Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

Linear summation of outputs in a balanced network model of motor cortex.

PubMed

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis.

Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

PubMed Central

Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

2015-01-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication

DOE PAGES

Azad, Ariful; Ballard, Grey; Buluc, Aydin; ...

2016-11-08

Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performance graph algorithms as well as for some linear solvers, such as algebraic multigrid. The scaling of existing parallel implementations of SpGEMM is heavily bound by communication. Even though 3D (or 2.5D) algorithms have been proposed and theoretically analyzed in the flat MPI model on Erdös-Rényi matrices, those algorithms had not been implemented in practice and their complexities had not been analyzed for the general case. In this work, we present the first implementation of the 3D SpGEMM formulation that exploits multiple (intranode and internode) levels of parallelism, achievingmore » significant speedups over the state-of-the-art publicly available codes at all levels of concurrencies. We extensively evaluate our implementation and identify bottlenecks that should be subject to further research.« less

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

On the Convenience of Using the Complete Linearization Method in Modelling the BLR of AGN

NASA Astrophysics Data System (ADS)

Patriarchi, P.; Perinotto, M.

The Complete Linearization Method (Mihalas, 1978) consists in the determination of the radiation field (at a set of frequency points), atomic level populations, temperature, electron density etc., by resolving the system of radiative transfer, thermal equilibrium, statistical equilibrium equations simultaneously and self-consistently. Since the system is not linear, it must be solved by iteration after linearization, using a perturbative method, starting from an initial guess solution. Of course the Complete Linearization Method is more time consuming than the previous one. But how great can this disadvantage be in the age of supercomputers? It is possible to approximately evaluate the CPU time needed to run a model by computing the number of multiplications necessary to solve the system.

Non-linear relationship of cell hit and transformation probabilities in a low dose of inhaled radon progenies.

PubMed

Balásházy, Imre; Farkas, Arpád; Madas, Balázs Gergely; Hofmann, Werner

2009-06-01

Cellular hit probabilities of alpha particles emitted by inhaled radon progenies in sensitive bronchial epithelial cell nuclei were simulated at low exposure levels to obtain useful data for the rejection or support of the linear-non-threshold (LNT) hypothesis. In this study, local distributions of deposited inhaled radon progenies in airway bifurcation models were computed at exposure conditions characteristic of homes and uranium mines. Then, maximum local deposition enhancement factors at bronchial airway bifurcations, expressed as the ratio of local to average deposition densities, were determined to characterise the inhomogeneity of deposition and to elucidate their effect on resulting hit probabilities. The results obtained suggest that in the vicinity of the carinal regions of the central airways the probability of multiple hits can be quite high, even at low average doses. Assuming a uniform distribution of activity there are practically no multiple hits and the hit probability as a function of dose exhibits a linear shape in the low dose range. The results are quite the opposite in the case of hot spots revealed by realistic deposition calculations, where practically all cells receive multiple hits and the hit probability as a function of dose is non-linear in the average dose range of 10-100 mGy.

Controller design for a class of nonlinear MIMO coupled system using multiple models and second level adaptation.

PubMed

Pandey, Vinay Kumar; Kar, Indrani; Mahanta, Chitralekha

2017-07-01

In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems. Multiple estimation models are used to tune the unknown parameters at the first level. The second level adaptation provides a single parameter vector for the controller. A feedback linearization technique is used to design a state feedback control. The efficacy of the designed controller is validated by conducting real time experiment on a laboratory setup of twin rotor MIMO system (TRMS). The TRMS setup is discussed in detail and the experiments were performed for regulation and tracking problem for pitch and yaw control using different reference signals. An Extended Kalman Filter (EKF) has been used to observe the unavailable states of the TRMS. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Fast, Low-Power, Hysteretic Level-Detector Circuit

NASA Technical Reports Server (NTRS)

Arditti, Mordechai

1993-01-01

Circuit for detection of preset levels of voltage or current intended to replace standard fast voltage comparator. Hysteretic analog/digital level detector operates at unusually low power with little sacrifice of speed. Comprises low-power analog circuit and complementary metal oxide/semiconductor (CMOS) digital circuit connected in overall closed feedback loop to decrease rise and fall times, provide hysteresis, and trip-level control. Contains multiple subloops combining linear and digital feedback. Levels of sensed signals and hysteresis level easily adjusted by selection of components to suit specific application.

FAST TRACK PAPER: Non-iterative multiple-attenuation methods: linear inverse solutions to non-linear inverse problems - II. BMG approximation

NASA Astrophysics Data System (ADS)

Ikelle, Luc T.; Osen, Are; Amundsen, Lasse; Shen, Yunqing

2004-12-01

The classical linear solutions to the problem of multiple attenuation, like predictive deconvolution, τ-p filtering, or F-K filtering, are generally fast, stable, and robust compared to non-linear solutions, which are generally either iterative or in the form of a series with an infinite number of terms. These qualities have made the linear solutions more attractive to seismic data-processing practitioners. However, most linear solutions, including predictive deconvolution or F-K filtering, contain severe assumptions about the model of the subsurface and the class of free-surface multiples they can attenuate. These assumptions limit their usefulness. In a recent paper, we described an exception to this assertion for OBS data. We showed in that paper that a linear and non-iterative solution to the problem of attenuating free-surface multiples which is as accurate as iterative non-linear solutions can be constructed for OBS data. We here present a similar linear and non-iterative solution for attenuating free-surface multiples in towed-streamer data. For most practical purposes, this linear solution is as accurate as the non-linear ones.

Linear summation of outputs in a balanced network model of motor cortex

PubMed Central

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis. PMID:26097452

Level-Set Topology Optimization with Aeroelastic Constraints

NASA Technical Reports Server (NTRS)

Dunning, Peter D.; Stanford, Bret K.; Kim, H. Alicia

2015-01-01

Level-set topology optimization is used to design a wing considering skin buckling under static aeroelastic trim loading, as well as dynamic aeroelastic stability (flutter). The level-set function is defined over the entire 3D volume of a transport aircraft wing box. Therefore, the approach is not limited by any predefined structure and can explore novel configurations. The Sequential Linear Programming (SLP) level-set method is used to solve the constrained optimization problems. The proposed method is demonstrated using three problems with mass, linear buckling and flutter objective and/or constraints. A constraint aggregation method is used to handle multiple buckling constraints in the wing skins. A continuous flutter constraint formulation is used to handle difficulties arising from discontinuities in the design space caused by a switching of the critical flutter mode.

Integration of Attributes from Non-Linear Characterization of Cardiovascular Time-Series for Prediction of Defibrillation Outcomes

PubMed Central

Shandilya, Sharad; Kurz, Michael C.; Ward, Kevin R.; Najarian, Kayvan

2016-01-01

Objective The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR), rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA) patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals. Materials and Methods Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF) was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI) model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA) technique. Results 358 defibrillations were evaluated (218 unsuccessful and 140 successful). Non-linear properties (Lyapunov exponent > 0) of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity) outperformed AMSA (53.6% sensitivity). At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity. Conclusion At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations. Addition of partial end-tidal carbon dioxide (PetCO2) signal improves accuracy and sensitivity of the MDI prediction model. PMID:26741805

Empirical Modeling of Microbial Indicators at a South Carolina Beach

EPA Science Inventory

Public concerns about water quality at beaches have prompted the development of multiple linear regression and other models that can be used to "nowcast" levels of bacterial indicators. Hydrometeorological and biogeochemical data from summer, 2009 were used to develop empirical m...

Mathematics Readiness of First-Year University Students

ERIC Educational Resources Information Center

Atuahene, Francis; Russell, Tammy A.

2016-01-01

The majority of high school students, particularly underrepresented minorities (URMs) from low socioeconomic backgrounds are graduating from high school less prepared academically for advanced-level college mathematics. Using 2009 and 2010 course enrollment data, several statistical analyses (multiple linear regression, Cochran Mantel Haenszel…

Associations of blood lead, cadmium, and mercury with estimated glomerular filtration rate in the Korean general population: Analysis of 2008-2010 Korean National Health and Nutrition Examination Survey data

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

Kim, Yangho; Lee, Byung-Kook, E-mail: bklee@sch.ac.kr

Introduction: The objective of this study was to evaluate associations between blood lead, cadmium, and mercury levels with estimated glomerular filtration rate in a general population of South Korean adults. Methods: This was a cross-sectional study based on data obtained in the Korean National Health and Nutrition Examination Survey (KNHANES) (2008-2010). The final analytical sample consisted of 5924 participants. Estimated glomerular filtration rate (eGFR) was calculated using the MDRD Study equation as an indicator of glomerular function. Results: In multiple linear regression analysis of log2-transformed blood lead as a continuous variable on eGFR, after adjusting for covariates including cadmium andmore » mercury, the difference in eGFR levels associated with doubling of blood lead were -2.624 mL/min per 1.73 m Superscript-Two (95% CI: -3.803 to -1.445). In multiple linear regression analysis using quartiles of blood lead as the independent variable, the difference in eGFR levels comparing participants in the highest versus the lowest quartiles of blood lead was -3.835 mL/min per 1.73 m Superscript-Two (95% CI: -5.730 to -1.939). In a multiple linear regression analysis using blood cadmium and mercury, as continuous or categorical variables, as independent variables, neither metal was a significant predictor of eGFR. Odds ratios (ORs) and 95% CI values for reduced eGFR calculated for log2-transformed blood metals and quartiles of the three metals showed similar trends after adjustment for covariates. Discussion: In this large, representative sample of South Korean adults, elevated blood lead level was consistently associated with lower eGFR levels and with the prevalence of reduced eGFR even in blood lead levels below 10 {mu}g/dL. In conclusion, elevated blood lead level was associated with lower eGFR in a Korean general population, supporting the role of lead as a risk factor for chronic kidney disease.« less

Trends in Physical Medicine and Rehabilitation Publications Over the Past 16 Years.

PubMed

Mimouni, Michael; Cismariu-Potash, Keren; Ratmansky, Motti; Shaklai, Sharon; Amir, Hagay; Mimouni-Bloch, Aviva

2016-06-01

To test the hypothesis that the number of publications in the field of physical medicine and rehabilitation (PMR) has increased over the last 16 years in a linear fashion, and to compare the trends in publication between the pediatric and adult literature. We evaluated all MEDLINE articles from January 1, 1998, to December 31, 2013, using Medical Subject Headings categories of rehabilitation. An age filter separated adult and pediatric articles. We divided articles into those with a low level of scientific evidence such as letters and editorials, and those with a high level of evidence such as controlled trials and meta-analyses. We used regression analysis to evaluate the effect of the year of publication on the number of publications of each type. Not applicable. Not applicable. Not applicable. Not applicable. MEDLINE reported a total of 98,501 adult publications and 30,895 pediatric publications during the evaluated period. There was a significant linear increase in the total number of publications in adult and pediatric rehabilitation publications with multiplication factors of 3.3 and 2.9, respectively. Importantly, publications with a high level of evidence showed larger multiplication factors compared with those with a low level of evidence (5.5 and 5.1 vs 2.1 and 2.0) for the adult and pediatric literature. The number of publications in the PMR field, especially those with a high level of scientific evidence, has increased linearly over the years, reflecting the rapid evolution of both adult and pediatric PMR. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Evaluation of accuracy of complete-arch multiple-unit abutment-level dental implant impressions using different impression and splinting materials.

PubMed

Buzayan, Muaiyed; Baig, Mirza Rustum; Yunus, Norsiah

2013-01-01

This in vitro study evaluated the accuracy of multiple-unit dental implant casts obtained from splinted or nonsplinted direct impression techniques using various splinting materials by comparing the casts to the reference models. The effect of two different impression materials on the accuracy of the implant casts was also evaluated for abutment-level impressions. A reference model with six internal-connection implant replicas placed in the completely edentulous mandibular arch and connected to multi-base abutments was fabricated from heat-curing acrylic resin. Forty impressions of the reference model were made, 20 each with polyether (PE) and polyvinylsiloxane (PVS) impression materials using the open tray technique. The PE and PVS groups were further subdivided into four subgroups of five each on the bases of splinting type: no splinting, bite registration PE, bite registration addition silicone, or autopolymerizing acrylic resin. The positional accuracy of the implant replica heads was measured on the poured casts using a coordinate measuring machine to assess linear differences in interimplant distances in all three axes. The collected data (linear and three-dimensional [3D] displacement values) were compared with the measurements calculated on the reference resin model and analyzed with nonparametric tests (Kruskal-Wallis and Mann-Whitney). No significant differences were found between the various splinting groups for both PE and PVS impression materials in terms of linear and 3D distortions. However, small but significant differences were found between the two impression materials (PVS, 91 μm; PE, 103 μm) in terms of 3D discrepancies, irrespective of the splinting technique employed. Casts obtained from both impression materials exhibited differences from the reference model. The impression material influenced impression inaccuracy more than the splinting material for multiple-unit abutment-level impressions.

Children's environmental chemical exposures in the USA, NHANES 2003-2012.

PubMed

Hendryx, Michael; Luo, Juhua

2018-02-01

Children are vulnerable to environmental chemical exposures, but little is known about the extent of multiple chemical exposures among children. We analyzed biomonitoring data from five cycles (2003-2012) of the National Health and Nutrition Examination Survey (NHANES) to describe multiple chemical exposures in US children, examine levels of chemical concentrations present over time, and examine differences in chemical exposures by selected demographic groups. We analyzed data for 36 chemical analytes across five chemical classes in a sample of 4299 children aged 6-18. Classes included metals, pesticides, phthalates, phenols, and polycyclic aromatic hydrocarbons. We calculated the number and percent of chemicals detected and tested for secular trends over time in chemical concentrations. We compared log concentrations among groups defined by age, sex, race/ethnicity, and poverty using multiple linear regression models and report adjusted geometric means. Among a smaller subgroup of 733 children with data across chemical classes, we calculated the linear correlations within and between classes and conducted a principal component analysis. The percentage of children with detectable concentrations of an individual chemical ranged from 26 to 100%; the average was 93%, and 29 of 36 were detected in more than 90% of children. Concentrations of most tested chemicals were either unchanged or declined from earlier to more recent years. Many differences in concentrations were present by age, sex, poverty, and race/ethnicity categories. Within and between class correlations were all significant and positive, and the principal component analysis suggested a one factor solution, indicating that children exposed to higher levels of one chemical were exposed to higher levels of other chemicals. In conclusion, children in the USA are exposed to multiple simultaneous chemicals at uneven risk across socioeconomic and demographic groups. Further efforts to understand the effects of multiple exposures on child health and development are warranted.

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Parts-Per-Billion Mass Measurement Accuracy Achieved through the Combination of Multiple Linear Regression and Automatic Gain Control in a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

PubMed Central

Williams, D. Keith; Muddiman, David C.

2008-01-01

Fourier transform ion cyclotron resonance mass spectrometry has the ability to achieve unprecedented mass measurement accuracy (MMA); MMA is one of the most significant attributes of mass spectrometric measurements as it affords extraordinary molecular specificity. However, due to space-charge effects, the achievable MMA significantly depends on the total number of ions trapped in the ICR cell for a particular measurement. Even through the use of automatic gain control (AGC), the total ion population is not constant between spectra. Multiple linear regression calibration in conjunction with AGC is utilized in these experiments to formally account for the differences in total ion population in the ICR cell between the external calibration spectra and experimental spectra. This ability allows for the extension of dynamic range of the instrument while allowing mean MMA values to remain less than 1 ppm. In addition, multiple linear regression calibration is used to account for both differences in total ion population in the ICR cell as well as relative ion abundance of a given species, which also affords mean MMA values at the parts-per-billion level. PMID:17539605

An efficient method for generalized linear multiplicative programming problem with multiplicative constraints.

PubMed

Zhao, Yingfeng; Liu, Sanyang

2016-01-01

We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.

Longitudinal performance of plasma neurofilament light and tau in professional fighters: The Professional Fighters Brain Health Study.

PubMed

Bernick, Charles; Zetterberg, Henrik; Shan, Guogen; Banks, Sarah; Blennow, Kaj

2018-04-02

The objective of this study is to evaluate longitudinal change in plasma neurofilament light (NF-L) and tau levels in relationship to clinical and radiological measures in professional fighters. Participants (active and retired professional fighters and control group) underwent annual blood sampling, 3 Tesla MRI brain imaging, computerized cognitive testing, and assessment of exposure to head trauma. Plasma tau and NF-L concentrations were measured using Simoa assays. Multiple linear regression models were used to compare the difference across groups in regard to baseline measurements, while mixed linear models was used for the longitudinal data with multiple measurements for each participant. Plasma samples were available on 471 participants. Baseline NF-L measures differed across groups (F_3,393=6.99, p=0.0001), with the active boxers having the highest levels. Higher NF-L levels at baseline were correlated with lower baseline MRI regional volumes and lower cognitive scores. The number of sparring rounds completed by the active fighters was correlated with NF-L (95% CI 0.0116-0.4053, p=0.0381), but not tau, levels. Among 126 subjects having multiple yearly samples, there was a significant difference in average yearly percentage change in tau across groups (F_3,83=3.87, p=0.0121).). We conclude that plasma NF-L and tau behave differently in a group of active and retired fighters; NF-L better reflects acute exposure whereas the role of plasma tau levels in signifying chronic change in brain structure over time requires further study.

Separation of detector non-linearity issues and multiple ionization satellites in alpha-particle PIXE

NASA Astrophysics Data System (ADS)

Campbell, John L.; Ganly, Brianna; Heirwegh, Christopher M.; Maxwell, John A.

2018-01-01

Multiple ionization satellites are prominent features in X-ray spectra induced by MeV energy alpha particles. It follows that the accuracy of PIXE analysis using alpha particles can be improved if these features are explicitly incorporated in the peak model description when fitting the spectra with GUPIX or other codes for least-squares fitting PIXE spectra and extracting element concentrations. A method for this incorporation is described and is tested using spectra recorded on Mars by the Curiosity rover's alpha particle X-ray spectrometer. These spectra are induced by both PIXE and X-ray fluorescence, resulting in a spectral energy range from ∼1 to ∼25 keV. This range is valuable in determining the energy-channel calibration, which departs from linearity at low X-ray energies. It makes it possible to separate the effects of the satellites from an instrumental non-linearity component. The quality of least-squares spectrum fits is significantly improved, raising the level of confidence in analytical results from alpha-induced PIXE.

Serum 25-hydroxyvitamin D level is associated with myopia in the Korea national health and nutrition examination survey.

PubMed

Kwon, Jin-Woo; Choi, Jin A; La, Tae Yoon

2016-11-01

The aim of this article was to assess the associations of serum 25-hydroxyvitamin D [25(OH)D] and daily sun exposure time with myopia in Korean adults.This study is based on the Korea National Health and Nutrition Examination Survey (KNHANES) of Korean adults in 2010-2012; multiple logistic regression analyses were performed to examine the associations of serum 25(OH)D levels and daily sun exposure time with myopia, defined as spherical equivalent ≤-0.5D, after adjustment for age, sex, household income, body mass index (BMI), exercise, intraocular pressure (IOP), and education level. Also, multiple linear regression analyses were performed to examine the relationship between serum 25(OH)D levels with spherical equivalent after adjustment for daily sun exposure time in addition to the confounding factors above.Between the nonmyopic and myopic groups, spherical equivalent, age, IOP, BMI, waist circumference, education level, household income, and area of residence differed significantly (all P < 0.05). Compared with subjects with daily sun exposure time <2 hour, subjects with sun exposure time ≥2 to <5 hour, and those with sun exposure time ≥5 hour had significantly less myopia (P < 0.001). In addition, compared with subjects were categorized into quartiles of serum 25(OH)D, the higher quartiles had gradually lower prevalences of myopia after adjustment for confounding factors (P < 0.001). In multiple linear regression analyses, spherical equivalent was significantly associated with serum 25(OH)D concentration after adjustment for confounding factors (P = 0.002).Low serum 25(OH)D levels and shorter daily sun exposure time may be independently associated with a high prevalence of myopia in Korean adults. These data suggest a direct role for vitamin D in the development of myopia.

Fasting insulin levels and metabolic risk factors in type 2 diabetic patients at the first visit in Japan: a 10-year, nationwide, observational study (JDDM 28).

PubMed

Matsuba, Ikuro; Saito, Kazumi; Takai, Masahiko; Hirao, Koichi; Sone, Hirohito

2012-09-01

To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs.

Fasting Insulin Levels and Metabolic Risk Factors in Type 2 Diabetic Patients at the First Visit in Japan

PubMed Central

Matsuba, Ikuro; Saito, Kazumi; Takai, Masahiko; Hirao, Koichi; Sone, Hirohito

2012-01-01

OBJECTIVE To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. RESEARCH DESIGN AND METHODS In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. RESULTS Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. CONCLUSIONS During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs. PMID:22665215

The Elementary Operations of Human Vision Are Not Reducible to Template-Matching

PubMed Central

Neri, Peter

2015-01-01

It is generally acknowledged that biological vision presents nonlinear characteristics, yet linear filtering accounts of visual processing are ubiquitous. The template-matching operation implemented by the linear-nonlinear cascade (linear filter followed by static nonlinearity) is the most widely adopted computational tool in systems neuroscience. This simple model achieves remarkable explanatory power while retaining analytical tractability, potentially extending its reach to a wide range of systems and levels in sensory processing. The extent of its applicability to human behaviour, however, remains unclear. Because sensory stimuli possess multiple attributes (e.g. position, orientation, size), the issue of applicability may be asked by considering each attribute one at a time in relation to a family of linear-nonlinear models, or by considering all attributes collectively in relation to a specified implementation of the linear-nonlinear cascade. We demonstrate that human visual processing can operate under conditions that are indistinguishable from linear-nonlinear transduction with respect to substantially different stimulus attributes of a uniquely specified target signal with associated behavioural task. However, no specific implementation of a linear-nonlinear cascade is able to account for the entire collection of results across attributes; a satisfactory account at this level requires the introduction of a small gain-control circuit, resulting in a model that no longer belongs to the linear-nonlinear family. Our results inform and constrain efforts at obtaining and interpreting comprehensive characterizations of the human sensory process by demonstrating its inescapably nonlinear nature, even under conditions that have been painstakingly fine-tuned to facilitate template-matching behaviour and to produce results that, at some level of inspection, do conform to linear filtering predictions. They also suggest that compliance with linear transduction may be the targeted outcome of carefully crafted nonlinear circuits, rather than default behaviour exhibited by basic components. PMID:26556758

Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy.

PubMed

Huppert, Theodore J

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.

The isoform A of reticulon-4 (Nogo-A) in cerebrospinal fluid of primary brain tumor patients: influencing factors.

PubMed

Koper, Olga Martyna; Kamińska, Joanna; Milewska, Anna; Sawicki, Karol; Mariak, Zenon; Kemona, Halina; Matowicka-Karna, Joanna

2018-05-18

The influence of isoform A of reticulon-4 (Nogo-A), also known as neurite outgrowth inhibitor, on primary brain tumor development was reported. Therefore the aim was the evaluation of Nogo-A concentrations in cerebrospinal fluid (CSF) and serum of brain tumor patients compared with non-tumoral individuals. All serum results, except for two cases, obtained both in brain tumors and non-tumoral individuals, were below the lower limit of ELISA detection. Cerebrospinal fluid Nogo-A concentrations were significantly lower in primary brain tumor patients compared to non-tumoral individuals. The univariate linear regression analysis found that if white blood cell count increases by 1 × 10 3 /μL, the mean cerebrospinal fluid Nogo-A concentration value decreases 1.12 times. In the model of multiple linear regression analysis predictor variables influencing cerebrospinal fluid Nogo-A concentrations included: diagnosis, sex, and sodium level. The mean cerebrospinal fluid Nogo-A concentration value was 1.9 times higher for women in comparison to men. In the astrocytic brain tumor group higher sodium level occurs with lower cerebrospinal fluid Nogo-A concentrations. We found the opposite situation in non-tumoral individuals. Univariate linear regression analysis revealed, that cerebrospinal fluid Nogo-A concentrations change in relation to white blood cell count. In the created model of multiple linear regression analysis we found, that within predictor variables influencing CSF Nogo-A concentrations were diagnosis, sex, and sodium level. Results may be relevant to the search for cerebrospinal fluid biomarkers and potential therapeutic targets in primary brain tumor patients. Nogo-A concentrations were tested by means of enzyme-linked immunosorbent assay (ELISA).

Development of a laser Doppler displacement encoder system with ultra-low-noise-level for linear displacement measurement with subnanometer resolution - Final CRADA Report

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

Shu, Deming

An U.S. DOE Cooperative Research and Development Agreement (CRADA) between ANL and Optodyne, Inc. has been established to develop a prototype laser Doppler displacement encoder system with ultra-low noise level for linear measurements to sub-nanometer resolution for synchrotron radiation applications. We have improved the heterodyne efficiency and reduced the detector shot noises by proper shielding and adding a low-pass filter. The laser Doppler displacement encoder system prototype demonstrated a ~ 1 nm system output noise floor with single reflection optics. With multiple-pass optical arrangement, 0.1 nm scale closed-loop feedback control is achieved.

Is impaired cerebral vasoreactivity an early marker of cognitive decline in multiple sclerosis patients?

PubMed

Metzger, Aude; Le Bars, Emmanuelle; Deverdun, Jeremy; Molino, François; Maréchal, Bénédicte; Picot, Marie-Christine; Ayrignac, Xavier; Carra, Clarisse; Bauchet, Luc; Krainik, Alexandre; Labauge, Pierre; Menjot de Champfleur, Nicolas

2018-03-01

The link between cerebral vasoreactivity and cognitive status in multiple sclerosis remains unclear. The aim of the present study was to investigate a potential decrease of cerebral vasoreactivity in multiple sclerosis patients and correlate it with cognitive status. Thirty-three patients with multiple sclerosis (nine progressive and 24 remitting forms, median age: 39 years, 12 males) and 22 controls underwent MRI with a hypercapnic challenge to assess cerebral vasoreactivity and a neuropsychological assessment. Cerebral vasoreactivity, measured as the cerebral blood flow percent increase normalised by end-tidal carbon dioxide variation, was assessed globally and by regions of interest using the blood oxygen level-dependent technique. Non-parametric statistics tests were used to assess differences between groups, and associations were estimated using linear models. Cerebral vasoreactivity was lower in patients with cognitive impairment than in cognitively normal patients (p=0.004) and was associated with education level in patients (R 2 = 0.35; p = 0.047). There was no decrease in cerebral vasoreactivity between patients and controls. Cognitive impairment in multiple sclerosis may be mediated through decreased cerebral vasoreactivity. Cerebral vasoreactivity could therefore be considered as a marker of cognitive decline in multiple sclerosis. • Cerebral vasoreactivity does not differ between multiple sclerosis patients and controls. • Cerebral vasoreactivity measure is linked to cognitive impairment in multiple sclerosis. • Cerebral vasoreactivity is linked to level of education in multiple sclerosis.

Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period

PubMed Central

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

Abstract Objective: To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. Methods: This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95%, was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α <5%. Results: From 226 women included, 200 (88.5%) were 20-44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. Conclusions: This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. PMID:26100593

Nonclinical pharmacokinetic and pharmacodynamic characterisation of somapacitan: A reversible non-covalent albumin-binding growth hormone.

PubMed

Thygesen, Peter; Andersen, Henrik Sune; Behrens, Carsten; Fels, Johannes Josef; Nørskov-Lauritsen, Leif; Rischel, Christian; Johansen, Nils Langeland

2017-08-01

Somapacitan is an albumin-binding growth hormone derivative intended for once weekly administration, currently in clinical development for treatment of adult as well as juvenile GH deficiency. Nonclinical in vivo pharmacological characterisation of somapacitan was performed to support the clinical trials. Here we present the pharmacokinetic and pharmacodynamic effects of somapacitan in rats, minipigs, and cynomolgus monkeys. Pharmacokinetic studies investigating exposure, absorption, clearance, and bioavailability after single intravenous (i.v.) and subcutaneous (s.c.) administration were performed in all species. A dose-response study with five dose levels and a multiple dose pharmacodynamic study with four once weekly doses was performed in hypophysectomised rats to evaluate the effect of somapacitan on growth and IGF-I production. Pharmacokinetic profiles indicated first order absorption from the subcutaneous tissue after s.c. injections for somapacitan in all three species. Apparent terminal half-lives were 5-6h in rats, 10-12h in minipigs, and 17-20h in monkeys. Somapacitan induced a dose-dependent growth in hypophysectomised rats (p<0.001) and an increase in plasma IGF-I levels in rats (p<0.01), minipigs (p<0.01), and cynomolgus monkeys (p<0.05) after single dose administration. Multiple once weekly dosing of somapacitan in hypophysectomised rats induced a step-wise increase in body weight with an initial linear phase the first 3-4days in each dosing interval (p<0.001). The nonclinical pharmacokinetic and pharmacodynamic studies of somapacitan showed similar pharmacokinetic properties, with no absorption-limited elimination, increased clearance and increased and sustained levels of IGF-I in plasma for up to 10days after a single dose administration in all three species. Somapacitan induced a dose-dependent increase in body weight and IGF-I levels in hypophysectomised rats. Multiple dosing of somapacitan in hypophysectomised rats suggested a linear growth for the first 3-4days in each weekly dosing interval, whereas daily hGH dosing showed linear growth for approximately two weeks before reaching a plateau level. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

PubMed Central

Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

2008-01-01

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

PubMed

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P < 0.01), and correlated significantly with AF traits (P < 0.05). The best multiple linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.

Correction of the significance level when attempting multiple transformations of an explanatory variable in generalized linear models

PubMed Central

2013-01-01

Background In statistical modeling, finding the most favorable coding for an exploratory quantitative variable involves many tests. This process involves multiple testing problems and requires the correction of the significance level. Methods For each coding, a test on the nullity of the coefficient associated with the new coded variable is computed. The selected coding corresponds to that associated with the largest statistical test (or equivalently the smallest pvalue). In the context of the Generalized Linear Model, Liquet and Commenges (Stat Probability Lett,71:33–38,2005) proposed an asymptotic correction of the significance level. This procedure, based on the score test, has been developed for dichotomous and Box-Cox transformations. In this paper, we suggest the use of resampling methods to estimate the significance level for categorical transformations with more than two levels and, by definition those that involve more than one parameter in the model. The categorical transformation is a more flexible way to explore the unknown shape of the effect between an explanatory and a dependent variable. Results The simulations we ran in this study showed good performances of the proposed methods. These methods were illustrated using the data from a study of the relationship between cholesterol and dementia. Conclusion The algorithms were implemented using R, and the associated CPMCGLM R package is available on the CRAN. PMID:23758852

Cancer Patients Enrolled in a Smoking Cessation Clinical Trial: Characteristics and Correlates of Smoking Rate and Nicotine Dependence.

PubMed

Miele, Andrew; Thompson, Morgan; Jao, Nancy C; Kalhan, Ravi; Leone, Frank; Hogarth, Lee; Hitsman, Brian; Schnoll, Robert

2018-01-01

A substantial proportion of cancer patients continue to smoke after their diagnosis but few studies have evaluated correlates of nicotine dependence and smoking rate in this population, which could help guide smoking cessation interventions. This study evaluated correlates of smoking rate and nicotine dependence among 207 cancer patients. A cross-sectional analysis using multiple linear regression evaluated disease, demographic, affective, and tobacco-seeking correlates of smoking rate and nicotine dependence. Smoking rate was assessed using a timeline follow-back method. The Fagerström Test for Nicotine Dependence measured levels of nicotine dependence. A multiple linear regression predicting nicotine dependence showed an association with smoking to alleviate a sense of addiction from the Reasons for Smoking scale and tobacco-seeking behavior from the concurrent choice task ( p < .05), but not with affect measured by the HADS and PANAS ( p > .05). Multiple linear regression predicting prequit showed an association with smoking to alleviate addiction ( p < .05). ANOVA showed that Caucasian participants reported greater rates of smoking compared to other races. The results suggest that behavioral smoking cessation interventions that focus on helping patients to manage tobacco-seeking behavior, rather than mood management interventions, could help cancer patients quit smoking.

Zinc Levels in Left Ventricular Hypertrophy.

PubMed

Huang, Lei; Teng, Tianming; Bian, Bo; Yao, Wei; Yu, Xuefang; Wang, Zhuoqun; Xu, Zhelong; Sun, Yuemin

2017-03-01

Zinc is one of the most important trace elements in the body and zinc homeostasis plays a critical role in maintaining cellular structure and function. Zinc dyshomeostasis can lead to many diseases, such as cardiovascular disease. Our aim was to investigate whether there is a relationship between zinc and left ventricular hypertrophy (LVH). A total of 519 patients was enrolled and their serum zinc levels were measured in this study. We performed analyses on the relationship between zinc levels and LVH and the four LV geometry pattern patients: normal LV geometry, concentric remodeling, eccentric LVH, and concentric LVH. We performed further linear and multiple regression analyses to confirm the relationship between zinc and left ventricular mass (LVM), left ventricular mass index (LVMI), and relative wall thickness (RWT). Our data showed that zinc levels were 710.2 ± 243.0 μg/L in the control group and were 641.9 ± 215.2 μg/L in LVH patients. We observed that zinc levels were 715 ± 243.5 μg/L, 694.2 ± 242.7 μg/L, 643.7 ± 225.0 μg/L, and 638.7 ± 197.0 μg/L in normal LV geometry, concentric remodeling, eccentric LVH, and concentric LVH patients, respectively. We further found that there was a significant inverse linear relationship between zinc and LVM (p = 0.001) and LVMI (p = 0.000) but did not show a significant relationship with RWT (p = 0.561). Multiple regression analyses confirmed that the linear relationship between zinc and LVM and LVMI remained inversely significant. The present study revealed that serum zinc levels were significantly decreased in the LVH patients, especially in the eccentric LVH and concentric LVH patients. Furthermore, zinc levels were significantly inversely correlated with LVM and LVMI.

Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

ERIC Educational Resources Information Center

Xu, Xueli; von Davier, Matthias

2008-01-01

The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…

Lichen-based critical loads for atmospheric nitrogen deposition in Western Oregon and Washington forests, USA

Treesearch

Linda H. Geiser; Sarah E. Jovan; Doug A. Glavich; Matthew K. Porter

2010-01-01

Critical loads (CLs) define maximum atmospheric deposition levels apparently preventative of ecosystem harm. We present first nitrogen CLs for northwestern North America's maritime forests. Using multiple linear regression, we related epiphytic-macrolichen community composition to: 1) wet deposition from the National Atmospheric Deposition Program, 2) wet, dry,...

Maintenance Operations in Mission Oriented Protective Posture Level IV (MOPPIV)

DTIC Science & Technology

1987-10-01

Repair FADAC Printed Circuit Board ............. 6 3. Data Analysis Techniques ............................. 6 a. Multiple Linear Regression... ANALYSIS /DISCUSSION ............................... 12 1. Exa-ple of Regression Analysis ..................... 12 S2. Regression results for all tasks...6 * TABLE 9. Task Grouping for Analysis ........................ 7 "TABXLE 10. Remove/Replace H60A3 Power Pack................. 8 TABLE

Cue Reliance in L2 Written Production

ERIC Educational Resources Information Center

Wiechmann, Daniel; Kerz, Elma

2014-01-01

Second language learners reach expert levels in relative cue weighting only gradually. On the basis of ensemble machine learning models fit to naturalistic written productions of German advanced learners of English and expert writers, we set out to reverse engineer differences in the weighting of multiple cues in a clause linearization problem. We…

Classical Michaelis-Menten and system theory approach to modeling metabolite formation kinetics.

PubMed

Popović, Jovan

2004-01-01

When single doses of drug are administered and kinetics are linear, techniques, which are based on the compartment approach and the linear system theory approach, in modeling the formation of the metabolite from the parent drug are proposed. Unlike the purpose-specific compartment approach, the methodical, conceptual and computational uniformity in modeling various linear biomedical systems is the dominant characteristic of the linear system approach technology. Saturation of the metabolic reaction results in nonlinear kinetics according to the Michaelis-Menten equation. The two compartment open model with Michaelis-Menten elimination kinetics is theorethicaly basic when single doses of drug are administered. To simulate data or to fit real data using this model, one must resort to numerical integration. A biomathematical model for multiple dosage regimen calculations of nonlinear metabolic systems in steady-state and a working example with phenytoin are presented. High correlation between phenytoin steady-state serum levels calculated from individual Km and Vmax values in the 15 adult epileptic outpatients and the observed levels at the third adjustment of phenytoin daily dose (r=0.961, p<0.01) were found.

The performance of integrated transconductance amplifiers as variable current sources for bio-electric impedance measurements.

PubMed

Smith, D N

1992-01-01

Multiple applied current impedance measurement systems require numbers of current sources which operate simultaneously at the same frequency and within the same phase but at variable amplitudes. Investigations into the performance of some integrated operational transconductance amplifiers as variable current sources are described. Measurements of breakthrough, non-linearity and common-mode output levels for LM13600, NE5517 and CA3280 were carried out. The effects of such errors on the overall performance and stability of multiple current systems when driving floating loads are considered.

[Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period].

PubMed

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado Junior, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95% was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α<5%. From 226 women included, 200 (88.5%) were 20 to 44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

Bayesian dynamical systems modelling in the social sciences.

PubMed

Ranganathan, Shyam; Spaiser, Viktoria; Mann, Richard P; Sumpter, David J T

2014-01-01

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.

Gross motor development in full-term Greek infants assessed by the Alberta Infant Motor Scale: reference values and socioeconomic impact.

PubMed

Syrengelas, Dimitrios; Kalampoki, Vassiliki; Kleisiouni, Paraskevi; Konstantinou, Dimitrios; Siahanidou, Tania

2014-07-01

The aims of this study were to investigate gross motor development in Greek infants and establish AIMS percentile curves and to examine possible association of AIMS scores with socioeconomic parameters. Mean AIMS scores of 1068 healthy Greek full-term infants were compared at monthly age level with the respective mean scores of the Canadian normative sample. In a subgroup of 345 study participants, parents provided, via interview, information about family socioeconomic status. Multiple linear regression analysis was performed to evaluate the relationship of infant motor development with socioeconomic parameters. Mean AIMS scores did not differ significantly between Greek and Canadian infants in any of the 19 monthly levels of age. In multiple linear regression analysis, the educational level of the mother and also whether the infant was being raised by grandparents/babysitter were significantly associated with gross motor development (p=0.02 and p<0.001, respectively), whereas there was no significant correlation of mean AIMS scores with gender, birth order, maternal age, paternal educational level and family monthly income. Gross motor development of healthy Greek full-term infants, assessed by AIMS during the first 19months of age, follows a similar course to that of the original Canadian sample. Specific socioeconomic factors are associated with the infants' motor development. Copyright © 2014 Elsevier Ltd. All rights reserved.

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 ...

Curriculum-Based Measurement of Oral Reading: Quality of Progress Monitoring Outcomes

ERIC Educational Resources Information Center

Christ, Theodore J.; Zopluoglu, Cengiz; Long, Jeffery D.; Monaghen, Barbara D.

2012-01-01

Curriculum-based measurement of oral reading (CBM-R) is frequently used to set student goals and monitor student progress. This study examined the quality of growth estimates derived from CBM-R progress monitoring data. The authors used a linear mixed effects regression (LMER) model to simulate progress monitoring data for multiple levels of…

Multiple linear regression analysis

NASA Technical Reports Server (NTRS)

Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

The Challenge of Separating Effects of Simultaneous Education Projects on Student Achievement

ERIC Educational Resources Information Center

Ma, Xin; Ma, Lingling

2009-01-01

When multiple education projects operate in an overlapping or rear-ended manner, it is always a challenge to separate unique project effects on schooling outcomes. Our analysis represents a first attempt to address this challenge. A three-level hierarchical linear model (HLM) was presented as a general analytical framework to separate program…

Amesos2 and Belos: Direct and Iterative Solvers for Large Sparse Linear Systems

DOE PAGES

Bavier, Eric; Hoemmen, Mark; Rajamanickam, Sivasankaran; ...

2012-01-01

Solvers for large sparse linear systems come in two categories: direct and iterative. Amesos2, a package in the Trilinos software project, provides direct methods, and Belos, another Trilinos package, provides iterative methods. Amesos2 offers a common interface to many different sparse matrix factorization codes, and can handle any implementation of sparse matrices and vectors, via an easy-to-extend C++ traits interface. It can also factor matrices whose entries have arbitrary “Scalar” type, enabling extended-precision and mixed-precision algorithms. Belos includes many different iterative methods for solving large sparse linear systems and least-squares problems. Unlike competing iterative solver libraries, Belos completely decouples themore » algorithms from the implementations of the underlying linear algebra objects. This lets Belos exploit the latest hardware without changes to the code. Belos favors algorithms that solve higher-level problems, such as multiple simultaneous linear systems and sequences of related linear systems, faster than standard algorithms. The package also supports extended-precision and mixed-precision algorithms. Together, Amesos2 and Belos form a complete suite of sparse linear solvers.« less

Realization of quantum gates with multiple control qubits or multiple target qubits in a cavity

NASA Astrophysics Data System (ADS)

Waseem, Muhammad; Irfan, Muhammad; Qamar, Shahid

2015-06-01

We propose a scheme to realize a three-qubit controlled phase gate and a multi-qubit controlled NOT gate of one qubit simultaneously controlling n-target qubits with a four-level quantum system in a cavity. The implementation time for multi-qubit controlled NOT gate is independent of the number of qubit. Three-qubit phase gate is generalized to n-qubit phase gate with multiple control qubits. The number of steps reduces linearly as compared to conventional gate decomposition method. Our scheme can be applied to various types of physical systems such as superconducting qubits coupled to a resonator and trapped atoms in a cavity. Our scheme does not require adjustment of level spacing during the gate implementation. We also show the implementation of Deutsch-Joza algorithm. Finally, we discuss the imperfections due to cavity decay and the possibility of physical implementation of our scheme.

Single-Nucleotide Polymorphisms Associated with Skin Naphthyl–Keratin Adduct Levels in Workers Exposed to Naphthalene

PubMed Central

Jiang, Rong; French, John E.; Stober, Vandy P.; Kang-Sickel, Juei-Chuan C.; Zou, Fei

2012-01-01

Background: Individual genetic variation that results in differences in systemic response to xenobiotic exposure is not accounted for as a predictor of outcome in current exposure assessment models. Objective: We developed a strategy to investigate individual differences in single-nucleotide polymorphisms (SNPs) as genetic markers associated with naphthyl–keratin adduct (NKA) levels measured in the skin of workers exposed to naphthalene. Methods: The SNP-association analysis was conducted in PLINK using candidate-gene analysis and genome-wide analysis. We identified significant SNP–NKA associations and investigated the potential impact of these SNPs along with personal and workplace factors on NKA levels using a multiple linear regression model and the Pratt index. Results: In candidate-gene analysis, a SNP (rs4852279) located near the CYP26B1 gene contributed to the 2-naphthyl–keratin adduct (2NKA) level. In the multiple linear regression model, the SNP rs4852279, dermal exposure, exposure time, task replacing foam, age, and ethnicity all were significant predictors of 2NKA level. In genome-wide analysis, no single SNP reached genome-wide significance for NKA levels (all p ≥ 1.05 × 10–5). Pathway and network analyses of SNPs associated with NKA levels were predicted to be involved in the regulation of cellular processes and homeostasis. Conclusions: These results provide evidence that a quantitative biomarker can be used as an intermediate phenotype when investigating the association between genetic markers and exposure–dose relationship in a small, well-characterized exposed worker population. PMID:22391508

Leukocyte telomere length correlates with glucose control in adults with recently diagnosed type 2 diabetes.

PubMed

Rosa, Erica Carine Campos Caldas; Dos Santos, Renan Renato Cruz; Fernandes, Luis Fernando Amarante; Neves, Francisco de Assis Rocha; Coelho, Michella Soares; Amato, Angelica Amorim

2018-01-01

We investigated leukocyte relative telomere length (TL) in patients with type 2 diabetes (T2D) diagnosed for no longer than five years and its association with clinical and biochemical variables. Peripheral blood leukocyte relative TL was investigated in 108 patients with T2D (87 women, 21 men) and 125 (37 women, 88 men) age-matched control subjects with normal glucose tolerance, by quantitative polymerase chain reaction. Multiple linear regression analysis was used to examine the association between relative TL and demographic, anthropometric and biochemical indicators of metabolic control among patients with T2D. Patients with T2D had a median time since diagnosis of 1 year and most were on metformin monotherapy, with satisfactory glucose control determined by HbA1c levels. Median relative TL was not different between patients with T2D and control subjects. However, multiple linear regression analyses showed that relative TL was inversely associated with time since T2D diagnosis, fasting plasma glucose levels and HbA1c levels, but not with HbA1c levels assessed in the preceding 5-12 months, after adjustment for age, sex and body mass index. This study suggests that relative TL is not shorter in patients with recently diagnosed T2D, but is inversely correlated with glucose levels, even among patients with overall satisfactory glucose control. Copyright © 2017 Elsevier B.V. All rights reserved.

Elastico-mechanoluminescence in CaZr(PO4)2:Eu2+ with multiple trap levels.

PubMed

Zhang, Jun-Cheng; Xu, Chao-Nan; Long, Yun-Ze

2013-06-03

We report on a novel elastico-mechanoluminescence (EML) phosphor of CaZr(PO4)2:Eu2+ for simultaneous luminescent sensing and imaging to mechanical load by the light-emitting of Eu2+ ions. The EML properties of CaZr(PO4)2:Eu2+ show an intense luminance (above 15 mcd m(-2)), a low load threshold (below 5 N), a broad measurement range for the dynamic load (up to 2000 N), and an accurate linear relationship of EML intensity against the applied load. The excellent EML characteristics are considered to originate from the piezoelectric crystal structure and the multiple trap levels with appropriate depths. An EML mechanism based on the electrons as the main charge carriers is proposed.

Anxiety Levels Are Independently Associated With Cognitive Performance in an Australian Multiple Sclerosis Patient Cohort.

PubMed

Ribbons, Karen; Lea, Rodney; Schofield, Peter W; Lechner-Scott, Jeannette

2017-01-01

Neurological and psychological symptoms in multiple sclerosis can affect cognitive function. The objective of this study was to explore the relationship between psychological measures and cognitive performance in a patient cohort. In 322 multiple sclerosis patients, psychological symptoms were measured using the Depression Anxiety and Stress Scale, and cognitive function was evaluated using Audio Recorded Cognitive Screen. Multifactor linear regression analysis, accounting for all clinical covariates, found that anxiety was the only psychological measure to remain a significant predictor of cognitive performance (p<0.001), particularly memory function (p<0.001). Further prospective studies are required to determine whether treatment of anxiety improves cognitive impairment.

Ghrelin level negatively predicts quality of life in obese women.

PubMed

Lu, P H; Song, Y L; Hsu, C H

2017-02-01

A cross-sectional cohort study was conducted to investigate whether ghrelin level in obese women predicts the quality of life (QOL). A total of 307 subjects fulfilled the criteria: (1) age between 20 and 65 years old, (2) body mass index ≥27 kg/m 2 (3) waist circumference ≥80 cm were enrolled in the study. All subjects were assigned to one of the plasma ghrelin level categories according to the quartiles. The median of age and BMI of the 307 obese women were 45 ± 18 years and 29.9 ± 4.1 kg/m 2 , respectively. The main outcome evaluated is the associations of plasma ghrelin level and QOL, which were evaluated using multiple linear regression analysis. Results of linear trend test show significant statistical difference in plasma lipoproteins (triglyceride, cholesterol, HDL-cholestero and LDL-cholesterol = and levels of obesity-related hormone peptides, including leptin, adiponectin, insulin among quartiles of ghrelin. Multiple liner regression analysis of serum obesity-related hormone peptide level and QOL using stepwise method shows ghrelin concentration was the only predictor of QOL, including PCS-12 level (β = -0.18, p = 0.001), MCS-12 level (β = -0.14, p = 0.009), WHOQOL-BREF scores: physical (β = -0.13, p = 0.03), psychological (β = -0.16, p = 0.007), social (β = -0.21, p =  < 0.001), and environmental (β = -0.22, p =  <0.001), after adjusting other factors for obese female subjects. This study demonstrated that ghrelin concentration is strongly associated with QOL level among obese women. Hence, ghrelin concentration might be a valuable marker to be monitored in obese women.

Serum Albumin and Disease Severity of Non-Cystic Fibrosis Bronchiectasis.

