E. Davis, Fusion Technol. 8, 441 (1985)]. The EGF for the DIII-D gives quite an accurate representation of equilibrium magnetic surfaces close to the separatrix surface. This new approach is applied to demonstrate the sensitivity of stochastic broadening using a set of perturbations that generically approximate the size of the field errors and statistical topological noise expected in a poloidally diverted tokamak. Plans for future application of this approach are discussed.

Measurements of the Canonical Helicity Evolution of a Gyrating Kinked Flux Rope

NASA Astrophysics Data System (ADS)

von der Linden, J.; Sears, J.; Intrator, T.; You, S.

2017-12-01

Magnetic structures in the solar corona and planetary magnetospheres are often modelled as magnetic flux ropes governed by magnetohydrodynamics (MHD); however, inside these structures, as exhibited in reconnection, conversions between magnetic and kinetic energies occur over a wide range of scales. Flux ropes based on the flux of canonical momentum circulation extend the flux rope concept to include effects of finite particle momentum and present the distinct advantage of reconciling all plasma regimes - e.g. kinetic, two-fluid, and MHD - with the topological concept of helicity: twists, writhes, and linkages. This presentation shows the first visualization and analysis of the 3D dynamics of canonical flux ropes and their relative helicity evolution from laboratory measurements. Ion and electron canonical flux ropes are visualized from a dataset of Mach, triple, and Ḃ probe measurements at over 10,000 spatial locations of a gyrating kinked flux rope. The flux ropes co-gyrate with the peak density and electron temperature in and out of a measurement volume. The electron and ion canonical flux ropes twist with opposite handedness and the ion flux ropes writhe around the electron flux ropes. The relative cross helicity between the magnetic and ion flow vorticity flux ropes dominates the relative ion canonical helicity and is anti-correlated with the relative magnetic helicity. The 3D nature of the kink and a reverse eddy current affect the helicity evolution. This work is supported by DOE Grant DE-SC0010340 and the DOE Office of Science Graduate Student Research Program and prepared in part by LLNL under Contract DE-AC52-07NA27344. LLNL-ABS-735426

El Niño-Southern Oscillation-time scale covariation of sea surface salinity and freshwater flux in the western tropical and northern subtropical Pacific

NASA Astrophysics Data System (ADS)

Nagano, Akira; Hasegawa, Takuya; Ueki, Iwao; Ando, Kentaro

2017-07-01

We examined the covariation of sea surface salinity (SSS) and freshwater flux in the western tropical and northern subtropical Pacific on the El Niño-Southern Oscillation time scale, using a canonical correlation analysis of monthly data between 2001 and 2013. The dominant covariation, i.e., the first canonical mode, has large positive and negative amplitudes in regions east of the Philippines and New Guinea, respectively, and reaches peaks in autumn to winter of El Niño years. The positive SSS anomaly east of the Philippines is advected to the Kuroshio Extension region. We found that the second canonical mode is another coupled variation with localized amplitudes of SSS under the atmospheric convergence zones in winter to spring of La Niña years. However, the negative SSS anomaly is annihilated possibly by the evaporation in the subtropical region.

Measures and models for angular correlation and angular-linear correlation. [correlation of random variables

NASA Technical Reports Server (NTRS)

Johnson, R. A.; Wehrly, T.

1976-01-01

Population models for dependence between two angular measurements and for dependence between an angular and a linear observation are proposed. The method of canonical correlations first leads to new population and sample measures of dependence in this latter situation. An example relating wind direction to the level of a pollutant is given. Next, applied to pairs of angular measurements, the method yields previously proposed sample measures in some special cases and a new sample measure in general.

A Single RNaseIII Domain Protein from Entamoeba histolytica Has dsRNA Cleavage Activity and Can Help Mediate RNAi Gene Silencing in a Heterologous System.

PubMed

Pompey, Justine M; Foda, Bardees; Singh, Upinder

2015-01-01

Dicer enzymes process double-stranded RNA (dsRNA) into small RNAs that target gene silencing through the RNA interference (RNAi) pathway. Dicer enzymes are complex, multi-domain RNaseIII proteins, however structural minimalism of this protein has recently emerged in parasitic and fungal systems. The most minimal Dicer, Saccharomyces castellii Dicer1, has a single RNaseIII domain and two double stranded RNA binding domains. In the protozoan parasite Entamoeba histolytica 27nt small RNAs are abundant and mediate silencing, yet no canonical Dicer enzyme has been identified. Although EhRNaseIII does not exhibit robust dsRNA cleavage in vitro, it can process dsRNA in the RNAi-negative background of Saccharomyces cerevisiae, and in conjunction with S. castellii Argonaute1 can partially reconstitute the RNAi pathway. Thus, although EhRNaseIII lacks the domain architecture of canonical or minimal Dicer enzymes, it has dsRNA processing activity that contributes to gene silencing via RNAi. Our data advance the understanding of small RNA biogenesis in Entamoeba as well as broaden the spectrum of non-canonical Dicer enzymes that contribute to the RNAi pathway.

Extensions of PDZ domains as important structural and functional elements.

PubMed

Wang, Conan K; Pan, Lifeng; Chen, Jia; Zhang, Mingjie

2010-08-01

'Divide and conquer' has been the guiding strategy for the study of protein structure and function. Proteins are divided into domains with each domain having a canonical structural definition depending on its type. In this review, we push forward with the interesting observation that many domains have regions outside of their canonical definition that affect their structure and function; we call these regions 'extensions'. We focus on the highly abundant PDZ (PSD-95, DLG1 and ZO-1) domain. Using bioinformatics, we find that many PDZ domains have potential extensions and we developed an openly-accessible website to display our results ( http://bcz102.ust.hk/pdzex/ ). We propose, using well-studied PDZ domains as illustrative examples, that the roles of PDZ extensions can be classified into at least four categories: 1) protein dynamics-based modulation of target binding affinity, 2) provision of binding sites for macro-molecular assembly, 3) structural integration of multi-domain modules, and 4) expansion of the target ligand-binding pocket. Our review highlights the potential structural and functional importance of domain extensions, highlighting the significance of looking beyond the canonical boundaries of protein domains in general.

A Single RNaseIII Domain Protein from Entamoeba histolytica Has dsRNA Cleavage Activity and Can Help Mediate RNAi Gene Silencing in a Heterologous System

PubMed Central

Singh, Upinder

2015-01-01

Dicer enzymes process double-stranded RNA (dsRNA) into small RNAs that target gene silencing through the RNA interference (RNAi) pathway. Dicer enzymes are complex, multi-domain RNaseIII proteins, however structural minimalism of this protein has recently emerged in parasitic and fungal systems. The most minimal Dicer, Saccharomyces castellii Dicer1, has a single RNaseIII domain and two double stranded RNA binding domains. In the protozoan parasite Entamoeba histolytica 27nt small RNAs are abundant and mediate silencing, yet no canonical Dicer enzyme has been identified. Although EhRNaseIII does not exhibit robust dsRNA cleavage in vitro, it can process dsRNA in the RNAi-negative background of Saccharomyces cerevisiae, and in conjunction with S. castellii Argonaute1 can partially reconstitute the RNAi pathway. Thus, although EhRNaseIII lacks the domain architecture of canonical or minimal Dicer enzymes, it has dsRNA processing activity that contributes to gene silencing via RNAi. Our data advance the understanding of small RNA biogenesis in Entamoeba as well as broaden the spectrum of non-canonical Dicer enzymes that contribute to the RNAi pathway. PMID:26230096

Hierarchical classification in high dimensional numerous class cases

NASA Technical Reports Server (NTRS)

Kim, Byungyong; Landgrebe, D. A.

1990-01-01

As progress in new sensor technology continues, increasingly high resolution imaging sensors are being developed. These sensors give more detailed and complex data for each picture element and greatly increase the dimensionality of data over past systems. Three methods for designing a decision tree classifier are discussed: a top down approach, a bottom up approach, and a hybrid approach. Three feature extraction techniques are implemented. Canonical and extended canonical techniques are mainly dependent upon the mean difference between two classes. An autocorrelation technique is dependent upon the correlation differences. The mathematical relationship between sample size, dimensionality, and risk value is derived.

COSMOS-e'-soft Higgsotic attractors

NASA Astrophysics Data System (ADS)

Choudhury, Sayantan

2017-07-01

In this work, we have developed an elegant algorithm to study the cosmological consequences from a huge class of quantum field theories (i.e. superstring theory, supergravity, extra dimensional theory, modified gravity, etc.), which are equivalently described by soft attractors in the effective field theory framework. In this description we have restricted our analysis for two scalar fields - dilaton and Higgsotic fields minimally coupled with Einstein gravity, which can be generalized for any arbitrary number of scalar field contents with generalized non-canonical and non-minimal interactions. We have explicitly used R^2 gravity, from which we have studied the attractor and non-attractor phases by exactly computing two point, three point and four point correlation functions from scalar fluctuations using the In-In (Schwinger-Keldysh) and the δ N formalisms. We have also presented theoretical bounds on the amplitude, tilt and running of the primordial power spectrum, various shapes (equilateral, squeezed, folded kite or counter-collinear) of the amplitude as obtained from three and four point scalar functions, which are consistent with observed data. Also the results from two point tensor fluctuations and the field excursion formula are explicitly presented for the attractor and non-attractor phase. Further, reheating constraints, scale dependent behavior of the couplings and the dynamical solution for the dilaton and Higgsotic fields are also presented. New sets of consistency relations between two, three and four point observables are also presented, which shows significant deviation from canonical slow-roll models. Additionally, three possible theoretical proposals have presented to overcome the tachyonic instability at the time of late time acceleration. Finally, we have also provided the bulk interpretation from the three and four point scalar correlation functions for completeness.

Application of Adjusted Canonical Correlation Analysis (ACCA) to study the association between mathematics in Level 1 and Level 2 and performance of engineering disciplines in Level 2

NASA Astrophysics Data System (ADS)

Peiris, T. S. G.; Nanayakkara, K. A. D. S. A.

2017-09-01

Mathematics plays a key role in engineering sciences as it assists to develop the intellectual maturity and analytical thinking of engineering students and exploring the student academic performance has received great attention recently. The lack of control over covariates motivates the need for their adjustment when measuring the degree of association between two sets of variables in Canonical Correlation Analysis (CCA). Thus to examine the individual effects of mathematics in Level 1 and Level 2 on engineering performance in Level 2, two adjusted analyses in CCA: Part CCA and Partial CCA were applied for the raw marks of engineering undergraduates for three different disciplines, at the Faculty of Engineering, University of Moratuwa, Sri Lanka. The joint influence of mathematics in Level 1 and Level 2 is significant on engineering performance in Level 2 irrespective of the engineering disciplines. The individual effect of mathematics in Level 2 is significantly higher compared to the individual effect of mathematics in Level 1 on engineering performance in Level 2. Furthermore, the individual effect of mathematics in Level 1 can be negligible. But, there would be a notable indirect effect of mathematics in Level 1 on engineering performance in Level 2. It can be concluded that the joint effect of mathematics in both Level 1 and Level 2 is immensely beneficial to improve the overall academic performance at the end of Level 2 of the engineering students. Furthermore, it was found that the impact mathematics varies among engineering disciplines. As partial CCA and partial CCA are not widely explored in applied work, it is recommended to use these techniques for various applications.

Incentives and Barriers That Influence Clinical Computerization in Hong Kong: A Population-based Physician Survey

PubMed Central

Leung, Gabriel M.; Yu, Philip L. H.; Wong, Irene O. L.; Johnston, Janice M.; Tin, Keith Y. K.

2003-01-01

Objective: Given the slow adoption of medical informatics in Hong Kong and Asia, we sought to understand the contributory barriers and potential incentives associated with information technology implementation. Design and Measurements: A representative sample of 949 doctors (response rate = 77.0%) was asked through a postal survey to rank a list of nine barriers associated with clinical computerization according to self-perceived importance. They ranked seven incentives or catalysts that may influence computerization. We generated mean rank scores and used multidimensional preference analysis to explore key explanatory dimensions of these variables. A hierarchical cluster analysis was performed to identify homogenous subgroups of respondents. We further determined the relationships between the sets of barriers and incentives/catalysts collectively using canonical correlation. Results: Time costs, lack of technical support and large capital investments were the biggest barriers to computerization, whereas improved office efficiency and better-quality care were ranked highest as potential incentives to computerize. Cost vs. noncost, physician-related vs. patient-related, and monetary vs. nonmonetary factors were the key dimensions explaining the barrier variables. Similarly, within-practice vs external and “push” vs “pull” factors accounted for the incentive variables. Four clusters were identified for barriers and three for incentives/catalysts. Canonical correlation revealed that respondents who were concerned with the costs of computerization also perceived financial incentives and government regulation to be important incentives/catalysts toward computerization. Those who found the potential interference with communication important also believed that the promise of improved care from computerization to be a significant incentive. Conclusion: This study provided evidence regarding common barriers associated with clinical computerization. Our findings also identified possible incentive strategies that may be employed to accelerate uptake of computer systems. PMID:12595409

Observation of Genuine Three-Photon Interference

NASA Astrophysics Data System (ADS)

Agne, Sascha; Kauten, Thomas; Jin, Jeongwan; Meyer-Scott, Evan; Salvail, Jeff Z.; Hamel, Deny R.; Resch, Kevin J.; Weihs, Gregor; Jennewein, Thomas

2017-04-01

Multiparticle quantum interference is critical for our understanding and exploitation of quantum information, and for fundamental tests of quantum mechanics. A remarkable example of multi-partite correlations is exhibited by the Greenberger-Horne-Zeilinger (GHZ) state. In a GHZ state, three particles are correlated while no pairwise correlation is found. The manifestation of these strong correlations in an interferometric setting has been studied theoretically since 1990 but no three-photon GHZ interferometer has been realized experimentally. Here we demonstrate three-photon interference that does not originate from two-photon or single photon interference. We observe phase-dependent variation of three-photon coincidences with (92.7 ±4.6 )% visibility in a generalized Franson interferometer using energy-time entangled photon triplets. The demonstration of these strong correlations in an interferometric setting provides new avenues for multiphoton interferometry, fundamental tests of quantum mechanics, and quantum information applications in higher dimensions.

Normalization as a canonical neural computation

PubMed Central

Carandini, Matteo; Heeger, David J.

2012-01-01

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation. PMID:22108672

A Numerical-Analytical Approach Based on Canonical Transformations for Computing Optimal Low-Thrust Transfers

NASA Astrophysics Data System (ADS)

da Silva Fernandes, S.; das Chagas Carvalho, F.; Bateli Romão, J. V.

2018-04-01

A numerical-analytical procedure based on infinitesimal canonical transformations is developed for computing optimal time-fixed low-thrust limited power transfers (no rendezvous) between coplanar orbits with small eccentricities in an inverse-square force field. The optimization problem is formulated as a Mayer problem with a set of non-singular orbital elements as state variables. Second order terms in eccentricity are considered in the development of the maximum Hamiltonian describing the optimal trajectories. The two-point boundary value problem of going from an initial orbit to a final orbit is solved by means of a two-stage Newton-Raphson algorithm which uses an infinitesimal canonical transformation. Numerical results are presented for some transfers between circular orbits with moderate radius ratio, including a preliminary analysis of Earth-Mars and Earth-Venus missions.

Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

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

Zhou, Ping; Song, Heda; Wang, Hong

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improvemore » modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.« less

On measures of association among genetic variables

PubMed Central

Gianola, Daniel; Manfredi, Eduardo; Simianer, Henner

2012-01-01

Summary Systems involving many variables are important in population and quantitative genetics, for example, in multi-trait prediction of breeding values and in exploration of multi-locus associations. We studied departures of the joint distribution of sets of genetic variables from independence. New measures of association based on notions of statistical distance between distributions are presented. These are more general than correlations, which are pairwise measures, and lack a clear interpretation beyond the bivariate normal distribution. Our measures are based on logarithmic (Kullback-Leibler) and on relative ‘distances’ between distributions. Indexes of association are developed and illustrated for quantitative genetics settings in which the joint distribution of the variables is either multivariate normal or multivariate-t, and we show how the indexes can be used to study linkage disequilibrium in a two-locus system with multiple alleles and present applications to systems of correlated beta distributions. Two multivariate beta and multivariate beta-binomial processes are examined, and new distributions are introduced: the GMS-Sarmanov multivariate beta and its beta-binomial counterpart. PMID:22742500

SSVEP recognition using common feature analysis in brain-computer interface.

PubMed

Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2015-04-15

Canonical correlation analysis (CCA) has been successfully applied to steady-state visual evoked potential (SSVEP) recognition for brain-computer interface (BCI) application. Although the CCA method outperforms the traditional power spectral density analysis through multi-channel detection, it requires additionally pre-constructed reference signals of sine-cosine waves. It is likely to encounter overfitting in using a short time window since the reference signals include no features from training data. We consider that a group of electroencephalogram (EEG) data trials recorded at a certain stimulus frequency on a same subject should share some common features that may bear the real SSVEP characteristics. This study therefore proposes a common feature analysis (CFA)-based method to exploit the latent common features as natural reference signals in using correlation analysis for SSVEP recognition. Good performance of the CFA method for SSVEP recognition is validated with EEG data recorded from ten healthy subjects, in contrast to CCA and a multiway extension of CCA (MCCA). Experimental results indicate that the CFA method significantly outperformed the CCA and the MCCA methods for SSVEP recognition in using a short time window (i.e., less than 1s). The superiority of the proposed CFA method suggests it is promising for the development of a real-time SSVEP-based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.

The Generalization of Mutual Information as the Information between a Set of Variables: The Information Correlation Function Hierarchy and the Information Structure of Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Wolf, David R.

2004-01-01

The topic of this paper is a hierarchy of information-like functions, here named the information correlation functions, where each function of the hierarchy may be thought of as the information between the variables it depends upon. The information correlation functions are particularly suited to the description of the emergence of complex behaviors due to many- body or many-agent processes. They are particularly well suited to the quantification of the decomposition of the information carried among a set of variables or agents, and its subsets. In more graphical language, they provide the information theoretic basis for understanding the synergistic and non-synergistic components of a system, and as such should serve as a forceful toolkit for the analysis of the complexity structure of complex many agent systems. The information correlation functions are the natural generalization to an arbitrary number of sets of variables of the sequence starting with the entropy function (one set of variables) and the mutual information function (two sets). We start by describing the traditional measures of information (entropy) and mutual information.

Dynamical-statistical seasonal prediction for western North Pacific typhoons based on APCC multi-models

NASA Astrophysics Data System (ADS)

Kim, Ok-Yeon; Kim, Hye-Mi; Lee, Myong-In; Min, Young-Mi

2017-01-01

This study aims at predicting the seasonal number of typhoons (TY) over the western North Pacific with an Asia-Pacific Climate Center (APCC) multi-model ensemble (MME)-based dynamical-statistical hybrid model. The hybrid model uses the statistical relationship between the number of TY during the typhoon season (July-October) and the large-scale key predictors forecasted by APCC MME for the same season. The cross validation result from the MME hybrid model demonstrates high prediction skill, with a correlation of 0.67 between the hindcasts and observation for 1982-2008. The cross validation from the hybrid model with individual models participating in MME indicates that there is no single model which consistently outperforms the other models in predicting typhoon number. Although the forecast skill of MME is not always the highest compared to that of each individual model, the skill of MME presents rather higher averaged correlations and small variance of correlations. Given large set of ensemble members from multi-models, a relative operating characteristic score reveals an 82 % (above-) and 78 % (below-normal) improvement for the probabilistic prediction of the number of TY. It implies that there is 82 % (78 %) probability that the forecasts can successfully discriminate between above normal (below-normal) from other years. The forecast skill of the hybrid model for the past 7 years (2002-2008) is more skillful than the forecast from the Tropical Storm Risk consortium. Using large set of ensemble members from multi-models, the APCC MME could provide useful deterministic and probabilistic seasonal typhoon forecasts to the end-users in particular, the residents of tropical cyclone-prone areas in the Asia-Pacific region.

Exploring the Replicability of a Study's Results: Bootstrap Statistics for the Multivariate Case.

ERIC Educational Resources Information Center

Thompson, Bruce

1995-01-01

Use of the bootstrap method in a canonical correlation analysis to evaluate the replicability of a study's results is illustrated. More confidence may be vested in research results that replicate. (SLD)

The Use of Canonical Correlation Analysis to Assess the Relationship Between Executive Functioning and Verbal Memory in Older Adults

PubMed Central

Moreira, Pedro Silva; Santos, Nadine Correia; Sousa, Nuno

2015-01-01

Executive functioning (EF), which is considered to govern complex cognition, and verbal memory (VM) are constructs assumed to be related. However, it is not known the magnitude of the association between EF and VM, and how sociodemographic and psychological factors may affect this relationship, including in normal aging. In this study, we assessed different EF and VM parameters, via a battery of neurocognitive/psychological tests, and performed a Canonical Correlation Analysis (CCA) to explore the connection between these constructs, in a sample of middle-aged and older healthy individuals without cognitive impairment (N = 563, 50+ years of age). The analysis revealed a positive and moderate association between EF and VM independently of gender, age, education, global cognitive performance level, and mood. These results confirm that EF presents a significant association with VM performance. PMID:28138465

The integrated model of sport confidence: a canonical correlation and mediational analysis.

PubMed

Koehn, Stefan; Pearce, Alan J; Morris, Tony

2013-12-01

The main purpose of the study was to examine crucial parts of Vealey's (2001) integrated framework hypothesizing that sport confidence is a mediating variable between sources of sport confidence (including achievement, self-regulation, and social climate) and athletes' affect in competition. The sample consisted of 386 athletes, who completed the Sources of Sport Confidence Questionnaire, Trait Sport Confidence Inventory, and Dispositional Flow Scale-2. Canonical correlation analysis revealed a confidence-achievement dimension underlying flow. Bias-corrected bootstrap confidence intervals in AMOS 20.0 were used in examining mediation effects between source domains and dispositional flow. Results showed that sport confidence partially mediated the relationship between achievement and self-regulation domains and flow, whereas no significant mediation was found for social climate. On a subscale level, full mediation models emerged for achievement and flow dimensions of challenge-skills balance, clear goals, and concentration on the task at hand.

Strongly contracted canonical transformation theory

NASA Astrophysics Data System (ADS)

Neuscamman, Eric; Yanai, Takeshi; Chan, Garnet Kin-Lic

2010-01-01

Canonical transformation (CT) theory describes dynamic correlation in multireference systems with large active spaces. Here we discuss CT theory's intruder state problem and why our previous approach of overlap matrix truncation becomes infeasible for sufficiently large active spaces. We propose the use of strongly and weakly contracted excitation operators as alternatives for dealing with intruder states in CT theory. The performance of these operators is evaluated for the H2O, N2, and NiO molecules, with comparisons made to complete active space second order perturbation theory and Davidson-corrected multireference configuration interaction theory. Finally, using a combination of strongly contracted CT theory and orbital-optimized density matrix renormalization group theory, we evaluate the singlet-triplet gap of free base porphin using an active space containing all 24 out-of-plane 2p orbitals. Modeling dynamic correlation with an active space of this size is currently only possible using CT theory.

Accurate and balanced anisotropic Gaussian type orbital basis sets for atoms in strong magnetic fields.

PubMed

Zhu, Wuming; Trickey, S B

2017-12-28

In high magnetic field calculations, anisotropic Gaussian type orbital (AGTO) basis functions are capable of reconciling the competing demands of the spherically symmetric Coulombic interaction and cylindrical magnetic (B field) confinement. However, the best available a priori procedure for composing highly accurate AGTO sets for atoms in a strong B field [W. Zhu et al., Phys. Rev. A 90, 022504 (2014)] yields very large basis sets. Their size is problematical for use in any calculation with unfavorable computational cost scaling. Here we provide an alternative constructive procedure. It is based upon analysis of the underlying physics of atoms in B fields that allow identification of several principles for the construction of AGTO basis sets. Aided by numerical optimization and parameter fitting, followed by fine tuning of fitting parameters, we devise formulae for generating accurate AGTO basis sets in an arbitrary B field. For the hydrogen iso-electronic sequence, a set depends on B field strength, nuclear charge, and orbital quantum numbers. For multi-electron systems, the basis set formulae also include adjustment to account for orbital occupations. Tests of the new basis sets for atoms H through C (1 ≤ Z ≤ 6) and ions Li + , Be + , and B + , in a wide B field range (0 ≤ B ≤ 2000 a.u.), show an accuracy better than a few μhartree for single-electron systems and a few hundredths to a few mHs for multi-electron atoms. The relative errors are similar for different atoms and ions in a large B field range, from a few to a couple of tens of millionths, thereby confirming rather uniform accuracy across the nuclear charge Z and B field strength values. Residual basis set errors are two to three orders of magnitude smaller than the electronic correlation energies in multi-electron atoms, a signal of the usefulness of the new AGTO basis sets in correlated wavefunction or density functional calculations for atomic and molecular systems in an external strong B field.

Accurate and balanced anisotropic Gaussian type orbital basis sets for atoms in strong magnetic fields

NASA Astrophysics Data System (ADS)

Zhu, Wuming; Trickey, S. B.

2017-12-01

In high magnetic field calculations, anisotropic Gaussian type orbital (AGTO) basis functions are capable of reconciling the competing demands of the spherically symmetric Coulombic interaction and cylindrical magnetic (B field) confinement. However, the best available a priori procedure for composing highly accurate AGTO sets for atoms in a strong B field [W. Zhu et al., Phys. Rev. A 90, 022504 (2014)] yields very large basis sets. Their size is problematical for use in any calculation with unfavorable computational cost scaling. Here we provide an alternative constructive procedure. It is based upon analysis of the underlying physics of atoms in B fields that allow identification of several principles for the construction of AGTO basis sets. Aided by numerical optimization and parameter fitting, followed by fine tuning of fitting parameters, we devise formulae for generating accurate AGTO basis sets in an arbitrary B field. For the hydrogen iso-electronic sequence, a set depends on B field strength, nuclear charge, and orbital quantum numbers. For multi-electron systems, the basis set formulae also include adjustment to account for orbital occupations. Tests of the new basis sets for atoms H through C (1 ≤ Z ≤ 6) and ions Li+, Be+, and B+, in a wide B field range (0 ≤ B ≤ 2000 a.u.), show an accuracy better than a few μhartree for single-electron systems and a few hundredths to a few mHs for multi-electron atoms. The relative errors are similar for different atoms and ions in a large B field range, from a few to a couple of tens of millionths, thereby confirming rather uniform accuracy across the nuclear charge Z and B field strength values. Residual basis set errors are two to three orders of magnitude smaller than the electronic correlation energies in multi-electron atoms, a signal of the usefulness of the new AGTO basis sets in correlated wavefunction or density functional calculations for atomic and molecular systems in an external strong B field.

Scoping Study of Machine Learning Techniques for Visualization and Analysis of Multi-source Data in Nuclear Safeguards

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

Cui, Yonggang

In implementation of nuclear safeguards, many different techniques are being used to monitor operation of nuclear facilities and safeguard nuclear materials, ranging from radiation detectors, flow monitors, video surveillance, satellite imagers, digital seals to open source search and reports of onsite inspections/verifications. Each technique measures one or more unique properties related to nuclear materials or operation processes. Because these data sets have no or loose correlations, it could be beneficial to analyze the data sets together to improve the effectiveness and efficiency of safeguards processes. Advanced visualization techniques and machine-learning based multi-modality analysis could be effective tools in such integratedmore » analysis. In this project, we will conduct a survey of existing visualization and analysis techniques for multi-source data and assess their potential values in nuclear safeguards.« less

Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

PubMed

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-10-02

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

Adaptive Multi-Node Multiple Input and Multiple Output (MIMO) Transmission for Mobile Wireless Multimedia Sensor Networks

PubMed Central

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-01-01

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase. PMID:24152920

Recruitment success of different fish stocks in the North Sea in relation to climate variability

NASA Astrophysics Data System (ADS)

Dippner, Joachim W.

1997-09-01

Long-term data of year class strengths of different commercially harvested fish stocks based on a virtual population analysis (VPA) are available from ICES. The anomalies of these long-term data sets of year class strength are analyzed using Empirical Orthogonal Functions (EOFs) and are related to climate variability: the anomalies of the sea surface temperature (SST) in the northern North Sea and the North Atlantic Oscillation (NAO) index. A Canonical Correlation Analysis (CCA) between the leading eigenmodes is performed. The results suggest that the variability in the fish recruitment of western mackerel and three gadoids, namely North Sea cod, North Sea saithe, and North Sea whiting is highly correlated to the variability of the North Sea SST which is directly influenced by the NAO. For North Sea haddock and herring no meaningful correlation exists to North Sea SST and NAO. The results allow the conclusion that is seems possible to predict long-term changes in the fish recruitment from climate change scenarios for North Sea cod, North Sea saithe and western mackerel. Furthermore, the results indicate the possibility of recruitment failure for North Sea cod, North Sea whiting, and western mackerel in the case of global warming.

Literature in a TAFE Institute: The Curriculum, Students and Their Classroom Experiences.

ERIC Educational Resources Information Center

Hatters, Cathy

2001-01-01

Notes that teaching literature in a Technical and Further Education setting presents its own special set of problems and paradoxes not usually encountered by teachers in more conventional classrooms. Discusses students and their literature experiences; impact of the canon on teaching; and influence of modern literary theory on the reader-text…

Diagrammatic analysis of correlations in polymer fluids: Cluster diagrams via Edwards' field theory

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

Morse, David C.

2006-10-15

Edwards' functional integral approach to the statistical mechanics of polymer liquids is amenable to a diagrammatic analysis in which free energies and correlation functions are expanded as infinite sums of Feynman diagrams. This analysis is shown to lead naturally to a perturbative cluster expansion that is closely related to the Mayer cluster expansion developed for molecular liquids by Chandler and co-workers. Expansion of the functional integral representation of the grand-canonical partition function yields a perturbation theory in which all quantities of interest are expressed as functionals of a monomer-monomer pair potential, as functionals of intramolecular correlation functions of non-interacting molecules,more » and as functions of molecular activities. In different variants of the theory, the pair potential may be either a bare or a screened potential. A series of topological reductions yields a renormalized diagrammatic expansion in which collective correlation functions are instead expressed diagrammatically as functionals of the true single-molecule correlation functions in the interacting fluid, and as functions of molecular number density. Similar renormalized expansions are also obtained for a collective Ornstein-Zernicke direct correlation function, and for intramolecular correlation functions. A concise discussion is given of the corresponding Mayer cluster expansion, and of the relationship between the Mayer and perturbative cluster expansions for liquids of flexible molecules. The application of the perturbative cluster expansion to coarse-grained models of dense multi-component polymer liquids is discussed, and a justification is given for the use of a loop expansion. As an example, the formalism is used to derive a new expression for the wave-number dependent direct correlation function and recover known expressions for the intramolecular two-point correlation function to first-order in a renormalized loop expansion for coarse-grained models of binary homopolymer blends and diblock copolymer melts.« less

Decoding the auditory brain with canonical component analysis.

