Short-chain carboxylic acids, a new class of teratogens: studies of potential biochemical mechanisms.

PubMed

Coakley, M E; Rawlings, S J; Brown, N A

1986-12-01

Certain short-chain carboxylic acids (SCCA) appear to share a common teratogenic potential, although the structural requirements for activity remain obscure. By using a whole rat embryo culture model system, several biochemical processes have been examined, either as potential initial sites of teratogenic action or as early steps in the pathway to malformation. Valproate, methoxyacetate, and butyrate were the prototype SCCA examined. Measurement of [14C]glucose utilization and lactate production confirmed that energy production by the early organogenesis embryo is predominantly from glycolysis. While the positive control agent, iodoacetate, caused a significant inhibition of lactate production, none of the SCCA affected this process or glucose utilization at teratogenic concentrations. Valproate did not influence embryonic acetyl CoA levels, in marked contrast to the reported response of adult liver, the other major target of valproate toxicity. Pinocytosis by the visceral yolk sac (VYS) was measured by the uptake of [125I]polyvinylpyrrolidone. This process ultimately supplies the embryo with amino-acids and is essential for normal development. SCCA induce morphological abnormalities of the VYS in embryo culture. Pinocytosis was slightly reduced by valporate, but not the other SCCA. However, comparison with the action of an antiserum, for which inhibition of pinocytosis is the initial teratogenic insult, suggests that this is not the mechanism for valproate. Incorporation of [3H]thymidine into embryo or yolk sac was not affected after 3 hr of SCCA exposure, but there was a marked effect of the positive control, hydroxyurea. This suggests that DNA synthesis is not directly influenced by SCCA.(ABSTRACT TRUNCATED AT 250 WORDS)

Short-chain carboxylic acids, a new class of teratogens: studies of potential biochemical mechanisms.

PubMed Central

Coakley, M E; Rawlings, S J; Brown, N A

1986-01-01

Certain short-chain carboxylic acids (SCCA) appear to share a common teratogenic potential, although the structural requirements for activity remain obscure. By using a whole rat embryo culture model system, several biochemical processes have been examined, either as potential initial sites of teratogenic action or as early steps in the pathway to malformation. Valproate, methoxyacetate, and butyrate were the prototype SCCA examined. Measurement of [14C]glucose utilization and lactate production confirmed that energy production by the early organogenesis embryo is predominantly from glycolysis. While the positive control agent, iodoacetate, caused a significant inhibition of lactate production, none of the SCCA affected this process or glucose utilization at teratogenic concentrations. Valproate did not influence embryonic acetyl CoA levels, in marked contrast to the reported response of adult liver, the other major target of valproate toxicity. Pinocytosis by the visceral yolk sac (VYS) was measured by the uptake of [125I]polyvinylpyrrolidone. This process ultimately supplies the embryo with amino-acids and is essential for normal development. SCCA induce morphological abnormalities of the VYS in embryo culture. Pinocytosis was slightly reduced by valporate, but not the other SCCA. However, comparison with the action of an antiserum, for which inhibition of pinocytosis is the initial teratogenic insult, suggests that this is not the mechanism for valproate. Incorporation of [3H]thymidine into embryo or yolk sac was not affected after 3 hr of SCCA exposure, but there was a marked effect of the positive control, hydroxyurea. This suggests that DNA synthesis is not directly influenced by SCCA.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:3830097

Impact of socioeconomic status on survival for patients with anal cancer.

PubMed

Lin, Daniel; Gold, Heather T; Schreiber, David; Leichman, Lawrence P; Sherman, Scott E; Becker, Daniel J

2018-04-15

Although outcomes for patients with squamous cell carcinoma of the anus (SCCA) have improved, the gains in benefit may not be shared uniformly among patients of disparate socioeconomic status. In the current study, the authors investigated whether area-based median household income (MHI) is predictive of survival among patients with SCCA. Patients diagnosed with SCCA from 2004 through 2013 in the Surveillance, Epidemiology, and End Results registry were included. Socioeconomic status was defined by census-tract MHI level and divided into quintiles. Multivariable Cox proportional hazards models and logistic regression were used to study predictors of survival and radiotherapy receipt. A total of 9550 cases of SCCA were included. The median age of the patients was 58 years, 63% were female, 85% were white, and 38% were married. In multivariable analyses, patients living in areas with lower MHI were found to have worse overall survival and cancer-specific survival (CSS) compared with those in the highest income areas. Mortality hazard ratios for lowest to highest income were 1.32 (95% confidence interval [95% CI], 1.18-1.49), 1.31 (95% CI, 1.16-1.48), 1.19 (95% CI, 1.06-1.34), and 1.16 (95% CI, 1.03-1.30). The hazard ratios for CSS similarly ranged from 1.34 to 1.22 for lowest to highest income. Older age, black race, male sex, unmarried marital status, an earlier year of diagnosis, higher tumor grade, and later American Joint Committee on Cancer stage of disease also were associated with worse CSS. Income was not found to be associated with the odds of initiating radiotherapy in multivariable analysis (odds ratio of 0.87 for lowest to highest income level; 95% CI, 0.63-1.20). MHI appears to independently predict CSS and overall survival in patients with SCCA. Black race was found to remain a predictor of SCCA survival despite controlling for income. Further study is needed to understand the mechanisms by which socioeconomic inequalities affect cancer care and outcomes. Cancer 2018;124:1791-7. © 2018 American Cancer Society. © 2018 American Cancer Society.

A newly identified calculation discrepancy of the Sunset semi-continuous carbon analyzer

NASA Astrophysics Data System (ADS)

Zheng, G.; Cheng, Y.; He, K.; Duan, F.; Ma, Y.

2014-01-01

Sunset Semi-Continuous Carbon Analyzer (SCCA) is an instrument widely used for carbonaceous aerosol measurement. Despite previous validation work, here we identified a new type of SCCA calculation discrepancy caused by the default multi-point baseline correction method. When exceeding a certain threshold carbon load, multi-point correction could cause significant Total Carbon (TC) underestimation. This calculation discrepancy was characterized for both sucrose and ambient samples with three temperature protocols. For ambient samples, 22%, 36% and 12% TC was underestimated by the three protocols, respectively, with corresponding threshold being ~0, 20 and 25 μg C. For sucrose, however, such discrepancy was observed with only one of these protocols, indicating the need of more refractory SCCA calibration substance. The discrepancy was less significant for the NIOSH (National Institute for Occupational Safety and Health)-like protocol compared with the other two protocols based on IMPROVE (Interagency Monitoring of PROtected Visual Environments). Although the calculation discrepancy could be largely reduced by the single-point baseline correction method, the instrumental blanks of single-point method were higher. Proposed correction method was to use multi-point corrected data when below the determined threshold, while use single-point results when beyond that threshold. The effectiveness of this correction method was supported by correlation with optical data.

A newly identified calculation discrepancy of the Sunset semi-continuous carbon analyzer

NASA Astrophysics Data System (ADS)

Zheng, G. J.; Cheng, Y.; He, K. B.; Duan, F. K.; Ma, Y. L.

2014-07-01

The Sunset semi-continuous carbon analyzer (SCCA) is an instrument widely used for carbonaceous aerosol measurement. Despite previous validation work, in this study we identified a new type of SCCA calculation discrepancy caused by the default multipoint baseline correction method. When exceeding a certain threshold carbon load, multipoint correction could cause significant total carbon (TC) underestimation. This calculation discrepancy was characterized for both sucrose and ambient samples, with two protocols based on IMPROVE (Interagency Monitoring of PROtected Visual Environments) (i.e., IMPshort and IMPlong) and one NIOSH (National Institute for Occupational Safety and Health)-like protocol (rtNIOSH). For ambient samples, the IMPshort, IMPlong and rtNIOSH protocol underestimated 22, 36 and 12% of TC, respectively, with the corresponding threshold being ~ 0, 20 and 25 μgC. For sucrose, however, such discrepancy was observed only with the IMPshort protocol, indicating the need of more refractory SCCA calibration substance. Although the calculation discrepancy could be largely reduced by the single-point baseline correction method, the instrumental blanks of single-point method were higher. The correction method proposed was to use multipoint-corrected data when below the determined threshold, and use single-point results when beyond that threshold. The effectiveness of this correction method was supported by correlation with optical data.

Genomic Profiling of Penile Squamous Cell Carcinoma Reveals New Opportunities for Targeted Therapy.

PubMed

McDaniel, Andrew S; Hovelson, Daniel H; Cani, Andi K; Liu, Chia-Jen; Zhai, Yali; Zhang, Yajia; Weizer, Alon Z; Mehra, Rohit; Feng, Felix Y; Alva, Ajjai S; Morgan, Todd M; Montgomery, Jeffrey S; Siddiqui, Javed; Sadis, Seth; Bandla, Santhoshi; Williams, Paul D; Cho, Kathleen R; Rhodes, Daniel R; Tomlins, Scott A

2015-12-15

Penile squamous cell carcinoma (PeSCCA) is a rare malignancy for which there are limited treatment options due to a poor understanding of the molecular alterations underlying disease development and progression. Therefore, we performed comprehensive, targeted next-generation sequencing to identify relevant somatic genomic alterations in a retrospective cohort of 60 fixed tumor samples from 43 PeSCCA cases (including 14 matched primary/metastasis pairs). We identified a median of two relevant somatic mutations and one high-level copy-number alteration per sample (range, 0-5 and 0-6, respectively). Expression of HPV and p16 was detectable in 12% and 28% of patients, respectively. Furthermore, advanced clinical stage, lack of p16 expression, and MYC and CCND1 amplifications were significantly associated with shorter time to progression or PeSCCA-specific survival. Notably, four cases harbored EGFR amplifications and one demonstrated CDK4 amplification, genes for which approved and investigational targeted therapies are available. Importantly, although paired primary tumors and lymph node metastases were largely homogeneous for relevant somatic mutations, we identified heterogeneous EGFR amplification in primary tumor/lymph node metastases in 4 of 14 cases, despite uniform EGFR protein overexpression. Likewise, activating HRAS mutations occurred in 8 of 43 cases. Taken together, we provide the first comprehensive molecular PeSCCA analysis, which offers new insight into potential precision medicine approaches for this disease, including strategies targeting EGFR. ©2015 American Association for Cancer Research.

Outcomes following total laryngectomy for squamous cell carcinoma: one centre experience.

PubMed

Leong, S C; Kartha, S-S; Kathan, C; Sharp, J; Mortimore, S

2012-12-01

To evaluate the clinical outcomes of total laryngectomy (TL), complications and factors affecting survival. Retrospective review of hospital electronic database for head and neck squamous cell carcinoma (SCCa). Large district general hospital in England, United Kingdom. Patients who had TL between January 1994 and January 2008. 5-year disease specific survival (DSS) and disease-free survival (DFS). Seventy-one patients were reviewed, of whom 38 (54%) had laryngeal SCCa and 33 (46%) hypopharyngeal SCCa. The overall mean survival period following TL was 42.4 months. The 5-year DSS and DFS was better for laryngeal SCCa compared to hypopharyngeal SCCa, although not statistically significant (P=0.090, P=0.54 respectively). Patients treated for laryngeal SCCa had a mean survival period of 47.5 months compared to 36.5 months for hypopharyngeal disease. Those who had laryngeal recurrence after primary radiotherapy (RT) demonstrated statistically better survival probability than those who had hypopharyngeal recurrence (P=0.011). Patients without cervical lymphadenopathy had statistically better survival (P=0.049). The most common early complication was related to the cardiorespiratory system. One fatal complication of erosion of the brachiocephalic artery due to the laryngectomy tube was noted. The most common late complication was neopharyngeal stenosis. The commonest cause of death was due to locoregional recurrence, followed by medical co-morbidities. Patients referred to specialised head and neck clinic had a better survival probability than those referred to a general ENT clinic (P=0.37). While there is increasing tendency towards laryngeal conservation, total laryngectomy remains a robust treatment option in selected patients. Copyright © 2012. Published by Elsevier Masson SAS.

Levamisole and/or Chinese medicinal herbs can modulate the serum level of squamous cell carcinoma associated antigen in patients with erosive oral lichen planus.

PubMed

Sun, A; Chiang, C P

2001-10-01

The serum levels of squamous cell carcinoma associated antigen (SCCA) were determined by a microparticle enzyme immunoassay in a group of patients with stage I oral squamous cell carcinoma (OSCC), major or minor type erosive oral lichen planus (EOLP), recurrent aphthous stomatitis (RAS), Behçet's disease (BD), oral leukoplakia (OL), or oral submucous fibrosis (OSF), and in normal control subjects. About 97% of the normal control subjects and the patients with minor type EOLP, RAS, BD, OL or OSF had a serum level of SCCA within the normal limit of 1.2 ng/ml. However, 6 of the 12 (50%) patients with stage I OSCC and 14 of the 31 (45.2%) patients with major type EOLP had a serum level of SCCA greater than 1.2 ng/ml. The mean serum level of SCCA in stage I OSCC patients (1.38+/-1.16 ng/ml) or in major type EOLP patients (1.32+/-1.23 ng/ml) was significantly higher than that in normal control subjects (P<0.001) and that in the patients with minor type EOLP (P<0.001), RAS (P<0.001), BD (P<0.05), OL (P<0.05), or OSF (P<0.05). Either major or minor type EOLP patients could obtain a significant mean reduction of the serum SCCA level of 0.34-0.63 ng/ml after treatment with levamisole and/or Chinese medicinal herbs for 1-30 months. Combination therapy with levamisole plus Chinese medicinal herbs could achieve a shorter duration of treatment to get complete remission than the single therapy with either levamisole only or Chinese medicinal herbs only. We conclude that levamisole and/or Chinese medicinal herbs can modulate the serum SCCA level in EOLP patients. SCCA may be a useful marker in evaluating therapeutic effects and in monitoring the disease status of EOLP. For EOLP patients, the combination therapy is superior to the single therapy of levamisole or of Chinese medicinal herbs.

Elevated risk of human papillomavirus-related second cancers in survivors of anal canal cancer.

PubMed

Nelson, Rebecca A; Lai, Lily L

2017-10-15

Over the last decade, the causal link between human papillomavirus (HPV) infection and squamous cell carcinoma of the anus (SCCA) has been well described. Because HPV infection in one site is often associated with other sites of infection, it then follows that patients with SCCA may have an increased risk of additional HPV-related cancers. Identifying and targeting at-risk sites through cancer screening and surveillance may help to guide best practices. The current study sought to ascertain sites and risk of HPV-related second primary malignancies (SPMs) in survivors of SCCA. Using population-based data from 1992 through 2012, the authors identified patients with SCCA and determined their risk of HPV-related SPMs, including anal, oral, and genital cancers. Standardized incidence ratios (SIRs), defined as observed to expected cases, were calculated to determine excess risk. Of 10,537 patients with SCCA, 416 developed HPV-related SPMs, which corresponded to an overall SIR of 21.5 (99% confidence interval [99% CI], 19.0-24.2). Men were found to have a higher SIR (35.8; 99% CI, 30.7-41.6) compared with women (12.8; 99% CI, 10.4-15.5). SIRs for a second SCCA were markedly higher in men (127.5; 99% CI, 108.1-149.2) compared with women (47.0; 99% CI, 34.7-62.1), whereas SIRs for oral cavity and pharyngeal cancers were elevated in men (3.1; 99% CI, 1.5-5.7) and women (4.4; 99% CI, 1.5-9.7). SIRs for sex-specific sites also were elevated, with male genital cancers having an SIR of 19.6 (99% CI, 8.7-37.6) and female genital cancers an SIR of 8.3 (99% CI, 6.1-11.0). Patients with index SCCA are at an increased risk of subsequent HPV-related SPMs. The elevated risk is most striking in patients with second primary SCCAs; however, the risk of second cancers also appears to be increased in other HPV-related sites. Cancer 2017;123:4013-21. © 2017 American Cancer Society. © 2017 American Cancer Society.

Sensitive immunosensing of squamous cell carcinoma antigen based on a nanocomposite of poly{3-amine-N-[3-(N-pyrrole)propyl]imidazole bromide} ionic liquid and gold nanoroots.

PubMed

Wu, Yingying; Zhao, Yong; Wang, Yanying; Ye, Xiaoxue; Wu, Tsunghsueh; Deng, HongPing; Wu, Peng; Li, Chunya

2017-10-15

Squamous cell carcinoma antigen (SCCA) is a good specific antigen for cancer diagnosis specifically for squamous cell carcinomas. In this study, 3-amine-N-[3-(N-pyrrole)propyl]imidazole bromide (APPIBr) ionic liquid was successfully synthesized and characterized by 1 H NMR, HPLC-MS and FTIR. APPIBr ionic liquid is a unique functional material with a pyrrole moiety which can be polymerized by using electrochemical technique and an amine group for immobilizing biomolecules; thus, it is ideal for the fabrication of biosensors. Using chloroauric acid as precursor and N-dodecyl imidazole as functional monomer, gold nanoroots (AuNRs) were fabricated and characterized with TEM, SEM and XRD. An immunosensor was built on a glassy carbon electrode (GCE), through the steps of forming the poly(APPIBr)/AuNRs/GCE interface by electrodeposition of APPIBr, anti-SCCA immobilization, and several optimization steps to achieve a sensitive, accurate, precise, and selective anti-SCCA/poly(APPIBr)/AuNRs/GCE for the electrochemical immunosensing SCCA. It was found that poly(APPIBr)/AuNRs nanointerface can improve the sensing performance of the immunosensor. Under the optimized experimental conditions, there existed two linear regimes relating the peak current variation to the concentration of squamous cell carcinoma antigen in the range of 0.001-0.1ngmL -1 and 0.1-5.0ngmL -1 . The detection limit was calculated to be 0.3pgmL -1 . The developed sensor was demonstrated its capability in quantitative analysis of squamous cell carcinoma antigen in human serum with recoveries of 97.3%, 102.4% and 107.4%. Copyright © 2017 Elsevier B.V. All rights reserved.

Reconfigurable Microfluidic Magnetic Valve Arrays: Towards a Radiotherapy-Compatible Spheroid Culture Platform for the Combinatorial Screening of Cancer Therapies

PubMed Central

Labelle, Frédérique; Wong, Philip

2017-01-01

We introduce here a microfluidic cell culture platform or spheroid culture chamber array (SCCA) that can synthesize, culture, and enable fluorescence imaging of 3D cell aggregates (typically spheroids) directly on-chip while specifying the flow of reagents in each chamber via the use of an array of passive magnetic valves. The SCCA valves demonstrated sufficient resistance to burst (above 100 mBar), including after receiving radiotherapy (RT) doses of up to 8 Gy combined with standard 37 °C incubation for up to 7 days, enabling the simultaneous synthesis of multiple spheroids from different cell lines on the same array. Our results suggest that SCCA would be an asset in drug discovery processes, seeking to identify combinatorial treatments. PMID:28976942

Nivolumab for previously treated unresectable metastatic anal cancer (NCI9673): a multicentre, single-arm, phase 2 study.

PubMed

Morris, Van K; Salem, Mohamed E; Nimeiri, Halla; Iqbal, Syma; Singh, Preet; Ciombor, Kristen; Polite, Blase; Deming, Dustin; Chan, Emily; Wade, James L; Xiao, Lianchun; Bekaii-Saab, Tanios; Vence, Luis; Blando, Jorge; Mahvash, Armeen; Foo, Wai Chin; Ohaji, Chimela; Pasia, Manolo; Bland, Gail; Ohinata, Aki; Rogers, Jane; Mehdizadeh, Amir; Banks, Kimberly; Lanman, Richard; Wolff, Robert A; Streicher, Howard; Allison, James; Sharma, Padmanee; Eng, Cathy

2017-04-01

Squamous cell carcinoma of the anal canal (SCCA) is a rare malignancy associated with infection by human papillomavirus (HPV). No consensus treatment approach exists for the treatment of metastatic disease. Because intratumoral HPV oncoproteins upregulate immune checkpoint proteins such as PD-1 to evade immune-mediated cytotoxicity, we did a trial of the anti-PD-1 antibody nivolumab for patients with metastatic SCCA. We did this single-arm, multicentre, phase 2 trial at ten academic centres in the USA. We enrolled patients with treatment-refractory metastatic SCCA, who were given nivolumab every 2 weeks (3 mg/kg). The primary endpoint was response according to Response Evaluation Criteria in Solid Tumors, version 1.1, in the intention-to-treat population. At the time of data cutoff, the study was ongoing, with patients continuing to receive treatment. The study is registered with ClinicalTrials.gov, number NCT02314169. We screened 39 patients, of whom 37 were enrolled and received at least one dose of nivolumab. Among the 37 patients, nine (24% [95% CI 15-33]) had responses. There were two complete responses and seven partial responses. Grade 3 adverse events were anaemia (n=2), fatigue (n=1), rash (n=1), and hypothyroidism (n=1). No serious adverse events were reported. To our knowledge, this is the first completed phase 2 trial of immunotherapy for SCCA. Nivolumab is well tolerated and effective as a monotherapy for patients with metastatic SCCA. Immune checkpoint blockade appears to be a promising approach for patients with this orphan disease. National Cancer Institute/Cancer Therapy Evaluation Program, the HPV and Anal Cancer Foundation, the E B Anal Cancer Fund, The University of Texas MD Anderson Moon Shots Program, and an anonymous philanthropic donor. Copyright © 2017 Elsevier Ltd. All rights reserved.

Nivolumab for previously treated unresectable metastatic anal cancer (NCI9673): a multicentre, single-arm, phase 2 study

PubMed Central

Morris, Van K; Salem, Mohamed E; Nimeiri, Halla; Iqbal, Syma; Singh, Preet; Ciombor, Kristen; Polite, Blase; Deming, Dustin; Chan, Emily; Wade, James L; Xiao, Lianchun; Bekaii-Saab, Prof Tanios; Vence, Luis; Blando, Jorge; Mahvash, Armeen; Foo, Wai Chin; Ohaji, Chimela; Pasia, Manolo; Bland, Gail; Ohinata, Aki; Rogers, Jane; Mehdizadeh, Amir; Banks, Kimberly; Lanman, Richard; Wolff, Robert A; Streicher, Howard; Allison, Prof James; Sharma, Prof Padmanee; Eng, Prof Cathy

2018-01-01

Summary Background Squamous cell carcinoma of the anal canal (SCCA) is a rare malignancy associated with infection by human papillomavirus (HPV). No consensus treatment approach exists for the treatment of metastatic disease. Because intratumoral HPV oncoproteins upregulate immune checkpoint proteins such as PD-1 to evade immune-mediated cytotoxicity, we did a trial of the anti-PD-1 antibody nivolumab for patients with metastatic SCCA. Methods We did this single-arm, multicentre, phase 2 trial at ten academic centres in the USA. We enrolled patients with treatment-refractory metastatic SCCA, who were given nivolumab every 2 weeks (3 mg/kg). The primary endpoint was response according to Response Evaluation Criteria in Solid Tumors, version 1.1, in the intention-to-treat population. At the time of data cutoff, the study was ongoing, with patients continuing to receive treatment. The study is registered with ClinicalTrials.gov, number NCT02314169. Findings We screened 39 patients, of whom 37 were enrolled and received at least one dose of nivolumab. Among the 37 patients, nine (24% [95% CI 15–33]) had responses. There were two complete responses and seven partial responses. Grade 3 adverse events were anaemia (n=2), fatigue (n=1), rash (n=1), and hypothyroidism (n=1). No serious adverse events were reported. Interpretation To our knowledge, this is the first completed phase 2 trial of immunotherapy for SCCA. Nivolumab is well tolerated and effective as a monotherapy for patients with metastatic SCCA. Immune checkpoint blockade appears to be a promising approach for patients with this orphan disease. Funding National Cancer Institute/Cancer Therapy Evaluation Program, the HPV and Anal Cancer Foundation, the E B Anal Cancer Fund, The University of Texas MD Anderson Moon Shots Program, and an anonymous philanthropic donor. PMID:28223062

Molecular and structural characteristics in toxic algae cultures of Ostreopsis ovata and Ostreopsis spp. evidenced by FTIR and FTNIR spectroscopy

NASA Astrophysics Data System (ADS)

Mecozzi, Mauro; Pietroletti, Marco; Tornambè, Andrea

2011-05-01

In this article we investigated the compositional and structural characteristics of the principal biomolecules such as carbohydrates, proteins, lipids, nucleic acids and chlorophyll pigments present in biofilm cultures of Ostreopsis spp. and in batch cultures of Ostreopsis ovata. Our approach based on the use of infrared (FTIR) and near infrared (FTNIR) spectroscopy showed the marked differences existing between biofilm cultures and batch cultures. FTIR spectroscopy showed the higher contents of polysaccharides and chlorophyll pigments in O. ovata from batch cultures with respect to Ostreopsis spp. Second derivative FTIR spectroscopy showed different features concerning the secondary structure of proteins because in O. ovata samples the beta sheet and beta turn structures were observed whereas in Ostreopsis spp. samples the alpha helix structure was the most evident. FTNIR spectroscopy showed other structural differences observed existing between O. ovata and Ostreopsis spp. mainly related to hydrogen bond interactions determining more packed structures in the nucleus of O. ovata. In addition, the interpretation of FTIR and FTNIR spectral information was also supported by the application of two statistical methods, the independent component analysis (ICA) and the spectral cross correlation analysis (SCCA). ICA was used as spectral deconvolution technique to separate the effects of the interference bicarbonate ion from algal FTIR spectra so to verify the high similar qualitative composition of the three biofilm samples of Ostreopsis spp. At last, SCCA applied to FTIR and FTNIR spectra was useful to evidence some structural differences involving -CH and CH 2 groups of aliphatic chains in O. ovata and Ostreopsis spp. samples. Though preliminary, these results agree with some previous studies suggesting that the presence of different ecophysiological characteristics in O. ovata and Ostreopsis spp. depending on the parameters related to the condition growth.

Risk factors for infection by oncogenic human papillomaviruses in HIV-positive MSM patients in the ART era (2010-2016).

PubMed

Hidalgo-Tenorio, Carmen; Gil-Anguita, Concepción; Ramírez-Taboada, Jessica; Esquivias, Javier; López-Ruz, Miguel A; Balgahata, Omar Mohamed; Javier-Martinez, Rosario; Pasquau, Juan

2017-09-01

Squamous cell carcinoma of anus (SCCA) is one of the most frequent non-AIDS-defining diseases in HIV patients, mainly in men who have sex with men (MSM), and it is associated with human papillomavirus (HPV) infection.To determine the prevalence of high-risk HPV (HR-HPV) genotypes, premalignant lesions (HSIL) and SCCA in a cohort of HIV-positive MSM; to study the distribution of HPV genotypes according to anal histology results; and to analyze risk factors for this infection.This prospective single-center study was conducted between May 2010 and September 2016. At the study visit, cotton swabs were used to collect anal samples for cytology study in ThinPrep Pap Test liquid medium (Thin Prep Processor 2000, Hologic Corp, USA), and for HPV PCR (Linear Array HPV Genotyping Test). After, high-resolution anoscopy (HRA) (Zeiss 150 fc) was carried out. Logistic regression analysis was performed to identify risk factors for HR-HPV infection.The study included 319 patients, with mean age of 36.7 years; HR-HPV was detected in 81.3%. The prevalence of HSIL was 13.5% and SCCA was 0.3%. With regard to the distribution of HPV genotypes according to histology results, HPV 16 was the most frequent genotype in normal anal mucosa (26.7%), in LSILs (36.9%), and in HSILs (38%). In multivariate analysis, CD4 nadir < 200 cells/μL was the factor associated with infection by HR-HPV (OR 3.66, 95% CI 1.05%-12.75%).HIV-positive MSM showed a high prevalence of HSIL+ lesions and of infection by oncogenic HPV, which appears to be favored by a deficient immune system. HPV 16 was the most frequently isolated genotype in anal mucosa, regardless of lesion type.

Cumulative HIV viremia and non-AIDS-defining malignancies among a sample of HIV-infected male veterans.

PubMed

Kowalkowski, Marc A; Day, Rena S; Du, Xianglin L; Chan, Wenyaw; Chiao, Elizabeth Y

2014-10-01

Research suggests that cumulative measurement of HIV exposure is associated with mortality, AIDS, and AIDS-defining malignancies. However, the relationship between cumulative HIV and non-AIDS-defining malignancies (NADMs) remains unclear. The aim of this study was to evaluate the effect of different HIV measures on NADM hazard among HIV-infected male veterans. We performed a retrospective cohort study using Veterans Affairs HIV Clinical Case Registry data from 1985 to 2010. We analyzed the relationship between HIV exposure (recent HIV RNA, % undetectable HIV RNA, and HIV copy-years viremia) and NADM. To evaluate the effect of HIV, we calculated hazard ratios for 3 common virally associated NADM [ie, hepatocarcinoma (HCC), Hodgkin lymphoma (HL), and squamous cell carcinoma of the anus (SCCA)] in multivariable Cox regression models. Among 31,576 HIV-infected male veterans, 383 HCC, 211 HL, and 373 SCCA cases were identified. In multivariable regression models, cross-sectional HIV measurement was not associated with NADM. However, compared with <20% undetectable HIV, individuals with ≥80% had decreased HL [adjusted hazard ratio (aHR) = 0.62; 95% confidence interval (CI): 0.37 to 1.02] and SCCA (aHR = 0.64; 95% CI: 0.44 to 0.93). Conversely, each log10 increase in HIV copy-years was associated with elevated HL (aHR = 1.22; 95% CI: 1.06 to 1.40) and SCCA (aHR = 1.36; 95% CI: 1.21 to 1.52). Model fit was best with HIV copy-years. Cumulative HIV was not associated with HCC. Cumulative HIV was associated with certain virally associated NADM (ie, HL and SCCA), independent of measured covariates. Findings underline the importance of early treatment initiation and durable medication adherence to reduce cumulative HIV burden. Future research should prioritize how to best apply cumulative HIV measures in screening for these cancers.

Pemphigus vulgaris antigen mRNA quantification for the staging of sentinel lymph nodes in head and neck cancer

PubMed Central

Solassol, J; Burcia, V; Costes, V; Lacombe, J; Mange, A; Barbotte, E; de Verbizier, D; Cartier, C; Makeieff, M; Crampette, L; Boulle, N; Maudelonde, T; Guerrier, B; Garrel, R

2009-01-01

Background: Molecular diagnosis has been proposed to enhance the intra-operative diagnosis of sentinel lymph node (SLN) invasion in head and neck squamous cell carcinoma (HNSCC). Although cytokeratin (CK) mRNA quantification with real-time reverse transcriptase-PCR (QRT–PCR) has produced encouraging results, the more discriminating markers remain to be identified. Methods: Pemphigus vulgaris antigen (PVA), squamous cell carcinoma antigen (SCCA), and CK17 mRNA were quantified using QRT–PCR, and the results were compared with an extensive histopathological examination of the entire SLNs on 78 SLNs harvested from 22 patients with HNSCC. Results: SCCA and CK17 quantification showed significantly higher mRNA values for macrometastases (MAs) than for either negative or isolated tumour cell (ITC) SLNs (P<0.01). Pemphigus vulgaris antigen allowed the discrimination of all MAs and micrometastases from both negative and ITC SLNs (P<0.001). For the neck staging of patients, considering metastatic vs non-metastatic status, receiver-operating characteristic curve analysis found areas under the curve of 93.8, 97.9, and 100% for CK17, SCCA, and PVA, respectively. With PVA, a cutoff value of 562 copies per 100 ng of cDNA permitted the correct distinction between patients with positive as opposed to negative neck nodes in all cases. Conclusion: PVA seems to be a highly promising marker for accurate intra-operative SLN staging in HNSCC by QRT–PCR. PMID:19997107

Speech-language pathology care and short- and long-term outcomes of oropharyngeal cancer treatment in the elderly.

PubMed

Webster, Kimberly T; Tippett, Donna; Simpson, Marissa; Abrams, Rina; Pietsch, Kristine; Herbert, Robert J; Eisele, David W; Gourin, Christine G

2018-06-01

To examine associations between speech-language pathology (SLP) care and pretreatment variables, short-term and long-term swallowing and airway impairment, and survival in elderly patients treated for oropharyngeal squamous cell cancer (SCCA). Retrospective analysis of Surveillance, Epidemiology, and End Results-Medicare data. We evaluated longitudinal data from 666 patients diagnosed with oropharyngeal SCCA from 2004 to 2007 using cross-tabulations, multivariate logistic regression, and survival analysis. SLP care was documented in 25% of patients. High-volume hospital care (odds ratio (OR) = 3.2 [1.0-10.0]) and dysphagia during treatment (OR = 13.0 [3.6-47.1]) were the only significant predictors of SLP care during the initial treatment period. SLP care was significantly more likely during the first year (OR = 5.3 [3.1-9.1]) and second year (OR = 4.5 [2.4-8.2]) following initial treatment. Subsequent dysphagia (OR = 32.5 [16.9-62.4]), stricture (OR = 2.2 [1.2-4.0]), gastrostomy (OR = 1.7 [1.1-2.7]), and tracheostomy tube use (OR = 2.4 [1.2-4.8]) were significantly associated with long-term SLP care. After controlling for patient, tumor, and treatment-related variables, SLP care was associated with significant relative attenuation of the OR for dysphagia (93%), stricture (35%), weight loss (8%), and airway obstruction (34%). Survival analysis, controlling for all other variables, demonstrated improved survival for patients under SLP care (hazard ratio = 0.73 [0.57-0.95]). SLP care is underutilized in elderly oropharyngeal SCCA patients and largely utilized after the onset of impaired airway and swallowing function, but is associated with improved outcomes. These data suggest a need for treatment guidelines that incorporate the routine use of SLP care in this population during the initial treatment period and beyond. 2c. Laryngoscope, 128:1403-1411, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Outcomes of transoral robotic surgery: a preliminary clinical experience.

PubMed

Hurtuk, Agnes; Agrawal, Amit; Old, Matthew; Teknos, Theodoros N; Ozer, Enver

2011-08-01

To report a single institution's experience with transoral robotic surgery (TORS) and its clinical outcomes. Preliminary clinical data from a prospective TORS study. University tertiary care facility. Patients who underwent TORS at The Ohio State University Medical Center. Demographic, intraoperative, clinicopathological, and follow-up functional data were collected. Sixty-four patients underwent TORS with a median age of 56.9 years. A total of 113 TORS procedures were performed. Fifty-four patients with squamous cell cancer (SCCA) were included in the final analysis. Mean follow-up time was 11.8 months (range, 2-29). There was a trend toward longer TORS setup time, operative time, estimated blood loss, and hospital length of stay with advanced (T(3)) compared with early-stage tumors (T(1-2)). There were no major intraoperative complications, and none of the procedures were aborted because of inability to remove the tumor. Negative resection margins were achieved in 93% of cases of SCCA. No patients experienced immediate postoperative complications, and all of the patients tolerated an oral diet without any airway compromise on the day of surgery. Forty-nine patients (91%) underwent adjuvant radiation therapy (RT), with 11 patients requiring gastrostomy tube placement during RT. Addition of TORS to overall management of head and neck SCCA spared adjuvant RT or combined chemotherapy and RT (CRT) in 50% of stage I/II tumors and spared chemotherapy in 34% of stage III/IV tumors. TORS is a safe procedure with minimal complications and favorable clinical and functional outcomes. It is a promising future alternative surgical treatment for laryngopharyngeal tumors.

Squamous cell carcinoma of the anus-an opportunistic cancer in HIV-positive male homosexuals

PubMed Central

Gervaz, Pascal; Calmy, Alexandra; Durmishi, Ymer; Allal, Abdelkarim S; Morel, Philippe

2011-01-01

Squamous cell carcinoma of the anus (SCCA) is a common cancer in the human immunodeficiency virus (HIV)-infected population, and its incidence continues to increase in male homosexuals. Combined chemoradiation with mitomycin C and 5-fluorouracil was poorly tolerated by severely immunocompromised patients in the early 1990s. In the era of highly active antiretroviral therapy (HAART), however, recent data indicate that: (1) most HIV patients with anal cancer can tolerate standard chemotherapy regimens; and (2) this approach is associated with survival rates similar to those of HIV-negative patients. However, HIV-positive patients with SCCA are much younger, more likely to develop local tumor recurrence, and ultimately die from anal cancer than immune competent patients. Taken together, these findings suggest that anal cancer is an often fatal neoplasia in middle-aged HIV-positive male homosexuals. In this population, SCCA is an opportunistic disease resulting in patients with suboptimal immune function from persistent infection and prolonged exposition to oncogenic human papillomaviruses (HPVs). Large-scale cancer-prevention strategies (routine anuscopy and anal papanicolaou testing) should be implemented in this population. In addition, definitive eradication of oncogenic HPVs within the anogenital mucosa of high-risk individuals might require a proactive approach with repeated vaccination. PMID:21799644

HPV circulating tumor DNA to monitor the efficacy of anti-PD-1 therapy in metastatic squamous cell carcinoma of the anal canal: A case report.

PubMed

Cabel, Luc; Bidard, François-Clément; Servois, Vincent; Cacheux, Wulfran; Mariani, Pascale; Romano, Emanuela; Minsat, Mathieu; Bieche, Ivan; Farkhondeh, Fereshteh; Jeannot, Emmanuelle; Buecher, Bruno

2017-10-15

Squamous cell carcinoma of the anal canal (SCCA) is a rare HPV-associated cancer with limited sensitivity to standard chemotherapy. In a phase 2 study, nivolumab, an anti PD-1 immune checkpoint inhibitor, demonstrated significant efficacy as single-agent therapy in metastatic SCCA patients. Nevertheless, imaging assessment by standard RECIST criteria of the efficacy of immune therapy can be difficult in some patients due to tumor immune cell infiltration, and biomarkers of treatment efficacy are needed. We have previously developed a quantitative droplet digital PCR (ddPCR) technique to detect HPV circulating tumor DNA (HPV ctDNA), with excellent sensitivity and specificity. Here, we report, for the first time, the kinetics of HPV ctDNA during therapy in a patient with metastatic SCCA, who obtained sustained partial response to single-agent nivolumab. We observed an early and very significant decrease of HPV ctDNA during therapy from the baseline level of 3713 copies/ml plasma to 564 copies/ml plasma at 4 weeks, and 156 copies/ml at 6 weeks, followed by a plateau. This observation provides proof-of-concept that HPV ctDNA can be used as a noninvasive early dynamic biomarker to monitor the efficacy of new immunotherapy agents. © 2017 UICC.

Lymph node retrieval in abdominoperineal surgical specimen is radiation time-dependent

PubMed Central

Sermier, Alain; Gervaz, Pascal; Egger, Jean F; Dao, My; Allal, Abdelkarim S; Bonet, Marta; Morel, Philippe

2006-01-01

Background A low yield of lymph nodes (LN) in abdominoperineal resection (APR) specimen has been associated with preoperative radiation therapy (XRT) in population-based studies, which may preclude adequate staging of anorectal carcinomas. We hypothesized that the number of LN retrieved in APR specimen was correlated with the dose and the timing of pelvic irradiation. Patients and methods We performed a retrospective study of 102 patients who underwent APR in a single institution between 1980 and 2004. Pathological reports were reviewed and the number of lymph nodes retrieved in APR specimens was correlated with: 1) Preoperative radiation; 2) Dose of pelvic irradiation; and 3) Time interval between the end of XRT and surgery. Results There were 61 men and 41 women, with a median age of 66 (range 25–89) years. There were 12 patients operated for squamous cell carcinoma of the anal canal (SCCA) and 90 for rectal cancer. 83% and 46% of patients with anal and rectal cancer respectively underwent radical/neoadjuvant radiotherapy. The mean ± SD number of LN in APR specimen was 9.2 ± 5.9. The mean number of LN in APR specimen was significantly lower in patients who underwent preoperative XRT (8 ± 5.5 vs. 10.5 ± 6.1, Mann-Whitney U test, p = 0.02). The mean number of LN was not significantly different after XRT in patients with SCCA than in patients with rectal cancer (6.2 ± 5.3 vs. 7.8 ± 5.3, p = 0.33). Finally, there was an inverse correlation between the yield of LN and the time elapsed between XRT and surgery (linear regression coefficient r = -0.32, p = 0.03). Conclusion Our data indicate that: 1) radiation therapy affects the yield of LN retrieval in APR specimen; 2) this impact is time-dependent. These findings have important implications with regard to anatomic-pathological staging of anal and rectal cancers and subsequent decision-making regarding adjuvant chemotherapy. PMID:16749931

CD10/neutral endopeptidase 24.11 hydrolyzes bombesin-like peptides and regulates the growth of small cell carcinomas of the lung.

PubMed Central

Shipp, M A; Tarr, G E; Chen, C Y; Switzer, S N; Hersh, L B; Stein, H; Sunday, M E; Reinherz, E L

1991-01-01

Bombesin-like peptides are essential autocrine growth factors for many small cell carcinomas (SCCas) of the lung. Herein, we demonstrate that these malignant pulmonary neuroendocrine cells express low levels of the cell surface metalloendopeptidase CD10/neutral endopeptidase 24.11 (CD10/NEP, common acute lymphoblastic leukemia antigen) and that this enzyme hydrolyzes bombesin-like peptides. The growth of bombesin-like peptide-dependent SCC as is inhibited by CD10/NEP and potentiated by CD10/NEP inhibition. The results provide evidence that CD10/NEP is involved in the regulation of tumor cell proliferation. Since SCCa of the lung occurs almost exclusively in cigarette smokers and cigarette smoke inactivates CD10/NEP, decreased cell surface CD10/NEP enzymatic activity may be causally related to the development of SCCa of the lung. Images PMID:1660144

CD10/neutral endopeptidase 24.11 hydrolyzes bombesin-like peptides and regulates the growth of small cell carcinomas of the lung.

PubMed

Shipp, M A; Tarr, G E; Chen, C Y; Switzer, S N; Hersh, L B; Stein, H; Sunday, M E; Reinherz, E L

1991-12-01

Bombesin-like peptides are essential autocrine growth factors for many small cell carcinomas (SCCas) of the lung. Herein, we demonstrate that these malignant pulmonary neuroendocrine cells express low levels of the cell surface metalloendopeptidase CD10/neutral endopeptidase 24.11 (CD10/NEP, common acute lymphoblastic leukemia antigen) and that this enzyme hydrolyzes bombesin-like peptides. The growth of bombesin-like peptide-dependent SCC as is inhibited by CD10/NEP and potentiated by CD10/NEP inhibition. The results provide evidence that CD10/NEP is involved in the regulation of tumor cell proliferation. Since SCCa of the lung occurs almost exclusively in cigarette smokers and cigarette smoke inactivates CD10/NEP, decreased cell surface CD10/NEP enzymatic activity may be causally related to the development of SCCa of the lung.

QIN. Early experiences in establishing a regional quantitative imaging network for PET/CT clinical trials

PubMed Central

Doot, Robert K.; Thompson, Tove; Greer, Benjamin E.; Allberg, Keith C.; Linden, Hannah M.; Mankoff, David A.; Kinahan, Paul E.

2012-01-01

The Seattle Cancer Care Alliance (SCCA) is a Pacific Northwest regional network that enables patients from community cancer centers to participate in multicenter oncology clinical trials where patients can receive some trial-related procedures at their local center. Results of positron emission tomography (PET) scans performed at community cancer centers are not currently used in SCCA Network trials since clinical trials customarily accept results from only trial-accredited PET imaging centers located at academic and large hospitals. Oncologists would prefer the option of using standard clinical PET scans from Network sites in multicenter clinical trials to increase accrual of patients for whom additional travel requirements for imaging is a barrier to recruitment. In an effort to increase accrual of rural and other underserved populations to Network trials, researchers and clinicians at the University of Washington, SCCA and its Network are assessing feasibility of using PET scans from all Network sites in their oncology clinical trials. A feasibility study is required because the reproducibility of multicenter PET measurements ranges from approximately 3% to 40% at national academic centers. Early experiences from both national and local PET phantom imaging trials are discussed and next steps are proposed for including patient PET scans from the emerging regional quantitative imaging network in clinical trials. There are feasible methods to determine and characterize PET quantitation errors and improve data quality by either prospective scanner calibration or retrospective post hoc corrections. These methods should be developed and implemented in multicenter clinical trials employing quantitative PET imaging of patients. PMID:22795929

Management Strategies for Skull Base Inverted Papilloma.

PubMed

Grayson, Jessica W; Khichi, Sunny S; Cho, Do-Yeon; Riley, Kristen O; Woodworth, Bradford A

2016-07-01

Inverted papilloma attached to the ventral skull base presents a surgical dilemma because surgical removal of the bony pedicle is critical to decrease risk of recurrence. The objective of this study is to evaluate the effectiveness of endoscopic management of skull base inverted papilloma. Case series with planned data collection. Tertiary medical center. Patients with skull base inverted papilloma. Over 7 years, 49 patients with skull base inverted papilloma were referred for surgical resection. Demographics, operative technique, pathology, complications, recurrence, and postoperative follow-up were evaluated. Average age at presentation was 57 years. Twenty-six patients (53%) had prior attempts at resection elsewhere, and 5 had squamous cell carcinoma (SCCA) arising in an inverted papilloma. Six patients (12%) suffered major complications, including skull base osteomyelitis in 2 previously irradiated patients, cerebrospinal fluid leak with pneumocephalus (n = 1), meningitis (n = 1), invasive fungal sinusitis (n = 1), and cerebrovascular accident (n = 1). The mean disease-free interval was 29 months (range, 10-78 months). One patient with SCCA recurred in the nasopharynx (overall 2% recurrence rate). He is disease-free 3 years following endoscopic nasopharyngectomy. Three patients with SCCA had endoscopic resection of the skull base, while 1 subject with inverted papilloma pedicled on the superior orbital roof had an osteoplastic flap in conjunction with a Draf III procedure. All others received endoscopic resection. Removal of the bony pedicle resulted in excellent local control of skull base inverted papillomas. Our experience demonstrates that disease eradication with limited morbidity is attainable with this approach. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2016.

Early experiences in establishing a regional quantitative imaging network for PET/CT clinical trials.

PubMed

Doot, Robert K; Thompson, Tove; Greer, Benjamin E; Allberg, Keith C; Linden, Hannah M; Mankoff, David A; Kinahan, Paul E

2012-11-01

The Seattle Cancer Care Alliance (SCCA) is a Pacific Northwest regional network that enables patients from community cancer centers to participate in multicenter oncology clinical trials where patients can receive some trial-related procedures at their local center. Results of positron emission tomography (PET) scans performed at community cancer centers are not currently used in SCCA Network trials since clinical trials customarily accept results from only trial-accredited PET imaging centers located at academic and large hospitals. Oncologists would prefer the option of using standard clinical PET scans from Network sites in multicenter clinical trials to increase accrual of patients for whom additional travel requirements for imaging are a barrier to recruitment. In an effort to increase accrual of rural and other underserved populations to Network trials, researchers and clinicians at the University of Washington, SCCA and its Network are assessing the feasibility of using PET scans from all Network sites in their oncology clinical trials. A feasibility study is required because the reproducibility of multicenter PET measurements ranges from approximately 3% to 40% at national academic centers. Early experiences from both national and local PET phantom imaging trials are discussed, and next steps are proposed for including patient PET scans from the emerging regional quantitative imaging network in clinical trials. There are feasible methods to determine and characterize PET quantitation errors and improve data quality by either prospective scanner calibration or retrospective post hoc corrections. These methods should be developed and implemented in multicenter clinical trials employing quantitative PET imaging of patients. Copyright © 2012 Elsevier Inc. All rights reserved.

Group III mGluR regulation of synaptic transmission at the SC-CA1 synapse is developmentally regulated

PubMed Central

Ayala, Jennifer E.; Niswender, Colleen M.; Luo, Qingwei; Banko, Jessica L.; Conn, P. Jeffrey

2008-01-01

Summary Group III metabotropic glutamate receptors (mGluRs) reduce synaptic transmission at the Schaffer collateral-CA1 (SC-CA1) synapse in rats by a presynaptic mechanism. Previous studies show that low concentrations of the group III-selective agonist, L-AP4, reduce synaptic transmission in slices from neonatal but not adult rats, whereas high micromolar concentrations reduce transmission in both age groups. L-AP4 activates mGluRs 4 and 8 at much lower concentrations than those required to activate mGluR7, suggesting that the group III mGluR subtype modulating transmission is a high affinity receptor in neonates and a low affinity receptor in adults. The previous lack of subtype selective ligands has made it difficult to test this hypothesis. We have measured fEPSPs in the presence of novel subtype selective agents to address this question. We show that the effects of L-AP4 can be blocked by LY341495 in both neonates and adults, verifying that these effects are mediated by mGluRs. In addition, the selective mGluR8 agonist, DCPG, has a significant effect in slices from neonatal rats but does not reduce synaptic transmission in adult slices. The mGluR4 selective allosteric potentiator, PHCCC, is unable to potentiate the L-AP4-induced effects at either age. Taken together, our data suggest that group III mGluRs regulate transmission at the SC-CA1 synapse throughout development but there is a developmental regulation of the subtypes involved so that that both mGluR8 serves this role in neonates but not adults whereas mGluR7 is involved in regulating transmission at this synapse in throughout postnatal development. PMID:18255102

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

Treatment, survival, and costs of laryngeal cancer care in the elderly.

PubMed

Gourin, Christine G; Dy, Sydney M; Herbert, Robert J; Blackford, Amanda L; Quon, Harry; Forastiere, Arlene A; Eisele, David W; Frick, Kevin D

2014-08-01

To examine associations between treatment and volume with survival and costs in elderly patients with laryngeal squamous cell cancer (SCCA). Retrospective cross-sectional analysis of Surveillance, Epidemiology, and End Results-Medicare data. We evaluated 2,370 patients diagnosed with laryngeal SCCA from 2004 to 2007 using cross-tabulations, multivariate logistic and generalized linear regression modeling, and survival analysis. Chemoradiation was significantly associated with supraglottic tumors (relative risk ratio: 2.6, 95% confidence interval [CI]: 1.7-4.0), additional cancer-directed treatment (odds ratio [OR]: 1.8, 95% CI: 1.2-2.7), and a reduced likelihood of surgical salvage (OR: 0.3, 95% CI: 0.2-0.6). Surgery with postoperative radiation was associated with significantly improved survival (hazard ratio [HR]: 0.7, 95% CI: 0.6-0.9), after controlling for patient and tumor variables including salvage. High-volume care was not associated with survival for nonoperative treatment but was associated with improved survival (HR: 0.7, 95% CI: 0.5-0.8) among surgical patients. Initial treatment and 5-year overall costs for chemoradiation were higher than for all other treatment categories. High-volume care was associated with significantly lower costs of care for surgical patients but was not associated with differences in costs of care for nonoperative treatment. Chemoradiation in elderly patients with laryngeal cancer was associated with increased costs, additional cancer-directed treatment, and a reduced likelihood of surgical salvage. Surgery with postoperative radiation was associated with improved survival in this cohort, and high-volume hospital surgical care was associated with improved survival and lower costs. These findings have implications for improving the quality of laryngeal cancer treatment at a time of both rapid growth in the elderly population and diminishing healthcare resources. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Clinical applications of squamous cell carcinoma antigen-immunoglobulins M to monitor chronic hepatitis C

PubMed Central

Martini, Andrea; Gallotta, Andrea; Pontisso, Patrizia; Fassina, Giorgio

2015-01-01

Hepatitis C virus (HCV) is the main cause of chronic liver disease and cirrhosis in Western countries. Over time, the majority of cirrhotic patients develop hepatocellular carcinoma (HCC), one of the most common fatal cancers worldwide - fourth for incidence rate. A high public health priority need is the development of biomarkers to screen for liver disease progression and for early diagnosis of HCC development, particularly in the high risk population represented by HCV-positive patients with cirrhosis. Several studies have shown that serological determination of a novel biomarker, squamous cell carcinoma antigen-immunoglobulins M (SCCA-IgM), might be useful to identify patients with progressive liver disease. In the initial part of this review we summarize the main clinical studies that have investigated this new circulating biomarker on HCV-infected patients, providing evidence that in chronic hepatitis C SCCA-IgM may be used to monitor progression of liver disease, and also to assess the virological response to antiviral treatment. In the last part of this review we address other, not less important, clinical applications of this biomarker in hepatology. PMID:26689503

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

Alginate-caseinate composites: Molecular interactions and characterization of cross-linked beads for the delivery of anticandidals.