PubMed

Lee, Seung Jun; Kim, Hyo-Jung; Kim, Ju-Young; Ju, Sunmi; Lim, Sujin; Yoo, Jung Wan; Nam, Sung-Jin; Lee, Gi Dong; Cho, Hyun Seop; Kim, Rock Bum; Cho, Yu Ji; Jeong, Yi Yeong; Kim, Ho Cheol; Lee, Jong Deog

2017-08-01

A clinical classification system has been developed to define the severity and predict the prognosis of subjects with non-cystic fibrosis (CF) bronchiectasis. We aimed to identify laboratory parameters that are correlated with the bronchiectasis severity index (BSI) and FACED score. The medical records of 107 subjects with non-CF bronchiectasis for whom BSI and FACED scores could be calculated were retrospectively reviewed. The correlations between the laboratory parameters and BSI or FACED score were assessed, and multiple-linear regression analysis was performed to identify variables independently associated with BSI and FACED score. An additional subgroup analysis was performed according to sex. Among all of the enrolled subjects, 49 (45.8%) were male and 58 (54.2%) were female. The mean BSI and FACED scores were 9.43 ± 3.81 and 1.92 ± 1.59, respectively. The serum albumin level (r = -0.49), bilirubin level (r = -0.31), C-reactive protein level (r = 0.22), hemoglobin level (r = -0.2), and platelet/lymphocyte ratio (r = 0.31) were significantly correlated with BSI. Meanwhile, serum albumin (r = -0.37) and bilirubin level (r = -0.25) showed a significant correlation with the FACED score. Multiple-linear regression analysis showed that the serum bilirubin level was independently associated with BSI, and the serum albumin level was independently associated with both scoring systems. Subgroup analysis revealed that the level of uric acid was also a significant variable independently associated with the BSI in male bronchiectasis subjects. Several laboratory variables were identified as possible prognostic factors for non-CF bronchiectasis. Among them, the serum albumin level exhibited the strongest correlation and was identified as an independent variable associated with the BSI and FACED scores. Copyright © 2017 by Daedalus Enterprises.

Contrast effects on speed perception for linear and radial motion.

PubMed

Champion, Rebecca A; Warren, Paul A

2017-11-01

Speed perception is vital for safe activity in the environment. However, considerable evidence suggests that perceived speed changes as a function of stimulus contrast, with some investigators suggesting that this might have meaningful real-world consequences (e.g. driving in fog). In the present study we investigate whether the neural effects of contrast on speed perception occur at the level of local or global motion processing. To do this we examine both speed discrimination thresholds and contrast-dependent speed perception for two global motion configurations that have matched local spatio-temporal structure. Specifically we compare linear and radial configurations, the latter of which arises very commonly due to self-movement. In experiment 1 the stimuli comprised circular grating patches. In experiment 2, to match stimuli even more closely, motion was presented in multiple local Gabor patches equidistant from central fixation. Each patch contained identical linear motion but the global configuration was either consistent with linear or radial motion. In both experiments 1 and 2, discrimination thresholds and contrast-induced speed biases were similar in linear and radial conditions. These results suggest that contrast-based speed effects occur only at the level of local motion processing, irrespective of global structure. This result is interpreted in the context of previous models of speed perception and evidence suggesting differences in perceived speed of locally matched linear and radial stimuli. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-disease analysis of maternal antibody decay using non-linear mixed models accounting for censoring.

PubMed

Goeyvaerts, Nele; Leuridan, Elke; Faes, Christel; Van Damme, Pierre; Hens, Niel

2015-09-10

Biomedical studies often generate repeated measures of multiple outcomes on a set of subjects. It may be of interest to develop a biologically intuitive model for the joint evolution of these outcomes while assessing inter-subject heterogeneity. Even though it is common for biological processes to entail non-linear relationships, examples of multivariate non-linear mixed models (MNMMs) are still fairly rare. We contribute to this area by jointly analyzing the maternal antibody decay for measles, mumps, rubella, and varicella, allowing for a different non-linear decay model for each infectious disease. We present a general modeling framework to analyze multivariate non-linear longitudinal profiles subject to censoring, by combining multivariate random effects, non-linear growth and Tobit regression. We explore the hypothesis of a common infant-specific mechanism underlying maternal immunity using a pairwise correlated random-effects approach and evaluating different correlation matrix structures. The implied marginal correlation between maternal antibody levels is estimated using simulations. The mean duration of passive immunity was less than 4 months for all diseases with substantial heterogeneity between infants. The maternal antibody levels against rubella and varicella were found to be positively correlated, while little to no correlation could be inferred for the other disease pairs. For some pairs, computational issues occurred with increasing correlation matrix complexity, which underlines the importance of further developing estimation methods for MNMMs. Copyright © 2015 John Wiley & Sons, Ltd.

How well do elderly people cope with uncertainty in a learning task?

PubMed

Chasseigne, G; Grau, S; Mullet, E; Cama, V

1999-11-01

The relation between age, task complexity and learning performance in a Multiple Cue Probability Learning task was studied by systematically varying the level of uncertainty present in the task, keeping constant the direction of relationships. Four age groups were constituted: young adults (mean age = 21), middle-aged adults (45), elderly people (69) and very elderly people (81). Five uncertainty levels were considered: predictability = 0.96, 0.80, 0.64, 0.48, and 0.32. All relationships involved were direct ones. A strong effect of uncertainty on 'control', a measure of the subject's consistency with respect to a linear model, was found. This effect was essentially a linear one. To each decrement in predictability of the task corresponded an equal decrement in participants' level of control. This level of decrement was the same, regardless of the age of the participant. It can be concluded that elderly people cope with uncertainty in probability learning tasks as well as young adults.

How Team-Level and Individual-Level Conflict Influences Team Commitment: A Multilevel Investigation.

PubMed

Lee, Sanghyun; Kwon, Seungwoo; Shin, Shung J; Kim, MinSoo; Park, In-Jo

2017-01-01

We investigate how two different types of conflict (task conflict and relationship conflict) at two different levels (individual-level and team-level) influence individual team commitment. The analysis was conducted using data we collected from 193 employees in 31 branch offices of a Korean commercial bank. The relationships at multiple levels were tested using hierarchical linear modeling (HLM). The results showed that individual-level relationship conflict was negatively related to team commitment while individual-level task conflict was not. In addition, both team-level task and relationship conflict were negatively associated with team commitment. Finally, only team-level relationship conflict significantly moderated the relationship between individual-level relationship conflict and team commitment. We further derive theoretical implications of these findings.

How Team-Level and Individual-Level Conflict Influences Team Commitment: A Multilevel Investigation

PubMed Central

Lee, Sanghyun; Kwon, Seungwoo; Shin, Shung J.; Kim, MinSoo; Park, In-Jo

2018-01-01

We investigate how two different types of conflict (task conflict and relationship conflict) at two different levels (individual-level and team-level) influence individual team commitment. The analysis was conducted using data we collected from 193 employees in 31 branch offices of a Korean commercial bank. The relationships at multiple levels were tested using hierarchical linear modeling (HLM). The results showed that individual-level relationship conflict was negatively related to team commitment while individual-level task conflict was not. In addition, both team-level task and relationship conflict were negatively associated with team commitment. Finally, only team-level relationship conflict significantly moderated the relationship between individual-level relationship conflict and team commitment. We further derive theoretical implications of these findings. PMID:29387033

Multiple epitope presentation and surface density control enabled by chemoselective immobilization lead to enhanced performance in IgE-binding fingerprinting on peptide microarrays.

PubMed

Gori, Alessandro; Cretich, Marina; Vanna, Renzo; Sola, Laura; Gagni, Paola; Bruni, Giulia; Liprino, Marta; Gramatica, Furio; Burastero, Samuele; Chiari, Marcella

2017-08-29

Multiple ligand presentation is a powerful strategy to enhance the affinity of a probe for its corresponding target. A promising application of this concept lies in the analytical field, where surface immobilized probes interact with their corresponding targets in the context of complex biological samples. Here we investigate the effect of multiple epitope presentation (MEP) in the challenging context of IgE-detection in serum samples using peptide microarrays, and evaluate the influence of probes surface density on the assay results. Using the milk allergen alpha-lactalbumin as a model, we have synthesized three immunoreactive epitope sequences in a linear, branched and tandem form and exploited a chemoselective click strategy (CuAAC) for their immobilization on the surface of two biosensors, a microarray and an SPR chip both modified with the same clickable polymeric coating. We first demonstrated that a fine tuning of the surface peptide density plays a crucial role to fully exploit the potential of oriented and multiple peptide display. We then compared the three multiple epitope presentations in a microarray assay using sera samples from milk allergic patients, confirming that a multiple presentation, in particular that of the tandem construct, allows for a more efficient characterization of IgE-binding fingerprints at a statistically significant level. To gain insights on the binding parameters that characterize antibody/epitopes affinity, we selected the most reactive epitope of the series (LAC1) and performed a Surface Plasmon Resonance Imaging (SPRi) analysis comparing different epitope architectures (linear versus branched versus tandem). We demonstrated that the tandem peptide provides an approximately twofold increased binding capacity with respect to the linear and branched peptides, that could be attributed to a lower rate of dissociation (K d ). Copyright © 2017 Elsevier B.V. All rights reserved.

Linear increases in carbon nanotube density through multiple transfer technique.

PubMed

Shulaker, Max M; Wei, Hai; Patil, Nishant; Provine, J; Chen, Hong-Yu; Wong, H-S P; Mitra, Subhasish

2011-05-11

We present a technique to increase carbon nanotube (CNT) density beyond the as-grown CNT density. We perform multiple transfers, whereby we transfer CNTs from several growth wafers onto the same target surface, thereby linearly increasing CNT density on the target substrate. This process, called transfer of nanotubes through multiple sacrificial layers, is highly scalable, and we demonstrate linear CNT density scaling up to 5 transfers. We also demonstrate that this linear CNT density increase results in an ideal linear increase in drain-source currents of carbon nanotube field effect transistors (CNFETs). Experimental results demonstrate that CNT density can be improved from 2 to 8 CNTs/μm, accompanied by an increase in drain-source CNFET current from 4.3 to 17.4 μA/μm.

Impact of pine tip moth attack on loblolly pine

Treesearch

Roy Hedden

1999-01-01

Data on the impact of Nantucket pine tip moth, Rhyacionia frustrana, attack on the height of loblolly pine, Pinus taeda, in the first three growing seasons after planting from three locations in eastern North Carolina (U.S.A.) was used to develop multiple linear regression models relating tree height to tip moth infestation level in each growing season. These models...

A simple and selective method for the measurement of azadirachtin and related azadirachtoid levels in fruits and vegetables using liquid chromatography electrospray ionization tandem mass spectrometry.

PubMed

Sarais, Giorgia; Caboni, Pierluigi; Sarritzu, Erika; Russo, Mariateresa; Cabras, Paolo

2008-05-14

Neem-based insecticides containing azadirachtin and related azadirachtoids are widely used in agriculture. Here, we report an analytical method for the rapid and accurate quantification of the insecticide azadirachtin A and B and other azadirachtoids such as salannin, nimbin, and their deacetylated analogues on tomatoes and peaches. Azadirachtoids were extracted from fruits and vegetables with acetonitrile. Using high-performance liquid chromatography/electrospray ionization tandem mass spectrometer, azadirachtoids were selectively detected monitoring the multiple reaction transitions of sodium adduct precursor ions. For azadirachtin A, calibration was linear over a working range of 1-1000 microg/L with r > 0.996. The limit of detection and limit of quantification for azadirachtin A were 0.4 and 0.8 microg/kg, respectively. The presence of interfering compounds in the peach and tomato extracts was evaluated and found to be minimal. Because of the linear behavior, it was concluded that the multiple reaction transitions of sodium adduct ions can be used for analytical purposes, that is, for the identification and quantification of azadirachtin A and B and related azadirachtoids in fruit and vegetable extracts at trace levels.

Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

ERIC Educational Resources Information Center

Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

2006-01-01

Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

Emotional expression in music: contribution, linearity, and additivity of primary musical cues

PubMed Central

Eerola, Tuomas; Friberg, Anders; Bresin, Roberto

2013-01-01

The aim of this study is to manipulate musical cues systematically to determine the aspects of music that contribute to emotional expression, and whether these cues operate in additive or interactive fashion, and whether the cue levels can be characterized as linear or non-linear. An optimized factorial design was used with six primary musical cues (mode, tempo, dynamics, articulation, timbre, and register) across four different music examples. Listeners rated 200 musical examples according to four perceived emotional characters (happy, sad, peaceful, and scary). The results exhibited robust effects for all cues and the ranked importance of these was established by multiple regression. The most important cue was mode followed by tempo, register, dynamics, articulation, and timbre, although the ranking varied across the emotions. The second main result suggested that most cue levels contributed to the emotions in a linear fashion, explaining 77–89% of variance in ratings. Quadratic encoding of cues did lead to minor but significant increases of the models (0–8%). Finally, the interactions between the cues were non-existent suggesting that the cues operate mostly in an additive fashion, corroborating recent findings on emotional expression in music (Juslin and Lindström, 2010). PMID:23908642

Emotional expression in music: contribution, linearity, and additivity of primary musical cues.

PubMed

Eerola, Tuomas; Friberg, Anders; Bresin, Roberto

2013-01-01

The aim of this study is to manipulate musical cues systematically to determine the aspects of music that contribute to emotional expression, and whether these cues operate in additive or interactive fashion, and whether the cue levels can be characterized as linear or non-linear. An optimized factorial design was used with six primary musical cues (mode, tempo, dynamics, articulation, timbre, and register) across four different music examples. Listeners rated 200 musical examples according to four perceived emotional characters (happy, sad, peaceful, and scary). The results exhibited robust effects for all cues and the ranked importance of these was established by multiple regression. The most important cue was mode followed by tempo, register, dynamics, articulation, and timbre, although the ranking varied across the emotions. The second main result suggested that most cue levels contributed to the emotions in a linear fashion, explaining 77-89% of variance in ratings. Quadratic encoding of cues did lead to minor but significant increases of the models (0-8%). Finally, the interactions between the cues were non-existent suggesting that the cues operate mostly in an additive fashion, corroborating recent findings on emotional expression in music (Juslin and Lindström, 2010).

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues.

PubMed

Shang, Yu; Yu, Guoqiang

2014-09-29

Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a N th-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in homogenous tissues with arbitrary geometries for extraction of BFI (i.e., αD B ). The purpose of this study is to extend the capability of the N th-order linear algorithm for extracting BFI in heterogeneous tissues with arbitrary geometries. The previous linear algorithm was modified to extract BFIs in different types of tissues simultaneously through utilizing DCS data at multiple source-detector separations. We compared the proposed linear algorithm with the semi-infinite homogenous solution in a computer model of adult head with heterogeneous tissue layers of scalp, skull, cerebrospinal fluid, and brain. To test the capability of the linear algorithm for extracting relative changes of cerebral blood flow (rCBF) in deep brain, we assigned ten levels of αD B in the brain layer with a step decrement of 10% while maintaining αD B values constant in other layers. Simulation results demonstrate the accuracy (errors < 3%) of high-order ( N  ≥ 5) linear algorithm in extracting BFIs in different tissue layers and rCBF in deep brain. By contrast, the semi-infinite homogenous solution resulted in substantial errors in rCBF (34.5% ≤ errors ≤ 60.2%) and BFIs in different layers. The N th-order linear model simplifies data analysis, thus allowing for online data processing and displaying. Future study will test this linear algorithm in heterogeneous tissues with different levels of blood flow variations and noises.

Emotional Desensitization to Violence Contributes to Adolescents' Violent Behavior.

PubMed

Mrug, Sylvie; Madan, Anjana; Windle, Michael

2016-01-01

Many adolescents are exposed to violence in their schools, communities and homes. Exposure to violence at high levels or across multiple contexts has been linked with emotional desensitization, indicated by low levels of internalizing symptoms. However, the long-term consequences of such desensitization are unknown. This study examined emotional desensitization to violence, together with externalizing problems, as mediators of the relationship between exposure to violence in pre-adolescence and violent behavior in late adolescence. A community sample of youth (N = 704; 48% female; 76% African American, 22% Caucasian) reported on their exposure to violence in multiple settings at ages 11, 13 and 18. Internalizing and externalizing problems were assessed at ages 11 and 13; violent behavior was measured at age 18. Structural Equation Modeling showed that exposure to high levels of violence at age 11 was associated with lower levels of internalizing problems (quadratic effect) at age 13, as was exposure to violence across multiple contexts (linear effect). In turn, fewer internalizing problems and more externalizing problems at age 13 predicted more violent behavior at age 18. The results suggest that emotional desensitization to violence in early adolescence contributes to serious violence in late adolescence.

Emotional Desensitization to Violence Contributes to Adolescents’ Violent Behavior

PubMed Central

Mrug, Sylvie; Madan, Anjana; Windle, Michael

2015-01-01

Many adolescents are exposed to violence in their schools, communities and homes. Exposure to violence at high levels or across multiple contexts has been linked with emotional desensitization, indicated by low levels of internalizing symptoms. However, the long-term consequences of such desensitization are unknown. This study examined emotional desensitization to violence, together with externalizing problems, as mediators of the relationship between exposure to violence in pre-adolescence and violent behavior in late adolescence. A community sample of youth (N=704; 48% female; 76% African American, 22% Caucasian) reported on their exposure to violence in multiple settings at ages 11, 13 and 18. Internalizing and externalizing problems were assessed at ages 11 and 13; violent behavior was measured at age 18. Structural Equation Modeling showed that exposure to high levels of violence at age 11 was associated with lower levels of internalizing problems (quadratic effect) at age 13, as was exposure to violence across multiple contexts (linear effect). In turn, fewer internalizing problems and more externalizing problems at age 13 predicted more violent behavior at age 18. The results suggest that emotional desensitization to violence in early adolescence contributes to serious violence in late adolescence. PMID:25684447

Work related stress and blood glucose levels.

PubMed

Sancini, A; Ricci, S; Tomei, F; Sacco, C; Pacchiarotti, A; Nardone, N; Ricci, P; Suppi, A; De Cesare, D P; Anzelmo, V; Giubilati, R; Pimpinella, B; Rosati, M V; Tomei, G

2017-01-01

The aim of the study is to evaluate work-related subjective stress in a group of workers on a major Italian company in the field of healthcare through the administration of a valid "questionnaire-tool indicator" (HSE Indicator Tool), and to analyze any correlation between stress levels taken from questionnaire scores and blood glucose values. We studied a final sample consisting of 241 subjects with different tasks. The HSE questionnaire - made up of 35 items (divided into 7 organizational dimensions) with 5 possible answers - has been distributed to all the subjects in occasion of the health surveillance examinations provided by law. The questionnaire was then analyzed using its specific software to process the results related to the 7 dimensions. These results were compared using the Pearson correlation and multiple linear regression with the blood glucose values obtained from each subject. From the analysis of the data the following areas resulted critical, in other words linked to an intermediate (yellow area) or high (red area) condition of stress: sustain from managers, sustain from colleagues, quality of relationships and professional changes. A significant positive correlation (p <0.05) between the mean values of all critical areas and the concentrations of glucose values have been highlighted with the correlation index of Pearson. Multiple linear regression confirmed these findings, showing that the critical dimensions resulting from the questionnaire were the significant variables that can increase the levels of blood glucose. The preliminary results indicate that perceived work stress can be statistically associated with increased levels of blood glucose.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Multilevel linear modelling of the response-contingent learning of young children with significant developmental delays.

PubMed

Raab, Melinda; Dunst, Carl J; Hamby, Deborah W

2018-02-27

The purpose of the study was to isolate the sources of variations in the rates of response-contingent learning among young children with multiple disabilities and significant developmental delays randomly assigned to contrasting types of early childhood intervention. Multilevel, hierarchical linear growth curve modelling was used to analyze four different measures of child response-contingent learning where repeated child learning measures were nested within individual children (Level-1), children were nested within practitioners (Level-2), and practitioners were nested within the contrasting types of intervention (Level-3). Findings showed that sources of variations in rates of child response-contingent learning were associated almost entirely with type of intervention after the variance associated with differences in practitioners nested within groups were accounted for. Rates of child learning were greater among children whose existing behaviour were used as the building blocks for promoting child competence (asset-based practices) compared to children for whom the focus of intervention was promoting child acquisition of missing skills (needs-based practices). The methods of analysis illustrate a practical approach to clustered data analysis and the presentation of results in ways that highlight sources of variations in the rates of response-contingent learning among young children with multiple developmental disabilities and significant developmental delays. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

ERIC Educational Resources Information Center

Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Reduction of interferences in graphite furnace atomic absorption spectrometry by multiple linear regression modelling

NASA Astrophysics Data System (ADS)

Grotti, Marco; Abelmoschi, Maria Luisa; Soggia, Francesco; Tiberiade, Christian; Frache, Roberto

2000-12-01

The multivariate effects of Na, K, Mg and Ca as nitrates on the electrothermal atomisation of manganese, cadmium and iron were studied by multiple linear regression modelling. Since the models proved to efficiently predict the effects of the considered matrix elements in a wide range of concentrations, they were applied to correct the interferences occurring in the determination of trace elements in seawater after pre-concentration of the analytes. In order to obtain a statistically significant number of samples, a large volume of the certified seawater reference materials CASS-3 and NASS-3 was treated with Chelex-100 resin; then, the chelating resin was separated from the solution, divided into several sub-samples, each of them was eluted with nitric acid and analysed by electrothermal atomic absorption spectrometry (for trace element determinations) and inductively coupled plasma optical emission spectrometry (for matrix element determinations). To minimise any other systematic error besides that due to matrix effects, accuracy of the pre-concentration step and contamination levels of the procedure were checked by inductively coupled plasma mass spectrometric measurements. Analytical results obtained by applying the multiple linear regression models were compared with those obtained with other calibration methods, such as external calibration using acid-based standards, external calibration using matrix-matched standards and the analyte addition technique. Empirical models proved to efficiently reduce interferences occurring in the analysis of real samples, allowing an improvement of accuracy better than for other calibration methods.

[Study of Cervical Exfoliated Cell's DNA Quantitative Analysis Based on Multi-Spectral Imaging Technology].

PubMed

Wu, Zheng; Zeng, Li-bo; Wu, Qiong-shui

2016-02-01

The conventional cervical cancer screening methods mainly include TBS (the bethesda system) classification method and cellular DNA quantitative analysis, however, by using multiple staining method in one cell slide, which is staining the cytoplasm with Papanicolaou reagent and the nucleus with Feulgen reagent, the study of achieving both two methods in the cervical cancer screening at the same time is still blank. Because the difficulty of this multiple staining method is that the absorbance of the non-DNA material may interfere with the absorbance of DNA, so that this paper has set up a multi-spectral imaging system, and established an absorbance unmixing model by using multiple linear regression method based on absorbance's linear superposition character, and successfully stripped out the absorbance of DNA to run the DNA quantitative analysis, and achieved the perfect combination of those two kinds of conventional screening method. Through a series of experiment we have proved that between the absorbance of DNA which is calculated by the absorbance unmixxing model and the absorbance of DNA which is measured there is no significant difference in statistics when the test level is 1%, also the result of actual application has shown that there is no intersection between the confidence interval of the DNA index of the tetraploid cells which are screened by using this paper's analysis method when the confidence level is 99% and the DNA index's judging interval of cancer cells, so that the accuracy and feasibility of the quantitative DNA analysis with multiple staining method expounded by this paper have been verified, therefore this analytical method has a broad application prospect and considerable market potential in early diagnosis of cervical cancer and other cancers.

Effects of Hydrostatic Pressure and Electric Field on the Electron-Related Optical Properties in GaAs Multiple Quantum Well.

PubMed

Ospina, D A; Mora-Ramos, M E; Duque, C A

2017-02-01

The properties of the electronic structure of a finite-barrier semiconductor multiple quantum well are investigated taking into account the effects of the application of a static electric field and hydrostatic pressure. With the information of the allowed quasi-stationary energy states, the coefficients of linear and nonlinear optical absorption and of the relative refractive index change associated to transitions between allowed subbands are calculated with the use of a two-level scheme for the density matrix equation of motion and the rotating wave approximation. It is noticed that the hydrostatic pressure enhances the amplitude of the nonlinear contribution to the optical response of the multiple quantum well, whilst the linear one becomes reduced. Besides, the calculated coefficients are blueshifted due to the increasing of the applied electric field, and shows systematically dependence upon the hydrostatic pressure. The comparison of these results with those related with the consideration of a stationary spectrum of states in the heterostructure-obtained by placing infinite confining barriers at a conveniently far distance-shows essential differences in the pressure-induced effects in the sense of resonant frequency shifting as well as in the variation of the amplitudes of the optical responses.

The Ability of American Football Helmets to Manage Linear Acceleration With Repeated High-Energy Impacts.

PubMed

Cournoyer, Janie; Post, Andrew; Rousseau, Philippe; Hoshizaki, Blaine

2016-03-01

Football players can receive up to 1400 head impacts per season, averaging 6.3 impacts per practice and 14.3 impacts per game. A decrease in the capacity of a helmet to manage linear acceleration with multiple impacts could increase the risk of traumatic brain injury. To investigate the ability of football helmets to manage linear acceleration with multiple high-energy impacts. Descriptive laboratory study. Laboratory. We collected linear-acceleration data for 100 impacts at 6 locations on 4 helmets of different models currently used in football. Impacts 11 to 20 were compared with impacts 91 to 100 for each of the 6 locations. Linear acceleration was greater after multiple impacts (91-100) than after the first few impacts (11-20) for the front, front-boss, rear, and top locations. However, these differences are not clinically relevant as they do not affect the risk for head injury. American football helmet performance deteriorated with multiple impacts, but this is unlikely to be a factor in head-injury causation during a game or over a season.

Bilevel formulation of a policy design problem considering multiple objectives and incomplete preferences

NASA Astrophysics Data System (ADS)

Hawthorne, Bryant; Panchal, Jitesh H.

2014-07-01

A bilevel optimization formulation of policy design problems considering multiple objectives and incomplete preferences of the stakeholders is presented. The formulation is presented for Feed-in-Tariff (FIT) policy design for decentralized energy infrastructure. The upper-level problem is the policy designer's problem and the lower-level problem is a Nash equilibrium problem resulting from market interactions. The policy designer has two objectives: maximizing the quantity of energy generated and minimizing policy cost. The stakeholders decide on quantities while maximizing net present value and minimizing capital investment. The Nash equilibrium problem in the presence of incomplete preferences is formulated as a stochastic linear complementarity problem and solved using expected value formulation, expected residual minimization formulation, and the Monte Carlo technique. The primary contributions in this article are the mathematical formulation of the FIT policy, the extension of computational policy design problems to multiple objectives, and the consideration of incomplete preferences of stakeholders for policy design problems.

Reinvestigating the surface and bulk electronic properties of Cd3As2

NASA Astrophysics Data System (ADS)

Roth, S.; Lee, H.; Sterzi, A.; Zacchigna, M.; Politano, A.; Sankar, R.; Chou, F. C.; Di Santo, G.; Petaccia, L.; Yazyev, O. V.; Crepaldi, A.

2018-04-01

Cd3As2 is widely considered among the few materials realizing the three-dimensional (3D) Dirac semimetal phase. Linearly dispersing states, responsible for the ultrahigh charge mobility, have been reported by several angle-resolved photoelectron spectroscopy (ARPES) investigations. However, in spite of the general agreement between these studies, some details are at odds. From scanning tunneling microscopy and optical experiments under magnetic field, a puzzling scenario emerges in which multiple states show linear dispersion at different energy scales. Here, we solve this apparent controversy by reinvestigating the electronic properties of the (112) surface of Cd3As2 by combining ARPES and theoretical calculations. We disentangle the presence of massive and massless metallic bulk and surface states, characterized by different symmetries. Our systematic experimental and theoretical study clarifies the complex band dispersion of Cd3As2 by extending the simplistic 3D Dirac semimetal model to account for multiple bulk and surface states crossing the Fermi level, and thus contributing to the unique material transport properties.

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

PubMed

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

Deficiencies of Circulating Mucosal-associated Invariant T Cells and Natural Killer T Cells in Patients with Multiple Trauma.

PubMed

Jo, Young Goun; Choi, Hyun Jung; Kim, Jung Chul; Cho, Young Nan; Kang, Jeong Hwa; Jin, Hye Mi; Kee, Seung Jung; Park, Yong Wook

2017-05-01

Mucosal-associated invariant T (MAIT) cells and natural killer T (NKT) cells are known to play important roles in autoimmunity, infectious diseases and cancers. However, little is known about the roles of these invariant T cells in multiple trauma. The purposes of this study were to examine MAIT and NKT cell levels in patients with multiple trauma and to investigate potential relationships between these cell levels and clinical parameters. The study cohort was composed of 14 patients with multiple trauma and 22 non-injured healthy controls (HCs). Circulating MAIT and NKT cell levels in the peripheral blood were measured by flow cytometry. The severity of injury was categorised according to the scoring systems, such as Acute Physiology and Chronic Health Evaluation (APACHE) II score, Simplified Acute Physiology Score (SAPS) II, and Injury Severity Score (ISS). Circulating MAIT and NKT cell numbers were significantly lower in multiple trauma patients than in HCs. Linear regression analysis showed that circulating MAIT cell numbers were significantly correlated with age, APACHE II, SAPS II, ISS category, hemoglobin, and platelet count. NKT cell numbers in the peripheral blood were found to be significantly correlated with APACHE II, SAPS II, and ISS category. This study shows numerical deficiencies of circulating MAIT cells and NKT cells in multiple trauma. In addition, these invariant T cell deficiencies were found to be associated with disease severity. These findings provide important information for predicting the prognosis of multiple trauma. © 2017 The Korean Academy of Medical Sciences.

Multiple-degree-of-freedom vehicle

DOEpatents

Borenstein, Johann

1995-01-01

A multi-degree-of-freedom vehicle employs a compliant linkage to accommodate the need for a variation in the distance between drive wheels or drive systems which are independently steerable and drivable. The subject vehicle is provided with rotary encodes to provide signals representative of the orientation of the steering pivot associated with each such drive wheel or system, and a linear encoder which issues a signal representative of the fluctuations in the distance between the drive elements. The wheels of the vehicle are steered and driven in response to the linear encoder signal, there being provided a controller system for minimizing the fluctuations in the distance. The controller system is a software implementation of a plurality of controllers, operating at the chassis level and at the vehicle level. A trajectory interpolator receives x-displacement, y-displacement, and .theta.-displacement signals and produces to the vehicle level controller trajectory signals corresponding to interpolated control signals. The x-displacement, y-displacement, and .theta.-displacement signals are received from a human operator, via a manipulable joy stick.

Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming.

PubMed

Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun

2015-01-01

The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Shang, Yu; Yu, Guoqiang, E-mail: guoqiang.yu@uky.edu

Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in homogenous tissues with arbitrary geometries for extraction of BFI (i.e., αD{sub B}). The purpose of this study is to extend the capability of the Nth-order linear algorithm for extracting BFI in heterogeneous tissues with arbitrary geometries. The previous linear algorithm was modified to extract BFIs in different typesmore » of tissues simultaneously through utilizing DCS data at multiple source-detector separations. We compared the proposed linear algorithm with the semi-infinite homogenous solution in a computer model of adult head with heterogeneous tissue layers of scalp, skull, cerebrospinal fluid, and brain. To test the capability of the linear algorithm for extracting relative changes of cerebral blood flow (rCBF) in deep brain, we assigned ten levels of αD{sub B} in the brain layer with a step decrement of 10% while maintaining αD{sub B} values constant in other layers. Simulation results demonstrate the accuracy (errors < 3%) of high-order (N ≥ 5) linear algorithm in extracting BFIs in different tissue layers and rCBF in deep brain. By contrast, the semi-infinite homogenous solution resulted in substantial errors in rCBF (34.5% ≤ errors ≤ 60.2%) and BFIs in different layers. The Nth-order linear model simplifies data analysis, thus allowing for online data processing and displaying. Future study will test this linear algorithm in heterogeneous tissues with different levels of blood flow variations and noises.« less

Advanced statistics: linear regression, part I: simple linear regression.

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Fast linear feature detection using multiple directional non-maximum suppression.

PubMed

Sun, C; Vallotton, P

2009-05-01

The capacity to detect linear features is central to image analysis, computer vision and pattern recognition and has practical applications in areas such as neurite outgrowth detection, retinal vessel extraction, skin hair removal, plant root analysis and road detection. Linear feature detection often represents the starting point for image segmentation and image interpretation. In this paper, we present a new algorithm for linear feature detection using multiple directional non-maximum suppression with symmetry checking and gap linking. Given its low computational complexity, the algorithm is very fast. We show in several examples that it performs very well in terms of both sensitivity and continuity of detected linear features.

Axonal loss in the multiple sclerosis spinal cord revisited.

PubMed

Petrova, Natalia; Carassiti, Daniele; Altmann, Daniel R; Baker, David; Schmierer, Klaus

2018-05-01

Preventing chronic disease deterioration is an unmet need in people with multiple sclerosis, where axonal loss is considered a key substrate of disability. Clinically, chronic multiple sclerosis often presents as progressive myelopathy. Spinal cord cross-sectional area (CSA) assessed using MRI predicts increasing disability and has, by inference, been proposed as an indirect index of axonal degeneration. However, the association between CSA and axonal loss, and their correlation with demyelination, have never been systematically investigated using human post mortem tissue. We extensively sampled spinal cords of seven women and six men with multiple sclerosis (mean disease duration= 29 years) and five healthy controls to quantify axonal density and its association with demyelination and CSA. 396 tissue blocks were embedded in paraffin and immuno-stained for myelin basic protein and phosphorylated neurofilaments. Measurements included total CSA, areas of (i) lateral cortico-spinal tracts, (ii) gray matter, (iii) white matter, (iv) demyelination, and the number of axons within the lateral cortico-spinal tracts. Linear mixed models were used to analyze relationships. In multiple sclerosis CSA reduction at cervical, thoracic and lumbar levels ranged between 19 and 24% with white (19-24%) and gray (17-21%) matter atrophy contributing equally across levels. Axonal density in multiple sclerosis was lower by 57-62% across all levels and affected all fibers regardless of diameter. Demyelination affected 24-48% of the gray matter, most extensively at the thoracic level, and 11-13% of the white matter, with no significant differences across levels. Disease duration was associated with reduced axonal density, however not with any area index. Significant association was detected between focal demyelination and decreased axonal density. In conclusion, over nearly 30 years multiple sclerosis reduces axonal density by 60% throughout the spinal cord. Spinal cord cross sectional area, reduced by about 20%, appears to be a poor predictor of axonal density. © 2017 The Authors. Brain Pathology published by John Wiley & Sons Ltd on behalf of International Society of Neuropathology.

Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

Combination free electron and gaseous laser

DOEpatents

Brau, Charles A.; Rockwood, Stephen D.; Stein, William E.

1980-01-01

A multiple laser having one or more gaseous laser stages and one or more free electron stages. Each of the free electron laser stages is sequentially pumped by a microwave linear accelerator. Subsequently, the electron beam is directed through a gaseous laser, in the preferred embodiment, and in an alternative embodiment, through a microwave accelerator to lower the energy level of the electron beam to pump one or more gaseous lasers. The combination laser provides high pulse repetition frequencies, on the order of 1 kHz or greater, high power capability, high efficiency, and tunability in the synchronous production of multiple beams of coherent optical radiation.

Circulating levels of perfluoroalkyl substances and prevalent diabetes in the elderly.

PubMed

Lind, Lars; Zethelius, Björn; Salihovic, Samira; van Bavel, Bert; Lind, P Monica

2014-03-01

Several environmental contaminants, such as polychlorinated biphenyls, dioxins, bisphenol A and phthalates, have been linked to diabetes. We therefore investigated whether other kinds of contaminants, perfluoroalkyl substances (PFAS), also called perfluorinated compounds (PFCs), are also associated with diabetes. The Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study investigated 1,016 men and women aged 70 years. Seven PFAS were detected in almost all participant sera by ultra-high performance liquid chromatograph/tandem mass spectrometry. Diabetes was defined as use of hypoglycaemic agents or fasting glucose >7.0 mmol/l. 114 people had diabetes. In the linear analysis, no significant relationships were seen between the seven PFAS and prevalent diabetes. However, inclusion of the quadratic terms of the PFAS revealed a significant non-linear relationship between perfluorononanoic acid (PFNA) and diabetes, even after adjusting for multiple confounders (OR 1.96, 95% CI 1.19, 3.22, p = 0.008 for the linear term and OR 1.25, 95% CI 1.08, 1.44, p = 0.002 for the quadratic term). Perfluorooctanoic acid (PFOA) also showed such a relationship (p = 0.01). PFOA was related to the proinsulin/insulin ratio (a marker of insulin secretion), but none of the PFAS was related to the HOMA-IR (a marker of insulin resistance) following adjustment for multiple confounders. PFNA was related to prevalent diabetes in a non-monotonic fashion in this cross-sectional study, supporting the view that this perfluoroalkyl substance might influence glucose metabolism in humans at the level of exposure seen in the general elderly population.

Understanding the Positive Role of Neighborhood Socioeconomic Advantage in Achievement: The Contribution of the Home, Child Care and School Environments

PubMed Central

Dupéré, Véronique; Leventhal, Tama; Crosnoe, Robert; Dion, Éric

2011-01-01

The goal of this study was to examine the mechanisms underlying associations between neighborhood socioeconomic advantage and children’s achievement trajectories between 54 months and 15 years old. Results of hierarchical linear growth models based on a diverse sample of 1,364 children indicate that neighborhood socioeconomic advantage was non-linearly associated with youths’ initial vocabulary and reading scores, such that the presence of educated, affluent professionals in the neighborhood had a favorable association with children’s achievement among those in less advantaged neighborhoods until it leveled off at moderate levels of advantage. A similar tendency was observed for math achievement. The quality of the home and child care environments as well as school advantage partially explained these associations. The findings suggest that multiple environments need to be considered simultaneously for understanding neighborhood-achievement links. PMID:20822235

SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

EPA Science Inventory

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...

Prediction system of hydroponic plant growth and development using algorithm Fuzzy Mamdani method

NASA Astrophysics Data System (ADS)

Sudana, I. Made; Purnawirawan, Okta; Arief, Ulfa Mediaty

2017-03-01

Hydroponics is a method of farming without soil. One of the Hydroponic plants is Watercress (Nasturtium Officinale). The development and growth process of hydroponic Watercress was influenced by levels of nutrients, acidity and temperature. The independent variables can be used as input variable system to predict the value level of plants growth and development. The prediction system is using Fuzzy Algorithm Mamdani method. This system was built to implement the function of Fuzzy Inference System (Fuzzy Inference System/FIS) as a part of the Fuzzy Logic Toolbox (FLT) by using MATLAB R2007b. FIS is a computing system that works on the principle of fuzzy reasoning which is similar to humans' reasoning. Basically FIS consists of four units which are fuzzification unit, fuzzy logic reasoning unit, base knowledge unit and defuzzification unit. In addition to know the effect of independent variables on the plants growth and development that can be visualized with the function diagram of FIS output surface that is shaped three-dimensional, and statistical tests based on the data from the prediction system using multiple linear regression method, which includes multiple linear regression analysis, T test, F test, the coefficient of determination and donations predictor that are calculated using SPSS (Statistical Product and Service Solutions) software applications.

Reverse genetics in high throughput: rapid generation of complete negative strand RNA virus cDNA clones and recombinant viruses thereof.

PubMed

Nolden, T; Pfaff, F; Nemitz, S; Freuling, C M; Höper, D; Müller, T; Finke, Stefan

2016-04-05

Reverse genetics approaches are indispensable tools for proof of concepts in virus replication and pathogenesis. For negative strand RNA viruses (NSVs) the limited number of infectious cDNA clones represents a bottleneck as clones are often generated from cell culture adapted or attenuated viruses, with limited potential for pathogenesis research. We developed a system in which cDNA copies of complete NSV genomes were directly cloned into reverse genetics vectors by linear-to-linear RedE/T recombination. Rapid cloning of multiple rabies virus (RABV) full length genomes and identification of clones identical to field virus consensus sequence confirmed the approache's reliability. Recombinant viruses were recovered from field virus cDNA clones. Similar growth kinetics of parental and recombinant viruses, preservation of field virus characters in cell type specific replication and virulence in the mouse model were confirmed. Reduced titers after reporter gene insertion indicated that the low level of field virus replication is affected by gene insertions. The flexibility of the strategy was demonstrated by cloning multiple copies of an orthobunyavirus L genome segment. This important step in reverse genetics technology development opens novel avenues for the analysis of virus variability combined with phenotypical characterization of recombinant viruses at a clonal level.

The set of triple-resonance sequences with a multiple quantum coherence evolution period

NASA Astrophysics Data System (ADS)

Koźmiński, Wiktor; Zhukov, Igor

2004-12-01

The new pulse sequence building block that relies on evolution of heteronuclear multiple quantum coherences is proposed. The particular chemical shifts are obtained in multiple quadrature, using linear combinations of frequencies taken from spectra measured at different quantum levels. The pulse sequences designed in this way consist of small number of RF-pulses, are as short as possible, and could be applied for determination of coupling constants. The examples presented involve 2D correlations H NCO, H NCA, H N(CO) CA, and H(N) COCA via heteronuclear zero and double coherences, as well as 2D H NCOCA technique with simultaneous evolution of triple and three distinct single quantum coherences. Applications of the new sequences are presented for 13C, 15N-labeled ubiquitin.

Optimal space communications techniques. [using digital and phase locked systems for signal processing

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1974-01-01

Digital multiplication of two waveforms using delta modulation (DM) is discussed. It is shown that while conventional multiplication of two N bit words requires N2 complexity, multiplication using DM requires complexity which increases linearly with N. Bounds on the signal-to-quantization noise ratio (SNR) resulting from this multiplication are determined and compared with the SNR obtained using standard multiplication techniques. The phase locked loop (PLL) system, consisting of a phase detector, voltage controlled oscillator, and a linear loop filter, is discussed in terms of its design and system advantages. Areas requiring further research are identified.

Dynamic characteristics of a multi-wavelength Brillouin-Raman fiber laser assisted by multiple four-wave mixing processes in a ring cavity

NASA Astrophysics Data System (ADS)

Shirazi, M. R.; Mohamed Taib, J.; De La Rue, R. M.; Harun, S. W.; Ahmad, H.

2015-03-01

Dynamic characteristics of a multi-wavelength Brillouin-Raman fiber laser (MBRFL) assisted by four-wave mixing have been investigated through the development of Stokes and anti-Stokes lines under different combinations of Brillouin and Raman pump power levels and different Raman pumping schemes in a ring cavity. For a Stokes line of order higher than three, the threshold power was less than the saturation power of its last-order Stokes line. By increasing the Brillouin pump power, the nth order anti-Stokes and the (n+4)th order Stokes power levels were unexpectedly increased almost the same before the Stokes line threshold power. It was also found out that the SBS threshold reduction (SBSTR) depended linearly on the gain factor for the 1st and 2nd Stokes lines, as the first set. This relation for the 3rd and 4th Stokes lines as the second set, however, was almost linear with the same slope before SBSTR -6 dB, then, it approached to the linear relation in the first set when the gain factor was increased to 50 dB. Therefore, the threshold power levels of Stokes lines for a given Raman gain can be readily estimated only by knowing the threshold power levels in which there is no Raman amplification.

Statistical analysis of water-level, springflow, and streamflow data for the Edwards Aquifer in south-central Texas

USGS Publications Warehouse

Puente, Celso

1976-01-01

Water-level, springflow, and streamflow data were used to develop simple and multiple linear-regression equations for use in estimating water levels in wells and the flow of three major springs in the Edwards aquifer in the eastern San Antonio area. The equations provide daily, monthly, and annual estimates that compare very favorably with observed data. Analyses of geologic and hydrologic data indicate that the water discharged by the major springs is supplied primarily by regional underflow from the west and southwest and by local recharge in the infiltration area in northern Bexar, Comal, and Hays Counties.

The association of reproductive and lifestyle factors with a score of multiple endogenous hormones

PubMed Central

Shafrir, Amy L.; Zhang, Xuehong; Poole, Elizabeth M.; Hankinson, Susan E.; Tworoger, Shelley S.

2014-01-01

Introduction We recently reported that high levels of multiple sex and growth hormones were associated with increased postmenopausal breast cancer risk. Limited research has explored the relationship between reproductive, anthropometric, and lifestyle factors and levels of multiple hormones simultaneously. Methods This cross-sectional analysis included 738 postmenopausal Nurses' Health Study participants who were controls in a breast cancer nested case-control study and had measured levels of estrone, estradiol, estrone sulfate, testosterone, androstenedione, dehydroepiandrosterone sulfate, prolactin and sex hormone binding globulin (SHBG). A score was created by summing the number of hormones a woman had above (below for SHBG) each hormone's age-adjusted geometric mean. The association between lifestyle, anthropometric, and reproductive exposures and the score was assessed using generalized linear models. Results The hormone score ranged from 0 to 8 with a mean of 4.0 (standard deviation=2.2). Body mass index (BMI) and alcohol consumption at blood draw were positively associated with the hormone score: a 5 unit increase in BMI was associated with a 0.79 (95%CI: 0.63, 0.95) unit increase in the score (p<0.0001) and each 15 grams/day increase in alcohol consumption was associated with a 0.41 (95%CI: 0.18, 0.63) unit increase in the score (p=0.0004). Family history of breast cancer, age at menarche, and physical activity were not associated with the score. Conclusions Reproductive breast cancer risk factors were not associated with elevated levels of multiple endogenous hormones, whereas anthropometric and lifestyle factors, particularly BMI and alcohol consumption, tended to be associated with higher levels of multiple hormones. PMID:25048255

The association of reproductive and lifestyle factors with a score of multiple endogenous hormones.

PubMed

Shafrir, Amy L; Zhang, Xuehong; Poole, Elizabeth M; Hankinson, Susan E; Tworoger, Shelley S

2014-10-01

We recently reported that high levels of multiple sex and growth hormones were associated with increased postmenopausal breast cancer risk. Limited research has explored the relationship between reproductive, anthropometric, and lifestyle factors and levels of multiple hormones simultaneously. This cross-sectional analysis included 738 postmenopausal Nurses' Health Study participants who were controls in a breast cancer nested case-control study and had measured levels of estrone, estradiol, estrone sulfate, testosterone, androstenedione, dehydroepiandrosterone sulfate, prolactin, and sex hormone binding globulin (SHBG). A score was created by summing the number of hormones a woman had above (below for SHBG) each hormone's age-adjusted geometric mean. The association between lifestyle, anthropometric, and reproductive exposures and the score was assessed using generalized linear models. The hormone score ranged from 0 to 8 with a mean of 4.0 (standard deviation = 2.2). Body mass index (BMI) and alcohol consumption at blood draw were positively associated with the hormone score: a 5 unit increase in BMI was associated with a 0.79 (95%CI: 0.63, 0.95) unit increase in the score (p < 0.0001) and each 15 g/day increase in alcohol consumption was associated with a 0.41 (95%CI: 0.18, 0.63) unit increase in the score (p = 0.0004). Family history of breast cancer, age at menarche, and physical activity were not associated with the score. Reproductive breast cancer risk factors were not associated with elevated levels of multiple endogenous hormones, whereas anthropometric and lifestyle factors, particularly BMI and alcohol consumption, tended to be associated with higher levels of multiple hormones.

Utilizing the Zero-One Linear Programming Constraints to Draw Multiple Sets of Matched Samples from a Non-Treatment Population as Control Groups for the Quasi-Experimental Design

ERIC Educational Resources Information Center

Li, Yuan H.; Yang, Yu N.; Tompkins, Leroy J.; Modarresi, Shahpar

2005-01-01

The statistical technique, "Zero-One Linear Programming," that has successfully been used to create multiple tests with similar characteristics (e.g., item difficulties, test information and test specifications) in the area of educational measurement, was deemed to be a suitable method for creating multiple sets of matched samples to be…

Glucose biosensors with enzyme entrapped in polymer coating.

PubMed

Yang, S; Atanasov, P; Wilkins, E

1995-01-01

The pursuit of reliable biosensors for measuring glucose levels has been ongoing for decades. Their importance lies partly in the development of the implantable artificial pancrease, which can be used to deliver insulin to diabetics without the need to test glucose levels externally, with automatic delivery based on physiologic demand. Glucose sensors can also be used in short-term monitoring of glucose levels in hospitals and clinical laboratories. Three types of glucose biosensors were studied. All were based on a two-electrode system: an insulated platinum wire as a hydrogen peroxide electrode, and a silver wire twisted around the platinum wire as both a reference and a counter electrode. Each was coated with the enzyme glucose oxidase entrapped in a polymer matrix of cellulose acetate (CA) or poly 2-hydroxyethyl methacrylate (HEMA), then dip-coated by an additional polymer coating of polyvinylchloride (PVC), polyurethane (PU), or HEMA. The experiments were designed mainly to study the effectiveness of polymer coatings as diffusion-limiting membranes. The effect of each coating on the linear response to glucose concentration was examined. It was shown that additional (multiple) coatings can increase the linearity of the sensor response. The best results were obtained when the sensor was PVC-dip-coated three times. This preparation had a linear response up to 600 mg/DL glucose concentration. The sensors coated with PU and HEMA have linearity up to 280 and 240 mg/DL glucose concentrations, respectively. It was also shown that the coatings reduce interference from certain body chemicals.

Determinants of plasma NT-pro-BNP levels in patients with atrial fibrillation and preserved left ventricular ejection fraction.

