The influence of HLA mismatches and immunosuppression on kidney graft survival: an analysis of more than 1300 patients.

PubMed

Martins, L; Fonseca, I; Sousa, S; Matos, C; Santos, J; Dias, L; Henriques, A C; Sarmento, A M; Cabrita, A

2007-10-01

New immunosuppressive drugs used in kidney transplantation decreased the incidence of acute rejection. It was hypothesized that, with their power, the importance of HLA matching was decreased. To evaluate the influence of HLA matching, immunosuppression, and other possible risk factors, we analyzed data of 1314 consecutive deceased donor kidney transplantation. We divided the patient population into 4 cohorts, according to the era of transplantation: era 1, before 1990, azathioprine (Aza) and cyclosporine (Csa) no microemulsion; era 2, between 1990 and 1995, Csa microemulsion; era 3, between 1996 and 2000, wide use of mycophenolate mofetil (MMF) and anti-thymocyte globulin (ATG); and era 4, after 2000, marked by sirolimus and tacrolimus (TAC) use. Multivariate analysis compared death-censored graft survival. Using as reference the results obtained with 0 HLA mismatches, we verified, during era 1 and era 2, an increased risk of graft loss for all of the subgroups with HLA mismatch >0. However, during era 3 and era 4, the number of HLA mismatches did not influence graft survival. Although acute rejection and delayed graft function, which decreased in the later periods, remained as prognostic factors for graft loss. Considering the immunosuppressive protocol with Csa+Aza+Pred as reference, protocols used after 1995 with Pred+Csa+ATG, with Pred+Csa+MMF, and with Pred+Tac+MMF presented better survival results. Results showed that the significance of HLA matching decreased while the results improved with the new immunosuppressant drugs. These observations support the hypothesis that the weakened importance of HLA matching may be a consequence of the increasing efficacy of the immunosuppression.

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

The rise of Clostridium difficile infection in lung transplant recipients in the modern era.

PubMed

Lee, Janet T; Hertz, Marshall I; Dunitz, Jordan M; Kelly, Rosemary F; D'Cunha, Jonathan; Whitson, Bryan A; Shumway, Sara J

2013-01-01

Clostridium difficile infection (CDI) rates have been rising in recent years. We aimed to characterize CDI in lung transplant recipients in the modern era and hypothesized that CDI would increase the mortality risk. We performed a retrospective chart review of patients undergoing transplantation at our center from 1/2006 to 7/2011. Attributes of CDI+ and CDI- groups were compared using Student's t- and chi-square tests (α = 0.05). Multivariate Cox proportional hazard models were used to control for confounding factors. Overall CDI incidence was 22.5%. Seven of 151 patients (4.6%) developed CDI during the initial hospitalization after transplantation (mean time 10.6 ± 6 d) while 27 patients (19.7%) developed CDI after discharge (mean time 467 ± 471 d). Incidence rate was 224.6 cases/100 000 patient-days compared to 110 cases/100 000 patient-days (rate for entire hospital). CDI was not predictive of mortality (HR 2.06, 95% CI 0.94-4.52). CDI rates in lung transplant recipients are high in the modern era. No risk factors for CDI were identified. Although not statistically significant, CDI+ patients had a higher risk of death. The economic burden of CDI and trend toward worse outcomes for CDI patients have important implications for post-operative surveillance of CDI-related complications and need for CDI prophylaxis. © 2013 John Wiley & Sons A/S.

Linking stressors and ecological responses

USGS Publications Warehouse

Gentile, J.H.; Solomon, K.R.; Butcher, J.B.; Harrass, M.; Landis, W.G.; Power, M.; Rattner, B.A.; Warren-Hicks, W.J.; Wenger, R.; Foran, Jeffery A.; Ferenc, Susan A.

1999-01-01

To characterize risk, it is necessary to quantify the linkages and interactions between chemical, physical and biological stressors and endpoints in the conceptual framework for ecological risk assessment (ERA). This can present challenges in a multiple stressor analysis, and it will not always be possible to develop a quantitative stressor-response profile. This review commences with a conceptual representation of the problem of developing a linkage analysis for multiple stressors and responses. The remainder of the review surveys a variety of mathematical and statistical methods (e.g., ranking methods, matrix models, multivariate dose-response for mixtures, indices, visualization, simulation modeling and decision-oriented methods) for accomplishing the linkage analysis for multiple stressors. Describing the relationships between multiple stressors and ecological effects are critical components of 'effects assessment' in the ecological risk assessment framework.

Inpatient mortality rates during an era of increased access to HIV testing and ART: A prospective observational study in Lilongwe, Malawi.

PubMed

Matoga, Mitch M; Rosenberg, Nora E; Stanley, Christopher C; LaCourse, Sylvia; Munthali, Charles K; Nsona, Dominic P; Haac, Bryce; Hoffman, Irving; Hosseinipour, Mina C

2018-01-01

In the era of increased access to HIV testing and antiretroviral treatment (ART), the impact of HIV and ART status on inpatient mortality in Malawi is unknown. We prospectively followed adult inpatients at Kamuzu Central Hospital medical wards in Lilongwe, Malawi, between 2011 and 2012, to evaluate causes of mortality, and the impact of HIV and ART status on mortality. We divided the study population into five categories: HIV-negative, new HIV-positive, ART-naïve patients, new ART-initiators, and ART-experienced. We used multivariate binomial regression models to compare risk of death between categories. Among 2911 admitted patients the mean age was 38.5 years, and 50% were women. Eighty-one percent (81%) of patients had a known HIV status at the time of discharge or death. Mortality was 19.4% and varied between 13.9% (HIV-negative patients) and 32.9% (HIV-positive patients on ART ≤1 year). In multivariable analyses adjusted for age, sex and leading causes of mortality, being new HIV-positive (RR = 1.64 95% CI: 1.16-2.32), ART-naive (RR = 2.28 95% CI: 1.66-2.32) or being a new ART-initiator (RR = 2.41 95% CI: 1.85-3.14) were associated with elevated risk of mortality compared to HIV-negative patients. ART-experienced patients had comparable mortality (RR = 1.33 95% CI: 0.94-1.88) to HIV-negative patients. HIV related mortality remains high among medical inpatients, especially among HIV-positive patients who recently initiated ART or have not started ART yet.

Singular F(R) cosmology unifying early- and late-time acceleration with matter and radiation domination era

NASA Astrophysics Data System (ADS)

Odintsov, S. D.; Oikonomou, V. K.

2016-06-01

We present some cosmological models which unify the late- and early-time acceleration eras with the radiation and the matter domination era, and we realize the cosmological models by using the theoretical framework of F(R) gravity. Particularly, the first model unifies the late- and early-time acceleration with the matter domination era, and the second model unifies all the evolution eras of our Universe. The two models are described in the same way at early and late times, and only the intermediate stages of the evolution have some differences. Each cosmological model contains two Type IV singularities which are chosen to occur one at the end of the inflationary era and one at the end of the matter domination era. The cosmological models at early times are approximately identical to the R 2 inflation model, so these describe a slow-roll inflationary era which ends when the slow-roll parameters become of order one. The inflationary era is followed by the radiation era and after that the matter domination era follows, which lasts until the second Type IV singularity, and then the late-time acceleration era follows. The models have two appealing features: firstly they produce a nearly scale invariant power spectrum of primordial curvature perturbations and a scalar-to-tensor ratio which are compatible with the most recent observational data and secondly, it seems that the deceleration-acceleration transition is crucially affected by the presence of the second Type IV singularity which occurs at the end of the matter domination era. As we demonstrate, the Hubble horizon at early times shrinks, as expected for an initially accelerating Universe, then during the matter domination era, it expands and finally after the Type IV singularity, the Hubble horizon starts to shrink again, during the late-time acceleration era. Intriguingly enough, the deceleration-acceleration transition, occurs after the second Type IV singularity. In addition, we investigate which F(R) gravity can successfully realize each of the four cosmological epochs.

Impact of physician-less pediatric critical care transport: Making a decision on team composition.

PubMed

Kawaguchi, Atsushi; Nielsen, Charlene C; Saunders, L Duncan; Yasui, Yutaka; de Caen, Allan

2018-06-01

To explore the impact of a physician non-accompanying pediatric critical care transport program, and to identify factors associated with the selection of specific transport team compositions. Children transported to a Canadian academic children's hospital were included. Two eras (Physician-accompanying Transport (PT)-era: 2000-07 when physicians commonly accompanied the transport team; and Physician-Less Transport (PLT)-era: 2010-15 when a physician non-accompanying team was increasingly used) were compared with respect to transport and PICU outcomes. Transport and patient characteristics for the PLT-era cohort were examined to identify factors associated with the selection of a physician accompanying team, with multivariable logistic regression with triage physicians as random effects. In the PLT-era (N=1177), compared to the PT-era (N=1490) the probability of PICU admission was significantly lower, and patient outcomes including mortality were not significantly different. Associations were noted between the selection of a physician non-accompanying team and specific transport characteristics. There was appreciable variability among the triage physicians for the selection of a physician non-accompanying team. No significant differences were observed with increasing use of a physician non-accompanying team. Selection of transport team compositions was influenced by clinical and system factors, but appreciable variation still remained among triage physicians. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

Culture and alcohol use: historical and sociocultural themes from 75 years of alcohol research.

PubMed

Castro, Felipe Gonzalez; Barrera, Manuel; Mena, Laura A; Aguirre, Katherine M

2014-01-01

For the period of almost 75 years, we examined the literature for studies regarding the influences of culture on alcohol use and misuse. This review is a chronology of research articles published from 1940 to 2013. From a structured literature search with select criteria, 38 articles were identified and 34 reviewed. This analysis revealed a progression across this period of research from studies that began as descriptive ethnographic evaluations of one or more indigenous societies or cultural groups, evolving to studies using complex multivariate models to test cross-cultural effects in two or more cultural groups. Major findings across this period include the assertions that (a) a function of alcohol use may be to reduce anxiety, (b) certain cultural groups possess features of alcohol use that are not associated with negative consequences, (c) the disruptive effects of acculturative change and the stressors of new demands are associated with an increase in alcohol consumption, (d) cultural groups shape expectations about the effects of alcohol use and their definition of drunkenness, and (e) the hypothesized relationships of culture with alcohol use and misuse have been demonstrated in multivariate model analyses. Across this 75-year period, the early proposition that culture is an important and prominent correlate of alcohol use and misuse has persisted. Within the current era of alcohol studies, this proposition has been supported by multivariate model analyses. Thus, the proposition that culture might affect alcohol use remains prominent and is as relevant today as it was when it was first proposed nearly 75 years ago.

High early cardiovascular mortality following liver transplantation

PubMed Central

VanWagner, Lisa B.; Lapin, Brittany; Levitsky, Josh; Wilkins, John T.; Abecassis, Michael M.; Skaro, Anton I.; Lloyd-Jones, Donald M.

2014-01-01

Cardiovascular disease (CVD) contributes to excess long-term mortality after liver transplantation (LT), however little is known about early post-operative CVD mortality in the current era. In addition, there is no model to predict early post-operative CVD mortality across centers. We analyzed adult recipients of primary LT in the Organ Procurement and Transplantation Network (OPTN) database between February 2002 and December 2012 to assess prevalence and predictors of early (30-day) CVD mortality, defined as death from arrhythmia, heart failure, myocardial infarction, cardiac arrest, thromboembolism, and/or stroke. We performed logistic regression with stepwise selection to develop a predictive model of early CVD mortality. Sex and center volume were forced into the final model, which was validated using bootstrapping techniques. Among 54,697 LT recipients, there were 1576 (2.9%) deaths within 30 days. CVD death was the leading cause of 30-day mortality (42.1%), followed by infection (27.9%) and graft failure (12.2%). In multivariate analysis, 9 (6 recipient, 2 donor, 1 operative) significant covariates were identified: age, pre-operative hospitalization, ICU and ventilator status, calculated MELD score, portal vein thrombosis, national organ sharing, donor BMI and cold ischemia time. The model showed moderate discrimination (c-statistic 0.66, 95% CI: 0.63–0.68). We provide the first multicenter prognostic model for the prediction of early post-LT CVD death, the most common cause of early post-LT mortality in the current transplant era. However, evaluation of additional CVD-related variables not collected by the OPTN are needed in order to improve model accuracy and potential clinical utility. PMID:25044256

Multivariate Analysis and Machine Learning in Cerebral Palsy Research

PubMed Central

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP. PMID:29312134

Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

PubMed

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

Isotropic cosmological models in F(T,TG) theory

NASA Astrophysics Data System (ADS)

Sharif, M.; Nazir, Kanwal

2016-09-01

This paper is devoted to study evolution of the isotropic universe models in the framework of F(T,TG) gravity (T represents torsion scalar and TG is the teleparallel equivalent of the Gauss-Bonnet (GB) term). We construct F(T,TG) models by taking different eras of the universe like non-relativistic and relativistic matter eras, dark energy (DE) dominated era and their combinations. It is found that the reconstructed models indicate decreasing behavior for DE dominated era and its combination with other eras. We also discuss stability of each reconstructed model. Finally, we evaluate equation of state (EoS) parameter by considering two models and study its behavior graphically.

Gravitational Wave Detection of Compact Binaries Through Multivariate Analysis

NASA Astrophysics Data System (ADS)

Atallah, Dany Victor; Dorrington, Iain; Sutton, Patrick

2017-01-01

The first detection of gravitational waves (GW), GW150914, as produced by a binary black hole merger, has ushered in the era of GW astronomy. The detection technique used to find GW150914 considered only a fraction of the information available describing the candidate event: mainly the detector signal to noise ratios and chi-squared values. In hopes of greatly increasing detection rates, we want to take advantage of all the information available about candidate events. We employ a technique called Multivariate Analysis (MVA) to improve LIGO sensitivity to GW signals. MVA techniques are efficient ways to scan high dimensional data spaces for signal/noise classification. Our goal is to use MVA to classify compact-object binary coalescence (CBC) events composed of any combination of black holes and neutron stars. CBC waveforms are modeled through numerical relativity. Templates of the modeled waveforms are used to search for CBCs and quantify candidate events. Different MVA pipelines are under investigation to look for CBC signals and un-modelled signals, with promising results. One such MVA pipeline used for the un-modelled search can theoretically analyze far more data than the MVA pipelines currently explored for CBCs, potentially making a more powerful classifier. In principle, this extra information could improve the sensitivity to GW signals. We will present the results from our efforts to adapt an MVA pipeline used in the un-modelled search to classify candidate events from the CBC search.

Factors associated with improvement in disability-adjusted life years in patients with HIV/AIDS

PubMed Central

Bermudez-Tamayo, Clara; Martin, Jose Jesus Martin; Ruiz-Pérez, Isabel; Lima, Antonio Olry de Labry

2008-01-01

Background The epidemic of HIV/AIDS and treatments that have emerged to alleviate, have brought about a shift in the burden of disease from death to quality of life/disability. The aim was to determine which factors are associated with improvements in the level of health of male and female patients with HIV/AIDS in Andalusia, in terms of disability-adjusted life years. Methods Descriptive study based on a sample group of 8800 people on the Andalusian AIDS register between 1983 and 2004. Dependent variables: Life lost due to premature mortality (YLL), years lost due to disability (YLD) and disability-adjusted life years (DALY). Independent variables: vital state, sex, age at the time of diagnosis, age at the time of death, transmission category, province of residence, AIDS-indicator disease and the period of diagnosis. A bivariate analysis was carried out to find out if the health level variables changed in accordance with the independent variables. Using the independent variables which had a statistically significant link with the level of health variables, a multivariate linear regression model, disaggregated by gender, was constructed. Results Amongst the women, we found a model which explained the level of health of 64.9%: a link was found between a higher level of health (lower DALYs) and not intravenous drug use, the province of residence, being diagnosed during the HAART era and older age at the time of diagnosis. Amongst the men, we found a model which explained the level of health of 64.4%: a link was found between a higher level of health (lower DALYs) and intravenous drug use, the province of residence, being diagnosed during the HAART era and older age at the time of diagnosis. Conclusion A higher level of health (lower DALY) amongst both men and women was found to be linked to not be intravenous drug user, the province of residence, being diagnosed during the HAART era and older age at the time of diagnosis. PMID:18939970

Anemia and Red Blood Cell Indices Predict HIV-Associated Neurocognitive Impairment in the Highly Active Antiretroviral Therapy Era

PubMed Central

Kallianpur, Asha R.; Wang, Quan; Jia, Peilin; Hulgan, Todd; Zhao, Zhongming; Letendre, Scott L.; Ellis, Ronald J.; Heaton, Robert K.; Franklin, Donald R.; Barnholtz-Sloan, Jill; Collier, Ann C.; Marra, Christina M.; Clifford, David B.; Gelman, Benjamin B.; McArthur, Justin C.; Morgello, Susan; Simpson, David M.; McCutchan, J. A.; Grant, Igor

2016-01-01

Background. Anemia has been linked to adverse human immunodeficiency virus (HIV) outcomes, including dementia, in the era before highly active antiretroviral therapy (HAART). Milder forms of HIV-associated neurocognitive disorder (HAND) remain common in HIV-infected persons, despite HAART, but whether anemia predicts HAND in the HAART era is unknown. Methods. We evaluated time-dependent associations of anemia and cross-sectional associations of red blood cell indices with neurocognitive impairment in a multicenter, HAART-era HIV cohort study (N = 1261), adjusting for potential confounders, including age, nadir CD4+ T-cell count, zidovudine use, and comorbid conditions. Subjects underwent comprehensive neuropsychiatric and neuromedical assessments. Results. HAND, defined according to standardized criteria, occurred in 595 subjects (47%) at entry. Mean corpuscular volume and mean corpuscular hemoglobin were positively associated with the global deficit score, a continuous measure of neurocognitive impairment (both P < .01), as well as with all HAND, milder forms of HAND, and HIV-associated dementia in multivariable analyses (all P < .05). Anemia independently predicted development of HAND during a median follow-up of 72 months (adjusted hazard ratio, 1.55; P < .01). Conclusions. Anemia and red blood cell indices predict HAND in the HAART era and may contribute to risk assessment. Future studies should address whether treating anemia may help to prevent HAND or improve cognitive function in HIV-infected persons. PMID:26690344

Preemptive Therapy Prevents Cytomegalovirus End-Organ Disease in Treatment-Naïve Patients with Advanced HIV-1 Infection in the HAART Era

PubMed Central

Mizushima, Daisuke; Nishijima, Takeshi; Gatanaga, Hiroyuki; Tsukada, Kunihisa; Teruya, Katsuji; Kikuchi, Yoshimi; Oka, Shinichi

2013-01-01

Background The efficacy of preemptive therapy against cytomegalovirus (CMV) infection remains unknown in treatment-naïve patients with advanced HIV-1 infection in the HAART era. Methods The subjects of this single-center observation study were126 treatment-naïve HIV-1 infected patients with positive CMV viremia between January 1, 2000 and December 31, 2006. Inclusion criteria were age more than 17 years, CD4 count less than 100/μl, plasma CMV DNA positive, never having received antiretroviral therapy (ART) and no CMV end-organ disease (EOD) at first visit. The incidence of CMV-EOD was compared in patients with and without preemptive therapy against CMV-EOD. The effects of the CMV preemptive therapy were estimated in uni- and multivariate Cox hazards models. Results CMV-EOD was diagnosed in 30 of the 96 patients of the non-preemptive therapy group (31%, 230.3 per 1000 person-years), compared with 3 of the 30 patients of the preemptive therapy group (10%, 60.9 per 1000 person-years). Univariate (HR = 0.286; 95%CI, 0.087–0.939; p = 0.039) and multivariate (adjusted HR = 0.170; 95%CI, 0.049–0.602; p = 0.005) analyses confirmed that CMV-EOD is significantly prevented by CMV preemptive therapy. Multivariate analysis showed that plasma CMV DNA level correlated significantly with CMV-EOD (per log10/ml, adjusted HR = 1.941; 95%CI, 1.266–2.975; p = 0.002). Among the 30 patients on preemptive therapy, 7 (23.3%) developed grade 3–4 leukopenia. The mortality rate was not significantly different between the two groups (p = 0.193, Log-rank test). Conclusions The results indicate that preemptive therapy lowers the incidence of CMV-EOD by almost 25%. Preemptive therapy for treatment-naïve patients with CMV viremia is effective, although monitoring of potential treatment-related side effects is required. PMID:23724140

Multivariate Data Analysis

DTIC Science & Technology

1975-02-03

the anthropometrists, biologists, and psychologists of that era. Such initial contributors to modern statistics as Francis Galton and Karl Pearson...1159-78. [5] Galton , Francis (1888), "Co-relations and Their Measurements, Chiefly from Anthropometric Data," Proceedings of the...stem from that period. Galton seemed to be perpetually engaged in data analysis. He and his cousin, Darwin, and others revolved in an age of

Inflation with a smooth constant-roll to constant-roll era transition

NASA Astrophysics Data System (ADS)

Odintsov, S. D.; Oikonomou, V. K.

2017-07-01

In this paper, we study canonical scalar field models, with a varying second slow-roll parameter, that allow transitions between constant-roll eras. In the models with two constant-roll eras, it is possible to avoid fine-tunings in the initial conditions of the scalar field. We mainly focus on the stability of the resulting solutions, and we also investigate if these solutions are attractors of the cosmological system. We shall calculate the resulting scalar potential and, by using a numerical approach, we examine the stability and attractor properties of the solutions. As we show, the first constant-roll era is dynamically unstable towards linear perturbations, and the cosmological system is driven by the attractor solution to the final constant-roll era. As we demonstrate, it is possible to have a nearly scale-invariant power spectrum of primordial curvature perturbations in some cases; however, this is strongly model dependent and depends on the rate of the final constant-roll era. Finally, we present, in brief, the essential features of a model that allows oscillations between constant-roll eras.

Three out of four disease-modifying anti-rheumatic drug-naïve rheumatoid arthritis patients meet 28-joint Disease Activity Score remission at 12 months: results from the FIN-ERA cohort.

PubMed

Rannio, T; Asikainen, J; Hannonen, P; Yli-Kerttula, T; Ekman, P; Pirilä, L; Kuusalo, L; Mali, M; Puurtinen-Vilkki, M; Kortelainen, S; Paltta, J; Taimen, K; Kauppi, M; Laiho, K; Nyrhinen, S; Mäkinen, H; Isomäki, P; Uotila, T; Aaltonen, K; Kautiainen, H; Sokka, T

2017-11-01

To assess what proportion of patients with disease-modifying anti-rheumatic drug (DMARD)-naïve early rheumatoid arthritis (ERA) reach 28-joint Disease Activity Score (DAS28) remission over 1 year, and remission variability across clinics in Finland. Patients with DMARD-naïve newly diagnosed inflammatory arthritis were recruited. The proportion of patients in 28-joint Disease Activity Score with three variables (DAS28-3) remission was compared across sites. Repeated measures were analysed using a mixed models approach with appropriate distribution and link function. In total, 611 patients were recruited at five sites: 67% were female; the mean (sd) age was 57 (16) years; 71% and 68% were positive for rheumatoid factor and anti-cyclic citrullinated peptides, respectively; and 23% had radiographic erosions. A total of 506 (83%) fulfilled the American College of Rheumatology/European League Against Rheumatism 2010 classification criteria for rheumatoid arthritis for further analyses. DAS28-3 remission was met by 68% and 75% at 3 and 12 months, respectively. The clinical site had no effect on remission when adjusted for confounders. At baseline, 68% used methotrexate-based combination therapy, and 31% used triple therapy with methotrexate, hydroxychloroquine, and sulphasalazine (the Fin-RACo regimen). In multivariate analysis, the only independent predictors of DAS28-3 remission at 12 months were lower baseline DAS28-3 and triple therapy as the initial treatment. Three out of four DMARD-naïve ERA patients in Finland are in remission during the first year from the diagnosis. High remission rates were achieved for most patients with the use of conventional synthetic DMARDs in combination. Treatment of DMARD-naïve ERA patients with the FIN-RACo regimen is a predictor of DAS28-3 remission in real-life rheumatology settings.

Differential Clinical Implications of High-Degree Atrioventricular Block Complicating ST-Segment Elevation Myocardial Infarction according to the Location of Infarction in the Era of Primary Percutaneous Coronary Intervention

PubMed Central

Kim, Kyung Hwan; Ahn, Youngkeun; Kim, Young Jo; Cho, Myeong Chan; Kim, Wan

2016-01-01

Background and Objectives The clinical implication of high-degree (second- and third-degree) atrioventricular block (HAVB) complicating ST-segment elevation myocardial infarction (STEMI) is ripe for investigation in this era of primary percutaneous coronary intervention (PCI). We sought to address the incidence, predictors and prognosis of HAVB according to the location of infarct in STEMI patients treated with primary PCI. Subjects and Methods A total of 16536 STEMI patients (anterior infarction: n=9354, inferior infarction: n=7692) treated with primary PCI were enrolled from a multicenter registry. We compared in-hospital mortality between patients with HAVB and those without HAVB with anterior or inferior infarction, separately. Multivariate analyses were performed to unearth predictors of HAVB and to identify whether HAVB is independently associated with in-hospital mortality. Results STEMI patients with HAVB showed higher in-hospital mortality than those without HAVB in both anterior (hazard ratio [HR]=9.821, 95% confidence interval [CI]: 4.946-19.503, p<0.001) and inferior infarction (HR=2.819, 95% CI: 2.076-3.827, p<0.001). In multivariate analyses, HAVB was associated with increased in-hospital mortality in anterior myocardial infarction (HR=19.264, 95% CI: 5.804-63.936, p<0.001). However, HAVB in inferior infarction was not an independent predictor of increased in-hospital mortality (HR=1.014, 95% CI: 0.547-1.985, p=0.901). Conclusion In this era of primary PCI, the prognostic impact of HAVB is different according to the location of infarction. Because of recent improvements in reperfusion strategy, the negative prognostic impact of HAVB in inferior STEMI is no longer prominent. PMID:27275168

Concussion Nondisclosure During Professional Career Among a Cohort of Former National Football League Athletes.

PubMed

Kerr, Zachary Y; Register-Mihalik, Johna K; Kay, Melissa C; DeFreese, J D; Marshall, Stephen W; Guskiewicz, Kevin M

2018-01-01

Despite a focus on the incidence and effects of concussion, nondisclosure of sports-related concussions among retired players from the National Football League (NFL) has yet to be examined. Examine the prevalence of and factors associated with nondisclosure of sports-related concussions in former NFL athletes. Cross-sectional study; Level of evidence, 3. A sample of 829 former NFL players completed a general health survey. This historical cohort included players who had played before World War II to 2001. Respondents retrospectively recalled sports-related concussions that they sustained during their professional careers and whether at least one of these sports-related concussions was not reported to medical staff. We computed the prevalence of nondisclosure among those recalling sport-related concussions during their professional careers. Multivariable binomial regression estimated adjusted prevalence ratios (PR) with 95% confidence intervals (CIs) controlling for race/ethnicity, number of years played, primary position played, professional career concussion history, and playing era. Playing era was categorized by whether the majority of a player's career was before or after a 1976 rule change to limit contact ("spearing"). Overall, 417 (50.3%) respondents reported they had sustained a concussion and did not inform medical staff at least once during their professional playing career. Nonwhite respondents had a higher prevalence of nondisclosure than white/non-Hispanic respondents (adjusted PR = 1.19; 95% CI, 1.02-1.38). An interaction between professional career concussion history and playing era was also found ( P = .08). Compared with those in the pre-spearing rule change group with 1 or 2 concussions, all other groups had larger prevalences of nondisclosure (increases ranging from 41% to 153% in multivariable models). Across concussion strata, nondisclosure prevalence was generally higher in the post-spearing rule change group than the pre-spearing rule change group, with the largest differences found among those with 1 or 2 concussions or those with 3 or 4 concussions. A large proportion of former NFL players in this historical cohort reported at least one instance of not disclosing sports-related concussions to medical staff. Future research on concussion nondisclosure needs to identify mechanisms to improve football players' intentions to disclose concussion-related symptoms to health care providers and to equip health care providers with more effective strategies for timely identification of concussion.

Realizing Women Living with HIV's Reproductive Rights in the Era of ART: The Negative Impact of Non-consensual HIV Disclosure on Pregnancy Decisions Amongst Women Living with HIV in a Canadian Setting.

PubMed

Duff, Putu; Kestler, Mary; Chamboko, Patience; Braschel, Melissa; Ogilvie, Gina; Krüsi, Andrea; Montaner, Julio; Money, Deborah; Shannon, Kate

2018-04-07

To better understand the structural drivers of women living with HIV's (WLWH's) reproductive rights and choices, this study examined the structural correlates, including non-consensual HIV disclosure, on WLWH's pregnancy decisions and describes access to preconception care. Analyses drew on data (2014-present) from SHAWNA, a longitudinal community-based cohort with WLWH across Metro-Vancouver, Canada. Multivariable logistic regression was used to model the effect of non-consensual HIV disclosure on WLWH's pregnancy decisions. Of the 218 WLWH included in our analysis, 24.8% had ever felt discouraged from becoming pregnant and 11.5% reported accessing preconception counseling. In multivariable analyses, non-consensual HIV disclosure was positively associated with feeling discouraged from wanting to become pregnant (AOR 3.76; 95% CI 1.82-7.80). Non-consensual HIV disclosure adversely affects WLWH's pregnancy decisions. Supporting the reproductive rights of WLWH will require further training among general practitioners on the reproductive health of WLWH and improved access to women-centred, trauma-informed care, including non-judgmental preconception counseling.

Addiction treatment outcomes, process and change: Texas Institute of Behavioral Research at Texas Christian University.

PubMed

Simpson, D Dwayne; Joe, George W; Dansereau, Donald F; Flynn, Patrick M

2011-10-01

For more than 40 years the Texas Institute of Behavioral Research (IBR) has given special attention to assessment and evaluation of drug user populations, addiction treatment services and various cognitive and behavioral interventions. Emphasis has been on studies in real-world settings and the use of multivariate methodologies to address evaluation issues within the context of longitudinal natural designs. Historically, its program of addiction treatment research may be divided into three sequential epochs-the first era dealt mainly with client assessment and its role in treatment outcome and evaluation (1969-89), the second focused upon modeling the treatment process and the importance of conceptual frameworks (1989-2009) in explaining the relationships among treatment environment, client attributes, treatment process and outcome, and the third (and current) era has expanded into studying tactical deployment of innovations and implementation. Recent projects focus upon adapting and implementing innovations for improving early engagement in adolescent residential treatment settings and drug-dependent criminal justice populations. Related issues include the spread of human immunodeficiency virus/acquired immune deficiency syndrome and other infectious diseases, organizational and systems functioning, treatment costs and process related to implementation of evidence-based practices. © 2010 The Authors, Addiction © 2010 Society for the Study of Addiction.

Early-time cosmology with stiff era from modified gravity

NASA Astrophysics Data System (ADS)

Odintsov, S. D.; Oikonomou, V. K.

2017-11-01

In this work, we shall incorporate a stiff era in the Universe's evolution in the context of F (R ) gravity. After deriving the vacuum F (R ) gravity, which may realize a stiff evolution, we combine the stiff F (R ) gravity with an R2 model, and we construct a qualitative model for the inflationary and stiff era, with the latter commencing after the end of the inflationary era. We assume that the baryogenesis occurs during the stiff era, and we calculate the baryon to entropy ratio, which effectively constraints the functional form of the stiff F (R ) gravity. Further constraints on the stiff F (R ) gravity may come from the primordial gravitational waves, and particularly their scalar mode, which is characteristic of the F (R ) gravity theory. The stiff era presence does not contradict the standard cosmology era, namely, inflation, and the radiation-matter domination eras. Furthermore, we investigate which F (R ) gravity may realize a dust and stiff matter dominated Einstein-Hilbert evolution.

Growth of semimetallic ErAs films epitaxially embedded in GaAs

NASA Astrophysics Data System (ADS)

Crook, Adam M.; Nair, Hari P.; Lee, Jong H.; Ferrer, Domingo A.; Akinwande, Deji; Bank, Seth R.

2011-10-01

We present models for the growth and electrical conductivity of ErAs films grown with the nanoparticle-seeded film growth technique. This growth mode overcomes the mismatch in rotational symmetry between the rocksalt ErAs crystal structure and the zincblende GaAs crystal structure. This results in films of ErAs grown through a thin film of GaAs that preserves the symmetry of the substrate. The conductivity of the films, as a function of film thickness, are investigated and a surface roughness model is used to explain observed trends. Transmission electron micrographs confirm the suppression of anti-phase domains. A simple diffusion model is developed to describe the diffusion and incorporation of surface erbium into subsurface ErAs layers and predict potential failure mechanisms of the growth method.

The Impact of Anesthesia-Influenced Process Measure Compliance on Length of Stay: Results From an Enhanced Recovery After Surgery for Colorectal Surgery Cohort.

PubMed

Grant, Michael C; Pio Roda, Claro M; Canner, Joseph K; Sommer, Philip; Galante, Daniel; Hobson, Deborah; Gearhart, Susan; Wu, Christopher L; Wick, Elizabeth

2018-05-17

Process measure compliance has been associated with improved outcomes in enhanced recovery after surgery (ERAS) programs. Herein, we sought to assess the impact of compliance with measures directly influenced by anesthesiology in an ERAS for colorectal surgery cohort. From January 2013 to April 2015, data from 1140 consecutive patients were collected for all patients before (pre-ERAS) and after (ERAS) implementation of an ERAS program. Compliance with 9 specific process measures directly influenced by the anesthesiologist or acute pain service was analyzed to determine the impact on hospital length of stay (LOS). Process measure compliance was associated with a stepwise reduction in LOS. Patients who received >4 process measures (high compliance) had a significantly shorter LOS (incident rate ratio [IRR], 0.77; 95% CI, 0.70-0.85); P < .001) compared to low compliance (0-2 process measures) counterparts. Multivariable regression suggests that utilization of multimodal nausea and vomiting prophylaxis (IRR, 0.78; 95% CI, 0.68-0.89; P < .001), scheduled postoperative nonsteroidal pain medication use (IRR, 0.76; 95% CI, 0.67-0.85; P < .001), and strict adherence to a postoperative opioid administration (IRR, 0.58; 95% CI, 0.51-0.67; P < .001) protocol for breakthrough pain were independently associated with reduced LOS. Our findings suggest that increased compliance with process measures directly influenced by the anesthesiologists and in concert with a formal anesthesia protocol is associated with reduced LOS. Engaging anesthesiology colleagues throughout the surgical encounter increases the overall value of perioperative care.

Multivariate analysis in the pharmaceutical industry: enabling process understanding and improvement in the PAT and QbD era.

PubMed

Ferreira, Ana P; Tobyn, Mike

2015-01-01

In the pharmaceutical industry, chemometrics is rapidly establishing itself as a tool that can be used at every step of product development and beyond: from early development to commercialization. This set of multivariate analysis methods allows the extraction of information contained in large, complex data sets thus contributing to increase product and process understanding which is at the core of the Food and Drug Administration's Process Analytical Tools (PAT) Guidance for Industry and the International Conference on Harmonisation's Pharmaceutical Development guideline (Q8). This review is aimed at providing pharmaceutical industry professionals an introduction to multivariate analysis and how it is being adopted and implemented by companies in the transition from "quality-by-testing" to "quality-by-design". It starts with an introduction to multivariate analysis and the two methods most commonly used: principal component analysis and partial least squares regression, their advantages, common pitfalls and requirements for their effective use. That is followed with an overview of the diverse areas of application of multivariate analysis in the pharmaceutical industry: from the development of real-time analytical methods to definition of the design space and control strategy, from formulation optimization during development to the application of quality-by-design principles to improve manufacture of existing commercial products.

Multivariable Sensors for Ubiquitous Monitoring of Gases in the Era of Internet of Things and Industrial Internet.

PubMed

Potyrailo, Radislav A

2016-10-12

Modern gas monitoring scenarios for medical diagnostics, environmental surveillance, industrial safety, and other applications demand new sensing capabilities. This Review provides analysis of development of new generation of gas sensors based on the multivariable response principles. Design criteria of these individual sensors involve a sensing material with multiresponse mechanisms to different gases and a multivariable transducer with independent outputs to recognize these different gas responses. These new sensors quantify individual components in mixtures, reject interferences, and offer more stable response over sensor arrays. Such performance is attractive when selectivity advantages of classic gas chromatography, ion mobility, and mass spectrometry instruments are canceled by requirements for no consumables, low power, low cost, and unobtrusive form factors for Internet of Things, Industrial Internet, and other applications. This Review is concluded with a perspective for future needs in fundamental and applied aspects of gas sensing and with the 2025 roadmap for ubiquitous gas monitoring.

Prediction versus aetiology: common pitfalls and how to avoid them.

PubMed

van Diepen, Merel; Ramspek, Chava L; Jager, Kitty J; Zoccali, Carmine; Dekker, Friedo W

2017-04-01

Prediction research is a distinct field of epidemiologic research, which should be clearly separated from aetiological research. Both prediction and aetiology make use of multivariable modelling, but the underlying research aim and interpretation of results are very different. Aetiology aims at uncovering the causal effect of a specific risk factor on an outcome, adjusting for confounding factors that are selected based on pre-existing knowledge of causal relations. In contrast, prediction aims at accurately predicting the risk of an outcome using multiple predictors collectively, where the final prediction model is usually based on statistically significant, but not necessarily causal, associations in the data at hand.In both scientific and clinical practice, however, the two are often confused, resulting in poor-quality publications with limited interpretability and applicability. A major problem is the frequently encountered aetiological interpretation of prediction results, where individual variables in a prediction model are attributed causal meaning. This article stresses the differences in use and interpretation of aetiological and prediction studies, and gives examples of common pitfalls. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Constraints on single entity driven inflationary and radiation eras

NASA Astrophysics Data System (ADS)

Bouhmadi-López, Mariam; Chen, Pisin; Liu, Yen-Wei

2012-07-01

We present a model that attempts to fuse the inflationary era and the subsequent radiation dominated era under a unified framework so as to provide a smooth transition between the two. The model is based on a modification of the generalized Chaplygin gas. We constrain the model observationally by mapping the primordial power spectrum of the scalar perturbations to the latest data of WMAP7. We compute as well the spectrum of the primordial gravitational waves as would be measured today.

Modelling fire frequency and area burned across phytoclimatic regions in Spain using reanalysis data and the Canadian Fire Weather Index System

NASA Astrophysics Data System (ADS)

Bedia, J.; Herrera, S.; Gutiérrez, J. M.

2013-09-01

We develop fire occurrence and burned area models in peninsular Spain, an area of high variability in climate and fuel types, for the period 1990-2008. We based the analysis on a phytoclimatic classification aiming to the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climatic and fuel conditions. We used generalized linear models (GLM) and multivariate adaptive regression splines (MARS) as modelling algorithms and temperature, relative humidity, precipitation and wind speed, taken from the ERA-Interim reanalysis, as well as the components of the Canadian Forest Fire Weather Index (FWI) System as predictors. We also computed the standardized precipitation-evapotranspiration index (SPEI) as an additional predictor for the models of burned area. We found two contrasting fire regimes in terms of area burned and number of fires: one characterized by a bimodal annual pattern, characterizing the Nemoral and Oro-boreal phytoclimatic types, and another one exhibiting an unimodal annual cycle, with the fire season concentrated in the summer months in the Mediterranean and Arid regions. The fire occurrence models attained good skill in most of the phytoclimatic zones considered, yielding in some zones notably high correlation coefficients between the observed and modelled inter-annual fire frequencies. Total area burned also exhibited a high dependence on the meteorological drivers, although their ability to reproduce the observed annual burned area time series was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, and also SPEI in some of the burned area models, highlighting the adequacy of the FWI system for fire modelling applications and leaving the door opened to the development a more complex modelling framework based on these predictors. Furthermore, we demonstrate the potential usefulness of ERA-Interim reanalysis data for the reconstruction of historical fire-climate relationships at the scale of analysis. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as response variable.

A global validation of ERA-Interim integrated water vapor estimates using ground-based GNSS observations

NASA Astrophysics Data System (ADS)

Ahmed, F.; Dousa, J.; Hunegnaw, A.; Teferle, F. N.; Bingley, R.

2017-12-01

Integrated water vapor (IWV) derived from climate reanalysis models, such as the European Centre for Medium-range Weather Forecasts (ECMWF) ReAnalysis-Interim (ERA-Interim), is widely used in many atmospheric applications. Therefore, it is of interest to assess the quality of this reanalysis product using available observations. Observations from Global Navigation Satellite Systems (GNSS) are, as of now, available for a period of over 2 decades and their global availability makes it possible to validate the IWV obtained from climate reanalysis models in different geographical and climatic regions. In this study, primarily, three 5-year long homogeneously reprocessed GNSS-derived IWV datasets containing over 400 globally distributed ground-based GNSS stations have been used to validate the IWV estimates obtained from the ERA-Interim climate reanalysis model in 25 different climate zones. The IWV from ERA-Interim has been obtained by vertically integrating the specific humidity at all model levels above the locations of GNSS stations. It has been studied how the difference between the ERA-Interim IWV and the GNSS-derived IWV varies with respect to the different climate zones as well as with respect to the difference in the model orography and latitude. The results show a dependence of the ability of ERA-Interim to model the IWV on difference in climate types and latitude. This dependence, however, is dictated by the concentration of water vapor in different climate zones and at different latitudes. Furthermore, as a secondary focus of this study, the weighted mean atmospheric temperature (Tm) obtained from ERA-Interim has been compared to its equivalent obtained using two widely used approximations globally.

The impact of perioperative fluid therapy on short-term outcomes and 5-year survival among patients undergoing colorectal cancer surgery - A prospective cohort study within an ERAS protocol.

PubMed

Asklid, D; Segelman, J; Gedda, C; Hjern, F; Pekkari, K; Gustafsson, U O

2017-08-01

Restricted perioperative fluid therapy is one of several interventions in the enhanced recovery after surgery (ERAS) protocol, designed to reduce morbidity and hospital stay after surgery. The impact of this single intervention on short and long term outcome after colorectal surgery is unknown. This cohort study includes all consecutive patients operated with abdominal resection of colorectal cancer 2002-2007 at Ersta Hospital, Stockholm, Sweden. All patients were treated within an ERAS protocol and registered in the ERAS-database. Compliance to interventions in the ERAS protocol was analysed. The impact of a restrictive perioperative fluid therapy (≤3000 ml on the day of surgery) protocol on short-term outcomes as well as 5-year survival was assessed with multivariable analysis adjusted for confounding factors. Nine hundred and eleven patients were included. Patients receiving ≤3000 ml of intravenous fluids on the day of surgery had a lower risk of complications OR 0.44 (95% C I 0.28-0.71), symptoms delaying discharge OR 0.47(95% C I 0.32-0.70) and shorter length of stay compared with patients receiving >3000 ml. In cox regression analysis, the risk of cancer specific death was reduced with 55% HR 0.45(95% C I 0.25-0.81) for patients receiving ≤ 3000 ml compared with patients receiving >3000 ml. A restrictive compared with a non-restrictive perioperative fluid therapy on the day of surgery may be associated with lower short-term complication rates, faster recovery, shorter length of stay and improved 5-year survival. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Active and passive compliance in an enhanced recovery programme.

PubMed

Thorn, Christopher C; White, Ian; Burch, Jennie; Malietzis, George; Kennedy, Robin; Jenkins, John T

2016-07-01

Enhanced recovery after surgery (ERAS) is a well-established and accepted practice following colorectal surgery and has been demonstrated to reduce hospital length of stay (LOS) and 30-day morbidity. Despite evidence to support the individual elements on which the programme is based, there remains uncertainty as to how many and which of these are required to realise its benefits. Furthermore, elements of an ERAS programme might either precipitate or reflect recovery, in which case compliance could have a role in the improvement or prediction of outcome. A multidimensional prospective database of 799 consecutive patients undergoing colorectal surgery within an established ERAS programme at a single institution was interrogated. After application of exclusion criteria, 614 patients were studied. The novel concept of 'active compliance' is introduced. An ERAS element is classified as 'active' if the participation of the patient is required to achieve its compliance. This contrasts with 'passive' compliance, where an intervention is delivered to the patient without their direct contribution. The short-term surgical outcomes of this cohort are reported with reference to ERAS protocol compliance. Compliance with the passive elements of the programme was higher than with the active elements. Univariate and multivariate analyses demonstrate that poor compliance with active but not passive elements of the programme was significantly associated with major morbidity. Receiver operator characteristic curve analysis demonstrated active compliance to be a stronger predictor of both major morbidity (AUC 0.71 vs. AUC 0.56) and length of stay (AUC 0.83 vs. 0.57) when compared with passive compliance. The results suggest that poor active compliance may be a surrogate marker of morbidity which can be recognised in the early post-operative period. This implies the potential for timely diagnosis and intervention. This aspect of ERAS compliance is clinically relevant yet has achieved scant attention. Independent validation of our observations is required.

Recent Reanalysis Activities at ECMWF: Results from ERA-20C and Plans for ERA5

NASA Astrophysics Data System (ADS)

Dragani, R.; Hersbach, H.; Poli, P.; Pebeuy, C.; Hirahara, S.; Simmons, A.; Dee, D.

2015-12-01

This presentation will provide an overview of the most recent reanalysis activities performed at the European Centre for Medium-Range Weather Forecasts (ECMWF). A pilot reanalysis of the 20th-century (ERA-20C) has recently been completed. Funded through the European FP7 collaborative project ERA-CLIM, ERA-20C is part of a suite of experiments that also includes a model-only integration (ERA-20CM) and a land-surface reanalysis (ERA-20CL). Its data assimilation system is constrained by only surface observations obtained from ISPD (3.2.6) and ICOADS (2.5.1). Surface boundary conditions are provided by the Hadley Centre (HadISST2.1.0.0) and radiative forcing follows CMIP5 recommended data sets. First-guess uncertainty estimates are based on a 10-member ensemble of Data Assimilations, ERA-20C ensemble, run prior to ERA-20C using ten SST and sea-ice realizations from the Hadley Centre. In November 2014, the European Commission entrusted ECMWF to run on its behalf the Copernicus Climate Change Service (C3S) aiming at producing quality-assured information about the past, current and future states of the climate at both European and global scales. Reanalysis will be one of the main components of the C3S portfolio and the first one to be produced is a global modern era reanalysis (ERA5) covering the period from 1979 onwards. Based on a recent version of the ECMWF data assimilation system, ERA5 will replace the widely used ERA-Interim dataset. This new production will benefit from a much improved model, and better characterized and exploited observations compared to its predecessor. The first part of the presentation will focus on the ERA-20C production, provide an overview of its main characteristics and discuss some of the key results from its assessment. The second part of the talk will give an overview of ERA5, and briefly discuss some of its challenges.

An overview of structurally complex network-based modeling of public opinion in the “We the Media” era

NASA Astrophysics Data System (ADS)

Wang, Guanghui; Wang, Yufei; Liu, Yijun; Chi, Yuxue

2018-05-01

As the transmission of public opinion on the Internet in the “We the Media” era tends to be supraterritorial, concealed and complex, the traditional “point-to-surface” transmission of information has been transformed into “point-to-point” reciprocal transmission. A foundation for studies of the evolution of public opinion and its transmission on the Internet in the “We the Media” era can be laid by converting the massive amounts of fragmented information on public opinion that exists on “We the Media” platforms into structurally complex networks of information. This paper describes studies of structurally complex network-based modeling of public opinion on the Internet in the “We the Media” era from the perspective of the development and evolution of complex networks. The progress that has been made in research projects relevant to the structural modeling of public opinion on the Internet is comprehensively summarized. The review considers aspects such as regular grid-based modeling of the rules that describe the propagation of public opinion on the Internet in the “We the Media” era, social network modeling, dynamic network modeling, and supernetwork modeling. Moreover, an outlook for future studies that address complex network-based modeling of public opinion on the Internet is put forward as a summary from the perspective of modeling conducted using the techniques mentioned above.

An eigensystem realization algorithm using data correlations (ERA/DC) for modal parameter identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Cooper, J. E.; Wright, J. R.

1987-01-01

A modification to the Eigensystem Realization Algorithm (ERA) for modal parameter identification is presented in this paper. The ERA minimum order realization approach using singular value decomposition is combined with the philosophy of the Correlation Fit method in state space form such that response data correlations rather than actual response values are used for modal parameter identification. This new method, the ERA using data correlations (ERA/DC), reduces bias errors due to noise corruption significantly without the need for model overspecification. This method is tested using simulated five-degree-of-freedom system responses corrupted by measurement noise. It is found for this case that, when model overspecification is permitted and a minimum order solution obtained via singular value truncation, the results from the two methods are of similar quality.

Towards a landscape scale management of pesticides: ERA using changes in modelled occupancy and abundance to assess long-term population impacts of pesticides.

PubMed

Topping, Chris J; Craig, Peter S; de Jong, Frank; Klein, Michael; Laskowski, Ryszard; Manachini, Barbara; Pieper, Silvia; Smith, Rob; Sousa, José Paulo; Streissl, Franz; Swarowsky, Klaus; Tiktak, Aaldrik; van der Linden, Ton

2015-12-15

Pesticides are regulated in Europe and this process includes an environmental risk assessment (ERA) for non-target arthropods (NTA). Traditionally a non-spatial or field trial assessment is used. In this study we exemplify the introduction of a spatial context to the ERA as well as suggest a way in which the results of complex models, necessary for proper inclusion of spatial aspects in the ERA, can be presented and evaluated easily using abundance and occupancy ratios (AOR). We used an agent-based simulation system and an existing model for a widespread carabid beetle (Bembidion lampros), to evaluate the impact of a fictitious highly-toxic pesticide on population density and the distribution of beetles in time and space. Landscape structure and field margin management were evaluated by comparing scenario-based ERAs for the beetle. Source-sink dynamics led to an off-crop impact even when no pesticide was present off-crop. In addition, the impacts increased with multi-year application of the pesticide whereas current ERA considers only maximally one year. These results further indicated a complex interaction between landscape structure and pesticide effect in time, both in-crop and off-crop, indicating the need for NTA ERA to be conducted at landscape- and multi-season temporal-scales. Use of AOR indices to compare ERA outputs facilitated easy comparison of scenarios, allowing simultaneous evaluation of impacts and planning of mitigation measures. The landscape and population ERA approach also demonstrates that there is a potential to change from regulation of a pesticide in isolation, towards the consideration of pesticide management at landscape scales and provision of biodiversity benefits via inclusion and testing of mitigation measures in authorisation procedures. Copyright © 2015 Elsevier B.V. All rights reserved.

Implementation Costs of an Enhanced Recovery After Surgery Program in the United States: A Financial Model and Sensitivity Analysis Based on Experiences at a Quaternary Academic Medical Center.

PubMed

Stone, Alexander B; Grant, Michael C; Pio Roda, Claro; Hobson, Deborah; Pawlik, Timothy; Wu, Christopher L; Wick, Elizabeth C

2016-03-01

Despite positive results from several international Enhanced Recovery After Surgery (ERAS) protocols, the United States has been slow to adopt ERAS protocols, in part due to concern regarding the expenses of such a program. We sought to evaluate the potential annual net cost savings of implementing a US-based ERAS program. Using data from existing publications and experience with an ERAS program, a model of net financial costs was developed for surgical groups of escalating numbers of annual cases. Our example scenario provided a financial analysis of the implementation of an ERAS program at a United States academic institution based on data from the ERAS Program for Colorectal Surgery at The Johns Hopkins Hospital. Based on available data from the United States, ERAS programs lead to reductions in lengths of hospital stay that range from 0.7 to 2.7 days and substantial direct cost savings. Using example data from a quaternary hospital, the considerable cost of $552,783 associated with implementation of an ERAS program was offset by even greater savings in the first year of nearly $948,500, yielding a net savings of $395,717. Sensitivity analysis across several caseload and direct cost scenarios yielded similar savings in 20 of the 27 projections. Enhanced Recovery After Surgery protocols have repeatedly led to reduction in length of hospital stay and improved surgical outcomes. A financial model, based on published data and experience, projects that investment in an ERAS program can also lead to net financial savings for US hospitals. Copyright © 2016 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

A three-dimensional multivariate representation of atmospheric variability

NASA Astrophysics Data System (ADS)

Žagar, Nedjeljka; Jelić, Damjan; Blaauw, Marten; Jesenko, Blaž

2016-04-01

A recently developed MODES software has been applied to the ECMWF analyses and forecasts and to several reanalysis datasets to describe the global variability of the balanced and inertio-gravity (IG) circulation across many scales by considering both mass and wind field and the whole model depth. In particular, the IG spectrum, which has only recently become observable in global datasets, can be studied simultaneously in the mass field and wind field and considering the whole model depth. MODES is open-access software that performs the normal-mode function decomposition of the 3D global datasets. Its application to the ERA Interim dataset reveals several aspects of the large-scale circulation after it has been partitioned into the linearly balanced and IG components. The global energy distribution is dominated by the balanced energy while the IG modes contribute around 8% of the total wave energy. However, on subsynoptic scales IG energy dominates and it is associated with the main features of tropical variability on all scales. The presented energy distribution and features of the zonally-averaged and equatorial circulation provide a reference for the intercomparison of several reanalysis datasets and for the validation of climate models. Features of the global IG circulation are compared in ERA Interim, MERRA and JRA reanalysis datasets and in several CMIP5 models. Since October 2014 the operational medium-range forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been analyzed by MODES daily and an online archive of all the outputs is available at http://meteo.fmf.uni-lj.si/MODES. New outputs are made available daily based on the 00 UTC run and subsequent 12-hour forecasts up to 240-hour forecast. In addition to the energy spectra and horizontal circulation on selected levels for the balanced and IG components, the equatorial Kelvin waves are presented in time and space as the most energetic tropical IG modes propagating vertically and along the equator from its main generation regions in the upper troposphere over the Indian and Pacific region. The validation of the 10-day ECMWF forecasts with analyses in the modal space suggests a lack of variability in the tropics in the medium range. Reference: Žagar, N. et al., 2015: Normal-mode function representation of global 3-D data sets: open-access software for the atmospheric research community. Geosci. Model Dev., 8, 1169-1195, doi:10.5194/gmd-8-1169-2015 Žagar, N., R. Buizza, and J. Tribbia, 2015: A three-dimensional multivariate modal analysis of atmospheric predictability with application to the ECMWF ensemble. J. Atmos. Sci., 72, 4423-4444 The MODES software is available from http://meteo.fmf.uni-lj.si/MODES.

Hospital Volume and Operative Mortality in the Modern Era

PubMed Central

Reames, Bradley N.; Ghaferi, Amir A.; Birkmeyer, John D.; Dimick, Justin B.

2014-01-01

Background It is generally accepted that hospital volume is associated with mortality in high-risk procedures. However, as surgical safety has improved over the last decade, recent evidence has suggested that the inverse relationship has diminished or been eliminated. Objective To determine whether the relationship between hospital volume and mortality has changed over time. Methods Using national Medicare claims data from 2000 through 2009, we examined mortality among 3,282,127 patients who underwent one of eight gastrointestinal, cardiac, or vascular procedures. Hospitals were stratified into quintiles of operative volume. Using multivariable logistic regression models to adjust for patient characteristics, we examined the relationship between hospital volume and mortality, and assessed for changes over time. We performed sensitivity analyses using hierarchical logistic regression modeling with hospital-level random effects to confirm our results. Results Throughout the ten-year period, a significant inverse relationship was observed in all procedures. In five of the eight procedures studied, the strength of the volume-outcome relationship increased over time. In esophagectomy, for example, the adjusted odds ratio of mortality in very low volume hospitals compared to very high volume hospitals increased from 2.25 [95%CI: 1.57-3.23] in 2000-2001 to 3.68 [95%CI: 2.66-5.11] in 2008-2009. Only pancreatectomy showed a notable decrease in strength of the relationship over time, from 5.83 [95%CI: 3.64-9.36] in 2000-2001, to 3.08 [95%CI: 2.07 - 4.57] in 2008-2009. Conclusion For all procedures examined, higher volume hospitals had significantly lower mortality rates compared to lower volume hospitals. Despite recent improvements in surgical safety, the strong inverse relationship between hospital volume and mortality persists in the modern era. PMID:24368634

[Multidisciplinary team building in enhanced recovery after surgery].

PubMed

Jia, W D

2018-01-01

There has been 10 years to explore the road in line with China's actual enhanced recovery after surgery(ERAS) since Academician Li Jieshou introduced the view of ERAS into China. ERAS has been widely carried out in the field of surgery, and gradually formed with Chinese characteristics of ERAS clinical pathway.The clinical implementation of ERAS relies on the effective integration of a series of perioperative methods, and any single technique or method can't completely reduce the perioperative physiological and psychological traumatic stress of the patient, so as to achieve the patient's rapid rehabilitation patient-centered multidisciplinary team(MDT)collaboration is an inevitable trend in ERAS development. On the basis of drawing lessons from foreign experience, the establishment of ERAS-MDT model in line with China's national conditions is a new subject that needs to be studied at present. The construction of ERAS-MDT might promote the development of new ERAS services, new technologies, and ultimately promote the improvement of surgical treatment, and bring the greatest clinical benefit to the society and patients.

Implementation of Enhanced Recovery After Surgery: a strategy to transform surgical care across a health system.

PubMed

Gramlich, Leah M; Sheppard, Caroline E; Wasylak, Tracy; Gilmour, Loreen E; Ljungqvist, Olle; Basualdo-Hammond, Carlota; Nelson, Gregg

2017-05-19

Enhanced Recovery After Surgery (ERAS) programs have been shown to have a positive impact on outcome. The ERAS care system includes an evidence-based guideline, an implementation program, and an interactive audit system to support practice change. The purpose of this study is to describe the use of the Theoretic Domains Framework (TDF) in changing surgical care and application of the Quality Enhancement Research Initiative (QUERI) model to analyze end-to-end implementation of ERAS in colorectal surgery across multiple sites within a single health system. The ultimate intent of this work is to allow for the development of a model for spread, scale, and sustainability of ERAS in Alberta Health Services (AHS). ERAS for colorectal surgery was implemented at two sites and then spread to four additional sites. The ERAS Interactive Audit System (EIAS) was used to assess compliance with the guidelines, length of stay, readmissions, and complications. Data sources informing knowledge translation included surveys, focus groups, interviews, and other qualitative data sources such as minutes and status updates. The QUERI model and TDF were used to thematically analyze 189 documents with 2188 quotes meeting the inclusion criteria. Data sources were analyzed for barriers or enablers, organized into a framework that included individual to organization impact, and areas of focus for guideline implementation. Compliance with the evidence-based guidelines for ERAS in colorectal surgery at baseline was 40%. Post implementation compliance, consistent with adoption of best practice, improved to 65%. Barriers and enablers were categorized as clinical practice (22%), individual provider (26%), organization (19%), external environment (7%), and patients (25%). In the Alberta context, 26% of barriers and enablers to ERAS implementation occurred at the site and unit levels, with a provider focus 26% of the time, a patient focus 26% of the time, and a system focus 22% of the time. Using the ERAS care system and applying the QUERI model and TDF allow for identification of strategies that can support diffusion and sustainment of innovation of Enhanced Recovery After Surgery across multiple sites within a health care system.

Trends in Wait-list Mortality in Children Listed for Heart Transplantation in the United States

PubMed Central

Singh, Tajinder P.; Almond, Christopher S.; Piercey, Gary; Gauvreau, Kimberlee

2014-01-01

We sought to evaluate trends in overall and race-specific pediatric heart transplant (HT) wait-list mortality in the United States (US) during the last 20 years. We identified all children <18 years old listed for primary HT in the US during 1989–2009 (N=8096, 62% white, 19% black, 13% Hispanic, 6% other) using the Organ Procurement and Transplant Network database. Wait-list mortality was assessed in 4 successive eras (1989–1994, 1995–1999, 2000–2004, and 2005–2009). Overall wait-list mortality declined in successive eras (26%, 23%, 18% and 13%, respectively). The decline across eras remained significant in adjusted analysis (hazard ratio [HR] 0.70 in successive eras, 95% confidence interval [CI] 0.67, 0.74) and was 67% lower for children listed during 2005–2009 vs. those listed during 1989–1994 (HR 0.33, CI 0.28, 0.39). In models stratified by race, wait-list mortality decreased in all racial groups in successive eras. In models stratified by era, minority children were not at higher risk of wait-list mortality in the most recent era. We conclude that the risk of wait-list mortality among US children listed for HT has decreased by two-thirds during the last 20 years. Racial gaps in wait-list mortality present variably in the past are not present in the current era. PMID:21883920

An intercomparison of multidecadal observational and reanalysis data sets for global total ozone trends and variability analysis

NASA Astrophysics Data System (ADS)

Bai, Kaixu; Chang, Ni-Bin; Shi, Runhe; Yu, Huijia; Gao, Wei

2017-07-01

A four-step adaptive ozone trend estimation scheme is proposed by integrating multivariate linear regression (MLR) and ensemble empirical mode decomposition (EEMD) to analyze the long-term variability of total column ozone from a set of four observational and reanalysis total ozone data sets, including the rarely explored ERA-Interim total ozone reanalysis, from 1979 to 2009. Consistency among the four data sets was first assessed, indicating a mean relative difference of 1% and root-mean-square error around 2% on average, with respect to collocated ground-based total ozone observations. Nevertheless, large drifts with significant spatiotemporal inhomogeneity were diagnosed in ERA-Interim after 1995. To emphasize long-term trends, natural ozone variations associated with the solar cycle, quasi-biennial oscillation, volcanic aerosols, and El Niño-Southern Oscillation were modeled with MLR and then removed from each total ozone record, respectively, before performing EEMD analyses. The resulting rates of change estimated from the proposed scheme captured the long-term ozone variability well, with an inflection time of 2000 clearly detected. The positive rates of change after 2000 suggest that the ozone layer seems to be on a healing path, but the results are still inadequate to conclude an actual recovery of the ozone layer, and more observational evidence is needed. Further investigations suggest that biases embedded in total ozone records may significantly impact ozone trend estimations by resulting in large uncertainty or even negative rates of change after 2000.

Mortality among people living with HIV/AIDS with non-small-cell lung cancer in the modern HAART Era.

PubMed

Smith, Danielle M; Salters, Kate A; Eyawo, Oghenowede; Franco-Villalobos, Conrado; Jabbari, Shahab; Wiseman, Sam M; Press, Natasha; Montaner, Julio S G; Man, S F Paul; Hull, Mark; Hogg, Robert S

2018-02-07

People living with HIV (PLWHA) with adequate access to modern combination antiretroviral therapy (cART) are living longer and experiencing reduced AIDS-related morbidity and mortality. However, increases in non-AIDS related conditions, such as certain cancers, have accompanied these therapeutic advances over time. As such, our study objective was to determine the impact of HIV on all-cause and lung cancer-specific mortality amongst PLWHA with diagnoses of non-small-cell lung cancer (NSCLC) and HIV-negative individuals with NSCLC. This analysis was inclusive of PLWHA on and off cART over the age of 19 years and a 10% comparison sample from the BC population ≥19 years, over a 13-year period (2000-2013). Kaplan-Meier estimates, Cox PH models, and competing risk analysis for all-cause and cause-specific mortality (respectively) compared PLWHA to HIV-negative individuals, controlling for age, gender, cancer stage, co-morbidities; and nadir CD4 count, viral load, and injection drug use for a HIV-positive specific analysis. We identified 71 PLWHA and 2463 HIV-negative individuals diagnosed with NSCLC between 2000 and 2013. PLWHA with NSCLC were diagnosed at a significantly younger age than HIV-negative individuals (median age 57 vs 71 years, p < 0.01). We found no significant difference in lung cancer-specific mortality. However, in multivariate analysis, HIV was associated with greater all-cause mortality (adjusted hazard ratio [aHR]:1.44; 95% confidence interval [CI]: 1.08-1.90), with median survival of 4 months for PLWHA, and 10 months for HIV-negative. Higher nadir CD4 count was protective against mortality (aHR: 0.33, 95% CI: 0.17-0.64) amongst PLWHA in multivariate analysis. Our analysis suggests that PLWHA in the modern cART era experience similar lung cancer survival outcomes compared to the general BC population with NSCLC. However, we also observed significantly higher all-cause mortality among PLWHA with NSCLC, which may warrant further inquiry into the role of HIV in exacerbating mortality among PLWHA with comorbidities and cancer.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

PubMed

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

The pros and cons of ecological risk assessment based on data from different levels of biological organization

PubMed Central

Rohr, Jason R.; Salice, Christopher J.; Nisbet, Roger M.

2016-01-01

Ecological risk assessment (ERA) is the process used to evaluate the safety of manufactured chemicals to the environment. Here we review the pros and cons of ERA across levels of biological organization, including suborganismal (e.g. biomarkers), individual, population, community, ecosystem, and landscapes levels. Our review revealed that level of biological organization is often related negatively with ease at assessing cause-effect relationships, ease of high-throughput screening of large numbers of chemicals (it is especially easier for suborganismal endpoints), and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected). In contrast, level of biological organization is often related positively with sensitivity to important negative and positive feedbacks and context dependencies within biological systems, and ease at capturing recovery from adverse contaminant effects. Some endpoints did not show obvious trends across levels of biological organization, such as the use of vertebrate animals in chemical testing and ease at screening large numbers of species, and other factors lacked sufficient data across levels of biological organization, such as repeatability, variability, cost per study, and cost per species of effects assessment, the latter of which might be a more defensible way to compare costs of ERAs than cost per study. To compensate for weaknesses of ERA at any particular level of biological organization, we also review mathematical modeling approaches commonly used to extrapolate effects across levels of organization. Finally, we provide recommendations for next generation ERA, submitting that if there is an ideal level of biological organization to conduct ERA, it will only emerge if ERA is approached simultaneously from the bottom of biological organization up as well as from the top down, all while employing mathematical modeling approaches where possible to enhance ERA. Because top-down ERA is unconventional, we also offer some suggestions for how it might be implemented efficaciously. We hope this review helps researchers in the field of ERA fill key information gaps and helps risk assessors identify the best levels of biological organization to conduct ERAs with differing goals. PMID:27340745

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

Genetic and Environmental Influences of General Cognitive Ability: Is g a valid latent construct?

PubMed Central

Panizzon, Matthew S.; Vuoksimaa, Eero; Spoon, Kelly M.; Jacobson, Kristen C.; Lyons, Michael J.; Franz, Carol E.; Xian, Hong; Vasilopoulos, Terrie; Kremen, William S.

2014-01-01

Despite an extensive literature, the “g” construct remains a point of debate. Different models explaining the observed relationships among cognitive tests make distinct assumptions about the role of g in relation to those tests and specific cognitive domains. Surprisingly, these different models and their corresponding assumptions are rarely tested against one another. In addition to the comparison of distinct models, a multivariate application of the twin design offers a unique opportunity to test whether there is support for g as a latent construct with its own genetic and environmental influences, or whether the relationships among cognitive tests are instead driven by independent genetic and environmental factors. Here we tested multiple distinct models of the relationships among cognitive tests utilizing data from the Vietnam Era Twin Study of Aging (VETSA), a study of middle-aged male twins. Results indicated that a hierarchical (higher-order) model with a latent g phenotype, as well as specific cognitive domains, was best supported by the data. The latent g factor was highly heritable (86%), and accounted for most, but not all, of the genetic effects in specific cognitive domains and elementary cognitive tests. By directly testing multiple competing models of the relationships among cognitive tests in a genetically-informative design, we are able to provide stronger support than in prior studies for g being a valid latent construct. PMID:24791031

Fatal motor vehicle crashes among veterans of the 1991 Gulf War and exposure to munitions demolitions at Khamisiyah: a nested case-control study.