PubMed

de Cheveigné, Alain; Wong, Daniel D E; Di Liberto, Giovanni M; Hjortkjær, Jens; Slaney, Malcolm; Lalor, Edmund

2018-05-15

The relation between a stimulus and the evoked brain response can shed light on perceptual processes within the brain. Signals derived from this relation can also be harnessed to control external devices for Brain Computer Interface (BCI) applications. While the classic event-related potential (ERP) is appropriate for isolated stimuli, more sophisticated "decoding" strategies are needed to address continuous stimuli such as speech, music or environmental sounds. Here we describe an approach based on Canonical Correlation Analysis (CCA) that finds the optimal transform to apply to both the stimulus and the response to reveal correlations between the two. Compared to prior methods based on forward or backward models for stimulus-response mapping, CCA finds significantly higher correlation scores, thus providing increased sensitivity to relatively small effects, and supports classifier schemes that yield higher classification scores. CCA strips the brain response of variance unrelated to the stimulus, and the stimulus representation of variance that does not affect the response, and thus improves observations of the relation between stimulus and response. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Classification of multipartite entanglement via negativity fonts

NASA Astrophysics Data System (ADS)

Sharma, S. Shelly; Sharma, N. K.

2012-04-01

Partial transposition of state operator is a well-known tool to detect quantum correlations between two parts of a composite system. In this paper, the global partial transpose (GPT) is linked to conceptually multipartite underlying structures in a state—the negativity fonts. If K-way negativity fonts with nonzero determinants exist, then selective partial transposition of a pure state, involving K of the N qubits (K⩽N), yields an operator with negative eigenvalues, identifying K-body correlations in the state. Expansion of GPT in terms of K-way partially transposed (KPT) operators reveals the nature of intricate intrinsic correlations in the state. Classification criteria for multipartite entangled states based on the underlying structure of global partial transpose of canonical state are proposed. The number of N-partite entanglement types for an N-qubit system is found to be 2N-1-N+2, while the number of major entanglement classes is 2N-1-1. Major classes for three- and four-qubit states are listed. Subclasses are determined by the number and type of negativity fonts in canonical states.

Spatio-temporal Model of Endogenous ROS and Raft-Dependent WNT/Beta-Catenin Signaling Driving Cell Fate Commitment in Human Neural Progenitor Cells

PubMed Central

Haack, Fiete; Lemcke, Heiko; Ewald, Roland; Rharass, Tareck; Uhrmacher, Adelinde M.

2015-01-01

Canonical WNT/β-catenin signaling is a central pathway in embryonic development, but it is also connected to a number of cancers and developmental disorders. Here we apply a combined in-vitro and in-silico approach to investigate the spatio-temporal regulation of WNT/β-catenin signaling during the early neural differentiation process of human neural progenitors cells (hNPCs), which form a new prospect for replacement therapies in the context of neurodegenerative diseases. Experimental measurements indicate a second signal mechanism, in addition to canonical WNT signaling, being involved in the regulation of nuclear β-catenin levels during the cell fate commitment phase of neural differentiation. We find that the biphasic activation of β-catenin signaling observed experimentally can only be explained through a model that combines Reactive Oxygen Species (ROS) and raft dependent WNT/β-catenin signaling. Accordingly after initiation of differentiation endogenous ROS activates DVL in a redox-dependent manner leading to a transient activation of down-stream β-catenin signaling, followed by continuous auto/paracrine WNT signaling, which crucially depends on lipid rafts. Our simulation studies further illustrate the elaborate spatio-temporal regulation of DVL, which, depending on its concentration and localization, may either act as direct inducer of the transient ROS/β-catenin signal or as amplifier during continuous auto-/parcrine WNT/β-catenin signaling. In addition we provide the first stochastic computational model of WNT/β-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent β-catenin activation. The model’s predictive ability is demonstrated under a wide range of varying conditions for in-vitro and in-silico reference data sets. Our in-silico approach is realized in a multi-level rule-based language, that facilitates the extension and modification of the model. Thus, our results provide both new insights and means to further our understanding of canonical WNT/β-catenin signaling and the role of ROS as intracellular signaling mediator. PMID:25793621

Factors associated with the nutritional status of children less than 5 years of age

PubMed Central

Miglioli, Teresa Cristina; Fonseca, Vania Matos; Gomes, Saint Clair; da Silva, Katia Silveira; de Lira, Pedro Israel Cabral; Batista, Malaquias

2015-01-01

OBJECTIVE To analyze if the nutritional status of children aged less than five years is related to the biological conditions of their mothers, environmental and socioeconomic factors, and access to health services and social programs. METHODS This cross-sectional population-based study analyzed 664 mothers and 790 children using canonical correlation analysis. Dependent variables were characteristics of the children (weight/age, height/age, BMI/age, hemoglobin, and retinol serum levels). Independent variables were those related to the mothers’ nutritional status (BMI, hemoglobin, and retinol serum levels), age, environmental and socioeconomic factors and access to health service and social programs. A < 0.05 significance level was adopted to select the interpreted canonical functions (CF) and ± 0.40 as canonical load value of the analyzed variables. RESULTS Three canonical functions were selected, concentrating 89.9% of the variability of the relationship among the groups. In the first canonical function, weight/age (-0.73) and height/age (-0.99) of the children were directly related to the mother’s height (-0.82), prenatal appointments (-0.43), geographical area of the residence (-0.41), and household income per capita (-0.42). Inverse relationship between the variables related to the children and people/room (0.44) showed that the larger the number of people/room, the poorer their nutritional status. Rural residents were found to have the worse nutritional conditions. In the second canonical function, the BMI of the mother (-0.48) was related to BMI/age and retinol of the children, indicating that as women gained weight so did their children. Underweight women tended to have children with vitamin A deficiency. In the third canonical function, hemoglobin (-0.72) and retinol serum levels (-0.40) of the children were directly related to the mother’s hemoglobin levels (-0.43). CONCLUSIONS Mothers and children were associated concerning anemia, vitamin A deficiency and anthropometric markers. Living in rural areas is a determining factor for the families health status. PMID:26398874

Optimization of the linear-scaling local natural orbital CCSD(T) method: Redundancy-free triples correction using Laplace transform.

PubMed

Nagy, Péter R; Kállay, Mihály

2017-06-07

An improved algorithm is presented for the evaluation of the (T) correction as a part of our local natural orbital (LNO) coupled-cluster singles and doubles with perturbative triples [LNO-CCSD(T)] scheme [Z. Rolik et al., J. Chem. Phys. 139, 094105 (2013)]. The new algorithm is an order of magnitude faster than our previous one and removes the bottleneck related to the calculation of the (T) contribution. First, a numerical Laplace transformed expression for the (T) fragment energy is introduced, which requires on average 3 to 4 times fewer floating point operations with negligible compromise in accuracy eliminating the redundancy among the evaluated triples amplitudes. Second, an additional speedup factor of 3 is achieved by the optimization of our canonical (T) algorithm, which is also executed in the local case. These developments can also be integrated into canonical as well as alternative fragmentation-based local CCSD(T) approaches with minor modifications. As it is demonstrated by our benchmark calculations, the evaluation of the new Laplace transformed (T) correction can always be performed if the preceding CCSD iterations are feasible, and the new scheme enables the computation of LNO-CCSD(T) correlation energies with at least triple-zeta quality basis sets for realistic three-dimensional molecules with more than 600 atoms and 12 000 basis functions in a matter of days on a single processor.

Optimization of the linear-scaling local natural orbital CCSD(T) method: Redundancy-free triples correction using Laplace transform

PubMed Central

2017-01-01

An improved algorithm is presented for the evaluation of the (T) correction as a part of our local natural orbital (LNO) coupled-cluster singles and doubles with perturbative triples [LNO-CCSD(T)] scheme [Z. Rolik et al., J. Chem. Phys. 139, 094105 (2013)]. The new algorithm is an order of magnitude faster than our previous one and removes the bottleneck related to the calculation of the (T) contribution. First, a numerical Laplace transformed expression for the (T) fragment energy is introduced, which requires on average 3 to 4 times fewer floating point operations with negligible compromise in accuracy eliminating the redundancy among the evaluated triples amplitudes. Second, an additional speedup factor of 3 is achieved by the optimization of our canonical (T) algorithm, which is also executed in the local case. These developments can also be integrated into canonical as well as alternative fragmentation-based local CCSD(T) approaches with minor modifications. As it is demonstrated by our benchmark calculations, the evaluation of the new Laplace transformed (T) correction can always be performed if the preceding CCSD iterations are feasible, and the new scheme enables the computation of LNO-CCSD(T) correlation energies with at least triple-zeta quality basis sets for realistic three-dimensional molecules with more than 600 atoms and 12 000 basis functions in a matter of days on a single processor. PMID:28576082

Patterns of internet use and mental health of high school students in Istria County, Croatia: cross-sectional study

PubMed Central

Bezinović, Petar; Roviš, Darko; Rončević, Nena; Bilajac, Lovorka

2015-01-01

Aim To examine associations between different forms of internet use and a number of psychological variables related to mental health in adolescents. Methods A cross-sectional survey was carried out on a representative sample of students (N = 1539) from all high schools in the region of Istria in Croatia (14-19 years). The associations between four factors of internet use and nine mental health indicators were analyzed using canonical correlation analysis. Results The four canonical functions suggested a significant association between different types of internet use and specific indicators of mental health (P < 0.001). Problematic internet use, more typical among boys, was associated with general aggressive behavior and substance abuse (P < 0.001). Experiences of harassment, more typical among girls, were associated with health complaints, symptoms of depression, loneliness, and fear of negative evaluation (P < 0.001). Using the internet for communication and entertainment was associated with better relationships with peers (P < 0.001), while use of the internet for academic purposes was associated with conscientiousness (P < 0.001). Conclusion The results suggest that different patterns of internet use are significantly associated with specific sets of positive and negative mental health indicators. The data support the assumption that internet use can have both positive and adverse effects on the mental health of youth. PMID:26088855

Studying Canonical Analysis: A Reply to Thorndike's Comments

ERIC Educational Resources Information Center

Barcikowski, Robert S.; Stevens, James P.

1976-01-01

This article is a rejoinder to TM 502 249. Each of Thorndike's comments are examined. A possible solution to the large number of subjects necessary for stable weights and variate-variable correlations using ridge regression procedures is suggested. (RC)

Assessing exotic plant species invasions and associated soil characteristics: A case study in eastern Rocky Mountain National Park, Colorado, USA, using the pixel nested plot design

USGS Publications Warehouse

Kalkhan, M.A.; Stafford, E.J.; Woodly, P.J.; Stohlgren, T.J.

2007-01-01

Rocky Mountain National Park (RMNP), Colorado, USA, contains a diversity of plant species. However, many exotic plant species have become established, potentially impacting the structure and function of native plant communities. Our goal was to quantify patterns of exotic plant species in relation to native plant species, soil characteristics, and other abiotic factors that may indicate or predict their establishment and success. Our research approach for field data collection was based on a field plot design called the pixel nested plot. The pixel nested plot provides a link to multi-phase and multi-scale spatial modeling-mapping techniques that can be used to estimate total species richness and patterns of plant diversity at finer landscape scales. Within the eastern region of RMNP, in an area of approximately 35,000 ha, we established a total of 60 pixel nested plots in 9 vegetation types. We used canonical correspondence analysis (CCA) and multiple linear regressions to quantify relationships between soil characteristics and native and exotic plant species richness and cover. We also used linear correlation, spatial autocorrelation and cross correlation statistics to test for the spatial patterns of variables of interest. CCA showed that exotic species were significantly (P < 0.05) associated with photosynthetically active radiation (r = 0.55), soil nitrogen (r = 0.58) and bare ground (r = -0.66). Pearson's correlation statistic showed significant linear relationships between exotic species, organic carbon, soil nitrogen, and bare ground. While spatial autocorrelations indicated that our 60 pixel nested plots were spatially independent, the cross correlation statistics indicated that exotic plant species were spatially associated with bare ground, in general, exotic plant species were most abundant in areas of high native species richness. This indicates that resource managers should focus on the protection of relatively rare native rich sites with little canopy cover, and fertile soils. Using the pixel nested plot approach for data collection can facilitate the ecological monitoring of these vulnerable areas at the landscape scale in a time- and cost-effective manner. ?? 2006 Elsevier B.V. All rights reserved.

Quantum canonical ensemble: A projection operator approach

NASA Astrophysics Data System (ADS)

Magnus, Wim; Lemmens, Lucien; Brosens, Fons

2017-09-01

Knowing the exact number of particles N, and taking this knowledge into account, the quantum canonical ensemble imposes a constraint on the occupation number operators. The constraint particularly hampers the systematic calculation of the partition function and any relevant thermodynamic expectation value for arbitrary but fixed N. On the other hand, fixing only the average number of particles, one may remove the above constraint and simply factorize the traces in Fock space into traces over single-particle states. As is well known, that would be the strategy of the grand-canonical ensemble which, however, comes with an additional Lagrange multiplier to impose the average number of particles. The appearance of this multiplier can be avoided by invoking a projection operator that enables a constraint-free computation of the partition function and its derived quantities in the canonical ensemble, at the price of an angular or contour integration. Introduced in the recent past to handle various issues related to particle-number projected statistics, the projection operator approach proves beneficial to a wide variety of problems in condensed matter physics for which the canonical ensemble offers a natural and appropriate environment. In this light, we present a systematic treatment of the canonical ensemble that embeds the projection operator into the formalism of second quantization while explicitly fixing N, the very number of particles rather than the average. Being applicable to both bosonic and fermionic systems in arbitrary dimensions, transparent integral representations are provided for the partition function ZN and the Helmholtz free energy FN as well as for two- and four-point correlation functions. The chemical potential is not a Lagrange multiplier regulating the average particle number but can be extracted from FN+1 -FN, as illustrated for a two-dimensional fermion gas.

Managing Multi-center Flow Cytometry Data for Immune Monitoring

PubMed Central

White, Scott; Laske, Karoline; Welters, Marij JP; Bidmon, Nicole; van der Burg, Sjoerd H; Britten, Cedrik M; Enzor, Jennifer; Staats, Janet; Weinhold, Kent J; Gouttefangeas, Cécile; Chan, Cliburn

2014-01-01

With the recent results of promising cancer vaccines and immunotherapy1–5, immune monitoring has become increasingly relevant for measuring treatment-induced effects on T cells, and an essential tool for shedding light on the mechanisms responsible for a successful treatment. Flow cytometry is the canonical multi-parameter assay for the fine characterization of single cells in solution, and is ubiquitously used in pre-clinical tumor immunology and in cancer immunotherapy trials. Current state-of-the-art polychromatic flow cytometry involves multi-step, multi-reagent assays followed by sample acquisition on sophisticated instruments capable of capturing up to 20 parameters per cell at a rate of tens of thousands of cells per second. Given the complexity of flow cytometry assays, reproducibility is a major concern, especially for multi-center studies. A promising approach for improving reproducibility is the use of automated analysis borrowing from statistics, machine learning and information visualization21–23, as these methods directly address the subjectivity, operator-dependence, labor-intensive and low fidelity of manual analysis. However, it is quite time-consuming to investigate and test new automated analysis techniques on large data sets without some centralized information management system. For large-scale automated analysis to be practical, the presence of consistent and high-quality data linked to the raw FCS files is indispensable. In particular, the use of machine-readable standard vocabularies to characterize channel metadata is essential when constructing analytic pipelines to avoid errors in processing, analysis and interpretation of results. For automation, this high-quality metadata needs to be programmatically accessible, implying the need for a consistent Application Programming Interface (API). In this manuscript, we propose that upfront time spent normalizing flow cytometry data to conform to carefully designed data models enables automated analysis, potentially saving time in the long run. The ReFlow informatics framework was developed to address these data management challenges. PMID:26085786

Erythroleukemia cells acquire an alternative mitophagy capability.

PubMed

Wang, Jian; Fang, Yixuan; Yan, Lili; Yuan, Na; Zhang, Suping; Xu, Li; Nie, Meilan; Zhang, Xiaoying; Wang, Jianrong

2016-04-19

Leukemia cells are superior to hematopoietic cells with a normal differentiation potential in buffering cellular stresses, but the underlying mechanisms for this leukemic advantage are not fully understood. Using CRISPR/Cas9 deletion of the canonical autophagy-essential gene Atg7, we found that erythroleukemia K562 cells are armed with two sets of autophagic machinery. Alternative mitophagy is functional regardless of whether the canonical autophagic mechanism is intact or disrupted. Although canonical autophagy defects attenuated cell cycling, proliferation and differentiation potential, the leukemia cells retained their abilities for mitochondrial clearance and for maintaining low levels of reactive oxygen species (ROS) and apoptosis. Treatment with a specific inducer of mitophagy revealed that the canonical autophagy-defective erythroleukemia cells preserved a mitophagic response. Selective induction of mitophagy was associated with the upregulation and localization of RAB9A on the mitochondrial membrane in both wild-type and Atg7(-/-) leukemia cells. When the leukemia cells were treated with the alternative autophagy inhibitor brefeldin A or when the RAB9A was knocked down, this mitophagy was prohibited. This was accompanied by elevated ROS levels and apoptosis as well as reduced DNA damage repair. Therefore, the results suggest that erythroleukemia K562 cells possess an ATG7-independent alternative mitophagic mechanism that functions even when the canonical autophagic process is impaired, thereby maintaining the ability to respond to stresses such as excessive ROS and DNA damage.

CPMIP: measurements of real computational performance of Earth system models in CMIP6

NASA Astrophysics Data System (ADS)

Balaji, Venkatramani; Maisonnave, Eric; Zadeh, Niki; Lawrence, Bryan N.; Biercamp, Joachim; Fladrich, Uwe; Aloisio, Giovanni; Benson, Rusty; Caubel, Arnaud; Durachta, Jeffrey; Foujols, Marie-Alice; Lister, Grenville; Mocavero, Silvia; Underwood, Seth; Wright, Garrett

2017-01-01

A climate model represents a multitude of processes on a variety of timescales and space scales: a canonical example of multi-physics multi-scale modeling. The underlying climate system is physically characterized by sensitive dependence on initial conditions, and natural stochastic variability, so very long integrations are needed to extract signals of climate change. Algorithms generally possess weak scaling and can be I/O and/or memory-bound. Such weak-scaling, I/O, and memory-bound multi-physics codes present particular challenges to computational performance. Traditional metrics of computational efficiency such as performance counters and scaling curves do not tell us enough about real sustained performance from climate models on different machines. They also do not provide a satisfactory basis for comparative information across models. codes present particular challenges to computational performance. We introduce a set of metrics that can be used for the study of computational performance of climate (and Earth system) models. These measures do not require specialized software or specific hardware counters, and should be accessible to anyone. They are independent of platform and underlying parallel programming models. We show how these metrics can be used to measure actually attained performance of Earth system models on different machines, and identify the most fruitful areas of research and development for performance engineering. codes present particular challenges to computational performance. We present results for these measures for a diverse suite of models from several modeling centers, and propose to use these measures as a basis for a CPMIP, a computational performance model intercomparison project (MIP).

Cluster Analysis and Gaussian Mixture Estimation of Correlated Time-Series by Means of Multi-dimensional Scaling

NASA Astrophysics Data System (ADS)

Ibuki, Takero; Suzuki, Sei; Inoue, Jun-ichi

We investigate cross-correlations between typical Japanese stocks collected through Yahoo!Japan website ( http://finance.yahoo.co.jp/ ). By making use of multi-dimensional scaling (MDS) for the cross-correlation matrices, we draw two-dimensional scattered plots in which each point corresponds to each stock. To make a clustering for these data plots, we utilize the mixture of Gaussians to fit the data set to several Gaussian densities. By minimizing the so-called Akaike Information Criterion (AIC) with respect to parameters in the mixture, we attempt to specify the best possible mixture of Gaussians. It might be naturally assumed that all the two-dimensional data points of stocks shrink into a single small region when some economic crisis takes place. The justification of this assumption is numerically checked for the empirical Japanese stock data, for instance, those around 11 March 2011.

Pair 2-electron reduced density matrix theory using localized orbitals

NASA Astrophysics Data System (ADS)

Head-Marsden, Kade; Mazziotti, David A.

2017-08-01

Full configuration interaction (FCI) restricted to a pairing space yields size-extensive correlation energies but its cost scales exponentially with molecular size. Restricting the variational two-electron reduced-density-matrix (2-RDM) method to represent the same pairing space yields an accurate lower bound to the pair FCI energy at a mean-field-like computational scaling of O (r3) where r is the number of orbitals. In this paper, we show that localized molecular orbitals can be employed to generate an efficient, approximately size-extensive pair 2-RDM method. The use of localized orbitals eliminates the substantial cost of optimizing iteratively the orbitals defining the pairing space without compromising accuracy. In contrast to the localized orbitals, the use of canonical Hartree-Fock molecular orbitals is shown to be both inaccurate and non-size-extensive. The pair 2-RDM has the flexibility to describe the spectra of one-electron RDM occupation numbers from all quantum states that are invariant to time-reversal symmetry. Applications are made to hydrogen chains and their dissociation, n-acene from naphthalene through octacene, and cadmium telluride 2-, 3-, and 4-unit polymers. For the hydrogen chains, the pair 2-RDM method recovers the majority of the energy obtained from similar calculations that iteratively optimize the orbitals. The localized-orbital pair 2-RDM method with its mean-field-like computational scaling and its ability to describe multi-reference correlation has important applications to a range of strongly correlated phenomena in chemistry and physics.

Estimating error cross-correlations in soil moisture data sets using extended collocation analysis

USDA-ARS?s Scientific Manuscript database

Consistent global soil moisture records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based soil moisture data into water balance models or merging multi-source soil moisture retrievals int...

Probabilistic multi-catalogue positional cross-match

NASA Astrophysics Data System (ADS)

Pineau, F.-X.; Derriere, S.; Motch, C.; Carrera, F. J.; Genova, F.; Michel, L.; Mingo, B.; Mints, A.; Nebot Gómez-Morán, A.; Rosen, S. R.; Ruiz Camuñas, A.

2017-01-01

Context. Catalogue cross-correlation is essential to building large sets of multi-wavelength data, whether it be to study the properties of populations of astrophysical objects or to build reference catalogues (or timeseries) from survey observations. Nevertheless, resorting to automated processes with limited sets of information available on large numbers of sources detected at different epochs with various filters and instruments inevitably leads to spurious associations. We need both statistical criteria to select detections to be merged as unique sources, and statistical indicators helping in achieving compromises between completeness and reliability of selected associations. Aims: We lay the foundations of a statistical framework for multi-catalogue cross-correlation and cross-identification based on explicit simplified catalogue models. A proper identification process should rely on both astrometric and photometric data. Under some conditions, the astrometric part and the photometric part can be processed separately and merged a posteriori to provide a single global probability of identification. The present paper addresses almost exclusively the astrometrical part and specifies the proper probabilities to be merged with photometric likelihoods. Methods: To select matching candidates in n catalogues, we used the Chi (or, indifferently, the Chi-square) test with 2(n-1) degrees of freedom. We thus call this cross-match a χ-match. In order to use Bayes' formula, we considered exhaustive sets of hypotheses based on combinatorial analysis. The volume of the χ-test domain of acceptance - a 2(n-1)-dimensional acceptance ellipsoid - is used to estimate the expected numbers of spurious associations. We derived priors for those numbers using a frequentist approach relying on simple geometrical considerations. Likelihoods are based on standard Rayleigh, χ and Poisson distributions that we normalized over the χ-test acceptance domain. We validated our theoretical results by generating and cross-matching synthetic catalogues. Results: The results we obtain do not depend on the order used to cross-correlate the catalogues. We applied the formalism described in the present paper to build the multi-wavelength catalogues used for the science cases of the Astronomical Resource Cross-matching for High Energy Studies (ARCHES) project. Our cross-matching engine is publicly available through a multi-purpose web interface. In a longer term, we plan to integrate this tool into the CDS XMatch Service.

A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs.

PubMed

Forkan, Abdur Rahim Mohammad; Khalil, Ibrahim

2017-02-01

In home-based context-aware monitoring patient's real-time data of multiple vital signs (e.g. heart rate, blood pressure) are continuously generated from wearable sensors. The changes in such vital parameters are highly correlated. They are also patient-centric and can be either recurrent or can fluctuate. The objective of this study is to develop an intelligent method for personalized monitoring and clinical decision support through early estimation of patient-specific vital sign values, and prediction of anomalies using the interrelation among multiple vital signs. In this paper, multi-label classification algorithms are applied in classifier design to forecast these values and related abnormalities. We proposed a completely new approach of patient-specific vital sign prediction system using their correlations. The developed technique can guide healthcare professionals to make accurate clinical decisions. Moreover, our model can support many patients with various clinical conditions concurrently by utilizing the power of cloud computing technology. The developed method also reduces the rate of false predictions in remote monitoring centres. In the experimental settings, the statistical features and correlations of six vital signs are formulated as multi-label classification problem. Eight multi-label classification algorithms along with three fundamental machine learning algorithms are used and tested on a public dataset of 85 patients. Different multi-label classification evaluation measures such as Hamming score, F1-micro average, and accuracy are used for interpreting the prediction performance of patient-specific situation classifications. We achieved 90-95% Hamming score values across 24 classifier combinations for 85 different patients used in our experiment. The results are compared with single-label classifiers and without considering the correlations among the vitals. The comparisons show that multi-label method is the best technique for this problem domain. The evaluation results reveal that multi-label classification techniques using the correlations among multiple vitals are effective ways for early estimation of future values of those vitals. In context-aware remote monitoring this process can greatly help the doctors in quick diagnostic decision making. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Revelations of X-ray spectral analysis of the enigmatic black hole binary GRS 1915+105

NASA Astrophysics Data System (ADS)

Peris, Charith; Remillard, Ronald A.; Steiner, James; Vrtilek, Saeqa Dil; Varniere, Peggy; Rodriguez, Jerome; Pooley, Guy

2016-01-01

Of the black hole binaries discovered thus far, GRS 1915+105 stands out as an exceptional source primarily due to its wild X-ray variability, the diversity of which has not been replicated in any other stellar-mass black hole. Although extreme variability is commonplace in its light-curve, about half of the observations of GRS1915+105 show fairly steady X-ray intensity. We report on the X-ray spectral behavior within these steady observations. Our work is based on a vast RXTE/PCA data set obtained on GRS 1915+105 during the course of its entire mission and 10 years of radio data from the Ryle Telescope, which overlap the X-ray data. We find that the steady observations within the X-ray data set naturally separate into two regions in a color-color diagram, which we refer to as steady-soft and steady-hard. GRS 1915+105 displays significant curvature in the Comptonization component within the PCA band pass suggesting significantly heating from a hot disk present in all states. A new Comptonization model 'simplcut' was developed in order to model this curvature to best effect. A majority of the steady-soft observations display a roughly constant inner radius; remarkably reminiscent of canonical soft state black hole binaries. In contrast, the steady-hard observations display a growing disk truncation that is correlated to the mass accretion rate through the disk, which suggests a magnetically truncated disk. A comparison of X-ray model parameters to the canonical state definitions show that almost all steady-soft observations match the criteria of either thermal or steep power law state, while the thermal state observations dominate the constant radius branch. A large portion (80%) of the steady-hard observations matches the hard state criteria when the disk fraction constraint is neglected. These results suggest that within the complexity of this source is a simpler underlying basis of states, which map to those observed in canonical black hole binaries. When represented in a color-color diagram, state assignments appear to map to ``A, B and C'' (Belloni et al. 2000) regions that govern fast variability cycles in GRS 1915+105 demonstrating a compelling link between short and long time scales in its phenomenology.

Grand canonical electronic density-functional theory: Algorithms and applications to electrochemistry

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

Sundararaman, Ravishankar; Goddard, III, William A.; Arias, Tomas A.

First-principles calculations combining density-functional theory and continuum solvation models enable realistic theoretical modeling and design of electrochemical systems. When a reaction proceeds in such systems, the number of electrons in the portion of the system treated quantum mechanically changes continuously, with a balancing charge appearing in the continuum electrolyte. A grand-canonical ensemble of electrons at a chemical potential set by the electrode potential is therefore the ideal description of such systems that directly mimics the experimental condition. We present two distinct algorithms: a self-consistent field method and a direct variational free energy minimization method using auxiliary Hamiltonians (GC-AuxH), to solvemore » the Kohn-Sham equations of electronic density-functional theory directly in the grand canonical ensemble at fixed potential. Both methods substantially improve performance compared to a sequence of conventional fixed-number calculations targeting the desired potential, with the GC-AuxH method additionally exhibiting reliable and smooth exponential convergence of the grand free energy. Lastly, we apply grand-canonical density-functional theory to the under-potential deposition of copper on platinum from chloride-containing electrolytes and show that chloride desorption, not partial copper monolayer formation, is responsible for the second voltammetric peak.« less

Grand canonical electronic density-functional theory: Algorithms and applications to electrochemistry.

PubMed

Sundararaman, Ravishankar; Goddard, William A; Arias, Tomas A

2017-03-21

First-principles calculations combining density-functional theory and continuum solvation models enable realistic theoretical modeling and design of electrochemical systems. When a reaction proceeds in such systems, the number of electrons in the portion of the system treated quantum mechanically changes continuously, with a balancing charge appearing in the continuum electrolyte. A grand-canonical ensemble of electrons at a chemical potential set by the electrode potential is therefore the ideal description of such systems that directly mimics the experimental condition. We present two distinct algorithms: a self-consistent field method and a direct variational free energy minimization method using auxiliary Hamiltonians (GC-AuxH), to solve the Kohn-Sham equations of electronic density-functional theory directly in the grand canonical ensemble at fixed potential. Both methods substantially improve performance compared to a sequence of conventional fixed-number calculations targeting the desired potential, with the GC-AuxH method additionally exhibiting reliable and smooth exponential convergence of the grand free energy. Finally, we apply grand-canonical density-functional theory to the under-potential deposition of copper on platinum from chloride-containing electrolytes and show that chloride desorption, not partial copper monolayer formation, is responsible for the second voltammetric peak.

Grand canonical electronic density-functional theory: Algorithms and applications to electrochemistry

DOE PAGES

Sundararaman, Ravishankar; Goddard, III, William A.; Arias, Tomas A.