PubMed

Khlibsuwan, Rapee; Khunkitti, Watcharee; Pongjanyakul, Thaned

2018-04-19

Polysaccharide-protein composites offer potential utility for the delivery of drugs. The objectives of this work were to investigate the molecular interactions between sodium alginate (SA) and sodium caseinate (SC) in dispersions and films and to characterize calcium alginate (CA) beads mixed with SC for the delivery of fluconazole (FZ) and clotrimazole (CZ). The results demonstrated that SA could interact with SC, which caused a viscosity synergism in the dispersions. Hydrogen bonding between the carboxyl or hydroxyl groups of SA and the amide groups of SC led to the formation of soluble complexes that could reinforce the CA beads prepared by calcium cross-linking. The SC-CA beads provided higher drug entrapment efficiency, lower water uptake and erosion, and slower drug release than for the CA beads. The loaded FZ was an amorphous form, but CZ crystals were embedded in the bead matrix due to the low water solubility of this drug. However, SC micellization could enhance the water solubility and efficacy of CZ against Candida albicans. This finding indicates that SA can interact with SC via hydrogen bonding to form complexes and that the anticandidal-loaded SC-CA beads can be used as drug delivery systems and drug reservoirs in tablets for oral candidiasis. Copyright © 2018 Elsevier B.V. All rights reserved.

Nanoporous Glass Integrated in Volumetric Bar-Chart Chip for Point-of-Care Diagnostics of Non-Small Cell Lung Cancer.

PubMed

Li, Ying; Xuan, Jie; Song, Yujun; Qi, Wenjin; He, Bangshun; Wang, Ping; Qin, Lidong

2016-01-26

Point-of-care (POC) testing has the potential to enable rapid, low-cost, and large-scale screening. POC detection of a multiplexed biomarker panel can facilitate the early diagnosis of non-small cell lung cancer (NSCLC) and, thus, may allow for more timely surgical intervention for life-saving treatment. Herein, we report the nanoporous glass (NPG) integrated volumetric bar-chart chip (V-Chip) for POC detection of the three NSCLC biomarkers CEA, CYFRA 21-1, and SCCA, by the naked eye. The 3D nanostructures in the NPG membrane efficiently increase the number of binding sites for antibodies and decrease the diffusion distance between antibody and antigen, enabling the low detection limit and rapid analysis time of the NPG-V-Chip. We utilized the NPG-V-Chip to test the NSCLC biomarker panel and found that the limit of detection can reach 50 pg/mL (10-fold improvement over the original V-Chip), and the total assay time can be decreased from 4 to 0.5 h. We then detected CEA in 21 serum samples from patients with common cancers, and the on-chip results showed good correlation with the clinical results. We further assayed 10 lung cancer samples using the device and confirmed the results obtained using conventional ELISA methods. In summary, the NPG-V-Chip platform has the ability of multiplex, low detection limit, low cost, lack of need for accessory equipment, and rapid analysis time, which may render the V-Chip a useful platform for quantitative POC detection in resource-limited settings and personalized diagnostics.

Nosocomial Transmission of Respiratory Syncytial Virus in an Outpatient Cancer Center

PubMed Central

Chu, Helen Y.; Englund, Janet A.; Podczervinski, Sara; Kuypers, Jane; Campbell, Angela P.; Boeckh, Michael; Pergam, Steven A.; Casper, Crey

2014-01-01

Background Respiratory syncytial virus (RSV) outbreaks in inpatient settings are associated with poor outcomes in cancer patients. The use of molecular epidemiology to document RSV transmission in the outpatient setting has not been well described. Methods We performed a retrospective cohort study of two nosocomial outbreaks of RSV at the Seattle Cancer Care Alliance (SCCA). Subjects included patients seen at the SCCA with RSV detected in two outbreaks in 2007-2008 and 2012, and all employees with respiratory viruses detected in the 2007-2008 outbreak. A subset of samples was sequenced using semi-nested polymerase chain reaction targeting the RSV attachment glycoprotein coding region. Results Fifty-one cases of RSV were identified in 2007-2008. Clustering of identical viral strains was detected in 10 (67%) of 15 patients with RSV sequenced from 2007-2008. As part of a multimodal infection control strategy implemented as a response to the outbreak, symptomatic employees had nasal washes collected. Of 254 employee samples, 91 (34%) tested positive for a respiratory virus, including 14 with RSV. In another RSV outbreak in 2012, 24 cases of RSV were identified; nine (90%) of 10 patients had the same viral strain, and 1 (10%) had another viral strain. Conclusions We document spread of clonal strains within an outpatient cancer care setting. Infection control interventions should be implemented in outpatient, as well as inpatient, settings to reduce person-to-person transmission and limit progression of RSV outbreaks. PMID:24607551

Bladder cancer in patients with spinal cord injury.

PubMed

Hess, Marika J; Zhan, Ellen H; Foo, Dominic K; Yalla, Subbarao V

2003-01-01

The incidence of bladder cancer in spinal cord injury (SCI) is 16 to 28 times higher than that in the general population. The objective of this study was to investigate the characteristics of bladder cancer that are unique to the SCI population. Retrospective review. The charts of 16 patients diagnosed with bladder cancer from 1982 to 2001 were reviewed for type of cancer, exposure to risk factors, presenting symptoms, and survival time. The presenting manifestations were gross hematuria in 14 patients, papillary urethral growth in 1 patient, and acute obstructive renal failure in 1 patient. The diagnosis was made on initial cystoscopic evaluation in 16 patients; 3 patients required further evaluation. Eight of the 11 screening cytologies were suspicious for a malignancy prior to the diagnosis. Seven patients had transitional cell carcinoma, 6 patients had squamous cell carcinoma (SCCA), and 3 patients had both. The bladder wasmanaged with chronic indwelling catheter in 12 patients. Nine patients died of bladder cancer metastases and the remaining 3 patients died of other causes. Six patients survived 5 years or more; 4 were still alive at the completion of this study. Gross hematuria in individuals with SCI warrants aggressive assessment for bladder cancer. Chronic indwelling catheter, smoking, and renal and bladder stones are important risk factors for cancer. The incidence of SCCA in the SCI popullation is much higher than in the general population. Cystoscopic and cytologic evaluation in patients with advanced disease may fail to confirm the diagnosis in a high proportion of patients.

Short-term field stimulation mimics synaptic maturation of hippocampal synapses.

PubMed

Bagley, Elena E; Westbrook, Gary L

2012-04-01

Many aspects of synaptic transmission are modified during development, reflecting not only the consequence of developmental programmes of gene expression, but also the effects of ongoing neural activity. We investigated the role of synaptic activity in the maturation of Schaffer collateral (SC)-CA1 synapses using sustained low frequency field stimulation of acute brain slices. Between postnatal days 4-6 and 14-16, mouse SC-CA1 synapses in naïve slices showed a developmental decrease in the probability of transmitter release (P(r)) and an increase in the contribution of GluN2A (NR2A) subunits to the NMDA receptor-mediated excitatory postsynaptic current (EPSC). Surprisingly, these developmental changes could be mimicked by short term (4 h) in vitro synaptic activity in slices taken from postnatal days (PND) 4-6 mice. However, different activity levels were required to alter release probability compared to the NMDA receptor subunit composition. Spontaneous synaptic activity was sufficient to alter the NMDA receptor subunit composition, but sustained low-frequency field stimulation of the brain slice (0.1 Hz, 4 h) was necessary to reduce release probability, as assessed 1 h following the cessation of stimulation. The protein synthesis inhibitor anisomycin blocked the effect of field stimulation on release probability. These results indicate that features of mature excitatory synapses can be rapidly induced in immature neurons. The activity dependence of the P(r) and NMDA receptor subunit composition serves as a sensitive indicator of prior neural activity, and provides dual mechanisms for homeostatic control of excitatory synaptic efficacy.

Risk factors for oropharynx cancer in a cohort of HIV-infected veterans.

PubMed

Chew, Erin Y; Hartman, Christine M; Richardson, Peter A; Zevallos, Jose P; Sikora, Andrew G; Kramer, Jennifer R; Chiao, Elizabeth Y

2017-05-01

To evaluate HIV-related and other clinical risk factors associated with oropharynx cancer (OPSCC) in HIV-infected U.S. Veterans. Retrospective cohort study utilizing Veterans Affairs HIV Clinical Case Registry (CCR) data from 1985 to 2010. Outcome was incident OPSCC as indicated by 1 inpatient or 2 outpatient ICD-9 codes. Cox proportional hazard models were used to determine hazard ratios (HR) and 95% confidence intervals (CI) for each risk factor on the time to OPSCC diagnosis. A total of 40,996 HIV-infected male veterans were included in the cohort with 97 cases of OPSCC. The age adjusted incidence rate was 23.2/100,000 [95% CI 17.8-29.2]. Age>50 (aHR=3.8, 95% CI 1.9-7.8), recent CD4<200 (aHR=3.8, 95% CI 2.0-7.3), and undetectable HIV viral loads 40-79% of the time (aHR=1.8, 95% CI 1.1-3.0) were associated with an increased risk of OPSCC. Era of HIV diagnosis, utilization of cART, nadir CD4 count, race, smoking history, and previous risk of HPV disease, including condyloma or invasive squamous cell carcinoma of the anus (SCCA) were not associated with increased risk of OPSCC. Patients who were older at beginning of follow up, had lower CD4 counts around the time of OPSCC diagnosis, and moderate HIV viral control during follow-up had an increased risk of OPSCC. Other HPV-related diseases such as SCCA and condyloma did not increase the risk for OPSCC. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Role of mGlu Receptors in Hippocampal Plasticity Deficits in Neurological and Psychiatric Disorders: Implications for Allosteric Modulators as Novel Therapeutic Strategies

PubMed Central

Senter, Rebecca K.; Ghoshal, Ayan; Walker, Adam G.; Xiang, Zixiu; Niswender, Colleen M.; Conn, P. Jeffrey

2016-01-01

Long-term potentiation (LTP) and long-term depression (LTD) are two distinct forms of synaptic plasticity that have been extensively characterized at the Schaffer collateral-CA1 (SC-CA1) synapse and the mossy fiber (MF)-CA3 synapse within the hippocampus, and are postulated to be the molecular underpinning for several cognitive functions. Deficits in LTP and LTD have been implicated in the pathophysiology of several neurological and psychiatric disorders. Therefore, there has been a large effort focused on developing an understanding of the mechanisms underlying these forms of plasticity and novel therapeutic strategies that improve or rescue these plasticity deficits. Among many other targets, the metabotropic glutamate (mGlu) receptors show promise as novel therapeutic candidates for the treatment of these disorders. Among the eight distinct mGlu receptor subtypes (mGlu1-8), the mGlu1,2,3,5,7 subtypes are expressed throughout the hippocampus and have been shown to play important roles in the regulation of synaptic plasticity in this brain area. However, development of therapeutic agents that target these mGlu receptors has been hampered by a lack of subtype-selective compounds. Recently, discovery of allosteric modulators of mGlu receptors has provided novel ligands that are highly selective for individual mGlu receptor subtypes. The mGlu receptors modulate the multiple forms of synaptic plasticity at both SC-CA1 and MF synapses and allosteric modulators of mGlu receptors have emerged as potential therapeutic agents that may rescue plasticity deficits and improve cognitive function in patients suffering from multiple neurological and psychiatric disorders. PMID:27296640

[Quality of life after radical surgery and radiotherapy for advanced or recurrent laryngeal and hypopharyngeal cancers].

PubMed

Dequanter, D; Lothaire, P; Eekhout, D; Dheur, S; Colin, M; Andry, G

2009-01-01

To determine the functional disabilities and overall quality of life of patients operated for advanced (Stages III-IV) or recurrent squamous cell carcinomas (SCCA) after radiation therapy of the (pharyngo)larynx. From 1984 to 1997, 135 patients were consecutively treated for SCCA of the (pharyngo)larynx. There were 118 men and 17 women with a mean age of 60 years. The University of Washington QOL questionnaire (UW-QOL) (Deleyiannis et al) was administered to 19 long term survivors. Self-administered scale consisting of nine domains affected by treatment for head and neck cancer: pain, physical appareance, global activity, entertainement, employment, chewing, swallowing, speech and shoulder function. For each patient, a total score and weighted score were determined. Descriptive statistics were used. 9/19 patients reported that compared with one year prior to the diagnosis of cancer their general health was the same. Pain resolved in 78%; the physical appearance was juged not modified in 52% of the cases. Chewing and swallowing functions were respected in 94% of the cases. These functions were considered as very important in 53% and 68% respectively. Five patients are still at work; 11 patients retired. Work was considered as very important for 9/19 patients. Speech rehabilitation permitted a modified but well understandable communication in 63% of the cases. This function was considered by 88% of the patients as very important. Finally, 73% of the patients (14/19) reported having a good to excellent overall QOL. Though disabling, pharyngolaryngectomies do not necessarily translate into worse overall QOL; ultimate disabilities are widely variable. Many factors such family, friends, personal leisure, activities, employement, cultural habits were important and depending on each patient in enjoyement of life's estimation.

Multifunctional reduced graphene oxide trigged chemiluminescence resonance energy transfer: Novel signal amplification strategy for photoelectrochemical immunoassay of squamous cell carcinoma antigen.

PubMed

Zhang, Yan; Sun, Guoqiang; Yang, Hongmei; Yu, Jinghua; Yan, Mei; Song, Xianrang

2016-05-15

Herein, a photoelectrochemical (PEC) immunoassay is constructed for squamous cell carcinoma antigen (SCCA) detection using zinc oxide nanoflower-bismuth sulfide (Bi2S3) composites as photoactive materials and reduced graphene oxide (rGO) as signal labels. Horseradish peroxidase is used to block sites against nonspecific binding, and then participated in luminol-based chemiluminescence (CL) system. The induced CL emission is acted as an inner light source to excite photoactive materials, simplifying the instrument. A novel signal amplification strategy is stem from rGO because of the rGO acts as an energy acceptor, while luminol serves as a donor to rGO, triggering the CL resonance energy transfer phenomenon between luminol and rGO. Thus, the efficient CL emission to photoactive materials decreases. Furthermore, the signal amplification caused by rGO labeled signal antibodies is related to photogenerated electron-hole pairs: perfect matching of energy levels between rGO and Bi2S3 makes rGO a sink to capture photogenerated electrons from Bi2S3; the increased steric hindrance hinders the electron donor to the surface of Bi2S3 for reaction with the photogenerated holes. On the basis of the novel signal amplification strategy, the proposed immunosensor exhibits excellent analytical performance for PEC detection of SCCA, ranging from 0.8 pg mL(-1) to 80 ng mL(-1) with a low detection limit of 0.21 pg mL(-1). Meanwhile, the designed signal amplification strategy provides a general format for future development of PEC assays. Copyright © 2015 Elsevier B.V. All rights reserved.

Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks

NASA Astrophysics Data System (ADS)

Halicek, Martin; Little, James V.; Wang, Xu; Patel, Mihir; Griffith, Christopher C.; El-Deiry, Mark W.; Chen, Amy Y.; Fei, Baowei

2018-02-01

Successful outcomes of surgical cancer resection necessitate negative, cancer-free surgical margins. Currently, tissue samples are sent to pathology for diagnostic confirmation. Hyperspectral imaging (HSI) is an emerging, non-contact optical imaging technique. A reliable optical method could serve to diagnose and biopsy specimens in real-time. Using convolutional neural networks (CNNs) as a tissue classifier, we developed a method to use HSI to perform an optical biopsy of ex-vivo surgical specimens, collected from 21 patients undergoing surgical cancer resection. Training and testing on samples from different patients, the CNN can distinguish squamous cell carcinoma (SCCa) from normal aerodigestive tract tissues with an area under the curve (AUC) of 0.82, 81% accuracy, 81% sensitivity, and 80% specificity. Additionally, normal oral tissues can be sub-classified into epithelium, muscle, and glandular mucosa using a decision tree method, with an average AUC of 0.94, 90% accuracy, 93% sensitivity, and 89% specificity. After separately training on thyroid tissue, the CNN differentiates between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multi-nodular goiter (MNG) with an AUC of 0.93, 87% accuracy, 88% sensitivity, and 85% specificity. Classical-type papillary thyroid carcinoma is differentiated from benign MNG with an AUC of 0.91, 86% accuracy, 86% sensitivity, and 86% specificity. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multi-category diagnostic information for normal head-and-neck tissue, SCCa, and thyroid carcinomas. More patient data are needed in order to fully investigate the proposed technique to establish reliability and generalizability of the work.

GPR30 activation improves memory and facilitates DHPG-induced LTD in the hippocampal CA3 of middle-aged mice.

PubMed

Xu, Wen; Cao, Jian; Zhou, Yan; Wang, Lina; Zhu, Guoqi

2018-03-01

Reduced estrogen levels and decreased expression of related receptors are typical cerebral features of aging. The G protein-coupled estrogen receptor 1 (GPER1, also known as GPR30) is considered a novel therapeutic target for neurodegenerative diseases. In this study, we demonstrated that hippocampal GPR30 expression was reduced in middle-aged mice compared with young adult mice. GPR30 agonist G1 improved both fear and spatial memory in both male and female middle-aged mice, but not in young adult mice, which were blocked by the GPR30 antagonist G15. Interestingly, a group I metabotropic glutamate receptor (mGluR) agonist, 3,5-dihydroxyphenylglycine (DHPG)-induced long-term depression (LTD) in mossy fiber-cornu ammonis 3 (MF-CA3) synapses but not Schaffer collateral-CA1 (SC-CA1) synapses was facilitated in brain slices from G1-treated middle-aged mice. Long-term potentiation (LTP) in SC-CA1 synapses was not affected in slices from G1-treated mice. The effects of GPR30 activation on memory and DHPG-LTD in MF-CA3 synapses were further confirmed by viral expression of GPR30 in the CA3. The regulation of hippocampal synaptic plasticity by G1 treatment might be related to brain-derived neurotrophic factor (BDNF)-tropomyosin receptor kinase B (TrkB) signaling, as G15 also blocked G1-induced activation of the BDNF-TrkB pathway. Moreover, we found that DHPG triggered GluA internalization in slices from G1-treated mice but not control mice. Pharmacological experiments showed that G1-mediated facilitation of DHPG-induced LTD in MF-CA3 synapses was dependent on protein kinase B (Akt), mammalian target of rapamycin (mTor), and TrkB signaling. In conclusion, our results indicate that GPR30 activation improves memory in middle-aged mice, likely through facilitating synaptic plasticity in the CA3. This study provides novel evidence that GPR30 activation can improve memory in middle-aged animals. Copyright © 2018 Elsevier Inc. All rights reserved.

Extracting sets of chemical substructures and protein domains governing drug-target interactions.

PubMed

Yamanishi, Yoshihiro; Pauwels, Edouard; Saigo, Hiroto; Stoven, Véronique

2011-05-23

The identification of rules governing molecular recognition between drug chemical substructures and protein functional sites is a challenging issue at many stages of the drug development process. In this paper we develop a novel method to extract sets of drug chemical substructures and protein domains that govern drug-target interactions on a genome-wide scale. This is made possible using sparse canonical correspondence analysis (SCCA) for analyzing drug substructure profiles and protein domain profiles simultaneously. The method does not depend on the availability of protein 3D structures. From a data set of known drug-target interactions including enzymes, ion channels, G protein-coupled receptors, and nuclear receptors, we extract a set of chemical substructures shared by drugs able to bind to a set of protein domains. These two sets of extracted chemical substructures and protein domains form components that can be further exploited in a drug discovery process. This approach successfully clusters protein domains that may be evolutionary unrelated but that bind a common set of chemical substructures. As shown in several examples, it can also be very helpful for predicting new protein-ligand interactions and addressing the problem of ligand specificity. The proposed method constitutes a contribution to the recent field of chemogenomics that aims to connect the chemical space with the biological space.

Vulvar lichen sclerosus and squamous cell carcinoma: a cohort, case control, and investigational study with historical perspective; implications for chronic inflammation and sclerosis in the development of neoplasia.

PubMed

Carlson, J A; Ambros, R; Malfetano, J; Ross, J; Grabowski, R; Lamb, P; Figge, H; Mihm, M C

1998-09-01

The histological changes of lichen sclerosus (LS) are frequently found in association with vulvar squamous cell carcinoma (SCC). The importance of chronic inflammation and scarring in oncogenesis is well recognized. Thirty-two patients with symptomatic vulvar LS and 60 with vulvar SCC were studied. Paraffin sections of vulvar LS, and three controls groups (acute scars, normal vulva, and vulvar lichen simplex chronicus [LSC]) were investigated with a panel of seven tissue markers and for DNA content in areas without vulvar intraepithelial neoplasia (VIN). All published cases to date of vulvar LS associated with SCC were reviewed. Of the cohort of symptomatic vulvar LS patients (mean/median age, 60 years), 9% developed VIN lesions and 21% invasive SCC; symptomatic LS preceded the carcinoma by a mean of 4 years (range, 1 to 23 years). Second and third primary tumors developed in three of these patients. Of the series of 60 patients presenting with vulvar SCCa, the clinical setting and histological features of SCCs associated with LS were significantly distinctive compared with SCCas without LS: SCCs associated with LS occurred in an older age-group (74 v 65 years; P = .01), were located on the clitoris (41% v 5%; P = .003), were of conventional SCCa type (85% v 57%; P = .02), were associated with a prominent fibromyxoid stromal response (46% v 10%; P = .004), were not associated with VIN 3 (SCC in situ) (5% v 67%; P = .02) and diffusely expressed tumor suppressor gene product p53 (43% v 19%; P = .01) and cytokine TGF-beta (33% v 9%; P = .05). The epidermis of vulvar LS was similar to that of acute scars and differed significantly compared with normal vulva with respect to keratinocytic expression of markers to keratin AE 1, involucrin and filaggrin, epidermal thickness (0.13 mm [LS] v 0.05 mm [normal]; P < .03), and proliferative index by PCNA and Mib-1 labeling (53/60 [LS] v 15/19 [normal] per 200 basal cells [bc]; P < .003). Vulvar LS showed significantly higher expression of p53 than all three control groups (80 [LS] v 3 [normal]/44 [acute scar]/28 [LSC] per 200 bc; P < .008), and aneuploidy (33% v diploid controls) in the absence of VIN. Comparing LS with and without associated SCCa found significant increases in age of patients (74 v 66 years; P = .001), and DNA aneuploidy (52% v 11%; P = .0001) and no differences in epidermal thickness, sclerotic thickness, proliferative index, or p53 expression. However, those cases of LS with an aneuploid DNA content showed significantly elevated p53 expression (88 v 60/200 bc; P = .01) and epidermal thickness (0.16 v 0.11 mm; P = .005) compared with LS with a diploid DNA content. Review of published cases supports an association between LS and vulvar SCC. The phenomenon of chronic inflammation and scarring giving rise to carcinoma has been well documented. Vulvar lichen sclerosus (LS) is an inflammatory dermatosis characterized by clinicopathologic persistence and hypocellular fibrosis (sclerosis). A subset of vulvar SCCs is significantly associated with the presence of LS and diffusely express the p53 gene product. Keratinocytes affected by LS show a proliferative phenotype and can exhibit markers of neoplastic progression such as increased p53 expression and DNA aneuploidy. As a chronic scarring inflammatory dermatosis, vulvar LS could act as both "initiator and promoter" of carcinogenesis, explaining the frequent coexistence of these diseases. Because keratinocytes of LS significantly express tumor suppressor gene p53 protein, the p53 gene may be involved early in this proposed pathway of carcinogenesis.

The effect of neck dissection on quality of life after chemoradiation

PubMed Central

Lassig, Amy Anne Donatelli; Duffy, Sonia A.; Fowler, Karen E.; Ronis, David L.; Chepeha, Douglas B.; Terrell, Jeffrey E.

2010-01-01

Objective To determine differences in QOL between head and neck cancer patients receiving chemoradiation versus chemoradiation and neck dissection. Methods A prospective cohort study was conducted at 2 tertiary otolaryngology clinics and a VA. Sample: 103 oropharyngeal Stage IV SCCA patients treated via chemoradiation +/− neck dissection. Intervention: self-administered health survey collecting health, demographic, and QOL information pretreatment and 1 year later. Main outcome measures: QOL via SF-36 and HNQoL. Descriptive statistics were calculated for health / clinical characteristics, demographics, and QOL scores. T-tests evaluated changes in QOL over time. Results 65 patients received chemoradiation and 38 chemoradiation + neck dissection. Only the pain index of the SF-36 showed a significant difference between groups (p<.05) with the neck dissection group reporting greater pain. Conclusions After post-treatment neck dissection, patients experience statistically significant decrement in bodily pain domain scores, but other QOL scores are similar to those of patients undergoing chemoradiation alone. PMID:18922336

Risk Factors of Recurrence and Malignant Transformation of Sinonasal Inverted Papilloma

PubMed Central

Ścierski, Wojciech; Misiołek, Maciej

2017-01-01

Sinonasal inverted papilloma is a relatively rare disease; however, it is prevalent enough for every ENT practitioner to encounter it several times throughout medical routines. Despite the developments in experimental and clinical medicine as well as surgical techniques, our knowledge of this disease is still inadequate. With improved imaging and better diagnostic techniques, proper diagnosis and qualification for surgical approaches leave no doubt. Although the endoscopic approach seems to be the gold standard for such condition, some cases may additionally require an external approach. Regardless of the type of surgery, postoperative management is crucial for both healing and long-term follow-up. Unfortunately, the procedures are still lacking in explicit and standardized postoperative management guidelines. Moreover, an important issue is still the need for a biomarker indicative of inverted papilloma and its malignant transformation. Several particles, within the spotlight of the researchers, have been SCCA, Ki-67, Bcl-2, Wnt proteins, and many more. Nevertheless, the topic requires further investigations. PMID:29250552

Squamous Cell Carcinoma Antigen-encoding Genes SERPINB3/B4 as Potentially Useful Markers for the Stratification of HNSCC Tumours.

PubMed

Saidak, Zuzana; Morisse, Mony Chenda; Chatelain, Denis; Sauzay, Chloé; Houessinon, Aline; Guilain, Nelly; Soyez, Marion; Chauffert, Bruno; Dakpé, Stéphanie; Galmiche, Antoine

2018-03-01

The squamous cell carcinoma antigen (SCCA), encoded by the genes SERPINB3/B4, is a tumour marker produced by head and neck squamous cell carcinoma (HNSCC). We aimed to examine SERPINB3/B4 mRNA levels and its clinical significance in the therapeutic context. We retrieved mRNA expression levels, clinical, pathological and genomic data for 520 HNSCC from The Cancer Genome Atlas (TCGA). HNSCC tumours express high levels of SERPINB3/B4 mRNA. SERPINB3 expression differs depending on Human papillomavirus (HPV) infection status, primary tumour location, grade and differentiation, extension to lymph nodes and extracapsular spread. Interestingly, we observed an association between SERPINB3/B4 and the presence of tumour immune infiltrate as well as the expression of the immune checkpoint regulators PD-L1/PD-L2 that depended on HPV status. Our findings point to potential interest of SERPINB3/B4 for the stratification of HNSCC patients in the therapeutic context. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Mind bomb-1 is an essential modulator of long-term memory and synaptic plasticity via the Notch signaling pathway

PubMed Central

2012-01-01

Background Notch signaling is well recognized as a key regulator of the neuronal fate during embryonic development, but its function in the adult brain is still largely unknown. Mind bomb-1 (Mib1) is an essential positive regulator in the Notch pathway, acting non-autonomously in the signal-sending cells. Therefore, genetic ablation of Mib1 in mature neuron would give valuable insight to understand the cell-to-cell interaction between neurons via Notch signaling for their proper function. Results Here we show that the inactivation of Mib1 in mature neurons in forebrain results in impaired hippocampal dependent spatial memory and contextual fear memory. Consistently, hippocampal slices from Mib1-deficient mice show impaired late-phase, but not early-phase, long-term potentiation and long-term depression without change in basal synaptic transmission at SC-CA1 synapses. Conclusions These data suggest that Mib1-mediated Notch signaling is essential for long-lasting synaptic plasticity and memory formation in the rodent hippocampus. PMID:23111145

Can axial-based nodal size criteria be used in other imaging planes to accurately determine "enlarged" head and neck lymph nodes?

PubMed

Bartlett, Eric S; Walters, Thomas D; Yu, Eugene

2013-01-01

Objective. We evaluate if axial-based lymph node size criteria can be applied to coronal and sagittal planes. Methods. Fifty pretreatment computed tomographic (CT) neck exams were evaluated in patients with head and neck squamous cell carcinoma (SCCa) and neck lymphadenopathy. Axial-based size criteria were applied to all 3 imaging planes, measured, and classified as "enlarged" if equal to or exceeding size criteria. Results. 222 lymph nodes were "enlarged" in one imaging plane; however, 53.2% (118/222) of these were "enlarged" in all 3 planes. Classification concordance between axial versus coronal/sagittal planes was poor (kappa = -0.09 and -0.07, resp., P < 0.05). The McNemar test showed systematic misclassification when comparing axial versus coronal (P < 0.001) and axial versus sagittal (P < 0.001) planes. Conclusion. Classification of "enlarged" lymph nodes differs between axial versus coronal/sagittal imaging planes when axial-based nodal size criteria are applied independently to all three imaging planes, and exclusively used without other morphologic nodal data.

Can Axial-Based Nodal Size Criteria Be Used in Other Imaging Planes to Accurately Determine “Enlarged” Head and Neck Lymph Nodes?

PubMed Central

Bartlett, Eric S.; Walters, Thomas D.; Yu, Eugene

2013-01-01

Objective. We evaluate if axial-based lymph node size criteria can be applied to coronal and sagittal planes. Methods. Fifty pretreatment computed tomographic (CT) neck exams were evaluated in patients with head and neck squamous cell carcinoma (SCCa) and neck lymphadenopathy. Axial-based size criteria were applied to all 3 imaging planes, measured, and classified as “enlarged” if equal to or exceeding size criteria. Results. 222 lymph nodes were “enlarged” in one imaging plane; however, 53.2% (118/222) of these were “enlarged” in all 3 planes. Classification concordance between axial versus coronal/sagittal planes was poor (kappa = −0.09 and −0.07, resp., P < 0.05). The McNemar test showed systematic misclassification when comparing axial versus coronal (P < 0.001) and axial versus sagittal (P < 0.001) planes. Conclusion. Classification of “enlarged” lymph nodes differs between axial versus coronal/sagittal imaging planes when axial-based nodal size criteria are applied independently to all three imaging planes, and exclusively used without other morphologic nodal data. PMID:23984099

Papilloma Virus Infected Northeastern Thai Women

PubMed

Phuthong, Sophida; Settheetham-Ishida, Wannapa; Natphopsuk, Sitakan; Ishida, Takafumi

2018-02-26

Objective: We aimed to investigate any association between a genetic polymorphism of the detoxification GSTP1 gene and risk of cervical cancer in northeastern Thailand. Materials and Methods: Genotyping of GSTP1 was performed for 198 squamous cell cervical cancer (SCCA) patients and 198 age-matched healthy controls with the PCR-RFLP method. Results: The respective frequencies of the G allele were 0.33 and 0.26 in the controls and cases, the difference being significant (OR = 0.69 [95% CI: 0.50-0.95, p=0.0192]). Among women infected with high-risk types of HPV, being a heterozygous carrier was associated with a reduced risk of cervical cancer (adjusted OR = 0.32 [95% CI: 0.12-0.91, p=0.031]). Similarly, a decreased risk was observed in heterozygous women with a non-smoking partner (adjusted OR = 0.27 [95% CI: 0.09-0.83, p=0.023]). Conclusions: GSTP1 polymorphism could influence susceptibility to cervical cancer among northeast Thai women; either as a independent factor or in combination with high-risk HPV infection. Dual-testing of HPV and the GSTP1 might prove an effective screening tool for cervical cancer. Creative Commons Attribution License

Dithiocarbamates with potent inhibitory activity against the Saccharomyces cerevisiae β-carbonic anhydrase.

PubMed

Bozdag, Murat; Carta, Fabrizio; Vullo, Daniela; Isik, Semra; AlOthman, Zeid; Osman, Sameh M; Scozzafava, Andrea; Supuran, Claudiu T

2016-01-01

Dithiocarbamates (DTCs) prepared from primary or secondary amines, which incorporated amino/hydroxyl-alkyl, mono-/bicyclic aliphatic/heterocyclic rings based on the quinuclidine, piperidine, hydroxy-/carboxy-/amino-substituted piperidine, morpholine and piperazine scaffolds, were investigated for the inhibition of α- and β-carbonic anhydrases (CAs, EC 4.2.1.1) of pharmacologic relevance, such as the human (h) isoform hCA I and II, as well as the Saccharomyces cerevisiae β-CA, scCA. The yeast and its β-CA were shown earlier to be useful models of pathogenic fungal infections. The DTCs investigated here were medium potency hCA I inhibitors (K(I)s of 66.5-910 nM), were more effective as hCA II inhibitors (K(I)s of 8.9-107 nM) and some of them showed excellent, low nanomolar activity against the yeast enzyme, with inhibition constants ranging between 6.4 and 259 nM. The detailed structure activity relationship for inhibition of the yeast and human enzymes is discussed. Several of the investigated DTCs showed excellent selectivity ratios for inhibiting the yeast over the human cytosolic CA isoforms.

Evaluation of Cadmium Ratio and Foil Activation Measurements for a Beryllium-Reflected Assembly of U(93.15)O 2 Fuel Rods (1.506-cm Triangular Pitch)

DOE PAGES

Marshall, Margaret A.

2014-11-04

A series of small, compact critical assembly (SCCA) experiments were completed from 1962 to 1965 at Oak Ridge National Laboratory’s Critical Experiments Facility (ORCEF) in support of the Medium-Power Reactor Experiments (MPRE) program. Initial experiments, performed in November and December of 1962, consisted of a core of un-moderated stainless-steel tubes, each containing 26 UOIdaho National Laboratory (INL), Idaho Falls, ID (United States) fuel pellets, surrounded by a graphite reflector. Measurements were performed to determine critical reflector arrangements, fission-rate distributions, and cadmium ratio distributions. The graphite reflectors were then changed to beryllium reflectors. For the beryllium reflected assemblies, the fuel wasmore » in 1.506-cm-triangular and 7-tube clusters leading to two critical configurations. Once the critical configurations had been achieved, various measurements of reactivity, relative axial and radial activation rates of 235U, and cadmium ratios were performed. The cadmium ratio, reactivity, and activation rate measurements, performed on the 1.506-cm-array critical configuration, have been evaluated and are described in this paper.« less

Presynaptic muscarinic control of glutamatergic synaptic transmission.

PubMed

Buño, W; Cabezas, C; Fernández de Sevilla, D

2006-01-01

The hippocampus receives cholinergic projections from the medial septal nucleus and Broca's diagonal band that terminate in the CA1, CA3, and dentate gyrus regions (Frotscher and Leranth, 1985). Glutamatergic synapses between CA3 and CA1 pyramidal neurons are presynaptically inhibited by acetylcholine (ACh), via activation of muscarinic ACh receptors (mAChRs) at the terminals of Schaffer collaterals (SCs) (Hounsgaard, 1978; Fernández de Sevilla et al., 2002, 2003). There are two types of SC-CA1 pyramidal neuron synapses. One type, called functional synapse, shows postsynaptic alpha- amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA)-receptor mediated currents at resting potential (Vm) and both AMPA and N-methyl-D-aspartate receptor (NMDAR)-mediated currents when depolarized. The other type, termed silent synapse, only displays postsynaptic NMDAR-mediated currents at depolarized Vms, but does not respond at the resting Vm (Isaac et al., 1995). Using hippocampal slices obtained from young Wistar rats, we examined the effects of activation of cholinergic afferents at the stratum oriens/alveus on excitatory postsynaptic currents (EPSCs) evoked in CA1 pyramidal neurons by stimulation of SCs. We also tested the action of the nonhydrolyzable cholinergic agonist carbamylcholine chloride (CCh) on EPSCs evoked by minimal stimulation of SCs (which activates a single or very few synapses) in functional and silent synapses.

Premalignant Lesions of the Anal Canal and Squamous Cell Carcinoma of the Anal Canal

PubMed Central

Poggio, Juan Lucas

2011-01-01

Squamous cell carcinoma of the anus (SCCA) is a rare tumor. However, its incidence has been increasing in men and women over the past 25 years worldwide. Risk factors associated with this cancer are those behaviors that predispose individuals to human papillomavirus (HPV) infection and immunosuppression. Anal cancer is generally preceded by high-grade anal intraepithelial neoplasia (HGAIN), which is most prevalent in human immunodeficiency virus-positive men who have sex with men. High-risk patients may benefit from screening. The most common presentation is rectal bleeding, which is present in nearly 50% of patients. Twenty percent of patients have no symptoms at the time of presentation. Clinical staging of anal cancer requires a digital rectal exam and a positron emission tomography/computed tomography scan of the chest, abdomen, and pelvis. Endorectal/endoanal ultrasound appears to add more-specific staging information when compared with digital rectal examination alone. Treatment of anal cancer prior to the 1970s involved an abdominoperineal resection. However, the current standard of care for localized anal cancer is concurrent chemoradiation therapy, primarily because of its sphincter-saving and colostomy-sparing potential. Studies have addressed alternative chemoradiation regimens to improve the standard protocol of fluorouracil, misogynic, and radiation, but no alternative regimen has proven superior. Surgery is reserved for those patients with residual disease or recurrence. PMID:22942800

Acceptability of an Electronic Self Report Assessment Program for Patients with Cancer

PubMed Central

Wolpin, S.; Berry, D.; Austin-Seymour, M.; Bush, N.; Fann, J.R.; Halpenny, B.; Lober, W.; McCorkle, Ruth

2010-01-01

Background Eliciting symptom and quality of life information from patients is an important component of medical and nursing care processes. Traditionally, this information has been collected with paper and pencil. However, this approach presents several barriers, including delays in receiving information, difficulty integrating responses with electronic records and the time required to manual score questionnaires for measurement purposes. One solution that addresses many of these barriers is the adoption of computerized screening for symptom and quality of life information. Objective This research explored the acceptability of asking symptom and quality of life questions using the Electronic Self Report Assessment – Cancer program on wireless laptops equipped with touch screen format. Methods Acceptability data was explored with respect to whether any differences may be attributed to demographics, and symptom and quality of life levels such as depression, cognitive and emotional functioning. This evaluation utilized descriptive and univariate statistics to examine data from 342 participants from the ongoing ESRA-C randomized clinical trial. Research participants for the ESRA-C study were recruited from the Seattle Cancer Care Alliance (SCCA), a consortium between the University of Washington Medical Center, Fred Hutchinson Cancer Research Center, and Children’s Hospital and Regional Medical Center in Seattle, Washington. Results The sample consisted of 342 adult participants who completed both baseline and follow-up survey sessions. Medical Oncology represented the largest recruitment group (45.3%), followed by Stem Cell Transplant (34.5%) and Radiation Oncology (20.2%). The primary finding was that patients were generally able to utilize ESRA-C quickly and without difficulty in a real-world clinical setting and that they were overall quite satisfied with the ESRA-C program. Significant differences were found in several acceptability areas with respect to demographics and quality of life measures, such as age, gender, and severe distress. Conclusions This analysis confirms that the ESRA-C application for collecting symptom and quality of life information is easy for patients to use and acceptable across a range of user characteristics. We intend to build on our work by using the survey platform in other modalities while ensuring that the patient’s preferences are considered at all times. PMID:19047882

A unique cell-surface protein phenotype distinguishes human small-cell from non-small-cell lung cancer

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

Baylin, S.B.; Gazdar, A.F.; Minna, J.D.

1982-08-01

Radioiodination (/sup 125/I) and two-dimensional polyacrylamide gel electrophoresis was used to determine that small-(oat) cell lung carcinoma (SCC)-a tumor with neuroedocrine features-possesses a surface protein pattern distinct from the other types of lung cancer cells (squamous, adeno-, and large-cell undifferentiated carcinoma). Twelve distinguishing proteins, 40 to 70 kilodaltons (kDal), characterized four separate lines of SCC; three of these, designated E (60 kDal; pI = 7.3), S (30 kDal; pI = 6.0), and U 57 kDal; pI = 5.6), may be unique SCC gene products and were identified only in (/sup 35/S)methionine labeling of SCC and not in non-SCC or humanmore » fibroblasts. Two lines of adeno-, one of squamous, and one of undifferentiated large-cell lung carcinoma exhibited similar surface protein patterns to one another. Nine distinguishing proteins (40 to 100 kDal) and at least five large proteins (>100 kDal) were unique to these lines. The surface protein phenotypes for SCC and non-SCC were distinct from those for human lymphoblastoid cells and fibroblasts. However, the neuroendocrine features of SCC were further substantiated because 6 of the 12 distinguishing SCC surface proteins, including E and U, were identified on human neuroblastoma cells. The proteins identified should (i) help define differentiation steps for normal and neoplastic bronchial epithelial cells, (ii) prove useful in better classifying lung cancers, and (iii) be instrumental in tracing formation of neuroendocrine cells.« less

Down-Regulation of Neuregulin1/ErbB4 Signaling in the Hippocampus Is Critical for Learning and Memory.

PubMed

Tian, Jia; Geng, Fei; Gao, Feng; Chen, Yi-Hua; Liu, Ji-Hong; Wu, Jian-Lin; Lan, Yu-Jie; Zeng, Yuan-Ning; Li, Xiao-Wen; Yang, Jian-Ming; Gao, Tian-Ming

2017-08-01

Hippocampal function is important for learning and memory, and dysfunction of the hippocampus has been linked to the pathophysiology of neuropsychiatric diseases such as schizophrenia. Neuregulin1 (NRG1) and ErbB4, two susceptibility genes for schizophrenia, reportedly modulate long-term potentiation (LTP) at hippocampal Schaffer collateral (SC)-CA1 synapses. However, little is known regarding the contribution of hippocampal NRG1/ErbB4 signaling to learning and memory function. Here, quantitative real-time PCR and Western blotting were used to assess the mRNA and protein levels of NRG1 and ErbB4. Pharmacological and genetic approaches were used to manipulate NRG1/ErbB4 signaling, following which learning and memory behaviors were evaluated using the Morris water maze, Y-maze test, and the novel object recognition test. Spatial learning was found to reduce hippocampal NRG1 and ErbB4 expression. The blockade of NRG1/ErbB4 signaling in hippocampal CA1, either by neutralizing endogenous NRG1 or inhibiting/ablating ErbB4 receptor activity, enhanced hippocampus-dependent spatial learning, spatial working memory, and novel object recognition memory. Accordingly, administration of exogenous NRG1 impaired those functions. More importantly, the specific ablation of ErbB4 in parvalbumin interneurons also improved learning and memory performance. The manipulation of NRG1/ErbB4 signaling in the present study revealed that NRG1/ErbB4 activity in the hippocampus is critical for learning and memory. These findings might provide novel insights on the pathophysiological mechanisms of schizophrenia and a new target for the treatment of Alzheimer's disease, which is characterized by a progressive decline in cognitive function.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

Functional Multiple-Set Canonical Correlation Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

2012-01-01

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

A hybrid correlation analysis with application to imaging genetics

NASA Astrophysics Data System (ADS)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding the correlation between brain imaging and genomic data.

Multifractal detrended Cross Correlation Analysis of Foreign Exchange and SENSEX fluctuation in Indian perspective

NASA Astrophysics Data System (ADS)

Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita

2016-12-01

The manuscript studies autocorrelation and cross correlation of SENSEX fluctuations and Forex Exchange Rate in respect to Indian scenario. Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended cross correlation analysis (MFDXA) were employed to study the correlation between the two series. It was observed that the two series are strongly cross correlated. The change of degree of cross correlation with time was studied and the results are interpreted qualitatively.

Regularized Generalized Canonical Correlation Analysis

ERIC Educational Resources Information Center

Tenenhaus, Arthur; Tenenhaus, Michel

2011-01-01

Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to three or more sets of variables. It constitutes a general framework for many multi-block data analysis methods. It combines the power of multi-block data analysis methods (maximization of well identified criteria) and…

Fuzzy correlation analysis with realization

NASA Astrophysics Data System (ADS)

Tang, Yue Y.; Fan, Xinrui; Zheng, Ying N.

1998-10-01

The fundamental concept of fuzzy correlation is briefly discussed. Based on the correlation coefficient of classic correlation, polarity correlation and fuzzy correlation, the relationship between the correlations are analyzed. A fuzzy correlation analysis has the merits of both rapidity and accuracy as some amplitude information of random signals has been utilized. It has broad prospects for application. The form of fuzzy correlative analyzer with NLX 112 fuzzy data correlator and single-chip microcomputer is introduced.

Sensitivity analysis of a sound absorption model with correlated inputs

NASA Astrophysics Data System (ADS)

Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.

2017-04-01

Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.

Allowing for Correlations between Correlations in Random-Effects Meta-Analysis of Correlation Matrices

ERIC Educational Resources Information Center

Prevost, A. Toby; Mason, Dan; Griffin, Simon; Kinmonth, Ann-Louise; Sutton, Stephen; Spiegelhalter, David

2007-01-01

Practical meta-analysis of correlation matrices generally ignores covariances (and hence correlations) between correlation estimates. The authors consider various methods for allowing for covariances, including generalized least squares, maximum marginal likelihood, and Bayesian approaches, illustrated using a 6-dimensional response in a series of…

Combining Correlation Matrices: Simulation Analysis of Improved Fixed-Effects Methods

ERIC Educational Resources Information Center

Hafdahl, Adam R.

2007-01-01

The originally proposed multivariate meta-analysis approach for correlation matrices--analyze Pearson correlations, with each study's observed correlations replacing their population counterparts in its conditional-covariance matrix--performs poorly. Two refinements are considered: Analyze Fisher Z-transformed correlations, and substitute better…

SERPINB3 in the chicken model of ovarian cancer: a prognostic factor for platinum resistance and survival in patients with epithelial ovarian cancer.

PubMed

Lim, Whasun; Kim, Hee Seung; Jeong, Wooyoung; Ahn, Suzie E; Kim, Jinyoung; Kim, Yong Beom; Kim, Min A; Kim, Mi-Kyung; Chung, Hyun Hoon; Song, Yong Sang; Bazer, Fuller W; Han, Jae Yong; Song, Gwonhwa

2012-01-01

Serine protease inhibitors (SERPINs) appear to be ubiquitously expressed in a variety of species and play important roles in pivotal physiological processes such as angiogenesis, immune responses, blood coagulation and fibronolysis. Of these, squamous cell carcinoma antigen 1 (SCCA1), also known as a SERPINB3, was first identified in squamous cell carcinoma tissue from the cervix of women. However, there is little known about the SERPINB3 expression in human epithelial ovarian cancer (EOC). Therefore, in the present study, we investigated the functional role of SERPINB3 gene in human EOC using chickens, the most relevant animal model. In 136 chickens, EOC was found in 10 (7.4%). SERPINB3 mRNA was induced in cancerous, but not normal ovaries of chickens (P<0.01), and it was abundant only in the glandular epithelium of cancerous ovaries of chickens. Further, several microRNAs, specifically miR-101, miR-1668 and miR-1681 were discovered to influence SERPINB3 expression via its 3'-UTR which suggests that post-transcriptional regulation influences SERPINB3 expression in chickens. SERPINB3 protein was localized predominantly to the glandular epithelium in cancerous ovaries of chickens, and it was abundant in the nucleus of both chicken and human ovarian cancer cell lines. In 109 human patients with EOC, 15 (13.8%), 66 (60.6%) and 28 (25.7%) patients showed weak, moderate and strong expression of SERPINB3 protein, respectively. Strong expression of SERPINB3 protein was a prognostic factor for platinum resistance (adjusted OR; odds ratio, 5.94; 95% Confidence Limits, 1.21-29.15), and for poor progression-free survival (PFS; adjusted HR; hazard ratio, 2.07; 95% CI; confidence interval, 1.03-4.41). Therefore, SERPINB3 may play an important role in ovarian carcinogenesis and be a novel biomarker for predicting platinum resistance and a poor prognosis for survival in patients with EOC.

SERPINB3 in the Chicken Model of Ovarian Cancer: A Prognostic Factor for Platinum Resistance and Survival in Patients with Epithelial Ovarian Cancer

PubMed Central

Jeong, Wooyoung; Ahn, Suzie E.; Kim, Jinyoung; Kim, Yong Beom; Kim, Min A.; Kim, Mi-Kyung; Chung, Hyun Hoon; Song, Yong Sang; Bazer, Fuller W.; Han, Jae Yong; Song, Gwonhwa

2012-01-01

Serine protease inhibitors (SERPINs) appear to be ubiquitously expressed in a variety of species and play important roles in pivotal physiological processes such as angiogenesis, immune responses, blood coagulation and fibronolysis. Of these, squamous cell carcinoma antigen 1 (SCCA1), also known as a SERPINB3, was first identified in squamous cell carcinoma tissue from the cervix of women. However, there is little known about the SERPINB3 expression in human epithelial ovarian cancer (EOC). Therefore, in the present study, we investigated the functional role of SERPINB3 gene in human EOC using chickens, the most relevant animal model. In 136 chickens, EOC was found in 10 (7.4%). SERPINB3 mRNA was induced in cancerous, but not normal ovaries of chickens (P<0.01), and it was abundant only in the glandular epithelium of cancerous ovaries of chickens. Further, several microRNAs, specifically miR-101, miR-1668 and miR-1681 were discovered to influence SERPINB3 expression via its 3′-UTR which suggests that post-transcriptional regulation influences SERPINB3 expression in chickens. SERPINB3 protein was localized predominantly to the glandular epithelium in cancerous ovaries of chickens, and it was abundant in the nucleus of both chicken and human ovarian cancer cell lines. In 109 human patients with EOC, 15 (13.8%), 66 (60.6%) and 28 (25.7%) patients showed weak, moderate and strong expression of SERPINB3 protein, respectively. Strong expression of SERPINB3 protein was a prognostic factor for platinum resistance (adjusted OR; odds ratio, 5.94; 95% Confidence Limits, 1.21–29.15), and for poor progression-free survival (PFS; adjusted HR; hazard ratio, 2.07; 95% CI; confidence interval, 1.03–4.41). Therefore, SERPINB3 may play an important role in ovarian carcinogenesis and be a novel biomarker for predicting platinum resistance and a poor prognosis for survival in patients with EOC. PMID:23185467

Within-Subject Correlation Analysis to Detect Functional Areas Associated With Response Inhibition.

PubMed

Yamasaki, Tomoko; Ogawa, Akitoshi; Osada, Takahiro; Jimura, Koji; Konishi, Seiki

2018-01-01

Functional areas in fMRI studies are often detected by brain-behavior correlation, calculating across-subject correlation between the behavioral index and the brain activity related to a function of interest. Within-subject correlation analysis is also employed in a single subject level, which utilizes cognitive fluctuations in a shorter time period by correlating the behavioral index with the brain activity across trials. In the present study, the within-subject analysis was applied to the stop-signal task, a standard task to probe response inhibition, where efficiency of response inhibition can be evaluated by the stop-signal reaction time (SSRT). Since the SSRT is estimated, by definition, not in a trial basis but from pooled trials, the correlation across runs was calculated between the SSRT and the brain activity related to response inhibition. The within-subject correlation revealed negative correlations in the anterior cingulate cortex and the cerebellum. Moreover, the dissociation pattern was observed in the within-subject analysis when earlier vs. later parts of the runs were analyzed: negative correlation was dominant in earlier runs, whereas positive correlation was dominant in later runs. Regions of interest analyses revealed that the negative correlation in the anterior cingulate cortex, but not in the cerebellum, was dominant in earlier runs, suggesting multiple mechanisms associated with inhibitory processes that fluctuate on a run-by-run basis. These results indicate that the within-subject analysis compliments the across-subject analysis by highlighting different aspects of cognitive/affective processes related to response inhibition.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

PubMed

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

PubMed Central

Faltermeier, Rupert; Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses. PMID:26693250

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis

NASA Astrophysics Data System (ADS)

Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

2013-03-01

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF -XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF -XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis.

PubMed

Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

2013-03-01

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF-XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF-XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

Autocorrelation and cross-correlation in time series of homicide and attempted homicide

NASA Astrophysics Data System (ADS)

Machado Filho, A.; da Silva, M. F.; Zebende, G. F.

2014-04-01

We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ρ(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify auto-correlations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n>90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.