PubMed

Gackstetter, Gary D; Hooper, Tomoko I; DeBakey, Samar F; Johnson, Amy; Nagaraj, Barbara E; Heller, Jack M; Kang, Han K

2006-04-01

A proposed explanation for the observed higher risk of fatal motor vehicle crashes (MVC) among 1991 Gulf War-deployed veterans is neurocognitive deficits resulting from nerve agent exposure at Khamisiyah, Iraq. Our objective was to assess any association between postwar fatal MVC and possible nerve agent exposure based on 2000 modeled plume data. Cases were defined as MVC deaths with a record in the Department of Transportation Fatality Analysis Reporting System through 1995. Cases (n = 282) and controls (n = 3,131) were derived from a larger nested case-control study of Gulf War-era veterans and limited to Army, male, deployed personnel. Exposure and cumulative dose by case-control status were analyzed using multivariate techniques. Exposure status was not associated with fatal MVC (OR 0.96, 95% CI 0.72-1.26), nor were tertiles of cumulative dose. Findings do not support an association between possible exposures at Khamisiyah and postwar fatal MVC among Gulf War veterans.

The Italian Middle School in a Deregulation Era: Modernity through Path-Dependency and Global Models

ERIC Educational Resources Information Center

Mincu, Monica E.

2015-01-01

In the current context of intensified moves towards educational deregulation, the configuration of the Italian middle school and its relationship to education governance is an interesting case. Historically, it represents a unique example of the successful "decision-making" model of the welfarist era. Despite some internal constraints,…

Conceptual Design and Structural Optimization of NASA Environmentally Responsible Aviation (ERA) Hybrid Wing Body Aircraft

NASA Technical Reports Server (NTRS)

Quinlan, Jesse R.; Gern, Frank H.

2016-01-01

Simultaneously achieving the fuel consumption and noise reduction goals set forth by NASA's Environmentally Responsible Aviation (ERA) project requires innovative and unconventional aircraft concepts. In response, advanced hybrid wing body (HWB) aircraft concepts have been proposed and analyzed as a means of meeting these objectives. For the current study, several HWB concepts were analyzed using the Hybrid wing body Conceptual Design and structural optimization (HCDstruct) analysis code. HCDstruct is a medium-fidelity finite element based conceptual design and structural optimization tool developed to fill the critical analysis gap existing between lower order structural sizing approaches and detailed, often finite element based sizing methods for HWB aircraft concepts. Whereas prior versions of the tool used a half-model approach in building the representative finite element model, a full wing-tip-to-wing-tip modeling capability was recently added to HCDstruct, which alleviated the symmetry constraints at the model centerline in place of a free-flying model and allowed for more realistic center body, aft body, and wing loading and trim response. The latest version of HCDstruct was applied to two ERA reference cases, including the Boeing Open Rotor Engine Integration On an HWB (OREIO) concept and the Boeing ERA-0009H1 concept, and results agreed favorably with detailed Boeing design data and related Flight Optimization System (FLOPS) analyses. Following these benchmark cases, HCDstruct was used to size NASA's ERA HWB concepts and to perform a related scaling study.

A comparison of mental health outcomes in persons entering U.S. military service before and after September 11, 2001.

PubMed

Wells, Timothy S; Ryan, Margaret A K; Jones, Kelly A; Hooper, Tomoko I; Boyko, Edward J; Jacobson, Isabel G; Smith, Tyler C; Gackstetter, Gary D

2012-02-01

It has been hypothesized that those who entered military service in the pre-September 11, 2001 era might have expectations incongruent with their subsequent experiences, increasing the risk for posttraumatic stress disorder (PTSD) or other mental disorders. A subset of Millennium Cohort Study participants who joined the military during 1995-1999 was selected and compared with a subset of members who joined the military in 2002 or later. Outcomes included new-onset symptoms of PTSD, depression, panic/anxiety, and alcohol-related problems. Multivariable methods adjusted for differences in demographic and military characteristics. More than 11,000 cohort members were included in the analyses. Those who entered service in the pre-September 11 era had lower odds of new-onset PTSD symptoms (odds ratio [OR] 0.74, 95% CI [0.59, 0.93]) compared with the post-September 11 cohort. There were no statistically significant differences in rates of new-onset symptoms of depression, panic/anxiety, or alcohol-related problems between the groups. The cohort who entered military service in the pre-September 11 era did not experience higher rates of new-onset mental health challenges compared with the cohort who entered service after September 11, 2001. Findings support the concept that the experience of war, and resulting psychological morbidity, is not a function of incongruent expectations. Copyright © 2012 International Society for Traumatic Stress Studies.

Evaluation of the biomarker candidate MFAP4 for non-invasive assessment of hepatic fibrosis in hepatitis C patients.

PubMed

Bracht, Thilo; Mölleken, Christian; Ahrens, Maike; Poschmann, Gereon; Schlosser, Anders; Eisenacher, Martin; Stühler, Kai; Meyer, Helmut E; Schmiegel, Wolff H; Holmskov, Uffe; Sorensen, Grith L; Sitek, Barbara

2016-07-04

The human microfibrillar-associated protein 4 (MFAP4) is located to extracellular matrix fibers and plays a role in disease-related tissue remodeling. Previously, we identified MFAP4 as a serum biomarker candidate for hepatic fibrosis and cirrhosis in hepatitis C patients. The aim of the present study was to elucidate the potential of MFAP4 as biomarker for hepatic fibrosis with a focus on the differentiation of no to moderate (F0-F2) and severe fibrosis stages and cirrhosis (F3 and F4, Desmet-Scheuer scoring system). MFAP4 levels were measured using an AlphaLISA immunoassay in a retrospective study including n = 542 hepatitis C patients. We applied a univariate logistic regression model based on MFAP4 serum levels and furthermore derived a multivariate model including also age and gender. Youden-optimal cutoffs for binary classification were determined for both models without restrictions and considering a lower limit of 80 % sensitivity (correct classification of F3 and F4), respectively. To assess the generalization error, leave-one-out cross validation (LOOCV) was performed. MFAP4 levels were shown to differ between no to moderate fibrosis stages F0-F2 and severe stages (F3 and F4) with high statistical significance (t test on log scale, p value <2.2·10(-16)). In the LOOCV, the univariate classification resulted in 85.8 % sensitivity and 54.9 % specificity while the multivariate model yielded 81.3 % sensitivity and 61.5 % specificity (restricted approaches). We confirmed the applicability of MFAP4 as a novel serum biomarker for assessment of hepatic fibrosis and identification of high-risk patients with severe fibrosis stages in hepatitis C. The combination of MFAP4 with existing tests might lead to a more accurate non-invasive diagnosis of hepatic fibrosis and allow a cost-effective disease management in the era of new direct acting antivirals.

Global trends in significant wave height and marine wind speed from the ERA-20CM

NASA Astrophysics Data System (ADS)

Aarnes, Ole Johan; Breivik, Øyvind

2016-04-01

The ERA-20CM is one of the latest additions to the ERA-series produced at the European Center for Medium-Range Weather Forecasts (ECMWF). This 10 member ensemble is generated with a version of the Integrated Forecast System (IFS), a coupled atmosphere-wave model. The model integration is run as a AMIP (Atmospheric Model Intercomparison Project) constrained by CMIP5 recommended radiative forcing and different realizations of sea-surface temperature (SST) and sea-ice cover (SIC) prescribed by the HadISST2 (Met Office Hadley Center). While the ERA-20CM is unable to reproduce the actual synoptic conditions, it is designed to offer a realistic statistical representation of the past climate, spanning the period 1899-2010. In this study we investigate global trends in significant wave height and marine wind speed based on ERA-20CM, using monthly mean data, upper percentiles and monthly/annual maxima. The aim of the study is to assess the quality of the trends and how these estimates are affected by different SST and SIC. Global trends are compared against corresponding estimates obtained with ERA-Interim (1979-2009), but also crosschecked against ERA-20C - an ECMWF pilot reanalysis of the 20th-century, known to most trustworthy in the Northern Hemisphere extratropics. Over the period 1900-2009, the 10 member ensemble yields trends mainly within +/- 5% per century. However, significant trends of opposite signs are found locally. Certain areas, like the eastern equatorial Pacific, highly affected by the El Niño Southern Oscillation, show stronger trends. In general, trends based on statistical quantities further into the tail of the distribution are found less reliable.

Application of Deterministic and Probabilistic System Design Methods and Enhancements of Conceptual Design Tools for ERA Project

NASA Technical Reports Server (NTRS)

Mavris, Dimitri N.; Schutte, Jeff S.

2016-01-01

This report documents work done by the Aerospace Systems Design Lab (ASDL) at the Georgia Institute of Technology, Daniel Guggenheim School of Aerospace Engineering for the National Aeronautics and Space Administration, Aeronautics Research Mission Directorate, Integrated System Research Program, Environmentally Responsible Aviation (ERA) Project. This report was prepared under contract NNL12AA12C, "Application of Deterministic and Probabilistic System Design Methods and Enhancement of Conceptual Design Tools for ERA Project". The research within this report addressed the Environmentally Responsible Aviation (ERA) project goal stated in the NRA solicitation "to advance vehicle concepts and technologies that can simultaneously reduce fuel burn, noise, and emissions." To identify technology and vehicle solutions that simultaneously meet these three metrics requires the use of system-level analysis with the appropriate level of fidelity to quantify feasibility, benefits and degradations, and associated risk. In order to perform the system level analysis, the Environmental Design Space (EDS) [Kirby 2008, Schutte 2012a] environment developed by ASDL was used to model both conventional and unconventional configurations as well as to assess technologies from the ERA and N+2 timeframe portfolios. A well-established system design approach was used to perform aircraft conceptual design studies, including technology trade studies to identify technology portfolios capable of accomplishing the ERA project goal and to obtain accurate tradeoffs between performance, noise, and emissions. The ERA goal, shown in Figure 1, is to simultaneously achieve the N+2 benefits of a cumulative noise margin of 42 EPNdB relative to stage 4, a 75 percent reduction in LTO NOx emissions relative to CAEP 6 and a 50 percent reduction in fuel burn relative to the 2005 best in class aircraft. There were 5 research task associated with this research: 1) identify technology collectors, 2) model technology collectors in EDS, 3) model and assess ERA technologies, 4) LTO and cruise emission prediction, and 5) probabilistic analysis of technology collectors and portfolios.

Geophysical excitation of LOD/UT1 estimated from the output of the global circulation models of the atmosphere - ERA-40 reanalysis and of the ocean - OMCT

NASA Astrophysics Data System (ADS)

Korbacz, A.; Brzeziński, A.; Thomas, M.

2008-04-01

We use new estimates of the global atmospheric and oceanic angular momenta (AAM, OAM) to study the influence on LOD/UT1. The AAM series was calculated from the output fields of the atmospheric general circulation model ERA-40 reanalysis. The OAM series is an outcome of global ocean model OMCT simulation driven by global fields of the atmospheric parameters from the ERA- 40 reanalysis. The excitation data cover the period between 1963 and 2001. Our calculations concern atmospheric and oceanic effects in LOD/UT1 over the periods between 20 days and decades. Results are compared to those derived from the alternative AAM/OAM data sets.

Entropy in universes evolving from initial to final de Sitter eras

NASA Astrophysics Data System (ADS)

Mimoso, José P.; Pavón, Diego

2014-05-01

This work studies the behavior of entropy in recent cosmological models that start with an initial de Sitter expansion phase, go through the conventional radiation and matter dominated eras to be followed by a final de Sitter epoch. In spite of their seemingly similarities (observationally they are close to the Λ-CDM model), different models deeply differ in their physics. The second law of thermodynamics encapsulates the underlying microscopic, statistical description, and hence we investigate it in the present work. Our study reveals that the entropy of the apparent horizon plus that of matter and radiation inside it, increases and is a concave function of the scale factor. Thus thermodynamic equilibrium is approached in the last de Sitter era, and this class of models is thermodynamically correct. Cosmological models that do not approach equilibrium appear in conflict with the second law of thermodynamics. (Based on Mimoso & Pavon 2013)

A mathematical simulation model of a 1985-era tilt-rotor passenger aircraft

NASA Technical Reports Server (NTRS)

Mcveigh, M. A.; Widdison, C. A.

1976-01-01

A mathematical model for use in real-time piloted simulation of a 1985-era tilt rotor passenger aircraft is presented. The model comprises the basic six degrees-of-freedom equations of motion, and a large angle of attack representation of the airframe and rotor aerodynamics, together with equations and functions used to model turbine engine performance, aircraft control system and stability augmentation system. A complete derivation of the primary equations is given together with a description of the modeling techniques used. Data for the model is included in an appendix.

Apneic oxygenation reduces hypoxemia during endotracheal intubation in the pediatric emergency department.

PubMed

Vukovic, Adam A; Hanson, Holly R; Murphy, Shelley L; Mercurio, Danielle; Sheedy, Craig A; Arnold, Donald H

2018-04-18

Apneic oxygenation (AO) has been evaluated in adult patients as a means of reducing hypoxemia during endotracheal intubation (ETI). While less studied in pediatric patients, its practice has been largely adopted. Determine association between AO and hypoxemia in pediatric patients undergoing ETI. Observational study at an urban, tertiary children's hospital emergency department. Pediatric patients undergoing ETI were examined during eras without (January 2011-June 2011) and with (August 2014-March 2017) apneic oxygenation. The primary outcome was hypoxemia, defined as pulse oximetry (SpO 2 ) < 90%. The χ 2 and Wilcoxon rank-sum tests examined differences between cohorts. Multivariable regression models examined adjusted associations between covariates and hypoxemia. 149 patients were included. Cohorts were similar except for greater incidence of altered mental status in those receiving AO (26% vs. 7%, p = 0.03). Nearly 50% of the pre-AO cohort experienced hypoxemia during ETI, versus <25% in the AO cohort. Median [IQR] lowest SpO 2 during ETI was 93 (69, 99) for pre-AO and 100 [95, 100] for the AO cohort (p < 0.001). In a multivariable logistic regression model, hypoxemia during ETI was associated with AO (aOR 0.3, 95% confidence interval [CI] 0.1-0.8), increased age (for 1 year, aOR 0.8, 95% CI 0.7-1.0), lowest SpO 2 before ETI (for 1% increase, aOR 0.9, 95% CI 0.8-1.0), and each additional intubation attempt (aOR 4.0, 95% CI 2.2-7.2). Apneic oxygenation is an easily-applied intervention associated with decreases in hypoxemia during pediatric ETI. Nearly 50% of children not receiving AO experienced hypoxemia. Copyright © 2018 Elsevier Inc. All rights reserved.

Is pre-transplant sensitization against angiotensin II type 1 receptor still a risk factor of graft and patient outcome in kidney transplantation in the anti-HLA Luminex era? A retrospective study.

PubMed

Deltombe, Clement; Gillaizeau, Florence; Anglicheau, Daniel; Morelon, Emmanuel; Trébern-Launay, Katy; Le Borgne, Florent; Rimbert, Marie; Guérif, Pierrick; Malard-Castagnet, Stéphanie; Foucher, Yohann; Giral, Magali

2017-11-01

We aimed to assess the correlation of anti-angiotensin II type 1 receptor antibodies (anti-AT1R-Abs) before transplantation on a multicentric cohort of kidney transplant recipients (2008-2012), under tacrolimus and mycophenolate mofetil (MMF), screened by Luminex technology for anti-HLA immunization. Anti-AT1R antibody levels were measured by ELISA in pretransplantation sera of 940 kidney recipients from three French centers of the DIVAT cohort. Multivariable Cox models estimated the association between pretransplant anti-angiotensin II type 1 receptor antibodies and time to acute rejection episodes (ARE) or time to graft failure. Within our cohort, 387 patients (41.2%) had pretransplant AT1R-Abs higher than 10 U/ml and only 8% (72/970) greater than 17 U/ml. The cumulative probability of clinically relevant (cr)-ARE was 22.5% at 1 year post-transplantation [95% CI (19.9-25.4%)]. The cumulative probability of graft failure and patient death were 10.6% [95% CI (8.4-13.3%)] and 5.7% [95% CI (4.0-8.1%)] at 3 years post-transplantation, respectively. Multivariate Cox models indicated that pretransplant anti-AT1R antibody levels higher than 10 U/ml were not significantly independently associated with higher risks of acute rejection episodes [HR = 1.04, 95% CI (0.80-1.35)] nor with risk of graft failure [HR = 0.86, 95% CI (0.56-1.33)]. Our study did not confirm an association between pretransplant anti-AT1R antibody levels and kidney transplant outcomes. © 2017 Steunstichting ESOT.

Promoting health (implicitly)? A longitudinal content analysis of implicit health information in cigarette advertising, 1954-2003.

PubMed

Paek, Hye-Jin; Reid, Leonard N; Choi, Hojoon; Jeong, Hyun Ju

2010-10-01

Tobacco studies indicate that health-related information in cigarette advertising leads consumers to underestimate the detrimental health effects of smoking and contributes to their smoking-related perceptions, beliefs, and attitudes. This study examined the frequencies and kinds of implicit health information in cigarette advertising across five distinct smoking eras covering the years 1954-2003. Analysis of 1,135 cigarette advertisements collected through multistage probability sampling of three popular consumer magazines found that the level of implicit health information (i.e., "light" cigarette, cigarette pack color, verbal and visual health cues, cigarette portrayals, and human model-cigarette interaction) in post-Master Settlement Agreement [MSA] era ads is similar to the level in ads from early smoking eras. Specifically, "light" cigarettes were frequently promoted, and presence of light colors in cigarette packs seemed dominant after the probroadcast ban era. Impressionistic verbal health cues (e.g., soft, mild, and refreshing) appeared more frequently in post-MSA era ads than in pre-MSA era ads. Most notably, a majority of the cigarette ads portrayed models smoking, lighting, or offering a cigarette to others. The potential impact of implicit health information is discussed in the contexts of social cognition and Social Cognitive Theory. Policy implications regarding our findings are also detailed.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

Standard International prognostic index remains a valid predictor of outcome for patients with aggressive CD20+ B-cell lymphoma in the rituximab era.

PubMed

Ziepert, Marita; Hasenclever, Dirk; Kuhnt, Evelyn; Glass, Bertram; Schmitz, Norbert; Pfreundschuh, Michael; Loeffler, Markus

2010-05-10

The International Prognostic Index (IPI) is widely used for risk stratification of patients with aggressive B-cell lymphoma. The introduction of rituximab has markedly improved outcome, and R-CHOP (rituximab + cyclophosphamide, doxorubicin, vincristine, prednisone) has become the standard treatment for CD20(+) diffuse large B-cell lymphoma. To investigate whether the IPI has maintained its power for risk stratification when rituximab is combined with CHOP, we analyzed the prognostic relevance of IPI in three prospective clinical trials. In total, 1,062 patients treated with rituximab were included (MabThera International Trial [MInT], 380 patients; dose-escalated regimen of cyclophosphamide, doxorubicin, vincristine, etoposide, and prednisone (MegaCHOEP) trial, 72 patients; CHOP + rituximab for patients older than age 60 years [RICOVER-60] trial, 610 patients). A multivariate proportional hazards modeling was performed for single IPI factors under rituximab on event-free, progression-free, and overall survival. IPI score was significant for all three end points. Rituximab significantly improved treatment outcome within each IPI group resulting in a quenching of the Kaplan-Meier estimators. However, IPI was a significant prognostic factor in all three end points and the ordering of the IPI groups remained valid. The relative risk estimates of single IPI factors and their order in patients treated with R-CHOP were similar to those found with CHOP. The effects of rituximab were superimposed on the effects of CHOP with no interactions between chemotherapy and antibody therapy. These results demonstrate that the IPI is still valid in the R-CHOP era.

Radiation biology and oncology in the genomic era.

PubMed

Kerns, Sarah L; Chuang, Kuang-Hsiang; Hall, William; Werner, Zachary; Chen, Yuhchyau; Ostrer, Harry; West, Catharine; Rosenstein, Barry

2018-06-14

Radiobiology research is building the foundation for applying genomics in precision radiation oncology. Advances in high-throughput approaches will underpin increased understanding of radiosensitivity and the development of future predictive assays for clinical application. There is an established contribution of genetics as a risk factor for radiotherapy side effects. An individual's radiosensitivity is an inherited polygenic trait with an architecture that includes rare mutations in a few genes that confer large effects and common variants in many genes with small effects. Current thinking is that some will be tissue specific, and future tests will be tailored to the normal tissues at risk. The relationship between normal and tumor cell radiosensitivity is poorly understood. Data are emerging suggesting interplay between germline genetic variation and epigenetic modification with growing evidence that changes in DNA methylation regulate the radiosensitivity of cancer cells and histone acetyltransferase inhibitors have radiosensitizing effects. Changes in histone methylation can also impair DNA damage response signaling and alter radiosensitivity. An important effort to advance radiobiology in the genomic era was establishment of the Radiogenomics Consortium to enable the creation of the large radiotherapy cohorts required to exploit advances in genomics. To address challenges in harmonizing data from multiple cohorts, the consortium established the REQUITE project to collect standardized data and genotyping for ~5,000 patients. The collection of detailed dosimetric data is important to produce validated multivariable models. Continued efforts will identify new genes that impact on radiosensitivity to generate new knowledge on toxicity pathogenesis and tests to incorporate into the clinical decision-making process.

Psychology of change: Models and implications for nuclear plants in an era of deregulation

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

Gates, W.G.; Stark, J.A.

This presentation explores the psychology of change in the implications that it has for nuclear plants during this era of deregulation. The authors analyze models that work, models that have failed in the past, and specific findings and applications based on 2 yr of research, as well as the results regarding the impact of the psychology of change on the Fort Calhoun nuclear station in Nebraska.

Evaluation of the sensitivity of the Amazonian diurnal cycle to convective intensity in reanalyses

NASA Astrophysics Data System (ADS)

Itterly, Kyle F.; Taylor, Patrick C.

2017-02-01

Model parameterizations of tropical deep convection are unable to reproduce the observed diurnal and spatial variability of convection in the Amazon, which contributes to climatological biases in the water cycle and energy budget. Convective intensity regimes are defined using percentiles of daily minimum 3-hourly averaged outgoing longwave radiation (OLR) from Clouds and the Earth's Radiant Energy System (CERES). This study compares the observed spatial variability of convective diurnal cycle statistics for each regime to MERRA-2 and ERA-Interim (ERA) reanalysis data sets. Composite diurnal cycle statistics are computed for daytime hours (06:00-21:00 local time) in the wet season (December-January-February). MERRA-2 matches observations more closely than ERA for domain averaged composite diurnal statistics—specifically precipitation. However, ERA reproduces mesoscale features of OLR and precipitation phase associated with topography and the propagation of the coastal squall line. Both reanalysis models are shown to underestimate extreme convection.

Evaluation of the Sensitivity of the Amazonian Diurnal Cycle to Convective Intensity in Reanalyses

NASA Technical Reports Server (NTRS)

Itterly, Kyle F.; Taylor, Patrick C.

2016-01-01

Model parameterizations of tropical deep convection are unable to reproduce the observed diurnal and spatial variability of convection in the Amazon, which contributes to climatological biases in the water cycle and energy budget. Convective intensity regimes are defined using percentiles of daily minimum 3-hourly averaged outgoing longwave radiation (OLR) from Clouds and the Earth's Radiant Energy System (CERES). This study compares the observed spatial variability of convective diurnal cycle statistics for each regime to MERRA-2 and ERA-Interim (ERA) reanalysis data sets. Composite diurnal cycle statistics are computed for daytime hours (06:00-21:00 local time) in the wet season (December-January-February). MERRA-2 matches observations more closely than ERA for domain averaged composite diurnal statistics-specifically precipitation. However, ERA reproduces mesoscale features of OLR and precipitation phase associated with topography and the propagation of the coastal squall line. Both reanalysis models are shown to underestimate extreme convection.

Moisture balance over the Iberian Peninsula computed using a high resolution regional climate model. The impact of 3DVAR data assimilation.

NASA Astrophysics Data System (ADS)

González-Rojí, Santos J.; Sáenz, Jon; Ibarra-Berastegi, Gabriel

2016-04-01

A numerical downscaling exercise over the Iberian Peninsula has been run nesting the WRF model inside ERA Interim. The Iberian Peninsula has been covered by a 15km x 15 km grid with 51 vertical levels. Two model configurations have been tested in two experiments spanning the period 2010-2014 after a one year spin-up (2009). In both cases, the model uses high resolution daily-varying SST fields and the Noah land surface model. In the first experiment (N), after the model is initialised, boundary conditions drive the model, as usual in numerical downscaling experiments. The second experiment (D) is configured the same way as the N case, but 3DVAR data assimilation is run every six hours (00Z, 06Z, 12Z and 18Z) using observations obtained from the PREPBUFR dataset (NCEP ADP Global Upper Air and Surface Weather Observations) using a 120' window around analysis times. For the data assimilation experiment (D), seasonally (monthly) varying background error covariance matrices have been prepared according to the parameterisations used and the mesoscale model domain. For both N and D runs, the moisture balance of the model runs has been evaluated over the Iberian Peninsula, both internally according to the model results (moisture balance in the model) and also in terms of the observed moisture fields from observational datasets (particularly precipitable water and precipitation from observations). Verification has been performed both at the daily and monthly time scales. The verification has also been performed for ERA Interim, the driving coarse-scale dataset used to drive the regional model too. Results show that the leading terms that must be considered over the area are the tendency in the precipitable water column, the divergence of moisture flux, evaporation (computed from latent heat flux at the surface) and precipitation. In the case of ERA Interim, the divergence of Qc is also relevant, although still a minor player in the moisture balance. Both mesoscale model runs are more effective at closing the moisture balance over the whole Iberian Peninsula than ERA Interim. The N experiment (no data assimilation) shows a better closure than the D case, as could be expected from the lack of analysis increments in it. This result is robust both at the daily and monthly time scales. Both ERA Interim and the D experiment produce a negative residual in the balance equation (compatible with excess evaporation or increased convergence of moisture over the Iberian Peninsula). This is a result of the data assimilation process in the D dataset, since in the N experiment the residual is mainly positive. The seasonal cycle of evaporation is much closer in the D experiment to the one in ERA Interim than in the N case, with a higher evaporation during summer months. However, both regional climate model runs show a lower evaporation rate than ERA Interim, particularly during summer months.

How air pollution influences clinical management of respiratory diseases. A case-crossover study in Milan.

PubMed

Santus, Pierachille; Russo, Antonio; Madonini, Enzo; Allegra, Luigi; Blasi, Francesco; Centanni, Stefano; Miadonna, Antonio; Schiraldi, Gianfranco; Amaducci, Sandro

2012-10-18

Environmental pollution is a known risk factor for multiple diseases and furthermore increases rate of hospitalisations. We investigated the correlation between emergency room admissions (ERAs) of the general population for respiratory diseases and the environmental pollutant levels in Milan, a metropolis in northern Italy. We collected data from 45770 ERAs for respiratory diseases. A time-stratified case-crossover design was used to investigate the association between air pollution levels and ERAs for acute respiratory conditions. The effects of air pollutants were investigated at lag 0 to lag 5, lag 0-2 and lag 3-5 in both single and multi-pollutant models, adjusted for daily weather variables. An increase in ozone (O(3)) levels at lag 3-5 was associated with a 78% increase in the number of ERAs for asthma, especially during the warm season. Exposure to carbon monoxide (CO) proved to be a risk factor for pneumonia at lag 0-2 and in the warm season increased the risk of ERA by 66%. A significant association was found between ERAs for COPD exacerbation and levels of sulphur dioxide (SO(2)), CO, nitrate dioxide (NO(2)), and particulate matter (PM(10) and PM(2.5)). The multipollutant model that includes all pollutants showed a significant association between CO (26%) and ERA for upper respiratory tract diseases at lag 0-2. For chronic obstructive pulmonary disease (COPD) exacerbations, only CO (OR 1.19) showed a significant association. Exposure to environmental pollution, even at typical low levels, can increase the risk of ERA for acute respiratory diseases and exacerbation of obstructive lung diseases in the general population.

True survival benefit of lung transplantation for cystic fibrosis patients: the Zurich experience.

PubMed

Hofer, Markus; Benden, Christian; Inci, Ilhan; Schmid, Christoph; Irani, Sarosh; Speich, Rudolf; Weder, Walter; Boehler, Annette

2009-04-01

Lung transplantation is the ultimate therapy for end-stage cystic fibrosis (CF) lung disease; however, the debate continues as to whether lung transplantation improves survival. We report post-transplant outcome in CF at our institution by comparing 5-year post-transplant survival with a calculated 5-year survival without lung transplantation, using a predictive 5-year survivorship model, and describe pre-transplant parameters influencing transplant outcome. CF patients undergoing lung transplantation at our center were included (1992 to 2007). Survival rates were calculated and compared, and univariate and multivariate Cox regression analyses were used for statistical assessment. Eighty transplants were performed in CF patients, 11 (13.8%) of whom were children. Mean age at transplant was 26.2 years (95% confidence interval: 24.4 to 28.0). The Liou raw score at transplant was -20 (95% confidence interval: -16 to -24), resulting in an estimated 5-year survival without transplantation of 33 +/- 14%, compared with a 5-year post-transplant survival of 68.2 +/- 5.6%. Further improvement was noted in the recent transplant era (since 2000), with a 5-year survival of 72.7 +/- 7.3%. Univariate analysis revealed that later year of transplant and diagnosis of diabetes influenced survival positively. Pediatric age had no negative impact. In the multivariate analysis, only diabetes influenced survival, in a positive manner. Lung transplantation performed at centers having experience with the procedure can offer a true survival benefit to patients with end-stage CF lung disease.

A new multivariate zero-adjusted Poisson model with applications to biomedicine.

PubMed

Liu, Yin; Tian, Guo-Liang; Tang, Man-Lai; Yuen, Kam Chuen

2018-05-25

Recently, although advances were made on modeling multivariate count data, existing models really has several limitations: (i) The multivariate Poisson log-normal model (Aitchison and Ho, ) cannot be used to fit multivariate count data with excess zero-vectors; (ii) The multivariate zero-inflated Poisson (ZIP) distribution (Li et al., 1999) cannot be used to model zero-truncated/deflated count data and it is difficult to apply to high-dimensional cases; (iii) The Type I multivariate zero-adjusted Poisson (ZAP) distribution (Tian et al., 2017) could only model multivariate count data with a special correlation structure for random components that are all positive or negative. In this paper, we first introduce a new multivariate ZAP distribution, based on a multivariate Poisson distribution, which allows the correlations between components with a more flexible dependency structure, that is some of the correlation coefficients could be positive while others could be negative. We then develop its important distributional properties, and provide efficient statistical inference methods for multivariate ZAP model with or without covariates. Two real data examples in biomedicine are used to illustrate the proposed methods. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Physical abuse in the era of financial crisis in Greece.

PubMed

Kontos, Michael; Moris, Demetrios; Davakis, Spyridon; Schizas, Dimitrios; Pikoulis, Emmanouil; Liakakos, Theodoros

2017-04-01

Greece is suffering an economic recession of enormous magnitude, but whether its health has deteriorated as a result, has not yet been well established. We aim to present and analyze differences in demographics and clinical distribution of patients victims of physical abuse examined at the surgical emergency room in an Academic institution in the era of financial crisis. A retrospective database analysis of all patients that were examined to surgical emergency room (ER), between January 1st 2008 and December 31st 2014, was conducted. We only analyzed and evaluated data for the years 2008 to 2014. The number of patients being examined in the ER in 2011 was higher compared with that of 2014 and to 2008 respectively (P<0.05). There was an increase of the total cases of physical abuse (P<0.05). The majority of cases examined for physical abuse were men, with a constant tendency of increasing number of women abused throughout the years of crisis. Financial crisis seems to have a multivariable effect on epidemiology and clinical diversity of the patients, victims of physical abuse, being examined in the ER.

Effects of past logging and grazing on understory plant communities in a montane Colorado forest

USGS Publications Warehouse

Fornwalt, P.J.; Kaufmann, M.R.; Huckaby, L.S.; Stohlgren, T.J.

2009-01-01

Throughout Pinus ponderosa-Pseudotsuga menziesii forests of the southern Colorado Front Range, USA, intense logging and domestic grazing began at the time of Euro-American settlement in the late 1800s and continued until the early 1900s. We investigated the long-term impacts of these settlement-era activities on understory plant communities by comparing understory composition at a historically logged and grazed site to that of an environmentally similar site which was protected from past use. We found that species richness and cover within functional groups rarely differed between sites in either upland or riparian areas. Multivariate analyses revealed little difference in species composition between sites on uplands, though compositional differences were apparent in riparian zones. Our findings suggest that settlement-era logging and grazing have had only minor long-term impacts on understories of upland Front Range P. ponderosa-P. menziesii forests, though they have had a greater long-term influence on riparian understories, where these activities were likely the most intense. ?? 2008 Springer Science+Business Media B.V.

Assessment of moisture budget over West Africa using MERRA-2's aerological model and satellite data

NASA Astrophysics Data System (ADS)

Igbawua, Tertsea; Zhang, Jiahua; Yao, Fengmei; Zhang, Da

2018-02-01

The study assessed the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and MERRA-2 aerological (P-E*) model in reproducing the salient features of West Africa water balance including its components from 1980 to 2013. In this study we have shown that recent reanalysis efforts have generated imbalances between regional integrated precipitation (P) and surface evaporation (E), and the effect is more in the newly released MERRA-2. The atmospheric water balance of MERRA and MERRA-2 were inter-compared and thereafter compared with model forecast output of European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-I) and Japanese 55-year Reanalysis (JRA-55). Results indicated that a bias of 12-20 (5-13) mm/month in MERRA-2 (ERA-I) leads to the classification of the Sahel (14°N-20°N) as a moisture source during the West African Summer Monsoon. Comparisons between MERRA/MERRA-2 and prognostic fields from two ERA-I and JRA-55 indicated that the average P-E* in MERRA is 18.94 (52.24) mm/month which is less than ERA-I (JRA-55) over Guinea domain and 25.03 (4.53) mm/month greater than ERA-I (JRA-55) over the Sahel. In MERRA-2, average P-E* indicated 25.76 (59.06) mm/month which is less than ERA-I (JRA-55) over Guinea and 73.72 (94.22) mm/month less than ERA-I (JRA-55) over the Sahel respectively. These imbalances are due to adjustments in data assimilation methods, satellite calibration and observational data base. The change in convective P parameterization and increased re-evaporation of P in MERRA-2 is suggestive of the cause of positive biases in P and E. The little disagreements between MERRA/MERRA-2 and CRU precipitation highlights one of the major challenges associated with climate research in West Africa and major improvements in observation data and surface fluxes from reanalysis remain vital.

Seasonal evaluation of evapotranspiration fluxes from MODIS satellite and mesoscale model downscaled global reanalysis datasets

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Petropoulos, George P.; Gupta, Manika; Dai, Qiang

2016-04-01

Reference evapotranspiration (ETo) is an important variable in hydrological modeling, which is not always available, especially for ungauged catchments. Satellite data, such as those available from the MODerate Resolution Imaging Spectroradiometer (MODIS), and global datasets via the European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis (ERA) interim and National Centers for Environmental Prediction (NCEP) reanalysis are important sources of information for ETo. This study explored the seasonal performances of MODIS (MOD16) and Weather Research and Forecasting (WRF) model downscaled global reanalysis datasets, such as ERA interim and NCEP-derived ETo, against ground-based datasets. Overall, on the basis of the statistical metrics computed, ETo derived from ERA interim and MODIS were more accurate in comparison to the estimates from NCEP for all the seasons. The pooled datasets also revealed a similar performance to the seasonal assessment with higher agreement for the ERA interim (r = 0.96, RMSE = 2.76 mm/8 days; bias = 0.24 mm/8 days), followed by MODIS (r = 0.95, RMSE = 7.66 mm/8 days; bias = -7.17 mm/8 days) and NCEP (r = 0.76, RMSE = 11.81 mm/8 days; bias = -10.20 mm/8 days). The only limitation with downscaling ERA interim reanalysis datasets using WRF is that it is time-consuming in contrast to the readily available MODIS operational product for use in mesoscale studies and practical applications.

An economic evaluation of the Enhanced Recovery After Surgery (ERAS) multisite implementation program for colorectal surgery in Alberta

PubMed Central

Thanh, Nguyen X.; Chuck, Anderson W.; Wasylak, Tracy; Lawrence, Jeannette; Faris, Peter; Ljungqvist, Olle; Nelson, Gregg; Gramlich, Leah M.

2016-01-01

Background In February 2013, Alberta Health Services established an Enhanced Recovery After Surgery (ERAS) implementation program for adopting the ERAS Society colorectal guidelines into 6 sites (initial phase) that perform more than 75% of all colorectal surgeries in the province. We conducted an economic evaluation of this initiative to not only determine its cost-effectiveness, but also to inform strategy for the spread and scale of ERAS to other surgical protocols and sites. Methods We assessed the impact of ERAS on patients’ health services utilization (HSU; length of stay [LOS], readmissions, emergency department visits, general practitioner and specialist visits) within 30 days of discharge by comparing pre- and post-ERAS groups using multilevel negative binomial regressions. We estimated the net health care costs/savings and the return on investment (ROI) associated with those impacts for post-ERAS patients using a decision analytic modelling technique. Results We included 331 pre- and 1295 post-ERAS patients in our analyses. ERAS was associated with a reduction in all HSU outcomes except visits to specialists. However, only the reduction in primary LOS was significant. The net health system savings were estimated at $2 290 000 (range $1 191 000–$3 391 000), or $1768 (range $920–$2619) per patient. The probability for the program to be cost-saving was 73%–83%. In terms of ROI, every $1 invested in ERAS would bring $3.8 (range $2.4–$5.1) in return. Conclusion The initial phase of ERAS implementation for colorectal surgery in Alberta is cost-saving. The total savings has the potential to be more substantial when ERAS is spread for other surgical protocols and across additional sites. PMID:28445024

Loop quantum cosmology scalar field models

NASA Astrophysics Data System (ADS)

Kleidis, K.; Oikonomou, V. K.

In this work, we use the Loop Quantum Cosmology (LQC) modified scalar-tensor reconstruction techniques in order to investigate how bouncing and inflationary cosmologies can be realized. With regard to the inflationary cosmologies, we shall be interested in realizing the intermediate inflation and the Type IV singular inflation, while with regard to bouncing cosmologies, we shall realize the superbounce and the symmetric bounce. In all the cases, we shall find the kinetic term of the LQC holonomy corrected scalar-tensor theory and the corresponding scalar potential. In addition, we shall include a study of the effective Equation of State (EoS), emphasizing at the early- and late-time eras. As we demonstrate, in some cases it is possible to have a nearly de Sitter EoS at the late-time era, a result that could be interpreted as the description of a late-time acceleration era. Also, in all cases we shall examine the dynamical stability of the LQC holonomy corrected scalar-tensor theory, and we shall confront the results with those coming from the corresponding classical dynamical stability theory. The most appealing cosmological scenario is that of a Type IV singular inflationary scenario, in which the singularity may occur at the late-time era. As we demonstrate, for this model, during the dark energy era, a transition from non-phantom to a phantom dark energy era occurs.

Emotion-regulation ability, role stress and teachers' mental health.

PubMed

Mérida-López, S; Extremera, N; Rey, L

2017-10-01

Work-related stressors, including role ambiguity and role conflict, are related to psychological maladjustment and mental ill-health. However, to date, the role of personal resources such as emotion-regulation ability (ERA) in the prediction of mental health indicators has not been addressed. To examine whether ERA would contribute to explaining teachers' depression, anxiety and stress symptoms beyond role ambiguity and role conflict. We carried out a cross-sectional questionnaire survey. We used a correlation matrix and hierarchical regression models to analyse the data. Three hundred and thirty-six Spanish teachers (185 female) from several grade levels completed the surveys (40% response rate). Role ambiguity and role conflict were positively related to depression, anxiety and stress symptoms. ERA was negatively related to teachers' scores on depressive, anxious and stress symptoms, with predictive power above the main effects of role ambiguity and role conflict. An interaction between role ambiguity and ERA was also significant in predicting depression. Our study provides preliminary evidence suggesting the development of integrative models considering work-related stressors along with personal resources such as ERA aiming to prevent teachers' mental ill-health. Future studies should examine the influence of ERA on psychological symptoms using longitudinal designs. © The Author 2017. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Impact of variational assimilation using multivariate background error covariances on the simulation of monsoon depressions over India

NASA Astrophysics Data System (ADS)

Dhanya, M.; Chandrasekar, A.

2016-02-01

The background error covariance structure influences a variational data assimilation system immensely. The simulation of a weather phenomenon like monsoon depression can hence be influenced by the background correlation information used in the analysis formulation. The Weather Research and Forecasting Model Data assimilation (WRFDA) system includes an option for formulating multivariate background correlations for its three-dimensional variational (3DVar) system (cv6 option). The impact of using such a formulation in the simulation of three monsoon depressions over India is investigated in this study. Analysis and forecast fields generated using this option are compared with those obtained using the default formulation for regional background error correlations (cv5) in WRFDA and with a base run without any assimilation. The model rainfall forecasts are compared with rainfall observations from the Tropical Rainfall Measurement Mission (TRMM) and the other model forecast fields are compared with a high-resolution analysis as well as with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis. The results of the study indicate that inclusion of additional correlation information in background error statistics has a moderate impact on the vertical profiles of relative humidity, moisture convergence, horizontal divergence and the temperature structure at the depression centre at the analysis time of the cv5/cv6 sensitivity experiments. Moderate improvements are seen in two of the three depressions investigated in this study. An improved thermodynamic and moisture structure at the initial time is expected to provide for improved rainfall simulation. The results of the study indicate that the skill scores of accumulated rainfall are somewhat better for the cv6 option as compared to the cv5 option for at least two of the three depression cases studied, especially at the higher threshold levels. Considering the importance of utilising improved flow-dependent correlation structures for efficient data assimilation, the need for more studies on the impact of background error covariances is obvious.

Consistent scalar and tensor perturbation power spectra in single fluid matter bounce with dark energy era

NASA Astrophysics Data System (ADS)

Bacalhau, Anna Paula; Pinto-Neto, Nelson; Vitenti, Sandro Dias Pinto

2018-04-01

We investigate cosmological scenarios containing one canonical scalar field with an exponential potential in the context of bouncing models, in which the bounce happens due to quantum cosmological effects. The only possible bouncing solutions in this scenario (discarding an infinitely fine-tuned exception) must have one and only one dark energy phase, occurring either in the contracting era or in the expanding era. Hence, these bounce solutions are necessarily asymmetric. Naturally, the more convenient solution is the one in which the dark energy phase happens in the expanding era, in order to be a possible explanation for the current accelerated expansion indicated by cosmological observations. In this case, one has the picture of a Universe undergoing a classical dust contraction from very large scales, the initial repeller of the model, moving to a classical stiff-matter contraction near the singularity, which is avoided due to the quantum bounce. The Universe is then launched to a dark energy era, after passing through radiation- and dust-dominated phases, finally returning to the dust expanding phase, the final attractor of the model. We calculate the spectral indices and amplitudes of scalar and tensor perturbations numerically, considering the whole history of the model, including the bounce phase itself, without making any approximation nor using any matching condition on the perturbations. As the background model is necessarily dust dominated in the far past, the usual adiabatic vacuum initial conditions can be easily imposed in this era. Hence, this is a cosmological model in which the presence of dark energy behavior in the Universe does not turn the usual vacuum initial conditions prescription for cosmological perturbation in bouncing models problematic. Scalar and tensor perturbations end up being almost scale invariant, as expected. The background parameters can be adjusted, without fine-tunings, to yield the observed amplitude for scalar perturbations and also for the ratio between tensor and scalar amplitudes, r =T /S ≲0.1 . The amplification of scalar perturbations over tensor perturbations takes place only around the bounce, due to quantum effects, and it would not occur if General Relativity has remained valid throughout this phase. Hence, this is a bouncing model in which a single field induces not only an expanding background dark energy phase but also produces all observed features of cosmological perturbations of quantum mechanical origin at linear order.

Risk of second malignancies in patients with early-stage classical Hodgkin's lymphoma treated in a modern era.

PubMed

LeMieux, Melissa H; Solanki, Abhishek A; Mahmood, Usama; Chmura, Steven J; Koshy, Matthew

2015-04-01

Second malignancies remain an issue affecting morbidity and mortality in long-term survivors of early stage Hodgkin's lymphoma (HL). We undertook this study to determine if treatment in the modern era resulted in decreased second malignancies. Patients diagnosed with stage I-II cHL between 1988 and 2009 who received radiation therapy (RT) were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Freedom from second malignancy (FFSM) was estimated using the Kaplan-Meier method. Univariate analysis (UVA) was performed using the Log-Rank test, and included age, gender, year of diagnosis, and stage. Multivariable analysis (MVA) was performed using Cox Proportional Hazards modeling. The study cohort included 8807 patients. The median age at diagnosis was 32 years (range: 2-85). The majority of patients had stage II disease (n = 6044, 69%), 597 (7%) had extranodal involvement (ENI), and 1925 (22%) had B symptoms. Median follow-up for the entire cohort was 7.2 years (range: 0-22). Five hundred twenty-three (6%) patients developed a second malignancy. Median latency to second malignancy was 5.8 years (range: 0.1-21.5). Of the 523 patients that developed a second malignancy, 228 (44%) occurred in the first 5 years, 139 (27%) were diagnosed between years 5-10, and 156 (30%) beyond 10 years. The 10 year FFSM for patients treated between 1988 and 1999 was 93.0% versus 95.1% for patients treated between 2000 and 2009 (P = 0.04), On MVA, treatment between 2000 and 2009 was associated with a HR for second malignancy of 0.77 (95% Confidence Interval: 0.62-0.96, P = 0.02) compared to the treatment between 1988 and 1999. Our analysis suggests that in patients treated with RT for stage I or II cHL, treatment prior to 2000 had a slightly higher risk of second malignancy compared to treatment in 2000 and later. Further studies, with longer follow-up of patients treated in the modern era are needed to confirm these findings. © 2015 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Central nervous system event in patients with diffuse large B-cell lymphoma in the rituximab era.

PubMed

Tomita, Naoto; Yokoyama, Masahiro; Yamamoto, Wataru; Watanabe, Reina; Shimazu, Yutaka; Masaki, Yasufumi; Tsunoda, Saburo; Hashimoto, Chizuko; Murayama, Kayoko; Yano, Takahiro; Okamoto, Rumiko; Kikuchi, Ako; Tamura, Kazuo; Sato, Kazuya; Sunami, Kazutaka; Shibayama, Hirohiko; Takimoto, Rishu; Ohshima, Rika; Hatta, Yoshihiro; Moriuchi, Yukiyoshi; Kinoshita, Tomohiro; Yamamoto, Masahide; Numata, Ayumi; Ishigatsubo, Yoshiaki; Takeuchi, Kengo

2012-02-01

Central nervous system (CNS) events, including CNS relapse and progression to CNS, are known to be serious complications in the clinical course of patients with lymphoma. This study aimed to evaluate the risk of CNS events in patients with diffuse large B-cell lymphoma in the rituximab era. We performed a retrospective survey of Japanese patients diagnosed with diffuse large B-cell lymphoma who underwent primary therapy with R-CHOP chemoimmunotherapy between September 2003 and December 2006. Patients who had received any prophylactic CNS treatment were excluded. Clinical data from 1221 patients were collected from 47 institutions. The median age of patients was 64 years (range, 15-91 years). We noted 82 CNS events (6.7%) and the cumulative 5-year probability of CNS events was 8.4%. Patients with a CNS event demonstrated significantly worse overall survival (P < 0.001). The 2-year overall survival rate after a CNS event was 27.1%. In a multivariate analysis, involvement of breast (relative risk [RR] 10.5), adrenal gland (RR 4.6) and bone (RR 2.0) were identified as independent risk factors for CNS events. We conclude that patients with these risk factors, in addition to patients with testicular involvement in whom CNS prophylaxis has been already justified, are at high risk for CNS events in the rituximab era. The efficacy and manner of CNS prophylaxis in patients for each involvement site should be evaluated further. © 2011 Japanese Cancer Association.

A 13-year time trend analysis of 3724 small bowel video capsule endoscopies and a forecast model during the financial crisis in Greece.

PubMed

Triantafyllou, Konstantinos; Gkolfakis, Paraskevas; Viazis, Nikos; Tsibouris, Panagiotis; Tsigaridas, Athanasios; Apostolopoulos, Periklis; Anastasiou, John; Hounda, Eleni; Skianis, Ioannis; Katopodi, Konstantina; Ndini, Xhoela; Alexandrakis, George; Karamanolis, Demetrios G

2017-02-01

Since its introduction, small bowel video capsule endoscopy (VCE) use has evolved considerably. Evaluation of the temporal changes of small bowel VCE utilization in three tertiary centers in Greece in Era 1 (2002-2009) and Era 2 (2010-2014) and the development a forecast model for future VCE use during 2015-2017. Data from all small bowel VCE examinations were retrieved and analyzed in terms of the annual number of the performed examinations, their indications and the significance of their findings. Overall, we evaluated 3724 VCE examinations. The number of studies peaked in 2009 (n=595) and then decreased to reach 225 in 2014. Overall, more (53.8 vs. 51.4%) patients with iron-deficiency anemia and obscure gastrointestinal bleeding (IDA/OGIB) and fewer (10.7 vs. 14%) patients with chronic diarrhea were evaluated in Era 2 compared with Era 1 (P=0.046). In Era 2, there were more nondiagnostic examinations (39.5 vs. 29.3%, P<0.001), whereas the rate of cases with relevant findings decreased from 47.8 to 40.9%. According to the time trend analysis, we developed a forecast model with two scenarios: the pessimistic and the optimistic. Validation of the model with 2015 data showed that reality was close to the pessimistic scenario: the number of exams further decreased to 190, studies carried out for IDA/OGIB increased to 67%, and there were more negative than positive exams (40.7 vs. 39.2%). The number of VCE studies carried out after the emergence of the financial crisis decreased significantly and VCE indications were optimized. Our forecast model predicts lower numbers of VCE studies, with IDA/OGIB being the dominant indication. However, the predicted increase of negative exams requires further evaluation.

Impact of archeomagnetic field model data on modern era geomagnetic forecasts

NASA Astrophysics Data System (ADS)

Tangborn, Andrew; Kuang, Weijia

2018-03-01

A series of geomagnetic data assimilation experiments have been carried out to demonstrate the impact of assimilating archeomagnetic data via the CALS3k.4 geomagnetic field model from the period between 10 and 1590 CE. The assimilation continues with the gufm1 model from 1590 to 1990 and CM4 model from 1990 to 2000 as observations, and comparisons between these models and the geomagnetic forecasts are used to determine an optimal maximum degree for the archeomagnetic observations, and to independently estimate errors for these observations. These are compared with an assimilation experiment that uses the uncertainties provided with CALS3k.4. Optimal 20 year forecasts in 1990 are found when the Gauss coefficients up to degree 3 are assimilated. In addition we demonstrate how a forecast and observation bias correction scheme could be used to reduce bias in modern era forecasts. Initial experiments show that this approach can reduce modern era forecast biases by as much as 50%.

Biodiversity, ecosystem functions and services in environmental risk assessment: introduction to the special issue.

PubMed

Schäfer, Ralf B

2012-01-15

This Special Issue focuses on the questions if and how biodiversity, ecosystem functions and resulting services could be incorporated into the Ecological Risk Assessment (ERA). Therefore, three articles provide a framework for the integration of ecosystem services into ERA of soils, sediments and pesticides. Further articles demonstrate ways how stakeholders can be integrated into an ecosystem service-based ERA for soils and describe how the current monitoring could be adapted to new assessment endpoints that are directly linked to ecosystem services. Case studies show that the current ERA may not be protective for biodiversity, ecosystem functions and resulting services and that both pesticides and salinity currently adversely affect ecosystem functions in the field. Moreover, ecological models can be used for prediction of new protection goals and could finally support their implementation into the ERA. Overall, the Special Issue stresses the urgent need to enhance current procedures of ERA if biodiversity, ecosystem functions and resulting services are to be protected. Copyright © 2011 Elsevier B.V. All rights reserved.

[Enhanced recovery after surgery based on medical ethics].

PubMed

Zhao, Qingchuan

2016-03-01

Enhanced recovery after surgery (ERAS), a new model of perioperative management developed in recent years, can shorten hospital stay, reduce medical cost and postoperative discomfort. However, some of these measures under the strategy are negation of the traditional recommendation and many surgeons are concerned about the medical tangle by the complications coming with the ERAS strategy. In this paper, ERAS strategy is evaluated from an ethical standpoint and the assessment factors of medical behavior are introduced based on medical virtues and medical ethnics. It is also analyzed that how to deal with the conflicts between the textbooks and the ERAS strategy, and elaborated that the medical ethics should be observed if the ERAS strategy is implemented. The scientific principles must be followed, the rights and interests of the patients need to be protected, and the informed consent should be guaranteed.

Multivariate Strategies in Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Hansen, Lars Kai

2007-01-01

We discuss aspects of multivariate fMRI modeling, including the statistical evaluation of multivariate models and means for dimensional reduction. In a case study we analyze linear and non-linear dimensional reduction tools in the context of a "mind reading" predictive multivariate fMRI model.

Investigating College and Graduate Students' Multivariable Reasoning in Computational Modeling

ERIC Educational Resources Information Center

Wu, Hsin-Kai; Wu, Pai-Hsing; Zhang, Wen-Xin; Hsu, Ying-Shao

2013-01-01

Drawing upon the literature in computational modeling, multivariable reasoning, and causal attribution, this study aims at characterizing multivariable reasoning practices in computational modeling and revealing the nature of understanding about multivariable causality. We recruited two freshmen, two sophomores, two juniors, two seniors, four…

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

NASA Astrophysics Data System (ADS)

Akperov, Mirseid; Rinke, Annette; Mokhov, Igor I.; Matthes, Heidrun; Semenov, Vladimir A.; Adakudlu, Muralidhar; Cassano, John; Christensen, Jens H.; Dembitskaya, Mariya A.; Dethloff, Klaus; Fettweis, Xavier; Glisan, Justin; Gutjahr, Oliver; Heinemann, Günther; Koenigk, Torben; Koldunov, Nikolay V.; Laprise, René; Mottram, Ruth; Nikiéma, Oumarou; Scinocca, John F.; Sein, Dmitry; Sobolowski, Stefan; Winger, Katja; Zhang, Wenxin

2018-03-01

The ability of state-of-the-art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic-CORDEX initiative. Some models employ large-scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA-Interim, National Centers for Environmental Prediction-Climate Forecast System Reanalysis, National Aeronautics and Space Administration-Modern-Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency-Japanese 55-year reanalysis) in winter and summer for 1981-2010 period. In addition, we compare cyclone statistics between ERA-Interim and the Arctic System Reanalysis reanalyses for 2000-2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large-scale spectral nudging show a better agreement with ERA-Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.

A Multivariate Model for the Study of Parental Acceptance-Rejection and Child Abuse.

ERIC Educational Resources Information Center

Rohner, Ronald P.; Rohner, Evelyn C.

This paper proposes a multivariate strategy for the study of parental acceptance-rejection and child abuse and describes a research study on parental rejection and child abuse which illustrates the advantages of using a multivariate, (rather than a simple-model) approach. The multivariate model is a combination of three simple models used to study…

Evaluation of ERA-Interim precipitation data in complex terrain

NASA Astrophysics Data System (ADS)

Gao, Lu; Bernhardt, Matthias; Schulz, Karsten

2013-04-01

Precipitation controls a large variety of environmental processes, which is an essential input parameter for land surface models e.g. in hydrology, ecology and climatology. However, rain gauge networks provides the necessary information, are commonly sparse in complex terrains, especially in high mountainous regions. Reanalysis products (e.g. ERA-40 and NCEP-NCAR) as surrogate data are increasing applied in the past years. Although they are improving forward, previous studies showed that these products should be objectively evaluated due to their various uncertainties. In this study, we evaluated the precipitation data from ERA-Interim, which is a latest reanalysis product developed by ECMWF. ERA-Interim daily total precipitation are compared with high resolution gridded observation dataset (E-OBS) at 0.25°×0.25° grids for the period 1979-2010 over central Alps (45.5-48°N, 6.25-11.5°E). Wet or dry day is defined using different threshold values (0.5mm, 1mm, 5mm, 10mm and 20mm). The correspondence ratio (CR) is applied for frequency comparison, which is the ratio of days when precipitation occurs in both ERA-Interim and E-OBS dataset. The result shows that ERA-Interim captures precipitation occurrence very well with a range of CR from 0.80 to 0.97 for 0.5mm to 20mm thresholds. However, the bias of intensity increases with rising thresholds. Mean absolute error (MAE) varies between 4.5 mm day-1 and 9.5 mm day-1 in wet days for whole area. In term of mean annual cycle, ERA-Interim almost has the same standard deviation of the interannual variability of daily precipitation with E-OBS, 1.0 mm day-1. Significant wet biases happened in ERA-Interim throughout warm season (May to August) and dry biases in cold season (November to February). The spatial distribution of mean annual daily precipitation shows that ERA-Interim significant underestimates precipitation intensity in high mountains and northern flank of Alpine chain from November to March while pronounced overestimate in the southern flank of Alps. The poor topographical and flow related characteristic representation of ERA-Interim model is possibly responsible for the bias. Particularly, the mountain block effect of moisture is weak captured. The comparison demonstrates that ERA-Interim precipitation intensity needs bias correction for further alpine climate studies, although it reasonably captures precipitation frequency. This critical evaluation not only diagnosed the data quality of ERA-Interim, but also provided the evidence for reanalysis products downscaling and bias correction in complex terrain.

Scanning capacitance microscopy of ErAs nanoparticles embedded in GaAs pn junctions

NASA Astrophysics Data System (ADS)

Park, K. W.; Nair, H. P.; Crook, A. M.; Bank, S. R.; Yu, E. T.

2011-09-01

Scanning capacitance microscopy is used to characterize the electronic properties of ErAs nanoparticles embedded in GaAs pn junctions grown by molecular beam epitaxy. Voltage-dependent capacitance images reveal localized variations in subsurface electronic structure near buried ErAs nanoparticles at lateral length scales of 20-30 nm. Numerical modeling indicates that these variations arise from inhomogeneities in charge modulation due to Fermi level pinning behavior associated with the embedded ErAs nanoparticles. Statistical analysis of image data yields an average particle radius of 6-8 nm—well below the direct resolution limit in scanning capacitance microscopy but discernible via analysis of patterns in nanoscale capacitance images.

Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data.

PubMed

Zhou, Hua; Blangero, John; Dyer, Thomas D; Chan, Kei-Hang K; Lange, Kenneth; Sobel, Eric M

2017-04-01

Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even datasets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper, we reexamine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (six CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1,388 individuals in 124 pedigrees) takes less than 2 min and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 min and 1.5 GB of memory. The algorithm is implemented as the Ped-GWAS Analysis (Option 29) in the Mendel statistical genetics package, which is freely available for Macintosh, Linux, and Windows platforms from http://genetics.ucla.edu/software/mendel. © 2016 WILEY PERIODICALS, INC.

Varicella-zoster virus seroprevalence in children and adolescents in the pre-varicella vaccine era, Germany.

PubMed

Wiese-Posselt, Miriam; Siedler, Anette; Mankertz, Annette; Sauerbrei, Andreas; Hengel, Hartmut; Wichmann, Ole; Poethko-Müller, Christina

2017-05-19

In 2004, universal childhood varicella vaccination was introduced in Germany. We aimed to determine the age-specific prevalence of anti-varicella zoster virus (VZV) IgG-antibodies among children in the pre-varicella vaccine era in Germany, to identify factors associated with VZV seropositivity, and to assess the suitability of a commercially available ELISA for VZV seroepidemiological studies by comparing it with an in-house fluorescent antibody to membrane antigen test (FAMA) as the gold standard. Serum samples of 13,433 children and adolescents aged 1-17 years included in the population-based German Health Interview and Examination Survey for Children and Adolescents (KiGGS; conducted 2003-2006) were tested for anti-VZV IgG by ELISA. All samples with equivocal ELISA results and a random selection of ELISA-negative and -positive samples were tested by FAMA. Statistical analyses were conducted using a weighting factor adjusting the study population to the total population in Germany. Seroprevalences were calculated as percentages (%) with a 95% confidence interval (CI). Odds ratios (OR) were computed by multivariate logistic regression to determine the association between socio-demographic factors and VZV seropositivity. The VZV seropositivity rate was 80.3% (95% CI: 79.3-81.3) in varicella-unvaccinated children and adolescents. VZV seropositivity rates differed significantly between age groups up to age 6 years, but not by gender. Of 118 retested serum samples with an equivocal ELISA result, 45.8% were FAMA-positive. The proportion of samples tested as false-negative in by ELISA varied by age group: 2.6% in children aged 1-6 and 9% in children aged 7-17 years. Multivariate analyses showed that age, having older siblings, and early daycare start were associated with seropositivity in preschoolers; migration background reduced the chance of VZV seropositivity in schoolchildren (OR: 0.65; 0.43-0.99) and adolescents (OR: 0.62; 0.4-0.97). In the pre-varicella vaccine era, most children in Germany contracted varicella by age six. Schoolchildren with a migration background and children without siblings have an increased risk of being VZV seronegative and should be targeted for catch-up vaccination, if they have no history of chickenpox. ELISAs are suitable for use in population-level serosurveys on VZV, but samples with equivocal ELISA results should be retested by FAMA.

Impact of postmastectomy radiotherapy in T3N0 invasive carcinoma of the breast: a Surveillance, Epidemiology, and End Results database analysis.

PubMed

McCammon, Robert; Finlayson, Christina; Schwer, Amanda; Rabinovitch, Rachel

2008-08-15

Randomized trials provide evidence for improved outcomes with postmastectomy radiotherapy (PMRT) in high-risk patients. It has been suggested that patients with T3N0 breast cancer represent a favorable subgroup for which PMRT renders little benefit. In the current study, the authors used a United States population database to evaluate PMRT in this subgroup. The cause-specific survival (CSS) and overall survival (OS) of women with T3N0M0 breast cancer in the Surveillance, Epidemiology, and End Results database after mastectomy and axillary staging from 1988 to 2002 were analyzed. Univariate analysis was performed to relate CSS with PMRT (yes vs no), tumor size (< or =7 cm vs >7 cm), grade (1 vs 2 or 3), patient age (< or =50 years vs >50 years), the number of lymph nodes dissected (< or =13 vs >13), and the era treated (1988-1997 vs 1998-2002). Multivariate analyses for CSS and OS were also performed. In total, 1865 women met the analysis criteria for OS; CSS data were available for 98.8% of those women. Of the women who were diagnosed during the era from 1988 to 1997, 22% received PMRT, and that rate increased to 41% during the era from 1998 to 2002. The actuarial 10-year CSS for those who received PMRT versus those who did not receive PMRT was 81.6% versus 79.8%, respectively (P = .38). PMRT was not associated with a CSS benefit in any subgroup, a finding that persisted in multivariate analyses. Women who received PMRT had an increased 10-year OS rate (70.7% vs 58.4%; P < .001) that was confined to women aged >50 years in a subgroup analysis. This retrospective, population-based analysis demonstrated no increase in CSS with PMRT for women with T3N0 breast cancer, lending further support to the hypothesis that T3N0 disease postmastectomy represents a favorable subset of locally advanced breast cancer. The increased OS associated with PMRT in the absence of improved CSS likely reflects patient selection in this nonrandomized dataset. Prospective evaluation of PMRT in this population subset is warranted. 2008 American Cancer Society

Extensions to Multivariate Space Time Mixture Modeling of Small Area Cancer Data.

PubMed

Carroll, Rachel; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Aregay, Mehreteab; Watjou, Kevin

2017-05-09

Oral cavity and pharynx cancer, even when considered together, is a fairly rare disease. Implementation of multivariate modeling with lung and bronchus cancer, as well as melanoma cancer of the skin, could lead to better inference for oral cavity and pharynx cancer. The multivariate structure of these models is accomplished via the use of shared random effects, as well as other multivariate prior distributions. The results in this paper indicate that care should be taken when executing these types of models, and that multivariate mixture models may not always be the ideal option, depending on the data of interest.

Age of air and heating rates: comparison of ERA-40 with ERA-Interim

NASA Astrophysics Data System (ADS)

Legras, B.; Fueglistaler, S.

2009-04-01

The age of air in the stratosphere is often used as a test for the good representation of the Brewer-Dobson circulation by atmospheric models. This is a critical requirement to modelize the distribution of long-lived species in chemical models. It is often advocated that using heating rates for vertical transport in the stratosphere performs better that standard analysed velocities from weather centers. This work is based on an extensive comparison of the age of air using 5 years of heating rates from the ERA-40 reanalysis and from the new ERA-interim reanalysis built with 4D-Var assimilation. The ERA-40 exhibits both too young ages with analyzed velocities and too old ages with heating rates. The reason for too young ages is spurious transport associated with too noisy wind, as a result of 3D-Var assimilation. Heating rates provide a much less noisy meridional circulation and preserve transport barriers and polar vortex confinement. However, excessive cooling near 30 hPa in the tropics blocks the ascending motion within the tropical pipe over extended periods of time inducing very old ages. This effect is usually corrected by an empirical correction which can exceed in some regions the calculated heating rate in magnitude, with opposite sign. We relate this correction to the assimilation temperature increment that is required to compensate the bias of the model, notably the excessive negative heat transport due to the noisy vertical velocities and the lack of mass conservation in the isentropic frame. The new ERA-interim exhibits much reduced noise in the vertical velocity and is ten times less diffusive than the ERA-40 in the tropics. Age of air is then found to be slightly older than given by the observations. The biases in the heating rate have also been considerably reduced with respect to ERA-40 and the assimilation increment is now only a fraction of the heating rate. The age of air is in fairly good aggreement with the observations at 20 km and higher altitudes. Further improvements combining heating rates and a filtered version of the assimilation increment for vertical transport in the stratosphere are discussed. We study the effect of restoring the mass conservation by recalculating a mass divergence balancing the modified heating rates. The new velocity dataset generated in isentropic coordinates is then used to study the interranual variability of the Brewer-Dobson and of heating rate, in relation with the QBO cycle.

Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran.

PubMed

Malekmohammadi, Bahram; Tayebzadeh Moghadam, Negar

2018-04-13

Environmental risk assessment (ERA) is a commonly used, effective tool applied to reduce adverse effects of environmental risk factors. In this study, ERA was investigated using the Bayesian network (BN) model based on a hierarchical structure of variables in an influence diagram (ID). ID facilitated ranking of the different alternatives under uncertainty that were then used to evaluate comparisons of the different risk factors. BN was used to present a new model for ERA applicable to complicated development projects such as dam construction. The methodology was applied to the Gabric Dam, in southern Iran. The main environmental risk factors in the region, presented by the Gabric Dam, were identified based on the Delphi technique and specific features of the study area. These included the following: flood, water pollution, earthquake, changes in land use, erosion and sedimentation, effects on the population, and ecosensitivity. These risk factors were then categorized based on results from the output decision node of the BN, including expected utility values for risk factors in the decision node. ERA was performed for the Gabric Dam using the analytical hierarchy process (AHP) method to compare results of BN modeling with those of conventional methods. Results determined that a BN-based hierarchical structure to ERA present acceptable and reasonable risk assessment prioritization in proposing suitable solutions to reduce environmental risks and can be used as a powerful decision support system for evaluating environmental risks.