2017-03-16

First-principles calculations combining density-functional theory and continuum solvation models enable realistic theoretical modeling and design of electrochemical systems. When a reaction proceeds in such systems, the number of electrons in the portion of the system treated quantum mechanically changes continuously, with a balancing charge appearing in the continuum electrolyte. A grand-canonical ensemble of electrons at a chemical potential set by the electrode potential is therefore the ideal description of such systems that directly mimics the experimental condition. We present two distinct algorithms: a self-consistent field method and a direct variational free energy minimization method using auxiliary Hamiltonians (GC-AuxH), to solvemore » the Kohn-Sham equations of electronic density-functional theory directly in the grand canonical ensemble at fixed potential. Both methods substantially improve performance compared to a sequence of conventional fixed-number calculations targeting the desired potential, with the GC-AuxH method additionally exhibiting reliable and smooth exponential convergence of the grand free energy. Lastly, we apply grand-canonical density-functional theory to the under-potential deposition of copper on platinum from chloride-containing electrolytes and show that chloride desorption, not partial copper monolayer formation, is responsible for the second voltammetric peak.« less

Isolation and characterization of novel RECK tumor suppressor gene splice variants

PubMed Central

Trombetta-Lima, Marina; Winnischofer, Sheila Maria Brochado; Demasi, Marcos Angelo Almeida; Filho, Renato Astorino; Carreira, Ana Claudia Oliveira; Wei, Beiyang; de Assis Ribas, Thais; Konig, Michelle Silberspitz; Bowman-Colin, Christian; Oba-Shinjo, Sueli Mieko; Marie, Suely Kazue Nagahashi; Stetler-Stevenson, William; Sogayar, Mari Cleide

2015-01-01

Glioblastoma multiforme is the most common and lethal of the central nervous system glial-derived tumors. RECK suppresses tumor invasion by negatively regulating at least three members of the matrix metalloproteinase family: MMP-9, MMP-2, and MT1-MMP. A positive correlation has been observed between the abundance of RECK expression in tumor samples and a more favorable prognosis for patients with several types of tumors. In the present study, novel alternatively spliced variants of the RECK gene: RECK-B and RECK-I were isolated by RT-PCR and sequenced. The expression levels and profiles of these alternative RECK transcripts, as well as canonical RECK were determined in tissue samples of malignant astrocytomas of different grades and in a normal tissue RNA panel by qRT-PCR. Our results show that higher canonical RECK expression, accompanied by a higher canonical to alternative transcript expression ratio, positively correlates with higher overall survival rate after chemotherapeutic treatment of GBM patients. U87MG and T98G cells over-expressing the RECK-B alternative variant display higher anchorage-independent clonal growth and do not display modulation of, respectively, MMP-2 and MMP-9 expression. Our findings suggest that RECK transcript variants might have opposite roles in GBM biology and the ratio of their expression levels may be informative for the prognostic outcome of GBM patients. PMID:26431549

Formulation of state projected centroid molecular dynamics: Microcanonical ensemble and connection to the Wigner distribution.

PubMed

Orr, Lindsay; Hernández de la Peña, Lisandro; Roy, Pierre-Nicholas

2017-06-07

A derivation of quantum statistical mechanics based on the concept of a Feynman path centroid is presented for the case of generalized density operators using the projected density operator formalism of Blinov and Roy [J. Chem. Phys. 115, 7822-7831 (2001)]. The resulting centroid densities, centroid symbols, and centroid correlation functions are formulated and analyzed in the context of the canonical equilibrium picture of Jang and Voth [J. Chem. Phys. 111, 2357-2370 (1999)]. The case where the density operator projects onto a particular energy eigenstate of the system is discussed, and it is shown that one can extract microcanonical dynamical information from double Kubo transformed correlation functions. It is also shown that the proposed projection operator approach can be used to formally connect the centroid and Wigner phase-space distributions in the zero reciprocal temperature β limit. A Centroid Molecular Dynamics (CMD) approximation to the state-projected exact quantum dynamics is proposed and proven to be exact in the harmonic limit. The state projected CMD method is also tested numerically for a quartic oscillator and a double-well potential and found to be more accurate than canonical CMD. In the case of a ground state projection, this method can resolve tunnelling splittings of the double well problem in the higher barrier regime where canonical CMD fails. Finally, the state-projected CMD framework is cast in a path integral form.

Formulation of state projected centroid molecular dynamics: Microcanonical ensemble and connection to the Wigner distribution

NASA Astrophysics Data System (ADS)

Orr, Lindsay; Hernández de la Peña, Lisandro; Roy, Pierre-Nicholas

2017-06-01

A derivation of quantum statistical mechanics based on the concept of a Feynman path centroid is presented for the case of generalized density operators using the projected density operator formalism of Blinov and Roy [J. Chem. Phys. 115, 7822-7831 (2001)]. The resulting centroid densities, centroid symbols, and centroid correlation functions are formulated and analyzed in the context of the canonical equilibrium picture of Jang and Voth [J. Chem. Phys. 111, 2357-2370 (1999)]. The case where the density operator projects onto a particular energy eigenstate of the system is discussed, and it is shown that one can extract microcanonical dynamical information from double Kubo transformed correlation functions. It is also shown that the proposed projection operator approach can be used to formally connect the centroid and Wigner phase-space distributions in the zero reciprocal temperature β limit. A Centroid Molecular Dynamics (CMD) approximation to the state-projected exact quantum dynamics is proposed and proven to be exact in the harmonic limit. The state projected CMD method is also tested numerically for a quartic oscillator and a double-well potential and found to be more accurate than canonical CMD. In the case of a ground state projection, this method can resolve tunnelling splittings of the double well problem in the higher barrier regime where canonical CMD fails. Finally, the state-projected CMD framework is cast in a path integral form.

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Rana, Arun; Moradkhani, Hamid; Sharma, Ashish

2017-04-01

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.

Association between females' perceptions of college aerobic class motivational climates and their responses.

PubMed

Brown, Theresa C; Fry, Mary D

2013-01-01

The aim of this study was to examine the relationship between female college students' perceptions of the motivational climate in their aerobics classes to their adaptive exercise responses. Data were collected from university group exercise classes in spring 2008. The participants (N = 213) responded to a questionnaire measuring perceptions of the climate (i.e., caring, task-, and ego-involving), correlates of intrinsic motivation (i.e., interest/enjoyment, perceived competence, effort/importance, and tension/pressure), commitment to exercise, and reasons for exercising. Canonical correlation analyses revealed that participants who perceived a predominately caring, task-involving climate reported higher interest/enjoyment, perceived competence, effort/importance, and commitment to exercise, as well as lower tension/pressure. Further, those who perceived a high caring, task-involving, and low ego-involving climate were also more likely to report more health-related reasons for exercise versus appearance-focused reasons. Results suggested that important motivational benefits might exist when women perceive caring, task-involving climates in their aerobics class settings. Aerobics class instructors who intentionally create caring, task-involving climates may promote more adaptive motivational responses among their female participants.

The influence of compressibility on nonlinear spectral energy transfer - Part 1: Fundamental mechanisms

NASA Astrophysics Data System (ADS)

Praturi, Divya Sri; Girimaji, Sharath

2017-11-01

Nonlinear spectral energy transfer by triadic interactions is one of the foundational processes in fluid turbulence. Much of our current knowledge of this process is contingent upon pressure being a Lagrange multiplier with the only function of re-orienting the velocity wave vector. In this study, we examine how the nonlinear spectral transfer is affected in compressible turbulence when pressure is a true thermodynamic variable with a wave character. We perform direct numerical simulations of multi-mode evolution at different turbulent Mach numbers of Mt = 0.03 , 0.6 . Simulations are performed with initial modes that are fully solenoidal, fully dilatational and mixed solenoidal-dilatational. It is shown that solenoidal-solenoidal interactions behave in canonical manner at all Mach numbers. However, dilatational and mixed mode interactions are profoundly different. This is due to the fact that wave-pressure leads to kinetic-internal energy exchange via the pressure-dilatation mechanism. An important consequence of this exchange is that the triple correlation term, responsible for spectral transfer, experiences non-monotonic behavior resulting in inefficient energy transfer to other modes.

Efficiency of multi-breed genomic selection for dairy cattle breeds with different sizes of reference population.

PubMed

Hozé, C; Fritz, S; Phocas, F; Boichard, D; Ducrocq, V; Croiseau, P

2014-01-01

Single-breed genomic selection (GS) based on medium single nucleotide polymorphism (SNP) density (~50,000; 50K) is now routinely implemented in several large cattle breeds. However, building large enough reference populations remains a challenge for many medium or small breeds. The high-density BovineHD BeadChip (HD chip; Illumina Inc., San Diego, CA) containing 777,609 SNP developed in 2010 is characterized by short-distance linkage disequilibrium expected to be maintained across breeds. Therefore, combining reference populations can be envisioned. A population of 1,869 influential ancestors from 3 dairy breeds (Holstein, Montbéliarde, and Normande) was genotyped with the HD chip. Using this sample, 50K genotypes were imputed within breed to high-density genotypes, leading to a large HD reference population. This population was used to develop a multi-breed genomic evaluation. The goal of this paper was to investigate the gain of multi-breed genomic evaluation for a small breed. The advantage of using a large breed (Normande in the present study) to mimic a small breed is the large potential validation population to compare alternative genomic selection approaches more reliably. In the Normande breed, 3 training sets were defined with 1,597, 404, and 198 bulls, and a unique validation set included the 394 youngest bulls. For each training set, estimated breeding values (EBV) were computed using pedigree-based BLUP, single-breed BayesC, or multi-breed BayesC for which the reference population was formed by any of the Normande training data sets and 4,989 Holstein and 1,788 Montbéliarde bulls. Phenotypes were standardized by within-breed genetic standard deviation, the proportion of polygenic variance was set to 30%, and the estimated number of SNP with a nonzero effect was about 7,000. The 2 genomic selection (GS) approaches were performed using either the 50K or HD genotypes. The correlations between EBV and observed daughter yield deviations (DYD) were computed for 6 traits and using the different prediction approaches. Compared with pedigree-based BLUP, the average gain in accuracy with GS in small populations was 0.057 for the single-breed and 0.086 for multi-breed approach. This gain was up to 0.193 and 0.209, respectively, with the large reference population. Improvement of EBV prediction due to the multi-breed evaluation was higher for animals not closely related to the reference population. In the case of a breed with a small reference population size, the increase in correlation due to multi-breed GS was 0.141 for bulls without their sire in reference population compared with 0.016 for bulls with their sire in reference population. These results demonstrate that multi-breed GS can contribute to increase genomic evaluation accuracy in small breeds. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Development of knowledge tests for multi-disciplinary emergency training: a review and an example.

PubMed

Sørensen, J L; Thellesen, L; Strandbygaard, J; Svendsen, K D; Christensen, K B; Johansen, M; Langhoff-Roos, P; Ekelund, K; Ottesen, B; Van Der Vleuten, C

2015-01-01

The literature is sparse on written test development in a post-graduate multi-disciplinary setting. Developing and evaluating knowledge tests for use in multi-disciplinary post-graduate training is challenging. The objective of this study was to describe the process of developing and evaluating a multiple-choice question (MCQ) test for use in a multi-disciplinary training program in obstetric-anesthesia emergencies. A multi-disciplinary working committee with 12 members representing six professional healthcare groups and another 28 participants were involved. Recurrent revisions of the MCQ items were undertaken followed by a statistical analysis. The MCQ items were developed stepwise, including decisions on aims and content, followed by testing for face and content validity, construct validity, item-total correlation, and reliability. To obtain acceptable content validity, 40 out of originally 50 items were included in the final MCQ test. The MCQ test was able to distinguish between levels of competence, and good construct validity was indicated by a significant difference in the mean score between consultants and first-year trainees, as well as between first-year trainees and medical and midwifery students. Evaluation of the item-total correlation analysis in the 40 items set revealed that 11 items needed re-evaluation, four of which addressed content issues in local clinical guidelines. A Cronbach's alpha of 0.83 for reliability was found, which is acceptable. Content and construct validity and reliability were acceptable. The presented template for the development of this MCQ test could be useful to others when developing knowledge tests and may enhance the overall quality of test development. © 2014 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

The Use of Multi-Component Statistical Techniques in Understanding Subduction Zone Arc Granitic Geochemical Data Sets

NASA Astrophysics Data System (ADS)

Pompe, L.; Clausen, B. L.; Morton, D. M.

2015-12-01

Multi-component statistical techniques and GIS visualization are emerging trends in understanding large data sets. Our research applies these techniques to a large igneous geochemical data set from southern California to better understand magmatic and plate tectonic processes. A set of 480 granitic samples collected by Baird from this area were analyzed for 39 geochemical elements. Of these samples, 287 are from the Peninsular Ranges Batholith (PRB) and 164 from part of the Transverse Ranges (TR). Principal component analysis (PCA) summarized the 39 variables into 3 principal components (PC) by matrix multiplication and for the PRB are interpreted as follows: PC1 with about 30% of the variation included mainly compatible elements and SiO2 and indicates extent of differentation; PC2 with about 20% of the variation included HFS elements and may indicate crustal contamination as usually identified by Sri; PC3 with about 20% of the variation included mainly HRE elements and may indicate magma source depth as often diplayed using REE spider diagrams and possibly Sr/Y. Several elements did not fit well in any of the three components: Cr, Ni, U, and Na2O.For the PRB, the PC1 correlation with SiO2 was r=-0.85, the PC2 correlation with Sri was r=0.80, and the PC3 correlation with Gd/Yb was r=-0.76 and with Sr/Y was r=-0.66 . Extending this method to the TR, correlations were r=-0.85, -0.21, -0.06, and -0.64, respectively. A similar extent of correlation for both areas was visually evident using GIS interpolation.PC1 seems to do well at indicating differentiation index for both the PRB and TR and correlates very well with SiO2, Al2O3, MgO, FeO*, CaO, K2O, Sc, V, and Co, but poorly with Na2O and Cr. If the crustal component is represented by Sri, PC2 correlates well and less expesively with this indicator in the PRB, but not in the TR. Source depth has been related to the slope on REE spidergrams, and PC3 based on only the HREE and using the Sr/Y ratios gives a reasonable correlation for both PRB and TR, but the Gd/Yb ratio gives a reasonable correlation for only the PRB. The PRB data provide reasonable correlation between principal components and standard geochemical indicators, perhaps because of the well-recognized monotonic variation from SW to NE. Data sets from the TR give similar results in some cases, but poor correlation in others.

Symplectic approach to calculation of magnetic field line trajectories in physical space with realistic magnetic geometry in divertor tokamaks

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

Punjabi, Alkesh; Ali, Halima

A new approach to integration of magnetic field lines in divertor tokamaks is proposed. In this approach, an analytic equilibrium generating function (EGF) is constructed in natural canonical coordinates ({psi},{theta}) from experimental data from a Grad-Shafranov equilibrium solver for a tokamak. {psi} is the toroidal magnetic flux and {theta} is the poloidal angle. Natural canonical coordinates ({psi},{theta},{phi}) can be transformed to physical position (R,Z,{phi}) using a canonical transformation. (R,Z,{phi}) are cylindrical coordinates. Another canonical transformation is used to construct a symplectic map for integration of magnetic field lines. Trajectories of field lines calculated from this symplectic map in natural canonicalmore » coordinates can be transformed to trajectories in real physical space. Unlike in magnetic coordinates [O. Kerwin, A. Punjabi, and H. Ali, Phys. Plasmas 15, 072504 (2008)], the symplectic map in natural canonical coordinates can integrate trajectories across the separatrix surface, and at the same time, give trajectories in physical space. Unlike symplectic maps in physical coordinates (x,y) or (R,Z), the continuous analog of a symplectic map in natural canonical coordinates does not distort trajectories in toroidal planes intervening the discrete map. This approach is applied to the DIII-D tokamak [J. L. Luxon and L. E. Davis, Fusion Technol. 8, 441 (1985)]. The EGF for the DIII-D gives quite an accurate representation of equilibrium magnetic surfaces close to the separatrix surface. This new approach is applied to demonstrate the sensitivity of stochastic broadening using a set of perturbations that generically approximate the size of the field errors and statistical topological noise expected in a poloidally diverted tokamak. Plans for future application of this approach are discussed.« less

Cortico-striatal language pathways dynamically adjust for syntactic complexity: A computational study.

PubMed

Szalisznyó, Krisztina; Silverstein, David; Teichmann, Marc; Duffau, Hugues; Smits, Anja

2017-01-01

A growing body of literature supports a key role of fronto-striatal circuits in language perception. It is now known that the striatum plays a role in engaging attentional resources and linguistic rule computation while also serving phonological short-term memory capabilities. The ventral semantic and the dorsal phonological stream dichotomy assumed for spoken language processing also seems to play a role in cortico-striatal perception. Based on recent studies that correlate deep Broca-striatal pathways with complex syntax performance, we used a previously developed computational model of frontal-striatal syntax circuits and hypothesized that different parallel language pathways may contribute to canonical and non-canonical sentence comprehension separately. We modified and further analyzed a thematic role assignment task and corresponding reservoir computing model of language circuits, as previously developed by Dominey and coworkers. We examined the models performance under various parameter regimes, by influencing how fast the presented language input decays and altering the temporal dynamics of activated word representations. This enabled us to quantify canonical and non-canonical sentence comprehension abilities. The modeling results suggest that separate cortico-cortical and cortico-striatal circuits may be recruited differently for processing syntactically more difficult and less complicated sentences. Alternatively, a single circuit would need to dynamically and adaptively adjust to syntactic complexity. Copyright © 2016. Published by Elsevier Inc.

Stable micron-scale holes are a general feature of canonical holins

PubMed Central

Savva, Christos G.; Dewey, Jill S.; Moussa, Samir H.; To, Kam H.; Holzenburg, Andreas; Young, Ry

2014-01-01

Summary At a programmed time in phage infection cycles, canonical holins suddenly trigger to cause lethal damage to the cytoplasmic membrane, resulting in the cessation of respiration and the non-specific release of pre-folded, fully active endolysins to the periplasm. For the paradigm holin S105 of lambda, triggering is correlated with the formation of micron-scale membrane holes, visible as interruptions in the bilayer in cryo-electron microscopic images and tomographic reconstructions. Here we report that the size distribution of the holes is stable for long periods after triggering. Moreover, early triggering caused by an early lysis allele of S105 formed approximately the same number of holes, but the lesions were significantly smaller. In contrast, early triggering prematurely induced by energy poisons resulted in many fewer visible holes, consistent with previous sizing studies. Importantly, the unrelated canonical holins P2 Y and T4 T were found to cause the formation of holes of approximately the same size and number as for lambda. In contrast, no such lesions were visible after triggering of the pinholin S2168. These results generalize the hole formation phenomenon for canonical holins. A model is presented suggesting the unprecedentedly large size of these holes is related to the timing mechanism. PMID:24164554

Stable micron-scale holes are a general feature of canonical holins.

PubMed

Savva, Christos G; Dewey, Jill S; Moussa, Samir H; To, Kam H; Holzenburg, Andreas; Young, Ry

2014-01-01

At a programmed time in phage infection cycles, canonical holins suddenly trigger to cause lethal damage to the cytoplasmic membrane, resulting in the cessation of respiration and the non-specific release of pre-folded, fully active endolysins to the periplasm. For the paradigm holin S105 of lambda, triggering is correlated with the formation of micron-scale membrane holes, visible as interruptions in the bilayer in cryo-electron microscopic images and tomographic reconstructions. Here we report that the size distribution of the holes is stable for long periods after triggering. Moreover, early triggering caused by an early lysis allele of S105 formed approximately the same number of holes, but the lesions were significantly smaller. In contrast, early triggering prematurely induced by energy poisons resulted in many fewer visible holes, consistent with previous sizing studies. Importantly, the unrelated canonical holins P2 Y and T4 T were found to cause the formation of holes of approximately the same size and number as for lambda. In contrast, no such lesions were visible after triggering of the pinholin S(21) 68. These results generalize the hole formation phenomenon for canonical holins. A model is presented suggesting the unprecedentedly large size of these holes is related to the timing mechanism. © 2013 John Wiley & Sons Ltd.

Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface

NASA Astrophysics Data System (ADS)

Chen, Xiaogang; Wang, Yijun; Gao, Shangkai; Jung, Tzyy-Ping; Gao, Xiaorong

2015-08-01

Objective. Recently, canonical correlation analysis (CCA) has been widely used in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) due to its high efficiency, robustness, and simple implementation. However, a method with which to make use of harmonic SSVEP components to enhance the CCA-based frequency detection has not been well established. Approach. This study proposed a filter bank canonical correlation analysis (FBCCA) method to incorporate fundamental and harmonic frequency components to improve the detection of SSVEPs. A 40-target BCI speller based on frequency coding (frequency range: 8-15.8 Hz, frequency interval: 0.2 Hz) was used for performance evaluation. To optimize the filter bank design, three methods (M1: sub-bands with equally spaced bandwidths; M2: sub-bands corresponding to individual harmonic frequency bands; M3: sub-bands covering multiple harmonic frequency bands) were proposed for comparison. Classification accuracy and information transfer rate (ITR) of the three FBCCA methods and the standard CCA method were estimated using an offline dataset from 12 subjects. Furthermore, an online BCI speller adopting the optimal FBCCA method was tested with a group of 10 subjects. Main results. The FBCCA methods significantly outperformed the standard CCA method. The method M3 achieved the highest classification performance. At a spelling rate of ˜33.3 characters/min, the online BCI speller obtained an average ITR of 151.18 ± 20.34 bits min-1. Significance. By incorporating the fundamental and harmonic SSVEP components in target identification, the proposed FBCCA method significantly improves the performance of the SSVEP-based BCI, and thereby facilitates its practical applications such as high-speed spelling.

The Propagation of Movement Variability in Time: A Methodological Approach for Discrete Movements with Multiple Degrees of Freedom.

PubMed

Krüger, Melanie; Straube, Andreas; Eggert, Thomas

2017-01-01

In recent years, theory-building in motor neuroscience and our understanding of the synergistic control of the redundant human motor system has significantly profited from the emergence of a range of different mathematical approaches to analyze the structure of movement variability. Approaches such as the Uncontrolled Manifold method or the Noise-Tolerance-Covariance decomposition method allow to detect and interpret changes in movement coordination due to e.g., learning, external task constraints or disease, by analyzing the structure of within-subject, inter-trial movement variability. Whereas, for cyclical movements (e.g., locomotion), mathematical approaches exist to investigate the propagation of movement variability in time (e.g., time series analysis), similar approaches are missing for discrete, goal-directed movements, such as reaching. Here, we propose canonical correlation analysis as a suitable method to analyze the propagation of within-subject variability across different time points during the execution of discrete movements. While similar analyses have already been applied for discrete movements with only one degree of freedom (DoF; e.g., Pearson's product-moment correlation), canonical correlation analysis allows to evaluate the coupling of inter-trial variability across different time points along the movement trajectory for multiple DoF-effector systems, such as the arm. The theoretical analysis is illustrated by empirical data from a study on reaching movements under normal and disturbed proprioception. The results show increased movement duration, decreased movement amplitude, as well as altered movement coordination under ischemia, which results in a reduced complexity of movement control. Movement endpoint variability is not increased under ischemia. This suggests that healthy adults are able to immediately and efficiently adjust the control of complex reaching movements to compensate for the loss of proprioceptive information. Further, it is shown that, by using canonical correlation analysis, alterations in movement coordination that indicate changes in the control strategy concerning the use of motor redundancy can be detected, which represents an important methodical advance in the context of neuromechanics.

A zero dead-time multi-particle time and position sensitive detector based on correlation between brightness and amplitude

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

Urbain, X., E-mail: xavier.urbain@uclouvain.be; Bech, D.; Van Roy, J.-P.

A new multi-particle time and position sensitive detector using only a set of microchannel plates, a waveform digitizer, a phosphor screen, and a CMOS camera is described. The assignment of the timing information, as taken from the microchannel plates by fast digitizing, to the positions, as recorded by the camera, is based on the COrrelation between the BRightness of the phosphor screen spots, defined as their integrated intensity and the Amplitude of the electrical signals (COBRA). Tests performed by observing the dissociation of HeH, the fragmentation of H{sub 3} into two or three fragments, and the photo-double-ionization of Xenon atomsmore » are presented, which illustrate the performances of the COBRA detection scheme.« less

Instrumental measurement of beer taste attributes using an electronic tongue.

PubMed

Rudnitskaya, Alisa; Polshin, Evgeny; Kirsanov, Dmitry; Lammertyn, Jeroen; Nicolai, Bart; Saison, Daan; Delvaux, Freddy R; Delvaux, Filip; Legin, Andrey

2009-07-30

The present study deals with the evaluation of the electronic tongue multisensor system as an analytical tool for the rapid assessment of taste and flavour of beer. Fifty samples of Belgian and Dutch beers of different types (lager beers, ales, wheat beers, etc.), which were characterized with respect to the sensory properties, were measured using the electronic tongue (ET) based on potentiometric chemical sensors developed in Laboratory of Chemical Sensors of St. Petersburg University. The analysis of the sensory data and the calculation of the compromise average scores was made using STATIS. The beer samples were discriminated using both sensory panel and ET data based on PCA, and both data sets were compared using Canonical Correlation Analysis. The ET data were related to the sensory beer attributes using Partial Least Square regression for each attribute separately. Validation was done based on a test set comprising one-third of all samples. The ET was capable of predicting with good precision 20 sensory attributes of beer including such as bitter, sweet, sour, fruity, caramel, artificial, burnt, intensity and body.

Imbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites.

PubMed

He, Jianjun; Gu, Hong; Liu, Wenqi

2012-01-01

It is well known that an important step toward understanding the functions of a protein is to determine its subcellular location. Although numerous prediction algorithms have been developed, most of them typically focused on the proteins with only one location. In recent years, researchers have begun to pay attention to the subcellular localization prediction of the proteins with multiple sites. However, almost all the existing approaches have failed to take into account the correlations among the locations caused by the proteins with multiple sites, which may be the important information for improving the prediction accuracy of the proteins with multiple sites. In this paper, a new algorithm which can effectively exploit the correlations among the locations is proposed by using gaussian process model. Besides, the algorithm also can realize optimal linear combination of various feature extraction technologies and could be robust to the imbalanced data set. Experimental results on a human protein data set show that the proposed algorithm is valid and can achieve better performance than the existing approaches.

Psychosocial correlates of parenting a child with autistic disorder.

PubMed

Dardas, Latefa Ali; Ahmad, Muayyad M

2014-09-01

The lifelong experience of raising a child with a complex developmental disability such as autistic disorder is considered one of the most significant parenting stressors, with the potential to spill over into various areas of the life of parents. Therefore, studying the psychological functioning for parents of children with developmental disabilities requires the consideration of multiple factors acting and interacting concurrently. The purpose of this study was to examine the relationship between two sets of variables in a sample of parents of children with autistic disorder. The first set was composed of the parents' characteristics and the coping strategies used. The second set was composed of three stress subscales-parental distress (PD), parent-child dysfunctional interaction (PCDI), and difficult child (DC)-and the parental quality of life (QOL). Canonical correlation multivariate analysis was used to examine the relationship between the sets of variables in 184 Jordanian parents of children with autistic disorder. The analyses revealed that the parents who have higher incomes, use diverse problem-solving strategies, exhibit less escape-avoidance, and exhibit less responsibility acceptance behavior tended to report lower PD, PCDI, and DC scores and a higher QOL score. The analyses also revealed that being an older parent, having more time since the child's autistic diagnosis, and using more distancing coping strategies were associated with lower PD scores, higher PCDI and DC scores, and better QOL. This study is the first to investigate a wide range of parental psychosocial impacts as well as several sociodemographic factors that are possibly associated with raising a child with autistic disorder. The results indicate that health professionals working with parents of children with autistic disorder need to consider holistically the factors that can potentially affect the parents' health and well-being and provide care that focuses on the parents as both clients and caregivers.

Model Identification of Integrated ARMA Processes

ERIC Educational Resources Information Center

Stadnytska, Tetiana; Braun, Simone; Werner, Joachim

2008-01-01

This article evaluates the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF), automated methods for the Autoregressive Integrated Moving-Average (ARIMA) model selection commonly available in current versions of SAS for Windows, as identification tools for integrated processes. SCAN and ESACF can…

Global Optimality of the Successive Maxbet Algorithm.

ERIC Educational Resources Information Center

Hanafi, Mohamed; ten Berge, Jos M. F.

2003-01-01

It is known that the Maxbet algorithm, which is an alternative to the method of generalized canonical correlation analysis and Procrustes analysis, may converge to local maxima. Discusses an eigenvalue criterion that is sufficient, but not necessary, for global optimality of the successive Maxbet algorithm. (SLD)

MULTIVARIATE ANALYSIS OF MACROINVERTEBRATE ASSEMBLAGES TO DETERMINE IMPACTS ON ROCKY MOUNTAIN STREAM ECOSYSTEMS

EPA Science Inventory

Using reduncancy (RDA) and canonical correlation analysis (CCA) we assessed relationships between chemical and physical characteristics and periphyton at 105 stream sites sampled by REMAP in the mineral belt of the southern Rockies ecoregion in Colorado. We contrasted results ob...

A Feature Fusion Based Forecasting Model for Financial Time Series

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

2014-01-01

Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455

Oblique rotaton in canonical correlation analysis reformulated as maximizing the generalized coefficient of determination.

PubMed

Satomura, Hironori; Adachi, Kohei

2013-07-01

To facilitate the interpretation of canonical correlation analysis (CCA) solutions, procedures have been proposed in which CCA solutions are orthogonally rotated to a simple structure. In this paper, we consider oblique rotation for CCA to provide solutions that are much easier to interpret, though only orthogonal rotation is allowed in the existing formulations of CCA. Our task is thus to reformulate CCA so that its solutions have the freedom of oblique rotation. Such a task can be achieved using Yanai's (Jpn. J. Behaviormetrics 1:46-54, 1974; J. Jpn. Stat. Soc. 11:43-53, 1981) generalized coefficient of determination for the objective function to be maximized in CCA. The resulting solutions are proved to include the existing orthogonal ones as special cases and to be rotated obliquely without affecting the objective function value, where ten Berge's (Psychometrika 48:519-523, 1983) theorems on suborthonormal matrices are used. A real data example demonstrates that the proposed oblique rotation can provide simple, easily interpreted CCA solutions.

Hierarchical competitions subserving multi-attribute choice

PubMed Central

Hunt, Laurence T; Dolan, Raymond J; Behrens, Timothy EJ

2015-01-01

Valuation is a key tenet of decision neuroscience, where it is generally assumed that different attributes of competing options are assimilated into unitary values. Such values are central to current neural models of choice. By contrast, psychological studies emphasize complex interactions between choice and valuation. Principles of neuronal selection also suggest competitive inhibition may occur in early valuation stages, before option selection. Here, we show behavior in multi-attribute choice is best explained by a model involving competition at multiple levels of representation. This hierarchical model also explains neural signals in human brain regions previously linked to valuation, including striatum, parietal and prefrontal cortex, where activity represents competition within-attribute, competition between attributes, and option selection. This multi-layered inhibition framework challenges the assumption that option values are computed before choice. Instead our results indicate a canonical competition mechanism throughout all stages of a processing hierarchy, not simply at a final choice stage. PMID:25306549

A Multi-Discipline, Multi-Genre Digital Library for Research and Education

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.

2004-01-01

We describe NCSTRL+, a unified, canonical digital library for educational and scientific and technical information (STI). NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible digital library (DL) that provides access to over 100 university departments and laboratories. NCSTRL+ implements two new technologies: cluster functionality and publishing "buckets". We have extended the Dienst protocol, the protocol underlying NCSTRL, to provide the ability to "cluster" independent collections into a logically centralized digital library based upon subject category classification, type of organization, and genres of material. The concept of "buckets" provides a mechanism for publishing and managing logically linked entities with multiple data formats. The NCSTRL+ prototype DL contains the holdings of NCSTRL and the NASA Technical Report Server (NTRS). The prototype demonstrates the feasibility of publishing into a multi-cluster DL, searching across clusters, and storing and presenting buckets of information.