Long-term correlations and cross-correlations in IBovespa and constituent companies

NASA Astrophysics Data System (ADS)

de Lima, Neílson F.; Fernandes, Leonardo H. S.; Jale, Jader S.; de Mattos Neto, Paulo S. G.; Stošić, Tatijana; Stošić, Borko; Ferreira, Tiago A. E.

2018-02-01

We study auto-correlations and cross-correlations of IBovespa index and its constituent companies. We use Detrended Fluctuation Analysis (DFA) to quantify auto-correlations and Detrended Cross-Correlation Analysis (DCCA) to quantify cross-correlations in absolute returns of daily closing prices of IBovespa and the individual companies. We find persistent long-term correlations and cross-correlations which are weaker than those found for USA market. Our results indicate that market indices of developing markets exhibit weaker coupling with its constituents than for mature developed markets.

Long-Range Temporal Correlations, Multifractality, and the Causal Relation between Neural Inputs and Movements

PubMed Central

Hu, Jing; Zheng, Yi; Gao, Jianbo

2013-01-01

Understanding the causal relation between neural inputs and movements is very important for the success of brain-machine interfaces (BMIs). In this study, we analyze 104 neurons’ firings using statistical, information theoretic, and fractal analysis. The latter include Fano factor analysis, multifractal adaptive fractal analysis (MF-AFA), and wavelet multifractal analysis. We find neuronal firings are highly non-stationary, and Fano factor analysis always indicates long-range correlations in neuronal firings, irrespective of whether those firings are correlated with movement trajectory or not, and thus does not reveal any actual correlations between neural inputs and movements. On the other hand, MF-AFA and wavelet multifractal analysis clearly indicate that when neuronal firings are not well correlated with movement trajectory, they do not have or only have weak temporal correlations. When neuronal firings are well correlated with movements, they are characterized by very strong temporal correlations, up to a time scale comparable to the average time between two successive reaching tasks. This suggests that neurons well correlated with hand trajectory experienced a “re-setting” effect at the start of each reaching task, in the sense that within the movement correlated neurons the spike trains’ long-range dependences persisted about the length of time the monkey used to switch between task executions. A new task execution re-sets their activity, making them only weakly correlated with their prior activities on longer time scales. We further discuss the significance of the coalition of those important neurons in executing cortical control of prostheses. PMID:24130549

Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

PubMed

Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

2018-06-01

Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Multifractal detrended cross-correlation analysis in the MENA area

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane; Benbachir, Saâd

2013-12-01

In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.

Nonparametric Bayesian models for a spatial covariance.

PubMed

Reich, Brian J; Fuentes, Montserrat

2012-01-01

A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.

Long memory of abnormal investor attention and the cross-correlations between abnormal investor attention and trading volume, volatility respectively

NASA Astrophysics Data System (ADS)

Fan, Xiaoqian; Yuan, Ying; Zhuang, Xintian; Jin, Xiu

2017-03-01

Taking Baidu Index as a proxy for abnormal investor attention (AIA), the long memory property in the AIA of Shanghai Stock Exchange (SSE) 50 Index component stocks was empirically investigated using detrended fluctuation analysis (DFA) method. The results show that abnormal investor attention is power-law correlated with Hurst exponents between 0.64 and 0.98. Furthermore, the cross-correlations between abnormal investor attention and trading volume, volatility respectively are studied using detrended cross-correlation analysis (DCCA) and the DCCA cross-correlation coefficient (ρDCCA). The results suggest that there are positive correlations between AIA and trading volume, volatility respectively. In addition, the correlations for trading volume are in general higher than the ones for volatility. By carrying on rescaled range analysis (R/S) and rolling windows analysis, we find that the results mentioned above are effective and significant.

Analysis/forecast experiments with a flow-dependent correlation function using FGGE data

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Carus, H.; Nestler, M. S.

1986-01-01

The use of a flow-dependent correlation function to improve the accuracy of an optimum interpolation (OI) scheme is examined. The development of the correlation function for the OI analysis scheme used for numerical weather prediction is described. The scheme uses a multivariate surface analysis over the oceans to model the pressure-wind error cross-correlation and it has the ability to use an error correlation function that is flow- and geographically-dependent. A series of four-day data assimilation experiments, conducted from January 5-9, 1979, were used to investigate the effect of the different features of the OI scheme (error correlation) on forecast skill for the barotropic lows and highs. The skill of the OI was compared with that of a successive correlation method (SCM) of analysis. It is observed that the largest difference in the correlation statistics occurred in barotropic and baroclinic lows and highs. The comparison reveals that the OI forecasts were more accurate than the SCM forecasts.

Cross-correlations between RMB exchange rate and international commodity markets

NASA Astrophysics Data System (ADS)

Lu, Xinsheng; Li, Jianfeng; Zhou, Ying; Qian, Yubo

2017-11-01

This paper employs multifractal detrended analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) to study cross-correlation behaviors between China's RMB exchange rate market and four international commodity markets, using a comprehensive set of data covering the period from 22 July 2005 to 15 March 2016. Our empirical results from MF-DFA indicate that the RMB exchange rate is the most inefficient among the 4 selected markets. The results from quantitative analysis have testified the existence of cross-correlations and the result from MF-DCCA have further confirmed a strong multifractal behavior between RMB exchange rate and international commodity markets. We also demonstrate that the recent financial crisis has significant impact on the cross-correlated behavior. Through the rolling window analysis, we find that the RMB exchange rates and international commodity prices are anti-persistent cross-correlated. The main sources of multifractality in the cross-correlations are long-range correlations between RMB exchange rate and the aggregate commodity, energy and metals index.

[Correlation analysis of major agronomic characters and the polysaccharide contents in Dendrobium officinale].

PubMed

Zhang, Lei; Zheng, Xi-Long; Qiu, Dao-Shou; Cai, Shi-Ke; Luo, Huan-Ming; Deng, Rui-Yun; Liu, Xiao-Jin

2013-10-01

In order to provide theoretical and technological basis for the germplasm innovation and variety breeding in Dendrobium officinale, a study of the correlation between polysaccharide content and agronomic characters was conducted. Based on the polysaccharide content determination and the agronomic characters investigation of 30 copies (110 individual plants) of Dendrobium officinale germplasm resources, the correlation between polysaccharide content and agronomic characters was analyzed via path and correlation analysis. Correlation analysis results showed that there was a significant negative correlation between average spacing and polysaccharide content, the correlation coefficient was -0.695. And the blade thickness was positively correlated with the polysaccharide content, but the correlation was not significant. The path analysis results showed that the stem length was the maximum influence factor to the polysaccharide, and it was positive effect, the direct path coefficient was 1.568. According to thess results, the polysaccharide content can be easily and intuitively estimated by the agronomic characters investigating data in the germpalsm resources screening and variety breeding. Therefore, it is a visual and practical technology guidance in quality variety breeding of Dendrobium officinale.

Extension and Application of High-Speed Digital Imaging Analysis Via Spatiotemporal Correlation and Eigenmode Analysis of Vocal Fold Vibration Before and After Polyp Excision.

PubMed

Wang, Jun-Sheng; Olszewski, Emily; Devine, Erin E; Hoffman, Matthew R; Zhang, Yu; Shao, Jun; Jiang, Jack J

2016-08-01

To evaluate the spatiotemporal correlation of vocal fold vibration using eigenmode analysis before and after polyp removal and explore the potential clinical relevance of spatiotemporal analysis of correlation length and entropy as quantitative voice parameters. We hypothesized that increased order in the vibrating signal after surgical intervention would decrease the eigenmode-based entropy and increase correlation length. Prospective case series. Forty subjects (23 males, 17 females) with unilateral (n = 24) or bilateral (n = 16) polyps underwent polyp removal. High-speed videoendoscopy was performed preoperatively and 2 weeks postoperatively. Spatiotemporal analysis was performed to determine entropy, quantification of signal disorder, correlation length, size, and spatially ordered structure of vocal fold vibration in comparison to full spatial consistency. The signal analyzed consists of the vibratory pattern in space and time derived from the high-speed video glottal area contour. Entropy decreased (Z = -3.871, P < .001) and correlation length increased (t = -8.913, P < .001) following polyp excision. The intraclass correlation coefficients (ICC) for correlation length and entropy were 0.84 and 0.93. Correlation length and entropy are sensitive to mass lesions. These parameters could potentially be used to augment subjective visualization after polyp excision when evaluating procedural efficacy. © The Author(s) 2016.

CADDIS Volume 4. Data Analysis: Exploratory Data Analysis

EPA Pesticide Factsheets

Intro to exploratory data analysis. Overview of variable distributions, scatter plots, correlation analysis, GIS datasets. Use of conditional probability to examine stressor levels and impairment. Exploring correlations among multiple stressors.

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…

Frontiers of Two-Dimensional Correlation Spectroscopy. Part 1. New concepts and noteworthy developments

NASA Astrophysics Data System (ADS)

Noda, Isao

2014-07-01

A comprehensive survey review of new and noteworthy developments, which are advancing forward the frontiers in the field of 2D correlation spectroscopy during the last four years, is compiled. This review covers books, proceedings, and review articles published on 2D correlation spectroscopy, a number of significant conceptual developments in the field, data pretreatment methods and other pertinent topics, as well as patent and publication trends and citation activities. Developments discussed include projection 2D correlation analysis, concatenated 2D correlation, and correlation under multiple perturbation effects, as well as orthogonal sample design, predicting 2D correlation spectra, manipulating and comparing 2D spectra, correlation strategy based on segmented data blocks, such as moving-window analysis, features like determination of sequential order and enhanced spectral resolution, statistical 2D spectroscopy using covariance and other statistical metrics, hetero-correlation analysis, and sample-sample correlation technique. Data pretreatment operations prior to 2D correlation analysis are discussed, including the correction for physical effects, background and baseline subtraction, selection of reference spectrum, normalization and scaling of data, derivatives spectra and deconvolution technique, and smoothing and noise reduction. Other pertinent topics include chemometrics and statistical considerations, peak position shift phenomena, variable sampling increments, computation and software, display schemes, such as color coded format, slice and power spectra, tabulation, and other schemes.

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

The effects of common risk factors on stock returns: A detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

Do Deregulated Cas Proteins Induce Genomic Instability in Early-Stage Ovarian Cancer

DTIC Science & Technology

2006-12-01

use Western blot analysis of tumor lysates to correlate expression of HEF1, p130Cas, Aurora A, and phospho-Aurora A. This analysis is in progress. In...and importantly, evaluated a number of different detection/image analysis systems to ensure reproducible quantitative results. We have used a pilot...reproducible Interestingly, preliminary statistical analysis using Spearman and Pearson correlation indicates at least one striking correlation

Correlating Detergent Fiber Analysis and Dietary Fiber Analysis Data for Corn Stover

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

Wolfrum, E. J.; Lorenz, A. J.; deLeon, N.

There exist large amounts of detergent fiber analysis data [neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL)] for many different potential cellulosic ethanol feedstocks, since these techniques are widely used for the analysis of forages. Researchers working in the area of cellulosic ethanol are interested in the structural carbohydrates in a feedstock (principally glucan and xylan), which are typically determined by acid hydrolysis of the structural fraction after multiple extractions of the biomass. These so-called dietary fiber analysis methods are significantly more involved than detergent fiber analysis methods. The purpose of this study was to determinemore » whether it is feasible to correlate detergent fiber analysis values to glucan and xylan content determined by dietary fiber analysis methods for corn stover. In the detergent fiber analysis literature cellulose is often estimated as the difference between ADF and ADL, while hemicellulose is often estimated as the difference between NDF and ADF. Examination of a corn stover dataset containing both detergent fiber analysis data and dietary fiber analysis data predicted using near infrared spectroscopy shows that correlations between structural glucan measured using dietary fiber techniques and cellulose estimated using detergent techniques, and between structural xylan measured using dietary fiber techniques and hemicellulose estimated using detergent techniques are high, but are driven largely by the underlying correlation between total extractives measured by fiber analysis and NDF/ADF. That is, detergent analysis data is correlated to dietary fiber analysis data for structural carbohydrates, but only indirectly; the main correlation is between detergent analysis data and solvent extraction data produced during the dietary fiber analysis procedure.« less

WGCNA: an R package for weighted correlation network analysis.

PubMed

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

WGCNA: an R package for weighted correlation network analysis

PubMed Central

Langfelder, Peter; Horvath, Steve

2008-01-01

Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008

Correlation analysis of respiratory signals by using parallel coordinate plots.

PubMed

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Complex Networks/Foundations of Information Systems

DTIC Science & Technology

2013-03-06

the benefit of feedback or dynamic correlations in coding and protocol. Using Renyi correlation analysis and entropy to model this wider class of...dynamic heterogeneous conditions. Lizhong Zheng, MIT Renyi Channel Correlation Analysis (connected to geometric curvature) Network Channel

Clustering stocks using partial correlation coefficients

NASA Astrophysics Data System (ADS)

Jung, Sean S.; Chang, Woojin

2016-11-01

A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.

Financial liberalization and stock market cross-correlation: MF-DCCA analysis based on Shanghai-Hong Kong Stock Connect

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Zhang, Shuhua; Lv, Dayong; Lu, Xinsheng

2018-02-01

Based on the implementation of Shanghai-Hong Kong Stock Connect in China, this paper examines the effects of financial liberalization on stock market comovement using both multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) methods. Results based on MF-DFA confirm the multifractality of Shanghai and Hong Kong stock markets, and the market efficiency of Shanghai stock market increased after the implementation of this connect program. Besides, analysis based on MF-DCCA has verified the existence of persistent cross-correlation between Shanghai and Hong Kong stock markets, and the cross-correlation gets stronger after the launch of this liberalization program. Finally, we find that fat-tail distribution is the main source of multifractality in the cross-correlations before the stock connect program, while long-range correlation contributes to the multifractality after this program.

Weighted network analysis of high-frequency cross-correlation measures

NASA Astrophysics Data System (ADS)

Iori, Giulia; Precup, Ovidiu V.

2007-03-01

In this paper we implement a Fourier method to estimate high-frequency correlation matrices from small data sets. The Fourier estimates are shown to be considerably less noisy than the standard Pearson correlation measures and thus capable of detecting subtle changes in correlation matrices with just a month of data. The evolution of correlation at different time scales is analyzed from the full correlation matrix and its minimum spanning tree representation. The analysis is performed by implementing measures from the theory of random weighted networks.

Modal energy analysis for mechanical systems excited by spatially correlated loads

NASA Astrophysics Data System (ADS)

Zhang, Peng; Fei, Qingguo; Li, Yanbin; Wu, Shaoqing; Chen, Qiang

2018-10-01

MODal ENergy Analysis (MODENA) is an energy-based method, which is proposed to deal with vibroacoustic problems. The performance of MODENA on the energy analysis of a mechanical system under spatially correlated excitation is investigated. A plate/cavity coupling system excited by a pressure field is studied in a numerical example, in which four kinds of pressure fields are involved, which include the purely random pressure field, the perfectly correlated pressure field, the incident diffuse field, and the turbulent boundary layer pressure fluctuation. The total energies of subsystems differ to reference solution only in the case of purely random pressure field and only for the non-excited subsystem (the cavity). A deeper analysis on the scale of modal energy is further conducted via another numerical example, in which two structural modes excited by correlated forces are coupled with one acoustic mode. A dimensionless correlation strength factor is proposed to determine the correlation strength between modal forces. Results show that the error on modal energy increases with the increment of the correlation strength factor. A criterion is proposed to establish a link between the error and the correlation strength factor. According to the criterion, the error is negligible when the correlation strength is weak, in this situation the correlation strength factor is less than a critical value.

Two-dimensional correlation spectroscopy — Biannual survey 2007-2009

NASA Astrophysics Data System (ADS)

Noda, Isao

2010-06-01

The publication activities in the field of 2D correlation spectroscopy are surveyed with the emphasis on papers published during the last two years. Pertinent review articles and conference proceedings are discussed first, followed by the examination of noteworthy developments in the theory and applications of 2D correlation spectroscopy. Specific topics of interest include Pareto scaling, analysis of randomly sampled spectra, 2D analysis of data obtained under multiple perturbations, evolution of 2D spectra along additional variables, comparison and quantitative analysis of multiple 2D spectra, orthogonal sample design to eliminate interfering cross peaks, quadrature orthogonal signal correction and other data transformation techniques, data pretreatment methods, moving window analysis, extension of kernel and global phase angle analysis, covariance and correlation coefficient mapping, variant forms of sample-sample correlation, and different display methods. Various static and dynamic perturbation methods used in 2D correlation spectroscopy, e.g., temperature, composition, chemical reactions, H/D exchange, physical phenomena like sorption, diffusion and phase transitions, optical and biological processes, are reviewed. Analytical probes used in 2D correlation spectroscopy include IR, Raman, NIR, NMR, X-ray, mass spectrometry, chromatography, and others. Application areas of 2D correlation spectroscopy are diverse, encompassing synthetic and natural polymers, liquid crystals, proteins and peptides, biomaterials, pharmaceuticals, food and agricultural products, solutions, colloids, surfaces, and the like.

Multiple correlation analyses revealed complex relationship between DNA methylation and mRNA expression in human peripheral blood mononuclear cells.

PubMed

Xie, Fang-Fei; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Hong; Wu, Jian; Guo, Yu-Fan; Zeng, Ke-Qin; Wang, Ming-Jun; Zhu, Xiao-Wei; Xia, Wei; Wang, Lan; He, Pei; Bing, Peng-Fei; Lu, Xin; Zhang, Yong-Hong; Lei, Shu-Feng

2018-01-01

DNA methylation is an important regulator on the mRNA expression. However, a genome-wide correlation pattern between DNA methylation and mRNA expression in human peripheral blood mononuclear cells (PBMCs) is largely unknown. The comprehensive relationship between mRNA and DNA methylation was explored by using four types of correlation analyses and a genome-wide methylation-mRNA expression quantitative trait locus (eQTL) analysis in PBMCs in 46 unrelated female subjects. An enrichment analysis was performed to detect biological function for the detected genes. Single pair correlation coefficient (r T1 ) between methylation level and mRNA is moderate (-0.63-0.62) in intensity, and the negative and positive correlations are nearly equal in quantity. Correlation analysis on each gene (T4) found 60.1% genes showed correlations between mRNA and gene-based methylation at P < 0.05 and more than 5.96% genes presented very strong correlation (R T4  > 0.8). Methylation sites have regulation effects on mRNA expression in eQTL analysis, with more often observations in region of transcription start site (TSS). The genes under significant methylation regulation both in correlation analysis and eQTL analysis tend to cluster to the categories (e.g., transcription, translation, regulation of transcription) that are essential for maintaining the basic life activities of cells. Our findings indicated that DNA methylation has predictive regulation effect on mRNA with a very complex pattern in PBMCs. The results increased our understanding on correlation of methylation and mRNA and also provided useful clues for future epigenetic studies in exploring biological and disease-related regulatory mechanisms in PBMC.

Analytic uncertainty and sensitivity analysis of models with input correlations

NASA Astrophysics Data System (ADS)

Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

2018-03-01

Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

Scaling analysis of stock markets

NASA Astrophysics Data System (ADS)

Bu, Luping; Shang, Pengjian

2014-06-01

In this paper, we apply the detrended fluctuation analysis (DFA), local scaling detrended fluctuation analysis (LSDFA), and detrended cross-correlation analysis (DCCA) to investigate correlations of several stock markets. DFA method is for the detection of long-range correlations used in time series. LSDFA method is to show more local properties by using local scale exponents. DCCA method is a developed method to quantify the cross-correlation of two non-stationary time series. We report the results of auto-correlation and cross-correlation behaviors in three western countries and three Chinese stock markets in periods 2004-2006 (before the global financial crisis), 2007-2009 (during the global financial crisis), and 2010-2012 (after the global financial crisis) by using DFA, LSDFA, and DCCA method. The findings are that correlations of stocks are influenced by the economic systems of different countries and the financial crisis. The results indicate that there are stronger auto-correlations in Chinese stocks than western stocks in any period and stronger auto-correlations after the global financial crisis for every stock except Shen Cheng; The LSDFA shows more comprehensive and detailed features than traditional DFA method and the integration of China and the world in economy after the global financial crisis; When it turns to cross-correlations, it shows different properties for six stock markets, while for three Chinese stocks, it reaches the weakest cross-correlations during the global financial crisis.

Maximum entropy analysis of polarized fluorescence decay of (E)GFP in aqueous solution

NASA Astrophysics Data System (ADS)

Novikov, Eugene G.; Skakun, Victor V.; Borst, Jan Willem; Visser, Antonie J. W. G.

2018-01-01

The maximum entropy method (MEM) was used for the analysis of polarized fluorescence decays of enhanced green fluorescent protein (EGFP) in buffered water/glycerol mixtures, obtained with time-correlated single-photon counting (Visser et al 2016 Methods Appl. Fluoresc. 4 035002). To this end, we used a general-purpose software module of MEM that was earlier developed to analyze (complex) laser photolysis kinetics of ligand rebinding reactions in oxygen binding proteins. We demonstrate that the MEM software provides reliable results and is easy to use for the analysis of both total fluorescence decay and fluorescence anisotropy decay of aqueous solutions of EGFP. The rotational correlation times of EGFP in water/glycerol mixtures, obtained by MEM as maxima of the correlation-time distributions, are identical to the single correlation times determined by global analysis of parallel and perpendicular polarized decay components. The MEM software is also able to determine homo-FRET in another dimeric GFP, for which the transfer correlation time is an order of magnitude shorter than the rotational correlation time. One important advantage utilizing MEM analysis is that no initial guesses of parameters are required, since MEM is able to select the least correlated solution from the feasible set of solutions.

Correlational Analysis of Ordinal Data: From Pearson's "r" to Bayesian Polychoric Correlation

ERIC Educational Resources Information Center

Choi, Jaehwa; Peters, Michelle; Mueller, Ralph O.

2010-01-01

Correlational analyses are one of the most popular quantitative methods, yet also one of the mostly frequently misused methods in social and behavioral research, especially when analyzing ordinal data from Likert or other rating scales. Although several correlational analysis options have been developed for ordinal data, there seems to be a lack…

Multifractal detrended cross-correlation analysis on air pollutants of University of Hyderabad Campus, India

NASA Astrophysics Data System (ADS)

Manimaran, P.; Narayana, A. C.

2018-07-01

In this paper, we study the multifractal characteristics and cross-correlation behaviour of Air Pollution Index (API) time series data through multifractal detrended cross-correlation analysis method. We analyse the daily API records of nine air pollutants of the university of Hyderabad campus for a period of three years (2013-2016). The cross-correlation behaviour has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, it is found that the cross-correlation analysis shows anti-correlation behaviour for all possible 36 bivariate time series. We also observe the existence of multifractal nature in all the bivariate time series in which many of them show strong multifractal behaviour. In particular, the hazardous particulate matter PM2.5 and inhalable particulate matter PM10 shows anti-correlated behaviour with all air pollutants.

METHANOL MEASUREMENT IN AUTO EXHAUST USING A GAS-FILTER CORRELATION SPECTROMETER

EPA Science Inventory

Spectroscopic methods offer an alternative to wet chemical methods for analysis of methanol emissions from automobiles. The gas filter correlation infrared optical analysis approach appears very promising. The report describes the gas correlation optical system constructed to ana...

Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan; Ma, Guofeng

2017-02-01

In this paper, we investigate the cross-correlations between the Hang Seng China Enterprises Index and RMB exchange markets on the basis of a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). MF-DCCA has, at best, serious limitations for most of the signals describing complex natural processes and often indicates multifractal cross-correlations when there are none. In order to prevent these false multifractal cross-correlations, we apply MFCCA to verify the cross-correlations. Qualitatively, we find that the return series of the Hang Seng China Enterprises Index and RMB exchange markets were, overall, significantly cross-correlated based on the statistical analysis. Quantitatively, we find that the cross-correlations between the stock index and RMB exchange markets were strongly multifractal, and the multifractal degree of the onshore RMB exchange markets was somewhat larger than the offshore RMB exchange markets. Moreover, we use the absolute return series to investigate and confirm the fact of multifractality. The results from the rolling windows show that the short-term cross-correlations between volatility series remain high.

Dynamic test/analysis correlation using reduced analytical models

NASA Technical Reports Server (NTRS)

Mcgowan, Paul E.; Angelucci, A. Filippo; Javeed, Mehzad

1992-01-01

Test/analysis correlation is an important aspect of the verification of analysis models which are used to predict on-orbit response characteristics of large space structures. This paper presents results of a study using reduced analysis models for performing dynamic test/analysis correlation. The reduced test-analysis model (TAM) has the same number and orientation of DOF as the test measurements. Two reduction methods, static (Guyan) reduction and the Improved Reduced System (IRS) reduction, are applied to the test/analysis correlation of a laboratory truss structure. Simulated test results and modal test data are used to examine the performance of each method. It is shown that selection of DOF to be retained in the TAM is critical when large structural masses are involved. In addition, the use of modal test results may provide difficulties in TAM accuracy even if a large number of DOF are retained in the TAM.

Multiple Correlation versus Multiple Regression.

ERIC Educational Resources Information Center

Huberty, Carl J.

2003-01-01

Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)

Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images

PubMed Central

Gutmann, Michael U.; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation. PMID:24533049

Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.

PubMed

Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

NASA Astrophysics Data System (ADS)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

Fatality analysis reporting system and roadway inventory correlation.

DOT National Transportation Integrated Search

2013-01-01

In this project, we developed an integrated database to provide new analysis capabilities : for discovering correlations between roadway characteristics and the occurrence of : fatality collisions. Specifically, the aim of this data analysis project ...

ADC histogram analysis of muscle lymphoma - Correlation with histopathology in a rare entity.

PubMed

Meyer, Hans-Jonas; Pazaitis, Nikolaos; Surov, Alexey

2018-06-21

Diffusion weighted imaging (DWI) is able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize lesion on MRI. The purpose of this study is to correlate histogram parameters derived from apparent diffusion coefficient- (ADC) maps with histopathology parameters in muscle lymphoma. Eight patients (mean age 64.8 years, range 45-72 years) with histopathologically confirmed muscle lymphoma were retrospectively identified. Cell count, total nucleic and average nucleic areas were estimated using ImageJ. Additionally, Ki67-index was calculated. DWI was obtained on a 1.5T scanner by using the b values of 0 and 1000 s/mm2. Histogram analysis was performed as a whole lesion measurement by using a custom-made Matlabbased application. The correlation analysis revealed statistically significant correlation between cell count and ADCmean (p=-0.76, P=0.03) as well with ADCp75 (p=-0.79, P=0.02). Kurtosis and entropy correlated with average nucleic area (p=-0.81, P=0.02, p=0.88, P=0.007, respectively). None of the analyzed ADC parameters correlated with total nucleic area and with Ki67-index. This study identified significant correlations between cellularity and histogram parameters derived from ADC maps in muscle lymphoma. Thus, histogram analysis parameters reflect histopathology in muscle tumors. Advances in knowledge: Whole lesion ADC histogram analysis is able to reflect histopathology parameters in muscle lymphomas.

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…

Interuser Interference Analysis for Direct-Sequence Spread-Spectrum Systems Part I: Partial-Period Cross-Correlation

NASA Technical Reports Server (NTRS)

Ni, Jianjun (David)

2012-01-01

This presentation discusses an analysis approach to evaluate the interuser interference for Direct-Sequence Spread-Spectrum (DSSS) Systems for Space Network (SN) Users. Part I of this analysis shows that the correlation property of pseudo noise (PN) sequences is the critical factor which determines the interuser interference performance of the DSSS system. For non-standard DSSS systems in which PN sequence s period is much larger than one data symbol duration, it is the partial-period cross-correlation that determines the system performance. This study reveals through an example that a well-designed PN sequence set (e.g. Gold Sequence, in which the cross-correlation for a whole-period is well controlled) may have non-controlled partial-period cross-correlation which could cause severe interuser interference for a DSSS system. Since the analytical derivation of performance metric (bit error rate or signal-to-noise ratio) based on partial-period cross-correlation is prohibitive, the performance degradation due to partial-period cross-correlation will be evaluated using simulation in Part II of this analysis in the future.

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.

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…

Price-volume multifractal analysis of the Moroccan stock market

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane

2017-11-01

In this paper, we analyzed price-volume multifractal cross-correlations of Moroccan Stock Exchange. We chose the period from January 1st 2000 to January 20th 2017 to investigate the multifractal behavior of price change and volume change series. Then, we used multifractal detrended cross-correlations analysis method (MF-DCCA) and multifractal detrended fluctuation analysis (MF-DFA) to analyze the series. We computed bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively cross-correlations. Furthermore, we used detrended cross-correlations coefficient (DCCA) and cross-correlation test (Q(m)) to analyze cross-correlation quantitatively and qualitatively. By analyzing results, we found existence of price-volume multifractal cross-correlations. The spectrum width has a strong multifractal cross-correlation. We remarked that volume change series is anti-persistent when we analyzed the generalized Hurst exponent for all moments q. The cross-correlation test showed the presence of a significant cross-correlation. However, DCCA coefficient had a small positive value, which means that the level of correlation is not very significant. Finally, we analyzed sources of multifractality and their degree of contribution in the series.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

PubMed

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Complex-valued time-series correlation increases sensitivity in FMRI analysis.

PubMed

Kociuba, Mary C; Rowe, Daniel B

2016-07-01

To develop a linear matrix representation of correlation between complex-valued (CV) time-series in the temporal Fourier frequency domain, and demonstrate its increased sensitivity over correlation between magnitude-only (MO) time-series in functional MRI (fMRI) analysis. The standard in fMRI is to discard the phase before the statistical analysis of the data, despite evidence of task related change in the phase time-series. With a real-valued isomorphism representation of Fourier reconstruction, correlation is computed in the temporal frequency domain with CV time-series data, rather than with the standard of MO data. A MATLAB simulation compares the Fisher-z transform of MO and CV correlations for varying degrees of task related magnitude and phase amplitude change in the time-series. The increased sensitivity of the complex-valued Fourier representation of correlation is also demonstrated with experimental human data. Since the correlation description in the temporal frequency domain is represented as a summation of second order temporal frequencies, the correlation is easily divided into experimentally relevant frequency bands for each voxel's temporal frequency spectrum. The MO and CV correlations for the experimental human data are analyzed for four voxels of interest (VOIs) to show the framework with high and low contrast-to-noise ratios in the motor cortex and the supplementary motor cortex. The simulation demonstrates the increased strength of CV correlations over MO correlations for low magnitude contrast-to-noise time-series. In the experimental human data, the MO correlation maps are noisier than the CV maps, and it is more difficult to distinguish the motor cortex in the MO correlation maps after spatial processing. Including both magnitude and phase in the spatial correlation computations more accurately defines the correlated left and right motor cortices. Sensitivity in correlation analysis is important to preserve the signal of interest in fMRI data sets with high noise variance, and avoid excessive processing induced correlation. Copyright © 2016 Elsevier Inc. All rights reserved.

Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.

PubMed

Ulgen, Ayse; Han, Zhihua; Li, Wentian

2003-12-31

We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.

A correlational analysis of the effects of changing environmental conditions on the NR atomic hydrogen maser

NASA Technical Reports Server (NTRS)

Dragonette, Richard A.; Suter, Joseph J.

1992-01-01

An extensive statistical analysis has been undertaken to determine if a correlation exists between changes in an NR atomic hydrogen maser's frequency offset and changes in environmental conditions. Correlation analyses have been performed comparing barometric pressure, humidity, and temperature with maser frequency offset as a function of time for periods ranging from 5.5 to 17 days. Semipartial correlation coefficients as large as -0.9 have been found between barometric pressure and maser frequency offset. Correlation between maser frequency offset and humidity was small compared to barometric pressure and unpredictable. Analysis of temperature data indicates that in the most current design, temperature does not significantly affect maser frequency offset.

Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data

NASA Technical Reports Server (NTRS)

Romero-Wolf, A. F.; Jacobs, C. S.

2011-01-01

The standard VLBI analysis models measurement noise as purely thermal errors modeled according to uncorrelated Gaussian distributions. As the price of recording bits steadily decreases, thermal errors will soon no longer dominate. It is therefore expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become more relevant for optimal analysis. This paper will discuss the advantages of including the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen ow model pioneered by Treuhaft and Lanyi. We will show examples of applying these correlated noise spectra to the weighting of VLBI data analysis.

Analyzing the Cross-Correlation Between Onshore and Offshore RMB Exchange Rates Based on Multifractal Detrended Cross-Correlation Analysis (MF-DCCA)

NASA Astrophysics Data System (ADS)

Xie, Chi; Zhou, Yingying; Wang, Gangjin; Yan, Xinguo

We use the multifractal detrended cross-correlation analysis (MF-DCCA) method to explore the multifractal behavior of the cross-correlation between exchange rates of onshore RMB (CNY) and offshore RMB (CNH) against US dollar (USD). The empirical data are daily prices of CNY/USD and CNH/USD from May 1, 2012 to February 29, 2016. The results demonstrate that: (i) the cross-correlation between CNY/USD and CNH/USD is persistent and its fluctuation is smaller when the order of fluctuation function is negative than that when the order is positive; (ii) the multifractal behavior of the cross-correlation between CNY/USD and CNH/USD is significant during the sample period; (iii) the dynamic Hurst exponents obtained by the rolling windows analysis show that the cross-correlation is stable when the global economic situation is good and volatile in bad situation; and (iv) the non-normal distribution of original data has a greater effect on the multifractality of the cross-correlation between CNY/USD and CNH/USD than the temporary correlation.

Theory and simulations of covariance mapping in multiple dimensions for data analysis in high-event-rate experiments

NASA Astrophysics Data System (ADS)

Zhaunerchyk, V.; Frasinski, L. J.; Eland, J. H. D.; Feifel, R.

2014-05-01

Multidimensional covariance analysis and its validity for correlation of processes leading to multiple products are investigated from a theoretical point of view. The need to correct for false correlations induced by experimental parameters which fluctuate from shot to shot, such as the intensity of self-amplified spontaneous emission x-ray free-electron laser pulses, is emphasized. Threefold covariance analysis based on simple extension of the two-variable formulation is shown to be valid for variables exhibiting Poisson statistics. In this case, false correlations arising from fluctuations in an unstable experimental parameter that scale linearly with signals can be eliminated by threefold partial covariance analysis, as defined here. Fourfold covariance based on the same simple extension is found to be invalid in general. Where fluctuations in an unstable parameter induce nonlinear signal variations, a technique of contingent covariance analysis is proposed here to suppress false correlations. In this paper we also show a method to eliminate false correlations associated with fluctuations of several unstable experimental parameters.

A comparison of correlation-length estimation methods for the objective analysis of surface pollutants at Environment and Climate Change Canada.

PubMed

Ménard, Richard; Deshaies-Jacques, Martin; Gasset, Nicolas

2016-09-01

An objective analysis is one of the main components of data assimilation. By combining observations with the output of a predictive model we combine the best features of each source of information: the complete spatial and temporal coverage provided by models, with a close representation of the truth provided by observations. The process of combining observations with a model output is called an analysis. To produce an analysis requires the knowledge of observation and model errors, as well as its spatial correlation. This paper is devoted to the development of methods of estimation of these error variances and the characteristic length-scale of the model error correlation for its operational use in the Canadian objective analysis system. We first argue in favor of using compact support correlation functions, and then introduce three estimation methods: the Hollingsworth-Lönnberg (HL) method in local and global form, the maximum likelihood method (ML), and the [Formula: see text] diagnostic method. We perform one-dimensional (1D) simulation studies where the error variance and true correlation length are known, and perform an estimation of both error variances and correlation length where both are non-uniform. We show that a local version of the HL method can capture accurately the error variances and correlation length at each observation site, provided that spatial variability is not too strong. However, the operational objective analysis requires only a single and globally valid correlation length. We examine whether any statistics of the local HL correlation lengths could be a useful estimate, or whether other global estimation methods such as by the global HL, ML, or [Formula: see text] should be used. We found in both 1D simulation and using real data that the ML method is able to capture physically significant aspects of the correlation length, while most other estimates give unphysical and larger length-scale values. This paper describes a proposed improvement of the objective analysis of surface pollutants at Environment and Climate Change Canada (formerly known as Environment Canada). Objective analyses are essentially surface maps of air pollutants that are obtained by combining observations with an air quality model output, and are thought to provide a complete and more accurate representation of the air quality. The highlight of this study is an analysis of methods to estimate the model (or background) error correlation length-scale. The error statistics are an important and critical component to the analysis scheme.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

PubMed

Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

2015-01-01

In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Phase and vortex correlations in superconducting Josephson-junction arrays at irrational magnetic frustration.

PubMed

Granato, Enzo

2008-07-11

Phase coherence and vortex order in a Josephson-junction array at irrational frustration are studied by extensive Monte Carlo simulations using the parallel-tempering method. A scaling analysis of the correlation length of phase variables in the full equilibrated system shows that the critical temperature vanishes with a power-law divergent correlation length and critical exponent nuph, in agreement with recent results from resistivity scaling analysis. A similar scaling analysis for vortex variables reveals a different critical exponent nuv, suggesting that there are two distinct correlation lengths associated with a decoupled zero-temperature phase transition.

Detecting coupled collective motions in protein by independent subspace analysis

NASA Astrophysics Data System (ADS)

Sakuraba, Shun; Joti, Yasumasa; Kitao, Akio

2010-11-01

Protein dynamics evolves in a high-dimensional space, comprising aharmonic, strongly correlated motional modes. Such correlation often plays an important role in analyzing protein function. In order to identify significantly correlated collective motions, here we employ independent subspace analysis based on the subspace joint approximate diagonalization of eigenmatrices algorithm for the analysis of molecular dynamics (MD) simulation trajectories. From the 100 ns MD simulation of T4 lysozyme, we extract several independent subspaces in each of which collective modes are significantly correlated, and identify the other modes as independent. This method successfully detects the modes along which long-tailed non-Gaussian probability distributions are obtained. Based on the time cross-correlation analysis, we identified a series of events among domain motions and more localized motions in the protein, indicating the connection between the functionally relevant phenomena which have been independently revealed by experiments.

TACT: A Set of MSC/PATRAN- and MSC/NASTRAN- based Modal Correlation Tools

NASA Technical Reports Server (NTRS)

Marlowe, Jill M.; Dixon, Genevieve D.

1998-01-01

This paper describes the functionality and demonstrates the utility of the Test Analysis Correlation Tools (TACT), a suite of MSC/PATRAN Command Language (PCL) tools which automate the process of correlating finite element models to modal survey test data. The initial release of TACT provides a basic yet complete set of tools for performing correlation totally inside the PATRAN/NASTRAN environment. Features include a step-by-step menu structure, pre-test accelerometer set evaluation and selection, analysis and test result export/import in Universal File Format, calculation of frequency percent difference and cross-orthogonality correlation results using NASTRAN, creation and manipulation of mode pairs, and five different ways of viewing synchronized animations of analysis and test modal results. For the PATRAN-based analyst, TACT eliminates the repetitive, time-consuming and error-prone steps associated with transferring finite element data to a third-party modal correlation package, which allows the analyst to spend more time on the more challenging task of model updating. The usefulness of this software is presented using a case history, the correlation for a NASA Langley Research Center (LaRC) low aspect ratio research wind tunnel model. To demonstrate the improvements that TACT offers the MSC/PATRAN- and MSC/DIASTRAN- based structural analysis community, a comparison of the modal correlation process using TACT within PATRAN versus external third-party modal correlation packages is presented.

Structural Analysis of Covariance and Correlation Matrices.

ERIC Educational Resources Information Center

Joreskog, Karl G.

1978-01-01

A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…

DGCA: A comprehensive R package for Differential Gene Correlation Analysis.

PubMed

McKenzie, Andrew T; Katsyv, Igor; Song, Won-Min; Wang, Minghui; Zhang, Bin

2016-11-15

Dissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct condition. In this study we develop an R package, DGCA (for Differential Gene Correlation Analysis), which offers a suite of tools for computing and analyzing differential correlations between gene pairs across multiple conditions. To minimize parametric assumptions, DGCA computes empirical p-values via permutation testing. To understand differential correlations at a systems level, DGCA performs higher-order analyses such as measuring the average difference in correlation and multiscale clustering analysis of differential correlation networks. Through a simulation study, we show that the straightforward z-score based method that DGCA employs significantly outperforms the existing alternative methods for calculating differential correlation. Application of DGCA to the TCGA RNA-seq data in breast cancer not only identifies key changes in the regulatory relationships between TP53 and PTEN and their target genes in the presence of inactivating mutations, but also reveals an immune-related differential correlation module that is specific to triple negative breast cancer (TNBC). DGCA is an R package for systematically assessing the difference in gene-gene regulatory relationships under different conditions. This user-friendly, effective, and comprehensive software tool will greatly facilitate the application of differential correlation analysis in many biological studies and thus will help identification of novel signaling pathways, biomarkers, and targets in complex biological systems and diseases.

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.

Emerging spectra of singular correlation matrices under small power-map deformations

NASA Astrophysics Data System (ADS)

Vinayak; Schäfer, Rudi; Seligman, Thomas H.

2013-09-01

Correlation matrices are a standard tool in the analysis of the time evolution of complex systems in general and financial markets in particular. Yet most analysis assume stationarity of the underlying time series. This tends to be an assumption of varying and often dubious validity. The validity of the assumption improves as shorter time series are used. If many time series are used, this implies an analysis of highly singular correlation matrices. We attack this problem by using the so-called power map, which was introduced to reduce noise. Its nonlinearity breaks the degeneracy of the zero eigenvalues and we analyze the sensitivity of the so-emerging spectra to correlations. This sensitivity will be demonstrated for uncorrelated and correlated Wishart ensembles.

Emerging spectra of singular correlation matrices under small power-map deformations.

PubMed

Vinayak; Schäfer, Rudi; Seligman, Thomas H

2013-09-01

Correlation matrices are a standard tool in the analysis of the time evolution of complex systems in general and financial markets in particular. Yet most analysis assume stationarity of the underlying time series. This tends to be an assumption of varying and often dubious validity. The validity of the assumption improves as shorter time series are used. If many time series are used, this implies an analysis of highly singular correlation matrices. We attack this problem by using the so-called power map, which was introduced to reduce noise. Its nonlinearity breaks the degeneracy of the zero eigenvalues and we analyze the sensitivity of the so-emerging spectra to correlations. This sensitivity will be demonstrated for uncorrelated and correlated Wishart ensembles.

Modeling cross-correlations and efficiency of Islamic and conventional banks from Saudi Arabia: Evidence from MF-DFA and MF-DXA approaches

NASA Astrophysics Data System (ADS)

Mensi, Walid; Hamdi, Atef; Shahzad, Syed Jawad Hussain; Shafiullah, Muhammad; Al-Yahyaee, Khamis Hamed

2018-07-01

This paper analyzes the dynamic efficiency and interdependence of Islamic and conventional banks of Saudi Arabia. This analysis applies the Multifractal Detrended Fluctuation Analysis (MF-DFA) and Multifractal Detrended Cross-Correlation Analysis (MF-DXA) approaches. The MF-DFA results show strong multifractality in the daily returns of Saudi banks. Moreover, all eight banks studied exhibit persistence correlation, which demonstrates inefficiency. The rolling window results show significant change in the inefficiency levels over the time. The cross-correlation analysis between bank-pairs exhibits long term interdependence between most of them. These findings indicate that the banking sector in Saudi Arabia suffers from inefficiency and exhibits long term memory.

Coexpression of aPKCλ/ι and IL-6 in prostate cancer tissue correlates with biochemical recurrence.

PubMed

Ishiguro, Hitoshi; Akimoto, Kazunori; Nagashima, Yoji; Kagawa, Eriko; Sasaki, Takeshi; Sano, Jin-yu; Takagawa, Ryo; Fujinami, Kiyoshi; Sasaki, Kazunori; Aoki, Ichiro; Ohno, Shigeo; Kubota, Yoshinobu; Uemura, Hiroji

2011-08-01

Atypical protein kinase C λ/ι (aPKCλ/ι) and interleukin-6 (IL-6) have been implicated in prostate cancer progression, the mechanisms of which have been demonstrated both in vitro and in vivo. However, the clinical significance of the correlation between the expressions of these factors remains to be clarified. In the present study, we report a significant correlation between aPKCλ/ι and IL-6 proteins in prostate cancer tissue by immunohistochemical staining. We evaluated the association of both proteins by analyzing clinicopathological parameters using chi-square test, Kaplan-Meier with log-rank test, and a Cox proportional hazard regression model in univariate and multivariate analyses. The results again showed that the expression of aPKCλ/ι and IL-6 correlates in prostate cancer tissue (P < 0.001). Atypical protein kinase C λ/ι was also found to correlate with the Gleason score (P < 0.001) and with biochemical recurrence after prostatectomy (P = 0.02). Furthermore, aPKCλ/ι correlated with biochemical recurrence in a Kaplan-Meier and log-rank test (P = 0.01) and Cox analysis (P = 0.02 in the univariate analysis, P = 0.02 in the multivariate analysis). The coexpression of aPKCλ/ι and IL-6 also correlated with biochemical recurrence by Kaplan-Meier and log-rank test (P = 0.005) and Cox analysis (P = 0.01 in the univariate analysis, P = 0.03 in the multivariate analysis). These results indicate a strong correlation between aPKCλ/ι and IL-6 in prostate tumors, and that the aPKCλ/ι-IL-6 axis is a reliable prognostic factor for the biochemical recurrence of this cancer. © 2011 Japanese Cancer Association.

Digital Correlation Microwave Polarimetry: Analysis and Demonstration

NASA Technical Reports Server (NTRS)

Piepmeier, J. R.; Gasiewski, A. J.; Krebs, Carolyn A. (Technical Monitor)

2000-01-01

The design, analysis, and demonstration of a digital-correlation microwave polarimeter for use in earth remote sensing is presented. We begin with an analysis of three-level digital correlation and develop the correlator transfer function and radiometric sensitivity. A fifth-order polynomial regression is derived for inverting the digital correlation coefficient into the analog statistic. In addition, the effects of quantizer threshold asymmetry and hysteresis are discussed. A two-look unpolarized calibration scheme is developed for identifying correlation offsets. The developed theory and calibration method are verified using a 10.7 GHz and a 37.0 GHz polarimeter. The polarimeters are based upon 1-GS/s three-level digital correlators and measure the first three Stokes parameters. Through experiment, the radiometric sensitivity is shown to approach the theoretical as derived earlier in the paper and the two-look unpolarized calibration method is successfully compared with results using a polarimetric scheme. Finally, sample data from an aircraft experiment demonstrates that the polarimeter is highly-useful for ocean wind-vector measurement.

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

NASA Astrophysics Data System (ADS)

Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing

2015-10-01

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

Correlation Between Posttraumatic Growth and Posttraumatic Stress Disorder Symptoms Based on Pearson Correlation Coefficient: A Meta-Analysis.

PubMed

Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong

2017-05-01

The literature on posttraumatic growth (PTG) is burgeoning, with the inconsistencies in the literature of the relationship between PTG and posttraumatic stress disorder (PTSD) symptoms becoming a focal point of attention. Thus, this meta-analysis aims to explore the relationship between PTG and PTSD symptoms through the Pearson correlation coefficient. A systematic search of the literature from January 1996 to November 2015 was completed. We retrieved reports on 63 studies that involved 26,951 patients. The weighted correlation coefficient revealed an effect size of 0.22 with a 95% confidence interval of 0.18 to 0.25. Meta-analysis provides evidence that PTG may be positively correlated with PTSD symptoms and that this correlation may be modified by age, trauma type, and time since trauma. Accordingly, people with high levels of PTG should not be ignored, but rather, they should continue to receive help to alleviate their PTSD symptoms.

L2 Reading Comprehension and Its Correlates: A Meta-Analysis

ERIC Educational Resources Information Center

Jeon, Eun Hee; Yamashita, Junko

2014-01-01

The present meta-analysis examined the overall average correlation (weighted for sample size and corrected for measurement error) between passage-level second language (L2) reading comprehension and 10 key reading component variables investigated in the research domain. Four high-evidence correlates (with 18 or more accumulated effect sizes: L2…

Psycholinguistic Correlates of Progress in Literature of Students of Russian Vocational Training School

ERIC Educational Resources Information Center

Nuriakhmetov, Aidar

2012-01-01

The article describes psycholinguistic correlates of progress in literature, discovered on the basis of correlation analysis of grades, and results of several psychological and psycholinguistic tests were taken in the context of comprehensive psycholinguistic research based on one of Russian vocational training schools. Analysis revealed a list of…

(abstract) Cross with Your Spectra? Cross-Correlate Instead!

NASA Technical Reports Server (NTRS)

Beer, Reinhard

1994-01-01

The use of cross-correlation for certain types of spectral analysis is discussed. Under certain circumstances, the use of cross-correlation between a real spectrum and either a model or another spectrum can provide a very powerful tool for spectral analysis. The method (and its limitations) will be described with concrete examples using ATMOS data.

Affective, Continuance, and Normative Commitment to the Organization: A Meta-analysis of Antecedents, Correlates, and Consequences.

ERIC Educational Resources Information Center

Meyer, John P.; Stanley, David J.; Herscovitch, Lynne; Topolnytsky, Laryssa

2002-01-01

Meta-analysis of 155 research reports that used one of three commitment scales (affective, continuance, or normative) found strong correlations between the scales and correlates of jobs satisfaction, job involvement, and organizational commitment. All three were negatively related to withdrawal and turnover. Perceived organizational support had…

Structural Analysis of Correlated Factors: Lessons from the Verbal-Performance Dichotomy of the Wechsler Scales.

ERIC Educational Resources Information Center

Macmann, Gregg M.; Barnett, David W.

1994-01-01

Describes exploratory and confirmatory analyses of verbal-performance procedures to illustrate concepts and procedures for analysis of correlated factors. Argues that, based on convergent and discriminant validity criteria, factors should have higher correlations with variables that they purport to measure than with other variables. Discusses…

Effects of Correlated Errors on the Analysis of Space Geodetic Data

NASA Technical Reports Server (NTRS)

Romero-Wolf, Andres; Jacobs, C. S.

2011-01-01

As thermal errors are reduced instrumental and troposphere correlated errors will increasingly become more important. Work in progress shows that troposphere covariance error models improve data analysis results. We expect to see stronger effects with higher data rates. Temperature modeling of delay errors may further reduce temporal correlations in the data.

Self-Informant Agreement in Well-Being Ratings: A Meta-Analysis

ERIC Educational Resources Information Center

Schneider, Leann; Schimmack, Ulrich

2009-01-01

A meta-analysis of published studies that reported correlations between self-ratings and informant ratings of well-being (life-satisfaction, happiness, positive affect, negative affect) was performed. The average self-informant correlation based on 44 independent samples and 81 correlations for a total of 8,897 participants was r = 0.42 [99%…

Analysis of Doppler radar windshear data

NASA Technical Reports Server (NTRS)

Williams, F.; Mckinney, P.; Ozmen, F.

1989-01-01

The objective of this analysis is to process Lincoln Laboratory Doppler radar data obtained during FLOWS testing at Huntsville, Alabama, in the summer of 1986, to characterize windshear events. The processing includes plotting velocity and F-factor profiles, histogram analysis to summarize statistics, and correlation analysis to demonstrate any correlation between different data fields.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Two-dimensional auto-correlation analysis and Fourier-transform analysis of second-harmonic-generation image for quantitative analysis of collagen fiber in human facial skin

NASA Astrophysics Data System (ADS)

Ogura, Yuki; Tanaka, Yuji; Hase, Eiji; Yamashita, Toyonobu; Yasui, Takeshi

2018-02-01

We compare two-dimensional auto-correlation (2D-AC) analysis and two-dimensional Fourier transform (2D-FT) for evaluation of age-dependent structural change of facial dermal collagen fibers caused by intrinsic aging and extrinsic photo-aging. The age-dependent structural change of collagen fibers for female subjects' cheek skin in their 20s, 40s, and 60s were more noticeably reflected in 2D-AC analysis than in 2D-FT analysis. Furthermore, 2D-AC analysis indicated significantly higher correlation with the skin elasticity measured by Cutometer® than 2D-AC analysis. 2D-AC analysis of SHG image has a high potential for quantitative evaluation of not only age-dependent structural change of collagen fibers but also skin elasticity.

[Relativity among starch quantity, polysaccharides content and total alkaloid content of Dendrobium loddigesii].