Relevance of the immunoglobulin VH somatic mutation status in patients with chronic lymphocytic leukemia treated with fludarabine, cyclophosphamide, and rituximab (FCR) or related chemoimmunotherapy regimens.

PubMed

Lin, Katherine I; Tam, Constantine S; Keating, Michael J; Wierda, William G; O'Brien, Susan; Lerner, Susan; Coombes, Kevin R; Schlette, Ellen; Ferrajoli, Alessandra; Barron, Lynn L; Kipps, Thomas J; Rassenti, Laura; Faderl, Stefan; Kantarjian, Hagop; Abruzzo, Lynne V

2009-04-02

Although immunoglobulin V(H) mutation status (IgV(H) MS) is prognostic in patients with chronic lymphocytic leukemia (CLL) who are treated with alkylating agents or single-agent fludarabine, its significance in the era of chemoimmunotherapy is not known. We determined the IgV(H) somatic mutation status (MS) in 177 patients enrolled in a phase 2 study of fludarabine, cyclophosphamide, and rituximab (FCR) and in 127 patients treated with subsequent chemoimmunotherapy protocols. IgV(H) MS did not impact significantly on the complete remission (CR) rate of patients receiving FCR or related regimens. However, CR duration was significantly shorter in patients with CLL that used unmutated IgV(H) than those whose CLL used mutated IgV(H) (TTP 47% vs 82% at 6 years, P < .001). In a multivariate model considering all baseline characteristics, IgV(H) MS emerged as the only determinant of remission duration (hazard ratio 3.8, P < .001). Our results suggest that postremission interventions should be targeted toward patients with unmutated IgV(H) status.

Downscaling Reanalysis over Continental Africa with a Regional Model: NCEP Versus ERA Interim Forcing

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.; Fulakeza, Matthew B.

2013-01-01

Five annual climate cycles (1998-2002) are simulated for continental Africa and adjacent oceans by a regional atmospheric model (RM3). RM3 horizontal grid spacing is 0.44deg at 28 vertical levels. Each of 2 simulation ensembles is driven by lateral boundary conditions from each of 2 alternative reanalysis data sets. One simulation downs cales National Center for Environmental Prediction reanalysis 2 (NCPR2) and the other the European Centre for Medium Range Weather Forecasts Interim reanalysis (ERA-I). NCPR2 data are archived at 2.5deg grid spacing, while a recent version of ERA-I provides data at 0.75deg spacing. ERA-I-forced simulations are recomrp. ended by the Coordinated Regional Downscaling Experiment (CORDEX). Comparisons of the 2 sets of simulations with each other and with observational evidence assess the relative performance of each downscaling system. A third simulation also uses ERA-I forcing, but degraded to the same horizontal resolution as NCPR2. RM3-simulated pentad and monthly mean precipitation data are compared to Tropical Rainfall Measuring Mission (TRMM) data, gridded at 0.5deg, and RM3-simulated circulation is compared to both reanalyses. Results suggest that each downscaling system provides advantages and disadvantages relative to the other. The RM3/NCPR2 achieves a more realistic northward advance of summer monsoon rains over West Africa, but RM3/ERA-I creates the more realistic monsoon circulation. Both systems recreate some features of JulySeptember 1999 minus 2002 precipitation differences. Degrading the resolution of ERA-I driving data unrealistically slows the monsoon circulation and considerably diminishes summer rainfall rates over West Africa. The high resolution of ERA-I data, therefore, contributes to the quality of the downscaling, but NCPR2laterai boundary conditions nevertheless produce better simulations of some features.

A Multi-Component Strategy to Decrease Wound Complications after Open Infra-Inguinal Re-Vascularization.

PubMed

Zamani, Nader; Sharath, Sherene E; Vo, Elaine; Awad, Samir S; Kougias, Panos; Barshes, Neal R

2018-01-01

Wound complications remain a significant source of morbidity for patients undergoing open infra-inguinal re-vascularization. The purpose of this study was to determine the impact of several infection-control strategies on post-operative wound complications after open infra-inguinal re-vascularization. A retrospective cohort study was conducted among all patients who underwent an open infra-inguinal re-vascularization procedure before and after 2014. Since 2014, we have implemented strategies to reduce post-operative wound complications, including: (1) Decreasing the use of incisional skin staples, (2) increasing the use of negative pressure wound therapy (NPWT) dressings, and (3) implementing an outpatient elective decontamination protocol for methicillin-resistant Staphylococcus aureus. "Pre-era" is defined as the period between January 2012 and December 2013, before the implementation of infection control strategies; "Post-era" is between January 2015 and August 2016, after implementation. The primary outcome of interest is 30-day wound complications (infection or dehiscence). Multi-variable logistic regression analysis was used to identify significant predictors of wound-related complications between the two cohorts. Propensity score adjustment controlled for baseline patient characteristics, peri-operative variables, and surgeon experience. A total of 338 open infra-inguinal procedures were performed: 175 in the pre-era and 163 in the post-era. Chlorhexidine skin preparation was used in the majority (321 [95%]) of cases. Comparing the periods, the post-era is characterized by a significant decrease in the use of groin staples (118 [67%] vs. 51 [31%], p < 0.001), and an increased application of NPWT dressings (6 [4%] vs. 66 [43%], p < 0.001). Thirty-five (37%) outpatient elective cases received the pre-operative decontamination protocol in the post-era. Compared with the pre-era, there was a decrease in the 30-day rate of wound complications (68 [39%] to 42 [26%], p = 0.011), and infection-related re-admissions (31 [17.7%] to 21 [12.9%], p = 0.220). When adjusting for patient characteristics, operative variables, and surgeon experience, post-era had significantly lower wound complications (odds ratio [OR] 0.33, p = 0.002) and re-operations (OR 0.16, p = 0.007). Among outpatient elective cases, the decontamination protocol was also independently associated with these two outcomes (wound complications: OR 0.05, p = 0.006; re-operations: 0.06, p = 0.002). The use of groin staples was an independent predictor of deep groin infections (OR 248, p < 0.001) and re-operations (OR 8.16, p = 0.032). Wound complications after open infra-inguinal re-vascularization have decreased significantly after the implementation of several infection-control strategies. Findings suggest that skin staples should be avoided in groin wounds, and anti-staphylococcal decontamination protocols decrease wound complications and prevent re-operations.

Parameterisation of Orographic Cloud Dynamics in a GCM

DTIC Science & Technology

2007-01-01

makes use of both satellite observations of a case study, and a simulation in which the Unified Model is nudged to- wards ERA-40 assimilated winds...this parameterisation makes use of both satellite observations of a case study, and a simulation in which the Unified Model is nudged towards ERA-40...by ANSI Std Z39-18 et al. (1999), predicted the temperature perturbations in the lower stratosphere which can influence polar stratospheric clouds

The risk of hepatocellular carcinoma among individuals with acquired immunodeficiency syndrome in the United States.

PubMed

Sahasrabuddhe, Vikrant V; Shiels, Meredith S; McGlynn, Katherine A; Engels, Eric A

2012-12-15

Hepatocellular carcinoma (HCC) is a concern among individuals with human immunodeficiency virus (HIV) infection and acquired immunodeficiency syndrome (AIDS). The authors analyzed population-based registry linkage data from the US HIV/AIDS Cancer Match Study (1980-2009) to examine the risk and trends of HCC among individuals with AIDS. Standardized incidence ratios (SIRs) were used to measure HCC risk relative to the general population, and Poisson regression was used to calculate incidence rate ratios (RR) comparing incidence among individuals with AIDS. People with AIDS were categorized according to their HIV risk group into high and low hepatitis C virus (HCV) prevalence groups based on their HIV transmission risk category. Among 615,150 individuals with AIDS, HCC risk was elevated almost 4 times compared with the risk in the general population (N = 366; SIR, 3.8; 95% confidence interval, 3.5-4.3). Although HCC incidence increased steadily across calendar periods (P(trend) < .0001; adjusted for sex and age), the excess risk in individuals with AIDS compared with the general population remained somewhat constant (SIRs range, 3.5-3.9) between the monotherapy/dual therapy era (1990-1995) and the recent highly active antiretroviral therapy era (2001-2009). In a multivariate model adjusting for sex, race/ethnicity, and attained calendar period, HCC incidence increased with advancing age (P(trend) < .0001) and was associated with HIV risk groups with a known higher prevalence of HCV (adjusted RR, 2.2; 95% confidence interval, 1.8-2.8). HCC incidence in individuals with AIDS has increased over time despite improved HIV treatment regimens, likely reflecting prolonged survival with chronic liver disease. The high incidence in older adults suggests that this cancer will increase in importance with aging of the HIV-infected population. Published 2012 American Cancer Society.

Studying plant-pathogen interactions in the genomics era: beyond molecular Koch’s postulates to systems biology

USDA-ARS?s Scientific Manuscript database

Molecular factors enabling microbial pathogens to cause plant diseases have been sought with increasing efficacy over three research eras, which successively introduced the tools of disease physiology, single-gene molecular genetics, and genomics. From this work emerged a unified model of the intera...

The Educational Challenge of Korea in the Global Era: The Role of Family, School, and Government.

ERIC Educational Resources Information Center

Park, Young-Shin; Kim, Uichol

1999-01-01

Investigates the psychological, social, and cultural factors essential for the educational achievements in Korea. Outlines a cross-cultural model and three major factors influencing adolescents' educational achievement. Reviews four empirical studies on academic achievement. Discusses challenges for Korea in the global era. (CMK)

Selective use of preoperative endoscopic retrograde cholangiopancreatography in the era of laparoscopic cholecystectomy.

PubMed

Nataly, Yogesh; Merrie, Arend E; Stewart, Ian D

2002-03-01

The use of endoscopic retrograde cholangiopancreatography (ERCP) in the management of suspected common bile duct (CBD) stones prior to laparoscopic cholecystectomy is common. The associated morbidity can be significant. The present study determines significant predictors of CBD stones and improves the selection of patients for preoperative ERCP. All preoperative ERCP for suspected CBD stones in the year 1998 were studied retrospectively. Univariate and multivariate analyses of a number of clinical, biochemical and radiological variables were carried out to determine the best predictors of CBD stones. A total of 112 patients had successful preoperative ERCP. Sixty-one per cent of these were negative for stones and the morbidity was 9%. Univariate analysis revealed the following variables as predictors: cholangitis (P = 0.006), abnormal serum bilirubin > or = 3 days (P = 0.002), serum alkaline phosphatase > or = 130 U/L (P = 0.002), deranged liver function tests (P = < 0.001) and CBD diameter > or = 8 mm (P = 0.009) with positive predictive values of 80%, 68%, 49%, 38% and 52%, respectively. Multivariate analysis revealed the model with the best ability to discriminate for CBD stones (P = 0.0005) was cholangitis, abnormal serum bilirubin for > or = 3 days and CBD diameter > or = 8 mm. The best predictors from this study had a sensitivity of 80% and a specificity of 27%. The predictors of CBD stones are imprecise. Until laparoscopic exploration of CBD becomes widely available, ERCP prior to cholecystectomy will remain popular. The use of stricter selection criteria can reduce the number of negative preoperative ERCP.

Outcomes following Kidney transplantation in IgA nephropathy: a UNOS/OPTN analysis.

PubMed

Kadiyala, Aditya; Mathew, Anna T; Sachdeva, Mala; Sison, Cristina P; Shah, Hitesh H; Fishbane, Steven; Jhaveri, Kenar D

2015-10-01

This study updates assessment of post-transplant outcomes in IgAN patients in the modern era of immunosuppression. Using UNOS/OPTN data, patients ≥18 yr of age with first kidney transplant (1/1/1999 to 12/31/2008) were analyzed. Multivariable Cox regression models and propensity score-based matching techniques were used to estimate hazard ratios (HRs) for death-censored allograft survival (DCGS) and patient survival in IgAN compared to non-IgAN. Results of multivariable regression were stratified by donor type (living vs. deceased). A total of 107, 747 recipients were included (4589 with IgAN and 103 158 with non-IgAN). Adjusted HR for DCGS showed no significant difference between IgAN and non-IgAN. IgAN had higher patient survival compared to non-IgAN (HR 0.54, 95% CI 0.47-0.62, p < 0.0001 for deceased donors; HR 0.42, 95% CI 0.33-0.54, p < 0.0001 for living donors). Propensity score-matched analysis was similar, with no significant difference in DCGS between matched groups and higher patient survival in IgAN patients compared to non-IgAN group (HR 0.54, 95% CI 0.47, 0.63; p-value <0.0001). IgAN patients with first kidney transplant have superior patient survival and similar graft survival compared to non-IgAN recipients. Results can be used in prognostication and informed decision-making about kidney transplantation in patients with IgAN. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

Big genomics and clinical data analytics strategies for precision cancer prognosis.

PubMed

Ow, Ghim Siong; Kuznetsov, Vladimir A

2016-11-07

The field of personalized and precise medicine in the era of big data analytics is growing rapidly. Previously, we proposed our model of patient classification termed Prognostic Signature Vector Matching (PSVM) and identified a 37 variable signature comprising 36 let-7b associated prognostic significant mRNAs and the age risk factor that stratified large high-grade serous ovarian cancer patient cohorts into three survival-significant risk groups. Here, we investigated the predictive performance of PSVM via optimization of the prognostic variable weights, which represent the relative importance of one prognostic variable over the others. In addition, we compared several multivariate prognostic models based on PSVM with classical machine learning techniques such as K-nearest-neighbor, support vector machine, random forest, neural networks and logistic regression. Our results revealed that negative log-rank p-values provides more robust weight values as opposed to the use of other quantities such as hazard ratios, fold change, or a combination of those factors. PSVM, together with the classical machine learning classifiers were combined in an ensemble (multi-test) voting system, which collectively provides a more precise and reproducible patient stratification. The use of the multi-test system approach, rather than the search for the ideal classification/prediction method, might help to address limitations of the individual classification algorithm in specific situation.

Dissecting DNA repair in adult high grade gliomas for patient stratification in the post-genomic era

PubMed Central

Perry, Christina; Agarwal, Devika; Abdel-Fatah, Tarek M.A.; Lourdusamy, Anbarasu; Grundy, Richard; Auer, Dorothee T.; Walker, David; Lakhani, Ravi; Scott, Ian S.; Chan, Stephen; Ball, Graham; Madhusudan, Srinivasan

2014-01-01

Deregulation of multiple DNA repair pathways may contribute to aggressive biology and therapy resistance in gliomas. We evaluated transcript levels of 157 genes involved in DNA repair in an adult glioblastoma Test set (n=191) and validated in ‘The Cancer Genome Atlas’ (TCGA) cohort (n=508). A DNA repair prognostic index model was generated. Artificial neural network analysis (ANN) was conducted to investigate global gene interactions. Protein expression by immunohistochemistry was conducted in 61 tumours. A fourteen DNA repair gene expression panel was associated with poor survival in Test and TCGA cohorts. A Cox multivariate model revealed APE1, NBN, PMS2, MGMT and PTEN as independently associated with poor prognosis. A DNA repair prognostic index incorporating APE1, NBN, PMS2, MGMT and PTEN stratified patients in to three prognostic sub-groups with worsening survival. APE1, NBN, PMS2, MGMT and PTEN also have predictive significance in patients who received chemotherapy and/or radiotherapy. ANN analysis of APE1, NBN, PMS2, MGMT and PTEN revealed interactions with genes involved in transcription, hypoxia and metabolic regulation. At the protein level, low APE1 and low PTEN remain associated with poor prognosis. In conclusion, multiple DNA repair pathways operate to influence biology and clinical outcomes in adult high grade gliomas. PMID:25026297

Massive Halos in Millennium Gas Simulations: Multivariate Scaling Relations

NASA Astrophysics Data System (ADS)

Stanek, R.; Rasia, E.; Evrard, A. E.; Pearce, F.; Gazzola, L.

2010-06-01

The joint likelihood of observable cluster signals reflects the astrophysical evolution of the coupled baryonic and dark matter components in massive halos, and its knowledge will enhance cosmological parameter constraints in the coming era of large, multiwavelength cluster surveys. We present a computational study of intrinsic covariance in cluster properties using halo populations derived from Millennium Gas Simulations (MGS). The MGS are re-simulations of the original 500 h -1 Mpc Millennium Simulation performed with gas dynamics under two different physical treatments: shock heating driven by gravity only (GO) and a second treatment with cooling and preheating (PH). We examine relationships among structural properties and observable X-ray and Sunyaev-Zel'dovich (SZ) signals for samples of thousands of halos with M 200 >= 5 × 1013 h -1 M sun and z < 2. While the X-ray scaling behavior of PH model halos at low redshift offers a good match to local clusters, the model exhibits non-standard features testable with larger surveys, including weakly running slopes in hot gas observable-mass relations and ~10% departures from self-similar redshift evolution for 1014 h -1 M sun halos at redshift z ~ 1. We find that the form of the joint likelihood of signal pairs is generally well described by a multivariate, log-normal distribution, especially in the PH case which exhibits less halo substructure than the GO model. At fixed mass and epoch, joint deviations of signal pairs display mainly positive correlations, especially the thermal SZ effect paired with either hot gas fraction (r = 0.88/0.69 for PH/GO at z = 0) or X-ray temperature (r = 0.62/0.83). The levels of variance in X-ray luminosity, temperature, and gas mass fraction are sensitive to the physical treatment, but offsetting shifts in the latter two measures maintain a fixed 12% scatter in the integrated SZ signal under both gas treatments. We discuss halo mass selection by signal pairs, and find a minimum mass scatter of 4% in the PH model by combining thermal SZ and gas fraction measurements.

A 60-year reconstructed high-resolution local meteorological data set in Central Sahel (1950-2009): evaluation, analysis and application to land surface modelling

NASA Astrophysics Data System (ADS)

Leauthaud, Crystele; Cappelaere, Bernard; Demarty, Jérôme; Guichard, Françoise; Velluet, Cécile; Kergoat, Laurent; Vischel, Théo; Grippa, Manuela; Mouhaimouni, Mohammed; Bouzou Moussa, Ibrahim; Mainassara, Ibrahim; Sultan, Benjamin

2017-04-01

The Sahel has experienced strong climate variability in the past decades. Understanding its implications for natural and cultivated ecosystems is pivotal in a context of high population growth and mainly agriculture-based livelihoods. However, efforts to model processes at the land-atmosphere interface are hindered, particularly when the multi-decadal timescale is targeted, as climatic data are scarce, largely incomplete and often unreliable. This study presents the generation of a long-term, high-temporal resolution, multivariate local climatic data set for Niamey, Central Sahel. The continuous series spans the period 1950-2009 at a 30-min timescale and includes ground station-based meteorological variables (precipitation, air temperature, relative and specific humidity, air pressure, wind speed, downwelling long- and short-wave radiation) as well as process-modelled surface fluxes (upwelling long- and short-wave radiation,latent, sensible and soil heat fluxes and surface temperature). A combination of complementary techniques (linear/spline regressions, a multivariate analogue method, artificial neural networks and recursive gap filling) was used to reconstruct missing meteorological data. The complete surface energy budget was then obtained for two dominant land cover types, fallow bush and millet, by applying the meteorological forcing data set to a finely field-calibrated land surface model. Uncertainty in reconstructed data was expressed by means of a stochastic ensemble of plausible historical time series. Climatological statistics were computed at sub-daily to decadal timescales and compared with local, regional and global data sets such as CRU and ERA-Interim. The reconstructed precipitation statistics, ˜1°C increase in mean annual temperature from 1950 to 2009, and mean diurnal and annual cycles for all variables were in good agreement with previous studies. The new data set, denoted NAD (Niamey Airport-derived set) and publicly available, can be used to investigate the water and energy cycles in Central Sahel, while the methodology can be applied to reconstruct series at other stations. The study has been published in Int. J. Climatol. (2016), DOI: 10.1002/joc.4874

Selection criteria for internal medicine residency applicants and professionalism ratings during internship.

PubMed

Cullen, Michael W; Reed, Darcy A; Halvorsen, Andrew J; Wittich, Christopher M; Kreuziger, Lisa M Baumann; Keddis, Mira T; McDonald, Furman S; Beckman, Thomas J

2011-03-01

To determine whether standardized admissions data in residents' Electronic Residency Application Service (ERAS) submissions were associated with multisource assessments of professionalism during internship. ERAS applications for all internal medicine interns (N=191) at Mayo Clinic entering training between July 1, 2005, and July 1, 2008, were reviewed by 6 raters. Extracted data included United States Medical Licensing Examination scores, medicine clerkship grades, class rank, Alpha Omega Alpha membership, advanced degrees, awards, volunteer activities, research experiences, first author publications, career choice, and red flags in performance evaluations. Medical school reputation was quantified using U.S. News & World Report rankings. Strength of comparative statements in recommendation letters (0 = no comparative statement, 1 = equal to peers, 2 = top 20%, 3 = top 10% or "best") were also recorded. Validated multisource professionalism scores (5-point scales) were obtained for each intern. Associations between application variables and professionalism scores were examined using linear regression. The mean ± SD (minimum-maximum) professionalism score was 4.09 ± 0.31 (2.13-4.56). In multivariate analysis, professionalism scores were positively associated with mean strength of comparative statements in recommendation letters (β = 0.13; P = .002). No other associations between ERAS application variables and professionalism scores were found. Comparative statements in recommendation letters for internal medicine residency applicants were associated with professionalism scores during internship. Other variables traditionally examined when selecting residents were not associated with professionalism. These findings suggest that faculty physicians' direct observations, as reflected in letters of recommendation, are useful indicators of what constitutes a best student. Residency selection committees should scrutinize applicants' letters for strongly favorable comparative statements.

A comparison of daily evaporation downscaled using WRFDA model and GLEAM dataset over the Iberian Peninsula.

NASA Astrophysics Data System (ADS)

José González-Rojí, Santos; Sáenz, Jon; Ibarra-Berastegi, Gabriel

2017-04-01

GLEAM dataset was presented a few years ago and since that moment, it has just been used for validation of evaporation in a few places of the world (Australia and Africa). The Iberian Peninsula is composed of different soil types and it is affected by different weather regimes, with different climate regions. It is this feature which makes it a very interesting zone for the study of the meteorological cycle, including evaporation. For that purpose, a numerical downscaling exercise over the Iberian Peninsula was run nesting the WRF model inside ERA Interim. Two model configurations were tested in two experiments spanning the period 2010-2014 after a one-year spin-up (2009). In the first experiment (N), boundary conditions drive the model. The second experiment (D) is configured the same way as the N case, but 3DVAR data assimilation is run every six hours (00Z, 06Z, 12Z and 18Z) using observations obtained from the PREPBUFR dataset. For both N and D runs and ERA Interim, the evaporation of the model runs was compared to GLEAM v3.0b and v3.0c datasets over the Iberian Peninsula, both at the daily and monthly time scales. GLEAM v3.0a was not used for validation as it uses for forcing radiation and air temperature data from ERA Interim. Results show that the experiment with data assimilation (D) improve the results obtained for N experiment. Moreover, correlations values are comparable to the ones obtained with ERA Interim. However, some negative correlation values are observed at Portuguese and Mediterranean coasts for both WRF runs. All of these problematic points are considered as urban sites by the NOAH land surface model. Because of that, the model is not able to simulate a correct evaporation value. Even with these discrepancies, better results than for ERA Interim are observed for seasonal Biases and daily RMSEs over Iberian Peninsula, obtaining the best values inland. Minimal differences are observed for the two GLEAM datasets selected.

Detecting spatial regimes in ecosystems

USGS Publications Warehouse

Sundstrom, Shana M.; Eason, Tarsha; Nelson, R. John; Angeler, David G.; Barichievy, Chris; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Gunderson, Lance; Knutson, Melinda; Nash, Kirsty L.; Spanbauer, Trisha; Stow, Craig A.; Allen, Craig R.

2017-01-01

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

Multivariate assessment of subjective and objective measures of social and family satisfaction in Veterans with history of traumatic brain injury.

PubMed

Orff, Henry J; Hays, Chelsea C; Twamley, Elizabeth W

2016-01-01

Approximately 20% of current-era Veterans have sustained a traumatic brain injury (TBI), which can result in persistent postconcussive symptoms. These symptoms may disrupt family and social functioning. We explored psychiatric, postconcussive, and cognitive factors as correlates of objective functioning and subjective satisfaction in family and social relationships. At entry into a supported employment study, 50 unemployed Veterans with a history of mild to moderate TBI and current cognitive impairment were administered baseline assessments. Multivariate stepwise regressions determined that higher levels of depressive symptomatology were strongly associated with less frequent social contact, as well as lower subjective satisfaction with family and social relationships. Worse verbal fluency predicted less frequent social contact, whereas worse processing speed and switching predicted higher levels of subjective satisfaction with family relationships. The pattern of results remained similar when examining those Veterans with only mild TBI. Depressive symptoms and cognitive functioning may impact Veterans' social contact and satisfaction with family and social relationships. Evidence-based interventions addressing depression and cognition may therefore aid in improving community reintegration and satisfaction with social and family relationships.

Entering AN ERA of Synthesis of Modeling

NASA Astrophysics Data System (ADS)

Guerin, Stephen

First, I believe we're entering an era of synthesis of modeling. Over the past 20 years, we've seen the proliferation of many isolated complex systems models. I think we now need tools for researchers, policy makers and the public to share models. Sharing could happen by stacking different layers of spatial agent-based models in geographic information systems and projecting interactive visualization out onto shared surfaces. Further, we need to make model authoring tools much more accessible to the point where motivated policy makers can author on their own. With the increased ability to author and share models, I believe this will allow us to scale our research to understand and manage the many interacting systems that make up our complex world...

A multivariate time series approach to modeling and forecasting demand in the emergency department.

PubMed

Jones, Spencer S; Evans, R Scott; Allen, Todd L; Thomas, Alun; Haug, Peter J; Welch, Shari J; Snow, Gregory L

2009-02-01

The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

Comparison of Multidimensional Item Response Models: Multivariate Normal Ability Distributions versus Multivariate Polytomous Ability Distributions. Research Report. ETS RR-08-45

ERIC Educational Resources Information Center

Haberman, Shelby J.; von Davier, Matthias; Lee, Yi-Hsuan

2008-01-01

Multidimensional item response models can be based on multivariate normal ability distributions or on multivariate polytomous ability distributions. For the case of simple structure in which each item corresponds to a unique dimension of the ability vector, some applications of the two-parameter logistic model to empirical data are employed to…

An analysis of the factors influencing the residual refractive astigmatism after cataract surgery with toric intraocular lenses.

PubMed

Savini, Giacomo; Næser, Kristian

2015-01-13

To investigate the influence of posterior corneal astigmatism, surgically-induced corneal astigmatism (SICA), intraocular lens (IOL) orientation, and effective lens position on the refractive outcome of toric IOLs. Five models were prospectively investigated. Keratometric astigmatism and an intended SICA of 0.2 diopters (D) were entered into model 1. Total corneal astigmatism, measured by a rotating Scheimpflug camera, was used instead of keratometric astigmatism in model 2. The mean postoperative SICA, the actual postoperative IOL orientation, and the influence of the effective lens position were added, respectively, into models 3, 4, and 5. Astigmatic data were vectorially described by meridional and torsional powers. A set of equations was developed to describe the error in refractive astigmatism (ERA) as the difference between the postoperative refractive astigmatism and the target refractive astigmatism. We enrolled 40 consecutive eyes. In model 1, ERA calculations revealed significant cylinder overcorrection in with-the-rule (WTR) eyes (meridional power = -0.59 ± 0.34 D, P < 0.0001) and undercorrection in against-the-rule (ATR) eyes (0.32 ± 0.42 D, P = 0.01). When total corneal astigmatism was used instead of keratometric astigmatism (model 2), the ERA meridional power decreased in WTR (-0.13 ± 0.42 D) and ATR (0.07 ± 0.59 D) eyes, both values being not statistically significant. Models 3 to 5 did not lead to significant improvement. Posterior corneal astigmatism exerts the highest influence on the ERA after toric IOL implantation. Basing calculations on total corneal astigmatism rather than keratometric astigmatism improves the prediction of the residual refractive astigmatism. Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.

Analysing the teleconnection systems affecting the climate of the Carpathian Basin

NASA Astrophysics Data System (ADS)

Kristóf, Erzsébet; Bartholy, Judit; Pongrácz, Rita

2017-04-01

Nowadays, the increase of the global average near-surface air temperature is unequivocal. Atmospheric low-frequency variabilities have substantial impacts on climate variables such as air temperature and precipitation. Therefore, assessing their effects is essential to improve global and regional climate model simulations for the 21st century. The North Atlantic Oscillation (NAO) is one of the best-known atmospheric teleconnection patterns affecting the Carpathian Basin in Central Europe. Besides NAO, we aim to analyse other interannual-to-decadal teleconnection patterns, which might have significant impacts on the Carpathian Basin, namely, the East Atlantic/West Russia pattern, the Scandinavian pattern, the Mediterranean Oscillation, and the North-Sea Caspian Pattern. For this purpose primarily the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-20C atmospheric reanalysis dataset and multivariate statistical methods are used. The indices of each teleconnection pattern and their correlations with temperature and precipitation will be calculated for the period of 1961-1990. On the basis of these data first the long range (i. e. seasonal and/or annual scale) forecast ability is evaluated. Then, we aim to calculate the same indices of the relevant teleconnection patterns for the historical and future simulations of Coupled Model Intercomparison Project Phase 5 (CMIP5) models and compare them against each other using statistical methods. Our ultimate goal is to examine all available CMIP5 models and evaluate their abilities to reproduce the selected teleconnection systems. Thus, climate predictions for the 21st century for the Carpathian Basin may be improved using the best-performing models among all CMIP5 model simulations.

Stochastic modelling of temperatures affecting the in situ performance of a solar-assisted heat pump: The multivariate approach and physical interpretation

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

Loveday, D.L.; Craggs, C.

Box-Jenkins-based multivariate stochastic modeling is carried out using data recorded from a domestic heating system. The system comprises an air-source heat pump sited in the roof space of a house, solar assistance being provided by the conventional tile roof acting as a radiation absorber. Multivariate models are presented which illustrate the time-dependent relationships between three air temperatures - at external ambient, at entry to, and at exit from, the heat pump evaporator. Using a deterministic modeling approach, physical interpretations are placed on the results of the multivariate technique. It is concluded that the multivariate Box-Jenkins approach is a suitable techniquemore » for building thermal analysis. Application to multivariate Box-Jenkins approach is a suitable technique for building thermal analysis. Application to multivariate model-based control is discussed, with particular reference to building energy management systems. It is further concluded that stochastic modeling of data drawn from a short monitoring period offers a means of retrofitting an advanced model-based control system in existing buildings, which could be used to optimize energy savings. An approach to system simulation is suggested.« less

The misalignment of institutional "pillars": consequences for the U.S. health care field.

PubMed

Caronna, Carol A

2004-01-01

This paper uses an institutional perspective (Scott, 1994; 2001; DiMaggio and Powell, 1991) to analyze the history and current state of the American health care field in terms of the alignment of its normative, cognitive, and regulatory elements. I depict the relation between institutional elements in each of three historical eras of the health care field (Scott et al. 2000): the era of professional dominance (1945--1965), the era of federal involvement (1966--1982), and the era of managerial control and market mechanisms (after 1983 to the present). I argue that a weakening of alignment between these elements, beginning in the 1970s and increasing in the 1980s, led to consumer and provider dissatisfaction with managed care, and that the state of the field in the beginning of the 21st century suggests that a new era is emerging with renewed alignment between normative beliefs and values, cognitive models, and regulation. Implications for the future of health care and institutional theory are discussed.

Early onset of industrial-era warming across the oceans and continents.

PubMed

Abram, Nerilie J; McGregor, Helen V; Tierney, Jessica E; Evans, Michael N; McKay, Nicholas P; Kaufman, Darrell S

2016-08-25

The evolution of industrial-era warming across the continents and oceans provides a context for future climate change and is important for determining climate sensitivity and the processes that control regional warming. Here we use post-ad 1500 palaeoclimate records to show that sustained industrial-era warming of the tropical oceans first developed during the mid-nineteenth century and was nearly synchronous with Northern Hemisphere continental warming. The early onset of sustained, significant warming in palaeoclimate records and model simulations suggests that greenhouse forcing of industrial-era warming commenced as early as the mid-nineteenth century and included an enhanced equatorial ocean response mechanism. The development of Southern Hemisphere warming is delayed in reconstructions, but this apparent delay is not reproduced in climate simulations. Our findings imply that instrumental records are too short to comprehensively assess anthropogenic climate change and that, in some regions, about 180 years of industrial-era warming has already caused surface temperatures to emerge above pre-industrial values, even when taking natural variability into account.

Informing Federal Policy on Firearm Restrictions for Veterans with Fiduciaries: Risk Indicators in the Post-Deployment Mental Health Study.

PubMed

Swanson, Jeffrey; Easter, Michele; Brancu, Mira; Fairbank, John A

2018-05-24

This article examines the public safety rationale for a federal policy of prohibiting gun sales to veterans with psychiatric disabilities who are assigned a fiduciary to manage their benefits from the Department of Veterans Affairs. The policy was evaluated using data on 3200 post-deployment veterans from the Iraq and Afghanistan war era. Three proxy measures of fiduciary need-based on intellectual disability, drug abuse, or acute psychopathology-were associated in bivariate analysis with interpersonal violence and suicidality. In multivariate analysis, statistical significance remained only for the measure based on acute psychopathology. Implications for reforms to the fiduciary firearm restriction policy are discussed.

Lagrangian large eddy simulations of boundary layer clouds on ERA-Interim and ERA5 trajectories

NASA Astrophysics Data System (ADS)

Kazil, J.; Feingold, G.; Yamaguchi, T.

2017-12-01

This exploratory study examines Lagrangian large eddy simulations of boundary layer clouds along wind trajectories from the ERA-Interim and ERA5 reanalyses. The study is motivated by the need for statistically representative sets of high resolution simulations of cloud field evolution in realistic meteorological conditions. The study will serve as a foundation for the investigation of biomass burning effects on the transition from stratocumulus to shallow cumulus clouds in the South-East Atlantic. Trajectories that pass through a location with radiosonde data (St. Helena) and which exhibit a well-defined cloud structure and evolution were identified in satellite imagery, and sea surface temperature and atmospheric vertical profiles along the trajectories were extracted from the reanalysis data sets. The System for Atmospheric Modeling (SAM) simulated boundary layer turbulence and cloud properties along the trajectories. Mean temperature and moisture (in the free troposphere) and mean wind speed (at all levels) were nudged towards the reanalysis data. Atmospheric and cloud properties in the large eddy simulations were compared with those from the reanalysis products, and evaluated with satellite imagery and radiosonde data. Simulations using ERA-Interim data and the higher resolution ERA5 data are contrasted.

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Academic Dishonesty in Distance Higher Education: Challenges and Models for Moral Education in the Digital Era

ERIC Educational Resources Information Center

Farisi, Mohammad Imam

2013-01-01

Today, in the era of open access to digital-based information and communication, one of the biggest challenges in higher education to realize moral education and to build academic culture and integrity is the emergence of academic dishonesty behaviors among academic members. The paper describes academic dishonesty behaviors in Distance Higher…

A Heuristic Model of Primordial Chemical Evolution in the Reionization Era

NASA Astrophysics Data System (ADS)

McArdle, Ryan T.; Stancil, Phillip C.

2017-06-01

We develop a model of the evolution of the chemical composition of the early Universe under the influence of Population III (Pop III) stars. Solving rate equations for primordial atomic and molecular species subject to the Cosmic Background Radiation (CBR), we predict the fractional abundances of these species as a function of redshift (z). The CBR, however, eventually becomes negligible after the first stars become active. To extend the recombination era model (Gay et al. 2011), we simulate the formation of many stars from a cloud of a given mass, constrained by the Initial Mass Function (IMF), and assign to each star a mass appropriate lifetime, effective temperature, and radius (Schaerer 2002). We randomly distribute the stars across a parcel of gas with the number being controlled by the star formation rate as a function of z (Hartwig et al. 2015). Runs of our chemistry code are then spawned for each star in parallel once a star turns on. We model the propagation of the radiation front as it expands and ionizes the surrounding region, until the star has lived its lifetime. Taking the average of the data sets produce by the collection of stars in the region, we are able to obtain a prediction of the evolution of the chemical composition of the entire modeled region from the Recombination era into the Reionization era.Gay, C., et al. 2011, ApJ, 735, 44Hartwig, T., et al. 2015, MNRAS, 447, 3892Schaerer, D. 2002, A&A, 382, 28The work of RTM was partially supported by a UGA Center for Undergraduate Research Opportunities Award.

Elevated levels of Era GTPase improve growth, 16S rRNA processing, and 70S ribosome assembly of Escherichia coli lacking highly conserved multifunctional YbeY endoribonuclease.

PubMed

Ghosal, Anubrata; Babu, Vignesh M P; Walker, Graham C

2018-06-18

YbeY is a highly conserved, multifunctional endoribonuclease that plays a significant role in ribosome biogenesis and has several additional roles. Here, we show in Escherichia coli that overexpressing the conserved GTPase, Era, partially suppresses the growth defect of a ΔybeY strain while improving 16S rRNA processing and 70S ribosome assembly. This suppression requires both Era's ability to hydrolyze GTP and the function of three exoribonucleases, RNase II, RNase R and RNase PH, suggesting a model for Era's action. Overexpressing Vibrio cholerae Era similarly partially suppresses the defects of an E. coli ΔybeY strain indicating this property of Era is conserved in bacteria other than E. coli Importance This work provides additional insights into the critical, but still incompletely understood, mechanism of the processing of the E. coli 16S rRNA 3'-terminus. The highly conserved GTPase, Era, is known to bind to the precursor of the 16S rRNA near its 3-end. Both the endoribonuclease YbeY, which binds to Era, and four exoribonucleases have been implicated in this 3'-end processing. Results reported here offer additional insights into the role of Era in 16S rRNA 3'-maturation and into the relationship between the action of the endoribonuclease YbeY and the four exoribonucleases. This study also hints at why YbeY is only essential in some bacteria and suggests that the YbeY could be a target for a new class of antibiotic in these bacteria. Copyright © 2018 American Society for Microbiology.

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Increased threat of tropical cyclones and coastal flooding to New York City during the anthropogenic era.

PubMed

Reed, Andra J; Mann, Michael E; Emanuel, Kerry A; Lin, Ning; Horton, Benjamin P; Kemp, Andrew C; Donnelly, Jeffrey P

2015-10-13

In a changing climate, future inundation of the United States' Atlantic coast will depend on both storm surges during tropical cyclones and the rising relative sea levels on which those surges occur. However, the observational record of tropical cyclones in the North Atlantic basin is too short (A.D. 1851 to present) to accurately assess long-term trends in storm activity. To overcome this limitation, we use proxy sea level records, and downscale three CMIP5 models to generate large synthetic tropical cyclone data sets for the North Atlantic basin; driving climate conditions span from A.D. 850 to A.D. 2005. We compare pre-anthropogenic era (A.D. 850-1800) and anthropogenic era (A.D.1970-2005) storm surge model results for New York City, exposing links between increased rates of sea level rise and storm flood heights. We find that mean flood heights increased by ∼1.24 m (due mainly to sea level rise) from ∼A.D. 850 to the anthropogenic era, a result that is significant at the 99% confidence level. Additionally, changes in tropical cyclone characteristics have led to increases in the extremes of the types of storms that create the largest storm surges for New York City. As a result, flood risk has greatly increased for the region; for example, the 500-y return period for a ∼2.25-m flood height during the pre-anthropogenic era has decreased to ∼24.4 y in the anthropogenic era. Our results indicate the impacts of climate change on coastal inundation, and call for advanced risk management strategies.

Increased threat of tropical cyclones and coastal flooding to New York City during the anthropogenic era

PubMed Central

Reed, Andra J.; Mann, Michael E.; Emanuel, Kerry A.; Lin, Ning; Horton, Benjamin P.; Kemp, Andrew C.; Donnelly, Jeffrey P.

2015-01-01

In a changing climate, future inundation of the United States’ Atlantic coast will depend on both storm surges during tropical cyclones and the rising relative sea levels on which those surges occur. However, the observational record of tropical cyclones in the North Atlantic basin is too short (A.D. 1851 to present) to accurately assess long-term trends in storm activity. To overcome this limitation, we use proxy sea level records, and downscale three CMIP5 models to generate large synthetic tropical cyclone data sets for the North Atlantic basin; driving climate conditions span from A.D. 850 to A.D. 2005. We compare pre-anthropogenic era (A.D. 850–1800) and anthropogenic era (A.D.1970–2005) storm surge model results for New York City, exposing links between increased rates of sea level rise and storm flood heights. We find that mean flood heights increased by ∼1.24 m (due mainly to sea level rise) from ∼A.D. 850 to the anthropogenic era, a result that is significant at the 99% confidence level. Additionally, changes in tropical cyclone characteristics have led to increases in the extremes of the types of storms that create the largest storm surges for New York City. As a result, flood risk has greatly increased for the region; for example, the 500-y return period for a ∼2.25-m flood height during the pre-anthropogenic era has decreased to ∼24.4 y in the anthropogenic era. Our results indicate the impacts of climate change on coastal inundation, and call for advanced risk management strategies. PMID:26417111

Controlled meteorological (CMET) free balloon profiling of the Arctic atmospheric boundary layer around Spitsbergen compared to ERA-Interim and Arctic System Reanalyses

NASA Astrophysics Data System (ADS)

Roberts, Tjarda J.; Dütsch, Marina; Hole, Lars R.; Voss, Paul B.

2016-09-01

Observations from CMET (Controlled Meteorological) balloons are analysed to provide insights into tropospheric meteorological conditions (temperature, humidity, wind) around Svalbard, European High Arctic. Five Controlled Meteorological (CMET) balloons were launched from Ny-Ålesund in Svalbard (Spitsbergen) over 5-12 May 2011 and measured vertical atmospheric profiles over coastal areas to both the east and west. One notable CMET flight achieved a suite of 18 continuous soundings that probed the Arctic marine boundary layer (ABL) over a period of more than 10 h. Profiles from two CMET flights are compared to model output from ECMWF Era-Interim reanalysis (ERA-I) and to a high-resolution (15 km) Arctic System Reanalysis (ASR) product. To the east of Svalbard over sea ice, the CMET observed a stable ABL profile with a temperature inversion that was reproduced by ASR but not captured by ERA-I. In a coastal ice-free region to the west of Svalbard, the CMET observed a stable ABL with strong wind shear. The CMET profiles document increases in ABL temperature and humidity that are broadly reproduced by both ASR and ERA-I. The ASR finds a more stably stratified ABL than observed but captured the wind shear in contrast to ERA-I. Detailed analysis of the coastal CMET-automated soundings identifies small-scale temperature and humidity variations with a low-level flow and provides an estimate of local wind fields. We demonstrate that CMET balloons are a valuable approach for profiling the free atmosphere and boundary layer in remote regions such as the Arctic, where few other in situ observations are available for model validation.

Use of Longitudinal Data in Genetic Studies in the Genome-wide Association Studies Era: Summary of Group 14

PubMed Central

Kerner, Berit; North, Kari E; Fallin, M Daniele

2010-01-01

Participants analyzed actual and simulated longitudinal data from the Framingham Heart Study for various metabolic and cardiovascular traits. The genetic information incorporated into these investigations ranged from selected single-nucleotide polymorphisms to genome-wide association arrays. Genotypes were incorporated using a broad range of methodological approaches including conditional logistic regression, linear mixed models, generalized estimating equations, linear growth curve estimation, growth modeling, growth mixture modeling, population attributable risk fraction based on survival functions under the proportional hazards models, and multivariate adaptive splines for the analysis of longitudinal data. The specific scientific questions addressed by these different approaches also varied, ranging from a more precise definition of the phenotype, bias reduction in control selection, estimation of effect sizes and genotype associated risk, to direct incorporation of genetic data into longitudinal modeling approaches and the exploration of population heterogeneity with regard to longitudinal trajectories. The group reached several overall conclusions: 1) The additional information provided by longitudinal data may be useful in genetic analyses. 2) The precision of the phenotype definition as well as control selection in nested designs may be improved, especially if traits demonstrate a trend over time or have strong age-of-onset effects. 3) Analyzing genetic data stratified for high-risk subgroups defined by a unique development over time could be useful for the detection of rare mutations in common multi-factorial diseases. 4) Estimation of the population impact of genomic risk variants could be more precise. The challenges and computational complexity demanded by genome-wide single-nucleotide polymorphism data were also discussed. PMID:19924713

Potential impact of climate change on coffee rust over Mexico and Central America

NASA Astrophysics Data System (ADS)

Calderon-Ezquerro, Maria del Carmen; Martinez-Lopez, Benjamin; Cabos Narvaez, William David; Sein, Dmitry

2017-04-01

In this work, some meteorological variables from a regional climate model are used to characterize the dispersion of coffee rust (a fungal disease) from Central America to Mexico, during the 20 Century. The climate model consists of the regional atmosphere model REMO coupled to the MPIOM global ocean model with increased resolution in the Atlantic Ocean. Lateral atmospheric and upper oceanic boundary conditions outside the coupled domain were prescribed using both ERA-40 and ERA-Interim reanalysis data. In addition to the historical simulation, a projection of the evolution of the coffee rust for the 21 Century was obtained from a REMO run using MPIESM data for the lateral forcing.

Reduction in liver transplant wait-listing in the era of direct-acting antiviral therapy.

PubMed

Flemming, Jennifer A; Kim, W Ray; Brosgart, Carol L; Terrault, Norah A

2017-03-01

Direct-acting antiviral (DAA) therapy, recently approved for patients with decompensated cirrhosis (DC) secondary to hepatitis C virus (HCV), is associated with improved hepatic function. We analyzed trends in liver transplant (LT) wait-listing (WL) to explore potential impact of effective medical therapy on WL registration. This is a cohort study using the Scientific Registry of Transplant Recipients database from 2003 to 2015. A total of 47,591 adults wait-listed for LT from HCV, hepatitis B virus (HBV), and nonalcoholic steatohepatitis (NASH) were identified. LT indication was defined as DC if the Model for End-Stage Liver Disease (MELD) at WL was ≥15 or hepatocellular carcinoma (HCC). Era of listing was divided into interferon (IFN; 2003-2010), protease inhibitor (PI; 2011-2013), and direct-acting antiviral (DAA; 2014-2015). Annual standardized incidence rates of WL were analyzed using Poisson regression. Adjusted incidences of LT WL for DC in HCV patients decreased by 5% in the PI era (P = 0.004) and 32% in the DAA era (P < 0.001) compared to the IFN era. Listing for DC in HBV also decreased in the PI (-17%; P = 0.002) and DAA eras (-24%; P < 0.001). Conversely, WL for DC in NASH increased by 41% in the PI era (P < 0.001) and 81% in the DAA era (P < 0.001). WL for HCC in both the HCV and NASH populations increased in both the PI and DAA eras (P < 0.001 for all) whereas HCC WL in HBV remained stable (P > 0.05 for all). The rate of LT WL for HCV complicated by DC has decreased by over 30% in the era of DAA therapy. Further reductions in WL are anticipated with increased testing, linkage to care, and access to DAA therapy. (Hepatology 2017;65:804-812). © 2016 by the American Association for the Study of Liver Diseases.

Performance and quality assessment of the global ocean eddy-permitting physical reanalysis GLORYS2V4.

NASA Astrophysics Data System (ADS)

Garric, Gilles; Parent, Laurent; Greiner, Eric; Drévillon, Marie; Hamon, Mathieu; Lellouche, Jean-Michel; Régnier, Charly; Desportes, Charles; Le Galloudec, Olivier; Bricaud, Clement; Drillet, Yann; Hernandez, Fabrice; Le Traon, Pierre-Yves

2017-04-01

The purpose of this presentation is to give an overview of the recent upgrade of GLORYS2 (version 4 and GLORYS2V4 hereafter), the latest ocean reanalysis produced at Mercator Ocean that covers the altimetry era (1993-2015) in the framework of Copernicus Marine Environment Monitoring Service (CMEMS; http://marine.copernicus.eu/). The reanalysis is run at eddy-permitting resolution (¼° horizontal resolution and 75 vertical levels) with the NEMO model and driven at the surface by ERA-Interim reanalysis from ECMWF (European Centre for Medium-Range Weather Forecasts). The reanalysis system uses a multi-data and multivariate reduced order Kalman filter based on the singular extended evolutive Kalman (SEEK) filter formulation together with a 3D-VAR large scale bias correction. The assimilated observations are along-track satellite altimetry, sea surface temperature, sea ice concentration and in-situ profiles of temperature and salinity. With respect to the previous version (GLORYS2V3), GLORYS2V4 contains a number of improvements. In particular: a) new initial temperature and salinity conditions derived from EN4 data base with a better mass equilibrium with altimetry, b) the use of the updated delayed mode CORA in situ observations from CMEMS, c) a new hybrid Mean Dynamical Topography (MDT) for the assimilation scheme referenced over the 1993-2013 period, d) a better observation operator for altimetry observations for the data assimilation scheme: e) A correction of large scale ERA-Interim atmospheric surface (precipitations and radiative) fluxes as in GLORYS2V3 but towards new satellite data set f) an update of the climatological runoff data base by using the latest version of Dai's 2009 data set for the global ocean together with better account of freshwater fluxes from polar ice sheet's glaciers. The presentation will show that the new reanalysis outperforms the previous version in many aspects such as biases and root mean squared error and, especially in representing the variability of global heat and salt content and associated steric sea level in the last two decades. The dataset is available in NetCDF format and GLORYS2V4 best analysis products are distributed onto the CMEMS data portal.

HIV Infection Is Associated With Poor Outcomes for Patients With Anal Cancer in the Highly Active Antiretroviral Therapy Era.

PubMed

Grew, David; Bitterman, Danielle; Leichman, Cynthia G; Leichman, Lawrence; Sanfilippo, Nicholas; Moore, Harvey G; Du, Kevin

2015-12-01

HIV status may affect outcomes after definitive chemoradiotherapy for anal cancer. Here, we report a large series in the highly active antiretroviral therapy era comparing outcomes between HIV-positive and HIV-negative patients with anal cancer. This was a retrospective chart review. The study was conducted at an outpatient oncology clinic at large academic center. A total of 107 patients were reviewed, 39 HIV positive and 68 HIV negative. All of the patients underwent definitive chemoradiation for anal cancer. Data on patient characteristics, treatment, toxicity, and outcomes were collected. Overall survival, colostomy-free survival, local recurrence-free survival, and distant metastasis-free survival were analyzed. Median follow-up was 15 months. HIV-positive patients were younger (median, 52 vs 64 years; p < 0.001) and predominantly men (82% men vs 49% men; p = 0.001). There were no significant differences in T, N, or stage groups. HIV-positive patients had a significantly longer duration from biopsy to start of chemoradiation (mean number of days, 82 vs 54; p = 0.042). There were no differences in rates of acute toxicities including diarrhea, fatigue, or dermatitis. HIV-positive patients had significantly higher rates of hospitalization (33% vs 15%; p = 0.024). The 3-year overall survival rate was 42% in HIV-positive and 76% in HIV-negative patients (p = 0.037; HR, 2.335 (95% CI, 1.032-5.283)). Three-year colostomy-free survival was 67% in HIV-positive and 88% in HIV-negative patients (p = 0.036; HR, 3.231 (95% CI, 1.014-10.299)). Differences in overall survival rates were not significant on multivariate analysis. This study was limited by its retrospective design and small patient numbers. In this cohort, HIV-positive patients had significantly worse overall and colostomy-free survival rates than HIV-negative patients. However, differences in survival were not significant on multivariate analysis. Additional studies are necessary to establish the etiology of this difference.

Prognostic value of the physical examination in patients with heart failure and atrial fibrillation: insights from the AF-CHF trial (atrial fibrillation and chronic heart failure).

PubMed

Caldentey, Guillem; Khairy, Paul; Roy, Denis; Leduc, Hugues; Talajic, Mario; Racine, Normand; White, Michel; O'Meara, Eileen; Guertin, Marie-Claude; Rouleau, Jean L; Ducharme, Anique

2014-02-01

This study sought to assess the prognostic value of physical examination in a modern treated heart failure population. The physical examination is the cornerstone of the evaluation and monitoring of patients with heart failure. Yet, the prognostic value of congestive signs (i.e., peripheral edema, jugular venous distension, a third heart sound, and pulmonary rales) has not been assessed in the current era. A post-hoc analysis was conducted on all 1,376 patients, 81% male, mean age 67 ± 11 years, with symptomatic left ventricular systolic dysfunction enrolled in the AF-CHF (Atrial Fibrillation and Congestive Heart Failure) trial. The prognostic value of baseline physical examination findings was assessed in univariate and multivariate Cox regression analyses. Peripheral edema was observed in 425 (30.9%), jugular venous distension in 297 (21.6%), a third heart sound in 207 (15.0%), and pulmonary rales in 178 (12.9%) patients. Death from cardiovascular causes occurred in 357 (25.9%) patients over a mean follow-up of 37 ± 19 months. All 4 physical examination findings were associated with cardiovascular mortality in univariate analyses (all p values <0.01). In multivariate analyses, taking all 4 signs as potential covariates, only rales (hazard ratio 1.41; 95% confidence interval: 1.07 to 1.86; p = 0.013) and peripheral edema (hazard ratio: 1.25; 95% confidence interval: 1.00 to 1.57; p = 0.048) were associated with cardiovascular mortality, independent of other variables. In the modern era, congestive signs on the physical examination (i.e., peripheral edema, jugular venous distension, a third heart sound, and pulmonary rales) continue to provide important prognostic information in patients with congestive heart failure. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Cultural Democracy in an Era of Internationalism and Subnationalism: A New Model for Effective Cultural Integration in Korea

ERIC Educational Resources Information Center

Fry, Gerald W.

2016-01-01

The context for this paper is the rapid globalization and international migration occurring across the globe. An insightful metaphor for this era is "the death of distance." The influx of new migrants into countries such as Korea, Japan, Thailand, and the United States presents many challenges for those societies. In Minnesota, people of…

Leading for Innovative Practice: Melding Theories of Organizational Change, Adult Learning, and Conditions of Learning

ERIC Educational Resources Information Center

Mirci, Philip S.; Hensley, Phyllis A.

2010-01-01

We live in an era of unique challenges requiring us to face a new reality mired in information overload for the 21st Century. This new reality emphasizes the critical need for educational leaders who can think and act systemically rather than bureaucratically. The bureaucratic model inherited from the Industrial Era still prevails in many…

Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models

ERIC Educational Resources Information Center

Price, Larry R.

2012-01-01

The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Growth trajectories in early childhood, their relationship with antenatal and postnatal factors, and development of obesity by age 9 years: results from an Australian birth cohort study.

PubMed

Giles, L C; Whitrow, M J; Davies, M J; Davies, C E; Rumbold, A R; Moore, V M

2015-07-01

In an era where around one in four children in the United Kingdom, the United States, and Australia are overweight or obese, the development of obesity in early life needs to be better understood. We aimed to identify groups of children with distinct trajectories of growth in infancy and early childhood, to examine any association between these trajectories and body size at age 9, and to assess the relative influence of antenatal and postnatal exposures on growth trajectories. Prospective Australian birth cohort study. In total, 557 children with serial height and weight measurements from birth to 9 years were included in the study. Latent class growth models were used to derive distinct groups of growth trajectories from birth to age 3½ years. Multivariable logistic regression models were used to explore antenatal and postnatal predictors of growth trajectory groups, and multivariable linear and logistic regression models were used to examine the relationships between growth trajectory groups and body size at age 9 years. We identified four discrete growth trajectories from birth to age 3½ years, characterised as low, intermediate, high, or accelerating growth. Relative to the intermediate growth group, the low group had reduced z-body mass index (BMI) (-0.75 s.d.; 95% confidence interval (CI) -1.02, -0.47), and the high and accelerating groups were associated with increased body size at age 9 years (high: z-BMI 0.70 s.d.; 95% CI 0.49, 0.62; accelerating: z-BMI 1.64 s.d.; 95% CI 1.16, 2.11). Of the antenatal and postnatal exposures considered, the most important differentiating factor was maternal obesity in early pregnancy, associated with a near quadrupling of risk of membership of the accelerating growth trajectory group compared with the intermediate growth group (odds ratio (OR) 3.72; 95% CI 1.15, 12.05). Efforts to prevent childhood obesity may need to be embedded within population-wide strategies that also pay attention to healthy weight for women in their reproductive years.

Weather patterns as a downscaling tool - evaluating their skill in stratifying local climate variables

NASA Astrophysics Data System (ADS)

Murawski, Aline; Bürger, Gerd; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

The use of a weather pattern based approach for downscaling of coarse, gridded atmospheric data, as usually obtained from the output of general circulation models (GCM), allows for investigating the impact of anthropogenic greenhouse gas emissions on fluxes and state variables of the hydrological cycle such as e.g. on runoff in large river catchments. Here we aim at attributing changes in high flows in the Rhine catchment to anthropogenic climate change. Therefore we run an objective classification scheme (simulated annealing and diversified randomisation - SANDRA, available from the cost733 classification software) on ERA20C reanalyses data and apply the established classification to GCMs from the CMIP5 project. After deriving weather pattern time series from GCM runs using forcing from all greenhouse gases (All-Hist) and using natural greenhouse gas forcing only (Nat-Hist), a weather generator will be employed to obtain climate data time series for the hydrological model. The parameters of the weather pattern classification (i.e. spatial extent, number of patterns, classification variables) need to be selected in a way that allows for good stratification of the meteorological variables that are of interest for the hydrological modelling. We evaluate the skill of the classification in stratifying meteorological data using a multi-variable approach. This allows for estimating the stratification skill for all meteorological variables together, not separately as usually done in existing similar work. The advantage of the multi-variable approach is to properly account for situations where e.g. two patterns are associated with similar mean daily temperature, but one pattern is dry while the other one is related to considerable amounts of precipitation. Thus, the separation of these two patterns would not be justified when considering temperature only, but is perfectly reasonable when accounting for precipitation as well. Besides that, the weather patterns derived from reanalyses data should be well represented in the All-Hist GCM runs in terms of e.g. frequency, seasonality, and persistence. In this contribution we show how to select the most appropriate weather pattern classification and how the classes derived from it are reflected in the GCMs.

Early relapse after single auto-SCT for multiple myeloma is a major predictor of survival in the era of novel agents.

PubMed

Jimenez-Zepeda, V H; Reece, D E; Trudel, S; Chen, C; Tiedemann, R; Kukreti, V

2015-02-01

The role of auto-SCT in the treatment of multiple myeloma (MM) in the era of novel agents continues to evolve. It is now clear that the depth of response and clinical outcomes have significantly improved as a result of the combination of these strategies. However, not all patients with MM who undergo auto-SCT are able to sustain a meaningful response and 20% of patients relapse shortly after auto-SCT. In this study, we aimed to assess the impact of early relapse (ER) after auto-SCT on OS for MM patients undergoing single auto-SCT who had received novel agent-based induction regimens. All consecutive patients with MM undergoing single auto-SCT from January 2002 to September 2012 who had novel induction therapy were evaluated. A total of 184 patients were identified. The median OS and PFS for the group of transplanted patients were 93 and 25.4 months, respectively. Median time to relapse was 17.2 months with 40% having relapsed at the time of analysis. ER (<12 months post auto-SCT) was seen in 27 (36%) out of 75 patients who had relapsed, and median OS was significantly shorter than in those with non-ER. Multivariate analysis showed ER as the major independent prognostic factor for OS. On the basis of these findings, we conclude that not only attainment of a good response, but sustainability of it, appears to be a major prognostic variable in MM in the era of novel therapy. Patients with ER post auto-SCT should biologically be characterized in prospective studies to better understand the mechanisms of resistance associated with this particular entity.

Post-treatment plasma EBV-DNA positivity predicts early relapse and poor prognosis for patients with extranodal NK/T cell lymphoma in the era of asparaginase.

PubMed

Wang, Liang; Wang, Hua; Wang, Jing-hua; Xia, Zhong-jun; Lu, Yue; Huang, Hui-qiang; Jiang, Wen-qi; Zhang, Yu-jing

2015-10-06

Circulating Epstein-Barr virus (EBV) DNA is a biomarker of EBV-associated malignancies. Its prognostic value in early stage NK/T-cell lymphoma (NKTCL) in the era of asparaginase was investigated. 68 patients were treated with a median of 4 cycles of asparaginase-based chemotherapy followed by a median of 54.6 Gy (range 50-60 Gy) radiation. The amount of EBV-DNA was prospectively measured in both pretreatment and post-treatment plasma samples by real-time quantitative PCR. At the end of treatment, complete response (CR) rate was 79.4%, and overall response rate (ORR) was 88.2%. Patients with negative pretreatment EBV-DNA had a higher CR rate (96.0% vs. 69.8%, p = 0.023). The 3-year progression-free survival (PFS) rate and overall survival (OS) rate was 71% and 83%, respectively. In multivariate survival analysis, post-treatment EBV-DNA positivity and treatment response (non-CR) were prognostic factors for both worse PFS and OS (p < 0.05). Local tumor invasion was also a prognostic factor for worse OS (p = 0.010). In patients with CR, post-treatment EBV-DNA positivity correlated with inferior PFS and OS (both p < 0.0001). In patients with positive pretreatment EBV-DNA, negative post-treatment EBV-DNA correlated with better PFS and OS (both p < 0.0001). These findings indicate that post-treatment EBV-DNA positivity can predict early relapse and poor prognosis for patients with early stage NKTCL in the era of asparaginase, and may be used as an indicator of minimal residual disease.

High Prevalence of Echocardiographic Abnormalities among HIV-infected Persons in the Era of Highly Active Antiretroviral Therapy.

PubMed

Mondy, Kristin E; Gottdiener, John; Overton, E Turner; Henry, Keith; Bush, Tim; Conley, Lois; Hammer, John; Carpenter, Charles C; Kojic, Erna; Patel, Pragna; Brooks, John T

2011-02-01

in the era of highly active antiretroviral therapy (HAART), human immunodeficiency virus (HIV)-infected persons have higher cardiovascular disease risk. Little is known about asymptomatic abnormalities in cardiac structure and function in this population. the Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy (SUN Study) is a prospective, observational, multi-site cohort of 656 HIV-infected participants who underwent baseline echocardiography during 2004-2006. We examined prevalence of and factors associated with left ventricular systolic dysfunction (LVSD), diastolic dysfunction (DD), pulmonary hypertension (PHTN), left ventricular hypertrophy (LVH), and left atrial enlargement (LAE). participant characteristics were as follows: median age, 41 years; 24% women; 29% non-Hispanic black; 73% receiving HAART; and median CD4+ cell count, 462 cells/μL. Among evaluable participants, 18% had LVSD, 26% had DD, 57% had PHTN (right ventricular pressure >30 mm Hg), 6.5% had LVH, and 40% had LAE. In multivariate analyses, significant factors (P < .05) associated with LVSD were history of MI, elevated highly sensitive C-reactive protein (hsCRP) level, and current tobacco smoking; for DD, elevated hsCRP level and hypertension; for PHTN, current use of ritonavir; for LVH, hypertension, diabetes, non-white race, female sex with elevated body mass index, calculated as the weight in kilograms divided by the square of height in meters, of ≥ 25, elevated hsCRP level, and current use of abacavir; for LAE, hypertension and recent marijuana use. in this large contemporary HIV cohort, the prevalence of subclinical functional and structural cardiac abnormalities was greater than expected for age. Abnormalities were mostly associated with expected and often modifiable risks. Lifestyle modification should become a greater priority in the management of chronic HIV disease.

Margin Status Remains an Important Determinant of Survival after Surgical Resection of Colorectal Liver Metastases in the Era of Modern Chemotherapy

PubMed Central

Andreou, Andreas; Aloia, Thomas A.; Brouquet, Antoine; Dickson, Paxton V.; Zimmitti, Giuseppe; Maru, Dipen M.; Kopetz, Scott; Loyer, Evelyne M.; Curley, Steven A.; Abdalla, Eddie K.; Vauthey, Jean-Nicolas

2013-01-01

Objective To determine the impact of surgical margin status on overall survival (OS) of patients undergoing hepatectomy for colorectal liver metastases (CLM) after modern preoperative chemotherapy. Summary Background Data In the era of effective chemotherapy for CLM, the association between surgical margin status and survival has become controversial. Methods Clinicopathologic data and outcomes for 378 patients treated with modern preoperative chemotherapy and hepatectomy were analyzed. The effect of positive margins on OS was analyzed in relation to pathologic and computed tomography-based morphologic response to chemotherapy. Results Fifty-two of 378 resections (14%) were R1 resections (tumor-free margin < 1 mm). The 5-year OS rates for patients with R0 resection (margin ≥ 1 mm) and R1 resection were 55% and 26%, respectively (P=0.017). Multivariate analysis identified R1 resection (P=0.03) and minor pathologic response to chemotherapy (P=0.002) as the 2 factors independently associated with worse survival. The survival benefit associated with negative margins (R0 vs. R1 resection) was greater in patients with suboptimal morphologic response (5-year OS rate: 62% vs. 11%, P=0.007) than in patients with optimal response (3-year OS rate: 92% vs. 88%, P=0.917) and greater in patients with minor pathologic response (5-year OS rate: 46% vs. 0%, P=0.002) than in patients with major response (5-year OS rate: 63% vs. 67%, P=0.587). Conclusions In the era of modern chemotherapy, negative margins remain an important determinant of survival and should be the primary goal of surgical therapy. The impact of positive margins is most pronounced in patients with suboptimal response to systemic therapy. PMID:23426338

Margin status remains an important determinant of survival after surgical resection of colorectal liver metastases in the era of modern chemotherapy.

PubMed

Andreou, Andreas; Aloia, Thomas A; Brouquet, Antoine; Dickson, Paxton V; Zimmitti, Giuseppe; Maru, Dipen M; Kopetz, Scott; Loyer, Evelyne M; Curley, Steven A; Abdalla, Eddie K; Vauthey, Jean-Nicolas

2013-06-01

To determine the impact of surgical margin status on overall survival (OS) of patients undergoing hepatectomy for colorectal liver metastases after modern preoperative chemotherapy. In the era of effective chemotherapy for colorectal liver metastases, the association between surgical margin status and survival has become controversial. Clinicopathologic data and outcomes for 378 patients treated with modern preoperative chemotherapy and hepatectomy were analyzed. The effect of positive margins on OS was analyzed in relation to pathologic and computed tomography-based morphologic response to chemotherapy. Fifty-two of 378 resections (14%) were R1 resections (tumor-free margin <1 mm). The 5-year OS rates for patients with R0 resection (margin ≥1 mm) and R1 resection were 55% and 26%, respectively (P = 0.017). Multivariate analysis identified R1 resection (P = 0.03) and a minor pathologic response to chemotherapy (P = 0.002) as the 2 factors independently associated with worse survival. The survival benefit associated with negative margins (R0 vs R1 resection) was greater in patients with suboptimal morphologic response (5-year OS rate: 62% vs 11%; P = 0.007) than in patients with optimal response (3-year OS rate: 92% vs 88%; P = 0.917) and greater in patients with a minor pathologic response (5-year OS rate: 46% vs 0%; P = 0.002) than in patients with a major response (5-year OS rate: 63% vs 67%; P = 0.587). In the era of modern chemotherapy, negative margins remain an important determinant of survival and should be the primary goal of surgical therapy. The impact of positive margins is most pronounced in patients with suboptimal response to systemic therapy.

Selection Criteria for Internal Medicine Residency Applicants and Professionalism Ratings During Internship

PubMed Central

Cullen, Michael W.; Reed, Darcy A.; Halvorsen, Andrew J.; Wittich, Christopher M.; Kreuziger, Lisa M. Baumann; Keddis, Mira T.; McDonald, Furman S.; Beckman, Thomas J.