NCSTRL+: Adding Multi-Discipline and Multi-Genre Support to the Dienst Protocol Using Clusters and Buckets

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.; Zubair, Mohammad

1998-01-01

We describe NCSTRL+, a unified, canonical digital library for scientific and technical information (STI). NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible digital library (DL) that provides access to over 100 university departments and laboratories. NCSTRL+ implements two new technologies: cluster functionality and publishing buckets. We have extended Dienst, the protocol underlying NCSTRL, to provide the ability to cluster independent collections into a logically centralized digital library based upon subject category classification, type of organization, and genres of material. The bucket construct provides a mechanism for publishing and managing logically linked entities with multiple data forms as a single object. The NCSTRL+ prototype DL contains the holdings of NCSTRL and the NASA Technical Report Server (NTRS). The prototype demonstrates the feasibility of publishing into a multi-cluster DL, searching across clusters, and storing and presenting buckets of information.

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition

PubMed Central

Lv, Yong; Song, Gangbing

2018-01-01

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal. PMID:29659510

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition.

PubMed

Yuan, Rui; Lv, Yong; Song, Gangbing

2018-04-16

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal.

Quantitative assessment of viable cells of Lactobacillus plantarum strains in single, dual and multi-strain biofilms.

PubMed

Fernández Ramírez, Mónica D; Kostopoulos, Ioannis; Smid, Eddy J; Nierop Groot, Masja N; Abee, Tjakko

2017-03-06

Biofilms of Lactobacillus plantarum are a potential source for contamination and recontamination of food products. Although biofilms have been mostly studied using single species or even single strains, it is conceivable that in a range of environmental settings including food processing areas, biofilms are composed of multiple species with each species represented by multiple strains. In this study six spoilage related L. plantarum strains FBR1-FBR6 and the model strain L. plantarum WCFS1 were characterised in single, dual and multiple strain competition models. A quantitative PCR approach was used with added propidium monoazide (PMA) enabling quantification of intact cells in the biofilm, representing the viable cell fraction that determines the food spoilage risk. Our results show that the performance of individual strains in multi-strain cultures generally correlates with their performance in pure culture, and relative strain abundance in multi-strain biofilms positively correlated with the relative strain abundance in suspended (planktonic) cultures. Performance of individual strains in dual-strain biofilms was highly influenced by the presence of the secondary strain, and in most cases no correlation between the relative contributions of viable planktonic cells and viable cells in the biofilm was noted. The total biofilm quantified by CV staining of the dual and multi-strain biofilms formed was mainly correlated to CV values of the dominant strain obtained in single strain studies. However, the combination of strain FBR5 and strain WCFS1 showed significantly higher CV values compared to the individual performances of both strains indicating that total biofilm formation was higher in this specific condition. Notably, L. plantarum FBR5 was able to outgrow all other strains and showed the highest relative abundance in dual and multi-strain biofilms. All the dual and multi-strain biofilms contained a considerable number of viable cells, representing a potential source of contamination. Copyright © 2016 Elsevier B.V. All rights reserved.

Gaussian Elimination-Based Novel Canonical Correlation Analysis Method for EEG Motion Artifact Removal.

PubMed

Roy, Vandana; Shukla, Shailja; Shukla, Piyush Kumar; Rawat, Paresh

2017-01-01

The motion generated at the capturing time of electro-encephalography (EEG) signal leads to the artifacts, which may reduce the quality of obtained information. Existing artifact removal methods use canonical correlation analysis (CCA) for removing artifacts along with ensemble empirical mode decomposition (EEMD) and wavelet transform (WT). A new approach is proposed to further analyse and improve the filtering performance and reduce the filter computation time under highly noisy environment. This new approach of CCA is based on Gaussian elimination method which is used for calculating the correlation coefficients using backslash operation and is designed for EEG signal motion artifact removal. Gaussian elimination is used for solving linear equation to calculate Eigen values which reduces the computation cost of the CCA method. This novel proposed method is tested against currently available artifact removal techniques using EEMD-CCA and wavelet transform. The performance is tested on synthetic and real EEG signal data. The proposed artifact removal technique is evaluated using efficiency matrices such as del signal to noise ratio (DSNR), lambda ( λ ), root mean square error (RMSE), elapsed time, and ROC parameters. The results indicate suitablity of the proposed algorithm for use as a supplement to algorithms currently in use.

The Heisenberg-Weyl algebra on the circle and a related quantum mechanical model for hindered rotation.

PubMed

Kouri, Donald J; Markovich, Thomas; Maxwell, Nicholas; Bodmann, Bernhard G

2009-07-02

We discuss a periodic variant of the Heisenberg-Weyl algebra, associated with the group of translations and modulations on the circle. Our study of uncertainty minimizers leads to a periodic version of canonical coherent states. Unlike the canonical, Cartesian case, there are states for which the uncertainty product associated with the generators of the algebra vanishes. Next, we explore the supersymmetric (SUSY) quantum mechanical setting for the uncertainty-minimizing states and interpret them as leading to a family of "hindered rotors". Finally, we present a standard quantum mechanical treatment of one of these hindered rotor systems, including numerically generated eigenstates and energies.

Logarithmic violation of scaling in strongly anisotropic turbulent transfer of a passive vector field

NASA Astrophysics Data System (ADS)

Antonov, N. V.; Gulitskiy, N. M.

2015-01-01

Inertial-range asymptotic behavior of a vector (e.g., magnetic) field, passively advected by a strongly anisotropic turbulent flow, is studied by means of the field-theoretic renormalization group and the operator product expansion. The advecting velocity field is Gaussian, not correlated in time, with the pair correlation function of the form ∝δ (t -t') /k⊥d -1 +ξ , where k⊥=|k⊥| and k⊥ is the component of the wave vector, perpendicular to the distinguished direction ("direction of the flow")—the d -dimensional generalization of the ensemble introduced by Avellaneda and Majda [Commun. Math. Phys. 131, 381 (1990), 10.1007/BF02161420]. The stochastic advection-diffusion equation for the transverse (divergence-free) vector field includes, as special cases, the kinematic dynamo model for magnetohydrodynamic turbulence and the linearized Navier-Stokes equation. In contrast to the well-known isotropic Kraichnan's model, where various correlation functions exhibit anomalous scaling behavior with infinite sets of anomalous exponents, here the dependence on the integral turbulence scale L has a logarithmic behavior: Instead of powerlike corrections to ordinary scaling, determined by naive (canonical) dimensions, the anomalies manifest themselves as polynomials of logarithms of L . The key point is that the matrices of scaling dimensions of the relevant families of composite operators appear nilpotent and cannot be diagonalized. The detailed proof of this fact is given for the correlation functions of arbitrary order.

LBNP as useful tool for pilot candidates selection to the Polish Air Force: a preliminary study.

PubMed

Romuald, M; Mariusz, Z; Artur, D; Krzysztof, R

2001-07-01

Candidates to the Polish Air Force are to fulfill strict medical conditions. Every candidate, wanting to become a fighter pilot or not, has to pass a rigorous centrifuge examination. This is a costly and especially stressful process for the candidates, as first-timers. This article explores possibility for different approach to candidates fitness to fly assessment. 14 candidates (21-22 yrs old) were subjected to a regular GOR centrifuge profile (0.1 G/s; up to +7.0 Gz; unprotected) and to lower body negative pressure (LBNP) examination (2 min. rest period followed by 3 min. at -40 mm Hg; supine position). Both, centrifuge and LBNP examinations were carried out the same day, with about 1 hour gap between them. ECG and impedance cardiography (ICG) were being recorded during both tests. The following parameters were calculated: HR and QZ (time between ventricular depolarization [beginning of the Q wave in ECG] and local maximum of the first derivative [dZ/dt] in ICG). QZ was considered to be an effective measure of dynamic heart function. +Gz tolerance for the group was +5.94 +/- 0.98 Gz. Correlation between +Gz tolerance and QZ values during LBNP test (-40 mm Hg) for all subjects was equal to r=0.6. Correlation between sets of parameters (canonical analysis) for LBNP and centrifuge was equal to r=0.78. Both results were statistically insignificant (p<0.09). Baseline HR values were 121 +/- 19 bpm and 75 +/- 12 bpm, and maximal HR values were 172 +/- 21 bpm and 81 +/- 13 bpm, respectively for centrifuge and LBNP. For both, baseline and maximal HR during LBNP and G exposure canonical correlation was equal to r=0.72. The results were statistically not significant, however. Centrifuge examination is much more stressful than LBNP test. This could have implication on the objective results of centrifuge test. The results may suggest that LBNP test could be a used in pilot candidates selection, especially those presenting high baseline HR values.

Comment on 'Controversy concerning the definition of quark and gluon angular momentum' by Elliot Leader [PRD 83, 096012 (2011)

NASA Astrophysics Data System (ADS)

Lin, Huey-Wen; Liu, Keh-Fei

2012-03-01

It is argued by the author that the canonical form of the quark energy-momentum tensor with a partial derivative instead of the covariant derivative is the correct definition for the quark momentum and angular momentum fraction of the nucleon in covariant quantization. Although it is not manifestly gauge-invariant, its matrix elements in the nucleon will be nonvanishing and are gauge-invariant. We test this idea in the path-integral quantization by calculating correlation functions on the lattice with a gauge-invariant nucleon interpolation field and replacing the gauge link in the quark lattice momentum operator with unity, which corresponds to the partial derivative in the continuum. We find that the ratios of three-point to two-point functions are zero within errors for both the u and d quarks, contrary to the case without setting the gauge links to unity.

Real-time mobile phone dialing system based on SSVEP

NASA Astrophysics Data System (ADS)

Wang, Dongsheng; Kobayashi, Toshiki; Cui, Gaochao; Watabe, Daishi; Cao, Jianting

2017-03-01

Brain computer interface (BCI) systems based on the steady state visual evoked potential (SSVEP) provide higher information transfer rates and require shorter training time than BCI systems using other brain signals. It has been widely used in brain science, rehabilitation engineering, biomedical engineering and intelligent information processing. In this paper, we present a real-time mobile phone dialing system based on SSVEP, and it is more portable than other dialing system because the flashing dial interface is set on a small tablet. With this online BCI system, we can take advantage of this system based on SSVEP to identify the specific frequency on behalf of a number using canonical correlation analysis (CCA) method and dialed out successfully without using any physical movements such as finger tapping. This phone dialing system will be promising to help disable patients to improve the quality of lives.

Statistical manifestation of quantum correlations via disequilibrium

NASA Astrophysics Data System (ADS)

Pennini, F.; Plastino, A.

2017-12-01

The statistical notion of disequilibrium (D) was introduced by López-Ruiz, Mancini, and Calbet (LMC) (1995) [1] more than 20 years ago. D measures the amount of ;correlational structure; of a system. We wish to use D to analyze one of the simplest types of quantum correlations, those present in gaseous systems due to symmetry considerations. To this end we extend the LMC formalism to the grand canonical environment and show that D displays distinctive behaviors for simple gases, that allow for interesting insights into their structural properties.

Relationship among side channels, fish assemblages, and environmental gradients in the unimpounded Upper Mississippi River

USGS Publications Warehouse

Barko, V.A.; Herzog, D.P.

2003-01-01

We analyzed fish abundance and environmental data collected over nine years from six side channels of the unimpounded upper Mississippi River between river km 46.7 and 128.7. A partial canonical correspondence analysis revealed differences in fish assemblages and environmental factors correlated with the six side channels. Fishes correlated with open side channels represented large river species tolerant of current and/or turbidity. Fishes correlated with closed side channels represented assemblages preferring either moderate to low turbidity/current or pools.

Reading Ability as a Predictor of Academic Procrastination among African American Graduate Students

ERIC Educational Resources Information Center

Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.; Jiao, Qun G.

2008-01-01

The present study examined the relationship between reading ability (i.e., reading comprehension and reading vocabulary) and academic procrastination among 120 African American graduate students. A canonical correlation analysis revealed statistically significant and practically significant multivariate relationships between these two reading…

A Perspective on Quercus Life History Characteristics and Forest Diturbance

Treesearch

Richard P. Guyette; Rose-Marie Muzika; John Kabrick; Michael C. Stambaugh

2004-01-01

Plant strategy theory suggests that life history characteristics reflect growth and reproductive adaptations to environmental disturbance. Species characteristics and abundance should correspond to predictions based on competitive ability and maximizing fitness in a given disturbance environment. A significant canonical correlation between oak growth attributes (height...

Multidimensional Relationships in the WAIS-R Subscales and Demographic Variables.

ERIC Educational Resources Information Center

Chastain, Robert L.; Joe, George W.

This study attempts to integrate and extend previous research by multivariate investigation to determine multidimensional relationships among both the Wechsler Adult Intelligence Scale-Revised (WAIS-R) subscales and the demographic variables for the 1981 WAIS-R standardization sample. Canonical correlation with orthogonal rotation of composite…

Statistical field theory with constraints: Application to critical Casimir forces in the canonical ensemble.

PubMed

Gross, Markus; Gambassi, Andrea; Dietrich, S

2017-08-01

The effect of imposing a constraint on a fluctuating scalar order parameter field in a system of finite volume is studied within statistical field theory. The canonical ensemble, corresponding to a fixed total integrated order parameter (e.g., the total number of particles), is obtained as a special case of the theory. A perturbative expansion is developed which allows one to systematically determine the constraint-induced finite-volume corrections to the free energy and to correlation functions. In particular, we focus on the Landau-Ginzburg model in a film geometry (i.e., in a rectangular parallelepiped with a small aspect ratio) with periodic, Dirichlet, or Neumann boundary conditions in the transverse direction and periodic boundary conditions in the remaining, lateral directions. Within the expansion in terms of ε=4-d, where d is the spatial dimension of the bulk, the finite-size contribution to the free energy of the confined system and the associated critical Casimir force are calculated to leading order in ε and are compared to the corresponding expressions for an unconstrained (grand canonical) system. The constraint restricts the fluctuations within the system and it accordingly modifies the residual finite-size free energy. The resulting critical Casimir force is shown to depend on whether it is defined by assuming a fixed transverse area or a fixed total volume. In the former case, the constraint is typically found to significantly enhance the attractive character of the force as compared to the grand canonical case. In contrast to the grand canonical Casimir force, which, for supercritical temperatures, vanishes in the limit of thick films, in the canonical case with fixed transverse area the critical Casimir force attains for thick films a negative value for all boundary conditions studied here. Typically, the dependence of the critical Casimir force both on the temperaturelike and on the fieldlike scaling variables is different in the two ensembles.

Statistical field theory with constraints: Application to critical Casimir forces in the canonical ensemble

NASA Astrophysics Data System (ADS)

Gross, Markus; Gambassi, Andrea; Dietrich, S.

2017-08-01

The effect of imposing a constraint on a fluctuating scalar order parameter field in a system of finite volume is studied within statistical field theory. The canonical ensemble, corresponding to a fixed total integrated order parameter (e.g., the total number of particles), is obtained as a special case of the theory. A perturbative expansion is developed which allows one to systematically determine the constraint-induced finite-volume corrections to the free energy and to correlation functions. In particular, we focus on the Landau-Ginzburg model in a film geometry (i.e., in a rectangular parallelepiped with a small aspect ratio) with periodic, Dirichlet, or Neumann boundary conditions in the transverse direction and periodic boundary conditions in the remaining, lateral directions. Within the expansion in terms of ɛ =4 -d , where d is the spatial dimension of the bulk, the finite-size contribution to the free energy of the confined system and the associated critical Casimir force are calculated to leading order in ɛ and are compared to the corresponding expressions for an unconstrained (grand canonical) system. The constraint restricts the fluctuations within the system and it accordingly modifies the residual finite-size free energy. The resulting critical Casimir force is shown to depend on whether it is defined by assuming a fixed transverse area or a fixed total volume. In the former case, the constraint is typically found to significantly enhance the attractive character of the force as compared to the grand canonical case. In contrast to the grand canonical Casimir force, which, for supercritical temperatures, vanishes in the limit of thick films, in the canonical case with fixed transverse area the critical Casimir force attains for thick films a negative value for all boundary conditions studied here. Typically, the dependence of the critical Casimir force both on the temperaturelike and on the fieldlike scaling variables is different in the two ensembles.

A canonical theory of dynamic decision-making.

PubMed

Fox, John; Cooper, Richard P; Glasspool, David W

2013-01-01

Decision-making behavior is studied in many very different fields, from medicine and economics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptualization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering.

A Canonical Theory of Dynamic Decision-Making

PubMed Central

Fox, John; Cooper, Richard P.; Glasspool, David W.

2012-01-01

Decision-making behavior is studied in many very different fields, from medicine and economics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptualization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering. PMID:23565100

Noncanonical spike-related BOLD responses in focal epilepsy

PubMed Central

Lemieux, Louis; Laufs, Helmut; Carmichael, David; Paul, Joseph Suresh; Walker, Matthew C; Duncan, John S

2008-01-01

Till now, most studies of the Blood Oxygen Level-Dependent (BOLD) response to interictal epileptic discharges (IED) have assumed that its time course matches closely to that of brief physiological stimuli, commonly called the canonical event-related haemodynamic response function (canonical HRF). Analyses based on that assumption have produced significant response patterns that are generally concordant with prior electroclinical data. In this work, we used a more flexible model of the event-related response, a Fourier basis set, to investigate the presence of other responses in relation to individual IED in 30 experiments in patients with focal epilepsy. We found significant responses that had a noncanonical time course in 37% of cases, compared with 40% for the conventional, canonical HRF-based approach. In two cases, the Fourier analysis suggested activations where the conventional model did not. The noncanonical activations were almost always remote from the presumed generator of epileptiform activity. In the majority of cases with noncanonical responses, the noncanonical responses in single-voxel clusters were suggestive of artifacts. We did not find evidence for IED-related noncanonical HRFs arising from areas of pathology, suggesting that the BOLD response to IED is primarily canonical. Noncanonical responses may represent a number of phenomena, including artefacts and propagated epileptiform activity. Hum Brain Mapp 2008. © 2007 Wiley-Liss, Inc. PMID:17510926

Ensemble Canonical Correlation Prediction of Seasonal Precipitation Over the United States: Raising the Bar for Dynamical Model Forecasts

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, Kyu-Myong; Shen, S. P.

2001-01-01

This paper presents preliminary results of an ensemble canonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into non-overlapping sectors. The canonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all the regions of the US in every season compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible to the enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduces the spring predictability barrier over all the regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and additional local observations. The enhanced ECC forecast skill provides a new benchmark for evaluating dynamical model forecasts.

A Possible Literary Canon in Upper School English Literature in Various Australian States, 1945-2005

ERIC Educational Resources Information Center

Yiannakis, John

2014-01-01

Using information gathered from a specifically created database, ALIAS, this paper sets out to examine the variations and changes to the works that appeared on the English reading lists of the different Australian states in their literature course(s) between 1945 and 2005. All those states which offered a set of public examinations at the end of…

Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography

NASA Astrophysics Data System (ADS)

Kazantsev, Daniil; Jørgensen, Jakob S.; Andersen, Martin S.; Lionheart, William R. B.; Lee, Peter D.; Withers, Philip J.

2018-06-01

Rapid developments in photon-counting and energy-discriminating detectors have the potential to provide an additional spectral dimension to conventional x-ray grayscale imaging. Reconstructed spectroscopic tomographic data can be used to distinguish individual materials by characteristic absorption peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually correlated it can be advantageous to exploit this additional knowledge. In this paper, we propose a novel method which jointly reconstructs all energy channels while imposing a strong structural correlation. The core of the proposed algorithm is to employ a variational framework of parallel level sets to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction techniques including channel-wise total variation and correlative total nuclear variation regularization. Realistic simulation experiments demonstrate the performance improvements achievable by using correlative regularization methods.

Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework

NASA Astrophysics Data System (ADS)

Balaji, V.; Benson, Rusty; Wyman, Bruce; Held, Isaac

2016-10-01

Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by. We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath. We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models. We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.

Microcanonical thermodynamics and statistical fragmentation of dissipative systems. The topological structure of the N-body phase space

NASA Astrophysics Data System (ADS)

Gross, D. H. E.

1997-01-01

This review is addressed to colleagues working in different fields of physics who are interested in the concepts of microcanonical thermodynamics, its relation and contrast to ordinary, canonical or grandcanonical thermodynamics, and to get a first taste of the wide area of new applications of thermodynamical concepts like hot nuclei, hot atomic clusters and gravitating systems. Microcanonical thermodynamics describes how the volume of the N-body phase space depends on the globally conserved quantities like energy, angular momentum, mass, charge, etc. Due to these constraints the microcanonical ensemble can behave quite differently from the conventional, canonical or grandcanonical ensemble in many important physical systems. Microcanonical systems become inhomogeneous at first-order phase transitions, or with rising energy, or with external or internal long-range forces like Coulomb, centrifugal or gravitational forces. Thus, fragmentation of the system into a spatially inhomogeneous distribution of various regions of different densities and/or of different phases is a genuine characteristic of the microcanonical ensemble. In these cases which are realized by the majority of realistic systems in nature, the microcanonical approach is the natural statistical description. We investigate this most fundamental form of thermodynamics in four different nontrivial physical cases: (I) Microcanonical phase transitions of first and second order are studied within the Potts model. The total energy per particle is a nonfluctuating order parameter which controls the phase which the system is in. In contrast to the canonical form the microcanonical ensemble allows to tune the system continuously from one phase to the other through the region of coexisting phases by changing the energy smoothly. The configurations of coexisting phases carry important informations about the nature of the phase transition. This is more remarkable as the canonical ensemble is blind against these configurations. It is shown that the three basic quantities which specify a phase transition of first order - Transition temperature, latent heat, and interphase surface entropy - can be well determined for finite systems from the caloric equation of state T( E) in the coexistence region. Their values are already for a lattice of only ~ 30 ∗ 30 spins close to the ones of the corresponding infinite system. The significance of the backbending of the caloric equation of state T( E) is clarified. It is the signal for a phase transition of first order in a finite isolated system. (II) Fragmentation is shown to be a specific and generic phase transition of finite systems. The caloric equation of state T( E) for hot nuclei is calculated. The phase transition towards fragmentation can unambiguously be identified by the anomalies in T( E). As microcanonical thermodynamics is a full N-body theory it determines all many-body correlations as well. Consequently, various statistical multi-fragment correlations are investigated which give insight into the details of the equilibration mechanism. (III) Fragmentation of neutral and multiply charged atomic clusters is the next example of a realistic application of microcanonical thermodynamics. Our simulation method, microcanonical Metropolis Monte Carlo, combines the explicit microscopic treatment of the fragmentational degrees of freedom with the implicit treatment of the internal degrees of freedom of the fragments described by the experimental bulk specific heat. This micro-macro approach allows us to study the fragmentation of also larger fragments. Characteristic details of the fission of multiply charged metal clusters find their explanation by the different bulk properties. (IV) Finally, the fragmentation of strongly rotating nuclei is discussed as an example for a microcanonical ensemble under the action of a two-dimensional repulsive force.

Auditory-Phonetic Projection and Lexical Structure in the Recognition of Sine-Wave Words

ERIC Educational Resources Information Center

Remez, Robert E.; Dubowski, Kathryn R.; Broder, Robin S.; Davids, Morgana L.; Grossman, Yael S.; Moskalenko, Marina; Pardo, Jennifer S.; Hasbun, Sara Maria

2011-01-01

Speech remains intelligible despite the elimination of canonical acoustic correlates of phonemes from the spectrum. A portion of this perceptual flexibility can be attributed to modulation sensitivity in the auditory-to-phonetic projection, although signal-independent properties of lexical neighborhoods also affect intelligibility in utterances…

Elementary Students' Scientific Epistemological Beliefs in Relation to Socio-Economic Status and Gender

ERIC Educational Resources Information Center

Ozkal, Kudret; Tekkaya, Ceren; Sungur, Semra; Cakiroglu, Jale; Cakiroglu, Erdinc

2010-01-01

This study investigated students' scientific epistemological beliefs in relation to socio-economic status (SES) and gender. Data were obtained from 1,152 eight grade Turkish elementary school students using Scientific Epistemological Beliefs instrument. Canonical correlation analysis indicated that students with a working mother and educated…

The Relationship between Occupational Interests and Values

ERIC Educational Resources Information Center

Smith, Thomas J.; Campbell, Cynthia

2009-01-01

A values characterization of the RIASEC occupational interest categories was developed using the U.S. Department of Labor's O*NET occupational data. Values profile plots were constructed for each interest category, then correspondence analysis and canonical correlation were carried out to assess the relationship between the interest and values…

Five-Factor Model of Personality and Career Exploration

ERIC Educational Resources Information Center

Reed, Mary Beth; Bruch, Monroe A.; Haase, Richard F.

2004-01-01

This study investigates whether the dimensions of the five-factor model (FFM) of personality are related to specific career exploration variables. Based on the FFM, predictions were made about the relevance of particular traits to career exploration variables. Results from a canonical correlation analysis showed that variable loadings on three…

Civic Engagement in College Students: Connections between Involvement and Attitudes

ERIC Educational Resources Information Center

O'Leary, Lisa S.

2014-01-01

This chapter describes how canonical correlation was used in conjunction with an item response theory model to address the relationship between college students' civic engagement involvement and attitudes as undergraduates. The constructs of interest were students' participation in civic, political, and expressive activities, as well as…

An Extension of Dominance Analysis to Canonical Correlation Analysis

ERIC Educational Resources Information Center

Huo, Yan; Budescu, David V.

2009-01-01

Dominance analysis (Budescu, 1993) offers a general framework for determination of relative importance of predictors in univariate and multivariate multiple regression models. This approach relies on pairwise comparisons of the contribution of predictors in all relevant subset models. In this article we extend dominance analysis to canonical…

Inference on the Ranks of the Canonical Correlation Matrices for Elliptically Symmetric Populations.

DTIC Science & Technology

1985-05-01

robust estimates of the covariance matrix, the reader is referred to Devlin, Gnanadesikan and Kettenring (1975) and Maronna (1976). Murihead and...contoured distributions. J. Multivariate Anal. 11, 368-385. 6. DEVLIN, S.J. GNANADESIKAN , R. and KETTENRING, J. (1975). Robust estima- tion and outlier

Loss of FTO antagonises Wnt signaling and leads to developmental defects associated with ciliopathies.

PubMed

Osborn, Daniel P S; Roccasecca, Rosa Maria; McMurray, Fiona; Hernandez-Hernandez, Victor; Mukherjee, Sriparna; Barroso, Inês; Stemple, Derek; Cox, Roger; Beales, Philip L; Christou-Savina, Sonia

2014-01-01

Common intronic variants in the Human fat mass and obesity-associated gene (FTO) are found to be associated with an increased risk of obesity. Overexpression of FTO correlates with increased food intake and obesity, whilst loss-of-function results in lethality and severe developmental defects. Despite intense scientific discussions around the role of FTO in energy metabolism, the function of FTO during development remains undefined. Here, we show that loss of Fto leads to developmental defects such as growth retardation, craniofacial dysmorphism and aberrant neural crest cells migration in Zebrafish. We find that the important developmental pathway, Wnt, is compromised in the absence of FTO, both in vivo (zebrafish) and in vitro (Fto(-/-) MEFs and HEK293T). Canonical Wnt signalling is down regulated by abrogated β-Catenin translocation to the nucleus whilst non-canonical Wnt/Ca(2+) pathway is activated via its key signal mediators CaMKII and PKCδ. Moreover, we demonstrate that loss of Fto results in short, absent or disorganised cilia leading to situs inversus, renal cystogenesis, neural crest cell defects and microcephaly in Zebrafish. Congruently, Fto knockout mice display aberrant tissue specific cilia. These data identify FTO as a protein-regulator of the balanced activation between canonical and non-canonical branches of the Wnt pathway. Furthermore, we present the first evidence that FTO plays a role in development and cilia formation/function.

Correlations in star networks: from Bell inequalities to network inequalities

NASA Astrophysics Data System (ADS)

Tavakoli, Armin; Olivier Renou, Marc; Gisin, Nicolas; Brunner, Nicolas

2017-07-01

The problem of characterizing classical and quantum correlations in networks is considered. Contrary to the usual Bell scenario, where distant observers share a physical system emitted by one common source, a network features several independent sources, each distributing a physical system to a subset of observers. In the quantum setting, the observers can perform joint measurements on initially independent systems, which may lead to strong correlations across the whole network. In this work, we introduce a technique to systematically map a Bell inequality to a family of Bell-type inequalities bounding classical correlations on networks in a star-configuration. Also, we show that whenever a given Bell inequality can be violated by some entangled state ρ, then all the corresponding network inequalities can be violated by considering many copies of ρ distributed in the star network. The relevance of these ideas is illustrated by applying our method to a specific multi-setting Bell inequality. We derive the corresponding network inequalities, and study their quantum violations.

Babbling in children with neurodevelopmental disability and validity of a simplified way of measuring canonical babbling ratio.

PubMed

Nyman, Anna; Lohmander, Anette

2018-01-01

Babbling is an important precursor to speech, but has not yet been thoroughly investigated in children with neurodevelopmental disabilities. Canonical babbling ratio (CBR) is a commonly used but time-consuming measure for quantifying babbling. The aim of this study was twofold: to validate a simplified version of the CBR (CBR UTTER ), and to use this measure to determine if early precursors to speech and language development could be detected in children with different neurodevelopmental disabilities. Two different data sets were used. In Part I, CBR UTTER was compared to two other CBR measures using previously obtained phonetic transcriptions of 3571 utterances from 38 audio recordings of 12-18 month old children with and without cleft palate. In CBR UTTER , number of canonical utterances was divided by total number of utterances. In CBR syl , number of canonical syllables was divided by total number of syllables. In CBR utt , number of canonical syllables was divided by total number of utterances. High agreement was seen between CBR UTTER and CBR syl , suggesting CBR UTTER as an alternative. In Part II, babbling in children with neurodevelopmental disability was examined. Eighteen children aged 12-22 months with Down syndrome, cerebral palsy or developmental delay were audio-video recorded during interaction with a parent. Recordings were analysed by observation of babbling, consonant production, calculation of CBR UTTER , and compared to data from controls. The study group showed significantly lower occurrence of all variables, except for of plosives. The long-term relevance of the findings for the speech and language development of the children needs to be investigated.

Get Your Atoms in Order--An Open-Source Implementation of a Novel and Robust Molecular Canonicalization Algorithm.