PubMed

Zhu, Hua; Teng, Jianbei; Cai, Yi; Liang, Jie; Zhu, Yilin; Wei, Tao

2011-12-01

To find out the relativity among starch quantity, polysaccharides content and total alkaloid content of Dendrobium loddigesii. Microscopy-counting process was applied to starch quantity statistics, sulfuric acid-anthrone colorimetry was used to assay polysaccharides content and bromocresol green colorimetry was used to assay alkaloid content. Pearson product moment correlation analysis, Kendall's rank correlation analysis and Spearman's concordance coefficient analysis were applied to study their relativity. Extremely significant positive correlation was found between starch quantity and polysaccharides content, and significant negative correlation between alkaloid content and starch quantity was discovered, as well was between alkaloid content and polysaccharides content.

Optical signal processing

NASA Technical Reports Server (NTRS)

Casasent, D.

1978-01-01

The article discusses several optical configurations used for signal processing. Electronic-to-optical transducers are outlined, noting fixed window transducers and moving window acousto-optic transducers. Folded spectrum techniques are considered, with reference to wideband RF signal analysis, fetal electroencephalogram analysis, engine vibration analysis, signal buried in noise, and spatial filtering. Various methods for radar signal processing are described, such as phased-array antennas, the optical processing of phased-array data, pulsed Doppler and FM radar systems, a multichannel one-dimensional optical correlator, correlations with long coded waveforms, and Doppler signal processing. Means for noncoherent optical signal processing are noted, including an optical correlator for speech recognition and a noncoherent optical correlator.

Revealing time bunching effect in single-molecule enzyme conformational dynamics.

PubMed

Lu, H Peter

2011-04-21

In this perspective, we focus our discussion on how the single-molecule spectroscopy and statistical analysis are able to reveal enzyme hidden properties, taking the study of T4 lysozyme as an example. Protein conformational fluctuations and dynamics play a crucial role in biomolecular functions, such as in enzymatic reactions. Single-molecule spectroscopy is a powerful approach to analyze protein conformational dynamics under physiological conditions, providing dynamic perspectives on a molecular-level understanding of protein structure-function mechanisms. Using single-molecule fluorescence spectroscopy, we have probed T4 lysozyme conformational motions under the hydrolysis reaction of a polysaccharide of E. coli B cell walls by monitoring the fluorescence resonant energy transfer (FRET) between a donor-acceptor probe pair tethered to T4 lysozyme domains involving open-close hinge-bending motions. Based on the single-molecule spectroscopic results, molecular dynamics simulation, a random walk model analysis, and a novel 2D statistical correlation analysis, we have revealed a time bunching effect in protein conformational motion dynamics that is critical to enzymatic functions. Bunching effect implies that conformational motion times tend to bunch in a finite and narrow time window. We show that convoluted multiple Poisson rate processes give rise to the bunching effect in the enzymatic reaction dynamics. Evidently, the bunching effect is likely common in protein conformational dynamics involving in conformation-gated protein functions. In this perspective, we will also discuss a new approach of 2D regional correlation analysis capable of analyzing fluctuation dynamics of complex multiple correlated and anti-correlated fluctuations under a non-correlated noise background. Using this new method, we are able to map out any defined segments along the fluctuation trajectories and determine whether they are correlated, anti-correlated, or non-correlated; after which, a cross correlation analysis can be applied for each specific segment to obtain a detailed fluctuation dynamics analysis.

Updating signal typing in voice: addition of type 4 signals.

PubMed

Sprecher, Alicia; Olszewski, Aleksandra; Jiang, Jack J; Zhang, Yu

2010-06-01

The addition of a fourth type of voice to Titze's voice classification scheme is proposed. This fourth voice type is characterized by primarily stochastic noise behavior and is therefore unsuitable for both perturbation and correlation dimension analysis. Forty voice samples were classified into the proposed four types using narrowband spectrograms. Acoustic, perceptual, and correlation dimension analyses were completed for all voice samples. Perturbation measures tended to increase with voice type. Based on reliability cutoffs, the type 1 and type 2 voices were considered suitable for perturbation analysis. Measures of unreliability were higher for type 3 and 4 voices. Correlation dimension analyses increased significantly with signal type as indicated by a one-way analysis of variance. Notably, correlation dimension analysis could not quantify the type 4 voices. The proposed fourth voice type represents a subset of voices dominated by noise behavior. Current measures capable of evaluating type 4 voices provide only qualitative data (spectrograms, perceptual analysis, and an infinite correlation dimension). Type 4 voices are highly complex and the development of objective measures capable of analyzing these voices remains a topic of future investigation.

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.

Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market.

PubMed

Kenett, Dror Y; Tumminello, Michele; Madi, Asaf; Gur-Gershgoren, Gitit; Mantegna, Rosario N; Ben-Jacob, Eshel

2010-12-20

What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001-2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market.

Market Correlation Structure Changes Around the Great Crash: A Random Matrix Theory Analysis of the Chinese Stock Market

NASA Astrophysics Data System (ADS)

Han, Rui-Qi; Xie, Wen-Jie; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.

The behaviour of share returns of football clubs: An econophysics approach

NASA Astrophysics Data System (ADS)

Ferreira, Paulo; Loures, Luís; Nunes, José Rato; Dionísio, Andreia

2017-04-01

Football is a sport that moves thousands of people and millions of euros. Since 1983, several clubs entered the stock markets with shares, and now twenty two clubs are listed in the Stoxx Football Index. In this study, we analyse the behaviour of the return rates of such shares, with Detrended Fluctuation Analysis and Detrended Cross-Correlation Analysis (and its correlation coefficient). With Detrended Fluctuation Analysis, we are able to observe that the shares of several clubs are far from the behaviour of a random walk, which is expected by the theory. Using Detrended Cross-Correlation Analysis, we calculate the cross correlations of clubs' returns with national indexes and then with the Stoxx Football Index. Although almost all of them are positive, they do not seem to be strong.

K-Fold Crossvalidation in Canonical Analysis.

ERIC Educational Resources Information Center

Liang, Kun-Hsia; And Others

1995-01-01

A computer-assisted, K-fold cross-validation technique is discussed in the framework of canonical correlation analysis of randomly generated data sets. Analysis results suggest that this technique can effectively reduce the contamination of canonical variates and canonical correlations by sample-specific variance components. (Author/SLD)

The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis.

PubMed

Chen, Lihua; Liu, Min; Bao, Jing; Xia, Yunbao; Zhang, Jiuquan; Zhang, Lin; Huang, Xuequan; Wang, Jian

2013-01-01

To perform a meta-analysis exploring the correlation between the apparent diffusion coefficient (ADC) and tumor cellularity in patients. We searched medical and scientific literature databases for studies discussing the correlation between the ADC and tumor cellularity in patients. Only studies that were published in English or Chinese prior to November 2012 were considered for inclusion. Summary correlation coefficient (r) values were extracted from each study, and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses were performed to investigate potential heterogeneity. Of 189 studies, 28 were included in the meta-analysis, comprising 729 patients. The pooled r for all studies was -0.57 (95% CI: -0.62, -0.52), indicating notable heterogeneity (P<0.001). After the sensitivity analysis, two studies were excluded, and the pooled r was -0.61 (95% CI: -0.66, -0.56) and was not significantly heterogeneous (P = 0.127). Regarding tumor type subgroup analysis, there were sufficient data to support a strong negative correlation between the ADC and cellularity for brain tumors. There was no notable evidence of publication bias. There is a strong negative correlation between the ADC and tumor cellularity in patients, particularly in the brain. However, larger, prospective studies are warranted to validate these findings in other cancer types.

Meta-Analysis of Correlations Revisited: Attempted Replication and Extension of Field's (2001) Simulation Studies

ERIC Educational Resources Information Center

Hafdahl, Adam R.; Williams, Michelle A.

2009-01-01

In 2 Monte Carlo studies of fixed- and random-effects meta-analysis for correlations, A. P. Field (2001) ostensibly evaluated Hedges-Olkin-Vevea Fisher-[zeta] and Schmidt-Hunter Pearson-r estimators and tests in 120 conditions. Some authors have cited those results as evidence not to meta-analyze Fisher-[zeta] correlations, especially with…

Correlation between Wavelength Dispersive X-ray Fluorescence (WDXRF) analysis of hardened concrete for chlorides vs. Atomic Absorption (AA) analysis in accordance with AASHTO T- 260; sampling and testing for chloride ion in concrete and concrete raw mater

DOT National Transportation Integrated Search

2014-04-01

A correlation between Wavelength Dispersive X-ray Fluorescence(WDXRF) analysis of Hardened : Concrete for Chlorides and Atomic Absorption (AA) analysis (current method AASHTO T-260, procedure B) has been : found and a new method of analysis has been ...

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Cross-correlations between crude oil and exchange markets for selected oil rich economies

NASA Astrophysics Data System (ADS)

Li, Jianfeng; Lu, Xinsheng; Zhou, Ying

2016-07-01

Using multifractal detrended cross-correlation analysis (MF-DCCA), this paper studies the cross-correlation behavior between crude oil market and five selected exchange rate markets. The dataset covers the period of January 1,1996-December 31,2014, and contains 4,633 observations for each of the series, including daily closing prices of crude oil, Australian Dollars, Canadian Dollars, Mexican Pesos, Russian Rubles, and South African Rand. Our empirical results obtained from cross-correlation statistic and cross-correlation coefficient have confirmed the existence of cross-correlations, and the MF-DCCA results have demonstrated a strong multifractality between cross-correlated crude oil market and exchange rate markets in both short term and long term. Using rolling window analysis, we have also found the persistent cross-correlations between the exchange rates and crude oil returns, and the cross-correlation scaling exponents exhibit volatility during some time periods due to its sensitivity to sudden events.

Systematic reviews: I. The correlation between laboratory tests on marginal quality and bond strength. II. The correlation between marginal quality and clinical outcome.

PubMed

Heintze, Siegward D

2007-01-01

An accepted principle in restorative dentistry states that restorations should be placed with the best marginal quality possible to avoid postoperative sensitivity, marginal discoloration, and secondary caries. Different laboratory methods claim to predict the clinical performance of restorative materials, for example, tests of bond strength and microleakage and gap analysis. The purpose of this review was twofold: (1) find studies that correlated the results of bond strength tests with either microleakage or gap analysis for the same materials, and (2) find studies that correlated the results of microleakage and/or gaps with the clinical parameters for the same materials. Furthermore, influencing factors on the results of the laboratory tests were reviewed and assessed. For the first question, searches for studies were conducted in the MEDLINE database and IADR/AADR abtracts online with specific search and inclusion criteria. The outcome for each study was assessed on the basis of the statistical test applied in the study, and finally the number of studies with or without correlation was compiled. For the second question, results of the quantitative marginal analysis of Class V restorations published by the University of Zürich with the same test protocol and prospective clinical trials were searched that investigated the same materials for at least 2 years in Class V cavities. Pearson correlation coefficients were calculated for pooled data of materials and clinical outcome parameters such as retention loss, marginal discoloration, marginal integrity, and secondary caries. For the correlation of dye penetration and clinical outcome, studies on Class V restorations published by the same research institute were searched in MEDLINE that examined the same adhesive systems as the selected clinical trials. For the correlation bond strength/microleakage, 30 studies were included into the review, and for the correlation bond strength/gap analysis 18 studies. For both topics, about 80% of the studies revealed that there was no correlation between the two methods. For the correlation quantitative marginal analysis/clinical outcome, data were compared to the clinical outcome of 11 selected clinical studies. In only 2 out of the 11 studies (18%) did the clinical outcome match the prognosis based on the laboratory tests; the remaining studies did not show any correlation. When pooling data on 20 adhesive systems, no correlation was found between the percentage of continuous margin of restorations placed in extracted premolars and the percentage of teeth that showed no retention loss in clinical studies, no discoloured margins, acceptable margins, or absence of secondary caries. With regard to the correlation of dye penetration and clinical studies, no sufficient number of studies was found that matched the inclusion criteria. However, literature data suggest that there is no correlation between microleakage data as measured in the laboratory and clinical parameters. The results of bond strength tests did not correlate with laboratory tests that evaluated the marginal seal of restorations such as microleakage or gap analysis. The quantitative marginal analysis of Class V fillings in the laboratory was unable to predict the performance of the same materials in vivo. Therefore, microleakage tests or the quantitative marginal analysis should be abandoned and research should focus on laboratory tests that are validated with regard to their ability to satisfactorily predict the clinical performance of restorative materials.

Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer.

PubMed

Rizzardi, Anthony E; Zhang, Xiaotun; Vogel, Rachel Isaksson; Kolb, Suzanne; Geybels, Milan S; Leung, Yuet-Kin; Henriksen, Jonathan C; Ho, Shuk-Mei; Kwak, Julianna; Stanford, Janet L; Schmechel, Stephen C

2016-07-11

Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-β2 (ERβ2). Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERβ2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy. We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERβ2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012). Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

The Infinitesimal Jackknife with Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

2012-01-01

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

Multifractal detrended cross-correlation analysis for two nonstationary signals.

PubMed

Zhou, Wei-Xing

2008-06-01

We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series.

Ontology-aided feature correlation for multi-modal urban sensing

NASA Astrophysics Data System (ADS)

Misra, Archan; Lantra, Zaman; Jayarajah, Kasthuri

2016-05-01

The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

Multifractal Detrended Cross-correlation Analysis of Market Clearing Price of electricity and SENSEX in India

NASA Astrophysics Data System (ADS)

Ghosh, Dipak; Dutta, Srimonti; Chakraborty, Sayantan

2015-09-01

This paper reports a study on the cross-correlation between the electric bid price and SENSEX using Multifractal Detrended Cross-correlation Analysis (MF-DXA). MF-DXA is a very rigorous and robust technique for assessment of cross-correction between two non-linear time series. The study reveals power law cross-correlation between Market Clearing Price (MCP) and SENSEX which suggests that a change in the value of one can create a subjective change in the value of the other.

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis

PubMed Central

Kim, Seong-Gil

2018-01-01

Background The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. Material/Methods This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. Results In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). Conclusions Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement. PMID:29760375

A new method for correlation analysis of compositional (environmental) data - a worked example.

PubMed

Reimann, C; Filzmoser, P; Hron, K; Kynčlová, P; Garrett, R G

2017-12-31

Most data in environmental sciences and geochemistry are compositional. Already the unit used to report the data (e.g., μg/l, mg/kg, wt%) implies that the analytical results for each element are not free to vary independently of the other measured variables. This is often neglected in statistical analysis, where a simple log-transformation of the single variables is insufficient to put the data into an acceptable geometry. This is also important for bivariate data analysis and for correlation analysis, for which the data need to be appropriately log-ratio transformed. A new approach based on the isometric log-ratio (ilr) transformation, leading to so-called symmetric coordinates, is presented here. Summarizing the correlations in a heat-map gives a powerful tool for bivariate data analysis. Here an application of the new method using a data set from a regional geochemical mapping project based on soil O and C horizon samples is demonstrated. Differences to 'classical' correlation analysis based on log-transformed data are highlighted. The fact that some expected strong positive correlations appear and remain unchanged even following a log-ratio transformation has probably led to the misconception that the special nature of compositional data can be ignored when working with trace elements. The example dataset is employed to demonstrate that using 'classical' correlation analysis and plotting XY diagrams, scatterplots, based on the original or simply log-transformed data can easily lead to severe misinterpretations of the relationships between elements. Copyright © 2017 Elsevier B.V. All rights reserved.

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis.

PubMed

Kim, Seong-Gil; Kim, Wan-Soo

2018-05-15

BACKGROUND The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. MATERIAL AND METHODS This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. RESULTS In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). CONCLUSIONS Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement.

Respiratory-phase domain analysis of heart rate variability can accurately estimate cardiac vagal activity during a mental arithmetic task.

PubMed

Kotani, Kiyoshi; Takamasu, Kiyoshi; Tachibana, Makoto

2007-01-01

The objectives of this paper were to present a method to extract the amplitude of RSA in the respiratory-phase domain, to compare that with subjective or objective indices of the MWL (mental workload), and to compare that with a conventional frequency analysis in terms of its accuracy during a mental arithmetic task. HRV (heart rate variability), ILV (instantaneous lung volume), and motion of the throat were measured under a mental arithmetic experiment and subjective and objective indices were also obtained. The amplitude of RSA was extracted in the respiratory-phase domain, and its correlation with the load level was compared with the results of the frequency domain analysis, which is the standard analysis of the HRV. The subjective and objective indices decreased as the load level increased, showing that the experimental protocol was appropriate. Then, the amplitude of RSA in the respiratory-phase domain also decreased with the increase in the load level. The results of the correlation analysis showed that the respiratory-phase domain analysis has higher negative correlations, -0.84 and -0.82, with the load level as determined by simple correlation and rank correlation, respectively, than does frequency analysis, for which the correlations were found to be -0.54 and -0.63, respectively. In addition, it was demonstrated that the proposed method could be applied to the short-term extraction of RSA amplitude. We proposed a simple and effective method to extract the amplitude of the respiratory sinus arrhythmia (RSA) in the respiratory-phase domain and the results show that this method can estimate cardiac vagal activity more accurately than frequency analysis.

Study of photon correlation techniques for processing of laser velocimeter signals

NASA Technical Reports Server (NTRS)

Mayo, W. T., Jr.

1977-01-01

The objective was to provide the theory and a system design for a new type of photon counting processor for low level dual scatter laser velocimeter (LV) signals which would be capable of both the first order measurements of mean flow and turbulence intensity and also the second order time statistics: cross correlation auto correlation, and related spectra. A general Poisson process model for low level LV signals and noise which is valid from the photon-resolved regime all the way to the limiting case of nonstationary Gaussian noise was used. Computer simulation algorithms and higher order statistical moment analysis of Poisson processes were derived and applied to the analysis of photon correlation techniques. A system design using a unique dual correlate and subtract frequency discriminator technique is postulated and analyzed. Expectation analysis indicates that the objective measurements are feasible.

Signatures of van der Waals binding: A coupling-constant scaling analysis

NASA Astrophysics Data System (ADS)

Jiao, Yang; Schröder, Elsebeth; Hyldgaard, Per

2018-02-01

The van der Waals (vdW) density functional (vdW-DF) method [Rep. Prog. Phys. 78, 066501 (2015), 10.1088/0034-4885/78/6/066501] describes dispersion or vdW binding by tracking the effects of an electrodynamic coupling among pairs of electrons and their associated exchange-correlation holes. This is done in a nonlocal-correlation energy term Ecnl, which permits density functional theory calculation in the Kohn-Sham scheme. However, to map the nature of vdW forces in a fully interacting materials system, it is necessary to also account for associated kinetic-correlation energy effects. Here, we present a coupling-constant scaling analysis, which permits us to compute the kinetic-correlation energy Tcnl that is specific to the vdW-DF account of nonlocal correlations. We thus provide a more complete spatially resolved analysis of the electrodynamical-coupling nature of nonlocal-correlation binding, including vdW attraction, in both covalently and noncovalently bonded systems. We find that kinetic-correlation energy effects play a significant role in the account of vdW or dispersion interactions among molecules. Furthermore, our mapping shows that the total nonlocal-correlation binding is concentrated to pockets in the sparse electron distribution located between the material fragments.

Functional network connectivity analysis based on partial correlation in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Zhang, Nan; Guan, Xiaoting; Zhang, Yumei; Li, Jingjing; Chen, Hongyan; Chen, Kewei; Fleisher, Adam; Yao, Li; Wu, Xia

2009-02-01

Functional network connectivity (FNC) measures the temporal dependency among the time courses of functional networks. However, the marginal correlation between two networks used in the classic FNC analysis approach doesn't separate the FNC from the direct/indirect effects of other networks. In this study, we proposed an alternative approach based on partial correlation to evaluate the FNC, since partial correlation based FNC can reveal the direct interaction between a pair of networks, removing dependencies or influences from others. Previous studies have demonstrated less task-specific activation and less rest-state activity in Alzheimer's disease (AD). We applied present approach to contrast FNC differences of resting state network (RSN) between AD and normal controls (NC). The fMRI data under resting condition were collected from 15 AD and 16 NC. FNC was calculated for each pair of six RSNs identified using Group ICA, thus resulting in 15 (2 out of 6) pairs for each subject. Partial correlation based FNC analysis indicated 6 pairs significant differences between groups, while marginal correlation only revealed 2 pairs (involved in the partial correlation results). Additionally, patients showed lower correlation than controls among most of the FNC differences. Our results provide new evidences for the disconnection hypothesis in AD.

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…

[Preliminary study on effective components of Tripterygium wilfordii for liver toxicity based on spectrum-effect correlation analysis].

PubMed

Zhao, Xiao-Mei; Pu, Shi-Biao; Zhao, Qing-Guo; Gong, Man; Wang, Jia-Bo; Ma, Zhi-Jie; Xiao, Xiao-He; Zhao, Kui-Jun

2016-08-01

In this paper, the spectrum-effect correlation analysis method was used to explore the main effective components of Tripterygium wilfordii for liver toxicity, and provide reference for promoting the quality control of T. wilfordii. Chinese medicine T.wilfordii was taken as the study object, and LC-Q-TOF-MS was used to characterize the chemical components in T. wilfordii samples from different areas, and their main components were initially identified after referring to the literature. With the normal human hepatocytes (LO2 cell line)as the carrier, acetaminophen as positive medicine, and cell inhibition rate as testing index, the simple correlation analysis and multivariate linear correlation analysis methods were used to screen the main components of T. wilfordii for liver toxicity. As a result, 10 kinds of main components were identified, and the spectrum-effect correlation analysis showed that triptolide may be the toxic component, which was consistent with previous results of traditional literature. Meanwhile it was found that tripterine and demethylzeylasteral may greatly contribute to liver toxicity in multivariate linear correlation analysis. T. wilfordii samples of different varieties or different origins showed large difference in quality, and the T. wilfordii from southwest China showed lower liver toxicity, while those from Hunan and Anhui province showed higher liver toxicity. This study will provide data support for further rational use of T. wilfordii and research on its liver toxicity ingredients. Copyright© by the Chinese Pharmaceutical Association.

Accurate Structural Correlations from Maximum Likelihood Superpositions

PubMed Central

Theobald, Douglas L; Wuttke, Deborah S

2008-01-01

The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology. PMID:18282091

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma

PubMed Central

Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-01-01

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADCmean, ADCmin, ADCmedian, and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADCmean, ADCmin, ADCmedian, P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading. PMID:29805759

[A cross-correlational analysis of the background neuronal pulse trains in surviving slices of the guinea pig neocortex].

PubMed

Bortnik, A T; Iakupova, L P

1991-01-01

Cross-correlation analysis of interdependence of the background spike activity was carried out for pairs of adjacent neurons simultaneously recorded in the incubated slices of the neocortex of guinea-pig. Statistical correlation of spike discharges was detected in 16 out of 26 recorded pairs of the neurons. Significant correlation was observed mainly in the range of +/- 100 ms from the null point. Cross-correlation had symmetric or asymmetric maxima up to 150 ms long and negative shifts up to 200 ms long. More complex positive-negative types of cross-correlations were also obtained. The data were compared to those known from other authors for the intact brain. The contribution of intrinsic intracortical interactions and extrinsic afferent influences in these correlations of activity is discussed.

HIV incidence and CDC's HIV prevention budget: an exploratory correlational analysis.

PubMed

Holtgrave, David R; Kates, Jennifer

2007-01-01

The central evaluative question about a national HIV prevention program is whether that program affects HIV incidence. Numerous factors may influence incidence, including public investment in HIV prevention. Few studies, however, have examined the relationship between public investment and the HIV epidemic in the United States. This 2006 exploratory analysis examined the period from 1978 through 2006 using a quantitative, lagged, correlational analysis to capture the relationship between national HIV incidence and Centers for Disease Control and Prevention's HIV prevention budget in the United States over time. The analyses suggest that early HIV incidence rose in advance of the nation's HIV prevention investment until the mid-1980s (1-year lag correlation, r=0.972, df=2, p <0.05). From that point on, it appears that the nation's investment in HIV prevention became a strong correlate of HIV incidence (1-year lag correlation, r=-0.905, df=18, p <0.05). This exploratory study provides correlational evidence of a relationship between U.S. HIV incidence and the federal HIV prevention budget over time, and calls for further analysis of the role of funding and other factors that may influence the direction of a nation's HIV epidemic.

An Analysis of Shoreline Change At Little Lagoon, Alabama

DTIC Science & Technology

2006-06-14

AN ANALYSIS OF SHORELINE CHANGE AT LITTLE LAGOON, ALABAMA By Glen R. Gibson THESIS...control number. 1. REPORT DATE 14 JUN 2006 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE An Analysis Of Shoreline Change At...correlation analysis conducted on the gulf shoreline and Little Lagoon’s southern shoreline showed that although weak overall correlation values

A cyber-event correlation framework and metrics

NASA Astrophysics Data System (ADS)

Kang, Myong H.; Mayfield, Terry

2003-08-01

In this paper, we propose a cyber-event fusion, correlation, and situation assessment framework that, when instantiated, will allow cyber defenders to better understand the local, regional, and global cyber-situation. This framework, with associated metrics, can be used to guide assessment of our existing cyber-defense capabilities, and to help evaluate the state of cyber-event correlation research and where we must focus our future cyber-event correlation research. The framework, based on the cyber-event gathering activities and analysis functions, consists of five operational steps, each of which provides a richer set of contextual information to support greater situational understanding. The first three steps are categorically depicted as increasingly richer and broader-scoped contexts achieved through correlation activity, while in the final two steps, these richer contexts are achieved through analytical activities (situation assessment, and threat analysis & prediction). Category 1 Correlation focuses on the detection of suspicious activities and the correlation of events from a single cyber-event source. Category 2 Correlation clusters the same or similar events from multiple detectors that are located at close proximity and prioritizes them. Finally, the events from different time periods and event sources at different location/regions are correlated at Category 3 to recognize the relationship among different events. This is the category that focuses on the detection of large-scale and coordinated attacks. The situation assessment step (Category 4) focuses on the assessment of cyber asset damage and the analysis of the impact on missions. The threat analysis and prediction step (Category 5) analyzes attacks based on attack traces and predicts the next steps. Metrics that can distinguish correlation and cyber-situation assessment tools for each category are also proposed.

[Correlation research on contents of podophyllotoxin and total lignans in Sinopodophyllum hexandrum and ecological factors].

PubMed

Li, Min; Zhong, Guo-yue; Wu, Ao-lin; Zhang, Shou-wen; Jiang, Wei; Liang, Jian

2015-05-01

To explore the correlation between the ecological factors and the contents of podophyllotoxin and total lignans in root and rhizome of Sinopodophyllum hexandrum, podophyllotoxin in 87 samples (from 5 provinces) was determined by HPLC and total lignans by UV. A correlation and regression analysis was made by software SPSS 16.0 in combination with ecological factors (terrain, soil and climate). The content determination results showed a great difference between podophyllotoxin and total lignans, attaining 1.001%-6.230% and 5.350%-16.34%, respective. The correlation and regression analysis by SPSS showed a positive linear correlation between their contents, strong positive correlation between their contents, latitude and annual average rainfall within the sampling area, weak negative correlation with pH value and organic material in soil, weaker and stronger positive correlations with soil potassium, weak negative correlation with slope and annual average temperature and weaker positive correlation between the podophyllotoxin content and soil potassium.

Multicenter study of quantitative computed tomography analysis using a computer-aided three-dimensional system in patients with idiopathic pulmonary fibrosis.

PubMed

Iwasawa, Tae; Kanauchi, Tetsu; Hoshi, Toshiko; Ogura, Takashi; Baba, Tomohisa; Gotoh, Toshiyuki; Oba, Mari S

2016-01-01

To evaluate the feasibility of automated quantitative analysis with a three-dimensional (3D) computer-aided system (i.e., Gaussian histogram normalized correlation, GHNC) of computed tomography (CT) images from different scanners. Each institution's review board approved the research protocol. Informed patient consent was not required. The participants in this multicenter prospective study were 80 patients (65 men, 15 women) with idiopathic pulmonary fibrosis. Their mean age was 70.6 years. Computed tomography (CT) images were obtained by four different scanners set at different exposures. We measured the extent of fibrosis using GHNC, and used Pearson's correlation analysis, Bland-Altman plots, and kappa analysis to directly compare the GHNC results with manual scoring by radiologists. Multiple linear regression analysis was performed to determine the association between the CT data and forced vital capacity (FVC). For each scanner, the extent of fibrosis as determined by GHNC was significantly correlated with the radiologists' score. In multivariate analysis, the extent of fibrosis as determined by GHNC was significantly correlated with FVC (p < 0.001). There was no significant difference between the results obtained using different CT scanners. Gaussian histogram normalized correlation was feasible, irrespective of the type of CT scanner used.

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results

PubMed Central

Morelli, Maria Sole; Giannoni, Alberto; Passino, Claudio; Landini, Luigi; Emdin, Michele; Vanello, Nicola

2016-01-01

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings. PMID:27809243

Multifractal Cross Wavelet Analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene

Complex systems are composed of mutually interacting components and the output values of these components usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, we find the empirical joint multifractality of MFXWT to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indices, and in pairs of index returns and volatilities we find an intriguing joint multifractal behavior. The tests on surrogate series also reveal that the cross correlation behavior, particularly the cross correlation with zero lag, is the main origin of cross multifractality.

The cross-correlation analysis of multi property of stock markets based on MM-DFA

NASA Astrophysics Data System (ADS)

Yang, Yujun; Li, Jianping; Yang, Yimei

2017-09-01

In this paper, we propose a new method called DH-MXA based on distribution histograms of Hurst surface and multiscale multifractal detrended fluctuation analysis. The method allows us to investigate the cross-correlation characteristics among multiple properties of different stock time series. It may provide a new way of measuring the nonlinearity of several signals. It also can provide a more stable and faithful description of cross-correlation of multiple properties of stocks. The DH-MXA helps us to present much richer information than multifractal detrented cross-correlation analysis and allows us to assess many universal and subtle cross-correlation characteristics of stock markets. We show DH-MXA by selecting four artificial data sets and five properties of four stock time series from different countries. The results show that our proposed method can be adapted to investigate the cross-correlation of stock markets. In general, the American stock markets are more mature and less volatile than the Chinese stock markets.

Circulating leptin level in rheumatoid arthritis and its correlation with disease activity: a meta-analysis.

PubMed

Lee, Y H; Bae, S-C

2016-12-01

This study aimed to evaluate the relationship between the circulating serum leptin level and rheumatoid arthritis (RA) and to establish a correlation between serum leptin levels and RA activity. We searched the PUBMED, EMBASE, and Cochrane databases. A meta-analysis was performed, comparing the serum/plasma leptin levels in patients with RA and healthy controls. Correlation coefficients between serum leptin level and either disease activity score 28 (DAS28) or C‑reactive protein (CRP) in RA patients were also examined. Thirteen studies with a total of 648 RA patients and 426 controls were included in this meta-analysis. Circulating leptin level was significantly higher in the RA group than in the control group (SMD = 1.056, 95 % CI = 0.647-1.465, p = 4.2 × 10 -7 ). In addition, stratification by ethnicity showed a significantly elevated leptin level in the RA group in Caucasian, Turkish, and Arab populations (SMD = 0.813, 95 % CI = 0.137-1.490, p = 0.018, SMD = 0.981, 95 % CI = 0.307-1.655, p = 0.004, and SMD = 1.469, 95 % CI = 0.443-2.495, p = 0.005 respectively). A meta-analysis of correlation coefficients showed a small but significantly positive correlation between the circulating leptin level and either DAS28 (correlation coefficient = 0.275, 95 % CI = 0.076-0.452, p = 0.007) or CRP (correlation coefficient = 0.274, 95 % CI = 0.068-0.458, p = 0.010). Our meta-analysis demonstrated that the circulating leptin level is significantly higher in patients with RA and that a small but significantly positive correlation exists between leptin levels and RA activity.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets.

PubMed

Mainali, Kumar P; Bewick, Sharon; Thielen, Peter; Mehoke, Thomas; Breitwieser, Florian P; Paudel, Shishir; Adhikari, Arjun; Wolfe, Joshua; Slud, Eric V; Karig, David; Fagan, William F

2017-01-01

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson's correlation coefficient (r) and Jaccard's index (J)-two of the most common metrics for correlation analysis of presence-absence data-can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson's correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard's index of similarity (J) can yield improvements over Pearson's correlation coefficient. However, the standard null model for Jaccard's index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard's index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa.

Thermal Analysis and Correlation of the Mars Odyssey Spacecraft's Solar Array During Aerobraking Operations

NASA Technical Reports Server (NTRS)

Dec, John A.; Gasbarre, Joseph F.; George, Benjamin E.

2002-01-01

The Mars Odyssey spacecraft made use of multipass aerobraking to gradually reduce its orbit period from a highly elliptical insertion orbit to its final science orbit. Aerobraking operations provided an opportunity to apply advanced thermal analysis techniques to predict the temperature of the spacecraft's solar array for each drag pass. Odyssey telemetry data was used to correlate the thermal model. The thermal analysis was tightly coupled to the flight mechanics, aerodynamics, and atmospheric modeling efforts being performed during operations. Specifically, the thermal analysis predictions required a calculation of the spacecraft's velocity relative to the atmosphere, a prediction of the atmospheric density, and a prediction of the heat transfer coefficients due to aerodynamic heating. Temperature correlations were performed by comparing predicted temperatures of the thermocouples to the actual thermocouple readings from the spacecraft. Time histories of the spacecraft relative velocity, atmospheric density, and heat transfer coefficients, calculated using flight accelerometer and quaternion data, were used to calculate the aerodynamic heating. During aerobraking operations, the correlations were used to continually update the thermal model, thus increasing confidence in the predictions. This paper describes the thermal analysis that was performed and presents the correlations to the flight data.

Whole lesion histogram analysis of meningiomas derived from ADC values. Correlation with several cellularity parameters, proliferation index KI 67, nucleic content, and membrane permeability.

PubMed

Surov, Alexey; Hamerla, Gordian; Meyer, Hans Jonas; Winter, Karsten; Schob, Stefan; Fiedler, Eckhard

2018-09-01

To analyze several histopathological features and their possible correlations with whole lesion histogram analysis derived from ADC maps in meningioma. The retrospective study involved 36 patients with primary meningiomas. For every tumor, the following histogram analysis parameters of apparent diffusion coefficient (ADC) were calculated: ADC mean , ADC max , ADC min , ADC median , ADC mode , ADC percentiles: P10, P25, P75, P90, as well kurtosis, skewness, and entropy. All measures were performed by two radiologists. Proliferation index KI 67, minimal, maximal and mean cell count, total nucleic area, and expression of water channel aquaporin 4 (AQP4) were estimated. Spearman's correlation coefficient was used to analyze associations between investigated parameters. A perfect interobserver agreement for all ADC values (0.84-0.97) was identified. All ADC values correlated inversely with tumor cellularity with the strongest correlation between P10, P25 and mean cell count (-0.558). KI 67 correlated inversely with all ADC values except ADC min . ADC parameters did not correlate with total nucleic area. All ADC values correlated statistically significant with expression of AQP4. ADC histogram analysis is a valid method with an excellent interobserver agreement. Cellularity parameters and proliferation potential are associated with different ADC values. Membrane permeability may play a greater role for water diffusion than cell count and proliferation activity. Copyright © 2018 Elsevier Inc. All rights reserved.

Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2014-06-01

In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and issue.

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.

Mosaic organization of DNA nucleotides

NASA Technical Reports Server (NTRS)

Peng, C. K.; Buldyrev, S. V.; Havlin, S.; Simons, M.; Stanley, H. E.; Goldberger, A. L.

1994-01-01

Long-range power-law correlations have been reported recently for DNA sequences containing noncoding regions. We address the question of whether such correlations may be a trivial consequence of the known mosaic structure ("patchiness") of DNA. We analyze two classes of controls consisting of patchy nucleotide sequences generated by different algorithms--one without and one with long-range power-law correlations. Although both types of sequences are highly heterogenous, they are quantitatively distinguishable by an alternative fluctuation analysis method that differentiates local patchiness from long-range correlations. Application of this analysis to selected DNA sequences demonstrates that patchiness is not sufficient to account for long-range correlation properties.

Parallel auto-correlative statistics with VTK.

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

Pebay, Philippe Pierre; Bennett, Janine Camille

2013-08-01

This report summarizes existing statistical engines in VTK and presents both the serial and parallel auto-correlative statistics engines. It is a sequel to [PT08, BPRT09b, PT09, BPT09, PT10] which studied the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k-means, and order statistics engines. The ease of use of the new parallel auto-correlative statistics engine is illustrated by the means of C++ code snippets and algorithm verification is provided. This report justifies the design of the statistics engines with parallel scalability in mind, and provides scalability and speed-up analysis results for the autocorrelative statistics engine.

Performance analysis of MIMO wireless optical communication system with Q-ary PPM over correlated log-normal fading channel

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Lynette, Kibe; Cao, Minghua

2018-06-01

The performance of multiple-input multiple-output wireless optical communication systems that adopt Q-ary pulse position modulation over spatial correlated log-normal fading channel is analyzed in terms of its un-coded bit error rate and ergodic channel capacity. The analysis is based on the Wilkinson's method which approximates the distribution of a sum of correlated log-normal random variables to a log-normal random variable. The analytical and simulation results corroborate the increment of correlation coefficients among sub-channels lead to system performance degradation. Moreover, the receiver diversity has better performance in resistance of spatial correlation caused channel fading.

Hierarchical multivariate covariance analysis of metabolic connectivity.

PubMed

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Accuracy of the Parallel Analysis Procedure with Polychoric Correlations

ERIC Educational Resources Information Center

Cho, Sun-Joo; Li, Feiming; Bandalos, Deborah

2009-01-01

The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…

Development of Test-Analysis Models (TAM) for correlation of dynamic test and analysis results

NASA Technical Reports Server (NTRS)

Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul

1992-01-01

The primary objective of structural analysis of aerospace applications is to obtain a verified finite element model (FEM). The verified FEM can be used for loads analysis, evaluate structural modifications, or design control systems. Verification of the FEM is generally obtained as the result of correlating test and FEM models. A test analysis model (TAM) is very useful in the correlation process. A TAM is essentially a FEM reduced to the size of the test model, which attempts to preserve the dynamic characteristics of the original FEM in the analysis range of interest. Numerous methods for generating TAMs have been developed in the literature. The major emphasis of this paper is a description of the procedures necessary for creation of the TAM and the correlation of the reduced models with the FEM or the test results. Herein, three methods are discussed, namely Guyan, Improved Reduced System (IRS), and Hybrid. Also included are the procedures for performing these analyses using MSC/NASTRAN. Finally, application of the TAM process is demonstrated with an experimental test configuration of a ten bay cantilevered truss structure.

Parameter motivated mutual correlation analysis: Application to the study of currency exchange rates based on intermittency parameter and Hurst exponent

NASA Astrophysics Data System (ADS)

Cristescu, Constantin P.; Stan, Cristina; Scarlat, Eugen I.; Minea, Teofil; Cristescu, Cristina M.

2012-04-01

We present a novel method for the parameter oriented analysis of mutual correlation between independent time series or between equivalent structures such as ordered data sets. The proposed method is based on the sliding window technique, defines a new type of correlation measure and can be applied to time series from all domains of science and technology, experimental or simulated. A specific parameter that can characterize the time series is computed for each window and a cross correlation analysis is carried out on the set of values obtained for the time series under investigation. We apply this method to the study of some currency daily exchange rates from the point of view of the Hurst exponent and the intermittency parameter. Interesting correlation relationships are revealed and a tentative crisis prediction is presented.

Characterizing scaling properties of complex signals with missed data segments using the multifractal analysis.

PubMed

Pavlov, A N; Pavlova, O N; Abdurashitov, A S; Sindeeva, O A; Semyachkina-Glushkovskaya, O V; Kurths, J

2018-01-01

The scaling properties of complex processes may be highly influenced by the presence of various artifacts in experimental recordings. Their removal produces changes in the singularity spectra and the Hölder exponents as compared with the original artifacts-free data, and these changes are significantly different for positively correlated and anti-correlated signals. While signals with power-law correlations are nearly insensitive to the loss of significant parts of data, the removal of fragments of anti-correlated signals is more crucial for further data analysis. In this work, we study the ability of characterizing scaling features of chaotic and stochastic processes with distinct correlation properties using a wavelet-based multifractal analysis, and discuss differences between the effect of missed data for synchronous and asynchronous oscillatory regimes. We show that even an extreme data loss allows characterizing physiological processes such as the cerebral blood flow dynamics.

Principal regression analysis and the index leverage effect

NASA Astrophysics Data System (ADS)

Reigneron, Pierre-Alain; Allez, Romain; Bouchaud, Jean-Philippe

2011-09-01

We revisit the index leverage effect, that can be decomposed into a volatility effect and a correlation effect. We investigate the latter using a matrix regression analysis, that we call ‘Principal Regression Analysis' (PRA) and for which we provide some analytical (using Random Matrix Theory) and numerical benchmarks. We find that downward index trends increase the average correlation between stocks (as measured by the most negative eigenvalue of the conditional correlation matrix), and makes the market mode more uniform. Upward trends, on the other hand, also increase the average correlation between stocks but rotates the corresponding market mode away from uniformity. There are two time scales associated to these effects, a short one on the order of a month (20 trading days), and a longer time scale on the order of a year. We also find indications of a leverage effect for sectorial correlations as well, which reveals itself in the second and third mode of the PRA.

Characterizing scaling properties of complex signals with missed data segments using the multifractal analysis

NASA Astrophysics Data System (ADS)

Pavlov, A. N.; Pavlova, O. N.; Abdurashitov, A. S.; Sindeeva, O. A.; Semyachkina-Glushkovskaya, O. V.; Kurths, J.

2018-01-01

The scaling properties of complex processes may be highly influenced by the presence of various artifacts in experimental recordings. Their removal produces changes in the singularity spectra and the Hölder exponents as compared with the original artifacts-free data, and these changes are significantly different for positively correlated and anti-correlated signals. While signals with power-law correlations are nearly insensitive to the loss of significant parts of data, the removal of fragments of anti-correlated signals is more crucial for further data analysis. In this work, we study the ability of characterizing scaling features of chaotic and stochastic processes with distinct correlation properties using a wavelet-based multifractal analysis, and discuss differences between the effect of missed data for synchronous and asynchronous oscillatory regimes. We show that even an extreme data loss allows characterizing physiological processes such as the cerebral blood flow dynamics.

Advanced MRI in Acute Military TBI

DTIC Science & Technology

2015-11-01

advanced MRI methods, DTI and resting-state fMRI correlation analysis, in military TBI patients acutely after injury and correlate findings with TBI...14 4 Introduction The objective of the project was to test two advanced MRI methods, DTI and resting-state fMRI correlation analysis, in...of Concussion Exam (MACE )(44) were reviewed. This brief cognitive test 279 assesses orientation, immediate verbal memory , concentration, and short

Correlation of Spacecraft Mission and Project Costs

NASA Technical Reports Server (NTRS)

Swan, Christopher; Jarrett, Shawn

2007-01-01

A key component of any cost risk analysis is the level of correlation between individual elements of cost. This analysis supplements the available historical records with the cost estimates from the JPL Advanced Design Team. The costs from actual JPL flight projects are then used to validate the results, clearly indicating that, on average, the correlation between elements of cost is between 0.4 and 0.7.

Anti-correlation and multifractal features of Spain electricity spot market

NASA Astrophysics Data System (ADS)

Norouzzadeh, P.; Dullaert, W.; Rahmani, B.

2007-07-01

We use multifractal detrended fluctuation analysis (MF-DFA) to numerically investigate correlation, persistence, multifractal properties and scaling behavior of the hourly spot prices for the Spain electricity exchange-Compania O Peradora del Mercado de Electricidad (OMEL). Through multifractal analysis, fluctuations behavior, the scaling exponents and generalized Hurst exponents are studied. Moreover, contribution of fat-tailed probability distributions and nonlinear temporal correlations to multifractality is studied.

Cross-Linguistic Transfer of Oral Language, Decoding, Phonological Awareness and Reading Comprehension: A Meta-Analysis of the Correlational Evidence

ERIC Educational Resources Information Center

Melby-Lervag, Monica; Lervag, Arne

2011-01-01

We present a meta-analysis of cross-linguistic transfer of oral language (vocabulary and listening comprehension), phonology (decoding and phonological awareness) and reading comprehension. Our findings show a small meta-correlation between first (L1) and second (L2) oral language and a moderate to large correlation between L1 and L2 phonological…

PCAN: Probabilistic Correlation Analysis of Two Non-normal Data Sets

PubMed Central

Zoh, Roger S.; Mallick, Bani; Ivanov, Ivan; Baladandayuthapani, Veera; Manyam, Ganiraju; Chapkin, Robert S.; Lampe, Johanna W.; Carroll, Raymond J.

2016-01-01

Summary Most cancer research now involves one or more assays profiling various biological molecules, e.g., messenger RNA and micro RNA, in samples collected on the same individuals. The main interest with these genomic data sets lies in the identification of a subset of features that are active in explaining the dependence between platforms. To quantify the strength of the dependency between two variables, correlation is often preferred. However, expression data obtained from next-generation sequencing platforms are integer with very low counts for some important features. In this case, the sample Pearson correlation is not a valid estimate of the true correlation matrix, because the sample correlation estimate between two features/variables with low counts will often be close to zero, even when the natural parameters of the Poisson distribution are, in actuality, highly correlated. We propose a model-based approach to correlation estimation between two non-normal data sets, via a method we call Probabilistic Correlations ANalysis, or PCAN. PCAN takes into consideration the distributional assumption about both data sets and suggests that correlations estimated at the model natural parameter level are more appropriate than correlations estimated directly on the observed data. We demonstrate through a simulation study that PCAN outperforms other standard approaches in estimating the true correlation between the natural parameters. We then apply PCAN to the joint analysis of a microRNA (miRNA) and a messenger RNA (mRNA) expression data set from a squamous cell lung cancer study, finding a large number of negative correlation pairs when compared to the standard approaches. PMID:27037601

PCAN: Probabilistic correlation analysis of two non-normal data sets.

PubMed

Zoh, Roger S; Mallick, Bani; Ivanov, Ivan; Baladandayuthapani, Veera; Manyam, Ganiraju; Chapkin, Robert S; Lampe, Johanna W; Carroll, Raymond J

2016-12-01

Most cancer research now involves one or more assays profiling various biological molecules, e.g., messenger RNA and micro RNA, in samples collected on the same individuals. The main interest with these genomic data sets lies in the identification of a subset of features that are active in explaining the dependence between platforms. To quantify the strength of the dependency between two variables, correlation is often preferred. However, expression data obtained from next-generation sequencing platforms are integer with very low counts for some important features. In this case, the sample Pearson correlation is not a valid estimate of the true correlation matrix, because the sample correlation estimate between two features/variables with low counts will often be close to zero, even when the natural parameters of the Poisson distribution are, in actuality, highly correlated. We propose a model-based approach to correlation estimation between two non-normal data sets, via a method we call Probabilistic Correlations ANalysis, or PCAN. PCAN takes into consideration the distributional assumption about both data sets and suggests that correlations estimated at the model natural parameter level are more appropriate than correlations estimated directly on the observed data. We demonstrate through a simulation study that PCAN outperforms other standard approaches in estimating the true correlation between the natural parameters. We then apply PCAN to the joint analysis of a microRNA (miRNA) and a messenger RNA (mRNA) expression data set from a squamous cell lung cancer study, finding a large number of negative correlation pairs when compared to the standard approaches. © 2016, The International Biometric Society.

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease

PubMed Central

Deng, Shengming; Wu, Zhifang; Wu, Yiwei; Zhang, Wei; Li, Jihui; Dai, Na

2017-01-01

The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of 18F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r-to-z transformation, correlation coefficient (r) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28) and exhibited a notable heterogeneity (I2 = 78.4%; P < 0.01). In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5) to −0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types. PMID:29097924

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease.

PubMed

Deng, Shengming; Wu, Zhifang; Wu, Yiwei; Zhang, Wei; Li, Jihui; Dai, Na; Zhang, Bin; Yan, Jianhua

2017-01-01

The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of 18 F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r -to- z transformation, correlation coefficient ( r ) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was -0.35 (95% CI: -0.42-0.28) and exhibited a notable heterogeneity ( I 2 = 78.4%; P < 0.01). In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from -0.12 (lymphoma, n = 5) to -0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.

Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

Validation of the Inventaire du Milieu Familial Questionnaire (French version of the Infant/Toddler HOME) into the Brazilian Portuguese language.

PubMed

Sudbrack, Simone; Barbosa, Fernanda P; Mattiello, Rita; Booij, Linda; Estorgato, Geovana R; Dutra, Moisés S; Assunção, Fabiana D de; Nunes, Magda L

2018-04-22

To validate the Brazilian Portuguese version of the Family Environment Assessment questionnaire (Inventaire du Milieu Familial). The validation process was carried out in two stages. First, translation and back-translation were performed, and in the second phase, the questionnaire was applied in 72 families of children between 0 and 24 months for the validation process. The tool consists of the following domains: mother's communication ability; behavior; organization of the physical and temporal environment; collection/quantity of toys; maternal attitude of constant attention toward her baby; diversification of stimuli; baby's behavior. The following was performed for the scale validation: 1 - content analysis (judgment); 2 - construct analysis (factorial analysis - Kaiser-Meyer-Olkin, Bartlett, and Pearson's correlation tests); 3 - criterion analysis (calculation of Cronbach's alpha coefficient, intraclass correlations, and split-half correlations). The mean age of the children was 9±6.7 months, and of these, 35 (48.6%) were males. Most correlations between items and domains were significant. In the factorial analysis of the scale, Kaiser-Meyer-Olkin values were 0.76, Bartlett's test showed a p-value<0.001, and correlation between items and domains showed a p-value<0.01. Regarding the validity, Cronbach's alpha was 0.92 (95% CI: 0.89-0.94). The intraclass correlation among the evaluators was 0.97 (0.96-0.98) and split-half correlations, r: 0.60, with p<0.01. The Portuguese version of the Inventaire du Milieu Familial showed good to excellent performance regarding the assessed psychometric properties. Copyright © 2018. Published by Elsevier Editora Ltda.

Analysis of Magnitude Correlations in a Self-Similar model of Seismicity

NASA Astrophysics Data System (ADS)

Zambrano, A.; Joern, D.

2017-12-01

A recent model of seismicity that incorporates a self-similar Omori-Utsu relation, which is used to describe the temporal evolution of earthquake triggering, has been shown to provide a more accurate description of seismicity in Southern California when compared to epidemic type aftershock sequence models. Forecasting of earthquakes is an active research area where one of the debated points is whether magnitude correlations of earthquakes exist within real world seismic data. Prior to this work, the analysis of magnitude correlations of the aforementioned self-similar model had not been addressed. Here we present statistical properties of the magnitude correlations for the self-similar model along with an analytical analysis of the branching ratio and criticality parameters.

Spatiotemporal image correlation analysis of blood flow in branched vessel networks of zebrafish embryos

NASA Astrophysics Data System (ADS)

Ceffa, Nicolo G.; Cesana, Ilaria; Collini, Maddalena; D'Alfonso, Laura; Carra, Silvia; Cotelli, Franco; Sironi, Laura; Chirico, Giuseppe

2017-10-01

Ramification of blood circulation is relevant in a number of physiological and pathological conditions. The oxygen exchange occurs largely in the capillary bed, and the cancer progression is closely linked to the angiogenesis around the tumor mass. Optical microscopy has made impressive improvements in in vivo imaging and dynamic studies based on correlation analysis of time stacks of images. Here, we develop and test advanced methods that allow mapping the flow fields in branched vessel networks at the resolution of 10 to 20 μm. The methods, based on the application of spatiotemporal image correlation spectroscopy and its extension to cross-correlation analysis, are applied here to the case of early stage embryos of zebrafish.

Moral distress and burnout syndrome: are there relationships between these phenomena in nursing workers?

PubMed

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; Silveira, Rosemary Silva da

2014-01-01

to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied.

Moral distress and Burnout syndrome: are there relationships between these phenomena in nursing workers?1

PubMed Central

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; da Silveira, Rosemary Silva

2014-01-01

Objective to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. Methods this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. Results the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. Conclusion the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied. PMID:24553701

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

Theoretical analysis of the correlation observed in fatigue crack growth rate parameters

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

Chay, S.C.; Liaw, P.K.