PubMed

Letsas, Konstantinos P; Filippatos, Gerasimos S; Pappas, Loukas K; Mihas, Constantinos C; Markou, Virginia; Alexanian, Ioannis P; Efremidis, Michalis; Sideris, Antonios; Maisel, Alan S; Kardaras, Fotios

2009-02-01

The present study aimed to investigate the clinical and echocardiographic determinants of plasma NT-pro-BNP levels in patients with atrial fibrillation (AF) and preserved left ventricular ejection fraction (LVEF). NT-pro-BNP levels were measured in 45 patients with paroxysmal AF, 41 patients with permanent AF and 48 controls. NT-pro-BNP levels were found significantly elevated in patients with paroxysmal (215+/-815 pg/ml) and permanent AF (1,086+/-835 pg/ml) in relation to control population (86.3+/-77.9 pg/ml) (P<0.001). According to the univariate linear regression analysis, age, hypertension, beta-blocker use, left atrial diameter (LAD), LVEF and AF status (paroxysmal or permanent or both) were significantly associated with NT-pro-BNP levels (P<0.05). In multiple linear regression analysis, LVEF (B coefficient: -53.030; CI: -95.738 to -10.322; P: 0.015) and LAD (B coefficient: 285.858; CI: 23.731-547.986; P: 0.033) were significant and independent determinants of NT-pro-BNP levels. Plasma NT-pro-BNP levels were significantly higher in patients with paroxysmal and permanent AF compared to those with sinus rhythm in the setting of preserved left ventricular systolic function. LVEF and LAD were independent predictors of NT-pro-BNP levels.

Depression-related differences in lean body mass distribution from National Health and Nutrition Examination Survey 2005-2006.

PubMed

Li, Ying; Meng, Lu; Li, Yue; Sato, Yasuto

2014-03-01

Although the association between depression and body composition has been widely discussed, the effects of depression on lean body mass (LBM) are unclear. The present study aimed to investigate the association of depression with LBM. The study included 2406 participants aged 18-69 years. The sex and body mass index (BMI) stratified analysis of covariance was performed to compare total LBM and percentage LBM (%LBM) in subjects with different depression score levels. Multiple linear regression analysis was conducted to estimate the association between depression score and serum albumin level. An analysis of covariance stratified by sex showed that participants with moderate-to-severe depression had significantly decreased total LBM and total and regional %LBM in men, except for total LBM and percentage gynoid LBM, which was observed in women. In the BMI stratified analysis of covariance, depression was significantly associated with decreased total and regional %LBM and with increased total and regional percentage fat body mass. In people with BMI≥25kg/m(2), the associations between depression or depressive syndrome and LBM, and total and regional %LBM are stronger compared to those with BMI<25kg/m(2). Multiple linear regression analysis showed that depression score was significantly negatively associated with serum albumin level. This is a cross-sectional study based on a general population, some information about clinical diagnosis and medication use is not available. Depression had a significant negative association with LBM and serum albumin level. Copyright © 2014 Elsevier B.V. All rights reserved.

The relationship between vitronectin and hepatic insulin resistance in type 2 diabetes mellitus.

PubMed

Cao, Yan; Li, Xinyu; Lu, Chong; Zhan, Xiaorong

2018-05-18

The World Health Organization (WHO) estimates that approximately 300 million people will suffer from diabetes mellitus by 2025. Type 2 diabetes mellitus (T2DM) is much more prevalent. T2DM comprises approximately 90% of diabetes mellitus cases, and it is caused by a combination of insulin resistance and inadequate compensatory insulin secretory response. In this study, we aimed to compare the plasma vitronectin (VN) levels between patients with T2DM and insulin resistance (IR) and healthy controls. Seventy patients with IR and 70 age- and body mass index (BMI)-matched healthy controls were included in the study. The insulin, Waist-to-Hip Ratio (WHR), C-peptide (CP) and VN levels of all participants were examined. The homeostasis model of assessment for insulin resistence index (HOMA-IR (CP)) formula was used to calculate insulin resistance. The levels of BMI, fasting plasma gluose (FPG), 2-hour postprandial glucose (2hPG), glycated hemoglobins (HbA1c), and HOMA-IR (CP) were significantly elevated in case group compared with controls. VN was found to be significantly decreased in case group. (VN Mean (Std): 8.55 (2.92) versus 12.88 (1.26) ng/mL p < 0.001). Multiple linear regression analysis was performed. This model explained 43.42% of the total variability of VN. Multiple linear regression analysis showed that HOMA-IR (CP) and age independently predicted VN levels. The VN may be a candidate target for the appraisal of hepatic insulin resistance in patients with T2DM.

An approach to the development of numerical algorithms for first order linear hyperbolic systems in multiple space dimensions: The constant coefficient case

NASA Technical Reports Server (NTRS)

Goodrich, John W.

1995-01-01

Two methods for developing high order single step explicit algorithms on symmetric stencils with data on only one time level are presented. Examples are given for the convection and linearized Euler equations with up to the eighth order accuracy in both space and time in one space dimension, and up to the sixth in two space dimensions. The method of characteristics is generalized to nondiagonalizable hyperbolic systems by using exact local polynominal solutions of the system, and the resulting exact propagator methods automatically incorporate the correct multidimensional wave propagation dynamics. Multivariate Taylor or Cauchy-Kowaleskaya expansions are also used to develop algorithms. Both of these methods can be applied to obtain algorithms of arbitrarily high order for hyperbolic systems in multiple space dimensions. Cross derivatives are included in the local approximations used to develop the algorithms in this paper in order to obtain high order accuracy, and improved isotropy and stability. Efficiency in meeting global error bounds is an important criterion for evaluating algorithms, and the higher order algorithms are shown to be up to several orders of magnitude more efficient even though they are more complex. Stable high order boundary conditions for the linearized Euler equations are developed in one space dimension, and demonstrated in two space dimensions.

Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts.

PubMed

Howe, Laura D; Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S; Barros, Aluísio Jd; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A

2016-10-01

Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. © The Author(s) 2013.

Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts

PubMed Central

Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S.; Barros, Aluísio JD; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A

2013-01-01

Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. PMID:24108269

Density dependence governs when population responses to multiple stressors are magnified or mitigated.

PubMed

Hodgson, Emma E; Essington, Timothy E; Halpern, Benjamin S

2017-10-01

Population endangerment typically arises from multiple, potentially interacting anthropogenic stressors. Extensive research has investigated the consequences of multiple stressors on organisms, frequently focusing on individual life stages. Less is known about population-level consequences of exposure to multiple stressors, especially when exposure varies through life. We provide the first theoretical basis for identifying species at risk of magnified effects from multiple stressors across life history. By applying a population modeling framework, we reveal conditions under which population responses from stressors applied to distinct life stages are either magnified (synergistic) or mitigated. We find that magnification or mitigation critically depends on the shape of density dependence, but not the life stage in which it occurs. Stressors are always magnified when density dependence is linear or concave, and magnified or mitigated when it is convex. Using Bayesian numerical methods, we estimated the shape of density dependence for eight species across diverse taxa, finding support for all three shapes. © 2017 by the Ecological Society of America.

School league tables: a new population based predictor of dental restorative treatment need.

PubMed

Crowley, Evelyn; O'Brien, Graham; Marcenes, Wagner

2003-06-01

To test whether dental restorative treatment need was related to the school league tables and level of social deprivation of the school ward. An ecological study using clinical data aggregated at school level, collected in the school dental screening examinations (1996-97), National Census (1991) and the results of the UK school league tables--Key Stage 2 SATs (1996-97). State primary schools in the Greenwich District of SE London, UK (1996-97). 12,854 pupils (6-11 years of age) in 62 schools. The percentage of 6 to 11 year old pupils per school requiring dental restorative treatment. Deprivation as measured by the overall Jarman Under Privileged Area Index (UPA) of the school ward was not associated with dental restorative treatment need (p > 0.05). Only two components of the Jarman Index, level of unemployment and the number of lone parent families in the school ward were found to be significantly associated with dental restorative treatment need (p < 0.05). Results of stepwise multiple linear regression analysis showed that the association with the school league table results in all three subjects, English, Mathematics and Science remained statistically significant after adjusting for levels of unemployment and single parents. Results of multiple linear regression analysis showed that a high level of dental restorative treatment need was significantly associated with poor school league table results in English, Mathematics and Science (p < 0.05) after adjusting for the overall Jarman score of the school ward. A separate analysis for the 11-year-old pupils aggregated by school (n = 46 schools) gave similar results. Aggregate measures of academic achievement may be a potential indicator of dental restorative treatment need.

Intelligent query by humming system based on score level fusion of multiple classifiers

NASA Astrophysics Data System (ADS)

Pyo Nam, Gi; Thu Trang Luong, Thi; Ha Nam, Hyun; Ryoung Park, Kang; Park, Sung-Joo

2011-12-01

Recently, the necessity for content-based music retrieval that can return results even if a user does not know information such as the title or singer has increased. Query-by-humming (QBH) systems have been introduced to address this need, as they allow the user to simply hum snatches of the tune to find the right song. Even though there have been many studies on QBH, few have combined multiple classifiers based on various fusion methods. Here we propose a new QBH system based on the score level fusion of multiple classifiers. This research is novel in the following three respects: three local classifiers [quantized binary (QB) code-based linear scaling (LS), pitch-based dynamic time warping (DTW), and LS] are employed; local maximum and minimum point-based LS and pitch distribution feature-based LS are used as global classifiers; and the combination of local and global classifiers based on the score level fusion by the PRODUCT rule is used to achieve enhanced matching accuracy. Experimental results with the 2006 MIREX QBSH and 2009 MIR-QBSH corpus databases show that the performance of the proposed method is better than that of single classifier and other fusion methods.

Intimate relationship quality, self-concept and illness acceptance in those with multiple sclerosis.

PubMed

Wright, Thomas M; Kiropoulos, Litza A

2017-02-01

Lower levels of Intimate Relationship Quality (IRQ) have been found in those with Multiple Sclerosis (MS) compared to the general population. This study examined an MS sample to see whether IRQ was positively associated with self-concept, whether IRQ was positively associated with MS illness acceptance and whether IRQ was predicted by self-concept and illness acceptance. In this cross-sectional study, 115 participants with MS who were in an intimate relationship completed an online survey advertised on MS related websites. The survey assessed demographic variables, MS illness variables and levels of IRQ, self-concept and illness acceptance. Results revealed that IRQ was significantly positively associated with self-concept and with illness acceptance. Multiple hierarchical linear regression analysis revealed that, after controlling for illness duration and level of disability, self-concept significantly predicted IRQ but illness acceptance did not significantly predict IRQ. This study addressed several gaps and methodological flaws in the literature and was the first known to assess predictors of IRQ in those with MS. The results suggest that self-concept could be a potential target for individual and couple psychological interventions to improve IRQ and contribute to improved outcomes for those with MS.

Transmethylation of homocysteine to methionine: efficiency in the rat and chick.

PubMed

Baker, D H; Czarnecki, G L

1985-10-01

Experiments were conducted with young chicks and rats to quantify the efficacy of L-homocysteine as a methionine precursor. Linear growth responses were obtained to both L-methionine and L-homocysteine when added to a methionine-deficient intact-protein diet containing a plethora of cystine. Slope-ratio multiple regression methodology indicated L-homocysteine to be 64.5% as efficacious as L-methionine in rats and 62.5% as efficacious in chicks. Plasma-free methionine also increased linearly as graded levels of either L-methionine or L-homocysteine were added to the diet of rats. At higher dosages of L-homocysteine, betaine, but not choline, showed some efficacy in enhancing the conversion of homocysteine to methionine. In the linear response surface of the growth curve, however, supplemental betaine was without effect on L-homocysteine bioefficacy, as was also the case for supplemental sarcosine and N5-methyltetrahydrofolic acid.

Theory of chromatic noise masking applied to testing linearity of S-cone detection mechanisms.

PubMed

Giulianini, Franco; Eskew, Rhea T

2007-09-01

A method for testing the linearity of cone combination of chromatic detection mechanisms is applied to S-cone detection. This approach uses the concept of mechanism noise, the noise as seen by a postreceptoral neural mechanism, to represent the effects of superposing chromatic noise components in elevating thresholds and leads to a parameter-free prediction for a linear mechanism. The method also provides a test for the presence of multiple linear detectors and off-axis looking. No evidence for multiple linear mechanisms was found when using either S-cone increment or decrement tests. The results for both S-cone test polarities demonstrate that these mechanisms combine their cone inputs nonlinearly.

White Blood Cells, Neutrophils, and Reactive Oxygen Metabolites among Asymptomatic Subjects.

PubMed

Kotani, Kazuhiko; Sakane, Naoki

2012-06-01

Chronic inflammation and oxidative stress are associated with health and the disease status. The objective of the present study was to investigate the association among white blood cell (WBC) counts, neutrophil counts as a WBC subpopulation, and diacron reactive oxygen metabolites (d-ROMs) levels in an asymptomatic population. The clinical data, including general cardiovascular risk variables and high-sensitivity C-reactive protein (hs-CRP), were collected from 100 female subjects (mean age, 62 years) in outpatient clinics. The correlation of the d-ROMs with hs-CRP, WBC, and neutrophil counts was examined. The mean/median levels were WBC counts 5.9 × 10(9)/L, neutrophil counts 3.6 × 10(9)/L, hs-CRP 0.06 mg/dL, and d-ROMs 359 CURR U. A simple correlation analysis showed a significant positive correlation of the d-ROMs with the WBC counts, neutrophil counts, or hs-CRP levels. The correlation between d-ROMs and neutrophil counts (β = 0.22, P < 0.05), as well as that between d-ROMs and hs-CRP (β = 0.28, P < 0.01), remained significant and independent in a multiple linear regression analysis adjusted for other variables. A multiple linear regression analysis showed that WBC counts had only a positive correlation tendency to the d-ROMs. Neutrophils may be slightly but more involved in the oxidative stress status, as assessed by d-ROMs, in comparison to the overall WBC. Further studies are needed to clarify the biologic mechanism(s) of the observed relationship.

Comparison of Mental Toughness and Power Test Performances in High-Level Kickboxers by Competitive Success.

PubMed

Slimani, Maamer; Miarka, Bianca; Briki, Walid; Cheour, Foued

2016-06-01

Kickboxing is a high-intensity intermittent striking combat sport, which is characterized by complex skills and tactical key actions with short duration. The present study compared and verified the relationship between mental toughness (MT), countermovement jump (CMJ) and medicine ball throw (MBT) power tests by outcomes of high-level kickboxers during National Championship. Thirty two high-level male kickboxers (winner = 16 and loser = 16: 21.2 ± 3.1 years, 1.73 ± 0.07 m, and 70.2 ± 9.4 kg) were analyzed using the CMJ, MBT tests and sports mental toughness questionnaire (SMTQ; based in confidence, constancy and control subscales), before the fights of the 2015 national championship (16 bouts). In statistical analysis, Mann-Withney test and a multiple linear regression were used to compare groups and to observe relationships, respectively, P ≤ 0.05. The present results showed significant differences between losers vs. winners, respectively, of total MT (7(7;8) vs. 11(10.2;11), confidence (3(3;3) vs. 4(4;4)), constancy (2(2;2) vs. 3(3;3)), control (2(2;3) vs. 4(4;4)) subscales and MBT (4.1(4;4.3) vs. 4.6(4.4;4.8)). The multiple linear regression showed a strong associations between MT results and outcome (r = 0.89), MBT (r = 0.84) and CMJ (r = 0.73). The findings suggest that MT will be more predictive of performance in those sports and in the outcome of competition.

An analytical approach to reduce between-plate variation in multiplex assays that measure antibodies to Plasmodium falciparum antigens.

PubMed

Fang, Rui; Wey, Andrew; Bobbili, Naveen K; Leke, Rose F G; Taylor, Diane Wallace; Chen, John J

2017-07-17

Antibodies play an important role in immunity to malaria. Recent studies show that antibodies to multiple antigens, as well as, the overall breadth of the response are associated with protection from malaria. Yet, the variability and reliability of antibody measurements against a combination of malarial antigens using multiplex assays have not been well characterized. A normalization procedure for reducing between-plate variation using replicates of pooled positive and negative controls was investigated. Sixty test samples (30 from malaria-positive and 30 malaria-negative individuals), together with five pooled positive-controls and two pooled negative-controls, were screened for antibody levels to 9 malarial antigens, including merozoite antigens (AMA1, EBA175, MSP1, MSP2, MSP3, MSP11, Pf41), sporozoite CSP, and pregnancy-associated VAR2CSA. The antibody levels were measured in triplicate on each of 3 plates, and the experiments were replicated on two different days by the same technician. The performance of the proposed normalization procedure was evaluated with the pooled controls for the test samples on both the linear and natural-log scales. Compared with data on the linear scale, the natural-log transformed data were less skewed and reduced the mean-variance relationship. The proposed normalization procedure using pooled controls on the natural-log scale significantly reduced between-plate variation. For malaria-related research that measure antibodies to multiple antigens with multiplex assays, the natural-log transformation is recommended for data analysis and use of the normalization procedure with multiple pooled controls can improve the precision of antibody measurements.

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels.

PubMed

Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J

2017-05-01

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.

INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

EPA Science Inventory

Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...

The impact of professional identity on role stress in nursing students: A cross-sectional study.

PubMed

Sun, Li; Gao, Ying; Yang, Juan; Zang, Xiao-Ying; Wang, Yao-Gang

2016-11-01

As newcomers to the clinical workplace, nursing students will encounter a high degree of role stress, which is an important predictor of burnout and engagement. Professional identity is theorised to be a key factor in providing high-quality care to improve patient outcomes and is thought to mediate the negative effects of a high-stress workplace and improve clinical performance and job retention. To investigate the level of nursing students' professional identity and role stress at the end of the first sub-internship, and to explore the impact of the nursing students' professional identity and other characteristics on role stress. A cross-sectional study. Three nursing schools in China. Nursing students after a 6-month sub-internship in a general hospital (n=474). The Role Stress Scale (score range: 12-60) and the Professional Identity Questionnaire for Nursing students (score range: 17-85) were used to investigate the levels of nursing students' role stress and professional identity. Higher scores indicated higher levels of role stress and professional identity. Basic demographic information about the nursing students was collected. The Pearson correlation, point-biserial correlation and multiple linear regression analysis were used to analyse the data. The mean total scores of the Role Stress Scale and Professional Identity Questionnaire for Nursing Students were 34.04 (SD=6.57) and 57.63 (SD=9.63), respectively. In the bivariate analyses, the following independent variables were found to be significantly associated with the total score of the Role Stress Scale: the total score of the Professional Identity Questionnaire for Nursing Students (r=-0.295, p<0.01), age (r=0.145, p<0.01), whether student was an only child or not (r=-0.114, p<0.05), education level (r=0.295, p<0.01) and whether student had experience in community organisations or not (r=0.151, p<0.01). In the multiple linear regression analysis, the total score of the Professional Identity Questionnaire for Nursing Students (standardised coefficient Beta: -0.260, p<0.001), education level (standardised coefficient Beta: 0.212, p<0.001) and whether or not student had experience in community organisations (standardised coefficient Beta: 0.107, p<0.016) were the factors significantly associated with the total score of the Role Stress Scale. The multiple linear regression model explained 18.2% (adjusted R 2 scores 16.5%) of the Role Stress Scale scores variance. The nursing students' level of role stress at the end of the first sub-internship was high. The students with higher professional identity values had lower role stress levels. Compared with other personal characteristics, professional identity and education level had the strongest impact on the nursing students' level of role stress. This is a new perspective that shows that developing and improving professional identity may prove helpful for nursing students in managing role stress. Copyright © 2016 Elsevier Ltd. All rights reserved.

Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method.

PubMed

Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza

2015-11-18

Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available.

Impact of divorce on the quality of life in school-age children.

PubMed

Eymann, Alfredo; Busaniche, Julio; Llera, Julián; De Cunto, Carmen; Wahren, Carlos

2009-01-01

To assess psychosocial quality of life in school-age children of divorced parents. A cross-sectional survey was conducted at the pediatric outpatient clinic of a community hospital. Children 5 to 12 years old from married families and divorced families were included. Child quality of life was assessed through maternal reports using a Child Health Questionnaire-Parent Form 50. A multiple linear regression model was constructed including clinically relevant variables significant on univariate analysis (beta coefficient and 95%CI). Three hundred and thirty families were invited to participate and 313 completed the questionnaire. Univariate analysis showed that quality of life was significantly associated with parental separation, child sex, time spent with the father, standard of living, and maternal education. In a multiple linear regression model, quality of life scores decreased in boys -4.5 (-6.8 to -2.3) and increased for time spent with the father 0.09 (0.01 to 0.2). In divorced families, multiple linear regression showed that quality of life scores increased when parents had separated by mutual agreement 6.1 (2.7 to 9.4), when the mother had university level education 5.9 (1.7 to 10.1) and for each year elapsed since separation 0.6 (0.2 to 1.1), whereas scores decreased in boys -5.4 (-9.5 to -1.3) and for each one-year increment of maternal age -0.4 (-0.7 to -0.05). Children's psychosocial quality of life was affected by divorce. The Child Health Questionnaire can be useful to detect a decline in the psychosocial quality of life.

Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method

PubMed Central

Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza

2016-01-01

Introduction: Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. Methods: This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. Results: From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). Conclusion: This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available. PMID:26925889

Ranking Forestry Investments With Parametric Linear Programming

Treesearch

Paul A. Murphy

1976-01-01

Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.

Serum bilirubin levels are positively associated with glycemic variability in women with type 2 diabetes.

PubMed

Kim, Lee Kyung; Roh, Eun; Kim, Min Joo; Kim, Min Kyeong; Park, Kyeong Seon; Kwak, Soo Heon; Cho, Young Min; Park, Kyong Soo; Jang, Hak Chul; Jung, Hye Seung

2016-11-01

Glycemic variability is known to induce oxidative stress. We investigated the relationships between glycemic variability and serum bilirubin levels, an endogenous anti-oxidant, in patients with diabetes. A cross-sectional study was carried out with 77 patients with type 2 diabetes who had been recruited to two clinical studies from 2008 to 2014. There were no participants with diseases of the pancreas, liver, biliary tract and chronic renal insufficiency. Glycemic variation was calculated by a continuous glucose monitoring system, and correlation analyses were carried out to evaluate their association with bilirubin levels. Multiple linear regression was carried out to identify independent factors influencing bilirubin levels and glycemic variation. Among the participants, 42.3% were men. The mean (standard deviation) age was 61.5 years (10.4 years), body mass index was 24.2 kg/m 2 (2.8 kg/m 2 ), diabetes duration was 17.7 years (9.5 years), hemoglobin A 1c was 60.7 mmol/mol (7.1 mmol/mol; 7.7 [0.7]%) and bilirubin was 11.8 μmol/L (4.10 μmol/L). Serum bilirubin levels were not different according to age, body mass index and hemoglobin A 1c . However, the mean amplitude of glucose excursion was positively associated with bilirubin levels in women (r = 0.588, P < 0.001). After adjustment with duration of diabetes, serum albumin, liver enzymes, and mean glucose, the correlation between bilirubin and mean amplitude of glucose excursion remained significant (r = 0.566, P < 0.001). Multiple linear regression analyses showed that bilirubin was an independent determinant for the mean amplitude of glucose excursion in women. 1,5-Anhydroglucitol was also associated with bilirubin levels in women. Bilirubin level within the physiological range might be an independent predictor for glycemic variability in women with type 2 diabetes. © 2016 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

Consumption of non-cow's milk beverages and serum vitamin D levels in early childhood.

PubMed

Lee, Grace J; Birken, Catherine S; Parkin, Patricia C; Lebovic, Gerald; Chen, Yang; L'Abbé, Mary R; Maguire, Jonathon L

2014-11-18

Vitamin D fortification of non-cow's milk beverages is voluntary in North America. The effect of consuming non-cow's milk beverages on serum 25-hydroxyvitamin D levels in children is unclear. We studied the association between non-cow's milk consumption and 25-hydroxyvitamin D levels in healthy preschool-aged children. We also explored whether cow's milk consumption modified this association and analyzed the association between daily non-cow's milk and cow's milk consumption. In this cross-sectional study, we recruited children 1-6 years of age attending routinely scheduled well-child visits. Survey responses, and anthropometric and laboratory measurements were collected. The association between non-cow's milk consumption and 25-hydroxyvitamin D levels was tested using multiple linear regression and logistic regression. Cow's milk consumption was explored as an effect modifier using an interaction term. The association between daily intake of non-cow's milk and cow's milk was explored using multiple linear regression. A total of 2831 children were included. The interaction between non-cow's milk and cow's milk consumption was statistically significant (p = 0.03). Drinking non-cow's milk beverages was associated with a 4.2-nmol/L decrease in 25-hydroxyvitamin D level per 250-mL cup consumed among children who also drank cow's milk (p = 0.008). Children who drank only non-cow's milk were at higher risk of having a 25-hydroxyvitamin D level below 50 nmol/L than children who drank only cow's milk (odds ratio 2.7, 95% confidence interval 1.6 to 4.7). Consumption of non-cow's milk beverages was associated with decreased serum 25-hydroxyvitamin D levels in early childhood. This association was modified by cow's milk consumption, which suggests a trade-off between consumption of cow's milk fortified with higher levels of vitamin D and non-cow's milk with lower vitamin D content. © 2014 Canadian Medical Association or its licensors.

Writing and compiling code into biochemistry.

PubMed

Shea, Adam; Fett, Brian; Riedel, Marc D; Parhi, Keshab

2010-01-01

This paper presents a methodology for translating iterative arithmetic computation, specified as high-level programming constructs, into biochemical reactions. From an input/output specification, we generate biochemical reactions that produce output quantities of proteins as a function of input quantities performing operations such as addition, subtraction, and scalar multiplication. Iterative constructs such as "while" loops and "for" loops are implemented by transferring quantities between protein types, based on a clocking mechanism. Synthesis first is performed at a conceptual level, in terms of abstract biochemical reactions - a task analogous to high-level program compilation. Then the results are mapped onto specific biochemical reactions selected from libraries - a task analogous to machine language compilation. We demonstrate our approach through the compilation of a variety of standard iterative functions: multiplication, exponentiation, discrete logarithms, raising to a power, and linear transforms on time series. The designs are validated through transient stochastic simulation of the chemical kinetics. We are exploring DNA-based computation via strand displacement as a possible experimental chassis.

Association between injury pattern of patients with multiple injuries and circulating levels of soluble tumor necrosis factor receptors, interleukin-6 and interleukin-10, and polymorphonuclear neutrophil elastase.

PubMed

Hensler, Thorsten; Sauerland, Stefan; Bouillon, Bertil; Raum, Marcus; Rixen, Dieter; Helling, Hanns-J; Andermahr, Jonas; Neugebauer, Edmund A M

2002-05-01

Our knowledge about the bidirectional interactions between brain and whole organism after trauma is still limited. It was the purpose of this prospective clinical study to determine the influence of severe head trauma (SHT) as well as trauma in different anatomic injury regions on posttraumatic inflammatory mediator levels from patients with multiple injuries. Thirty-five healthy controls, 33 patients with an isolated SHT, 47 patients with multiple injuries without SHT, and 45 patients with both SHT and multiple injuries were studied. The posttraumatic plasma levels of soluble tumor necrosis factor receptors p55 and p75, interleukin (IL)-6, IL-10, and polymorphonuclear neutrophil (PMN) elastase were monitored using enzyme-linked immunosorbent assay technique. The influence of head injuries as well as thorax, abdomen, and extremity injuries on the mediator release from patients with multiple injuries was investigated by multivariate linear regression models. The soluble tumor necrosis factor receptor p55/p75 ratio was significantly elevated within 3 hours of trauma in all three injury groups and returned to reference ratios after 12 hours. The lowest increase was found in patients suffering from an isolated SHT. Lowest mediator levels in this patient population were also found for IL-6, IL-10, and PMN elastase during the first 36 hours after trauma. Additional injuries to the head, thorax, abdomen, and extremity modulated mediator levels to a different degree. No specific effect was found for SHT when compared with other injury groups. Thorax injuries caused the quickest rise in mediator levels, whereas abdominal injuries significantly increased PMN elastase levels 12 to 24 hours after trauma. Traumatic injuries cause the liberation of various mediators, without any specific association between anatomic injury pattern and the pattern of mediator release.

Site-level progression of periodontal disease during a follow-up period

PubMed Central

Morozumi, Toshiya; Nakagawa, Taneaki; Sugaya, Tsutomu; Kawanami, Masamitsu; Suzuki, Fumihiko; Takahashi, Keiso; Abe, Yuzo; Sato, Soh; Makino-Oi, Asako; Saito, Atsushi; Takano, Satomi; Minabe, Masato; Nakayama, Yohei; Ogata, Yorimasa; Kobayashi, Hiroaki; Izumi, Yuichi; Sugano, Naoyuki; Ito, Koichi; Sekino, Satoshi; Numabe, Yukihiro; Fukaya, Chie; Yoshinari, Nobuo; Fukuda, Mitsuo; Noguchi, Toshihide; Kono, Tomoo; Umeda, Makoto; Fujise, Osamu; Nishimura, Fusanori; Yoshimura, Atsutoshi; Hara, Yoshitaka; Nakamura, Toshiaki; Noguchi, Kazuyuki; Kakuta, Erika; Hanada, Nobuhiro; Takashiba, Shogo; Amitani, Yasuharu; Yoshie, Hiromasa

2017-01-01

Periodontal disease is assessed and its progression is determined via observations on a site-by-site basis. Periodontal data are complex and structured in multiple levels; thus, applying a summary statistical approach (i.e., the mean) for site-level evaluations results in loss of information. Previous studies have shown the availability of mixed effects modeling. However, clinically beneficial information on the progression of periodontal disease during the follow-up period is not available. We conducted a multicenter prospective cohort study. Using mixed effects modeling, we analyzed 18,834 sites distributed on 3,139 teeth in 124 patients, and data were collected 5 times over a 24-month follow-up period. The change in the clinical attachment level (CAL) was used as the outcome variable. The CAL at baseline was an important determinant of the CAL changes, which varied widely according to the tooth surface. The salivary levels of periodontal pathogens, such as Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans, were affected by CAL progression. “Linear”- and “burst”-type patterns of CAL progression occurred simultaneously within the same patient. More than half of the teeth that presented burst-type progression sites also presented linear-type progression sites, and most of the progressions were of the linear type. Maxillary premolars and anterior teeth tended to show burst-type progression. The parameters identified in this study may guide practitioners in determining the type and extent of treatment needed at the site and patient levels. In addition, these results show that prior hypotheses concerning "burst" and "linear" theories are not valid. PMID:29206238

Three-dimensional passive sensing photon counting for object classification

NASA Astrophysics Data System (ADS)

Yeom, Seokwon; Javidi, Bahram; Watson, Edward

2007-04-01

In this keynote address, we address three-dimensional (3D) distortion-tolerant object recognition using photon-counting integral imaging (II). A photon-counting linear discriminant analysis (LDA) is discussed for classification of photon-limited images. We develop a compact distortion-tolerant recognition system based on the multiple-perspective imaging of II. Experimental and simulation results have shown that a low level of photons is sufficient to classify out-of-plane rotated objects.

Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

NASA Astrophysics Data System (ADS)

Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

2015-03-01

Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

Development of the Complex General Linear Model in the Fourier Domain: Application to fMRI Multiple Input-Output Evoked Responses for Single Subjects

PubMed Central

Rio, Daniel E.; Rawlings, Robert R.; Woltz, Lawrence A.; Gilman, Jodi; Hommer, Daniel W.

2013-01-01

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function. PMID:23840281

Development of the complex general linear model in the Fourier domain: application to fMRI multiple input-output evoked responses for single subjects.

PubMed

Rio, Daniel E; Rawlings, Robert R; Woltz, Lawrence A; Gilman, Jodi; Hommer, Daniel W

2013-01-01

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function.

Cumulative risk effects for the development of behaviour difficulties in children and adolescents with special educational needs and disabilities.

PubMed

Oldfield, Jeremy; Humphrey, Neil; Hebron, Judith

2015-01-01

Research has identified multiple risk factors for the development of behaviour difficulties. What have been less explored are the cumulative effects of exposure to multiple risks on behavioural outcomes, with no study specifically investigating these effects within a population of young people with special educational needs and disabilities (SEND). Furthermore, it is unclear whether a threshold or linear risk model better fits the data for this population. The sample included 2660 children and 1628 adolescents with SEND. Risk factors associated with increases in behaviour difficulties over an 18-month period were summed to create a cumulative risk score, with this explanatory variable being added into a multi-level model. A quadratic term was then added to test the threshold model. There was evidence of a cumulative risk effect, suggesting that exposure to higher numbers of risk factors, regardless of their exact nature, resulted in increased behaviour difficulties. The relationship between risk and behaviour difficulties was non-linear, with exposure to increasing risk having a disproportionate and detrimental impact on behaviour difficulties in child and adolescent models. Interventions aimed at reducing behaviour difficulties need to consider the impact of multiple risk variables. Tailoring interventions towards those exposed to large numbers of risks would be advantageous. Copyright © 2015 Elsevier Ltd. All rights reserved.

The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

NASA Astrophysics Data System (ADS)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.

Multiple solution of linear algebraic systems by an iterative method with recomputed preconditioner in the analysis of microstrip structures

NASA Astrophysics Data System (ADS)

Ahunov, Roman R.; Kuksenko, Sergey P.; Gazizov, Talgat R.

2016-06-01

A multiple solution of linear algebraic systems with dense matrix by iterative methods is considered. To accelerate the process, the recomputing of the preconditioning matrix is used. A priory condition of the recomputing based on change of the arithmetic mean of the current solution time during the multiple solution is proposed. To confirm the effectiveness of the proposed approach, the numerical experiments using iterative methods BiCGStab and CGS for four different sets of matrices on two examples of microstrip structures are carried out. For solution of 100 linear systems the acceleration up to 1.6 times, compared to the approach without recomputing, is obtained.

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Conjoint Analysis: A Study of the Effects of Using Person Variables.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…

Sparse matrix multiplications for linear scaling electronic structure calculations in an atom-centered basis set using multiatom blocks.

PubMed

Saravanan, Chandra; Shao, Yihan; Baer, Roi; Ross, Philip N; Head-Gordon, Martin

2003-04-15

A sparse matrix multiplication scheme with multiatom blocks is reported, a tool that can be very useful for developing linear-scaling methods with atom-centered basis functions. Compared to conventional element-by-element sparse matrix multiplication schemes, efficiency is gained by the use of the highly optimized basic linear algebra subroutines (BLAS). However, some sparsity is lost in the multiatom blocking scheme because these matrix blocks will in general contain negligible elements. As a result, an optimal block size that minimizes the CPU time by balancing these two effects is recovered. In calculations on linear alkanes, polyglycines, estane polymers, and water clusters the optimal block size is found to be between 40 and 100 basis functions, where about 55-75% of the machine peak performance was achieved on an IBM RS6000 workstation. In these calculations, the blocked sparse matrix multiplications can be 10 times faster than a standard element-by-element sparse matrix package. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 618-622, 2003

Waste management under multiple complexities: Inexact piecewise-linearization-based fuzzy flexible programming

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

Sun Wei; Huang, Guo H., E-mail: huang@iseis.org; Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan, S4S 0A2

2012-06-15

Highlights: Black-Right-Pointing-Pointer Inexact piecewise-linearization-based fuzzy flexible programming is proposed. Black-Right-Pointing-Pointer It's the first application to waste management under multiple complexities. Black-Right-Pointing-Pointer It tackles nonlinear economies-of-scale effects in interval-parameter constraints. Black-Right-Pointing-Pointer It estimates costs more accurately than the linear-regression-based model. Black-Right-Pointing-Pointer Uncertainties are decreased and more satisfactory interval solutions are obtained. - Abstract: To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerancemore » intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities.« less

Non-linear molecular pattern classification using molecular beacons with multiple targets.

PubMed

Lee, In-Hee; Lee, Seung Hwan; Park, Tai Hyun; Zhang, Byoung-Tak

2013-12-01

In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Multiple imputation of rainfall missing data in the Iberian Mediterranean context

NASA Astrophysics Data System (ADS)

Miró, Juan Javier; Caselles, Vicente; Estrela, María José

2017-11-01

Given the increasing need for complete rainfall data networks, in recent years have been proposed diverse methods for filling gaps in observed precipitation series, progressively more advanced that traditional approaches to overcome the problem. The present study has consisted in validate 10 methods (6 linear, 2 non-linear and 2 hybrid) that allow multiple imputation, i.e., fill at the same time missing data of multiple incomplete series in a dense network of neighboring stations. These were applied for daily and monthly rainfall in two sectors in the Júcar River Basin Authority (east Iberian Peninsula), which is characterized by a high spatial irregularity and difficulty of rainfall estimation. A classification of precipitation according to their genetic origin was applied as pre-processing, and a quantile-mapping adjusting as post-processing technique. The results showed in general a better performance for the non-linear and hybrid methods, highlighting that the non-linear PCA (NLPCA) method outperforms considerably the Self Organizing Maps (SOM) method within non-linear approaches. On linear methods, the Regularized Expectation Maximization method (RegEM) was the best, but far from NLPCA. Applying EOF filtering as post-processing of NLPCA (hybrid approach) yielded the best results.

Testing a single regression coefficient in high dimensional linear models

PubMed Central

Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2017-01-01

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z-test to assess the significance of each covariate. Based on the p-value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively. PMID:28663668

Testing a single regression coefficient in high dimensional linear models.

PubMed

Lan, Wei; Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2016-11-01

In linear regression models with high dimensional data, the classical z -test (or t -test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z -test to assess the significance of each covariate. Based on the p -value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively.

Impact of Texas high school science teacher credentials on student performance in high school science

NASA Astrophysics Data System (ADS)

George, Anna Ray Bayless

A study was conducted to determine the relationship between the credentials held by science teachers who taught at a school that administered the Science Texas Assessment on Knowledge and Skills (Science TAKS), the state standardized exam in science, at grade 11 and student performance on a state standardized exam in science administered in grade 11. Years of teaching experience, teacher certification type(s), highest degree level held, teacher and school demographic information, and the percentage of students who met the passing standard on the Science TAKS were obtained through a public records request to the Texas Education Agency (TEA) and the State Board for Educator Certification (SBEC). Analysis was performed through the use of canonical correlation analysis and multiple linear regression analysis. The results of the multiple linear regression analysis indicate that a larger percentage of students met the passing standard on the Science TAKS state attended schools in which a large portion of the high school science teachers held post baccalaureate degrees, elementary and physical science certifications, and had 11-20 years of teaching experience.

Association of Alimentary Factors and Nutritional Status with Caries in Children of Leon, Mexico.

PubMed

Guizar, Juan Manuel; Muñoz, Nathalie; Amador, Norma; Garcia, Gabriela

To determine the association between types of food consumed, nutritional status (BMI) and caries in schoolchildren. A cross-sectional study was performed with 224 schoolchildren 6 to 12 years of age. DMFT/ dmft indices, level of oral hygiene, nutritional status as quantified by BMI and types of food consumed were determined in all participants. Data were analysed using multiple linear regression with significance set at p < 0.05. Caries prevalence was 36%. In the multiple linear regression analysis adjusted for BMI, variables related to a higher number of caries were younger age and lower intake of vitamin D, calcium and fiber, with higher consumption of phosphorous and carbohydrates (R2 = 0.30; p < 0.0001 for the model). Sweetened softdrinks and chewy candy were risk factors for higher caries prevalence, while consuming milk and carrots were protectors. Caries in schoolchildren is highly prevalent in this community and is related to younger age and lower intake of vitamin D, calcium and fiber, but a higher consumption of phosphorous and carbohydrates. No relationship was found between caries and nutritional status.

Investigation of dose characteristics in three-dimensional MAGAT-type polymer gel dosimetry with MSE MR imaging

NASA Astrophysics Data System (ADS)

Lee, Jason J. S.; Tsai, Chia-Jung; Lo, Man-Kuok; Huang, Yung-Hui; Chen, Chien-Chuan; Wu, Jay; Tyan, Yeu-Sheng; Wu, Tung-Hsin

2008-05-01

A new type of normoxic polymer gel dosimeter, named MAGAT responses well to absorbed dose even when manufacturing in the presence of normal levels of oxygen. The aim of this study was to evaluate dose response, diffusion effect and cumulated dose response under multiple fractional irradiations of the MAGAT gel dosimeter using Multiple Spin-Echo (MSE) Magnetic Resonance (MR) sequence. Dose response was performed by irradiating MAGAT-gel-filled testing vials with a 6 MV linear accelerator and a linear relationship was present with doses from 0 to 6 Gy, but gradually, a bi-exponential function result was obtained with given doses up to 20 Gy. No significant difference in dose response was present between single and cumulated doses (p > 0.05). For study of diffusion effect, edge sharpness of the R2 map imaging between two split doses was smaller than 1 cm of dose profile penumbra between 20% and 80%. In conclusion, the MAGAT polymer gel dosimeter with MSE MR imaging is a promising method for dose verification in clinical radiation therapy practice.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Two-Level Hierarchical FEM Method for Modeling Passive Microwave Devices

NASA Astrophysics Data System (ADS)

Polstyanko, Sergey V.; Lee, Jin-Fa

1998-03-01

In recent years multigrid methods have been proven to be very efficient for solving large systems of linear equations resulting from the discretization of positive definite differential equations by either the finite difference method or theh-version of the finite element method. In this paper an iterative method of the multiple level type is proposed for solving systems of algebraic equations which arise from thep-version of the finite element analysis applied to indefinite problems. A two-levelV-cycle algorithm has been implemented and studied with a Gauss-Seidel iterative scheme used as a smoother. The convergence of the method has been investigated, and numerical results for a number of numerical examples are presented.

Using the Multiplicative Schwarz Alternating Algorithm (MSAA) for Solving the Large Linear System of Equations Related to Global Gravity Field Recovery up to Degree and Order 120

NASA Astrophysics Data System (ADS)

Safari, A.; Sharifi, M. A.; Amjadiparvar, B.

2010-05-01

The GRACE mission has substantiated the low-low satellite-to-satellite tracking (LL-SST) concept. The LL-SST configuration can be combined with the previously realized high-low SST concept in the CHAMP mission to provide a much higher accuracy. The line of sight (LOS) acceleration difference between the GRACE satellite pair is the mostly used observable for mapping the global gravity field of the Earth in terms of spherical harmonic coefficients. In this paper, mathematical formulae for LOS acceleration difference observations have been derived and the corresponding linear system of equations has been set up for spherical harmonic up to degree and order 120. The total number of unknowns is 14641. Such a linear equation system can be solved with iterative solvers or direct solvers. However, the runtime of direct methods or that of iterative solvers without a suitable preconditioner increases tremendously. This is the reason why we need a more sophisticated method to solve the linear system of problems with a large number of unknowns. Multiplicative variant of the Schwarz alternating algorithm is a domain decomposition method, which allows it to split the normal matrix of the system into several smaller overlaped submatrices. In each iteration step the multiplicative variant of the Schwarz alternating algorithm solves linear systems with the matrices obtained from the splitting successively. It reduces both runtime and memory requirements drastically. In this paper we propose the Multiplicative Schwarz Alternating Algorithm (MSAA) for solving the large linear system of gravity field recovery. The proposed algorithm has been tested on the International Association of Geodesy (IAG)-simulated data of the GRACE mission. The achieved results indicate the validity and efficiency of the proposed algorithm in solving the linear system of equations from accuracy and runtime points of view. Keywords: Gravity field recovery, Multiplicative Schwarz Alternating Algorithm, Low-Low Satellite-to-Satellite Tracking

Evaluation of initial posttrauma cardiovascular levels in association with acute PTSD symptoms following a serious motor vehicle accident.

PubMed

Buckley, Beth; Nugent, Nicole; Sledjeski, Eve; Raimonde, A Jay; Spoonster, Eileen; Bogart, Laura M; Delahanty, Douglas L

2004-08-01

The present study examined the relationship between heart rate (HR) and blood pressure (BP) levels assessed at multiple time points posttrauma and subsequent acute posttraumatic stress disorder (PTSD) symptoms present at a 1-month follow-up. HR and BP levels were measured in 65 motor vehicle accident (MVA) survivors during Emergency Medical Service transport, upon admission to the trauma unit, for the first 20 min postadmission and on the day of discharge. Hierarchical linear modeling analyses revealed no significant relationships between cardiovascular levels and acute PTSD symptoms. Given the small sample size, these results should be interpreted with caution. However, the present results question the use of initial cardiovascular levels as predictors of subsequent acute PTSD in seriously injured MVA victims.

The Effect of the Thickness of the Sensitive Layer on the Performance of the Accumulating NOx Sensor

PubMed Central

Groß, Andrea; Richter, Miriam; Kubinski, David J.; Visser, Jacobus H.; Moos, Ralf

2012-01-01

A novel and promising method to measure low levels of NOx utilizes the accumulating sensor principle. During an integration cycle, incoming NOx molecules are stored in a sensitive layer based on an automotive lean NOx trap (LNT) material that changes its electrical resistivity proportional to the amount of stored NOx, making the sensor suitable for long-term detection of low levels of NOx. In this study, the influence of the thickness of the sensitive layer, prepared by multiple screen-printing, is investigated. All samples show good accumulating sensing properties for both NO and NO2. In accordance to a simplified model, the base resistance of the sensitive layer and the sensitivity to NOx decrease with increasing thickness. Contrarily, the sensor response time increases. The linear measurement range of all samples ends at a sensor response of about 30% resulting in an increase of the linearly detectable amount with the thickness. Hence, the variation of the thickness of the sensitive layer is a powerful tool to adapt the linear measurement range (proportional to the thickness) as well as the sensitivity (proportional to the inverse thickness) to the application requirements. Calculations combining the sensor model with the measurement results indicate that for operation in the linear range, about 3% of the LNT material is converted to nitrate.

Solving a mixture of many random linear equations by tensor decomposition and alternating minimization.

DOT National Transportation Integrated Search

2016-09-01

We consider the problem of solving mixed random linear equations with k components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple linear models from mixed samples in the case where the labels (which sample...

Multiple pass laser amplifier system

DOEpatents

Brueckner, Keith A.; Jorna, Siebe; Moncur, N. Kent

1977-01-01

A laser amplification method for increasing the energy extraction efficiency from laser amplifiers while reducing the energy flux that passes through a flux limited system which includes apparatus for decomposing a linearly polarized light beam into multiple components, passing the components through an amplifier in delayed time sequence and recombining the amplified components into an in phase linearly polarized beam.

Statistical linearization for multi-input/multi-output nonlinearities

NASA Technical Reports Server (NTRS)

Lin, Ching-An; Cheng, Victor H. L.

1991-01-01

Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.

Some Applied Research Concerns Using Multiple Linear Regression Analysis.

ERIC Educational Resources Information Center

Newman, Isadore; Fraas, John W.

The intention of this paper is to provide an overall reference on how a researcher can apply multiple linear regression in order to utilize the advantages that it has to offer. The advantages and some concerns expressed about the technique are examined. A number of practical ways by which researchers can deal with such concerns as…

A new linear least squares method for T1 estimation from SPGR signals with multiple TRs

NASA Astrophysics Data System (ADS)

Chang, Lin-Ching; Koay, Cheng Guan; Basser, Peter J.; Pierpaoli, Carlo

2009-02-01

The longitudinal relaxation time, T1, can be estimated from two or more spoiled gradient recalled echo x (SPGR) images with two or more flip angles and one or more repetition times (TRs). The function relating signal intensity and the parameters are nonlinear; T1 maps can be computed from SPGR signals using nonlinear least squares regression. A widely-used linear method transforms the nonlinear model by assuming a fixed TR in SPGR images. This constraint is not desirable since multiple TRs are a clinically practical way to reduce the total acquisition time, to satisfy the required resolution, and/or to combine SPGR data acquired at different times. A new linear least squares method is proposed using the first order Taylor expansion. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy and precision of the estimated T1 from the proposed linear and the nonlinear methods. We show that the new linear least squares method provides T1 estimates comparable in both precision and accuracy to those from the nonlinear method, allowing multiple TRs and reducing computation time significantly.

Detection and Measurement of Unhealthy, Environment-Derived Aerosol Materials in an Emergency Department.

PubMed

Choi, Bryan Y; Kobayashi, Leo; Pathania, Shivany; Miller, Courtney B; Locke, Emma R; Stearns, Branden C; Hudepohl, Nathan J; Patefield, Scott S; Suner, Selim; Williams, Kenneth A; Machan, Jason T; Jay, Gregory D

2015-01-01

To measure unhealthy aerosol materials in an Emergency Department (ED) and identify their sources for mitigation efforts. Based on pilot findings of elevated ED particulate matter (PM) levels, investigators hypothesized that unhealthy aerosol materials derive from exogenous (vehicular) sources at ambulance receiving entrances. The Aerosol Environmental Toxicity in Healthcare-related Exposure and Risk program was conducted as an observational study. Calibrated sensors monitored PM and toxic gases at Ambulance Triage Exterior (ATE), Ambulance Triage Desk (ATD), and control Public Triage Desk (PTD) on a 3/3/3-day cycle. Cassette sampling characterized PM; meteorological and ambulance traffic data were logged. Descriptive and multiple linear regression analyses assessed for interactions between aerosol material levels, location, temporal variables, ambulance activity, and meteorological factors. Sensors acquired 93,682 PM0.3, 90,250 PM2.5, and 93,768 PM5 measurements over 366 days to generate a data set representing at least 85.6% of planned measurements. PM0.3, PM2.5, and PM5 mean counts were lowest in PTD; 56%, 224%, and 223% higher in ATD; and 996%, 200%, and 63% higher in ATE, respectively (all p < .001). Qualitative analyses showed similar PM compositions in ATD and ATE. On multiple linear regression analysis, PM0.3 counts correlated primarily with location; PM2.5 and PM5 counts correlated most strongly with location and ambulance presence. PM < 2.5 and toxic gas concentrations at ATD and PTD patient care areas did not exceed hazard levels; PM0.3 counts did not have formal safety thresholds for comparison. Higher levels of PM were linked with ED ambulance areas, although their health impact is unclear. © The Author(s) 2015.