PubMed

Schneider, Nadine; Sayle, Roger A; Landrum, Gregory A

2015-10-26

Finding a canonical ordering of the atoms in a molecule is a prerequisite for generating a unique representation of the molecule. The canonicalization of a molecule is usually accomplished by applying some sort of graph relaxation algorithm, the most common of which is the Morgan algorithm. There are known issues with that algorithm that lead to noncanonical atom orderings as well as problems when it is applied to large molecules like proteins. Furthermore, each cheminformatics toolkit or software provides its own version of a canonical ordering, most based on unpublished algorithms, which also complicates the generation of a universal unique identifier for molecules. We present an alternative canonicalization approach that uses a standard stable-sorting algorithm instead of a Morgan-like index. Two new invariants that allow canonical ordering of molecules with dependent chirality as well as those with highly symmetrical cyclic graphs have been developed. The new approach proved to be robust and fast when tested on the 1.45 million compounds of the ChEMBL 20 data set in different scenarios like random renumbering of input atoms or SMILES round tripping. Our new algorithm is able to generate a canonical order of the atoms of protein molecules within a few milliseconds. The novel algorithm is implemented in the open-source cheminformatics toolkit RDKit. With this paper, we provide a reference Python implementation of the algorithm that could easily be integrated in any cheminformatics toolkit. This provides a first step toward a common standard for canonical atom ordering to generate a universal unique identifier for molecules other than InChI.

Utilization of an Enhanced Canonical Correlation Analysis (ECCA) to Predict Daily Precipitation and Temperature in a Semi-Arid Environment

NASA Astrophysics Data System (ADS)

Lopez, S. R.; Hogue, T. S.

2011-12-01

Global climate models (GCMs) are primarily used to generate historical and future large-scale circulation patterns at a coarse resolution (typical order of 50,000 km2) and fail to capture climate variability at the ground level due to localized surface influences (i.e topography, marine, layer, land cover, etc). Their inability to accurately resolve these processes has led to the development of numerous 'downscaling' techniques. The goal of this study is to enhance statistical downscaling of daily precipitation and temperature for regions with heterogeneous land cover and topography. Our analysis was divided into two periods, historical (1961-2000) and contemporary (1980-2000), and tested using sixteen predictand combinations from four GCMs (GFDL CM2.0, GFDL CM2.1, CNRM-CM3 and MRI-CGCM2 3.2a. The Southern California area was separated into five county regions: Santa Barbara, Ventura, Los Angeles, Orange and San Diego. Principle component analysis (PCA) was performed on ground-based observations in order to (1) reduce the number of redundant gauges and minimize dimensionality and (2) cluster gauges that behave statistically similarly for post-analysis. Post-PCA analysis included extensive testing of predictor-predictand relationships using an enhanced canonical correlation analysis (ECCA). The ECCA includes obtaining the optimal predictand sets for all models within each spatial domain (county) as governed by daily and monthly overall statistics. Results show all models maintain mean annual and monthly behavior within each county and daily statistics are improved. The level of improvement highly depends on the vegetation extent within each county and the land-to-ocean ratio within the GCM spatial grid. The utilization of the entire historical period also leads to better statistical representation of observed daily precipitation. The validated ECCA technique is being applied to future climate scenarios distributed by the IPCC in order to provide forcing data for regional hydrologic models and assess future water resources in the Southern California region.

Extraction of the brachialis muscle activity using HD-sEMG technique and canonical correlation analysis.

PubMed

Al Harrach, M; Afsharipour, B; Boudaoud, S; Carriou, V; Marin, F; Merletti, R

2016-08-01

The Brachialis (BR) is placed under the Biceps Brachii (BB) deep in the upper arm. Therefore, the detection of the corresponding surface Electromyogram (sEMG) is a complex task. The BR is an important elbow flexor, but it is usually not considered in the sEMG based force estimation process. The aim of this study was to attempt to separate the two sEMG activities of the BR and the BB by using a High Density sEMG (HD-sEMG) grid placed at the upper arm and Canonical Component Analysis (CCA) technique. For this purpose, we recorded sEMG signals from seven subjects with two 8 × 4 electrode grids placed over BB and BR. Four isometric voluntary contraction levels were recorded (5, 10, 30 and 50 %MVC) for 90° elbow angle. Then using CCA and image processing tools the sources of each muscle activity were separated. Finally, the corresponding sEMG signals were reconstructed using the remaining canonical components in order to retrieve the activity of the BB and the BR muscles.

Free Fermions and the Classical Compact Groups

NASA Astrophysics Data System (ADS)

Cunden, Fabio Deelan; Mezzadri, Francesco; O'Connell, Neil

2018-06-01

There is a close connection between the ground state of non-interacting fermions in a box with classical (absorbing, reflecting, and periodic) boundary conditions and the eigenvalue statistics of the classical compact groups. The associated determinantal point processes can be extended in two natural directions: (i) we consider the full family of admissible quantum boundary conditions (i.e., self-adjoint extensions) for the Laplacian on a bounded interval, and the corresponding projection correlation kernels; (ii) we construct the grand canonical extensions at finite temperature of the projection kernels, interpolating from Poisson to random matrix eigenvalue statistics. The scaling limits in the bulk and at the edges are studied in a unified framework, and the question of universality is addressed. Whether the finite temperature determinantal processes correspond to the eigenvalue statistics of some matrix models is, a priori, not obvious. We complete the picture by constructing a finite temperature extension of the Haar measure on the classical compact groups. The eigenvalue statistics of the resulting grand canonical matrix models (of random size) corresponds exactly to the grand canonical measure of free fermions with classical boundary conditions.

Concentration-dependent and configuration-dependent interactions of monovalent ions with an RNA tetraloop

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

Miner, Jacob Carlson; Garcia, Angel Enrique

Monovalent salt solutions have strongly coupled interactions with biopolymers, from large polyelectrolytes to small RNA oligomers. High salt concentrations have been known to induce transitions in the structure of RNA, producing non-canonical configurations and even driving RNA to precipitate out of solution. Using all-atom molecular dynamics simulations, we model a monovalent salt species (KCL) at high concentrations (0.1–3m) and calculate the equilibrium distributions of water and ions around a small tetraloop-forming RNA oligomer in a variety of structural arrangements: folded A-RNA (canonical) and Z-RNA (non-canonical) tetraloops and unfolded configurations. From these data, we calculate the ion preferential binding coefficients andmore » Donnan coefficients for the RNA oligomer as a function of concentration and structure. We find that cation accumulation is highest around non-canonical Z-RNA configurations at concentrations below 0.5m, while unfolded configurations accumulate the most co-ions in all concentrations. By contrast, canonical A-RNA structures consistently show the lowest accumulations for all ion species. Water distributions vary markedly with RNA configuration but show little dependency on KCL concentration. Based on Donnan coefficient calculations, the net charge of the solution at the surface of the RNA decreases linearly as a function of salt concentration and becomes net-neutral near 2.5–3m KCL for folded configurations, while unfolded configurations still show a positive solution charge. Our findings show that all-atom molecular dynamics can describe the equilibrium distributions of monovalent salt in the presence of small RNA oligomers at KCL concentrations where ion correlation effects become important. Furthermore, these results provide valuable insights into the distributions of water and ions near the RNA oligomer surface as a function of structural configuration.« less

Concentration-dependent and configuration-dependent interactions of monovalent ions with an RNA tetraloop

DOE PAGES

Miner, Jacob Carlson; Garcia, Angel Enrique

2018-05-29

Monovalent salt solutions have strongly coupled interactions with biopolymers, from large polyelectrolytes to small RNA oligomers. High salt concentrations have been known to induce transitions in the structure of RNA, producing non-canonical configurations and even driving RNA to precipitate out of solution. Using all-atom molecular dynamics simulations, we model a monovalent salt species (KCL) at high concentrations (0.1–3m) and calculate the equilibrium distributions of water and ions around a small tetraloop-forming RNA oligomer in a variety of structural arrangements: folded A-RNA (canonical) and Z-RNA (non-canonical) tetraloops and unfolded configurations. From these data, we calculate the ion preferential binding coefficients andmore » Donnan coefficients for the RNA oligomer as a function of concentration and structure. We find that cation accumulation is highest around non-canonical Z-RNA configurations at concentrations below 0.5m, while unfolded configurations accumulate the most co-ions in all concentrations. By contrast, canonical A-RNA structures consistently show the lowest accumulations for all ion species. Water distributions vary markedly with RNA configuration but show little dependency on KCL concentration. Based on Donnan coefficient calculations, the net charge of the solution at the surface of the RNA decreases linearly as a function of salt concentration and becomes net-neutral near 2.5–3m KCL for folded configurations, while unfolded configurations still show a positive solution charge. Our findings show that all-atom molecular dynamics can describe the equilibrium distributions of monovalent salt in the presence of small RNA oligomers at KCL concentrations where ion correlation effects become important. Furthermore, these results provide valuable insights into the distributions of water and ions near the RNA oligomer surface as a function of structural configuration.« less

Concentration-dependent and configuration-dependent interactions of monovalent ions with an RNA tetraloop

NASA Astrophysics Data System (ADS)

Miner, Jacob Carlson; García, Angel Enrique

2018-06-01

Monovalent salt solutions have strongly coupled interactions with biopolymers, from large polyelectrolytes to small RNA oligomers. High salt concentrations have been known to induce transitions in the structure of RNA, producing non-canonical configurations and even driving RNA to precipitate out of solution. Using all-atom molecular dynamics simulations, we model a monovalent salt species (KCL) at high concentrations (0.1-3m) and calculate the equilibrium distributions of water and ions around a small tetraloop-forming RNA oligomer in a variety of structural arrangements: folded A-RNA (canonical) and Z-RNA (non-canonical) tetraloops and unfolded configurations. From these data, we calculate the ion preferential binding coefficients and Donnan coefficients for the RNA oligomer as a function of concentration and structure. We find that cation accumulation is highest around non-canonical Z-RNA configurations at concentrations below 0.5m, while unfolded configurations accumulate the most co-ions in all concentrations. By contrast, canonical A-RNA structures consistently show the lowest accumulations for all ion species. Water distributions vary markedly with RNA configuration but show little dependency on KCL concentration. Based on Donnan coefficient calculations, the net charge of the solution at the surface of the RNA decreases linearly as a function of salt concentration and becomes net-neutral near 2.5-3m KCL for folded configurations, while unfolded configurations still show a positive solution charge. Our findings show that all-atom molecular dynamics can describe the equilibrium distributions of monovalent salt in the presence of small RNA oligomers at KCL concentrations where ion correlation effects become important. Furthermore, these results provide valuable insights into the distributions of water and ions near the RNA oligomer surface as a function of structural configuration.

Concentration-dependent and configuration-dependent interactions of monovalent ions with an RNA tetraloop.

PubMed

Miner, Jacob Carlson; García, Angel Enrique

2018-06-14

Monovalent salt solutions have strongly coupled interactions with biopolymers, from large polyelectrolytes to small RNA oligomers. High salt concentrations have been known to induce transitions in the structure of RNA, producing non-canonical configurations and even driving RNA to precipitate out of solution. Using all-atom molecular dynamics simulations, we model a monovalent salt species (KCL) at high concentrations (0.1-3m) and calculate the equilibrium distributions of water and ions around a small tetraloop-forming RNA oligomer in a variety of structural arrangements: folded A-RNA (canonical) and Z-RNA (non-canonical) tetraloops and unfolded configurations. From these data, we calculate the ion preferential binding coefficients and Donnan coefficients for the RNA oligomer as a function of concentration and structure. We find that cation accumulation is highest around non-canonical Z-RNA configurations at concentrations below 0.5m, while unfolded configurations accumulate the most co-ions in all concentrations. By contrast, canonical A-RNA structures consistently show the lowest accumulations for all ion species. Water distributions vary markedly with RNA configuration but show little dependency on KCL concentration. Based on Donnan coefficient calculations, the net charge of the solution at the surface of the RNA decreases linearly as a function of salt concentration and becomes net-neutral near 2.5-3m KCL for folded configurations, while unfolded configurations still show a positive solution charge. Our findings show that all-atom molecular dynamics can describe the equilibrium distributions of monovalent salt in the presence of small RNA oligomers at KCL concentrations where ion correlation effects become important. Furthermore, these results provide valuable insights into the distributions of water and ions near the RNA oligomer surface as a function of structural configuration.

Efficient selection of tagging single-nucleotide polymorphisms in multiple populations.

PubMed

Howie, Bryan N; Carlson, Christopher S; Rieder, Mark J; Nickerson, Deborah A

2006-08-01

Common genetic polymorphism may explain a portion of the heritable risk for common diseases, so considerable effort has been devoted to finding and typing common single-nucleotide polymorphisms (SNPs) in the human genome. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), suggesting that only a subset of all SNPs (known as tagging SNPs, or tagSNPs) need to be genotyped for disease association studies. Based on the genetic differences that exist among human populations, most tagSNP sets are defined in a single population and applied only in populations that are closely related. To improve the efficiency of multi-population analyses, we have developed an algorithm called MultiPop-TagSelect that finds a near-minimal union of population-specific tagSNP sets across an arbitrary number of populations. We present this approach as an extension of LD-select, a tagSNP selection method that uses a greedy algorithm to group SNPs into bins based on their pairwise association patterns, although the MultiPop-TagSelect algorithm could be used with any SNP tagging approach that allows choices between nearly equivalent SNPs. We evaluate the algorithm by considering tagSNP selection in candidate-gene resequencing data and lower density whole-chromosome data. Our analysis reveals that an exhaustive search is often intractable, while the developed algorithm can quickly and reliably find near-optimal solutions even for difficult tagSNP selection problems. Using populations of African, Asian, and European ancestry, we also show that an optimal multi-population set of tagSNPs can be substantially smaller (up to 44%) than a typical set obtained through independent or sequential selection.

On the quantization of the massless Bateman system

NASA Astrophysics Data System (ADS)

Takahashi, K.

2018-03-01

The so-called Bateman system for the damped harmonic oscillator is reduced to a genuine dual dissipation system (DDS) by setting the mass to zero. We explore herein the condition under which the canonical quantization of the DDS is consistently performed. The roles of the observable and auxiliary coordinates are discriminated. The results show that the complete and orthogonal Fock space of states can be constructed on the stable vacuum if an anti-Hermite representation of the canonical Hamiltonian is adopted. The amplitude of the one-particle wavefunction is consistent with the classical solution. The fields can be quantized as bosonic or fermionic. For bosonic systems, the quantum fluctuation of the field is directly associated with the dissipation rate.

Multisensory integration: flexible use of general operations

PubMed Central

van Atteveldt, Nienke; Murray, Micah M.; Thut, Gregor; Schroeder, Charles

2014-01-01

Research into the anatomical substrates and “principles” for integrating inputs from separate sensory surfaces has yielded divergent findings. This suggests that multisensory integration is flexible and context-dependent, and underlines the need for dynamically adaptive neuronal integration mechanisms. We propose that flexible multisensory integration can be explained by a combination of canonical, population-level integrative operations, such as oscillatory phase-resetting and divisive normalization. These canonical operations subsume multisensory integration into a fundamental set of principles as to how the brain integrates all sorts of information, and they are being used proactively and adaptively. We illustrate this proposition by unifying recent findings from different research themes such as timing, behavioral goal and experience-related differences in integration. PMID:24656248

A multimodal spatiotemporal cardiac motion atlas from MR and ultrasound data.

PubMed

Puyol-Antón, Esther; Sinclair, Matthew; Gerber, Bernhard; Amzulescu, Mihaela Silvia; Langet, Hélène; Craene, Mathieu De; Aljabar, Paul; Piro, Paolo; King, Andrew P

2017-08-01

Cardiac motion atlases provide a space of reference in which the motions of a cohort of subjects can be directly compared. Motion atlases can be used to learn descriptors that are linked to different pathologies and which can subsequently be used for diagnosis. To date, all such atlases have been formed and applied using data from the same modality. In this work we propose a framework to build a multimodal cardiac motion atlas from 3D magnetic resonance (MR) and 3D ultrasound (US) data. Such an atlas will benefit from the complementary motion features derived from the two modalities, and furthermore, it could be applied in clinics to detect cardiovascular disease using US data alone. The processing pipeline for the formation of the multimodal motion atlas initially involves spatial and temporal normalisation of subjects' cardiac geometry and motion. This step was accomplished following a similar pipeline to that proposed for single modality atlas formation. The main novelty of this paper lies in the use of a multi-view algorithm to simultaneously reduce the dimensionality of both the MR and US derived motion data in order to find a common space between both modalities to model their variability. Three different dimensionality reduction algorithms were investigated: principal component analysis, canonical correlation analysis and partial least squares regression (PLS). A leave-one-out cross validation on a multimodal data set of 50 volunteers was employed to quantify the accuracy of the three algorithms. Results show that PLS resulted in the lowest errors, with a reconstruction error of less than 2.3 mm for MR-derived motion data, and less than 2.5  mm for US-derived motion data. In addition, 1000 subjects from the UK Biobank database were used to build a large scale monomodal data set for a systematic validation of the proposed algorithms. Our results demonstrate the feasibility of using US data alone to analyse cardiac function based on a multimodal motion atlas. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Providing data science support for systems pharmacology and its implications to drug discovery.

PubMed

Hart, Thomas; Xie, Lei

2016-01-01

The conventional one-drug-one-target-one-disease drug discovery process has been less successful in tracking multi-genic, multi-faceted complex diseases. Systems pharmacology has emerged as a new discipline to tackle the current challenges in drug discovery. The goal of systems pharmacology is to transform huge, heterogeneous, and dynamic biological and clinical data into interpretable and actionable mechanistic models for decision making in drug discovery and patient treatment. Thus, big data technology and data science will play an essential role in systems pharmacology. This paper critically reviews the impact of three fundamental concepts of data science on systems pharmacology: similarity inference, overfitting avoidance, and disentangling causality from correlation. The authors then discuss recent advances and future directions in applying the three concepts of data science to drug discovery, with a focus on proteome-wide context-specific quantitative drug target deconvolution and personalized adverse drug reaction prediction. Data science will facilitate reducing the complexity of systems pharmacology modeling, detecting hidden correlations between complex data sets, and distinguishing causation from correlation. The power of data science can only be fully realized when integrated with mechanism-based multi-scale modeling that explicitly takes into account the hierarchical organization of biological systems from nucleic acid to proteins, to molecular interaction networks, to cells, to tissues, to patients, and to populations.

Can multi-slice or navigator-gated R2* MRI replace single-slice breath-hold acquisition for hepatic iron quantification?

PubMed

Loeffler, Ralf B; McCarville, M Beth; Wagstaff, Anne W; Smeltzer, Matthew P; Krafft, Axel J; Song, Ruitian; Hankins, Jane S; Hillenbrand, Claudia M

2017-01-01

Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be interchangeably used in existing R2*-HIC calibrations.

Towards a psychopathology specific to Substance Use Disorder: Should emotional responses to life events be included?

PubMed

Maremmani, Angelo G I; Maiello, Marco; Carbone, Manuel Glauco; Pallucchini, Alessandro; Brizzi, Francesca; Belcari, Iacopo; Conversano, Ciro; Perugi, Giulio; Maremmani, Icro

2018-01-01

The severity of emotional responses to life events (PTSD spectrum) as part of Post Traumatic Stress Disorder (PTSD) in Substance Use Disorder (SUD) patients has often been considered from a unitary perspective. Light has also been shed on the possible definition of a specific psychopathology of SUD patients. This psychopathology has been proved to be independent of treatment choice, of being active in using substances, of lifetime psychiatric comorbidity and primary substance of abuse (heroin, alcohol, cocaine). To further support this unitary perspective, in this study we have compared the severity and typology of the five psychopathological dimensions found in SUD patients, by dividing 93 HUD patients (77.4% males and 22.6% females), characterized by the lifetime absence of exposure to actual or threatened death, serious injury, or sexual violence, on the basis of the severity of their PTSD spectrum. We used the cut-off that differentiated people developing (High PTSD spectrum; H-PTSD/S) or not developing (Low PTSD spectrum; L-PTSD/S) a PTSD after the earthquake that hit L'Aquila, Italy, in April 2009. Using a canonical correlation analysis, the significant (p<0.001) canonical variate set-one (psychopathology) is saturated negatively by "panic anxiety" and positively by the "worthlessness-being trapped" and "violence-suicide" dimensions. Set-two (PTSD spectrum) is saturated negatively by "emotional, physical and cognitive responses to loss and traumas", and positively by "grief reactions", "re-experiencing numbing", "arousal symptoms" and "personality traits". When comparing the two groups, all five psychopathological dimensions were significantly more severe in H-PTSD/S patients, who were distinguished by higher values of worthlessness-being trapped, sensitivity-psychoticism and violence-suicide symptomatology. No differences were observed regarding the typology of psychopathology. This study further supports the SUD-PTSD spectrum unitary perspective and argues in favor of the inclusion of the PTSD spectrum in the psychopathology of SUD. Copyright © 2017 Elsevier Inc. All rights reserved.

Hamilton-Jacobi formalism for Podolsky's electromagnetic theory on the null-plane

NASA Astrophysics Data System (ADS)

Bertin, M. C.; Pimentel, B. M.; Valcárcel, C. E.; Zambrano, G. E. R.

2017-08-01

We develop the Hamilton-Jacobi formalism for Podolsky's electromagnetic theory on the null-plane. The main goal is to build the complete set of Hamiltonian generators of the system as well as to study the canonical and gauge transformations of the theory.

Canonical Naimark extension for generalized measurements involving sets of Pauli quantum observables chosen at random

NASA Astrophysics Data System (ADS)

Sparaciari, Carlo; Paris, Matteo G. A.

2013-01-01

We address measurement schemes where certain observables Xk are chosen at random within a set of nondegenerate isospectral observables and then measured on repeated preparations of a physical system. Each observable has a probability zk to be measured, with ∑kzk=1, and the statistics of this generalized measurement is described by a positive operator-valued measure. This kind of scheme is referred to as quantum roulettes, since each observable Xk is chosen at random, e.g., according to the fluctuating value of an external parameter. Here we focus on quantum roulettes for qubits involving the measurements of Pauli matrices, and we explicitly evaluate their canonical Naimark extensions, i.e., their implementation as indirect measurements involving an interaction scheme with a probe system. We thus provide a concrete model to realize the roulette without destroying the signal state, which can be measured again after the measurement or can be transmitted. Finally, we apply our results to the description of Stern-Gerlach-like experiments on a two-level system.

Turbulent scaling laws as solutions of the multi-point correlation equation using statistical symmetries

NASA Astrophysics Data System (ADS)

Oberlack, Martin; Rosteck, Andreas; Avsarkisov, Victor

2013-11-01

Text-book knowledge proclaims that Lie symmetries such as Galilean transformation lie at the heart of fluid dynamics. These important properties also carry over to the statistical description of turbulence, i.e. to the Reynolds stress transport equations and its generalization, the multi-point correlation equations (MPCE). Interesting enough, the MPCE admit a much larger set of symmetries, in fact infinite dimensional, subsequently named statistical symmetries. Most important, theses new symmetries have important consequences for our understanding of turbulent scaling laws. The symmetries form the essential foundation to construct exact solutions to the infinite set of MPCE, which in turn are identified as classical and new turbulent scaling laws. Examples on various classical and new shear flow scaling laws including higher order moments will be presented. Even new scaling have been forecasted from these symmetries and in turn validated by DNS. Turbulence modellers have implicitly recognized at least one of the statistical symmetries as this is the basis for the usual log-law which has been employed for calibrating essentially all engineering turbulence models. An obvious conclusion is to generally make turbulence models consistent with the new statistical symmetries.

Screening metal-organic frameworks for selective noble gas adsorption in air: effect of pore size and framework topology.

PubMed

Parkes, Marie V; Staiger, Chad L; Perry, John J; Allendorf, Mark D; Greathouse, Jeffery A

2013-06-21

The adsorption of noble gases and nitrogen by sixteen metal-organic frameworks (MOFs) was investigated using grand canonical Monte Carlo simulation. The MOFs were chosen to represent a variety of net topologies, pore dimensions, and metal centers. Three commercially available MOFs (HKUST-1, AlMIL-53, and ZIF-8) and PCN-14 were also included for comparison. Experimental adsorption isotherms, obtained from volumetric and gravimetric methods, were used to compare krypton, argon, and nitrogen uptake with the simulation results. Simulated trends in gas adsorption and predicted selectivities among the commercially available MOFs are in good agreement with experiment. In the low pressure regime, the expected trend of increasing adsorption with increasing noble gas polarizabilty is seen. For each noble gas, low pressure adsorption correlates with several MOF properties, including free volume, topology, and metal center. Additionally, a strong correlation exists between the Henry's constant and the isosteric heat of adsorption for all gases and MOFs considered. Finally, we note that the simulated and experimental gas selectivities demonstrated by this small set of MOFs show improved performance compared to similar values reported for zeolites.

Angiopoietin-1, Angiopoietin-2 and Bicarbonate as Diagnostic Biomarkers in Children with Severe Sepsis

PubMed Central

Wang, Kun; Bhandari, Vineet; Giuliano, John S.; O′Hern, Corey S.; Shattuck, Mark D.; Kirby, Michael

2014-01-01

Severe pediatric sepsis continues to be associated with high mortality rates in children. Thus, an important area of biomedical research is to identify biomarkers that can classify sepsis severity and outcomes. The complex and heterogeneous nature of sepsis makes the prospect of the classification of sepsis severity using a single biomarker less likely. Instead, we employ machine learning techniques to validate the use of a multiple biomarkers scoring system to determine the severity of sepsis in critically ill children. The study was based on clinical data and plasma samples provided by a tertiary care center's Pediatric Intensive Care Unit (PICU) from a group of 45 patients with varying sepsis severity at the time of admission. Canonical Correlation Analysis with the Forward Selection and Random Forests methods identified a particular set of biomarkers that included Angiopoietin-1 (Ang-1), Angiopoietin-2 (Ang-2), and Bicarbonate (HCO) as having the strongest correlations with sepsis severity. The robustness and effectiveness of these biomarkers for classifying sepsis severity were validated by constructing a linear Support Vector Machine diagnostic classifier. We also show that the concentrations of Ang-1, Ang-2, and HCO enable predictions of the time dependence of sepsis severity in children. PMID:25255212

Building Multi-Discipline, Multi-Format Digital Libraries Using Clusters and Buckets. Degree rewarded by Old Dominion Univ. on Aug. 1997

NASA Technical Reports Server (NTRS)

Nelson, Michael L.

1997-01-01

Our objective was to study the feasibility of extending the Dienst protocol to enable a multi-discipline, multi-format digital library. We implemented two new technologies: cluster functionality and publishing buckets. We have designed a possible implementation of clusters and buckets, and have prototyped some aspects of the resultant digital library. Currently, digital libraries are segregated by the disciplines they serve (computer science, aeronautics, etc.), and by the format of their holdings (reports, software, datasets, etc.). NCSTRL+ is a multi-discipline, multi-format digital library (DL) prototype created to explore the feasibility of the design and implementation issues involved with created a unified, canonical scientific and technical information (STI) DL. NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible DL that provides access to over 80 university departments and laboratories. We have extended the Dienst protocol (version 4.1.8), the protocol underlying NCSTRL, to provide the ability to cluster independent collections into a logically centralized DL based upon subject category classification, type of organization, and genre of material. The concept of buckets provides a mechanism for publishing and managing logically linked entities with multiple data formats.

Multi-modality 3D breast imaging with X-Ray tomosynthesis and automated ultrasound.

PubMed

Sinha, Sumedha P; Roubidoux, Marilyn A; Helvie, Mark A; Nees, Alexis V; Goodsitt, Mitchell M; LeCarpentier, Gerald L; Fowlkes, J Brian; Chalek, Carl L; Carson, Paul L

2007-01-01

This study evaluated the utility of 3D automated ultrasound in conjunction with 3D digital X-Ray tomosynthesis for breast cancer detection and assessment, to better localize and characterize lesions in the breast. Tomosynthesis image volumes and automated ultrasound image volumes were acquired in the same geometry and in the same view for 27 patients. 3 MQSA certified radiologists independently reviewed the image volumes, visually correlating the images from the two modalities with in-house software. More sophisticated software was used on a smaller set of 10 cases, which enabled the radiologist to draw a 3D box around the suspicious lesion in one image set and isolate an anatomically correlated, similarly boxed region in the other modality image set. In the primary study, correlation was found to be moderately useful to the readers. In the additional study, using improved software, the median usefulness rating increased and confidence in localizing and identifying the suspicious mass increased in more than half the cases. As automated scanning and reading software techniques advance, superior results are expected.

Correlations, soliton modes, and non-Hermitian linear mode transmutation in the one-dimensional noisy Burgers equation.

PubMed

Fogedby, Hans C

2003-08-01

Using the previously developed canonical phase space approach applied to the noisy Burgers equation in one dimension, we discuss in detail the growth morphology in terms of nonlinear soliton modes and superimposed linear modes. We moreover analyze the non-Hermitian character of the linear mode spectrum and the associated dynamical pinning, and mode transmutation from diffusive to propagating behavior induced by the solitons. We discuss the anomalous diffusion of growth modes, switching and pathways, correlations in the multisoliton sector, and in detail the correlations and scaling properties in the two-soliton sector.

A multi-scale study of the adsorption of lanthanum on the (110) surface of tungsten

NASA Astrophysics Data System (ADS)

Samin, Adib J.; Zhang, Jinsuo

2016-07-01

In this study, we utilize a multi-scale approach to studying lanthanum adsorption on the (110) plane of tungsten. The energy of the system is described from density functional theory calculations within the framework of the cluster expansion method. It is found that including two-body figures up to the sixth nearest neighbor yielded a reasonable agreement with density functional theory calculations as evidenced by the reported cross validation score. The results indicate that the interaction between the adsorbate atoms in the adlayer is important and cannot be ignored. The parameterized cluster expansion expression is used in a lattice gas Monte Carlo simulation in the grand canonical ensemble at 773 K and the adsorption isotherm is recorded. Implications of the obtained results for the pyroprocessing application are discussed.

Association between somatotypes and blood pressure in an adult Chuvasha population.

PubMed

Kalichman, Leonid; Livshits, Gregory; Kobyliansky, Eugene

2004-01-01

The relationship between blood pressure (BP) and anthropometrical characteristics has been indeed examined extensively, but only a few studies have investigated any connection of somatotypes to BP. to evaluate the association between BP and various anthropometrical characteristics, including components of somatotypes (using the methods of Heath and Carter and of Deriabin). The study sample comprised 783 males aged 18-89 years and 720 females aged 18-90 years, all residents of the Chuvasha, Russian Federation. We used multiple regression, Pearson's and canonical correlation analyses. Significant correlations (r = 0.19-0.28, p < 0.05) were obtained between BP and anthropometric characteristics associated with body compositions and somatotypes. The most impressive were the canonical correlations between BP and somatotype components derived according to Heath and Carter (0.275), and according to Deriabin's (0.333) method. Different body types were highly significantly (P < 0.001) associated with systolic and diastolic BP. Individuals of robust physique (with high endomorphy and mesomorphy) showed high mean values of systolic and diastolic BP, whereas the smallest persons had the lowest BP values. These findings suggest the existence of common physiological paths in the development of body physique and blood pressure regulation and may possibly be indicative of the involvement of pleiotropic genetic and/or epigenetic mechanisms in this regulation.