Fatigue crack growth rates have been found to follow the Paris-Erdogan rule, da/dN = C{sub o}({Delta}K){sup n}, for many steels, aluminum, nickel and copper alloys. The fatigue crack growth rate behavior in the Paris regime, thus, can be characterized by the parameters C{sub o} and n, which have been obtained for various materials. When n vs the logarithm of C{sub o} were plotted for various experimental results, a very definite linear relationship has been observed by many investigators, and questions have been raised as to the nature of this correlation. This paper presents a theoretical analysis that explains precisely whymore » such a linear correlation should exist between the two parameters, how strong the relationship should be, and how it can be predicted by analysis. This analysis proves that the source of such a correlation is of mathematical nature rather than physical.« less

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

A new approach for SSVEP detection using PARAFAC and canonical correlation analysis.

PubMed

Tello, Richard; Pouryazdian, Saeed; Ferreira, Andre; Beheshti, Soosan; Krishnan, Sridhar; Bastos, Teodiano

2015-01-01

This paper presents a new way for automatic detection of SSVEPs through correlation analysis between tensor models. 3-way EEG tensor of channel × frequency × time is decomposed into constituting factor matrices using PARAFAC model. PARAFAC analysis of EEG tensor enables us to decompose multichannel EEG into constituting temporal, spectral and spatial signatures. SSVEPs characterized with localized spectral and spatial signatures are then detected exploiting a correlation analysis between extracted signatures of the EEG tensor and the corresponding simulated signatures of all target SSVEP signals. The SSVEP that has the highest correlation is selected as the intended target. Two flickers blinking at 8 and 13 Hz were used as visual stimuli and the detection was performed based on data packets of 1 second without overlapping. Five subjects participated in the experiments and the highest classification rate of 83.34% was achieved, leading to the Information Transfer Rate (ITR) of 21.01 bits/min.

Combined magnetic and gravity analysis

NASA Technical Reports Server (NTRS)

Hinze, W. J.; Braile, L. W.; Chandler, V. W.; Mazella, F. E.

1975-01-01

Efforts are made to identify methods of decreasing magnetic interpretation ambiguity by combined gravity and magnetic analysis, to evaluate these techniques in a preliminary manner, to consider the geologic and geophysical implications of correlation, and to recommend a course of action to evaluate methods of correlating gravity and magnetic anomalies. The major thrust of the study was a search and review of the literature. The literature of geophysics, geology, geography, and statistics was searched for articles dealing with spatial correlation of independent variables. An annotated bibliography referencing the Germane articles and books is presented. The methods of combined gravity and magnetic analysis techniques are identified and reviewed. A more comprehensive evaluation of two types of techniques is presented. Internal correspondence of anomaly amplitudes is examined and a combined analysis is done utilizing Poisson's theorem. The geologic and geophysical implications of gravity and magnetic correlation based on both theoretical and empirical relationships are discussed.

The Secant Rate of Corrosion: Correlating Observations of the USS Arizona Submerged in Pearl Harbor

NASA Astrophysics Data System (ADS)

Johnson, Donald L.; DeAngelis, Robert J.; Medlin, Dana J.; Johnson, Jon E.; Carr, James D.; Conlin, David L.

2018-03-01

Contrary to previous linear projections of steel corrosion in seawater, analysis of an inert marker embedded in USS Arizona concretion since the 7 December 1941 attack on Pearl Harbor reveals evidence that the effective corrosion rate decreases with time. The secant rate of corrosion, or SRC correlation, derived from this discovery could have a significant impact on failure analysis investigations for concreted shipwrecks or underwater structures. The correlation yields a lower rate of metal thinning than predicted. Development of the correlation is described.

On the equivalence of the RTI and SVM approaches to time correlated analysis

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

Croft, S.; Favalli, A.; Henzlova, D.

2014-11-21

Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal [1,2]. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in [1] is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in [2]. Mathematically we could alsomore » use other numerical ways to extract the time correlated information from the histogram data including for example what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.« less

Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data

NASA Technical Reports Server (NTRS)

Romero-Wolf, A.; Jacobs, C. S.; Ratcliff, J. T.

2012-01-01

The standard VLBI analysis models the distribution of measurement noise as Gaussian. Because the price of recording bits is steadily decreasing, thermal errors will soon no longer dominate. As a result, it is expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become increasingly relevant for optimal analysis. We discuss the advantages of modeling the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen flow assumption pioneered by Treuhaft and Lanyi. We then apply these correlated noise spectra to the weighting of VLBI data analysis for two case studies: X/Ka-band global astrometry and Earth orientation. In both cases we see improved results when the analyses are weighted with correlated noise models vs. the standard uncorrelated models. The X/Ka astrometric scatter improved by approx.10% and the systematic Delta delta vs. delta slope decreased by approx. 50%. The TEMPO Earth orientation results improved by 17% in baseline transverse and 27% in baseline vertical.

The association between body mass index and severe biliary infections: a multivariate analysis.

PubMed

Stewart, Lygia; Griffiss, J McLeod; Jarvis, Gary A; Way, Lawrence W

2012-11-01

Obesity has been associated with worse infectious disease outcomes. It is a risk factor for cholesterol gallstones, but little is known about associations between body mass index (BMI) and biliary infections. We studied this using factors associated with biliary infections. A total of 427 patients with gallstones were studied. Gallstones, bile, and blood (as applicable) were cultured. Illness severity was classified as follows: none (no infection or inflammation), systemic inflammatory response syndrome (fever, leukocytosis), severe (abscess, cholangitis, empyema), or multi-organ dysfunction syndrome (bacteremia, hypotension, organ failure). Associations between BMI and biliary bacteria, bacteremia, gallstone type, and illness severity were examined using bivariate and multivariate analysis. BMI inversely correlated with pigment stones, biliary bacteria, bacteremia, and increased illness severity on bivariate and multivariate analysis. Obesity correlated with less severe biliary infections. BMI inversely correlated with pigment stones and biliary bacteria; multivariate analysis showed an independent correlation between lower BMI and illness severity. Most patients with severe biliary infections had a normal BMI, suggesting that obesity may be protective in biliary infections. This study examined the correlation between BMI and biliary infection severity. Published by Elsevier Inc.

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

PubMed

Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

2018-04-01

To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (p<0.05), with the exception of between K 10th , K 90th and histological grades. In contrast, significant negative correlations were observed between 25th, 50th percentiles and mean values of ADC and D, as well as ADC 10th , with tumour T stages (p< 0.05). Meanwhile, lower 75th and 90th percentiles of ADC and D values were also correlated inversely with nodal involvement (p< 0.05). K mean showed a relatively higher area under the curve (AUC) and higher specificity than other percentiles for differentiation of lesions with nodal involvement. DKI metrics with whole-tumour volume histogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

PubMed

Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-04-01

To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-05-04

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADC min , ADC median , ADC mode , P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADC mean , ADC min , ADC median , and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADC mean , ADC min , ADC median , P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading.

The use and misuse of statistical analyses. [in geophysics and space physics

NASA Technical Reports Server (NTRS)

Reiff, P. H.

1983-01-01

The statistical techniques most often used in space physics include Fourier analysis, linear correlation, auto- and cross-correlation, power spectral density, and superposed epoch analysis. Tests are presented which can evaluate the significance of the results obtained through each of these. Data presented without some form of error analysis are frequently useless, since they offer no way of assessing whether a bump on a spectrum or on a superposed epoch analysis is real or merely a statistical fluctuation. Among many of the published linear correlations, for instance, the uncertainty in the intercept and slope is not given, so that the significance of the fitted parameters cannot be assessed.

Correlation of finite-element structural dynamic analysis with measured free vibration characteristics for a full-scale helicopter fuselage

NASA Technical Reports Server (NTRS)

Kenigsberg, I. J.; Dean, M. W.; Malatino, R.

1974-01-01

The correlation achieved with each program provides the material for a discussion of modeling techniques developed for general application to finite-element dynamic analyses of helicopter airframes. Included are the selection of static and dynamic degrees of freedom, cockpit structural modeling, and the extent of flexible-frame modeling in the transmission support region and in the vicinity of large cut-outs. The sensitivity of predicted results to these modeling assumptions are discussed. Both the Sikorsky Finite-Element Airframe Vibration analysis Program (FRAN/Vibration Analysis) and the NASA Structural Analysis Program (NASTRAN) have been correlated with data taken in full-scale vibration tests of a modified CH-53A helicopter.

Study on power grid characteristics in summer based on Linear regression analysis

NASA Astrophysics Data System (ADS)

Tang, Jin-hui; Liu, You-fei; Liu, Juan; Liu, Qiang; Liu, Zhuan; Xu, Xi

2018-05-01

The correlation analysis of power load and temperature is the precondition and foundation for accurate load prediction, and a great deal of research has been made. This paper constructed the linear correlation model between temperature and power load, then the correlation of fault maintenance work orders with the power load is researched. Data details of Jiangxi province in 2017 summer such as temperature, power load, fault maintenance work orders were adopted in this paper to develop data analysis and mining. Linear regression models established in this paper will promote electricity load growth forecast, fault repair work order review, distribution network operation weakness analysis and other work to further deepen the refinement.

Performance of Modified Test Statistics in Covariance and Correlation Structure Analysis under Conditions of Multivariate Nonnormality.

ERIC Educational Resources Information Center

Fouladi, Rachel T.

2000-01-01

Provides an overview of standard and modified normal theory and asymptotically distribution-free covariance and correlation structure analysis techniques and details Monte Carlo simulation results on Type I and Type II error control. Demonstrates through the simulation that robustness and nonrobustness of structure analysis techniques vary as a…

Visual Skills and Chinese Reading Acquisition: A Meta-Analysis of Correlation Evidence

ERIC Educational Resources Information Center

Yang, Ling-Yan; Guo, Jian-Peng; Richman, Lynn C.; Schmidt, Frank L.; Gerken, Kathryn C.; Ding, Yi

2013-01-01

This paper used meta-analysis to synthesize the relation between visual skills and Chinese reading acquisition based on the empirical results from 34 studies published from 1991 to 2011. We obtained 234 correlation coefficients from 64 independent samples, with a total of 5,395 participants. The meta-analysis revealed that visual skills as a…

Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

NASA Astrophysics Data System (ADS)

Hsiao, Y. R.; Tsai, C.

2017-12-01

As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

Auto Correlation Analysis of Coda Waves from Local Earthquakes for Detecting Temporal Changes in Shallow Subsurface Structures: the 2011 Tohoku-Oki, Japan Earthquake

NASA Astrophysics Data System (ADS)

Nakahara, Hisashi

2015-02-01

For monitoring temporal changes in subsurface structures I propose to use auto correlation functions of coda waves from local earthquakes recorded at surface receivers, which probably contain more body waves than surface waves. Use of coda waves requires earthquakes resulting in decreased time resolution for monitoring. Nonetheless, it may be possible to monitor subsurface structures in sufficient time resolutions in regions with high seismicity. In studying the 2011 Tohoku-Oki, Japan earthquake (Mw 9.0), for which velocity changes have been previously reported, I try to validate the method. KiK-net stations in northern Honshu are used in this analysis. For each moderate earthquake normalized auto correlation functions of surface records are stacked with respect to time windows in the S-wave coda. Aligning the stacked, normalized auto correlation functions with time, I search for changes in phases arrival times. The phases at lag times of <1 s are studied because changes at shallow depths are focused. Temporal variations in the arrival times are measured at the stations based on the stretching method. Clear phase delays are found to be associated with the mainshock and to gradually recover with time. The amounts of the phase delays are 10 % on average with the maximum of about 50 % at some stations. The deconvolution analysis using surface and subsurface records at the same stations is conducted for validation. The results show the phase delays from the deconvolution analysis are slightly smaller than those from the auto correlation analysis, which implies that the phases on the auto correlations are caused by larger velocity changes at shallower depths. The auto correlation analysis seems to have an accuracy of about several percent, which is much larger than methods using earthquake doublets and borehole array data. So this analysis might be applicable in detecting larger changes. In spite of these disadvantages, this analysis is still attractive because it can be applied to many records on the surface in regions where no boreholes are available.

Relations among soil radon, environmental parameters, volcanic and seismic events at Mt. Etna (Italy)

NASA Astrophysics Data System (ADS)

Giammanco, S.; Ferrera, E.; Cannata, A.; Montalto, P.; Neri, M.

2013-12-01

From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol probe located on the upper NE flank of Mt. Etna volcano (Italy), close both to the Piano Provenzana fault and to the NE-Rift. Seismic, volcanological and radon data were analysed together with data on environmental parameters, such as air and soil temperature, barometric pressure, snow and rain fall. In order to find possible correlations among the above parameters, and hence to reveal possible anomalous trends in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-day time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-day moving averages showed that, similar to multivariate linear regression analysis, the summer period was characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allowed to study the relations among different signals either in the time or in the frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Using the above analysis, two periods were recognized when radon variations were significantly correlated with marked soil temperature changes and also with local seismic or volcanic activity. This allowed to produce two different physical models of soil gas transport that explain the observed anomalies. Our work suggests that in order to make an accurate analysis of the relations among different signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be the most effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.

Factorial Structure of the French Version of the Rosenberg Self-Esteem Scale among the Elderly

ERIC Educational Resources Information Center

Gana, Kamel; Alaphilippe, Daniel; Bailly, Nathalie

2005-01-01

Ten different confirmatory factor analysis models, including ones with correlated traits correlated methods, correlated traits correlated uniqueness, and correlated traits uncorrelated methods, were proposed to examine the factorial structure of the French version of the Rosenberg Self-Esteem Scale (Rosenberg, 1965). In line with previous studies…

Novel Assessment of Interstitial Lung Disease Using the "Computer-Aided Lung Informatics for Pathology Evaluation and Rating" (CALIPER) Software System in Idiopathic Inflammatory Myopathies.

PubMed

Ungprasert, Patompong; Wilton, Katelynn M; Ernste, Floranne C; Kalra, Sanjay; Crowson, Cynthia S; Rajagopalan, Srinivasan; Bartholmai, Brian J

2017-10-01

To evaluate the correlation between measurements from quantitative thoracic high-resolution CT (HRCT) analysis with "Computer-Aided Lung Informatics for Pathology Evaluation and Rating" (CALIPER) software and measurements from pulmonary function tests (PFTs) in patients with idiopathic inflammatory myopathies (IIM)-associated interstitial lung disease (ILD). A cohort of patients with IIM-associated ILD seen at Mayo Clinic was identified from medical record review. Retrospective analysis of HRCT data and PFTs at baseline and 1 year was performed. The abnormalities in HRCT were quantified using CALIPER software. A total of 110 patients were identified. At baseline, total interstitial abnormalities as measured by CALIPER, both by absolute volume and by percentage of total lung volume, had a significant negative correlation with diffusing capacity for carbon monoxide (DLCO), total lung capacity (TLC), and oxygen saturation. Analysis by subtype of interstitial abnormality revealed significant negative correlations between ground glass opacities (GGO) and reticular density (RD) with DLCO and TLC. At one year, changes of total interstitial abnormalities compared with baseline had a significant negative correlation with changes of TLC and oxygen saturation. A negative correlation between changes of total interstitial abnormalities and DLCO was also observed, but it was not statistically significant. Analysis by subtype of interstitial abnormality revealed negative correlations between changes of GGO and RD and changes of DLCO, TLC, and oxygen saturation, but most of the correlations did not achieve statistical significance. CALIPER measurements correlate well with functional measurements in patients with IIM-associated ILD.

Cavitation in liquid cryogens. 2: Hydrofoil

NASA Technical Reports Server (NTRS)

Hord, J.

1973-01-01

Boundary layer principles, along with two-phase concepts, are used to improve existing correlative theory for developed cavity data. Details concerning cavity instrumentation, data analysis, correlative techniques, and experimental and theoretical aspects of a cavitating hydrofoil are given. Both desinent and thermodynamic data, using liquid hydrogen and liquid nitrogen, are reported. The thermodynamic data indicated that stable thermodynamic equilibrium exists throughout the vaporous cryogen cavities. The improved correlative formulas were used to evaluate these data. A new correlating parameter based on consideration of mass limiting two-phase flow flux across the cavity interface, is proposed. This correlating parameter appears attractive for future correlative and predictive applications. Agreement between theory and experiment is discussed, and directions for future analysis are suggested. The front half of the cavities, developed on the hydrofoil, may be considered as parabolically shaped.

Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Nelson, P. I.

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

NASA Astrophysics Data System (ADS)

Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

2018-03-01

We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Development problem analysis of correlation leak detector’s software

NASA Astrophysics Data System (ADS)

Faerman, V. A.; Avramchuk, V. S.; Marukyan, V. M.

2018-05-01

In the article, the practical application and the structure of the correlation leak detectors’ software is studied and the task of its designing is analyzed. In the first part of the research paper, the expediency of the facilities development of correlation leak detectors for the following operating efficiency of public utilities exploitation is shown. The analysis of the functional structure of correlation leak detectors is conducted and its program software tasks are defined. In the second part of the research paper some development steps of the software package – requirement forming, program structure definition and software concept creation – are examined in the context of the usage experience of the hardware-software prototype of correlation leak detector.

Intracellular applications of fluorescence correlation spectroscopy: prospects for neuroscience.

PubMed

Kim, Sally A; Schwille, Petra

2003-10-01

Based on time-averaging fluctuation analysis of small fluorescent molecular ensembles in equilibrium, fluorescence correlation spectroscopy has recently been applied to investigate processes in the intracellular milieu. The exquisite sensitivity of fluorescence correlation spectroscopy provides access to a multitude of measurement parameters (rates of diffusion, local concentration, states of aggregation and molecular interactions) in real time with fast temporal and high spatial resolution. The introduction of dual-color cross-correlation, imaging, two-photon excitation, and coincidence analysis coupled with fluorescence correlation spectroscopy has expanded the utility of the technique to encompass a wide range of promising applications in living cells that may provide unprecedented insight into understanding the molecular mechanisms of intracellular neurobiological processes.

Asymmetric multiscale detrended fluctuation analysis of California electricity spot price

NASA Astrophysics Data System (ADS)

Fan, Qingju

2016-01-01

In this paper, we develop a new method called asymmetric multiscale detrended fluctuation analysis, which is an extension of asymmetric detrended fluctuation analysis (A-DFA) and can assess the asymmetry correlation properties of series with a variable scale range. We investigate the asymmetric correlations in California 1999-2000 power market after filtering some periodic trends by empirical mode decomposition (EMD). Our findings show the coexistence of symmetric and asymmetric correlations in the price series of 1999 and strong asymmetric correlations in 2000. What is more, we detect subtle correlation properties of the upward and downward price series for most larger scale intervals in 2000. Meanwhile, the fluctuations of Δα(s) (asymmetry) and | Δα(s) | (absolute asymmetry) are more significant in 2000 than that in 1999 for larger scale intervals, and they have similar characteristics for smaller scale intervals. We conclude that the strong asymmetry property and different correlation properties of upward and downward price series for larger scale intervals in 2000 have important implications on the collapse of California power market, and our findings shed a new light on the underlying mechanisms of power price.

[The relationship between Cognitive Emotion Regulation Questionnaire (CERQ) and depression, anxiety: Meta-analysis].

PubMed

Sakakibara, Ryota; Kitahara, Mizuho

2016-06-01

This study aimed to investigate the relations between CERQ and depression, and anxiety and also aimed to reveal the characteristics of a Japanese sample through meta-analysis. The results showed that self-blame, acceptance, rumination, catastrophizing, and blaming others had significantly positive correlations with both depression and anxiety, whereas positive refocusing, refocus on planning, positive reappraisal, and putting into perspective had significantly negative correlations with both variables. Moreover, when comparing the correlation coefficients of the Japanese samples and the combined value, correlations between depression and positive reappraisal were significantly larger than the combined value. On the other hand, regarding the correlation coefficients of depression and putting into perspective, the combined value was larger than the value of Japanese samples. In addition, compared to the combined value, the Japanese sample's positive correlation between anxiety and rumination, and negative correlation between anxiety and positive reappraisal were larger.

Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market

NASA Astrophysics Data System (ADS)

Sun, Xuelian; Liu, Zixian

2016-02-01

In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.

Speckle-correlation analysis of the microcapillary blood circulation in nail bed

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

Vilenskii, M A; Agafonov, D N; Zimnyakov, D A

2011-04-30

We present the results of the experimental studies of the possibility of monitoring the blood microcirculation in human finger nail bed with application of speckle-correlation analysis, based on estimating the contrast of time-averaged dynamic speckles. The hemodynamics at normal blood circulation and under conditions of partially suppressed blood circulation is analysed. A microscopic analysis is performed to visualise the structural changes in capillaries that are caused by suppressing blood circulation. The problems and prospects of speckle-correlation monitoring of the nail bed microhemodynamics under laboratory and clinical conditions are discussed. (optical technologies in biophysics and medicine)

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

Modal Test/Analysis Correlation of Space Station Structures Using Nonlinear Sensitivity

NASA Technical Reports Server (NTRS)

Gupta, Viney K.; Newell, James F.; Berke, Laszlo; Armand, Sasan

1992-01-01

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlation. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Modal test/analysis correlation of Space Station structures using nonlinear sensitivity

NASA Technical Reports Server (NTRS)

Gupta, Viney K.; Newell, James F.; Berke, Laszlo; Armand, Sasan

1992-01-01

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlations. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Correlation Analysis of Experimental Remote-Sensing Data and Models of Microwave Rough Sea-Surface Emission

NASA Astrophysics Data System (ADS)

Sazonov, D. S.

2017-12-01

A correlation analysis of the model calculations and experimental measurements of wind-speed sensitivity of a rough sea-surface microwave emission at a frequency of 37.5 GHz are presented. The field data used in the research were collected over 3 years in the summer and autumn periods at the oceanographic platform of the Marine Hydrophysical Institute, Russian Academy of Sciences (RAS). A hypothesis about a significant correlation between the model calculations and experimentally measured sea-surface emission ability caused by wind forcing was formulated and tested to reveal this correlation. An evaluation of the discrepancy between the model and experimental data has been performed by an analysis of residuals. Our studies have shown that among the selected models not a single one adequately describes the experimental data.

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.

Wavelet analysis for the study of the relations among soil radon anomalies, volcanic and seismic events: the case of Mt. Etna (Italy)

NASA Astrophysics Data System (ADS)

Ferrera, Elisabetta; Giammanco, Salvatore; Cannata, Andrea; Montalto, Placido

2013-04-01

From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol® probe located on the upper NE flank of Mt. Etna volcano, close either to the Piano Provenzana fault or to the NE-Rift. Seismic and volcanological data have been analyzed together with radon data. We also analyzed air and soil temperature, barometric pressure, snow and rain fall data. In order to find possible correlations among the above parameters, and hence to reveal possible anomalies in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-days time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-days moving averages showed that, similar to multivariate linear regression analysis, the summer period is characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allows to study the relations among different signals either in time or frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Our work suggests that in order to make an accurate analysis of the relations among distinct signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be very effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.

Statistical Development of Flood Frequency and Magnitude Equations for the Cosumnes and Mokelumne River Drainage Basins, Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Burns, R. G.; Meyer, R. W.; Cornwell, K.

2003-12-01

In-basin statistical relations allow for development of regional flood frequency and magnitude equations in the Cosumnes River and Mokelumne River drainage basins. Current equations were derived from data collected through 1975, and do not reflect newer data with some significant flooding. Physical basin characteristics (area, mean basin elevation, slope of longest reach, and mean annual precipitation) were correlated against predicted flood discharges for each of the 5, 10, 25, 50, 100, 200, and 500-year recurrence intervals in a multivariate analysis. Predicted maximum instantaneous flood discharges were determined using the PEAKFQ program with default settings, for 24 stream gages within the study area presumed not affected by flow management practices. For numerical comparisons, GIS-based methods using Spatial Analyst and the Arc Hydro Tools extension were applied to derive physical basin characteristics as predictor variables from a 30m digital elevation model (DEM) and a mean annual precipitation raster (PRISM). In a bivariate analysis, examination of Pearson correlation coefficients, F-statistic, and t & p thresholds show good correlation between area and flood discharges. Similar analyses show poor correlation for mean basin elevation, slope and precipitation, with flood discharge. Bivariate analysis suggests slope may not be an appropriate predictor term for use in the multivariate analysis. Precipitation and elevation correlate very well, demonstrating possible orographic effects. From the multivariate analysis, less than 6% of the variability in the correlation is not explained for flood recurrences up to 25 years. Longer term predictions up to 500 years accrue greater uncertainty with as much as 15% of the variability in the correlation left unexplained.

Principal component analysis-based pattern analysis of dose-volume histograms and influence on rectal toxicity.

PubMed

Söhn, Matthias; Alber, Markus; Yan, Di

2007-09-01

The variability of dose-volume histogram (DVH) shapes in a patient population can be quantified using principal component analysis (PCA). We applied this to rectal DVHs of prostate cancer patients and investigated the correlation of the PCA parameters with late bleeding. PCA was applied to the rectal wall DVHs of 262 patients, who had been treated with a four-field box, conformal adaptive radiotherapy technique. The correlated changes in the DVH pattern were revealed as "eigenmodes," which were ordered by their importance to represent data set variability. Each DVH is uniquely characterized by its principal components (PCs). The correlation of the first three PCs and chronic rectal bleeding of Grade 2 or greater was investigated with uni- and multivariate logistic regression analyses. Rectal wall DVHs in four-field conformal RT can primarily be represented by the first two or three PCs, which describe approximately 94% or 96% of the DVH shape variability, respectively. The first eigenmode models the total irradiated rectal volume; thus, PC1 correlates to the mean dose. Mode 2 describes the interpatient differences of the relative rectal volume in the two- or four-field overlap region. Mode 3 reveals correlations of volumes with intermediate doses ( approximately 40-45 Gy) and volumes with doses >70 Gy; thus, PC3 is associated with the maximal dose. According to univariate logistic regression analysis, only PC2 correlated significantly with toxicity. However, multivariate logistic regression analysis with the first two or three PCs revealed an increased probability of bleeding for DVHs with more than one large PC. PCA can reveal the correlation structure of DVHs for a patient population as imposed by the treatment technique and provide information about its relationship to toxicity. It proves useful for augmenting normal tissue complication probability modeling approaches.

Physiologic and laboratory correlates of depression, anxiety, and poor sleep in liver cirrhosis.

PubMed

Ko, Fang-Yuan; Yang, Albert C; Tsai, Shih-Jen; Zhou, Yang; Xu, Lie-Ming

2013-01-22

Studies have shown psychological distress in patients with cirrhosis, yet no studies have evaluated the laboratory and physiologic correlates of psychological symptoms in cirrhosis. This study therefore measured both biochemistry data and heart rate variability (HRV) analyses, and aimed to identify the physiologic correlates of depression, anxiety, and poor sleep in cirrhosis. A total of 125 patients with cirrhosis and 55 healthy subjects were recruited. Each subject was assessed through routine biochemistry, 5-minutes ECG monitoring, and psychological ratings of depression, anxiety, and sleep. HRV analysis were used to evaluate autonomic functions. The relationship between depression, sleep, and physiologic correlates was assessed using a multiple regression analysis and stepwise method, controlling for age, duration of illness, and severity of cirrhosis. Reduced vagal-related HRV was found in patients with severe liver cirrhosis. Severity of cirrhosis measured by the Child-Pugh score was not correlated with depression or anxiety, and only had a weak correlation with poor sleep. The psychological distress in cirrhosis such as depression, anxiety, and insomnia were correlated specifically to increased levels of aspartate aminotransferase (AST), increased ratios of low frequency to high frequency power, or reduced nonlinear properties of HRV (α1 exponent of detrended fluctuation analysis). Increased serum AST and abnormal autonomic nervous activities by HRV analysis were associated with psychological distress in cirrhosis. Because AST is an important mediator of inflammatory process, further research is needed to delineate the role of inflammation in the cirrhosis comorbid with depression.

Physiologic and laboratory correlates of depression, anxiety, and poor sleep in liver cirrhosis

PubMed Central

2013-01-01

Background Studies have shown psychological distress in patients with cirrhosis, yet no studies have evaluated the laboratory and physiologic correlates of psychological symptoms in cirrhosis. This study therefore measured both biochemistry data and heart rate variability (HRV) analyses, and aimed to identify the physiologic correlates of depression, anxiety, and poor sleep in cirrhosis. Methods A total of 125 patients with cirrhosis and 55 healthy subjects were recruited. Each subject was assessed through routine biochemistry, 5-minutes ECG monitoring, and psychological ratings of depression, anxiety, and sleep. HRV analysis were used to evaluate autonomic functions. The relationship between depression, sleep, and physiologic correlates was assessed using a multiple regression analysis and stepwise method, controlling for age, duration of illness, and severity of cirrhosis. Results Reduced vagal-related HRV was found in patients with severe liver cirrhosis. Severity of cirrhosis measured by the Child-Pugh score was not correlated with depression or anxiety, and only had a weak correlation with poor sleep. The psychological distress in cirrhosis such as depression, anxiety, and insomnia were correlated specifically to increased levels of aspartate aminotransferase (AST), increased ratios of low frequency to high frequency power, or reduced nonlinear properties of HRV (α1 exponent of detrended fluctuation analysis). Conclusions Increased serum AST and abnormal autonomic nervous activities by HRV analysis were associated with psychological distress in cirrhosis. Because AST is an important mediator of inflammatory process, further research is needed to delineate the role of inflammation in the cirrhosis comorbid with depression. PMID:23339829

Statistical correlations of crime with arrests

NASA Astrophysics Data System (ADS)

Kuelling, Albert C.

1997-01-01

Regression analysis shows that the overall crime rate correlates with the overall arrest rate. Violent crime only weakly correlates with the violent arrest rate, but strongly correlates with the property arrest rate. Contrary to common impressions, increasing arrest rates do not significantly increase loading on incarceration facilities.

Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series

NASA Astrophysics Data System (ADS)

Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.

2014-12-01

We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q<0 and greater than GHE when q>0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets

PubMed Central

Bewick, Sharon; Thielen, Peter; Mehoke, Thomas; Breitwieser, Florian P.; Paudel, Shishir; Adhikari, Arjun; Wolfe, Joshua; Slud, Eric V.; Karig, David; Fagan, William F.

2017-01-01

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson’s correlation coefficient (r) and Jaccard’s index (J)–two of the most common metrics for correlation analysis of presence-absence data–can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson’s correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard’s index of similarity (J) can yield improvements over Pearson’s correlation coefficient. However, the standard null model for Jaccard’s index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard’s index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa. PMID:29145425

Multifractal analysis of the Korean agricultural market

NASA Astrophysics Data System (ADS)

Kim, Hongseok; Oh, Gabjin; Kim, Seunghwan

2011-11-01

We have studied the long-term memory effects of the Korean agricultural market using the detrended fluctuation analysis (DFA) method. In general, the return time series of various financial data, including stock indices, foreign exchange rates, and commodity prices, are uncorrelated in time, while the volatility time series are strongly correlated. However, we found that the return time series of Korean agricultural commodity prices are anti-correlated in time, while the volatility time series are correlated. The n-point correlations of time series were also examined, and it was found that a multifractal structure exists in Korean agricultural market prices.

The Correlation of Active and Passive Microwave Outputs for the Skylab S-193 Sensor

NASA Technical Reports Server (NTRS)

Krishen, K.

1976-01-01

This paper presents the results of the correlation analysis of the Skylab S-193 13.9 GHz Radiometer/Scatterometer data. Computer analysis of the S-193 data shows more than 50 percent of the radiometer and scatterometer data are uncorrelated. The correlation coefficients computed for the data gathered over various ground scenes indicates the desirability of using both active and passive sensors for the determination of various Earth phenomena.

Three field tests of a gas filter correlation radiometer

NASA Technical Reports Server (NTRS)

Campbell, S. A.; Casas, J. C.; Condon, E. P.

1977-01-01

Test flights to remotely measure nonurban carbon monoxide (CO) concentrations by gas filter correlation radiometry are discussed. The inferred CO concentrations obtained through use of the Gas Filter Correlation Radiometer (GFCR) agreed with independent measurements obtained by gas chromatography air sample bottle analysis to within 20 percent. The equipment flown on board the aircraft, the flight test procedure, the gas chromatograph direct air sampling procedure, and the GFCR data analysis procedure are reported.

Sexual Harassment Retaliation Climate DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

exploratory factor analysis, and bivariate correlations (sample 1) 2) To determine the factor structure of the remaining (final) questions via...statistics, reliability analysis, exploratory factor analysis, and bivariate correlations of the prospective Sexual Harassment Retaliation Climate...reported by the survey requester). For information regarding the composition of sample, refer to Table 1. Table 1. Sample 1 Demographics n

Correlation between polar values and vector analysis.

PubMed

Naeser, K; Behrens, J K

1997-01-01

To evaluate the possible correlation between polar value and vector analysis assessment of surgically induced astigmatism. Department of Ophthalmology, Aalborg Sygehus Syd, Denmark. The correlation between polar values and vector analysis was evaluated by simple mathematical and optical methods using accepted principles of trigonometry and first-order optics. Vector analysis and polar values report different aspects of surgically induced astigmatism. Vector analysis describes the total astigmatic change, characterized by both astigmatic magnitude and direction, while the polar value method produces a single, reduced figure that reports flattening or steepening in preselected directions, usually the plane of the surgical meridian. There is a simple Pythagorean correlation between vector analysis and two polar values separated by an arch of 45 degrees. The polar value calculated in the surgical meridian indicates the power or the efficacy of the surgical procedure. The polar value calculated in a plane inclined 45 degrees to the surgical meridian indicates the degree of cylinder rotation induced by surgery. These two polar values can be used to obtain other relevant data such as magnitude, direction, and sphere of an induced cylinder. Consistent use of these methods will enable surgeons to control and in many cases reduce preoperative astigmatism.

Hierarchical multivariate covariance analysis of metabolic connectivity

PubMed Central

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-01-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI). PMID:25294129

Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

NASA Astrophysics Data System (ADS)

Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

2012-10-01

In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

On the use of two-time correlation functions for X-ray photon correlation spectroscopy data analysis.

PubMed

Bikondoa, Oier

2017-04-01

Multi-time correlation functions are especially well suited to study non-equilibrium processes. In particular, two-time correlation functions are widely used in X-ray photon correlation experiments on systems out of equilibrium. One-time correlations are often extracted from two-time correlation functions at different sample ages. However, this way of analysing two-time correlation functions is not unique. Here, two methods to analyse two-time correlation functions are scrutinized, and three illustrative examples are used to discuss the implications for the evaluation of the correlation times and functional shape of the correlations.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data

PubMed Central

Ying, Gui-shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-01-01

Purpose To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field data in the elderly. Results When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D, P=0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, P=0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller P-values, while analysis of the worse eye provided larger P-values than mixed effects models and marginal models. Conclusion In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. PMID:28102741

Cross-correlation earthquake precursors in the hydrogeochemical and geoacoustic signals for the Kamchatka peninsula

NASA Astrophysics Data System (ADS)

Ryabinin, Gennadiy; Gavrilov, Valeriy; Polyakov, Yuriy; Timashev, Serge

2012-06-01

We propose a new type of earthquake precursor based on the analysis of correlation dynamics between geophysical signals of different nature. The precursor is found using a two-parameter cross-correlation function introduced within the framework of flicker-noise spectroscopy, a general statistical physics approach to the analysis of time series. We consider an example of cross-correlation analysis for water salinity time series, an integral characteristic of the chemical composition of groundwater, and geoacoustic emissions recorded at the G-1 borehole on the Kamchatka peninsula in the time frame from 2001 to 2003, which is characterized by a sequence of three groups of significant seismic events. We found that cross-correlation precursors took place 27, 31, and 35 days ahead of the strongest earthquakes for each group of seismic events, respectively. At the same time, precursory anomalies in the signals themselves were observed only in the geoacoustic emissions for one group of earthquakes.

Impact of distal mutations on the network of coupled motions correlated to hydride transfer in dihydrofolate reductase.

PubMed

Wong, Kim F; Selzer, Tzvia; Benkovic, Stephen J; Hammes-Schiffer, Sharon

2005-05-10

A comprehensive analysis of the network of coupled motions correlated to hydride transfer in dihydrofolate reductase is presented. Hybrid quantum/classical molecular dynamics simulations are combined with a rank correlation analysis method to extract thermally averaged properties that vary along the collective reaction coordinate according to a prescribed target model. Coupled motions correlated to hydride transfer are identified throughout the enzyme. Calculations for wild-type dihydrofolate reductase and a triple mutant, along with the associated single and double mutants, indicate that each enzyme system samples a unique distribution of coupled motions correlated to hydride transfer. These coupled motions provide an explanation for the experimentally measured nonadditivity effects in the hydride transfer rates for these mutants. This analysis illustrates that mutations distal to the active site can introduce nonlocal structural perturbations and significantly impact the catalytic rate by altering the conformational motions of the entire enzyme and the probability of sampling conformations conducive to the catalyzed reaction.

Volatility and correlation-based systemic risk measures in the US market

NASA Astrophysics Data System (ADS)

Civitarese, Jamil

2016-10-01

This paper deals with the problem of how to use simple systemic risk measures to assess portfolio risk characteristics. Using three simple examples taken from previous literature, one based on raw and partial correlations, another based on the eigenvalue decomposition of the covariance matrix and the last one based on an eigenvalue entropy, a Granger-causation analysis revealed some of them are not always a good measure of risk in the S&P 500 and in the VIX. The measures selected do not Granger-cause the VIX index in all windows selected; therefore, in the sense of risk as volatility, the indicators are not always suitable. Nevertheless, their results towards returns are similar to previous works that accept them. A deeper analysis has shown that any symmetric measure based on eigenvalue decomposition of correlation matrices, however, is not useful as a measure of "correlation" risk. The empirical counterpart analysis of this proposition stated that negative correlations are usually small and, therefore, do not heavily distort the behavior of the indicator.

Joint Blind Source Separation by Multi-set Canonical Correlation Analysis

PubMed Central

Li, Yi-Ou; Adalı, Tülay; Wang, Wei; Calhoun, Vince D

2009-01-01

In this work, we introduce a simple and effective scheme to achieve joint blind source separation (BSS) of multiple datasets using multi-set canonical correlation analysis (M-CCA) [1]. We first propose a generative model of joint BSS based on the correlation of latent sources within and between datasets. We specify source separability conditions, and show that, when the conditions are satisfied, the group of corresponding sources from each dataset can be jointly extracted by M-CCA through maximization of correlation among the extracted sources. We compare source separation performance of the M-CCA scheme with other joint BSS methods and demonstrate the superior performance of the M-CCA scheme in achieving joint BSS for a large number of datasets, group of corresponding sources with heterogeneous correlation values, and complex-valued sources with circular and non-circular distributions. We apply M-CCA to analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects and show its utility in estimating meaningful brain activations from a visuomotor task. PMID:20221319

Multiscale multifractal detrended cross-correlation analysis of financial time series

NASA Astrophysics Data System (ADS)

Shi, Wenbin; Shang, Pengjian; Wang, Jing; Lin, Aijing

2014-06-01

In this paper, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). The method allows us to extend the description of the cross-correlation properties between two time series. MM-DCCA may provide new ways of measuring the nonlinearity of two signals, and it helps to present much richer information than multifractal detrended cross-correlation analysis (MF-DCCA) by sweeping all the range of scale at which the multifractal structures of complex system are discussed. Moreover, to illustrate the advantages of this approach we make use of the MM-DCCA to analyze the cross-correlation properties between financial time series. We show that this new method can be adapted to investigate stock markets under investigation. It can provide a more faithful and more interpretable description of the dynamic mechanism between financial time series than traditional MF-DCCA. We also propose to reduce the scale ranges to analyze short time series, and some inherent properties which remain hidden when a wide range is used may exhibit perfectly in this way.

Cross-correlations and influence in world gold markets

NASA Astrophysics Data System (ADS)

Lin, Min; Wang, Gang-Jin; Xie, Chi; Stanley, H. Eugene

2018-01-01

Using the detrended cross-correlation analysis (DCCA) coefficient and the detrended partial cross-correlation analysis (DPCCA) coefficient, we investigate cross-correlations and net cross-correlations among five major world gold markets (London, New York, Shanghai, Tokyo, and Mumbai) at different time scales. We propose multiscale influence measures for examining the influence of individual markets on other markets and on the entire system. We find (i) that the cross-correlations, net cross-correlations, and net influences among the five gold markets vary across time scales, (ii) that the cross-market correlation between London and New York at each time scale is intense and inherent, meaning that the influence of other gold markets on the London-New York market is negligible, (iii) that the remaining cross-market correlations (i.e., those other than London-New York) are greatly affected by other gold markets, and (iv) that the London gold market significantly affects the other four gold markets and dominates the world-wide gold market. Our multiscale findings give market participants and market regulators new information on cross-market linkages in the world-wide gold market.

Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.

PubMed

Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino

2017-01-10

In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.

Estimation of stature from sternal lengths. A correlation meta-analysis.

PubMed

Yammine, Kaissar; Assi, Chahine

2017-01-01

Methods based on the positive linear relationship existing between stature and long bones are most commonly used to estimate living stature in forensic anthropology. The length of the sternum and its parts has been advanced as a plausible alternative to estimate stature when such long bones are missing or damaged. This meta-analysis aims to quantify evidence on the correlation between the sternum/sternal parts length and stature. Nine studies were included with 1118 sternal bones. Analyses showed that the length of the meso-sternum (manubrium + body) yielded the best correlation with stature; 53.5% and 55.42% for men and women, respectively. The second best variable is the total sternal length with correlations of 44.3% and 55% for men and women, respectively. Subgroup analysis of autopsy studies demonstrated even a higher correlation of 58.2% for the meso-sternal length. Manubrium and body lengths showed the least correlation values. Except for the body length, females exhibit a better correlation than man between all other sternal lengths and stature. While the meso-sternal length is found to be the most correlated variable with stature, all sternal lengths are to be considered with caution when estimating stature. The relatively low values of the weighted correlation results should raise the question of reliability and limit the use of sternal length when long bones are available. Future research using larger samples from different populations and taking into account the fusion status of the sternum are needed.

Bayesian Correlation Analysis for Sequence Count Data

PubMed Central

Lau, Nelson; Perkins, Theodore J.

2016-01-01

Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities’ measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low—especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities’ signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset. PMID:27701449

[Tobacco quality analysis of industrial classification of different years using near-infrared (NIR) spectrum].

PubMed

Wang, Yi; Xiang, Ma; Wen, Ya-Dong; Yu, Chun-Xia; Wang, Luo-Ping; Zhao, Long-Lian; Li, Jun-Hui

2012-11-01

In this study, tobacco quality analysis of main Industrial classification of different years was carried out applying spectrum projection and correlation methods. The group of data was near-infrared (NIR) spectrum from Hongta Tobacco (Group) Co., Ltd. 5730 tobacco leaf Industrial classification samples from Yuxi in Yunnan province from 2007 to 2010 year were collected using near infrared spectroscopy, which from different parts and colors and all belong to tobacco varieties of HONGDA. The conclusion showed that, when the samples were divided to two part by the ratio of 2:1 randomly as analysis and verification sets in the same year, the verification set corresponded with the analysis set applying spectrum projection because their correlation coefficients were above 0.98. The correlation coefficients between two different years applying spectrum projection were above 0.97. The highest correlation coefficient was the one between 2008 and 2009 year and the lowest correlation coefficient was the one between 2007 and 2010 year. At the same time, The study discussed a method to get the quantitative similarity values of different industrial classification samples. The similarity and consistency values were instructive in combination and replacement of tobacco leaf blending.

Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study

PubMed Central

Brawanski, Alexander

2017-01-01

Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data. PMID:28255331

Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study.

PubMed

Proescholdt, Martin A; Faltermeier, Rupert; Bele, Sylvia; Brawanski, Alexander

2017-01-01

Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults.

PubMed

Azcárate, T; Mendoza, B

2017-09-01

We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults

NASA Astrophysics Data System (ADS)

Azcárate, T.; Mendoza, B.

2017-09-01

We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

Quantifying the correlation between photoplethysmography and laser Doppler flowmetry microvascular low-frequency oscillations

NASA Astrophysics Data System (ADS)

Mizeva, Irina; Di Maria, Costanzo; Frick, Peter; Podtaev, Sergey; Allen, John

2015-03-01

Photoplethysmography (PPG) and laser Doppler flowmetry (LDF) are two recognized optical techniques that can track low-frequency perfusion changes in microcirculation. The aim of this study was to determine, in healthy subjects, the correlation between the techniques for specific low-frequency bands previously defined for microcirculation. Twelve healthy male subjects (age range 18 to 50 years) were studied, with PPG and LDF signals recorded for 20 min from their right and left index (PPG) and middle (LDF) fingers. Wavelet analysis comprised dividing the low-frequency integral wavelet spectrum (IWS) into five established physiological bands relating to cardiac, respiratory, myogenic, neurogenic, and endothelial activities. The correlation between PPG and LDF was quantified using wavelet correlation analysis and Spearman correlation analysis of the median IWS amplitude. The median wavelet correlation between signals (right-left side average) was 0.45 (cardiac), 0.49 (respiratory), 0.86 (myogenic), 0.91 (neurogenic), and 0.91 (endothelial). The correlation of IWS amplitude values (right-left side average) was statistically significant for the cardiac (ρ=0.64, p<0.05) and endothelial (ρ=0.62, p<0.05) bands. This pilot study has shown good correlation between PPG and LDF for specific physiological frequency bands. In particular, the results suggest that PPG has the potential to be a low-cost replacement for LDF for endothelial activity assessments.

Global Terrestrial Water Storage Changes and Connections to ENSO Events

NASA Astrophysics Data System (ADS)

Ni, Shengnan; Chen, Jianli; Wilson, Clark R.; Li, Jin; Hu, Xiaogong; Fu, Rong

2018-01-01

Improved data quality of extended record of the Gravity Recovery and Climate Experiment (GRACE) satellite gravity solutions enables better understanding of terrestrial water storage (TWS) variations. Connections of TWS and climate change are critical to investigate regional and global water cycles. In this study, we provide a comprehensive analysis of global connections between interannual TWS changes and El Niño Southern Oscillation (ENSO) events, using multiple sources of data, including GRACE measurements, land surface model (LSM) predictions and precipitation observations. We use cross-correlation and coherence spectrum analysis to examine global connections between interannual TWS changes and the Niño 3.4 index, and select four river basins (Amazon, Orinoco, Colorado, and Lena) for more detailed analysis. The results indicate that interannual TWS changes are strongly correlated with ENSO over much of the globe, with maximum cross-correlation coefficients up to 0.70, well above the 95% significance level ( 0.29) derived by the Monte Carlo experiments. The strongest correlations are found in tropical and subtropical regions, especially in the Amazon, Orinoco, and La Plata basins. While both GRACE and LSM TWS estimates show reasonably good correlations with ENSO and generally consistent spatial correlation patterns, notably higher correlations are found between GRACE TWS and ENSO. The existence of significant correlations in middle-high latitudes shows the large-scale impact of ENSO on the global water cycle.

Correlation of gingival thickness with gingival width, probing depth, and papillary fill in maxillary anterior teeth in students of a dental college in Navi Mumbai

PubMed Central

Singh, Jyotsna; Rathod, Varsha J.; Rao, Prajakta R.; Patil, Aardra A.; Langade, Deepak G.; Singh, Roshan K.

2016-01-01

Context: The gingival biotype is of utmost importance for esthetics and biologic function. Anatomical characteristic of periodontium such as gingival thickness (GT), width of keratinized gingiva, and alveolar bone morphology will determine the behavior of periodontium when subjected to physical, chemical, or bacterial insult or during therapeutic procedure. Aims: The aim of this study was to correlate the GT with gingival width (GW), probing depth (PD), and papillary fill (PF) in relation to maxillary anterior region. Settings and Design: Undergraduate dental students and interns from a dental college in Navi Mumbai were enrolled in the study according to the inclusion criteria. Six teeth per subject were assessed; a total of 2178 maxillary anterior teeth were examined. Subjects and Methods: Subjects were examined clinically for GT, width of keratinized gingiva, pocket depth, and interdental PF. The data obtained was tabulated and subjected to statistical analysis. Statistical Analysis Used: Spearman's correlation analysis test was performed to find the correlation of GT with GW, PD, and PF. Results: Positive correlation was found between GT and GW (r = 0.241). No significant correlation could be found between GT and PD; and between GT and PF. Conclusions: The present study confirmed a positive correlation between GT and GW. A weak negative correlation was found between GT and PD. PMID:27994424

Local and Global Correlations between Neurons in the Middle Temporal Area of Primate Visual Cortex.

PubMed

Solomon, Selina S; Chen, Spencer C; Morley, John W; Solomon, Samuel G

2015-09-01

In humans and other primates, the analysis of visual motion includes populations of neurons in the middle-temporal (MT) area of visual cortex. Motion analysis will be constrained by the structure of neural correlations in these populations. Here, we use multi-electrode arrays to measure correlations in anesthetized marmoset, a New World monkey where area MT lies exposed on the cortical surface. We measured correlations in the spike count between pairs of neurons and within populations of neurons, for moving dot fields and moving gratings. Correlations were weaker in area MT than in area V1. The magnitude of correlations in area MT diminished with distance between receptive fields, and difference in preferred direction. Correlations during presentation of moving gratings were stronger than those during presentation of moving dot fields, extended further across cortex, and were less dependent on the functional properties of neurons. Analysis of the timescales of correlation suggests presence of 2 mechanisms. A local mechanism, associated with near-synchronous spiking activity, is strongest in nearby neurons with similar direction preference and is independent of visual stimulus. A global mechanism, operating over larger spatial scales and longer timescales, is independent of direction preference and is modulated by the type of visual stimulus presented. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Analysis of noise-induced temporal correlations in neuronal spike sequences

NASA Astrophysics Data System (ADS)

Reinoso, José A.; Torrent, M. C.; Masoller, Cristina

2016-11-01

We investigate temporal correlations in sequences of noise-induced neuronal spikes, using a symbolic method of time-series analysis. We focus on the sequence of time-intervals between consecutive spikes (inter-spike-intervals, ISIs). The analysis method, known as ordinal analysis, transforms the ISI sequence into a sequence of ordinal patterns (OPs), which are defined in terms of the relative ordering of consecutive ISIs. The ISI sequences are obtained from extensive simulations of two neuron models (FitzHugh-Nagumo, FHN, and integrate-and-fire, IF), with correlated noise. We find that, as the noise strength increases, temporal order gradually emerges, revealed by the existence of more frequent ordinal patterns in the ISI sequence. While in the FHN model the most frequent OP depends on the noise strength, in the IF model it is independent of the noise strength. In both models, the correlation time of the noise affects the OP probabilities but does not modify the most probable pattern.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Correlations between brain structure and symptom dimensions of psychosis in schizophrenia, schizoaffective, and psychotic bipolar I disorders.

PubMed

Padmanabhan, Jaya L; Tandon, Neeraj; Haller, Chiara S; Mathew, Ian T; Eack, Shaun M; Clementz, Brett A; Pearlson, Godfrey D; Sweeney, John A; Tamminga, Carol A; Keshavan, Matcheri S

2015-01-01

Structural alterations may correlate with symptom severity in psychotic disorders, but the existing literature on this issue is heterogeneous. In addition, it is not known how cortical thickness and cortical surface area correlate with symptom dimensions of psychosis. Subjects included 455 individuals with schizophrenia, schizoaffective, or bipolar I disorders. Data were obtained as part of the Bipolar Schizophrenia Network for Intermediate Phenotypes study. Diagnosis was made through the Structured Clinical Interview for DSM-IV. Positive and negative symptom subscales were assessed using the Positive and Negative Syndrome Scale. Structural brain measurements were extracted from T1-weight structural MRIs using FreeSurfer v5.1 and were correlated with symptom subscales using partial correlations. Exploratory factor analysis was also used to identify factors among those regions correlating with symptom subscales. The positive symptom subscale correlated inversely with gray matter volume (GMV) and cortical thickness in frontal and temporal regions, whereas the negative symptom subscale correlated inversely with right frontal cortical surface area. Among regions correlating with the positive subscale, factor analysis identified four factors, including a temporal cortical thickness factor and frontal GMV factor. Among regions correlating with the negative subscale, factor analysis identified a frontal GMV-cortical surface area factor. There was no significant diagnosis by structure interactions with symptom severity. Structural measures correlate with positive and negative symptom severity in psychotic disorders. Cortical thickness demonstrated more associations with psychopathology than cortical surface area. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Effects of Helicity on Lagrangian and Eulerian Time Correlations in Turbulence

NASA Technical Reports Server (NTRS)

Rubinstein, Robert; Zhou, Ye

1998-01-01

Taylor series expansions of turbulent time correlation functions are applied to show that helicity influences Eulerian time correlations more strongly than Lagrangian time correlations: to second order in time, the helicity effect on Lagrangian time correlations vanishes, but the helicity effect on Eulerian time correlations is nonzero. Fourier analysis shows that the helicity effect on Eulerian time correlations is confined to the largest inertial range scales. Some implications for sound radiation by swirling flows are discussed.