2011-01-01

OBJECTIVE: To determine whether standardized admissions data in residents' Electronic Residency Application Service (ERAS) submissions were associated with multisource assessments of professionalism during internship. PARTICIPANTS AND METHODS: ERAS applications for all internal medicine interns (N=191) at Mayo Clinic entering training between July 1, 2005, and July 1, 2008, were reviewed by 6 raters. Extracted data included United States Medical Licensing Examination scores, medicine clerkship grades, class rank, Alpha Omega Alpha membership, advanced degrees, awards, volunteer activities, research experiences, first author publications, career choice, and red flags in performance evaluations. Medical school reputation was quantified using U.S. News & World Report rankings. Strength of comparative statements in recommendation letters (0 = no comparative statement, 1 = equal to peers, 2 = top 20%, 3 = top 10% or “best”) were also recorded. Validated multisource professionalism scores (5-point scales) were obtained for each intern. Associations between application variables and professionalism scores were examined using linear regression. RESULTS: The mean ± SD (minimum-maximum) professionalism score was 4.09±0.31 (2.13-4.56). In multivariate analysis, professionalism scores were positively associated with mean strength of comparative statements in recommendation letters (β=0.13; P=.002). No other associations between ERAS application variables and professionalism scores were found. CONCLUSION: Comparative statements in recommendation letters for internal medicine residency applicants were associated with professionalism scores during internship. Other variables traditionally examined when selecting residents were not associated with professionalism. These findings suggest that faculty physicians' direct observations, as reflected in letters of recommendation, are useful indicators of what constitutes a best student. Residency selection committees should scrutinize applicants' letters for strongly favorable comparative statements. PMID:21364111

On the physical air-sea fluxes for climate modeling

NASA Astrophysics Data System (ADS)

Bonekamp, J. G.

2001-02-01

At the sea surface, the atmosphere and the ocean exchange momentum, heat and freshwater. Mechanisms for the exchange are wind stress, turbulent mixing, radiation, evaporation and precipitation. These surface fluxes are characterized by a large spatial and temporal variability and play an important role in not only the mean atmospheric and oceanic circulation, but also in the generation and sustainment of coupled climate fluctuations such as the El Niño/La Niña phenomenon. Therefore, a good knowledge of air-sea fluxes is required for the understanding and prediction of climate changes. As part of long-term comprehensive atmospheric reanalyses with `Numerical Weather Prediction/Data assimilation' systems, data sets of global air-sea fluxes are generated. A good example is the 15-year atmospheric reanalysis of the European Centre for Medium--Range Weather Forecasts (ECMWF). Air-sea flux data sets from these reanalyses are very beneficial for climate research, because they combine a good spatial and temporal coverage with a homogeneous and consistent method of calculation. However, atmospheric reanalyses are still imperfect sources of flux information due to shortcomings in model variables, model parameterizations, assimilation methods, sampling of observations, and quality of observations. Therefore, assessments of the errors and the usefulness of air-sea flux data sets from atmospheric (re-)analyses are relevant contributions to the quantitative study of climate variability. Currently, much research is aimed at assessing the quality and usefulness of the reanalysed air-sea fluxes. Work in this thesis intends to contribute to this assessment. In particular, it attempts to answer three relevant questions. The first question is: What is the best parameterization of the momentum flux? A comparison is made of the wind stress parameterization of the ERA15 reanalysis, the currently generated ERA40 reanalysis and the wind stress measurements over the open ocean. The comparison reveals some clear differences in the mean drag coefficient. In addition, this study has indicated that progress has been made from the ERA15 to the ERA40 reanalyses by replacing the model parameterization with a constant Charnock parameter with one which depends on the sea state. The second research question is whether comparison of the response of an ocean model with ocean observations can be exploited to assess the quality of air-sea fluxes of the ERA15 reanalysis. To answer this question in a systematic way an inverse modeling approach is adopted using a four-dimensional variational data assimilation (4DVAR) scheme. Firstly, the functioning of the 4DVAR system is demonstrated from identical twin experiments. These experiments reveal that in the equatorial Pacific, a large reduction in wind-stress and upper-ocean temperature misfits can be achieved using an assimilation time window of eight weeks. It is concluded that the usefulness of inverse ocean modeling technique for global surface flux assessment is limited. The main merit of the developed ocean 4DVAR scheme will be to diagnose errors in the ocean analyses of the ocean model. The last research question is: are the ERA15 fluxes useful for the study of regional patterns of climate variability? The climate mode of consideration is the Antarctic Circumpolar Wave. This study stresses the importance to have the right climatological forcing conditions to assess time scales of climate variability and it confirms the usefulness of ERA15 air-sea fluxes as ocean model forcing fields to study climate variability on the interannual time scale.

Epidemiology of Pneumocystis carinii pneumonia in an era of effective prophylaxis: the relative contribution of non-adherence and drug failure.

PubMed

Lundberg, B E; Davidson, A J; Burman, W J

2000-11-10

To determine the relative contribution of patient non-adherence, provider failure to prescribe prophylaxis, and drug failure to the continued occurrence of Pneumocystis carinii pneumonia (PCP), and to determine correlates of non-adherence. Retrospective case-control study. Patients with confirmed or presumptive PCP from May 1995 to September 1997 who had at least 6 months of prior HIV care (cases) were compared to controls matched for initial CD4 cell count and date of initial HIV care. The incidence of PCP declined by 85% in the 28 months of the study. Of the 118 cases of PCP identified, 59 (50%) were in HIV care for > 6 months prior to PCP diagnosis. In a multivariate logistic regression model, risk factors for PCP among patients in HIV care were patient non-adherence [odds ratio (OR), 12.4; 95% confidence interval (CI), 6.4-23.5], use of prophylaxis other than trimethoprim-sulfamethoxazole (OR, 27.0; 95% CI, 13.8-52.9), and absence of antiretroviral use (OR, 7.5; 95% CI, 4.5-12.5). Provider non-adherence occurred in one out of 59 cases (2%), and five out of 106 controls (5%). Of the patients who developed PCP on prophylaxis, 18 cases (30%) appeared due to drug failure; there were no cases of apparent drug failure among patients on trimethoprim-sulfamethoxazole. In multivariate analysis, non-adherence was more common among patients of non-white race, those with a history of injecting drug use, and those with active substance abuse or psychiatric illness. Patient non-adherence was the most common reason for the occurrence of PCP among patients in HIV care; provider non-adherence was uncommon. Drug failure occurred only among patients on prophylaxis other than trimethoprim-sulfamethoxazole.

Hydroxyurea is associated with lower prevalence of albuminuria in adults with sickle cell disease.

PubMed

Laurin, Louis-Philippe; Nachman, Patrick H; Desai, Payal C; Ataga, Kenneth I; Derebail, Vimal K

2014-06-01

Albuminuria is an early manifestation of sickle cell nephropathy. Prior small case series suggests benefit of hydroxyurea in reducing albuminuria, with a similar trend noted in pediatric studies. We aimed to comprehensively evaluate hydroxyurea use and prevalence of albuminuria in adult sickle cell patients. We performed a cross-sectional study of 149 adult patients followed between 2000 and 2011 in a comprehensive sickle cell clinic. All patients were assessed for albuminuria either by direct measurement or by urinary chemical strip (dipstick) testing. Urinary albumin-to-creatinine ratios (UACRs) were available for 112 patients. Hydroxyurea exposure was defined as ≥3 months of therapy before the assessment of albuminuria. Albuminuria was defined as either UACR ≥30 mg/g or ≥1+ proteinuria on two separate dipsticks. We constructed a multivariate logistic regression model to assess the association between hydroxyurea and albuminuria. The prevalence of albuminuria was lower among patients on hydroxyurea (34.7 versus 55.4%; P = 0.01) as was median albumin excretion (17.9 versus 40.5 mg/g; P = 0.04). In multivariate analysis, hydroxyurea was associated with a lower likelihood of albuminuria (odds ratio 0.28, 95% CI: 0.11-0.75, P = 0.01), adjusting for age, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker use, tricuspid regurgitant jet velocity, hypertension and acute chest syndrome. In our population of sickle cell patients, those using hydroxyurea were less than one-third as likely to exhibit albuminuria. Hydroxyurea use may prevent development of overt nephropathy or the progression of sickle cell disease nephropathy to end-stage renal disease, and its use for this indication merits further investigation. © The Author 2013. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Incidence and Clinical Features of Early Stent Thrombosis in the Era of New P2y12 Inhibitors (PLATIS-2)

PubMed Central

Asher, Elad; Abu-Much, Arsalan; Goldenberg, Ilan; Segev, Amit; Sabbag, Avi; Mazin, Israel; Shlezinger, Meital; Atar, Shaul; Zahger, Doron; Polak, Arthur; Beigel, Roy; Matetzky, Shlomi

2016-01-01

Early stent thrombosis (EST) (≤ 30 days after stent implantation) is a relatively rare but deleterious complication of percutaneous coronary intervention (PCI). Administration of newer P2Y12 inhibitors (prasugrel and ticagrelor) combined with aspirin has been shown to reduce the incidence of sub-acute and late stent thrombosis, compared with clopidogrel. We investigated the “real life” incidence of EST in patients from a large acute coronary syndrome (ACS) national registry, where newer P2Y12 inhibitors are widely used. Patients were derived from the ACS Israeli Survey (ACSIS), conducted during 2006, 2008, 2010 and 2013. Major adverse cardiac events (MACE) at 30days were defined as all-cause death, recurrent ACS, EST and stroke.Of the 4717 ACS patients who underwent PCI and stenting, 83% received clopidogrel and 17% newer P2Y12 inhibitors. The rate of EST was similar in both groups (1.7% in the newer P2Y12 inhibitor group vs. 1.4% in the clopidogrel-treated patients, p = 0.42). Results were consistent after multivariate analysis (adjusted HR = 1.06 [p = 0.89]). MACE occurred in 6.4% in the newer P2Y12 inhibitor group compared with 9.2% in the clopidogrel group (P<0.01). However, multivariate logistic regression modeling showed that treatment with newer P2Y12 inhibitors was not significantly associated with the secondary endpoint of MACE when compared with clopidogrel therapy [OR = 1.26 95%CI (0.93–1.73), P = 0.136]. The incidence of "real life" EST at 1month is relatively low, and appears to be similar in patients who receive newer P2Y12 inhibitors as well as in those who receive clopidogrel. PMID:27310147

Incidence and Clinical Features of Early Stent Thrombosis in the Era of New P2y12 Inhibitors (PLATIS-2).

PubMed

Asher, Elad; Abu-Much, Arsalan; Goldenberg, Ilan; Segev, Amit; Sabbag, Avi; Mazin, Israel; Shlezinger, Meital; Atar, Shaul; Zahger, Doron; Polak, Arthur; Beigel, Roy; Matetzky, Shlomi

2016-01-01

Early stent thrombosis (EST) (≤ 30 days after stent implantation) is a relatively rare but deleterious complication of percutaneous coronary intervention (PCI). Administration of newer P2Y12 inhibitors (prasugrel and ticagrelor) combined with aspirin has been shown to reduce the incidence of sub-acute and late stent thrombosis, compared with clopidogrel. We investigated the "real life" incidence of EST in patients from a large acute coronary syndrome (ACS) national registry, where newer P2Y12 inhibitors are widely used. Patients were derived from the ACS Israeli Survey (ACSIS), conducted during 2006, 2008, 2010 and 2013. Major adverse cardiac events (MACE) at 30days were defined as all-cause death, recurrent ACS, EST and stroke.Of the 4717 ACS patients who underwent PCI and stenting, 83% received clopidogrel and 17% newer P2Y12 inhibitors. The rate of EST was similar in both groups (1.7% in the newer P2Y12 inhibitor group vs. 1.4% in the clopidogrel-treated patients, p = 0.42). Results were consistent after multivariate analysis (adjusted HR = 1.06 [p = 0.89]). MACE occurred in 6.4% in the newer P2Y12 inhibitor group compared with 9.2% in the clopidogrel group (P<0.01). However, multivariate logistic regression modeling showed that treatment with newer P2Y12 inhibitors was not significantly associated with the secondary endpoint of MACE when compared with clopidogrel therapy [OR = 1.26 95%CI (0.93-1.73), P = 0.136]. The incidence of "real life" EST at 1month is relatively low, and appears to be similar in patients who receive newer P2Y12 inhibitors as well as in those who receive clopidogrel.

An appraisal of drug development timelines in the Era of precision oncology

PubMed Central

Jardim, Denis Leonardo; Schwaederle, Maria; Hong, David S.; Kurzrock, Razelle

2016-01-01

The effects of incorporating a biomarker-based (personalized or precision) selection strategy on drug development timelines for new oncology drugs merit investigation. Here we accessed documents from the Food and Drug Administration (FDA) database for anticancer agents approved between 09/1998 and 07/2014 to compare drugs developed with and without a personalized strategy. Sixty-three drugs were included (28 [44%] personalized and 35 [56%] non-personalized). No differences in access to FDA-expedited programs were observed between personalized and non-personalized drugs. A personalized approach for drug development was associated with faster clinical development (Investigational New Drug [IND] to New Drug Application [NDA] submission; median = 58.8 months [95% CI 53.8–81.8] vs. 93.5 months [95% CI 73.9–112.9], P =.001), but a similar approval time (NDA submission to approval; median=6.0 months [95% CI 5.5–8.4] vs. 6.1 months [95% CI 5.9–8.3], P = .756) compared to a non-personalized strategy. In the multivariate model, class of drug stratified by personalized status (targeted personalized vs. targeted non-personalized vs. cytotoxic) was the only independent factor associated with faster total time of clinical drug development (clinical plus approval phase, median = 64.6 vs 87.1 vs. 112.7 months [cytotoxic], P = .038). Response rates (RR) in early trials were positively correlated with RR in registration trials (r = 0.63, P = <.001), and inversely associated with total time of drug development (r = −0.29, P = .049). In conclusion, targeted agents were developed faster than cytotoxic agents. Shorter times to approval were associated, in multivariate analysis, with a biomarker-based clinical development strategy. PMID:27419632

A comparison of daily precipitation metrics downscaled using SDSM and WRF + WRFDA models over the Iberian Peninsula.

NASA Astrophysics Data System (ADS)

José González-Rojí, Santos; Wilby, Robert L.; Sáenz, Jon; Ibarra-Berastegi, Gabriel

2017-04-01

Downscaling via the Statistical DownScaling Model (SDSM) version 5.2 and two different configurations of the dynamical WRF model (with and without 3DVAR data assimilation) was evaluated for the estimation of daily precipitation over 21 sites across the Iberian Peninsula during the period 2010-2014. Six different strategies were used to calibrate the SDSM model. These options cover (1) use of NCEP/NCAR R1 Reanalysis and (2) ERA Interim data for downscaling predictor variables calibrated with data from periods (3) 1948-2009 (NCEP/NCAR R1) and (4) 1979-2009 (NCEP/NCAR R1 and ERA Interim). Additionally, for the ERA Interim case, two different grid resolutions have been used, (5) 2.5° and (6) 0.75°. On the other side, for the NCEP/NCAR R1 case, only the 2.5° resolution has been used. Configuring the SDSM model in this way allows testing the sensitivity of the results to different origins of the predictors, fit to different calibration periods and use of different reanalysis resolutions. On the other hand, ERA Interim data at the highest resolution was used as the initial/boundary conditions to run WRF simulations with a 15 km x 15 km horizontal resolution over the Iberian Peninsula, for two different configurations. The first experiment (N) was run using the same configuration typically used for numerical downscaling, with information being fed through the boundaries of the domain. The second experiment (D) was run using 3DVAR data assimilation at 00UTC, 06UTC, 12UTC and 18UTC. In both cases, WRF simulations were run over the period 2009-2014, using the first year (2009) as spin-up for the soil model. Results from the WRF N and D runs and comparable SDSM set up for the period 2010-2014 were evaluated using observations from ECA and E-OBS datasets. In each case, model skill was assessed using seven daily precipitation metrics (absolute mean, wet-day intensity, 90th percentile, maximum 5-day total, maximum number of consecutive dry days, fraction of total from heavy events and number of heavy events defined here as values over the threshold of 90th percentile. Our results show that the SDSM model improves its behaviour when using predictors from the ERA Interim Reanalysis. Improvements are even more impressive when using the 0.75° resolution for ERA Interim. Better results than using WRF D are obtained with this configuration of the SDSM model for mean precipitation and precipitation intensity. Overall, the analysis reveals the extent to which the skill of SDSM can be improved through judicious choice of downscaling predictor source, grid resolution and calibration period. Moreover, the computationally efficient SDSM tool can achieve comparable skill to WRF over a range of precipitation metrics and the contrasting rainfall regimes of the Iberian Peninsula.

Modeling surface response of the Greenland Ice Sheet to interglacial climate

NASA Astrophysics Data System (ADS)

Rau, Dominik; Rogozhina, Irina

2013-04-01

We present a new parameterization of surface mass balance (SMB) of the Greenland Ice Sheet (GIS) under interglacial climate conditions validated against recent satellite observations on a regional scale. Based on detailed analysis of the modeled surface melting and refreezing rates, we conclude that the existing SMB parameterizations fail to capture either spatial pattern or amplitude of the observed surface response of the GIS. This is due to multiple simplifying assumptions adopted by the majority of modeling studies within the frame of the positive degree day method. Modeled spatial distribution of surface melting is found to be highly sensitive to a choice of daily temperature standard deviation (SD) and degree-day factors, which are generally assumed to have uniform distribution across the entire Greenland region. However, the use of uniform SD distribution and the range of commonly used SD values are absolutely unsupported by the ERA-40 and ERA-Interim climate data. In this region, SD distribution is highly inhomogeneous and characterized by low amplitudes during the summer months in the areas where most surface ice melting occurs. In addition, the use of identical degree day factors on both the eastern and western slopes of the GIS results in overestimation of surface runoff along the western coast of Greenland and significant underestimation along its eastern coast. Our approach is to make use of (i) spatially and seasonally variable SDs derived from ERA-40 and ERA-Interim time series, and (ii) spatially variable degree-day factors, measured across Greenland, Arctic Canada, Norway, Spitsbergen and Iceland. We demonstrate that the new approach is extremely efficient for modeling the evolution of the GIS during the observational period and the entire Holocene interglacial.

Global trends and variability in integrated water vapour from ground-based GPS data and atmospheric models

NASA Astrophysics Data System (ADS)

Bock, Olivier; Parracho, Ana; Bastin, Sophie; Hourdin, Frededic; Mellul, Lidia

2016-04-01

A high-quality, consistent, global, long-term dataset of integrated water vapour (IWV) was produced from Global Positioning System (GPS) measurements at more than 400 sites over the globe among which 120 sites have more than 15 years of data. The GPS delay data were converted to IWV using surface pressure and weighted mean temperature estimates from ERA-Interim reanalysis. A two-step screening method was developed to detect and remove outliers in the IWV data. It is based on: 1) GPS data processing information and delay formal errors, and 2) intercomparison with ERA-Interim reanalysis data. The GPS IWV data are also homogenized to correct for offsets due to instrumental changes and other unknown factors. The differential homogenization method uses ERA-Interim IWV as a reference. The resulting GPS data are used to document the mean distribution, the global trends and the variability of IWV over the period 1995-2010, and are analysed in coherence with precipitation and surface temperature data (from observations and ERA-Interim reanalysis). These data are also used to assess global climate model simulations extracted from the IPCC AR5 archive. Large coherent spatial patterns of moistening and drying are evidenced but significant discrepancies are also seen between GPS measurements, reanalysis and climate models in various regions. In terms of variability, the monthly mean anomalies are intercompared. The temporal correlation between GPS and the climate model simulations is overall quite small but the spatial variation of the magnitude of the anomalies is globally well simulated. GPS IWV data prove to be useful to validate global climate model simulations and highlight deficiencies in their representation of the water cycle.

Experiential Avoidance Mediates the Association between Emotion Regulation Abilities and Loneliness.

PubMed

Shi, Rui; Zhang, Shilei; Zhang, Qianwen; Fu, Shaoping; Wang, Zhenhong

2016-01-01

Experiential avoidance (EA) involves the unwillingness to remain in contact with aversive experiences such as painful feelings, thoughts, and emotions. EA is often associated with the development and maintenance of emotional problems. Since loneliness is characterized by negative emotions such as sadness and pessimism, which is often linked to emotional problems, this study aims to test the mediating effects of EA on the relationship between emotion regulation abilities (ERA) and loneliness in a sample of Chinese adults. Five hundred undergraduates completed questionnaires measuring EA (Acceptance and Action Questionnaire; AAQ-Ⅱ), ERA (Failure-relate action orientation; Action Control Scale, ACS-90) and loneliness (UCLA Loneliness Scale). Structural equation modeling showed that EA fully-mediated the relationship between ERA and loneliness. The findings suggest EA is a key mechanism in explaining why people with high ERA are prone to feeling lower levels of loneliness. In particular, these findings have important implications for designing effective psychological interventions for loneliness.

Cytoreductive Nephrectomy in Elderly Patients with Metastatic Renal Cell Carcinoma in the Targeted Therapy Era.

PubMed

Uprety, Dipesh; Bista, Amir; Smith, Angela L; Vallatharasu, Yazhini; Marinier, David E

2018-05-01

The role of cytoreductive nephrectomy (CN) for metastatic renal cell cancer (mRCC) is not clearly understood after the approval of targeted therapies, particularly in the elderly population. The aim of this study was to compare survivals between patients who did and did not receive CN. The SEER-18 database was utilized in order to identify elderly patients with mRCC to compare overall survival (OS) and cancer-specific survival (CSS) between patients who did or did not receive CN between February 2006 and 2012. Kaplan-Meier curve and log rank test were used to compare OS and CSS between these two arms. Cox proportional hazard model was used for multivariate analysis and statistical significance was defined as p≤0.05. There was a significant survival benefit for those who received CN compared to those who did not receive CN (median OS: 18 months vs. 4 months, p<0.001; median CSS: 21 months vs. 5 months, p<0.001). CN offered significant survival benefit, even in elderly patients with metastatic renal cell cancer. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Exploring the Determinants of the Perceived Risk of Food Allergies in Canada

PubMed Central

Harrington, Daniel W.; Elliott, Susan J.; Clarke, Ann E.; Ben-Shoshan, Moshe; Godefroy, Samuel

2012-01-01

Food allergies are emerging health risks in much of the Western world, and some evidence suggests prevalence is increasing. Despite lacking scientific consensus around prevalence and management, policies and regulations are being implemented in public spaces (e.g., schools). These policies have been criticized as extreme in the literature, in the media, and by the non-allergic population. Backlash appears to be resulting from different perceptions of risk between different groups. This article uses a recently assembled national dataset (n = 3,666) to explore how Canadians perceive the risks of food allergy. Analyses revealed that almost 20% self-report having an allergic person in the household, while the average respondent estimated the prevalence of food allergies in Canada to be 30%. Both of these measures overestimate the true clinically defined prevalence (7.5%), indicating an inflated public understanding of the risks of food allergies. Seventy percent reported food allergies to be substantial risks to the Canadian population. Multivariate logistic regression models revealed important determinants of risk perception including demographic, experience-based, attitudinal, and regional predictors. Results are discussed in terms of understanding emerging health risks in the post-industrial era, and implications for both policy and risk communication. PMID:23172987

Genetic Complexity of Episodic Memory: A Twin Approach to Studies of Aging

PubMed Central

Kremen, William S.; Spoon, Kelly M.; Jacobson, Kristen C.; Vasilopoulos, Terrie; McCaffery, Jeanne M.; Panizzon, Matthew S.; Franz, Carol E.; Vuoksimaa, Eero; Xian, Hong; Rana, Brinda K.; Toomey, Rosemary; McKenzie, Ruth; Lyons, Michael J.

2016-01-01

Episodic memory change is a central issue in cognitive aging, and understanding that process will require elucidation of its genetic underpinnings. A key limiting factor in genetically informed research on memory has been lack of attention to genetic and phenotypic complexity, as if “memory is memory” and all well-validated assessments are essentially equivalent. Here we applied multivariate twin models to data from late-middle-aged participants in the Vietnam Era Twin Study of Aging to examine the genetic architecture of 6 measures from 3 standard neuropsychological tests: the California Verbal Learning Test-2, and Wechsler Memory Scale-III Logical Memory (LM) and Visual Reproductions (VR). An advantage of the twin method is that it can estimate the extent to which latent genetic influences are shared or independent across different measures before knowing which specific genes are involved. The best-fitting model was a higher order common pathways model with a heritable higher order general episodic memory factor and three test-specific subfactors. More importantly, substantial genetic variance was accounted for by genetic influences that were specific to the latent LM and VR subfactors (28% and 30%, respectively) and independent of the general factor. Such unique genetic influences could partially account for replication failures. Moreover, if different genes influence different memory phenotypes, they could well have different age-related trajectories. This approach represents an important step toward providing critical information for all types of genetically informative studies of aging and memory. PMID:24956007

Multivariate Models of Parent-Late Adolescent Gender Dyads: The Importance of Parenting Processes in Predicting Adjustment

ERIC Educational Resources Information Center

McKinney, Cliff; Renk, Kimberly

2008-01-01

Although parent-adolescent interactions have been examined, relevant variables have not been integrated into a multivariate model. As a result, this study examined a multivariate model of parent-late adolescent gender dyads in an attempt to capture important predictors in late adolescents' important and unique transition to adulthood. The sample…

Structural Equation Models in a Redundancy Analysis Framework With Covariates.

PubMed

Lovaglio, Pietro Giorgio; Vittadini, Giorgio

2014-01-01

A recent method to specify and fit structural equation modeling in the Redundancy Analysis framework based on so-called Extended Redundancy Analysis (ERA) has been proposed in the literature. In this approach, the relationships between the observed exogenous variables and the observed endogenous variables are moderated by the presence of unobservable composites, estimated as linear combinations of exogenous variables. However, in the presence of direct effects linking exogenous and endogenous variables, or concomitant indicators, the composite scores are estimated by ignoring the presence of the specified direct effects. To fit structural equation models, we propose a new specification and estimation method, called Generalized Redundancy Analysis (GRA), allowing us to specify and fit a variety of relationships among composites, endogenous variables, and external covariates. The proposed methodology extends the ERA method, using a more suitable specification and estimation algorithm, by allowing for covariates that affect endogenous indicators indirectly through the composites and/or directly. To illustrate the advantages of GRA over ERA we propose a simulation study of small samples. Moreover, we propose an application aimed at estimating the impact of formal human capital on the initial earnings of graduates of an Italian university, utilizing a structural model consistent with well-established economic theory.

Did the Women's Colleges Founded in the Progressive Era Represent a New Model? Connecticut College for Women as a Case Study

ERIC Educational Resources Information Center

Marthers, Paul P.

2013-01-01

Connecticut College for Women and its Progressive Era sister colleges (Douglass, Simmons, Skidmore, and William Smith) are distinctive for the prominent vocational and service elements each college had in its original mission and curriculum. Historians however have often left Connecticut College for Women out of the story of American women's…

Early respiratory acidosis is a new risk factor for pneumonia after lung resection.

PubMed

Planquette, Benjamin; Le Pimpec-Barthes, Françoise; Trinquart, Ludovic; Meyer, Guy; Riquet, Marc; Sanchez, Olivier

2012-03-01

Postoperative pneumonia (POP) is a life-threatening complication of lung resection (LR). Its risk factors, bacteriological profile and outcome are not well known. The aims of this study were to describe the outcome and causal bacteria and to identify risk factors for POP. We reviewed all cases admitted to intensive care after LR. Clinical parameters, operative and postoperative data were recorded. POP was suspected on the basis of fever, radiographic infiltrate, and either leucocytosis or purulent sputum. The diagnosis was confirmed by culture of a respiratory sample. Risk factors for POP were identified by univariate and multivariate analysis. We included 159 patients in this study. POP was diagnosed in 23 patients (14.4%) and was associated with a higher hospital mortality rate (30% versus 5%, P = 0.0007) and a longer hospital stay. Members of the Enterobacteriaceae and Pseudomonas species were the most frequently identified pathogens. Early respiratory acidosis (ERA; OR, 2.94; 95% CI, 1.1-8.1), blood transfusion (OR, 3.8; 95% CI, 1.1-13.1), bilobectomy (OR, 7.26; 95% CI, 1.2-43.1) and smoking history (OR, 1.84; 95% CI, 1.1-3) were identified as independent risk factors. ERA may be a risk factor for POP and could serve as a target for therapeutic interventions.

A multivariate model and statistical method for validating tree grade lumber yield equations

Treesearch

Donald W. Seegrist

1975-01-01

Lumber yields within lumber grades can be described by a multivariate linear model. A method for validating lumber yield prediction equations when there are several tree grades is presented. The method is based on multivariate simultaneous test procedures.

Mapping as a visual health communication tool: promises and dilemmas.

PubMed

Parrott, Roxanne; Hopfer, Suellen; Ghetian, Christie; Lengerich, Eugene

2007-01-01

In the era of evidence-based public health promotion and planning, the use of maps as a form of evidence to communicate about the multiple determinants of cancer is on the rise. Geographic information systems and mapping technologies make future proliferation of this strategy likely. Yet disease maps as a communication form remain largely unexamined. This content analysis considers the presence of multivariate information, credibility cues, and the communication function of publicly accessible maps for cancer control activities. Thirty-six state comprehensive cancer control plans were publicly available in July 2005 and were reviewed for the presence of maps. Fourteen of the 36 state cancer plans (39%) contained map images (N = 59 static maps). A continuum of map inter activity was observed, with 10 states having interactive mapping tools available to query and map cancer information. Four states had both cancer plans with map images and interactive mapping tools available to the public on their Web sites. Of the 14 state cancer plans that depicted map images, two displayed multivariate data in a single map. Nine of the 10 states with interactive mapping capability offered the option to display multivariate health risk messages. The most frequent content category mapped was cancer incidence and mortality, with stage at diagnosis infrequently available. The most frequent communication function served by the maps reviewed was redundancy, as maps repeated information contained in textual forms. The social and ethical implications for communicating about cancer through the use of visual geographic representations are discussed.

Multivariate Boosting for Integrative Analysis of High-Dimensional Cancer Genomic Data

PubMed Central

Xiong, Lie; Kuan, Pei-Fen; Tian, Jianan; Keles, Sunduz; Wang, Sijian

2015-01-01

In this paper, we propose a novel multivariate component-wise boosting method for fitting multivariate response regression models under the high-dimension, low sample size setting. Our method is motivated by modeling the association among different biological molecules based on multiple types of high-dimensional genomic data. Particularly, we are interested in two applications: studying the influence of DNA copy number alterations on RNA transcript levels and investigating the association between DNA methylation and gene expression. For this purpose, we model the dependence of the RNA expression levels on DNA copy number alterations and the dependence of gene expression on DNA methylation through multivariate regression models and utilize boosting-type method to handle the high dimensionality as well as model the possible nonlinear associations. The performance of the proposed method is demonstrated through simulation studies. Finally, our multivariate boosting method is applied to two breast cancer studies. PMID:26609213

Integrated presentation of ecological risk from multiple stressors

NASA Astrophysics Data System (ADS)

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-10-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Integrated presentation of ecological risk from multiple stressors.

PubMed

Goussen, Benoit; Price, Oliver R; Rendal, Cecilie; Ashauer, Roman

2016-10-26

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Improvement of long-term outcomes in pancreatic cancer and its associated factors within the gemcitabine era: a collaborative retrospective multicenter clinical review of 1,082 patients.

PubMed

Kuroda, Taira; Kumagi, Teru; Yokota, Tomoyuki; Seike, Hirotaka; Nishiyama, Mari; Imai, Yusuke; Inada, Nobu; Shibata, Naozumi; Imamine, Satoshi; Okada, Shin-ichi; Koizumi, Mitsuhito; Yamanishi, Hirofumi; Azemoto, Nobuaki; Miyaike, Jiro; Tanaka, Yoshinori; Tatsukawa, Haruka; Utsunomiya, Hiroki; Ohno, Yoshinori; Miyake, Teruki; Hirooka, Masashi; Furukawa, Shinya; Abe, Masanori; Ikeda, Yoshiou; Matsuura, Bunzo; Hiasa, Yoichi; Onji, Morikazu

2013-08-31

Although the outcomes of pancreatic cancer have been improved by gemcitabine, the changes in its characteristics and long-term outcomes within the gemcitabine era remain unclear. This study was conducted to identify clinical characteristics of pancreatic cancer patients within the gemcitabine era. A retrospective chart review was performed at 10 centers for 1,248 consecutive patients who were ever considered to have a diagnosis of pancreatic cancer between 2001 and 2010. Data collected included demographics, diagnosis date, clinical stage, treatment, and outcome 1,082 patients met the inclusion criteria and were analyzed further. The chi-square test, Student's t-test, and Mann-Whitney U-test were used for statistical analysis. Outcomes were analyzed using the Kaplan-Meier method and Cox proportional hazards regression. Differences in survival analyses were determined using the log-rank test. The distribution of clinical stages was: I, 2.2% II, 3.4% III, 13% IVa, 27% and IVb, 55%. Chemotherapy alone was administered to 42% of patients and 17% underwent resection. The 1-, 3-, and 5-year survival rates were 39%, 13%, and 6.9%, respectively. The median survival time was 257 days, but differed considerably among treatments and clinical stages. Demographics, distribution of clinical stage, and cause of death did not differ between groups A (2001-2005, n=406) and B (2006-2010, n=676). However, group B included more patients who underwent chemotherapy (P<0.0001) and fewer treated with best supportive care (P=0.0004), mirroring improvements in this group's long-term outcomes (P=0.0063). Finally, factors associated with long-term outcomes derived from multivariate analysis were clinical stage (P<0.0001), location of the tumor (P=0.0294) and treatments (surgery, chemotherapy) (<0.0001). Long-term outcomes in pancreatic cancer has improved even within the gemcitabine era, suggesting the importance of offering chemotherapy to patients previously only considered for best supportive care. Most patients are still diagnosed at an advanced stage, making clinical strategy development for diagnosing pancreatic cancer at earlier stages essential.

Model construction of “earning money by taking photos”

NASA Astrophysics Data System (ADS)

Yang, Jingmei

2018-03-01

In the era of information, with the increasingly developed network, “to earn money by taking photos” is a self-service model under the mobile Internet. The user downloads the APP, registers as a member of the APP, and then takes a task that needs to take photographs from the APP and earns the reward of the task on the APP. The article uses the task data and membership information data of an already completed project, including the member’s location and reputation value. On the basis of reasonable assumption, the data was processed with the MATLAB, SPSS and Excel software. This article mainly studied problems of the function relationship between the task performance, task position (GPS latitude and GPS longitude) and task price of users, analyzed the project’s task pricing rules and the reasons why the task is not completed, and applied multivariate regression function and GeoQ software to analyze the data, studied the task pricing rules, applied the chart method to solve the complex data, clear and easy to understand, and also reality simulation is applied to analyze why the tasks are not completed. Also, compared with the previous program, a new task pricing program is designed for the project to obtain the confidence level by means of the SPSS software, to estimate the reasonable range of the task pricing, predict and design a new pricing program on the reasonable price range.

Integrating ecological risk assessments across levels of organization using the Franklin-Noss model of biodiversity

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

Brugger, K.E.; Tiebout, H.M. III

1994-12-31

Wildlife toxicologists pioneered methodologies for assessing ecological risk to nontarget species. Historically, ecological risk assessments (ERAS) focused on a limited array of species and were based on a relatively few population-level endpoints (mortality, reproduction). Currently, risk assessment models are becoming increasingly complex that factor in multi-species interactions (across trophic levels) and utilize an increasingly diverse number of ecologically significant endpoints. This trend suggests the increasing importance of safeguarding not only populations of individual species, but also the overall integrity of the larger biotic systems that support them. In this sense, ERAs are in alignment with Conservation Biology, an applied sciencemore » of ecological knowledge used to conserve biodiversity. A theoretical conservation biology model could be incorporated in ERAs to quantify impacts to biodiversity (structure, function or composition across levels of biological organization). The authors suggest that the Franklin-Noss model for evaluating biodiversity, with its nested, hierarchical approach, may provide a suitable paradigm for assessing and integrating the ecological risk that chemical contaminants pose to biological systems from the simplest levels (genotypes, individual organisms) to the most complex levels of organization (communities and ecosystems). The Franklin-Noss model can accommodate the existing ecotoxicological database and, perhaps more importantly, indicate new areas in which critical endpoints should be identified and investigated.« less

[Public health conceptual models and paradigms].

PubMed

Hernández-Girón, Carlos; Orozco-Núñez, Emanuel; Arredondo-López, Armando

2012-01-01

The epidemiological transition model proposed by Omhran at the beginning of the 1970s (decreased fecundity rate and increased life expectancy), together with modifications in lifestyles and diet, showed increased mortality due to chronically degenerative causes. This essay thus discusses and makes a comparative analysis of some currents of thought, taking as its common thread an analysis of epidemiological change identified in different eras or stages and relationships with some public health models or conceptual frameworks. Discussing public health paradigms leads to a historical recapitulation of conceptual models ranging from magical-religious conceptions to ecological and socio-medical models. M. Susser proposed 3 eras in this discipline's evolution in his speech on the future of the epidemiology. The epidemiological changes analysed through different approaches constitute elements of analysis that all models discussed in this essay include to delimit the contributions and variables so determining them.

Cost analysis of enhanced recovery after surgery in microvascular breast reconstruction.

PubMed

Oh, Christine; Moriarty, James; Borah, Bijan J; Mara, Kristin C; Harmsen, William S; Saint-Cyr, Michel; Lemaine, Valerie

2018-06-01

Enhanced recovery after surgery (ERAS) pathways have been shown in multiple surgical specialties to decrease hospital length of stay (LOS) after surgery. ERAS in breast reconstruction has been found to decrease hospital LOS and inpatient opioid use. ERAS protocols can facilitate a patient's recovery and can potentially increase the quality of care while decreasing costs. A standardized ERAS pathway was developed through multidisciplinary collaboration. It addressed all phases of surgical care for patients undergoing free-flap breast reconstruction utilizing an abdominal donor site. In this retrospective cohort study, clinical variables associated with hospitalization costs for patients who underwent free-flap breast reconstruction with the ERAS pathway were compared with those of historical controls, termed traditional recovery after surgery (TRAS). All patients included in the study underwent surgery between September 2010 and September 2014. Predicted costs of the study groups were compared using generalized linear modeling. A total of 200 patients were analyzed: 82 in the ERAS cohort and 118 in the TRAS cohort. Clinical variables that were identified to potentially affect costs were found to have a statistically significant difference between groups and included unilateral versus bilateral procedures (p = 0.04) and the need for postoperative blood transfusion (p = 0.03). The cost regression analysis on the two cohorts was adjusted for these significant variables. Adjusted mean costs of patients with ERAS were found to be $4,576 lesser than those of the TRAS control group ($38,688 versus $43,264). Implementation of the ERAS pathway was associated with significantly decreased costs when compared to historical controls. There has been a healthcare focus toward prudent resource allocation, which dictates the need for plastic surgeons to recognize economic evaluation of clinical practice. The ERAS pathway can increase healthcare accountability by improving quality of care while simultaneously decreasing the costs associated with autologous breast reconstruction. Copyright © 2018 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

PubMed Central

Galván-Tejada, Carlos E.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L.

2017-01-01

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions. PMID:28216571

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis.

PubMed

Galván-Tejada, Carlos E; Zanella-Calzada, Laura A; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L

2017-02-14

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

Detecting spatial regimes in ecosystems | Science Inventory ...

EPA Pesticide Factsheets

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate spatial models of excess crash frequency at area level: case of Costa Rica.

PubMed

Aguero-Valverde, Jonathan

2013-10-01

Recently, areal models of crash frequency have being used in the analysis of various area-wide factors affecting road crashes. On the other hand, disease mapping methods are commonly used in epidemiology to assess the relative risk of the population at different spatial units. A natural next step is to combine these two approaches to estimate the excess crash frequency at area level as a measure of absolute crash risk. Furthermore, multivariate spatial models of crash severity are explored in order to account for both frequency and severity of crashes and control for the spatial correlation frequently found in crash data. This paper aims to extent the concept of safety performance functions to be used in areal models of crash frequency. A multivariate spatial model is used for that purpose and compared to its univariate counterpart. Full Bayes hierarchical approach is used to estimate the models of crash frequency at canton level for Costa Rica. An intrinsic multivariate conditional autoregressive model is used for modeling spatial random effects. The results show that the multivariate spatial model performs better than its univariate counterpart in terms of the penalized goodness-of-fit measure Deviance Information Criteria. Additionally, the effects of the spatial smoothing due to the multivariate spatial random effects are evident in the estimation of excess equivalent property damage only crashes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Climate Data Guide - Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)

NASA Technical Reports Server (NTRS)

Cullather, Richard; Bosilovich, Michael

2017-01-01

The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) is a global atmospheric reanalysis produced by the NASA Global Modeling and Assimilation Office (GMAO). It spans the satellite observing era from 1980 to the present. The goals of MERRA-2 are to provide a regularly-gridded, homogeneous record of the global atmosphere, and to incorporate additional aspects of the climate system including trace gas constituents (stratospheric ozone), and improved land surface representation, and cryospheric processes. MERRA-2 is also the first satellite-era global reanalysis to assimilate space-based observations of aerosols and represent their interactions with other physical processes in the climate system. The inclusion of these additional components are consistent with the overall objectives of an Integrated Earth System Analysis (IESA). MERRA-2 is intended to replace the original MERRA product, and reflects recent advances in atmospheric modeling and data assimilation. Modern hyperspectral radiance and microwave observations, along with GPS-Radio Occultation and NASA ozone datasets are now assimilated in MERRA-2. Much of the structure of the data files remains the same in MERRA-2. While the original MERRA data format was HDF-EOS, the MERRA-2 supplied binary data format is now NetCDF4 (with lossy compression to save space).

A Robust Bayesian Approach for Structural Equation Models with Missing Data

ERIC Educational Resources Information Center

Lee, Sik-Yum; Xia, Ye-Mao

2008-01-01

In this paper, normal/independent distributions, including but not limited to the multivariate t distribution, the multivariate contaminated distribution, and the multivariate slash distribution, are used to develop a robust Bayesian approach for analyzing structural equation models with complete or missing data. In the context of a nonlinear…

Role of protein farnesylation events in the ABA-mediated regulation of the Pinoresinol-Lariciresinol Reductase 1 (LuPLR1) gene expression and lignan biosynthesis in flax (Linum usitatissimum L.).

PubMed

Corbin, Cyrielle; Decourtil, Cédric; Marosevic, Djurdjica; Bailly, Marlène; Lopez, Tatiana; Renouard, Sullivan; Doussot, Joël; Dutilleul, Christelle; Auguin, Daniel; Giglioli-Guivarc'h, Nathalie; Lainé, Eric; Lamblin, Frédéric; Hano, Christophe

2013-11-01

A Linum usitatissimum LuERA1 gene encoding a putative ortholog of the ERA1 (Enhanced Response to ABA 1) gene of Arabidopsis thaliana (encoding the beta subunit of a farnesyltransferase) was analyzed in silico and for its expression in flax. The gene and the protein sequences are highly similar to other sequences already characterized in plants and all the features of a farnesyltransferase were detected. Molecular modeling of LuERA1 protein confirmed its farnesyltransferase nature. LuERA1 is expressed in the vegetative organs and also in the outer seedcoat of the flaxseed, where it could modulate the previously observed regulation operated by ABA on lignan synthesis. This effect could be mediated by the regulation of the transcription of a key gene for lignan synthesis in flax, the LuPLR1 gene, encoding a pinoresinol lariciresinol reductase. The positive effect of manumycin A, a specific inhibitor of farnesyltransferase, on lignan biosynthesis in flax cell suspension systems supports the hypothesis of the involvement of such an enzyme in the negative regulation of ABA action. In Arabidopsis, ERA1 is able to negatively regulate the ABA effects and the mutant era1 has an enhanced sensitivity to ABA. When expressed in an Arabidopsis cell suspension (heterologous system) LuERA1 is able to reverse the effect of the era1 mutation. RNAi experiments in flax targeting the farnesyltransferase β-subunit encoded by the LuERA1 gene led to an increase LuPLR1 expression level associated with an increased content of lignan in transgenic calli. Altogether these results strongly suggest a role of the product of this LuERA1 gene in the ABA-mediated upregulation of lignan biosynthesis in flax cells through the activation of LuPLR1 promoter. This ABA signaling pathway involving ERA1 probably acts through the ABRE box found in the promoter sequence of LuPLR1, a key gene for lignan synthesis in flax, as demonstrated by LuPLR1 gene promoter-reporter experiments in flax cells using wild type and mutated promoter sequences. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

The Risk of Hepatocellular Carcinoma Among Individuals With Acquired Immunodeficiency Syndrome in the United States

PubMed Central

Sahasrabuddhe, Vikrant V.; Shiels, Meredith S.; McGlynn, Katherine A.; Engels, Eric A.

2014-01-01

BACKGROUND Hepatocellular carcinoma (HCC) is a concern among individuals with human immunodeficiency virus (HIV) infection and acquired immunodeficiency syndrome (AIDS). METHODS The authors analyzed population-based registry linkage data from the US HIV/AIDS Cancer Match Study (1980–2009) to examine the risk and trends of HCC among individuals with AIDS. Standardized incidence ratios (SIRs) were used to measure HCC risk relative to the general population, and Poisson regression was used to calculate incidence rate ratios (RR) comparing incidence among individuals with AIDS. People with AIDS were categorized according to their HIV risk group into high and low hepatitis C virus (HCV) prevalence groups based on their HIV transmission risk category. RESULTS Among 615,150 individuals with AIDS, HCC risk was elevated almost 4 times compared with the risk in the general population (N = 366; SIR, 3.8; 95% confidence interval, 3.5–4.3). Although HCC incidence increased steadily across calendar periods (Ptrend < .0001; adjusted for sex and age), the excess risk in individuals with AIDS compared with the general population remained somewhat constant (SIRs range, 3.5–3.9) between the monotherapy/dual therapy era (1990–1995) and the recent highly active antiretroviral therapy era (2001–2009). In a multivariate model adjusting for sex, race/ethnicity, and attained calendar period, HCC incidence increased with advancing age (Ptrend < .0001) and was associated with HIV risk groups with a known higher prevalence of HCV (adjusted RR, 2.2; 95% confidence interval, 1.8–2.8). CONCLUSIONS HCC incidence in individuals with AIDS has increased over time despite improved HIV treatment regimens, likely reflecting prolonged survival with chronic liver disease. The high incidence in older adults suggests that this cancer will increase in importance with aging of the HIV-infected population. PMID:22736272

Thrombotic microangiopathy after allogeneic stem cell transplantation in the era of reduced-intensity conditioning: The incidence is not reduced.

PubMed

Shimoni, Avichai; Yeshurun, Moshe; Hardan, Izhar; Avigdor, Abraham; Ben-Bassat, Isaac; Nagler, Arnon

2004-07-01

Thrombotic microangiopathy (TMA) is one of the most severe complications of stem cell transplantation (SCT). Endothelial cell injury caused by the toxic effects of high-dose chemoradiotherapy is likely the primary event in pathogenesis. The incidence, clinical settings, and risk factors for TMA in the era of nonmyeloablative conditioning have not been well defined. The data on 147 consecutive SCTs in a single center were collected, and patients with TMA were identified. Patient characteristics, response to therapy, and outcome were recorded, and risk factors were determined. TMA occurred in 22 of 147 transplantations, with a projected incidence of 20% +/- 4%. TMA occurred in 3 clinical settings: classic multifactorial TMA, TMA associated with severe hepatic graft-versus-host disease (GVHD), and TMA associated with second SCT, with a projected incidence of 8% +/- 3%, 73% +/- 14%, and 70% +/- 16% of patients at risk, respectively. TMA occurred after 23% +/- 6% of nonmyeloablative and 16% +/- 5% of myeloablative conditioning regimens (not significant). Univariate analysis determined SCT from unrelated donors, SCT during advanced or active disease, second SCT within 6 months of a prior SCT, and acute GVHD as risk factors for TMA. The last 2 factors remained significant in a multivariate model. Thirty-two percent of patients responded to therapy. The peri-TMA mortality rate was 68% +/- 10%. Six patients had diffuse alveolar hemorrhage complicating TMA. SCT-associated TMA is a relatively common complication with unsatisfactory therapy and grim prognosis. Fludarabine-based nonmyeloablative conditioning does not confer a lesser risk for TMA. This observation may relate to the selective use of these regimens in elderly and heavily pretreated patients or to the lack of reduction of GVHD with these regimens, and fludarabine itself may be involved in causing endothelial damage. Further exploration of novel preventive and therapeutic measurements is required in high-risk settings.

Decreasing urinary organophosphate pesticide metabolites among pregnant women and their offspring in Jerusalem: Impact of regulatory restrictions on agricultural organophosphate pesticides use?

PubMed

Ein-Mor, Eliana; Ergaz-Shaltiel, Zivanit; Berman, Tamar; Göen, Thomas; Natsheh, Juma; Ben-Chetrit, Avraham; Haimov-Kochman, Ronit; Calderon-Margalit, Ronit

2018-06-01

Maternal urinary levels of dialkyl phosphate (DAP) metabolites of organophosphate pesticides (OP) during pregnancy are associated with adverse outcomes in the offspring. Between 2012 and 2014, eighteen active OP ingredients were restricted or banned in Israel for agricultural use. We aimed to study trends of urinary DAP metabolites among pregnant women and their offspring in the era of the new regulations. Pregnant women were recruited at 11-18 weeks of gestation and provided spot urine samples (n = 273). Soon after birth, neonatal urine samples were collected (n = 107). All urine specimens analyzed for DAP metabolites. Trends in DAP metabolites were tested using Mann-Kendall trend statistic (M-K S) and linear regression models were constructed to estimate the association between calendar period and DAP levels between September 2012 and March 2016. Over the study period, median maternal ∑DAP levels decreased from 248 nmol/L to 148 nmol/L. Time of recruitment was associated with a statistically significant decrease in DAP metabolites, which remained significant after multivariate adjustment. Overall, the results for the analysis of before and after June 2014 showed a significant decrease in ∑DAP of -0.198 log10 nmol/L (95%CI: -0.311,-0.084) which corresponds with a decrease of 36.6% in ∑DAP. A similar trend was found for DAP metabolites in neonatal urine. Compared to other studies, pregnant women in Jerusalem had higher ∑DAP levels, even at the end of the study period. We observed significant reductions in maternal and neonatal DAP urinary levels during the period of 2012-2016. Regulations restricting agricultural use of OP seem to be effective in reducing population exposure to OP, in an era when residential use of OP is banned. Copyright © 2018 Elsevier GmbH. All rights reserved.

Multi-centennial upper-ocean heat content reconstruction using online data assimilation

NASA Astrophysics Data System (ADS)

Perkins, W. A.; Hakim, G. J.

2017-12-01

The Last Millennium Reanalysis (LMR) provides an advanced paleoclimate ensemble data assimilation framework for multi-variate climate field reconstructions over the Common Era. Although reconstructions in this framework with full Earth system models remain prohibitively expensive, recent work has shown improved ensemble reconstruction validation using computationally inexpensive linear inverse models (LIMs). Here we leverage these techniques in pursuit of a new multi-centennial field reconstruction of upper-ocean heat content (OHC), synthesizing model dynamics with observational constraints from proxy records. OHC is an important indicator of internal climate variability and responds to planetary energy imbalances. Therefore, a consistent extension of the OHC record in time will help inform aspects of low-frequency climate variability. We use the Community Climate System Model version 4 (CCSM4) and Max Planck Institute (MPI) last millennium simulations to derive the LIMs, and the PAGES2K v.2.0 proxy database to perform annually resolved reconstructions of upper-OHC, surface air temperature, and wind stress over the last 500 years. Annual OHC reconstructions and uncertainties for both the global mean and regional basins are compared against observational and reanalysis data. We then investigate differences in dynamical behavior at decadal and longer time scales between the reconstruction and simulations in the last-millennium Coupled Model Intercomparison Project version 5 (CMIP5). Preliminary investigation of 1-year forecast skill for an OHC-only LIM shows largely positive spatial grid point local anomaly correlations (LAC) with a global average LAC of 0.37. Compared to 1-year OHC persistence forecast LAC (global average LAC of 0.30), the LIM outperforms the persistence forecasts in the tropical Indo-Pacific region, the equatorial Atlantic, and in certain regions near the Antarctic Circumpolar Current. In other regions, the forecast correlations are less than the persistence case but still positive overall.

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

ERIC Educational Resources Information Center

Wood, Terry M.; Safrit, Margaret J.

1987-01-01

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

Application of multivariate Gaussian detection theory to known non-Gaussian probability density functions

NASA Astrophysics Data System (ADS)

Schwartz, Craig R.; Thelen, Brian J.; Kenton, Arthur C.

1995-06-01

A statistical parametric multispectral sensor performance model was developed by ERIM to support mine field detection studies, multispectral sensor design/performance trade-off studies, and target detection algorithm development. The model assumes target detection algorithms and their performance models which are based on data assumed to obey multivariate Gaussian probability distribution functions (PDFs). The applicability of these algorithms and performance models can be generalized to data having non-Gaussian PDFs through the use of transforms which convert non-Gaussian data to Gaussian (or near-Gaussian) data. An example of one such transform is the Box-Cox power law transform. In practice, such a transform can be applied to non-Gaussian data prior to the introduction of a detection algorithm that is formally based on the assumption of multivariate Gaussian data. This paper presents an extension of these techniques to the case where the joint multivariate probability density function of the non-Gaussian input data is known, and where the joint estimate of the multivariate Gaussian statistics, under the Box-Cox transform, is desired. The jointly estimated multivariate Gaussian statistics can then be used to predict the performance of a target detection algorithm which has an associated Gaussian performance model.

A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution.

PubMed

Inouye, David; Yang, Eunho; Allen, Genevera; Ravikumar, Pradeep

2017-01-01

The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have been far less popular. Yet, real-world high-dimensional count-valued data found in word counts, genomics, and crime statistics, for example, exhibit rich dependencies, and motivate the need for multivariate distributions that can appropriately model this data. We review multivariate distributions derived from the univariate Poisson, categorizing these models into three main classes: 1) where the marginal distributions are Poisson, 2) where the joint distribution is a mixture of independent multivariate Poisson distributions, and 3) where the node-conditional distributions are derived from the Poisson. We discuss the development of multiple instances of these classes and compare the models in terms of interpretability and theory. Then, we empirically compare multiple models from each class on three real-world datasets that have varying data characteristics from different domains, namely traffic accident data, biological next generation sequencing data, and text data. These empirical experiments develop intuition about the comparative advantages and disadvantages of each class of multivariate distribution that was derived from the Poisson. Finally, we suggest new research directions as explored in the subsequent discussion section.

Cosmology with a stiff matter era

NASA Astrophysics Data System (ADS)

Chavanis, Pierre-Henri

2015-11-01

We consider the possibility that the Universe is made of a dark fluid described by a quadratic equation of state P =K ρ2 , where ρ is the rest-mass density and K is a constant. The energy density ɛ =ρ c2+K ρ2 is the sum of two terms: a rest-mass term ρ c2 that mimics "dark matter" (P =0 ) and an internal energy term u =K ρ2=P that mimics a "stiff fluid" (P =ɛ ) in which the speed of sound is equal to the speed of light. In the early universe, the internal energy dominates and the dark fluid behaves as a stiff fluid (P ˜ɛ , ɛ ∝a-6). In the late universe, the rest-mass energy dominates and the dark fluid behaves as pressureless dark matter (P ≃0 , ɛ ∝a-3). We provide a simple analytical solution of the Friedmann equations for a universe undergoing a stiff matter era, a dark matter era, and a dark energy era due to the cosmological constant. This analytical solution generalizes the Einstein-de Sitter solution describing the dark matter era, and the Λ CDM model describing the dark matter era and the dark energy era. Historically, the possibility of a primordial stiff matter era first appeared in the cosmological model of Zel'dovich where the primordial universe is assumed to be made of a cold gas of baryons. A primordial stiff matter era also occurs in recent cosmological models where dark matter is made of relativistic self-gravitating Bose-Einstein condensates (BECs). When the internal energy of the dark fluid mimicking stiff matter is positive, the primordial universe is singular like in the standard big bang theory. It expands from an initial state with a vanishing scale factor and an infinite density. We consider the possibility that the internal energy of the dark fluid is negative (while, of course, its total energy density is positive), so that it mimics anti-stiff matter. This happens, for example, when the BECs have an attractive self-interaction with a negative scattering length. In that case, the primordial universe is nonsingular and bouncing like in loop quantum cosmology. At t =0 , the scale factor is finite and the energy density is equal to zero. The universe first has a phantom behavior where the energy density increases with the scale factor, then a normal behavior where the energy density decreases with the scale factor. For the sake of generality, we consider a cosmological constant of arbitrary sign. When the cosmological constant is positive, the Universe asymptotically reaches a de Sitter regime where the scale factor increases exponentially rapidly with time. This can account for the accelerating expansion of the Universe that we observe at present. When the cosmological constant is negative (anti-de Sitter), the evolution of the Universe is cyclic. Therefore, depending on the sign of the internal energy of the dark fluid and on the sign of the cosmological constant, we obtain analytical solutions of the Friedmann equations describing singular and nonsingular expanding, bouncing, or cyclic universes.

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

What we learned from the Dust Bowl: lessons in science, policy, and adaptation.

PubMed

McLeman, Robert A; Dupre, Juliette; Berrang Ford, Lea; Ford, James; Gajewski, Konrad; Marchildon, Gregory

2014-01-01

This article provides a review and synthesis of scholarly knowledge of Depression-era droughts on the North American Great Plains, a time and place known colloquially as the Dust Bowl era or the Dirty Thirties. Recent events, including the 2008 financial crisis, severe droughts in the US corn belt, and the release of a popular documentary film, have spawned a resurgence in public interest in the Dust Bowl. Events of the Dust Bowl era have also proven in recent years to be of considerable interest to scholars researching phenomena related to global environmental change, including atmospheric circulation, drought modeling, land management, institutional behavior, adaptation processes, and human migration. In this review, we draw out common themes in terms of not only what natural and social scientists have learned about the Dust Bowl era itself, but also how insights gained from the study of that period are helping to enhance our understanding of climate-human relations more generally.

On the improvement of wave and storm surge hindcasts by downscaled atmospheric forcing: application to historical storms

NASA Astrophysics Data System (ADS)

Bresson, Émilie; Arbogast, Philippe; Aouf, Lotfi; Paradis, Denis; Kortcheva, Anna; Bogatchev, Andrey; Galabov, Vasko; Dimitrova, Marieta; Morvan, Guillaume; Ohl, Patrick; Tsenova, Boryana; Rabier, Florence

2018-04-01

Winds, waves and storm surges can inflict severe damage in coastal areas. In order to improve preparedness for such events, a better understanding of storm-induced coastal flooding episodes is necessary. To this end, this paper highlights the use of atmospheric downscaling techniques in order to improve wave and storm surge hindcasts. The downscaling techniques used here are based on existing European Centre for Medium-Range Weather Forecasts reanalyses (ERA-20C, ERA-40 and ERA-Interim). The results show that the 10 km resolution data forcing provided by a downscaled atmospheric model gives a better wave and surge hindcast compared to using data directly from the reanalysis. Furthermore, the analysis of the most extreme mid-latitude cyclones indicates that a four-dimensional blending approach improves the whole process, as it assimilates more small-scale processes in the initial conditions. Our approach has been successfully applied to ERA-20C (the 20th century reanalysis).

Experimental identification of closely spaced modes using NExT-ERA

NASA Astrophysics Data System (ADS)

Hosseini Kordkheili, S. A.; Momeni Massouleh, S. H.; Hajirezayi, S.; Bahai, H.

2018-01-01

This article presents a study on the capability of the time domain OMA method, NExT-ERA, to identify closely spaced structural dynamic modes. A survey in the literature reveals that few experimental studies have been conducted on the effectiveness of the NExT-ERA methodology in case of closely spaced modes specifically. In this paper we present the formulation for NExT-ERA. This formulation is then implemented in an algorithm and a code, developed in house to identify the modal parameters of different systems using their generated time history data. Some numerical models are firstly investigated to validate the code. Two different case studies involving a plate with closely spaced modes and a pulley ring with greater extent of closeness in repeated modes are presented. Both structures are excited by random impulses under the laboratory condition. The resulting time response acceleration data are then used as input in the developed code to extract modal parameters of the structures. The accuracy of the results is checked against those obtained from experimental tests.

Diverse data supports the transition of filamentous fungal model organisms into the post-genomics era

DOE PAGES

McCluskey, Kevin; Baker, Scott E.

2017-02-17

As model organisms filamentous fungi have been important since the beginning of modern biological inquiry and have benefitted from open data since the earliest genetic maps were shared. From early origins in simple Mendelian genetics of mating types, parasexual genetics of colony colour, and the foundational demonstration of the segregation of a nutritional requirement, the contribution of research systems utilising filamentous fungi has spanned the biochemical genetics era, through the molecular genetics era, and now are at the very foundation of diverse omics approaches to research and development. Fungal model organisms have come from most major taxonomic groups although Ascomycetemore » filamentous fungi have seen the most major sustained effort. In addition to the published material about filamentous fungi, shared molecular tools have found application in every area of fungal biology. Likewise, shared data has contributed to the success of model systems. Furthermore, the scale of data supporting research with filamentous fungi has grown by 10 to 12 orders of magnitude. From genetic to molecular maps, expression databases, and finally genome resources, the open and collaborative nature of the research communities has assured that the rising tide of data has lifted all of the research systems together.« less

Diverse data supports the transition of filamentous fungal model organisms into the post-genomics era

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

McCluskey, Kevin; Baker, Scott E.

As model organisms filamentous fungi have been important since the beginning of modern biological inquiry and have benefitted from open data since the earliest genetic maps were shared. From early origins in simple Mendelian genetics of mating types, parasexual genetics of colony colour, and the foundational demonstration of the segregation of a nutritional requirement, the contribution of research systems utilising filamentous fungi has spanned the biochemical genetics era, through the molecular genetics era, and now are at the very foundation of diverse omics approaches to research and development. Fungal model organisms have come from most major taxonomic groups although Ascomycetemore » filamentous fungi have seen the most major sustained effort. In addition to the published material about filamentous fungi, shared molecular tools have found application in every area of fungal biology. Likewise, shared data has contributed to the success of model systems. Furthermore, the scale of data supporting research with filamentous fungi has grown by 10 to 12 orders of magnitude. From genetic to molecular maps, expression databases, and finally genome resources, the open and collaborative nature of the research communities has assured that the rising tide of data has lifted all of the research systems together.« less

Objective tropical cyclone extratropical transition detection in high-resolution reanalysis and climate model data

DOE PAGES

Zarzycki, Colin M.; Thatcher, Diana R.; Jablonowski, Christiane

2017-01-22

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high-resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable-resolution Community Atmosphere Model (CAM) at two different resolutions (DX 55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, DX 38 km), and the ERA-Interim Reanalysis (ERA-I, DX 80 km).more » The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA-I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold-core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.« less

The Modern Era of Research in Biosphere Atmosphere Interactions

NASA Astrophysics Data System (ADS)

Fung, I. Y.; Sellers, P. J.; Randall, D. A.; Tucker, C. J.; Field, C. B.; Berry, J. A.; Ustin, S.

2015-12-01

Dr. Diane Wickland, the Program Scientist for NASA's EOS InterDisciplinary Science (IDS), encouraged and nurtured the growth of the field of global ecology and eco-climatology. This talk reviews the developments in, and integration of, theory, satellite and field observations that enabled the global modeling of biosphere-atmosphere interactions. Emphasis will be placed on the advances made during the EOS era in global datasets and global coupled carbon-climate models. The advances include functional classifications of the land surface using the NDVI, a global terrestrial carbon-energy-water model, and the greening of the CSU GCM. An equally important achievement of the EOS-IDS program is a new generation of multi-disciplinary scientists who are now leaders in the field.

Semiparametric Thurstonian Models for Recurrent Choices: A Bayesian Analysis

ERIC Educational Resources Information Center

Ansari, Asim; Iyengar, Raghuram

2006-01-01

We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…

An Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction

NASA Technical Reports Server (NTRS)

Juang, J. N.; Pappa, R. S.

1985-01-01

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

Dynamics in a Maximally Symmetric Universe

NASA Astrophysics Data System (ADS)

Bewketu, Asnakew

2016-03-01

Our present understanding of the evolution of the universe relies upon the Friedmann- Robertson- Walker cosmological models. This model is so successful that it is now being considered as the Standard Model of Cosmology. So in this work we derive the Fried- mann equations using the Friedmann-Robertson-Walker metric together with Einstein field equation and then we give a simple method to reduce Friedmann equations to a second order linear differential equation when it is supplemented with a time dependent equation of state. Furthermore, as illustrative examples, we solve this equation for some specific time dependent equation of states. And also by using the Friedmann equations with some time dependent equation of state we try to determine the cosmic scale factor(the rate at which the universe expands) and age of the Friedmann universe, for the matter dominated era, radiation dominated era and for both matter and radiation dominated era by considering different cases. We have finally discussed the observable quantities that can be evidences for the accelerated expansion of the Friedmann universe. I would like to acknowledge Addis Ababa University for its financial and material support to my work on the title mentioned above.

Integrated presentation of ecological risk from multiple stressors

PubMed Central

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-01-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic. PMID:27782171

Estimation and Validation of \\delta18O Global Distribution with Rayleigh-type two Dimensional Isotope Circulation Model

NASA Astrophysics Data System (ADS)

Yoshimura, K.; Oki, T.; Ohte, N.; Kanae, S.; Ichiyanagi, K.

2004-12-01

A simple water isotope circulation model on a global scale that includes a Rayleigh equation and the use of _grealistic_h external meteorological forcings estimates short-term variability of precipitation 18O. The results are validated by Global Network of Isotopes in Precipitation (GNIP) monthly observations and by daily observations at three sites in Thailand. This good agreement highlights the importance of large scale transport and mixing of vapor masses as a control factor for spatial and temporal variability of precipitation isotopes, rather than in-cloud micro processes. It also indicates the usefulness of the model and the isotopes observation databases for evaluation of two-dimensional atmospheric water circulation fields in forcing datasets. In this regard, two offline simulations for 1978-1993 with major reanalyses, i.e. NCEP and ERA15, were implemented, and the results show that, over Europe ERA15 better matched observations at both monthly and interannual time scales, mainly owing to better precipitation fields in ERA15, while in the tropics both produced similarly accurate isotopic fields. The isotope analyses diagnose accuracy of two-dimensional water circulation fields in datasets with a particular focus on precipitation processes.

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

Zarzycki, Colin M.; Thatcher, Diana R.; Jablonowski, Christiane

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high-resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable-resolution Community Atmosphere Model (CAM) at two different resolutions (DX 55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, DX 38 km), and the ERA-Interim Reanalysis (ERA-I, DX 80 km).more » The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA-I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold-core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.« less

Error Covariance Penalized Regression: A novel multivariate model combining penalized regression with multivariate error structure.