Structure, dynamics and RNA binding of the multi-domain splicing factor TIA-1

PubMed Central

Wang, Iren; Hennig, Janosch; Jagtap, Pravin Kumar Ankush; Sonntag, Miriam; Valcárcel, Juan; Sattler, Michael

2014-01-01

Alternative pre-messenger ribonucleic acid (pre-mRNA) splicing is an essential process in eukaryotic gene regulation. The T-cell intracellular antigen-1 (TIA-1) is an apoptosis-promoting factor that modulates alternative splicing of transcripts, including the pre-mRNA encoding the membrane receptor Fas. TIA-1 is a multi-domain ribonucleic acid (RNA) binding protein that recognizes poly-uridine tract RNA sequences to facilitate 5′ splice site recognition by the U1 small nuclear ribonucleoprotein (snRNP). Here, we characterize the RNA interaction and conformational dynamics of TIA-1 by nuclear magnetic resonance (NMR), isothermal titration calorimetry (ITC) and small angle X-ray scattering (SAXS). Our NMR-derived solution structure of TIA-1 RRM2–RRM3 (RRM2,3) reveals that RRM2 adopts a canonical RNA recognition motif (RRM) fold, while RRM3 is preceded by an non-canonical helix α0. NMR and SAXS data show that all three RRMs are largely independent structural modules in the absence of RNA, while RNA binding induces a compact arrangement. RRM2,3 binds to pyrimidine-rich FAS pre-mRNA or poly-uridine (U9) RNA with nanomolar affinities. RRM1 has little intrinsic RNA binding affinity and does not strongly contribute to RNA binding in the context of RRM1,2,3. Our data unravel the role of binding avidity and the contributions of the TIA-1 RRMs for recognition of pyrimidine-rich RNAs. PMID:24682828

The Contributions of Emotional Intelligence and Social Support for Adaptive Career Progress among Italian Youth

ERIC Educational Resources Information Center

Di Fabio, Annamaria; Kenny, Maureen E.

2015-01-01

Drawing from career construction and positive youth development perspectives, this study explores, among 254 Italian high school students, the relationship between emotional intelligence (EI) and support from friends and teachers with indices of adaptive career development. Results from the full canonical correlational model revealed that…

The Relationship between the Big-Five Model of Personality and Self-Regulated Learning Strategies

ERIC Educational Resources Information Center

Bidjerano, Temi; Dai, David Yun

2007-01-01

The study examined the relationship between the big-five model of personality and the use of self-regulated learning strategies. Measures of self-regulated learning strategies and big-five personality traits were administered to a sample of undergraduate students. Results from canonical correlation analysis indicated an overlap between the…

Investigating the Relationship between Conceptual and Procedural Errors in the Domain of Probability Problem-Solving.

ERIC Educational Resources Information Center

O'Connell, Ann Aileen

The relationships among types of errors observed during probability problem solving were studied. Subjects were 50 graduate students in an introductory probability and statistics course. Errors were classified as text comprehension, conceptual, procedural, and arithmetic. Canonical correlation analysis was conducted on the frequencies of specific…

Another View of the Relation of Environment to Mental Abilities: A Reply

ERIC Educational Resources Information Center

Marjoribanks, Kevin

1974-01-01

Harris and McArthur concluded that Marjoribanks' measure of the learning environment of the home was not differentially related to mental ability test performance. It is argued, here, that a canonical correlation analysis provides a better explanation of the data than Harris' and McArthur's interbattery factor analysis. (Author/SE)

Word Processing in Children with Autism Spectrum Disorders: Evidence from Event-Related Potentials

ERIC Educational Resources Information Center

Sandbank, Michael; Yoder, Paul; Key, Alexandra P.

2017-01-01

Purpose: This investigation was conducted to determine whether young children with autism spectrum disorders exhibited a canonical neural response to word stimuli and whether putative event-related potential (ERP) measures of word processing were correlated with a concurrent measure of receptive language. Additional exploratory analyses were used…

Parent Characteristics, Economic Stress and Neighborhood Context as Predictors of Parent Involvement in Preschool Children's Education

ERIC Educational Resources Information Center

Waanders, Christine; Mendez, Julia L.; Downer, Jason T.

2007-01-01

This study examines factors related to three dimensions of parent involvement in preschool: school-based involvement, home-based involvement, and the parent-teacher relationship. Participants were 154 predominantly African American parents recruited from two Head Start programs. Results of bivariate and canonical correlation analyses support the…

Assessment of mental stress effects on prefrontal cortical activities using canonical correlation analysis: an fNIRS-EEG study.

PubMed

Al-Shargie, Fares; Tang, Tong Boon; Kiguchi, Masashi

2017-05-01

This paper presents an investigation about the effects of mental stress on prefrontal cortex (PFC) subregions using simultaneous measurement of functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) signals. The aim is to explore canonical correlation analysis (CCA) technique to study the relationship among the bi-modality signals in mental stress assessment, and how we could fuse the signals for better accuracy in stress detection. Twenty-five male healthy subjects participated in the study while performing mental arithmetic task under control and stress (under time pressure with negative feedback) conditions. The fusion of brain signals acquired by fNIRS-EEG was performed at feature-level using CCA by maximizing the inter-subject covariance across modalities. The CCA result discovered the associations across the modalities and estimated the components responsible for these associations. The experiment results showed that mental stress experienced by this cohort of subjects is subregion specific and localized to the right ventrolateral PFC subregion. These suggest the right ventrolateral PFC as a suitable candidate region to extract biomarkers as performance indicators of neurofeedback training in stress coping.

Applications of temporal kernel canonical correlation analysis in adherence studies.

PubMed

John, Majnu; Lencz, Todd; Ferbinteanu, Janina; Gallego, Juan A; Robinson, Delbert G

2017-10-01

Adherence to medication is often measured as a continuous outcome but analyzed as a dichotomous outcome due to lack of appropriate tools. In this paper, we illustrate the use of the temporal kernel canonical correlation analysis (tkCCA) as a method to analyze adherence measurements and symptom levels on a continuous scale. The tkCCA is a novel method developed for studying the relationship between neural signals and hemodynamic response detected by functional MRI during spontaneous activity. Although the tkCCA is a powerful tool, it has not been utilized outside the application that it was originally developed for. In this paper, we simulate time series of symptoms and adherence levels for patients with a hypothetical brain disorder and show how the tkCCA can be used to understand the relationship between them. We also examine, via simulations, the behavior of the tkCCA under various missing value mechanisms and imputation methods. Finally, we apply the tkCCA to a real data example of psychotic symptoms and adherence levels obtained from a study based on subjects with a first episode of schizophrenia, schizophreniform or schizoaffective disorder.

Similarity in temperament between mother and offspring rhesus monkeys: Sex differences and the role of monoamine oxidase-A and serotonin transporter promoter polymorphism genotypes

PubMed Central

Sullivan, Erin C.; Mendoza, Sally P.; Capitanio, John P.

2011-01-01

Temperament is usually considered biologically based and largely inherited, however the environment can shape the development of temperament. Allelic variation may confer differential sensitivity to early environment resulting in variations in temperament. Here we explore the relationship between measures of temperament in mothers and their first-born offspring and the role of genetic sensitivity in establishing the strength of these associations. Temperament ratings were conducted on 3-4 month old rhesus monkeys after a 25-hour biobehavioral assessment. Factor analysis revealed a four factor structure of temperament. Females assessed as infants have reproduced and their offspring have also been evaluated through the standardized testing paradigm. Canonical correlation analysis revealed statistically significant associations between factor scores of mothers and sons, but not mothers and daughters. Further, offspring possessing the high activity, “low risk”, alleles of the rhMAOA-LPR or rh5-HTTLPR showed statistically significant canonical correlations, whereas those possessing other alleles did not, suggesting differential genetic sensitivity to the normative early experience of maternal temperament. PMID:21866539

The evaluation of rainfall influence on combined sewer overflows characteristics: the Berlin case study.

PubMed

Sandoval, S; Torres, A; Pawlowsky-Reusing, E; Riechel, M; Caradot, N

2013-01-01

The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSOs), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of partial least squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main influences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutant concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutant loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R² < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.

Revisiting the Robustness of PET-Based Textural Features in the Context of Multi-Centric Trials.

PubMed

Bailly, Clément; Bodet-Milin, Caroline; Couespel, Solène; Necib, Hatem; Kraeber-Bodéré, Françoise; Ansquer, Catherine; Carlier, Thomas

2016-01-01

This study aimed to investigate the variability of textural features (TF) as a function of acquisition and reconstruction parameters within the context of multi-centric trials. The robustness of 15 selected TFs were studied as a function of the number of iterations, the post-filtering level, input data noise, the reconstruction algorithm and the matrix size. A combination of several reconstruction and acquisition settings was devised to mimic multi-centric conditions. We retrospectively studied data from 26 patients enrolled in a diagnostic study that aimed to evaluate the performance of PET/CT 68Ga-DOTANOC in gastro-entero-pancreatic neuroendocrine tumors. Forty-one tumors were extracted and served as the database. The coefficient of variation (COV) or the absolute deviation (for the noise study) was derived and compared statistically with SUVmax and SUVmean results. The majority of investigated TFs can be used in a multi-centric context when each parameter is considered individually. The impact of voxel size and noise in the input data were predominant as only 4 TFs presented a high/intermediate robustness against SUV-based metrics (Entropy, Homogeneity, RP and ZP). When combining several reconstruction settings to mimic multi-centric conditions, most of the investigated TFs were robust enough against SUVmax except Correlation, Contrast, LGRE, LGZE and LZLGE. Considering previously published results on either reproducibility or sensitivity against delineation approach and our findings, it is feasible to consider Homogeneity, Entropy, Dissimilarity, HGRE, HGZE and ZP as relevant for being used in multi-centric trials.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

PubMed

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for personalized cancer therapy.

A radial map of multi-whisker correlation selectivity in the rat barrel cortex

PubMed Central

Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E.; Bourdieu, Laurent; Léger, Jean- François

2016-01-01

In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel–septal borders, forming rings of multi-whisker synchrony-preferring cells. PMID:27869114

A radial map of multi-whisker correlation selectivity in the rat barrel cortex.

PubMed

Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E; Bourdieu, Laurent; Léger, Jean-François

2016-11-21

In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel-septal borders, forming rings of multi-whisker synchrony-preferring cells.

RNAHelix: computational modeling of nucleic acid structures with Watson-Crick and non-canonical base pairs.

PubMed

Bhattacharyya, Dhananjay; Halder, Sukanya; Basu, Sankar; Mukherjee, Debasish; Kumar, Prasun; Bansal, Manju

2017-02-01

Comprehensive analyses of structural features of non-canonical base pairs within a nucleic acid double helix are limited by the availability of a small number of three dimensional structures. Therefore, a procedure for model building of double helices containing any given nucleotide sequence and base pairing information, either canonical or non-canonical, is seriously needed. Here we describe a program RNAHelix, which is an updated version of our widely used software, NUCGEN. The program can regenerate duplexes using the dinucleotide step and base pair orientation parameters for a given double helical DNA or RNA sequence with defined Watson-Crick or non-Watson-Crick base pairs. The original structure and the corresponding regenerated structure of double helices were found to be very close, as indicated by the small RMSD values between positions of the corresponding atoms. Structures of several usual and unusual double helices have been regenerated and compared with their original structures in terms of base pair RMSD, torsion angles and electrostatic potentials and very high agreements have been noted. RNAHelix can also be used to generate a structure with a sequence completely different from an experimentally determined one or to introduce single to multiple mutation, but with the same set of parameters and hence can also be an important tool in homology modeling and study of mutation induced structural changes.

A Review of Multivariate Methods for Multimodal Fusion of Brain Imaging Data

PubMed Central

Adali, Tülay; Yu, Qingbao; Calhoun, Vince D.

2011-01-01

The development of various neuroimaging techniques is rapidly improving the measurements of brain function/structure. However, despite improvements in individual modalities, it is becoming increasingly clear that the most effective research approaches will utilize multi-modal fusion, which takes advantage of the fact that each modality provides a limited view of the brain. The goal of multimodal fusion is to capitalize on the strength of each modality in a joint analysis, rather than a separate analysis of each. This is a more complicated endeavor that must be approached more carefully and efficient methods should be developed to draw generalized and valid conclusions from high dimensional data with a limited number of subjects. Numerous research efforts have been reported in the field based on various statistical approaches, e.g. independent component analysis (ICA), canonical correlation analysis (CCA) and partial least squares (PLS). In this review paper, we survey a number of multivariate methods appearing in previous reports, which are performed with or without prior information and may have utility for identifying potential brain illness biomarkers. We also discuss the possible strengths and limitations of each method, and review their applications to brain imaging data. PMID:22108139

Reduction hybrid artifacts of EMG-EOG in electroencephalography evoked by prefrontal transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Bai, Yang; Wan, Xiaohong; Zeng, Ke; Ni, Yinmei; Qiu, Lirong; Li, Xiaoli

2016-12-01

Objective. When prefrontal-transcranial magnetic stimulation (p-TMS) performed, it may evoke hybrid artifact mixed with muscle activity and blink activity in EEG recordings. Reducing this kind of hybrid artifact challenges the traditional preprocessing methods. We aim to explore method for the p-TMS evoked hybrid artifact removal. Approach. We propose a novel method used as independent component analysis (ICA) post processing to reduce the p-TMS evoked hybrid artifact. Ensemble empirical mode decomposition (EEMD) was used to decompose signal into multi-components, then the components were separated with artifact reduced by blind source separation (BSS) method. Three standard BSS methods, ICA, independent vector analysis, and canonical correlation analysis (CCA) were tested. Main results. Synthetic results showed that EEMD-CCA outperformed others as ICA post processing step in hybrid artifacts reduction. Its superiority was clearer when signal to noise ratio (SNR) was lower. In application to real experiment, SNR can be significantly increased and the p-TMS evoked potential could be recovered from hybrid artifact contaminated signal. Our proposed method can effectively reduce the p-TMS evoked hybrid artifacts. Significance. Our proposed method may facilitate future prefrontal TMS-EEG researches.

A high-speed brain speller using steady-state visual evoked potentials.

PubMed

Nakanishi, Masaki; Wang, Yijun; Wang, Yu-Te; Mitsukura, Yasue; Jung, Tzyy-Ping

2014-09-01

Implementing a complex spelling program using a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) remains a challenge due to difficulties in stimulus presentation and target identification. This study aims to explore the feasibility of mixed frequency and phase coding in building a high-speed SSVEP speller with a computer monitor. A frequency and phase approximation approach was developed to eliminate the limitation of the number of targets caused by the monitor refresh rate, resulting in a speller comprising 32 flickers specified by eight frequencies (8-15 Hz with a 1 Hz interval) and four phases (0°, 90°, 180°, and 270°). A multi-channel approach incorporating Canonical Correlation Analysis (CCA) and SSVEP training data was proposed for target identification. In a simulated online experiment, at a spelling rate of 40 characters per minute, the system obtained an averaged information transfer rate (ITR) of 166.91 bits/min across 13 subjects with a maximum individual ITR of 192.26 bits/min, the highest ITR ever reported in electroencephalogram (EEG)-based BCIs. The results of this study demonstrate great potential of a high-speed SSVEP-based BCI in real-life applications.

49 CFR 1103.10 - Introduction.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 8 2010-10-01 2010-10-01 false Introduction. 1103.10 Section 1103.10... OF TRANSPORTATION RULES OF PRACTICE PRACTITIONERS Canons of Ethics § 1103.10 Introduction. The... practice law and (b) others who have fulfilled the requirements set forth in § 1103.3. The former are bound...

Distribution of the Mosquito Communities (Diptera: Culicidae) in Oviposition Traps Introduced into the Atlantic Forest in the State of Rio de Janeiro, Brazil.

PubMed

Silva, Shayenne Olsson Freitas; Ferreira de Mello, Cecilia; Figueiró, Ronaldo; de Aguiar Maia, Daniele; Alencar, Jeronimo

2018-04-01

The Atlantic Rainforest of South America is one of the major biodiversity hotspots of the world and serves as a place of residence for a wide variety of Culicidae species. Mosquito studies in the natural environment are of considerable importance because of their role in transmitting pathogens to both humans and other vertebrates. Community diversity can have significant effects on the risk of their disease transmission. The objective of this study was to understand the distribution of mosquito communities using oviposition traps in a region of the Atlantic Forest. Sampling was carried out in Bom Retiro Private Natural Reserve (RPPNBR), located in Casimiro de Abreu, Rio de Janeiro, using oviposition traps, which were set in the forest environment, from October 2015 to December 2016. The canonical correspondence analysis was used to assess the influence of the climatic variables (precipitation, maximum dew point, and direction) throughout the seasons on the population density of the mosquito species. The results showed that population density was directly influenced by climatic variables, which acted as a limiting factor for the mosquito species studied. The climatic variables that were significantly correlated with the density of the mosquito species were precipitation, maximum dew point, and direction. Haemagogus janthinomys was positively correlated with the three climatic variables, whereas Haemagogus leucocelaenus was positively correlated with precipitation and maximum dew point, and negatively correlated with direction.

[Job stress of nursing aides in Swiss nursing homes : Nonlinear canonical analysis].

PubMed

Ziegler, A; Bernet, M; Metzenthin, P; Conca, A; Hahn, S

2016-08-01

Due to demographic changes, the demand for care in nursing homes for the elderly and infirmed is growing. At the same time nursing staff shortages are also increasing. Nursing aides are the primary care providers and comprise the largest staff group in Swiss nursing homes. They are exposed to various forms of job stress, which threaten job retention. The aim of this study was to discover which features of the work situation and which personal characteristics of the nursing aides were related to the workload. Data from nursing aides in Swiss nursing homes were investigated through a secondary analysis of a national quantitative cross-sectional study, using descriptive statistics and a nonlinear canonical correlation analysis. A total of 1054 nursing aides were included in the secondary analysis, 94.6 % of whom were women between the ages of 42 and 61 years. The job stress most frequently mentioned in the descriptive analysis, almost 60 % of the participants referred to it, was staff shortage. The nonlinear canonical correlation analysis revealed that many job strains are caused by social and organizational issues. In particular, a lack of support from supervisors was associated with staff not feeling appreciated. These job strains correlated with a high level of responsibility, the feeling of being unable to work independently and a feeling of being exploited. These strains were predominant in the nursing aides between 32 and 51 years old who had part time jobs but workloads of 80-90 %. Middle-aged nursing aides who worked to 80-90 % are particularly at risk to resign from the position prematurely. Measures need to be mainly implemented in the social and organizational areas. It can be assumed that a targeted individual support, recognition and promotion of nursing aides may decrease the level of job strain.

Coping styles used by sexual minority men who experience intimate partner violence.

PubMed

Goldberg-Looney, Lisa D; Perrin, Paul B; Snipes, Daniel J; Calton, Jenna M

2016-12-01

This study examined the coping styles used by sexual minority men who have experienced intimate partner violence, including sexual, emotional and physical victimisation, as well as physical injury. Although sexual minority men experience intimate partner violence at least as often as do heterosexuals, there is currently limited knowledge of intimate partner violence in this community or resources for sexual minority men who experience intimate partner violence. Cross-sectional design. Sexual minority men (N = 89) were recruited as part of a national online survey and completed questionnaires assessing lifetime experiences of intimate partner violence as well as various coping strategies. In terms of intimate partner violence, 34·8% of participants reported having been targets of sexual abuse, 38·2% targets of physical abuse, 69·7% targets of psychological abuse and 28·1% had experienced an injury as a result of intimate partner violence during their lifetime. Canonical correlation analyses found that intimate partner violence victimisation explained 32·5% of the variance in adaptive and 31·4% of the variance in maladaptive coping behaviours. In the adaptive coping canonical correlation, standardised loadings suggested that sexual minority men who experienced intimate partner violence resulting in injury were more likely to use religious coping, but less likely to use planning coping. In the maladaptive coping canonical correlation, sexual minority men who had been targets of intimate partner sexual victimisation and intimate partner violence resulting in injury tended to engage in increased behavioural disengagement coping. This study revealed several coping behaviours that are more or less likely as the severity of different forms of intimate partner violence increases. The identification of these coping styles could be applied to the development and modification of evidence-based interventions to foster effective and discourage ineffective coping styles, thereby improving outcomes for sexual minority men who experience intimate partner violence. © 2016 John Wiley & Sons Ltd.

Deadbeat Predictive Controllers

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh

1997-01-01

Several new computational algorithms are presented to compute the deadbeat predictive control law. The first algorithm makes use of a multi-step-ahead output prediction to compute the control law without explicitly calculating the controllability matrix. The system identification must be performed first and then the predictive control law is designed. The second algorithm uses the input and output data directly to compute the feedback law. It combines the system identification and the predictive control law into one formulation. The third algorithm uses an observable-canonical form realization to design the predictive controller. The relationship between all three algorithms is established through the use of the state-space representation. All algorithms are applicable to multi-input, multi-output systems with disturbance inputs. In addition to the feedback terms, feed forward terms may also be added for disturbance inputs if they are measurable. Although the feedforward terms do not influence the stability of the closed-loop feedback law, they enhance the performance of the controlled system.

Raspberry Pi camera with intervalometer used as crescograph

NASA Astrophysics Data System (ADS)

Albert, Stefan; Surducan, Vasile

2017-12-01

The intervalometer is an attachment or facility on a photo-camera that operates the shutter regularly at set intervals over a period. Professional cameras with built in intervalometers are expensive and quite difficult to find. The Canon CHDK open source operating system allows intervalometer implementation on Canon cameras only. However finding a Canon camera with near infra-red (NIR) photographic lens at affordable price is impossible. On experiments requiring several cameras (used to measure growth in plants - the crescographs, but also for coarse evaluation of the water content of leaves), the costs of the equipment are often over budget. Using two Raspberry Pi modules each equipped with a low cost NIR camera and a WIFI adapter (for downloading pictures stored on the SD card) and some freely available software, we have implemented two low budget intervalometer cameras. The shutting interval, the number of pictures to be taken, image resolution and some other parameters can be fully programmed. Cameras have been in use continuously for three months (July-October 2017) in a relevant environment (outside), proving the concept functionality.

Full-field drift Hamiltonian particle orbits in 3D geometry

NASA Astrophysics Data System (ADS)

Cooper, W. A.; Graves, J. P.; Brunner, S.; Isaev, M. Yu

2011-02-01

A Hamiltonian/Lagrangian theory to describe guiding centre orbit drift motion which is canonical in the Boozer coordinate frame has been extended to include full electromagnetic perturbed fields in anisotropic pressure 3D equilibria with nested magnetic flux surfaces. A redefinition of the guiding centre velocity to eliminate the motion due to finite equilibrium radial magnetic fields and the choice of a gauge condition that sets the radial component of the electromagnetic vector potential to zero are invoked to guarantee that the Boozer angular coordinates retain the canonical structure. The canonical momenta are identified and the guiding centre particle radial drift motion and parallel gyroradius evolution are derived. The particle coordinate position is linearly modified by wave-particle interactions. All the nonlinear wave-wave interactions appear explicitly only in the evolution of the parallel gyroradius. The radial variation of the electrostatic potential is related to the binormal component of the displacement vector for MHD-type perturbations. The electromagnetic vector potential projections can then be determined from the electrostatic potential and the radial component of the MHD displacement vector.

Signal Processing in Periodically Forced Gradient Frequency Neural Networks

PubMed Central

Kim, Ji Chul; Large, Edward W.

2015-01-01

Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

Emergence of superconductivity in the canonical heavy-electron metal YbRh₂Si₂.

PubMed

Schuberth, Erwin; Tippmann, Marc; Steinke, Lucia; Lausberg, Stefan; Steppke, Alexander; Brando, Manuel; Krellner, Cornelius; Geibel, Christoph; Yu, Rong; Si, Qimiao; Steglich, Frank

2016-01-29

The smooth disappearance of antiferromagnetic order in strongly correlated metals commonly furnishes the development of unconventional superconductivity. The canonical heavy-electron compound YbRh2Si2 seems to represent an apparent exception from this quantum critical paradigm in that it is not a superconductor at temperature T ≥ 10 millikelvin (mK). Here we report magnetic and calorimetric measurements on YbRh2Si2, down to temperatures as low as T ≈ 1 mK. The data reveal the development of nuclear antiferromagnetic order slightly above 2 mK and of heavy-electron superconductivity almost concomitantly with this order. Our results demonstrate that superconductivity in the vicinity of quantum criticality is a general phenomenon. Copyright © 2016, American Association for the Advancement of Science.

Study of multi-dimensional radiative energy transfer in molecular gases

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, S. N.

1993-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical arrow band model with an exponential-tailed inverse intensity distribution. Consideration of spectral correlation results in some distinguishing features of the Monte Carlo formulations. Validation of the Monte Carlo formulations has been conducted by comparing results of this method with other solutions. Extension of a one-dimensional problem to a multi-dimensional problem requires some special treatments in the Monte Carlo analysis. Use of different assumptions results in different sets of Monte Carlo formulations. The nongray narrow band formulations provide the most accurate results.

Health, well-being, and psychopathology in a clinical population: Structure and discriminant validity of Mental Health Continuum Short Form (MHC-SF).

PubMed

van Erp Taalman Kip, Rogier M; Hutschemaekers, Giel J M

2018-03-30

The literature suggests a distinction between illness (negative health) and the ability to cope with challenges such as illness (positive health). The two continua model of mental health distinguishes psychiatric symptoms (illness) from well-being (positive health). Well-being consists of hedonic, eudaimonic, and social well-being, constituting one factor that is moderately correlated with psychopathology in the general population. In a mental health care population, we examined whether the three dimensions of well-being are distinguishable and whether well-being is also moderately correlated with symptoms. A representative sample of 1,069 patients (63% female, 47% male; mean age: 42 years) voluntarily completed the Mental Health Continuum-Short Form (MHC-SF), a 14-item test that assesses three components of well-being. Confirmatory factor analysis revealed a model with strong correlations between the three subscales of the MHC-SF, indicating poor discriminant validity. Furthermore, the MHC-SF was strongly correlated (r = -.71) with the symptomatic distress scale of the OQ-45. Exploratory factor analysis permitted a two-factor solution, providing support for the two continua model of mental health. However, the explained variance of the second factor (well-being) was meager in comparison with the first factor (psychopathology). The results of a canonic correlation did not confirm the two continua model, and only a model with one common canonical factor was significant. For patients with clinical levels of psychopathology, the level of well-being and psychopathology correlate much higher than in the general population. Well-being and psychopathology are so entwined that the supposed distinction should be seriously questioned. © 2018 Wiley Periodicals, Inc.

MBARI CANON Experiment Visualization and Analysis

NASA Astrophysics Data System (ADS)

Fatland, R.; Oscar, N.; Ryan, J. P.; Bellingham, J. G.

2013-12-01

We describe the task of understanding a marine drift experiment conducted by MBARI in Fall 2012 ('CANON'). Datasets were aggregated from a drifting ADCP, from the MBARI Environmental Sample Processor, from Long Range Autonomous Underwater Vehicles (LRAUVs), from other in situ sensors, from NASA and NOAA remote sensing platforms, from moorings, from shipboard CTD casts and from post-experiment metagenomic analysis. We seek to combine existing approaches to data synthesis -- visual inspection, cross correlation and co.-- with three new ideas. This approach has the purpose of differentiating biological signals into three causal categories: Microcurrent advection, physical factors and microbe metabolism. Respective examples are aberrance from Lagrangian frame drift due to windage, changes in solar flux over several days, and microbial population responses to shifts in nitrate concentration. The three ideas we implemented are as follows: First, we advect LRAUV data to look for patterns in time series data for conserved quanitities such as salinity. We investigate whether such patterns can be used to support or undermine the premise of Lagrangian motion of the experiment ensemble. Second we built a set of configurable filters that enable us to visually isolate segments of data: By type, value, time, anomaly and location. Third we associated data hypotheses with a Bayesian inferrence engine for the purpose of model validation, again across sections taken from within the complete data complex. The end result is towards a free-form exploration of experimental data with low latency: from question to view, from hypothesis to test (albeit with considerable preparatory effort.) Preliminary results show the three causal categories shifting in relative influence.

A second-order unconstrained optimization method for canonical-ensemble density-functional methods

NASA Astrophysics Data System (ADS)

Nygaard, Cecilie R.; Olsen, Jeppe

2013-03-01

A second order converging method of ensemble optimization (SOEO) in the framework of Kohn-Sham Density-Functional Theory is presented, where the energy is minimized with respect to an ensemble density matrix. It is general in the sense that the number of fractionally occupied orbitals is not predefined, but rather it is optimized by the algorithm. SOEO is a second order Newton-Raphson method of optimization, where both the form of the orbitals and the occupation numbers are optimized simultaneously. To keep the occupation numbers between zero and two, a set of occupation angles is defined, from which the occupation numbers are expressed as trigonometric functions. The total number of electrons is controlled by a built-in second order restriction of the Newton-Raphson equations, which can be deactivated in the case of a grand-canonical ensemble (where the total number of electrons is allowed to change). To test the optimization method, dissociation curves for diatomic carbon are produced using different functionals for the exchange-correlation energy. These curves show that SOEO favors symmetry broken pure-state solutions when using functionals with exact exchange such as Hartree-Fock and Becke three-parameter Lee-Yang-Parr. This is explained by an unphysical contribution to the exact exchange energy from interactions between fractional occupations. For functionals without exact exchange, such as local density approximation or Becke Lee-Yang-Parr, ensemble solutions are favored at interatomic distances larger than the equilibrium distance. Calculations on the chromium dimer are also discussed. They show that SOEO is able to converge to ensemble solutions for systems that are more complicated than diatomic carbon.

The self-trapping transition in the non-half-filled strongly correlated extended Holstein-Hubbard model in two-dimensions

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

Sankar, I. V., E-mail: ivshankar27@gmail.com; Chatterjee, Ashok, E-mail: ivshankar27@gmail.com

2014-04-24

The two-dimensional extended Holstein-Hubbard model (EHH) has been considered at strong correlation regime in the non-half-filled band case to understand the self-trapping transition of electrons in strongly correlated electron system. We have used the method of optimized canonical transformations to transform an EHH model into an effective extended Hubbard (EEH) model. In the strong on-site correlation limit an EH model can be transformed into a t-J model which is finally solved using Hartree-Fock approximation (HFA). We found that, for non-half-filled band case, the transition is abrupt in the adiabatic region whereas it is continuous in the anti-adiabatic region.

Exactly solvable random graph ensemble with extensively many short cycles

NASA Astrophysics Data System (ADS)

Aguirre López, Fabián; Barucca, Paolo; Fekom, Mathilde; Coolen, Anthony C. C.

2018-02-01

We introduce and analyse ensembles of 2-regular random graphs with a tuneable distribution of short cycles. The phenomenology of these graphs depends critically on the scaling of the ensembles’ control parameters relative to the number of nodes. A phase diagram is presented, showing a second order phase transition from a connected to a disconnected phase. We study both the canonical formulation, where the size is large but fixed, and the grand canonical formulation, where the size is sampled from a discrete distribution, and show their equivalence in the thermodynamical limit. We also compute analytically the spectral density, which consists of a discrete set of isolated eigenvalues, representing short cycles, and a continuous part, representing cycles of diverging size.