Validation of a computerized algorithm to quantify fetal heart rate deceleration area.

PubMed

Gyllencreutz, Erika; Lu, Ke; Lindecrantz, Kaj; Lindqvist, Pelle G; Nordstrom, Lennart; Holzmann, Malin; Abtahi, Farhad

2018-05-16

Reliability in visual cardiotocography interpretation is unsatisfying, which has led to development of computerized cardiotocography. Computerized analysis is well established for antenatal fetal surveillance, but has yet not performed sufficiently during labor. We aimed to investigate the capacity of a new computerized algorithm compared to visual assessment in identifying intrapartum fetal heart rate baseline and decelerations. Three-hundred-and-twelve intrapartum cardiotocography tracings with variable decelerations were analysed by the computerized algorithm and visually examined by two observers, blinded to each other and the computer analysis. The width, depth and area of each deceleration was measured. Four cases (>100 variable decelerations) were subject to in-depth detailed analysis. The outcome measures were bias in seconds (width), beats per minute (depth), and beats (area) between computer and observers by using Bland-Altman analysis. Interobserver reliability was determined by calculating intraclass correlation and Spearman rank analysis. The analysis (312 cases) showed excellent intraclass correlation (0.89-0.95) and very strong Spearman correlation (0.82-0.91). The detailed analysis of > 100 decelerations in 4 cases revealed low bias between the computer and the two observers; width 1.4 and 1.4 seconds, depth 5.1 and 0.7 beats per minute, and area 0.1 and -1.7 beats. This was comparable to the bias between the two observers; 0.3 seconds (width), 4.4 beats per minute (depth), and 1.7 beats (area). The intraclass correlation was excellent (0.90-0.98). A novel computerized algorithm for intrapartum cardiotocography analysis is as accurate as gold standard visual assessment with high correlation and low bias. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Detrended Partial-Cross-Correlation Analysis: A New Method for Analyzing Correlations in Complex System

PubMed Central

Yuan, Naiming; Fu, Zuntao; Zhang, Huan; Piao, Lin; Xoplaki, Elena; Luterbacher, Juerg

2015-01-01

In this paper, a new method, detrended partial-cross-correlation analysis (DPCCA), is proposed. Based on detrended cross-correlation analysis (DCCA), this method is improved by including partial-correlation technique, which can be applied to quantify the relations of two non-stationary signals (with influences of other signals removed) on different time scales. We illustrate the advantages of this method by performing two numerical tests. Test I shows the advantages of DPCCA in handling non-stationary signals, while Test II reveals the “intrinsic” relations between two considered time series with potential influences of other unconsidered signals removed. To further show the utility of DPCCA in natural complex systems, we provide new evidence on the winter-time Pacific Decadal Oscillation (PDO) and the winter-time Nino3 Sea Surface Temperature Anomaly (Nino3-SSTA) affecting the Summer Rainfall over the middle-lower reaches of the Yangtze River (SRYR). By applying DPCCA, better significant correlations between SRYR and Nino3-SSTA on time scales of 6 ~ 8 years are found over the period 1951 ~ 2012, while significant correlations between SRYR and PDO on time scales of 35 years arise. With these physically explainable results, we have confidence that DPCCA is an useful method in addressing complex systems. PMID:25634341

In vitro burn model illustrating heat conduction patterns using compressed thermal papers.

PubMed

Lee, Jun Yong; Jung, Sung-No; Kwon, Ho

2015-01-01

To date, heat conduction from heat sources to tissue has been estimated by complex mathematical modeling. In the present study, we developed an intuitive in vitro skin burn model that illustrates heat conduction patterns inside the skin. This was composed of tightly compressed thermal papers with compression frames. Heat flow through the model left a trace by changing the color of thermal papers. These were digitized and three-dimensionally reconstituted to reproduce the heat conduction patterns in the skin. For standardization, we validated K91HG-CE thermal paper using a printout test and bivariate correlation analysis. We measured the papers' physical properties and calculated the estimated depth of heat conduction using Fourier's equation. Through contact burns of 5, 10, 15, 20, and 30 seconds on porcine skin and our burn model using a heated brass comb, and comparing the burn wound and heat conduction trace, we validated our model. The heat conduction pattern correlation analysis (intraclass correlation coefficient: 0.846, p < 0.001) and the heat conduction depth correlation analysis (intraclass correlation coefficient: 0.93, p < 0.001) showed statistically significant high correlations between the porcine burn wound and our model. Our model showed good correlation with porcine skin burn injury and replicated its heat conduction patterns. © 2014 by the Wound Healing Society.

Pelvic floor muscle strength of women consulting at the gynecology outpatient clinics and its correlation with sexual dysfunction: A cross-sectional study.

PubMed

Ozdemir, Filiz Ciledag; Pehlivan, Erkan; Melekoglu, Rauf

2017-01-01

To investigate the pelvic floor muscle strength of the women andevaluateits possible correlation with sexual dysfunction. In this cross-sectional type study, stratified clusters were used for the sampling method. Index of Female Sexual Function (IFSF) worksheetwere used for questions on sexual function. The pelvic floor muscle strength of subjects was assessed byperineometer. The chi-squared test, logistic regression and Pearson's correlation analysis were used for the statistical analysis. Four hundred thirty primiparous women, mean age 38.5 participated in this study. The average pelvic floor muscle strength value was found 31.4±9.6 cm H 2 O and the average Index of Female Sexual Function (IFSF) score was found 26.5±6.9. Parity (odds ratio OR=5.546) and age 40 or higher (OR=3.484) were found correlated with pelvic floor muscle weakness (p<0.05). The factors directly correlated with sexual dysfunction were found being overweight (OR=2.105) and age 40 or higher (OR=2.451) (p<0.05). Pearson's correlation analysis showed that there was a statistically significantlinear correlation between the muscular strength of the pelvic floor and sexual function (p=0.001). The results suggested subjects with decreased pelvic floor muscle strength value had higher frequency of sexual dysfunction.

Dynamic and Static Shape Test/Analysis Correlation of a 10 Meter Quadrant Solar Sail

NASA Technical Reports Server (NTRS)

Taleghani, Barmac K.; Lively, Peter S.; Gaspar, James L.; Murphy, David M.; Trautt, Thomas A.

2005-01-01

This paper describes finite element analyses and correlation studies to predict deformations and vibration modes/frequencies of a 10-meter quadrant solar sail system. Thin film membranes and booms were analyzed at the component and system-level. The objective was to verify the design and structural responses of the sail system and to mature solar sail technology to a TRL 5. The focus of this paper is in test/analysis correlation.

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment

PubMed Central

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis

2018-01-01

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks. PMID:29762505

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment.

PubMed

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Quiroga, Jabid

2018-05-15

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.

Analysis of the two-point velocity correlations in turbulent boundary layer flows

NASA Technical Reports Server (NTRS)

Oberlack, M.

1995-01-01

The general objective of the present work is to explore the use of Rapid Distortion Theory (RDT) in analysis of the two-point statistics of the log-layer. RDT is applicable only to unsteady flows where the non-linear turbulence-turbulence interaction can be neglected in comparison to linear turbulence-mean interactions. Here we propose to use RDT to examine the structure of the large energy-containing scales and their interaction with the mean flow in the log-region. The contents of the work are twofold: First, two-point analysis methods will be used to derive the law-of-the-wall for the special case of zero mean pressure gradient. The basic assumptions needed are one-dimensionality in the mean flow and homogeneity of the fluctuations. It will be shown that a formal solution of the two-point correlation equation can be obtained as a power series in the von Karman constant, known to be on the order of 0.4. In the second part, a detailed analysis of the two-point correlation function in the log-layer will be given. The fundamental set of equations and a functional relation for the two-point correlation function will be derived. An asymptotic expansion procedure will be used in the log-layer to match Kolmogorov's universal range and the one-point correlations to the inviscid outer region valid for large correlation distances.

Characteristics of angular cross correlations studied by light scattering from two-dimensional microsphere films

NASA Astrophysics Data System (ADS)

Schroer, M. A.; Gutt, C.; Grübel, G.

2014-07-01

Recently the analysis of scattering patterns by angular cross-correlation analysis (CCA) was introduced to reveal the orientational order in disordered samples with special focus to future applications on x-ray free-electron laser facilities. We apply this CCA approach to ultra-small-angle light-scattering data obtained from two-dimensional monolayers of microspheres. The films were studied in addition by optical microscopy. This combined approach allows to calculate the cross-correlations of the scattering patterns, characterized by the orientational correlation function Ψl(q), as well as to obtain the real-space structure of the monolayers. We show that CCA is sensitive to the orientational order of monolayers formed by the microspheres which are not directly visible from the scattering patterns. By mixing microspheres of different radii the sizes of ordered monolayer domains is reduced. For these samples it is shown that Ψl(q) quantitatively describes the degree of hexagonal order of the two-dimensional films. The experimental CCA results are compared with calculations based on the microscopy images. Both techniques show qualitatively similar features. Differences can be attributed to the wave-front distortion of the laser beam in the experiment. This effect is discussed by investigating the effect of different wave fronts on the cross-correlation analysis results. The so-determined characteristics of the cross-correlation analysis will be also relevant for future x-ray-based studies.

Quantitative skeletal evaluation based on cervical vertebral maturation: a longitudinal study of adolescents with normal occlusion.

PubMed

Chen, L; Liu, J; Xu, T; Long, X; Lin, J

2010-07-01

The study aims were to investigate the correlation between vertebral shape and hand-wrist maturation and to select characteristic parameters of C2-C5 (the second to fifth cervical vertebrae) for cervical vertebral maturation determination by mixed longitudinal data. 87 adolescents (32 males, 55 females) aged 8-18 years with normal occlusion were studied. Sequential lateral cephalograms and hand-wrist radiographs were taken annually for 6 consecutive years. Lateral cephalograms were divided into 11 maturation groups according to Fishman Skeletal Maturity Indicators (SMI). 62 morphological measurements of C2-C5 at 11 different developmental stages (SMI1-11) were measured and analysed. Locally weighted scatterplot smoothing, correlation coefficient analysis and variable cluster analysis were used for statistical analysis. Of the 62 cervical vertebral parameters, 44 were positively correlated with SMI, 6 were negatively correlated and 12 were not correlated. The correlation coefficients between cervical vertebral parameters and SMI were relatively high. Characteristic parameters for quantitative analysis of cervical vertebral maturation were selected. In summary, cervical vertebral maturation could be used reliably to evaluate the skeletal stage instead of the hand-wrist radiographic method. Selected characteristic parameters offered a simple and objective reference for the assessment of skeletal maturity and timing of orthognathic surgery. Copyright 2010 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Review of correlation techniques

NASA Technical Reports Server (NTRS)

Bowhill, S. A.

1983-01-01

Correlation analysis in MST radar to determine the scattered power, Doppler frequency and correlation time for a noisy signal is examined. It is assumed that coherent detection was employed, with two accurately balanced quadrature receiving channels and that coherent integration is performed with a window length significantly less than the correlation time of the signal.

Noninvasive deep Raman detection with 2D correlation analysis

NASA Astrophysics Data System (ADS)

Kim, Hyung Min; Park, Hyo Sun; Cho, Youngho; Jin, Seung Min; Lee, Kang Taek; Jung, Young Mee; Suh, Yung Doug

2014-07-01

The detection of poisonous chemicals enclosed in daily necessaries is prerequisite essential for homeland security with the increasing threat of terrorism. For the detection of toxic chemicals, we combined a sensitive deep Raman spectroscopic method with 2D correlation analysis. We obtained the Raman spectra from concealed chemicals employing spatially offset Raman spectroscopy in which incident line-shaped light experiences multiple scatterings before being delivered to inner component and yielding deep Raman signal. Furthermore, we restored the pure Raman spectrum of each component using 2D correlation spectroscopic analysis with chemical inspection. Using this method, we could elucidate subsurface component under thick powder and packed contents in a bottle.

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

PubMed

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

Research of diagnosis sensors fault based on correlation analysis of the bridge structural health monitoring system

NASA Astrophysics Data System (ADS)

Hu, Shunren; Chen, Weimin; Liu, Lin; Gao, Xiaoxia

2010-03-01

Bridge structural health monitoring system is a typical multi-sensor measurement system due to the multi-parameters of bridge structure collected from the monitoring sites on the river-spanning bridges. Bridge structure monitored by multi-sensors is an entity, when subjected to external action; there will be different performances to different bridge structure parameters. Therefore, the data acquired by each sensor should exist countless correlation relation. However, complexity of the correlation relation is decided by complexity of bridge structure. Traditionally correlation analysis among monitoring sites is mainly considered from physical locations. unfortunately, this method is so simple that it cannot describe the correlation in detail. The paper analyzes the correlation among the bridge monitoring sites according to the bridge structural data, defines the correlation of bridge monitoring sites and describes its several forms, then integrating the correlative theory of data mining and signal system to establish the correlation model to describe the correlation among the bridge monitoring sites quantificationally. Finally, The Chongqing Mashangxi Yangtze river bridge health measurement system is regards as research object to diagnosis sensors fault, and simulation results verify the effectiveness of the designed method and theoretical discussions.

A study of correlations between crude oil spot and futures markets: A rolling sample test

NASA Astrophysics Data System (ADS)

Liu, Li; Wan, Jieqiu

2011-10-01

In this article, we investigate the asymmetries of exceedance correlations and cross-correlations between West Texas Intermediate (WTI) spot and futures markets. First, employing the test statistic proposed by Hong et al. [Asymmetries in stock returns: statistical tests and economic evaluation, Review of Financial Studies 20 (2007) 1547-1581], we find that the exceedance correlations were overall symmetric. However, the results from rolling windows show that some occasional events could induce the significant asymmetries of the exceedance correlations. Second, employing the test statistic proposed by Podobnik et al. [Quantifying cross-correlations using local and global detrending approaches, European Physics Journal B 71 (2009) 243-250], we find that the cross-correlations were significant even for large lagged orders. Using the detrended cross-correlation analysis proposed by Podobnik and Stanley [Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series, Physics Review Letters 100 (2008) 084102], we find that the cross-correlations were weakly persistent and were stronger between spot and futures contract with larger maturity. Our results from rolling sample test also show the apparent effects of the exogenous events. Additionally, we have some relevant discussions on the obtained evidence.

Dynamical System Analysis of Reynolds Stress Closure Equations

NASA Technical Reports Server (NTRS)

Girimaji, Sharath S.

1997-01-01

In this paper, we establish the causality between the model coefficients in the standard pressure-strain correlation model and the predicted equilibrium states for homogeneous turbulence. We accomplish this by performing a comprehensive fixed point analysis of the modeled Reynolds stress and dissipation rate equations. The results from this analysis will be very useful for developing improved pressure-strain correlation models to yield observed equilibrium behavior.

Multiscale multifractal properties between ground-level ozone and its precursors in rural area in Hong Kong.

PubMed

He, Hong-di; Qiao, Zhong-Xia; Pan, Wei; Lu, Wei-Zhen

2017-07-01

In rural area, due to the reduction of NOx and CO emitted from vehicle exhausts, the ozone photochemical reaction exhibits relatively weak effect and ozone formation presents different pattern with its precursors in contrast to urban situation. Hence, in this study, we apply detrended cross-correlation analysis to investigate the multifractal properties between ozone and its precursors in a rural area in Hong Kong. The observed databases of ozone, NO 2 , NOx and CO levels during 2005-2014 are obtained from a rural monitoring station in Hong Kong. Based on the collected database, the cross-correlation analysis is carried out firstly to examine the cross-correlation patterns and the results indicate that close interactive relations exist between them. Then the detrended cross-correlation analysis is performed for further analysis. The multifractal characters occur between ozone and its precursors. The long-term cross-correlations behaviors in winter are verified to be stronger than that in other seasons. Additionally, the method is extended on daily averaged data to explore the multifractal property on various time scales. The long-term cross-correlation behavior of ozone vs NO 2 and NOx on daily basis becomes weaker while that of ozone vs CO becomes stronger. The multifractal properties for all pairs in summer are found to be the strongest among the whole year. These findings successfully illustrate that the multifractal analysis is a useful tool for describing the temporal scaling behaviors of ozone trends in different time series in rural areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Achievement Goals and Achievement Emotions: A Meta-Analysis

ERIC Educational Resources Information Center

Huang, Chiungjung

2011-01-01

This meta-analysis synthesized 93 independent samples (N = 30,003) in 77 studies that reported in 78 articles examining correlations between achievement goals and achievement emotions. Achievement goals were meaningfully associated with different achievement emotions. The correlations of mastery and mastery approach goals with positive achievement…

Correlates of Successful Aging: Are They Universal?

ERIC Educational Resources Information Center

Litwin, Howard

2005-01-01

The analysis compared differing correlates of life satisfaction among three diverse population groups in Israel, examining background and health status variables, social environment factors, and activity indicators. Multiple regression analysis revealed that veteran Jewish-Israelis (n = 2,043) had the largest set of predictors, the strongest of…

Concordance correlation for model performance assessment: An example with reference evapotranspiration

USDA-ARS?s Scientific Manuscript database

Procedures for assessing model performance in agronomy are often arbitrary and not always helpful. An omnibus analysis statistic, concordance correlation, is widely known and used in many other sciences. An illustrative example is presented here. The analysis assumes the exact relationship “observat...

The Correlation between Maternal Exposure to Air Pollution and the Risk of Orofacial Clefts in Infants: a Systematic Review and Meta-Analysis

PubMed Central

Rao, Ajit; Ahmed, Mairaj K.; Taub, Peter J.

2016-01-01

ABSTRACT Objectives The authors performed a systematic review and meta-analysis to investigate the possible correlation between ambient air pollution and orofacial cleft anomalies in newborns. Material and Methods A literature search was performed using the PubMed and Google Scholar, using the keywords “air pollution”, “cleft lip”, “cleft palate”, “carbon monoxide”, “ozone”, “sulfur dioxide”, “nitrogen oxide”, “nitrogen dioxide”, and “aerodynamic diameter”. Eight epidemiologic articles met the criteria of correlating either carbon monoxide (CO), ozone (O3), nitrogen oxides (NOx), airborne particulate matter of less than 10 µm in diameter (PM10), or sulfur dioxide (SO2) exposures with clefting of the palate alone, clefting of the lip alone, or clefting of the lip and palate. Odds ratios were extracted from the eight studies and tabulated in this meta-analysis. Quality analysis showed six high quality, one medium quality, and one low quality study. Results Meta-analysis of the combined data confirmed the association of O3 exposure and risk of orofacial cleft anomalies (OR = 1.08; P = 0.02). NOx was consistently associated with decreased risk of cleft lip with or without palate and cleft palate. Conclusions Ozone showed the strongest correlation with cleft lip and cleft palate anomalies. However, the studies overall showed an inconsistent correlation between orofacial clefts and air pollutants. PMID:27099696

Delay correlation analysis and representation for vital complaint VHDL models

DOEpatents

Rich, Marvin J.; Misra, Ashutosh

2004-11-09

A method and system unbind a rise/fall tuple of a VHDL generic variable and create rise time and fall time generics of each generic variable that are independent of each other. Then, according to a predetermined correlation policy, the method and system collect delay values in a VHDL standard delay file, sort the delay values, remove duplicate delay values, group the delay values into correlation sets, and output an analysis file. The correlation policy may include collecting all generic variables in a VHDL standard delay file, selecting each generic variable, and performing reductions on the set of delay values associated with each selected generic variable.

Auto correlation analysis of coda waves from local earthquakes for detecting temporal changes in shallow subsurface structures - The 2011 Tohoku-Oki, Japan, earthquake -

NASA Astrophysics Data System (ADS)

Nakahara, H.

2013-12-01

For monitoring temporal changes in subsurface structures, I propose to use auto correlation functions of coda waves from local earthquakes recorded at surface receivers, which probably contain more body waves than surface waves. Because the use of coda waves requires earthquakes, time resolution for monitoring decreases. But at regions with high seismicity, it may be possible to monitor subsurface structures in sufficient time resolutions. Studying the 2011 Tohoku-Oki (Mw 9.0), Japan, earthquake for which velocity changes have been already reported by previous studies, I try to validate the method. KiK-net stations in northern Honshu are used in the analysis. For each moderate earthquake, normalized auto correlation functions of surface records are stacked with respect to time windows in S-wave coda. Aligning the stacked normalized auto correlation functions with time, I search for changes in arrival times of phases. The phases at lag times of less than 1s are studied because changes at shallow depths are focused. Based on the stretching method, temporal variations in the arrival times are measured at the stations. Clear phase delays are found to be associated with the mainshock and to gradually recover with time. Amounts of the phase delays are in the order of 10% on average with the maximum of about 50% at some stations. For validation, the deconvolution analysis using surface and subsurface records at the same stations are conducted. The results show that the phase delays from the deconvolution analysis are slightly smaller than those from the auto correlation analysis, which implies that the phases on the auto correlations are caused by larger velocity changes at shallower depths. The auto correlation analysis seems to have an accuracy of about several percents, which is much larger than methods using earthquake doublets and borehole array data. So this analysis might be applicable to detect larger changes. In spite of these disadvantages, this analysis is still attractive because it can be applied to many records on the surface in regions where no boreholes are available. Acknowledgements: Seismograms recorded by KiK-net managed by National Research Institute for Earth Science and Disaster Prevention (NIED) were used in this study. This study was partially supported by JST J-RAPID program and JSPS KAKENHI Grant Numbers 24540449 and 23540449.

Influence of mandibular morphology on the hyoid bone in atypical deglutition: a correlational study.

PubMed

Machado, Almiro J; Crespo, Agrício N

2011-11-01

evaluate the possible correlation with the radiographic position of the hyoid bone and mandibular angle in lateral radiographs of children with atypical deglutition. This was an observational study using cephalometric analysis of lateral teleradiographs for the distances of H-MP (hyoid to mandibular plane). Spearman's correlation analysis was performed with MA (mandibular angle) in two groups: the experimental group with atypical deglutition and the control group normal deglutition. Both groups included subjects in mixed dentition stage. there was a significant moderate negative correlation between MA (mandibular angle) and hyoid bone (H-MP) in the normal group (R = -0.406, p = 0.021). However, there was no significant correlation between the MA and H-MP (R = 0.029, p = 0.83) in the group with atypical deglutition. there is a moderate negative correlation between the position of the hyoid bone and mandibular angle in the group of normal swallowing and there is no correlation between variables H-MP and MA in the group of atypical swallowing.

Inference for High-dimensional Differential Correlation Matrices.

PubMed

Cai, T Tony; Zhang, Anru

2016-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.

Multifractal detrended cross-correlation between the Chinese domestic and international gold markets based on DCCA and DMCA methods

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Han, Yan; Chen, Yuemeng; Yang, Chunxia

2014-05-01

Based on the daily price data of Shanghai and London gold spot markets, we applied detrended cross-correlation analysis (DCCA) and detrended moving average cross-correlation analysis (DMCA) methods to quantify power-law cross-correlation between domestic and international gold markets. Results show that the cross-correlations between the Chinese domestic and international gold spot markets are multifractal. Furthermore, forward DMCA and backward DMCA seems to outperform DCCA and centered DMCA for short-range gold series, which confirms the comparison results of short-range artificial data in L. Y. He and S. P. Chen [Physica A 390 (2011) 3806-3814]. Finally, we analyzed the local multifractal characteristics of the cross-correlation between Chinese domestic and international gold markets. We show that multifractal characteristics of the cross-correlation between the Chinese domestic and international gold markets are time-varying and that multifractal characteristics were strengthened by the financial crisis in 2007-2008.

A study of correlations in the stock market

NASA Astrophysics Data System (ADS)

Sharma, Chandradew; Banerjee, Kinjal

2015-08-01

We study the various sectors of the Bombay Stock Exchange (BSE) for a period of 8 years from April 2006 to March 2014. Using the data of daily returns of a period of eight years we make a direct model free analysis of the pattern of the sectorial indices movement and the correlations among them. Our analysis shows significant auto correlation among the individual sectors and also strong cross-correlation among sectors. We also find that auto correlations in some of the sectors persist in time. This is a very significant result and has not been reported so far in Indian context. These findings will be very useful in model building for prediction of price movement of equities, derivatives and portfolio management. We show that the Random Walk Hypothesis is not applicable in modeling the Indian market and mean-variance-skewness-kurtosis based portfolio optimization might be required. We also find that almost all sectors are highly correlated during large fluctuation periods and have only moderate correlation during normal periods.

Separate-channel analysis of two-channel microarrays: recovering inter-spot information.

PubMed

Smyth, Gordon K; Altman, Naomi S

2013-05-26

Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis is the most powerful of all. The common correlation method proposed in this article for separate-channel analysis of two-channel microarray data is no more difficult to apply in practice than the traditional log-ratio analysis. It provides an intuitive and powerful means to conduct analyses and make comparisons that might otherwise not be possible.

Novel Multidimensional Cross-Correlation Data Comparison Techniques for Spectroscopic Discernment in a Volumetrically Sensitive, Moderating Type Neutron Spectrometer

NASA Astrophysics Data System (ADS)

Hoshor, Cory; Young, Stephan; Rogers, Brent; Currie, James; Oakes, Thomas; Scott, Paul; Miller, William; Caruso, Anthony

2014-03-01

A novel application of the Pearson Cross-Correlation to neutron spectral discernment in a moderating type neutron spectrometer is introduced. This cross-correlation analysis will be applied to spectral response data collected through both MCNP simulation and empirical measurement by the volumetrically sensitive spectrometer for comparison in 1, 2, and 3 spatial dimensions. The spectroscopic analysis methods discussed will be demonstrated to discern various common spectral and monoenergetic neutron sources.

Analysis of DNA Sequences by an Optical ime-Integrating Correlator: Proposal

DTIC Science & Technology

1991-11-01

CURRENT TECHNOLOGY 2 3.0 TIME-INTEGRATING CORRELATOR 2 4.0 REPRESENTATIONS OF THE DNA BASES 8 5.0 DNA ANALYSIS STRATEGY 8 6.0 STRATEGY FOR COARSE...1)-correlation peak formed by the AxB term and (2)-pedestal formed by the A + B terms. 7 Figure 4: Short representations of the DNA bases where each...linear scale. 15 x LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits long pseudorandom

Complex Analysis of Combat in Afghanistan

DTIC Science & Technology

2014-12-01

analysis we have β−ffE ~)( where β= 2H - 1 = 1 - γ, with H being the Hurst exponent , related to the correlation exponent γ. Usually, real-world data are...statistical nature. In every instance we found strong power law correlations in the data, and were able to extract accurate scaling exponents . On the... exponents , α. The case αɘ.5 corresponds to long-term anti-correlations, meaning that large values are most likely to be followed by small values and

Loran-C monitor correlation over a 92-mile baseline in Ohio

NASA Technical Reports Server (NTRS)

Lilley, Robert W.; Edwards, Jamie S.

1988-01-01

Two Loran C monitors, at Galion and Athens, Ohio, were operated over a one-year period, measuring chain 9960 Time Delay (TD) and Signal to Noise Ratio (SNR). Analysis of data concentrated on correlation of short term TD variations during the winter months of 1985 to 86, over the 92 nm baseline. Excellent correlation was found, with slight additional improvement possible if local temperature is also included in the analysis. Although SNR and TD effects were suspected during the presence of thunderstorms near the monitors, the scope of the study did not permit storm by storm analysis. A computer tape data base of all measurements was produced, with measurements at both sites included. Data recording and analysis concentrated on the fall and winter months of September 1985 to February 1986.

An Interdisciplinary Meta-Analysis of the Potential Antecedents, Correlates, and Consequences of Protege Perceptions of Mentoring

ERIC Educational Resources Information Center

Eby, Lillian Turner de Tormes; Allen, Tammy D.; Hoffman, Brian J.; Baranik, Lisa E.; Sauer, Julia B.; Baldwin, Sean; Morrison, M. Ashley; Kinkade, Katie M.; Maher, Charleen P.; Curtis, Sara; Evans, Sarah C.

2013-01-01

This meta-analysis summarized youth, academic, and workplace research on the potential antecedents (demographics, human capital, and relationship attributes), correlates (interaction frequency, relationship length, performance, motivation, and social capital), and consequences (attitudinal, behavioral, career-related, and health-related outcomes)…

Bootstrap Confidence Intervals for Ordinary Least Squares Factor Loadings and Correlations in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Luo, Shanhong

2010-01-01

This article is concerned with using the bootstrap to assign confidence intervals for rotated factor loadings and factor correlations in ordinary least squares exploratory factor analysis. Coverage performances of "SE"-based intervals, percentile intervals, bias-corrected percentile intervals, bias-corrected accelerated percentile…

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…

Robustness of Type I Error and Power in Set Correlation Analysis of Contingency Tables.

ERIC Educational Resources Information Center

Cohen, Jacob; Nee, John C. M.

1990-01-01

The analysis of contingency tables via set correlation allows the assessment of subhypotheses involving contrast functions of the categories of the nominal scales. The robustness of such methods with regard to Type I error and statistical power was studied via a Monte Carlo experiment. (TJH)

Factors That Attenuate the Correlation Coefficient and Its Analogs.

ERIC Educational Resources Information Center

Dolenz, Beverly

The correlation coefficient is an integral part of many other statistical techniques (analysis of variance, t-tests, etc.), since all analytic methods are actually correlational (G. V. Glass and K. D. Hopkins, 1984). The correlation coefficient is a statistical summary that represents the degree and direction of relationship between two variables.…

Principal component analysis of the nonlinear coupling of harmonic modes in heavy-ion collisions

NASA Astrophysics Data System (ADS)

BoŻek, Piotr

2018-03-01

The principal component analysis of flow correlations in heavy-ion collisions is studied. The correlation matrix of harmonic flow is generalized to correlations involving several different flow vectors. The method can be applied to study the nonlinear coupling between different harmonic modes in a double differential way in transverse momentum or pseudorapidity. The procedure is illustrated with results from the hydrodynamic model applied to Pb + Pb collisions at √{sN N}=2760 GeV. Three examples of generalized correlations matrices in transverse momentum are constructed corresponding to the coupling of v22 and v4, of v2v3 and v5, or of v23,v33 , and v6. The principal component decomposition is applied to the correlation matrices and the dominant modes are calculated.

Anatomic, clinical, and neuropsychological correlates of spelling errors in primary progressive aphasia.

PubMed

Shim, Hyungsub; Hurley, Robert S; Rogalski, Emily; Mesulam, M-Marsel

2012-07-01

This study evaluates spelling errors in the three subtypes of primary progressive aphasia (PPA): agrammatic (PPA-G), logopenic (PPA-L), and semantic (PPA-S). Forty-one PPA patients and 36 age-matched healthy controls were administered a test of spelling. The total number of errors and types of errors in spelling to dictation of regular words, exception words and nonwords, were recorded. Error types were classified based on phonetic plausibility. In the first analysis, scores were evaluated by clinical diagnosis. Errors in spelling exception words and phonetically plausible errors were seen in PPA-S. Conversely, PPA-G was associated with errors in nonword spelling and phonetically implausible errors. In the next analysis, spelling scores were correlated to other neuropsychological language test scores. Significant correlations were found between exception word spelling and measures of naming and single word comprehension. Nonword spelling correlated with tests of grammar and repetition. Global language measures did not correlate significantly with spelling scores, however. Cortical thickness analysis based on MRI showed that atrophy in several language regions of interest were correlated with spelling errors. Atrophy in the left supramarginal gyrus and inferior frontal gyrus (IFG) pars orbitalis correlated with errors in nonword spelling, while thinning in the left temporal pole and fusiform gyrus correlated with errors in exception word spelling. Additionally, phonetically implausible errors in regular word spelling correlated with thinning in the left IFG pars triangularis and pars opercularis. Together, these findings suggest two independent systems for spelling to dictation, one phonetic (phoneme to grapheme conversion), and one lexical (whole word retrieval). Copyright © 2012 Elsevier Ltd. All rights reserved.

Modified cross sample entropy and surrogate data analysis method for financial time series

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2015-09-01

For researching multiscale behaviors from the angle of entropy, we propose a modified cross sample entropy (MCSE) and combine surrogate data analysis with it in order to compute entropy differences between original dynamics and surrogate series (MCSDiff). MCSDiff is applied to simulated signals to show accuracy and then employed to US and Chinese stock markets. We illustrate the presence of multiscale behavior in the MCSDiff results and reveal that there are synchrony containing in the original financial time series and they have some intrinsic relations, which are destroyed by surrogate data analysis. Furthermore, the multifractal behaviors of cross-correlations between these financial time series are investigated by multifractal detrended cross-correlation analysis (MF-DCCA) method, since multifractal analysis is a multiscale analysis. We explore the multifractal properties of cross-correlation between these US and Chinese markets and show the distinctiveness of NQCI and HSI among the markets in their own region. It can be concluded that the weaker cross-correlation between US markets gives the evidence for the better inner mechanism in the US stock markets than that of Chinese stock markets. To study the multiscale features and properties of financial time series can provide valuable information for understanding the inner mechanism of financial markets.

Development of an unsteady aerodynamics model to improve correlation of computed blade stresses with test data

NASA Technical Reports Server (NTRS)

Gangwani, S. T.

1985-01-01

A reliable rotor aeroelastic analysis operational that correctly predicts the vibration levels for a helicopter is utilized to test various unsteady aerodynamics models with the objective of improving the correlation between test and theory. This analysis called Rotor Aeroelastic Vibration (RAVIB) computer program is based on a frequency domain forced response analysis which utilizes the transfer matrix techniques to model helicopter/rotor dynamic systems of varying degrees of complexity. The results for the AH-1G helicopter rotor were compared with the flight test data during high speed operation and they indicated a reasonably good correlation for the beamwise and chordwise blade bending moments, but for torsional moments the correlation was poor. As a result, a new aerodynamics model based on unstalled synthesized data derived from the large amplitude oscillating airfoil experiments was developed and tested.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Research on criticality analysis method of CNC machine tools components under fault rate correlation

NASA Astrophysics Data System (ADS)

Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

2018-02-01

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

Variability in memory performance in aged healthy individuals: an fMRI study.

PubMed

Grön, Georg; Bittner, Daniel; Schmitz, Bernd; Wunderlich, Arthur P; Tomczak, Reinhard; Riepe, Matthias W

2003-01-01

Episodic memory performance varies in older subjects but underlying biological correlates remain as yet ambiguous. We investigated episodic memory in healthy older individuals (n=24; mean age: 64.4+/-6.7 years) without subjective memory complaints or objective cognitive impairment. Episodic memory was assessed with repetitive learning and recall of abstract geometric patterns during fMRI. Group analysis of brain activity during initial learning and maximum recall revealed hippocampal activation. Correlation analysis of brain activation and task performance demonstrated significant hippocampal activity during initial learning and maximum recall in a success-dependent manner. Neither age nor gray matter densities correlated with hippocampal activation. Functional imaging of episodic memory thus permits to detect objectively variability in hippocampal recruitment in healthy aged individuals without subjective memory complaints. Correlation analysis of brain activation and performance during an episodic memory task may be used to determine and follow-up hippocampal malfunction in a very sensitive manner.

Geographical Scale Effects on the Analysis of Leptospirosis Determinants

PubMed Central

Gracie, Renata; Barcellos, Christovam; Magalhães, Mônica; Souza-Santos, Reinaldo; Barrocas, Paulo Rubens Guimarães

2014-01-01

Leptospirosis displays a great diversity of routes of exposure, reservoirs, etiologic agents, and clinical symptoms. It occurs almost worldwide but its pattern of transmission varies depending where it happens. Climate change may increase the number of cases, especially in developing countries, like Brazil. Spatial analysis studies of leptospirosis have highlighted the importance of socioeconomic and environmental context. Hence, the choice of the geographical scale and unit of analysis used in the studies is pivotal, because it restricts the indicators available for the analysis and may bias the results. In this study, we evaluated which environmental and socioeconomic factors, typically used to characterize the risks of leptospirosis transmission, are more relevant at different geographical scales (i.e., regional, municipal, and local). Geographic Information Systems were used for data analysis. Correlations between leptospirosis incidence and several socioeconomic and environmental indicators were calculated at different geographical scales. At the regional scale, the strongest correlations were observed between leptospirosis incidence and the amount of people living in slums, or the percent of the area densely urbanized. At the municipal scale, there were no significant correlations. At the local level, the percent of the area prone to flooding best correlated with leptospirosis incidence. PMID:25310536

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.

Sequential Dictionary Learning From Correlated Data: Application to fMRI Data Analysis.

PubMed

Seghouane, Abd-Krim; Iqbal, Asif

2017-03-22

Sequential dictionary learning via the K-SVD algorithm has been revealed as a successful alternative to conventional data driven methods such as independent component analysis (ICA) for functional magnetic resonance imaging (fMRI) data analysis. fMRI datasets are however structured data matrices with notions of spatio-temporal correlation and temporal smoothness. This prior information has not been included in the K-SVD algorithm when applied to fMRI data analysis. In this paper we propose three variants of the K-SVD algorithm dedicated to fMRI data analysis by accounting for this prior information. The proposed algorithms differ from the K-SVD in their sparse coding and dictionary update stages. The first two algorithms account for the known correlation structure in the fMRI data by using the squared Q, R-norm instead of the Frobenius norm for matrix approximation. The third and last algorithm account for both the known correlation structure in the fMRI data and the temporal smoothness. The temporal smoothness is incorporated in the dictionary update stage via regularization of the dictionary atoms obtained with penalization. The performance of the proposed dictionary learning algorithms are illustrated through simulations and applications on real fMRI data.

Techniques for measurement of thoracoabdominal asynchrony

NASA Technical Reports Server (NTRS)

Prisk, G. Kim; Hammer, J.; Newth, Christopher J L.

2002-01-01

Respiratory motion measured by respiratory inductance plethysmography often deviates from the sinusoidal pattern assumed in the traditional Lissajous figure (loop) analysis used to determine thoraco-abdominal asynchrony, or phase angle phi. We investigated six different time-domain methods of measuring phi, using simulated data with sinusoidal and triangular waveforms, phase shifts of 0-135 degrees, and 10% noise. The techniques were then used on data from 11 lightly anesthetized rhesus monkeys (Macaca mulatta; 7.6 +/- 0.8 kg; 5.7 +/- 0.5 years old), instrumented with a respiratory inductive plethysmograph, and subjected to increasing levels of inspiratory resistive loading ranging from 5-1,000 cmH(2)O. L(-1). sec(-1).The best results were obtained from cross-correlation and maximum linear correlation, with errors less than approximately 5 degrees from the actual phase angle in the simulated data. The worst performance was produced by the loop analysis, which in some cases was in error by more than 30 degrees. Compared to correlation, other analysis techniques performed at an intermediate level. Maximum linear correlation and cross-correlation produced similar results on the data collected from monkeys (SD of the difference, 4.1 degrees ) but all other techniques had a high SD of the difference compared to the correlation techniques.We conclude that phase angles are best measured using cross-correlation or maximum linear correlation, techniques that are independent of waveform shape, and robust in the presence of noise. Copyright 2002 Wiley-Liss, Inc.

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

NASA Astrophysics Data System (ADS)

Gan, Luping; Li, Yan-Feng; Zhu, Shun-Peng; Yang, Yuan-Jian; Huang, Hong-Zhong

2014-06-01

Failure mode, effects and criticality analysis (FMECA) and Fault tree analysis (FTA) are powerful tools to evaluate reliability of systems. Although single failure mode issue can be efficiently addressed by traditional FMECA, multiple failure modes and component correlations in complex systems cannot be effectively evaluated. In addition, correlated variables and parameters are often assumed to be precisely known in quantitative analysis. In fact, due to the lack of information, epistemic uncertainty commonly exists in engineering design. To solve these problems, the advantages of FMECA, FTA, fuzzy theory, and Copula theory are integrated into a unified hybrid method called fuzzy probability weighted geometric mean (FPWGM) risk priority number (RPN) method. The epistemic uncertainty of risk variables and parameters are characterized by fuzzy number to obtain fuzzy weighted geometric mean (FWGM) RPN for single failure mode. Multiple failure modes are connected using minimum cut sets (MCS), and Boolean logic is used to combine fuzzy risk priority number (FRPN) of each MCS. Moreover, Copula theory is applied to analyze the correlation of multiple failure modes in order to derive the failure probabilities of each MCS. Compared to the case where dependency among multiple failure modes is not considered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quantitative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reassess the risk priority, which generalize the definition of probability weight and FRPN, resulting in a more accurate estimation than that of the traditional models. Finally, a basic fatigue analysis case drawn from turbine and compressor blades in aeroengine is used to demonstrate the effectiveness and robustness of the presented method. The result provides some important insights on fatigue reliability analysis and risk priority assessment of structural system under failure correlations.

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

PubMed

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies.

Determination of Shear Wave Velocity in Offshore Terengganu for Ground Response Analysis

NASA Astrophysics Data System (ADS)

Mazlina, M.; Liew, M. S.; Adnan, A.; Harahap, I. S. H.; Hamid, N. A.

2018-04-01

Amount of vibration received in any location can be analysed by conducting ground response analysis. Even though there are three different methods available in this analysis, One Dimensional ground response analysis method has been widely used. Shear wave velocity is one of the key parameters in this analysis. A lot of correlations have been formulated to determine shear wave velocity with cone penetration test. In this study, correlations developed for Quaternary geological age have been selected. Six equations have been adopted comprise of all soil and soil type dependent correlations. Two platforms sites consist of clay and combination of clay and sand have been analysed. Shear velocity to be used in ground response analysis has been obtained. Results have been illustrated in graphs where shear velocity for each case has been plotted. In avoiding under or over predicting of shear wave velocity, the average of all soil and soil type dependent results will be used as final Vs value.

A chemometrics as a powerful tool in the elucidation of the role of metals in the biosynthesis of volatile organic compounds in Hungarian thyme samples.

PubMed

Arsenijević, Jelena; Marković, Jelena; Soštarić, Ivan; Ražić, Slavica

2013-10-01

The volatile fraction of the leaves of Thymus pannonicus All. (Lamiaceae) was analyzed by headspace extraction followed by GC-FID and GC-MS analysis. The different headspace profiles were recognized, with citral and with monoterpene hydrocarbons as dominant compounds. In addition, the determination of Cr, Co, Ni, Mo, Cu, Zn, Mn, Fe, Mg, Ca, K and Na was conducted by spectroscopic techniques (FAAS, GFAAS and ICP-OES). In order to evaluate the relationship between volatile organic compounds and metals, a chemometrics approach was applied. The data obtained by analysis of the headspace and elemental content were subjected to correlation analysis, factor analysis, principal component analysis and cluster analysis. A number of significant correlations of metals with plant volatiles were found. Correlation of Zn with citral, Mn with oxygenated monoterpenes and Mg with β-bourbonene, could be explained by involvement of metals in the biosynthesis of volatile organic compounds. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

PubMed

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Recent advancement in the field of two-dimensional correlation spectroscopy

NASA Astrophysics Data System (ADS)

Noda, Isao

2008-07-01

The recent advancement in the field of 2D correlation spectroscopy is reviewed with the emphasis on a number of papers published during the last two years. Topics covered by this comprehensive review include books, review articles, and noteworthy developments in the theory and applications of 2D correlation spectroscopy. New 2D correlation techniques are discussed, such as kernel analysis and augmented 2D correlation, model-based correlation, moving window analysis, global phase angle, covariance and correlation coefficient mapping, sample-sample correlation, hybrid and hetero correlation, pretreatment and transformation of data, and 2D correlation combined with other chemometrics techniques. Perturbation methods of both static (e.g., temperature, composition, pressure and stress, spatial distribution and orientation) and dynamic types (e.g., rheo-optical and acoustic, chemical reactions and kinetics, H/D exchange, sorption and diffusion) currently in use are examined. Analytical techniques most commonly employed in 2D correlation spectroscopy are IR, Raman, and NIR, but the growing use of other probes is also noted, including fluorescence, emission, Raman optical activity and vibrational circular dichroism, X-ray absorption and scattering, NMR, mass spectrometry, and even chromatography. The field of applications for 2D correlation spectroscopy is very diverse, encompassing synthetic polymers, liquid crystals, Langmuir-Blodgett films, proteins and peptides, natural polymers and biomaterials, pharmaceuticals, food and agricultural products, water, solutions, inorganic, organic, hybrid or composite materials, and many more.

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

Pantoea ananatis Genetic Diversity Analysis Reveals Limited Genomic Diversity as Well as Accessory Genes Correlated with Onion Pathogenicity.

PubMed

Stice, Shaun P; Stumpf, Spencer D; Gitaitis, Ron D; Kvitko, Brian H; Dutta, Bhabesh

2018-01-01

Pantoea ananatis is a member of the family Enterobacteriaceae and an enigmatic plant pathogen with a broad host range. Although P. ananatis strains can be aggressive on onion causing foliar necrosis and onion center rot, previous genomic analysis has shown that P. ananatis lacks the primary virulence secretion systems associated with other plant pathogens. We assessed a collection of fifty P. ananatis strains collected from Georgia over three decades to determine genetic factors that correlated with onion pathogenic potential. Previous genetic analysis studies have compared strains isolated from different hosts with varying diseases potential and isolation sources. Strains varied greatly in their pathogenic potential and aggressiveness on different cultivated Allium species like onion, leek, shallot, and chive. Using multi-locus sequence analysis (MLSA) and repetitive extragenic palindrome repeat (rep)-PCR techniques, we did not observe any correlation between onion pathogenic potential and genetic diversity among strains. Whole genome sequencing and pan-genomic analysis of a sub-set of 10 strains aided in the identification of a novel series of genetic regions, likely plasmid borne, and correlating with onion pathogenicity observed on single contigs of the genetic assemblies. We named these loci Onion Virulence Regions (OVR) A-D. The OVR loci contain genes involved in redox regulation as well as pectate lyase and rhamnogalacturonase genes. Previous studies have not identified distinct genetic loci or plasmids correlating with onion foliar pathogenicity or pathogenicity on a single host pathosystem. The lack of focus on a single host system for this phytopathgenic disease necessitates the pan-genomic analysis performed in this study.

Pantoea ananatis Genetic Diversity Analysis Reveals Limited Genomic Diversity as Well as Accessory Genes Correlated with Onion Pathogenicity

PubMed Central

Stice, Shaun P.; Stumpf, Spencer D.; Gitaitis, Ron D.; Kvitko, Brian H.; Dutta, Bhabesh

2018-01-01

Pantoea ananatis is a member of the family Enterobacteriaceae and an enigmatic plant pathogen with a broad host range. Although P. ananatis strains can be aggressive on onion causing foliar necrosis and onion center rot, previous genomic analysis has shown that P. ananatis lacks the primary virulence secretion systems associated with other plant pathogens. We assessed a collection of fifty P. ananatis strains collected from Georgia over three decades to determine genetic factors that correlated with onion pathogenic potential. Previous genetic analysis studies have compared strains isolated from different hosts with varying diseases potential and isolation sources. Strains varied greatly in their pathogenic potential and aggressiveness on different cultivated Allium species like onion, leek, shallot, and chive. Using multi-locus sequence analysis (MLSA) and repetitive extragenic palindrome repeat (rep)-PCR techniques, we did not observe any correlation between onion pathogenic potential and genetic diversity among strains. Whole genome sequencing and pan-genomic analysis of a sub-set of 10 strains aided in the identification of a novel series of genetic regions, likely plasmid borne, and correlating with onion pathogenicity observed on single contigs of the genetic assemblies. We named these loci Onion Virulence Regions (OVR) A-D. The OVR loci contain genes involved in redox regulation as well as pectate lyase and rhamnogalacturonase genes. Previous studies have not identified distinct genetic loci or plasmids correlating with onion foliar pathogenicity or pathogenicity on a single host pathosystem. The lack of focus on a single host system for this phytopathgenic disease necessitates the pan-genomic analysis performed in this study. PMID:29491851

Analysis of 22 Elements in Milk, Feed, and Water of Dairy Cow, Goat, and Buffalo from Different Regions of China.

PubMed

Zhou, Xuewei; Qu, Xueyin; Zhao, Shengguo; Wang, Jiaqi; Li, Songli; Zheng, Nan

2017-03-01

The objectives of this study were to measure the concentrations of elements in raw milk by inductively coupled plasma-mass spectrometry (ICP-MS) and evaluate differences in element concentrations among animal species and regions of China. Furthermore, drinking water and feed samples were analyzed to investigate whether the element concentrations in raw milk are correlated with those in water and feed. All samples were analyzed by ICP-MS following microwave-assisted acid digestion. The mean recovery of the elements was 98.7 % from milk, 103.7 % from water, and 93.3 % from a certified reference material (cabbage). Principal component analysis results revealed that element concentrations differed among animal species and regions. Correlation analysis showed that trace elements Mn, Fe, Ni, Ga, Se, Sr, Cs, U in water and Co, Ni, Cu, Se, U in feed were significantly correlated with those in milk (p < 0.05). Toxic and potential toxic elements Cr, As, Cd, Tl, Pb in water and Al, Cr, As, Hg, Tl in feed were significantly correlated with those in milk (p < 0.05). Results of correlation analysis revealed that elements in water and feed might contribute to the elements in milk.

Automated measurement and classification of pulmonary blood-flow velocity patterns using phase-contrast MRI and correlation analysis.

PubMed

van Amerom, Joshua F P; Kellenberger, Christian J; Yoo, Shi-Joon; Macgowan, Christopher K

2009-01-01

An automated method was evaluated to detect blood flow in small pulmonary arteries and classify each as artery or vein, based on a temporal correlation analysis of their blood-flow velocity patterns. The method was evaluated using velocity-sensitive phase-contrast magnetic resonance data collected in vitro with a pulsatile flow phantom and in vivo in 11 human volunteers. The accuracy of the method was validated in vitro, which showed relative velocity errors of 12% at low spatial resolution (four voxels per diameter), but was reduced to 5% at increased spatial resolution (16 voxels per diameter). The performance of the method was evaluated in vivo according to its reproducibility and agreement with manual velocity measurements by an experienced radiologist. In all volunteers, the correlation analysis was able to detect and segment peripheral pulmonary vessels and distinguish arterial from venous velocity patterns. The intrasubject variability of repeated measurements was approximately 10% of peak velocity, or 2.8 cm/s root-mean-variance, demonstrating the high reproducibility of the method. Excellent agreement was obtained between the correlation analysis and radiologist measurements of pulmonary velocities, with a correlation of R2=0.98 (P<.001) and a slope of 0.99+/-0.01.

Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters.

PubMed

de Menezes, Alexandre B; Prendergast-Miller, Miranda T; Richardson, Alan E; Toscas, Peter; Farrell, Mark; Macdonald, Lynne M; Baker, Geoff; Wark, Tim; Thrall, Peter H

2015-08-01

Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co-correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

[Planning of esthetic oral rehabilitation according to correlative analysis of clinical and morphological features of the marginal gingiva].

PubMed

Stafeev, A A; Zinov'ev, G I; Drozdov, D D

2015-01-01

The orthopedic restoration and related to its clinical stages (preparation, gingival retraction, impression) is often associated with complications which arise from the marginal gingiva. The technology of indirect ceramic restoration requires an assessment of the clinical and morphological parameters of periodontal tissues. The study outlines correlation between the type of periodontal histhology and inflammatory and degenerative complications that has been established after the analysis of morphofunctional state of periodontal tissue. Results of clinical studies and correlation analysis of clinical and morphological parameters of marginal gingiva has shown that important parameter influencing the choice of manufacturing technology are the position of restoration margin relatively to marginal gingiva and periodontal morphotype.