PubMed

Allegrini, Franco; Braga, Jez W B; Moreira, Alessandro C O; Olivieri, Alejandro C

2018-06-29

A new multivariate regression model, named Error Covariance Penalized Regression (ECPR) is presented. Following a penalized regression strategy, the proposed model incorporates information about the measurement error structure of the system, using the error covariance matrix (ECM) as a penalization term. Results are reported from both simulations and experimental data based on replicate mid and near infrared (MIR and NIR) spectral measurements. The results for ECPR are better under non-iid conditions when compared with traditional first-order multivariate methods such as ridge regression (RR), principal component regression (PCR) and partial least-squares regression (PLS). Copyright © 2018 Elsevier B.V. All rights reserved.

Effects of Covariance Heterogeneity on Three Procedures for Analyzing Multivariate Repeated Measures Designs.

ERIC Educational Resources Information Center

Vallejo, Guillermo; Fidalgo, Angel; Fernandez, Paula

2001-01-01

Estimated empirical Type I error rate and power rate for three procedures for analyzing multivariate repeated measures designs: (1) the doubly multivariate model; (2) the Welch-James multivariate solution (H. Keselman, M. Carriere, a nd L. Lix, 1993); and (3) the multivariate version of the modified Brown-Forsythe procedure (M. Brown and A.…

Analysis of the variability of the North Atlantic eddy-driven jet stream in CMIP5

NASA Astrophysics Data System (ADS)

Iqbal, Waheed; Leung, Wai-Nang; Hannachi, Abdel

2017-09-01

The North Atlantic eddy-driven jet is a dominant feature of extratropical climate and its variability is associated with the large-scale changes in the surface climate of midlatitudes. Variability of this jet is analysed in a set of General Circulation Models (GCMs) from the Coupled Model Inter-comparison Project phase-5 (CMIP5) over the North Atlantic region. The CMIP5 simulations for the 20th century climate (Historical) are compared with the ERA40 reanalysis data. The jet latitude index, wind speed and jet persistence are analysed in order to evaluate 11 CMIP5 GCMs and to compare them with those from CMIP3 integrations. The phase of mean seasonal cycle of jet latitude and wind speed from historical runs of CMIP5 GCMs are comparable to ERA40. The wind speed mean seasonal cycle by CMIP5 GCMs is overestimated in winter months. A positive (negative) jet latitude anomaly in historical simulations relative to ERA40 is observed in summer (winter). The ensemble mean of jet latitude biases in historical simulations of CMIP3 and CMIP5 with respect to ERA40 are -2.43° and -1.79° respectively. Thus indicating improvements in CMIP5 in comparison to the CMIP3 GCMs. The comparison of historical and future simulations of CMIP5 under RCP4.5 and RCP8.5 for the period 2076-2099, shows positive anomalies in the jet latitude implying a poleward shifted jet. The results from the analysed models offer no specific improvements in simulating the trimodality of the eddy-driven jet.

Synchronization of world economic activity

NASA Astrophysics Data System (ADS)

Groth, Andreas; Ghil, Michael

2017-12-01

Common dynamical properties of business cycle fluctuations are studied in a sample of more than 100 countries that represent economic regions from all around the world. We apply the methodology of multivariate singular spectrum analysis (M-SSA) to identify oscillatory modes and to detect whether these modes are shared by clusters of phase- and frequency-locked oscillators. An extension of the M-SSA approach is introduced to help analyze structural changes in the cluster configuration of synchronization. With this novel technique, we are able to identify a common mode of business cycle activity across our sample, and thus point to the existence of a world business cycle. Superimposed on this mode, we further identify several major events that have markedly influenced the landscape of world economic activity in the postwar era.

Synchronization of world economic activity.

PubMed

Groth, Andreas; Ghil, Michael

2017-12-01

Common dynamical properties of business cycle fluctuations are studied in a sample of more than 100 countries that represent economic regions from all around the world. We apply the methodology of multivariate singular spectrum analysis (M-SSA) to identify oscillatory modes and to detect whether these modes are shared by clusters of phase- and frequency-locked oscillators. An extension of the M-SSA approach is introduced to help analyze structural changes in the cluster configuration of synchronization. With this novel technique, we are able to identify a common mode of business cycle activity across our sample, and thus point to the existence of a world business cycle. Superimposed on this mode, we further identify several major events that have markedly influenced the landscape of world economic activity in the postwar era.

Added value of high-resolution regional climate model over the Bohai Sea and Yellow Sea areas

NASA Astrophysics Data System (ADS)

Li, Delei; von Storch, Hans; Geyer, Beate

2016-04-01

Added value from dynamical downscaling has long been a crucial and debatable issue in regional climate studies. A 34 year (1979-2012) high-resolution (7 km grid) atmospheric hindcast over the Bohai Sea and the Yellow Sea (BYS) has been performed using COSMO-CLM (CCLM) forced by ERA-Interim reanalysis data (ERA-I). The accuracy of CCLM in surface wind reproduction and the added value of dynamical downscaling to ERA-I have been investigated through comparisons with the satellite data (including QuikSCAT Level2B 12.5 km version 3 (L2B12v3) swath data and MODIS images) and in situ observations, with adoption of quantitative metrics and qualitative assessment methods. The results revealed that CCLM has a reliable ability to reproduce the regional wind characteristics over the BYS areas. Over marine areas, added value to ERA-I has been detected in the coastal areas with complex coastlines and orography. CCLM was better able to represent light and moderate winds but has even more added value for strong winds relative to ERA-I. Over land areas, the high-resolution CCLM hindcast can add value to ERA-I in reproducing wind intensities and direction, wind probability distribution and extreme winds mainly at mountain areas. With respect to atmospheric processes, CCLM outperforms ERA-I in resolving detailed temporal and spatial structures for phenomena of a typhoon and of a coastal atmospheric front; CCLM generates some orography related phenomena such as a vortex street which is not captured by ERA-I. These added values demonstrate the utility of the 7-km-resolution CCLM for regional and local climate studies and applications. The simulation was constrained with adoption of spectral nudging method. The results may be different when simulations are considered, which are not constrained by spectral nudging.

Meta-analysis of self-reported health symptoms in 1990–1991 Gulf War and Gulf War-era veterans

PubMed Central

Maule, Alexis L; Janulewicz, Patricia A; Sullivan, Kimberly A; Krengel, Maxine H; Yee, Megan K; McClean, Michael; White, Roberta F

2018-01-01

Objectives Across diverse groups of Gulf War (GW) veterans, reports of musculoskeletal pain, cognitive dysfunction, unexplained fatigue, chronic diarrhoea, rashes and respiratory problems are common. GW illness is a condition resulting from GW service in veterans who report a combination of these symptoms. This study integrated the GW literature using meta-analytical methods to characterise the most frequently reported symptoms occurring among veterans who deployed to the 1990–1991 GW and to better understand the magnitude of ill health among GW-deployed veterans compared with non-deployed GW-era veterans. Design Meta-analysis. Methods Literature databases were searched for peer-reviewed studies published from January 1990 to May 2017 reporting health symptom frequencies in GW-deployed veterans and GW-era control veterans. Self-reported health symptom data were extracted from 21 published studies. A binomial-normal meta-analytical model was used to determine pooled prevalence of individual symptoms in GW-deployed veterans and GW-era control veterans and to calculate combined ORs of health symptoms comparing GW-deployed veterans and GW-era control veterans. Results GW-deployed veterans had higher odds of reporting all 56 analysed symptoms compared with GW-era controls. Odds of reporting irritability (OR 3.21, 95% CI 2.28 to 4.52), feeling detached (OR 3.59, 95% CI 1.83 to 7.03), muscle weakness (OR 3.19, 95% CI 2.73 to 3.74), diarrhoea (OR 3.24, 95% CI 2.51 to 4.17) and rash (OR 3.18, 95% CI 2.47 to 4.09) were more than three times higher among GW-deployed veterans compared with GW-era controls. Conclusions The higher odds of reporting mood-cognition, fatigue, musculoskeletal, gastrointestinal and dermatological symptoms among GW-deployed veterans compared with GW-era controls indicates these symptoms are important when assessing GW veteran health status. PMID:29440208

ERA-MIN: The European network (ERA-NET) on non-energy raw materials

NASA Astrophysics Data System (ADS)

vidal, o.; christmann, p.; Bol, d.; Goffé, b.; Groth, m.; Kohler, e.; Persson Nelson, k.; Schumacher, k.

2012-04-01

Non-energy raw materials are vital for the EU's economy, and for the development of environmentally friendly technologies. The EU is the world's largest consumers of non-energy minerals, but it remains dependent on the importation of many metals, as its domestic production is limited to about 3% of world production. We will present the project ERA-MIN, which is an ERA-NET on the Industrial Handling of Raw Materials for European industries, financially supported by the European Commission. The main objectives of ERA-MIN are: 1) Mapping and Networking: interconnecting the members of the currently fragmented European mineral resources research area, to the aim of fostering convergence of public research programs, industry, research institutes, academia and the European Commission, 2) Coordinating: establishing a permanent mechanism for planning and coordination of the European non-energy mineral raw materials research community (ENERC). 3) Roadmapping: defining the most important scientific and technological challenges that should be supported by the EU and its state members, 4) Programming: designing a Joint European Research Programme model and implementating it into a call for proposals open to academic and industrial research. The topics of interest in ERA-MIN are the primary continental and marine resources, the secondary resources and their related technologies, substitution and material efficiency, along with transversal topics such as environmental impact, public policy support, mineral intelligence, and public education and teaching. Public scientific research is very central in the scope of the ERA-MIN activity, whose consortium is indeed lead by a public organisation of fundamental research. Thus, universities and public research organisations are warmly invited to play an active role in defining the scientific questions and challenges that shall determine the European Raw Materials Roadmap and should be addressed by joint programming at the European scale. The various levels of possible involvement in ERA-MIN for the interested stakeholders will be presented.

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.

1998-01-01

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

REMO poor man's reanalysis

NASA Astrophysics Data System (ADS)

Ries, H.; Moseley, C.; Haensler, A.

2012-04-01

Reanalyses depict the state of the atmosphere as a best fit in space and time of many atmospheric observations in a physically consistent way. By essentially solving the data assimilation problem in a very accurate manner, reanalysis results can be used as reference for model evaluation procedures and as forcing data sets for different model applications. However, the spatial resolution of the most common and accepted reanalysis data sets (e.g. JRA25, ERA-Interim) ranges from approximately 124 km to 80 km. This resolution is too coarse to simulate certain small scale processes often associated with extreme events. In addition, many models need higher resolved forcing data ( e.g. land-surface models, tools for identifying and assessing hydrological extremes). Therefore we downscaled the ERA-Interim reanalysis over the EURO-CORDEX-Domain for the time period 1989 to 2008 to a horizontal resolution of approximately 12 km. The downscaling is performed by nudging REMO-simulations to lower and lateral boundary conditions of the reanalysis, and by re-initializing the model every 24 hours ("REMO in forecast mode"). In this study the three following questions will be addressed: 1.) Does the REMO poor man's reanalysis meet the needs (accuracy, extreme value distribution) in validation and forcing? 2.) What lessons can be learned about the model used for downscaling? As REMO is used as a pure downscaling procedure, any systematic deviations from ERA-Interim result from poor process modelling but not from predictability limitations. 3.) How much small scale information generated by the downscaling model is lost with frequent initializations? A comparison to a simulation that is performed in climate mode will be presented.

A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research.

PubMed

Meeker, Daniella; Jiang, Xiaoqian; Matheny, Michael E; Farcas, Claudiu; D'Arcy, Michel; Pearlman, Laura; Nookala, Lavanya; Day, Michele E; Kim, Katherine K; Kim, Hyeoneui; Boxwala, Aziz; El-Kareh, Robert; Kuo, Grace M; Resnic, Frederic S; Kesselman, Carl; Ohno-Machado, Lucila

2015-11-01

Centralized and federated models for sharing data in research networks currently exist. To build multivariate data analysis for centralized networks, transfer of patient-level data to a central computation resource is necessary. The authors implemented distributed multivariate models for federated networks in which patient-level data is kept at each site and data exchange policies are managed in a study-centric manner. The objective was to implement infrastructure that supports the functionality of some existing research networks (e.g., cohort discovery, workflow management, and estimation of multivariate analytic models on centralized data) while adding additional important new features, such as algorithms for distributed iterative multivariate models, a graphical interface for multivariate model specification, synchronous and asynchronous response to network queries, investigator-initiated studies, and study-based control of staff, protocols, and data sharing policies. Based on the requirements gathered from statisticians, administrators, and investigators from multiple institutions, the authors developed infrastructure and tools to support multisite comparative effectiveness studies using web services for multivariate statistical estimation in the SCANNER federated network. The authors implemented massively parallel (map-reduce) computation methods and a new policy management system to enable each study initiated by network participants to define the ways in which data may be processed, managed, queried, and shared. The authors illustrated the use of these systems among institutions with highly different policies and operating under different state laws. Federated research networks need not limit distributed query functionality to count queries, cohort discovery, or independently estimated analytic models. Multivariate analyses can be efficiently and securely conducted without patient-level data transport, allowing institutions with strict local data storage requirements to participate in sophisticated analyses based on federated research networks. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

SPACEHAB missions as pathfinders for ISS services development

NASA Astrophysics Data System (ADS)

Hamill, Doris; Jackson, Kenneth; Mirra, Carlo

2003-01-01

SPACEHAB, Inc. has established a commercial business model for providing access to space. The model, based on private initiative and investment, has offered "turn key" access to space including both launch and integration and operations services. Some features of this business model should be applied directly to providing service in the ISS era: offering packaged service at a fixed price; customer focus; private investment as the basis for offering services; and efficient and continually improving customer service. But International Space Station (ISS) will pose challenges that have not been pioneered in the STS era: a new base of customers must be developed; on-orbit hardware will be more difficult to modify; access to ISS is controlled by government space agencies. These problems will tax the ingenuity of those who wish to provide services in space on a commercial business model.

An assessment of historical Antarctic precipitation and temperature trend using CMIP5 models and reanalysis datasets

NASA Astrophysics Data System (ADS)

Tang, Malcolm S. Y.; Chenoli, Sheeba Nettukandy; Samah, Azizan Abu; Hai, Ooi See

2018-03-01

The study of Antarctic precipitation has attracted a lot of attention recently. The reliability of climate models in simulating Antarctic precipitation, however, is still debatable. This work assess the precipitation and surface air temperature (SAT) of Antarctica (90 oS to 60 oS) using 49 Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models and the European Centre for Medium-range Weather Forecasts "Interim" reanalysis (ERA-Interim); the National Centers for Environmental Prediction Climate Forecast System Reanalysis (CFSR); the Japan Meteorological Agency 55-year Reanalysis (JRA-55); and the Modern Era Retrospective-analysis for Research and Applications (MERRA) datasets for 1979-2005 (27 years). For precipitation, the time series show that the MERRA and JRA-55 have significantly increased from 1979 to 2005, while the ERA-Int and CFSR have insignificant changes. The reanalyses also have low correlation with one another (generally less than +0.69). 37 CMIP5 models show increasing trend, 18 of which are significant. The resulting CMIP5 MMM also has a significant increasing trend of 0.29 ± 0.06 mm year-1. For SAT, the reanalyses show insignificant changes and have high correlation with one another, while the CMIP5 MMM shows a significant increasing trend. Nonetheless, the variability of precipitation and SAT of MMM could affect the significance of its trend. One of the many reasons for the large differences of precipitation is the CMIP5 models' resolution.

The impact of lungs from diabetic donors on lung transplant recipients†.

PubMed

Ambur, Vishnu; Taghavi, Sharven; Jayarajan, Senthil; Kadakia, Sagar; Zhao, Huaqing; Gomez-Abraham, Jesus; Toyoda, Yoshiya

2017-02-01

We attempted to determine if transplants of lungs from diabetic donors (DDs) is associated with increased mortality of recipients in the modern era of the lung allocation score (LAS). The United Network for Organ Sharing (UNOS) database was queried for all adult lung transplant recipients from 2006 to 2014. Patients receiving a lung from a DD were compared to those receiving a transplant from a non-DD. Multivariate Cox regression analysis using variables associated with mortality was used to examine survival. A total of 13 159 adult lung transplants were performed between January 2006 and June 2014: 4278 (32.5%) were single-lung transplants (SLT) and 8881 (67.5%) were double-lung transplants (DLT). The log-rank test demonstrated a lower median survival in the DD group (5.6 vs 5.0 years, P = 0.003). We performed additional analysis by dividing this initial cohort into two cohorts by transplant type. On multivariate analysis, receiving an SLT from a DD was associated with increased mortality (HR 1.28, 95% CI 1.07–1.54, P = 0.011). Interestingly, multivariate analysis demonstrated no difference in mortality rates for patients receiving a DLT from a DD (HR 1.12, 95% CI 0.97–1.30, P = 0.14). DLT with DDs can be performed safely without increased mortality, but SLT using DDs results in worse survival and post-transplant outcomes. Preference should be given to DLT when using lungs from donors with diabetes. © The Author 2016. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

MULTIVARIATE RECEPTOR MODELS AND MODEL UNCERTAINTY. (R825173)

EPA Science Inventory

Abstract

Estimation of the number of major pollution sources, the source composition profiles, and the source contributions are the main interests in multivariate receptor modeling. Due to lack of identifiability of the receptor model, however, the estimation cannot be...

Publishing in open access era: focus on respiratory journals

PubMed Central

Xu, Dingyao; Zhong, Xiyao; Li, Li; Ling, Qibo; Bu, Zhaode

2014-01-01

We have entered an open access publishing era. The impact and significance of open access is still under debate after two decades of evolution. Open access journals benefit researchers and the general public by promoting visibility, sharing and communicating. Non-mainstream journals should turn the challenge of open access into opportunity of presenting best research articles to the global readership. Open access journals need to optimize their business models to promote the healthy and continuous development. PMID:24822120

Publishing in open access era: focus on respiratory journals.

PubMed

Dai, Ni; Xu, Dingyao; Zhong, Xiyao; Li, Li; Ling, Qibo; Bu, Zhaode

2014-05-01

We have entered an open access publishing era. The impact and significance of open access is still under debate after two decades of evolution. Open access journals benefit researchers and the general public by promoting visibility, sharing and communicating. Non-mainstream journals should turn the challenge of open access into opportunity of presenting best research articles to the global readership. Open access journals need to optimize their business models to promote the healthy and continuous development.

A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution

PubMed Central

Inouye, David; Yang, Eunho; Allen, Genevera; Ravikumar, Pradeep

2017-01-01

The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have been far less popular. Yet, real-world high-dimensional count-valued data found in word counts, genomics, and crime statistics, for example, exhibit rich dependencies, and motivate the need for multivariate distributions that can appropriately model this data. We review multivariate distributions derived from the univariate Poisson, categorizing these models into three main classes: 1) where the marginal distributions are Poisson, 2) where the joint distribution is a mixture of independent multivariate Poisson distributions, and 3) where the node-conditional distributions are derived from the Poisson. We discuss the development of multiple instances of these classes and compare the models in terms of interpretability and theory. Then, we empirically compare multiple models from each class on three real-world datasets that have varying data characteristics from different domains, namely traffic accident data, biological next generation sequencing data, and text data. These empirical experiments develop intuition about the comparative advantages and disadvantages of each class of multivariate distribution that was derived from the Poisson. Finally, we suggest new research directions as explored in the subsequent discussion section. PMID:28983398

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Schröter, Kai; Merz, Bruno

2016-05-01

Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

An error bound for a discrete reduced order model of a linear multivariable system

NASA Technical Reports Server (NTRS)

Al-Saggaf, Ubaid M.; Franklin, Gene F.

1987-01-01

The design of feasible controllers for high dimension multivariable systems can be greatly aided by a method of model reduction. In order for the design based on the order reduction to include a guarantee of stability, it is sufficient to have a bound on the model error. Previous work has provided such a bound for continuous-time systems for algorithms based on balancing. In this note an L-infinity bound is derived for model error for a method of order reduction of discrete linear multivariable systems based on balancing.

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Kimes, Daniel S.; Nelson, Ross F.

1998-01-01

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

Validation and uncertainty analysis for monthly and extreme precipitation in the ERA-20C reanalysis based on the WZN in-situ measurements

NASA Astrophysics Data System (ADS)

Rustemeier, Elke; Ziese, Markus; Raykova, Kristin; Meyer-Christoffer, Anja; Schneider, Udo; Finger, Peter; Becker, Andreas

2017-04-01

The proper representation of precipitation, in particular extreme precipitation, in global reanalyses is still challenging. This paper focuses on the potential of the ERA-20C centennial reanalysis to reproduce precipitation events. The global ERA-20C Reanalysis has been developed within the projects ERA-CLIM and its successor ERA-CLIM2 with the aim of a multi-decadal reanalysis of the global climate system. One of the objectives of ERA-CLIM2 is to provide useful information about the uncertainty of the various parameters. Since precipitation is a prognostic variable, it allows for independent validation by in-situ measurements. For this purpose, the Global Precipitation Climatology Centre (GPCC) operated by the DWD has compared the ERA-20C Reanalysis with the GPCC observational products "Full Data Monthly Version 7" (FDM-V7) and "Full Data Daily Version 1" (FDD-V1). ERA-20C is based on the ECMWF prediction model IFS version Cy38r1 with a spatial resolution of approximately 125 km and covers the 111 years from 1900 to 2010. The GPCC FDM-V7 raster data product, on the other hand, includes the global land surface in-situ measurements between 1901 and 2013 (Schneider et al., 2014) and the FDD-V1 raster data product covers daily precipitation from 1988 to 2013 with daily resolution. The most suitable resolution of 1° was used to validate ERA-20C. For the spatial and temporal validation of the ERA-20C Reanalysis, global temporal scores were calculated on monthly, seasonal and annual time scales. These include e.g. monthly contingency table scores, correlation or climate change indices (ETCCDI) for precipitation to determine extreme values and their temporal change (Peterson et al., 2001, Appendix A). Not surprisingly, the regions with the strongest differences are also those with data scarcity, mountain regions with their luv and lee effects or monsoon areas. They all show a strong systematic difference and breaks within the time series. Differences between ERA-20C and FDD-V1 based on ETCCDI diagnoses were detected particularly in regions with large precipitation totals especially in Africa in the ITCZ area and in Indonesia. The overall comparison reveals geo-spatially heterogeneous results with areas of similar precipitation characteristics, but also areas that still remain challenging for the reanalysis' fidelity to represent the FDM-V7 and FDD-F1 based diagnostics. The results serve good guidance where improvements of the future IFS model versions should be most effective. Peterson, T., Folland, C., Gruza, G., Hogg, W., Mokssit, A. and Plummer, N. (2001): Report on the activities of the working group on climate change detection and related rapporteurs. Geneva: World Meteorological Organization. Poli, P., H. Hersbach, D. Tan, D. Dee, J.-N. Thépaut, A. Simmons, C. Peubey, P. Laloy-aux, T. Komori, P. Berrisford, R. Dragani, Y. Trémolet, E. H ´lm, M. Bonavita, L. Isaksen und M. Fisher (2013): The data assimilation system and initial performance evaluation of the ECMWF pilot reanalysis of the 20th-century assimilating surface observations only (ERA-20C), ERA Report Series 14, http://www.ecmwf.int/publications/library/do/references/show?id=90833) Schneider, Udo, Andreas Becker, Peter Finger, Anja Meyer-Christoffer, Bruno Rudolf und Markus Ziese (2015): GPCC Full Data Reanalysis Version 7.0 at 1.0°: Monthly Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data. DOI: 10.5676/DWD_GPCC/FD_M_V7_100

Evaluation of Cloud Physical Properties of ECMWF Analysis and Re-Analysis (ERA-40 and ERA Interim) against CERES Tropical Deep Convective Cloud Object Observations

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2008-01-01

This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Center for Medium-range Weather Forecasts (ECMWF) operational analysis (EOA) and ECMWF Re-Analyses (ERA-40 and ERA Interim) are validated against those obtained from Earth Observing System satellite cloud object data for January-August 1998 and March 2000 periods. These properties include ice water path (IWP), cloud-top height and temperature, cloud optical depth and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud-object type for the January-August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The downgrade of data assimilation technique and the lack of snow water content information in ERA-40, not the coarser horizontal grid resolution, are also responsible for the disagreements with observed pdfs of cloud physical properties although the detection rates of cloud object occurrence are improved for small size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights with grid-cell dynamics. These conclusions will be rechecked using the ERA Interim data, due to recent changes in the ECMWF convective parameterization (Bechtold et al. 2004, 2008). Results from the ERA Interim will be presented at the meeting.

National data on stroke outcomes in Thailand.

PubMed

Kongbunkiat, Kannikar; Kasemsap, Narongrit; Thepsuthammarat, Kaewjai; Tiamkao, Somsak; Sawanyawisuth, Kittisak

2015-03-01

Stroke is a major public health problem worldwide. There are limited data on national stroke prevalence and outcomes after the beginning of the thrombolytic therapy era in Thailand. This study aimed to investigate the prevalence and factors associated with mortality in stroke patients in Thailand using the national reimbursement databases. Clinical data retrieved included individuals under the universal coverage, social security, and civil servant benefit systems between 1 October 2009 and 30 September 2010. The stroke diagnosis code was based on the International Classification of Diseases 10th revision system including G45 (transient cerebral ischemic attacks and related syndromes), I61 (intracerebral hemorrhage), and I63 (cerebral infarction). The prevalence and stroke outcomes were calculated from these coded data. Factors associated with death were evaluated by multivariable logistic regression analysis. We found that the most frequent stroke subtype was cerebral infarction with a prevalence of 122 patients per 100,000 of population, an average length of hospital stay of 6.8 days, an average hospital charge of 20,740 baht (∼$USD 691), a mortality rate of 7%, and thrombolytic prescriptions of 1%. The significant factors associated with stroke mortality were septicemia, pulmonary embolism, pneumonia, myocardial infarction, status epilepticus, and heart failure. In conclusion, the prevalence and outcomes of stroke in Thailand were comparable with other countries. The era of thrombolytic therapy has just begun in Thailand. Copyright © 2014 Elsevier Ltd. All rights reserved.

Symptomatic Perihepatic Fluid Collections After Hepatic Resection in the Modern Era.

PubMed

Konstantinidis, Ioannis T; Mastrodomenico, Pedro; Sofocleous, Constantinos T; Brown, Karen T; Getrajdman, George I; Gönen, Mithat; Allen, Peter J; Kingham, T Peter; DeMatteo, Ronald P; Fong, Yuman; Jarnagin, William R; D'Angelica, Michael I

2016-04-01

Improvements in liver surgery have led to decreased mortality rates. Symptomatic perihepatic collections (SPHCs) requiring percutaneous drainage remain a significant source of morbidity. A single institution's prospectively maintained hepatic resection database was reviewed to identify patients who underwent hepatectomy between January 2004 and February 2012. Data from 2173 hepatectomies performed in 2040 patients were reviewed. Overall, 200 (9%) patients developed an SPHC, the majority non-bilious (75.5%) and infected (54%). Major hepatic resections, larger than median blood loss (≥360 ml), use of surgical drains, and simultaneous performance of a colorectal procedure were associated with an SPHC on multivariate analysis. Non-bilious, non-infected (NBNI) collections were associated with lower white blood cell (WBC) counts, absence of a bilio-enteric anastomosis, use of hepatic arterial infusion pump (HAIP), and presence of metastatic disease, and resolved more frequently with a single interventional radiology (IR) procedure (85 vs. 46.5%, p < 0.001) more quickly (15 vs. 30 days, p = 0.001). SPHCs developed in 9% of patients in a modern series of hepatic resections, and in one third were non-bilious and non-infected. In the era of modern interventional radiology, the need for re-operation for SPHC is exceedingly rare. A significant proportion of minimally symptomatic SPHC patients may not require drainage, and strategies to avoid unnecessary drainage are warranted.

Risk factors and impact of non-Aspergillus mold infections following allogeneic HCT: a CIBMTR infection and immune reconstitution analysis.

PubMed

Riches, M L; Trifilio, S; Chen, M; Ahn, K W; Langston, A; Lazarus, H M; Marks, D I; Martino, R; Maziarz, R T; Papanicolou, G A; Wingard, J R; Young, J-A H; Bennett, C L

2016-02-01

Risk factors for non-Aspergillus mold infection (NAMI) and the impact on transplant outcome are poorly assessed in the current era of antifungal agents. Outcomes of 124 patients receiving allogeneic hematopoietic cell transplantation (HCT) diagnosed with either mucormycosis (n=72) or fusariosis (n=52) between days 0 and 365 after HCT are described and compared with a control cohort (n=11 856). Patients with NAMI had more advanced disease (mucormycois: 25%, fusariosis: 23% and controls: 18%; P=0.004) and were more likely to have a Karnofsky performance status (KPS) <90% at HCT (mucormycosis: 42%, fusariosis: 38% and controls: 28%; P=0.048). The 1-year survival after HCT was 22% (15-29%) for cases and was significantly inferior compared with controls (65% (64-65%); P<0.001). Survival from infection was similarly dismal regardless of mucormycosis: 15% (8-25%) and fusariosis: 21% (11-33%). In multivariable analysis, NAMI was associated with a sixfold higher risk of death (P<0.0001) regardless of the site or timing of infection. Risk factors for mucormycosis include preceding acute GvHD, prior Aspergillus infection and older age. For fusariosis, increased risks including receipt of cord blood, prior CMV infection and transplant before May 2002. In conclusion, NAMI occurs infrequently, is associated with high mortality and appears with similar frequency in the current antifungal era.

Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI

PubMed Central

Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Treviño, Victor; Tamez-Peña, José G.

2015-01-01

In this work, the potential of X-ray based multivariate prognostic models to predict the onset of chronic knee pain is presented. Using X-rays quantitative image assessments of joint-space-width (JSW) and paired semiquantitative central X-ray scores from the Osteoarthritis Initiative (OAI), a case-control study is presented. The pain assessments of the right knee at the baseline and the 60-month visits were used to screen for case/control subjects. Scores were analyzed at the time of pain incidence (T-0), the year prior incidence (T-1), and two years before pain incidence (T-2). Multivariate models were created by a cross validated elastic-net regularized generalized linear models feature selection tool. Univariate differences between cases and controls were reported by AUC, C-statistics, and ODDs ratios. Univariate analysis indicated that the medial osteophytes were significantly more prevalent in cases than controls: C-stat 0.62, 0.62, and 0.61, at T-0, T-1, and T-2, respectively. The multivariate JSW models significantly predicted pain: AUC = 0.695, 0.623, and 0.620, at T-0, T-1, and T-2, respectively. Semiquantitative multivariate models predicted paint with C-stat = 0.671, 0.648, and 0.645 at T-0, T-1, and T-2, respectively. Multivariate models derived from plain X-ray radiography assessments may be used to predict subjects that are at risk of developing knee pain. PMID:26504490

Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

Decadal Prediction Skill in the GEOS-5 Forecast System

NASA Technical Reports Server (NTRS)

Ham, Yoo-Geun; Rienecker, Michael M.; Suarez, M.; Vikhliaev, Yury V.; Zhao, Bin; Marshak, Jelena; Vernieres, Guillaume; Schubert, Siegfried D.

2012-01-01

A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office?s GEOS-5 Atmosphere-Ocean General Circulation Model (AOGCM). The hindcasts are initialized every December from 1959 to 2010 following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multi-variate ensemble optimal interpolation ocean and sea-ice reanalysis, and from the atmospheric reanalysis (MERRA, the Modern-Era Retrospective Analysis for Research and Applications) generated using the GEOS-5 atmospheric model. The forecast skill of a three-member-ensemble mean is compared to that of an experiment without initialization but forced with observed CO2. The results show that initialization acts to increase the forecast skill of Northern Atlantic SST compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. The annual-mean Atlantic Meridional Overturning Circulation (AMOC) index is predictable up to a 5-year lead time, consistent with the predictable signal in upper ocean heat content over the Northern Atlantic. While the skill measured by Mean Squared Skill Score (MSSS) shows 50% improvement up to 10-year lead forecast over the subtropical and mid-latitude Atlantic, however, prediction skill is relatively low in the subpolar gyre, due in part to the fact that the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region appears to be unrealistic. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.

Did Equity of Reproductive and Maternal Health Service Coverage Increase during the MDG Era? An Analysis of Trends and Determinants across 74 Low- and Middle-Income Countries

PubMed Central

Sharma, Suneeta

2015-01-01

Introduction Despite widespread gains toward the 5th Millennium Development Goal (MDG), pro-rich inequalities in reproductive health (RH) and maternal health (MH) are pervasive throughout the world. As countries enter the post-MDG era and strive toward UHC, it will be important to monitor the extent to which countries are achieving equity of RH and MH service coverage. This study explores how equity of service coverage differs across countries, and explores what policy factors are associated with a country’s progress, or lack thereof, toward more equitable RH and MH service coverage. Methods We used RH and MH service coverage data from Demographic and Health Surveys (DHS) for 74 countries to examine trends in equity between countries and over time from 1990 to 2014. We examined trends in both relative and absolute equity, and measured relative equity using a concentration index of coverage data grouped by wealth quintile. Through multivariate analysis we examined the relative importance of policy factors, such as political commitment to health, governance, and the level of prepayment, in determining countries’ progress toward greater equity in RH and MH service coverage. Results Relative equity for the coverage of RH and MH services has continually increased across all countries over the past quarter century; however, inequities in coverage persist, in some countries more than others. Multivariate analysis shows that higher education and greater political commitment (measured as the share of government spending allocated to health) were significantly associated with higher equity of service coverage. Neither country income, i.e., GDP per capita, nor better governance were significantly associated with equity. Conclusion Equity in RH and MH service coverage has improved but varies considerably across countries and over time. Even among the subset of countries that are close to achieving the MDGs, progress made on equity varies considerably across countries. Enduring disparities in access and outcomes underpin mounting support for targeted reforms within the broader context of universal health coverage (UHC). PMID:26331846

Cost comparison between home telemonitoring and usual care of older adults: a randomized trial (Tele-ERA).

PubMed

Upatising, Benjavan; Wood, Douglas L; Kremers, Walter K; Christ, Sharon L; Yih, Yuehwern; Hanson, Gregory J; Takahashi, Paul Y

2015-01-01

From 1992 to 2008, older adults in the United States incurred more healthcare expense per capita than any other age group. Home telemonitoring has emerged as a potential solution to reduce these costs, but evidence is mixed. The primary aim of the study was to evaluate whether the mean difference in total direct medical cost consequence between older adults receiving additional home telemonitoring care (TELE) (n=102) and those receiving usual medical care (UC) (n=103) were significant. Inpatient, outpatient, emergency department, decedents, survivors, and 30-day readmission costs were evaluated as secondary aim. Multivariate generalized linear models (GLMs) and parametric bootstrapping method were used to model cost and to determine significance of the cost differences. We also compared the differences in arithmetic mean costs. From the conditional GLMs, the estimated mean cost differences (TELE versus UC) for total, inpatient, outpatient, and ED were -$9,537 (p=0.068), -$8,482 (p =0.098), -$1,160 (p=0.177), and $106 (p=0.619), respectively. Mean postenrollment cost was 11% lower than the prior year for TELE versus 22% higher for UC. The ratio of mean cost for decedents to survivors was 2.1:1 (TELE) versus 12.7:1 (UC). There were no significant differences in the mean total cost between the two treatment groups. The TELE group had less variability in cost of care, lower decedents to survivors cost ratio, and lower total 30-day readmission cost than the UC group.

Prognostic and predictive implications of Sokal, Euro and EUTOS scores in chronic myeloid leukaemia in the imatinib era-experience from a tertiary oncology centre in Southern India.

PubMed

Kuntegowdanahalli, Lakshmaiah Chinnagiriyappa; Kanakasetty, Govind Babu; Thanky, Aditi Harsh; Dasappa, Lokanatha; Jacob, Linu Abraham; Mallekavu, Suresh Babu; Lakkavalli, Rajeev Krishnappa; Kadabur, Lokesh N; Haleshappa, Rudresha Antapura

2016-01-01

Chronic myeloid leukaemia (CML) is a myeloproliferative disorder. Over the years many prognostic models have been developed to better risk stratify this disease at baseline. Sokal, Euro, and EUTOS scores were developed in varied populations initially receiving various therapies. Here we try to identify their predictive and prognostic implication in a larger population of Indian patients with CML-CP (chronic phase) in the imatinib era.

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

NASA Astrophysics Data System (ADS)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin, particularly for annual maxima of the FWI distribution and spatiotemporal autocorrelation of precipitation fields.

A prognostic index for natural killer cell lymphoma after non-anthracycline-based treatment: a multicentre, retrospective analysis.

PubMed

Kim, Seok Jin; Yoon, Dok Hyun; Jaccard, Arnaud; Chng, Wee Joo; Lim, Soon Thye; Hong, Huangming; Park, Yong; Chang, Kian Meng; Maeda, Yoshinobu; Ishida, Fumihiro; Shin, Dong-Yeop; Kim, Jin Seok; Jeong, Seong Hyun; Yang, Deok-Hwan; Jo, Jae-Cheol; Lee, Gyeong-Won; Choi, Chul Won; Lee, Won-Sik; Chen, Tsai-Yun; Kim, Kiyeun; Jung, Sin-Ho; Murayama, Tohru; Oki, Yasuhiro; Advani, Ranjana; d'Amore, Francesco; Schmitz, Norbert; Suh, Cheolwon; Suzuki, Ritsuro; Kwong, Yok Lam; Lin, Tong-Yu; Kim, Won Seog

2016-03-01

The clinical outcome of extranodal natural killer T-cell lymphoma (ENKTL) has improved substantially as a result of new treatment strategies with non-anthracycline-based chemotherapies and upfront use of concurrent chemoradiotherapy or radiotherapy. A new prognostic model based on the outcomes obtained with these contemporary treatments was warranted. We did a retrospective study of patients with newly diagnosed ENKTL without any previous treatment history for the disease who were given non-anthracycline-based chemotherapies with or without upfront concurrent chemoradiotherapy or radiotherapy with curative intent. A prognostic model to predict overall survival and progression-free survival on the basis of pretreatment clinical and laboratory characteristics was developed by filling a multivariable model on the basis of the dataset with complete data for the selected risk factors for an unbiased prediction model. The final model was applied to the patients who had complete data for the selected risk factors. We did a validation analysis of the prognostic model in an independent cohort. We did multivariate analyses of 527 patients who were included from 38 hospitals in 11 countries in the training cohort. Analyses showed that age greater than 60 years, stage III or IV disease, distant lymph-node involvement, and non-nasal type disease were significantly associated with overall survival and progression-free survival. We used these data as the basis for the prognostic index of natural killer lymphoma (PINK), in which patients are stratified into low-risk (no risk factors), intermediate-risk (one risk factor), or high-risk (two or more risk factors) groups, which were associated with 3-year overall survival of 81% (95% CI 75-86), 62% (55-70), and 25% (20-34), respectively. In the 328 patients with data for Epstein-Barr virus DNA, a detectable viral DNA titre was an independent prognostic factor for overall survival. When these data were added to PINK as the basis for another prognostic index (PINK-E)-which had similar low-risk (zero or one risk factor), intermediate-risk (two risk factors), and high-risk (three or more risk factors) categories-significant associations with overall survival were noted (81% [95% CI 75-87%], 55% (44-66), and 28% (18-40%), respectively). These results were validated and confirmed in an independent cohort, although the PINK-E model was only significantly associated with the high-risk group compared with the low-risk group. PINK and PINK-E are new prognostic models that can be used to develop risk-adapted treatment approaches for patients with ENKTL being treated in the contemporary era of non-anthracycline-based therapy. Samsung Biomedical Research Institute. Copyright © 2016 Elsevier Ltd. All rights reserved.

Partial Least Squares Calibration Modeling Towards the Multivariate Limit of Detection for Enriched Isotopic Mixtures via Laser Ablation Molecular Isotopic Spectroscopy

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

Harris, Candace; Profeta, Luisa; Akpovo, Codjo

The psuedo univariate limit of detection was calculated to compare to the multivariate interval. ompared with results from the psuedounivariate LOD, the multivariate LOD includes other factors (i.e. signal uncertainties) and the reveals the significance in creating models that not only use the analyte’s emission line but also its entire molecular spectra.

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

A simplified parsimonious higher order multivariate Markov chain model

NASA Astrophysics Data System (ADS)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, a simplified parsimonious higher-order multivariate Markov chain model (SPHOMMCM) is presented. Moreover, parameter estimation method of TPHOMMCM is give. Numerical experiments shows the effectiveness of TPHOMMCM.

Energy Balance and Hydrological Modelling of Zongo Glacier, Bolivia, Using ERA-40 Reanalysis Data

NASA Astrophysics Data System (ADS)

Duguay, M.; Hock, R.; Sicart, J.; Coudrain, A.

2008-12-01

In the Andes several regions profit significantly from glacial melt water for drink water supply and electricity production. During the dry season, glacier melt is significant source of water in the semi-arid region of La Paz, Bolivia. The Andean glaciers are retreating and water resources after reaching a culmination, will decrease. This implicates serious environmental and socio-economical consequences. For an effective attenuation, it is crucial to furnish quantitative predictions of the glacier mass loss and its effects on the water resources in these regions. A distributed energy balance model has been developed to model mass balance and melt induced discharge of tropical glaciers. We want to predict the changes in glacier melt discharge in response to future climate change for the region of La Paz, Bolivia and later regionalize the model to a larger area. The model operates on daily steps, has a 20 m grid resolution, and is forced by daily data of air temperature, humidity, wind speed, global radiation and precipitation. As a test basin, we calibrate the model at Glaciar Zongo, Bolivia, 16°15'S , 68°°10'W which is monitored by the French Institute for Research for the Development (IRD) . Zongo Glacier is a 1,8 km2 large and the catchment is 63% glacierized. Mass balance, weather station and discharge data are available on daily basis from 1991 onward. The measurements have gaps and only two years (1994-95 and 1999-00) with continuous data are available. In order to allow for multi-year simulations we force the model by daily ERA-40 reanalysis data from the European Center for Weather Forecast (ECMWF). To downscale the data we compare the daily data 1991-2002 to the observations at the glacier. Results indicate a fair agreement for air temperature, but a rather poor correlation between the ERA-40 data and the observations for wind speed, global radiation and precipitation. The correlation is improved using monthly values. So far, test runs of the model using downscaled ERA-40 data for the Zongo Glacier show good agreement for the mass balances (r2=0.88) and relatively good estimate of the monthly melt discharge (r2=0.74). The transition between the wet and dry season is well captured by the model

Assessment of Multiple Daily Precipitation Statistics in ERA-Interim Driven Med-CORDEX and EURO-CORDEX Experiments Against High Resolution Observations

NASA Astrophysics Data System (ADS)

Coppola, E.; Fantini, A.; Raffaele, F.; Torma, C. Z.; Bacer, S.; Giorgi, F.; Ahrens, B.; Dubois, C.; Sanchez, E.; Verdecchia, M.

2017-12-01

We assess the statistics of different daily precipitation indices in ensembles of Med-CORDEX and EUROCORDEX experiments at high resolution (grid spacing of ˜0.11° , or RCM11) and medium resolution (grid spacing of ˜0.44° , or RCM44) with regional climate models (RCMs) driven by the ERA-Interim reanalysis of observations for the period 1989-2008. The assessment is carried out by comparison with a set of high resolution observation datasets for 9 European subregions. The statistics analyzed include quantitative metrics for mean precipitation, daily precipitation Probability Density Functions (PDFs), daily precipitation intensity, frequency, 95th percentile and 95th percentile of dry spell length. We assess both an ensemble including all Med-CORDEX and EURO-CORDEX models and one including the Med-CORDEX models alone. For the All Models ensembles, the RCM11 one shows a remarkable performance in reproducing the spatial patterns and seasonal cycle of mean precipitation over all regions, with a consistent and marked improvement compared to the RCM44 ensemble and the ERA-Interim reanalysis. A good consistency with observations by the RCM11 ensemble (and a substantial improvement compared to RCM44 and ERA-Interim) is found also for the daily precipitation PDFs, mean intensity and, to a lesser extent, the 95th percentile. In fact, for some regions the RCM11 ensemble overestimates the occurrence of very high intensity events while for one region the models underestimate the occurrence of the largest extremes. The RCM11 ensemble still shows a general tendency to underestimate the dry day frequency and 95th percentile of dry spell length over wetter regions, with only a marginal improvement compared to the lower resolution models. This indicates that the problem of the excessive production of low precipitation events found in many climate models persists also at relatively high resolutions, at least in wet climate regimes. Concerning the Med-CORDEX model ensembles we find that their performance is of similar quality as that of the all-models over the Mediterranean regions analyzed. Finally, we stress the need of consistent and quality checked fine scale observation datasets for the assessment of RCMs run at increasingly high horizontal resolutions.

Reconstructions of the 1900-2015 Greenland ice sheet surface mass balance using the regional climate MAR model

NASA Astrophysics Data System (ADS)

Fettweis, Xavier; Box, Jason E.; Agosta, Cécile; Amory, Charles; Kittel, Christoph; Lang, Charlotte; van As, Dirk; Machguth, Horst; Gallée, Hubert

2017-04-01

With the aim of studying the recent Greenland ice sheet (GrIS) surface mass balance (SMB) decrease relative to the last century, we have forced the regional climate MAR (Modèle Atmosphérique Régional; version 3.5.2) model with the ERA-Interim (ECMWF Interim Re-Analysis; 1979-2015), ERA-40 (1958-2001), NCEP-NCARv1 (National Centers for Environmental Prediction-National Center for Atmospheric Research Reanalysis version 1; 1948-2015), NCEP-NCARv2 (1979-2015), JRA-55 (Japanese 55-year Reanalysis; 1958-2014), 20CRv2(c) (Twentieth Century Reanalysis version 2; 1900-2014) and ERA-20C (1900-2010) reanalyses. While all these forcing products are reanalyses that are assumed to represent the same climate, they produce significant differences in the MAR-simulated SMB over their common period. A temperature adjustment of +1 °C (respectively -1 °C) was, for example, needed at the MAR boundaries with ERA-20C (20CRv2) reanalysis, given that ERA-20C (20CRv2) is ˜ 1 °C colder (warmer) than ERA-Interim over Greenland during the period 1980-2010. Comparisons with daily PROMICE (Programme for Monitoring of the Greenland Ice Sheet) near-surface observations support these adjustments. Comparisons with SMB measurements, ice cores and satellite-derived melt extent reveal the most accurate forcing datasets for the simulation of the GrIS SMB to be ERA-Interim and NCEP-NCARv1. However, some biases remain in MAR, suggesting that some improvements are still needed in its cloudiness and radiative schemes as well as in the representation of the bare ice albedo. Results from all MAR simulations indicate that (i) the period 1961-1990, commonly chosen as a stable reference period for Greenland SMB and ice dynamics, is actually a period of anomalously positive SMB (˜ +40 Gt yr-1) compared to 1900-2010; (ii) SMB has decreased significantly after this reference period due to increasing and unprecedented melt reaching the highest rates in the 120-year common period; (iii) before 1960, both ERA-20C and 20CRv2-forced MAR simulations suggest a significant precipitation increase over 1900-1950, but this increase could be the result of an artefact in the reanalyses that are not well-enough constrained by observations during this period and (iv) since the 1980s, snowfall is quite stable after having reached a maximum in the 1970s. These MAR-based SMB and accumulation reconstructions are, however, quite similar to those from Box (2013) after 1930 and confirm that SMB was quite stable from the 1940s to the 1990s. Finally, only the ERA-20C-forced simulation suggests that SMB during the 1920-1930 warm period over Greenland was comparable to the SMB of the 2000s, due to both higher melt and lower precipitation than normal.

Observational status of Tachyon Natural Inflation and reheating

NASA Astrophysics Data System (ADS)

Rashidi, Narges; Nozari, Kourosh; Grøn, Øyvind

2018-05-01

We study observational viability of Natural Inflation with a tachyon field as inflaton. By obtaining the main perturbation parameters in this model, we perform a numerical analysis on the parameter space of the model and in confrontation with 68% and 95% CL regions of Planck2015 data. By adopting a warped background geometry, we find some new constraints on the width of the potential in terms of its height and the warp factor. We show that the Tachyon Natural Inflation in the large width limit recovers the tachyon model with a phi2 potential which is consistent with Planck2015 observational data. Then we focus on the reheating era after inflation by treating the number of e-folds, temperature and the effective equation of state parameter in this era. Since it is likely that the value of the effective equation of state parameter during the reheating era to be in the range 0<= ωeff<= 1/3, we obtain some new constraints on the tensor to scalar ratio, r, as well as the e-folds number and reheating temperature in this Tachyon Natural Inflation model. In particular, we show that a prediction of this model is r<=8/3 δns, where δns is the scalar spectral tilt, δns=1‑ns. In this regard, given that from the Planck2015 data we have δns=0.032 (corresponding to ns=0.968), we get r<= 0.085.

Radial Variations in the Io Plasma Torus during the Cassini Era

NASA Technical Reports Server (NTRS)

Delamere, P. A.; Bagenal, F.; Steffl, A.

2005-01-01

A radial scan through the midnight sector of the Io plasma torus was made by the Cassini Ultraviolet Imaging Spectrograph on 14 January 2001, shortly after closest approach to Jupiter. From these data, Steffl et al. (2004a) derived electron temperature, plasma composition (ion mixing ratios), and electron column density as a function of radius from L = 6 to 0 as well as the total luminosity. We have advanced our homogeneous model of torus physical chemistry (Delamere and Bagenal, 2003) to include latitudinal and radial variations in a manner similar to the two-dimensional model by Schreier et al. (1998). The model variables include: (1) neutral source rate, (2) radial transport coefficient, (3) the hot electron fraction, (4) hot electron temperature, and (5) the neutral O/S ratio. The radial variation of parameters 1-4 are described by simple power laws, making a total of nine parameters. We have explored the sensitivity of the model results to variations in these parameters and compared the best fit with previous Voyager era models (schreier et al., 1998), galileo data (Crary et al., 1998), and Cassini observations (steffl et al., 2004a). We find that radial variations during the Cassini era are consistent with a neutral source rate of 700-1200 kg/s, an integrated transport time from L = 6 to 9 of 100-200 days, and that the core electron temperature is largely determined by a spatially and temporally varying superthermal electron population.

Piecewise multivariate modelling of sequential metabolic profiling data.

PubMed

Rantalainen, Mattias; Cloarec, Olivier; Ebbels, Timothy M D; Lundstedt, Torbjörn; Nicholson, Jeremy K; Holmes, Elaine; Trygg, Johan

2008-02-19

Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the sampling rate and number of sampling points are often restricted due to experimental and biological constraints. A supervised multivariate modelling approach with the objective to model the time-related variation in the data for short and sparsely sampled time-series is described. A set of piecewise Orthogonal Projections to Latent Structures (OPLS) models are estimated, describing changes between successive time points. The individual OPLS models are linear, but the piecewise combination of several models accommodates modelling and prediction of changes which are non-linear with respect to the time course. We demonstrate the method on both simulated and metabolic profiling data, illustrating how time related changes are successfully modelled and predicted. The proposed method is effective for modelling and prediction of short and multivariate time series data. A key advantage of the method is model transparency, allowing easy interpretation of time-related variation in the data. The method provides a competitive complement to commonly applied multivariate methods such as OPLS and Principal Component Analysis (PCA) for modelling and analysis of short time-series data.

Gauss-Bonnet cosmology unifying late and early-time acceleration eras with intermediate eras

NASA Astrophysics Data System (ADS)

Oikonomou, V. K.

2016-07-01

In this paper we demonstrate that with vacuum F(G) gravity it is possible to describe the unification of late and early-time acceleration eras with the radiation and matter domination era. The Hubble rate of the unified evolution contains two mild singularities, so called Type IV singularities, and the evolution itself has some appealing features, such as the existence of a deceleration-acceleration transition at late times. We also address quantitatively a fundamental question related to modified gravity models description of cosmological evolution: Is it possible for all modified gravity descriptions of our Universe evolution, to produce a nearly scale invariant spectrum of primordial curvature perturbations? As we demonstrate, the answer for the F(G) description is no, since the resulting power spectrum is not scale invariant, in contrast to the F(R) description studied in the literature. Therefore, although the cosmological evolution can be realized in the context of vacuum F(G) gravity, the evolution is not compatible with the observational data, in contrast to the F(R) gravity description of the same cosmological evolution.

Practical implications for genetic modeling in the genomics era

USDA-ARS?s Scientific Manuscript database

Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, incl...

Research needs for developing a commodity-driven freight modeling approach.

DOT National Transportation Integrated Search

2003-01-01

It is well known that better freight forecasting models and data are needed, but the literature does not clearly indicate which components of the modeling methodology are most in need of improvement, which is a critical need in an era of limited rese...

Radiology Consultation in the Era of Precision Oncology: A Review of Consultation Models and Services in the Tertiary Setting.

PubMed

DiPiro, Pamela J; Krajewski, Katherine M; Giardino, Angela A; Braschi-Amirfarzan, Marta; Ramaiya, Nikhil H

2017-01-01

The purpose of the article is to describe the various radiology consultation models in the Era of Precision Medicine. Since the inception of our specialty, radiologists have served as consultants to physicians of various disciplines. A variety of radiology consultation services have been described in the literature, including clinical decision support, patient-centric, subspecialty interpretation, and/or some combination of these. In oncology care in particular, case complexity often merits open dialogue with clinical providers. To explore the utility and impact of radiology consultation services in the academic setting, this article will further describe existing consultation models and the circumstances that precipitated their development. The hybrid model successful at our tertiary cancer center is discussed. In addition, the contributions of a consultant radiologist in breast cancer care are reviewed as the archetype of radiology consultation services provided to oncology practitioners.

Sensitivity studies of high-resolution RegCM3 simulations of precipitation over the European Alps: the effect of lateral boundary conditions and domain size

NASA Astrophysics Data System (ADS)

Nadeem, Imran; Formayer, Herbert

2016-11-01

A suite of high-resolution (10 km) simulations were performed with the International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM3) to study the effect of various lateral boundary conditions (LBCs), domain size, and intermediate domains on simulated precipitation over the Great Alpine Region. The boundary conditions used were ECMWF ERA-Interim Reanalysis with grid spacing 0.75∘, the ECMWF ERA-40 Reanalysis with grid spacing 1.125 and 2.5∘, and finally the 2.5∘ NCEP/DOE AMIP-II Reanalysis. The model was run in one-way nesting mode with direct nesting of the high-resolution RCM (horizontal grid spacing Δx = 10 km) with driving reanalysis, with one intermediate resolution nest (Δx = 30 km) between high-resolution RCM and reanalysis forcings, and also with two intermediate resolution nests (Δx = 90 km and Δx = 30 km) for simulations forced with LBC of resolution 2.5∘. Additionally, the impact of domain size was investigated. The results of multiple simulations were evaluated using different analysis techniques, e.g., Taylor diagram and a newly defined useful statistical parameter, called Skill-Score, for evaluation of daily precipitation simulated by the model. It has been found that domain size has the major impact on the results, while different resolution and versions of LBCs, e.g., 1.125∘ ERA40 and 0.7∘ ERA-Interim, do not produce significantly different results. It is also noticed that direct nesting with reasonable domain size, seems to be the most adequate method for reproducing precipitation over complex terrain, while introducing intermediate resolution nests seems to deteriorate the results.

A comparison of H1N1 influenza among pediatric inpatients in the pandemic and post pandemic era.

PubMed

Rao, Suchitra; Torok, Michelle R; Bagdure, Dayanand; Cunningham, Maureen A; Williams, Joshua T B; Curtis, Donna J; Wilson, Karen; Dominguez, Samuel R

2015-10-01

The novel influenza A H1N1 (A[H1N1]pdm09) strain emerged in 2009, contributing to significant morbidity and mortality. It is not known whether illness associated with A(H1N1) pdm09 in the post-pandemic era exhibits a similar disease profile. The objectives of this study were to compare the burden of disease of A(H1N1) pdm09 influenza from the 2009 pandemic year to the post-pandemic years (2010-2014), and to explore potential reasons for any differences. We conducted a retrospective cohort study of inpatients admitted to Children's Hospital Colorado with a positive respiratory specimen for influenza from May-December, 2009 and December, 2010-April, 2014. Univariate and multivariate analyses were conducted to compare the demographics and clinical characteristics of patients with H1N1 during the two periods. There were 388 inpatients with influenza A(H1N1) pdm09 in 2009, and 117 during the post-pandemic years. Ninety-four percent of all H1N1 during the post-pandemic era was observed during the 2013-2014 influenza season. Patients with A(H1N1) pdm09 during the post-pandemic year were less likely to have an underlying medical condition (P<0.01). Patients admitted to the ICU during the post-pandemic year had a lower median age (5 vs 8 years, P=0.01) and a lower proportion of patients were intubated, had mental status changes, and ARDS compared with the pandemic years, (P<0.01 for all), with decreased mortality (P=0.02). Patients with influenza A(H1N1) pdm09 during the post-pandemic years appeared to have less severe disease than patients with A(H1N1) pdm09 during the pandemic year. The reasons for this difference are likely multifactorial. Published by Elsevier B.V.

IL-33 and soluble ST2 levels as novel predictors for remission and progression of carotid plaque in early rheumatoid arthritis: A prospective study.

PubMed

Shen, Jiayun; Shang, Qing; Wong, Chun-Kwok; Li, Edmund K; Wang, Shang; Li, Rui-Jie; Lee, Ka-Lai; Leung, Ying-Ying; Ying, King-Yee; Yim, Cheuk-Wan; Kun, Emily W; Leung, Moon-Ho; Li, Martin; Li, Tena K; Zhu, Tracy Y; Yu, Shui-Lian; Kuan, Woon-Pang; Yu, Cheuk-Man; Tam, Lai-Shan

2015-08-01

To study the association between the baseline IL-33 and soluble ST2 (sST2) levels with disease remission and progression of carotid atherosclerosis in early rheumatoid arthritis (ERA) patients. A total of 98 ERA patients were enrolled. Disease activity and the presence of carotid plaque were evaluated at baseline and 12 months later. Plasma IL-33 and sST2 levels were determined using enzyme-linked immunosorbent assay kits. Baseline IL-33 and sST2 levels were associated with inflammatory markers and cardiovascular (CV) risk factors. Overall, 44(45%), 18(18%), and 21(21%) patients achieved remission based on 28-joint disease activity score (DAS28), Boolean, and simplified disease activity score (SDAI) criteria at 12 months, respectively. Patients with detectable IL-33 at baseline were less likely to achieve DAS28 (P = 0.010) and SDAI remission (P = 0.021), while a lower baseline sST2 level was able to predict DAS28, Boolean, and SDAI remission (P = 0.005, 0.001, and <0.001, respectively). Using multivariate analysis, a lower baseline sST2 level independently predict Boolean (OR = 0.789; P = 0.005) and SDAI remission (0.812; P = 0.008). Regarding carotid atherosclerosis, 9/98(9.2%) patients had plaque progression at 12 months. Baseline IL-33 was detectable in 8/9(89%) and 42/83(51%) of patients with and without plaque progression respectively (P = 0.029). Baseline detectable IL-33 was an independent predictor for plaque progression after adjusting for traditional CV risk factors (P = 0.017). Lower baseline sST2 levels independently predict disease remission and baseline detectable IL-33 independently predicts carotid plaque progression in ERA patients. This study suggests that inflammation induced by the IL-33/ST2 axis may play a significant role in the development of cardiovascular disease in RA. Copyright © 2015 Elsevier Inc. All rights reserved.

Mouse Models for Studying Oral Cancer: Impact in the Era of Cancer Immunotherapy.

PubMed

Luo, J J; Young, C D; Zhou, H M; Wang, X J

2018-04-01

Model systems for oral cancer research have progressed from tumor epithelial cell cultures to in vivo systems that mimic oral cancer genetics, pathological characteristics, and tumor-stroma interactions of oral cancer patients. In the era of cancer immunotherapy, it is imperative to use model systems to test oral cancer prevention and therapeutic interventions in the presence of an immune system and to discover mechanisms of stromal contributions to oral cancer carcinogenesis. Here, we review in vivo mouse model systems commonly used for studying oral cancer and discuss the impact these models are having in advancing basic mechanisms, chemoprevention, and therapeutic intervention of oral cancer while highlighting recent discoveries concerning the role of immune cells in oral cancer. Improvements to in vivo model systems that highly recapitulate human oral cancer hold the key to identifying features of oral cancer initiation, progression, and invasion as well as molecular and cellular targets for prevention, therapeutic response, and immunotherapy development.

Quantum matter bounce with a dark energy expanding phase

NASA Astrophysics Data System (ADS)

Colin, Samuel; Pinto-Neto, Nelson

2017-09-01

Analyzing quantum cosmological scenarios containing one scalar field with exponential potential, we have obtained a universe model which realizes a classical dust contraction from very large scales, the initial repeller of the model, and moves to a stiff matter contraction near the singularity, which is avoided due to a quantum bounce. The universe is then launched in a stiff matter expanding phase, which then moves to a dark energy era, finally returning to the dust expanding phase, the final attractor of the model. Hence, one has obtained a nonsingular cosmological model where a single scalar field can describe both the matter contracting phase of a bouncing model, necessary to give an almost scale invariant spectrum of scalar cosmological perturbations, and a transient expanding dark energy phase. As the universe is necessarily dust dominated in the far past, usual adiabatic vacuum initial conditions can be easily imposed in this era, avoiding the usual issues appearing when dark energy is considered in bouncing models.

Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-Interim reanalysis

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

Vuichard, N.; Papale, D.

In this study, exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robustmore » method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.« less

Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-Interim reanalysis

DOE PAGES

Vuichard, N.; Papale, D.

2015-07-13

In this study, exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robustmore » method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.« less

A tridiagonal parsimonious higher order multivariate Markov chain model

NASA Astrophysics Data System (ADS)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, we present a tridiagonal parsimonious higher-order multivariate Markov chain model (TPHOMMCM). Moreover, estimation method of the parameters in TPHOMMCM is give. Numerical experiments illustrate the effectiveness of TPHOMMCM.

The skill of ECMWF long range Forecasting System to drive impact models for health and hydrology in Africa

NASA Astrophysics Data System (ADS)

Di Giuseppe, F.; Tompkins, A. M.; Lowe, R.; Dutra, E.; Wetterhall, F.

2012-04-01

As the quality of numerical weather prediction over the monthly to seasonal leadtimes steadily improves there is an increasing motivation to apply these fruitfully to the impacts sectors of health, water, energy and agriculture. Despite these improvements, the accuracy of fields such as temperature and precipitation that are required to drive sectoral models can still be poor. This is true globally, but particularly so in Africa, the region of focus in the present study. In the last year ECMWF has been particularly active through EU research founded projects in demonstrating the capability of its longer range forecasting system to drive impact modeling systems in this region. A first assessment on the consequences of the documented errors in ECMWF forecasting system is therefore presented here looking at two different application fields which we found particularly critical for Africa - vector-born diseases prevention and hydrological monitoring. A new malaria community model (VECTRI) has been developed at ICTP and tested for the 3 target regions participating in the QWECI project. The impacts on the mean malaria climate is assessed using the newly realized seasonal forecasting system (Sys4) with the dismissed system 3 (Sys3) which had the same model cycle of the up-to-date ECMWF re-analysis product (ERA-Interim). The predictive skill of Sys4 to be employed for malaria monitoring and forecast are also evaluated by aggregating the fields to country level. As a part of the DEWFORA projects, ECMWF is also developing a system for drought monitoring and forecasting over Africa whose main meteorological input is precipitation. Similarly to what is done for the VECTRI model, the skill of seasonal forecasts of precipitation is, in this application, translated into the capability of predicting drought while ERA-Interim is used in monitoring. On a monitoring level, the near real-time update of ERA-Interim could compensate the lack of observations in the regions. However, ERA-Interim suffers from biases and drifts that limit its application for drought monitoring purposes in some regions.

MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)

EPA Science Inventory

We propose a multivariate linear mixed (MLMM) for the analysis of multiple outcomes, which generalizes the latent variable model of Sammel and Ryan. The proposed model assumes a flexible correlation structure among the multiple outcomes, and allows a global test of the impact of ...

Electricity Consumption in the Industrial Sector of Jordan: Application of Multivariate Linear Regression and Adaptive Neuro-Fuzzy Techniques

NASA Astrophysics Data System (ADS)

Samhouri, M.; Al-Ghandoor, A.; Fouad, R. H.

2009-08-01

In this study two techniques, for modeling electricity consumption of the Jordanian industrial sector, are presented: (i) multivariate linear regression and (ii) neuro-fuzzy models. Electricity consumption is modeled as function of different variables such as number of establishments, number of employees, electricity tariff, prevailing fuel prices, production outputs, capacity utilizations, and structural effects. It was found that industrial production and capacity utilization are the most important variables that have significant effect on future electrical power demand. The results showed that both the multivariate linear regression and neuro-fuzzy models are generally comparable and can be used adequately to simulate industrial electricity consumption. However, comparison that is based on the square root average squared error of data suggests that the neuro-fuzzy model performs slightly better for future prediction of electricity consumption than the multivariate linear regression model. Such results are in full agreement with similar work, using different methods, for other countries.

Approach and strategy for performing ecological risk assessments for the US Department of Energy`s Oak Ridge Reservation: 1995 revision

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

Suter, G.W. II; Sample, B.E.; Jones, D.S.

1995-09-01

The purpose of this document is to provide guidance for planning and performing ecological risk assessments (ERAs) on the Oak Ridge Reservation (ORR). It is the third such document prepared for this purpose. The first ecorisk strategy document described the ERA process and presented a tiered approach to ERAs appropriate to complex sites. The first revision was necessitated by the considerable progress that has been made by the parties to the Federal Facilities Agreement (FFA) for the ORR in resolving specific issues relating to ERA as a result of a series of data quality objectives (DQOs) meetings. The tiered approachmore » to ERAs as recommended in the first document was implemented, generic conceptual models were developed, and a general approach for developing ecological assessment endpoints and measurement endpoints was agreed upon. This revision is necessitated by comments from the US Environmental Protection Agency`s Region IV and the Tennessee Department of Environment and Conservation (TDEC) which clarified and modified the positions taken during the DQO process. In particular, support for the collection of data that would support ERAs for all OUs on the ORR have been withdrawn. Therefore, the work plan developed to fill the reservation-wide data needs identified in the DQO process has also been withdrawn, and portions that are still relevant have been incorporated into this document. The reader should be aware that this guidance is complex and lengthy because it attempts to cover all the reasonable contingencies that were considered to be potentially important to the FFA parties.« less

Comparing Within-Person Effects from Multivariate Longitudinal Models

ERIC Educational Resources Information Center

Bainter, Sierra A.; Howard, Andrea L.

2016-01-01

Several multivariate models are motivated to answer similar developmental questions regarding within-person (intraindividual) effects between 2 or more constructs over time, yet the within-person effects tested by each model are distinct. In this article, the authors clarify the types of within-person inferences that can be made from each model.…

Applying the multivariate time-rescaling theorem to neural population models

PubMed Central

Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

2011-01-01

Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

A review of UK housing policy: ideology and public health.

PubMed

Stewart, J

2005-06-01

The aim of this paper is to review UK public health policy, with a specific reference to housing as a key health determinant, since its inception in the Victorian era to contemporary times. This paper reviews the role of social and private housing policy in the development of the UK public health movement, tracing its initial medical routes through to the current socio-economic model of public health. The paper establishes five distinct ideologically and philosophically driven eras, placing public health and housing within liberal (Victorian era), state interventionist (post World War 1; post World War 2), neoliberal (post 1979) and "Third Way" (post 1997) models, showing the political perspective of policy interventions and overviewing their impact on public health. The paper particularly focuses on the contemporary model of public health since the Acheson Report, and how its recommendations have found their way into policy, also the impact on housing practice. Public health is closely related to political ideology, whether driven by the State, individual or partnership arrangements. The current political system, the Third Way, seeks to promote a sustainable "social contract" between citizens and the State, public, private and voluntary organizations in delivering community-based change in areas where health inequalities can be most progressively and successfully addressed.

Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

NASA Astrophysics Data System (ADS)

Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

2018-03-01

This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

Meta-Analytic Structural Equation Modeling (MASEM): Comparison of the Multivariate Methods

ERIC Educational Resources Information Center

Zhang, Ying

2011-01-01

Meta-analytic Structural Equation Modeling (MASEM) has drawn interest from many researchers recently. In doing MASEM, researchers usually first synthesize correlation matrices across studies using meta-analysis techniques and then analyze the pooled correlation matrix using structural equation modeling techniques. Several multivariate methods of…

MULTIVARIATE RECEPTOR MODELS-CURRENT PRACTICE AND FUTURE TRENDS. (R826238)

EPA Science Inventory

Multivariate receptor models have been applied to the analysis of air quality data for sometime. However, solving the general mixture problem is important in several other fields. This paper looks at the panoply of these models with a view of identifying common challenges and ...

Atmospheric forcing of sea ice anomalies in the Ross Sea polynya region

NASA Astrophysics Data System (ADS)

Dale, Ethan R.; McDonald, Adrian J.; Coggins, Jack H. J.; Rack, Wolfgang

2017-01-01

We investigate the impacts of strong wind events on the sea ice concentration within the Ross Sea polynya (RSP), which may have consequences on sea ice formation. Bootstrap sea ice concentration (SIC) measurements derived from satellite SSM/I brightness temperatures are correlated with surface winds and temperatures from Ross Ice Shelf automatic weather stations (AWSs) and weather models (ERA-Interim). Daily data in the austral winter period were used to classify characteristic weather regimes based on the percentiles of wind speed. For each regime a composite of a SIC anomaly was formed for the entire Ross Sea region and we found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea polynya and vice versa. By analyzing sea ice motion vectors derived from the SSM/I brightness temperatures we find significant sea ice motion anomalies throughout the Ross Sea during strong wind events, which persist for several days after a strong wind event has ended. Strong, negative correlations are found between SIC and AWS wind speed within the RSP indicating that strong winds cause significant advection of sea ice in the region. We were able to partially recreate these correlations using colocated, modeled ERA-Interim wind speeds. However, large AWS and model differences are observed in the vicinity of Ross Island, where ERA-Interim underestimates wind speeds by a factor of 1.7 resulting in a significant misrepresentation of RSP processes in this area based on model data. Thus, the cross-correlation functions produced by compositing based on ERA-Interim wind speeds differed significantly from those produced with AWS wind speeds. In general the rapid decrease in SIC during a strong wind event is followed by a more gradual recovery in SIC. The SIC recovery continues over a time period greater than the average persistence of strong wind events and sea ice motion anomalies. This suggests that sea ice recovery occurs through thermodynamic rather than dynamic processes.

Association of Depressive Symptoms and Heart Rate Variability in Vietnam War-Era Twins: A Longitudinal Twin Difference Study.

PubMed

Huang, Minxuan; Shah, Amit; Su, Shaoyong; Goldberg, Jack; Lampert, Rachel J; Levantsevych, Oleksiy M; Shallenberger, Lucy; Pimple, Pratik; Bremner, J Douglas; Vaccarino, Viola

2018-05-16

Depressive symptoms are associated with lower heart rate variability (HRV), an index of autonomic dysregulation, but the direction of the association remains unclear. To investigate the temporal association between depression and HRV. A longitudinal, cross-lagged twin difference study, with baseline assessments from March 2002 to March 2006 (visit 1) and a 7-year follow-up (visit 2) at an academic research center with participants recruited from a national twin registry. Twins (n = 166) from the Vietnam Era Twin Registry, who served in the US military during the Vietnam War, and were discordant for depression at baseline were recruited. At both visits, depressive symptoms were measured using the Beck Depression Inventory-II (BDI-II), and HRV was measured through 24-hour electrocardiogram monitoring. To assess the direction of the association, within-pair differences in multivariable mixed-effects regression models were examined, and standardized β coefficients for both pathways were calculated. The associations were evaluated separately in monozygotic and dizygotic twins. In the final analytic sample (N = 146), all participants were men, 138 (95%) were white, and the mean (SD) age was 54 (3) years at baseline. Results showed consistent associations between visit 1 HRV and visit 2 BDI score across all HRV domains and models (β coefficients ranging from -0.14 to -0.29), which were not explained by antidepressants or other participant characteristics. The magnitude of the association was similar in the opposite pathway linking visit 1 BDI score to visit 2 HRV, with β coefficients ranging from 0.05 to -0.30, but it was largely explained by antidepressant use. In stratified analysis by zygosity, significant associations were observed in monozygotic and dizygotic twins for the path linking visit 1 HRV to visit 2 BDI score, although the associations were slightly stronger in dizygotic twins. The association between depression and autonomic dysregulation, indexed by HRV, is bidirectional, with stronger evidence suggesting that autonomic function affects depression risk rather than vice versa. The opposite causal pathway from depression to lower HRV is mostly driven by antidepressant use. These findings highlight an important role of autonomic nervous system in the risk of depression and contribute new understanding of the mechanisms underlying the comorbidity of depression and cardiovascular disease.

A Framework for Linking Population Model Development with Ecological Risk Assessment Objectives.

EPA Science Inventory

The value of models that link organism‐level impacts to the responses of a population in ecological risk assessments (ERAs) has been demonstrated extensively over the past few decades. There is little debate about the utility of these models to translate multiple organism&#...

Regression Models For Multivariate Count Data

PubMed Central

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2016-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data. PMID:28348500

Regression Models For Multivariate Count Data.

PubMed

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2017-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.

Cost-Benefit Analysis of the Implementation of an Enhanced Recovery Program in Liver Surgery.

PubMed

Joliat, Gaëtan-Romain; Labgaa, Ismaïl; Hübner, Martin; Blanc, Catherine; Griesser, Anne-Claude; Schäfer, Markus; Demartines, Nicolas

2016-10-01

Enhanced recovery after surgery (ERAS) programs have been shown to ease the postoperative recovery and improve clinical outcomes for various surgery types. ERAS cost-effectiveness was demonstrated for colorectal surgery but not for liver surgery. The present study aim was to analyze the implementation costs and benefits of a specific ERAS program in liver surgery. A dedicated ERAS protocol for liver surgery was implemented in our department in July 2013. The subsequent year all consecutive patients undergoing liver surgery were treated according to this protocol (ERAS group). They were compared in terms of real in-hospital costs with a patient series before ERAS implementation (pre-ERAS group). Mean costs per patient were compared with a bootstrap T test. A cost-minimization analysis was performed. Seventy-four ERAS patients were compared with 100 pre-ERAS patients. There were no significant pre- and intraoperative differences between the two groups, except for the laparoscopy number (n = 18 ERAS, n = 9 pre-ERAS, p = 0.010). Overall postoperative complications were observed in 36 (49 %) and 64 patients (64 %) in the ERAS and pre-ERAS groups, respectively (p = 0.046). The median length of stay was significantly shorter for the ERAS group (8 vs. 10 days, p = 0.006). The total mean costs per patient were €38,726 and €42,356 for ERAS and pre-ERAS (p = 0.467). The cost-minimization analysis showed a total mean cost reduction of €3080 per patient after ERAS implementation. ERAS implementation for liver surgery induced a non-significant decrease in cost compared to standard care. Significant decreased complication rate and hospital stay were observed in the ERAS group.

Can f(T) gravity theories mimic ΛCDM cosmic history

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

Setare, M.R.; Mohammadipour, N., E-mail: rezakord@ipm.ir, E-mail: N.Mohammadipour@uok.ac.ir

2013-01-01

Recently the teleparallel Lagrangian density described by the torsion scalar T has been extended to a function of T. The f(T) modified teleparallel gravity has been proposed as the natural gravitational alternative for dark energy to explain the late time acceleration of the universe. In order to reconstruct the function f(T) by demanding a background ΛCDM cosmology we assume that, (i) the background cosmic history provided by the flat ΛCDM (the radiation ere with ω{sub eff} = (1/3), matter and de Sitter eras with ω{sub eff} = 0 and ω{sub eff} = −1, respectively) (ii) the radiation dominate in themore » radiation era with Ω{sub 0r} = 1 and the matter dominate during the matter phases when Ω{sub 0m} = 1. We find the cosmological dynamical system which can obey the ΛCDM cosmic history. In each era, we find a critical lines that, the radiation dominated and the matter dominated are one points of them in the radiation and matter phases, respectively. Also, we drive the cosmologically viability condition for these models. We investigate the stability condition with respect to the homogeneous scalar perturbations in each era and we obtain the stability conditions for the fixed points in each eras. Finally, we reconstruct the function f(T) which mimics cosmic expansion history.« less

A "Model" Multivariable Calculus Course.

ERIC Educational Resources Information Center

Beckmann, Charlene E.; Schlicker, Steven J.

1999-01-01

Describes a rich, investigative approach to multivariable calculus. Introduces a project in which students construct physical models of surfaces that represent real-life applications of their choice. The models, along with student-selected datasets, serve as vehicles to study most of the concepts of the course from both continuous and discrete…

Bayesian Estimation of Multivariate Latent Regression Models: Gauss versus Laplace

ERIC Educational Resources Information Center

Culpepper, Steven Andrew; Park, Trevor

2017-01-01

A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…

A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series

ERIC Educational Resources Information Center

Zhang, Guangjian; Chow, Sy-Miin; Ong, Anthony D.

2011-01-01

Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a…

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

A joint modeling and estimation method for multivariate longitudinal data with mixed types of responses to analyze physical activity data generated by accelerometers.

PubMed

Li, Haocheng; Zhang, Yukun; Carroll, Raymond J; Keadle, Sarah Kozey; Sampson, Joshua N; Matthews, Charles E

2017-11-10

A mixed effect model is proposed to jointly analyze multivariate longitudinal data with continuous, proportion, count, and binary responses. The association of the variables is modeled through the correlation of random effects. We use a quasi-likelihood type approximation for nonlinear variables and transform the proposed model into a multivariate linear mixed model framework for estimation and inference. Via an extension to the EM approach, an efficient algorithm is developed to fit the model. The method is applied to physical activity data, which uses a wearable accelerometer device to measure daily movement and energy expenditure information. Our approach is also evaluated by a simulation study. Copyright © 2017 John Wiley & Sons, Ltd.

The Mercator Océan operational and reanalysis systems: overview of recent improvements and scientific key issues

NASA Astrophysics Data System (ADS)

Hernandez, F.; Benkiran, M.; Bourdalle-Badie, R.; Bricaud, C.; Cailleau, S.; Chanut, J.; Desportes, C.; Dombrowsky, E.; drevillon, M.; Drillet, Y.; Elmoussaoui, A.; Ferry, N.; Garric, G.; Greiner, E.; Le Galloudec, O.; Lellouche, J.; Levier, B.; Parent, L.; Perruche, C.; Reffray, G.; Regnier, C.; Rémy, E.; Testut, C.; Tranchant, B.

2011-12-01

In the framework of the European project GMES/MyOcean, Mercator Océan has designed a hierarchy of ocean analysis, forecasting and reanalysis systems based on numerical models of the ocean/sea-ice, data assimilation methods and biogeochemistry model. Operational weekly analysis provide initial conditions for daily predictions. All ocean model configurations are based on NEMO. The 1/4° global and 1/12° Atlantic and Mediterranean configurations are improved with (i) the use of high frequency (3h) atmospheric forcings including the diurnal cycle, (ii) the use of the CORE bulk formulation, (iii) the use of a new TKE vertical mixing scheme, (iv) the use of the LIM2-EVP ice model. Leading to a better representation of the diurnal cycle, the stratification in upper layers, the sea-ice interannual extensions, or mesoscale features and WBC in the 1/12°. The 1/36° IBI regional configuration, adds non linear free surface, atmospheric pressure and tidal forcing, barotropic/baroclinic time splitting, and specific boundary conditions for operational nesting with the global system. At regional scale, a number of improvements (bathymetry and bottom friction) make it suitable for coastal modelling, validated state-of-art coastal ocean models. Data assimilation is based on reduced order Kalman filter using 3D multivariate modal decomposition of the forecast error. It assimilates jointly satellite altimetry, SST and in situ observations (temperature and salinity profiles, including ARGO data). Among difficulties, the assimilation has to be operated in real time, with limited and less accurate set of observations. Recent improvements in the global systems include (v) the insertion of the zonal/meridional velocity components into the control vector, (vi) the use of the IAU procedure, (vii) the insertion of new observational operators, (viii) the use of a new MDT, (ix) the introduction of pseudo-observations, (x) the use of a bias correction method based on a variational approach to estimate large scale biases. These improvements limit noise introduced by sequential assimilation, like in in the vertical dynamics. Water masses, on the shelves or near major run-off, like the Amazon discharge, are preserved. A biogeochemistry prediction system has been added, based on PISCES model. it uses spatial degradation of the real time physic provides by the 1/4° global system. A reanalysis covering the "altimetric era" (1992-2009) has been carried out in collaboration with the Drakkar community. GLORYS reanalyses describe the evolution of the ocean and sea-ice states; It is based on Mercator operational 1/4° global system, but with 75 levels vertical grid, ERA-Interim atmospheric forcing fields (corrected with satellite-based fluxes) and the assimilation of delayed time reprocessed and quality controlled observations. First studies show the reanalysis usefulness for interannual assessment of the mesoscale dynamics, but also the thermohaline circulations changes like MOC.

Brief Communication: Upper Air Relaxation in RACMO2 Significantly Improves Modelled Interannual Surface Mass Balance Variability in Antarctica

NASA Technical Reports Server (NTRS)

van de Berg, W. J.; Medley, B.

2016-01-01

The Regional Atmospheric Climate Model (RACMO2) has been a powerful tool for improving surface mass balance (SMB) estimates from GCMs or reanalyses. However, new yearly SMB observations for West Antarctica show that the modelled interannual variability in SMB is poorly simulated by RACMO2, in contrast to ERA-Interim, which resolves this variability well. In an attempt to remedy RACMO2 performance, we included additional upper-air relaxation (UAR) in RACMO2. With UAR, the correlation to observations is similar for RACMO2 and ERA-Interim. The spatial SMB patterns and ice-sheet-integrated SMB modelled using UAR remain very similar to the estimates of RACMO2 without UAR. We only observe an upstream smoothing of precipitation in regions with very steep topography like the Antarctic Peninsula. We conclude that UAR is a useful improvement for regional climate model simulations, although results in regions with steep topography should be treated with care.

Observing Inflationary Reheating

NASA Astrophysics Data System (ADS)

Martin, Jérôme; Ringeval, Christophe; Vennin, Vincent

2015-02-01

Reheating is the epoch which connects inflation to the subsequent hot big-bang phase. Conceptually very important, this era is, however, observationally poorly known. We show that the current Planck satellite measurements of the cosmic microwave background (CMB) anisotropies constrain the kinematic properties of the reheating era for most of the inflationary models. This result is obtained by deriving the marginalized posterior distributions of the reheating parameter for about 200 models of slow-roll inflation. Weighted by the statistical evidence of each model to explain the data, we show that the Planck 2013 measurements induce an average reduction of the posterior-to-prior volume by 40%. Making some additional assumptions on reheating, such as specifying a mean equation of state parameter, or focusing the analysis on peculiar scenarios, can enhance or reduce this constraint. Our study also indicates that the Bayesian evidence of a model can substantially be affected by the reheating properties. The precision of the current CMB data is therefore such that estimating the observational performance of a model now requires incorporating information about its reheating history.

Load compensation in a lean burn natural gas vehicle

NASA Astrophysics Data System (ADS)

Gangopadhyay, Anupam

A new multivariable PI tuning technique is developed in this research that is primarily developed for regulation purposes. Design guidelines are developed based on closed-loop stability. The new multivariable design is applied in a natural gas vehicle to combine idle and A/F ratio control loops. This results in better recovery during low idle operation of a vehicle under external step torques. A powertrain model of a natural gas engine is developed and validated for steady-state and transient operation. The nonlinear model has three states: engine speed, intake manifold pressure and fuel fraction in the intake manifold. The model includes the effect of fuel partial pressure in the intake manifold filling and emptying dynamics. Due to the inclusion of fuel fraction as a state, fuel flow rate into the cylinders is also accurately modeled. A linear system identification is performed on the nonlinear model. The linear model structure is predicted analytically from the nonlinear model and the coefficients of the predicted transfer function are shown to be functions of key physical parameters in the plant. Simulations of linear system and model parameter identification is shown to converge to the predicted values of the model coefficients. The multivariable controller developed in this research could be designed in an algebraic fashion once the plant model is known. It is thus possible to implement the multivariable PI design in an adaptive fashion combining the controller with identified plant model on-line. This will result in a self-tuning regulator (STR) type controller where the underlying design criteria is the multivariable tuning technique designed in this research.

Models and (some) Searches for CPT Violation: From Early Universe to the Present Era

NASA Astrophysics Data System (ADS)

Mavromatos, Nick E.

2017-07-01

In the talk, I review theoretical models, inspired by quantum gravity, that may violate CPT symmetry. The amount of violation today (which is constrained severely by a plethora of experiments that I will not describe due to lack of space) need not be the same with the one that occurred in the Early Universe,. In certain models, one can obtain a precise temperature dependence of CPT violating effects, which is such that these effects are significant during the radiation era of the Universe, but are damped quickly so that they do not to affect nucleosynthesis and are negligible in the present epoch (that is, beyond experimental detection with the current experimental sensitivity). The CPT Violation (CPTV) in these models may arise from special properties of the background over which the fields of the model are propagating upon and be responsible for the generation of a matter-antimatter asymmetry, where any CP violation effects could only assist in the creation of the asymmetry, the dominant effect being CPTV. However, there are cases, where the CPTV arises as a consequence of an ill-defined CPT operator due to decoherence as a result of quantum gravity environmental degrees of freedom, inaccessible to a low-energy observer. I also discuss briefly the current-era phenomenology of some of the above models; in particular, for the ones involving decoherence-induced CPT violation, I argue that entangled states of neutral mesons (Kaons or B-systems) can provide smoking-gun sensitive tests or even falsify some of these models. If CPT is ill-defined one may also encounter violations of the spin-statistics theorem, with possible consequences for the Pauli Exclusion Principle.

Tropical cyclone genesis potential index over the western North Pacific simulated by CMIP5 models

NASA Astrophysics Data System (ADS)

Song, Yajuan; Wang, Lei; Lei, Xiaoyan; Wang, Xidong

2015-11-01

Tropical cyclone (TC) genesis over the western North Pacific (WNP) is analyzed using 23 CMIP5 (Coupled Model Intercomparison Project Phase 5) models and reanalysis datasets. The models are evaluated according to TC genesis potential index (GPI). The spatial and temporal variations of the GPI are first calculated using three atmospheric reanalysis datasets (ERA-Interim, NCEP/NCAR Reanalysis-1, and NCEP/DOE Reanalysis-2). Spatial distributions of July-October-mean TC frequency based on the GPI from ERA-interim are more consistent with observed ones derived from IBTrACS global TC data. So, the ERA-interim reanalysis dataset is used to examine the CMIP5 models in terms of reproducing GPI during the period 1982-2005. Although most models possess deficiencies in reproducing the spatial distribution of the GPI, their multimodel ensemble (MME) mean shows a reasonable climatological GPI pattern characterized by a high GPI zone along 20°N in the WNP. There was an upward trend of TC genesis frequency during 1982 to 1998, followed by a downward trend. Both MME results and reanalysis data can represent a robust increasing trend during 1982-1998, but the models cannot simulate the downward trend after 2000. Analysis based on future projection experiments shows that the GPI exhibits no significant change in the first half of the 21st century, and then starts to decrease at the end of the 21st century under the representative concentration pathway (RCP) 2.6 scenario. Under the RCP8.5 scenario, the GPI shows an increasing trend in the vicinity of 20°N, indicating more TCs could possibly be expected over the WNP under future global warming.

Impact of generic antiretroviral therapy (ART) and free ART programs on time to initiation of ART at a tertiary HIV care center in Chennai, India.

PubMed

Solomon, Sunil S; Lucas, Gregory M; Kumarasamy, Nagalingeswaran; Yepthomi, Tokugha; Balakrishnan, Pachamuthu; Ganesh, Aylur K; Anand, Santhanam; Moore, Richard D; Solomon, Suniti; Mehta, Shruti H

2013-08-01

Antiretroviral therapy (ART) access in the developing world has improved, but whether increased access has translated to more rapid treatment initiation among those who need it is unknown. We characterize time to ART initiation across three eras of ART availability in Chennai, India (1996-1999: pregeneric; 2000-2003: generic; 2004-2007: free rollout). Between 1996 and 2007, 11,171 patients registered for care at the YR Gaitonde Centre for AIDS Research and Education (YRGCARE), a tertiary HIV referral center in southern India. Of these, 5726 patients became eligible for ART during this period as per Indian guidelines for initiation of ART. Generalized gamma survival models were used to estimate relative times (RT) to ART initiation by calendar periods of eligibility. Time to initiation of ART among patients in Chennai, India was also compared to an HIV clinical cohort in Baltimore, USA. Median age of the YRGCARE patients was 34 years; 77% were male. The median CD4 at presentation was 140 cells/µl. After adjustment for demographics, CD4 and WHO stage, persons in the pregeneric era took 3.25 times longer (95% confidence interval [CI]: 2.53-4.17) to initiate ART versus the generic era and persons in the free rollout era initiated ART more rapidly than the generic era (RT: 0.73; 95% CI: 0.63-0.83). Adjusting for differences across centers, patients at YRGCARE took longer than patients in the Johns Hopkins Clinical Cohort (JHCC) to initiate ART in the pregeneric era (RT: 4.90; 95% CI: 3.37-7.13) but in the free rollout era, YRGCARE patients took only about a quarter of the time (RT: 0.31; 95% CI: 0.22-0.44). These data demonstrate the benefits of generic ART and government rollouts on time to initiation of ART in one developing country setting and suggests that access to ART may be comparable to developed country settings.

Decreasing incidence of symptomatic Epstein-Barr virus disease and posttransplant lymphoproliferative disorder in pediatric liver transplant recipients: report of the studies of pediatric liver transplantation experience.

PubMed

Narkewicz, Michael R; Green, Michael; Dunn, Stephen; Millis, Michael; McDiarmid, Susan; Mazariegos, George; Anand, Ravinder; Yin, Wanrong

2013-07-01

Posttransplant lymphoproliferative disorder (PTLD) causes significant morbidity and mortality in pediatric recipients of liver transplantation (LT). Describe the incidence of PTLD and symptomatic Epstein-Barr virus (SEBV) disease in a large multicenter cohort of children who underwent LT with a focus on the risk factors and changes in incidence over time. SEBV and PTLD were prospectively determined in 2283 subjects who had undergone LT for the first time with at least 1 year of follow-up in the Studies of Pediatric Liver Transplantation database. SEBV was defined with specific criteria, and PTLD required tissue confirmation. The incidence of SEBV and PTLD was determined with a Kaplan-Meier analysis. Univariate and multivariate modeling of risk factors was performed with standard methods. SEBV occurred in 199 patients; 174 (87.4%) were EBV-negative at LT. Seventy-five patients developed PTLD, and 64 (85.3%) of these patients were EBV-negative at LT. Among the 2048 patients with at least 2 years of follow-up, 8.3% developed SEBV by the second year after LT, and 2.8% developed PTLD. There were lower rates of SEBV (5.9% versus 11.3%, P < 0.001) and PTLD (1.7% versus 4.2%, P = 0.001) in 2002-2007 versus 1995-2001. In 2002-2007, tacrolimus and cyclosporine trough blood levels in the first year after LT were significantly lower, and fewer children were receiving steroids. Biliary atresia, and recipient EBV status were correlated. In a multivariate analysis, era of LT, recipient EBV status, and frequent rejection episodes were associated with SEBV and PTLD. The incidence of SEBV and PTLD is decreasing in pediatric LT recipients concomitantly with a reduction in immunosuppression. Younger recipients and those with multiple rejections remain at higher risk for SEBV and PTLD. © 2013 American Association for the Study of Liver Diseases.

Practical implications for genetic modeling in the genomics era for the dairy industry

USDA-ARS?s Scientific Manuscript database

Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, incl...

Applying the Sport Education Model to Tennis

ERIC Educational Resources Information Center

Ayvazo, Shiri

2009-01-01

The physical education field abounds with theoretically sound curricular approaches such as fitness education, skill theme approach, tactical approach, and sport education. In an era that emphasizes authentic sport experiences, the Sport Education Model includes unique features that sets it apart from other curricular models and can be a valuable…

A Framework for Linking Population Model Development with Ecological Risk Assessment Objectives

EPA Science Inventory

The value of models that link organism-level impacts to the responses of a population in ecological risk assessments (ERA) has been demonstrated extensively over the past few decades. There is little debate about the utility of these models to translate multiple organism-level en...

Practical robustness measures in multivariable control system analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Lehtomaki, N. A.

1981-01-01

The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed.

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

Multivariate Phylogenetic Comparative Methods: Evaluations, Comparisons, and Recommendations.

PubMed

Adams, Dean C; Collyer, Michael L

2018-01-01

Recent years have seen increased interest in phylogenetic comparative analyses of multivariate data sets, but to date the varied proposed approaches have not been extensively examined. Here we review the mathematical properties required of any multivariate method, and specifically evaluate existing multivariate phylogenetic comparative methods in this context. Phylogenetic comparative methods based on the full multivariate likelihood are robust to levels of covariation among trait dimensions and are insensitive to the orientation of the data set, but display increasing model misspecification as the number of trait dimensions increases. This is because the expected evolutionary covariance matrix (V) used in the likelihood calculations becomes more ill-conditioned as trait dimensionality increases, and as evolutionary models become more complex. Thus, these approaches are only appropriate for data sets with few traits and many species. Methods that summarize patterns across trait dimensions treated separately (e.g., SURFACE) incorrectly assume independence among trait dimensions, resulting in nearly a 100% model misspecification rate. Methods using pairwise composite likelihood are highly sensitive to levels of trait covariation, the orientation of the data set, and the number of trait dimensions. The consequences of these debilitating deficiencies are that a user can arrive at differing statistical conclusions, and therefore biological inferences, simply from a dataspace rotation, like principal component analysis. By contrast, algebraic generalizations of the standard phylogenetic comparative toolkit that use the trace of covariance matrices are insensitive to levels of trait covariation, the number of trait dimensions, and the orientation of the data set. Further, when appropriate permutation tests are used, these approaches display acceptable Type I error and statistical power. We conclude that methods summarizing information across trait dimensions, as well as pairwise composite likelihood methods should be avoided, whereas algebraic generalizations of the phylogenetic comparative toolkit provide a useful means of assessing macroevolutionary patterns in multivariate data. Finally, we discuss areas in which multivariate phylogenetic comparative methods are still in need of future development; namely highly multivariate Ornstein-Uhlenbeck models and approaches for multivariate evolutionary model comparisons. © The Author(s) 2017. Published by Oxford University Press on behalf of the Systematic Biology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Worse outcomes for patients undergoing brain tumor and cerebrovascular procedures following the ACGME resident duty-hour restrictions

PubMed Central

Babu, Ranjith; Thomas, Steven; Hazzard, Matthew A.; Friedman, Allan H.; Sampson, John H.; Adamson, Cory; Zomorodi, Ali R.; Haglund, Michael M.; Patil, Chirag G.; Boakye, Maxwell; Lad, Shivanand P.

2015-01-01

Object On July 1, 2003, the Accreditation Council for Graduate Medical Education (ACGME) implemented duty-hour restrictions for resident physicians due to concerns for patient and resident safety. Though duty-hour restrictions have increased resident quality of life, studies have shown mixed results with respect to patient outcomes. In this study, the authors have evaluated the effect of duty-hour restrictions on morbidity, mortality, length of stay, and charges in patients who underwent brain tumor and cerebrovascular procedures. Methods The Nationwide Inpatient Sample was used to evaluate the effect of duty-hour restrictions on complications, mortality, length of stay, and charges by comparing the pre-reform (2000–2002) and post-reform (2005–2008) periods. Outcomes were compared between nonteaching and teaching hospitals using a difference-in-differences (DID) method. Results A total of 90,648 patients were included in the analysis. The overall complication rate was 11.7%, with the rates not significantly differing between the pre –and post–duty hour eras (p = 0.26). Examination of hospital teaching status revealed that complication rates decreased in nonteaching hospitals (12.1% vs 10.4%, p = 0.0004) and remained stable in teaching institutions (11.8% vs 11.9%, p = 0.73) in the post-reform era. Multivariate analysis demonstrated a significantly higher complication risk in teaching institutions (OR 1.33 [95% CI 1.11–1.59], p = 0.0022), with no significant change in nonteaching hospitals (OR 1.11 [95% CI 0.91–1.37], p = 0.31). A DID analysis to compare the magnitude in change between teaching and nonteaching institutions revealed that teaching hospitals had a significantly greater increase in complications during the post-reform era than nonteaching hospitals (p = 0.040). The overall mortality rate was 3.0%, with a significant decrease occurring in the post-reform era in both nonteaching (5.0% vs 3.2%, p < 0.0001) and teaching (3.2% vs 2.3%, p < 0.0001) hospitals. DID analysis to compare the changes in mortality between groups did not reveal a significant difference (p = 0.40). The mean length of stay for all patients was 8.7 days, with hospital stay decreasing from 9.2 days to 8.3 days in the post-reform era (p < 0.0001). The DID analysis revealed a greater length of stay decrease in nonteaching hospitals than teaching institutions, which approached significance (p = 0.055). Patient charges significantly increased in the post-reform era for all patients, increasing from $70,900 to $96,100 (p < 0.0001). The DID analysis did not reveal a significant difference between the changes in charges between teaching and nonteaching hospitals (p = 0.17). Conclusions The implementation of duty-hour restrictions correlated with an increased risk of postoperative complications for patients undergoing brain tumor and cerebrovascular neurosurgical procedures. Duty-hour reform may therefore be associated with worse patient outcomes, contrary to its intended purpose. Due to the critical condition of many neurosurgical patients, this patient population is most sensitive and likely to be negatively affected by proposed future increased restrictions. PMID:24926647

Worse outcomes for patients undergoing brain tumor and cerebrovascular procedures following the ACGME resident duty-hour restrictions.

PubMed

Babu, Ranjith; Thomas, Steven; Hazzard, Matthew A; Friedman, Allan H; Sampson, John H; Adamson, Cory; Zomorodi, Ali R; Haglund, Michael M; Patil, Chirag G; Boakye, Maxwell; Lad, Shivanand P

2014-08-01

On July 1, 2003, the Accreditation Council for Graduate Medical Education (ACGME) implemented duty-hour restrictions for resident physicians due to concerns for patient and resident safety. Though duty-hour restrictions have increased resident quality of life, studies have shown mixed results with respect to patient outcomes. In this study, the authors have evaluated the effect of duty-hour restrictions on morbidity, mortality, length of stay, and charges in patients who underwent brain tumor and cerebrovascular procedures. The Nationwide Inpatient Sample was used to evaluate the effect of duty-hour restrictions on complications, mortality, length of stay, and charges by comparing the pre-reform (2000-2002) and post-reform (2005-2008) periods. Outcomes were compared between nonteaching and teaching hospitals using a difference-in-differences (DID) method. A total of 90,648 patients were included in the analysis. The overall complication rate was 11.7%, with the rates not significantly differing between the pre- and post-duty hour eras (p = 0.26). Examination of hospital teaching status revealed that complication rates decreased in nonteaching hospitals (12.1% vs 10.4%, p = 0.0004) and remained stable in teaching institutions (11.8% vs 11.9%, p = 0.73) in the post-reform era. Multivariate analysis demonstrated a significantly higher complication risk in teaching institutions (OR 1.33 [95% CI 1.11-1.59], p = 0.0022), with no significant change in nonteaching hospitals (OR 1.11 [95% CI 0.91-1.37], p = 0.31). A DID analysis to compare the magnitude in change between teaching and nonteaching institutions revealed that teaching hospitals had a significantly greater increase in complications during the post-reform era than nonteaching hospitals (p = 0.040). The overall mortality rate was 3.0%, with a significant decrease occurring in the post-reform era in both nonteaching (5.0% vs 3.2%, p < 0.0001) and teaching (3.2% vs 2.3%, p < 0.0001) hospitals. DID analysis to compare the changes in mortality between groups did not reveal a significant difference (p = 0.40). The mean length of stay for all patients was 8.7 days, with hospital stay decreasing from 9.2 days to 8.3 days in the post-reform era (p < 0.0001). The DID analysis revealed a greater length of stay decrease in nonteaching hospitals than teaching institutions, which approached significance (p = 0.055). Patient charges significantly increased in the post-reform era for all patients, increasing from $70,900 to $96,100 (p < 0.0001). The DID analysis did not reveal a significant difference between the changes in charges between teaching and nonteaching hospitals (p = 0.17). The implementation of duty-hour restrictions correlated with an increased risk of postoperative complications for patients undergoing brain tumor and cerebrovascular neurosurgical procedures. Duty-hour reform may therefore be associated with worse patient outcomes, contrary to its intended purpose. Due to the critical condition of many neurosurgical patients, this patient population is most sensitive and likely to be negatively affected by proposed future increased restrictions.

Describing the Elephant: Structure and Function in Multivariate Data.

ERIC Educational Resources Information Center

McDonald, Roderick P.

1986-01-01

There is a unity underlying the diversity of models for the analysis of multivariate data. Essentially, they constitute a family of models, most generally nonlinear, for structural/functional relations between variables drawn from a behavior domain. (Author)

Adaptive Significance of ERα Splice Variants in Killifish ...

EPA Pesticide Factsheets

The possibility that chronic, multigenerational exposure to environmental estrogens selects for adaptive hormone response phenotypes is a critical unanswered question. Embryos/larvae of killifish from an estrogenic polluted environment (New Bedford Harbor, NBH), as compared to those from a reference site, overexpress estrogen receptor a (ERa) mRNA but are hypo-responsive to estradiol (E2). Analysis of ERa mRNAs in the two populations revealed differences in splicing of the gene encoding ERa (esr1). Here we tested the transactivation functions of four differentially expressed ERa mRNAs and tracked their association with the hypo-responsive phenotype for three generations after transfer of NBH parents to a clean environment. Deletion variants ERaΔ6 and ERaΔ6 – 8 were specific to NBH killifish; had dominant negative functions in an in vitro reporter assay; and were heritable. Morpholino-mediated induction of ERaΔ6 mRNA in zebrafish embryos verified its role as a dominant negative ER on natural estrogen-responsive promoters. Alternate long (ERaL) and short (ERaS) 5'-variants were similar transcriptionally but differed in estrogen responsiveness (ERaS >> ERaL). ERaS accounted for high total ERa expression in F1 NBH embryos/ larvae but this trait was abolished by transfer to clean water. By contrast, the hypo-responsive phenotype of F1 NBH embryos/larvae persisted after long term lab holding but reverted to a normal or hyper-responsive phenotype after two or thre

Dynamics of interacting quintessence models: Observational constraints

NASA Astrophysics Data System (ADS)

Olivares, Germán; Atrio-Barandela, Fernando; Pavón, Diego

2008-03-01

Interacting quintessence models have been proposed to explain or, at least, alleviate the coincidence problem of late cosmic acceleration. In this paper we are concerned with two aspects of these kind of models: (i) the dynamical evolution of the model of Chimento et al. [L. P. Chimento, A. S. Jakubi, D. Pavón, and W. Zimdahl, Phys. Rev. D 67, 083513 (2003).PRVDAQ0556-282110.1103/PhysRevD.67.083513], i.e., whether its cosmological evolution gives rise to a right sequence of radiation, dark matter, and dark energy dominated eras, and (ii) whether the dark matter dark energy ratio asymptotically evolves towards a nonzero constant. After showing that the model correctly reproduces these eras, we correlate three data sets that constrain the interaction at three redshift epochs: z≤104, z=103, and z=1. We discuss the model selection and argue that even if the model under consideration fulfills both requirements, it is heavily constrained by observation. The prospects that the coincidence problem can be explained by the coupling of dark matter to dark energy are not clearly favored by the data.

Modeling the Earth system in the Mission to Planet Earth era

NASA Technical Reports Server (NTRS)

Unninayar, Sushel; Bergman, Kenneth H.

1993-01-01

A broad overview is made of global earth system modeling in the Mission to Planet Earth (MTPE) era for the multidisciplinary audience encompassed by the Global Change Research Program (GCRP). Time scales of global system fluctuation and change are described in Section 2. Section 3 provides a rubric for modeling the global earth system, as presently understood. The ability of models to predict the future state of the global earth system and the extent to which their predictions are reliable are covered in Sections 4 and 5. The 'engineering' use of global system models (and predictions) is covered in Section 6. Section 7 covers aspects of an increasing need for improved transform algorithms and better methods to assimilate this information into global models. Future monitoring and data requirements are detailed in Section 8. Section 9 covers the NASA-initiated concept 'Mission to Planet Earth,' which employs space and ground based measurement systems to provide the scientific basis for understanding global change. Section 10 concludes this review with general remarks concerning the state of global system modeling and observing technology and the need for future research.

Clinical risk assessment of patients with chronic kidney disease by using clinical data and multivariate models.

PubMed

Chen, Zewei; Zhang, Xin; Zhang, Zhuoyong

2016-12-01

Timely risk assessment of chronic kidney disease (CKD) and proper community-based CKD monitoring are important to prevent patients with potential risk from further kidney injuries. As many symptoms are associated with the progressive development of CKD, evaluating risk of CKD through a set of clinical data of symptoms coupled with multivariate models can be considered as an available method for prevention of CKD and would be useful for community-based CKD monitoring. Three common used multivariate models, i.e., K-nearest neighbor (KNN), support vector machine (SVM), and soft independent modeling of class analogy (SIMCA), were used to evaluate risk of 386 patients based on a series of clinical data taken from UCI machine learning repository. Different types of composite data, in which proportional disturbances were added to simulate measurement deviations caused by environment and instrument noises, were also utilized to evaluate the feasibility and robustness of these models in risk assessment of CKD. For the original data set, three mentioned multivariate models can differentiate patients with CKD and non-CKD with the overall accuracies over 93 %. KNN and SVM have better performances than SIMCA has in this study. For the composite data set, SVM model has the best ability to tolerate noise disturbance and thus are more robust than the other two models. Using clinical data set on symptoms coupled with multivariate models has been proved to be feasible approach for assessment of patient with potential CKD risk. SVM model can be used as useful and robust tool in this study.

Cole-Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass.

PubMed

Dabros, Michal; Dennewald, Danielle; Currie, David J; Lee, Mark H; Todd, Robert W; Marison, Ian W; von Stockar, Urs

2009-02-01

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole-Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole-Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole-Cole and PLS models, the latter technique giving more satisfactory results.

Multivariate regression model for predicting lumber grade volumes of northern red oak sawlogs

Treesearch

Daniel A. Yaussy; Robert L. Brisbin

1983-01-01

A multivariate regression model was developed to predict green board-foot yields for the seven common factory lumber grades processed from northern red oak (Quercus rubra L.) factory grade logs. The model uses the standard log measurements of grade, scaling diameter, length, and percent defect. It was validated with an independent data set. The model...

A Hierarchical Multivariate Bayesian Approach to Ensemble Model output Statistics in Atmospheric Prediction

DTIC Science & Technology

2017-09-01

efficacy of statistical post-processing methods downstream of these dynamical model components with a hierarchical multivariate Bayesian approach to...Bayesian hierarchical modeling, Markov chain Monte Carlo methods , Metropolis algorithm, machine learning, atmospheric prediction 15. NUMBER OF PAGES...scale processes. However, this dissertation explores the efficacy of statistical post-processing methods downstream of these dynamical model components

Predictive and mechanistic multivariate linear regression models for reaction development

PubMed Central

Santiago, Celine B.; Guo, Jing-Yao

2018-01-01

Multivariate Linear Regression (MLR) models utilizing computationally-derived and empirically-derived physical organic molecular descriptors are described in this review. Several reports demonstrating the effectiveness of this methodological approach towards reaction optimization and mechanistic interrogation are discussed. A detailed protocol to access quantitative and predictive MLR models is provided as a guide for model development and parameter analysis. PMID:29719711

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Power of Models in Longitudinal Study: Findings from a Full-Crossed Simulation Design

ERIC Educational Resources Information Center

Fang, Hua; Brooks, Gordon P.; Rizzo, Maria L.; Espy, Kimberly Andrews; Barcikowski, Robert S.

2009-01-01

Because the power properties of traditional repeated measures and hierarchical multivariate linear models have not been clearly determined in the balanced design for longitudinal studies in the literature, the authors present a power comparison study of traditional repeated measures and hierarchical multivariate linear models under 3…

Species distribution modelling for plant communities: Stacked single species or multivariate modelling approaches?

Treesearch

Emilie B. Henderson; Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Harold S.J. Zald

2014-01-01

Landscape management and conservation planning require maps of vegetation composition and structure over large regions. Species distribution models (SDMs) are often used for individual species, but projects mapping multiple species are rarer. We compare maps of plant community composition assembled by stacking results from many SDMs with multivariate maps constructed...

IRT-ZIP Modeling for Multivariate Zero-Inflated Count Data

ERIC Educational Resources Information Center

Wang, Lijuan

2010-01-01

This study introduces an item response theory-zero-inflated Poisson (IRT-ZIP) model to investigate psychometric properties of multiple items and predict individuals' latent trait scores for multivariate zero-inflated count data. In the model, two link functions are used to capture two processes of the zero-inflated count data. Item parameters are…

Genetically modified crops and aquatic ecosystems: considerations for environmental risk assessment and non-target organism testing.

PubMed

Carstens, Keri; Anderson, Jennifer; Bachman, Pamela; De Schrijver, Adinda; Dively, Galen; Federici, Brian; Hamer, Mick; Gielkens, Marco; Jensen, Peter; Lamp, William; Rauschen, Stefan; Ridley, Geoff; Romeis, Jörg; Waggoner, Annabel

2012-08-01

Environmental risk assessments (ERA) support regulatory decisions for the commercial cultivation of genetically modified (GM) crops. The ERA for terrestrial agroecosystems is well-developed, whereas guidance for ERA of GM crops in aquatic ecosystems is not as well-defined. The purpose of this document is to demonstrate how comprehensive problem formulation can be used to develop a conceptual model and to identify potential exposure pathways, using Bacillus thuringiensis (Bt) maize as a case study. Within problem formulation, the insecticidal trait, the crop, the receiving environment, and protection goals were characterized, and a conceptual model was developed to identify routes through which aquatic organisms may be exposed to insecticidal proteins in maize tissue. Following a tiered approach for exposure assessment, worst-case exposures were estimated using standardized models, and factors mitigating exposure were described. Based on exposure estimates, shredders were identified as the functional group most likely to be exposed to insecticidal proteins. However, even using worst-case assumptions, the exposure of shredders to Bt maize was low and studies supporting the current risk assessments were deemed adequate. Determining if early tier toxicity studies are necessary to inform the risk assessment for a specific GM crop should be done on a case by case basis, and should be guided by thorough problem formulation and exposure assessment. The processes used to develop the Bt maize case study are intended to serve as a model for performing risk assessments on future traits and crops.

Global Trends and Variability in Integrated Water Vapor from Ground-Based GPS Data and Climate Models

NASA Astrophysics Data System (ADS)

Bock, O.; Parracho, A. C.; Bastin, S.; Hourdin, F.

2016-12-01

A high-quality, consistent, global, long-term dataset of integrated water vapor (IWV) was produced from Global Positioning System (GPS) measurements at more than 400 sites over the globe among which 120 sites have more than 15 years of data. The GPS delay data were converted to IWV using surface pressure and weighted mean temperature estimates from ERA-Interim reanalysis. A two-step screening method was developed to detect and remove outliers in the IWV data. It is based on: 1) GPS data processing information and delay formal errors, and 2) inter-comparison with ERA-Interim reanalysis data. The GPS IWV data are also homogenized to correct for offsets due to instrumental changes and other unknown factors. The differential homogenization method uses ERA-Interim IWV as a reference. The resulting GPS data are used to document the mean distribution, the global trends and the variability of IWV over the period 1995-2010, and to assess global climate model simulations extracted from the IPCC AR5 archive. Large coherent spatial patterns of moistening and drying are evidenced but significant discrepancies are also seen between GPS measurements, reanalysis and climate models in various regions. In terms of variability, the monthly mean anomalies are inter-compared. The temporal correlation between GPS and the climate model simulations is overall quite small but the spatial variation of the magnitude of the anomalies is globally well simulated. GPS IWV data prove to be useful to validate global climate model simulations and highlight deficiencies in their representation of the water cycle.

A flexible model for multivariate interval-censored survival times with complex correlation structure.

PubMed

Falcaro, Milena; Pickles, Andrew

2007-02-10

We focus on the analysis of multivariate survival times with highly structured interdependency and subject to interval censoring. Such data are common in developmental genetics and genetic epidemiology. We propose a flexible mixed probit model that deals naturally with complex but uninformative censoring. The recorded ages of onset are treated as possibly censored ordinal outcomes with the interval censoring mechanism seen as arising from a coarsened measurement of a continuous variable observed as falling between subject-specific thresholds. This bypasses the requirement for the failure times to be observed as falling into non-overlapping intervals. The assumption of a normal age-of-onset distribution of the standard probit model is relaxed by embedding within it a multivariate Box-Cox transformation whose parameters are jointly estimated with the other parameters of the model. Complex decompositions of the underlying multivariate normal covariance matrix of the transformed ages of onset become possible. The new methodology is here applied to a multivariate study of the ages of first use of tobacco and first consumption of alcohol without parental permission in twins. The proposed model allows estimation of the genetic and environmental effects that are shared by both of these risk behaviours as well as those that are specific. 2006 John Wiley & Sons, Ltd.

Can multivariate models based on MOAKS predict OA knee pain? Data from the Osteoarthritis Initiative

NASA Astrophysics Data System (ADS)

Luna-Gómez, Carlos D.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Galván-Tejada, Carlos E.; Celaya-Padilla, José M.

2017-03-01

Osteoarthritis is the most common rheumatic disease in the world. Knee pain is the most disabling symptom in the disease, the prediction of pain is one of the targets in preventive medicine, this can be applied to new therapies or treatments. Using the magnetic resonance imaging and the grading scales, a multivariate model based on genetic algorithms is presented. Using a predictive model can be useful to associate minor structure changes in the joint with the future knee pain. Results suggest that multivariate models can be predictive with future knee chronic pain. All models; T0, T1 and T2, were statistically significant, all p values were < 0.05 and all AUC > 0.60.

Multivariable and Bayesian Network Analysis of Outcome Predictors in Acute Aneurysmal Subarachnoid Hemorrhage: Review of a Pure Surgical Series in the Post-International Subarachnoid Aneurysm Trial Era.

PubMed

Zador, Zsolt; Huang, Wendy; Sperrin, Matthew; Lawton, Michael T

2018-06-01

Following the International Subarachnoid Aneurysm Trial (ISAT), evolving treatment modalities for acute aneurysmal subarachnoid hemorrhage (aSAH) has changed the case mix of patients undergoing urgent surgical clipping. To update our knowledge on outcome predictors by analyzing admission parameters in a pure surgical series using variable importance ranking and machine learning. We reviewed a single surgeon's case series of 226 patients suffering from aSAH treated with urgent surgical clipping. Predictions were made using logistic regression models, and predictive performance was assessed using areas under the receiver operating curve (AUC). We established variable importance ranking using partial Nagelkerke R2 scores. Probabilistic associations between variables were depicted using Bayesian networks, a method of machine learning. Importance ranking showed that World Federation of Neurosurgical Societies (WFNS) grade and age were the most influential outcome prognosticators. Inclusion of only these 2 predictors was sufficient to maintain model performance compared to when all variables were considered (AUC = 0.8222, 95% confidence interval (CI): 0.7646-0.88 vs 0.8218, 95% CI: 0.7616-0.8821, respectively, DeLong's P = .992). Bayesian networks showed that age and WFNS grade were associated with several variables such as laboratory results and cardiorespiratory parameters. Our study is the first to report early outcomes and formal predictor importance ranking following aSAH in a post-ISAT surgical case series. Models showed good predictive power with fewer relevant predictors than in similar size series. Bayesian networks proved to be a powerful tool in visualizing the widespread association of the 2 key predictors with admission variables, explaining their importance and demonstrating the potential for hypothesis generation.

Medicalising normality? Using a simulated dataset to assess the performance of different diagnostic criteria of HIV-associated cognitive impairment

PubMed Central

De Francesco, Davide; Leech, Robert; Sabin, Caroline A.; Winston, Alan

2018-01-01

Objective The reported prevalence of cognitive impairment remains similar to that reported in the pre-antiretroviral therapy era. This may be partially artefactual due to the methods used to diagnose impairment. In this study, we evaluated the diagnostic performance of the HIV-associated neurocognitive disorder (Frascati criteria) and global deficit score (GDS) methods in comparison to a new, multivariate method of diagnosis. Methods Using a simulated ‘normative’ dataset informed by real-world cognitive data from the observational Pharmacokinetic and Clinical Observations in PeoPle Over fiftY (POPPY) cohort study, we evaluated the apparent prevalence of cognitive impairment using the Frascati and GDS definitions, as well as a novel multivariate method based on the Mahalanobis distance. We then quantified the diagnostic properties (including positive and negative predictive values and accuracy) of each method, using bootstrapping with 10,000 replicates, with a separate ‘test’ dataset to which a pre-defined proportion of ‘impaired’ individuals had been added. Results The simulated normative dataset demonstrated that up to ~26% of a normative control population would be diagnosed with cognitive impairment with the Frascati criteria and ~20% with the GDS. In contrast, the multivariate Mahalanobis distance method identified impairment in ~5%. Using the test dataset, diagnostic accuracy [95% confidence intervals] and positive predictive value (PPV) was best for the multivariate method vs. Frascati and GDS (accuracy: 92.8% [90.3–95.2%] vs. 76.1% [72.1–80.0%] and 80.6% [76.6–84.5%] respectively; PPV: 61.2% [48.3–72.2%] vs. 29.4% [22.2–36.8%] and 33.9% [25.6–42.3%] respectively). Increasing the a priori false positive rate for the multivariate Mahalanobis distance method from 5% to 15% resulted in an increase in sensitivity from 77.4% (64.5–89.4%) to 92.2% (83.3–100%) at a cost of specificity from 94.5% (92.8–95.2%) to 85.0% (81.2–88.5%). Conclusion Our simulations suggest that the commonly used diagnostic criteria of HIV-associated cognitive impairment label a significant proportion of a normative reference population as cognitively impaired, which will likely lead to a substantial over-estimate of the true proportion in a study population, due to their lower than expected specificity. These findings have important implications for clinical research regarding cognitive health in people living with HIV. More accurate methods of diagnosis should be implemented, with multivariate techniques offering a promising solution. PMID:29641619

The NASA Modern Era Reanalysis for Research and Applications, Version-2 (MERRA-2)

NASA Astrophysics Data System (ADS)

Gelaro, R.; McCarty, W.; Molod, A.; Suarez, M.; Takacs, L.; Todling, R.

2014-12-01

The NASA Modern Era Reanalysis for Research Applications Version-2 (MERRA-2) is a reanalysis for the satellite era using an updated version of the Goddard Earth Observing System Data Assimilation System Version-5 (GEOS-5) produced by the Global Modeling and Assimilation Office (GMAO). MERRA-2 will assimilate meteorological and aerosol observations not available to MERRA and includes improvements to the GEOS-5 model and analysis scheme so as to provide an ongoing climate analysis beyond MERRA's terminus. MERRA-2 will also serve as a development milestone for a future GMAO coupled Earth system analysis. Production of MERRA-2 began in June 2014 in four processing streams, with convergence to a single near-real time climate analysis expected by early 2015. This talk provides an overview of the MERRA-2 system developments and key science results. For example, compared with MERRA, MERRA-2 exhibits a well-balanced relationship between global precipitation and evaporation, with significantly reduced sensitivity to changes in the global observing system through time. Other notable improvements include reduced biases in the tropical middle- and upper-tropospheric wind and near-surface temperature over continents.

Evolution of FX Markets via Globalization of Capital

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

This paper is about money, and why today's foreign exchange (FX) markets are unstable. According to the literature [1], FX markets were fundamentally different before and after WW I. Any attempt to discuss this topic within standard economic theory necessarily fails because money/liquidity/uncertainty is completely excluded from that theory [2]. Fortunately, our market dynamics models adequately serve our purpose. Eichengreen [1] has presented a stimulating history of the evolution of FX markets from the gold standard of the late nineteenth century through the Bretton Woods Agreement (post WWII-1971) and later the floating currencies of our present market deregulation era (1971-present). He asserts a change from stability to instability over the time interval of WWI. Making his argument precise, we describe how speculators could have made money systematically from a market in statistical equilibrium. The present era normal liquid FX markets are in contrast very hard, to a first approximation impossible, to beat, and consequently are described as `martingales'. The ideas of martingales and options/hedging were irrelevant in the pre-WWI era. I end my historical discussion with the empirical evidence for the stochastic model that describes FX market dynamics quantitatively accurately during the last 7-17 years [3].

Proton-hydrogen collisions for Rydberg n,l-changing transitions in the early Universe

NASA Astrophysics Data System (ADS)

Vrinceanu, Daniel

2013-05-01

Cosmic Microwave Background (CMB) is a vestige radiation generated during the Recombination era, some 390,000 years after the Big Bang, when the Universe had become transparent for the first time. Initial observations of CMB made by the Wilkinson Microwave Anisotropy Probe (WMAP) led to determining the age of the Universe. The mechanisms that drove the recombination have been discovered by using modeling of the primordial plasma and seeking agreement with the observations. The new Plank Surveyor Instrument launched in 2009 is expected to produce data about the recombination era of an unprecedented accuracy, that require including better information regarding the basic atomic physics processes into the present models. In this talk, I will review the results for various Rydberg atom - charge particle collisions and establish their relative importance during the stages of recombination era, with respect to each other and to radiative processes. Energy changing and angular momentum changing collisions with electrons and ions are considered. This work has been supported by NSF through grants to the Institute for Theoretical Atomic and Molecular Physics at Harvard Smithsonian Center for Astrophysics and to the Center for Research on Complex Networks at Texas Southern University.

An integrated approach for prioritizing pharmaceuticals found in the environment for risk assessment, monitoring and advanced research.

PubMed

Caldwell, Daniel J; Mastrocco, Frank; Margiotta-Casaluci, Luigi; Brooks, Bryan W

2014-11-01

Numerous active pharmaceutical ingredients (APIs), approved prior to enactment of detailed environmental risk assessment (ERA) guidance in the EU in 2006, have been detected in surface waters as a result of advancements in analytical technologies. Without adequate knowledge of the potential hazards these APIs may pose, assessing their environmental risk is challenging. As it would be impractical to commence hazard characterization and ERA en masse, several approaches to prioritizing substances for further attention have been published. Here, through the combination of three presentations given at a recent conference, "Pharmaceuticals in the Environment, Is there a problem?" (Nîmes, France, June 2013) we review several of these approaches, identify salient components, and present available techniques and tools that could facilitate a pragmatic, scientifically sound approach to prioritizing APIs for advanced study or ERA and, where warranted, fill critical data gaps through targeted, intelligent testing. We further present a modest proposal to facilitate future prioritization efforts and advanced research studies that incorporates mammalian pharmacology data (e.g., adverse outcomes pathways and the fish plasma model) and modeled exposure data based on pharmaceutical use. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multivariate-$t$ nonlinear mixed models with application to censored multi-outcome AIDS studies.

PubMed

Lin, Tsung-I; Wang, Wan-Lun

2017-10-01

In multivariate longitudinal HIV/AIDS studies, multi-outcome repeated measures on each patient over time may contain outliers, and the viral loads are often subject to a upper or lower limit of detection depending on the quantification assays. In this article, we consider an extension of the multivariate nonlinear mixed-effects model by adopting a joint multivariate-$t$ distribution for random effects and within-subject errors and taking the censoring information of multiple responses into account. The proposed model is called the multivariate-$t$ nonlinear mixed-effects model with censored responses (MtNLMMC), allowing for analyzing multi-outcome longitudinal data exhibiting nonlinear growth patterns with censorship and fat-tailed behavior. Utilizing the Taylor-series linearization method, a pseudo-data version of expectation conditional maximization either (ECME) algorithm is developed for iteratively carrying out maximum likelihood estimation. We illustrate our techniques with two data examples from HIV/AIDS studies. Experimental results signify that the MtNLMMC performs favorably compared to its Gaussian analogue and some existing approaches. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Multivariate analysis of longitudinal rates of change.

PubMed

Bryan, Matthew; Heagerty, Patrick J

2016-12-10

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed in the literature. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, 'accelerated time' methods have been developed which assume that covariates rescale time in longitudinal models for disease progression. In this manuscript, we detail an alternative multivariate model formulation that directly structures longitudinal rates of change and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging

PubMed Central

Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2015-01-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378

Criminal justice involvement, trauma, and negative affect in Iraq and Afghanistan war era veterans.

PubMed

Elbogen, Eric B; Johnson, Sally C; Newton, Virginia M; Straits-Troster, Kristy; Vasterling, Jennifer J; Wagner, H Ryan; Beckham, Jean C

2012-12-01

Although criminal behavior in veterans has been cited as a growing problem, little is known about why some veterans are at increased risk for arrest. Theories of criminal behavior postulate that people who have been exposed to stressful environments or traumatic events and who report negative affect such as anger and irritability are at increased risk of antisocial conduct. We hypothesized veterans with posttraumatic stress disorder (PTSD) or traumatic brain injury (TBI) who report anger/irritability would show higher rates of criminal arrests. To test this, we examined data in a national survey of N = 1,388 Iraq and Afghanistan war era veterans. We found that 9% of respondents reported arrests since returning home from military service. Most arrests were associated with nonviolent criminal behavior resulting in incarceration for less than 2 weeks. Unadjusted bivariate analyses revealed that veterans with probable PTSD or TBI who reported anger/irritability were more likely to be arrested than were other veterans. In multivariate analyses, arrests were found to be significantly related to younger age, male gender, having witnessed family violence, prior history of arrest, alcohol/drug misuse, and PTSD with high anger/irritability but were not significantly related to combat exposure or TBI. Findings show that a subset of veterans with PTSD and negative affect may be at increased risk of criminal arrest. Because arrests were more strongly linked to substance abuse and criminal history, clinicians should also consider non-PTSD factors when evaluating and treating veterans with criminal justice involvement.

Criminal Justice Involvement, Trauma, and Negative Affect in Iraq and Afghanistan War Era Veterans

PubMed Central

Elbogen, Eric B.; Johnson, Sally C.; Newton, Virginia M.; Straits-Troster, Kristy; Vasterling, Jennifer J.; Wagner, H. Ryan; Beckham, Jean C.

2012-01-01

Although criminal behavior in veterans has been cited as a growing problem, little is known about why some veterans are at increased risk for arrest. Theories of criminal behavior postulate that people who have been exposed to stressful environments or traumatic events and who report negative affect such as anger and irritability are at increased risk of antisocial conduct. We thus hypothesized that veterans with posttraumatic stress disorder (PTSD) or traumatic brain injury (TBI) who report anger/irritability would show higher rates of criminal arrests. To test this, we examined data in a national survey of N=1388 Iraq and Afghanistan War Era Veterans. We found that 9% of respondents reported arrests since returning home from military service. Most arrests were associated with nonviolent criminal behavior resulting in incarceration for less than two weeks. Unadjusted bivariate analyses revealed that veterans with probable PTSD or TBI who reported anger/irritability were most likely to be arrested. In multivariate analyses, arrests were found to be significantly related to younger age, male gender, having witnessed family violence, prior history of arrest, alcohol/drug misuse, and PTSD with high anger/irritability but were not significantly related to combat exposure or TBI. Findings show that a subset of veterans with PTSD and negative affect may be at increased risk of criminal arrest. Since arrests are more strongly linked to substance abuse and criminal history, clinicians should also consider non-PTSD factors when evaluating and treating veterans with criminal justice involvement. PMID:23025247

Islet product characteristics and factors related to successful human islet transplantation from the Collaborative Islet Transplant Registry (CITR) 1999-2010.

PubMed

Balamurugan, A N; Naziruddin, B; Lockridge, A; Tiwari, M; Loganathan, G; Takita, M; Matsumoto, S; Papas, K; Trieger, M; Rainis, H; Kin, T; Kay, T W; Wease, S; Messinger, S; Ricordi, C; Alejandro, R; Markmann, J; Kerr-Conti, J; Rickels, M R; Liu, C; Zhang, X; Witkowski, P; Posselt, A; Maffi, P; Secchi, A; Berney, T; O'Connell, P J; Hering, B J; Barton, F B

2014-11-01

The Collaborative Islet Transplant Registry (CITR) collects data on clinical islet isolations and transplants. This retrospective report analyzed 1017 islet isolation procedures performed for 537 recipients of allogeneic clinical islet transplantation in 1999-2010. This study describes changes in donor and islet isolation variables by era and factors associated with quantity and quality of final islet products. Donor body weight and BMI increased significantly over the period (p<0.001). Islet yield measures have improved with time including islet equivalent (IEQ)/particle ratio and IEQs infused. The average dose of islets infused significantly increased in the era of 2007-2010 when compared to 1999-2002 (445.4±156.8 vs. 421.3±155.4×0(3) IEQ; p<0.05). Islet purity and total number of β cells significantly improved over the study period (p<0.01 and <0.05, respectively). Otherwise, the quality of clinical islets has remained consistently very high through this period, and differs substantially from nonclinical islets. In multivariate analysis of all recipient, donor and islet factors, and medical management factors, the only islet product characteristic that correlated with clinical outcomes was total IEQs infused. This analysis shows improvements in both quantity and some quality criteria of clinical islets produced over 1999-2010, and these parallel improvements in clinical outcomes over the same period. © 2014 The Authors. American Journal of Transplantation Published by Wiley Periodicals, Inc. on behalf of American Society of Transplant Surgeons.

Islet Product Characteristics and Factors Related to Successful Human Islet Transplantation From the Collaborative Islet Transplant Registry (CITR) 1999–2010

PubMed Central

Balamurugan, A N; Naziruddin, B; Lockridge, A; Tiwari, M; Loganathan, G; Takita, M; Matsumoto, S; Papas, K; Trieger, M; Rainis, H; Kin, T; Kay, T W; Wease, S; Messinger, S; Ricordi, C; Alejandro, R; Markmann, J; Kerr-Conti, J; Rickels, M R; Liu, C; Zhang, X; Witkowski, P; Posselt, A; Maffi, P; Secchi, A; Berney, T; O’Connell, P J; Hering, B J; Barton, F B

2014-01-01

The Collaborative Islet Transplant Registry (CITR) collects data on clinical islet isolations and transplants. This retrospective report analyzed 1017 islet isolation procedures performed for 537 recipients of allogeneic clinical islet transplantation in 1999–2010. This study describes changes in donor and islet isolation variables by era and factors associated with quantity and quality of final islet products. Donor body weight and BMI increased significantly over the period (p < 0.001). Islet yield measures have improved with time including islet equivalent (IEQ)/particle ratio and IEQs infused. The average dose of islets infused significantly increased in the era of 2007–2010 when compared to 1999–2002 (445.4 ± 156.8 vs. 421.3 ± 155.4 ×103 IEQ; p < 0.05). Islet purity and total number of β cells significantly improved over the study period (p < 0.01 and <0.05, respectively). Otherwise, the quality of clinical islets has remained consistently very high through this period, and differs substantially from nonclinical islets. In multivariate analysis of all recipient, donor and islet factors, and medical management factors, the only islet product characteristic that correlated with clinical outcomes was total IEQs infused. This analysis shows improvements in both quantity and some quality criteria of clinical islets produced over 1999–2010, and these parallel improvements in clinical outcomes over the same period. PMID:25278159

Preliminary Multivariable Cost Model for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2010-01-01

Parametric cost models are routinely used to plan missions, compare concepts and justify technology investments. Previously, the authors published two single variable cost models based on 19 flight missions. The current paper presents the development of a multi-variable space telescopes cost model. The validity of previously published models are tested. Cost estimating relationships which are and are not significant cost drivers are identified. And, interrelationships between variables are explored

Models for small-scale structure on cosmic strings. II. Scaling and its stability

NASA Astrophysics Data System (ADS)

Vieira, J. P. P.; Martins, C. J. A. P.; Shellard, E. P. S.

2016-11-01

We make use of the formalism described in a previous paper [Martins et al., Phys. Rev. D 90, 043518 (2014)] to address general features of wiggly cosmic string evolution. In particular, we highlight the important role played by poorly understood energy loss mechanisms and propose a simple Ansatz which tackles this problem in the context of an extended velocity-dependent one-scale model. We find a general procedure to determine all the scaling solutions admitted by a specific string model and study their stability, enabling a detailed comparison with future numerical simulations. A simpler comparison with previous Goto-Nambu simulations supports earlier evidence that scaling is easier to achieve in the matter era than in the radiation era. In addition, we also find that the requirement that a scaling regime be stable seems to notably constrain the allowed range of energy loss parameters.

Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective

PubMed Central

Kassab, Ghassan S.; An, Gary; Sander, Edward A.; Miga, Michael; Guccione, Julius M.; Ji, Songbai; Vodovotz, Yoram

2016-01-01

In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for 1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with 2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery. PMID:27015816

Factorial invariance of posttraumatic stress disorder symptoms across three veteran samples.

PubMed

McDonald, Scott D; Beckham, Jean C; Morey, Rajendra; Marx, Christine; Tupler, Larry A; Calhoun, Patrick S

2008-06-01

Research generally supports a 4-factor structure of posttraumatic stress disorder (PTSD) symptoms. However, few studies have established factor invariance by comparing multiple groups. This study examined PTSD symptom structure using the Davidson Trauma Scale (DTS) across three veteran samples: treatment-seeking Vietnam-era veterans, treatment-seeking post-Vietnam-era veterans, and Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) veteran research participants. Confirmatory factor analyses of DTS items demonstrated that a 4-factor structural model of the DTS (reexperiencing, avoidance, numbing, and hyperarousal) was superior to five alternate models, including the conventional 3-factor model proposed by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; American Psychiatric Association, 1994). Results supported factor invariance across the three veteran cohorts, suggesting that cross-group comparisons are interpretable. Implications and applications for DSM-IV nosology and the validity of symptom measures are discussed.

Modelling plankton ecosystems in the meta-omics era. Are we ready?

PubMed

Stec, Krzysztof Franciszek; Caputi, Luigi; Buttigieg, Pier Luigi; D'Alelio, Domenico; Ibarbalz, Federico Matias; Sullivan, Matthew B; Chaffron, Samuel; Bowler, Chris; Ribera d'Alcalà, Maurizio; Iudicone, Daniele

2017-04-01

Recent progress in applying meta-omics approaches to the study of marine ecosystems potentially allows scientists to study the genetic and functional diversity of plankton at an unprecedented depth and with enhanced precision. However, while a range of persistent technical issues still need to be resolved, a much greater obstacle currently preventing a complete and integrated view of the marine ecosystem is the absence of a clear conceptual framework. Herein, we discuss the knowledge that has thus far been derived from conceptual and statistical modelling of marine plankton ecosystems, and illustrate the potential power of integrated meta-omics approaches in the field. We then propose the use of a semantic framework is necessary to support integrative ecological modelling in the meta-omics era, particularly when having to face the increased interdisciplinarity needed to address global issues related to climate change. Copyright © 2017. Published by Elsevier B.V.