The Perception of Assimilation in Newly Learned Novel Words

ERIC Educational Resources Information Center

Snoeren, Natalie D.; Gaskell, M. Gareth; Di Betta, Anna Maria

2009-01-01

The present study investigated the mechanisms underlying perceptual compensation for assimilation in novel words. During training, participants learned canonical versions of novel spoken words (e.g., "decibot") presented in isolation. Following exposure to a second set of novel words the next day, participants carried out a phoneme…

A powerful score-based test statistic for detecting gene-gene co-association.

PubMed

Xu, Jing; Yuan, Zhongshang; Ji, Jiadong; Zhang, Xiaoshuai; Li, Hongkai; Wu, Xuesen; Xue, Fuzhong; Liu, Yanxun

2016-01-29

The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.

Feasibility of multi-sector policy measures that create activity-friendly environments for children: results of a Delphi study.

PubMed

Aarts, Marie-Jeanne; Schuit, Albertine J; van de Goor, Ien Am; van Oers, Hans Am

2011-12-15

Although multi-sector policy is a promising strategy to create environments that stimulate physical activity among children, little is known about the feasibility of such a multi-sector policy approach. The aims of this study were: to identify a set of tangible (multi-sector) policy measures at the local level that address environmental characteristics related to physical activity among children; and to assess the feasibility of these measures, as perceived by local policy makers. In four Dutch municipalities, a Delphi study was conducted among local policy makers of different policy sectors (public health, sports, youth and education, spatial planning/public space, traffic and transportation, and safety). In the first Delphi round, respondents generated a list of possible policy measures addressing three environmental correlates of physical activity among children (social cohesion, accessibility of facilities, and traffic safety). In the second Delphi round, policy makers weighted different feasibility aspects (political feasibility, cultural/community acceptability, technical feasibility, cost feasibility, and legal feasibility) and assessed the feasibility of the policy measures derived from the first round. The third Delphi round was aimed at reaching consensus by feedback of group results. Finally, one overall feasibility score was calculated for each policy measure. Cultural/community acceptability, political feasibility, and cost feasibility were considered most important feasibility aspects. The Delphi studies yielded 16 feasible policy measures aimed at physical and social environmental correlates of physical activity among children. Less drastic policy measures were considered more feasible, whereas environmental policy measures were considered less feasible. This study showed that the Delphi technique can be a useful tool in reaching consensus about feasible multi-sector policy measures. The study yielded several feasible policy measures aimed at physical and social environmental correlates of physical activity among children and can assist local policy makers in designing multi-sector policies aimed at an activity-friendly environment for children.

On numerically pluricanonical cyclic coverings

NASA Astrophysics Data System (ADS)

Kulikov, V. S.; Kharlamov, V. M.

2014-10-01

We investigate some properties of cyclic coverings f\\colon Y\\to X (where X is a complex surface of general type) branched along smooth curves B\\subset X that are numerically equivalent to a multiple of the canonical class of X. Our main results concern coverings of surfaces of general type with p_g=0 and Miyaoka-Yau surfaces. In particular, such coverings provide new examples of multi-component moduli spaces of surfaces with given Chern numbers and new examples of surfaces that are not deformation equivalent to their complex conjugates.

State deadbeat response and observability in multi-modal systems

NASA Technical Reports Server (NTRS)

Conner, L. T., Jr.; Stanford, D. P.

1984-01-01

Two aspects of multimodal systems are examined. It is shown that any completely controllable system with state dimension n not exceeding three allows a choice of feedback matrices resulting in a state deadbeat response. Some of the results presented here are valid for arbitrary n, and it is suggested that for all n the state deadbeat response can be obtained under the hypothesis of complete controllability. The controllability canonical form for a multimodal system is refined by introducing a notion of observability which is dual to controllability for these systems.

Novel Chromosomal Rearrangements and breakpoints at the t(6;9) in Salivary Adenoid Cystic Carcinoma: association with MYB-NFIB chimeric fusion, MYB expression, and clinical outcome

PubMed Central

Mitani, Yoshitsugu; Rao, Pulivarthi H.; Futreal, P. Andrew; Roberts, Dianna B.; Stephens, Philip J.; Zhao, Yi-Jue; Zhang, Li; Mitani, Mutsumi; Weber, Randal S.; Lippman, Scott M.; Caulin, Carlos; El-Naggar, Adel K.

2011-01-01

Objective To investigate the molecular-genetic heterogeneity associated with the t(6:9) in adenoid cystic carcinoma (ACC) and correlate the findings with patient clinical outcome. Experimental Design Multi-molecular and genetic techniques complemented with massive pair-ended sequencing and SNP array analyses were used on tumor specimens from 30 new and 52 previously RT-PCR analyzed fusion transcript negative ACCs. MYB mRNA expression level was determined by quantitative RT-PCR. The results of 102 tumors (30 new and 72 previously reported cases) were correlated with the clinicopathologic factors and patients’ survival. Results The FISH analysis showed 34/82 (41.5%) fusion positive tumors and molecular techniques identified fusion transcripts in 21 of the 82 (25.6%) tumors. Detailed FISH analysis of 11 out the 15 tumors with gene fusion without transcript formation showed translocation of NFIB sequences to proximal or distal sites of the MYB gene. Massive pair-end sequencing of a subset of tumors confirmed the proximal translocation to an NFIB sequence and led to the identification of a new fusion gene (NFIB-AIG1) in one of the tumors. Overall, MYB-NFIB gene fusion rate by FISH was in 52.9% while fusion transcript forming incidence was 38.2%. Significant statistical association between the 5′ MYB transcript expression and patient survival was found. Conclusions We conclude that: 1) t(6;9) results in a complex genetic and molecular alterations in ACC, 2) MYB-NFIB gene fusion may not always be associated with chimeric transcript formation, 3) non-canonical MYB, NFIB gene fusions occur in a subset of tumors, 4) high MYB expression correlates with worse patient survival. PMID:21976542

Potential coupling effects of ammonia-oxidizing and anaerobic ammonium-oxidizing bacteria on completely autotrophic nitrogen removal over nitrite biofilm formation induced by the second messenger cyclic diguanylate.

PubMed

Wang, Chao; Liu, Sitong; Xu, Xiaochen; Zhao, Chuanqi; Yang, Fenglin; Wang, Dong

2017-05-01

The objective of this study was to investigate the influence of extracellular polymeric substance (EPS) on the coupling effects between ammonia-oxidizing bacteria (AOB) and anaerobic ammonium-oxidizing (anammox) bacteria for the completely autotrophic nitrogen removal over nitrite (CANON) biofilm formation in a moving bed biofilm reactor (MBBR). Analysis of the quantity of EPS and cyclic diguanylate (c-di-GMP) confirmed that the contents of polysaccharides and c-di-GMP were correlated in the AOB sludge, anammox sludge, and CANON biofilm. The anammox sludge secreted more EPS (especially polysaccharides) than AOB with a markedly higher c-di-GMP content, which could be used by the bacteria to regulate the synthesis of exopolysaccharides that are ultimately used as a fixation matrix, for the adhesion of biomass. Indeed, increased intracellular c-di-GMP concentrations in the anammox sludge enhanced the regulation of polysaccharides to promote the adhesion of AOB and formation of the CANON biofilm. Overall, the results of this study provide new comprehensive information regarding the coupling effects of AOB and anammox bacteria for the nitrogen removal process.

Eukaryotic tRNAs fingerprint invertebrates vis-à-vis vertebrates.

PubMed

Mitra, Sanga; Das, Pijush; Samadder, Arpa; Das, Smarajit; Betai, Rupal; Chakrabarti, Jayprokas

2015-01-01

During translation, aminoacyl-tRNA synthetases recognize the identities of the tRNAs to charge them with their respective amino acids. The conserved identities of 58,244 eukaryotic tRNAs of 24 invertebrates and 45 vertebrates in genomic tRNA database were analyzed and their novel features extracted. The internal promoter sequences, namely, A-Box and B-Box, were investigated and evidence gathered that the intervention of optional nucleotides at 17a and 17b correlated with the optimal length of the A-Box. The presence of canonical transcription terminator sequences at the immediate vicinity of tRNA genes was ventured. Even though non-canonical introns had been reported in red alga, green alga, and nucleomorph so far, fairly motivating evidence of their existence emerged in tRNA genes of other eukaryotes. Non-canonical introns were seen to interfere with the internal promoters in two cases, questioning their transcription fidelity. In a first of its kind, phylogenetic constructs based on tRNA molecules delineated and built the trees of the vast and diverse invertebrates and vertebrates. Finally, two tRNA models representing the invertebrates and the vertebrates were drawn, by isolating the dominant consensus in the positional fluctuations of nucleotide compositions.

A Canonical Correlation Analysis of Social Capital and Knowledge Exchange for Virtual Members of IT Teams

ERIC Educational Resources Information Center

Dutton Feliu, Genevieve

2018-01-01

Social capital theory conceptualized social capital as key to connecting team members into the flow of valued resources and activities, with knowledge deemed one of the most valuable of these resources. Yet, the literature found teams struggle to effectively share knowledge. This quantitative survey-based study assessed the interrelationship…

Canonical Correlation Analysis on Life Stress and Learning Burnout of College Students in Taiwan

ERIC Educational Resources Information Center

Huang, Yun-Chen; Lin, Shu Hui

2010-01-01

With rapid social changes, stress in life has increased significantly for everyone including college students. Understanding life stress among college students and how it may affect learning burnout has become an important concern for education researchers. The purposes of this study were (1) to assess the current status and factor structures of…

Measures of Writing Ability of Fourth, Fifth, and Sixth Grade Children.

ERIC Educational Resources Information Center

Simpson, George Franklin

The purpose of this canonical and multiple correlation study of measures of writing ability was to develop a valid weighted index of writing ability to replace the single measures now being used to evaluate elementary English programs. The subjects, 134 pupils from each fourth, fifth, and sixth grade level of Broadway and Dunham schools in Maple…

The Association between Learning and Learning Style in Instructional Marketing Games

ERIC Educational Resources Information Center

Garber, Lawrence L., Jr.; Hyatt, Eva M.; Boya, Unal O.; Ausherman, Babs

2012-01-01

To understand how learners of respective types respond to marketing games, a joint space generated by canonical correlation analysis is used to recreate Kolb's learning style-type plot and locate business students as points within it according to their learning style types. Two hundred twenty-three undergraduate students played The Marketing Game!…

Avian community composition and habitat importance in the Rio Grande corridor of New Mexico

Treesearch

David A. Leal; Raymond A. Meyer; Bruce C. Thompson

1996-01-01

We investigated avian species richness and abundance within vegetation communities of the Rio Grande Corridor of New Mexico during spring, summer, and fall 1992 and 1993. A subset of 64 transects, for which all bird and vegetation variables were available, representing 16 composite vegetation community types were subjected to canonical correlation analysis to...

The Role of Reinforcement Sensitivity in the Development of Childhood Personality

ERIC Educational Resources Information Center

Slobodskaya, Helena R.; Kuznetsova, Valeriya B.

2013-01-01

The study examined the contribution of reinforcement sensitivity to childhood personality at three levels of the hierarchical structure, mid-level traits, the Big Five and two higher-order factors, and the moderating role of sex and age in a sample of 3-18-year-olds. The canonical correlation analyses indicated that reinforcement sensitivity and…

Discovering the Listener within Us: The Impact of Trait-Like Personality Variables and Communicator Styles on Preferences for Listening Style

ERIC Educational Resources Information Center

Villaume, William A.; Bodie, Graham D.

2007-01-01

Extending past research, the present study provides an initial examination of the relationship between trait-like personality variables, communicator style, and individual listening preferences. A series of canonical correlations were run to ascertain to what degree certain communication preferences and trait-like personality variables are related…

A generic multi-hazard and multi-risk framework and its application illustrated in a virtual city

NASA Astrophysics Data System (ADS)

Mignan, Arnaud; Euchner, Fabian; Wiemer, Stefan

2013-04-01

We present a generic framework to implement hazard correlations in multi-risk assessment strategies. We consider hazard interactions (process I), time-dependent vulnerability (process II) and time-dependent exposure (process III). Our approach is based on the Monte Carlo method to simulate a complex system, which is defined from assets exposed to a hazardous region. We generate 1-year time series, sampling from a stochastic set of events. Each time series corresponds to one risk scenario and the analysis of multiple time series allows for the probabilistic assessment of losses and for the recognition of more or less probable risk paths. Each sampled event is associated to a time of occurrence, a damage footprint and a loss footprint. The occurrence of an event depends on its rate, which is conditional on the occurrence of past events (process I, concept of correlation matrix). Damage depends on the hazard intensity and on the vulnerability of the asset, which is conditional on previous damage on that asset (process II). Losses are the product of damage and exposure value, this value being the original exposure minus previous losses (process III, no reconstruction considered). The Monte Carlo method allows for a straightforward implementation of uncertainties and for implementation of numerous interactions, which is otherwise challenging in an analytical multi-risk approach. We apply our framework to a synthetic data set, defined by a virtual city within a virtual region. This approach gives the opportunity to perform multi-risk analyses in a controlled environment while not requiring real data, which may be difficultly accessible or simply unavailable to the public. Based on the heuristic approach, we define a 100 by 100 km region where earthquakes, volcanic eruptions, fluvial floods, hurricanes and coastal floods can occur. All hazards are harmonized to a common format. We define a 20 by 20 km city, composed of 50,000 identical buildings with a fixed economic value. Vulnerability curves are defined in terms of mean damage ratio as a function of hazard intensity. All data are based on simple equations found in the literature and on other simplifications. We show the impact of earthquake-earthquake interaction and hurricane-storm surge coupling, as well as of time-dependent vulnerability and exposure, on aggregated loss curves. One main result is the emergence of low probability-high consequences (extreme) events when correlations are implemented. While the concept of virtual city can suggest the theoretical benefits of multi-risk assessment for decision support, identifying their real-world practicality will require the study of real test sites.

SPAN: Ocean science

NASA Technical Reports Server (NTRS)

Thomas, Valerie L.; Koblinsky, Chester J.; Webster, Ferris; Zlotnicki, Victor; Green, James L.

1987-01-01

The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links space and Earth science research and data analysis computers. It provides a common working environment for sharing computer resources, sharing computer peripherals, solving proprietary problems, and providing the potential for significant time and cost savings for correlative data analysis. This is one of a series of discipline-specific SPAN documents which are intended to complement the SPAN primer and SPAN Management documents. Their purpose is to provide the discipline scientists with a comprehensive set of documents to assist in the use of SPAN for discipline specific scientific research.

Joint genomic evaluation of French dairy cattle breeds using multiple-trait models.

PubMed

Karoui, Sofiene; Carabaño, María Jesús; Díaz, Clara; Legarra, Andrés

2012-12-07

Using a multi-breed reference population might be a way of increasing the accuracy of genomic breeding values in small breeds. Models involving mixed-breed data do not take into account the fact that marker effects may differ among breeds. This study was aimed at investigating the impact on accuracy of increasing the number of genotyped candidates in the training set by using a multi-breed reference population, in contrast to single-breed genomic evaluations. Three traits (milk production, fat content and female fertility) were analyzed by genomic mixed linear models and Bayesian methodology. Three breeds of French dairy cattle were used: Holstein, Montbéliarde and Normande with 2976, 950 and 970 bulls in the training population, respectively and 964, 222 and 248 bulls in the validation population, respectively. All animals were genotyped with the Illumina Bovine SNP50 array. Accuracy of genomic breeding values was evaluated under three scenarios for the correlation of genomic breeding values between breeds (r(g)): uncorrelated (1), r(g) = 0; estimated r(g) (2); high, r(g) = 0.95 (3). Accuracy and bias of predictions obtained in the validation population with the multi-breed training set were assessed by the coefficient of determination (R(2)) and by the regression coefficient of daughter yield deviations of validation bulls on their predicted genomic breeding values, respectively. The genetic variation captured by the markers for each trait was similar to that estimated for routine pedigree-based genetic evaluation. Posterior means for rg ranged from -0.01 for fertility between Montbéliarde and Normande to 0.79 for milk yield between Montbéliarde and Holstein. Differences in R(2) between the three scenarios were notable only for fat content in the Montbéliarde breed: from 0.27 in scenario (1) to 0.33 in scenarios (2) and (3). Accuracies for fertility were lower than for other traits. Using a multi-breed reference population resulted in small or no increases in accuracy. Only the breed with a small data set and large genetic correlation with the breed with a large data set showed increased accuracy for the traits with moderate (milk) to high (fat content) heritability. No benefit was observed for fertility, a lowly heritable trait.

Joint genomic evaluation of French dairy cattle breeds using multiple-trait models

PubMed Central

2012-01-01

Background Using a multi-breed reference population might be a way of increasing the accuracy of genomic breeding values in small breeds. Models involving mixed-breed data do not take into account the fact that marker effects may differ among breeds. This study was aimed at investigating the impact on accuracy of increasing the number of genotyped candidates in the training set by using a multi-breed reference population, in contrast to single-breed genomic evaluations. Methods Three traits (milk production, fat content and female fertility) were analyzed by genomic mixed linear models and Bayesian methodology. Three breeds of French dairy cattle were used: Holstein, Montbéliarde and Normande with 2976, 950 and 970 bulls in the training population, respectively and 964, 222 and 248 bulls in the validation population, respectively. All animals were genotyped with the Illumina Bovine SNP50 array. Accuracy of genomic breeding values was evaluated under three scenarios for the correlation of genomic breeding values between breeds (rg): uncorrelated (1), rg = 0; estimated rg (2); high, rg = 0.95 (3). Accuracy and bias of predictions obtained in the validation population with the multi-breed training set were assessed by the coefficient of determination (R2) and by the regression coefficient of daughter yield deviations of validation bulls on their predicted genomic breeding values, respectively. Results The genetic variation captured by the markers for each trait was similar to that estimated for routine pedigree-based genetic evaluation. Posterior means for rg ranged from −0.01 for fertility between Montbéliarde and Normande to 0.79 for milk yield between Montbéliarde and Holstein. Differences in R2 between the three scenarios were notable only for fat content in the Montbéliarde breed: from 0.27 in scenario (1) to 0.33 in scenarios (2) and (3). Accuracies for fertility were lower than for other traits. Conclusions Using a multi-breed reference population resulted in small or no increases in accuracy. Only the breed with a small data set and large genetic correlation with the breed with a large data set showed increased accuracy for the traits with moderate (milk) to high (fat content) heritability. No benefit was observed for fertility, a lowly heritable trait. PMID:23216664

A Method of Relating General Circulation Model Simulated Climate to the Observed Local Climate. Part I: Seasonal Statistics.

NASA Astrophysics Data System (ADS)

Karl, Thomas R.; Wang, Wei-Chyung; Schlesinger, Michael E.; Knight, Richard W.; Portman, David

1990-10-01

Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model's internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between the output of a ten-year GCM control run and the surface-based observations are often smaller than the differences between the observations of two ten-year periods. Such positive results suggest that GCMs may already contain important climatological information that can be used to infer the local climate.

Entanglement entropy in causal set theory

NASA Astrophysics Data System (ADS)

Sorkin, Rafael D.; Yazdi, Yasaman K.

2018-04-01

Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Formulating a notion of entanglement entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which its definition typically relies is not available. Instead, we appeal to the more global expression given in Sorkin (2012 (arXiv:1205.2953)) which, for a Gaussian scalar field, expresses the entropy of a spacetime region in terms of the field’s correlation function within that region (its ‘Wightman function’ W(x, x') ). Carrying this formula over to the causal set, one obtains an entropy which is both finite and of a Lorentz invariant nature. We evaluate this global entropy-expression numerically for certain regions (primarily order-intervals or ‘causal diamonds’) within causal sets of 1  +  1 dimensions. For the causal-set counterpart of the entanglement entropy, we obtain, in the first instance, a result that follows a (spacetime) volume law instead of the expected (spatial) area law. We find, however, that one obtains an area law if one truncates the commutator function (‘Pauli–Jordan operator’) and the Wightman function by projecting out the eigenmodes of the Pauli–Jordan operator whose eigenvalues are too close to zero according to a geometrical criterion which we describe more fully below. In connection with these results and the questions they raise, we also study the ‘entropy of coarse-graining’ generated by thinning out the causal set, and we compare it with what one obtains by similarly thinning out a chain of harmonic oscillators, finding the same, ‘universal’ behaviour in both cases.

A multi-scale study of the adsorption of lanthanum on the (110) surface of tungsten

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

Samin, Adib J.; Zhang, Jinsuo

In this study, we utilize a multi-scale approach to studying lanthanum adsorption on the (110) plane of tungsten. The energy of the system is described from density functional theory calculations within the framework of the cluster expansion method. It is found that including two-body figures up to the sixth nearest neighbor yielded a reasonable agreement with density functional theory calculations as evidenced by the reported cross validation score. The results indicate that the interaction between the adsorbate atoms in the adlayer is important and cannot be ignored. The parameterized cluster expansion expression is used in a lattice gas Monte Carlomore » simulation in the grand canonical ensemble at 773 K and the adsorption isotherm is recorded. Implications of the obtained results for the pyroprocessing application are discussed.« less

Fully implicit Particle-in-cell algorithms for multiscale plasma simulation

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

Chacon, Luis

The outline of the paper is as follows: Particle-in-cell (PIC) methods for fully ionized collisionless plasmas, explicit vs. implicit PIC, 1D ES implicit PIC (charge and energy conservation, moment-based acceleration), and generalization to Multi-D EM PIC: Vlasov-Darwin model (review and motivation for Darwin model, conservation properties (energy, charge, and canonical momenta), and numerical benchmarks). The author demonstrates a fully implicit, fully nonlinear, multidimensional PIC formulation that features exact local charge conservation (via a novel particle mover strategy), exact global energy conservation (no particle self-heating or self-cooling), adaptive particle orbit integrator to control errors in momentum conservation, and canonical momenta (EM-PICmore » only, reduced dimensionality). The approach is free of numerical instabilities: ω peΔt >> 1, and Δx >> λ D. It requires many fewer dofs (vs. explicit PIC) for comparable accuracy in challenging problems. Significant CPU gains (vs explicit PIC) have been demonstrated. The method has much potential for efficiency gains vs. explicit in long-time-scale applications. Moment-based acceleration is effective in minimizing N FE, leading to an optimal algorithm.« less

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

PubMed

Martínez, C A; Khare, K; Rahman, S; Elzo, M A

2017-10-01

Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

PubMed Central

Lee, Anthony; Yau, Christopher; Giles, Michael B.; Doucet, Arnaud; Holmes, Christopher C.

2011-01-01

We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel computational devices that can be housed in conventional desktop and laptop computers and can be thought of as prototypes of the next generation of many-core processors. For certain classes of population-based Monte Carlo algorithms they offer massively parallel simulation, with the added advantage over conventional distributed multi-core processors that they are cheap, easily accessible, easy to maintain, easy to code, dedicated local devices with low power consumption. On a canonical set of stochastic simulation examples including population-based Markov chain Monte Carlo methods and Sequential Monte Carlo methods, we nd speedups from 35 to 500 fold over conventional single-threaded computer code. Our findings suggest that GPUs have the potential to facilitate the growth of statistical modelling into complex data rich domains through the availability of cheap and accessible many-core computation. We believe the speedup we observe should motivate wider use of parallelizable simulation methods and greater methodological attention to their design. PMID:22003276

Action Unit Models of Facial Expression of Emotion in the Presence of Speech

PubMed Central

Shah, Miraj; Cooper, David G.; Cao, Houwei; Gur, Ruben C.; Nenkova, Ani; Verma, Ragini

2014-01-01

Automatic recognition of emotion using facial expressions in the presence of speech poses a unique challenge because talking reveals clues for the affective state of the speaker but distorts the canonical expression of emotion on the face. We introduce a corpus of acted emotion expression where speech is either present (talking) or absent (silent). The corpus is uniquely suited for analysis of the interplay between the two conditions. We use a multimodal decision level fusion classifier to combine models of emotion from talking and silent faces as well as from audio to recognize five basic emotions: anger, disgust, fear, happy and sad. Our results strongly indicate that emotion prediction in the presence of speech from action unit facial features is less accurate when the person is talking. Modeling talking and silent expressions separately and fusing the two models greatly improves accuracy of prediction in the talking setting. The advantages are most pronounced when silent and talking face models are fused with predictions from audio features. In this multi-modal prediction both the combination of modalities and the separate models of talking and silent facial expression of emotion contribute to the improvement. PMID:25525561

A multi-dimensional, energy- and charge-conserving, nonlinearly implicit, electromagnetic Vlasov–Darwin particle-in-cell algorithm

DOE PAGES

Chen, G.; Chacón, L.

2015-08-11

For decades, the Vlasov–Darwin model has been recognized to be attractive for particle-in-cell (PIC) kinetic plasma simulations in non-radiative electromagnetic regimes, to avoid radiative noise issues and gain computational efficiency. However, the Darwin model results in an elliptic set of field equations that renders conventional explicit time integration unconditionally unstable. We explore a fully implicit PIC algorithm for the Vlasov–Darwin model in multiple dimensions, which overcomes many difficulties of traditional semi-implicit Darwin PIC algorithms. The finite-difference scheme for Darwin field equations and particle equations of motion is space–time-centered, employing particle sub-cycling and orbit-averaging. This algorithm conserves total energy, local charge,more » canonical-momentum in the ignorable direction, and preserves the Coulomb gauge exactly. An asymptotically well-posed fluid preconditioner allows efficient use of large cell sizes, which are determined by accuracy considerations, not stability, and can be orders of magnitude larger than required in a standard explicit electromagnetic PIC simulation. Finally, we demonstrate the accuracy and efficiency properties of the algorithm with various numerical experiments in 2D–3V.« less

Multi-scale variability and long-range memory in indoor Radon concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios; Barbosa, Susana

2014-05-01

The presence or absence of long-range correlations in the variations of indoor Radon concentrations has recently attracted considerable interest. As a radioactive gas naturally emitted from the ground in certain geological settings, understanding environmental factors controlling Radon concentrations and their dynamics is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we re-analyze two high-resolution records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements. In order to evaluate the presence of long-range correlations and fractal scaling, we utilize a multiplicity of complementary methods, including power spectral analysis, ARFIMA modeling, classical and multi-fractal detrended fluctuation analysis, and two different estimators of the signals' fractal dimensions. Power spectra and fluctuation functions reveal some complex behavior with qualitatively different properties on different time-scales: white noise in the high-frequency part, indications of some long-range correlated process dominating time scales of several hours to days, and pronounced low-frequency variability associated with tidal and/or meteorological forcing. In order to further decompose these different scales of variability, we apply two different approaches. On the one hand, applying multi-resolution analysis based on the discrete wavelet transform allows separately studying contributions on different time scales and characterize their specific correlation and scaling properties. On the other hand, singular system analysis (SSA) provides a reconstruction of the essential modes of variability. Specifically, by considering only the first leading SSA modes, we achieve an efficient de-noising of our environmental signals, highlighting the low-frequency variations together with some distinct scaling on sub-daily time-scales resembling the properties of a long-range correlated process.

Revisiting the Robustness of PET-Based Textural Features in the Context of Multi-Centric Trials

PubMed Central

Bailly, Clément; Bodet-Milin, Caroline; Couespel, Solène; Necib, Hatem; Kraeber-Bodéré, Françoise; Ansquer, Catherine; Carlier, Thomas

2016-01-01

Purpose This study aimed to investigate the variability of textural features (TF) as a function of acquisition and reconstruction parameters within the context of multi-centric trials. Methods The robustness of 15 selected TFs were studied as a function of the number of iterations, the post-filtering level, input data noise, the reconstruction algorithm and the matrix size. A combination of several reconstruction and acquisition settings was devised to mimic multi-centric conditions. We retrospectively studied data from 26 patients enrolled in a diagnostic study that aimed to evaluate the performance of PET/CT 68Ga-DOTANOC in gastro-entero-pancreatic neuroendocrine tumors. Forty-one tumors were extracted and served as the database. The coefficient of variation (COV) or the absolute deviation (for the noise study) was derived and compared statistically with SUVmax and SUVmean results. Results The majority of investigated TFs can be used in a multi-centric context when each parameter is considered individually. The impact of voxel size and noise in the input data were predominant as only 4 TFs presented a high/intermediate robustness against SUV-based metrics (Entropy, Homogeneity, RP and ZP). When combining several reconstruction settings to mimic multi-centric conditions, most of the investigated TFs were robust enough against SUVmax except Correlation, Contrast, LGRE, LGZE and LZLGE. Conclusion Considering previously published results on either reproducibility or sensitivity against delineation approach and our findings, it is feasible to consider Homogeneity, Entropy, Dissimilarity, HGRE, HGZE and ZP as relevant for being used in multi-centric trials. PMID:27467882

Iterative quantization: a Procrustean approach to learning binary codes for large-scale image retrieval.

PubMed

Gong, Yunchao; Lazebnik, Svetlana; Gordo, Albert; Perronnin, Florent

2013-12-01

This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multiclass spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or "classemes" on the ImageNet data set.

Towards SSVEP-based, portable, responsive Brain-Computer Interface.

PubMed

Kaczmarek, Piotr; Salomon, Pawel

2015-08-01

A Brain-Computer Interface in motion control application requires high system responsiveness and accuracy. SSVEP interface consisted of 2-8 stimuli and 2 channel EEG amplifier was presented in this paper. The observed stimulus is recognized based on a canonical correlation calculated in 1 second window, ensuring high interface responsiveness. A threshold classifier with hysteresis (T-H) was proposed for recognition purposes. Obtained results suggest that T-H classifier enables to significantly increase classifier performance (resulting in accuracy of 76%, while maintaining average false positive detection rate of stimulus different then observed one between 2-13%, depending on stimulus frequency). It was shown that the parameters of T-H classifier, maximizing true positive rate, can be estimated by gradient-based search since the single maximum was observed. Moreover the preliminary results, performed on a test group (N=4), suggest that for T-H classifier exists a certain set of parameters for which the system accuracy is similar to accuracy obtained for user-trained classifier.

Predictors of perceptions of mental illness and averseness to help: a survey of elite football players.

PubMed

Jones, Tiffanie-Victoria

2016-10-01

Hypermasculinity may impact elite football players' willingness to seek help for mental health problems. This quantitative study sought to identify what set of characteristics, including hypermasculinity, best predicts elite football players' mental health attitudes. The Attitude Scale for Mental Illness, Inventory of Attitudes toward Seeking Mental Health Services, and Athlete's Perception of Masculinity Scale were self-administered to 112 football players from the NFLPA and the Washington, DC metro area. Canonical correlation analysis was used to develop a regression model that best predicts elite football players' mental health attitudes. This study found that though the athletes have high levels of hypermasculinity (x = 19.66, SD = 7.43), other factors, including marital status and sport level lessen the effects of hypermasculinity and facilitate positive perceptions of mental illness and receptivity to help. Predictors suggest that therapeutic efforts targeted toward family and support networks, as well as intervention strategies for decreasing mental illness stigma are essential to encourage positive mental health attitudes in elite football players.

Application of ecological, geological and oceanographic ERTS-1 imagery to Delaware's coastal resources management

NASA Technical Reports Server (NTRS)

Klemas, V. (Principal Investigator); Bartlett, D. S.; Philpot, W. D.; Davis, G. R.; Rogers, R. H.; Reed, L.