Price-volume multifractal analysis and its application in Chinese stock markets

NASA Astrophysics Data System (ADS)

Yuan, Ying; Zhuang, Xin-tian; Liu, Zhi-ying

2012-06-01

An empirical research on Chinese stock markets is conducted using statistical tools. First, the multifractality of stock price return series, ri(ri=ln(Pt+1)-ln(Pt)) and trading volume variation series, vi(vi=ln(Vt+1)-ln(Vt)) is confirmed using multifractal detrended fluctuation analysis. Furthermore, a multifractal detrended cross-correlation analysis between stock price return and trading volume variation in Chinese stock markets is also conducted. It is shown that the cross relationship between them is also found to be multifractal. Second, the cross-correlation between stock price Pi and trading volume Vi is empirically studied using cross-correlation function and detrended cross-correlation analysis. It is found that both Shanghai stock market and Shenzhen stock market show pronounced long-range cross-correlations between stock price and trading volume. Third, a composite index R based on price and trading volume is introduced. Compared with stock price return series ri and trading volume variation series vi, R variation series not only remain the characteristics of original series but also demonstrate the relative correlation between stock price and trading volume. Finally, we analyze the multifractal characteristics of R variation series before and after three financial events in China (namely, Price Limits, Reform of Non-tradable Shares and financial crisis in 2008) in the whole period of sample to study the changes of stock market fluctuation and financial risk. It is found that the empirical results verified the validity of R.

Estimating the Geocenter from GNSS Observations

NASA Astrophysics Data System (ADS)

Dach, Rolf; Michael, Meindl; Beutler, Gerhard; Schaer, Stefan; Lutz, Simon; Jäggi, Adrian

2014-05-01

The satellites of the Global Navigation Satellite Systems (GNSS) are orbiting the Earth according to the laws of celestial mechanics. As a consequence, the satellites are sensitive to the coordinates of the center of mass of the Earth. The coordinates of the (ground) tracking stations are referring to the center of figure as the conventional origin of the reference frame. The difference between the center of mass and center of figure is the instantaneous geocenter. Following this definition the global GNSS solutions are sensitive to the geocenter. Several studies demonstrated strong correlations of the GNSS-derived geocenter coordinates with parameters intended to absorb radiation pressure effects acting on the GNSS satellites, and with GNSS satellite clock parameters. One should thus pose the question to what extent these satellite-related parameters absorb (or hide) the geocenter information. A clean simulation study has been performed to answer this question. The simulation environment allows it in particular to introduce user-defined shifts of the geocenter (systematic inconsistencies between the satellite's and station's reference frames). These geocenter shifts may be recovered by the mentioned parameters - provided they were set up in the analysis. If the geocenter coordinates are not estimated, one may find out which other parameters absorb the user-defined shifts of the geocenter and to what extent. Furthermore, the simulation environment also allows it to extract the correlation matrix from the a posteriori covariance matrix to study the correlations between different parameter types of the GNSS analysis system. Our results show high degrees of correlations between geocenter coordinates, orbit-related parameters, and satellite clock parameters. These correlations are of the same order of magnitude as the correlations between station heights, troposphere, and receiver clock parameters in each regional or global GNSS network analysis. If such correlations are accepted in a GNSS analysis when estimating station coordinates, geocenter coordinates must be considered as mathematically estimable in a global GNSS analysis. The geophysical interpretation may of course become difficult, e.g., if insufficient orbit models are used.

Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data

NASA Astrophysics Data System (ADS)

Manzo, Ciro; Braga, Federica; Zaggia, Luca; Brando, Vittorio Ernesto; Giardino, Claudia; Bresciani, Mariano; Bassani, Cristiana

2018-04-01

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013-2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

Regional-specific Stochastic Simulation of Spatially-distributed Ground-motion Time Histories using Wavelet Packet Analysis

NASA Astrophysics Data System (ADS)

Huang, D.; Wang, G.

2014-12-01

Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.

Semi-quantitative spectrographic analysis and rank correlation in geochemistry

USGS Publications Warehouse

Flanagan, F.J.

1957-01-01

The rank correlation coefficient, rs, which involves less computation than the product-moment correlation coefficient, r, can be used to indicate the degree of relationship between two elements. The method is applicable in situations where the assumptions underlying normal distribution correlation theory may not be satisfied. Semi-quantitative spectrographic analyses which are reported as grouped or partly ranked data can be used to calculate rank correlations between elements. ?? 1957.

Likelihood-Based Confidence Intervals in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Oort, Frans J.

2011-01-01

In exploratory or unrestricted factor analysis, all factor loadings are free to be estimated. In oblique solutions, the correlations between common factors are free to be estimated as well. The purpose of this article is to show how likelihood-based confidence intervals can be obtained for rotated factor loadings and factor correlations, by…

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…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

A Systematic Review and Meta-Analysis of the Cognitive Correlates of Bilingualism

ERIC Educational Resources Information Center

Adesope, Olusola O.; Lavin, Tracy; Thompson, Terri; Ungerleider, Charles

2010-01-01

A number of studies have documented the cognitive outcomes associated with bilingualism. To gain a clear understanding of the extent and diversity of these cognitive outcomes, the authors conducted a meta-analysis of studies that examined the cognitive correlates of bilingualism. Data from 63 studies (involving 6,022 participants) were extracted…

A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions

PubMed Central

2013-01-01

Background Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments. Results Correlation analysis has revealed statistically significant connections between metabolites, where differences in correlations between cells exposed to different oxygen levels have been highlighted as markers of hypoxic metabolism in cancer. Network mapping onto reconstructed human metabolic models is a novel addition to correlation analysis. Correlated metabolites have been mapped onto the Edinburgh human metabolic network (EHMN) with the aim of interlinking metabolites found to be regulated in a similar fashion in response to oxygen. This revealed novel pathways within the metabolic network that may be key to tumour cell survival at low oxygen. Results show that the metabolic responses to lowering oxygen availability can be conserved or specific to a particular cell line. Network-based correlation analysis identified conserved metabolites including malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate. In this way, this method has revealed metabolites not previously linked, or less well recognised, with respect to hypoxia before. Lactate fermentation is one of the key themes discussed in the field of hypoxia; however, malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate, which are connected by a single pathway, may provide a more significant marker of hypoxia in cancer. Conclusions Metabolic networks generated for each cell line were compared to identify conserved metabolite pathway responses to low oxygen environments. Furthermore, we believe this methodology will have general application within metabolomics. PMID:24153255

[Analysis of characteristics shown in self introduction letter and professor's recommendation letter].

PubMed

Kim, Sang Hyun

2013-09-01

The purpose of this study was to investigate applicants' behavioral characteristics based on the evaluation of cognitive, affective and social domain shown in self introduction letter and professor's recommendation letter. Self introduction letters and professor's recommendation letters of 109 applicants students who applied to medical school were collected. Frequency analysis and simple correlation were done in self introduction letter and professor's recommendation letter. Frequency analysis showed affective characteristics were most often mentioned in self introduction letter, and cognitive characteristics were most frequently described in professor's recommendation letter. There was a strong correlation between cognitive domains of self introduction letter and cognitive domain of professor's recommendation letter. There was a strong correlation between affective domain of self introduction letter and cognitive domain professor's recommendation letter. It is very important to make full use of self introduction letter and professor's recommendation letter for selecting medical students. Through the frequency analysis and simple correlation, more specific guidelines need to be suggested in order to secure fairness and objectivity in the evaluation of self-introduction letter and professor's recommendation letter.

Scanning electron microscopy combined with image processing technique: Analysis of microstructure, texture and tenderness in Semitendinous and Gluteus Medius bovine muscles.

PubMed

Pieniazek, Facundo; Messina, Valeria

2016-11-01

In this study the effect of freeze drying on the microstructure, texture, and tenderness of Semitendinous and Gluteus Medius bovine muscles were analyzed applying Scanning Electron Microscopy combined with image analysis. Samples were analyzed by Scanning Electron Microscopy at different magnifications (250, 500, and 1,000×). Texture parameters were analyzed by Texture analyzer and by image analysis. Tenderness by Warner-Bratzler shear force. Significant differences (p < 0.05) were obtained for image and instrumental texture features. A linear trend with a linear correlation was applied for instrumental and image features. Image texture features calculated from Gray Level Co-occurrence Matrix (homogeneity, contrast, entropy, correlation and energy) at 1,000× in both muscles had high correlations with instrumental features (chewiness, hardness, cohesiveness, and springiness). Tenderness showed a positive correlation in both muscles with image features (energy and homogeneity). Combing Scanning Electron Microscopy with image analysis can be a useful tool to analyze quality parameters in meat.Summary SCANNING 38:727-734, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Association between Low-density lipoprotein cholesterol and occipital periventricular hyperintensities in a group of Chinese patients: an observational study.

PubMed

Duan, Dazhi; Shen, Lin; Cui, Chun; Shu, Tongsheng; Zheng, Jian

2017-02-27

While occipital periventricular hyperintensities (OPVHs) are among the most common mild white matter hyperintensities, the clinical factors associated with OPVHs remain unclear. In this study, we investigated the role of clinical factors in development of pure OPVHs. This study included 97 patients with OPVHs and 73 healthy controls. Univariate analysis of clinical factors in OPVH patients and controls was followed by binomial logistic regression analysis to identify clinical factors significantly associated with OPVHs. Univariate analysis indicated that age, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein-B (Apo-B) levels differed significantly between the OPVH patients and controls (p < 0.05). Age and gender were correlated with OPVH scores (p < 0.05), while LDL-C, triglycerides, Apo-B and TC were anti-correlated with OPVHs scores (p < 0.05). Multivariate analysis indicated that LDL-C is negatively correlated with OPVHs (p < 0.05), and age is positively correlated with OPVHs (p < 0.001). In summary, LDL-C was negatively and age was positively associated with OPVHs among Chinese patients in a hospital.

[Using 2-DCOS to identify the molecular spectrum peaks for the isomer in the multi-component mixture gases Fourier transform infrared analysis].

PubMed

Zhao, An-Xin; Tang, Xiao-Jun; Zhang, Zhong-Hua; Liu, Jun-Hua

2014-10-01

The generalized two-dimensional correlation spectroscopy and Fourier transform infrared were used to identify hydrocarbon isomers in the mixed gases for absorption spectra resolution enhancement. The Fourier transform infrared spectrum of n-butane and iso-butane and the two-dimensional correlation infrared spectrum of concentration perturbation were used for analysis as an example. The all band and the main absorption peak wavelengths of Fourier transform infrared spectrum for single component gas showed that the spectra are similar, and if they were mixed together, absorption peaks overlap and peak is difficult to identify. The synchronous and asynchronous spectrum of two-dimensional correlation spectrum can clearly identify the iso-butane and normal butane and their respective characteristic absorption peak intensity. Iso-butane has strong absorption characteristics spectrum lines at 2,893, 2,954 and 2,893 cm(-1), and n-butane at 2,895 and 2,965 cm(-1). The analysis result in this paper preliminary verified that the two-dimensional infrared correlation spectroscopy can be used for resolution enhancement in Fourier transform infrared spectrum quantitative analysis.

Importance of the Correlation between Width and Length in the Shape Analysis of Nanorods: Use of a 2D Size Plot To Probe Such a Correlation.

PubMed

Zhao, Zhihua; Zheng, Zhiqin; Roux, Clément; Delmas, Céline; Marty, Jean-Daniel; Kahn, Myrtil L; Mingotaud, Christophe

2016-08-22

Analysis of nanoparticle size through a simple 2D plot is proposed in order to extract the correlation between length and width in a collection or a mixture of anisotropic particles. Compared to the usual statistics on the length associated with a second and independent statistical analysis of the width, this simple plot easily points out the various types of nanoparticles and their (an)isotropy. For each class of nano-objects, the relationship between width and length (i.e., the strong or weak correlations between these two parameters) may suggest information concerning the nucleation/growth processes. It allows one to follow the effect on the shape and size distribution of physical or chemical processes such as simple ripening. Various electron microscopy pictures from the literature or from the authors' own syntheses are used as examples to demonstrate the efficiency and simplicity of the proposed 2D plot combined with a multivariate analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multivariate meta-analysis using individual participant data.

PubMed

Riley, R D; Price, M J; Jackson, D; Wardle, M; Gueyffier, F; Wang, J; Staessen, J A; White, I R

2015-06-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Psychological Correlates of University Students' Academic Performance: A Systematic Review and Meta-Analysis

ERIC Educational Resources Information Center

Richardson, Michelle; Abraham, Charles; Bond, Rod

2012-01-01

A review of 13 years of research into antecedents of university students' grade point average (GPA) scores generated the following: a comprehensive, conceptual map of known correlates of tertiary GPA; assessment of the magnitude of average, weighted correlations with GPA; and tests of multivariate models of GPA correlates within and across…

A Reformulated Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data Effectively Increases Convergence and Admissibility Rates

ERIC Educational Resources Information Center

Fan, Yi; Lance, Charles E.

2017-01-01

The correlated trait-correlated method (CTCM) model for the analysis of multitrait-multimethod (MTMM) data is known to suffer convergence and admissibility (C&A) problems. We describe a little known and seldom applied reparameterized version of this model (CTCM-R) based on Rindskopf's reparameterization of the simpler confirmatory factor…

Correlation between X-ray flux and rotational acceleration in Vela X-1

NASA Technical Reports Server (NTRS)

Deeter, J. E.; Boynton, P. E.; Shibazaki, N.; Hayakawa, S.; Nagase, F.

1989-01-01

The results of a search for correlations between X-ray flux and angular acceleration for the accreting binary pulsar Vela X-1 are presented. Results are based on data obtained with the Hakucho satellite during the interval 1982 to 1984. In undertaking this correlation analysis, it was necessary to modify the usual statistical method to deal with conditions imposed by generally unavoidable satellite observing constraints, most notably a mismatch in sampling between the two variables. The results are suggestive of a correlation between flux and the absolute value of the angular acceleration, at a significance level of 96 percent. The implications of the methods and results for future observations and analysis are discussed.

MCM - 2 and Ki - 67 as proliferation markers in renal cell carcinoma: A quantitative and semi - quantitative analysis

PubMed Central

Mehdi, Muhammad Zain; Nagi, Abdul Hanan; Naseem, Nadia

2016-01-01

ABSTRACT Introduction/Background: Fuhrman nuclear grade is the most important histological parameter to predict prognosis in a patient of renal cell carcinoma (RCC). However, it suffers from inter-observer and intra-observer variation giving rise to need of a parameter that not only correlates with nuclear grade but is also objective and reproducible. Proliferation is the measure of aggressiveness of a tumour and it is strongly correlated with Fuhrman nuclear grade, clinical survival and recurrence in RCC. Ki-67 is conventionally used to assess proliferation. Mini-chromosome maintenance 2 (MCM-2) is a lesser known marker of proliferation and identifies a greater proliferation faction. This study was designed to assess the prognostic significance of MCM-2 by comparing it with Fuhrman nuclear grade and Ki-67. Material and Methods: n=50 cases of various ages, stages, histological subtypes and grades of RCC were selected for this study. Immunohistochemical staining using Ki-67(MIB-1, Mouse monoclonal antibody, Dako) and MCM-2 (Mouse monoclonal antibody, Thermo) was performed on the paraffin embedded blocks in the department of Morbid anatomy and Histopathology, University of Health Sciences, Lahore. Labeling indices (LI) were determined by two pathologists independently using quantitative and semi-quantitative analysis. Statistical analysis was carried out using SPSS 20.0. Kruskall-Wallis test was used to determine a correlation of proliferation markers with grade, and Pearson's correlate was used to determine correlation between the two proliferation markers. Results: Labeling index of MCM-2 (median=24.29%) was found to be much higher than Ki-67(median=13.05%). Both markers were significantly related with grade (p=0.00; Kruskall-Wallis test). LI of MCM-2 was found to correlate significantly with LI of Ki-67(r=0.0934;p=0.01 with Pearson's correlate). Results of semi-quantitative analysis correlated well with quantitative analysis. Conclusion: Both Ki-67 and MCM-2 are markers of proliferation which are closely linked to grade. Therefore, they can act as surrogate markers for grade in a manner that is more objective and reproducible. PMID:27532114

MCM - 2 and Ki - 67 as proliferation markers in renal cell carcinoma: A quantitative and semi - quantitative analysis.

PubMed

Mehdi, Muhammad Zain; Nagi, Abdul Hanan; Naseem, Nadia

2016-01-01

Fuhrman nuclear grade is the most important histological parameter to predict prognosis in a patient of renal cell carcinoma (RCC). However, it suffers from inter-observer and intra-observer variation giving rise to need of a parameter that not only correlates with nuclear grade but is also objective and reproducible. Proliferation is the measure of aggressiveness of a tumour and it is strongly correlated with Fuhrman nuclear grade, clinical survival and recurrence in RCC. Ki-67 is conventionally used to assess proliferation. Mini-chromosome maintenance 2 (MCM-2) is a lesser known marker of proliferation and identifies a greater proliferation faction. This study was designed to assess the prognostic significance of MCM-2 by comparing it with Fuhrman nuclear grade and Ki-67. n=50 cases of various ages, stages, histological subtypes and grades of RCC were selected for this study. Immunohistochemical staining using Ki-67(MIB-1, Mouse monoclonal antibody, Dako) and MCM-2 (Mouse monoclonal antibody, Thermo) was performed on the paraffin embedded blocks in the department of Morbid anatomy and Histopathology, University of Health Sciences, Lahore. Labeling indices (LI) were determined by two pathologists independently using quantitative and semi-quantitative analysis. Statistical analysis was carried out using SPSS 20.0. Kruskall-Wallis test was used to determine a correlation of proliferation markers with grade, and Pearson's correlate was used to determine correlation between the two proliferation markers. Labeling index of MCM-2 (median=24.29%) was found to be much higher than Ki-67(median=13.05%). Both markers were significantly related with grade (p=0.00; Kruskall-Wallis test). LI of MCM-2 was found to correlate significantly with LI of Ki-67(r=0.0934;p=0.01 with Pearson's correlate). Results of semi-quantitative analysis correlated well with quantitative analysis. Both Ki-67 and MCM-2 are markers of proliferation which are closely linked to grade. Therefore, they can act as surrogate markers for grade in a manner that is more objective and reproducible. Copyright® by the International Brazilian Journal of Urology.

Study of morphological changes in scattering and optically anisotropic medium through correlation images

NASA Astrophysics Data System (ADS)

Jain, Neha; Shukla, Prashant; Singh, Jai

2018-05-01

Correlation images are very useful in determining the morphological changes. We have investigated the correlation image analysis on depolarization and retardance matrices of polystyrene and gelatine samples respectively. We observed that that correlation images have a potential to show a significant variation with change in the concentration of samples (polystyrene and gelatine). For polystyrene microspheres the correlation value decreases with increasing scattering coefficient. In gelatine samples the correlation also decreases with sample concentration. This variation in correlation for retardance shows the change in a birefringence property of gelatine solution.

Utility of Urinary Protein-Creatinine Ratio and Protein Content in a 24-Hour Urine Collection in Systemic Lupus Erythematosus: A Systematic Review and Meta-Analysis.

PubMed

Medina-Rosas, Jorge; Yap, Kristy S; Anderson, Melanie; Su, Jiandong; Touma, Zahi

2016-09-01

To systematically review literature on the utility of spot urinary protein-creatinine ratio (PCR) as a screening test for proteinuria and its ability to accurately measure proteinuria compared with 24-hour urine collection (24H-P) in patients with systemic lupus erythematosus (SLE). We conducted a literature search (1900-2015) for articles comparing PCR and 24H-P in SLE patients in the databases Medline, Web of Science, and Embase. Included studies and their results were critically appraised and analyzed. Thirteen studies (1,001 patients; 84.01% women) were included. Ten studies reported on Pearson's correlation (range 0.67-0.94), and 3 studies reported on Spearman's correlation (range 0.78-1.00). The meta-analysis of studies with Pearson's correlation showed a high overall correlation of 0.80 between 24H-P and PCR, yet with high heterogeneity (I(2)  = 97.2%). Correlation analysis is not sufficient to evaluate the utility of a new test against the gold standard test, and analysis on agreement is required. Seven studies reported on agreement: 3 studies analyzed concordance correlation coefficient (0.48-0.94), 3 analyzed intraclass correlation coefficient (0.66-0.95), and 1 analyzed kappa coefficient (0.58). These results confirmed that the agreement between 24H-P and PCR was inappropriate. Three studies included Bland-Altman plots, and the results also demonstrated poor agreement between both tests. The PCR has a utility as a screening test for proteinuria in SLE patients. The studies' results of 24H-P and PCR showed poor agreement between both tests, signifying that PCR should not be a substitute for the gold standard test (24H-P) to accurately measure proteinuria. © 2016, American College of Rheumatology.

Phosphorylated neurofilament heavy: A potential blood biomarker to evaluate the severity of acute spinal cord injuries in adults

PubMed Central

Singh, Ajai; Kumar, Vineet; Ali, Sabir; Mahdi, Abbas Ali; Srivastava, Rajeshwer Nath

2017-01-01

Aims: The aim of this study is to analyze the serial estimation of phosphorylated neurofilament heavy (pNF-H) in blood plasma that would act as a potential biomarker for early prediction of the neurological severity of acute spinal cord injuries (SCI) in adults. Settings and Design: Pilot study/observational study. Subjects and Methods: A total of 40 patients (28 cases and 12 controls) of spine injury were included in this study. In the enrolled cases, plasma level of pNF-H was evaluated in blood samples and neurological evaluation was performed by the American Spinal Injury Association Injury Scale at specified period. Serial plasma neurofilament heavy values were then correlated with the neurological status of these patients during follow-up visits and were analyzed statistically. Statistical Analysis Used: Statistical analysis was performed using GraphPad InStat software (version 3.05 for Windows, San Diego, CA, USA). The correlation analysis between the clinical progression and pNF-H expression was done using Spearman's correlation. Results: The mean baseline level of pNF-H in cases was 6.40 ± 2.49 ng/ml, whereas in controls it was 0.54 ± 0.27 ng/ml. On analyzing the association between the two by Mann–Whitney U–test, the difference in levels was found to be statistically significant. The association between the neurological progression and pNF-H expression was determined using correlation analysis (Spearman's correlation). At 95% confidence interval, the correlation coefficient was found to be 0.64, and the correlation was statistically significant. Conclusions: Plasma pNF-H levels were elevated in accordance with the severity of SCI. Therefore, pNF-H may be considered as a potential biomarker to determine early the severity of SCI in adult patients. PMID:29291173

In-situ Isotopic Analysis at Nanoscale using Parallel Ion Electron Spectrometry: A Powerful New Paradigm for Correlative Microscopy

NASA Astrophysics Data System (ADS)

Yedra, Lluís; Eswara, Santhana; Dowsett, David; Wirtz, Tom

2016-06-01

Isotopic analysis is of paramount importance across the entire gamut of scientific research. To advance the frontiers of knowledge, a technique for nanoscale isotopic analysis is indispensable. Secondary Ion Mass Spectrometry (SIMS) is a well-established technique for analyzing isotopes, but its spatial-resolution is fundamentally limited. Transmission Electron Microscopy (TEM) is a well-known method for high-resolution imaging down to the atomic scale. However, isotopic analysis in TEM is not possible. Here, we introduce a powerful new paradigm for in-situ correlative microscopy called the Parallel Ion Electron Spectrometry by synergizing SIMS with TEM. We demonstrate this technique by distinguishing lithium carbonate nanoparticles according to the isotopic label of lithium, viz. 6Li and 7Li and imaging them at high-resolution by TEM, adding a new dimension to correlative microscopy.

Quantitative Evaluation of Head and Neck Cancer Treatment-Related Dysphagia in the Development of a Personalized Treatment Deintensification Paradigm.

PubMed

Quon, Harry; Hui, Xuan; Cheng, Zhi; Robertson, Scott; Peng, Luke; Bowers, Michael; Moore, Joseph; Choflet, Amanda; Thompson, Alex; Muse, Mariah; Kiess, Ana; Page, Brandi; Fakhry, Carole; Gourin, Christine; O'Hare, Jolyne; Graham, Peter; Szczesniak, Michal; Maclean, Julia; Cook, Ian; McNutt, Todd

2017-12-01

To test the hypothesis that quantifying swallow function with multiple patient-reported outcome (PRO) instruments is an important strategy to yield insights in the development of personalized deintensified therapies seeking to reduce the risk of head and neck cancer (HNC) treatment-related dysphagia (HNCTD). Irradiated HNC subjects seen in follow-up care (April 2015 to December 2015) who prospectively completed the Sydney Swallow Questionnaire (SSQ) and the MD Anderson Dysphagia Inventory (MDADI) concurrently on the web interface to our Oncospace database were evaluated. A correlation matrix quantified the relationship between the SSQ and MDADI. Machine-learning unsupervised cluster analysis using the elbow criterion and CLUSPLOT analysis to establish its validity was performed. We identified 89 subjects. The MDADI and SSQ scores were moderately but significantly correlated (correlation coefficient -0.69). K-means cluster analysis demonstrated that 3 unique statistical cohorts (elbow criterion) could be identified with CLUSPLOT analysis, confirming that 100% of variances were accounted for. Correlation coefficients between the individual items in the SSQ and the MDADI demonstrated weak to moderate negative correlation, except for SSQ17 (quality of life question). Pilot analysis demonstrates that the MDADI and SSQ are complementary. Three unique clusters of patients can be defined, suggesting that a unique dysphagia signature for HNCTD may be definable. Longitudinal studies relying on only a single PRO, such as MDADI, may be inadequate for classifying HNCTD. Copyright © 2017 Elsevier Inc. All rights reserved.

Continued investigation of potential application of Omega navigation to civil aviation

NASA Technical Reports Server (NTRS)

Baxa, E. G., Jr.

1978-01-01

Major attention is given to an analysis of receiver repeatability in measuring OMEGA phase data. Repeatability is defined as the ability of two like receivers which are co-located to achieve the same LOP phase readings. Specific data analysis is presented. A propagation model is described which has been used in the analysis of propagation anomalies. Composite OMEGA analysis is presented in terms of carrier phase correlation analysis and the determination of carrier phase weighting coefficients for minimizing composite phase variation. Differential OMEGA error analysis is presented for receiver separations. Three frequency analysis includes LOP error and position error based on three and four OMEGA transmissions. Results of phase amplitude correlation studies are presented.

Joint multifractal analysis based on wavelet leaders

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing

2017-12-01

Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.

Market impact and structure dynamics of the Chinese stock market based on partial correlation analysis

NASA Astrophysics Data System (ADS)

Li, Xing; Qiu, Tian; Chen, Guang; Zhong, Li-Xin; Wu, Xiao-Run

2017-04-01

Partial correlation analysis is employed to study the market impact on the Chinese stock market from both the native and external markets. Whereas the native market index is observed to have a great impact on the market correlations for both the Shanghai and Shenzhen stock markets, some external stock indices of the United States, European and Asian stock markets show a slight influence on the Chinese market. The individual stock can be affected by different economic sectors, but the dominant influence is from the sector the stock itself belongs to or closely related to, and the finance and insurance sector shows a weaker correlation with other economic sectors. Moreover, the market structure similarity exhibits a negative correlation with the price return in most time, and the structure similarity decays with the time interval.

Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences

PubMed Central

Bujkiewicz, Sylwia; Riley, Richard D

2016-01-01

Multivariate random-effects meta-analysis allows the joint synthesis of correlated results from multiple studies, for example, for multiple outcomes or multiple treatment groups. In a Bayesian univariate meta-analysis of one endpoint, the importance of specifying a sensible prior distribution for the between-study variance is well understood. However, in multivariate meta-analysis, there is little guidance about the choice of prior distributions for the variances or, crucially, the between-study correlation, ρB; for the latter, researchers often use a Uniform(−1,1) distribution assuming it is vague. In this paper, an extensive simulation study and a real illustrative example is used to examine the impact of various (realistically) vague prior distributions for ρB and the between-study variances within a Bayesian bivariate random-effects meta-analysis of two correlated treatment effects. A range of diverse scenarios are considered, including complete and missing data, to examine the impact of the prior distributions on posterior results (for treatment effect and between-study correlation), amount of borrowing of strength, and joint predictive distributions of treatment effectiveness in new studies. Two key recommendations are identified to improve the robustness of multivariate meta-analysis results. First, the routine use of a Uniform(−1,1) prior distribution for ρB should be avoided, if possible, as it is not necessarily vague. Instead, researchers should identify a sensible prior distribution, for example, by restricting values to be positive or negative as indicated by prior knowledge. Second, it remains critical to use sensible (e.g. empirically based) prior distributions for the between-study variances, as an inappropriate choice can adversely impact the posterior distribution for ρB, which may then adversely affect inferences such as joint predictive probabilities. These recommendations are especially important with a small number of studies and missing data. PMID:26988929

Analysis of Hand and Wrist Postural Synergies in Tolerance Grasping of Various Objects

PubMed Central

Liu, Yuan; Jiang, Li; Yang, Dapeng; Liu, Hong

2016-01-01

Human can successfully grasp various objects in different acceptable relative positions between human hand and objects. This grasp functionality can be described as the grasp tolerance of human hand, which is a significant functionality of human grasp. To understand the motor control of human hand completely, an analysis of hand and wrist postural synergies in tolerance grasping of various objects is needed. Ten healthy right-handed subjects were asked to perform the tolerance grasping with right hand using 6 objects of different shapes, sizes and relative positions between human hand and objects. Subjects were wearing CyberGlove attaching motion tracker on right hand, allowing a measurement of the hand and wrist postures. Correlation analysis of joints and inter-joint/inter-finger modules were carried on to explore the coordination between joints or modules. As the correlation between hand and wrist module is not obvious in tolerance grasping, individual analysis of wrist synergies would be more practical. In this case, postural synergies of hand and wrist were then presented separately through principal component analysis (PCA), expressed through the principal component (PC) information transmitted ratio, PC elements distribution and reconstructed angle error of joints. Results on correlation comparison of different module movements can be well explained by the influence factors of the joint movement correlation. Moreover, correlation analysis of joints and modules showed the wrist module had the lowest correlation among all inter-finger and inter-joint modules. Hand and wrist postures were both sufficient to be described by a few principal components. In terms of the PC elements distribution of hand postures, compared with previous investigations, there was a greater proportion of movement in the thumb joints especially the interphalangeal (IP) and opposition rotation (ROT) joint. The research could serve to a complete understanding of hand grasp, and the design, control of the anthropomorphic hand and wrist. PMID:27580298

Correlation between Volume of Apical Periodontitis Determined by Cone-beam Computed Tomography Analysis and Endotoxin Levels Found in Primary Root Canal Infection.

PubMed

Cardoso, Flávia G R; Ferreira, Nádia S; Martinho, Frederico C; Nascimento, Gustavo G; Manhães, Luiz R C; Rocco, Marco A; Carvalho, Cláudio A T; Valera, Marcia C

2015-07-01

This clinical study was conducted to correlate the levels of endotoxins and bacterial counts found in primary endodontic infection with the volume of periapical bone destruction determined by cone-beam computed tomography (CBCT) analysis. Moreover, the levels of bacteria and endotoxins were correlated with the development of clinical features. Twenty-four root canals with primary endodontic disease and apical periodontitis were selected. Clinical features such as pain on palpation, pain on percussion, and previous episode of pain were recorded. The volume (cubic millimeters) of periapical bone destruction was determined by CBCT analysis. Endotoxins and bacterial samplings were collected by using sterile/apyrogenic paper points. Endotoxins were quantified by using limulus amebocyte lysate assay (KQCL test), and bacterial count (colony-forming units [CFU]/mL) was determined by using anaerobic culture techniques. Data were analyzed by Pearson correlation and multiple logistic regression (P < .05). Endotoxins and bacteria were detected in 100% of the root canal samples (24 of 24), with median values of 10.92 endotoxin units (EU)/mL (1.75-128 EU/mL) and 7.5 × 10(5) CFU/mL (3.20 × 10(5)-8.16 × 10(6) CFU/mL), respectively. The median volume of bone destruction determined by CBCT analysis was 100 mm(3) (10-450 mm(3)). The multiple regression analysis revealed a positive correlation between higher levels of endotoxins present in root canal infection and larger volume of bone destruction (P < .05). Moreover, higher levels of endotoxins were also correlated with the presence of previous pain (P < .05). Our findings revealed that the levels of endotoxins found in root canal infection are related to the volume of periapical bone destruction determined by CBCT analysis. Moreover, the levels of endotoxin are related to the presence of previous pain. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

[Correlation of liver stiffness measured by FibroTouch and FibroScan with Ishak fibrosis score in patients with chronic hepatitis B].

PubMed

Chen, G F; Ping, J; Gu, H T; Zhao, Z M; Zhou, Y; Xing, F; Tao, Y Y; Mu, Y P; Liu, P; Liu, C H

2017-02-20

Objective: To investigate the correlation of liver stiffness measured by FibroTouch (FT) and FibroScan (FS) with Ishak fibrosis score in patients with chronic hepatitis B. Methods: A total of 313 patients with chronic hepatitis B who visited Department of Liver Cirrhosis in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 2014 to May 2016 were enrolled. All the patients underwent liver biopsy, and FT and FS were used to determine liver stiffness measurement (LSM). Serum biochemical parameters were measured, and the aspartate aminotransferase-to-platelet ratio index (APRI) in a multi-parameter model of liver fibrosis and fibrosis-4 (FIB-4) index were calculated. The consistency between the results of four noninvasive examinations and Ishak fibrosis score was compared. The t-test was used for comparison of LSM determined by FT and FS. Pearson correlation analysis was used investigate the correlation between LSM determined by FT and FS; Spearman correlation analysis was used to investigate the correlation of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels and Knodell score with LSM determined by FT and FS; the correlation between LSM determined by FT and FS and fibrosis stage was analyzed by partial correlation analysis adjusted by Knodell score for liver inflammatory activity; Spearman correlation analysis was used for APRI, FIB-4, and fibrosis stage. Based on the Ishak fibrosis score, the receiver operating characteristic (ROC) curve was used to analyze the values of four noninvasive methods in the diagnosis of liver fibrosis. Results: There was no significant difference in LSM measured by FT and FS in all patients (15.75±9.42 kPa vs 15.42±10.52 kPa, P > 0.05) and Pearson correlation analysis indicated a significant positive correlation between them ( r = 0.858, P < 0.01); serum ALT and AST levels and liver inflammatory activity were correlated with LSM determined by FT and FS. There was a significant positive correlation between LSM determined by FT and FS and fibrosis stage ( r = 0.501 and 0.526, both P < 0.001), and APRI and FIB-4 were also positively correlated with fibrosis stage ( r = 0.236 and 0.218, both P < 0.001). Based on the Ishak fibrosis score, in the diagnosis of fibrosis stages F3, F4, F5, and F6, the areas under the ROC curve were 0.915/0.856/0.839/0.816 for FT, 0.933/0.883/0.849/0.856 for FS, 0.618/0.630/0.608/0.638 for APRI, and 0.614/0.624/0.595/0.649 for FIB-4, and FT and FS had a significantly larger areas under the ROC curve than APRI and FIB-4. Conclusion: LSM determined by FT or FS has a good correlation with the Ishak fibrosis score, so FT and FS have a significantly better diagnostic performance for liver fibrosis than APRI and FIB-4.

Accuracy Evaluation of the Unified P-Value from Combining Correlated P-Values

PubMed Central

Alves, Gelio; Yu, Yi-Kuo

2014-01-01

Meta-analysis methods that combine -values into a single unified -value are frequently employed to improve confidence in hypothesis testing. An assumption made by most meta-analysis methods is that the -values to be combined are independent, which may not always be true. To investigate the accuracy of the unified -value from combining correlated -values, we have evaluated a family of statistical methods that combine: independent, weighted independent, correlated, and weighted correlated -values. Statistical accuracy evaluation by combining simulated correlated -values showed that correlation among -values can have a significant effect on the accuracy of the combined -value obtained. Among the statistical methods evaluated those that weight -values compute more accurate combined -values than those that do not. Also, statistical methods that utilize the correlation information have the best performance, producing significantly more accurate combined -values. In our study we have demonstrated that statistical methods that combine -values based on the assumption of independence can produce inaccurate -values when combining correlated -values, even when the -values are only weakly correlated. Therefore, to prevent from drawing false conclusions during hypothesis testing, our study advises caution be used when interpreting the -value obtained from combining -values of unknown correlation. However, when the correlation information is available, the weighting-capable statistical method, first introduced by Brown and recently modified by Hou, seems to perform the best amongst the methods investigated. PMID:24663491

Correlation between root respiration and the levels of biomass and glycyrrhizic acid in Glycyrrhiza uralensis

PubMed Central

Liu, Wenlan; Sun, Zhirong; Qu, Jixu; Yang, Chunning; Zhang, Xiaomin; Wei, Xinxin

2017-01-01

The aim of the present study was to investigate the correlation between root respiration and the levels of biomass and glycyrrhizic acid in Glycyrrhiza uralensis. Root respiration was determined using a biological oxygen analyzer. Respiration-related enzymes including glucose-6-phosphate dehydrogenase plus 6-phosphogluconate dehydrogenase, phosphohexose isomerase and succinate dehydrogenase, and respiratory pathways were evaluated. Biomass was determined by a drying-weighing method. In addition, the percentage of glycyrrhizic acid was detected using high-performance liquid chromatography. The association between root respiration and the levels of biomass and glycyrrhizic acid was investigated. The glycolysis pathway (EMP), tricarboxylic acid cycle (TCA) and pentose phosphate (PPP) pathway acted concurrently in the roots of G. uralensis. Grey correlation analysis showed that TCA had the strongest correlation (correlation coefficient, 0.8003) with biomass. Starch and acetyl coenzyme A had the closest association with above-ground biomass, while soluble sugar correlated less strongly with above-ground biomass. Grey correlation analysis between biochemical pathways and the intermediates showed that pyruvic acid had the strongest correlation with EMP, while acetyl coenzyme A correlated most strongly with TCA. Among the intermediates and pathways, pyruvic acid and EMP exhibited the greatest correlation with glycyrrhizic acid, while acetyl coenzyme A and TCA correlated with glycyrrhizic acid less closely. The results of this study may aid the cultivation of G. uralensis. However, these results require verification in further studies. PMID:28962162

Correlation between root respiration and the levels of biomass and glycyrrhizic acid in Glycyrrhiza uralensis.

PubMed

Liu, Wenlan; Sun, Zhirong; Qu, Jixu; Yang, Chunning; Zhang, Xiaomin; Wei, Xinxin

2017-09-01

The aim of the present study was to investigate the correlation between root respiration and the levels of biomass and glycyrrhizic acid in Glycyrrhiza uralensis . Root respiration was determined using a biological oxygen analyzer. Respiration-related enzymes including glucose-6-phosphate dehydrogenase plus 6-phosphogluconate dehydrogenase, phosphohexose isomerase and succinate dehydrogenase, and respiratory pathways were evaluated. Biomass was determined by a drying-weighing method. In addition, the percentage of glycyrrhizic acid was detected using high-performance liquid chromatography. The association between root respiration and the levels of biomass and glycyrrhizic acid was investigated. The glycolysis pathway (EMP), tricarboxylic acid cycle (TCA) and pentose phosphate (PPP) pathway acted concurrently in the roots of G. uralensis . Grey correlation analysis showed that TCA had the strongest correlation (correlation coefficient, 0.8003) with biomass. Starch and acetyl coenzyme A had the closest association with above-ground biomass, while soluble sugar correlated less strongly with above-ground biomass. Grey correlation analysis between biochemical pathways and the intermediates showed that pyruvic acid had the strongest correlation with EMP, while acetyl coenzyme A correlated most strongly with TCA. Among the intermediates and pathways, pyruvic acid and EMP exhibited the greatest correlation with glycyrrhizic acid, while acetyl coenzyme A and TCA correlated with glycyrrhizic acid less closely. The results of this study may aid the cultivation of G. uralensis . However, these results require verification in further studies.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

PubMed

Han, Fang; Liu, Han

2017-02-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.

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…

ANALYZING CORRELATIONS BETWEEN STREAM AND WATERSHED ATTRIBUTES

EPA Science Inventory

Bivariate correlation analysis has been widely used to explore relationships between stream and watershed attributes that have all been measured on the same set of watersheds or sampling locations. Researchers routinely test H0: =0 for each correlation in a large table and then ...

Relationships among the slopes of lines derived from various data analysis techniques and the associated correlation coefficient

NASA Technical Reports Server (NTRS)

Cohen, S. C.

1980-01-01

A technique for fitting a straight line to a collection of data points is given. The relationships between the slopes and correlation coefficients, and between the corresponding standard deviations and correlation coefficient are given.

A note on the correlation between circular and linear variables with an application to wind direction and air temperature data in a Mediterranean climate

NASA Astrophysics Data System (ADS)

Lototzis, M.; Papadopoulos, G. K.; Droulia, F.; Tseliou, A.; Tsiros, I. X.

2018-04-01

There are several cases where a circular variable is associated with a linear one. A typical example is wind direction that is often associated with linear quantities such as air temperature and air humidity. The analysis of a statistical relationship of this kind can be tested by the use of parametric and non-parametric methods, each of which has its own advantages and drawbacks. This work deals with correlation analysis using both the parametric and the non-parametric procedure on a small set of meteorological data of air temperature and wind direction during a summer period in a Mediterranean climate. Correlations were examined between hourly, daily and maximum-prevailing values, under typical and non-typical meteorological conditions. Both tests indicated a strong correlation between mean hourly wind directions and mean hourly air temperature, whereas mean daily wind direction and mean daily air temperature do not seem to be correlated. In some cases, however, the two procedures were found to give quite dissimilar levels of significance on the rejection or not of the null hypothesis of no correlation. The simple statistical analysis presented in this study, appropriately extended in large sets of meteorological data, may be a useful tool for estimating effects of wind on local climate studies.

Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data

NASA Astrophysics Data System (ADS)

Delignières, Didier; Marmelat, Vivien

2014-01-01

In this paper, we analyze empirical data, accounting for coordination processes between complex systems (bimanual coordination, interpersonal coordination, and synchronization with a fractal metronome), by using a recently proposed method: detrended cross-correlation analysis (DCCA). This work is motivated by the strong anticipation hypothesis, which supposes that coordination between complex systems is not achieved on the basis of local adaptations (i.e., correction, predictions), but results from a more global matching of complexity properties. Indeed, recent experiments have evidenced a very close correlation between the scaling properties of the series produced by two coordinated systems, despite a quite weak local synchronization. We hypothesized that strong anticipation should result in the presence of long-range cross-correlations between the series produced by the two systems. Results allow a detailed analysis of the effects of coordination on the fluctuations of the series produced by the two systems. In the long term, series tend to present similar scaling properties, with clear evidence of long-range cross-correlation. Short-term results strongly depend on the nature of the task. Simulation studies allow disentangling the respective effects of noise and short-term coupling processes on DCCA results, and suggest that the matching of long-term fluctuations could be the result of short-term coupling processes.

Characteristics of Loess Magnetic Susceptibility and Its Influencing Factors analysis in Hebei Country

NASA Astrophysics Data System (ADS)

Yuan, Jie; Cao, Guangchao; Chongyi, E.; Yuan, Youjing; Wu, Chengyong; Yu, Ming; Yang, Rongrong

2017-11-01

Taking the loess profile of Hebei countryside area as the research object, the magnetic susceptibility, particle size, SOC and chroma were measured respectively. The following conclusions are drawn from the analysis of the above indicators: Xhf value is between 20.56×10-8 m3 kg-1 and 107.81×10-8 m3 kg-1, Xfd value is between 0.31% and 8.74%. The content of silt (4 ∼ 63μm) is the largest in the particle size composition, followed by the clay content (<4μm), the sand content (>63μm) is the least. The SOC content of the whole profile was less, with an average of 8.69 g / kg. Among the chroma values, a* is between 6.65 and 10.3, L* is between 43.34 and 63.79, and b* is between 15.66 and 22.58. The correlation analysis showed that the correlation between grain size and Xhf was not significant (P>0.05), but has a significant correlation with Xfd (P<0.01) SOC has a significant correlation with magnetic susceptibility (P<0.01) There was a significant positive correlation between Xhf and chromaticity (P<0.01), but there was no correlation between Xfd (P>0.05).

Correlation between HIV-1 genotype and clinical progression in HIV/AIDS patients in Surabaya, Indonesia

NASA Astrophysics Data System (ADS)

Rachman, B. E.; Khairunisa, S. Q.; Witaningrum, A. M.; Yunifiar, M. Q.; Nasronudin

2018-03-01

Several factors such as host and viral factors can affect the progression of HIV/AIDS. This study aims to identify the correlation viral factors, especially the HIV-1 subtype with HIV/AIDS progression. Inpatient HIV/AIDS during the period March to September 2017 and willing to participate are included in the study. Historical data of disease and treatment was taken by medical record. Blood samples were amplified, sequenced and undergone phylogenetic analysis. Linear regression analysis was used to estimate beta coefficient (β) and 95%CI of HIV/AIDS progression (measured by the CD4 change rate, ΔCD4 cell count/time span in months).This study has 17 samples. The HIV-1 subtype was dominated by CRF01_AE (81.8%) followed by subtype B (18.2%). There was significant correlation between subtype HIV-1 (p = 0.04) and body mass index (p = 0.038) with HIV/AIDS clinical stage. Many factors were assumed to be correlated with increased rate of CD4, but we only subtype HIV-1 had a significant correlation (p = 0.024) with it. From multivariate analysis, we also found that subtype HIV-1 had a significant correlation (β = 0.788, 95%CI: 17.5-38.6, p = 0.004).

Correlation Analysis of Geomagnetic Data Synchronously Recorded by the INTERMAGNET Magnetic Laboratories

NASA Astrophysics Data System (ADS)

Vorobev, A. V.; Vorobeva, G. R.

2018-03-01

The results of the analysis of geomagnetic data synchronously recorded by the INTERMAGNET magnetic stations are presented. The goal of this research was to distinguish internal correlations between the data and to determine the optimal spatial interval of the geographical coordinates within which the efficient operation of only one magnetic observatory would be satisfactory in most occasions. The results of the observation of correlations between the geomagnetic data on a global scale are summarized and presented. Possible regions of application of these results are determined.

Heat and mass transfer correlations for liquid droplet of a pure fuel in combustion

NASA Astrophysics Data System (ADS)

Dgheim, J.; Chesneau, X.; Pietri, L.; Zeghmati, B.

The authors report a numerical analysis of heat and mass transfers, which govern the combustion of a fuel droplet assimilated to a sphere. The results are presented in the form of temperature, mass-fraction, Nusselt and Sherwood number profiles. The following heat and mass transfers correlations are developed: ; , which account for the effects of natural convection and the physical properties of the gas phase. These correlations agree with the results of detailed numerical analysis as well as the experimental data involving a single droplet.

Correlation analysis of the heat capacity and thermal expansion of solid mercury

NASA Astrophysics Data System (ADS)

Bodryakov, V. Yu.; Babintsev, Yu. N.

2015-06-01

A detailed analysis of the correlation between the volumetric thermal expansion coefficient o( T) and heat capacity C( T) of solid mercury has been performed. It has been shown that there is a clear correlation dependence o( C) not only in the low-temperature range, where it is linear and known as the Grüneisen law, but also up to the melting point of mercury. The dependence o( C) substantially deviates from the low-temperature linear behavior when the heat capacity reaches the classical Dulong-Petit limit of 3 R.

Long-range correlation in cosmic microwave background radiation.

PubMed

Movahed, M Sadegh; Ghasemi, F; Rahvar, Sohrab; Tabar, M Reza Rahimi

2011-08-01

We investigate the statistical anisotropy and gaussianity of temperature fluctuations of Cosmic Microwave Background (CMB) radiation data from the Wilkinson Microwave Anisotropy Probe survey, using the Multifractal Detrended Fluctuation Analysis, Rescaled Range, and Scaled Windowed Variance methods. Multifractal Detrended Fluctuation Analysis shows that CMB fluctuations has a long-range correlation function with a multifractal behavior. By comparing the shuffled and surrogate series of CMB data, we conclude that the multifractality nature of the temperature fluctuation of CMB radiation is mainly due to the long-range correlations, and the map is consistent with a gaussian distribution.

Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

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

Groen, E.A., E-mail: Evelyne.Groen@gmail.com; Heijungs, R.; Leiden University, Einsteinweg 2, Leiden 2333 CC

Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlationsmore » between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.« less

Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2017-07-01

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADC min and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau 2 =0.04 (p<0.0001), I 2 =73%, test for overall effect Z=8.67 (p<0.00001). ADC min correlated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Selling blood and gametes during tough economic times: insights from Google search.

PubMed

Wu, Jonathan A; Ngo, Tin C; Rothman, Cappy; Breyer, Benjamin N; Eisenberg, Michael L

2015-10-01

To use Google Insights search volume and publicly available economic indicators to test the hypothesis that sperm, egg, and blood donations increase during economic downturns and to demonstrate the feasibility of using Google search volume data to predict national trends in actual sperm, egg, and blood donations rates. Cross-correlation statistical analysis comparing Google search data for terms relating to blood, egg, and sperm donations with various economic indicators including the S&P 500 closing values, gross domestic product (GDP), the U.S. Index of Leading Indicators (U.S. Leading Index), gross savings rate, mortgage interest rates, unemployment rate, and consumer price index (CPI) from 2004-2011. A secondary analysis determined the Pearson correlation coefficient between Google search data with actual sperm, egg, and blood donation volume in the U.S. as measured by California Cryobank, the National Assisted Reproductive Technology Surveillance System, and the National Blood Collection and Utilization Survey, respectively. Significance of cross-correlation and Pearson correlation analysis as indicated by p value. There were several highly significant cross-correlation relationships between search volume and various economic indicators. Correlation between Google search volume for the term 'sperm donation,' 'egg donation,' and 'blood donation' with actual number of sperm, egg and blood donations in the United States demonstrated Pearson correlation coefficients of 0.2 (p > 0.10), -0.1 (p > 0.10), and 0.07 (p > 0.10), respectively. Temporal analysis showed an improved correlation coefficient of 0.9 (p < 0.05) for blood donation when shifted 12 months later relative to Google search volume. Google search volume data for search terms relating to sperm, egg, and blood donation increase during economic downturns. This finding suggests gamete and bodily fluid donations are influenced by market forces like other commodities. Google search may be useful for predicting blood donation trends but is more limited in predicting actual semen and oocyte donation patterns.

Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

PubMed

Veerkamp, R F; Koenen, E P; De Jong, G

2001-10-01

Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.

Analysis of the enhanced negative correlation between electron density and electron temperature related to earthquakes

NASA Astrophysics Data System (ADS)

Shen, X. H.; Zhang, X.; Liu, J.; Zhao, S. F.; Yuan, G. P.

2015-04-01

Ionospheric perturbations in plasma parameters have been observed before large earthquakes, but the correlation between different parameters has been less studied in previous research. The present study is focused on the relationship between electron density (Ne) and temperature (Te) observed by the DEMETER (Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions) satellite during local nighttime, in which a positive correlation has been revealed near the equator and a weak correlation at mid- and low latitudes over both hemispheres. Based on this normal background analysis, the negative correlation with the lowest percent in all Ne and Te points is studied before and after large earthquakes at mid- and low latitudes. The multiparameter observations exhibited typical synchronous disturbances before the Chile M8.8 earthquake in 2010 and the Pu'er M6.4 in 2007, and Te varied inversely with Ne over the epicentral areas. Moreover, statistical analysis has been done by selecting the orbits at a distance of 1000 km and ±7 days before and after the global earthquakes. Enhanced negative correlation coefficients lower than -0.5 between Ne and Te are found in 42% of points to be connected with earthquakes. The correlation median values at different seismic levels show a clear decrease with earthquakes larger than 7. Finally, the electric-field-coupling model is discussed; furthermore, a digital simulation has been carried out by SAMI2 (Sami2 is Another Model of the Ionosphere), which illustrates that the external electric field in the ionosphere can strengthen the negative correlation in Ne and Te at a lower latitude relative to the disturbed source due to the effects of the geomagnetic field. Although seismic activity is not the only source to cause the inverse Ne-Te variations, the present results demonstrate one possibly useful tool in seismo-electromagnetic anomaly differentiation, and a comprehensive analysis with multiple parameters helps to further understand the seismo-ionospheric coupling mechanism.