DUALITY IN MULTIVARIATE RECEPTOR MODEL. (R831078)

EPA Science Inventory

Multivariate receptor models are used for source apportionment of multiple observations of compositional data of air pollutants that obey mass conservation. Singular value decomposition of the data leads to two sets of eigenvectors. One set of eigenvectors spans a space in whi...

Sudden Cardiac Death After Non-ST-Segment Elevation Acute Coronary Syndrome.

PubMed

Hess, Paul L; Wojdyla, Daniel M; Al-Khatib, Sana M; Lokhnygina, Yuliya; Wallentin, Lars; Armstrong, Paul W; Roe, Matthew T; Ohman, E Magnus; Harrington, Robert A; Alexander, John H; White, Harvey D; Van de Werf, Frans; Piccini, Jonathan P; Held, Claes; Aylward, Philip E; Moliterno, David J; Mahaffey, Kenneth W; Tricoci, Pierluigi

2016-04-01

In the current therapeutic era, the risk for sudden cardiac death (SCD) after non-ST-segment elevation acute coronary syndrome (NSTE ACS) has not been characterized completely. To determine the cumulative incidence of SCD during long-term follow-up after NSTE ACS, to develop a risk model and risk score for SCD after NSTE ACS, and to assess the association between recurrent events after the initial ACS presentation and the risk for SCD. This pooled cohort analysis merged individual data from 48 286 participants in 4 trials: the Apixaban for Prevention of Acute Ischemic Events 2 (APPRAISE-2), Study of Platelet Inhibition and Patient Outcomes (PLATO), Thrombin Receptor Antagonist for Clinical Event Reduction in Acute Coronary Syndrome (TRACER), and Targeted Platelet Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes (TRILOGY ACS) trials. The cumulative incidence of SCD and cardiovascular death was examined according to time after NSTE ACS. Using competing risk and Cox proportional hazards models, clinical factors at baseline and after the index event that were associated with SCD after NSTE ACS were identified. Baseline factors were used to develop a risk model. Data were analyzed from January 2, 2014, to December 11, 2015. Sudden cardiac death. Of the initial 48 286 patients, 37 555 patients were enrolled after NSTE ACS (67.4% men; 32.6% women; median [interquartile range] age, 65 [57-72] years). Among these, 2109 deaths occurred after a median follow-up of 12.1 months. Of 1640 cardiovascular deaths, 513 (31.3%) were SCD. At 6, 18, and 30 months, the cumulative incidence estimates of SCD were 0.79%, 1.65%, and 2.37%, respectively. Reduced left ventricular ejection fraction, older age, diabetes mellitus, lower estimated glomerular filtration rate, higher heart rate, prior myocardial infarction, peripheral artery disease, Asian race, male sex, and high Killip class were significantly associated with SCD. A model developed to calculate the risk for SCD in trials with systematic collection of left ventricular ejection fraction had a C index of 0.77. An integer-based score was developed from this model and yielded a calculated SCD probability ranging from 0.1% to 56.7% (C statistic, 0.75). In a multivariable model that included time-dependent clinical events occurring after the index hospitalization for ACS, SCD was associated with recurrent myocardial infarction (hazard ratio [HR], 2.95; 95% CI, 2.29-3.80; P < .001) and any hospitalization (HR, 2.45; 95% CI, 1.98-3.03; P < .001), whereas coronary revascularization had a negative relationship with SCD (HR, 0.75; 95% CI, 0.58-0.98; P = .03). In the current therapeutic era, SCD accounts for about one-third of cardiovascular deaths after NSTE ACS. Risk stratification can be performed with good accuracy using commonly collected clinical variables. Clinical events occurring after the index hospitalization are underappreciated but important risk factors.

The Holocaust as Reflected in Communist and Post-Communist Romanian Textbooks

ERIC Educational Resources Information Center

Barbulescu, Ana; Degeratu, Laura; Gusu, Cosmina

2013-01-01

Romanian history textbooks were mostly silent about the Holocaust during the Communist era. The authors reconstructed the different models of remembering the Holocaust that are present in post-Communist Romanian textbooks. The analysis revealed the existence of six different models of recollecting this history. The six models of representing the…

Multivariate modelling of endophenotypes associated with the metabolic syndrome in Chinese twins.

PubMed

Pang, Z; Zhang, D; Li, S; Duan, H; Hjelmborg, J; Kruse, T A; Kyvik, K O; Christensen, K; Tan, Q

2010-12-01

The common genetic and environmental effects on endophenotypes related to the metabolic syndrome have been investigated using bivariate and multivariate twin models. This paper extends the pairwise analysis approach by introducing independent and common pathway models to Chinese twin data. The aim was to explore the common genetic architecture in the development of these phenotypes in the Chinese population. Three multivariate models including the full saturated Cholesky decomposition model, the common factor independent pathway model and the common factor common pathway model were fitted to 695 pairs of Chinese twins representing six phenotypes including BMI, total cholesterol, total triacylglycerol, fasting glucose, HDL and LDL. Performances of the nested models were compared with that of the full Cholesky model. Cross-phenotype correlation coefficients gave clear indication of common genetic or environmental backgrounds in the phenotypes. Decomposition of phenotypic correlation by the Cholesky model revealed that the observed phenotypic correlation among lipid phenotypes had genetic and unique environmental backgrounds. Both pathway models suggest a common genetic architecture for lipid phenotypes, which is distinct from that of the non-lipid phenotypes. The declining performance with model restriction indicates biological heterogeneity in development among some of these phenotypes. Our multivariate analyses revealed common genetic and environmental backgrounds for the studied lipid phenotypes in Chinese twins. Model performance showed that physiologically distinct endophenotypes may follow different genetic regulations.

Impact of bias-corrected reanalysis-derived lateral boundary conditions on WRF simulations

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro Benson; Sharma, Ashish; Evans, Jason Peter; Mehrotra, Rajeshwar; Rocheta, Eytan

2017-08-01

Lateral and lower boundary conditions derived from a suitable global reanalysis data set form the basis for deriving a dynamically consistent finer resolution downscaled product for climate and hydrological assessment studies. A problem with this, however, is that systematic biases have been noted to be present in the global reanalysis data sets that form these boundaries, biases which can be carried into the downscaled simulations thereby reducing their accuracy or efficacy. In this work, three Weather Research and Forecasting (WRF) model downscaling experiments are undertaken to investigate the impact of bias correcting European Centre for Medium range Weather Forecasting Reanalysis ERA-Interim (ERA-I) atmospheric temperature and relative humidity using Atmospheric Infrared Sounder (AIRS) satellite data. The downscaling is performed over a domain centered over southern Africa between the years 2003 and 2012. The sample mean and the mean as well as standard deviation at each grid cell for each variable are used for bias correction. The resultant WRF simulations of near-surface temperature and precipitation are evaluated seasonally and annually against global gridded observational data sets and compared with ERA-I reanalysis driving field. The study reveals inconsistencies between the impact of the bias correction prior to downscaling and the resultant model simulations after downscaling. Mean and standard deviation bias-corrected WRF simulations are, however, found to be marginally better than mean only bias-corrected WRF simulations and raw ERA-I reanalysis-driven WRF simulations. Performances, however, differ when assessing different attributes in the downscaled field. This raises questions about the efficacy of the correction procedures adopted.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

NASA Astrophysics Data System (ADS)

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-03-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

PubMed Central

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-01-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states. PMID:26996254

Changing outcomes after heart transplantation in patients with amyloid cardiomyopathy.

PubMed

Davis, Margot K; Lee, Peter H U; Witteles, Ronald M

2015-05-01

Amyloid cardiomyopathy (ACM) is associated with a poor prognosis. Previous reports have suggested unfavorable post-heart transplant (HT) survival in this population compared with other HT recipients. Data from the United Network for Organ Sharing (UNOS) registry were used to study outcomes among ACM patients undergoing HT in the modern era (Era 2, 2008 to 2013) as compared with the historical era (Era 1, 1987 to 2007). One hundred eighty-eight ACM patients underwent primary single-organ HT. Ninety-seven patients (51.6%) were transplanted in Era 1 and 91 (48.4%) in Era 2. ACM patients undergoing HT in Era 2 were older (p < 0.0001), had higher body mass index (p = 0.008) and longer ischemic times (p = 0.02), and were more likely to be African-American (p < 0.0001), UNOS Status 1A (p < 0.0001), male (p = 0.01) and highly sensitized (p < 0.0001) compared with those in Era 1. Compared with patients with other etiologies of restrictive cardiomyopathy (RCM; n = 339 in Era 1, n = 164 in Era 2), adjusted hazard ratios (HRs) for post-HT mortality of ACM were 2.08 (p < 0.0001) in Era 1 and 1.22 (p = not statistically significant) in Era 2. Adjusted HRs for mortality of ACM vs all other diagnoses (n = 36,334 in Era 1, n = 9,225 in Era 2) were 1.84 (p < 0.0001) in Era 1 and 1.38 (p = NS) in Era 2. Although post-HT survival did not change with time among non-ACM RCM patients, post-HT mortality was lower in Era 2 compared with Era 1 among ACM patients (HR 0.49, p = 0.03). Although historically associated with inferior survival, post-HT outcomes in ACM patients in the modern era are now approaching those of non-ACM patients. Changes in patients' demographics suggest that this may be related to improved patient selection, including an increased proportion of patients with transthyretin ACM. HT should be considered for appropriate candidates with ACM. Copyright © 2015 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy.

PubMed

Dankers, Frank; Wijsman, Robin; Troost, Esther G C; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L

2017-05-07

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy

NASA Astrophysics Data System (ADS)

Dankers, Frank; Wijsman, Robin; Troost, Esther G. C.; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L.

2017-05-01

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

Stress and Personal Resource as Predictors of the Adjustment of Parents to Autistic Children: A Multivariate Model

ERIC Educational Resources Information Center

Siman-Tov, Ayelet; Kaniel, Shlomo

2011-01-01

The research validates a multivariate model that predicts parental adjustment to coping successfully with an autistic child. The model comprises four elements: parental stress, parental resources, parental adjustment and the child's autism symptoms. 176 parents of children aged between 6 to 16 diagnosed with PDD answered several questionnaires…

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing disease resistance data

USDA-ARS?s Scientific Manuscript database

The mixed linear model (MLM) is currently among the most advanced and flexible statistical modeling techniques and its use in tackling problems in plant pathology has begun surfacing in the literature. The longitudinal MLM is a multivariate extension that handles repeatedly measured data, such as r...

Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

Treesearch

Denis Valle; Benjamin Baiser; Christopher W. Woodall; Robin Chazdon; Jerome Chave

2014-01-01

We propose a novel multivariate method to analyse biodiversity data based on the Latent Dirichlet Allocation (LDA) model. LDA, a probabilistic model, reduces assemblages to sets of distinct component communities. It produces easily interpretable results, can represent abrupt and gradual changes in composition, accommodates missing data and allows for coherent estimates...

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

Univariate and multivariate spatial models of health facility utilisation for childhood fevers in an area on the coast of Kenya.

PubMed

Ouma, Paul O; Agutu, Nathan O; Snow, Robert W; Noor, Abdisalan M

2017-09-18

Precise quantification of health service utilisation is important for the estimation of disease burden and allocation of health resources. Current approaches to mapping health facility utilisation rely on spatial accessibility alone as the predictor. However, other spatially varying social, demographic and economic factors may affect the use of health services. The exclusion of these factors can lead to the inaccurate estimation of health facility utilisation. Here, we compare the accuracy of a univariate spatial model, developed only from estimated travel time, to a multivariate model that also includes relevant social, demographic and economic factors. A theoretical surface of travel time to the nearest public health facility was developed. These were assigned to each child reported to have had fever in the Kenya demographic and health survey of 2014 (KDHS 2014). The relationship of child treatment seeking for fever with travel time, household and individual factors from the KDHS2014 were determined using multilevel mixed modelling. Bayesian information criterion (BIC) and likelihood ratio test (LRT) tests were carried out to measure how selected factors improve parsimony and goodness of fit of the time model. Using the mixed model, a univariate spatial model of health facility utilisation was fitted using travel time as the predictor. The mixed model was also used to compute a multivariate spatial model of utilisation, using travel time and modelled surfaces of selected household and individual factors as predictors. The univariate and multivariate spatial models were then compared using the receiver operating area under the curve (AUC) and a percent correct prediction (PCP) test. The best fitting multivariate model had travel time, household wealth index and number of children in household as the predictors. These factors reduced BIC of the time model from 4008 to 2959, a change which was confirmed by the LRT test. Although there was a high correlation of the two modelled probability surfaces (Adj R 2  = 88%), the multivariate model had better AUC compared to the univariate model; 0.83 versus 0.73 and PCP 0.61 versus 0.45 values. Our study shows that a model that uses travel time, as well as household and individual-level socio-demographic factors, results in a more accurate estimation of use of health facilities for the treatment of childhood fever, compared to one that relies on only travel time.

Survival in HIV-infected patients after a cancer diagnosis in the cART Era: results of an italian multicenter study.

PubMed

Gotti, Daria; Raffetti, Elena; Albini, Laura; Sighinolfi, Laura; Maggiolo, Franco; Di Filippo, Elisa; Ladisa, Nicoletta; Angarano, Gioacchino; Lapadula, Giuseppe; Pan, Angelo; Esposti, Anna Degli; Fabbiani, Massimiliano; Focà, Emanuele; Scalzini, Alfredo; Donato, Francesco; Quiros-Roldan, Eugenia

2014-01-01

We studied survival and associated risk factors in an Italian nationwide cohort of HIV-infected individuals after an AIDS-defining cancer (ADC) or non-AIDS-defining cancer (NADC) diagnosis in the modern cART era. Multi-center, retrospective, observational study of HIV patients included in the MASTER Italian Cohort with a cancer diagnosis from January 1998 to September 2012. Malignancies were divided into ADC or NADC on the basis of the Centre for Disease Control-1993 classification. Recurrence of cancer and metastases were excluded. Survivals were estimated according to the Kaplan-Meier method and compared according to the log-rank test. Statistically significant variables at univariate analysis were entered in a multivariate Cox regression model. Eight hundred and sixty-six cancer diagnoses were recorded among 13,388 subjects in the MASTER Database after 1998: 435 (51%) were ADCs and 431 (49%) were NADCs. Survival was more favorable after an ADC diagnosis than a NADC diagnosis (10-year survival: 62.7%±2.9% vs. 46%±4.2%; p = 0.017). Non-Hodgkin lymphoma had lower survival rates than patients with Kaposi sarcoma or cervical cancer (10-year survival: 48.2%±4.3% vs. 72.8%±4.0% vs. 78.5%±9.9%; p<0.001). Regarding NADCs, breast cancer showed better survival (10-year survival: 65.1%±14%) than lung cancer (1-year survival: 28%±8.7%), liver cancer (5-year survival: 31.9%±6.4%) or Hodgkin lymphoma (10-year survival: 24.8%±11.2%). Lower CD4+ count and intravenous drug use were significantly associated with decreased survival after ADCs or NADCs diagnosis. Exposure to cART was found to be associated with prolonged survival only in the case of ADCs. cART has improved survival in patients with an ADC diagnosis, whereas the prognosis after a diagnosis of NADCs is poor. Low CD4+ counts and intravenous drug use are risk factors for survival following a diagnosis of ADCs and Hodgkin lymphoma in the NADC group.

Survival in HIV-Infected Patients after a Cancer Diagnosis in the cART Era: Results of an Italian Multicenter Study

PubMed Central

Gotti, Daria; Raffetti, Elena; Albini, Laura; Sighinolfi, Laura; Maggiolo, Franco; Di Filippo, Elisa; Ladisa, Nicoletta; Angarano, Gioacchino; Lapadula, Giuseppe; Pan, Angelo; Esposti, Anna Degli; Fabbiani, Massimiliano; Focà, Emanuele; Scalzini, Alfredo; Donato, Francesco; Quiros-Roldan, Eugenia

2014-01-01

Objectives We studied survival and associated risk factors in an Italian nationwide cohort of HIV-infected individuals after an AIDS-defining cancer (ADC) or non-AIDS-defining cancer (NADC) diagnosis in the modern cART era. Methods Multi-center, retrospective, observational study of HIV patients included in the MASTER Italian Cohort with a cancer diagnosis from January 1998 to September 2012. Malignancies were divided into ADC or NADC on the basis of the Centre for Disease Control-1993 classification. Recurrence of cancer and metastases were excluded. Survivals were estimated according to the Kaplan-Meier method and compared according to the log-rank test. Statistically significant variables at univariate analysis were entered in a multivariate Cox regression model. Results Eight hundred and sixty-six cancer diagnoses were recorded among 13,388 subjects in the MASTER Database after 1998: 435 (51%) were ADCs and 431 (49%) were NADCs. Survival was more favorable after an ADC diagnosis than a NADC diagnosis (10-year survival: 62.7%±2.9% vs. 46%±4.2%; p = 0.017). Non-Hodgkin lymphoma had lower survival rates than patients with Kaposi sarcoma or cervical cancer (10-year survival: 48.2%±4.3% vs. 72.8%±4.0% vs. 78.5%±9.9%; p<0.001). Regarding NADCs, breast cancer showed better survival (10-year survival: 65.1%±14%) than lung cancer (1-year survival: 28%±8.7%), liver cancer (5-year survival: 31.9%±6.4%) or Hodgkin lymphoma (10-year survival: 24.8%±11.2%). Lower CD4+ count and intravenous drug use were significantly associated with decreased survival after ADCs or NADCs diagnosis. Exposure to cART was found to be associated with prolonged survival only in the case of ADCs. Conclusions cART has improved survival in patients with an ADC diagnosis, whereas the prognosis after a diagnosis of NADCs is poor. Low CD4+ counts and intravenous drug use are risk factors for survival following a diagnosis of ADCs and Hodgkin lymphoma in the NADC group. PMID:24760049

Adjustment of automatic control systems of production facilities at coal processing plants using multivariant physico- mathematical models

NASA Astrophysics Data System (ADS)

Evtushenko, V. F.; Myshlyaev, L. P.; Makarov, G. V.; Ivushkin, K. A.; Burkova, E. V.

2016-10-01

The structure of multi-variant physical and mathematical models of control system is offered as well as its application for adjustment of automatic control system (ACS) of production facilities on the example of coal processing plant.

A simplified parsimonious higher order multivariate Markov chain model with new convergence condition

NASA Astrophysics Data System (ADS)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, we present a simplified parsimonious higher-order multivariate Markov chain model with new convergence condition. (TPHOMMCM-NCC). Moreover, estimation method of the parameters in TPHOMMCM-NCC is give. Numerical experiments illustrate the effectiveness of TPHOMMCM-NCC.

Various forms of indexing HDMR for modelling multivariate classification problems

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

Aksu, Çağrı; Tunga, M. Alper

2014-12-10

The Indexing HDMR method was recently developed for modelling multivariate interpolation problems. The method uses the Plain HDMR philosophy in partitioning the given multivariate data set into less variate data sets and then constructing an analytical structure through these partitioned data sets to represent the given multidimensional problem. Indexing HDMR makes HDMR be applicable to classification problems having real world data. Mostly, we do not know all possible class values in the domain of the given problem, that is, we have a non-orthogonal data structure. However, Plain HDMR needs an orthogonal data structure in the given problem to be modelled.more » In this sense, the main idea of this work is to offer various forms of Indexing HDMR to successfully model these real life classification problems. To test these different forms, several well-known multivariate classification problems given in UCI Machine Learning Repository were used and it was observed that the accuracy results lie between 80% and 95% which are very satisfactory.« less

Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

PubMed

Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

2014-09-01

Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

Insights on multivariate updates of physical and biogeochemical ocean variables using an Ensemble Kalman Filter and an idealized model of upwelling

NASA Astrophysics Data System (ADS)

Yu, Liuqian; Fennel, Katja; Bertino, Laurent; Gharamti, Mohamad El; Thompson, Keith R.

2018-06-01

Effective data assimilation methods for incorporating observations into marine biogeochemical models are required to improve hindcasts, nowcasts and forecasts of the ocean's biogeochemical state. Recent assimilation efforts have shown that updating model physics alone can degrade biogeochemical fields while only updating biogeochemical variables may not improve a model's predictive skill when the physical fields are inaccurate. Here we systematically investigate whether multivariate updates of physical and biogeochemical model states are superior to only updating either physical or biogeochemical variables. We conducted a series of twin experiments in an idealized ocean channel that experiences wind-driven upwelling. The forecast model was forced with biased wind stress and perturbed biogeochemical model parameters compared to the model run representing the "truth". Taking advantage of the multivariate nature of the deterministic Ensemble Kalman Filter (DEnKF), we assimilated different combinations of synthetic physical (sea surface height, sea surface temperature and temperature profiles) and biogeochemical (surface chlorophyll and nitrate profiles) observations. We show that when biogeochemical and physical properties are highly correlated (e.g., thermocline and nutricline), multivariate updates of both are essential for improving model skill and can be accomplished by assimilating either physical (e.g., temperature profiles) or biogeochemical (e.g., nutrient profiles) observations. In our idealized domain, the improvement is largely due to a better representation of nutrient upwelling, which results in a more accurate nutrient input into the euphotic zone. In contrast, assimilating surface chlorophyll improves the model state only slightly, because surface chlorophyll contains little information about the vertical density structure. We also show that a degradation of the correlation between observed subsurface temperature and nutrient fields, which has been an issue in several previous assimilation studies, can be reduced by multivariate updates of physical and biogeochemical fields.

Simulation of tropospheric chemistry and aerosols with the climate model EC-Earth

NASA Astrophysics Data System (ADS)

van Noije, T. P. C.; Le Sager, P.; Segers, A. J.; van Velthoven, P. F. J.; Krol, M. C.; Hazeleger, W.; Williams, A. G.; Chambers, S. D.

2014-10-01

We have integrated the atmospheric chemistry and transport model TM5 into the global climate model EC-Earth version 2.4. We present an overview of the TM5 model and the two-way data exchange between TM5 and the IFS model from the European Centre for Medium-Range Weather Forecasts (ECMWF), the atmospheric general circulation model of EC-Earth. In this paper we evaluate the simulation of tropospheric chemistry and aerosols in a one-way coupled configuration. We have carried out a decadal simulation for present-day conditions and calculated chemical budgets and climatologies of tracer concentrations and aerosol optical depth. For comparison we have also performed offline simulations driven by meteorological fields from ECMWF's ERA-Interim reanalysis and output from the EC-Earth model itself. Compared to the offline simulations, the online-coupled system produces more efficient vertical mixing in the troposphere, which reflects an improvement of the treatment of cumulus convection. The chemistry in the EC-Earth simulations is affected by the fact that the current version of EC-Earth produces a cold bias with too dry air in large parts of the troposphere. Compared to the ERA-Interim driven simulation, the oxidizing capacity in EC-Earth is lower in the tropics and higher in the extratropics. The atmospheric lifetime of methane in EC-Earth is 9.4 years, which is 7% longer than the lifetime obtained with ERA-Interim but remains well within the range reported in the literature. We further evaluate the model by comparing the simulated climatologies of surface radon-222 and carbon monoxide, tropospheric and surface ozone, and aerosol optical depth against observational data. The work presented in this study is the first step in the development of EC-Earth into an Earth system model with fully interactive atmospheric chemistry and aerosols.

Maxwell's Enduring Legacy

NASA Astrophysics Data System (ADS)

Longair, Malcolm

2016-07-01

Preface; Acknowledgements; Figure credits; Part I. To 1874: 1. Physics in the nineteenth century; 2. Mathematics and physics in Cambridge in the nineteenth century; Part II. 1874 to 1879: 3. The Maxwell era; Part III. 1879 to 1884: 4. Rayleigh's Quinquennium; Part IV. 1884 to 1919: 5. The challenges facing J. J. Thomson; 6. The J. J. Thomson era, 1884-1900 - the electron; 7. The Thomson era, 1900-19 - atomic structure; Part V. 1919 to 1937: 8. Rutherford at McGill and Manchester Universities - new challenges in Cambridge; 9. The Rutherford era - the radioactivists; 10. Rutherford era - the seeds of the new physics; Part VI. 1938 to 1953: 11. Bragg and the war years; 12. Bragg and the post-war years; Part VII. 1953 to 1971: 13. The Mott era - an epoch of expansion; 14. The Mott era - radio astronomy and high energy physics; 15. The Mott era - the growth of condensed matter physics; Part VIII. 1971 to 1982: 16. The Pippard era - a new laboratory and a new vision; 17. The Pippard era - radio astronomy, high energy physics and laboratory astrophysics; 18. The Pippard era - condensed matter physics; Part IX. 1984 to 1995: 19. The Edwards era - a new epoch of expansion; 20. The Edwards era - new directions in condensed matter physics; 21. The Edwards era - high energy physics and radio astronomy; Part X. 1995 to present: 22. Towards the new millennium and beyond; 23. The evolution of the New Museums site; Notes; Bibliography; Author index; Index.

Cosmic infinity: a dynamical system approach

NASA Astrophysics Data System (ADS)

Bouhmadi-López, Mariam; Marto, João; Morais, João; Silva, César M.

2017-03-01

Dynamical system techniques are extremely useful to study cosmology. It turns out that in most of the cases, we deal with finite isolated fixed points corresponding to a given cosmological epoch. However, it is equally important to analyse the asymptotic behaviour of the universe. On this paper, we show how this can be carried out for 3-form models. In fact, we show that there are fixed points at infinity mainly by introducing appropriate compactifications and defining a new time variable that washes away any potential divergence of the system. The richness of 3-form models allows us as well to identify normally hyperbolic non-isolated fixed points. We apply this analysis to three physically interesting situations: (i) a pre-inflationary era; (ii) an inflationary era; (iii) the late-time dark matter/dark energy epoch.

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Modeling extreme sea levels due to tropical and extra-tropical cyclones at the global-scale

NASA Astrophysics Data System (ADS)

Muis, S.; Lin, N.; Verlaan, M.; Winsemius, H.; Ward, P.; Aerts, J.

2017-12-01

Extreme sea levels, a combination of storm surges and astronomical tides, can cause catastrophic floods. Due to their intense wind speeds and low pressure, tropical cyclones (TCs) typically cause higher storm surges than extra-tropical cyclones (ETCs), but ETCs may still contribute significantly to the overall flood risk. In this contribution, we show a novel approach to model extreme sea levels due to both tropical and extra-tropical cyclones at the global-scale. Using a global hydrodynamic model we have developed the Global Tide and Surge Reanalysis (GTSR) dataset (Muis et al., 2016), which provides daily maximum timeseries of storm tide from 1979 to 2014. GTSR is based on wind and pressure fields from the ERA-Interim climate reanalysis (Dee at al., 2011). A severe limitation of the GTSR dataset is the underrepresentation of TCs. This is due to the relatively coarse grid resolution of ERA-Interim, which means that the strong intensities of TCs are not fully included. Furthermore, the length of ERA-Interim is too short to estimate the probabilities of extreme TCs in a reliable way. We will discuss potential ways to address this limitation, and demonstrate how to improve the global GTSR framework. We will apply the improved framework to the east coast of the United States. First, we improve our meteorological forcing by applying a parametric hurricane model (Holland 1980), and we improve the tide and surge reanalysis dataset (Muis et al., 2016) by explicitly modeling the historical TCs in the Extended Best Track dataset (Demuth et al., 2006). Second, we improve our sampling by statistically extending the observed TC record to many thousands of years (Emanuel et al., 2006). The improved framework allows for the mapping of probabilities of extreme sea levels, including extremes TC events, for the east coast of the United States. ReferencesDee et al (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553-97. Emanuel et al (2006). A Statistical Deterministic Approach to Hurricane Risk Assessment/ Bull. Am. Meteorol. Soc. 87, 299-314. Holland (1980). An analytic model of the wind and pressure profiles in hurricanes. Mon. Weather Rev. 108, 1212-1218. Muis et al (2016). A global reanalysis of storm surge and extreme sea levels. Nat. Commun. 7, 1-11

The Future of Health Care Reform: What Is Driving Enrollment?

PubMed

Callaghan, Timothy H; Jacobs, Lawrence R

2017-04-01

Against a backdrop of ongoing operational challenges, insurance market turbulence, and the ever present pull of partisanship, enrollment in the ACA's programs has soared and significant variations have developed across states in terms of their pace of coverage expansion. Our article explores why ACA enrollment has varied so dramatically across states. We explore the potential influence of party control, presidential cueing, administrative capacity, the reverberating effects of ACA policy decisions, affluence, and unemployment on enrollment. Our multivariate analysis finds that party control dominated early state decision making, but that relative enrollment in insurance exchanges and the Medicaid expansion are driven by a changing mix of political and administrative factors. Health politics is entering a new era as Republicans replace the ACA and devolve significant discretion to states to administer Medicaid and other programs. Our findings offer insights into future directions in health reform and in learning and diffusion. Copyright © 2017 by Duke University Press.

Cost Comparison Between Home Telemonitoring and Usual Care of Older Adults: A Randomized Trial (Tele-ERA)

PubMed Central

Upatising, Benjavan; Wood, Douglas L.; Kremers, Walter K.; Christ, Sharon L.; Yih, Yuehwern; Hanson, Gregory J.

2015-01-01

Abstract Background: From 1992 to 2008, older adults in the United States incurred more healthcare expense per capita than any other age group. Home telemonitoring has emerged as a potential solution to reduce these costs, but evidence is mixed. The primary aim of the study was to evaluate whether the mean difference in total direct medical cost consequence between older adults receiving additional home telemonitoring care (TELE) (n=102) and those receiving usual medical care (UC) (n=103) were significant. Inpatient, outpatient, emergency department, decedents, survivors, and 30-day readmission costs were evaluated as secondary aim. Materials and Methods: Multivariate generalized linear models (GLMs) and parametric bootstrapping method were used to model cost and to determine significance of the cost differences. We also compared the differences in arithmetic mean costs. Results: From the conditional GLMs, the estimated mean cost differences (TELE versus UC) for total, inpatient, outpatient, and ED were −$9,537 (p=0.068), −$8,482 (p =0.098), −$1,160 (p=0.177), and $106 (p=0.619), respectively. Mean postenrollment cost was 11% lower than the prior year for TELE versus 22% higher for UC. The ratio of mean cost for decedents to survivors was 2.1:1 (TELE) versus 12.7:1 (UC). Conclusions: There were no significant differences in the mean total cost between the two treatment groups. The TELE group had less variability in cost of care, lower decedents to survivors cost ratio, and lower total 30-day readmission cost than the UC group. PMID:25453392

Genetic architecture of learning and delayed recall: a twin study of episodic memory.

PubMed

Panizzon, Matthew S; Lyons, Michael J; Jacobson, Kristen C; Franz, Carol E; Grant, Michael D; Eisen, Seth A; Xian, Hong; Kremen, William S

2011-07-01

Although episodic memory is often conceptualized as consisting of multiple component processes, there is a lack of understanding as to whether these processes are influenced by the same or different genetic determinants. The aim of the present study was to utilize multivariate twin analyses to elucidate the degree to which learning and delayed recall, two critical measures of episodic memory performance, have common or different genetic and environmental influences. Participants from the Vietnam Era Twin Study of Aging (314 monozygotic twin pairs, 259 dizygotic twin pairs, and 47 unpaired twins) were assessed using the second edition of the California Verbal Learning Test. Mean age at the time of the evaluation was 55.4 years (SD = 2.5). Model fitting revealed the presence of a higher-order latent factor influencing learning, short- and long-delay free recall, with a heritability of .36. The best-fitting model also indicated specific genetic influences on learning, which accounted for 10% of the overall variance. Given that learning involves the acquisition and retrieval of information, whereas delayed recall involves only retrieval, we conclude that these specific effects are likely to reflect genes that are specific to acquisition processes. These results demonstrate that even in nonclinical populations, it is possible to differentiate component processes in episodic memory. These different genetic influences may have implications for gene association studies, as well as other genetic studies of cognitive aging and disorders of episodic memory such as Alzheimer's disease or mild cognitive impairment. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Estimation and model selection of semiparametric multivariate survival functions under general censorship.

PubMed

Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

2010-07-01

We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root- n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.

Estimation and model selection of semiparametric multivariate survival functions under general censorship

PubMed Central

Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

2013-01-01

We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root-n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided. PMID:24790286

Usual Dietary Intakes: SAS Macros for Fitting Multivariate Measurement Error Models & Estimating Multivariate Usual Intake Distributions

Cancer.gov

The following SAS macros can be used to create a multivariate usual intake distribution for multiple dietary components that are consumed nearly every day or episodically. A SAS macro for performing balanced repeated replication (BRR) variance estimation is also included.

Comparative Robustness of Recent Methods for Analyzing Multivariate Repeated Measures Designs

ERIC Educational Resources Information Center

Seco, Guillermo Vallejo; Gras, Jaime Arnau; Garcia, Manuel Ato

2007-01-01

This study evaluated the robustness of two recent methods for analyzing multivariate repeated measures when the assumptions of covariance homogeneity and multivariate normality are violated. Specifically, the authors' work compares the performance of the modified Brown-Forsythe (MBF) procedure and the mixed-model procedure adjusted by the…

Galaxy formation in Lambda greater than 0 Friedmann models: Consequences for the number counts versus redshift test

NASA Technical Reports Server (NTRS)

Martel, Hugo

1994-01-01

We study the effect of the cosmological constant Lambda on galaxy formation using a simple spherical top-hat overdensity model. We consider models with Omega(sub 0) = 0.2, lambda(sub 0) = 0, and Omega(sub 0) = 0.2, lambda(sub 0) = 0.8 (where Omega(sub 0) is the density parameter, and lambda(sub 0) identically equal Lambda/3 H(sub 0 exp 2) where H(sub 0) is the Hubble constant). We adjust the initial power spectrum amplitude so that both models reproduce the same large-scale structures. The galaxy formation era in the lambda(sub 0) = 0 model occurs early (z approximately 6) and is very short, whereas in the lambda(sub 0) = 0.8 model the galaxy formation era starts later (z approximately 4), and last much longer, possibly all the way to the present. Consequently, galaxies at low redshift (z less than 1) are significantly more evolved in the lambda(sub 0) = 0 model than in the lambda(sub 0) = 0.8 model. This result implies that previous attempts to determine Lambda using the number counts versus redshift test are probably unreliable.

Multi-method Quantification of Sea-ice Production in Weddell Sea Polynyas (Antarctica)

NASA Astrophysics Data System (ADS)

Heinemann, G.; Zentek, R.; Stulic, L.; Paul, S.; Preusser, A.; Timmermann, R.

2017-12-01

Coastal polynyas occur frequently during winter in the Weddell Sea, which leads to strong sea ice production and to the formation of a highly saline water mass which is considered to be a major source of bottom water and one of the main drivers of the circulation beneath the Filchner-Ronne Ice Shelf. Thus the quantification of sea ice production in Weddell Sea polynyas is of vital interest for understanding water mass modification in this region. We use a multi-method approach to quantify sea ice production. Method 1) is based on the energy balance simulated by the regional climate model COSMO-CLM (CCLM) with 15 / 5 km resolution for the period 2002-2015 (nested in ERA-Interim data). Daily sea ice concentrations were taken from microwave satellite measurements. Method 2) is based on remote sensing using MODIS thermal infrared data at a resolution of 1-2km and a surface energy balance model taking atmospheric data from different reanalyses (ERA-Interim, JRA55, NCEP2) as well as data of CCLM. Method 3) relies on simulations using the Finite Element Sea ice-Ocean Model (FESOM). FESOM is run on a global grid with a resolution of about 5 km along the coast of the Weddell Sea using atmospheric forcing from reanalyses (ERA-Interim (80km) and CFSR (38km)) as well as from CCLM. In addition, an experiment with assimilation of MODIS thin ice retrievals was conducted. Estimates of polynya area (POLA) and sea ice production (IP) from the different methods are presented. The MODIS-based method with ERA-Interim shows the largest POLA as well as the largest IP for the Ronne polynya (RO, POLA / IP = 2800 km² / 29 km³/a) and for the polynya off Brunt Ice Shelf (BR, 3400 km² / 30 km³/a). Sensitivity to the choice of atmosphere data is high. In particular, too low temperatures in JRA55 cause very large ice production events and a strong overestimation of IP rates. Estimates based on CCLM simulations agree generally well with MODIS/ERA-Interim. FESOM yields a generally larger ice production and shows also a pronounced sensitivity to the atmospheric forcing, but the effect on POLA and IP depends on the region. For BR the FESOM simulations show much larger POLA and IP than other methods.

Critical elements on fitting the Bayesian multivariate Poisson Lognormal model

NASA Astrophysics Data System (ADS)

Zamzuri, Zamira Hasanah binti

2015-10-01

Motivated by a problem on fitting multivariate models to traffic accident data, a detailed discussion of the Multivariate Poisson Lognormal (MPL) model is presented. This paper reveals three critical elements on fitting the MPL model: the setting of initial estimates, hyperparameters and tuning parameters. These issues have not been highlighted in the literature. Based on simulation studies conducted, we have shown that to use the Univariate Poisson Model (UPM) estimates as starting values, at least 20,000 iterations are needed to obtain reliable final estimates. We also illustrated the sensitivity of the specific hyperparameter, which if it is not given extra attention, may affect the final estimates. The last issue is regarding the tuning parameters where they depend on the acceptance rate. Finally, a heuristic algorithm to fit the MPL model is presented. This acts as a guide to ensure that the model works satisfactorily given any data set.

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

NASA Technical Reports Server (NTRS)

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

1985-01-01

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Multivariate Bayesian modeling of known and unknown causes of events--an application to biosurveillance.

PubMed

Shen, Yanna; Cooper, Gregory F

2012-09-01

This paper investigates Bayesian modeling of known and unknown causes of events in the context of disease-outbreak detection. We introduce a multivariate Bayesian approach that models multiple evidential features of every person in the population. This approach models and detects (1) known diseases (e.g., influenza and anthrax) by using informative prior probabilities and (2) unknown diseases (e.g., a new, highly contagious respiratory virus that has never been seen before) by using relatively non-informative prior probabilities. We report the results of simulation experiments which support that this modeling method can improve the detection of new disease outbreaks in a population. A contribution of this paper is that it introduces a multivariate Bayesian approach for jointly modeling both known and unknown causes of events. Such modeling has general applicability in domains where the space of known causes is incomplete. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Personalized Estimate of Chemotherapy-Induced Nausea and Vomiting: Development and External Validation of a Nomogram in Cancer Patients Receiving Highly/Moderately Emetogenic Chemotherapy.

PubMed

Hu, Zhihuang; Liang, Wenhua; Yang, Yunpeng; Keefe, Dorothy; Ma, Yuxiang; Zhao, Yuanyuan; Xue, Cong; Huang, Yan; Zhao, Hongyun; Chen, Likun; Chan, Alexandre; Zhang, Li

2016-01-01

Chemotherapy-induced nausea and vomiting (CINV) is presented in over 30% of cancer patients receiving highly/moderately emetogenic chemotherapy (HEC/MEC). The currently recommended antiemetic therapy is merely based on the emetogenic level of chemotherapy, regardless of patient's individual risk factors. It is, therefore, critical to develop an approach for personalized management of CINV in the era of precision medicine.A number of variables were involved in the development of CINV. In the present study, we pooled the data from 2 multi-institutional investigations of CINV due to HEC/MEC treatment in Asian countries. Demographic and clinical variables of 881 patients were prospectively collected as defined previously, and 862 of them had full documentation of variables of interest. The data of 548 patients from Chinese institutions were used to identify variables associated with CINV using multivariate logistic regression model, and then construct a personalized prediction model of nomogram; while the remaining 314 patients out of China (Singapore, South Korea, and Taiwan) entered the external validation set. C-index was used to measure the discrimination ability of the model.The predictors in the final model included sex, age, alcohol consumption, history of vomiting pregnancy, history of motion sickness, body surface area, emetogenicity of chemotherapy, and antiemetic regimens. The C-index was 0.67 (95% CI, 0.62-0.72) for the training set and 0.65 (95% CI, 0.58-0.72) for the validation set. The C-index was higher than that of any single predictor, including the emetogenic level of chemotherapy according to current antiemetic guidelines. Calibration curves showed good agreement between prediction and actual occurrence of CINV.This easy-to-use prediction model was based on chemotherapeutic regimens as well as patient's individual risk factors. The prediction accuracy of CINV occurrence in this nomogram was well validated by an independent data set. It could facilitate the assessment of individual risk, and thus improve the personalized management of CINV.

Regional Climate Model sesitivity to different parameterizations schemes with WRF over Spain

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Hidalgo-Muñoz, Jose Manuel; Argüeso, Daniel; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2015-04-01

The ability of the Weather Research and Forecasting (WRF) model to simulate the regional climate depends on the selection of an adequate combination of parameterization schemes. This study assesses WRF sensitivity to different parameterizations using six different runs that combined three cumulus, two microphysics and three surface/planetary boundary layer schemes in a topographically complex region such as Spain, for the period 1995-1996. Each of the simulations spanned a period of two years, and were carried out at a spatial resolution of 0.088° over a domain encompassing the Iberian Peninsula and nested in the coarser EURO-CORDEX domain (0.44° resolution). The experiments were driven by Interim ECMWF Re-Analysis (ERA-Interim) data. In addition, two different spectral nudging configurations were also analysed. The simulated precipitation and maximum and minimum temperatures from WRF were compared with Spain02 version 4 observational gridded datasets. The comparison was performed at different time scales with the purpose of evaluating the model capability to capture mean values and high-order statistics. ERA-Interim data was also compared with observations to determine the improvement obtained using dynamical downscaling with respect to the driving data. For this purpose, several parameters were analysed by directly comparing grid-points. On the other hand, the observational gridded data were grouped using a multistep regionalization to facilitate the comparison in term of monthly annual cycle and the percentiles of daily values analysed. The results confirm that no configuration performs best, but some combinations that produce better results could be chosen. Concerning temperatures, WRF provides an improvement over ERA-Interim. Overall, model outputs reduce the biases and the RMSE for monthly-mean maximum and minimum temperatures and are higher correlated with observations than ERA-Interim. The analysis shows that the Yonsei University planetary boundary layer scheme is the most appropriate parameterization in term of temperatures because it better describes monthly minimum temperatures and seems to perform well for maximum temperatures. Regarding precipitation, ERA-Interim time series are slightly higher correlated with observations than WRF, but the bias and the RMSE are largely worse. These results also suggest that CAM V.5.1 2-moment 5-class microphysics schemes should not be used due to the computational cost with no apparent gain with respect to simpler schemes such as WRF single-moment 3-class. For the convection scheme, this study suggests that Betts-Miller-Janjic scheme is an appropriate choice due to its robustness and Kain-Fritsch cumulus scheme should not be used over this region. KEY WORDS: Regional climate modelling, physics schemes, parameterizations, WRF. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

FACTOR ANALYTIC MODELS OF CLUSTERED MULTIVARIATE DATA WITH INFORMATIVE CENSORING

EPA Science Inventory

This paper describes a general class of factor analytic models for the analysis of clustered multivariate data in the presence of informative missingness. We assume that there are distinct sets of cluster-level latent variables related to the primary outcomes and to the censorin...

Simulation of the West African monsoon onset using the HadGEM3-RA regional climate model

NASA Astrophysics Data System (ADS)

Diallo, Ismaïla; Bain, Caroline L.; Gaye, Amadou T.; Moufouma-Okia, Wilfran; Niang, Coumba; Dieng, Mame D. B.; Graham, Richard

2014-08-01

The performance of the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) in simulating the West African monsoon (WAM) is investigated. We focus on performance for monsoon onset timing and for rainfall totals over the June-July-August (JJA) season and on the model's representation of the underlying dynamical processes. Experiments are driven by the ERA-Interim reanalysis and follow the CORDEX experimental protocol. Simulations with the HadGEM3 global model, which shares a common physical formulation with HadGEM3-RA, are used to gain insight into the causes of HadGEM3-RA simulation errors. It is found that HadGEM3-RA simulations of monsoon onset timing are realistic, with an error in mean onset date of two pentads. However, the model has a dry bias over the Sahel during JJA of 15-20 %. Analysis suggests that this is related to errors in the positioning of the Saharan heat low, which is too far south in HadGEM3-RA and associated with an insufficient northward reach of the south-westerly low-level monsoon flow and weaker moisture convergence over the Sahel. Despite these biases HadGEM3-RA's representation of the general rainfall distribution during the WAM appears superior to that of ERA-Interim when using Global Precipitation Climatology Project or Tropical Rain Measurement Mission data as reference. This suggests that the associated dynamical features seen in HadGEM3-RA can complement the physical picture available from ERA-Interim. This approach is supported by the fact that the global HadGEM3 model generates realistic simulations of the WAM without the benefit of pseudo-observational forcing at the lateral boundaries; suggesting that the physical formulation shared with HadGEM3-RA, is able to represent the driving processes. HadGEM3-RA simulations confirm previous findings that the main rainfall peak near 10°N during June-August is maintained by a region of mid-tropospheric ascent located, latitudinally, between the cores of the African Easterly Jet and Tropical Easterly Jet that intensifies around the time of onset. This region of ascent is weaker and located further south near 5°N in the driving ERA-Interim reanalysis, for reasons that may be related to the coarser resolution or the physics of the underlying model, and this is consistent with a less realistic latitudinal rainfall profile than found in the HadGEM3-RA simulations.

Land Surface Precipitation and Hydrology in MERRA-2

NASA Technical Reports Server (NTRS)

Reichle, R.; Koster, R.; Draper, C.; Liu, Q.; Girotto, M.; Mahanama, S.; De Lannoy, G.; Partyka, G.

2017-01-01

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at 50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface. This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cyclingMERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourlyTRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim Land. Seasonal anomaly R values against naturalized stream flow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim Land, somewhat lower for MERRA-Land, and lower still for MERRA.

The polar WRF downscaled historical and projected 21st century climate for the coast and foothills of Arctic Alaska

NASA Astrophysics Data System (ADS)

Cai, Lei; Alexeev, Vladimir A.; Arp, Christopher D.; Jones, Benjamin M.; Liljedahl, Anna K.; Gädeke, Anne

2018-01-01

Climate change is most pronounced in the northern high latitude region. Yet, climate observations are unable to fully capture regional-scale dynamics due to the sparse weather station coverage, which limits our ability to make reliable climate-based assessments. A set of simulated data products was therefore developed for the North Slope of Alaska through a dynamical downscaling approach. The polar-optimized Weather Research & Forecast (Polar WRF) model was forced by three sources: The ERA-interim reanalysis data (for 1979-2014), the Community Earth System Model 1.0 (CESM1.0) historical simulation (for 1950-2005), and the CESM1.0 projected (for 2006-2100) simulations in two Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios. Climatic variables were produced in a 10-km grid spacing and a 3-hour interval. The ERA-interim forced WRF (ERA-WRF) proves the value of dynamical downscaling, which yields more realistic topographical-induced precipitation and air temperature, as well as corrects underestimations in observed precipitation. In summary, dry and cold biases to the north of the Brooks Range are presented in ERA-WRF, while CESM forced WRF (CESM-WRF) holds wet and warm biases in its historical period. A linear scaling method allowed for an adjustment of the biases, while keeping the majority of the variability and extreme values of modeled precipitation and air temperature. CESM-WRF under RCP 4.5 scenario projects smaller increase in precipitation and air temperature than observed in the historical CESM-WRF product, while the CESM-WRF under RCP8.5 scenario shows larger changes. The fine spatial and temporal resolution, long temporal coverage, and multi-scenario projections jointly make the dataset appropriate to address a myriad of physical and biological changes occurring on the North Slope of Alaska.

An Examination of the Domain of Multivariable Functions Using the Pirie-Kieren Model

ERIC Educational Resources Information Center

Sengul, Sare; Yildiz, Sevda Goktepe

2016-01-01

The aim of this study is to employ the Pirie-Kieren model so as to examine the understandings relating to the domain of multivariable functions held by primary school mathematics preservice teachers. The data obtained was categorized according to Pirie-Kieren model and demonstrated visually in tables and bar charts. The study group consisted of…

Multivariate regression model for predicting yields of grade lumber from yellow birch sawlogs

Treesearch

Andrew F. Howard; Daniel A. Yaussy

1986-01-01

A multivariate regression model was developed to predict green board-foot yields for the common grades of factory lumber processed from yellow birch factory-grade logs. The model incorporates the standard log measurements of scaling diameter, length, proportion of scalable defects, and the assigned USDA Forest Service log grade. Differences in yields between band and...

A Multivariate Model for the Meta-Analysis of Study Level Survival Data at Multiple Times

ERIC Educational Resources Information Center

Jackson, Dan; Rollins, Katie; Coughlin, Patrick

2014-01-01

Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and…

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

Heritability of carotid intima-media thickness: a twin study.

PubMed

Zhao, Jinying; Cheema, Faiz A; Bremner, J Douglas; Goldberg, Jack; Su, Shaoyong; Snieder, Harold; Maisano, Carisa; Jones, Linda; Javed, Farhan; Murrah, Nancy; Le, Ngoc-Anh; Vaccarino, Viola

2008-04-01

To estimate the heritability of carotid intima-media thickness (IMT), a surrogate marker for atherosclerosis, independent of traditional coronary risk factors. We performed a classical twin study of carotid IMT using 98 middle-aged male twin pairs, 58 monozygotic (MZ) and 40 dizygotic (DZ) pairs, from the Vietnam Era Twin Registry. All twins were free of overt cardiovascular disease. Carotid IMT was measured by ultrasound. Bivariate and multivariate analyses were used to determine the association between traditional cardiovascular risk factors and carotid IMT. Intraclass correlation coefficients and genetic modeling techniques were used to determine the relative contributions of genes and environment to the variation in carotid IMT. In our sample, the mean of the maximum carotid IMT was 0.75+/-0.11. Age, systolic blood pressure and HDL were significantly associated with carotid IMT. The intraclass correlation coefficient for carotid IMT was larger in MZ (0.66; 95% confidence interval [CI], 0.62-0.69) than in DZ twins (0.37; 95% CI, 0.29-0.44), and the unadjusted heritability was 0.69 (95% CI, 0.54-0.79). After adjusting for traditional coronary risk factors, the heritability of carotid IMT was slightly reduced but still of considerable magnitude (0.59; 95% CI, 0.39-0.73). Genetic factors have a substantial influence on the variation of carotid IMT. Most of this genetic effect occurs through pathways independent of traditional coronary risk factors.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China.

PubMed

Pei, Ling-Ling; Li, Qin; Wang, Zheng-Xin

2018-03-08

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China's pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N )) model based on the nonlinear least square (NLS) method. The Gauss-Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N ) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N ) and the NLS-based TNGM (1, N ) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO₂ and dust, alongside GDP per capita in China during the period 1996-2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N ) model presents greater precision when forecasting WDPC, SO₂ emissions and dust emissions per capita, compared to the traditional GM (1, N ) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO₂ and dust reduce accordingly.

Study on Innovation of Teacher Training Model in Basic Education from the Perspective of "Blended Learning"

ERIC Educational Resources Information Center

Bu, Huabai; Bu, Shizhen

2012-01-01

Gradual integration of synergetic technology, P2P technology and online learning community furnishes a new research field for innovation of teacher training model in a knowledge economy era. This article proposes the innovative model of "whole of three lines" in teacher training in basic education from the perspective of "blended…

Building Research Partnerships with Health Care Organizations: The Scholar Award Model in Action

ERIC Educational Resources Information Center

Aroian, Karen J.; Robertson, Patricia; Allred, Kelly; Andrews, Diane; Waldrop, Julee

2012-01-01

In the current era of limited funding, researchers need strategic alliances to launch or sustain programs of research to significantly impact the nation's health. This article presents a collaborative model, the Scholar Award Model, which is based on a strategic alliance between a College of Nursing in a research-intensive university and a…

Voxelwise multivariate analysis of multimodality magnetic resonance imaging.

PubMed

Naylor, Melissa G; Cardenas, Valerie A; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2014-03-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. Copyright © 2013 Wiley Periodicals, Inc.

Multivariate Analysis of Longitudinal Rates of Change

PubMed Central

Bryan, Matthew; Heagerty, Patrick J.

2016-01-01

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed by Roy and Lin [1]; Proust-Lima, Letenneur and Jacqmin-Gadda [2]; and Gray and Brookmeyer [3] among others. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, Gray and Brookmeyer [3] introduce an “accelerated time” method which assumes that covariates rescale time in longitudinal models for disease progression. In this manuscript we detail an alternative multivariate model formulation that directly structures longitudinal rates of change, and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. PMID:27417129

Developing ecological scenarios for the prospective aquatic risk assessment of pesticides.

PubMed

Rico, Andreu; Van den Brink, Paul J; Gylstra, Ronald; Focks, Andreas; Brock, Theo Cm

2016-07-01

The prospective aquatic environmental risk assessment (ERA) of pesticides is generally based on the comparison of predicted environmental concentrations in edge-of-field surface waters with regulatory acceptable concentrations derived from laboratory and/or model ecosystem experiments with aquatic organisms. New improvements in mechanistic effect modeling have allowed a better characterization of the ecological risks of pesticides through the incorporation of biological trait information and landscape parameters to assess individual, population and/or community-level effects and recovery. Similarly to exposure models, ecological models require scenarios that describe the environmental context in which they are applied. In this article, we propose a conceptual framework for the development of ecological scenarios that, when merged with exposure scenarios, will constitute environmental scenarios for prospective aquatic ERA. These "unified" environmental scenarios are defined as the combination of the biotic and abiotic parameters that are required to characterize exposure, (direct and indirect) effects, and recovery of aquatic nontarget species under realistic worst-case conditions. Ideally, environmental scenarios aim to avoid a potential mismatch between the parameter values and the spatial-temporal scales currently used in aquatic exposure and effect modeling. This requires a deeper understanding of the ecological entities we intend to protect, which can be preliminarily addressed by the formulation of ecological scenarios. In this article we present a methodological approach for the development of ecological scenarios and illustrate this approach by a case-study for Dutch agricultural ditches and the example focal species Sialis lutaria. Finally, we discuss the applicability of ecological scenarios in ERA and propose research needs and recommendations for their development and integration with exposure scenarios. Integr Environ Assess Manag 2016;12:510-521. © 2015 SETAC. © 2015 SETAC.

Assessment of the Temporal Evolution of Storm Surge via Land to Water Isopleths in Coastal Louisiana

NASA Astrophysics Data System (ADS)

Siverd, C. G.; Hagen, S. C.; Bilskie, M. V.; Braud, D.; Gao, S.; Peele, H.; Twilley, R.

2017-12-01

The low-lying coastal Louisiana deltaic landscape features an intricate system of fragmented wetlands, natural ridges, man-made navigation canals and flood protection infrastructure. Since 1900 and prior to the landfall of Hurricane Katrina in 2005, Louisiana lost approximately 480,000 ha (1,850 sq mi) of coastal wetlands and an additional 20,000 ha (77 sq mi) due to Katrina. This resulted in a total wetland storm protection value loss of USD 28.3 billion and USD 1.1 billion, respectively (Costanza 2008). To investigate the response of hurricane storm surge (e.g. peak water levels, inundation time and extent) through time due to land loss, hydrodynamic models that represent historical eras of the Louisiana coastal landscape were developed. Land:Water (L:W) isopleths (Gagliano 1970, 1971, Twilley 2016) have been calculated along the coast from the Sabine River to the Pearl River. These isopleths were utilized to create a simplified coastal landscape (bathymetry, topography, bottom roughness) representing circa 2010. Similar methodologies are employed with the objective of developing storm surge models that represent the coastal landscape for past eras. The goal is to temporally examine the evolution of storm surge along coastal Louisiana. The isopleths determined to best represent the Louisiana coast as a result of the methodology devised to develop the simple storm surge model for c.2010 are applied in the development of surge models for historical eras c.1930 and c.1970. The ADvaced CIRCulation (ADCIRC) code (Luettich 2004) is used to perform storm surge simulations with a predetermined suite of hurricane wind and pressure forcings. Hydrologic Unit Code 12 (HUC12) sub-watersheds provide geographical bounds to quantify mean maximum water surface elevations (WSEs), volume of inundation, and area of inundation. HUC12 sub-watersheds also provide a means to compare/contrast these quantified surge parameters on a HUC12-by-HUC12 basis for the c.1930, c.1970 and c.2010 eras. Results will provide insight into how storm surge has evolved in coastal Louisiana from 1930 to 2010 and assist to inform policy makers of regions with temporally accelerating storm surge.

Reanalysis comparisons of upper tropospheric-lower stratospheric jets and multiple tropopauses

NASA Astrophysics Data System (ADS)

Manney, Gloria L.; Hegglin, Michaela I.; Lawrence, Zachary D.; Wargan, Krzysztof; Millán, Luis F.; Schwartz, Michael J.; Santee, Michelle L.; Lambert, Alyn; Pawson, Steven; Knosp, Brian W.; Fuller, Ryan A.; Daffer, William H.

2017-09-01

The representation of upper tropospheric-lower stratospheric (UTLS) jet and tropopause characteristics is compared in five modern high-resolution reanalyses for 1980 through 2014. Climatologies of upper tropospheric jet, subvortex jet (the lowermost part of the stratospheric vortex), and multiple tropopause frequency distributions in MERRA (Modern-Era Retrospective analysis for Research and Applications), ERA-I (ERA-Interim; the European Centre for Medium-Range Weather Forecasts, ECMWF, interim reanalysis), JRA-55 (the Japanese 55-year Reanalysis), and CFSR (the Climate Forecast System Reanalysis) are compared with those in MERRA-2. Differences between alternate products from individual reanalysis systems are assessed; in particular, a comparison of CFSR data on model and pressure levels highlights the importance of vertical grid spacing. Most of the differences in distributions of UTLS jets and multiple tropopauses are consistent with the differences in assimilation model grids and resolution - for example, ERA-I (with coarsest native horizontal resolution) typically shows a significant low bias in upper tropospheric jets with respect to MERRA-2, and JRA-55 (the Japanese 55-year Reanalysis) a more modest one, while CFSR (with finest native horizontal resolution) shows a high bias with respect to MERRA-2 in both upper tropospheric jets and multiple tropopauses. Vertical temperature structure and grid spacing are especially important for multiple tropopause characterizations. Substantial differences between MERRA and MERRA-2 are seen in mid- to high-latitude Southern Hemisphere (SH) winter upper tropospheric jets and multiple tropopauses as well as in the upper tropospheric jets associated with tropical circulations during the solstice seasons; some of the largest differences from the other reanalyses are seen in the same times and places. Very good qualitative agreement among the reanalyses is seen between the large-scale climatological features in UTLS jet and multiple tropopause distributions. Quantitative differences may, however, have important consequences for transport and variability studies. Our results highlight the importance of considering reanalyses differences in UTLS studies, especially in relation to resolution and model grids; this is particularly critical when using high-resolution reanalyses as an observational reference for evaluating global chemistry-climate models.

A Multivariate Descriptive Model of Motivation for Orthodontic Treatment.

ERIC Educational Resources Information Center

Hackett, Paul M. W.; And Others

1993-01-01

Motivation for receiving orthodontic treatment was studied among 109 young adults, and a multivariate model of the process is proposed. The combination of smallest scale analysis and Partial Order Scalogram Analysis by base Coordinates (POSAC) illustrates an interesting methodology for health treatment studies and explores motivation for dental…

Mathematical Formulation of Multivariate Euclidean Models for Discrimination Methods.

ERIC Educational Resources Information Center

Mullen, Kenneth; Ennis, Daniel M.

1987-01-01

Multivariate models for the triangular and duo-trio methods are described, and theoretical methods are compared to a Monte Carlo simulation. Implications are discussed for a new theory of multidimensional scaling which challenges the traditional assumption that proximity measures and perceptual distances are monotonically related. (Author/GDC)

A Multivariate Model of Parent-Adolescent Relationship Variables in Early Adolescence

ERIC Educational Resources Information Center

McKinney, Cliff; Renk, Kimberly

2011-01-01

Given the importance of predicting outcomes for early adolescents, this study examines a multivariate model of parent-adolescent relationship variables, including parenting, family environment, and conflict. Participants, who completed measures assessing these variables, included 710 culturally diverse 11-14-year-olds who were attending a middle…

Evaluating global reanalysis datasets for provision of boundary conditions in regional climate modelling

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro B.; Evans, Jason P.; Sharma, Ashish

2016-11-01

Regional climate modelling studies often begin by downscaling a reanalysis dataset in order to simulate the observed climate, allowing the investigation of regional climate processes and quantification of the errors associated with the regional model. To date choice of reanalysis to perform such downscaling has been made based either on convenience or on performance of the reanalyses within the regional domain for relevant variables such as near-surface air temperature and precipitation. However, the only information passed from the reanalysis to the regional model are the atmospheric temperature, moisture and winds at the location of the boundaries of the regional domain. Here we present a methodology to evaluate reanalyses derived lateral boundary conditions for an example domain over southern Africa using satellite data. This study focusses on atmospheric temperature and moisture which are easily available. Five commonly used global reanalyses (NCEP1, NCEP2, ERA-I, 20CRv2, and MERRA) are evaluated against the Atmospheric Infrared Sounder satellite temperature and relative humidity over boundaries of two domains centred on southern Africa for the years 2003-2012 inclusive. The study reveals that MERRA is the most suitable for climate mean with NCEP1 the next most suitable. For climate variability, ERA-I is the best followed by MERRA. Overall, MERRA is preferred for generating lateral boundary conditions for this domain, followed by ERA-I. While a "better" LBC specification is not the sole precursor to an improved downscaling outcome, any reduction in uncertainty associated with the specification of LBCs is a step in the right direction.

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.

The Development of Enhanced Recovery After Surgery Across Surgical Specialties.

PubMed

Senturk, James C; Kristo, Gentian; Gold, Jason; Bleday, Ronald; Whang, Edward

2017-09-01

Enhanced recovery after surgery (ERAS ® ) principles have gained traction in variety of surgical disciplines. The promise of a reduced length of stay without compromising patient safety or increasing readmission rates has produced a body of literature examining the implementation of ERAS in the care of general, thoracic, urologic, and gynecologic surgery patients. We performed a review of the literature pertaining to studies of ERAS implementation across colorectal surgery, general surgery, thoracic surgery, urology, and gynecology. The extent of ERAS implementation and reported outcomes across key studies as well as systematic reviews and meta-analyses in each field were summarized. The implementation of ERAS protocols has not been uniform across surgical specialties. Despite this, ERAS has produced improvements in patient outcomes. The most commonly described benefit of ERAS application has been reduced length of stay; complication and readmission rates are most consistently decreased in the colorectal literature. Studies have started to measure more nuanced measures of postoperative patient well-being. Efforts are growing to standardize ERAS protocols across diverse fields and call attention to the need for quality control. Challenges remain in the study and execution of ERAS. Controlling for adherence to ERAS components and implementing uniform ERAS protocols across studies are burgeoning topics that have significant implications for study design. The practice of ERAS and its benefits to patients are expected to evolve. Assessing improvements in postdischarge quality of life, timing of return to work and independent living, and adherence to scheduled delivery of adjuvant treatments will strengthen future ERAS investigations.

How well do Reanalysis represent polar lows?

NASA Astrophysics Data System (ADS)

Zappa, G.; Shaffrey, L.; Hodges, K.

2013-12-01

Polar lows are intense maritime mesocyclones forming at high latitudes during polar air outbreaks. The associated high surface winds can be an important cause of coastal damage.They also seem to play a relevant role in the climate system by modulating the oceanic surface heat fluxes. This creates strong interest in understanding whether modern reanalysis datasets are able to represent polar lows, as well as how their representation may be sensitive to the model resolution. In this talk we investigate how ERA-Interim reanalysis represents the polar lows identified by the Norwegian meteorological services and listed in the STARS (Combination of Sea Surface Temperature and AltimeteR Synergy) dataset for the period 2002-2011. The sensitivity to resolution is explored by comparing ERA-Interim to the ECMWF operational analyses (2008-2011), which have three times higher horizontal resolution compared to ERA-Interim. We show that ERAI-Interim has excellent ability to capture the observed polar lows events with up to 90% of the observed events being found in the reanalysis. However, ERA-Interim tends to have polar lows of weaker dynamical intensity, in terms of both winds and vorticity, and with less spatial structure than in the ECMWF operational analyses (See Fig 1). Furthermore, we apply an objective feature tracking algorithm to the 3 hourly vorticity at 850 hPa with constraints on vorticity intensity and atmospheric static stability to objectively identify polar lows in the ERA-Interim reanalysis. We show that for the stronger polar lows the objective climatology shows good agreement with the STARS dataset over the 2002-2011 period. This allows us to extend the polar lows climatology over the whole ERA Interim period. Differences with another reanalysis product (NCEP-CFSR) will be also discussed. Fig 1: Composite of the tangential wind speed at 925 hPa for 34 polar lows observed in the Norwegian sea between 2008-2010 as represented by the ERA-Interim reanalysis (left) and by the ECMWF Operational analysis (right). Positive values indicate cyclonic circulation. The composite is centered on the polar low vorticity maxima and it is presented for a radial cap of 5 degrees of radius on the sphere (~550Km).

Global reanalyses over Antarctica and the Southern Ocean: Can they be used prior to 1979?

NASA Astrophysics Data System (ADS)

Bromwich, D. H.; Nicolas, J. P.

2017-12-01

High southern latitudes are a notoriously challenging area for global reanalyses, largely due to the scarcity of conventional observations in these regions. This lack of observational constraint not only reduces the reanalysis model forecast skill, but is also responsible for artifacts in their time series tied to changes in the observing system. For example, the introduction of new satellite observations (e.g., AMSU in 1998) is now a well-documented cause of widespread spurious changes in the reanalysis moisture and temperature fields, which are often exacerbated over Antarctica and the Southern Ocean. This lack of temporal consistency has significantly reduced the reliability of some reanalysis products and their suitability for trend analysis. Century-long reanalysis efforts such as 20CR and ERA-20C, which only assimilate surface pressure observations, have provided ways to achieve greater homogeneity in the observing system through time and (potentially) produce more temporally consistent datasets, particularly across 1979 and the onset of the modern satellite era. However, important issues quickly became apparent in these reanalyses, related in particular to the handling by their data assimilation systems of the near-complete absence of observations poleward of 50°S prior to the 1950s, or to the prescription of ocean boundary conditions (sea ice, SST) prior to 1979. Because of the data scarcity, comparing reanalyses with each other is one of the primary means to assess their reliability. As such, the release of the CERA-20C and ERA5 (partially) by ECMWF in 2017 provides an opportunity to reassess the skill of recent global reanalyses in high southern latitudes and take stock of the recent improvements and remaining challenges, particularly with regard to their use for long-term climate change studies. Our comparison will include both satellite-era comprehensive reanalyses (ERA-Interim, CFSR, MERRA2, JRA-55, and ERA5) and century-long limited reanalyses (20CR, ERA-20C, and CERA-20C). The focus will be placed on key climate variables such as sea level pressure, near-surface temperature, and precipitation.

Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

USGS Publications Warehouse

Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.

2013-01-01

In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

Multivariate missing data in hydrology - Review and applications

NASA Astrophysics Data System (ADS)

Ben Aissia, Mohamed-Aymen; Chebana, Fateh; Ouarda, Taha B. M. J.