1974-01-01

The author has identified the following significant results. Data from twelve successful ERTS-1 passes over Delaware Bay have been analyzed with special emphasis on coastal vegetation, land use, current circulation, water turbidity and pollution dispersion. Secchi depth, suspended sediment concentration and transmissivity as measured from helicopters and boats were correlated with ERTS-1 image radiance. Multispectral signatures of acid disposal plumes, sediment plumes and slick were investigated. Ten vegetative cover and water discrimination classes were selected for mapping: (1) forest-land; (2) Phragmites communis; (3) Spartina patens and Distichlis spicata; (4) Spartina alterniflora; (5) cropland; (6) plowed cropland; (7) sand and bare sandy soil; (8) bare mud; (9) deep water; and (10) sediment-laden and shallow water. Canonical analysis predicted good classification accuracies for most categories. The actual classification accuracies were very close to the predicted values with 8 of 10 categories classified with greater than 90% accuracy indicating that representative training sets had been selected.

Gene-to-metabolite network for biosynthesis of lignans in MeJA-elicited Isatis indigotica hairy root cultures

PubMed Central

Chen, Ruibing; Li, Qing; Tan, Hexin; Chen, Junfeng; Xiao, Ying; Ma, Ruifang; Gao, Shouhong; Zerbe, Philipp; Chen, Wansheng; Zhang, Lei

2015-01-01

Root and leaf tissue of Isatis indigotica shows notable anti-viral efficacy, and are widely used as “Banlangen” and “Daqingye” in traditional Chinese medicine. The plants' pharmacological activity is attributed to phenylpropanoids, especially a group of lignan metabolites. However, the biosynthesis of lignans in I. indigotica remains opaque. This study describes the discovery and analysis of biosynthetic genes and AP2/ERF-type transcription factors involved in lignan biosynthesis in I. indigotica. MeJA treatment revealed differential expression of three genes involved in phenylpropanoid backbone biosynthesis (IiPAL, IiC4H, Ii4CL), five genes involved in lignan biosynthesis (IiCAD, IiC3H, IiCCR, IiDIR, and IiPLR), and 112 putative AP2/ERF transcription factors. In addition, four intermediates of lariciresinol biosynthesis were found to be induced. Based on these results, a canonical correlation analysis using Pearson's correlation coefficient was performed to construct gene-to-metabolite networks and identify putative key genes and rate-limiting reactions in lignan biosynthesis. Over-expression of IiC3H, identified as a key pathway gene, was used for metabolic engineering of I. indigotica hairy roots, and resulted in an increase in lariciresinol production. These findings illustrate the utility of canonical correlation analysis for the discovery and metabolic engineering of key metabolic genes in plants. PMID:26579184

Late summer sea ice segmentation with multi-polarisation SAR features in C- and X-band

NASA Astrophysics Data System (ADS)

Fors, A. S.; Brekke, C.; Doulgeris, A. P.; Eltoft, T.; Renner, A. H. H.; Gerland, S.

2015-09-01

In this study we investigate the potential of sea ice segmentation by C- and X-band multi-polarisation synthetic aperture radar (SAR) features during late summer. Five high-resolution satellite SAR scenes were recorded in the Fram Strait covering iceberg-fast first-year and old sea ice during a week with air temperatures varying around zero degrees Celsius. In situ data consisting of sea ice thickness, surface roughness and aerial photographs were collected during a helicopter flight at the site. Six polarimetric SAR features were extracted for each of the scenes. The ability of the individual SAR features to discriminate between sea ice types and their temporally consistency were examined. All SAR features were found to add value to sea ice type discrimination. Relative kurtosis, geometric brightness, cross-polarisation ratio and co-polarisation correlation angle were found to be temporally consistent in the investigated period, while co-polarisation ratio and co-polarisation correlation magnitude were found to be temporally inconsistent. An automatic feature-based segmentation algorithm was tested both for a full SAR feature set, and for a reduced SAR feature set limited to temporally consistent features. In general, the algorithm produces a good late summer sea ice segmentation. Excluding temporally inconsistent SAR features improved the segmentation at air temperatures above zero degrees Celcius.

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

Santiago, Francisco; Oguma, Junya; Brown, Anthony M.C.

Highlights: Black-Right-Pointing-Pointer First demonstration of direct role for noncanonical Wnt in osteoclast differentiation. Black-Right-Pointing-Pointer Demonstration of Ryk as a Wnt5a/b receptor in inhibition of canonical Wnt signaling. Black-Right-Pointing-Pointer Modulation of noncanonical Wnt signaling by a clinically important drug, ritonavir. Black-Right-Pointing-Pointer Establishes a mechanism for an important clinical problem: HIV-associated bone loss. -- Abstract: Wnt proteins that signal via the canonical Wnt/{beta}-catenin pathway directly regulate osteoblast differentiation. In contrast, most studies of Wnt-related effects on osteoclasts involve indirect changes. While investigating bone mineral density loss in the setting of human immunodeficiency virus (HIV) infection and its treatment with the protease inhibitormore » ritonavir (RTV), we observed that RTV decreased nuclear localization of {beta}-catenin, critical to canonical Wnt signaling, in primary human and murine osteoclast precursors. This occurred in parallel with upregulation of Wnt5a and Wnt5b transcripts. These Wnts typically stimulate noncanonical Wnt signaling, and this can antagonize the canonical Wnt pathway in many cell types, dependent upon Wnt receptor usage. We now document RTV-mediated upregulation of Wnt5a/b protein in osteoclast precursors. Recombinant Wnt5b and retrovirus-mediated expression of Wnt5a enhanced osteoclast differentiation from human and murine monocytic precursors, processes facilitated by RTV. In contrast, canonical Wnt signaling mediated by Wnt3a suppressed osteoclastogenesis. Both RTV and Wnt5b inhibited canonical, {beta}-catenin/T cell factor-based Wnt reporter activation in osteoclast precursors. RTV- and Wnt5-induced osteoclast differentiation were dependent upon the receptor-like tyrosine kinase Ryk, suggesting that Ryk may act as a Wnt5a/b receptor in this context. This is the first demonstration of a direct role for Wnt signaling pathways and Ryk in regulation of osteoclast differentiation, and its modulation by a clinically important drug, ritonavir. These studies also reveal a potential role for noncanonical Wnt5a/b signaling in acceleration of bone mineral density loss in HIV-infected individuals, and illuminate a potential means of influencing such processes in disease states that involve enhanced osteoclast activity.« less

49 CFR 1103.5 - Discipline.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 8 2010-10-01 2010-10-01 false Discipline. 1103.5 Section 1103.5 Transportation... Board's rules including the Canons of Ethics set out in §§ 1103.10 through 1103.35; or (3) Engaged in... TRANSPORTATION RULES OF PRACTICE PRACTITIONERS General Information § 1103.5 Discipline. (a) A member of the Board...

Frames of Reference in Spatial Memories Acquired From Language

ERIC Educational Resources Information Center

Mou, Weimin; Zhang, Kan; McNamara, Timothy P.

2004-01-01

Four experiments examined reference systems in spatial memories acquired from language. Participants read narratives that located 4 objects in canonical (front, back, left, right) or noncanonical (left front, right front, left back, right back) positions around them. Participants' focus of attention was first set on each of the 4 objects, and then…

A Simple Model to Teach Business Cycle Macroeconomics for Emerging Market and Developing Economies

ERIC Educational Resources Information Center

Duncan, Roberto

2015-01-01

The canonical neoclassical model is insufficient to understand business cycle fluctuations in emerging market and developing economies. The author reformulates the model proposed by Aguiar and Gopinath (2007) in a simple setting that can be used to teach business cycle macroeconomics for emerging market and developing economies at the…

An Enduring Vision: The Melting Pot That Did Happen.

ERIC Educational Resources Information Center

Portes, Alejandro

2000-01-01

Discusses the 1963 book, "Beyond the Melting Pot," which argued that the melting pot never happened and neither assimilation nor cultural pluralism occurred (at least in New York City). Concludes that this is a landmark book because it challenges the canonical assimilation story, provides a new set of standards for expert knowledge in…

Late-phase synthesis of IκBα insulates the TLR4-activated canonical NF-κB pathway from noncanonical NF-κB signaling in macrophages

PubMed Central

Mukherjee, Tapas; Taye, Nandaraj; Vijayaragavan, Bharath; Chattopadhyay, Samit; Gomes, James; Basak, Soumen

2017-01-01

The nuclear factor κB (NF-κB) transcription factors coordinate the inflammatory immune response during microbial infection. Pathogenic substances engage canonical NF-κB signaling through the heterodimer RelA:p50, which is subjected to rapid negative feedback by inhibitor of κBα (IκBα). The noncanonical NF-κB pathway is required for the differentiation of immune cells; however, crosstalk between both pathways can occur. Concomitantly activated noncanonical signaling generates p52 from the p100 precursor. The synthesis of p100 is induced by canonical signaling, leading to formation of the late-acting RelA:p52 heterodimer. This crosstalk prolongs inflammatory RelA activity in epithelial cells to ensure pathogen clearance. We found that the Toll-like receptor 4 (TLR4)–activated canonical NF-κB signaling pathway is insulated from lymphotoxin β receptor (LTβR)–induced noncanonical signaling in mouse macrophage cell lines. Combined computational and biochemical studies indicated that the extent of NF-κB–responsive expression of Nfkbia, which encodes IκBα, inversely correlated with crosstalk. The Nfkbia promoter showed enhanced responsiveness to NF-κB activation in macrophages compared to that in fibroblasts. We found that this hyperresponsive promoter engaged the RelA:p52 dimer generated during costimulation of macrophages through TLR4 and LTβR to trigger synthesis of IκBα at late time points, which prevented the late-acting RelA crosstalk response. Together, these data suggest that despite the presence of identical signaling networks in cells of diverse lineages, emergent crosstalk between signaling pathways is subject to cell type–specific regulation. We propose that the insulation of canonical and noncanonical NF-κB pathways limits the deleterious effects of macrophage-mediated inflammation. PMID:27923915

Equivalence of linear canonical transform domains to fractional Fourier domains and the bicanonical width product: a generalization of the space-bandwidth product.

PubMed

Oktem, Figen S; Ozaktas, Haldun M

2010-08-01

Linear canonical transforms (LCTs) form a three-parameter family of integral transforms with wide application in optics. We show that LCT domains correspond to scaled fractional Fourier domains and thus to scaled oblique axes in the space-frequency plane. This allows LCT domains to be labeled and ordered by the corresponding fractional order parameter and provides insight into the evolution of light through an optical system modeled by LCTs. If a set of signals is highly confined to finite intervals in two arbitrary LCT domains, the space-frequency (phase space) support is a parallelogram. The number of degrees of freedom of this set of signals is given by the area of this parallelogram, which is equal to the bicanonical width product but usually smaller than the conventional space-bandwidth product. The bicanonical width product, which is a generalization of the space-bandwidth product, can provide a tighter measure of the actual number of degrees of freedom, and allows us to represent and process signals with fewer samples.

Multi-sensors acquisition, data fusion, knowledge mining and alarm triggering in health smart homes for elderly people.

PubMed

Demongeot, Jacques; Virone, Gilles; Duchêne, Florence; Benchetrit, Gila; Hervé, Thierry; Noury, Norbert; Rialle, Vincent

2002-06-01

We deal in this paper with the concept of health smart home (HSH) designed to follow dependent people at home in order to avoid the hospitalisation, limiting hospital sojourns to short acute care or fast specific diagnostic investigations. For elderly people the project of such a HSH has been called AISLE (Apartment with Intelligent Sensors for Longevity Effectiveness). For this purpose, system having three levels of automatic measuring (1) the circadian activity, (2) the vegetative state, and (3) some state variables specific of certain organs involved in precise diseases, has been developed within the framework of a 'Health Integrated Smart Home Information System' (HIS2). HIS2 is an experimental platform for technologic development and clinical evaluation, in order to ensure the medical security and quality of life for patients who need home based medical monitoring. Location sensors are placed in each room of the HIS2, allowing the monitoring of patient's successive daily activity phases within the patient's home environment. We proceed with a sampling in an hourly schedule to detect weak variations of the nycthemeral rhythms. Based on numerous measurements, we establish a mean value with confidence limits of activity variables in normal behaviour permitting to detect for example a sudden abnormal event (like a fall) as well as a chronic pathologic activity (like a pollakiuria), allowing us to define a canonical domain within which the patient's activity is qualified to be 'predictable'. Alerts are set off if the patient's activity deviates from a predictable canonical domain. Moreover, we can follow the cardio-respiratory state by measuring the intensity of the respiratory sinusal arrhythmia in order to quantify the integrity of the bulbar vegetative system, and we finally propose to carefully watch abnormal symptoms like arterial pressure or presence of plasma proteins in the expired air flow for early detecting respectively hypertension or pulmonary oedema.

Bayesian parameter estimation for the Wnt pathway: an infinite mixture models approach.

PubMed

Koutroumpas, Konstantinos; Ballarini, Paolo; Votsi, Irene; Cournède, Paul-Henry

2016-09-01

Likelihood-free methods, like Approximate Bayesian Computation (ABC), have been extensively used in model-based statistical inference with intractable likelihood functions. When combined with Sequential Monte Carlo (SMC) algorithms they constitute a powerful approach for parameter estimation and model selection of mathematical models of complex biological systems. A crucial step in the ABC-SMC algorithms, significantly affecting their performance, is the propagation of a set of parameter vectors through a sequence of intermediate distributions using Markov kernels. In this article, we employ Dirichlet process mixtures (DPMs) to design optimal transition kernels and we present an ABC-SMC algorithm with DPM kernels. We illustrate the use of the proposed methodology using real data for the canonical Wnt signaling pathway. A multi-compartment model of the pathway is developed and it is compared to an existing model. The results indicate that DPMs are more efficient in the exploration of the parameter space and can significantly improve ABC-SMC performance. In comparison to alternative sampling schemes that are commonly used, the proposed approach can bring potential benefits in the estimation of complex multimodal distributions. The method is used to estimate the parameters and the initial state of two models of the Wnt pathway and it is shown that the multi-compartment model fits better the experimental data. Python scripts for the Dirichlet Process Gaussian Mixture model and the Gibbs sampler are available at https://sites.google.com/site/kkoutroumpas/software konstantinos.koutroumpas@ecp.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Parallel Prebiotic Origin of Canonical and Non-Canonical Purine Nucleosides

NASA Astrophysics Data System (ADS)

Becker, S.; Carell, T.

2017-07-01

RNA of all living organisms is highly modified. It is unclear if these non-canonical bases are ancestors of an early Earth or biological inventions. We investigated a prebiotic pathway that leads to canonical and non-canonical purine nucleosides.

A Multi-Channel Method for Detecting Periodic Forced Oscillations in Power Systems

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

Follum, James D.; Tuffner, Francis K.

2016-11-14

Forced oscillations in electric power systems are often symptomatic of equipment malfunction or improper operation. Detecting and addressing the cause of the oscillations can improve overall system operation. In this paper, a multi-channel method of detecting forced oscillations and estimating their frequencies is proposed. The method operates by comparing the sum of scaled periodograms from various channels to a threshold. A method of setting the threshold to specify the detector's probability of false alarm while accounting for the correlation between channels is also presented. Results from simulated and measured power system data indicate that the method outperforms its single-channel counterpartmore » and is suitable for real-world applications.« less

Development of a selective left-hemispheric fronto-temporal network for processing syntactic complexity in language comprehension.

PubMed

Xiao, Yaqiong; Friederici, Angela D; Margulies, Daniel S; Brauer, Jens

2016-03-01

The development of language comprehension abilities in childhood is closely related to the maturation of the brain, especially the ability to process syntactically complex sentences. Recent studies proposed that the fronto-temporal connection within left perisylvian regions, supporting the processing of syntactically complex sentences, is still immature at preschool age. In the current study, resting state functional magnetic resonance imaging data were acquired from typically developing 5-year-old children and adults to shed further light on the brain functional development. Children additionally performed a behavioral syntactic comprehension test outside the scanner. The amplitude of low-frequency fluctuations was analyzed in order to identify the functional correlation networks of language-relevant brain regions. Results showed an intrahemispheric correlation between left inferior frontal gyrus (IFG) and left posterior superior temporal sulcus (pSTS) in adults, whereas an interhemispheric correlation between left IFG and its right-hemispheric homolog was predominant in children. Correlation analysis between resting-state functional connectivity and sentence processing performance in 5-year-olds revealed that local connectivity within the left IFG is associated with competence of processing syntactically simple canonical sentences, while long-range connectivity between IFG and pSTS in left hemisphere is associated with competence of processing syntactically relatively more complex non-canonical sentences. The present developmental data suggest that a selective left fronto-temporal connectivity network for processing complex syntax is already in functional connection at the age of 5 years when measured in a non-task situation. The correlational findings provide new insight into the relationship between intrinsic functional connectivity and syntactic language abilities in preschool children. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Analysis of the Effects of the Commander’s Battle Positioning on Unit Combat Performance

DTIC Science & Technology

1991-03-01

Analysis ......... .. 58 Logistic Regression Analysis ......... .. 61 Canonical Correlation Analysis ........ .. 62 Descriminant Analysis...entails classifying objects into two or more distinct groups, or responses. Dillon defines descriminant analysis as "deriving linear combinations of the...object given it’s predictor variables. The second objective is, through analysis of the parameters of the descriminant functions, determine those

Forest structure estimation and pattern exploration from discrete return lidar in subalpine forests of the Central Rockies

Treesearch

K. R. Sherrill; M. A. Lefsky; J. B. Bradford; M. G. Ryan

2008-01-01

This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory...

Forest structure estimation and pattern exploration from discrete-return lidar in subalpine forests of the central Rockies

Treesearch

K.R. Sherrill; M.A. Lefsky; J.B. Bradford; M.G. Ryan

2008-01-01

This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory...

Corrigendum to "Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data"

Treesearch

Andrew T. Hudak; Nicholas L. Crookston; Jeffrey S. Evans; David E. hall; Michael J. Falkowski

2009-01-01

The authors regret that an error was discovered in the code within the R software package, yaImpute (Crookston & Finley, 2008), which led to incorrect results reported in the above article. The Most Similar Neighbor (MSN) method computes the distance between reference observations and target observations in a projected space defined using canonical correlation...

A Canonical Correlation Analysis of the Influence of Social Comparison, Gender, and Grade Level on the Multidimensional Self-Concepts of Gifted Adolescents

ERIC Educational Resources Information Center

Rinn, Anne N.; Jamieson, Kelly M.; Gross, Candace M.; McQueen, Kand S.

2009-01-01

This study examines the effects of social comparison, gender, and grade level on gifted adolescents' multidimensional self-concept. Participants include 248 gifted adolescents who had completed the sixth through tenth grade during the previous academic year. Multidimensional self-concept was measured using the Self Description Questionnaire II…

Assessment of mental stress effects on prefrontal cortical activities using canonical correlation analysis: an fNIRS-EEG study

PubMed Central

Al-Shargie, Fares; Tang, Tong Boon; Kiguchi, Masashi

2017-01-01

This paper presents an investigation about the effects of mental stress on prefrontal cortex (PFC) subregions using simultaneous measurement of functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) signals. The aim is to explore canonical correlation analysis (CCA) technique to study the relationship among the bi-modality signals in mental stress assessment, and how we could fuse the signals for better accuracy in stress detection. Twenty-five male healthy subjects participated in the study while performing mental arithmetic task under control and stress (under time pressure with negative feedback) conditions. The fusion of brain signals acquired by fNIRS-EEG was performed at feature-level using CCA by maximizing the inter-subject covariance across modalities. The CCA result discovered the associations across the modalities and estimated the components responsible for these associations. The experiment results showed that mental stress experienced by this cohort of subjects is subregion specific and localized to the right ventrolateral PFC subregion. These suggest the right ventrolateral PFC as a suitable candidate region to extract biomarkers as performance indicators of neurofeedback training in stress coping. PMID:28663892

Extending local canonical correlation analysis to handle general linear contrasts for FMRI data.

PubMed

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

PubMed Central

Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai

2018-01-01

Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950

A Multifunctional Sensor in Ternary Solution Using Canonical Correlations for Variable Links Assessment

PubMed Central

Liu, Dan; Wang, Qisong; Liu, Xin; Niu, Ruixin; Zhang, Yan; Sun, Jinwei

2016-01-01

Accurately measuring the oil content and salt content of crude oil is very important for both estimating oil reserves and predicting the lifetime of an oil well. There are some problems with the current methods such as high cost, low precision, and difficulties in operation. To solve these problems, we present a multifunctional sensor, which applies, respectively, conductivity method and ultrasound method to measure the contents of oil, water, and salt. Based on cross sensitivity theory, these two transducers are ideally integrated for simplifying the structure. A concentration test of ternary solutions is carried out to testify its effectiveness, and then Canonical Correlation Analysis is applied to evaluate the data. From the perspective of statistics, the sensor inputs, for instance, oil concentration, salt concentration, and temperature, are closely related to its outputs including output voltage and time of flight of ultrasound wave, which further identify the correctness of the sensing theory and the feasibility of the integrated design. Combined with reconstruction algorithms, the sensor can realize the content measurement of the solution precisely. The potential development of the proposed sensor and method in the aspect of online test for crude oil is of important reference and practical value. PMID:27775640

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

PubMed Central

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic. PMID:22461786

Are neoclassical canons valid for southern Chinese faces?

PubMed

Jayaratne, Yasas S N; Deutsch, Curtis K; McGrath, Colman P J; Zwahlen, Roger A

2012-01-01

Proportions derived from neoclassical canons, initially described by Renaissance sculptors and painters, are still being employed as aesthetic guidelines during the clinical assessment of the facial morphology. 1. to determine the applicability of neoclassical canons for Southern Chinese faces and 2. to explore gender differences in relation to the applicability of the neoclassical canons and their variants. 3-D photographs acquired from 103 young adults (51 males and 52 females) without facial dysmorphology were used to test applicability of four neoclassical canons. Standard anthropometric measurements that determine the facial canons were made on these 3-D images. The validity of the canons as well as their different variants were quantified. The neoclassical cannons seldom applied to these individuals, and facial three-section and orbital canons did not apply at all. The orbitonasal canon was most frequently applicable, with a frequency of 19%. Significant sexual dimorphism was found relative to the prevalence of the variants of facial three-section and orbitonasal canons. The neoclassical canons did not appear to apply to our sample when rigorous quantitative measurements were employed. Thus, they should not be used as esthetic goals for craniofacial surgical interventions.

Canonical Probability Distributions for Model Building, Learning, and Inference

DTIC Science & Technology

2006-07-14

hand , are for Ranked nodes set at Unobservable and Auxiliary nodes. The value of alpha is set in the diagnostic window by moving the slider in the upper...right hand side of the window. The upper bound of alpha can be modified by typing the new value in the small edit box to the right of the slider. f...TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER University of Pittsburgh

Analysis of correlated mutations in HIV-1 protease using spectral clustering.

PubMed

Liu, Ying; Eyal, Eran; Bahar, Ivet

2008-05-15

The ability of human immunodeficiency virus-1 (HIV-1) protease to develop mutations that confer multi-drug resistance (MDR) has been a major obstacle in designing rational therapies against HIV. Resistance is usually imparted by a cooperative mechanism that can be elucidated by a covariance analysis of sequence data. Identification of such correlated substitutions of amino acids may be obscured by evolutionary noise. HIV-1 protease sequences from patients subjected to different specific treatments (set 1), and from untreated patients (set 2) were subjected to sequence covariance analysis by evaluating the mutual information (MI) between all residue pairs. Spectral clustering of the resulting covariance matrices disclosed two distinctive clusters of correlated residues: the first, observed in set 1 but absent in set 2, contained residues involved in MDR acquisition; and the second, included those residues differentiated in the various HIV-1 protease subtypes, shortly referred to as the phylogenetic cluster. The MDR cluster occupies sites close to the central symmetry axis of the enzyme, which overlap with the global hinge region identified from coarse-grained normal-mode analysis of the enzyme structure. The phylogenetic cluster, on the other hand, occupies solvent-exposed and highly mobile regions. This study demonstrates (i) the possibility of distinguishing between the correlated substitutions resulting from neutral mutations and those induced by MDR upon appropriate clustering analysis of sequence covariance data and (ii) a connection between global dynamics and functional substitution of amino acids.

Molecular signatures database (MSigDB) 3.0.

PubMed

Liberzon, Arthur; Subramanian, Aravind; Pinchback, Reid; Thorvaldsdóttir, Helga; Tamayo, Pablo; Mesirov, Jill P

2011-06-15

Well-annotated gene sets representing the universe of the biological processes are critical for meaningful and insightful interpretation of large-scale genomic data. The Molecular Signatures Database (MSigDB) is one of the most widely used repositories of such sets. We report the availability of a new version of the database, MSigDB 3.0, with over 6700 gene sets, a complete revision of the collection of canonical pathways and experimental signatures from publications, enhanced annotations and upgrades to the web site. MSigDB is freely available for non-commercial use at http://www.broadinstitute.org/msigdb.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

What is the benefit of driving a hydrological model with data from a multi-site weather generator compared to data from a simple delta change approach?"

NASA Astrophysics Data System (ADS)

Rössler, Ole; Keller, Denise; Fischer, Andreas

2016-04-01

In 2011 the Swiss national consortium C2SM providednew climate change scenarios were released in Switzerland that came with a comprehensive data set of temperature and precipitation changes under climate change conditions for every a large network of meteorological stations, and for aggregated as well as regions in across Switzerland. These climate change signals were generated for three emission scenarios and three different future time-periods and designed to be used asbased on a delta change factors approach. This data set proved to be very successful in Switzerland as many different users, researchers, private companies, and societal users were able to use and interpret the climate data set. Thus, a range of applications that are all based on the same climate data set enabled a comparable view on climate change impact in several disciplines. The main limitation and criticism to this data set was the usage of the delta change approach for downscaling as it comes with severe limitations such as underestimatinges changes in extreme values and neglecting changes in variability and changes in temporal sequencesneglecting changes in variability, be it year-to-year or day-to-day, and changes in temporal sequences . lacks a change in the day-to-day-variability. One way to overcome this the latter limitation is the usage of stochastic weather generators in a downscaling context. Weather generators are known to be one suitable downscaling technique, but A common limitation of most weather generators is the absence of spatial consistency rrelation in the generated daily time-series, resulting in an underestimation of areal means over several stations that are often low-biased. refer to one point scale (single-site) and lacks the spatial representation of weather. The latter A realistic representation of the inter-station correlation in the downscaled time-series This is of high particular importance in some impact studies, especially infor any hydrological impact studiesy. Recently, a multi-site weather generator was developed and tested for downscaling purposes over Switzerland. The weather generator is of type Richardson, that is run with spatially correlated random number streams to ensure spatial consistency. As a downside, multi-site weather generators are much more complex to develop, but they are a very promising alternative downscaling technique. A new multi-site-weather generator was developed for Switzerland in a previous study (Keller et al. 2014). In this study, we tested this new multi-site-weather generator against the "standard" delta change derived data in a hydrological impact assessment study that focused on runoff in the meso-scale catchment of the river Thur catchment. Two hydrological models of different complexity were run with the data sets under present (1980-2009) and under future conditions (2070-2099), assuming the SRES A1B emission2070-2100 scenario conditions. Eight meteorological stations were used to interpolate a meteorological field that served as input to calibrate and validate the two hydrological models against runoff. The downscaling intercomparison was done for We applied 10 GCM-RCM combinations simulations of the ENSEMBLES. In case of the weather generator, that allows for multiple synthetic realizations, we generated for which change factors for each station (delta change approach) were available and generated 25 realizations of multi-site weather. with each climate model projection. Results show that the delta change driven data constitutes only one appropriate representation compared to theof a bandwidth of runoff projections yielded by the multi-site weather generator data. Especially oOn average, differences between both the two approaches are small. Low and high runoff Runoff values to both extremes are however better reproduced with the weather generator driven data set. The stochastic representation of multiday rainfall events are considered as the main reason. Hence, tThere is a clear yet small added value to the delta change approach that in turn performs rather well. Although these small but considerable differences might questioning the need to construct a multi-site-weather generator with a huge effort, the potential and possibilities to further develop the multi-site weather generator is undoubted.

David Adler Lectureship Award: n-point Correlation Functions in Heterogeneous Materials.

NASA Astrophysics Data System (ADS)

Torquato, Salvatore

2009-03-01

The determination of the bulk transport, electromagnetic, mechanical, and optical properties of heterogeneous materials has a long and venerable history, attracting the attention of some of the luminaries of science, including Maxwell, Lord Rayleigh, and Einstein. The bulk properties can be shown to depend rigorously upon infinite sets of various n-point correlation functions. Many different types of correlation functions arise, depending on the physics of the problem. A unified approach to characterize the microstructure and bulk properties of a large class of disordered materials is developed [S. Torquato, Random Heterogeneous Materials: Microstructure and Macroscopic Properties (Springer-Verlag, New York, 2002)]. This is accomplished via a canonical n-point function Hn from which one can derive exact analytical expressions for any microstructural function of interest. This microstructural information can then be used to estimate accurately the bulk properties of the material. Unlike homogeneous materials, seemingly different bulk properties (e.g., transport and mechanical properties) of a heterogeneous material can be linked to one another because of the common microstructure that they share. Such cross-property relations can be used to estimate one property given a measurement of another. A recently identified decorrelation principle, roughly speaking, refers to the phenomenon that unconstrained correlations that exist in low-dimensional disordered materials vanish as the space dimension becomes large. Among other results, this implies that in sufficiently high dimensions the densest spheres packings may be disordered (rather than ordered) [S. Torquato and F. H. Stillinger, ``New Conjectural Lower Bounds on the Optimal Density of Sphere Packings," Experimental Mathematics, 15, 307 (2006)].

Separating the effects of repulsive and attractive forces on the phase diagram, interfacial, and critical properties of simple fluids

NASA Astrophysics Data System (ADS)

Fuentes-Herrera, M.; Moreno-Razo, J. A.; Guzmán, O.; López-Lemus, J.; Ibarra-Tandi, B.

2016-06-01

Molecular simulations in the canonical and isothermal-isobaric ensembles were performed to study the effect of varying the shape of the intermolecular potential on the phase diagram, critical, and interfacial properties of model fluids. The molecular interactions were modeled by the Approximate Non-Conformal (ANC) theory potentials. Unlike the Lennard-Jones or Morse potentials, the ANC interactions incorporate parameters (called softnesses) that modulate the steepness of the potential in their repulsive and attractive parts independently. This feature allowed us to separate unambiguously the role of each region of the potential on setting the thermophysical properties. In particular, we found positive linear correlation between all critical coordinates and the attractive and repulsive softness, except for the critical density and the attractive softness which are negatively correlated. Moreover, we found that the physical properties related to phase coexistence (such as span of the liquid phase between the critical and triple points, variations in the P-T vaporization curve, interface width, and surface tension) are more sensitive to changes in the attractive softness than to the repulsive one. Understanding the different roles of attractive and repulsive forces on phase coexistence may contribute to developing more accurate models of liquids and their mixtures.