Inference for High-dimensional Differential Correlation Matrices *

PubMed Central

Cai, T. Tony; Zhang, Anru

2015-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed. PMID:26500380

Correlated bursts and the role of memory range

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Perotti, Juan I.; Kaski, Kimmo; Kertész, János

2015-08-01

Inhomogeneous temporal processes in natural and social phenomena have been described by bursts that are rapidly occurring events within short time periods alternating with long periods of low activity. In addition to the analysis of heavy-tailed interevent time distributions, higher-order correlations between interevent times, called correlated bursts, have been studied only recently. As the underlying mechanism behind such correlated bursts is far from being fully understood, we devise a simple model for correlated bursts using a self-exciting point process with a variable range of memory. Whether a new event occurs is stochastically determined by a memory function that is the sum of decaying memories of past events. In order to incorporate the noise and/or limited memory capacity of systems, we apply two memory loss mechanisms: a fixed number or a variable number of memories. By analysis and numerical simulations, we find that too much memory effect may lead to a Poissonian process, implying that there exists an intermediate range of memory effect to generate correlated bursts comparable to empirical findings. Our conclusions provide a deeper understanding of how long-range memory affects correlated bursts.

Resonance frequency analysis, insertion torque, and bone to implant contact of 4 implant surfaces: comparison and correlation study in sheep.

PubMed

Dagher, Maroun; Mokbel, Nadim; Jabbour, Gabriel; Naaman, Nada

2014-12-01

Primary stability is evaluated using resonance frequency analysis (RFA) and insertion torque (IT). Although there is a strong correlation between RFA and IT, studies failed to find a correlation between RFA and bone to implant contact (BIC) or IT and BIC. To compare RFA, IT, and BIC of SLA, SLActive, Euroteknika, and TiUnite implant surfaces and evaluate the correlation between them. Thirty-two implants were placed in 8 sheep. RFA and IT were recorded. Animals were killed at 1 and 2 months. A significant difference was found in RFA between the 4 surfaces. No significant difference was found for IT. Mean BIC was different between all 4 surfaces. A significant positive correlation was found between RFA and IT with SLA. No significant correlation was found between RFA and BIC and between IT and BIC at 1 and 2 months. Implants with 4 different surfaces have similar IT values but different RFA and BIC. Additionally irrespective of the implant surface, there is no correlation between IT and BIC and between RFA and BIC.

Correlations between trans-membrane pressure (TMP) and sludge properties in submerged membrane electro-bioreactor (SMEBR) and conventional membrane bioreactor (MBR).

PubMed

Hasan, Shadi W; Elektorowicz, Maria; Oleszkiewicz, Jan A

2012-09-01

The influence of sludge properties in SMEBR and conventional MBR pilot systems on membrane fouling was investigated. Generated data were analyzed using statistical analysis Pearson's product momentum correlation coefficient (r(p)). Analysis showed that TMP had strong direct (r(p)=0.9182) and inverse (r(p)=-0.9205) correlations to mean particle size diameter in MBR and SMEBR, respectively. TMP in SMEBR had a strong direct correlation to the sludge mixed liquor suspended solids concentration (MLSS) (r(p)=0.7757) while a weak direct correlation (r(p)=0.1940) was observed in MBR. SMEBR showed a moderate inverse correlation (r(p)=-0.6118) between TMP and soluble carbohydrates (EPS(c)) and a very weak direct correlation (r(p)=0.3448) to soluble proteins (EPS(p)). Conversely, EPS(p) in MBR had more significant impact (r(p)=0.4856) on membrane fouling than EPS(c) (r(p)=0.3051). The results provide insight into optimization of operational conditions in SMEBR system to overcome membrane fouling. Copyright © 2012 Elsevier Ltd. All rights reserved.

Analysis of spatial correlation in predictive models of forest variables that use LiDAR auxiliary information

Treesearch

F. Mauro; Vicente J. Monleon; H. Temesgen; L.A. Ruiz

2017-01-01

Accounting for spatial correlation of LiDAR model errors can improve the precision of model-based estimators. To estimate spatial correlation, sample designs that provide close observations are needed, but their implementation might be prohibitively expensive. To quantify the gains obtained by accounting for the spatial correlation of model errors, we examined (

Spectral and correlation analysis with applications to middle-atmosphere radars

NASA Technical Reports Server (NTRS)

Rastogi, Prabhat K.

1989-01-01

The correlation and spectral analysis methods for uniformly sampled stationary random signals, estimation of their spectral moments, and problems arising due to nonstationary are reviewed. Some of these methods are already in routine use in atmospheric radar experiments. Other methods based on the maximum entropy principle and time series models have been used in analyzing data, but are just beginning to receive attention in the analysis of radar signals. These methods are also briefly discussed.

Materials Requirements for Advanced Energy Systems - New Fuels. Volume 3: Materials Research Needs in Advanced Energy Systems Using New Fuels

DTIC Science & Technology

1974-07-01

elec- Materials se: trode materials and associ- operational ated conductors. 2.5.1 General. H" (02) Materials resources Technoeconomic analysis - None...Advanced Energy Systems Using New Fnels VIII Correlation and Analysis of Materials Requirements IX Research Recommendations and Priorities The authois...of government and industrial organizal ions who gave us the benefit of their knowledge and experience. iv VIII CORRELATION ANU ANALYSIS OF MATERIALS

Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean

NASA Astrophysics Data System (ADS)

Sulistyo, A.; Purwantoro; Sari, K. P.

2018-01-01

Selection is a routine activity in plant breeding programs that must be done by plant breeders in obtaining superior plant genotypes. The use of appropriate selection criteria will determine the effectiveness of selection activities. The purpose of this study was to analysis the inheritable agronomic traits that contribute to soybean yield. A total of 91 soybean lines were planted in Muneng Experimental Station, Probolinggo District, East Java Province, Indonesia in 2016. All soybean lines were arranged in randomized complete block design with two replicates. Correlation analysis, path analysis and heritability estimation were performed on days to flowering, days to maturing, plant height, number of branches, number of fertile nodes, number of filled pods, weight of 100 seeds, and yield to determine selection criteria on soybean breeding program. The results showed that the heritability value of almost all agronomic traits observed is high except for the number of fertile nodes with low heritability. The result of correlation analysis shows that days to flowering, plant height and number of fertile nodes have positive correlation with seed yield per plot (0.056, 0.444, and 0.100, respectively). In addition, path analysis showed that plant height and number of fertile nodes have highest positive direct effect on soybean yield. Based on this result, plant height can be selected as one of selection criteria in soybean breeding program to obtain high yielding soybean variety.

Inferring common cognitive mechanisms from brain blood-flow lateralization data: a new methodology for fTCD analysis.

PubMed

Meyer, Georg F; Spray, Amy; Fairlie, Jo E; Uomini, Natalie T

2014-01-01

Current neuroimaging techniques with high spatial resolution constrain participant motion so that many natural tasks cannot be carried out. The aim of this paper is to show how a time-locked correlation-analysis of cerebral blood flow velocity (CBFV) lateralization data, obtained with functional TransCranial Doppler (fTCD) ultrasound, can be used to infer cerebral activation patterns across tasks. In a first experiment we demonstrate that the proposed analysis method results in data that are comparable with the standard Lateralization Index (LI) for within-task comparisons of CBFV patterns, recorded during cued word generation (CWG) at two difficulty levels. In the main experiment we demonstrate that the proposed analysis method shows correlated blood-flow patterns for two different cognitive tasks that are known to draw on common brain areas, CWG, and Music Synthesis. We show that CBFV patterns for Music and CWG are correlated only for participants with prior musical training. CBFV patterns for tasks that draw on distinct brain areas, the Tower of London and CWG, are not correlated. The proposed methodology extends conventional fTCD analysis by including temporal information in the analysis of cerebral blood-flow patterns to provide a robust, non-invasive method to infer whether common brain areas are used in different cognitive tasks. It complements conventional high resolution imaging techniques.

Uses and Misuses of the Correlation Coefficient.

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Daniel, Larry G.

The purpose of this paper is to provide an in-depth critical analysis of the use and misuse of correlation coefficients. Various analytical and interpretational misconceptions are reviewed, beginning with the egregious assumption that correlational statistics may be useful in inferring causality. Additional misconceptions, stemming from…

Comparative Analysis of Mass Spectral Similarity Measures on Peak Alignment for Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry

PubMed Central

2013-01-01

Peak alignment is a critical procedure in mass spectrometry-based biomarker discovery in metabolomics. One of peak alignment approaches to comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) data is peak matching-based alignment. A key to the peak matching-based alignment is the calculation of mass spectral similarity scores. Various mass spectral similarity measures have been developed mainly for compound identification, but the effect of these spectral similarity measures on the performance of peak matching-based alignment still remains unknown. Therefore, we selected five mass spectral similarity measures, cosine correlation, Pearson's correlation, Spearman's correlation, partial correlation, and part correlation, and examined their effects on peak alignment using two sets of experimental GC×GC-MS data. The results show that the spectral similarity measure does not affect the alignment accuracy significantly in analysis of data from less complex samples, while the partial correlation performs much better than other spectral similarity measures when analyzing experimental data acquired from complex biological samples. PMID:24151524

Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

ERIC Educational Resources Information Center

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Topics on Test Methods for Space Systems and Operations Safety: Applicability of Experimental Data

NASA Technical Reports Server (NTRS)

Hirsch, David B.

2009-01-01

This viewgraph presentation reviews topics on test methods for space systems and operations safety through experimentation and analysis. The contents include: 1) Perception of reality through experimentation and analysis; 2) Measurements, methods, and correlations with real life; and 3) Correlating laboratory aerospace materials flammability data with data in spacecraft environments.

Psychometric Evaluation of a Triage Decision Making Inventory

DTIC Science & Technology

2011-06-27

the correlation matrix and inter-item correlations were reviewed. The Bartlett’s test of sphericity and the Kaiser - Meyer Olkin (KMO) were examined to...nursing experience. Principal component factor analysis with Varimax rotation was conducted using SPSS version 16. The Kaiser - Meyer - Olkin Measure of...Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 7 iterations

Understanding the Relationship between School-Based Management, Emotional Intelligence and Performance of Religious Upper Secondary School Principals in Banten Province

ERIC Educational Resources Information Center

Muslihah, Oleh Eneng

2015-01-01

The research examines the correlation between the understanding of school-based management, emotional intelligences and headmaster performance. Data was collected, using quantitative methods. The statistical analysis used was the Pearson Correlation, and multivariate regression analysis. The results of this research suggest firstly that there is…

Predicting Performance on State Achievement Tests Using Curriculum-Based Measurement in Reading: A Multilevel Meta-Analysis

ERIC Educational Resources Information Center

Yeo, Seungsoo

2010-01-01

The purpose of this synthesis was to examine the relationship between Curriculum-Based Measurement (CBM) and statewide achievement tests in reading. A multilevel meta-analysis was used to calculate the correlation coefficient of the population for 27 studies that met the inclusion criteria. Results showed an overall large correlation coefficient…

Acoustic Analysis of the Tremulous Voice: Assessing the Utility of the Correlation Dimension and Perturbation Parameters

ERIC Educational Resources Information Center

Shao, Jun; MacCallum, Julia K.; Zhang, Yu; Sprecher, Alicia; Jiang, Jack J.

2010-01-01

Acoustic analysis may provide a useful means to quantitatively characterize the tremulous voice. Signals were obtained from 25 subjects with diagnoses of either Parkinson's disease or vocal polyps exhibiting vocal tremor. These were compared to signals from 24 subjects with normal voices. Signals were analyzed via correlation dimension and several…

Classical Item Analysis Using Latent Variable Modeling: A Note on a Direct Evaluation Procedure

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2011-01-01

A directly applicable latent variable modeling procedure for classical item analysis is outlined. The method allows one to point and interval estimate item difficulty, item correlations, and item-total correlations for composites consisting of categorical items. The approach is readily employed in empirical research and as a by-product permits…

The Relationship between Pay and Job Satisfaction: A Meta-Analysis of the Literature

ERIC Educational Resources Information Center

Judge, Timothy A.; Piccolo, Ronald F.; Podsakoff, Nathan P.; Shaw, John C.; Rich, Bruce L.

2010-01-01

Whereas the motivational aspects of pay are well-documented, the notion that high pay leads to high levels of satisfaction is not without debate. The current study used meta-analysis to estimate the population correlation between pay level and measures of pay and job satisfaction. Cumulating across 115 correlations from 92 independent samples,…

Principal components analysis in clinical studies.

PubMed

Zhang, Zhongheng; Castelló, Adela

2017-09-01

In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

Coherence Analysis of the Solar Wind Between l1 and the Lunar Orbit

NASA Astrophysics Data System (ADS)

Crane, S. O.; Fuqua, H.; Poppe, A. R.; Harada, Y.; Fatemi, S.; Delory, G. T.

2016-12-01

A cross correlation analysis of the lunar and solar wind interaction was performed to understand coherence length scales. This is mandatory for conducting tests in electromagnetic sounding of the moon with two measurement probes. Signal processing and data analysis methods encompass the study of the lunar electromagnetic plasma environment with properties of the solar wind at key positions outside of Earth's magnetosphere. Variations in solar activity detected by ACE, WIND, Kaguya and Lunar Prospector can be informative regarding how well correlated the magnetic properties of the solar wind are between the 1st Lagrange point (ACE & WIND orbits) and the lunar orbit (Kaguya & Lunar Prospector investigations). The analysis objective is to use cross correlation to understand the solar wind coherence between these positions. This requires mastering concrete analysis tools to filter and use data that yields high (>0.80) or intermediate (0.70-0.80) coherence values, while demonstrating an analysis of up to one month of data, and archiving poor (<0.50) cross correlation coefficients for effects of orbit position and downstream distance. We also consider the impact of high energy events such as Coronal Mass Ejections, Solar Flares, and shocks that may be recorded by `ACE's List of Disturbances and Transients' to the effect that, at the current level of analysis, various expected coefficients between 0.55 and 0.85 have been generated for up to 3 months of data, 2008-02-01 through 2008-05-03.

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

Association between perfluoroalkyl substances exposure and thyroid function in adults: A meta-analysis

PubMed Central

Oh, Byung-Chul; Jung, Dawoon; Ji, Kyunghee; Choi, Kyungho

2018-01-01

Objective Many people are exposed to perfluoroalkyl substances (PFASs) because these substances are widely used as industrial products. Although epidemiological studies suggest that PFASs can disrupt thyroid hormones, the association between PFAS exposure and thyroid function remains inconclusive. Therefore, we performed a comprehensive meta-analysis to investigate the association between PFASs exposure and thyroid hormones. Methods We searched medical literature databases for articles on the association between PFASs–perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS)–and thyroid hormone levels in adults. Twelve articles were included in the meta-analysis, and the pooled z values were calculated with correlation or regression coefficients. Results The blood PFOS concentration was positively correlated with free T4. The pooled z value was 0.05 (95% confidence interval (CI): 0.03, 0.08). PFOS was negatively correlated with total T4 and total T3 when excluding outlier studies. In a subgroup analysis stratified by mean PFOS concentration, PFOS was observed to be positively associated with free T4 and TSH and negatively associated with total T3 in the intermediate concentration group (8–16 ng/mL). PFOA concentration was negatively correlated with total T4 (z value, -0.06; 95% CI: -0.09, -0.03) after omitting one outlier study. PFHxS also showed a negative correlation with total T4 (z value, -0.04; 95% CI: -0.07, -0.01). A subgroup analysis of pregnant women showed that there was no association between PFASs and thyroid hormones. Conclusions Our meta-analysis suggests that PFASs are negatively associated with total T4, and their effect can be different depending on the PFAS concentration. PMID:29746532

A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

2016-06-01

In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865-1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields.

Application of the specular and diffuse reflection analysis for in vitro diagnostics of dental erosion: correlation with enamel softening, roughness, and calcium release

PubMed Central

Rakhmatullina, Ekaterina; Bossen, Anke; Höschele, Christoph; Wang, Xiaojie; Beyeler, Barbara; Meier, Christoph; Lussi, Adrian

2011-01-01

We present assembly and application of an optical reflectometer for the analysis of dental erosion. The erosive procedure involved acid-induced softening and initial substance loss phases, which are considered to be difficult for visual diagnosis in a clinic. Change of the specular reflection signal showed the highest sensitivity for the detection of the early softening phase of erosion among tested methods. The exponential decrease of the specular reflection intensity with erosive duration was compared to the increase of enamel roughness. Surface roughness was measured by optical analysis, and the observed tendency was correlated with scanning electron microscopy images of eroded enamel. A high correlation between specular reflection intensity and measurement of enamel softening (r2 ≥ −0.86) as well as calcium release (r2 ≥ −0.86) was found during erosion progression. Measurement of diffuse reflection revealed higher tooth-to-tooth deviation in contrast to the analysis of specular reflection intensity and lower correlation with other applied methods (r2 = 0.42–0.48). The proposed optical method allows simple and fast surface analysis and could be used for further optimization and construction of the first noncontact and cost-effective diagnostic tool for early erosion assessment in vivo. PMID:22029364

Combining individual participant and aggregated data in a meta-analysis with correlational studies.

PubMed

Pigott, Terri; Williams, Ryan; Polanin, Joshua

2012-12-01

This paper presents methods for combining individual participant data (IPD) with aggregated study level data (AD) in a meta-analysis of correlational studies. Although medical researchers have employed IPD in a wide range of studies, only a single example exists in the social sciences. New policies at the National Science Foundation requiring grantees to submit data archiving plans may increase social scientists' access to individual level data that could be combined with traditional meta-analysis. The methods presented here extend prior work on IPD to meta-analyses using correlational studies. The examples presented illustrate the synthesis of publicly available national datasets in education with aggregated study data from a meta-analysis examining the correlation of socioeconomic status measures and academic achievement. The major benefit of the inclusion of the individual level is that both within-study and between-study interactions among moderators of effect size can be estimated. Given the potential growth in data archives in the social sciences, we should see a corresponding increase in the ability to synthesize IPD and AD in a single meta-analysis, leading to a more complete understanding of how within-study and between-study moderators relate to effect size. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.

PubMed

Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A

2011-04-01

Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.

Application of the specular and diffuse reflection analysis for in vitro diagnostics of dental erosion: correlation with enamel softening, roughness, and calcium release

NASA Astrophysics Data System (ADS)

Rakhmatullina, Ekaterina; Bossen, Anke; Höschele, Christoph; Wang, Xiaojie; Beyeler, Barbara; Meier, Christoph; Lussi, Adrian

2011-10-01

We present assembly and application of an optical reflectometer for the analysis of dental erosion. The erosive procedure involved acid-induced softening and initial substance loss phases, which are considered to be difficult for visual diagnosis in a clinic. Change of the specular reflection signal showed the highest sensitivity for the detection of the early softening phase of erosion among tested methods. The exponential decrease of the specular reflection intensity with erosive duration was compared to the increase of enamel roughness. Surface roughness was measured by optical analysis, and the observed tendency was correlated with scanning electron microscopy images of eroded enamel. A high correlation between specular reflection intensity and measurement of enamel softening (r2 >= -0.86) as well as calcium release (r2 >= -0.86) was found during erosion progression. Measurement of diffuse reflection revealed higher tooth-to-tooth deviation in contrast to the analysis of specular reflection intensity and lower correlation with other applied methods (r2 = 0.42-0.48). The proposed optical method allows simple and fast surface analysis and could be used for further optimization and construction of the first noncontact and cost-effective diagnostic tool for early erosion assessment in vivo.

Frequency-phase analysis of resting-state functional MRI

PubMed Central

Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

2017-01-01

We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522

Blastocoele expansion degree predicts live birth after single blastocyst transfer for fresh and vitrified/warmed single blastocyst transfer cycles.

PubMed

Du, Qing-Yun; Wang, En-Yin; Huang, Yan; Guo, Xiao-Yi; Xiong, Yu-Jing; Yu, Yi-Ping; Yao, Gui-Dong; Shi, Sen-Lin; Sun, Ying-Pu

2016-04-01

To evaluate the independent effects of the degree of blastocoele expansion and re-expansion and the inner cell mass (ICM) and trophectoderm (TE) grades on predicting live birth after fresh and vitrified/warmed single blastocyst transfer. Retrospective study. Reproductive medical center. Women undergoing 844 fresh and 370 vitrified/warmed single blastocyst transfer cycles. None. Live-birth rate correlated with blastocyst morphology parameters by logistic regression analysis and Spearman correlations analysis. The degree of blastocoele expansion and re-expansion was the only blastocyst morphology parameter that exhibited a significant ability to predict live birth in both fresh and vitrified/warmed single blastocyst transfer cycles respectively by multivariate logistic regression and Spearman correlations analysis. Although the ICM grade was significantly related to live birth in fresh cycles according to the univariate model, its effect was not maintained in the multivariate logistic analysis. In vitrified/warmed cycles, neither ICM nor TE grade was correlated with live birth by logistic regression analysis. This study is the first to confirm that the degree of blastocoele expansion and re-expansion is a better predictor of live birth after both fresh and vitrified/warmed single blastocyst transfer cycles than ICM or TE grade. Copyright © 2016. Published by Elsevier Inc.

Ground reaction force analysed with correlation coefficient matrix in group of stroke patients.

PubMed

Szczerbik, Ewa; Krawczyk, Maciej; Syczewska, Małgorzata

2014-01-01

Stroke is the third cause of death in contemporary society and causes many disorders. Clinical scales, ground reaction force (GRF) and objective gait analysis are used for assessment of patient's rehabilitation progress during treatment. The goal of this paper is to assess whether signal correlation coefficient matrix applied to GRF can be used for evaluation of the status of post-stroke patients. A group of patients underwent clinical assessment and instrumented gait analysis simultaneously three times. The difference between components of patient's GRF (vertical, fore/aft, med/lat) and normal ones (reference GRF of healthy subjects) was calculated as correlation coefficient. Patients were divided into two groups ("worse" and "better") based on the clinical functional scale tests done at the beginning of rehabilitation process. The results obtained by these two groups were compared using statistical analysis. An increase of median value of correlation coefficient is observed in all components of GRF, but only in non-paretic leg. Analysis of GRF signal can be helpful in assessment of post-stroke patients during rehabilitation. Improvement in stroke patients was observed in non-paretic leg of the "worse" group. GRF analysis should not be the only tool for objective validation of patient's improvement, but could be used as additional source of information.

Correlation analysis of targeted proteins and metabolites to assess and engineer microbial isopentenol production.

PubMed

George, Kevin W; Chen, Amy; Jain, Aakriti; Batth, Tanveer S; Baidoo, Edward E K; Wang, George; Adams, Paul D; Petzold, Christopher J; Keasling, Jay D; Lee, Taek Soon

2014-08-01

The ability to rapidly assess and optimize heterologous pathway function is critical for effective metabolic engineering. Here, we develop a systematic approach to pathway analysis based on correlations between targeted proteins and metabolites and apply it to the microbial production of isopentenol, a promising biofuel. Starting with a seven-gene pathway, we performed a correlation analysis to reduce pathway complexity and identified two pathway proteins as the primary determinants of efficient isopentenol production. Aided by the targeted quantification of relevant pathway intermediates, we constructed and subsequently validated a conceptual model of isopentenol pathway function. Informed by our analysis, we assembled a strain which produced isopentenol at a titer 1.5 g/L, or 46% of theoretical yield. Our engineering approach allowed us to accurately identify bottlenecks and determine appropriate pathway balance. Paired with high-throughput cloning techniques and analytics, this strategy should prove useful for the analysis and optimization of increasingly complex heterologous pathways. © 2014 Wiley Periodicals, Inc.

Extreme values in the Chinese and American stock markets based on detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Zhang, Minjia

2015-10-01

This paper focuses on the comparative analysis of extreme values in the Chinese and American stock markets based on the detrended fluctuation analysis (DFA) algorithm using the daily data of Shanghai composite index and Dow Jones Industrial Average. The empirical results indicate that the multifractal detrended fluctuation analysis (MF-DFA) method is more objective than the traditional percentile method. The range of extreme value of Dow Jones Industrial Average is smaller than that of Shanghai composite index, and the extreme value of Dow Jones Industrial Average is more time clustering. The extreme value of the Chinese or American stock markets is concentrated in 2008, which is consistent with the financial crisis in 2008. Moreover, we investigate whether extreme events affect the cross-correlation between the Chinese and American stock markets using multifractal detrended cross-correlation analysis algorithm. The results show that extreme events have nothing to do with the cross-correlation between the Chinese and American stock markets.

Bias due to two-stage residual-outcome regression analysis in genetic association studies.

PubMed

Demissie, Serkalem; Cupples, L Adrienne

2011-11-01

Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

Correlates of perceived stigma for people living with epilepsy: A meta-analysis.

PubMed

Shi, Ying; Wang, Shouqi; Ying, Jie; Zhang, Meiling; Liu, Pengcheng; Zhang, Huanhuan; Sun, Jiao

2017-05-01

Epilepsy, one of the most common, serious chronic neurological diseases, is accompanied by different levels of perceived stigma that affects people in almost all age groups. This stigma can negatively impact the physical and mental health of people living with epilepsy (PLWE). Good knowledge of perceived stigma for PLWE is important. In this study, we conducted a meta-analysis to identify the correlates of perceived stigma for PLWE. Studies on factors associated with perceived stigma for PLWE, including sociodemographic, psychosocial, and disease-related variables, were searched in PubMed, PsychINFO, EMBASE, and Web of Science. Nineteen variables (k>1) were included in the meta-analysis. For sociodemographic characteristics, findings revealed that the significant weighted mean correlation (R) for "residence" and "poor financial status" were 0.177 and 0.286, respectively. For disease-related characteristics, all variables of significance, including "seizure severity," "seizure frequency," "number of medicines," and "adverse event" (R ranging from 0.190 to 0.362), were positively correlated with perceived stigma. For psychosocial characteristics, "depression" and "anxiety" with R values of 0.414 and 0.369 were significantly associated with perceived stigma. In addition, "social support," "quality of life (QOLIE-31,89)," "knowledge," and "attitude," with R values ranging from -0.444 to -0.200 indicating negative correlation with perceived stigma. The current meta-analysis evaluated the correlates of perceived stigma for PLWE. Results can serve as a basis for policymakers and healthcare professionals for formulating health promotion and prevention strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

Time Correlations of Lightning Flash Sequences in Thunderstorms Revealed by Fractal Analysis

NASA Astrophysics Data System (ADS)

Gou, Xueqiang; Chen, Mingli; Zhang, Guangshu

2018-01-01

By using the data of lightning detection and ranging system at the Kennedy Space Center, the temporal fractal and correlation of interevent time series of lightning flash sequences in thunderstorms have been investigated with Allan factor (AF), Fano factor (FF), and detrended fluctuation analysis (DFA) methods. AF, FF, and DFA methods are powerful tools to detect the time-scaling structures and correlations in point processes. Totally 40 thunderstorms with distinguishing features of a single-cell storm and apparent increase and decrease in the total flash rate were selected for the analysis. It is found that the time-scaling exponents for AF (αAF) and FF (αFF) analyses are 1.62 and 0.95 in average, respectively, indicating a strong time correlation of the lightning flash sequences. DFA analysis shows that there is a crossover phenomenon—a crossover timescale (τc) ranging from 54 to 195 s with an average of 114 s. The occurrence of a lightning flash in a thunderstorm behaves randomly at timescales <τc but shows strong time correlation at scales >τc. Physically, these may imply that the establishment of an extensive strong electric field necessary for the occurrence of a lightning flash needs a timescale >τc, which behaves strongly time correlated. But the initiation of a lightning flash within a well-established extensive strong electric field may involve the heterogeneities of the electric field at a timescale <τc, which behave randomly.

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

Analysis of Vibration and Noise of Construction Machinery Based on Ensemble Empirical Mode Decomposition and Spectral Correlation Analysis Method

NASA Astrophysics Data System (ADS)

Chen, Yuebiao; Zhou, Yiqi; Yu, Gang; Lu, Dan

In order to analyze the effect of engine vibration on cab noise of construction machinery in multi-frequency bands, a new method based on ensemble empirical mode decomposition (EEMD) and spectral correlation analysis is proposed. Firstly, the intrinsic mode functions (IMFs) of vibration and noise signals were obtained by EEMD method, and then the IMFs which have the same frequency bands were selected. Secondly, we calculated the spectral correlation coefficients between the selected IMFs, getting the main frequency bands in which engine vibration has significant impact on cab noise. Thirdly, the dominated frequencies were picked out and analyzed by spectral analysis method. The study result shows that the main frequency bands and dominated frequencies in which engine vibration have serious impact on cab noise can be identified effectively by the proposed method, which provides effective guidance to noise reduction of construction machinery.

Global Interactions Analysis of Epileptic ECoG Data

NASA Astrophysics Data System (ADS)

Ortega, Guillermo J.; Sola, Rafael G.; Pastor, Jesús

2007-05-01

Localization of the epileptogenic zone is an important issue in epileptology, even though there is not a unique definition of the epileptic focus. The objective of the present study is to test ultrametric analysis to uncover cortical interactions in human epileptic data. Correlation analysis has been carried out over intraoperative Electro-Corticography (ECoG) data in 2 patients suffering from temporal lobe epilepsy (TLE). Recordings were obtained using a grid of 20 electrodes (5×4) covering the lateral temporal lobe and a strip of either 4 or 8 electrodes at the mesial temporal lobe. Ultrametric analysis was performed in the averaged final correlation matrices. By using the matrix of linear correlation coefficients and the appropriate metric distance between pairs of electrodes time series, we were able to construct Minimum Spanning Trees (MST). The topological connectivity displayed by these trees gives useful and valuable information regarding physiological and pathological information in the temporal lobe of epileptic patients.

Local-feature analysis for automated coarse-graining of bulk-polymer molecular dynamics simulations.

PubMed

Xue, Y; Ludovice, P J; Grover, M A

2012-12-01

A method for automated coarse-graining of bulk polymers is presented, using the data-mining tool of local feature analysis. Most existing methods for polymer coarse-graining define superatoms based on their covalent bonding topology along the polymer backbone, but here superatoms are defined based only on their correlated motions, as observed in molecular dynamics simulations. Correlated atomic motions are identified in the simulation data using local feature analysis, between atoms in the same or in different polymer chains. Groups of highly correlated atoms constitute the superatoms in the coarse-graining scheme, and the positions of their seed coordinates are then projected forward in time. Based on only the seed positions, local feature analysis enables the full reconstruction of all atomic positions. This reconstruction suggests an iterative scheme to reduce the computation of the simulations to initialize another short molecular dynamic simulation, identify new superatoms, and again project forward in time.

Nonlinear Analysis on Cross-Correlation of Financial Time Series by Continuum Percolation System

NASA Astrophysics Data System (ADS)

Niu, Hongli; Wang, Jun

We establish a financial price process by continuum percolation system, in which we attribute price fluctuations to the investors’ attitudes towards the financial market, and consider the clusters in continuum percolation as the investors share the same investment opinion. We investigate the cross-correlations in two return time series, and analyze the multifractal behaviors in this relationship. Further, we study the corresponding behaviors for the real stock indexes of SSE and HSI as well as the liquid stocks pair of SPD and PAB by comparison. To quantify the multifractality in cross-correlation relationship, we employ multifractal detrended cross-correlation analysis method to perform an empirical research for the simulation data and the real markets data.

Coherent light depolarization by multiple scattering media and tissues: some fundamentals and applications

NASA Astrophysics Data System (ADS)

Zimnyakov, Dmitry A.; Tuchin, Valery V.; Yodh, Arjun G.; Mishin, Alexey A.; Peretochkin, Igor S.

1998-04-01

Relationships between decorrelation and depolarization of coherent light scattered by disordered media are examined by using the conception of the photon paths distribution functions. Analysis of behavior of the autocorrelation functions of the scattered field fluctuations and their polarization properties allows us to introduce generalized parameter of scattering media such as specific correlation time. Determination of specific correlation time has been carried out for phantom scattering media (water suspensions of polystyrene spheres). Results of statistical, correlation and polarization analysis of static and dynamic speckle patterns carried out in the experiments with human sclera with artificially controlled optical transmittance are presented. Some possibilities of applications of such polarization- correlation technique for monitoring and visualization of non- single scattering tissue structures are discussed.

Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Zhang, Hong; Gao, You

2017-01-01

Identifying the mutual interaction in aero-engine gas path system is a crucial problem that facilitates the understanding of emerging structures in complex system. By employing the multiscale multifractal detrended cross-correlation analysis method to aero-engine gas path system, the cross-correlation characteristics between gas path system parameters are established. Further, we apply multiscale multifractal detrended cross-correlation distance matrix and minimum spanning tree to investigate the mutual interactions of gas path variables. The results can infer that the low-spool rotor speed (N1) and engine pressure ratio (EPR) are main gas path parameters. The application of proposed method contributes to promote our understanding of the internal mechanisms and structures of aero-engine dynamics.

An analysis of high school students' perceptions and academic performance in laboratory experiences

NASA Astrophysics Data System (ADS)

Mirchin, Robert Douglas

This research study is an investigation of student-laboratory (i.e., lab) learning based on students' perceptions of experiences using questionnaire data and evidence of their science-laboratory performance based on paper-and-pencil assessments using Maryland-mandated criteria, Montgomery County Public Schools (MCPS) criteria, and published laboratory questions. A 20-item questionnaire consisting of 18 Likert-scale items and 2 open-ended items that addressed what students liked most and least about lab was administered to students before labs were observed. A pre-test and post-test assessing laboratory achievement were administered before and after the laboratory experiences. The three labs observed were: soda distillation, stoichiometry, and separation of a mixture. Five significant results or correlations were found. For soda distillation, there were two positive correlations. Student preference for analyzing data was positively correlated with achievement on the data analysis dimension of the lab rubric. A student preference for using numbers and graphs to analyze data was positively correlated with achievement on the analysis dimension of the lab rubric. For the separating a mixture lab data the following pairs of correlations were significant. Student preference for doing chemistry labs where numbers and graphs were used to analyze data had a positive correlation with writing a correctly worded hypothesis. Student responses that lab experiences help them learn science positively correlated with achievement on the data dimension of the lab rubric. The only negative correlation found related to the first result where students' preference for computers was inversely correlated to their performance on analyzing data on their lab report. Other findings included the following: students like actual experimental work most and the write-up and analysis of a lab the least. It is recommended that lab science instruction be inquiry-based, hands-on, and that students be tested for lab content acquisition. The final conclusion of the study is that students expressed a preference for working in groups and working with materials and equipment as opposed to individual, non-group work and analyzing data.

Investigation of grapevine photosynthesis using hyperspectral techniques and development of hyperspectral band ratio indices sensitive to photosynthesis.

PubMed

Ozelkan, Emre; Karaman, Muhittin; Candar, Serkan; Coskun, Zafer; Ormeci, Cankut

2015-01-01

The photosynthetic rate of 9 different grapevines were analyzed with simultaneous photosynthesis and spectroradiometric measurements on 08.08.2012 (veraison) and 06.09.2012 (harvest). The wavelengths and spectral regions, which most properly express photosynthetic rate, were determined using correlation and regression analysis. In addition, hyperspectral band ratio (BR) indices sensitive to photosynthesis were developed using optimum band ratio (OBRA) method. The relation of BR results with photosynthesis values are presented with the correlation matrix maps created in this study. The examinations were performed for both specific dates (i.e., veraison and harvest) and also in aggregate (i.e., correlation between total spectra and photosynthesis data). For specific dates wavelength based analysis, the photosynthesis were best determined with -0.929 correlation coefficient (r) 609 nm of yellow region at veraison stage, and -0.870 at 641 nm of red region at harvest stage. For wavelength based aggregate analysis, 640 nm of red region was found to be correlated with 0.921 and -0.867 r values respectively and red edge (RE) (695 nm) was found to be correlated with -0.922 and -0.860 r values, respectively. When BR indices results were analyzed with photosynthetic values for specific dates, -0.987 r with R8../R, at veraison stage and -0.911 r with R696/R944 at harvest stage were found most correlated. For aggregate analysis of BR, common BR presenting great correlation with photosynthesis for both measurements was found to be R632/R971 with -0.974, -0.881 r values, respectively and other R610/R760 with -0.976, -0.879 r values. The final results of this study indicate that the proportion of RE region to a region with direct or indirect correlation with photosynthetic provides information about rate of photosynthesis. With the indices created in this study, the photosynthesis rate of vineyards can be determined using in-situ hyperspectral remote sensing. The findings of this study would enable cost-efficient, rapid and effective control of viticulture activities.

A Pragmatic Bayesian Perspective on Correlation Analysis. The exoplanetary gravity - stellar activity case

NASA Astrophysics Data System (ADS)

Figueira, P.; Faria, J. P.; Adibekyan, V. Zh.; Oshagh, M.; Santos, N. C.

2016-11-01

We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, ρ, characterizing the strength of the correlation. We provide an implementation of these ideas and concepts using python programming language and the pyMC module in a very short (˜ 130 lines of code, heavily commented) and user-friendly program. We used this tool to assess the presence and properties of the correlation between planetary surface gravity and stellar activity level as measured by the log(R^' }_{ {HK}}) indicator. The results of the Bayesian analysis are qualitatively similar to those obtained via p-value analysis, and support the presence of a correlation in the data. The results are more robust in their derivation and more informative, revealing interesting features such as asymmetric posterior distributions or markedly different credible intervals, and allowing for a deeper exploration. We encourage the reader interested in this kind of problem to apply our code to his/her own scientific problems. The full understanding of what the Bayesian framework is can only be gained through the insight that comes by handling priors, assessing the convergence of Monte Carlo runs, and a multitude of other practical problems. We hope to contribute so that Bayesian analysis becomes a tool in the toolkit of researchers, and they understand by experience its advantages and limitations.

Detrended Cross Correlation Analysis: a new way to figure out the underlying cause of global warming

NASA Astrophysics Data System (ADS)

Hazra, S.; Bera, S. K.

2016-12-01

Analysing non-stationary time series is a challenging task in earth science, seismology, solar physics, climate, biology, finance etc. Most of the cases external noise like oscillation, high frequency noise, low frequency noise in different scales lead to erroneous result. Many statistical methods are proposed to find the correlation between two non-stationary time series. N. Scafetta and B. J. West, Phys. Rev. Lett. 90, 248701 (2003), reported a strong relationship between solar flare intermittency (SFI) and global temperature anomalies (GTA) using diffusion entropy analysis. It has been recently shown that detrended cross correlation analysis (DCCA) is better technique to remove the effects of any unwanted signal as well as local and periodic trend. Thus DCCA technique is more suitable to find the correlation between two non-stationary time series. By this technique, correlation coefficient at different scale can be estimated. Motivated by this here we have applied a new DCCA technique to find the relationship between SFI and GTA. We have also applied this technique to find the relationship between GTA and carbon di-oxide density, GTA and methane density on earth atmosphere. In future we will try to find the relationship between GTA and aerosols present in earth atmosphere, water vapour density on earth atmosphere, ozone depletion etc. This analysis will help us for better understanding about the reason behind global warming

CCLasso: correlation inference for compositional data through Lasso.

PubMed

Fang, Huaying; Huang, Chengcheng; Zhao, Hongyu; Deng, Minghua

2015-10-01

Direct analysis of microbial communities in the environment and human body has become more convenient and reliable owing to the advancements of high-throughput sequencing techniques for 16S rRNA gene profiling. Inferring the correlation relationship among members of microbial communities is of fundamental importance for genomic survey study. Traditional Pearson correlation analysis treating the observed data as absolute abundances of the microbes may lead to spurious results because the data only represent relative abundances. Special care and appropriate methods are required prior to correlation analysis for these compositional data. In this article, we first discuss the correlation definition of latent variables for compositional data. We then propose a novel method called CCLasso based on least squares with [Formula: see text] penalty to infer the correlation network for latent variables of compositional data from metagenomic data. An effective alternating direction algorithm from augmented Lagrangian method is used to solve the optimization problem. The simulation results show that CCLasso outperforms existing methods, e.g. SparCC, in edge recovery for compositional data. It also compares well with SparCC in estimating correlation network of microbe species from the Human Microbiome Project. CCLasso is open source and freely available from https://github.com/huayingfang/CCLasso under GNU LGPL v3. dengmh@pku.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Enhanced brainstem and cortical evoked response amplitudes: single-trial covariance analysis.

PubMed

Galbraith, G C

2001-06-01

The purpose of the present study was to develop analytic procedures that improve the definition of sensory evoked response components. Such procedures could benefit all recordings but would especially benefit difficult recordings where many trials are contaminated by muscle and movement artifacts. First, cross-correlation and latency adjustment analyses were applied to the human brainstem frequency-following response and cortical auditory evoked response recorded on the same trials. Lagged cross-correlation functions were computed, for each of 17 subjects, between single-trial data and templates consisting of the sinusoid stimulus waveform for the brainstem response and the subject's own smoothed averaged evoked response P2 component for the cortical response. Trials were considered in the analysis only if the maximum correlation-squared (r2) exceeded .5 (negatively correlated trials were thus included). Identical correlation coefficients may be based on signals with quite different amplitudes, but it is possible to assess amplitude by the nonnormalized covariance function. Next, an algorithm is applied in which each trial with negative covariance is matched to a trial with similar, but positive, covariance and these matched-trial pairs are deleted. When an evoked response signal is present in the data, the majority of trials positively correlate with the template. Thus, a residual of positively correlated trials remains after matched covariance trials are deleted. When these residual trials are averaged, the resulting brainstem and cortical responses show greatly enhanced amplitudes. This result supports the utility of this analysis technique in clarifying and assessing evoked response signals.

Optimization of selective breeding through analysis of morphological traits in Chinese sea bass (Lateolabrax maculatus).

PubMed

Wang, W; Ma, C Y; Chen, W; Ma, H Y; Zhang, H; Meng, Y Y; Ni, Y; Ma, L B

2016-08-19

Determining correlations between certain traits of economic importance constitutes an essential component of selective activities. In this study, our aim was to provide effective indicators for breeding programs of Lateolabrax maculatus, an important aquaculture species in China. We analyzed correlations between 20 morphometric traits and body weight, using correlation and path analyses. The results indicated that the correlations among all 21 traits were highly significant, with the highest correlation coefficient identified between total length and body weight. The path analysis indicated that total length (X 1 ), body width (X 5 ), distance from first dorsal fin origin to anal fin origin (X 10 ), snout length (X 16 ), eye diameter (X 17 ), eye cross (X 18 ), and slanting distance from snout tip to first dorsal fin origin (X 19 ) significantly affected body weight (Y) directly. The following multiple-regression equation was obtained using stepwise multiple-regression analysis: Y = -472.108 + 1.065X 1 + 7.728X 5 + 1.973X 10 - 7.024X 16 - 4.400X 17 - 3.338X 18 + 2.138X 19 , with an adjusted multiple-correlation coefficient of 0.947. Body width had the largest determinant coefficient, as well as the highest positive direct correlation with body weight. At the same time, high indirect effects with six other morphometric traits on L. maculatus body weight, through body width, were identified. Hence, body width could be a key factor that efficiently indicates significant effects on body weight in L. maculatus.

Estimation and Testing of Partial Covariances, Correlations, and Regression Weights Using Maximum Likelihood Factor Analysis.

ERIC Educational Resources Information Center

And Others; Werts, Charles E.

1979-01-01

It is shown how partial covariance, part and partial correlation, and regression weights can be estimated and tested for significance by means of a factor analytic model. Comparable partial covariance, correlations, and regression weights have identical significance tests. (Author)

Activity and selectivity of photocatalysts in photodegradation of phenols.

PubMed

Emeline, A V; Zhang, X; Murakami, T; Fujishima, A

2012-04-15

Photodegradation of phenol and 4-chlorophenol over six different TiO(2) samples was tested in order to establish whether an interconnection between the activity and selectivity of photocatalysts exists. The obtained experimental data were analyzed using correlation analysis. Some correlations between the activity in phenol(s) photodegradation and selectivity toward formation of primary intermediate products were established. The type of correlations depends on the type of studied photoreactions. The discussion of the observed correlations between the activity and selectivity of photocatalysts is given in terms of the difference of surface concentrations of electrons and holes and corresponding surface active sites which might be dependent on the types of dominating surface faces. On the basis of the obtained results of correlation analysis it was assumed that a higher activity of photocatalysts could be achieved provided that both reduction and oxidation reaction pathways occur with equally high efficiency. Copyright © 2011 Elsevier B.V. All rights reserved.

Multifractal cross-correlation effects in two-variable time series of complex network vertex observables

NASA Astrophysics Data System (ADS)

OświÈ©cimka, Paweł; Livi, Lorenzo; DroŻdŻ, Stanisław

2016-10-01

We investigate the scaling of the cross-correlations calculated for two-variable time series containing vertex properties in the context of complex networks. Time series of such observables are obtained by means of stationary, unbiased random walks. We consider three vertex properties that provide, respectively, short-, medium-, and long-range information regarding the topological role of vertices in a given network. In order to reveal the relation between these quantities, we applied the multifractal cross-correlation analysis technique, which provides information about the nonlinear effects in coupling of time series. We show that the considered network models are characterized by unique multifractal properties of the cross-correlation. In particular, it is possible to distinguish between Erdös-Rényi, Barabási-Albert, and Watts-Strogatz networks on the basis of fractal cross-correlation. Moreover, the analysis of protein contact networks reveals characteristics shared with both scale-free and small-world models.

Discriminative analysis of early Alzheimer's disease based on two intrinsically anti-correlated networks with resting-state fMRI.

PubMed

Wang, Kun; Jiang, Tianzi; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Liu, Zhening

2006-01-01

In this work, we proposed a discriminative model of Alzheimer's disease (AD) on the basis of multivariate pattern classification and functional magnetic resonance imaging (fMRI). This model used the correlation/anti-correlation coefficients of two intrinsically anti-correlated networks in resting brains, which have been suggested by two recent studies, as the feature of classification. Pseudo-Fisher Linear Discriminative Analysis (pFLDA) was then performed on the feature space and a linear classifier was generated. Using leave-one-out (LOO) cross validation, our results showed a correct classification rate of 83%. We also compared the proposed model with another one based on the whole brain functional connectivity. Our proposed model outperformed the other one significantly, and this implied that the two intrinsically anti-correlated networks may be a more susceptible part of the whole brain network in the early stage of AD.

Technical Report: Correlation Between the Repair of Cartilage and Subchondral Bone in an Osteochondral Defect Using Bilayered, Biodegradable Hydrogel Composites.

PubMed

Lu, Steven; Lam, Johnny; Trachtenberg, Jordan E; Lee, Esther J; Seyednejad, Hajar; van den Beucken, Jeroen J J P; Tabata, Yasuhiko; Kasper, F Kurtis; Scott, David W; Wong, Mark E; Jansen, John A; Mikos, Antonios G

2015-12-01

The present work investigated correlations between cartilage and subchondral bone repair, facilitated by a growth factor-delivering scaffold, in a rabbit osteochondral defect model. Histological scoring indices and microcomputed tomography morphological parameters were used to evaluate cartilage and bone repair, respectively, at 6 and 12 weeks. Correlation analysis revealed significant associations between specific cartilage indices and subchondral bone parameters that varied with location in the defect (cortical vs. trabecular region), time point (6 vs. 12 weeks), and experimental group (insulin-like growth factor-1 only, bone morphogenetic protein-2 only, or both growth factors). In particular, significant correlations consistently existed between cartilage surface regularity and bone quantity parameters. Overall, correlation analysis between cartilage and bone repair provided a fuller understanding of osteochondral repair and can help drive informed studies for future osteochondral regeneration strategies.

A study of the correlation between dengue and weather in Kandy City, Sri Lanka (2003 -2012) and lessons learned.

PubMed

Ehelepola, N D B; Ariyaratne, Kusalika; Buddhadasa, W M N P; Ratnayake, Sunil; Wickramasinghe, Malani

2015-09-24

Weather variables affect dengue transmission. This study aimed to identify a dengue weather correlation pattern in Kandy, Sri Lanka, compare the results with results of similar studies, and establish ways for better control and prevention of dengue. We collected data on reported dengue cases in Kandy and mid-year population data from 2003 to 2012, and calculated weekly incidences. We obtained daily weather data from two weather stations and converted it into weekly data. We studied correlation patterns between dengue incidence and weather variables using the wavelet time series analysis, and then calculated cross-correlation coefficients to find magnitudes of correlations. We found a positive correlation between dengue incidence and rainfall in millimeters, the number of rainy and wet days, the minimum temperature, and the night and daytime, as well as average, humidity, mostly with a five- to seven-week lag. Additionally, we found correlations between dengue incidence and maximum and average temperatures, hours of sunshine, and wind, with longer lag periods. Dengue incidences showed a negative correlation with wind run. Our results showed that rainfall, temperature, humidity, hours of sunshine, and wind are correlated with local dengue incidence. We have suggested ways to improve dengue management routines and to control it in these times of global warming. We also noticed that the results of dengue weather correlation studies can vary depending on the data analysis.

CAMERRA: An analysis tool for the computation of conformational dynamics by evaluating residue-residue associations.

PubMed

Johnson, Quentin R; Lindsay, Richard J; Shen, Tongye

2018-02-21

A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue-residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Comprehensive Analysis of Large Sets of Age-Related Physiological Indicators Reveals Rapid Aging around the Age of 55 Years.

PubMed

Lixie, Erin; Edgeworth, Jameson; Shamir, Lior

2015-01-01

While many studies show a correlation between chronological age and physiological indicators, the nature of this correlation is not fully understood. To perform a comprehensive analysis of the correlation between chronological age and age-related physiological indicators. Physiological aging scores were deduced using principal component analysis from a large dataset of 1,227 variables measured in a cohort of 4,796 human subjects, and the correlation between the physiological aging scores and chronological age was assessed. Physiological age does not progress linearly or exponentially with chronological age: a more rapid physiological change is observed around the age of 55 years, followed by a mild decline until around the age of 70 years. These findings provide evidence that the progression of physiological age is not linear with that of chronological age, and that periods of mild change in physiological age are separated by periods of more rapid aging. © 2015 S. Karger AG, Basel.

Coupling detrended fluctuation analysis of Asian stock markets

NASA Astrophysics Data System (ADS)

Wang, Qizhen; Zhu, Yingming; Yang, Liansheng; Mul, Remco A. H.

2017-04-01

This paper uses the coupling detrended fluctuation analysis (CDFA) method to investigate the multifractal characteristics of four Asian stock markets using three stock indices: stock price returns, trading volumes and the composite index. The results show that coupled correlations exist among the four stock markets and the coupled correlations have multifractal characteristics. We then use the chi square (χ2) test to identify the sources of multifractality. For the different stock indices, the contributions of a single series to multifractality are different. In other words, the contributions of each country to coupled correlations are different. The comparative analysis shows that the research on the combine effect of stock price returns and trading volumes may be more comprehensive than on an individual index. By comparing the strength of multifractality for original data with the residual errors of the vector autoregression (VAR) model, we find that the VAR model could not be used to describe the dynamics of the coupled correlations among four financial time series.

Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Zhang, Minjia; Li, Qingchen

2017-04-01

This study focuses on multifractal detrended cross-correlation analysis of the different volatility intervals of Mainland China, US, and Hong Kong stock markets. A volatility-constrained multifractal detrended cross-correlation analysis (VC-MF-DCCA) method is proposed to study the volatility conductivity of Mainland China, US, and Hong Kong stock markets. Empirical results indicate that fluctuation may be related to important activities in real markets. The Hang Seng Index (HSI) stock market is more influential than the Shanghai Composite Index (SCI) stock market. Furthermore, the SCI stock market is more influential than the Dow Jones Industrial Average stock market. The conductivity between the HSI and SCI stock markets is the strongest. HSI was the most influential market in the large fluctuation interval of 1991 to 2014. The autoregressive fractionally integrated moving average method is used to verify the validity of VC-MF-DCCA. Results show that VC-MF-DCCA is effective.

Analysis of cerebral vessels dynamics using experimental data with missed segments

NASA Astrophysics Data System (ADS)

Pavlova, O. N.; Abdurashitov, A. S.; Ulanova, M. V.; Shihalov, G. M.; Semyachkina-Glushkovskaya, O. V.; Pavlov, A. N.

2018-04-01

Physiological signals often contain various bad segments that occur due to artifacts, failures of the recording equipment or varying experimental conditions. The related experimental data need to be preprocessed to avoid such parts of recordings. In the case of few bad segments, they can simply be removed from the signal and its analysis is further performed. However, when there are many extracted segments, the internal structure of the analyzed physiological process may be destroyed, and it is unclear whether such signal can be used in diagnostic-related studies. In this paper we address this problem for the case of cerebral vessels dynamics. We perform analysis of simulated data in order to reveal general features of quantifying scaling features of complex signals with distinct correlation properties and show that the effects of data loss are significantly different for experimental data with long-range correlations and anti-correlations. We conclude that the cerebral vessels dynamics is significantly less sensitive to missed data fragments as compared with signals with anti-correlated statistics.