2017-12-01

Water resources planning and management require complete data sets of a number of hydrological variables, such as flood peaks and volumes. However, hydrologists are often faced with the problem of missing data (MD) in hydrological databases. Several methods are used to deal with the imputation of MD. During the last decade, multivariate approaches have gained popularity in the field of hydrology, especially in hydrological frequency analysis (HFA). However, treating the MD remains neglected in the multivariate HFA literature whereas the focus has been mainly on the modeling component. For a complete analysis and in order to optimize the use of data, MD should also be treated in the multivariate setting prior to modeling and inference. Imputation of MD in the multivariate hydrological framework can have direct implications on the quality of the estimation. Indeed, the dependence between the series represents important additional information that can be included in the imputation process. The objective of the present paper is to highlight the importance of treating MD in multivariate hydrological frequency analysis by reviewing and applying multivariate imputation methods and by comparing univariate and multivariate imputation methods. An application is carried out for multiple flood attributes on three sites in order to evaluate the performance of the different methods based on the leave-one-out procedure. The results indicate that, the performance of imputation methods can be improved by adopting the multivariate setting, compared to mean substitution and interpolation methods, especially when using the copula-based approach.

Models of Solar Irradiance Variability and the Instrumental Temperature Record

NASA Technical Reports Server (NTRS)

Marcus, S. L.; Ghil, M.; Ide, K.

1998-01-01

The effects of decade-to-century (Dec-Cen) variations in total solar irradiance (TSI) on global mean surface temperature Ts during the pre-Pinatubo instrumental era (1854-1991) are studied by using two different proxies for TSI and a simplified version of the IPCC climate model.

Experience, Reflect, Critique: The End of the "Learning Cycles" Era

ERIC Educational Resources Information Center

Seaman, Jayson

2008-01-01

According to prevailing models, experiential learning is by definition a stepwise process beginning with direct experience, followed by reflection, followed by learning. It has been argued, however, that stepwise models inadequately explain the holistic learning processes that are central to learning from experience, and that they lack scientific…

The E-R-A Model: A Heuristic Framework for Classification of Skill Training Programs for Couples and Families.

ERIC Educational Resources Information Center

Ulrici, Donna; And Others

1981-01-01

Provides a model for categorizing marital and family skill training programs according to their theoretical orientation. Describes emotional, reasoning, and action approaches to intervention which allow counselors to examine the relationship between client characteristics and intervention approaches. (JAC)

Technological Discontinuities and Dominant Designs: A Cyclical Model of Technological Change.

ERIC Educational Resources Information Center

Anderson, Philip; Tushman, Michael L.

1990-01-01

Based on longitudinal studies of the cement, glass, and minicomputer industries, this article proposes a technological change model in which a technological breakthrough, or discontinuity, initiates an era of intense technical variation and selection, culminating in a single dominant design and followed by a period of incremental technical…

An Examination of Advisor Concerns in the Era of Academic Analytics

ERIC Educational Resources Information Center

Daughtry, Jeremy J.

2017-01-01

Performance-based funding models are increasingly becoming the norm for many institutions of higher learning. Such models place greater emphasis on student retention and success metrics, for example, as requirements for receiving state appropriations. To stay competitive, universities have adopted academic analytics technologies capable of…

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Customer service in health care: a new era.

PubMed

Eisenberg, B

1997-01-01

Intensified competition in healthcare is stimulating an enhanced focus on consumer satisfaction. Critical barriers to customer service are being dismantled and hospitals are instituting comprehensive models to promote consumer-oriented environments.

Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record

NASA Astrophysics Data System (ADS)

Relan, Rishi; Tiels, Koen; Marconato, Anna; Dreesen, Philippe; Schoukens, Johan

2018-05-01

Many real world systems exhibit a quasi linear or weakly nonlinear behavior during normal operation, and a hard saturation effect for high peaks of the input signal. In this paper, a methodology to identify a parsimonious discrete-time nonlinear state space model (NLSS) for the nonlinear dynamical system with relatively short data record is proposed. The capability of the NLSS model structure is demonstrated by introducing two different initialisation schemes, one of them using multivariate polynomials. In addition, a method using first-order information of the multivariate polynomials and tensor decomposition is employed to obtain the parsimonious decoupled representation of the set of multivariate real polynomials estimated during the identification of NLSS model. Finally, the experimental verification of the model structure is done on the cascaded water-benchmark identification problem.

Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model.

PubMed

Snell, Kym I E; Hua, Harry; Debray, Thomas P A; Ensor, Joie; Look, Maxime P; Moons, Karel G M; Riley, Richard D

2016-01-01

Our aim was to improve meta-analysis methods for summarizing a prediction model's performance when individual participant data are available from multiple studies for external validation. We suggest multivariate meta-analysis for jointly synthesizing calibration and discrimination performance, while accounting for their correlation. The approach estimates a prediction model's average performance, the heterogeneity in performance across populations, and the probability of "good" performance in new populations. This allows different implementation strategies (e.g., recalibration) to be compared. Application is made to a diagnostic model for deep vein thrombosis (DVT) and a prognostic model for breast cancer mortality. In both examples, multivariate meta-analysis reveals that calibration performance is excellent on average but highly heterogeneous across populations unless the model's intercept (baseline hazard) is recalibrated. For the cancer model, the probability of "good" performance (defined by C statistic ≥0.7 and calibration slope between 0.9 and 1.1) in a new population was 0.67 with recalibration but 0.22 without recalibration. For the DVT model, even with recalibration, there was only a 0.03 probability of "good" performance. Multivariate meta-analysis can be used to externally validate a prediction model's calibration and discrimination performance across multiple populations and to evaluate different implementation strategies. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

The effect of pneumococcal conjugate vaccines on incidence and microbiology associated with complicated acute otitis media.

PubMed

Laursen, B B; Danstrup, C S; Hoffmann, S; Nørskov-Lauritsen, N; Christensen, A L B; Ovesen, T

2017-10-01

The objectives of this study were to investigate the incidence of complicated acute otitis media (cAOM) as well as the associated microbiology before and after introduction of the 7- and 13-valent pneumococcal conjugate vaccines (PCV-7 and -13), respectively. CAOM comprises "heavy" AOM (AOM demanding hospitalization), mastodismus (M) and acute mastoiditis (AM). A retrospective cohort study of the incidence and microbiology associated with cAOM during the non-PCV era, the PCV-7 and 13 eras, respectively. Clinical and microbiological data were prospectively registered in a local database. The incidences of cAOM as well as the distribution of various bacterial strains in the three eras were compared. A total of 246 cases of cAOM (125 in the pre-vaccine period (2001-2006), 50 in the PCV-7 period (2007-2010) and 71 in the PCV-13 period (2011-2015)) were identified. The incidence of hAOM decreased by 62% in the PCV7-era but increased to almost pre-vaccine levels in the PCV-13 era. In the M + AM group, a decrease by almost 21% in the PCV7-era was found compared to the pre vaccine era, whereas the decrease was only 12% in the PCV13-era. The three most common findings in both hAOM and M + AM were Streptococcus pneumonia (SP), group A streptococcus (GAS) and "no growth". In the hAOM group, SP decreased from 38% in the pre-vaccine era to 31% in the PCV7-era and further to 16% in the PCV13-era. GAS decreased from 17% in the pre-vaccine era to 0% in the PCV7-era and 16% in the PCV13-era. The percentage of "no growth" increased from 12% to 38% and 44%, respectively. In the M + AM group, SP decreased to 10% in the PCV13-era compared with 44% in the pre-vaccine era and 41% in the PCV7-era. An increase in GAS from 15% in the pre-vaccine era and PCV7-era to 30% in the PCV13-era was observed. The "no growth" percentage increased from 13% in the pre-vaccine era to 26% in the PCV7-era and 33% in the PCV13-era. Introduction of PCV7 and PCV13 has been associated with an overall reduction of cAOM in Central Region Denmark. Pneumococci were still one of the two most common bacteria species related to cAOM though a decrease in pneumococci positive cases was observed. We found an increase in M + AM induced by GAS and a relatively large increase in "no growth", which might be caused by a more aggressive pre-hospital approach to treatment with antibiotics. Consequently, it is not evident whether the reduction of incidences is caused by the vaccines or a more aggressive antimicrobial attitude to manage AOM. The shift to GAS from SP is worrisome, and therefore continuous surveillance of the microbiology associated with AOM is warranted. Copyright © 2017 Elsevier B.V. All rights reserved.

Multivariate Formation Pressure Prediction with Seismic-derived Petrophysical Properties from Prestack AVO inversion and Poststack Seismic Motion Inversion

NASA Astrophysics Data System (ADS)

Yu, H.; Gu, H.

2017-12-01

A novel multivariate seismic formation pressure prediction methodology is presented, which incorporates high-resolution seismic velocity data from prestack AVO inversion, and petrophysical data (porosity and shale volume) derived from poststack seismic motion inversion. In contrast to traditional seismic formation prediction methods, the proposed methodology is based on a multivariate pressure prediction model and utilizes a trace-by-trace multivariate regression analysis on seismic-derived petrophysical properties to calibrate model parameters in order to make accurate predictions with higher resolution in both vertical and lateral directions. With prestack time migration velocity as initial velocity model, an AVO inversion was first applied to prestack dataset to obtain high-resolution seismic velocity with higher frequency that is to be used as the velocity input for seismic pressure prediction, and the density dataset to calculate accurate Overburden Pressure (OBP). Seismic Motion Inversion (SMI) is an inversion technique based on Markov Chain Monte Carlo simulation. Both structural variability and similarity of seismic waveform are used to incorporate well log data to characterize the variability of the property to be obtained. In this research, porosity and shale volume are first interpreted on well logs, and then combined with poststack seismic data using SMI to build porosity and shale volume datasets for seismic pressure prediction. A multivariate effective stress model is used to convert velocity, porosity and shale volume datasets to effective stress. After a thorough study of the regional stratigraphic and sedimentary characteristics, a regional normally compacted interval model is built, and then the coefficients in the multivariate prediction model are determined in a trace-by-trace multivariate regression analysis on the petrophysical data. The coefficients are used to convert velocity, porosity and shale volume datasets to effective stress and then to calculate formation pressure with OBP. Application of the proposed methodology to a research area in East China Sea has proved that the method can bridge the gap between seismic and well log pressure prediction and give predicted pressure values close to pressure meassurements from well testing.

Time Series Model Identification by Estimating Information.

DTIC Science & Technology

1982-11-01

principle, Applications of Statistics, P. R. Krishnaiah , ed., North-Holland: Amsterdam, 27-41. Anderson, T. W. (1971). The Statistical Analysis of Time Series...E. (1969). Multiple Time Series Modeling, Multivariate Analysis II, edited by P. Krishnaiah , Academic Press: New York, 389-409. Parzen, E. (1981...Newton, H. J. (1980). Multiple Time Series Modeling, II Multivariate Analysis - V, edited by P. Krishnaiah , North Holland: Amsterdam, 181-197. Shibata, R

Determining the Relationship Between Moral Waivers and Marine Corps Unsuitability Attrition

DTIC Science & Technology

2008-03-01

observed characteristics. However, econometric research indicates that the magnitude of interaction effects estimated via probit or logit models may...1997 to 2005. Multivariate probit models were used to analyze the effects of moral waivers on unsatisfactory service separations. 15. NUMBER OF...files from fiscal years 1997 to 2005. Multivariate probit models were used to analyze the effects of moral waivers on unsatisfactory service

Protection goals in environmental risk assessment: a practical approach.

PubMed

Garcia-Alonso, Monica; Raybould, Alan

2014-12-01

Policy protection goals are set up in most countries to minimise harm to the environment, humans and animals caused by human activities. Decisions on whether to approve new agricultural products, like pesticides or genetically modified (GM) crops, take into account these policy protection goals. To support decision-making, applications for approval of commercial uses of GM crops usually comprise an environmental risk assessment (ERA). These risk assessments are analytical tools, based on science, that follow a conceptual model that includes a problem formulation step where policy protection goals are considered. However, in most countries, risk assessors face major problems in that policy protection goals set in the legislation are stated in very broad terms and are too ambiguous to be directly applicable in ERAs. This means that risk assessors often have to interpret policy protection goals without clear guidance on what effects would be considered harmful. In this paper we propose a practical approach that may help risk assessors to translate policy protection goals into unambiguous (i.e., operational) protection goals and to establish relevant assessment endpoints and risk hypotheses that can be used in ERAs. Examples are provided to show how this approach can be applied to two areas of environmental concern relevant to the ERAs of GM crops.

Forcing mechanism of the seasonally asymmetric quasi-biennial oscillation secondary circulation in ERA-40 and MAECHAM5

NASA Astrophysics Data System (ADS)

Peña-Ortiz, C.; Ribera, P.; García-Herrera, R.; Giorgetta, M. A.; García, R. R.

2008-08-01

The seasonality of the quasi-biennial oscillation (QBO) and its secondary circulation is analyzed in the European Reanalysis (ERA-40) and Middle Atmosphere European Centre Hamburg Model (MAECHAM5) general circulation model data sets through the multitaper method-singular value decomposition (MTM-SVD). In agreement with previous studies, the results reveal a strong seasonal dependence of the QBO secondary circulation. This is characterized by a two-cell structure symmetric about the equator during autumn and spring. However, anomalies strongly weaken in the summer hemisphere and strengthen in the winter hemisphere, leading to an asymmetric QBO secondary circulation characterized by a single-cell structure displaced into the winter hemisphere during the solstices. In ERA-40, this asymmetry is more pronounced during the northern than during the southern winter. These results provide the first observation of the QBO secondary circulation asymmetries in the ERA-40 reanalysis data set across the full stratosphere and the lower mesosphere, up to 0.1 hPa. The MTM-SVD reconstruction of the seasonal QBO signals in the residual circulation and the QBO signals in Eliassen Palm (EP) flux divergences suggest a particular mechanism for the seasonal asymmetries of the QBO secondary circulation and its extension across the midlatitudes. The analysis shows that the QBO modulates the EP flux in the winter hemispheric surf zone poleward of the QBO jets. The zonal wind forcing by EP flux divergence is transformed by the Coriolis effect into a meridional wind signal. The seasonality in the stratospheric EP flux and the hemispheric differences in planetary wave forcing cause the observed seasonality in the QBO secondary circulation and its hemispheric differences.

9th International Symposium on the Biosafety of Genetically Modified Organisms. Session II: Identifying and defining hazards and potential consequences I: Concepts for problem formulation and non-target risk assessment.

PubMed

Bigler, Franz

2006-01-01

The scientific organizers of the symposium put much emphasis on the identification and definition of hazard and the potential consequences thereof and three full sessions with a total of 13 presentations encompassing a wide range of related themes were planned for this topic. Unfortunately, one talk had to be cancelled because of illness of the speaker (BM Khadi, India). Some presentations covered conceptual approaches for environmental risk assessment (ERA) of GM plants (problem formulation in the risk assessment framework, familiarity approach, tiered and methodological frameworks, non-target risk assessment) and the use of models in assessing invasiveness and weediness of GM plants. Other presentations highlighted the lessons learned for future ERA from case studies and commercialized GM crops, and from monitoring of unintended releases to the environment. When the moderators of the three sessions came together after the presentations to align their summaries, there was an obvious need to restructure the 12 presentations in a way that allowed for a consistent summarizing discussion. The following new organization of the 12 talks was chosen: (1) Concepts for problem formulation and non-target risk assessment, (2) Modeling as a tool for predicting invasiveness of GM plants, (3) Case-studies of ERA of large-scale release, (4) Lessons learned for ERA from a commercialized GM plant, (5) Monitoring of unintended release of Bt maize in Mexico. The new thematic structure facilitates a more in-depth discussion of the presentations related to a specific topic, and the conclusions to be drawn are thus more consistent. Each moderator agreed to take responsibility for summarizing one or more themes and to prepare the respective report.

Enhancing Global Land Surface Hydrology Estimates from the NASA MERRA Reanalysis Using Precipitation Observations and Model Parameter Adjustments

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Koster, Randal; DeLannoy, Gabrielle; Forman, Barton; Liu, Qing; Mahanama, Sarith; Toure, Ally

2011-01-01

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides. in addition to atmospheric fields. global estimates of soil moisture, latent heat flux. snow. and runoff for J 979-present. This study introduces a supplemental and improved set of land surface hydrological fields ('MERRA-Land') generated by replaying a revised version of the land component of the MERRA system. Specifically. the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameters in the rainfall interception model, changes that effectively correct for known limitations in the MERRA land surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim reanalysis. MERRA-Land and ERA-Interim root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 15 basins in the western US) of MERRA and MERRA-Land is typically higher than that of ERA-Interim. With a few exceptions. the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using '\\-tERRA output for land surface hydrological studies.

Spatiotemporal Evaluation of Reanalysis and In-situ Surface Air Temperature over Ethiopia

NASA Astrophysics Data System (ADS)

Tesfaye, T.

2017-12-01

Tewodros Woldemariam Tesfaye*1, C.T. Dhanya 2,and A.K. Gosain3 1Research Scholar, Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India 2Assistant Professor, Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India 3 Professor, Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India, *e-mail: tewodros2002@gmail.com Abstract: Water resources management and modelling studies are often constrained by the scarcity of observed data, especially of the two major variables i.e., precipitation and temperature. Modellers, hence, rely on reanalysis datasets as a substitute; though its performance heavily vary depending on the data availability and regional characteristics. The present study aims at examining the ability of frequently used reanalysis datasets in capturing the spatiotemporal characteristics of maximum and minimum surface temperatures over Ethiopia and to highlight the biases, if any, in these over Ethiopian region. We considered ERA-Interim, NCEP 2, MERRA and CFSR reanalysis datasets and compared these with temperature observations from 15 synoptic stations spread over Ethiopia. In addition to the long term averages and annual cycle, a critical comparison of various extreme indices such as diurnal temperature range, warm days, warm nights, cool days, cool nights, summer days and tropical nights are also undertaken. Our results indicate that, the performance of CFSR followed by NCEP 2 is better in capturing majority of the aspects. ERA-Interim suffers a huge additive bias in the simulation of various aspects of minimum temperature in all the stations considered; while its performance is better for maximum temperature. The inferior performance of ERA-Interim is noted to be only because of the difficulty in simulating minimum temperature. Key words: ERA Interim; NCEP Reanalysis; MERRA; CFSR; Diurnal temperature range; reanalysis performance.

Growth of structure in the Szekeres class-II inhomogeneous cosmological models and the matter-dominated era

NASA Astrophysics Data System (ADS)

Ishak, Mustapha; Peel, Austin

2012-04-01

This study belongs to a series devoted to using the Szekeres inhomogeneous models in order to develop a theoretical framework where cosmological observations can be investigated with a wider range of possible interpretations. While our previous work addressed the question of cosmological distances versus redshift in these models, the current study is a start at looking into the growth rate of large-scale structure. The Szekeres models are exact solutions to Einstein’s equations that were originally derived with no symmetries. We use here a formulation of the Szekeres models that is due to Goode and Wainwright, who considered the models as exact perturbations of a Friedmann-Lemaître-Robertson-Walker (FLRW) background. Using the Raychaudhuri equation we write, for the two classes of the models, exact growth equations in terms of the under/overdensity and measurable cosmological parameters. The new equations in the overdensity split into two informative parts. The first part, while exact, is identical to the growth equation in the usual linearly perturbed FLRW models, while the second part constitutes exact nonlinear perturbations. We integrate numerically the full exact growth rate equations for the flat and curved cases. We find that for the matter-dominated cosmic era, the Szekeres growth rate is up to a factor of three to five stronger than the usual linearly perturbed FLRW cases, reflecting the effect of exact Szekeres nonlinear perturbations. We also find that the Szekeres growth rate with an Einstein-de Sitter background is stronger than that of the well-known nonlinear spherical collapse model, and the difference between the two increases with time. This highlights the distinction when we use general inhomogeneous models where shear and a tidal gravitational field are present and contribute to the gravitational clustering. Additionally, it is worth observing that the enhancement of the growth found in the Szekeres models during the matter-dominated era could suggest a substitute to the argument that dark matter is needed when using FLRW models to explain the enhanced growth and resulting large-scale structures that we observe today.

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Koster, Randal D.; deLannoy, Gabrielle J. M.; Forman, Barton A.; Liu, Qing; Mahanama, Sarith P. P.; Toure, Ally

2012-01-01

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-ofthe-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields ("MERRA-Land") generated by re-running a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim (ERA-I) reanalysis. MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 US basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

Evaluation of ERA-interim and MERRA Cloudiness in the Southern Oceans

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Booth, James F.; Del Genio, Anthony D.

2014-01-01

The Southern Ocean cloud cover modeled by the Interim ECMWF Re-Analysis (ERA-Interim) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) reanalyses are compared against Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) observations. ERA-Interim monthly mean cloud amounts match the observations within 5%, while MERRA significantly underestimates the cloud amount. For a compositing analysis of clouds in warm season extratropical cyclones, both reanalyses show a low bias in cloud cover. They display a larger bias to the west of the cyclones in the region of subsidence behind the cold fronts. This low bias is larger for MERRA than for ERA-Interim. Both MODIS and MISR retrievals indicate that the clouds in this sector are at a low altitude, often composed of liquid, and of a broken nature. The combined CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud profiles confirm these passive observations, but they also reveal that low-level clouds in other parts of the cyclones are also not properly represented in the reanalyses. The two reanalyses are in fairly good agreement for the dynamic and thermodynamic characteristics of the cyclones, suggesting that the cloud, convection, or boundary layer schemes are the problem instead. An examination of the lower-tropospheric stability distribution in the cyclones from both reanalyses suggests that the parameterization of shallow cumulus clouds may contribute in a large part to the problem. However, the differences in the cloud schemes and in particular in the precipitation processes, which may also contribute, cannot be excluded.

Cosmic infinity: a dynamical system approach

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

Bouhmadi-López, Mariam; Marto, João; Morais, João

2017-03-01

Dynamical system techniques are extremely useful to study cosmology. It turns out that in most of the cases, we deal with finite isolated fixed points corresponding to a given cosmological epoch. However, it is equally important to analyse the asymptotic behaviour of the universe. On this paper, we show how this can be carried out for 3-form models. In fact, we show that there are fixed points at infinity mainly by introducing appropriate compactifications and defining a new time variable that washes away any potential divergence of the system. The richness of 3-form models allows us as well to identifymore » normally hyperbolic non-isolated fixed points. We apply this analysis to three physically interesting situations: (i) a pre-inflationary era; (ii) an inflationary era; (iii) the late-time dark matter/dark energy epoch.« less

Targeted Feedback in the Milestones Era: Utilization of the Ask-Tell-Ask Feedback Model to Promote Reflection and Self-Assessment.

PubMed

French, Judith C; Colbert, Colleen Y; Pien, Lily C; Dannefer, Elaine F; Taylor, Christine A

2015-01-01

The Accreditation Council for Graduate Medical Education's Milestones Project focuses trainee education on the formation of valued behaviors and skills believed to be necessary for trainees to become independent practitioners. The development and refinement of behaviors and skills outlined within the milestones will require learners to monitor, reflect, and assess their own performance over time. External feedback provides an opportunity for learners to recalibrate their self-assessments, thereby enabling them to develop better self-monitoring and self-assessment skills. Yet, feedback to trainees is frequently generic, such as "great job," "nice work," or "you need to read more." In this article, we describe a feedback model that faculty can use to provide specific feedback, while increasing accountability for learners. We offer practical examples of its use in a variety of settings in the milestone era. The Ask-Tell-Ask (ATA) patient communication skills strategy, which was adapted for use as a trainee feedback model 10 years ago at our institution, is a learner-centered approach for reinforcing and modifying behaviors. The model is efficient, promotes learner accountability, and helps trainees develop reflection and self-assessment skills. A feedback agreement further enhances ATA by establishing a shared understanding of goals for the educational encounter. The ATA feedback model, combined with a feedback agreement, encourages learners to self-identify strengths and areas for improvement, before receiving feedback. Personal monitoring, reflection, self-assessment, and increased accountability make ATA an ideal learner-centered feedback model for the milestones era, which focuses on performance improvement over time. We believe the introduction of the ATA feedback model in surgical training programs is a step in the right direction towards meaningful programmatic culture change. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

A General Multivariate Latent Growth Model with Applications to Student Achievement

ERIC Educational Resources Information Center

Bianconcini, Silvia; Cagnone, Silvia

2012-01-01

The evaluation of the formative process in the University system has been assuming an ever increasing importance in the European countries. Within this context, the analysis of student performance and capabilities plays a fundamental role. In this work, the authors propose a multivariate latent growth model for studying the performances of a…

Bayesian Estimation of Random Coefficient Dynamic Factor Models

ERIC Educational Resources Information Center

Song, Hairong; Ferrer, Emilio

2012-01-01

Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…

Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

2001-01-01

Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…

Modeling Associations among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach

ERIC Educational Resources Information Center

Tchumtchoua, Sylvie; Dey, Dipak K.

2012-01-01

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the…

Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2010-01-01

A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments

PubMed Central

Avalappampatty Sivasamy, Aneetha; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better. PMID:26357668

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments.

PubMed

Sivasamy, Aneetha Avalappampatty; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

Predictive model for falling in Parkinson disease patients.

PubMed

Custodio, Nilton; Lira, David; Herrera-Perez, Eder; Montesinos, Rosa; Castro-Suarez, Sheila; Cuenca-Alfaro, Jose; Cortijo, Patricia

2016-12-01

Falls are a common complication of advancing Parkinson's disease (PD). Although numerous risk factors are known, reliable predictors of future falls are still lacking. The aim of this study was to develop a multivariate model to predict falling in PD patients. Prospective cohort with forty-nine PD patients. The area under the receiver-operating characteristic curve (AUC) was calculated to evaluate predictive performance of the purposed multivariate model. The median of PD duration and UPDRS-III score in the cohort was 6 years and 24 points, respectively. Falls occurred in 18 PD patients (30%). Predictive factors for falling identified by univariate analysis were age, PD duration, physical activity, and scores of UPDRS motor, FOG, ACE, IFS, PFAQ and GDS ( p -value < 0.001), as well as fear of falling score ( p -value = 0.04). The final multivariate model (PD duration, FOG, ACE, and physical activity) showed an AUC = 0.9282 (correctly classified = 89.83%; sensitivity = 92.68%; specificity = 83.33%). This study showed that our multivariate model have a high performance to predict falling in a sample of PD patients.

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

PubMed

Hurtado Rúa, Sandra M; Mazumdar, Madhu; Strawderman, Robert L

2015-12-30

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Outcome of adults with Eisenmenger syndrome treated with drugs specific to pulmonary arterial hypertension: A French multicentre study.

PubMed

Hascoet, Sebastien; Fournier, Emmanuelle; Jaïs, Xavier; Le Gloan, Lauriane; Dauphin, Claire; Houeijeh, Ali; Godart, Francois; Iriart, Xavier; Richard, Adelaïde; Radojevic, Jelena; Amedro, Pascal; Bosser, Gilles; Souletie, Nathalie; Bernard, Yvette; Moceri, Pamela; Bouvaist, Hélène; Mauran, Pierre; Barre, Elise; Basquin, Adeline; Karsenty, Clement; Bonnet, Damien; Iserin, Laurence; Sitbon, Olivier; Petit, Jérôme; Fadel, Elie; Humbert, Marc; Ladouceur, Magalie

2017-05-01

The relationship between pulmonary arterial hypertension-specific drug therapy (PAH-SDT) and mortality in Eisenmenger syndrome (ES) is controversial. To investigate outcomes in patients with ES, and their relationship with PAH-SDT. Retrospective, observational, nationwide, multicentre cohort study. We included 340 patients with ES: genetic syndrome (n=119; 35.3%); pretricuspid defect (n=75; 22.1%). Overall, 276 (81.2%) patients received PAH-SDT: monotherapy (endothelin receptor antagonist [ERA] or phosphodiesterase 5 inhibitor [PDE5I]) 46.7%; dual therapy (ERA+PDE5I) 40.9%; triple therapy (ERA+PDE5I+prostanoid) 9.1%. Median PAH-SDT duration was 5.5 years [3.0-9.1 years]. Events (death, lung or heart-lung transplantation) occurred in 95 (27.9%) patients at a median age of 40.5 years [29.4-47.6]. The cumulative occurrence of events was 16.7% [95% confidence interval 12.8-21.6%] and 46.4% [95% confidence interval 38.2-55.4%] at age 40 and 60 years, respectively. With age at evaluation or time since PAH diagnosis as time scales, cumulative occurrence of events was lower in patients taking one or two PAH-SDTs (P=0.0001 and P=0.004, respectively), with the largest differences in the post-tricuspid defect subgroup (P<0.001 and P<0.02, respectively) versus patients without PAH-SDT. By multivariable Cox analysis, with time since PAH diagnosis as time scale, New York Heart Association/World Health Organization functional class III/IV, lower peripheral arterial oxygen saturation and pretricuspid defect were associated with a higher risk of events (P=0.002, P=0.01 and P=0.04, respectively), and one or two PAH-SDTs with a lower risk of events (P=0.009). Outcomes are poor in ES, but seem better with PAH-SDT. ES with pretricuspid defects has worse outcomes despite the delayed disease onset. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Examining ABO compatible donors in double lung transplants during the era of lung allocation score.

PubMed

Taghavi, Sharven; Jayarajan, Senthil N; Furuya, Yuka; Komaroff, Eugene; Shiose, Akira; Leotta, Eros; Hisamoto, Kazuhiro; Patel, Namrata; Cordova, Francis; Criner, Gerard; Guy, T Sloane; Toyoda, Yoshiya

2014-10-01

The short-term and long-term effect of using ABO compatible donors in the era of lung allocation score is unknown. This study determined if carefully selected ABO compatible donors could be used in double lung transplantation (DLT) with good outcomes. The United Network for Organ Sharing database was retrospectively reviewed for adult DLT from May 2005 to December 2011. Of 6,655 double lung transplants, 493 (7.4%) were with ABO compatible donors and 6,162 (92.6%) were with ABO identical donors. In multivariate analysis, use of ABO compatible donors was not associated with mortality at 30 days (HR, 1.16; 95% CI, 0.76 to 1.79, p = 0.49), 1 year (HR, 1.10; 95% CI, 0.86 to 1.42, p = 0.46), and 5 years (HR, 1.06; 95% CI, 0.83 to 1.34, p = 0.65). Variables associated with mortality at 5 years were donor female sex, donor age 60 years or greater, prolonged ischemic time, increasing recipient creatinine, recipient age, race mismatch, and mechanical ventilation or extracorporeal membrane oxygenation as a bridge to transplantation. Length of stay was longer in the ABO compatible group (30.9 vs 25.9 days, p = 0.001). Acute rejection episodes on index hospitalization (8.8 vs. 8.9%, p = 1.00), peak posttransplant forced expiratory volume in 1 second (FEV1) (82.7 vs 79.7%, p = 0.053), and decrement in FEV1 over time were not different (p = 0.13). Freedom from bronchiolitis obliterans syndrome was similar (1,475 vs 1,454 days, p = 0.17). The use of ABO compatible donors in the era of lung allocation score was not associated with short-term or long-term mortality and resulted in equivalent posttransplant lung function. A DLT with carefully selected ABO compatible donors can result in excellent outcomes. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Assessing reanalysis quality with early sounders Nimbus-4 IRIS (1970) and Nimbus-6 HIRS (1975)

NASA Astrophysics Data System (ADS)

Poli, Paul; Brunel, Pascal

2018-07-01

This paper revisits the data collected by early sounders Nimbus-4 IRIS (1970) and Nimbus-6 HIRS (1975), after recovery of ageing tapes by NASA GES DISC. New quality controls are proposed to screen out erroneous or suspicious mission data, based on instrument health status data records and other inspection of the data. Radiative transfer coefficients are derived for the fast computation of clear-sky radiative transfer simulations. Atmospheric profiles from ERA-40 and ERA-20C reanalyses are used in input. These spatio-temporally complete datasets are interpolated to each sounding location, using the closest estimate in time. A modern cloud detection method derived for current hyperspectral sounders is applied to IRIS and yields maps of cloud cover that are in line with current knowledge of cloud climatology. For clear scenes, the standard deviation of brightness temperature differences between IRIS observations and simulations from ERA-20C is around 1 K for the lower-peaking temperature channels of the 15 μm CO2 band, and lower than 1 K for simulations from ERA-40. The IRIS and HIRS instrumental data records are projected in a common sub-space to alleviate issues with different field-of-view resolutions and spectral resolutions. A proxy cloud detection scheme screens out clouds in the same manner in both data records. Considering the month of August, common to both missions, a detailed analysis of the departures from observations suggests that ERA-40 suffers from spurious tropospheric warming, possibly caused by changes in the observation input during the 1970s including a known error in ERA-40 radiance assimilation bias correction. This result, confirmed by considering a climate model integration, demonstrates that it is possible to exploit early sounder data records to derive detailed insight from reanalyses, such as attempting to qualify separately random and systematic errors in reanalyses, even at times when few other independent observation data are available.

Temporal variability in wind-wave climate and its validation with ESSO-NIOT wave atlas for the head Bay of Bengal

NASA Astrophysics Data System (ADS)

Patra, Anindita; Bhaskaran, Prasad K.

2017-08-01

The head Bay region bordering the northern Bay of Bengal is a densely populated area with a complex geomorphologic setting, and highly vulnerable to extreme water levels along with other factors like sea level rise and impact of tropical cyclones. The influence of climate change on wind-wave regime from this region of Bay of Bengal is not known well and that requires special attention, and there is a need to perform its long-term assessment for societal benefits. This study provides a comprehensive analysis on the temporal variability in domain averaged wind speed, significant wave height (SWH) utilizing satellite altimeter data (1992-2012) and mean wave period using ECMWF reanalysis products ERA-Interim (1992-2012) and ERA-20C (1992-2010) over this region. The SWH derived from WAVEWATCH III (WW3) model along with the ERA-Interim reanalysis supplements the observed variability in satellite altimeter observations. Further, the study performs an extensive error estimation of SWH and mean wave period with ESSO-NIOT wave atlas that shows a high degree of under-estimation in the wave atlas mean wave period. Annual mean and wind speed maxima from altimeter show an increasing trend, and to a lesser extent in the SWH. Interestingly, the estimated trend is higher for maxima compared to the mean conditions. Analysis of decadal variability exhibits an increased frequency of higher waves in the present decade compared to the past. Linear trend analysis show significant upswing in spatially averaged ERA-20C mean wave period, whereas the noticed variations are marginal in the ERA-Interim data. A separate trend analysis for the wind-seas, swell wave heights and period from ERA-20C decipher the fact that distant swells governs the local wind-wave climatology over the head Bay region, and over time the swell activity have increased in this region.

Data Analysis of GPM Constellation Satellites-IMERG and ERA-Interim precipitation products over West of Iran

NASA Astrophysics Data System (ADS)

Sharifi, Ehsan; Steinacker, Reinhold; Saghafian, Bahram

2016-04-01

Precipitation is a critical component of the Earth's hydrological cycle. The primary requirement in precipitation measurement is to know where and how much precipitation is falling at any given time. Especially in data sparse regions with insufficient radar coverage, satellite information can provide a spatial and temporal context. Nonetheless, evaluation of satellite precipitation is essential prior to operational use. This is why many previous studies are devoted to the validation of satellite estimation. Accurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to hazards. In situ observations over mountainous areas are mostly limited, but currently available satellite precipitation products can potentially provide the precipitation estimation needed for meteorological and hydrological applications. One of the newest and blended methods that use multi-satellites and multi-sensors has been developed for estimating global precipitation. The considered data set known as Integrated Multi-satellitE Retrievals (IMERG) for GPM (Global Precipitation Measurement) is routinely produced by the GPM constellation satellites. Moreover, recent efforts have been put into the improvement of the precipitation products derived from reanalysis systems, which has led to significant progress. One of the best and a worldwide used model is developed by the European Centre for Medium Range Weather Forecasts (ECMWF). They have produced global reanalysis daily precipitation, known as ERA-Interim. This study has evaluated one year of precipitation data from the GPM-IMERG and ERA-Interim reanalysis daily time series over West of Iran. IMERG and ERA-Interim yield underestimate the observed values while IMERG underestimated slightly and performed better when precipitation is greater than 10mm. Furthermore, with respect to evaluation of probability of detection (POD), threat score (TS), false alarm ratio (FAR) and probability of false detection (POFD) IMERG yields a better value of POD, TS, FAR and POFD in comparison to era-Interim. Overall, ERA-Interim product produced fewer robust results when compared to IMERG.

Structural insights into cell cycle control by essential GTPase Era.

PubMed

Ji, Xinhua

Era (Escherichia coli Ras-like protein), essential for bacterial cell viability, is composed of an N-terminal GTPase domain and a C-terminal KH domain. In bacteria, it is required for the processing of 16S ribosomal RNA (rRNA) and maturation of 30S (small) ribosomal subunit. Era recognizes 10 nucleotides ( 1530 GAUCACCUCC 1539 ) near the 3' end of 16S rRNA and interacts with helix 45 (h45, nucleotides 1506-1529). GTP binding enables Era to bind RNA, RNA binding stimulates Era's GTP-hydrolyzing activity, and GTP hydrolysis releases Era from matured 30S ribosomal subunit. As such, Era controls cell growth rate via regulating the maturation of the 30S ribosomal subunit. Ribosomes manufacture proteins in all living organisms. The GAUCA sequence and h45 are highly conserved in all three kingdoms of life. Homologues of Era are present in eukaryotic cells. Hence, the mechanism of bacterial Era action also sheds light on the cell cycle control of eukaryotes.

Studying Resist Stochastics with the Multivariate Poisson Propagation Model

DOE PAGES

Naulleau, Patrick; Anderson, Christopher; Chao, Weilun; ...

2014-01-01

Progress in the ultimate performance of extreme ultraviolet resist has arguably decelerated in recent years suggesting an approach to stochastic limits both in photon counts and material parameters. Here we report on the performance of a variety of leading extreme ultraviolet resist both with and without chemical amplification. The measured performance is compared to stochastic modeling results using the Multivariate Poisson Propagation Model. The results show that the best materials are indeed nearing modeled performance limits.

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2005-01-01

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

Military deployment to the Gulf War as a risk factor for psychiatric illness among US troops.

PubMed

Fiedler, Nancy; Ozakinci, Gozde; Hallman, William; Wartenberg, Daniel; Brewer, Noel T; Barrett, Drue H; Kipen, Howard M

2006-05-01

Several studies document an excess of psychiatric symptoms among veterans of the the 1991 Gulf War. However, little is known about the prevalence of psychiatric disorders in those who were deployed to that conflict. To compare the 12-month prevalence and associated risk factors for DSM Axis I psychiatric diagnoses between random samples of Gulf War-deployed veterans and veterans of the same era not deployed to the Persian Gulf (era veterans). Interview data from 967 Gulf War veterans and 784 era veterans were examined to determine current health status, medical conditions, symptoms and Axis I psychiatric disorders. Logistic regression models evaluated risk factors for psychiatric disorder. Gulf War veterans had a significantly higher prevalence of psychiatric diagnoses, with twice the prevalence of anxiety disorders and depression. Lower rank, female gender and divorced or single marital status were significant independent predictors of psychiatric disorder. Deployment to the Gulf War is associated with a range of mental health outcomes more than 10 years after deployment.

The comet assay in Environmental Risk Assessment of marine pollutants: applications, assets and handicaps of surveying genotoxicity in non-model organisms.

PubMed

Martins, Marta; Costa, Pedro M

2015-01-01

Determining the genotoxic effects of pollutants has long been a priority in Environmental Risk Assessment (ERA) for coastal ecosystems, especially of complex areas such as estuaries and other confined waterbodies. The acknowledged link between DNA damage, mutagenicity and carcinogenicity to the exposure to certain toxicants has been responsible to the growing interest in determining the genotoxic effects of xenobiotics to wildlife as a measure of environmental risk. The comet assay, although widely employed in in vivo and in vitro toxicology, still holds many constraints in ERA, in large part owing to difficulties in obtaining conclusive cause-effect relationships from complex environments. Nevertheless, these challenges do not hinder the attempts to apply the alkaline comet assay on sentinel organisms, wild or subjected to bioassays in or ex situ (from fish to molluscs) as well to standardise protocols and establish general guidelines to the interpretation of findings. Fish have been regarded as an appealing subject due to the ease of performing the comet assay in whole blood. However, the application of the comet assay is becoming increasingly common in invertebrates (e.g. in molluscan haemocytes and solid tissues such as gills). Virtually all sorts of results have been obtained from the application of the comet assay in ERA (null, positive and inconclusive). However, it has become clear that interpreting DNA damage data from wild organisms is particularly challenging due to their ability to adapt to continuous environmental stressors, including toxicants. Also, the comet assay in non-model organisms for the purpose of ERA implies different constraints, assumptions and interpretation of findings, compared with the in vitro procedures from which most guidelines have been derived. This paper critically reviews the application of the comet assay in ERA, focusing on target organisms and tissues; protocol developments, case studies plus data handling and interpretation. © The Author 2014. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Synergies Between Grace and Regional Atmospheric Modeling Efforts

NASA Astrophysics Data System (ADS)

Kusche, J.; Springer, A.; Ohlwein, C.; Hartung, K.; Longuevergne, L.; Kollet, S. J.; Keune, J.; Dobslaw, H.; Forootan, E.; Eicker, A.

2014-12-01

In the meteorological community, efforts converge towards implementation of high-resolution (< 12km) data-assimilating regional climate modelling/monitoring systems based on numerical weather prediction (NWP) cores. This is driven by requirements of improving process understanding, better representation of land surface interactions, atmospheric convection, orographic effects, and better forecasting on shorter timescales. This is relevant for the GRACE community since (1) these models may provide improved atmospheric mass separation / de-aliasing and smaller topography-induced errors, compared to global (ECMWF-Op, ERA-Interim) data, (2) they inherit high temporal resolution from NWP models, (3) parallel efforts towards improving the land surface component and coupling groundwater models; this may provide realistic hydrological mass estimates with sub-diurnal resolution, (4) parallel efforts towards re-analyses, with the aim of providing consistent time series. (5) On the other hand, GRACE can help validating models and aids in the identification of processes needing improvement. A coupled atmosphere - land surface - groundwater modelling system is currently being implemented for the European CORDEX region at 12.5 km resolution, based on the TerrSysMP platform (COSMO-EU NWP, CLM land surface and ParFlow groundwater models). We report results from Springer et al. (J. Hydromet., accept.) on validating the water cycle in COSMO-EU using GRACE and precipitation, evapotranspiration and runoff data; confirming that the model does favorably at representing observations. We show that after GRACE-derived bias correction, basin-average hydrological conditions prior to 2002 can be reconstructed better than before. Next, comparing GRACE with CLM forced by EURO-CORDEX simulations allows identifying processes needing improvement in the model. Finally, we compare COSMO-EU atmospheric pressure, a proxy for mass corrections in satellite gravimetry, with ERA-Interim over Europe at timescales shorter/longer than 1 month, and spatial scales below/above ERA resolution. We find differences between regional and global model more pronounced at high frequencies, with magnitude at sub-grid scale and larger scale corresponding to 1-3 hPa (1-3 cm EWH); relevant for the assessment of post-GRACE concepts.

Order-restricted inference for multivariate longitudinal data with applications to the natural history of hearing loss.

PubMed

Rosen, Sophia; Davidov, Ori

2012-07-20

Multivariate outcomes are often measured longitudinally. For example, in hearing loss studies, hearing thresholds for each subject are measured repeatedly over time at several frequencies. Thus, each patient is associated with a multivariate longitudinal outcome. The multivariate mixed-effects model is a useful tool for the analysis of such data. There are situations in which the parameters of the model are subject to some restrictions or constraints. For example, it is known that hearing thresholds, at every frequency, increase with age. Moreover, this age-related threshold elevation is monotone in frequency, that is, the higher the frequency, the higher, on average, is the rate of threshold elevation. This means that there is a natural ordering among the different frequencies in the rate of hearing loss. In practice, this amounts to imposing a set of constraints on the different frequencies' regression coefficients modeling the mean effect of time and age at entry to the study on hearing thresholds. The aforementioned constraints should be accounted for in the analysis. The result is a multivariate longitudinal model with restricted parameters. We propose estimation and testing procedures for such models. We show that ignoring the constraints may lead to misleading inferences regarding the direction and the magnitude of various effects. Moreover, simulations show that incorporating the constraints substantially improves the mean squared error of the estimates and the power of the tests. We used this methodology to analyze a real hearing loss study. Copyright © 2012 John Wiley & Sons, Ltd.

The Standard Model from LHC to future colliders.

PubMed

Forte, S; Nisati, A; Passarino, G; Tenchini, R; Calame, C M Carloni; Chiesa, M; Cobal, M; Corcella, G; Degrassi, G; Ferrera, G; Magnea, L; Maltoni, F; Montagna, G; Nason, P; Nicrosini, O; Oleari, C; Piccinini, F; Riva, F; Vicini, A

This review summarizes the results of the activities which have taken place in 2014 within the Standard Model Working Group of the "What Next" Workshop organized by INFN, Italy. We present a framework, general questions, and some indications of possible answers on the main issue for Standard Model physics in the LHC era and in view of possible future accelerators.

Restoring natural fire regimes to the Sierra Nevada in an era of global change

Treesearch

Jon E. Keeley; Nathan L. Stephenson

2000-01-01

A conceptual model of fire and forest restoration and maintenance is presented. The process must begin with clearly articulated goals and depends upon derivation of science-driven models that describe the natural or desired conditions. Evaluating the extent to which contemporary landscapes depart from the model is a prerequisite to determining the need for restoration...

The Representation of Extra-tropical Cyclones in Recent Re-Analyses: ERA-Interim, NASA-MERRA, NCEP-CFS and JRA25

NASA Astrophysics Data System (ADS)

Hodges, K.

2010-12-01

Re-analyses are produced using a forecast model, data assimilation system and historical observations. Whilst the observations are common between the re-analyses the way they are assimilated and the forecast model used are often different between the re-analyses which can introduce uncertainty in the representation of particular phenomena between the re-analyses, for example the distribution and properties of weather systems. It is important to inter-compare re-analyses to determine the uncertainty in their representation of the atmosphere, its circulation and weather systems in order to have confidence in their use for studies of the atmosphere and validating climate models. The four recent re-analyses, ERA-Interim, NASA-MERRA, NCEP-CFS and JRA25 are explored and compared for the representation of synoptic scale extra-tropical cyclones. Previous studies of the older re-analyses. ERA40, NCEP-NCAR and DOE has shown that whilst in the NH there was relatively good agreement between the re-analyses in terms of the distribution and properties of extra-tropical cyclones, in the SH there was much larger uncertainty. The newest re-analyses are produced at much higher resolutions than previous re-analyses, in addition more modern data assimilation systems and forecast models have been used. Hence, it would be hoped that the representation of cyclones will be improved to the same extent as that seen in modern NWP systems. This study contrasts extra-tropical cyclones, their distribution and properties, between these new re-analyses and compares them with cyclones in the slightly older though lower resolution JRA25 re-analysis. Results will show that in general in the higher resolution re-analysis more cyclones are identified than in JRA25. In the NH the distribution of storms agrees as well if not better than was the case for the older re-analyses. However, it is in the SH that the largest improvement in agreement is seen for the distribution of storms. For ERA-Interim, NASA-MERRA and NCEP-CFS the agreement in the SH is almost as good as in the NH with the best agreement occurring between ERA-Interim and NCEP-CFS. However, the comparison with JRA25 shows the same level of uncertainty as seen with the older re-analyses. Determining the separation distances of storms using storm matching confirm these results. The biggest differences between the re-analyses occurs for the intensity of storms with the NASA-MERRA having consistently the strongest extreme storms in terms of pressure and winds and JRA25 the weakest, ERA-Interim and NCEP-CFS are very similar in this respect. Using vorticity as an intensity measure shows the greatest sensitivity and goes with resolution. If time permits a comparison of the structure of the storms will also be presented. The approach used only highlights the uncertainty between the re-analyses it does not say which one is right. To try to address this some early results of comparing the re-analyses directly with observations of low level winds from scatterometers in the vicinity of storms will be presented if time permits.

Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

NASA Astrophysics Data System (ADS)

Garrigues, S.; Olioso, A.; Carrer, D.; Decharme, B.; Calvet, J.-C.; Martin, E.; Moulin, S.; Marloie, O.

2015-10-01

Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations. The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m-2) compared to the negative biases found for SAFRAN (-10 W m-2) and the MSG satellite (-12 W m-2). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by -12 and -16 W m-2, respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The simulation of irrigation by the model provides an accurate irrigation amount over the crop cycle but the timing of irrigation occurrences is frequently unrealistic. Errors in the soil hydrodynamic parameters and the lack of irrigation in the simulation have the largest influence on ET compared to uncertainties in the large-scale climate reanalysis and the LAI climatology. Among climate variables, the errors in yearly ET are mainly related to the errors in yearly rainfall. The underestimation of the available water capacity and the soil hydraulic diffusivity induce a large underestimation of ET over 12 years. The underestimation of radiations by the reanalyses and the absence of irrigation in the simulation lead to the underestimation of ET while the overall overestimation of LAI by the ECOCLIMAP-II climatology induces an overestimation of ET over 12 years. This work shows that the key challenges to monitor the water balance of cropland at regional scale concern the representation of the spatial distribution of the soil hydrodynamic parameters, the variability of the irrigation practices, the seasonal and inter-annual dynamics of vegetation and the spatiotemporal heterogeneity of rainfall.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China

PubMed Central

Pei, Ling-Ling; Li, Qin

2018-01-01

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China’s pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N)) model based on the nonlinear least square (NLS) method. The Gauss–Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N) and the NLS-based TNGM (1, N) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO2 and dust, alongside GDP per capita in China during the period 1996–2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N) model presents greater precision when forecasting WDPC, SO2 emissions and dust emissions per capita, compared to the traditional GM (1, N) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO2 and dust reduce accordingly. PMID:29517985

Rework of the ERA software system: ERA-8

NASA Astrophysics Data System (ADS)

Pavlov, D.; Skripnichenko, V.

2015-08-01

The software system that has been powering many products of the IAA during decades has undergone a major rework. ERA has capabilities for: processing tables of observations of different kinds, fitting parameters to observations, integrating equations of motion of the Solar system bodies. ERA comprises a domain-specific language called SLON, tailored for astronomical tasks. SLON provides a convenient syntax for reductions of observations, choosing of IAU standards to use, applying rules for filtering observations or selecting parameters for fitting. Also, ERA includes a table editor and a graph plotter. ERA-8 has a number of improvements over previous versions such as: integration of the Solar system and TT xA1 TDB with arbitrary number of asteroids; option to use different ephemeris (including DE and INPOP); integrator with 80-bit floating point. The code of ERA-8 has been completely rewritten from Pascal to C (for numerical computations) and Racket (for running SLON programs and managing data). ERA-8 is portable across major operating systems. The format of tables in ERA-8 is based on SQLite. The SPICE format has been chosen as the main format for ephemeris in ERA-8.

Optimal weighted averaging of event related activity from acquisitions with artifacts.

PubMed

Vollero, Luca; Petrichella, Sara; Innello, Giulio

2016-08-01

In several biomedical applications that require the signal processing of biological data, the starting procedure for noise reduction is the ensemble averaging of multiple repeated acquisitions (trials). This method is based on the assumption that each trial is composed of two additive components: (i) a time-locked activity related to some sensitive/stimulation phenomenon (ERA, Event Related Activity in the following) and (ii) a sum of several other non time-locked background activities. The averaging aims at estimating the ERA activity under very low Signal to Noise and Interference Ratio (SNIR). Although averaging is a well established tool, its performance can be improved in the presence of high-power disturbances (artifacts) by a trials classification and removal stage. In this paper we propose, model and evaluate a new approach that avoids trials removal, managing trials classified as artifact-free and artifact-prone with two different weights. Based on the model, a weights tuning is possible and through modeling and simulations we show that, when optimally configured, the proposed solution outperforms classical approaches.

Northern Hemisphere climate trends in reanalysis and forecast model predictions: The 500 hPa annual means

NASA Astrophysics Data System (ADS)

Bordi, I.; Fraedrich, K.; Sutera, A.

2010-06-01

The lead time dependent climates of the ECMWF weather prediction model, initialized with ERA-40 reanalysis, are analysed using 44 years of day-1 to day-10 forecasts of the northern hemispheric 500-hPa geopotential height fields. The study addresses the question whether short-term tendencies have an impact on long-term trends. Comparing climate trends of ERA-40 with those of the forecasts, it seems that the forecast model rapidly loses the memory of initial conditions creating its own climate. All forecast trends show a high degree of consistency. Comparison results suggest that: (i) Only centers characterized by an upward trend are statistical significant when increasing the lead time. (ii) In midilatitudes an upward trend larger than the one observed in the reanalysis characterizes the forecasts, while in the tropics there is a good agreement. (iii) The downward trend in reanalysis at high latitudes characterizes also the day-1 forecast which, however, increasing lead time approaches zero.

The Era GTPase recognizes the GAUCACCUCC sequence and binds helix 45 near the 3; end of 16S rRNA

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

Tu, Chao; Zhou, Xiaomei; Tarasov, Sergey G.

2012-03-26

Era, composed of a GTPase domain and a K homology domain, is essential for bacterial cell viability. It is required for the maturation of 16S rRNA and assembly of the 30S ribosomal subunit. We showed previously that the protein recognizes nine nucleotides (1531{sup AUCACCUCC}1539) near the 3{prime} end of 16S rRNA, and that this recognition stimulates GTP-hydrolyzing activity of Era. In all three kingdoms of life, the 1530{sup GAUCA}1534 sequence and helix 45 (h45) (nucleotides 1506-1529) are highly conserved. It has been shown that the 1530{sup GA}1531 to 1530{sup AG}1531 double mutation severely affects the viability of bacteria. However, whethermore » Era interacts with G1530 and/or h45 and whether such interactions (if any) contribute to the stimulation of Era's GTPase activity were not known. Here, we report two RNA structures that contain nucleotides 1506-1542 (RNA301), one in complex with Era and GDPNP (GNP), a nonhydrolysable GTP-analogue, and the other in complex with Era, GNP, and the KsgA methyltransferase. The structures show that Era recognizes 10 nucleotides, including G1530, and that Era also binds h45. Moreover, GTPase assay experiments show that G1530 does not stimulate Era's GTPase activity. Rather, A1531 and A1534 are most important for stimulation and h45 further contributes to the stimulation. Although G1530 does not contribute to the intrinsic GTPase activity of Era, its interaction with Era is important for binding and is essential for the protein to function, leading to the discovery of a new cold-sensitive phenotype of Era.« less

Space-time variation of respiratory cancers in South Carolina: a flexible multivariate mixture modeling approach to risk estimation.

PubMed

Carroll, Rachel; Lawson, Andrew B; Kirby, Russell S; Faes, Christel; Aregay, Mehreteab; Watjou, Kevin

2017-01-01

Many types of cancer have an underlying spatiotemporal distribution. Spatiotemporal mixture modeling can offer a flexible approach to risk estimation via the inclusion of latent variables. In this article, we examine the application and benefits of using four different spatiotemporal mixture modeling methods in the modeling of cancer of the lung and bronchus as well as "other" respiratory cancer incidences in the state of South Carolina. Of the methods tested, no single method outperforms the other methods; which method is best depends on the cancer under consideration. The lung and bronchus cancer incidence outcome is best described by the univariate modeling formulation, whereas the "other" respiratory cancer incidence outcome is best described by the multivariate modeling formulation. Spatiotemporal multivariate mixture methods can aid in the modeling of cancers with small and sparse incidences when including information from a related, more common type of cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Multivariate Time Series Decomposition into Oscillation Components.

PubMed

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

Alcohol use and selected health conditions of 1991 Gulf War veterans: survey results, 2003-2005.

PubMed

Coughlin, Steven S; Kang, Han K; Mahan, Clare M

2011-05-01

A sizable literature has analyzed the frequency of alcohol consumption and patterns of drinking among veterans. However, few studies have examined patterns of alcohol use in veterans of the first Gulf War or factors associated with problem drinking in this population. We examined the frequency and patterns of alcohol use in male and female veterans who served in the 1991 Gulf War or during the same era and the relationships between alcohol use and selected health conditions. We analyzed data from a follow-up survey of health information among population-based samples of 15,000 Gulf War and 15,000 Gulf Era veterans. Data had been collected from 9,970 respondents during 2003 through 2005 via a structured questionnaire or telephone survey. Posttraumatic stress disorder (PTSD), major depressive disorder (MDD), unexplained multisymptom illness (MSI), and chronic fatigue syndrome (CFS)-like illness were more frequent among veterans with problem drinking than those without problem drinking. Approximately 28% of Gulf War veterans with problem drinking had PTSD compared with 13% of Gulf War veterans without problem drinking. In multivariate analysis, problem drinking was positively associated with PTSD, MDD, unexplained MSI, and CFS-like illness after adjustment for age, sex, race/ethnicity, branch of service, rank, and Gulf status. Veterans who were problem drinkers were 2.7 times as likely to have PTSD as veterans who were not problem drinkers. These findings indicate that access to evidence-based treatment programs and systems of care should be provided for veterans who abuse alcohol and who have PTSD and other war-related health conditions and illnesses.

Nutritional status in the era of target therapy: poor nutrition is a prognostic factor in non-small cell lung cancer with activating epidermal growth factor receptor mutations.

PubMed

Park, Sehhoon; Park, Seongyeol; Lee, Se-Hoon; Suh, Beomseok; Keam, Bhumsuk; Kim, Tae Min; Kim, Dong-Wan; Kim, Young Whan; Heo, Dae Seog

2016-11-01

Pretreatment nutritional status is an important prognostic factor in patients treated with conventional cytotoxic chemotherapy. In the era of target therapies, its value is overlooked and has not been investigated. The aim of our study is to evaluate the value of nutritional status in targeted therapy. A total of 2012 patients with non-small cell lung cancer (NSCLC) were reviewed and 630 patients with activating epidermal growth factor receptor (EGFR) mutation treated with EGFR tyrosine kinase inhibitor (TKI) were enrolled for the final analysis. Anemia, body mass index (BMI), and prognostic nutritional index (PNI) were considered as nutritional factors. Hazard ratio (HR), progression-free survival (PFS) and overall survival (OS) for each group were calculated by Cox proportional analysis. In addition, scores were applied for each category and the sum of scores was used for survival analysis. In univariable analysis, anemia (HR, 1.29; p = 0.015), BMI lower than 18.5 (HR, 1.98; p = 0.002), and PNI lower than 45 (HR, 1.57; p < 0.001) were poor prognostic factors for PFS. Among them, BMI and PNI were independent in multi-variable analysis. All of these were also significant prognostic values for OS. The higher the sum of scores, the poorer PFS and OS were observed. Pretreatment nutritional status is a prognostic marker in NSCLC patients treated with EGFR TKI. Hence, baseline nutritional status should be more carefully evaluated and adequate nutrition should be supplied to these patients.

Factors associated with mumps meningitis and the possible impact of vaccination

PubMed Central

Rhie, Kyuyol; Park, Heung-Keun; Kim, Young-Soo; Park, Ji Sook; Seo, Ji-Hyun; Park, Eun Sil; Lim, Jae-Young; Park, Chan-Hoo; Woo, Hyang-Ok; Youn, Hee-Shang

2016-01-01

Purpose Mumps meningitis is a common complication of mumps infection; however, information on mumps meningitis in the postvaccine era is limited. The purpose of the present study was to determine factors associated with mumps meningitis and to discuss the effect of vaccination on this disease. Methods We retrospectively reviewed patients younger than 19 years with mumps, diagnosed at a university hospital in Korea between 2003 and 2013. Patients were divided into groups with and without meningitis, and the clinical features of the 2 groups were compared. Results The study enrolled 119 patients: 19 patients with meningitis and 100 patients without. Univariate analysis showed that older age (median: 15 years vs. 9.5 years, respectively), a longer interval from last vaccination (median: 10.2 years vs. 4.8 years, respectively), and febrile presentation (94.7% vs. 31.0%, respectively) were significantly associated with mumps meningitis. Sex, number of vaccination doses, bilateral parotitis, and the presence of complications other than meningitis did not differ between the 2 groups. In multivariate logistic regression analysis, age (odds ratio, 1.38; 95% confidence interval, 1.01–1.89; P=0.04) and fever (odds ratio, 30.46; 95% confidence interval, 3.27–283.61; P<0.01) remained independent factors for mumps meningitis. Conclusion Clinicians in the postvaccine era should be aware of the possibility of mumps meningitis in febrile cases of mumps in adolescents, regardless of the number of vaccination doses. To establish the role of vaccination in mumps meningitis, further studies will be necessary. PMID:26893600

Effects of social support and resilient coping on violent behavior in military veterans.

PubMed

Van Voorhees, Elizabeth E; Wagner, H Ryan; Beckham, Jean C; Bradford, Daniel W; Neal, Lydia C; Penk, Walter E; Elbogen, Eric B

2018-05-01

Violence toward others has been identified as a serious postdeployment adjustment problem in a subset of Iraq- and Afghanistan-era veterans. In the current study, we examined the intricate links between posttraumatic stress disorder (PTSD), commonly cited psychosocial risk and protective factors, and violent behavior using a national randomly selected longitudinal sample of Iraq- and Afghanistan-era United States veterans. A total of 1,090 veterans from the 50 United States and all United States military branches completed 2 waves of self-report survey-data collection 1 year apart (retention rate = 79%). History of severe violent behavior at Wave 1 was the most substantial predictor of subsequent violence. In bivariate analyses, high correlations were observed among risk and protective factors, and between risk and protective factors and severe violence at both time points. In multivariate analyses, baseline violence (OR = 12.43, p < .001), baseline alcohol misuse (OR = 1.06, p < .05), increases in PTSD symptoms between Waves 1 and 2 (OR = 1.01, p < .05), and decreases in social support between Waves 1 and 2 (OR = .83, p < .05) were associated with increased risk for violence at Wave 2. Our findings suggest that rather than focusing specifically on PTSD symptoms, alcohol use, resilience, or social support in isolation, it may be more useful to consider how these risk and protective factors work in combination to convey how military personnel and veterans are managing the transition from wartime military service to civilian life, and at what point it might be most effective to intervene. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Mechanistic Basis Of Calmodulin Mediated Estrogen Receptor Alpha Activation and Antiestrogen Resistance

DTIC Science & Technology

2010-06-01

for solubility (Figure 5). We call this protein Trx -ERA241-320. We also produced a similar protein construct, but with only residues 241-273 of...ERa, as a “control” (Figure 5). We call this protein Trx -ERA241-273. Because CaM binds tightly to the N-terminal extended ligand binding domain of...ERa (residues 286- 552, see above), we hypothesized that Trx - ERA241-320 would bind tightly to CaM, but that Trx -ERA241-273 would not. The genetic

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

Eigensystem realization algorithm user's guide forVAX/VMS computers: Version 931216

NASA Technical Reports Server (NTRS)

Pappa, Richard S.

1994-01-01

The eigensystem realization algorithm (ERA) is a multiple-input, multiple-output, time domain technique for structural modal identification and minimum-order system realization. Modal identification is the process of calculating structural eigenvalues and eigenvectors (natural vibration frequencies, damping, mode shapes, and modal masses) from experimental data. System realization is the process of constructing state-space dynamic models for modern control design. This user's guide documents VAX/VMS-based FORTRAN software developed by the author since 1984 in conjunction with many applications. It consists of a main ERA program and 66 pre- and post-processors. The software provides complete modal identification capabilities and most system realization capabilities.

A simple cosmology with a varying fine structure constant.

PubMed

Sandvik, Håvard Bunes; Barrow, John D; Magueijo, João

2002-01-21

We investigate the cosmological consequences of a theory in which the electric charge e can vary. In this theory the fine structure "constant," alpha, remains almost constant in the radiation era, undergoes a small increase in the matter era, but approaches a constant value when the universe starts accelerating because of a positive cosmological constant. This model satisfies geonuclear, nucleosynthesis, and cosmic microwave background constraints on time variation in alpha, while fitting the observed accelerating Universe and evidence for small alpha variations in quasar spectra. It also places specific restrictions on the nature of the dark matter. Further tests, involving stellar spectra and Eötvös experiments, are proposed.

The evolution of personalized cancer genetic counseling in the era of personalized medicine.

PubMed

Vig, Hetal S; Wang, Catharine

2012-09-01

Practice changes in cancer genetic counseling have occurred to meet the demand for cancer genetic services. As cancer genetics continues to impact not only prevention strategies but also treatment decisions, current cancer genetic counseling models will need to be tailored to accommodate emerging clinical indications. These clinical indications include: surgical prophylactic bilateral mastectomy candidates, PARP-inhibitor candidates, patients with abnormal tumor screening results for Lynch syndrome, and post-test counseling patients (after genetic testing is ordered by another healthcare provider). A more personalized, multidisciplinary approach to selecting the best framework, for a given clinical indication, may become increasingly necessary in this era of personalized medicine.

Changes of Earthquake Vulnerability of Marunouchi and Ginza Area in Tokyo and Urban Recovery Digital Archives on Google Earth

NASA Astrophysics Data System (ADS)

Igarashi, Masayasu; Murao, Osamu

In this paper, the authors develop a multiple regression model which estimates urban earthquake vulnerability (building collapse risk and conflagration risk) for different eras, and clarify the historical changes of urban risk in Marunouchi and Ginza Districts in Tokyo, Japan using old maps and contemporary geographic information data. Also, we compare the change of urban vulnerability of the districts with the significant historical events in Tokyo. Finally, the results are loaded onto Google Earth with timescale extension to consider the possibility of urban recovery digital archives in the era of the recent geoinformatic technologies.

Design and validation of MEDRYS, a Mediterranean Sea reanalysis over the period 1992-2013

NASA Astrophysics Data System (ADS)

Hamon, Mathieu; Beuvier, Jonathan; Somot, Samuel; Lellouche, Jean-Michel; Greiner, Eric; Jordà, Gabriel; Bouin, Marie-Noëlle; Arsouze, Thomas; Béranger, Karine; Sevault, Florence; Dubois, Clotilde; Drevillon, Marie; Drillet, Yann

2016-04-01

The French research community in the Mediterranean Sea modeling and the French operational ocean forecasting center Mercator Océan have gathered their skill and expertise in physical oceanography, ocean modeling, atmospheric forcings and data assimilation to carry out a MEDiterranean sea ReanalYsiS (MEDRYS) at high resolution for the period 1992-2013. The ocean model used is NEMOMED12, a Mediterranean configuration of NEMO with a 1/12° ( ˜ 7 km) horizontal resolution and 75 vertical z levels with partial steps. At the surface, it is forced by a new atmospheric-forcing data set (ALDERA), coming from a dynamical downscaling of the ERA-Interim atmospheric reanalysis by the regional climate model ALADIN-Climate with a 12 km horizontal and 3 h temporal resolutions. This configuration is used to carry a 34-year hindcast simulation over the period 1979-2013 (NM12-FREE), which is the initial state of the reanalysis in October 1992. MEDRYS uses the existing Mercator Océan data assimilation system SAM2 that is based on a reduced-order Kalman filter with a three-dimensional (3-D) multivariate modal decomposition of the forecast error. Altimeter data, satellite sea surface temperature (SST) and temperature and salinity vertical profiles are jointly assimilated. This paper describes the configuration we used to perform MEDRYS. We then validate the skills of the data assimilation system. It is shown that the data assimilation restores a good average temperature and salinity at intermediate layers compared to the hindcast. No particular biases are identified in the bottom layers. However, the reanalysis shows slight positive biases of 0.02 psu and 0.15 °C above 150 m depth. In the validation stage, it is also shown that the assimilation allows one to better reproduce water, heat and salt transports through the Strait of Gibraltar. Finally, the ability of the reanalysis to represent the sea surface high-frequency variability is shown.