Early pregnancy fasting plasma glucose and lipid concentrations in pregnancy and association to offspring size: a retrospective cohort study.

PubMed

Liu, Bin; Geng, Huizhen; Yang, Juan; Zhang, Ying; Deng, Langhui; Chen, Weiqing; Wang, Zilian

2016-03-17

Hyperlipidemia and high fasting plasma glucose levels at the first prenatal visit (First Visit FPG) are both related to gestational diabetes mellitus, maternal obesity/overweight and fetal overgrowth. The purpose of the present study is to investigate the correlation between First Visit FPG and lipid concentrations, and their potential association with offspring size at delivery. Pregnant women that received regular prenatal care and delivered in our center in 2013 were recruited for the study. Fasting plasma glucose levels were tested at the first prenatal visit (First Visit FPG) and prior to delivery (Before Delivery FPG). HbA1c and lipid profiles were examined at the time of OGTT test. Maternal and neonatal clinical data were collected for analysis. Data was analyzed by independent sample t test, Pearson correlation, and Chi-square test, followed by partial correlation and multiple linear regression analyses to confirm association. Statistical significance level was α =0.05. Analyses were based on 1546 mother-baby pairs. First Visit FPG was not correlated with any lipid parameters after adjusting for maternal pregravid BMI, maternal age and gestational age at First Visit FPG. HbA1c was positively correlated with triglyceride and Apolipoprotein B in the whole cohort and in the NGT group after adjusting for maternal age and maternal BMI at OGTT test. Multiple linear regression analyses showed neonatal birth weight, head circumference and shoulder circumference were all associated with First Visit FPG and triglyceride levels. Fasting plasma glucose at first prenatal visit is not associated with lipid concentrations in mid-pregnancy, but may influence fetal growth together with triglyceride concentration.

Serum Folate Shows an Inverse Association with Blood Pressure in a Cohort of Chinese Women of Childbearing Age: A Cross-Sectional Study

PubMed Central

Shen, Minxue; Tan, Hongzhuan; Zhou, Shujin; Retnakaran, Ravi; Smith, Graeme N.; Davidge, Sandra T.; Trasler, Jacquetta; Walker, Mark C.; Wen, Shi Wu

2016-01-01

Background It has been reported that higher folate intake from food and supplementation is associated with decreased blood pressure (BP). The association between serum folate concentration and BP has been examined in few studies. We aim to examine the association between serum folate and BP levels in a cohort of young Chinese women. Methods We used the baseline data from a pre-conception cohort of women of childbearing age in Liuyang, China, for this study. Demographic data were collected by structured interview. Serum folate concentration was measured by immunoassay, and homocysteine, blood glucose, triglyceride and total cholesterol were measured through standardized clinical procedures. Multiple linear regression and principal component regression model were applied in the analysis. Results A total of 1,532 healthy normotensive non-pregnant women were included in the final analysis. The mean concentration of serum folate was 7.5 ± 5.4 nmol/L and 55% of the women presented with folate deficiency (< 6.8 nmol/L). Multiple linear regression and principal component regression showed that serum folate levels were inversely associated with systolic and diastolic BP, after adjusting for demographic, anthropometric, and biochemical factors. Conclusions Serum folate is inversely associated with BP in non-pregnant women of childbearing age with high prevalence of folate deficiency. PMID:27182603

An Application of Robust Method in Multiple Linear Regression Model toward Credit Card Debt

NASA Astrophysics Data System (ADS)

Amira Azmi, Nur; Saifullah Rusiman, Mohd; Khalid, Kamil; Roslan, Rozaini; Sufahani, Suliadi; Mohamad, Mahathir; Salleh, Rohayu Mohd; Hamzah, Nur Shamsidah Amir

2018-04-01

Credit card is a convenient alternative replaced cash or cheque, and it is essential component for electronic and internet commerce. In this study, the researchers attempt to determine the relationship and significance variables between credit card debt and demographic variables such as age, household income, education level, years with current employer, years at current address, debt to income ratio and other debt. The provided data covers 850 customers information. There are three methods that applied to the credit card debt data which are multiple linear regression (MLR) models, MLR models with least quartile difference (LQD) method and MLR models with mean absolute deviation method. After comparing among three methods, it is found that MLR model with LQD method became the best model with the lowest value of mean square error (MSE). According to the final model, it shows that the years with current employer, years at current address, household income in thousands and debt to income ratio are positively associated with the amount of credit debt. Meanwhile variables for age, level of education and other debt are negatively associated with amount of credit debt. This study may serve as a reference for the bank company by using robust methods, so that they could better understand their options and choice that is best aligned with their goals for inference regarding to the credit card debt.

Age is no barrier: predictors of academic success in older learners

NASA Astrophysics Data System (ADS)

Imlach, Abbie-Rose; Ward, David D.; Stuart, Kimberley E.; Summers, Mathew J.; Valenzuela, Michael J.; King, Anna E.; Saunders, Nichole L.; Summers, Jeffrey; Srikanth, Velandai K.; Robinson, Andrew; Vickers, James C.

2017-11-01

Although predictors of academic success have been identified in young adults, such predictors are unlikely to translate directly to an older student population, where such information is scarce. The current study aimed to examine cognitive, psychosocial, lifetime, and genetic predictors of university-level academic performance in older adults (50-79 years old). Participants were mostly female (71%) and had a greater than high school education level (M = 14.06 years, SD = 2.76), on average. Two multiple linear regression analyses were conducted. The first examined all potential predictors of grade point average (GPA) in the subset of participants who had volunteered samples for genetic analysis (N = 181). Significant predictors of GPA were then re-examined in a second multiple linear regression using the full sample (N = 329). Our data show that the cognitive domains of episodic memory and language processing, in conjunction with midlife engagement in cognitively stimulating activities, have a role in predicting academic performance as measured by GPA in the first year of study. In contrast, it was determined that age, IQ, gender, working memory, psychosocial factors, and common brain gene polymorphisms linked to brain function, plasticity and degeneration (APOE, BDNF, COMT, KIBRA, SERT) did not influence academic performance. These findings demonstrate that ageing does not impede academic achievement, and that discrete cognitive skills as well as lifetime engagement in cognitively stimulating activities can promote academic success in older adults.

Female married illiteracy as the most important continual determinant of total fertility rate among districts of Empowered Action Group States of India: Evidence from Annual Health Survey 2011-12.

PubMed

Kumar, Rajesh; Dogra, Vishal; Rani, Khushbu; Sahu, Kanti

2017-01-01

District level determinants of total fertility rate in Empowered Action Group states of India can help in ongoing population stabilization programs in India. Present study intends to assess the role of district level determinants in predicting total fertility rate among districts of the Empowered Action Group states of India. Data from Annual Health Survey (2011-12) was analysed using STATA and R software packages. Multiple linear regression models were built and evaluated using Akaike Information Criterion. For further understanding, recursive partitioning was used to prepare a regression tree. Female married illiteracy positively associated with total fertility rate and explained more than half (53%) of variance. Under multiple linear regression model, married illiteracy, infant mortality rate, Ante natal care registration, household size, median age of live birth and sex ratio explained 70% of total variance in total fertility rate. In regression tree, female married illiteracy was the root node and splits at 42% determined TFR <= 2.7. The next left side branch was again married illiteracy with splits at 23% to determine TFR <= 2.1. We conclude that female married illiteracy is one of the most important determinants explaining total fertility rate among the districts of an Empowered Action Group states. Focus on female literacy is required to stabilize the population growth in long run.

Optimal allocation model of construction land based on two-level system optimization theory

NASA Astrophysics Data System (ADS)

Liu, Min; Liu, Yanfang; Xia, Yuping; Lei, Qihong

2007-06-01

The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.

The Primordial Inflation Explorer (PIXIE)

NASA Technical Reports Server (NTRS)

Kogut, Alan; Chuss, David T.; Dotson, Jessie; Dwek, Eli; Fixsen, Dale J.; Halpern, Mark; Hinshaw, Gary F.; Meyer, Stephan; Moseley, S. Harvey; Seiffert, Michael D.;

Point-by-point model calculation of the prompt neutron multiplicity distribution ν(A) in the incident neutron energy range of multi-chance fission

NASA Astrophysics Data System (ADS)

Tudora, Anabella; Hambsch, Franz-Josef; Tobosaru, Viorel

2017-09-01

Prompt neutron multiplicity distributions ν(A) are required for prompt emission correction of double energy (2E) measurements of fission fragments to determine pre-neutron fragment properties. The lack of experimental ν(A) data especially at incident neutron energies (En) where the multi-chance fission occurs impose the use of ν(A) predicted by models. The Point-by-Point model of prompt emission is able to provide the individual ν(A) of the compound nuclei of the main and secondary nucleus chains undergoing fission at a given En. The total ν(A) is obtained by averaging these individual ν(A) over the probabilities of fission chances (expressed as total and partial fission cross-section ratios). An indirect validation of the total ν(A) results is proposed. At high En, above 70 MeV, the PbP results of individual ν(A) of the first few nuclei of the main and secondary nucleus chains exhibit an almost linear increase. This shape is explained by the damping of shell effects entering the super-fluid expression of the level density parameters. They tend to approach the asymptotic values for most of the fragments. This fact leads to a smooth and almost linear increase of fragment excitation energy with the mass number that is reflected in a smooth and almost linear behaviour of ν(A).

ADDING REALISM TO NUCLEAR MATERIAL DISSOLVING ANALYSIS

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

Williamson, B.

2011-08-15

Two new criticality modeling approaches have greatly increased the efficiency of dissolver operations in H-Canyon. The first new approach takes credit for the linear, physical distribution of the mass throughout the entire length of the fuel assembly. This distribution of mass is referred to as the linear density. Crediting the linear density of the fuel bundles results in using lower fissile concentrations, which allows higher masses to be charged to the dissolver. Also, this approach takes credit for the fact that only part of the fissile mass is wetted at a time. There are multiple assemblies stacked on top ofmore » each other in a bundle. On average, only 50-75% of the mass (the bottom two or three assemblies) is wetted at a time. This means that only 50-75% (depending on operating level) of the mass is moderated and is contributing to the reactivity of the system. The second new approach takes credit for the progression of the dissolving process. Previously, dissolving analysis looked at a snapshot in time where the same fissile material existed both in the wells and in the bulk solution at the same time. The second new approach models multiple consecutive phases that simulate the fissile material moving from a high concentration in the wells to a low concentration in the bulk solution. This approach is more realistic and allows higher fissile masses to be charged to the dissolver.« less

Association of dentine hypersensitivity with different risk factors - a cross sectional study.

PubMed

Vijaya, V; Sanjay, Venkataraam; Varghese, Rana K; Ravuri, Rajyalakshmi; Agarwal, Anil

2013-12-01

This study was done to assess the prevalence of Dentine hypersensitivity (DH) and its associated risk factors. This epidemiological study was done among patients coming to dental college regarding prevalence of DH. A self structured questionnaire along with clinical examination was done for assessment. Descriptive statistics were obtained and frequency distribution was calculated using Chi square test at p value <0.05. Stepwise multiple linear regression was also done to access frequency of DH with different factors. The study population was comprised of 655 participants with different age groups. Our study showed prevalence as 55% and it was more common among males. Similarly smokers and those who use hard tooth brush had more cases of DH. Step wise multiple linear regression showed that best predictor for DH was age followed by habit of smoking and type of tooth brush. Most aggravating factors were cold water (15.4%) and sweet foods (14.7%), whereas only 5% of the patients had it while brushing. A high level of dental hypersensitivity has been in this study and more common among males. A linear finding was shown with age, smoking and type of tooth brush. How to cite this article: Vijaya V, Sanjay V, Varghese RK, Ravuri R, Agarwal A. Association of Dentine Hypersensitivity with Different Risk Factors - A Cross Sectional Study. J Int Oral Health 2013;5(6):88-92 .

Unmasking the effects of masking on performance: The potential of multiple-voice masking in the office environment.

PubMed

Keus van de Poll, Marijke; Carlsson, Johannes; Marsh, John E; Ljung, Robert; Odelius, Johan; Schlittmeier, Sabine J; Sundin, Gunilla; Sörqvist, Patrik

2015-08-01

Broadband noise is often used as a masking sound to combat the negative consequences of background speech on performance in open-plan offices. As office workers generally dislike broadband noise, it is important to find alternatives that are more appreciated while being at least not less effective. The purpose of experiment 1 was to compare broadband noise with two alternatives-multiple voices and water waves-in the context of a serial short-term memory task. A single voice impaired memory in comparison with silence, but when the single voice was masked with multiple voices, performance was on level with silence. Experiment 2 explored the benefits of multiple-voice masking in more detail (by comparing one voice, three voices, five voices, and seven voices) in the context of word processed writing (arguably a more office-relevant task). Performance (i.e., writing fluency) increased linearly from worst performance in the one-voice condition to best performance in the seven-voice condition. Psychological mechanisms underpinning these effects are discussed.

Stochastic Swift-Hohenberg Equation with Degenerate Linear Multiplicative Noise

NASA Astrophysics Data System (ADS)

Hernández, Marco; Ong, Kiah Wah

2018-03-01

We study the dynamic transition of the Swift-Hohenberg equation (SHE) when linear multiplicative noise acting on a finite set of modes of the dominant linear flow is introduced. Existence of a stochastic flow and a local stochastic invariant manifold for this stochastic form of SHE are both addressed in this work. We show that the approximate reduced system corresponding to the invariant manifold undergoes a stochastic pitchfork bifurcation, and obtain numerical evidence suggesting that this picture is a good approximation for the full system as well.

A methodology based on reduced complexity algorithm for system applications using microprocessors

NASA Technical Reports Server (NTRS)

Yan, T. Y.; Yao, K.

1988-01-01

The paper considers a methodology on the analysis and design of a minimum mean-square error criterion linear system incorporating a tapped delay line (TDL) where all the full-precision multiplications in the TDL are constrained to be powers of two. A linear equalizer based on the dispersive and additive noise channel is presented. This microprocessor implementation with optimized power of two TDL coefficients achieves a system performance comparable to the optimum linear equalization with full-precision multiplications for an input data rate of 300 baud.

Ecological correlates of multiple sexual partnerships among adolescents and young adults in urban Cape Town: a cumulative risk factor approach.

PubMed

Muchiri, Evans; Odimegwu, Clifford; Banda, Pamela; Ntoimo, Lorreta; Adedini, Sunday

2017-07-01

Studies in South Africa have reported unsafe levels of risky sexual behvaiours among adolescents and young adults, with the country reporting the highest burden of HIV/AIDS globally, as well as a high rate of teenage pregnancy. While determinants of risky sexual behaviours have been investigated for factors occurring at the individual and household levels, not fully explored in the literature is the effect of community level factors. Furthermore, it is unclear whether risk factors occurring within the ecology of adolescents and young adults act cumulatively to influence their sexual practices. This article aims to address this knowledge gap using a case study of the Cape Area Panel Study of adolescents and young adults in urban Cape Town, South Africa. The ecological framework was adopted to guide the selection of risk factors at the individual, household, and community levels. Multivariate linear discriminant function analyses were used to select significant risk factors for multiple sexual partnerships and used to produce risk indices for the respondents. The cumulative risk approach was applied to test whether significant risk factors acted cumulatively. Findings point to the importance of ecological factors in influencing outcomes of multiple sexual partnerships among respondents and further demonstrate that ecological risk factors may act cumulatively. These findings are important for South Africa that is grappling with teenage pregnancy and disproportionate HIV epidemic among the youth.

Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

PubMed

Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena

2013-01-01

The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Evaluation of Relationship between Trunk Muscle Endurance and Static Balance in Male Students

PubMed Central

Barati, Amirhossein; SafarCherati, Afsaneh; Aghayari, Azar; Azizi, Faeze; Abbasi, Hamed

2013-01-01

Purpose Fatigue of trunk muscle contributes to spinal instability over strenuous and prolonged physical tasks and therefore may lead to injury, however from a performance perspective, relation between endurance efficient core muscles and optimal balance control has not been well-known. The purpose of this study was to examine the relationship of trunk muscle endurance and static balance. Methods Fifty male students inhabitant of Tehran university dormitory (age 23.9±2.4, height 173.0±4.5 weight 70.7±6.3) took part in the study. Trunk muscle endurance was assessed using Sørensen test of trunk extensor endurance, trunk flexor endurance test, side bridge endurance test and static balance was measured using single-limb stance test. A multiple linear regression analysis was applied to test if the trunk muscle endurance measures significantly predicted the static balance. Results There were positive correlations between static balance level and trunk flexor, extensor and lateral endurance measures (Pearson correlation test, r=0.80 and P<0.001; r=0.71 and P<0.001; r=0.84 and P<0.001, respectively). According to multiple regression analysis for variables predicting static balance, the linear combination of trunk muscle endurance measures was significantly related to the static balance (F (3,46) = 66.60, P<0.001). Endurance of trunk flexor, extensor and lateral muscles were significantly associated with the static balance level. The regression model which included these factors had the sample multiple correlation coefficient of 0.902, indicating that approximately 81% of the variance of the static balance is explained by the model. Conclusion There is a significant relationship between trunk muscle endurance and static balance. PMID:24800004

Molecular evolution of multiple-level control of heme biosynthesis pathway in animal kingdom.

PubMed

Tzou, Wen-Shyong; Chu, Ying; Lin, Tzung-Yi; Hu, Chin-Hwa; Pai, Tun-Wen; Liu, Hsin-Fu; Lin, Han-Jia; Cases, Ildeofonso; Rojas, Ana; Sanchez, Mayka; You, Zong-Ye; Hsu, Ming-Wei

2014-01-01

Adaptation of enzymes in a metabolic pathway can occur not only through changes in amino acid sequences but also through variations in transcriptional activation, mRNA splicing and mRNA translation. The heme biosynthesis pathway, a linear pathway comprised of eight consecutive enzymes in animals, provides researchers with ample information for multiple types of evolutionary analyses performed with respect to the position of each enzyme in the pathway. Through bioinformatics analysis, we found that the protein-coding sequences of all enzymes in this pathway are under strong purifying selection, from cnidarians to mammals. However, loose evolutionary constraints are observed for enzymes in which self-catalysis occurs. Through comparative genomics, we found that in animals, the first intron of the enzyme-encoding genes has been co-opted for transcriptional activation of the genes in this pathway. Organisms sense the cellular content of iron, and through iron-responsive elements in the 5' untranslated regions of mRNAs and the intron-exon boundary regions of pathway genes, translational inhibition and exon choice in enzymes may be enabled, respectively. Pathway product (heme)-mediated negative feedback control can affect the transport of pathway enzymes into the mitochondria as well as the ubiquitin-mediated stability of enzymes. Remarkably, the positions of these controls on pathway activity are not ubiquitous but are biased towards the enzymes in the upstream portion of the pathway. We revealed that multiple-level controls on the activity of the heme biosynthesis pathway depend on the linear depth of the enzymes in the pathway, indicating a new strategy for discovering the molecular constraints that shape the evolution of a metabolic pathway.

Incentives for Optimal Multi-level Allocation of HIV Prevention Resources

PubMed Central

Malvankar, Monali M.; Zaric, Gregory S.

2013-01-01

HIV/AIDS prevention funds are often allocated at multiple levels of decision-making. Optimal allocation of HIV prevention funds maximizes the number of HIV infections averted. However, decision makers often allocate using simple heuristics such as proportional allocation. We evaluate the impact of using incentives to encourage optimal allocation in a two-level decision-making process. We model an incentive based decision-making process consisting of an upper-level decision maker allocating funds to a single lower-level decision maker who then distributes funds to local programs. We assume that the lower-level utility function is linear in the amount of the budget received from the upper-level, the fraction of funds reserved for proportional allocation, and the number of infections averted. We assume that the upper level objective is to maximize the number of infections averted. We illustrate with an example using data from California, U.S. PMID:23766551

Influence on serum asymmetric dimethylarginine (ADMA) concentrations of human paraoxonase 1 polymorphism (Q192R) and exposure to polycyclic aromatic hydrocarbons (PAHs) in Mexican women, a gene-environment interaction.

PubMed

Ochoa-Martínez, Ángeles C; Ruíz-Vera, Tania; Almendarez-Reyna, Claudia I; Orta-García, Sandra T; Pérez-Maldonado, Iván N

2017-11-01

It has been demonstrated that Cardiovascular Diseases (CVD) are a consequence of the combination of genetic and environmental factors and/or the interaction between them. Therefore, the aim of this study was to evaluate the impact of polycyclic aromatic hydrocarbon (PAHs) exposure and PON1 Q192R polymorphism (genetic susceptibility) on serum asymmetric dimethylarginine (ADMA) levels in Mexican women (n = 206). Urinary 1-hydroxypyrene concentrations (1-OHP; exposure biomarker for PAHs) were quantified using a high-performance liquid chromatography technique, PON1 Q192R polymorphism was genotyped using TaqMan probes and serum ADMA concentrations were evaluated using a commercially available ELISA kit. Urinary 1-OHP levels detected in this study ranged from 0.07 to 9.37 μmol/mol of creatinine (0.13-18.0 μg/g of creatinine). Regarding allele frequency (PON1 Q192R polymorphism), the 192Q-allele frequency was 0.43 and for the 192R-allele it was 0.57. In relation to serum ADMA levels, the levels ranged from 0.06 to 1.46 μmol/L. Moreover, multiple linear regression analysis was performed and associations between urinary 1-OHP levels (β = 0.05, p = 0.002), PON1 Q192R polymorphism (β = 0.04, p = 0.003) and serum ADMA concentrations were found. Besides, an interaction (gene-environment interaction) of both independent variables (1-OHP and PON1 polymorphism) on serum ADMA levels was found (β = 0.04, p = 0.02) in the constructed multiple linear model. Therefore, according to the significance of this research, it is necessary to execute health programs to reduce cardiovascular risk in the assessed population. Copyright © 2017 Elsevier Ltd. All rights reserved.

The prevalence of low serum zinc and copper levels and dietary habits associated with serum zinc and copper in 12- to 36-month-old children from low-income families at risk for iron deficiency.

PubMed

Schneider, Julie M; Fujii, Mary L; Lamp, Catherine L; Lönnerdal, Bo; Zidenberg-Cherr, Sheri

2007-11-01

Iron and zinc share common food sources, and children at risk of iron deficiency may also develop zinc deficiency. We determined the prevalence of zinc and copper deficiency and examined factors associated with serum zinc and copper in young children from low-income families at risk of iron deficiency. A cross-sectional study design was used to assess serum zinc and copper, along with an interview-assisted survey to assess factors associated with serum zinc and copper in a convenience sample. Participants were 435 children aged 12 to 36 months recruited from select clinics of the Special Supplemental Nutrition Program for Women, Infants, and Children in Contra Costa and Tulare Counties, California. Frequencies were used to report prevalence. Multiple linear regressions were conducted to examine factors associated with serum zinc and copper, controlling for age, sex, and ethnicity. The prevalence of low serum zinc level (<70 microg/dL [<10.7 micromol/L]) was 42.8%, and low serum copper level (<90 microg/dL [<14.2 micromol/L]) was <1%. Mean+/-standard deviation of serum copper was 150+/-22 microg/dL (23.6+/-3.5 micromol/L) and 140+/-24 microg/dL (22.1+/-3.8 micromol/L) for anemic and non-anemic children, respectively (t test, P=0.026). In multiple linear regression consumption of sweetened beverages was negatively associated with serum zinc level, and consumption of >15 g/day meat was positively associated with serum zinc level, whereas current consumption of breast milk and >15 g/day beans were positively associated with serum copper level. The prevalence of low serum zinc concentration in the sample was high, and warrants further investigation amongst vulnerable populations.

Error in geometric morphometric data collection: Combining data from multiple sources.

PubMed

Robinson, Chris; Terhune, Claire E

2017-09-01

This study compares two- and three-dimensional morphometric data to determine the extent to which intra- and interobserver and intermethod error influence the outcomes of statistical analyses. Data were collected five times for each method and observer on 14 anthropoid crania using calipers, a MicroScribe, and 3D models created from NextEngine and microCT scans. ANOVA models were used to examine variance in the linear data at the level of genus, species, specimen, observer, method, and trial. Three-dimensional data were analyzed using geometric morphometric methods; principal components analysis was employed to examine how trials of all specimens were distributed in morphospace and Procrustes distances among trials were calculated and used to generate UPGMA trees to explore whether all trials of the same individual grouped together regardless of observer or method. Most variance in the linear data was at the genus level, with greater variance at the observer than method levels. In the 3D data, interobserver and intermethod error were similar to intraspecific distances among Callicebus cupreus individuals, with interobserver error being higher than intermethod error. Generally, taxa separate well in morphospace, with different trials of the same specimen typically grouping together. However, trials of individuals in the same species overlapped substantially with one another. Researchers should be cautious when compiling data from multiple methods and/or observers, especially if analyses are focused on intraspecific variation or closely related species, as in these cases, patterns among individuals may be obscured by interobserver and intermethod error. Conducting interobserver and intermethod reliability assessments prior to the collection of data is recommended. © 2017 Wiley Periodicals, Inc.

Glutamatergic system abnormalities in posttraumatic stress disorder.

PubMed

Nishi, Daisuke; Hashimoto, Kenji; Noguchi, Hiroko; Hamazaki, Kei; Hamazaki, Tomohito; Matsuoka, Yutaka

2015-12-01

Accumulating evidence suggests involvement of the glutamatergic system in the biological mechanisms of posttraumatic stress disorder (PTSD), but few studies have demonstrated an association between glutamatergic system abnormalities and PTSD diagnosis or severity. We aimed to examine whether abnormalities in serum glutamate and in the glutamine/glutamate ratio were associated with PTSD diagnosis and severity in severely injured patients at risk for PTSD and major depressive disorder (MDD). This is a nested case-control study in TPOP (Tachikawa project for prevention of posttraumatic stress disorder with polyunsaturated fatty acid) trial. Diagnosis and severity of PTSD were assessed 3 months after the accidents using the Clinician-Administered PTSD Scale. The associations of glutamate levels and the glutamine/glutamate ratio with diagnosis and severity of PTSD and MDD were investigated by univariate and multiple linear regression analyses. Ninety-seven of 110 participants (88 %) completed assessments at 3 months. Serum glutamate levels were significantly higher for participants with full or partial PTSD than for participants without PTSD (p = 0.049) and for participants with MDD than for participants without MDD (p = 0.048). Multiple linear regression analyses showed serum glutamate levels were significantly positively associated with PTSD severity (p = 0.02) and MDD severity (p = 0.03). The glutamine/glutamate ratio was also significantly inversely associated with PTSD severity (p = 0.03), but not with MDD severity (p = 0.07). These findings suggest that the glutamatergic system may play a major role in the pathogenesis of PTSD and the need for new treatments targeting the glutamatergic system to be developed for PTSD.

Comparison of Mental Toughness and Power Test Performances in High-Level Kickboxers by Competitive Success

PubMed Central

Slimani, Maamer; Miarka, Bianca; Briki, Walid; Cheour, Foued

2016-01-01

Background Kickboxing is a high-intensity intermittent striking combat sport, which is characterized by complex skills and tactical key actions with short duration. Objectives The present study compared and verified the relationship between mental toughness (MT), countermovement jump (CMJ) and medicine ball throw (MBT) power tests by outcomes of high-level kickboxers during National Championship. Materials and Methods Thirty two high-level male kickboxers (winner = 16 and loser = 16: 21.2 ± 3.1 years, 1.73 ± 0.07 m, and 70.2 ± 9.4 kg) were analyzed using the CMJ, MBT tests and sports mental toughness questionnaire (SMTQ; based in confidence, constancy and control subscales), before the fights of the 2015 national championship (16 bouts). In statistical analysis, Mann-Withney test and a multiple linear regression were used to compare groups and to observe relationships, respectively, P ≤ 0.05. Results The present results showed significant differences between losers vs. winners, respectively, of total MT (7(7;8) vs. 11(10.2;11), confidence (3(3;3) vs. 4(4;4)), constancy (2(2;2) vs. 3(3;3)), control (2(2;3) vs. 4(4;4)) subscales and MBT (4.1(4;4.3) vs. 4.6(4.4;4.8)). The multiple linear regression showed a strong associations between MT results and outcome (r = 0.89), MBT (r = 0.84) and CMJ (r = 0.73). Conclusions The findings suggest that MT will be more predictive of performance in those sports and in the outcome of competition. PMID:27625755

Multiple metals predict prolactin and thyrotropin (TSH) levels in men

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

Meeker, John D., E-mail: meekerj@umich.edu; Rossano, Mary G.; Protas, Bridget

2009-10-15

Exposure to a number of metals can affect neuroendocrine and thyroid signaling, which can result in adverse effects on development, behavior, metabolism, reproduction, and other functions. The present study assessed the relationship between metal concentrations in blood and serum prolactin (PRL) and thyrotropin (TSH) levels, markers of dopaminergic, and thyroid function, respectively, among men participating in a study of environmental influences on male reproductive health. Blood samples from 219 men were analyzed for concentrations of 11 metals and serum levels of PRL and TSH. In multiple linear regression models adjusted for age, BMI and smoking, PRL was inversely associated withmore » arsenic, cadmium, copper, lead, manganese, molybdenum, and zinc, but positively associated with chromium. Several of these associations (Cd, Pb, Mo) are consistent with limited studies in humans or animals, and a number of the relationships (Cr, Cu, Pb, Mo) remained when additionally considering multiple metals in the model. Lead and copper were associated with non-monotonic decrease in TSH, while arsenic was associated with a dose-dependent increase in TSH. For arsenic these findings were consistent with recent experimental studies where arsenic inhibited enzymes involved in thyroid hormone synthesis and signaling. More research is needed for a better understanding of the role of metals in neuroendocrine and thyroid function and related health implications.« less

Non-linear relationship between serum 25-hydroxyvitamin D concentration and subsequent hip fracture.

PubMed

de Koning, L; Henne, D; Hemmelgarn, B R; Woods, P; Naugler, C

2013-07-01

Serum 25-OH vitamin D levels were compared in 254 hip fracture subjects and 2,402 matched control subjects. There was a significant inverse association between 25-OH vitamin D and hip fracture only between 0 and 70 nmol/L. Vitamin D is integral to bone metabolism, however the utility of serum 25-OH vitamin D as a risk marker for hip fractures is controversial. We conducted a case-control study of patients admitted to the hospitals with hip fractures in Calgary, Alberta, (catchment population 1.4 million) between January 1, 2007 and August 31, 2011. We searched the laboratory information system of Calgary Laboratory Services for serum 25-OH vitamin D levels within 6 months prior to admission on patients admitted to hospital with hip fractures. Cases were identified through the Calgary Laboratory Services laboratory information system and were matched to controls for age, sex, and month of testing. The hip fracture-25-OH vitamin D association was examined using multiple linear and spline regression. Of 305 subjects initially identified with hip fractures, serum 25-OH vitamin D levels were available for 254 (83 %). These were matched to 2,402 control subjects. We observed a significant (p < 0.01) non-linear relationship such that 25-OH vitamin D was inversely associated with hip fracture only below 70 nmol/L (odds ratio = 0.81 per 10 nmol/L increase; 95 % CI 0.86-0.93). The utility of 25-OH vitamin D level as a risk marker for hip fracture depends on the cut-off level used and was of potential use only for lower levels of 25-OH vitamin D.

A Quantitative and Combinatorial Approach to Non-Linear Meanings of Multiplication

ERIC Educational Resources Information Center

Tillema, Erik; Gatza, Andrew

2016-01-01

We provide a conceptual analysis of how combinatorics problems have the potential to support students to establish non-linear meanings of multiplication (NLMM). The problems we analyze we have used in a series of studies with 6th, 8th, and 10th grade students. We situate the analysis in prior work on students' quantitative and multiplicative…

Homomorphic filtering textural analysis technique to reduce multiplicative noise in the 11Oba nano-doped liquid crystalline compounds

NASA Astrophysics Data System (ADS)

Madhav, B. T. P.; Pardhasaradhi, P.; Manepalli, R. K. N. R.; Pisipati, V. G. K. M.

2015-07-01

The compound undecyloxy benzoic acid (11Oba) exhibits nematic and smectic-C phases while a nano-doped undecyloxy benzoic acid with ZnO exhibits the same nematic and smectic-C phases with reduced clearing temperature as expected. The doping is done with 0.5% and 1% ZnO molecules. The clearing temperatures are reduced by approximately 4 ° and 6 °, respectively (differential scanning calorimeter data). While collecting the images from a polarizing microscope connected with hot stage and camera, the illumination and reflectance combined multiplicatively and the image quality was reduced to identify the exact phase in the compound. A novel technique of homomorphic filtering is used in this manuscript through which multiplicative noise components of the image are separated linearly in the frequency domain. This technique provides a frequency domain procedure to improve the appearance of an image by gray level range compression and contrast enhancement.

Analysis of Slope Limiters on Irregular Grids

NASA Technical Reports Server (NTRS)

Berger, Marsha; Aftosmis, Michael J.

2005-01-01

This paper examines the behavior of flux and slope limiters on non-uniform grids in multiple dimensions. Many slope limiters in standard use do not preserve linear solutions on irregular grids impacting both accuracy and convergence. We rewrite some well-known limiters to highlight their underlying symmetry, and use this form to examine the proper - ties of both traditional and novel limiter formulations on non-uniform meshes. A consistent method of handling stretched meshes is developed which is both linearity preserving for arbitrary mesh stretchings and reduces to common limiters on uniform meshes. In multiple dimensions we analyze the monotonicity region of the gradient vector and show that the multidimensional limiting problem may be cast as the solution of a linear programming problem. For some special cases we present a new directional limiting formulation that preserves linear solutions in multiple dimensions on irregular grids. Computational results using model problems and complex three-dimensional examples are presented, demonstrating accuracy, monotonicity and robustness.

Characterisation of tissue-type metabolic content in secondary progressive multiple sclerosis: a magnetic resonance spectroscopic imaging study.

PubMed

Marshall, Ian; Thrippleton, Michael J; Bastin, Mark E; Mollison, Daisy; Dickie, David A; Chappell, Francesca M; Semple, Scott I K; Cooper, Annette; Pavitt, Sue; Giovannoni, Gavin; Wheeler-Kingshott, Claudia A M Gandini; Solanky, Bhavana S; Weir, Christopher J; Stallard, Nigel; Hawkins, Clive; Sharrack, Basil; Chataway, Jeremy; Connick, Peter; Chandran, Siddharthan

2018-05-30

Proton magnetic resonance spectroscopy yields metabolic information and has proved to be a useful addition to structural imaging in neurological diseases. We applied short-echo time Spectroscopic Imaging in a cohort of 42 patients with secondary progressive multiple sclerosis (SPMS). Linear modelling with respect to brain tissue type yielded metabolite levels that were significantly different in white matter lesions compared with normal-appearing white matter, suggestive of higher myelin turnover (higher choline), higher metabolic rate (higher creatine) and increased glial activity (higher myo-inositol) within the lesions. These findings suggest that the lesions have ongoing cellular activity that is not consistent with the usual assumption of 'chronic' lesions in SPMS, and may represent a target for repair therapies.

Radiation pattern synthesis of planar antennas using the iterative sampling method

NASA Technical Reports Server (NTRS)

Stutzman, W. L.; Coffey, E. L.

1975-01-01

A synthesis method is presented for determining an excitation of an arbitrary (but fixed) planar source configuration. The desired radiation pattern is specified over all or part of the visible region. It may have multiple and/or shaped main beams with low sidelobes. The iterative sampling method is used to find an excitation of the source which yields a radiation pattern that approximates the desired pattern to within a specified tolerance. In this paper the method is used to calculate excitations for line sources, linear arrays (equally and unequally spaced), rectangular apertures, rectangular arrays (arbitrary spacing grid), and circular apertures. Examples using these sources to form patterns with shaped main beams, multiple main beams, shaped sidelobe levels, and combinations thereof are given.

Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering.

PubMed

He, Zhaoshui; Xie, Shengli; Zdunek, Rafal; Zhou, Guoxu; Cichocki, Andrzej

2011-12-01

Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on symmetric NMF (SNMF), which is a special case of NMF decomposition. Three parallel multiplicative update algorithms using level 3 basic linear algebra subprograms directly are developed for this problem. First, by minimizing the Euclidean distance, a multiplicative update algorithm is proposed, and its convergence under mild conditions is proved. Based on it, we further propose another two fast parallel methods: α-SNMF and β -SNMF algorithms. All of them are easy to implement. These algorithms are applied to probabilistic clustering. We demonstrate their effectiveness for facial image clustering, document categorization, and pattern clustering in gene expression.

Finite-Length Line Source Superposition Model (FLLSSM)

NASA Astrophysics Data System (ADS)

1980-03-01

A linearized thermal conduction model was developed to economically determine media temperatures in geologic repositories for nuclear wastes. Individual canisters containing either high level waste or spent fuel assemblies were represented as finite length line sources in a continuous media. The combined effects of multiple canisters in a representative storage pattern were established at selected points of interest by superposition of the temperature rises calculated for each canister. The methodology is outlined and the computer code FLLSSM which performs required numerical integrations and superposition operations is described.

The brain as a dynamic physical system.

PubMed

McKenna, T M; McMullen, T A; Shlesinger, M F

1994-06-01

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.

European Multicenter Study on Analytical Performance of DxN Veris System HCV Assay.

PubMed

Braun, Patrick; Delgado, Rafael; Drago, Monica; Fanti, Diana; Fleury, Hervé; Gismondo, Maria Rita; Hofmann, Jörg; Izopet, Jacques; Kühn, Sebastian; Lombardi, Alessandra; Marcos, Maria Angeles; Sauné, Karine; O'Shea, Siobhan; Pérez-Rivilla, Alfredo; Ramble, John; Trimoulet, Pascale; Vila, Jordi; Whittaker, Duncan; Artus, Alain; Rhodes, Daniel W

2017-04-01

The analytical performance of the Veris HCV Assay for use on the new and fully automated Beckman Coulter DxN Veris Molecular Diagnostics System (DxN Veris System) was evaluated at 10 European virology laboratories. Precision, analytical sensitivity, specificity, and performance with negative samples, linearity, and performance with hepatitis C virus (HCV) genotypes were evaluated. Precision for all sites showed a standard deviation (SD) of 0.22 log 10 IU/ml or lower for each level tested. Analytical sensitivity determined by probit analysis was between 6.2 and 9.0 IU/ml. Specificity on 94 unique patient samples was 100%, and performance with 1,089 negative samples demonstrated 100% not-detected results. Linearity using patient samples was shown from 1.34 to 6.94 log 10 IU/ml. The assay demonstrated linearity upon dilution with all HCV genotypes. The Veris HCV Assay demonstrated an analytical performance comparable to that of currently marketed HCV assays when tested across multiple European sites. Copyright © 2017 American Society for Microbiology.

Bayesian Correction for Misclassification in Multilevel Count Data Models.

PubMed

Nelson, Tyler; Song, Joon Jin; Chin, Yoo-Mi; Stamey, James D

2018-01-01

Covariate misclassification is well known to yield biased estimates in single level regression models. The impact on hierarchical count models has been less studied. A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed. Models with a single diagnostic test and with multiple diagnostic tests are considered. Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators. A real data example further demonstrated the consequences of ignoring the misclassification. Ignoring misclassification yielded a model that indicated there was a significant, positive impact on the number of children of females who observed spousal abuse between their parents. When the misclassification was accounted for, the relationship switched to negative, but not significant. Ignoring misclassification in standard linear and generalized linear models is well known to lead to biased results. We provide an approach to extend misclassification modeling to the important area of hierarchical generalized linear models.

The effect of operations on the ground noise footprints associated with a large multibladed, nonbanging helicopter

NASA Technical Reports Server (NTRS)

Hilton, D. A.; Henderson, H. R.; Maglieri, D. J.; Bigler, W. B., II

1978-01-01

In order to expand the data base of helicopter external noise characteristics, a flyover noise measurement program was conducted utilizing the NASA Civil Helicopter Research Aircraft. The remotely operated multiple array acoustics range (ROMAAR) and a 2560-m linear microphone array were utilized for the purpose of documenting the noise characteristics of the test helicopter during flyby and landing operations. By utilizing both ROMAAR concept and the linear array, the data necessary to plot the ground noise footprints and noise radiation patterns were obtained. Examples of the measured noise signature of the test helicopter, the ground noise footprint or contours, and the directivity patterns measured during level flyby and landing operations of a large, multibladed, nonbanging helicopter, the CH-53, are presented.

Vector Potential Generation for Numerical Relativity Simulations

NASA Astrophysics Data System (ADS)

Silberman, Zachary; Faber, Joshua; Adams, Thomas; Etienne, Zachariah; Ruchlin, Ian

2017-01-01

Many different numerical codes are employed in studies of highly relativistic magnetized accretion flows around black holes. Based on the formalisms each uses, some codes evolve the magnetic field vector B, while others evolve the magnetic vector potential A, the two being related by the curl: B=curl(A). Here, we discuss how to generate vector potentials corresponding to specified magnetic fields on staggered grids, a surprisingly difficult task on finite cubic domains. The code we have developed solves this problem in two ways: a brute-force method, whose scaling is nearly linear in the number of grid cells, and a direct linear algebra approach. We discuss the success both algorithms have in generating smooth vector potential configurations and how both may be extended to more complicated cases involving multiple mesh-refinement levels. NSF ACI-1550436

An improved multiple flame photometric detector for gas chromatography.

PubMed

Clark, Adrian G; Thurbide, Kevin B

2015-11-20

An improved multiple flame photometric detector (mFPD) is introduced, based upon interconnecting fluidic channels within a planar stainless steel (SS) plate. Relative to the previous quartz tube mFPD prototype, the SS mFPD provides a 50% reduction in background emission levels, an orthogonal analytical flame, and easier more sensitive operation. As a result, sulfur response in the SS mFPD spans 4 orders of magnitude, yields a minimum detectable limit near 9×10(-12)gS/s, and has a selectivity approaching 10(4) over carbon. The device also exhibits exceptionally large resistance to hydrocarbon response quenching. Additionally, the SS mFPD uniquely allows analyte emission monitoring in the multiple worker flames for the first time. The findings suggest that this mode can potentially further improve upon the analytical flame response of sulfur (both linear HSO, and quadratic S2) and also phosphorus. Of note, the latter is nearly 20-fold stronger in S/N in the collective worker flames response and provides 6 orders of linearity with a detection limit of about 2.0×10(-13)gP/s. Overall, the results indicate that this new SS design notably improves the analytical performance of the mFPD and can provide a versatile and beneficial monitoring tool for gas chromatography. Copyright © 2015 Elsevier B.V. All rights reserved.

Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information.

PubMed

Hieke, Stefanie; Benner, Axel; Schlenl, Richard F; Schumacher, Martin; Bullinger, Lars; Binder, Harald

2016-08-30

High-throughput technology allows for genome-wide measurements at different molecular levels for the same patient, e.g. single nucleotide polymorphisms (SNPs) and gene expression. Correspondingly, it might be beneficial to also integrate complementary information from different molecular levels when building multivariable risk prediction models for a clinical endpoint, such as treatment response or survival. Unfortunately, such a high-dimensional modeling task will often be complicated by a limited overlap of molecular measurements at different levels between patients, i.e. measurements from all molecular levels are available only for a smaller proportion of patients. We propose a sequential strategy for building clinical risk prediction models that integrate genome-wide measurements from two molecular levels in a complementary way. To deal with partial overlap, we develop an imputation approach that allows us to use all available data. This approach is investigated in two acute myeloid leukemia applications combining gene expression with either SNP or DNA methylation data. After obtaining a sparse risk prediction signature e.g. from SNP data, an automatically selected set of prognostic SNPs, by componentwise likelihood-based boosting, imputation is performed for the corresponding linear predictor by a linking model that incorporates e.g. gene expression measurements. The imputed linear predictor is then used for adjustment when building a prognostic signature from the gene expression data. For evaluation, we consider stability, as quantified by inclusion frequencies across resampling data sets. Despite an extremely small overlap in the application example with gene expression and SNPs, several genes are seen to be more stably identified when taking the (imputed) linear predictor from the SNP data into account. In the application with gene expression and DNA methylation, prediction performance with respect to survival also indicates that the proposed approach might work well. We consider imputation of linear predictor values to be a feasible and sensible approach for dealing with partial overlap in complementary integrative analysis of molecular measurements at different levels. More generally, these results indicate that a complementary strategy for integrating different molecular levels can result in more stable risk prediction signatures, potentially providing a more reliable insight into the underlying biology.

Addressing Chronic Malnutrition through Multi-Sectoral, Sustainable Approaches: A Review of the Causes and Consequences

PubMed Central

Reinhardt, Kristina; Fanzo, Jessica

2014-01-01

Chronic malnutrition, including stunting, is an important example of a global challenge that spans multiple sectors, specifically health, agriculture, and the environment. The objective of this paper is to review current knowledge on the causes and consequences of chronic malnutrition and their relationship with multiple sectors. Understanding the causes includes approaching chronic malnutrition from the basic, underlying, and immediate levels. The causes reach from macro-level environmental influences to specific micronutrient intake. In order to effectively address stunting, it is important to understand the timing of stunting and the ability of individuals to catch up in terms of linear growth, cognitive ability, and immune function. The consequences of chronic malnutrition are transgenerational and they have an impact at the individual, community, and national level in the short- and long-term. There are still many gaps in knowledge regarding both the causes and consequences of chronic malnutrition, particularly when it comes to the interaction with agriculture and the environment, and understanding these gaps is important to addressing the burden of chronic malnutrition through evidence-based interventions. PMID:25988116

A modified discrete algebraic reconstruction technique for multiple grey image reconstruction for limited angle range tomography.

PubMed

Liang, Zhiting; Guan, Yong; Liu, Gang; Chen, Xiangyu; Li, Fahu; Guo, Pengfei; Tian, Yangchao

2016-03-01

The `missing wedge', which is due to a restricted rotation range, is a major challenge for quantitative analysis of an object using tomography. With prior knowledge of the grey levels, the discrete algebraic reconstruction technique (DART) is able to reconstruct objects accurately with projections in a limited angle range. However, the quality of the reconstructions declines as the number of grey levels increases. In this paper, a modified DART (MDART) was proposed, in which each independent region of homogeneous material was chosen as a research object, instead of the grey values. The grey values of each discrete region were estimated according to the solution of the linear projection equations. The iterative process of boundary pixels updating and correcting the grey values of each region was executed alternately. Simulation experiments of binary phantoms as well as multiple grey phantoms show that MDART is capable of achieving high-quality reconstructions with projections in a limited angle range. The interesting advancement of MDART is that neither prior knowledge of the grey values nor the number of grey levels is necessary.

Noise reduction in long‐period seismograms by way of array summing

USGS Publications Warehouse

Ringler, Adam; Wilson, David; Storm, Tyler; Marshall, Benjamin T.; Hutt, Charles R.; Holland, Austin

2016-01-01

Long‐period (>100  s period) seismic data can often be dominated by instrumental noise as well as local site noise. When multiple collocated sensors are installed at a single site, it is possible to improve the overall station noise levels by applying stacking methods to their traces. We look at the noise reduction in long‐period seismic data by applying the time–frequency phase‐weighted stacking method of Schimmel and Gallart (2007) as well as the phase‐weighted stacking (PWS) method of Schimmel and Paulssen (1997) to four collocated broadband sensors installed in the quiet Albuquerque Seismological Laboratory underground vault. We show that such stacking methods can improve vertical noise levels by as much as 10 dB over the mean background noise levels at 400 s period, suggesting that greater improvements could be achieved with an array involving multiple sensors. We also apply this method to reduce local incoherent noise on horizontal seismic records of the 2 March 2016 Mw 7.8 Sumatra earthquake, where the incoherent noise levels at very long periods are similar in amplitude to the earthquake signal. To maximize the coherency, we apply the PWS method to horizontal data where relative azimuths between collocated sensors are estimated and compared with a simpler linear stack with no azimuthal rotation. Such methods could help reduce noise levels at various seismic stations where multiple high‐quality sensors have been deployed. Such small arrays may also provide a solution to improving long‐period noise levels at Global Seismographic Network stations.

Simulated bi-SQUID Arrays Performing Direction Finding

DTIC Science & Technology

2015-09-01

First, we applied the multiple signal classification ( MUSIC ) algorithm on linearly polarized signals. We included multiple signals in the output...both of the same frequency and different fre- quencies. Next, we explored a modified MUSIC algorithm called dimensionality reduction MUSIC (DR- MUSIC ... MUSIC algorithm is able to determine the AoA from the simulated SQUID data for linearly polarized signals. The MUSIC algorithm could accurately find

Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis

PubMed Central

Khalil, Mohamed H.; Shebl, Mostafa K.; Kosba, Mohamed A.; El-Sabrout, Karim; Zaki, Nesma

2016-01-01

Aim: This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens’ eggs. Materials and Methods: Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. Results: The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. Conclusion: A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens. PMID:27651666

A non-linear regression analysis program for describing electrophysiological data with multiple functions using Microsoft Excel.

PubMed

Brown, Angus M

2006-04-01

The objective of this present study was to demonstrate a method for fitting complex electrophysiological data with multiple functions using the SOLVER add-in of the ubiquitous spreadsheet Microsoft Excel. SOLVER minimizes the difference between the sum of the squares of the data to be fit and the function(s) describing the data using an iterative generalized reduced gradient method. While it is a straightforward procedure to fit data with linear functions, and we have previously demonstrated a method of non-linear regression analysis of experimental data based upon a single function, it is more complex to fit data with multiple functions, usually requiring specialized expensive computer software. In this paper we describe an easily understood program for fitting experimentally acquired data, in this case the stimulus-evoked compound action potential from the mouse optic nerve, with multiple Gaussian functions. The program is flexible and can be applied to describe data with a wide variety of user-input functions.

Adaptive receiver structures for asynchronous CDMA systems

NASA Astrophysics Data System (ADS)

Rapajic, Predrag B.; Vucetic, Branka S.

1994-05-01

Adaptive linear and decision feedback receiver structures for coherent demodulation in asynchronous code division multiple access (CDMA) systems are considered. It is assumed that the adaptive receiver has no knowledge of the signature waveforms and timing of other users. The receiver is trained by a known training sequence prior to data transmission and continuously adjusted by an adaptive algorithm during data transmission. The proposed linear receiver is as simple as a standard single-user detector receiver consisting of a matched filter with constant coefficients, but achieves essential advantages with respect to timing recovery, multiple access interference elimination, near/far effect, narrowband and frequency-selective fading interference suppression, and user privacy. An adaptive centralized decision feedback receiver has the same advantages of the linear receiver but, in addition, achieves a further improvement in multiple access interference cancellation at the expense of higher complexity. The proposed receiver structures are tested by simulation over a channel with multipath propagation, multiple access interference, narrowband interference, and additive white Gaussian noise.

Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model

PubMed Central

Seaman, Shaun R; White, Ian R; Carpenter, James R

2015-01-01

Missing covariate data commonly occur in epidemiological and clinical research, and are often dealt with using multiple imputation. Imputation of partially observed covariates is complicated if the substantive model is non-linear (e.g. Cox proportional hazards model), or contains non-linear (e.g. squared) or interaction terms, and standard software implementations of multiple imputation may impute covariates from models that are incompatible with such substantive models. We show how imputation by fully conditional specification, a popular approach for performing multiple imputation, can be modified so that covariates are imputed from models which are compatible with the substantive model. We investigate through simulation the performance of this proposal, and compare it with existing approaches. Simulation results suggest our proposal gives consistent estimates for a range of common substantive models, including models which contain non-linear covariate effects or interactions, provided data are missing at random and the assumed imputation models are correctly specified and mutually compatible. Stata software implementing the approach is freely available. PMID:24525487

A new adaptive multiple modelling approach for non-linear and non-stationary systems

NASA Astrophysics Data System (ADS)

Chen, Hao; Gong, Yu; Hong, Xia

2016-07-01

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.

Robust control of a parallel hybrid drivetrain with a CVT

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

Mayer, T.; Schroeder, D.

1996-09-01

In this paper the design of a robust control system for a parallel hybrid drivetrain is presented. The drivetrain is based on a continuously variable transmission (CVT) and is therefore a highly nonlinear multiple-input-multiple-output system (MIMO-System). Input-Output-Linearization offers the possibility of linearizing and of decoupling the system. Since for example the vehicle mass varies with the load and the efficiency of the gearbox depends strongly on the actual working point, an exact linearization of the plant will mostly fail. Therefore a robust control algorithm based on sliding mode is used to control the drivetrain.

Factors associated with self-management by people undergoing hemodialysis: a descriptive study.

PubMed

Li, Hui; Jiang, Ya-Fang; Lin, Chiu-Chu

2014-02-01

Improving the level of self-management by people undergoing hemodialysis is an effective way to reduce the incidence of mortality and complications and improve quality of life. A better understanding of what influences an individual's level of self-management can help nurses find appropriate ways to improve self-management. To examine self-management levels, and discuss the factors influencing self-management, in a sample of patients undergoing hemodialysis in Beijing. A descriptive study design was chosen. A convenience sample of 216 patients undergoing hemodialysis was recruited from dialysis centers in three tertiary hospitals in Beijing from September 2010 to January 2011. Questionnaires were used to examine the variables: level of self-management; knowledge of hemodialysis; self-efficacy; anxiety and depression; and social support. Data analysis involved descriptive statistics, including frequency, percentage, mean and standard deviations, while Spearman correlation, non-parametric Z and χ(2) and multiple linear regression were used for comparative purposes. The number of returned questionnaires was 198 (91.67% response rate). The overall score of self-management was 56.01 (SD=10.75). The average item scores for each of the four self-management subscales were 3.02 for partnership, 2.98 for problem-solving skills, 2.74 for self-care and 2.47 for emotional management. Multiple linear regression analyses for overall self-management and the four subscales indicated that knowledge, self-efficacy, the availability of social support and depression were the main influencing factors which explained 34.1% of the variance of self-management. The level of self-management by those undergoing hemodialysis in this study was less than ideal, varying from 'rare' to 'sometimes' for use of self-management behaviors. For the different subscales of self-management, partnership was the most used and emotional management the least used strategy. Patients' knowledge, self-efficacy, the availability of social support and depression were the main factors influencing self-management. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Resting metabolic rate estimated by bioelectrical impedance analysis and its determinants in maintenance hemodialysis patients].

PubMed

Da, J J; Peng, H Y; Lin, X; Shen, Y; Zhao, J Q; He, S; Zha, Y

2018-03-27

Objective: To explore the level of resting energy expenditure (REE) estimated by bioelectrical impedance analysis and the association of resting metabolic rate (RMR) with clinical related factors, and provide new ideas for improving protein energy wasting (PEW) in maintenance hemodialysis (MHD) patients. Methods: Seven hundred and sixty-five subjects receiving MHD between July 2015 and September 2016 in 11 hemodialysis centers in Guizhou province were enrolled in this cross-sectional study. Bioelectrical impedance analysis was used to measure RMR and body composition, such as lean body mass, fat mass and body cell mass (BCM). Baseline characteristics, routine blood test indexes and biochemical data of hemodialysis patients were collected. The level of RMR and body composition in hemodialysis patients was compared by gender grouping. Then the patients were divided into four groups according to the cutoff value of RMR quartile. Spearman correlation analysis and multiple linear regression analysis were used to analyze the relationships between RMR and clinical related factors. Results: The average age of MHD patients was (54.96±15.78) years and the duriation of dialysis was (42.3±9.0) months. The level of RMR in male patients (474 cases, 61.96%) was significantly higher than that in female patients [1 591(1 444, 1 764) kcal/d vs 1 226 (1 104, 1 354) kcal/d, P <0.001]. However, this significant difference of RMR between different genders disappeared after adjusting for lean body mass ( P =0.193). Multiple linear regression analysis showed that RMR was positively correlated with body surface area (β=0.817) and lactate dehydrogenase (LDH) (β=0.198), and negatively correlated with age (β=-0.141), all P <0.05. Conclusion: RMR levels in patients with maintenance hemodialysis are associated with lactate dehydrogenase level, which may become a new index to evaluate energy consumption.

Modified Hyperspheres Algorithm to Trace Homotopy Curves of Nonlinear Circuits Composed by Piecewise Linear Modelled Devices

PubMed Central

Vazquez-Leal, H.; Jimenez-Fernandez, V. M.; Benhammouda, B.; Filobello-Nino, U.; Sarmiento-Reyes, A.; Ramirez-Pinero, A.; Marin-Hernandez, A.; Huerta-Chua, J.

2014-01-01

We present a homotopy continuation method (HCM) for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL) representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation. PMID:25184157

Features in visual search combine linearly

PubMed Central

Pramod, R. T.; Arun, S. P.

2014-01-01

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features (intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and co-activation models (based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features—in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search. PMID:24715328

Dose-Response for Multiple Biomarkers of Exposure and Genotoxic Effect Following Repeated Treatment of Rats with the Alkylating Agents, MMS and MNU.

PubMed

Ji, Zhiying; LeBaron, Matthew J; Schisler, Melissa R; Zhang, Fagen; Bartels, Michael J; Gollapudi, B Bhaskar; Pottenger, Lynn H

2016-05-01

The nature of the dose-response relationship for various in vivo endpoints of exposure and effect were investigated using the alkylating agents, methyl methanesulfonate (MMS) and methylnitrosourea (MNU). Six male F344 rats/group were dosed orally with 0, 0.5, 1, 5, 25 or 50mg/kg bw/day (mkd) of MMS, or 0, 0.01, 0.1, 1, 5, 10, 25 or 50 mkd of MNU, for 4 consecutive days and sacrificed 24h after the last dose. The dose-responses for multiple biomarkers of exposure and genotoxic effect were investigated. In MMS-treated rats, the hemoglobin adduct level, a systemic exposure biomarker, increased linearly with dose (r (2) = 0.9990, P < 0.05), indicating the systemic availability of MMS; however, the N7MeG DNA adduct, a target exposure biomarker, exhibited a non-linear dose-response in blood and liver tissues. Blood reticulocyte micronuclei (MN), a genotoxic effect biomarker, exhibited a clear no-observed-genotoxic-effect-level (NOGEL) of 5 mkd as a point of departure (PoD) for MMS. Two separate dose-response models, the Lutz and Lutz model and the stepwise approach using PROC REG both supported a bilinear/threshold dose-response for MN induction. Liver gene expression, a mechanistic endpoint, also exhibited a bilinear dose-response. Similarly, in MNU-treated rats, hepatic DNA adducts, gene expression changes and MN all exhibited clear PoDs, with a NOGEL of 1 mkd for MN induction, although dose-response modeling of the MNU-induced MN data showed a better statistical fit for a linear dose-response. In summary, these results provide in vivo data that support the existence of clear non-linear dose-responses for a number of biologically significant events along the pathway for genotoxicity induced by DNA-reactive agents. © The Author 2015. 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.

Multiple-Targeted Graphene-based Nanocarrier for Intracellular Imaging of mRNAs

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

Wang, Ying; Li, Zhaohui; Liu, Misha

Simultaneous detection and imaging of multiple intracellular messenger RNA (mRNAs) hold great significant for early cancer diagnostics and preventive medicine development. Herein, we propose a multiple-targeted graphene oxide (GO) nanocarrier that can simultaneously detect and image different type mRNAs in living cells. First of all, in vitro detection of multiple targets have been realized successfully based on the multiple-targeted GO nanocarrier with linear relationship ranging from 3 nM to 200 nM, as well as sensitive detection limit of 1.84 nM for manganese superoxide dismutase (Mn-SOD) mRNA and 2.45 nM for β-actin mRNA. Additionally, this nanosensing platform composed of fluorescent labeledmore » single strand DNA probes and GO nanocarrier can identify Mn-SOD mRNA and endogenous mRNA of β-actin in living cancer cells, showing rapid response, high specificity, nuclease stability, and good biocompatibility during the cell imaging. Thirdly, changes of the expression levels of mRNA in living cells before or after the drug treatment can be monitored successfully. By using multiple ssDNA as probes and GO nanocarrier as the cellular delivery cargo, the proposed simultaneous multiple-targeted sensing platform will be of great potential as a powerful tool for intracellular trafficking process from basic research to clinical diagnosis.« less

Tipping points? Curvilinear associations between activity level and mental development in toddlers.

PubMed

Flom, Megan; Cohen, Madeleine; Saudino, Kimberly J

2017-05-01

The Theory of Optimal Stimulation (Zentall & Zentall, Psychological Bulletin, 94, 1983, 446) posits that the relation between activity level (AL) and cognitive performance follows an inverted U shape where midrange AL predicts better cognitive performance than AL at the extremes. We explored this by fitting linear and quadratic models predicting mental development from AL assessed via multiple methods (parent ratings, observations, and actigraphs) and across multiple situations (laboratory play, laboratory test, home) in over 600 twins (2- and 3-year olds). Only observed AL in the laboratory was curvilinearly related to mental development scores. Results replicated across situations, age, and twin samples, providing strong support for the optimal stimulation model for this measure of AL in early childhood. Different measures of AL provide different information. Observations of AL which include both qualitative and quantitative aspects of AL within structured situations are able to capture beneficial aspects of normative AL as well as detriments of both low and high AL. © 2016 Association for Child and Adolescent Mental Health.

Bayesian model reduction and empirical Bayes for group (DCM) studies

PubMed Central

Friston, Karl J.; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E.; van Wijk, Bernadette C.M.; Ziegler, Gabriel; Zeidman, Peter

2016-01-01

This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level – e.g., dynamic causal models – and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. PMID:26569570

Analysis of Sequence Data Under Multivariate Trait-Dependent Sampling.

PubMed

Tao, Ran; Zeng, Donglin; Franceschini, Nora; North, Kari E; Boerwinkle, Eric; Lin, Dan-Yu

2015-06-01

High-throughput DNA sequencing allows for the genotyping of common and rare variants for genetic association studies. At the present time and for the foreseeable future, it is not economically feasible to sequence all individuals in a large cohort. A cost-effective strategy is to sequence those individuals with extreme values of a quantitative trait. We consider the design under which the sampling depends on multiple quantitative traits. Under such trait-dependent sampling, standard linear regression analysis can result in bias of parameter estimation, inflation of type I error, and loss of power. We construct a likelihood function that properly reflects the sampling mechanism and utilizes all available data. We implement a computationally efficient EM algorithm and establish the theoretical properties of the resulting maximum likelihood estimators. Our methods can be used to perform separate inference on each trait or simultaneous inference on multiple traits. We pay special attention to gene-level association tests for rare variants. We demonstrate the superiority of the proposed methods over standard linear regression through extensive simulation studies. We provide applications to the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study and the National Heart, Lung, and Blood Institute Exome Sequencing Project.

Risk factors for development of multiple-class resistance to Streptococcus pneumoniae Strains in Belgium over a 10-year period: antimicrobial consumption, population density, and geographic location.

PubMed

Van Eldere, Johan; Mera, Robertino M; Miller, Linda A; Poupard, James A; Amrine-Madsen, Heather

2007-10-01

We investigated the impact of the usage of antibiotics in ambulatory patients in Belgium in 147 defined geographical circumscriptions and at the individual isolate level. The study included 14,448 Streptococcus pneumoniae strains collected by the Belgium national reference lab from 1994 to 2004. Additional risk factors for resistance, such as population density/structure and day care attendance, were investigated for the same time-space window. A statistical model that included resistance to two or more antimicrobial classes offered the best fit for measuring the changes in nonsusceptibility to penicillin, macrolides, and tetracycline over time and place in Belgium. Analysis at the geographic level identified antimicrobial consumption with a 1-year lag (0.5% increase per additional defined daily dose) and population density as independent predictors of multiple resistance. Independent risk factors at the isolate level were age (odds ratio [OR], 1.55 for children aged <5 years), population density (7% increase in multiple resistance per 100 inhabitants/km(2)), conjugate 7-valent vaccine serotype (OR, 14.3), location (OR, 1.55 for regions bordering high-resistance France), and isolate source (OR, 1.54 for ear isolates). The expansion of multiple-resistant strains explains most of the overall twofold increase and subsequent decrease in single antimicrobial resistance between 1994 and 2004. We conclude that factors in addition to antibiotic use, such as high population density and proximity to high-resistance regions, favor multiple resistance. Regional resistance rates are not linearly related to actual antibiotic use but are linked to past antibiotic use plus a combination of demographic and geographic factors.

Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector

NASA Technical Reports Server (NTRS)

Huntington, Andrew

2013-01-01

The purpose of this program was to develop single-photon-sensitive short-wavelength infrared (SWIR) and mid-wavelength infrared (MWIR) avalanche photodiode (APD) receivers based on linear-mode HgCdTe APDs, for application by NASA in light detection and ranging (lidar) sensors. Linear-mode photon-counting APDs are desired for lidar because they have a shorter pixel dead time than Geiger APDs, and can detect sequential pulse returns from multiple objects that are closely spaced in range. Linear-mode APDs can also measure photon number, which Geiger APDs cannot, adding an extra dimension to lidar scene data for multi-photon returns. High-gain APDs with low multiplication noise are required for efficient linear-mode detection of single photons because of APD gain statistics -- a low-excess-noise APD will generate detectible current pulses from single photon input at a much higher rate of occurrence than will a noisy APD operated at the same average gain. MWIR and LWIR electron-avalanche HgCdTe APDs have been shown to operate in linear mode at high average avalanche gain (M > 1000) without excess multiplication noise (F = 1), and are therefore very good candidates for linear-mode photon counting. However, detectors fashioned from these narrow-bandgap alloys require aggressive cooling to control thermal dark current. Wider-bandgap SWIR HgCdTe APDs were investigated in this program as a strategy to reduce detector cooling requirements.

Brain-derived neurotrophic factor mediates cognitive improvements following acute exercise.

PubMed

Borror, Andrew

2017-09-01

The mechanisms causing improved cognition following acute exercise are poorly understood. This article proposes that brain-derived neurotrophic factor (BDNF) is the main factor contributing to improved cognition following exercise. Additionally, it argues that cerebral blood flow (CBF) and oxidative stress explain the release of BDNF from cerebral endothelial cells. One way to test these hypotheses is to block endothelial function and measure the effect on BDNF levels and cognitive performance. The CBF and oxidative stress can also be examined in relationship to BDNF using a multiple linear regression. If these hypotheses are true, there would be a linear relationship between CBF+oxidative stress and BDNF levels as well as between BDNF levels and cognitive performance. The novelty of these hypotheses comes from the emphasis on the cerebral endothelium and the interplay between BDNF, CBF, and oxidative stress. If found to be valid, these hypotheses would draw attention to the cerebral endothelium and provide direction for future research regarding methods to optimize BDNF release and enhance cognition. Elucidating these mechanisms would provide direction for expediting recovery in clinical populations, such as stroke, and maintaining quality of life in the elderly. Copyright © 2017 Elsevier Ltd. All rights reserved.

Existing methods for improving the accuracy of digital-to-analog converters

NASA Astrophysics Data System (ADS)

Eielsen, Arnfinn A.; Fleming, Andrew J.

2017-09-01

The performance of digital-to-analog converters is principally limited by errors in the output voltage levels. Such errors are known as element mismatch and are quantified by the integral non-linearity. Element mismatch limits the achievable accuracy and resolution in high-precision applications as it causes gain and offset errors, as well as harmonic distortion. In this article, five existing methods for mitigating the effects of element mismatch are compared: physical level calibration, dynamic element matching, noise-shaping with digital calibration, large periodic high-frequency dithering, and large stochastic high-pass dithering. These methods are suitable for improving accuracy when using digital-to-analog converters that use multiple discrete output levels to reconstruct time-varying signals. The methods improve linearity and therefore reduce harmonic distortion and can be retrofitted to existing systems with minor hardware variations. The performance of each method is compared theoretically and confirmed by simulations and experiments. Experimental results demonstrate that three of the five methods provide significant improvements in the resolution and accuracy when applied to a general-purpose digital-to-analog converter. As such, these methods can directly improve performance in a wide range of applications including nanopositioning, metrology, and optics.

Female married illiteracy as the most important continual determinant of total fertility rate among districts of Empowered Action Group States of India: Evidence from Annual Health Survey 2011–12

PubMed Central

Kumar, Rajesh; Dogra, Vishal; Rani, Khushbu; Sahu, Kanti

2017-01-01

Background: District level determinants of total fertility rate in Empowered Action Group states of India can help in ongoing population stabilization programs in India. Objective: Present study intends to assess the role of district level determinants in predicting total fertility rate among districts of the Empowered Action Group states of India. Material and Methods: Data from Annual Health Survey (2011-12) was analysed using STATA and R software packages. Multiple linear regression models were built and evaluated using Akaike Information Criterion. For further understanding, recursive partitioning was used to prepare a regression tree. Results: Female married illiteracy positively associated with total fertility rate and explained more than half (53%) of variance. Under multiple linear regression model, married illiteracy, infant mortality rate, Ante natal care registration, household size, median age of live birth and sex ratio explained 70% of total variance in total fertility rate. In regression tree, female married illiteracy was the root node and splits at 42% determined TFR <= 2.7. The next left side branch was again married illiteracy with splits at 23% to determine TFR <= 2.1. Conclusion: We conclude that female married illiteracy is one of the most important determinants explaining total fertility rate among the districts of an Empowered Action Group states. Focus on female literacy is required to stabilize the population growth in long run. PMID:29416999

Inexact fuzzy-stochastic mixed-integer programming approach for long-term planning of waste management--Part A: methodology.

PubMed

Guo, P; Huang, G H

2009-01-01

In this study, an inexact fuzzy chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is proposed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing inexact two-stage programming and mixed-integer linear programming techniques by incorporating uncertainties expressed as multiple uncertainties of intervals and dual probability distributions within a general optimization framework. The developed method can provide an effective linkage between the predefined environmental policies and the associated economic implications. Four special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it provides a linkage to predefined policies that have to be respected when a modeling effort is undertaken; secondly, it is useful for tackling uncertainties presented as intervals, probabilities, fuzzy sets and their incorporation; thirdly, it facilitates dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period, multi-level, and multi-option context; fourthly, the penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised solid waste-generation rates are violated. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the City of Regina, Canada.

Associations between Bisphenol A Exposure and Reproductive Hormones among Female Workers

PubMed Central

Miao, Maohua; Yuan, Wei; Yang, Fen; Liang, Hong; Zhou, Zhijun; Li, Runsheng; Gao, Ersheng; Li, De-Kun

2015-01-01

The associations between Bisphenol-A (BPA) exposure and reproductive hormone levels among women are unclear. A cross-sectional study was conducted among female workers from BPA-exposed and unexposed factories in China. Women’s blood samples were collected for assay of follicle-stimulating hormone (FSH), luteinizing hormone (LH), 17β-Estradiol (E2), prolactin (PRL), and progesterone (PROG). Their urine samples were collected for BPA measurement. In the exposed group, time weighted average exposure to BPA for an 8-h shift (TWA8), a measure incorporating historic exposure level, was generated based on personal air sampling. Multiple linear regression analyses were used to examine linear associations between urine BPA concentration and reproductive hormones after controlling for potential confounders. A total of 106 exposed and 250 unexposed female workers were included in this study. A significant positive association between increased urine BPA concentration and higher PRL and PROG levels were observed. Similar associations were observed after the analysis was carried out separately among the exposed and unexposed workers. In addition, a positive association between urine BPA and E2 was observed among exposed workers with borderline significance, while a statistically significant inverse association between urine BPA and FSH was observed among unexposed group. The results suggest that BPA exposure may lead to alterations in female reproductive hormone levels. PMID:26506366

Associations between Bisphenol A Exposure and Reproductive Hormones among Female Workers.

PubMed

Miao, Maohua; Yuan, Wei; Yang, Fen; Liang, Hong; Zhou, Zhijun; Li, Runsheng; Gao, Ersheng; Li, De-Kun

2015-10-22

The associations between Bisphenol-A (BPA) exposure and reproductive hormone levels among women are unclear. A cross-sectional study was conducted among female workers from BPA-exposed and unexposed factories in China. Women's blood samples were collected for assay of follicle-stimulating hormone (FSH), luteinizing hormone (LH), 17β-Estradiol (E2), prolactin (PRL), and progesterone (PROG). Their urine samples were collected for BPA measurement. In the exposed group, time weighted average exposure to BPA for an 8-h shift (TWA8), a measure incorporating historic exposure level, was generated based on personal air sampling. Multiple linear regression analyses were used to examine linear associations between urine BPA concentration and reproductive hormones after controlling for potential confounders. A total of 106 exposed and 250 unexposed female workers were included in this study. A significant positive association between increased urine BPA concentration and higher PRL and PROG levels were observed. Similar associations were observed after the analysis was carried out separately among the exposed and unexposed workers. In addition, a positive association between urine BPA and E2 was observed among exposed workers with borderline significance, while a statistically significant inverse association between urine BPA and FSH was observed among unexposed group. The results suggest that BPA exposure may lead to alterations in female reproductive hormone levels.

Regional investigations of soil and overburden analysis and plant uptake of metals

USGS Publications Warehouse

Gough, L.P.

1984-01-01

Regional studies on the bioavailability of metals at native and disturbed sites were conducted over the past seven years by the USGS. The work was concentrated in the Fort Union, Powder River, and Green River coal resource regions where measures of extractable metals in soils were found to have limited use in predicting metal levels in plants. Correlations between Cu, Fe, and Zn in plants and extractable (DTPA, EDTA, and oxalate) or total levels in native A- and C-horizons of soil were occasionally significant. A simple linear model is generally not adequate, however, in estimating element uptake by plants. Prediction capabilities were improved when a number of soil chemical and physical parameters were included as independent variables in a stepwise linear multiple regression analysis; however, never more than 54% of the total variability in the data was explained by the equations for these metals. Soil pH was the most important variable relating soil chemistry to plant chemistry. This relation was always positive and apparently a response to soil levels of metal carbonates and not Fe and Mn oxides. Studies that compared the metal uptake by rehabilitation species to extractable (DTPA) metal levels in mice soils produced similar results. ?? 1984 Science and Technology Letters.

Linear and Nonlinear Thinking: A Multidimensional Model and Measure

ERIC Educational Resources Information Center

Groves, Kevin S.; Vance, Charles M.

2015-01-01

Building upon previously developed and more general dual-process models, this paper provides empirical support for a multidimensional thinking style construct comprised of linear thinking and multiple dimensions of nonlinear thinking. A self-report assessment instrument (Linear/Nonlinear Thinking Style Profile; LNTSP) is presented and…

Abnormal dynamics of language in schizophrenia.

PubMed

Stephane, Massoud; Kuskowski, Michael; Gundel, Jeanette

2014-05-30

Language could be conceptualized as a dynamic system that includes multiple interactive levels (sub-lexical, lexical, sentence, and discourse) and components (phonology, semantics, and syntax). In schizophrenia, abnormalities are observed at all language elements (levels and components) but the dynamic between these elements remains unclear. We hypothesize that the dynamics between language elements in schizophrenia is abnormal and explore how this dynamic is altered. We, first, investigated language elements with comparable procedures in patients and healthy controls. Second, using measures of reaction time, we performed multiple linear regression analyses to evaluate the inter-relationships among language elements and the effect of group on these relationships. Patients significantly differed from controls with respect to sub-lexical/lexical, lexical/sentence, and sentence/discourse regression coefficients. The intercepts of the regression slopes increased in the same order above (from lower to higher levels) in patients but not in controls. Regression coefficients between syntax and both sentence level and discourse level semantics did not differentiate patients from controls. This study indicates that the dynamics between language elements is abnormal in schizophrenia. In patients, top-down flow of linguistic information might be reduced, and the relationship between phonology and semantics but not between syntax and semantics appears to be altered. Published by Elsevier Ireland Ltd.

Symptom profile of multiple chemical sensitivity in actual life.

PubMed

Saito, Mariko; Kumano, Hiroaki; Yoshiuchi, Kazuhiro; Kokubo, Naomi; Ohashi, Kyoko; Yamamoto, Yoshiharu; Shinohara, Naohide; Yanagisawa, Yukio; Sakabe, Kou; Miyata, Mikio; Ishikawa, Satoshi; Kuboki, Tomifusa

2005-01-01

This study was conducted to confirm the definition of multiple chemical sensitivity (MCS) in actual life: that multiple symptoms are provoked in multiple organs by exposure to, and ameliorated by avoidance of, multiple chemicals at low levels. We used the Ecological Momentary Assessment to monitor everyday symptoms and the active sampling and passive sampling methods to measure environmental chemical exposure. Eighteen patients with MCS, diagnosed according to the 1999 consensus criteria, and 12 healthy controls participated in this study. Fourteen patients and 12 controls underwent 1-week measurement of physical and psychologic symptoms and of the levels of exposure to various chemicals. Linear mixed models were used to test the hypotheses regarding the symptom profile of MCS patients. Some causative chemicals were detected in 11 of 14 MCS patients. Two other patients did not report any hypersensitivity episodes, whereas passive sampling showed far less exposure to chemicals than control subjects. Another subject reported episodic symptoms but was excluded from the following analyses because no possible chemical was detected. Eleven of the 17 physical symptoms and all four mood subscales examined were significantly aggravated in the interview based on "patient-initiated symptom prompts." On the other hand, there were no differences in physical symptoms or mood subscales between MCS patients and control subjects in the interview based on "random prompts." MCS patients do not have either somatic or psychologic symptoms under chemical-free conditions, and symptoms may be provoked only when exposed to chemicals.

Association of Dentine Hypersensitivity with Different Risk Factors – A Cross Sectional Study

PubMed Central

Vijaya, V; Sanjay, Venkataraam; Varghese, Rana K; Ravuri, Rajyalakshmi; Agarwal, Anil

2013-01-01

Background: This study was done to assess the prevalence of Dentine hypersensitivity (DH) and its associated risk factors. Materials & Methods: This epidemiological study was done among patients coming to dental college regarding prevalence of DH. A self structured questionnaire along with clinical examination was done for assessment. Descriptive statistics were obtained and frequency distribution was calculated using Chi square test at p value <0.05. Stepwise multiple linear regression was also done to access frequency of DH with different factors. Results: The study population was comprised of 655 participants with different age groups. Our study showed prevalence as 55% and it was more common among males. Similarly smokers and those who use hard tooth brush had more cases of DH. Step wise multiple linear regression showed that best predictor for DH was age followed by habit of smoking and type of tooth brush. Most aggravating factors were cold water (15.4%) and sweet foods (14.7%), whereas only 5% of the patients had it while brushing. Conclusion: A high level of dental hypersensitivity has been in this study and more common among males. A linear finding was shown with age, smoking and type of tooth brush. How to cite this article: Vijaya V, Sanjay V, Varghese RK, Ravuri R, Agarwal A. Association of Dentine Hypersensitivity with Different Risk Factors – A Cross Sectional Study. J Int Oral Health 2013;5(6):88-92 . PMID:24453451

Multiple Intelligence Scores of Science Stream Students and Their Relation with Reading Competency in Malaysian University English Test (MUET)

ERIC Educational Resources Information Center

Razak, Norizan Abdul; Zaini, Nuramirah

2014-01-01

Many researches have shown that different approach needed in analysing linear and non-linear reading comprehension texts and different cognitive skills are required. This research attempts to discover the relationship between Science Stream students' reading competency on linear and non-linear texts in Malaysian University English Test (MUET) with…

Increased plasma/serum levels of prolactin in multiple sclerosis: a meta-analysis.

PubMed

Wei, Wei; Liu, Lei; Cheng, Zhong-Le; Hu, Bo

2017-08-01

Prolactin (PRL) is a polypeptide hormone that is known to stimulate humoral and cell mediated immune responses. PRL levels have been investigated in several autoimmune diseases including multiple sclerosis (MS); however, these have yielded different and inconsistent results. This study aims to perform a more precise evaluation on the plasma/serum PRL levels in MS patients, and to explore the available influential factors. Research related to plasma/serum PRL levels in MS patients and healthy controls were gathered using PubMed, EMBASE and The Cochrane Library database (until Mar 31 2016). Pooled standard mean difference (SMD) with 95% confidence interval (CI) was calculated by fixed-effects or random-effect model analysis. Heterogeneity test was performed by the Q statistic and quantified using I 2 , and publication bias was evaluated using a funnel plot and Egger's linear regression test. 516 articles were obtained after searching databases, and 8 studies with 426 MS patients and 296 controls were finally included. Meta-analysis revealed that, compared with the control group, the MS group had significantly higher plasma/serum PRL levels, with the SMD of 0.55 and 95%CI (0.39, 0.72). Subgroup analyses showed that region, age and disease duration were associated with PRL level in MS patients. In summary, our meta-analysis revealed a significantly higher PRL level in MS patients than healthy controls, and it is influenced by region, age and disease duration.

Factors associated with added sugars intake among adolescents living in São Paulo, Brazil.

PubMed

Colucci, Ana Carolina A; Cesar, Chester L G; Marchioni, Dirce M L; Fisberg, Regina M

2012-08-01

To measure added sugars intake among adolescents and describe its demographic, socioeconomic, and nutritional status determinants. The study was conducted based on a household survey carried out between March and December 2003. Food intake was assessed through 24-hour food recalls, and an adjustment approach was applied using external variance estimates derived from 195 adolescents of the same age in 2007. Population-based cross-sectional study, city of São Paulo, Brazil. Seven hundred and ninety-three male (n = 410) and female (n = 383) adolescents aged 10-19 years. MEASURE OF OUTCOME: Foods with greater contributions toward the added sugars intake were identified. Multiple linear regression analysis was performed, with calories from added sugars as the dependent continuous variable and the remaining factors (socioeconomic, demographic, lifestyle, household condition, and food intake) as independent variables. The average contribution of added sugars to total energy value was 12.28% (95% confidence interval [CI]: 11.87-12.70) with no statistically significant sex difference (p > 0.05). Soft drinks were a major source of added sugars among the adolescents (34.2% among males and 32.0% among females), followed by sugars (sucrose and honey) and chocolate powder (around 11%). In the multiple linear regression analysis, the head of household's education level and calories from protein, fats, and carbohydrates other than sugars had an independent effect on added sugars intake. This study showed that the percentage contribution of added sugars to energy intake among adolescents in the city of São Paulo, Brazil, was above the current recommended levels. Socioeconomic condition (represented by the head of the household's education level) and macronutrient intake were shown to be determinants of sugars intake.

DYGABCD: A program for calculating linear A, B, C, and D matrices from a nonlinear dynamic engine simulation

NASA Technical Reports Server (NTRS)

Geyser, L. C.

1978-01-01

A digital computer program, DYGABCD, was developed that generates linearized, dynamic models of simulated turbofan and turbojet engines. DYGABCD is based on an earlier computer program, DYNGEN, that is capable of calculating simulated nonlinear steady-state and transient performance of one- and two-spool turbojet engines or two- and three-spool turbofan engines. Most control design techniques require linear system descriptions. For multiple-input/multiple-output systems such as turbine engines, state space matrix descriptions of the system are often desirable. DYGABCD computes the state space matrices commonly referred to as the A, B, C, and D matrices required for a linear system description. The report discusses the analytical approach and provides a users manual, FORTRAN listings, and a sample case.

Transmit Designs for the MIMO Broadcast Channel With Statistical CSI

NASA Astrophysics Data System (ADS)

Wu, Yongpeng; Jin, Shi; Gao, Xiqi; McKay, Matthew R.; Xiao, Chengshan

2014-09-01

We investigate the multiple-input multiple-output broadcast channel with statistical channel state information available at the transmitter. The so-called linear assignment operation is employed, and necessary conditions are derived for the optimal transmit design under general fading conditions. Based on this, we introduce an iterative algorithm to maximize the linear assignment weighted sum-rate by applying a gradient descent method. To reduce complexity, we derive an upper bound of the linear assignment achievable rate of each receiver, from which a simplified closed-form expression for a near-optimal linear assignment matrix is derived. This reveals an interesting construction analogous to that of dirty-paper coding. In light of this, a low complexity transmission scheme is provided. Numerical examples illustrate the significant performance of the proposed low complexity scheme.

Non-linear wave-particle interactions and fast ion loss induced by multiple Alfvén eigenmodes in the DIII-D tokamak

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

Chen, Xi; Kramer, Gerrit J.; Heidbrink, William W.

2014-05-21

A new non-linear feature has been observed in fast-ion loss from tokamak plasmas in the form of oscillations at the sum, difference and second harmonic frequencies of two independent Alfvén eigenmodes (AEs). Full orbit calculations and analytic theory indicate this non-linearity is due to coupling of fast-ion orbital response as it passes through each AE — a change in wave-particle phase k • r by one mode alters the force exerted by the next. Furthermore, the loss measurement is of barely confined, non-resonant particles, while similar non-linear interactions can occur between well-confined particles and multiple AEs leading to enhanced fast-ionmore » transport.« less

Optimal design of compact and connected nature reserves for multiple species.

PubMed

Wang, Yicheng; Önal, Hayri

2016-04-01

When designing a conservation reserve system for multiple species, spatial attributes of the reserves must be taken into account at species level. The existing optimal reserve design literature considers either one spatial attribute or when multiple attributes are considered the analysis is restricted only to one species. We built a linear integer programing model that incorporates compactness and connectivity of the landscape reserved for multiple species. The model identifies multiple reserves that each serve a subset of target species with a specified coverage probability threshold to ensure the species' long-term survival in the reserve, and each target species is covered (protected) with another probability threshold at the reserve system level. We modeled compactness by minimizing the total distance between selected sites and central sites, and we modeled connectivity of a selected site to its designated central site by selecting at least one of its adjacent sites that has a nearer distance to the central site. We considered structural distance and functional distances that incorporated site quality between sites. We tested the model using randomly generated data on 2 species, one ground species that required structural connectivity and the other an avian species that required functional connectivity. We applied the model to 10 bird species listed as endangered by the state of Illinois (U.S.A.). Spatial coherence and selection cost of the reserves differed substantially depending on the weights assigned to these 2 criteria. The model can be used to design a reserve system for multiple species, especially species whose habitats are far apart in which case multiple disjunct but compact and connected reserves are advantageous. The model can be modified to increase or decrease the distance between reserves to reduce or promote population connectivity. © 2015 Society for Conservation Biology.

Oral health literacy and information sources among adults in Tehran, Iran.

PubMed

Sistani, M M Naghibi; Yazdani, R; Virtanen, J; Pakdaman, A; Murtomaa, H

2013-09-01

To assess oral health literacy level and oral health information of Iranian adults in Tehran, and to determine the factors related to oral health literacy. A cross-sectional population study. A random sample of 1,031 adults in Tehran, Iran. Oral health literacy was measured using an oral health adult literacy questionnaire (OHL-AQ). Variation in use of information sources by socio-economic and demographic background was estimated by odds ratios. A multiple linear regression model served to determine predictor factors of OHL-AQ scores controlling for characteristics of the subjects and number of information sources. The mean OHL-AQ score was 10.5 (sd 3.0). Women (p < 0.001), younger (p < 0.001), and better educated participants (p < 0.001) had higher OHL-AQ scores. The most common sources of oral health information were dentists (52.6%), and TV/Radio (49.5%). According to the regression model, females (p = 0.001), high educational level (p < 0.001), and use of multiple information sources (two sources p = 0.01, three sources or more p = 0.002) were the main predictor factors of OHL-AQ scores. The average oral health literacy level of Iranian adults was low. Disseminating evidence-based oral health care information from multiple sources including TV/radio, dentists, and other health professionals in different settings should improve public oral health literacy.

A Constrained Linear Estimator for Multiple Regression

ERIC Educational Resources Information Center

Davis-Stober, Clintin P.; Dana, Jason; Budescu, David V.

2010-01-01

"Improper linear models" (see Dawes, Am. Psychol. 34:571-582, "1979"), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of "improper" linear models as "proper" statistical models with a single predictor. We…

Social ecology of child soldiers: child, family, and community determinants of mental health, psychosocial well-being, and reintegration in Nepal.

PubMed

Kohrt, Brandon A; Jordans, Mark J D; Tol, Wietse A; Perera, Em; Karki, Rohit; Koirala, Suraj; Upadhaya, Nawaraj

2010-11-01

This study employed a social ecology framework to evaluate psychosocial well-being in a cross-sectional sample of 142 former child soldiers in Nepal. Outcome measures included the Depression Self Rating Scale (DSRS), Child Posttraumatic Stress Disorder Symptom Scale (CPSS), and locally developed measures of functional impairment and reintegration. Hierarchical linear modeling was used to examine the contribution of factors at multiple levels. At the child level, traumatic exposures, especially torture, predicted poor outcomes, while education improved outcomes. At the family level, conflict-related death of a relative, physical abuse in the household, and loss of wealth during the conflict predicted poor outcomes. At the community level, living in high caste Hindu communities predicted lack of reintegration supports. Ultimately, social ecology is well suited to identify intervention foci across ecological levels based on community differences in vulnerability and protective factors.

The relationship between volatile sulphur compounds, tongue coating and periodontal disease.

PubMed

Calil, C; Liberato, F L; Pereira, A C; de Castro Meneghim, M; Goodson, J M; Groppo, F C

2009-11-01

The purpose of the present study was to observe the casual levels of volatile sulphur compounds (VSC) in volunteers with different clinical scores of tongue coating, periodontal pockets depth and Gingival Bleeding Index. Seventy-two subjects who attended for the first time at the dental clinic of the University were randomly selected for intra-oral and periodontal examinations. Systemic and dental histories were also obtained. The subjects were unaware of all procedures. The level of VSC was assessed by using a portable sulphide monitor (Halimeter; Interscan Co., Chatsworth, CA, USA). High tongue coating levels were related with more VSC counts (multivariate anova, P = 0.01). No statistically significant relation (multiple linear regression, P > 0.05) was observed among the VSC levels considering age, bleeding and periodontal pockets sites (depth > 4 mm). We concluded that the tongue coating was one of the main factors influencing the VSC levels.

Arctic Ocean Freshwater Content and Its Decadal Memory of Sea-Level Pressure

NASA Astrophysics Data System (ADS)

Johnson, Helen L.; Cornish, Sam B.; Kostov, Yavor; Beer, Emma; Lique, Camille

2018-05-01

Arctic freshwater content (FWC) has increased significantly over the last two decades, with potential future implications for the Atlantic meridional overturning circulation downstream. We investigate the relationship between Arctic FWC and atmospheric circulation in the control run of a coupled climate model. Multiple linear lagged regression is used to extract the response of total Arctic FWC to a hypothetical step increase in the principal components of sea-level pressure. The results demonstrate that the FWC adjusts on a decadal timescale, consistent with the idea that wind-driven ocean dynamics and eddies determine the response of Arctic Ocean circulation and properties to a change in surface forcing, as suggested by idealized models and theory. Convolving the response of FWC to a change in sea-level pressure with historical sea-level pressure variations reveals that the recent observed increase in Arctic FWC is related to natural variations in sea-level pressure.

Glucose concentration measured by the hybrid coherent anti-Stokes Raman-scattering technique

NASA Astrophysics Data System (ADS)

Wang, Xi; Zhang, Aihua; Zhi, Miaochan; Sokolov, Alexei V.; Welch, George R.

2010-01-01

We investigate the possibility of using a hybrid coherent anti-Stokes Raman scattering technique for noninvasive monitoring of blood glucose levels. Our technique combines instantaneous coherent excitation of several characteristic molecular vibrations with subsequent probing of these vibrations by an optimally shaped, time-delayed, narrowband laser pulse. This pulse configuration mitigates the nonresonant four-wave mixing background while maximizing the Raman-resonant signal and allows rapid and highly specific detection even in the presence of multiple scattering. Under certain conditions we find that the measured signal is linearly proportional to the glucose concentration due to optical interference with the residual background light, which allows reliable detection of spectral signatures down to medically relevant glucose levels.

Vibration ride comfort criteria

NASA Technical Reports Server (NTRS)

Dempsey, T. K.; Leatherwood, J. D.

1976-01-01

Results are presented for an experimental study directed to derive equal vibration discomfort curves, to determine the influence of vibration masking in order to account for the total discomfort of any random vibration, and to develop a scale of total vibration discomfort in the case of human response to whole-body vertical vibration. Discomfort is referred to as a subjective discomfort associated with the acceleration level of a particular frequency band. It is shown that passenger discomfort to whole-body vibration increases linearly with acceleration level for each frequency. Empirical data provide a mechanism for determining the degree of masking (or summation) of the discomfort of multiple frequency vibration. A scale for the prediction of passenger discomfort is developed.

Random number generators tested on quantum Monte Carlo simulations.

PubMed

Hongo, Kenta; Maezono, Ryo; Miura, Kenichi

2010-08-01

We have tested and compared several (pseudo) random number generators (RNGs) applied to a practical application, ground state energy calculations of molecules using variational and diffusion Monte Carlo metheds. A new multiple recursive generator with 8th-order recursion (MRG8) and the Mersenne twister generator (MT19937) are tested and compared with the RANLUX generator with five luxury levels (RANLUX-[0-4]). Both MRG8 and MT19937 are proven to give the same total energy as that evaluated with RANLUX-4 (highest luxury level) within the statistical error bars with less computational cost to generate the sequence. We also tested the notorious implementation of linear congruential generator (LCG), RANDU, for comparison. (c) 2010 Wiley Periodicals, Inc.

Is serum zinc level associated with prediabetes and diabetes?: a cross-sectional study from Bangladesh.

PubMed

Islam, Md Rafiqul; Arslan, Iqbal; Attia, John; McEvoy, Mark; McElduff, Patrick; Basher, Ariful; Rahman, Waliur; Peel, Roseanne; Akhter, Ayesha; Akter, Shahnaz; Vashum, Khanrin P; Milton, Abul Hasnat

2013-01-01

To determine serum zinc level and other relevant biological markers in normal, prediabetic and diabetic individuals and their association with Homeostasis Model Assessment (HOMA) parameters. This cross-sectional study was conducted between March and December 2009. Any patient aged ≥ 30 years attending the medicine outpatient department of a medical university hospital in Dhaka, Bangladesh and who had a blood glucose level ordered by a physician was eligible to participate. A total of 280 participants were analysed. On fasting blood sugar results, 51% were normal, 13% had prediabetes and 36% had diabetes. Mean serum zinc level was lowest in prediabetic compared to normal and diabetic participants (mean differences were approximately 65 ppb/L and 33 ppb/L, respectively). In multiple linear regression, serum zinc level was found to be significantly lower in prediabetes than in those with normoglycemia. Beta cell function was significantly lower in prediabetes than normal participants. Adjusted linear regression for HOMA parameters did not show a statistically significant association between serum zinc level, beta cell function (P = 0.07) and insulin resistance (P = 0.08). Low serum zinc accentuated the increase in insulin resistance seen with increasing BMI. Participants with prediabetes have lower zinc levels than controls and zinc is significantly associated with beta cell function and insulin resistance. Further longitudinal population based studies are warranted and controlled trials would be valuable for establishing whether zinc supplementation in prediabetes could be a useful strategy in preventing progression to Type 2 diabetes.

A Common Mechanism for Resistance to Oxime Reactivation of Acetylcholinesterase Inhibited by Organophosphorus Compounds

DTIC Science & Technology

2013-01-01

application of the Hammett equation with the constants rph in the chemistry of organophosphorus compounds, Russ. Chem. Rev. 38 (1969) 795–811. [13...of oximes and OP compounds and the ability of oximes to reactivate OP- inhibited AChE. Multiple linear regression equations were analyzed using...phosphonate pairs, 21 oxime/ phosphoramidate pairs and 12 oxime/phosphate pairs. The best linear regression equation resulting from multiple regression anal

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

New nonlinear control algorithms for multiple robot arms

NASA Technical Reports Server (NTRS)

Tarn, T. J.; Bejczy, A. K.; Yun, X.

1988-01-01

Multiple coordinated robot arms are modeled by considering the arms as closed kinematic chains and as a force-constrained mechanical system working on the same object simultaneously. In both formulations, a novel dynamic control method is discussed. It is based on feedback linearization and simultaneous output decoupling technique. By applying a nonlinear feedback and a nonlinear coordinate transformation, the complicated model of the multiple robot arms in either formulation is converted into a linear and output decoupled system. The linear system control theory and optimal control theory are used to design robust controllers in the task space. The first formulation has the advantage of automatically handling the coordination and load distribution among the robot arms. In the second formulation, it was found that by choosing a general output equation it became possible simultaneously to superimpose the position and velocity error feedback with the force-torque error feedback in the task space.

Higher direct bilirubin levels during mid-pregnancy are associated with lower risk of gestational diabetes mellitus.

PubMed

Liu, Chaoqun; Zhong, Chunrong; Zhou, Xuezhen; Chen, Renjuan; Wu, Jiangyue; Wang, Weiye; Li, Xiating; Ding, Huisi; Guo, Yanfang; Gao, Qin; Hu, Xingwen; Xiong, Guoping; Yang, Xuefeng; Hao, Liping; Xiao, Mei; Yang, Nianhong

2017-01-01

Bilirubin concentrations have been recently reported to be negatively associated with type 2 diabetes mellitus. We examined the association between bilirubin concentrations and gestational diabetes mellitus. In a prospective cohort study, 2969 pregnant women were recruited prior to 16 weeks of gestation and were followed up until delivery. The value of bilirubin was tested and oral glucose tolerance test was conducted to screen gestational diabetes mellitus. The relationship between serum bilirubin concentration and gestational weeks was studied by two-piecewise linear regression. A subsample of 1135 participants with serum bilirubin test during 16-18 weeks gestation was conducted to research the association between serum bilirubin levels and risk of gestational diabetes mellitus by logistic regression. Gestational diabetes mellitus developed in 8.5 % of the participants (223 of 2969). Two-piecewise linear regression analyses demonstrated that the levels of bilirubin decreased with gestational week up to the turning point 23 and after that point, levels of bilirubin were increased slightly. In multiple logistic regression analysis, the relative risk of developing gestational diabetes mellitus was lower in the highest tertile of direct bilirubin than that in the lowest tertile (RR 0.60; 95 % CI, 0.35-0.89). The results suggested that women with higher serum direct bilirubin levels during the second trimester of pregnancy have lower risk for development of gestational diabetes mellitus.

Association of suboptimal health status with psychosocial stress, plasma cortisol and mRNA expression of glucocorticoid receptor α/β in lymphocyte.

PubMed

Yan, Yu-Xiang; Dong, Jing; Liu, You-Qin; Zhang, Jie; Song, Man-Shu; He, Yan; Wang, Wei

2015-01-01

Suboptimal health status (SHS) has become a new public health challenge in China. This study investigated whether high SHS is associated with psychosocial stress, changes in cortisol level and/or glucocorticoid receptor (GR) isoform expression. Three-hundred eighty-six workers employed in three companies in Beijing were recruited. The SHS score was derived from data collection in the SHS questionnaire (SHSQ-25). The short standard version of the Copenhagen Psychosocial Questionnaire (COPSOQ) was used to assess job-related psychosocial stress. The mean value of the five scales of COPSOQ and distribution of plasma cortisol and mRNA expression of GRα/GRβ between the high level of SHS group and the low level of SHS group were compared using a general linear model procedure. Multiple linear regression analysis was used to analyze the effect of psychosocial stress on SHS. We identified three factors that were predictive of SHS, including "demands at work", "interpersonal relations and leadership" and "insecurity at work". Significantly higher levels of plasma cortisol and GRβ/GRα mRNA ratio were observed among the high SHS group. High level of SHS is associated with decreased mRNA expression of GRα. This study confirmed the association between chronic psychosocial stress and SHS, indicating that improving the psychosocial work environment may reduce SHS and then prevent chronic diseases effectively.

Periodontitis in coronary heart disease patients: strong association between bleeding on probing and systemic biomarkers.

PubMed

Bokhari, Syed Akhtar H; Khan, Ayyaz A; Butt, Arshad K; Hanif, Mohammad; Izhar, Mateen; Tatakis, Dimitris N; Ashfaq, Mohammad

2014-11-01

Few studies have examined the relationship of individual periodontal parameters with individual systemic biomarkers. This study assessed the possible association between specific clinical parameters of periodontitis and systemic biomarkers of coronary heart disease risk in coronary heart disease patients with periodontitis. Angiographically proven coronary heart disease patients with periodontitis (n = 317), aged >30 years and without other systemic illness were examined. Periodontal clinical parameters of bleeding on probing (BOP), probing depth (PD), and clinical attachment level (CAL) and systemic levels of high-sensitivity C-reactive protein (CRP), fibrinogen (FIB) and white blood cells (WBC) were noted and analyzed to identify associations through linear and stepwise multiple regression analyses. Unadjusted linear regression showed significant associations between periodontal and systemic parameters; the strongest association (r = 0.629; p < 0.001) was found between BOP and CRP levels, the periodontal and systemic inflammation marker, respectively. Stepwise regression analysis models revealed that BOP was a predictor of systemic CRP levels (p < 0.0001). BOP was the only periodontal parameter significantly associated with each systemic parameter (CRP, FIB, and WBC). In coronary heart disease patients with periodontitis, BOP is strongly associated with systemic CRP levels; this association possibly reflects the potential significance of the local periodontal inflammatory burden for systemic inflammation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies

PubMed Central

Liu, Zhonghua; Lin, Xihong

2017-01-01

Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391

Multiple phenotype association tests using summary statistics in genome-wide association studies.

PubMed

Liu, Zhonghua; Lin, Xihong

2018-03-01

We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.

Precision-feeding dairy heifers a high rumen-undegradable protein diet with different proportions of dietary fiber and forage-to-concentrate ratios.

PubMed

Koch, L E; Gomez, N A; Bowyer, A; Lascano, G J

2017-12-01

The addition of dietary fiber can alter nutrient and N utilization in precision-fed dairy heifers and may further benefit from higher inclusion levels of RUP. The objective of this experiment was to determine the effects of feeding a high-RUP diet when dietary fiber content was manipulated within differing forage-to-concentrate ratios (F:C) on nutrient utilization of precision-fed dairy heifers. Six rumen-cannulated Holstein heifers (555.4 ± 31.4 kg BW; 17.4 ± 0.1 mo) were randomly assigned to 2 levels of forage, high forage (HF; 60% forage) or low forage (LF; 45% forage), and to a fiber proportion sequence (low fiber: 100% oat hay and silage [OA], 0% wheat straw [WS]; medium fiber: 83.4% OA, 16.6% WS; and high fiber: 66.7% OA, 33.3% WS) administered according to a split-plot 3 × 3 Latin square design (21-d periods). Similar levels of N intake (1.70 g N/kg BW) and RUP (55% of CP) were provided. Data were analyzed as a split-plot, 3 × 3 Latin square design using a mixed model with fixed effects of period and treatment. A repeated measures model was used with data that had multiple measurements over time. No differences were observed for DM, OM, NDF, or ADF apparent digestibility coefficients (dC) between HF- and LF-fed heifers. Heifers receiving LF diets had greater starch dC compared to HF heifers. Increasing the fiber level through WS addition resulted in a linear reduction of OM dC. There was a linear interaction for DM dC with a concurrent linear interaction in NDF dC. Nitrogen intake, dC, and retention did not differ; however, urine and total N excretion increased linearly with added fiber. Predicted microbial CP flow (MP) linearly decreased with WS inclusion mainly in LF heifers, as indicated by a significant interaction between F:C and WS. Rumen pH linearly increased with WS addition, although no F:C effect was detected. Ruminal ammonia concentration had an opposite linear effect with respect to MP as WS increased. Diets with the higher proportion of fiber benefited the most from a high RUP supply, complementing the substantial reduction in predicted MP caused by the incremental dietary fiber concentration. These results suggest that RUP supplementation is a practical method for reestablishing optimal ruminal N balance in the event of increased dietary fiber through forage inclusion in precision-fed dairy heifer diets.

Readability Levels of Dental Patient Education Brochures.

PubMed

Boles, Catherine D; Liu, Ying; November-Rider, Debra

2016-02-01

The objective of this study was to evaluate dental patient education brochures produced since 2000 to determine if there is any change in the Flesch-Kincaid grade level readability. A convenience sample of 36 brochures was obtained for analysis of the readability of the patient education material on multiple dental topics. Readability was measured using the Flesch-Kincaid Grade Level through Microsoft Word. Pearson's correlation was used to describe the relationship among the factors of interest. Backward model selection of multiple linear regression model was used to investigate the relationship between Flesch-Kincaid Grade level and a set of predictors included in this study. A convenience sample (n=36) of dental education brochures produced from 2000 to 2014 showed a mean Flesch-Kincaid reading grade level of 9.15. Weak to moderate correlations existed between word count and grade level (r=0.40) and characters count and grade level (r=0.46); strong correlations were found between grade level and average words per sentence (r=0.70), average characters per word (r=0.85) and Flesch Reading Ease (r=-0.98). Only 1 brochure out of the sample met the recommended sixth grade reading level (Flesch-Kincaid Grade Level 5.7). Overall, the Flesch-Kincaid Grade Level of all brochures was significantly higher than the recommended sixth grade reading level (p<0.0001). The findings from this study demonstrated that there has generally been an improvement in the Flesch-Kincaid grade level readability of the brochures. However, the majority of the brochures analyzed are still testing above the recommended sixth grade reading level. Copyright © 2016 The American Dental Hygienists’ Association.

Multiple Heavy Metal Tolerance of Soil Bacterial Communities and Its Measurement by a Thymidine Incorporation Technique

PubMed Central

Díaz-Raviña, Montserrat; Bååth, Erland; Frostegård, Åsa

1994-01-01

A thymidine incorporation technique was used to determine the tolerance of a soil bacterial community to Cu, Cd, Zn, Ni, and Pb. An agricultural soil was artificially contaminated in our laboratory with individual metals at three different concentrations, and the results were compared with the results obtained by using the plate count technique. Thymidine incorporation was found to be a simple and rapid method for measuring tolerance. Data obtained by this technique were very reproducible. A linear relationship was found between changes in community tolerance levels obtained by the thymidine incorporation and plate count techniques (r = 0.732, P < 0.001). An increase in tolerance to the metal added to soil was observed for the bacterial community obtained from each polluted soil compared with the community obtained from unpolluted soil. The only exception was when Pb was added; no indication of Pb tolerance was found. An increase in the tolerance to metals other than the metal originally added to soil was also observed, indicating that there was multiple heavy metal tolerance at the community level. Thus, Cu pollution, in addition to increasing tolerance to Cu, also induced tolerance to Zn, Cd, and Ni. Zn and Cd pollution increased community tolerance to all five metals. Ni amendment increased tolerance to Ni the most but also increased community tolerance to Zn and, to lesser degrees, increased community tolerance to Pb and Cd. In soils polluted with Pb increased tolerance to other metals was found in the following order: Ni > Cd > Zn > Cu. We found significant positive relationships between changes in Cd, Zn, and Pb tolerance and, to a lesser degree, between changes in Pb and Ni tolerance when all metals and amendment levels were compared. The magnitude of the increase in heavy metal tolerance was found to be linearly related to the logarithm of the metal concentration added to the soil. Threshold tolerance concentrations were estimated from these linear relationships, and changes in tolerance could be detected at levels of soil contamination similar to those reported previously to result in changes in the phospholipid fatty acid pattern (Å. Frostegård, A. Tunlid, and E. Bååth, Appl. Environ. Microbiol. 59: 3605-3617, 1993). PMID:16349314

Study of process variables associated with manufacturing hermetically-sealed nickel-cadmium cells

NASA Technical Reports Server (NTRS)

Miller, L.; Doan, D. J.; Carr, E. S.

1971-01-01

A program to determine and study the critical process variables associated with the manufacture of aerospace, hermetically-sealed, nickel-cadmium cells is described. The determination and study of the process variables associated with the positive and negative plaque impregnation/polarization process are emphasized. The experimental data resulting from the implementation of fractional factorial design experiments are analyzed by means of a linear multiple regression analysis technique. This analysis permits the selection of preferred levels for certain process variables to achieve desirable impregnated plaque characteristics.

The quest for solvable multistate Landau-Zener models

DOE PAGES

Sinitsyn, Nikolai A.; Chernyak, Vladimir Y.

2017-05-24

Recently, integrability conditions (ICs) in mutistate Landau-Zener (MLZ) theory were proposed. They describe common properties of all known solved systems with linearly time-dependent Hamiltonians. Here we show that ICs enable efficient computer assisted search for new solvable MLZ models that span complexity range from several interacting states to mesoscopic systems with many-body dynamics and combinatorially large phase space. This diversity suggests that nontrivial solvable MLZ models are numerous. Additionally, we refine the formulation of ICs and extend the class of solvable systems to models with points of multiple diabatic level crossing.

Multiple-channel ultra-violet absorbance detector for two-dimensional chromatographic separations.

PubMed

Lynch, Kyle B; Yang, Yu; Ren, Jiangtao; Liu, Shaorong

2018-05-01

In recent years, much research has gone into developing online comprehensive two-dimensional liquid chromatographic systems allowing for high peak capacities in comparable separation times to that of one-dimensional liquid chromatographic systems. However, the speed requirements in the second dimension (2nd-D) still remain one challenge for complex biological samples due to the current configuration of two column/two detector systems. Utilization of multiple 2nd-D columns can mitigate this challenge. To adapt this approach, we need a multiple channel detector. Here we develop a versatile multichannel ultraviolet (UV) light absorbance detector that is capable of simultaneously monitoring separations in 12 columns. The detector consists of a deuterium lighthouse, a flow cell assembly (a 13-channel flow cell fitted with a 13-photodiode-detection system), and a data acquisition and monitoring terminal. Through the use of a custom high optical quality furcated fiber to improve light transmission, precise machining of a flow cell to reduce background stray light through precision alignment, and sensitive electronic circuitry to reduce electronic noise through an active low pass filter, the background noise level is measured in the tens of µAU. We obtain a linear dynamic range of close to three orders of magnitude. Compared to a commercialized multichannel UV light absorbance detector like the Waters 2488 UV/Vis, our device provides an increase in channel detection while residing within the same noise region and linear range. Copyright © 2018 Elsevier B.V. All rights reserved.

Refill Adherence in Relation to Substitution and the Use of Multiple Medications: A Nationwide Population Based Study on New ACE-Inhibitor Users

PubMed Central

Jönsson, Anna K.; Lesén, Eva; Mårdby, Ann-Charlotte; Sundell, Karolina Andersson

2016-01-01

Objective Generic substitution has contributed to economic savings but switching products may affect patient adherence, particularly among those using multiple medications. The aim was to analyse if use of multiple medications influenced the association between switching products and refill adherence to angiotensin-converting-enzyme (ACE) inhibitors in Sweden. Study Design and Setting New users of ACE-inhibitors, starting between 1 July 2006 and 30 June 2007, were identified in the Swedish Prescribed Drug Register. Refill adherence was assessed using the continuous measure of medication acquisition (CMA) and analysed with linear regression and analysis of covariance. Results The study population included 42735 individuals whereof 51.2% were exposed to switching ACE-inhibitor and 39.6% used multiple medications. Refill adherence was higher among those exposed to switching products than those not, but did not vary depending on the use of multiple medications or among those not. Refill adherence varied with age, educational level, household income, country of birth, previous hospitalisation and previous cardiovascular diagnosis. Conclusion The results indicate a positive association between refill adherence and switching products, mainly due to generic substitution, among new users of ACE-inhibitors in Sweden. This association was independent of use of multiple medications. PMID:27192203

Linearized inversion of multiple scattering seismic energy

NASA Astrophysics Data System (ADS)

Aldawood, Ali; Hoteit, Ibrahim; Zuberi, Mohammad

2014-05-01

Internal multiples deteriorate the quality of the migrated image obtained conventionally by imaging single scattering energy. So, imaging seismic data with the single-scattering assumption does not locate multiple bounces events in their actual subsurface positions. However, imaging internal multiples properly has the potential to enhance the migrated image because they illuminate zones in the subsurface that are poorly illuminated by single scattering energy such as nearly vertical faults. Standard migration of these multiples provides subsurface reflectivity distributions with low spatial resolution and migration artifacts due to the limited recording aperture, coarse sources and receivers sampling, and the band-limited nature of the source wavelet. The resultant image obtained by the adjoint operator is a smoothed depiction of the true subsurface reflectivity model and is heavily masked by migration artifacts and the source wavelet fingerprint that needs to be properly deconvolved. Hence, we proposed a linearized least-square inversion scheme to mitigate the effect of the migration artifacts, enhance the spatial resolution, and provide more accurate amplitude information when imaging internal multiples. The proposed algorithm uses the least-square image based on single-scattering assumption as a constraint to invert for the part of the image that is illuminated by internal scattering energy. Then, we posed the problem of imaging double-scattering energy as a least-square minimization problem that requires solving the normal equation of the following form: GTGv = GTd, (1) where G is a linearized forward modeling operator that predicts double-scattered seismic data. Also, GT is a linearized adjoint operator that image double-scattered seismic data. Gradient-based optimization algorithms solve this linear system. Hence, we used a quasi-Newton optimization technique to find the least-square minimizer. In this approach, an estimate of the Hessian matrix that contains curvature information is modified at every iteration by a low-rank update based on gradient changes at every step. At each iteration, the data residual is imaged using GT to determine the model update. Application of the linearized inversion to synthetic data to image a vertical fault plane demonstrate the effectiveness of this methodology to properly delineate the vertical fault plane and give better amplitude information than the standard migrated image using the adjoint operator that takes into account internal multiples. Thus, least-square imaging of multiple scattering enhances the spatial resolution of the events illuminated by internal scattering energy. It also deconvolves the source signature and helps remove the fingerprint of the acquisition geometry. The final image is obtained by the superposition of the least-square solution based on single scattering assumption and the least-square solution based on double scattering assumption.

Spacecraft nonlinear control

NASA Technical Reports Server (NTRS)

Sheen, Jyh-Jong; Bishop, Robert H.

1992-01-01

The feedback linearization technique is applied to the problem of spacecraft attitude control and momentum management with control moment gyros (CMGs). The feedback linearization consists of a coordinate transformation, which transforms the system to a companion form, and a nonlinear feedback control law to cancel the nonlinear dynamics resulting in a linear equivalent model. Pole placement techniques are then used to place the closed-loop poles. The coordinate transformation proposed here evolves from three output functions of relative degree four, three, and two, respectively. The nonlinear feedback control law is presented. Stability in a neighborhood of a controllable torque equilibrium attitude (TEA) is guaranteed and this fact is demonstrated by the simulation results. An investigation of the nonlinear control law shows that singularities exist in the state space outside the neighborhood of the controllable TEA. The nonlinear control law is simplified by a standard linearization technique and it is shown that the linearized nonlinear controller provides a natural way to select control gains for the multiple-input, multiple-output system. Simulation results using the linearized nonlinear controller show good performance relative to the nonlinear controller in the neighborhood of the TEA.

A class of stochastic optimization problems with one quadratic & several linear objective functions and extended portfolio selection model

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Li, Jun

2002-09-01

In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduction of random variables' expectation. The reference direction approach is used to deal with linear objectives and results in a linear parametric optimization formula with a single linear objective function. This objective function is combined with the quadratic function using the weighted sums. The quadratic problem is transformed into a linear (parametric) complementary problem, the basic formula for the proposed approach. The sufficient and necessary conditions for (properly, weakly) efficient solutions and some construction characteristics of (weakly) efficient solution sets are obtained. An interactive algorithm is proposed based on reference direction and weighted sums. Varying the parameter vector on the right-hand side of the model, the DM can freely search the efficient frontier with the model. An extended portfolio selection model is formed when liquidity is considered as another objective to be optimized besides expectation and risk. The interactive approach is illustrated with a practical example.

Stochastic nature of Landsat MSS data

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J.

1987-01-01

A multiple series generalization of the ARIMA models is used to model Landsat MSS scan lines as sequences of vectors, each vector having four elements (bands). The purpose of this work is to investigate if Landsat scan lines can be described by a general multiple series linear stochastic model and if the coefficients of such a model vary as a function of satellite system and target attributes. To accomplish this objective, an exploratory experimental design was set up incorporating six factors, four representing target attributes - location, cloud cover, row (within location), and column (within location) - and two factors representing system attributes - satellite number and detector bank. Each factor was included in the design at two levels and, with two replicates per treatment, 128 scan lines were analyzed. The results of the analysis suggests that a multiple AR(4) model is an adequate representation across all scan lines. Furthermore, the coefficients of the AR(4) model vary with location, particularly changes in physiography (slope regimes), and with percent cloud cover, but are insensitive to changes in system attributes.

Multi-criteria decision aid approach for the selection of the best compromise management scheme for ELVs: the case of Cyprus.

PubMed

Mergias, I; Moustakas, K; Papadopoulos, A; Loizidou, M

2007-08-25

Each alternative scheme for treating a vehicle at its end of life has its own consequences from a social, environmental, economic and technical point of view. Furthermore, the criteria used to determine these consequences are often contradictory and not equally important. In the presence of multiple conflicting criteria, an optimal alternative scheme never exists. A multiple-criteria decision aid (MCDA) method to aid the Decision Maker (DM) in selecting the best compromise scheme for the management of End-of-Life Vehicles (ELVs) is presented in this paper. The constitution of a set of alternatives schemes, the selection of a list of relevant criteria to evaluate these alternative schemes and the choice of an appropriate management system are also analyzed in this framework. The proposed procedure relies on the PROMETHEE method which belongs to the well-known family of multiple criteria outranking methods. For this purpose, level, linear and Gaussian functions are used as preference functions.

Biomonitoring for Exposure Assessment to Styrene in the Fibreglass Reinforced Plastic Industry: Determinants and Interferents.

PubMed

Bonanni, Rossana Claudia; Gatto, Maria Pia; Paci, Enrico; Gordiani, Andrea; Gherardi, Monica; Tranfo, Giovanna

2015-10-01

Fifty-eight workers exposed to styrene were monitored in four fibreglass reinforced plastic industries of Central Italy. The aim of the study was to explore the factors that can influence the levels of styrene exposure biomarkers of the workers and the aspects that might interfere with the exposure assessment measures, such as the co-exposure to acetone. Personal monitoring of professional exposure to airborne styrene and acetone was carried out by Radiello samplers and GC/MS analysis. Biological monitoring was performed by the determination of urinary metabolites, mandelic (MA), and phenylglyoxylic (PGA) acids with HPLC/MS/MS and unmetabolized styrene in saliva and venous blood by HS/GC/MS. The median values of the four sites ranged between 24.1 to 94.0mg m(-3) and 7.3 to 331.1mg g(-1) creatinine for airborne styrene and MA + PGA, respectively. A good linear correlation was found between styrene in air and its urinary metabolites (r = 0.854). The median value for airborne styrene was found to exceed the (Threshold Limit Value - Time Weighted Average) of 85 mg m(-3) in one site for all the workers and in two if only moulders are considered. The multiple linear regression model showed that the determinants of urinary MA + PGA excretion were the type of process, workers' tasks, level of acetone co-exposure, and the use of respiratory protection devices. Data show that the simultaneous exposure to acetone modify the styrene metabolism with a reduction in the levels of (MA + PGA) excreted. A significant linear log-correlation was found between salivary levels of styrene and blood concentration (r = 0.746) sampled at the same t x time. © The Author 2015. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

The Association between Noise, Cortisol and Heart Rate in a Small-Scale Gold Mining Community—A Pilot Study

PubMed Central

Green, Allyson; Jones, Andrew D.; Sun, Kan; Neitzel, Richard L.

2015-01-01

We performed a cross-sectional pilot study on salivary cortisol, heart rate, and personal noise exposures in a small-scale gold mining village in northeastern Ghana in 2013. Cortisol level changes between morning and evening among participants showed a relatively low decline in cortisol through the day (−1.44 ± 4.27 nmol/L, n = 18), a pattern consistent with chronic stress. A multiple linear regression, adjusting for age, sex, smoking status, and time between samples indicated a significant increase of 0.25 nmol/L cortisol from afternoon to evening per 1 dBA increase in equivalent continuous noise exposure (Leq) over that period (95% CI: 0.08–0.42, Adj R2 = 0.502, n = 17). A mixed effect linear regression model adjusting for age and sex indicated a significant increase of 0.29 heart beats per minute (BPM) for every 1 dB increase in Leq. Using standard deviations (SDs) as measures of variation, and adjusting for age and sex over the sampling period, we found that a 1 dBA increase in noise variation over time (Leq SD) was associated with a 0.5 BPM increase in heart rate SD (95% CI: 0.04–−0.9, Adj. R2 = 0.229, n = 16). Noise levels were consistently high, with 24-hour average Leq exposures ranging from 56.9 to 92.0 dBA, with a mean daily Leq of 82.2 ± 7.3 dBA (mean monitoring duration 22.1 ± 1.9 hours, n = 22). Ninety-five percent of participants had 24-hour average Leq noise levels over the 70 dBA World health Organization (WHO) guideline level for prevention of hearing loss. These findings suggest that small-scale mining communities may face multiple, potentially additive health risks that are not yet well documented, including hearing loss and cardiovascular effects of stress and noise. PMID:26308019

The Association between Noise, Cortisol and Heart Rate in a Small-Scale Gold Mining Community-A Pilot Study.

PubMed

Green, Allyson; Jones, Andrew D; Sun, Kan; Neitzel, Richard L

2015-08-21

We performed a cross-sectional pilot study on salivary cortisol, heart rate, and personal noise exposures in a small-scale gold mining village in northeastern Ghana in 2013. Cortisol level changes between morning and evening among participants showed a relatively low decline in cortisol through the day (-1.44 ± 4.27 nmol/L, n = 18), a pattern consistent with chronic stress. A multiple linear regression, adjusting for age, sex, smoking status, and time between samples indicated a significant increase of 0.25 nmol/L cortisol from afternoon to evening per 1 dBA increase in equivalent continuous noise exposure (Leq) over that period (95% CI: 0.08-0.42, Adj R(2) = 0.502, n = 17). A mixed effect linear regression model adjusting for age and sex indicated a significant increase of 0.29 heart beats per minute (BPM) for every 1 dB increase in Leq. Using standard deviations (SDs) as measures of variation, and adjusting for age and sex over the sampling period, we found that a 1 dBA increase in noise variation over time (Leq SD) was associated with a 0.5 BPM increase in heart rate SD (95% CI: 0.04--0.9, Adj. R(2) = 0.229, n = 16). Noise levels were consistently high, with 24-hour average Leq exposures ranging from 56.9 to 92.0 dBA, with a mean daily Leq of 82.2 ± 7.3 dBA (mean monitoring duration 22.1 ± 1.9 hours, n = 22). Ninety-five percent of participants had 24-hour average Leq noise levels over the 70 dBA World health Organization (WHO) guideline level for prevention of hearing loss. These findings suggest that small-scale mining communities may face multiple, potentially additive health risks that are not yet well documented, including hearing loss and cardiovascular effects of stress and noise.

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed Central

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-01-01

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. PMID:28952708

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-09-27

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. Creative Commons Attribution License

Aerobic Fitness Level Affects Cardiovascular and Salivary Alpha Amylase Responses to Acute Psychosocial Stress.

PubMed

Wyss, Thomas; Boesch, Maria; Roos, Lilian; Tschopp, Céline; Frei, Klaus M; Annen, Hubert; La Marca, Roberto

2016-12-01

Good physical fitness seems to help the individual to buffer the potential harmful impact of psychosocial stress on somatic and mental health. The aim of the present study is to investigate the role of physical fitness levels on the autonomic nervous system (ANS; i.e. heart rate and salivary alpha amylase) responses to acute psychosocial stress, while controlling for established factors influencing individual stress reactions. The Trier Social Stress Test for Groups (TSST-G) was executed with 302 male recruits during their first week of Swiss Army basic training. Heart rate was measured continuously, and salivary alpha amylase was measured twice, before and after the stress intervention. In the same week, all volunteers participated in a physical fitness test and they responded to questionnaires on lifestyle factors and personal traits. A multiple linear regression analysis was conducted to determine ANS responses to acute psychosocial stress from physical fitness test performances, controlling for personal traits, behavioural factors, and socioeconomic data. Multiple linear regression revealed three variables predicting 15 % of the variance in heart rate response (area under the individual heart rate response curve during TSST-G) and four variables predicting 12 % of the variance in salivary alpha amylase response (salivary alpha amylase level immediately after the TSST-G) to acute psychosocial stress. A strong performance at the progressive endurance run (high maximal oxygen consumption) was a significant predictor of ANS response in both models: low area under the heart rate response curve during TSST-G as well as low salivary alpha amylase level after TSST-G. Further, high muscle power, non-smoking, high extraversion, and low agreeableness were predictors of a favourable ANS response in either one of the two dependent variables. Good physical fitness, especially good aerobic endurance capacity, is an important protective factor against health-threatening reactions to acute psychosocial stress.

Nonlinear aeroservoelastic analysis of a controlled multiple-actuated-wing model with free-play

NASA Astrophysics Data System (ADS)

Huang, Rui; Hu, Haiyan; Zhao, Yonghui

2013-10-01

In this paper, the effects of structural nonlinearity due to free-play in both leading-edge and trailing-edge outboard control surfaces on the linear flutter control system are analyzed for an aeroelastic model of three-dimensional multiple-actuated-wing. The free-play nonlinearities in the control surfaces are modeled theoretically by using the fictitious mass approach. The nonlinear aeroelastic equations of the presented model can be divided into nine sub-linear modal-based aeroelastic equations according to the different combinations of deflections of the leading-edge and trailing-edge outboard control surfaces. The nonlinear aeroelastic responses can be computed based on these sub-linear aeroelastic systems. To demonstrate the effects of nonlinearity on the linear flutter control system, a single-input and single-output controller and a multi-input and multi-output controller are designed based on the unconstrained optimization techniques. The numerical results indicate that the free-play nonlinearity can lead to either limit cycle oscillations or divergent motions when the linear control system is implemented.

Laboratory studies of scales for measuring helicopter noise

NASA Technical Reports Server (NTRS)

Ollerhead, J. B.

1982-01-01

The adequacy of the effective perceived noise level (EPNL) procedure for rating helicopter noise annoyance was investigated. Recordings of 89 helicopters and 30 fixed wing aircraft (CTOL) flyover sounds were rated with respect to annoyance by groups of approximately 40 subjects. The average annoyance scores were transformed to annoyance levels defined as the equally annoying sound levels of a fixed reference sound. The sound levels of the test sounds were measured on various scales, with and without corrections for duration, tones, and impulsiveness. On average, the helicopter sounds were judged equally annoying to CTOL sounds when their duration corrected levels are approximately 2 dB higher. Multiple regression analysis indicated that, provided the helicopter/CTOL difference of about 2 dB is taken into account, the particular linear combination of level, duration, and tone corrections inherent in EPNL is close to optimum. The results reveal no general requirement for special EPNL correction terms to penalize helicopter sounds which are particularly impulsive; impulsiveness causes spectral and temporal changes which themselves adequately amplify conventionally measured sound levels.

Optical properties of an atomic ensemble coupled to a band edge of a photonic crystal waveguide

NASA Astrophysics Data System (ADS)

Munro, Ewan; Kwek, Leong Chuan; Chang, Darrick E.

2017-08-01

We study the optical properties of an ensemble of two-level atoms coupled to a 1D photonic crystal waveguide (PCW), which mediates long-range coherent dipole-dipole interactions between the atoms. We show that the long-range interactions can dramatically alter the linear and nonlinear optical behavior, as compared to a typical atomic ensemble. In particular, in the linear regime, we find that the transmission spectrum contains multiple transmission dips, whose properties we characterize. Moreover, we show how the linear spectrum may be used to infer the number of atoms present in the system, constituting an important experimental tool in a regime where techniques for conventional ensembles break down. We also show that some of the transmission dips are associated with an effective ‘two-level’ resonance that forms due to the long-range interactions. In particular, under strong global driving and appropriate conditions, we find that the atomic ensemble is only capable of absorbing and emitting single collective excitations at a time. Our results are of direct relevance to atom-PCW experiments that should soon be realizable.

Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.

PubMed

Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen

2015-05-01

Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.

Coexistence and local μ-stability of multiple equilibrium points for memristive neural networks with nonmonotonic piecewise linear activation functions and unbounded time-varying delays.

PubMed

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2016-12-01

In this paper, the coexistence and dynamical behaviors of multiple equilibrium points are discussed for a class of memristive neural networks (MNNs) with unbounded time-varying delays and nonmonotonic piecewise linear activation functions. By means of the fixed point theorem, nonsmooth analysis theory and rigorous mathematical analysis, it is proven that under some conditions, such n-neuron MNNs can have 5 n equilibrium points located in ℜ n , and 3 n of them are locally μ-stable. As a direct application, some criteria are also obtained on the multiple exponential stability, multiple power stability, multiple log-stability and multiple log-log-stability. All these results reveal that the addressed neural networks with activation functions introduced in this paper can generate greater storage capacity than the ones with Mexican-hat-type activation function. Numerical simulations are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Electrostatic turbulence in the earth's central plasma sheet produced by multiple-ring ion distributions

NASA Technical Reports Server (NTRS)

Huba, J. D.; Chen, J.; Anderson, R. R.

1992-01-01

Attention is given to a mechanism to generate a broad spectrum of electrostatic turbulence in the quiet time central plasma sheet (CPS) plasma. It is shown theoretically that multiple-ring ion distributions can generate short-wavelength (less than about 1), electrostatic turbulence with frequencies less than about kVj, where Vj is the velocity of the jth ring. On the basis of a set of parameters from measurements made in the CPS, it is found that electrostatic turbulence can be generated with wavenumbers in the range of 0.02 and 1.0, with real frequencies in the range of 0 and 10, and with linear growth rates greater than 0.01 over a broad range of angles relative to the magnetic field (5-90 deg). These theoretical results are compared with wave data from ISEE 1 using an ion distribution function exhibiting multiple-ring structures observed at the same time. The theoretical results in the linear regime are found to be consistent with the wave data.

Digital processing of array seismic recordings

USGS Publications Warehouse

Ryall, Alan; Birtill, John

1962-01-01

This technical letter contains a brief review of the operations which are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these operations (the "UK Method" and multiple correlation). Examples are presented of analyses by the several techniques on array recordings which were obtained by the U.S. Geological Survey during chemical and nuclear explosions in the western United States. Seismograms are synthesized using actual noise and Pn-signal recordings, such that the signal-to-noise ratio, onset time and velocity of the signal are predetermined for the synthetic record. These records are then analyzed by summation, cross-multiplication, multiple correlation and the UK technique, and the results are compared. For all of the examples presented, analysis by the non-linear techniques of multiple correlation and cross-multiplication of the traces on an array recording are preferred to analyses by the linear operations involved in summation and the UK Method.

Multimodal biometric system using rank-level fusion approach.

PubMed

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.

Indoor molds and lung function in healthy adults.

PubMed

Hernberg, Samu; Sripaiboonkij, Penpatra; Quansah, Reginald; Jaakkola, Jouni J K; Jaakkola, Maritta S

2014-05-01

Indoor mold exposure is common worldwide and constitutes an important health problem. There are very few studies assessing the relation between mold exposure and lung function levels among non-asthmatic adults. Our objective was to assess the relations between dampness and mold exposures at home and at work and lung function. In particular, we elaborated the importance of different exposure indicators. In a population-based study, 269 non-asthmatic adults from South Finland answered a questionnaire on indoor dampness and mold exposures at home or at work and other factors potentially influencing lung function, and performed spirometry. Multiple linear regression model was applied to study the relations between exposures and spirometric lung function levels. In linear regression adjusting for confounding, FEV1 level was reduced on average 200 ml related to mold odor at home (effect estimate -0.20, 95% CI -0.60 to 0.21) and FVC level was reduced on average 460 ml (-0.46, -0.95 to 0.03) respectively. Exposure to mold odor at home or at work or both was related to reduced FEV1 (-0.15, -0.42 to 0.12) and FVC (-0.22, -0.55 to 0.11) levels. Women had on average 510 ml reduced FEV1 levels (-0.51, -1.0 to 0.03) and 820 ml reduced FVC levels (-0.82, -1.4 to -0.20) related to mold odor exposure at home. Mold odor exposure was related to lower lung function levels among non-asthmatic adults, especially among women. Copyright © 2014 Elsevier Ltd. All rights reserved.

BIODEGRADATION PROBABILITY PROGRAM (BIODEG)

EPA Science Inventory

The Biodegradation Probability Program (BIODEG) calculates the probability that a chemical under aerobic conditions with mixed cultures of microorganisms will biodegrade rapidly or slowly. It uses fragment constants developed using multiple linear and non-linear regressions and d...

The Use of Linear Programming for Prediction.

ERIC Educational Resources Information Center

Schnittjer, Carl J.

The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

Linear mixed-effects modeling approach to FMRI group analysis

PubMed Central

Chen, Gang; Saad, Ziad S.; Britton, Jennifer C.; Pine, Daniel S.; Cox, Robert W.

2013-01-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance–covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance–covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. PMID:23376789

Emission and distribution of phosphine in paddy fields and its relationship with greenhouse gases.

PubMed

Chen, Weiyi; Niu, Xiaojun; An, Shaorong; Sheng, Hong; Tang, Zhenghua; Yang, Zhiquan; Gu, Xiaohong

2017-12-01

Phosphine (PH 3 ), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO 2 ) and methane (CH 4 ) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO 2 emission flux and PH 3 emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH 4 and PH 3 (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH 3 ] flux =0.007[CO 2 ] flux +0.063[CH 4 ] flux -4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO 2 ), and soil methane (SCH 4 ) in paddy soils. However, there was a significant positive correlation between MBP and SCO 2 at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO 2 and SCH 4 . Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Linear mixed-effects modeling approach to FMRI group analysis.

PubMed

Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W

2013-06-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. Published by Elsevier Inc.

Factors Associated With Patient-perceived Hoarseness in Spasmodic Dysphonia Patients.

PubMed

Hu, Amanda; Hillel, Al; Meyer, Tanya

2016-11-01

The American Academy of Otolaryngology-Head and Neck Surgery Clinical Practice Guidelines on Hoarseness distinguishes between hoarseness, which is a symptom perceived by the patient, and dysphonia, which is a diagnosis made by the clinician. Our objective was to determine factors that are associated with patient-perceived hoarseness in spasmodic dysphonia (SD) patients. Retrospective study. Adductor SD patients who presented for botulinum toxin injections from September 2011 to June 2012 were recruited. The main outcome variable, Voice Handicap Index-10 (VHI-10), was used to quantify patient-perceived hoarseness. Clinical data, Hospital Anxiety and Depression Scale (HADS), and VHI-10 were collected. Clinician-perceived dysphonia was measured by a speech-language pathologist with Consensus Auditory Perceptual Evaluation of Voice (CAPE-V). Statistical analysis included univariate analyses and multiple linear regression. One hundred thirty-nine SD patients had VHI-10 score of 26.0 ± 7.2 (mean ± standard deviation), disease duration of 10.5 + 7.0 years, CAPE-V overall score of 43.2 ± 21.8, HADS anxiety score of 6.7 ± 3.8, and HADS depression score of 3.6 ± 2.8. In univariate analyses, there were positive correlations (P < 0.05) between VHI-10 and female gender, CAPE-V overall, older age, HADS anxiety, and depression. There was no correlation with professional voice use and disease duration. In multiple linear regression (R 2  = 0.178, P < 0.001), age, HADS anxiety, female gender, and CAPE-V were significant. Older age, higher anxiety levels, female gender, and clinician-perceived dysphonia are associated with higher levels of patient-perceived hoarseness in SD patients. Hoarseness is a very personal symptom. Multiple factors determine its self-perception. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Multi-Wavelength, Multi-Beam, and Polarization-Sensitive Laser Transmitter for Surface Mapping

NASA Technical Reports Server (NTRS)

Yu, Anthony W.; Ramos-Izquierdo, Luis; Harding, David; Huss, Tim

2011-01-01

A multi-beam, multi-color, polarized laser transmitter has been developed for mapping applications. It uses commercial off-the-shelf components for a lowcost approach for a ruggedized laser suitable for field deployment. The laser transmitter design is capable of delivering dual wavelengths, multiple beams on each wavelength with equal (or variable) intensities per beam, and a welldefined state of polarization. This laser transmitter has been flown on several airborne campaigns for the Slope Imaging Multi-Polarization Photon Counting Lidar (SIMPL) instrument, and at the time of this reporting is at a technology readiness level of between 5 and 6. The laser is a 1,064-nm microchip high-repetition-rate laser emitting energy of about 8 microjoules per pulse. The beam was frequency-doubled to 532 nm using a KTP (KTiOPO4) nonlinear crystal [other nonlinear crystals such as LBO (LiB3O5) or periodically poled lithium niobiate can be used as well, depending on the conversion efficiency requirements], and the conversion efficiency was approximately 30 percent. The KTP was under temperature control using a thermoelectric cooler and a feedback monitoring thermistor. The dual-wavelength beams were then spectrally separated and each color went through its own optical path, which consisted of a beam-shaping lens, quarterwave plate (QWP), and a birefringent crystal (in this case, a calcite crystal, but others such as vanadate can be used). The QWP and calcite crystal set was used to convert the laser beams from a linearly polarized state to circularly polarized light, which when injected into a calcite crystal, will spatially separate the circularly polarized light into the two linear polarized components. The spatial separation of the two linearly polarized components is determined by the length of the crystal. A second set of QWP and calcite then further separated the two beams into four. Additional sets of QWP and calcite can be used to further split the beams into multiple orders of two. The spatially separated beams had alternating linearly polarization states; a half-wave plate (HWP) array was then made to rotate the alternating states of A multi-beam, multi-color, polarized laser transmitter has been developed for mapping applications. It uses commercial off-the-shelf components for a lowcost approach for a ruggedized laser suitable for field deployment. The laser transmitter design is capable of delivering dual wavelengths, multiple beams on each wavelength with equal (or variable) intensities per beam, and a welldefined state of polarization. This laser transmitter has been flown on several airborne campaigns for the Slope Imaging Multi-Polarization Photon Counting Lidar (SIMPL) instrument, and at the time of this reporting is at a technology readiness level of between 5 and 6. The laser is a 1,064-nm microchip high-repetition-rate laser emitting energy of about 8 microjoules per pulse. The beam was frequency-doubled to 532 nm using a KTP (KTiOPO4) nonlinear crystal [other nonlinear crystals such as LBO (LiB3O5) or periodically poled lithium niobiate can be used as well, depending on the conversion efficiency requirements], and the conversion efficiency was approximately 30 percent. The KTP was under temperature control using a thermoelectric cooler and a feedback monitoring thermistor. The dual-wavelength beams were then spectrally separated and each color went through its own optical path, which consisted of a beam-shaping lens, quarterwave plate (QWP), and a birefringent crystal (in this case, a calcite crystal, but others such as vanadate can be used). The QWP and calcite crystal set was used to convert the laser beams from a linearly polarized state to circularly polarized light, which when injected into a calcite crystal, will spatially separate the circularly polarized light into the two linear polarized components. The spatial separation of the two linearly polarized components is determined by the length of the crystal. A cond set of QWP and calcite then further separated the two beams into four. Additional sets of QWP and calcite can be used to further split the beams into multiple orders of two. The spatially separated beams had alternating linearly polarization states; a half-wave plate (HWP) array was then made to rotate the alternating states of

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia.

PubMed

Rodriguez-Sabate, Clara; Morales, Ingrid; Sanchez, Alberto; Rodriguez, Manuel

2017-01-01

The complexity of basal ganglia (BG) interactions is often condensed into simple models mainly based on animal data and that present BG in closed-loop cortico-subcortical circuits of excitatory/inhibitory pathways which analyze the incoming cortical data and return the processed information to the cortex. This study was aimed at identifying functional relationships in the BG motor-loop of 24 healthy-subjects who provided written, informed consent and whose BOLD-activity was recorded by MRI methods. The analysis of the functional interaction between these centers by correlation techniques and multiple linear regression showed non-linear relationships which cannot be suitably addressed with these methods. The multiple correspondence analysis (MCA), an unsupervised multivariable procedure which can identify non-linear interactions, was used to study the functional connectivity of BG when subjects were at rest. Linear methods showed different functional interactions expected according to current BG models. MCA showed additional functional interactions which were not evident when using lineal methods. Seven functional configurations of BG were identified with MCA, two involving the primary motor and somatosensory cortex, one involving the deepest BG (external-internal globus pallidum, subthalamic nucleus and substantia nigral), one with the input-output BG centers (putamen and motor thalamus), two linking the input-output centers with other BG (external pallidum and subthalamic nucleus), and one linking the external pallidum and the substantia nigral. The results provide evidence that the non-linear MCA and linear methods are complementary and should be best used in conjunction to more fully understand the nature of functional connectivity of brain centers.

Development of a Multiple Linear Regression Model to Forecast Facility Electrical Consumption at an Air Force Base.

DTIC Science & Technology

1981-09-01

corresponds to the same square footage that consumed the electrical energy. 3. The basic assumptions of multiple linear regres- sion, as enumerated in...7. Data related to the sample of bases is assumed to be representative of bases in the population. Limitations Basic limitations on this research were... Ratemaking --Overview. Rand Report R-5894, Santa Monica CA, May 1977. Chatterjee, Samprit, and Bertram Price. Regression Analysis by Example. New York: John

Impact of Learning Styles on Air Force Technical Training: Multiple and Linear Imagery in the Presentation of a Comparative Visual Location Task to Visual and Haptic Subjects. Interim Report for Period January 1977-January 1978.

ERIC Educational Resources Information Center

Ausburn, Floyd B.

A U.S. Air Force study was designed to develop instruction based on the supplantation theory, in which tasks are performed (supplanted) for individuals who are unable to perform them due to their cognitive style. The study examined the effects of linear and multiple imagery in presenting a task requiring visual comparison and location to…

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Rising tides, cumulative impacts and cascading changes to estuarine ecosystem functions.

PubMed

O'Meara, Theresa A; Hillman, Jenny R; Thrush, Simon F

2017-08-31

In coastal ecosystems, climate change affects multiple environmental factors, yet most predictive models are based on simple cause-and-effect relationships. Multiple stressor scenarios are difficult to predict because they can create a ripple effect through networked ecosystem functions. Estuarine ecosystem function relies on an interconnected network of physical and biological processes. Estuarine habitats play critical roles in service provision and represent global hotspots for organic matter processing, nutrient cycling and primary production. Within these systems, we predicted functional changes in the impacts of land-based stressors, mediated by changing light climate and sediment permeability. Our in-situ field experiment manipulated sea level, nutrient supply, and mud content. We used these stressors to determine how interacting environmental stressors influence ecosystem function and compared results with data collected along elevation gradients to substitute space for time. We show non-linear, multi-stressor effects deconstruct networks governing ecosystem function. Sea level rise altered nutrient processing and impacted broader estuarine services ameliorating nutrient and sediment pollution. Our experiment demonstrates how the relationships between nutrient processing and biological/physical controls degrade with environmental stress. Our results emphasise the importance of moving beyond simple physically-forced relationships to assess consequences of climate change in the context of ecosystem interactions and multiple stressors.

Summary of the SeaRISE Project's Experiments on Modeled Ice-Sheet Contributions to Future Sea Level: Linearities and Non-linearities

NASA Astrophysics Data System (ADS)

Bindschadler, Robert

2013-04-01

The SeaRISE (Sea-level Response to Ice Sheet Evolution) project achieved ice-sheet model ensemble responses to a variety of prescribed changes to surface mass balance, basal sliding and ocean boundary melting. Greenland ice sheet models are more sensitive than Antarctic ice sheet models to likely atmospheric changes in surface mass balance, while Antarctic models are most sensitive to basal melting of its ice shelves. An experiment approximating the IPCC's RCP8.5 scenario produces first century contributions to sea level of 22.3 and 7.3 cm from Greenland and Antarctica, respectively, with a range among models of 62 and 17 cm, respectively. By 200 years, these projections increase to 53.2 and 23.4 cm, respectively, with ranges of 79 and 57 cm. The considerable range among models was not only in the magnitude of ice lost, but also in the spatial pattern of response to identical forcing. Despite this variation, the response of any single model to a large range in the forcing intensity was remarkably linear in most cases. Additionally, the results of sensitivity experiments to single types of forcing (i.e., only one of the surface mass balance, or basal sliding, or ocean boundary melting) could be summed to accurately predict any model's result for an experiment when multiple forcings were applied simultaneously. This suggests a limited amount of feedback through the ice sheet's internal dynamics between these types of forcing over the time scale of a few centuries (SeaRISE experiments lasted 500 years).

On application of kernel PCA for generating stimulus features for fMRI during continuous music listening.

PubMed

Tsatsishvili, Valeri; Burunat, Iballa; Cong, Fengyu; Toiviainen, Petri; Alluri, Vinoo; Ristaniemi, Tapani

2018-06-01

There has been growing interest towards naturalistic neuroimaging experiments, which deepen our understanding of how human brain processes and integrates incoming streams of multifaceted sensory information, as commonly occurs in real world. Music is a good example of such complex continuous phenomenon. In a few recent fMRI studies examining neural correlates of music in continuous listening settings, multiple perceptual attributes of music stimulus were represented by a set of high-level features, produced as the linear combination of the acoustic descriptors computationally extracted from the stimulus audio. NEW METHOD: fMRI data from naturalistic music listening experiment were employed here. Kernel principal component analysis (KPCA) was applied to acoustic descriptors extracted from the stimulus audio to generate a set of nonlinear stimulus features. Subsequently, perceptual and neural correlates of the generated high-level features were examined. The generated features captured musical percepts that were hidden from the linear PCA features, namely Rhythmic Complexity and Event Synchronicity. Neural correlates of the new features revealed activations associated to processing of complex rhythms, including auditory, motor, and frontal areas. Results were compared with the findings in the previously published study, which analyzed the same fMRI data but applied linear PCA for generating stimulus features. To enable comparison of the results, methodology for finding stimulus-driven functional maps was adopted from the previous study. Exploiting nonlinear relationships among acoustic descriptors can lead to the novel high-level stimulus features, which can in turn reveal new brain structures involved in music processing. Copyright © 2018 Elsevier B.V. All rights reserved.

A newly recognized syndrome of severe growth deficiency, microcephaly, intellectual disability, and characteristic facial features.

PubMed

Vinkler, Chana; Leshinsky-Silver, Esther; Michelson, Marina; Haas, Dorothea; Lerman-Sagie, Tally; Lev, Dorit

2014-01-01

Genetic syndromes with proportionate severe short stature are rare. We describe two sisters born to nonconsanguineous parents with severe linear growth retardation, poor weight gain, microcephaly, characteristic facial features, cutaneous syndactyly of the toes, high myopia, and severe intellectual disability. During infancy and early childhood, the girls had transient hepatosplenomegaly and low blood cholesterol levels that normalized later. A thorough evaluation including metabolic studies, radiological, and genetic investigations were all normal. Cholesterol metabolism and transport were studied and no definitive abnormality was found. No clinical deterioration was observed and no metabolic crises were reported. After due consideration of other known hereditary causes of post-natal severe linear growth retardation, microcephaly, and intellectual disability, we propose that this condition represents a newly recognized autosomal recessive multiple congenital anomaly-intellectual disability syndrome. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

An improved SRC method based on virtual samples for face recognition

NASA Astrophysics Data System (ADS)

Fu, Lijun; Chen, Deyun; Lin, Kezheng; Li, Ao

2018-07-01

The sparse representation classifier (SRC) performs classification by evaluating which class leads to the minimum representation error. However, in real world, the number of available training samples is limited due to noise interference, training samples cannot accurately represent the test sample linearly. Therefore, in this paper, we first produce virtual samples by exploiting original training samples at the aim of increasing the number of training samples. Then, we take the intra-class difference as data representation of partial noise, and utilize the intra-class differences and training samples simultaneously to represent the test sample in a linear way according to the theory of SRC algorithm. Using weighted score level fusion, the respective representation scores of the virtual samples and the original training samples are fused together to obtain the final classification results. The experimental results on multiple face databases show that our proposed method has a very satisfactory classification performance.

Multiple metal exposures and their correlation with monoamine neurotransmitter metabolism in Chinese electroplating workers.

PubMed

Wu, Lin-Lin; Gong, Wei; Shen, Si-Peng; Wang, Zhong-He; Yao, Jia-Xi; Wang, Jun; Yu, Jing; Gao, Rong; Wu, Gang

2017-09-01

Excessive metal exposure has been recognized as one of the detrimental factors for brain damage. However, the potential adverse effects induced by heavy metals on monoamine neurotransmitter pathways remains poorly understood. Our study aimed to investigate the possible association between metal exposure and neurotransmitter metabolism. By a cross-sectional investigation, 224 electroplating workers and 213 non-electroplating exposure workers were recruited in the exposure and control groups. Metal exposure levels were analyzed using inductively-coupled plasma mass spectrometry and monoamine neurotransmitter pathway metabolites were measured by ultra-performance liquid chromatography tandem mass spectrometry in human urine samples. Multivariate linear regression model was used to assess the dose-response relationships of urinary metals and neurotransmitter pathway metabolites. Significant dose-dependent trends of urinary vanadium quartiles with all metabolites were observed, and the trends demonstrated significance after multiple testing correction. It also showed that urinary chromium levels were significantly associated with decreased serotonin level and cadmium was positively associated with norepinephrine and epinephrine. In addition, arsenic was positively associated with tryptophan, serotonin, dopamine and norepinephrine. Iron was positively associated with increased homovanillic acid (HVA) and epinephrine while nickel was negatively associated with increased epinephrine levels. Zinc was positively related to tryptophan, kynurenin (KYN), 5-hydroxyindole acetic acid (5-HIAA), dopamine, HVA and norepinephrine. There was no significant association between urinary copper with any other metabolites after adjusting of multiple metal models. Metal exposure may be associated with neurotransmitter metabolism disturbances. The present work is expected to provide some support in the prevention and management of metal-associated neurological diseases. Copyright © 2017. Published by Elsevier Ltd.

Robust set-point regulation for ecological models with multiple management goals.

PubMed

Guiver, Chris; Mueller, Markus; Hodgson, Dave; Townley, Stuart

2016-05-01

Population managers will often have to deal with problems of meeting multiple goals, for example, keeping at specific levels both the total population and population abundances in given stage-classes of a stratified population. In control engineering, such set-point regulation problems are commonly tackled using multi-input, multi-output proportional and integral (PI) feedback controllers. Building on our recent results for population management with single goals, we develop a PI control approach in a context of multi-objective population management. We show that robust set-point regulation is achieved by using a modified PI controller with saturation and anti-windup elements, both described in the paper, and illustrate the theory with examples. Our results apply more generally to linear control systems with positive state variables, including a class of infinite-dimensional systems, and thus have broader appeal.

Anxiety and depression are more prevalent in patients with graves' disease than in patients with nodular goitre.

PubMed

Bové, Kira Bang; Watt, Torquil; Vogel, Asmus; Hegedüs, Laszlo; Bjoerner, Jakob Bue; Groenvold, Mogens; Bonnema, Steen Joop; Rasmussen, Åse Krogh; Feldt-Rasmussen, Ulla

2014-09-01

Graves' disease has been associated with an increased psychiatric morbidity. It is unclarified whether this relates to Graves' disease or chronic disease per se. The aim of our study was to estimate the prevalence of anxiety and depression symptoms in patients with Graves' disease compared to patients with another chronic thyroid disease, nodular goitre, and to investigate determinants of anxiety and depression in Graves' disease. 157 cross-sectionally sampled patients with Graves' disease, 17 newly diagnosed, 140 treated, and 251 controls with nodular goitre completed the Hospital Anxiety and Depression Scale (HADS). The differences in the mean HADS scores between the groups were analysed using multiple linear regression, controlling for socio-demographic variables. HADS scores were also analysed dichotomized: a score >10 indicating probable 'anxiety'/probable 'depression'. Determinants of anxiety and depression symptoms in Graves' disease were examined using multiple linear regression. In Graves' disease levels of anxiety (p = 0.008) and depression (p = 0.014) were significantly higher than in controls. The prevalence of depression was 10% in Graves' disease versus 4% in nodular goitre (p = 0.038), anxiety was 18 versus 13% (p = 0.131). Symptoms of anxiety (p = 0.04) and depression (p = 0.01) increased with comorbidity. Anxiety symptoms increased with duration of Graves' disease (p = 0.04). Neither thyroid function nor autoantibody levels were associated with anxiety and depression symptoms. Anxiety and depression symptoms were more severe in Graves' disease than in nodular goitre. Symptoms were positively correlated to comorbidity and duration of Graves' disease but neither to thyroid function nor thyroid autoimmunity.

QSRR modeling for the chromatographic retention behavior of some β-lactam antibiotics using forward and firefly variable selection algorithms coupled with multiple linear regression.

PubMed

Fouad, Marwa A; Tolba, Enas H; El-Shal, Manal A; El Kerdawy, Ahmed M

2018-05-11

The justified continuous emerging of new β-lactam antibiotics provokes the need for developing suitable analytical methods that accelerate and facilitate their analysis. A face central composite experimental design was adopted using different levels of phosphate buffer pH, acetonitrile percentage at zero time and after 15 min in a gradient program to obtain the optimum chromatographic conditions for the elution of 31 β-lactam antibiotics. Retention factors were used as the target property to build two QSRR models utilizing the conventional forward selection and the advanced nature-inspired firefly algorithm for descriptor selection, coupled with multiple linear regression. The obtained models showed high performance in both internal and external validation indicating their robustness and predictive ability. Williams-Hotelling test and student's t-test showed that there is no statistical significant difference between the models' results. Y-randomization validation showed that the obtained models are due to significant correlation between the selected molecular descriptors and the analytes' chromatographic retention. These results indicate that the generated FS-MLR and FFA-MLR models are showing comparable quality on both the training and validation levels. They also gave comparable information about the molecular features that influence the retention behavior of β-lactams under the current chromatographic conditions. We can conclude that in some cases simple conventional feature selection algorithm can be used to generate robust and predictive models comparable to that are generated using advanced ones. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool.

PubMed

Aqil, Muhammad; Kita, Ichiro; Yano, Akira; Nishiyama, Soichi

2007-10-01

Traditionally, the multiple linear regression technique has been one of the most widely used models in simulating hydrological time series. However, when the nonlinear phenomenon is significant, the multiple linear will fail to develop an appropriate predictive model. Recently, neuro-fuzzy systems have gained much popularity for calibrating the nonlinear relationships. This study evaluated the potential of a neuro-fuzzy system as an alternative to the traditional statistical regression technique for the purpose of predicting flow from a local source in a river basin. The effectiveness of the proposed identification technique was demonstrated through a simulation study of the river flow time series of the Citarum River in Indonesia. Furthermore, in order to provide the uncertainty associated with the estimation of river flow, a Monte Carlo simulation was performed. As a comparison, a multiple linear regression analysis that was being used by the Citarum River Authority was also examined using various statistical indices. The simulation results using 95% confidence intervals indicated that the neuro-fuzzy model consistently underestimated the magnitude of high flow while the low and medium flow magnitudes were estimated closer to the observed data. The comparison of the prediction accuracy of the neuro-fuzzy and linear regression methods indicated that the neuro-fuzzy approach was more accurate in predicting river flow dynamics. The neuro-fuzzy model was able to improve the root mean square error (RMSE) and mean absolute percentage error (MAPE) values of the multiple linear regression forecasts by about 13.52% and 10.73%, respectively. Considering its simplicity and efficiency, the neuro-fuzzy model is recommended as an alternative tool for modeling of flow dynamics in the study area.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

NASA Astrophysics Data System (ADS)

Huang, Zhi; Fan, Baozheng; Song, Xiaolin

2018-03-01

As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

Multiband selection with linear array detectors

NASA Technical Reports Server (NTRS)

Richard, H. L.; Barnes, W. L.

1985-01-01

Several techniques that can be used in an earth-imaging system to separate the linear image formed after the collecting optics into the desired spectral band are examined. The advantages and disadvantages of the Multispectral Linear Array (MLA) multiple optics, the MLA adjacent arrays, the imaging spectrometer, and the MLA beam splitter are discussed. The beam-splitter design approach utilizes, in addition to relatively broad spectral region separation, a movable Multiband Selection Device (MSD), placed between the exit ports of the beam splitter and a linear array detector, permitting many bands to be selected. The successful development and test of the MSD is described. The device demonstrated the capacity to provide a wide field of view, visible-to-near IR/short-wave IR and thermal IR capability, and a multiplicity of spectral bands and polarization measuring means, as well as a reasonable size and weight at minimal cost and risk compared to a spectrometer design approach.

Waste management under multiple complexities: inexact piecewise-linearization-based fuzzy flexible programming.

PubMed

Sun, Wei; Huang, Guo H; Lv, Ying; Li, Gongchen

2012-06-01

To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities. Copyright © 2012 Elsevier Ltd. All rights reserved.

Stroop Color-Word Interference Test: Normative data for Spanish-speaking pediatric population.

PubMed

Rivera, D; Morlett-Paredes, A; Peñalver Guia, A I; Irías Escher, M J; Soto-Añari, M; Aguayo Arelis, A; Rute-Pérez, S; Rodríguez-Lorenzana, A; Rodríguez-Agudelo, Y; Albaladejo-Blázquez, N; García de la Cadena, C; Ibáñez-Alfonso, J A; Rodriguez-Irizarry, W; García-Guerrero, C E; Delgado-Mejía, I D; Padilla-López, A; Vergara-Moragues, E; Barrios Nevado, M D; Saracostti Schwartzman, M; Arango-Lasprilla, J C

2017-01-01

To generate normative data for the Stroop Word-Color Interference test in Spanish-speaking pediatric populations. The sample consisted of 4,373 healthy children from nine countries in Latin America (Chile, Cuba, Ecuador, Guatemala, Honduras, Mexico, Paraguay, Peru, and Puerto Rico) and Spain. Each participant was administered the Stroop Word-Color Interference test as part of a larger neuropsychological battery. The Stroop Word, Stroop Color, Stroop Word-Color, and Stroop Interference scores were normed using multiple linear regressions and standard deviations of residual values. Age, age2, sex, and mean level of parental education (MLPE) were included as predictors in the analyses. The final multiple linear regression models showed main effects for age on all scores, except on Stroop Interference for Guatemala, such that scores increased linearly as a function of age. Age2 affected Stroop Word scores for all countries, Stroop Color scores for Ecuador, Mexico, Peru, and Spain; Stroop Word-Color scores for Ecuador, Mexico, and Paraguay; and Stroop Interference scores for Cuba, Guatemala, and Spain. MLPE affected Stroop Word scores for Chile, Mexico, and Puerto Rico; Stroop Color scores for Mexico, Puerto Rico, and Spain; Stroop Word-Color scores for Ecuador, Guatemala, Mexico, Puerto Rico and Spain; and Stroop-Interference scores for Ecuador, Mexico, and Spain. Sex affected Stroop Word scores for Spain, Stroop Color scores for Mexico, and Stroop Interference for Honduras. This is the largest Spanish-speaking pediatric normative study in the world, and it will allow neuropsychologists from these countries to have a more accurate approach to interpret the Stroop Word-Color Interference test in pediatric populations.

[Correlation of retinol binding protein 4 with 
metabolic indexes of glucose and 
lipid, bile cholesterol saturation index].

PubMed

Wang, Wen; Li, Nianfeng

2015-06-01

To measure retinol binding protein 4 (RBP4) levels in serum and bile and to analyze their relationship with insulin resistance, dyslipidemia or cholesterol saturation index (CSI).
 A total of 60 patients with gallstone were divided into a diabetes group (n=30) and a control group (n=30). The concentrations of RBP4 in serum and bile were detected by enzyme-linked immunosorbent assay (ELISA). Enzyme colorimetric method was used to measure the concentration of biliary cholesterol, bile acid and phospholipid. Biliary CSI was calculated by Carey table. Partial correlation and multiple linear regression analysis were used to evaluate the correlation between the RBP4 levels in serum or bile and the above indexes.
 The RBP4 concentrations in serum and bile in the diabetes group were significantly elevated compared with those in the control group (both P<0.01). There was no significant difference in the serum total bile acid (TBA), serum triglyceride (TG), serum high-density lipoprotein (HDL), bile TBA, bile total cholesterol (TC) , bile phospholipids and bile CSI between the 2 groups (all P>0.05); but the serum TC, low density lipoprotein (LDL), fasting blood glucose (FBG), fasting insulin (FINS), and homeostasis model assessment for insulin resistance (HOMA-IR) in the diabetes group were significantly increased compared to those in the control group (all P<0.05). The partial correlation analysis, which was adjusted by age, showed that the bile RBP4 was positively correlated with body mass index (BMI), waist circumference (WC), FINS, FBG, TC, LDL and HOMA-IR (r=0.283, 0.405, 0.685, 0.667, 0.553, 0.424 and 0.735, respectively), and the serum RBP4 was also positively correlated with the WC, FINS, FBG, TC, LDL and HOMA-IR (r=0.317, 0.734, 0.609, 0.528, 0.386 and 0.751, respectively). Stepwise multivariate linear regression analysis suggested that the HOMA-IR, BMI and WC were independently correlated with the level of bile RBP4 (multiple regression equation: Ybile RBP4=2.372XHOMA-IR+0.420XBMI+0.178XWC-26.813), and the serum RBP4 level was correlated with the HOMA-IR and WC independently (multiple regression equation: Yserum RBP4=2.832XHOMA-IR +0.235XWC-20.128). Multiple regression equations showed that HOMA-IR was the strongest correlation factor with RBP4.
 RBP4 concentrations in serum and bile in the diabetes group are significantly higher than those in the control group. HOMA-IR, BMI and WC are independently correlated with the level of bile RBP4. HOMA-IR and WC are independently correlated with the serum RBP4 level. HOMA-IR is the strongest correlation factor with RBP4. RBP4 might play an important role in the course of gallstone formation in Type 2 diabetes mellitus.

Factors contributing to tooth loss among the elderly: A cross sectional study.

PubMed

Natto, Zuhair S; Aladmawy, Majdi; Alasqah, Mohammed; Papas, Athena

2014-12-01

The present study evaluates the influence of several demographic, health, personal, and clinical factors on the number of missing teeth in old age sample. The number of patients included was 259; they received a full mouth examination and answered a questionnaire provided by one examiner. All the variables related to teeth loss based on the literature were included. These variables focused on age, gender, race, marital status, clinical attachment level, pocket depth, year of smoking, number of cigarettes smoked per day, number of medications, root decay, coronal decay, health status, and year of education. Statistical analysis involved stepwise multivariate linear regression. Teeth loss was statistically associated with clinical attachment level (CAL)(p value 0.0001), pocket depth (PD) (0.0007) and education level (0.0048). When smoking was included in the model, age was significantly associated with teeth loss (0.0037). At least one of these four factors was also related to teeth loss in several specific groups such as diabetes mellitus, male, and White. The multiple linear regressions for all the proposed variables showed that they contributed to teeth loss by about 23%. It can be concluded that less education or increased clinical attachment level loss may increase number of missing teeth. Additionally, age may cause teeth loss in the presence of smoking. Copyright © 2014. Published by Elsevier B.V.

Impacts of rising tropospheric ozone on photosynthesis and metabolite levels on field grown soybean.

PubMed

Sun, Jindong; Feng, Zhaozhong; Ort, Donald R

2014-09-01

The response of leaf photosynthesis and metabolite profiles to ozone (O3) exposure ranging from 37 to 116 ppb was investigated in two soybean cultivars Dwight and IA3010 in the field under fully open-air conditions. Leaf photosynthesis, total non-structural carbohydrates (TNC) and total free amino acids (TAA) decreased linearly with increasing O3 levels in both cultivars with average decrease of 7% for an increase in O3 levels by 10 ppb. Ozone interacted with developmental stages and leaf ages, and caused higher damage at later reproductive stages and in older leaves. Ozone affected yield mainly via reduction of maximum rate of Rubisco carboxylation (Vcmax) and maximum rates of electron transport (Jmax) as well as a shorter growing season due to earlier onset of canopy senescence. For all parameters investigated the critical O3 levels (∼50 ppb) for detectable damage fell within O3 levels that occur routinely in soybean fields across the US and elsewhere in the world. Strong correlations were observed in O3-induced changes among yield, photosynthesis, TNC, TAA and many metabolites. The broad range of metabolites that showed O3 dose dependent effect is consistent with multiple interaction loci and thus multiple targets for improving the tolerance of soybean to O3. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

MRM assay for quantitation of complement components in human blood plasma - a feasibility study on multiple sclerosis.

PubMed

Rezeli, Melinda; Végvári, Akos; Ottervald, Jan; Olsson, Tomas; Laurell, Thomas; Marko-Varga, György

2011-12-10

As a proof-of-principle study, a multiple reaction monitoring (MRM) assay was developed for quantitation of proteotypic peptides, representing seven plasma proteins associated with inflammation (complement components and C-reactive protein). The assay development and the sample analysis were performed on a linear ion trap mass spectrometer. We were able to quantify 5 of the 7 target proteins in depleted plasma digests with reasonable reproducibility over a 2 orders of magnitude linear range (RSD≤25%). The assay panel was utilized for the analysis of a small multiple sclerosis sample cohort with 10 diseased and 8 control patients. Copyright © 2011 Elsevier B.V. All rights reserved.

A case of unilateral, systematized linear hair follicle nevi associated with epidermal nevus-like lesions.

PubMed

Ikeda, Shigaku; Kawada, Juri; Yaguchi, Hitoshi; Ogawa, Hideoki

2003-01-01

Multiple hair follicle nevi are an extremely rare condition. In 1998, a case of unilateral multiple hair follicle nevi, ipsilateral alopecia and ipsilateral leptomeningeal angiomatosis of the brain was first reported from Japan. Very recently, hair follicle nevus in a distribution following Blaschko's lines has also been reported. In this paper, we observed a congenital case of unilateral, systematized linear hair follicle nevi associated with congenital, ipsilateral, multiple plaque lesions resembling epidermal nevi but lacking leptomeningeal angiomatosis of the brain. These cases implicate the possibility of a novel neurocutaneous syndrome. Additional cases should be sought in order to determine whether this condition is pathophysiologically distinct. Copyright 2003 S. Karger AG, Basel

Iterative-method performance evaluation for multiple vectors associated with a large-scale sparse matrix

NASA Astrophysics Data System (ADS)

Imamura, Seigo; Ono, Kenji; Yokokawa, Mitsuo

2016-07-01

Ensemble computing, which is an instance of capacity computing, is an effective computing scenario for exascale parallel supercomputers. In ensemble computing, there are multiple linear systems associated with a common coefficient matrix. We improve the performance of iterative solvers for multiple vectors by solving them at the same time, that is, by solving for the product of the matrices. We implemented several iterative methods and compared their performance. The maximum performance on Sparc VIIIfx was 7.6 times higher than that of a naïve implementation. Finally, to deal with the different convergence processes of linear systems, we introduced a control method to eliminate the calculation of already converged vectors.

Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

PubMed Central

Brinkworth, Russell S. A.; O'Carroll, David C.

2009-01-01

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors. PMID:19893631

An environmental-level, real-time, pulsed photon dosemeter.

PubMed

Olsher, R H; Frymire, A; Gregoire, T

2005-01-01

Radiation sources producing short pulses of photon radiation are widespread. Such sources include electron linear accelerators and field emission impulse generators. It is often desirable to measure leakage and skyshine radiation for these sources in real time and at environmental levels as low as 0.02 microSv per pulse. This note provides an overview of the design and performance of a commercial, real-time, pulsed photon dosemeter (PPD) capable of single-pulse dose measurements over the range from 0.02 to 20 microSv. The PPD may also be operated in a multiple-pulse mode that integrates the dose from a train of pulses over a 3 s period. A pulse repetition rate of up to 300 Hz is accommodated.

Applications of multivariate modeling to neuroimaging group analysis: A comprehensive alternative to univariate general linear model

PubMed Central

Chen, Gang; Adleman, Nancy E.; Saad, Ziad S.; Leibenluft, Ellen; Cox, RobertW.

2014-01-01

All neuroimaging packages can handle group analysis with t-tests or general linear modeling (GLM). However, they are quite hamstrung when there are multiple within-subject factors or when quantitative covariates are involved in the presence of a within-subject factor. In addition, sphericity is typically assumed for the variance–covariance structure when there are more than two levels in a within-subject factor. To overcome such limitations in the traditional AN(C)OVA and GLM, we adopt a multivariate modeling (MVM) approach to analyzing neuroimaging data at the group level with the following advantages: a) there is no limit on the number of factors as long as sample sizes are deemed appropriate; b) quantitative covariates can be analyzed together with within- subject factors; c) when a within-subject factor is involved, three testing methodologies are provided: traditional univariate testing (UVT)with sphericity assumption (UVT-UC) and with correction when the assumption is violated (UVT-SC), and within-subject multivariate testing (MVT-WS); d) to correct for sphericity violation at the voxel level, we propose a hybrid testing (HT) approach that achieves equal or higher power via combining traditional sphericity correction methods (Greenhouse–Geisser and Huynh–Feldt) with MVT-WS. PMID:24954281

Combined effects of Hurricane Katrina and Hurricane Gustav on the mental health of mothers of small children.

PubMed

Harville, E W; Xiong, X; Smith, B W; Pridjian, G; Elkind-Hirsch, K; Buekens, P

2011-05-01

Few studies have assessed the results of multiple exposures to disaster. Our objective was to examine the effect of experiencing Hurricane Gustav on mental health of women previously exposed to Hurricane Katrina. A total of 102 women from Southern Louisiana were interviewed by telephone. Experience of the hurricanes was assessed with questions about injury, danger and damage, while depression was assessed with the Edinburgh Depression Scale and post-traumatic stress disorder using the Post-Traumatic Checklist. Minor stressors, social support, trait resilience and perceived benefit had been measured previously. Mental health was examined with linear and log-linear models. Women who had a severe experience of both Gustav and Katrina scored higher on the mental health scales, but finding new ways to cope after Katrina or feeling more prepared was not protective. About half the population had better mental health scores after Gustav than at previous measures. Improvement was more likely among those who reported high social support or low levels of minor stressors, or were younger. Trait resilience mitigated the effect of hurricane exposure. Multiple disaster experiences are associated with worse mental health overall, although many women are resilient. Perceiving benefit after the first disaster was not protective. © 2010 Blackwell Publishing.

Emergent properties of interacting populations of spiking neurons.

PubMed

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.

Plasma amino acid profile associated with fatty liver disease and co-occurrence of metabolic risk factors.

PubMed

Yamakado, Minoru; Tanaka, Takayuki; Nagao, Kenji; Imaizumi, Akira; Komatsu, Michiharu; Daimon, Takashi; Miyano, Hiroshi; Tani, Mizuki; Toda, Akiko; Yamamoto, Hiroshi; Horimoto, Katsuhisa; Ishizaka, Yuko

2017-11-03

Fatty liver disease (FLD) increases the risk of diabetes, cardiovascular disease, and steatohepatitis, which leads to fibrosis, cirrhosis, and hepatocellular carcinoma. Thus, the early detection of FLD is necessary. We aimed to find a quantitative and feasible model for discriminating the FLD, based on plasma free amino acid (PFAA) profiles. We constructed models of the relationship between PFAA levels in 2,000 generally healthy Japanese subjects and the diagnosis of FLD by abdominal ultrasound scan by multiple logistic regression analysis with variable selection. The performance of these models for FLD discrimination was validated using an independent data set of 2,160 subjects. The generated PFAA-based model was able to identify FLD patients. The area under the receiver operating characteristic curve for the model was 0.83, which was higher than those of other existing liver function-associated markers ranging from 0.53 to 0.80. The value of the linear discriminant in the model yielded the adjusted odds ratio (with 95% confidence intervals) for a 1 standard deviation increase of 2.63 (2.14-3.25) in the multiple logistic regression analysis with known liver function-associated covariates. Interestingly, the linear discriminant values were significantly associated with the progression of FLD, and patients with nonalcoholic steatohepatitis also exhibited higher values.

Emergent Properties of Interacting Populations of Spiking Neurons

PubMed Central

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations. PMID:22207844

Predicting Retention Times of Naturally Occurring Phenolic Compounds in Reversed-Phase Liquid Chromatography: A Quantitative Structure-Retention Relationship (QSRR) Approach

PubMed Central

Akbar, Jamshed; Iqbal, Shahid; Batool, Fozia; Karim, Abdul; Chan, Kim Wei

2012-01-01

Quantitative structure-retention relationships (QSRRs) have successfully been developed for naturally occurring phenolic compounds in a reversed-phase liquid chromatographic (RPLC) system. A total of 1519 descriptors were calculated from the optimized structures of the molecules using MOPAC2009 and DRAGON softwares. The data set of 39 molecules was divided into training and external validation sets. For feature selection and mapping we used step-wise multiple linear regression (SMLR), unsupervised forward selection followed by step-wise multiple linear regression (UFS-SMLR) and artificial neural networks (ANN). Stable and robust models with significant predictive abilities in terms of validation statistics were obtained with negation of any chance correlation. ANN models were found better than remaining two approaches. HNar, IDM, Mp, GATS2v, DISP and 3D-MoRSE (signals 22, 28 and 32) descriptors based on van der Waals volume, electronegativity, mass and polarizability, at atomic level, were found to have significant effects on the retention times. The possible implications of these descriptors in RPLC have been discussed. All the models are proven to be quite able to predict the retention times of phenolic compounds and have shown remarkable validation, robustness, stability and predictive performance. PMID:23203132

Neural network and multiple linear regression to predict school children dimensions for ergonomic school furniture design.

PubMed

Agha, Salah R; Alnahhal, Mohammed J

2012-11-01

The current study investigates the possibility of obtaining the anthropometric dimensions, critical to school furniture design, without measuring all of them. The study first selects some anthropometric dimensions that are easy to measure. Two methods are then used to check if these easy-to-measure dimensions can predict the dimensions critical to the furniture design. These methods are multiple linear regression and neural networks. Each dimension that is deemed necessary to ergonomically design school furniture is expressed as a function of some other measured anthropometric dimensions. Results show that out of the five dimensions needed for chair design, four can be related to other dimensions that can be measured while children are standing. Therefore, the method suggested here would definitely save time and effort and avoid the difficulty of dealing with students while measuring these dimensions. In general, it was found that neural networks perform better than multiple linear regression in the current study. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

A survey of the state of the art and focused research in range systems, task 2

NASA Technical Reports Server (NTRS)

Yao, K.

1986-01-01

Many communication, control, and information processing subsystems are modeled by linear systems incorporating tapped delay lines (TDL). Such optimized subsystems result in full precision multiplications in the TDL. In order to reduce complexity and cost in a microprocessor implementation, these multiplications can be replaced by single-shift instructions which are equivalent to powers of two multiplications. Since, in general, the obvious operation of rounding the infinite precision TDL coefficients to the nearest powers of two usually yield quite poor system performance, the optimum powers of two coefficient solution was considered. Detailed explanations on the use of branch-and-bound algorithms for finding the optimum powers of two solutions are given. Specific demonstration of this methodology to the design of a linear data equalizer and its implementation in assembly language on a 8080 microprocessor with a 12 bit A/D converter are reported. This simple microprocessor implementation with optimized TDL coefficients achieves a system performance comparable to the optimum linear equalization with full precision multiplications for an input data rate of 300 baud. The philosophy demonstrated in this implementation is dully applicable to many other microprocessor controlled information processing systems.

Is Serum Zinc Level Associated with Prediabetes and Diabetes?: A Cross-Sectional Study from Bangladesh

PubMed Central

Islam, Md. Rafiqul; Arslan, Iqbal; Attia, John; McEvoy, Mark; McElduff, Patrick; Basher, Ariful; Rahman, Waliur; Peel, Roseanne; Akhter, Ayesha; Akter, Shahnaz; Vashum, Khanrin P.; Milton, Abul Hasnat

2013-01-01

Aims To determine serum zinc level and other relevant biological markers in normal, prediabetic and diabetic individuals and their association with Homeostasis Model Assessment (HOMA) parameters. Methods This cross-sectional study was conducted between March and December 2009. Any patient aged ≥30 years attending the medicine outpatient department of a medical university hospital in Dhaka, Bangladesh and who had a blood glucose level ordered by a physician was eligible to participate. Results A total of 280 participants were analysed. On fasting blood sugar results, 51% were normal, 13% had prediabetes and 36% had diabetes. Mean serum zinc level was lowest in prediabetic compared to normal and diabetic participants (mean differences were approximately 65 ppb/L and 33 ppb/L, respectively). In multiple linear regression, serum zinc level was found to be significantly lower in prediabetes than in those with normoglycemia. Beta cell function was significantly lower in prediabetes than normal participants. Adjusted linear regression for HOMA parameters did not show a statistically significant association between serum zinc level, beta cell function (P = 0.07) and insulin resistance (P = 0.08). Low serum zinc accentuated the increase in insulin resistance seen with increasing BMI. Conclusion Participants with prediabetes have lower zinc levels than controls and zinc is significantly associated with beta cell function and insulin resistance. Further longitudinal population based studies are warranted and controlled trials would be valuable for establishing whether zinc supplementation in prediabetes could be a useful strategy in preventing progression to Type 2 diabetes. PMID:23613929

Evidence for the Concerted Evolution between Short Linear Protein Motifs and Their Flanking Regions

PubMed Central

Chica, Claudia; Diella, Francesca; Gibson, Toby J.

2009-01-01

Background Linear motifs are short modules of protein sequences that play a crucial role in mediating and regulating many protein–protein interactions. The function of linear motifs strongly depends on the context, e.g. functional instances mainly occur inside flexible regions that are accessible for interaction. Sometimes linear motifs appear as isolated islands of conservation in multiple sequence alignments. However, they also occur in larger blocks of sequence conservation, suggesting an active role for the neighbouring amino acids. Results The evolution of regions flanking 116 functional linear motif instances was studied. The conservation of the amino acid sequence and order/disorder tendency of those regions was related to presence/absence of the instance. For the majority of the analysed instances, the pairs of sequences conserving the linear motif were also observed to maintain a similar local structural tendency and/or to have higher local sequence conservation when compared to pairs of sequences where one is missing the linear motif. Furthermore, those instances have a higher chance to co–evolve with the neighbouring residues in comparison to the distant ones. Those findings are supported by examples where the regulation of the linear motif–mediated interaction has been shown to depend on the modifications (e.g. phosphorylation) at neighbouring positions or is thought to benefit from the binding versatility of disordered regions. Conclusion The results suggest that flanking regions are relevant for linear motif–mediated interactions, both at the structural and sequence level. More interestingly, they indicate that the prediction of linear motif instances can be enriched with contextual information by performing a sequence analysis similar to the one presented here. This can facilitate the understanding of the role of these predicted instances in determining the protein function inside the broader context of the cellular network where they arise. PMID:19584925

A distributed system for fast alignment of next-generation sequencing data.

PubMed

Srimani, Jaydeep K; Wu, Po-Yen; Phan, John H; Wang, May D

2010-12-01

We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be prohibitively large, requiring significant computing resources to obtain sequence alignment results. Moreover, as the data and alignment algorithms become more prevalent, it will become necessary to examine the effect of the multitude of alignment parameters on various NGS systems. We validate the distributed software system by (1) computing simple timing results to show the speed-up gained by using multiple computers, (2) optimizing alignment parameters using simulated NGS data, and (3) computing NGS expression levels for a single biological sample using optimal parameters and comparing these expression levels to that of a microarray sample. Results indicate that the distributed alignment system achieves approximately a linear speed-up and correctly distributes sequence data to and gathers alignment results from multiple compute clients.

Bayesian model reduction and empirical Bayes for group (DCM) studies.

PubMed

Friston, Karl J; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E; van Wijk, Bernadette C M; Ziegler, Gabriel; Zeidman, Peter

2016-03-01

This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level - e.g., dynamic causal models - and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Correlation and simple linear regression.

PubMed

Eberly, Lynn E

2007-01-01

This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

Diagnostic value of the plasmatic ADM level for early ectopic pregnancy.

PubMed

Yan, Qi; Lu, Qi; Tao, Yu; Wang, Yu-Dong; Zhao, Wen-Xia

2015-01-01

To analyze the plasmatic ADM level in early pregnancy and to investigate the diagnostic value of ADM in early ectopic pregnancy (EP). 70 patients with EP who had menopause for 5~8 weeks were included as study group, while 155 women with normal intrauterine pregnancy were also included as control group. The correlation between ADM level and menopause weeks was statistically analyzed and ROC curve was used to identify the diagnostic value of ADM. (1) In 155 cases of normal intrauterine pregnancy, the plasmatic ADM level was increased with menopause weeks in linear relationship, and the correlation coefficient (R) was 0.991 (P<0.05). In 70 patients with EP, no significant increase was found with menopause weeks and no linear relationship can be found between ADM level and menopause weeks in EP group. The correlation coefficient (R) was 0.744 (P>0.05). (2) The multiple of median of plasmatic ADM level in EP group of menopause for 8 weeks was obviously lower than the intrauterine control group (P<0.01). (3) ROC curve was used to analyze the cut-off value of ADM level in the diagnosis of EP, and the area under the ROC curve was 0.523 (P>0.05) regardless of menopause weeks, however, the area under the ROC curve was 0.702 (P<0.05) at 8 weeks after menopause with sensitivity of 53.50% and specificity of 85.00%. Different from normal intrauterine pregnancy, plasmatic ADM level in early EP was relatively lower and no significant increase was found with menopause weeks; further studies are still needed for plasmatic ADM level as an indicator in the early diagnosis of EP.

Too much job control? Two studies on curvilinear relations between job control and eldercare workers' well-being.

PubMed

Kubicek, Bettina; Korunka, Christian; Tement, Sara

2014-12-01

Longer life expectancy and changes in family patterns in Western societies have increased the need for professional caregivers to the elderly. A detailed understanding of job resources, especially of job control, may help preserve eldercare workers' work-related well-being. The aim of the present study was to determine optimal levels of job control for eldercare workers' work-related well-being. Cross-sectional (Study 1) and longitudinal (Study 2) data were used to assess the linear and non-linear relations between job control and eldercare workers' work-related well-being. As indicators of well-being, irritation was examined cross-sectionally, whereas burnout and engagement were used in the longitudinal study. In both studies, demographic variables and time pressure were included as controls. In Study 2, results were additionally controlled for baseline levels of the outcome variables. Study participants were recruited from the nursing staff of 10 publicly financed nursing homes for the elderly (Study 1) and from 18 privately and 20 publicly financed nursing homes for the elderly (Study 2). In both studies, eldercare workers (i.e., registered nurses, orderlies, and nursing assistants) were invited to answer paper-pencil questionnaires. In Study 1, 606 persons followed this invitation (response rate: 65%). In Study 2, 591 persons provided data on both measurement points (response rate: 35% of Time 1 participants). The samples of both studies were predominantly female and between 20 and 65 years of age. Hierarchical multiple regressions with linear and quadratic terms were conducted. Curvilinear effects of job control were found in both studies. In Study 1, low as well as high levels of job control were associated with higher levels of irritation compared to medium levels of job control. The longitudinal data from Study 2 supported these results. Eldercare workers with higher and lower levels of job control reported a higher tendency to depersonalize care recipients and a lower tendency to feel dedicated to, absorbed by and vigorous at work than those with medium levels of job control. Higher levels of job control are not necessarily advantageous for work-related well-being of eldercare workers. Copyright © 2014 Elsevier Ltd. All rights reserved.

Scalings of Alfvén-cyclotron and ion Bernstein instabilities on temperature anisotropy of a ring-like velocity distribution in the inner magnetosphere

DOE PAGES

Min, Kyungguk; Liu, Kaijun; Gary, S. Peter

2016-03-18

Here, a ring-like proton velocity distribution with ∂f p(v ⊥)/∂v ⊥>0 and which is sufficiently anisotropic can excite two distinct types of growing modes in the inner magnetosphere: ion Bernstein instabilities with multiple ion cyclotron harmonics and quasi-perpendicular propagation and an Alfvén-cyclotron instability at frequencies below the proton cyclotron frequency and quasi-parallel propagation. Recent particle-in-cell simulations have demonstrated that even if the maximum linear growth rate of the latter instability is smaller than the corresponding growth of the former instability, the saturation levels of the fluctuating magnetic fields can be greater for the Alfvén-cyclotron instability than for the ion Bernsteinmore » instabilities. In this study, linear dispersion theory and two-dimensional particle-in-cell simulations are used to examine scalings of the linear growth rate and saturation level of the two types of growing modes as functions of the temperature anisotropy T ⊥/T || for a general ring-like proton distribution with a fixed ring speed of 2v A, where v A is the Alfvén speed. For the proton distribution parameters chosen, the maximum linear theory growth rate of the Alfvén-cyclotron waves is smaller than that of the fastest-growing Bernstein mode for the wide range of anisotropies (1≤T ⊥/T ||≤7) considered here. Yet the corresponding particle-in-cell simulations yield a higher saturation level of the fluctuating magnetic fields for the Alfvén-cyclotron instability than for the Bernstein modes as long as inline image. Since fast magnetosonic waves with ion Bernstein instability properties observed in the magnetosphere are often not accompanied by electromagnetic ion cyclotron waves, the results of the present study indicate that the ring-like proton distributions responsible for the excitation of these fast magnetosonic waves should not be very anisotropic.« less

On the linear programming bound for linear Lee codes.

PubMed

Astola, Helena; Tabus, Ioan

2016-01-01

Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.

Circulating leptin and adiponectin are associated with insulin resistance in healthy postmenopausal women with hot flashes.

PubMed

Huang, Wan-Yu; Chang, Chia-Chu; Chen, Dar-Ren; Kor, Chew-Teng; Chen, Ting-Yu; Wu, Hung-Ming

2017-01-01

Hot flashes have been postulated to be linked to the development of metabolic disorders. This study aimed to evaluate the relationship between hot flashes, adipocyte-derived hormones, and insulin resistance in healthy, non-obese postmenopausal women. In this cross-sectional study, a total of 151 women aged 45-60 years were stratified into one of three groups according to hot-flash status over the past three months: never experienced hot flashes (Group N), mild-to-moderate hot flashes (Group M), and severe hot flashes (Group S). Variables measured in this study included clinical parameters, hot flash experience, fasting levels of circulating glucose, lipid profiles, plasma insulin, and adipocyte-derived hormones. Multiple linear regression analysis was used to evaluate the associations of hot flashes with adipocyte-derived hormones, and with insulin resistance. The study was performed in a hospital medical center. The mean (standard deviation) of body-mass index was 22.8(2.7) for Group N, 22.6(2.6) for Group M, and 23.5(2.4) for Group S, respectively. Women in Group S displayed statistically significantly higher levels of leptin, fasting glucose, and insulin, and lower levels of adiponectin than those in Groups M and N. Multivariate linear regression analysis revealed that hot-flash severity was significantly associated with higher leptin levels, lower adiponectin levels, and higher leptin-to-adiponectin ratio. Univariate linear regression analysis revealed that hot-flash severity was strongly associated with a higher HOMA-IR index (% difference, 58.03%; 95% confidence interval, 31.00-90.64; p < 0.001). The association between hot flashes and HOMA-IR index was attenuated after adjusting for leptin or adiponectin and was no longer significant after simultaneously adjusting for leptin and adiponectin. The present study provides evidence that hot flashes are associated with insulin resistance in postmenopausal women. It further suggests that hot flash association with insulin resistance is dependent on the combination of leptin and adiponectin variables.

Multiple monolithic fiber solid-phase microextraction based on a polymeric ionic liquid with high-performance liquid chromatography for the determination of steroid sex hormones in water and urine.

PubMed

Liao, Keren; Mei, Meng; Li, Haonan; Huang, Xiaojia; Wu, Cuiqin

2016-02-01

The development of a simple and sensitive analytical approach that combines multiple monolithic fiber solid-phase microextraction with liquid desorption followed by high-performance liquid chromatography with diode array detection is proposed for the determination of trace levels of seven steroid sex hormones (estriol, 17β-estradiol, testosterone, ethinylestradiol, estrone, progesterone and mestranol) in water and urine matrices. To extract the target analytes effectively, multiple monolithic fiber solid-phase microextraction based on a polymeric ionic liquid was used to concentrate hormones. Several key extraction parameters including desorption solvent, extraction and desorption time, pH value and ionic strength in sample matrix were investigated in detail. Under the optimal experimental conditions, the limits of detection were found to be in the range of 0.027-0.12 μg/L. The linear range was 0.10-200 μg/L for 17β-estradiol, 0.25-200 μg/L estriol, ethinylestradiol and estrone, and 0.50-200 μg/L for the other hormones. Satisfactory linearities were achieved for analytes with the correlation coefficients above 0.99. Acceptable method reproducibility was achieved by evaluating the repeatability and intermediate precision with relative standard deviations of both less than 8%. The enrichment factors ranged from 54- to 74-fold. Finally, the proposed method was successfully applied to the analysis of steroid sex hormones in environmental water samples and human urines with spiking recoveries ranged from 75.6 to 116%. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Disposable skin staplers for closure of linear gastrointestinal incisions in dogs.

PubMed

Schwartz, Zeev; Coolman, Bradley R

2018-02-01

To report the clinical features and outcomes of linear gastrointestinal incisions closed with skin staples in dogs. Historical cohort study. 333 client-owned dogs. Medical records from 1 private referral hospital were searched for dogs that underwent gastrointestinal surgery between November 1999 and October 2015. Cases were included if skin staplers were used to close linear gastrointestinal incisions. Information regarding preoperative, surgical, and postoperative factors was collected. Complications were diagnosed in 8 of 245 (3.27%) dogs, including 3 of 245 (1.22%) dogs that died or were euthanized, 3 of 245 (1.22%) dogs with incisional dehiscence, and 2 of 245 (0.81%) dogs with attachment of a linear foreign body to the staples at the intestinal lumen. Dehiscence was noted at the enterotomy sites in 3 dogs at a mean time of 44 hours after surgery (SD ± 6.93). Two dogs presented with another linear foreign body that was attached to the staples in the intestinal lumen at postoperative days 24 and 42. The risk factors associated with incisional dehiscence included multiple gastrointestinal incisions performed in 1 surgery (χ 2 , P < .001) and the presence of a linear foreign body (χ 2 , P = .02253). No associations were detected between dogs' age, sex, weight, surgery time, indication for surgical intervention, surgery location in the gastrointestinal tract, or surgeon experience and incisional dehiscence. Skin staplers provide safe and effective closure of gastrotomies, enterotomies, and colonotomies in dogs. This method is reliable, efficient, and affordable in the hands of veterinary surgeons with varying skill levels. © 2017 The American College of Veterinary Surgeons.

Using Strassen's algorithm to accelerate the solution of linear systems

NASA Technical Reports Server (NTRS)

Bailey, David H.; Lee, King; Simon, Horst D.

1990-01-01

Strassen's algorithm for fast matrix-matrix multiplication has been implemented for matrices of arbitrary shapes on the CRAY-2 and CRAY Y-MP supercomputers. Several techniques have been used to reduce the scratch space requirement for this algorithm while simultaneously preserving a high level of performance. When the resulting Strassen-based matrix multiply routine is combined with some routines from the new LAPACK library, LU decomposition can be performed with rates significantly higher than those achieved by conventional means. We succeeded in factoring a 2048 x 2048 matrix on the CRAY Y-MP at a rate equivalent to 325 MFLOPS.

Prediction of health levels by remote sensing

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

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

SU-E-T-197: Helical Cranial-Spinal Treatments with a Linear Accelerator

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

Anderson, J; Bernard, D; Liao, Y

2014-06-01

Purpose: Craniospinal irradiation (CSI) of systemic disease requires a high level of beam intensity modulation to reduce dose to bone marrow and other critical structures. Current helical delivery machines can take 30 minutes or more of beam-on time to complete these treatments. This pilot study aims to test the feasibility of performing helical treatments with a conventional linear accelerator using longitudinal couch travel during multiple gantry revolutions. Methods: The VMAT optimization package of the Eclipse 10.0 treatment planning system was used to optimize pseudo-helical CSI plans of 5 clinical patient scans. Each gantry revolution was divided into three 120° arcsmore » with each isocenter shifted longitudinally. Treatments requiring more than the maximum 10 arcs used multiple plans with each plan after the first being optimized including the dose of the others (Figure 1). The beam pitch was varied between 0.2 and 0.9 (couch speed 5- 20cm/revolution and field width of 22cm) and dose-volume histograms of critical organs were compared to tomotherapy plans. Results: Viable pseudo-helical plans were achieved using Eclipse. Decreasing the pitch from 0.9 to 0.2 lowered the maximum lens dose by 40%, the mean bone marrow dose by 2.1% and the maximum esophagus dose by 17.5%. (Figure 2). Linac-based helical plans showed dose results comparable to tomotherapy delivery for both target coverage and critical organ sparing, with the D50 of bone marrow and esophagus respectively 12% and 31% lower in the helical linear accelerator plan (Figure 3). Total mean beam-on time for the linear accelerator plan was 8.3 minutes, 54% faster than the tomotherapy average for the same plans. Conclusions: This pilot study has demonstrated the feasibility of planning pseudo-helical treatments for CSI targets using a conventional linac and dynamic couch movement, and supports the ongoing development of true helical optimization and delivery.« less

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Correlations of neutron multiplicity and γ -ray multiplicity with fragment mass and total kinetic energy in spontaneous fission of Cf 252

DOE PAGES

Wang, Taofeng; Li, Guangwu; Zhu, Liping; ...

2016-01-08

The dependence of correlations of neutron multiplicity ν and γ-ray multiplicity M γ in spontaneous fission of 252Cf on fragment mass A* and total kinetic energy (TKE) have been investigated by employing the ratio of M γ/ν and the form of M γ(ν). We show for the first time that M γ and ν have a complex correlation for heavy fragment masses, while there is a positive dependence of Mγ for light fragment masses and for near-symmetric mass splits. The ratio M γ/ν exhibits strong shell effects for neutron magic number N=50 and near doubly magic number shell closure atmore » Z=50 and N=82. The γ-ray multiplicity Mγ has a maximum for TKE=165-170 MeV. Above 170 MeV M γ(TKE) is approximately linear, while it deviates significantly from a linear dependence at lower TKE. The correlation between the average neutron and γ-ray multiplicities can be partly reproduced by model calculations.« less

A longitudinal cross-level model of leader and salesperson influences on sales force technology use and performance.

PubMed

Mathieu, John; Ahearne, Michael; Taylor, Scott R

2007-03-01

The authors examined the influence of the introduction of a new suite of technology tools on the performance of 592 salespersons. They hypothesized that the salespersons' work experience would have a negative effect on their technology self-efficacy, which in turn would relate positively to their use of technology. Sales performance was hypothesized to be positively related to both past performance and the use of new technology tools. Further, the authors hypothesized that leaders' commitment to sales technology would enhance salespersons' technology self-efficacy and usage, and leaders' empowering behaviors would influence salespersons' technology self-efficacy and moderate the individual-level relationships. Hierarchical linear modeling analyses confirmed all of the hypothesized individual-level relationships and most of the cross-level relationships stemming from average leader behaviors. In particular, empowering leadership exhibited multiple cross-level interactions, as anticipated. Results are discussed in terms of the importance of social-psychological factors related to the success of sales force technology interventions. (c) 2007 APA, all rights reserved.

A scalable parallel algorithm for multiple objective linear programs

NASA Technical Reports Server (NTRS)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.

Predicting musically induced emotions from physiological inputs: linear and neural network models.

PubMed

Russo, Frank A; Vempala, Naresh N; Sandstrom, Gillian M

2013-01-01

Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of "felt" emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants-heart rate (HR), respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA) dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a non-linear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The non-linear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the non-linear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.

Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

NASA Astrophysics Data System (ADS)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger-)causes vegetation dynamics in most regions globally. More specifically, water availability is the most dominant vegetation driver, being the dominant vegetation driver in 54% of the vegetated surface. Furthermore, our results show that precipitation and soil moisture have prolonged impacts on vegetation in semiarid regions, with up to 10% of additional explained variance on the vegetation dynamics occurring three months later. Finally, hydro-climatic extremes seem to have a remarkable impact on vegetation, since they also explain up to 10% of additional variance of vegetation in certain regions despite their infrequent occurrence. References [1] Papagiannopoulou, C., Miralles, D. G., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger causality framework to investigate climate-vegetation dynamics, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-266, in review, 2016.

Valid statistical approaches for analyzing sholl data: Mixed effects versus simple linear models.

PubMed

Wilson, Machelle D; Sethi, Sunjay; Lein, Pamela J; Keil, Kimberly P

2017-03-01

The Sholl technique is widely used to quantify dendritic morphology. Data from such studies, which typically sample multiple neurons per animal, are often analyzed using simple linear models. However, simple linear models fail to account for intra-class correlation that occurs with clustered data, which can lead to faulty inferences. Mixed effects models account for intra-class correlation that occurs with clustered data; thus, these models more accurately estimate the standard deviation of the parameter estimate, which produces more accurate p-values. While mixed models are not new, their use in neuroscience has lagged behind their use in other disciplines. A review of the published literature illustrates common mistakes in analyses of Sholl data. Analysis of Sholl data collected from Golgi-stained pyramidal neurons in the hippocampus of male and female mice using both simple linear and mixed effects models demonstrates that the p-values and standard deviations obtained using the simple linear models are biased downwards and lead to erroneous rejection of the null hypothesis in some analyses. The mixed effects approach more accurately models the true variability in the data set, which leads to correct inference. Mixed effects models avoid faulty inference in Sholl analysis of data sampled from multiple neurons per animal by accounting for intra-class correlation. Given the widespread practice in neuroscience of obtaining multiple measurements per subject, there is a critical need to apply mixed effects models more widely. Copyright © 2017 Elsevier B.V. All rights reserved.

Unambiguous discrimination between linearly dependent equidistant states with multiple copies

NASA Astrophysics Data System (ADS)

Zhang, Wen-Hai; Ren, Gang

2018-07-01

Linearly independent quantum states can be unambiguously discriminated, but linearly dependent ones cannot. For linearly dependent quantum states, however, if C copies of the single states are available, then they may form linearly independent states, and can be unambiguously discriminated. We consider unambiguous discrimination among N = D + 1 linearly dependent states given that C copies are available and that the single copies span a D-dimensional space with equal inner products. The maximum unambiguous discrimination probability is derived for all C with equal a priori probabilities. For this classification of the linearly dependent equidistant states, our result shows that if C is even then adding a further copy fails to increase the maximum discrimination probability.

Update on Linear Mode Photon Counting with the HgCdTe Linear Mode Avalanche Photodiode

NASA Technical Reports Server (NTRS)

Beck, Jeffrey D.; Kinch, Mike; Sun, Xiaoli

2014-01-01

The behavior of the gain-voltage characteristic of the mid-wavelength infrared cutoff HgCdTe linear mode avalanche photodiode (e-APD) is discussed both experimentally and theoretically as a function of the width of the multiplication region. Data are shown that demonstrate a strong dependence of the gain at a given bias voltage on the width of the n- gain region. Geometrical and fundamental theoretical models are examined to explain this behavior. The geometrical model takes into account the gain-dependent optical fill factor of the cylindrical APD. The theoretical model is based on the ballistic ionization model being developed for the HgCdTe APD. It is concluded that the fundamental theoretical explanation is the dominant effect. A model is developed that combines both the geometrical and fundamental effects. The model also takes into account the effect of the varying multiplication width in the low bias region of the gain-voltage curve. It is concluded that the lower than expected gain seen in the first 2 × 8 HgCdTe linear mode photon counting APD arrays, and higher excess noise factor, was very likely due to the larger than typical multiplication region length in the photon counting APD pixel design. The implications of these effects on device photon counting performance are discussed.

Multiple-Input Multiple-Output (MIMO) Linear Systems Extreme Inputs/Outputs

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

Smallwood, David O.

2007-01-01

A linear structure is excited at multiple points with a stationary normal random process. The response of the structure is measured at multiple outputs. If the autospectral densities of the inputs are specified, the phase relationships between the inputs are derived that will minimize or maximize the trace of the autospectral density matrix of the outputs. If the autospectral densities of the outputs are specified, the phase relationships between the outputs that will minimize or maximize the trace of the input autospectral density matrix are derived. It is shown that other phase relationships and ordinary coherence less than one willmore » result in a trace intermediate between these extremes. Least favorable response and some classes of critical response are special cases of the development. It is shown that the derivation for stationary random waveforms can also be applied to nonstationary random, transients, and deterministic waveforms.« less

Precision magnetic suspension linear bearing

NASA Technical Reports Server (NTRS)

Trumper, David L.; Queen, Michael A.

1992-01-01

We have shown the design and analyzed the electromechanics of a linear motor suitable for independently controlling two suspension degrees of freedom. This motor, at least on paper, meets the requirements for driving an X-Y stage of 10 Kg mass with about 4 m/sq sec acceleration, with travel of several hundred millimeters in X and Y, and with reasonable power dissipation. A conceptual design for such a stage is presented. The theoretical feasibility of linear and planar bearings using single or multiple magnetic suspension linear motors is demonstrated.

Performance of coagulation tests in patients on therapeutic doses of dabigatran: a cross-sectional pharmacodynamic study based on peak and trough plasma levels.

PubMed

Hawes, E M; Deal, A M; Funk-Adcock, D; Gosselin, R; Jeanneret, C; Cook, A M; Taylor, J M; Whinna, H C; Winkler, A M; Moll, S

2013-08-01

Knowledge of anticoagulation status during dabigatran therapy may be desirable in certain clinical situations. To determine the coagulation tests that are most useful for assessing dabigatran's anticoagulant effect. Peak and trough blood samples from 35 patients taking dabigatran 150 mg twice daily, and one sample each from 30 non-anticoagulated individuals, were collected. Mass spectrometry and various coagulation assays were performed. 'Therapeutic range' was defined as the range of plasma dabigatran concentrations determined by mass spectrometry between the 2.5th and 97.5th percentiles of all values. The therapeutic range was 27-411 ng mL(-1) . The prothrombin time (PT) and activated partial thromboplastin time (APTT), determined with multiple reagents, and activated clotting time (ACT) were insensitive to therapeutic dabigatran: 29%, 18% and 40% of samples had a normal PT, APTT, and ACT, respectively. However, normal PT, ACT and APTT ruled out dabigatran levels above the 75th percentile. The thrombin clotting time (TCT) correlated well and linearly with dabigatran levels below the 50th percentile, but was unmeasurable above it. The dilute thrombin time, ecarin clotting time and ecarin chromogenic assay showed linear correlations with dabigatran levels over a broad range, and identified therapeutic and supratherapeutic levels. The prothrombin time, APTT and ACT are often normal in spite of therapeutic dabigatran plasma levels. The TCT is useful for detecting minimal dabigatran levels. The dilute thrombin time and chromogenic and clotting ecarin assays accurately identify therapeutic and supratherapeutic dabigatran levels. This trial is registered at www.clinicaltrials.gov (#NCT01588327). © 2013 International Society on Thrombosis and Haemostasis.

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

Dilations and the Equation of a Line

ERIC Educational Resources Information Center

Yopp, David A.

2016-01-01

Students engage in proportional reasoning when they use covariance and multiple comparisons. Without rich connections to proportional reasoning, students may develop inadequate understandings of linear relationships and the equations that model them. Teachers can improve students' understanding of linear relationships by focusing on realistic…

Extensions of algebraic image operators: An approach to model-based vision

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morelli, Michael V.

1990-01-01

Researchers extend their previous research on a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets. Addition and multiplication are defined for the set of all grey-level images, which can then be described as polynomials of two variables. Utilizing this new algebraic structure, researchers devised an innovative, efficient edge detection scheme. An accurate method for deriving gradient component information from this edge detector is presented. Based upon this new edge detection system researchers developed a robust method for linear feature extraction by combining the techniques of a Hough transform and a line follower. The major advantage of this feature extractor is its general, object-independent nature. Target attributes, such as line segment lengths, intersections, angles of intersection, and endpoints are derived by the feature extraction algorithm and employed during model matching. The algebraic operators are global operations which are easily reconfigured to operate on any size or shape region. This provides a natural platform from which to pursue dynamic scene analysis. A method for optimizing the linear feature extractor which capitalizes on the spatially reconfiguration nature of the edge detector/gradient component operator is discussed.

Determinants of anti-benzo[a]pyrene diol epoxide-DNA adduct formation in lymphomonocytes of the general population.

PubMed

Pavanello, Sofia; Pulliero, Alessandra; Saia, Bruno Onofrio; Clonfero, Erminio

2006-12-10

We evaluated determinants of anti-benzo[a]pyrenediolepoxide-(B[a]PDE)-DNA adduct formation (adduct induced by the ultimate carcinogenic metabolite of B[a]P) in lymphomonocytes of subjects environmentally exposed to low doses of polycyclic aromatic hydrocarbons (PAHs) (B[a]P). Our study population consisted of 585 Caucasian subjects, all municipal workers living in North-East Italy and recruited during their periodic check-ups after informed consent. PAH (B[a]P) exposure was assessed by questionnaire. Anti-B[a]PDE-DNA levels were measured by HPLC fluorescence analysis. We found that cigarette smoking (smokers (22%) versus non-smokers, p<0.0001), dietary intake of PAH-rich meals (> or =52 (38%) versus <52 times/year, p<0.0001), and outdoor exposure (> or =4 (19%) versus <4h/day; p=0.0115) significantly influenced adduct levels. Indoor exposure significantly increased the frequency of positive subjects (> or =0.5 adducts/10(8) nucleotides; chi(2) for linear trend, p=0.051). In linear multiple regression analysis the major determinants of increased DNA adduct levels (ln values) were smoking (t=6.362, p<0.0001) and diet (t=4.035, p<0.0001). In this statistical analysis, indoor and outdoor exposure like other factors of PAH exposure had no influence. In non-smokers, the influence of diet (p<0.0001) and high indoor exposure (p=0.016) on anti-B[a]PDE-DNA adduct formation became more evident, but not that of outdoor exposure, as was confirmed by linear multiple regression analysis (diet, t=3.997, p<0.0001 and high indoor exposure, t=2.522, p=0.012). This study indicates that anti-B[a]PDE-DNA adducts can be detected in the general population and are modulated by PAH (B[a]P) exposure not only with smoking - information already known from studies with limited number of subjects - but also with dietary habits and high indoor exposure. In non-smokers, these two factors are the principal determinants of DNA adduct formation. The information provided here seems to be important, since DNA adduct formation in surrogate tissue is an index of genotoxic exposure also in target organs (e.g., lung) and their increase may also be predictive of higher risk for PAH-related cancers.

Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

NASA Astrophysics Data System (ADS)

Bevilacqua, R.; Lehmann, T.; Romano, M.

2011-04-01

This work introduces a novel control algorithm for close proximity multiple spacecraft autonomous maneuvers, based on hybrid linear quadratic regulator/artificial potential function (LQR/APF), for applications including autonomous docking, on-orbit assembly and spacecraft servicing. Both theoretical developments and experimental validation of the proposed approach are presented. Fuel consumption is sub-optimized in real-time through re-computation of the LQR at each sample time, while performing collision avoidance through the APF and a high level decisional logic. The underlying LQR/APF controller is integrated with a customized wall-following technique and a decisional logic, overcoming problems such as local minima. The algorithm is experimentally tested on a four spacecraft simulators test bed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School. The metrics to evaluate the control algorithm are: autonomy of the system in making decisions, successful completion of the maneuver, required time, and propellant consumption.

Linear time-varying models can reveal non-linear interactions of biomolecular regulatory networks using multiple time-series data.

PubMed

Kim, Jongrae; Bates, Declan G; Postlethwaite, Ian; Heslop-Harrison, Pat; Cho, Kwang-Hyun

2008-05-15

Inherent non-linearities in biomolecular interactions make the identification of network interactions difficult. One of the principal problems is that all methods based on the use of linear time-invariant models will have fundamental limitations in their capability to infer certain non-linear network interactions. Another difficulty is the multiplicity of possible solutions, since, for a given dataset, there may be many different possible networks which generate the same time-series expression profiles. A novel algorithm for the inference of biomolecular interaction networks from temporal expression data is presented. Linear time-varying models, which can represent a much wider class of time-series data than linear time-invariant models, are employed in the algorithm. From time-series expression profiles, the model parameters are identified by solving a non-linear optimization problem. In order to systematically reduce the set of possible solutions for the optimization problem, a filtering process is performed using a phase-portrait analysis with random numerical perturbations. The proposed approach has the advantages of not requiring the system to be in a stable steady state, of using time-series profiles which have been generated by a single experiment, and of allowing non-linear network interactions to be identified. The ability of the proposed algorithm to correctly infer network interactions is illustrated by its application to three examples: a non-linear model for cAMP oscillations in Dictyostelium discoideum, the cell-cycle data for Saccharomyces cerevisiae and a large-scale non-linear model of a group of synchronized Dictyostelium cells. The software used in this article is available from http://sbie.kaist.ac.kr/software

Role of multiparton interactions on J /ψ production in p +p collisions at LHC energies

NASA Astrophysics Data System (ADS)

Thakur, Dhananjaya; De, Sudipan; Sahoo, Raghunath; Dansana, Soumya

2018-05-01

The production mechanism of quarkonia states in hadronic collisions is still to be understood by the scientific community. In high-multiplicity p +p collisions, underlying event observables are of major interest. The multiparton interactions (MPIs) are underlying event observables, in which several interactions occur at the partonic level in a single p +p event. This leads to dependence of particle production on event multiplicity. If the MPI occurs in a harder scale, there will be a correlation between the yield of quarkonia and total charged-particle multiplicity. The ALICE experiment at the LHC in p +p collisions at √{s }=7 and 13 TeV has observed an approximate linear increase of relative J /ψ yield, (d/NJ /ψ/d y ⟨d NJ /ψ/d y ⟩ ), with relative charged-particle multiplicity density, (d/Nch/d y ⟨d Nch/d y ⟩ ). In our present work, we have performed a comprehensive study of the production of charmonia as a function of charged-particle multiplicity in p +p collisions at LHC energies using the perturbative QCD-inspired multiparton interaction model, pythia8 tune 4C, with and without the color reconnection scheme. A detailed multiplicity and energy-dependent study is performed to understand the effects of MPI on J /ψ production. The ratio of ψ (2 S ) to J /ψ is also studied as a function of charged-particle multiplicity at LHC energies.

Inventory of forest resources (including water) by multi-level sampling. [nine northern Virginia coastal plain counties

NASA Technical Reports Server (NTRS)

Aldrich, R. C.; Dana, R. W.; Roberts, E. H. (Principal Investigator)

1977-01-01

The author has identified the following significant results. A stratified random sample using LANDSAT band 5 and 7 panchromatic prints resulted in estimates of water in counties with sampling errors less than + or - 9% (67% probability level). A forest inventory using a four band LANDSAT color composite resulted in estimates of forest area by counties that were within + or - 6.7% and + or - 3.7% respectively (67% probability level). Estimates of forest area for counties by computer assisted techniques were within + or - 21% of operational forest survey figures and for all counties the difference was only one percent. Correlations of airborne terrain reflectance measurements with LANDSAT radiance verified a linear atmospheric model with an additive (path radiance) term and multiplicative (transmittance) term. Coefficients of determination for 28 of the 32 modeling attempts, not adverseley affected by rain shower occurring between the times of LANDSAT passage and aircraft overflights, exceeded 0.83.

Bayesian Group Bridge for Bi-level Variable Selection.

PubMed

Mallick, Himel; Yi, Nengjun

2017-06-01

A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.

Towards a better understanding of helicopter external noise

NASA Astrophysics Data System (ADS)

Damongeot, A.; Dambra, F.; Masure, B.

The problem of helicopter external noise generation is studied taking into consideration simultaneously the multiple noise sources: rotor rotational-, rotor broadband -, and engine noise. The main data are obtained during flight tests of the rather quiet AS 332 Super Puma. The flight procedures settled by ICAO for noise regulations are used: horizontal flyover at 90 percent of the maximum speed, approach at minimum power velocity, take-off at best rate of climb. Noise source levels are assessed through narrow band analysis of ground microphone recordings, ground measurements of engine noise and theoretical means. With the perceived noise level unit used throughout the study, relative magnitude of noise sources is shown to be different from that obtained with linear noise unit. A parametric study of the influence of some helicopter parameters on external noise has shown that thickness-tapered, chord-tapered, and swept-back blade tips are good means to reduce the overall noise level in flyover and approach.

Dynamic strength of cylindrical fiber-glass shells and basalt plastic shells under multiple explosive loading

NASA Astrophysics Data System (ADS)

Syrunin, M. A.; Fedorenko, A. G.

2006-08-01

We have shown experimentally that, for cylindrical shells made of oriented fiberglass platic and basalt plastic there exists a critical level of deformations, at which a structure sustains a given number of explosions from the inside. The magnitude of critical deformation for cylindrical fiberglass shells depends linearly on the logarithm of the number of loads that cause failure. For a given type of fiberglass, there is a limiting level of explosive action, at which the number of loads that do not lead to failure can be sufficiently large (more than ˜ 102). This level is attained under loads, which are an order of magnitude lower than the limiting loads under a single explosive action. Basalt plastic shells can be repeatedly used even at the loads, which cause deformation by ˜ 30-50% lower than the safe value ˜ 3.3.5% at single loading.

Regression and multivariate models for predicting particulate matter concentration level.

PubMed

Nazif, Amina; Mohammed, Nurul Izma; Malakahmad, Amirhossein; Abualqumboz, Motasem S

2018-01-01

The devastating health effects of particulate matter (PM 10 ) exposure by susceptible populace has made it necessary to evaluate PM 10 pollution. Meteorological parameters and seasonal variation increases PM 10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM 10 concentration levels. The analyses were carried out using daily average PM 10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM 10 concentration levels having coefficient of determination (R 2 ) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

Factors Related to Social Support in Neurological and Mental Disorders

PubMed Central

Kamenov, Kaloyan; Cabello, Maria; Caballero, Francisco Félix; Cieza, Alarcos; Sabariego, Carla; Raggi, Alberto; Anczewska, Marta; Pitkänen, Tuuli; Ayuso-Mateos, Jose Luis

2016-01-01

Despite the huge body of research on social support, literature has been primarily focused on its beneficial role for both physical and mental health. It is still unclear why people with mental and neurological disorders experience low levels of social support. The main objective of this study was to explore what are the strongest factors related to social support and how do they interact with each other in neuropsychiatric disorders. The study used cross-sectional data from 722 persons suffering from dementia, depression, epilepsy, migraine, multiple sclerosis, Parkinson's disease, schizophrenia, stroke, and substance use disorders. Multiple linear regressions showed that disability was the strongest factor for social support. Extraversion and agreeableness were significant personality variables, but when the interaction terms between personality traits and disability were included, disability remained the only significant variable. Moreover, level of disability mediated the relationship between personality (extraversion and agreeableness) and level of social support. Moderation analysis revealed that people that had mental disorders experienced lower levels of support when being highly disabled compared to people with neurological disorders. Unlike previous literature, focused on increasing social support as the origin of improving disability, this study suggested that interventions improving day-to-day functioning or maladaptive personality styles might also have an effect on the way people perceive social support. Future longitudinal research, however, is warranted to explore causality. PMID:26900847

Model, analysis, and evaluation of the effects of analog VLSI arithmetic on linear subspace-based image recognition.

PubMed

Carvajal, Gonzalo; Figueroa, Miguel

2014-07-01

Typical image recognition systems operate in two stages: feature extraction to reduce the dimensionality of the input space, and classification based on the extracted features. Analog Very Large Scale Integration (VLSI) is an attractive technology to achieve compact and low-power implementations of these computationally intensive tasks for portable embedded devices. However, device mismatch limits the resolution of the circuits fabricated with this technology. Traditional layout techniques to reduce the mismatch aim to increase the resolution at the transistor level, without considering the intended application. Relating mismatch parameters to specific effects in the application level would allow designers to apply focalized mismatch compensation techniques according to predefined performance/cost tradeoffs. This paper models, analyzes, and evaluates the effects of mismatched analog arithmetic in both feature extraction and classification circuits. For the feature extraction, we propose analog adaptive linear combiners with on-chip learning for both Least Mean Square (LMS) and Generalized Hebbian Algorithm (GHA). Using mathematical abstractions of analog circuits, we identify mismatch parameters that are naturally compensated during the learning process, and propose cost-effective guidelines to reduce the effect of the rest. For the classification, we derive analog models for the circuits necessary to implement Nearest Neighbor (NN) approach and Radial Basis Function (RBF) networks, and use them to emulate analog classifiers with standard databases of face and hand-writing digits. Formal analysis and experiments show how we can exploit adaptive structures and properties of the input space to compensate the effects of device mismatch at the application level, thus reducing the design overhead of traditional layout techniques. Results are also directly extensible to multiple application domains using linear subspace methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

A chick bioassay approach for determining the bioavailable choline concentration in normal and overheated soybean meal, canola meal and peanut meal.

PubMed

Emmert, J L; Baker, D H

1997-05-01

Our objectives were to use a soy protein isolate (SPI) diet containing 2-amino-2-methyl-1-propanol, an inhibitor of choline biosynthesis, to determine the bioavailable choline content of normal and overheated soybean meal (SBM), canola meal (CM) and peanut meal (PM). In the first four experiments, it was determined that weight gain of chicks fed the basal diet would respond linearly (P < 0.05) to graded levels of crystalline choline and would not respond to betaine, and that when fortified with adequate choline, no weight gain or feed intake response would occur upon addition of 100 g/kg SBM, CM or PM to the basal diet. Furthermore, addition of crystalline amino acids simulating the amino acid composition of 100 g/kg SBM did not alter the utilization of crystalline choline. In Experiment 5, feeding graded doses of choline, SBM, CM or PM resulted in linear (P < 0.05) increases in weight gain. Multiple linear regression analysis indicated bioavailable choline concentrations of 1708, 1545 and 1203 mg/kg for SBM, CM and PM, respectively. In Experiment 6, no differences (P > 0.05) in bioavailable choline concentrations occurred between normal and overheated SBM, CM or PM, and the bioavailable choline concentration of normal SBM, CM and PM was 2002, 1464 and 1320 mg/kg, respectively. Average bioavailable choline levels were 83, 24 and 76% of analytically determined choline levels in SBM, CM and PM, respectively. Canola meal, although three times as rich in total choline as SBM, has less bioavailable choline than SBM. A substantial portion of choline in SBM, CM and PM is unavailable, and overheating does not appear to decrease the bioavailability of choline in these products.

Integrable generalizations of non-linear multiple three-wave interaction models

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

1989-07-01

Integrable generalizations of multiple three-wave interaction models in terms of r-matrix formulation are investigated. The Lax representations, complete sets of first integrals in involution are constructed, the quantization leading to Gaudin's models is discussed.

Characteristics of compound multiplicity in 84Kr36 with various light and heavy targets at 1 GeV per nucleon

NASA Astrophysics Data System (ADS)

Chouhan, N. S.; Singh, M. K.; Singh, V.; Pathak, R.

2013-12-01

Interactions of 84Kr36 having kinetic energy around 1 GeV per nucleon with NIKFI BR-2 nuclear emulsion detector's target reveal some of the important features of compound multiplicity. Present article shows that width of compound multiplicity distributions and value of mean compound multiplicity have linear relationship with mass number of the projectile colliding system.

The optimal hormonal replacement modality selection for multiple organ procurement from brain-dead organ donors

PubMed Central

Mi, Zhibao; Novitzky, Dimitri; Collins, Joseph F; Cooper, David KC

2015-01-01

The management of brain-dead organ donors is complex. The use of inotropic agents and replacement of depleted hormones (hormonal replacement therapy) is crucial for successful multiple organ procurement, yet the optimal hormonal replacement has not been identified, and the statistical adjustment to determine the best selection is not trivial. Traditional pair-wise comparisons between every pair of treatments, and multiple comparisons to all (MCA), are statistically conservative. Hsu’s multiple comparisons with the best (MCB) – adapted from the Dunnett’s multiple comparisons with control (MCC) – has been used for selecting the best treatment based on continuous variables. We selected the best hormonal replacement modality for successful multiple organ procurement using a two-step approach. First, we estimated the predicted margins by constructing generalized linear models (GLM) or generalized linear mixed models (GLMM), and then we applied the multiple comparison methods to identify the best hormonal replacement modality given that the testing of hormonal replacement modalities is independent. Based on 10-year data from the United Network for Organ Sharing (UNOS), among 16 hormonal replacement modalities, and using the 95% simultaneous confidence intervals, we found that the combination of thyroid hormone, a corticosteroid, antidiuretic hormone, and insulin was the best modality for multiple organ procurement for transplantation. PMID:25565890

MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes.

PubMed

Kim, Sungjin; Jinich, Adrián; Aspuru-Guzik, Alán

2017-04-24

We propose a multiple descriptor multiple kernel (MultiDK) method for efficient molecular discovery using machine learning. We show that the MultiDK method improves both the speed and accuracy of molecular property prediction. We apply the method to the discovery of electrolyte molecules for aqueous redox flow batteries. Using multiple-type-as opposed to single-type-descriptors, we obtain more relevant features for machine learning. Following the principle of "wisdom of the crowds", the combination of multiple-type descriptors significantly boosts prediction performance. Moreover, by employing multiple kernels-more than one kernel function for a set of the input descriptors-MultiDK exploits nonlinear relations between molecular structure and properties better than a linear regression approach. The multiple kernels consist of a Tanimoto similarity kernel and a linear kernel for a set of binary descriptors and a set of nonbinary descriptors, respectively. Using MultiDK, we achieve an average performance of r 2 = 0.92 with a test set of molecules for solubility prediction. We also extend MultiDK to predict pH-dependent solubility and apply it to a set of quinone molecules with different ionizable functional groups to assess their performance as flow battery electrolytes.

Associates of an elevated natriuretic peptide level in stable heart failure patients: implications for targeted management.

PubMed

Jan, Aftab; Dawkins, Ian; Murphy, Niamh; Collier, Patrick; Baugh, John; Ledwidge, Mark; McDonald, Kenneth; Watson, Chris J

2013-01-01

Persistently elevated natriuretic peptide (NP) levels in heart failure (HF) patients are associated with impaired prognosis. Recent work suggests that NP-guided therapy can improve outcome, but the mechanisms behind an elevated BNP remain unclear. Among the potential stimuli for NP in clinically stable patients are persistent occult fluid overload, wall stress, inflammation, fibrosis, and ischemia. The purpose of this study was to identify associates of B-type natriuretic peptide (BNP) in a stable HF population. In a prospective observational study of 179 stable HF patients, the association between BNP and markers of collagen metabolism, inflammation, and Doppler-echocardiographic parameters including left ventricular ejection fraction (LVEF), left atrial volume index (LAVI), and E/e prime (E/e') was measured. Univariable associates of elevated BNP were age, LVEF, LAVI, E/e', creatinine, and markers of collagen turnover. In a multiple linear regression model, age, creatinine, and LVEF remained significant associates of BNP. E/e' and markers of collagen turnover had a persistent impact on BNP independent of these covariates. Multiple variables are associated with persistently elevated BNP levels in stable HF patients. Clarification of the relative importance of NP stimuli may help refine NP-guided therapy, potentially improving outcome for this at-risk population.

Periprocedural Management of Non-Vitamin K Oral Anticoagulants in Chronic Kidney Disease: A Review of Existing Heterogeneity and Contemporary Evidence.

PubMed

Gunasekaran, Prasad; Parashara, Deepak K

2015-12-01

Non vitamin-K oral anticoagulants (NOAC) have considerably enhanced anticoagulation practice for non-valvular atrial fibrillation with specific advantages of fixed dosing, non-fluctuant therapeutic levels and obviation of therapeutic level monitoring. NOAC pharmacology is remarkable for considerable renal excretion. Heterogeneity in the precise time cut-offs for discontinuation of NOACs prior to elective surgical or percutaneous procedures arise from the non-linear variations of drug excretion with different levels of creatinine clearances as in chronic kidney disease. Multiple authors have suggested cut-offs leading to ambiguity among practicing clinicians. Recent data pertaining to systemic thromboembolism, stroke and major bleeding derived from randomized controlled clinical trials have simplified the periprocedural management of NOACs. This review focusses on heterogeneity in the management of NOACs in patients with CKD in this peculiar scenario and highlights the contemporary evidence to support a unified approach towards perioperative management of NOACs. Multiple antidotes targeted towards binding of specific NOACs have been developed and are in the testing phase, thereby offering immense potential for rapid and complete reversal of NOAC activity in emergent procedures and major bleeding episodes. Targeted research on thromboembolism, stroke and major bleeding following temporary periprocedural interruption of NOACs using multicentric registries could further expand the clinical utility of these agents.

Early Parallel Activation of Semantics and Phonology in Picture Naming: Evidence from a Multiple Linear Regression MEG Study

PubMed Central

Miozzo, Michele; Pulvermüller, Friedemann; Hauk, Olaf

2015-01-01

The time course of brain activation during word production has become an area of increasingly intense investigation in cognitive neuroscience. The predominant view has been that semantic and phonological processes are activated sequentially, at about 150 and 200–400 ms after picture onset. Although evidence from prior studies has been interpreted as supporting this view, these studies were arguably not ideally suited to detect early brain activation of semantic and phonological processes. We here used a multiple linear regression approach to magnetoencephalography (MEG) analysis of picture naming in order to investigate early effects of variables specifically related to visual, semantic, and phonological processing. This was combined with distributed minimum-norm source estimation and region-of-interest analysis. Brain activation associated with visual image complexity appeared in occipital cortex at about 100 ms after picture presentation onset. At about 150 ms, semantic variables became physiologically manifest in left frontotemporal regions. In the same latency range, we found an effect of phonological variables in the left middle temporal gyrus. Our results demonstrate that multiple linear regression analysis is sensitive to early effects of multiple psycholinguistic variables in picture naming. Crucially, our results suggest that access to phonological information might begin in parallel with semantic processing around 150 ms after picture onset. PMID:25005037

Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics

USGS Publications Warehouse

Lee, L.; Helsel, D.

2005-01-01

Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

Prenatal Exposure to Organophosphate Pesticides and Neurobehavioral Development of Neonates: A Birth Cohort Study in Shenyang, China

PubMed Central

Zhang, Ying; Han, Song; Liang, Duohong; Shi, Xinzhu; Wang, Fengzhi; Liu, Wei; Zhang, Li; Chen, Lixin; Gu, Yingzi; Tian, Ying

2014-01-01

Background A large amount of organophosphate pesticides (OPs) are used in agriculture in China every year, contributing to exposure of OPs through dietary consumption among the general population. However, the level of exposure to OPs in China is still uncertain. Objective To investigate the effect of the exposure to OPs on the neonatal neurodevelopment during pregnancy in Shenyang, China. Methods 249 pregnant women enrolled in the Central Hospital Affiliated to Shenyang Medical College from February 2011 to August 2012. A cohort of the mothers and their neonates participated in the study and information on each subject was obtained by questionnaire. Dialkyl phosphate (DAP) metabolites were detected in the urine of mothers during pregnancy to evaluate the exposure level to OPs. Neonate neurobehavioral developmental levels were assessed according to the standards of the Neonatal Behavioral Neurological Assessment (NBNA). Multiple linear regressions were utilized to analyze the association between pregnancy exposure to OPs and neonatal neurobehavioral development. Results The geometric means (GM) of urinary metabolites for dimethyl phosphate (DMP), dimethyl thiophosphate (DMTP), diethyl phosphate (DEP), and diethyl thiophosphate (DETP) in pregnant women were 18.03, 8.53, 7.14, and 5.64 µg/L, respectively. Results from multiple linear regressions showed that prenatal OP exposure was one of the most important factors affecting NBNA scores. Prenatal total DAP concentrations were inversely associated with scores on the NBNA scales.?Additionally, a 10-fold increase in DAP concentrations was associated with a decrease of 1.78 regarding the Summary NBNA (95% CI, −2.12 to −1.45). And there was an estimated 2.11-point difference in summary NBNA scores between neonates in the highest quintile of prenatal OP exposure and the lowest quintile group. Conclusion The high exposure of pregnant women to OPs in Shenyang, China was the predominant risk factor for neonatal neurobehavioral development. PMID:24551109

Emergency multiple sclerosis hospital admissions attributable to chemical and acoustic pollution: Madrid (Spain), 2001-2009.

PubMed

Carmona, Rocío; Linares, Cristina; Recio, Alberto; Ortiz, Cristina; Díaz, Julio

2018-01-15

Multiple sclerosis (MS) is the most prevalent neurological disease among young adults in Spain. A number of recent studies have linked traffic-related pollution, both chemical and acoustic, to the aetiology and exacerbation of neurodegenerative diseases. To analyse the existence of a significant short-term association between daily emergency MS hospital admissions and chemical and acoustic pollution caused by traffic in Madrid. We conducted a longitudinal ecological time series study, in which the dependent variable was the number of daily emergency MS hospital admissions (ICD-9: 340) registered in Madrid from 1 January 2001 to 31 December 2009. The independent variables were daily mean concentrations (μg/m 3 ) of PM 2.5 , PM 10 , O 3 and NO 2 . Equivalent diurnal (Leqd), nocturnal (Leqn) and daily equivalent noise levels (Leq24) were also considered. In addition, we controlled for linear trends, seasonality and the autoregressive nature of the series itself. Day of the week was also added as a covariate. Significant environmental variables were determined using Poisson GLM models. Relative risk (RR) and attributable risk (AR) values were calculated for increases of 10μg/m 3 in the case of chemical pollutants and 1dB(A) in noise levels. While there was no association between chemical pollutants caused by traffic and MS admissions, such an association was in evidence for Leqd at lag zero. This association is linear without a threshold, with there being a level above 67dB(A) from which this effect is more pronounced. The RRs were as follows: for all Leqd values, 1.21 (95% CI: 1.16, 1.26); and for Leqd >67dB(A), 1.62 (95% CI: 1.24, 2.13). The above results indicate that traffic noise can exacerbate MS symptoms, leading to hospital admissions due to this cause. Copyright © 2017 Elsevier B.V. All rights reserved.

A boost of confidence: The role of the ventromedial prefrontal cortex in memory, decision-making, and schemas.

PubMed

Hebscher, Melissa; Gilboa, Asaf

2016-09-01

The ventromedial prefrontal cortex (vmPFC) has been implicated in a wide array of functions across multiple domains. In this review, we focus on the vmPFC's involvement in mediating strategic aspects of memory retrieval, memory-related schema functions, and decision-making. We suggest that vmPFC generates a confidence signal that informs decisions and memory-guided behaviour. Confidence is central to these seemingly diverse functions: (1) Strategic retrieval: lesions to the vmPFC impair an early, automatic, and intuitive monitoring process ("feeling of rightness"; FOR) often associated with confabulation (spontaneous reporting of erroneous memories). Critically, confabulators typically demonstrate high levels of confidence in their false memories, suggesting that faulty monitoring following vmPFC damage may lead to indiscriminate confidence signals. (2) Memory schemas: the vmPFC is critically involved in instantiating and maintaining contextually relevant schemas, broadly defined as higher level knowledge structures that encapsulate lower level representational elements. The correspondence between memory retrieval cues and these activated schemas leads to FOR monitoring. Stronger, more elaborate schemas produce stronger FOR and influence confidence in the veracity of memory candidates. (3) Finally, we review evidence on the vmPFC's role in decision-making, extending this role to decision-making during memory retrieval. During non-mnemonic and mnemonic decision-making the vmPFC automatically encodes confidence. Confidence signal in the vmPFC is revealed as a non-linear relationship between a first-order monitoring assessment and second-order action or choice. Attempting to integrate the multiple functions of the vmPFC, we propose a posterior-anterior organizational principle for this region. More posterior vmPFC regions are involved in earlier, automatic, subjective, and contextually sensitive functions, while more anterior regions are involved in controlled actions based on these earlier functions. Confidence signals reflect the non-linear relationship between first-order, posterior-mediated and second-order, anterior-mediated processes and are represented along the entire axis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Attitudes toward concordance and self-efficacy in decision making: a cross-sectional study on pharmacist-patient consultations.

PubMed

Ng, Yew Keong; Shah, Noraida Mohamed; Loong, Ly Sia; Pee, Lay Ting; Hidzir, Sarina Anim M; Chong, Wei Wen

2018-01-01

This study investigated patients' and pharmacists' attitudes toward concordance in a pharmacist-patient consultation and how patients' attitudes toward concordance relate to their involvement and self-efficacy in decision making associated with medication use. A cross-sectional study was conducted among patients with chronic diseases and pharmacists from three public hospitals in Malaysia. The Revised United States Leeds Attitudes toward Concordance (RUS-LATCon) was used to measure attitudes toward concordance in both patients and pharmacists. Patients also rated their perceived level of involvement in decision making and completed the Decision Self-Efficacy scale. One-way analysis of variance (ANOVA) and independent t -test were used to determine significant differences between different subgroups on attitudes toward concordance, and multiple linear regression was performed to find the predictors of patients' self-efficacy in decision making. A total of 389 patients and 93 pharmacists participated in the study. Pharmacists and patients scored M=3.92 (SD=0.37) and M=3.84 (SD=0.46) on the RUS-LATCon scale, respectively. Seven items were found to be significantly different between pharmacists and patients on the subscale level. Patients who felt fully involved in decision making (M=3.94, SD=0.462) scored significantly higher on attitudes toward concordance than those who felt partially involved (M=3.82, SD=0.478) and not involved at all (M=3.68, SD=0.471; p <0.001). Patients had an average score of 76.7% (SD=14.73%) on the Decision Self-Efficacy scale. In multiple linear regression analysis, ethnicity, number of medications taken by patients, patients' perceived level of involvement, and attitudes toward concordance are significant predictors of patients' self-efficacy in decision making ( p <0.05). Patients who felt involved in their consultations had more positive attitudes toward concordance and higher confidence in making an informed decision. Further study is recommended on interventions involving pharmacists in supporting patients' involvement in medication-related decision making.

A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway Is Associated With Major Depressive Disorder.

PubMed

Zeng, Yanni; Navarro, Pau; Fernandez-Pujals, Ana M; Hall, Lynsey S; Clarke, Toni-Kim; Thomson, Pippa A; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Wray, Naomi R; Deary, Ian J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M

2017-02-15

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk. We integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested. In GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model. These post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Rayleigh imaging in spectral mammography

NASA Astrophysics Data System (ADS)

Berggren, Karl; Danielsson, Mats; Fredenberg, Erik

2016-03-01

Spectral imaging is the acquisition of multiple images of an object at different energy spectra. In mammography, dual-energy imaging (spectral imaging with two energy levels) has been investigated for several applications, in particular material decomposition, which allows for quantitative analysis of breast composition and quantitative contrast-enhanced imaging. Material decomposition with dual-energy imaging is based on the assumption that there are two dominant photon interaction effects that determine linear attenuation: the photoelectric effect and Compton scattering. This assumption limits the number of basis materials, i.e. the number of materials that are possible to differentiate between, to two. However, Rayleigh scattering may account for more than 10% of the linear attenuation in the mammography energy range. In this work, we show that a modified version of a scanning multi-slit spectral photon-counting mammography system is able to acquire three images at different spectra and can be used for triple-energy imaging. We further show that triple-energy imaging in combination with the efficient scatter rejection of the system enables measurement of Rayleigh scattering, which adds an additional energy dependency to the linear attenuation and enables material decomposition with three basis materials. Three available basis materials have the potential to improve virtually all applications of spectral imaging.

A European multicenter study on the analytical performance of the VERIS HBV assay.

PubMed

Braun, Patrick; Delgado, Rafael; Drago, Monica; Fanti, Diana; Fleury, Hervé; Izopet, Jacques; Lombardi, Alessandra; Mancon, Alessandro; Marcos, Maria Angeles; Sauné, Karine; O Shea, Siobhan; Pérez-Rivilla, Alfredo; Ramble, John; Trimoulet, Pascale; Vila, Jordi; Whittaker, Duncan; Artus, Alain; Rhodes, Daniel

Hepatitis B viral load monitoring is an essential part of managing patients with chronic Hepatits B infection. Beckman Coulter has developed the VERIS HBV Assay for use on the fully automated Beckman Coulter DxN VERIS Molecular Diagnostics System. 1 OBJECTIVES: To evaluate the analytical performance of the VERIS HBV Assay at multiple European virology laboratories. Precision, analytical sensitivity, negative sample performance, linearity and performance with major HBV genotypes/subtypes for the VERIS HBV Assay was evaluated. Precision showed an SD of 0.15 log 10 IU/mL or less for each level tested. Analytical sensitivity determined by probit analysis was between 6.8-8.0 IU/mL. Clinical specificity on 90 unique patient samples was 100.0%. Performance with 754 negative samples demonstrated 100.0% not detected results, and a carryover study showed no cross contamination. Linearity using clinical samples was shown from 1.23-8.23 log 10 IU/mL and the assay detected and showed linearity with major HBV genotypes/subtypes. The VERIS HBV Assay demonstrated comparable analytical performance to other currently marketed assays for HBV DNA monitoring. Copyright © 2017 Elsevier B.V. All rights reserved.

Conceptualizing Matrix Multiplication: A Framework for Student Thinking, an Historical Analysis, and a Modeling Perspective

ERIC Educational Resources Information Center

Larson, Christine

2010-01-01

Little is known about the variety of ways students conceptualize matrix multiplication, yet this is a fundamental part of most introductory linear algebra courses. My dissertation follows a three-paper format, with the three papers exploring conceptualizations of matrix multiplication from a variety of viewpoints. In these papers, I explore (1)…

A multi-level analysis of risk perception, poverty and sexual risk-taking among young people in Cape Town, South Africa.

PubMed

Tenkorang, Eric Y; Maticka-Tyndale, Eleanor; Rajulton, Fernando

2011-03-01

Various studies have underscored the relevance of community-level factors to sexual behavior and HIV/AIDS prevention efforts in Africa. However, there is a paucity of research and theorizing in this area compared to the preponderance of prevention models that focus solely on individual-level factors. Using data from the Cape Area Panel Survey and hierarchical linear models, this study examines the effects of a combination of individual-level factors and community-level poverty on sexual behaviors. Male and female respondents who perceived themselves to be at great risk of HIV infection were less likely to indulge in risky sexual behaviors. For females, race and community-level poverty were confounded such that race mediated the effects of community-level poverty. Results from this study indicate that multiple rationalities affect sexual behaviors in Cape Town, South Africa and that there is a need to consider both the social embeddedness of sexual behaviors and the rational components of decision making when designing HIV/AIDS prevention programs. Copyright © 2010 Elsevier Ltd. All rights reserved.

A clinical study of electrophysiological correlates of behavioural comfort levels in cochlear implantees.

PubMed

Raghunandhan, S; Ravikumar, A; Kameswaran, Mohan; Mandke, Kalyani; Ranjith, R

2014-05-01

Indications for cochlear implantation have expanded today to include very young children and those with syndromes/multiple handicaps. Programming the implant based on behavioural responses may be tedious for audiologists in such cases, wherein matching an effective Measurable Auditory Percept (MAP) and appropriate MAP becomes the key issue in the habilitation program. In 'Difficult to MAP' scenarios, objective measures become paramount to predict optimal current levels to be set in the MAP. We aimed to (a) study the trends in multi-modal electrophysiological tests and behavioural responses sequentially over the first year of implant use; (b) generate normative data from the above; (c) correlate the multi-modal electrophysiological thresholds levels with behavioural comfort levels; and (d) create predictive formulae for deriving optimal comfort levels (if unknown), using linear and multiple regression analysis. This prospective study included 10 profoundly hearing impaired children aged between 2 and 7 years with normal inner ear anatomy and no additional handicaps. They received the Advanced Bionics HiRes 90 K Implant with Harmony Speech processor and used HiRes-P with Fidelity 120 strategy. They underwent, impedance telemetry, neural response imaging, electrically evoked stapedial response telemetry (ESRT), and electrically evoked auditory brainstem response (EABR) tests at 1, 4, 8, and 12 months of implant use, in conjunction with behavioural mapping. Trends in electrophysiological and behavioural responses were analyzed using paired t-test. By Karl Pearson's correlation method, electrode-wise correlations were derived for neural response imaging (NRI) thresholds versus most comfortable level (M-levels) and offset based (apical, mid-array, and basal array) correlations for EABR and ESRT thresholds versus M-levels were calculated over time. These were used to derive predictive formulae by linear and multiple regression analysis. Such statistically predicted M-levels were compared with the behaviourally recorded M-levels among the cohort, using Cronbach's alpha reliability test method for confirming the efficacy of this method. NRI, ESRT, and EABR thresholds showed statistically significant positive correlations with behavioural M-levels, which improved with implant use over time. These correlations were used to derive predicted M-levels using regression analysis. On an average, predicted M-levels were found to be statistically reliable and they were a fair match to the actual behavioural M-levels. When applied in clinical practice, the predicted values were found to be useful for programming members of the study group. However, individuals showed considerable deviations in behavioural M-levels, above and below the electrophysiologically predicted values, due to various factors. While the current method appears helpful as a reference to predict initial maps in 'difficult to Map' subjects, it is recommended that behavioural measures are mandatory to further optimize the maps for these individuals. The study explores the trends, correlations and individual variabilities that occur between electrophysiological tests and behavioural responses, recorded over time among a cohort of cochlear implantees. The statistical method shown may be used as a guideline to predict optimal behavioural levels in difficult situations among future implantees, bearing in mind that optimal M-levels for individuals can vary from predicted values. In 'Difficult to MAP' scenarios, following a protocol of sequential behavioural programming, in conjunction with electrophysiological correlates will provide the best outcomes.

Linear and non-linear contributions to oxygen transport and utilization during moderate random exercise in humans.

PubMed

Beltrame, T; Hughson, R L

2017-05-01

What is the central question of this study? The pulmonary oxygen uptake (pV̇O2) data used to study the muscle aerobic system dynamics during moderate-exercise transitions is classically described as a mono-exponential function controlled by a complex interaction of the oxygen delivery-utilization balance. This elevated complexity complicates the acquisition of relevant information regarding aerobic system dynamics based on pV̇O2 data during a varying exercise stimulus. What is the main finding and its importance? The elevated complexity of pV̇O2 dynamics is a consequence of a multiple-order interaction between muscle oxygen uptake and circulatory distortion. Our findings challenge the use of a first-order function to study the influences of the oxygen delivery-utilization balance over the pV̇O2 dynamics. The assumption of aerobic system linearity implies that the pulmonary oxygen uptake (pV̇O2) dynamics during exercise transitions present a first-order characteristic. The main objective of this study was to test the linearity of the oxygen delivery-utilization balance during random moderate exercise. The cardiac output (Q̇) and deoxygenated haemoglobin concentration ([HHb]) were measured to infer the central and local O 2 availability, respectively. Thirteen healthy men performed two consecutive pseudorandom binary sequence cycling exercises followed by an incremental protocol. The system input and the outputs pV̇O2, [HHb] and Q̇ were submitted to frequency-domain analysis. The linearity of the variables was tested by computing the ability of the response at a specific frequency to predict the response at another frequency. The predictability levels were assessed by the coefficient of determination. In a first-order system, a participant who presents faster dynamics at a specific frequency should also present faster dynamics at any other frequency. All experimentally obtained variables (pV̇O2, [HHb] and Q̇) presented a certainly degree of non-linearity. The local O 2 availability, evaluated by the ratio pV̇O2/[HHb], presented the most irregular behaviour. The overall [HHb] kinetics were faster than pV̇O2 and Q̇ kinetics. In conclusion, the oxygen delivery-utilization balance behaved as a non-linear phenomenon. Therefore, the elevated complexity of the pulmonary oxygen uptake dynamics is governed by a complex multiple-order interaction between the oxygen delivery and utilization systems. © 2017 The Authors. Experimental Physiology © 2017 The Physiological Society.

Persistent Organochlorine Pollutants with Endocrine Activity and Blood Steroid Hormone Levels in Middle-Aged Men

PubMed Central

Emeville, Elise; Giton, Frank; Giusti, Arnaud; Oliva, Alejandro; Fiet, Jean; Thomé, Jean-Pierre; Blanchet, Pascal; Multigner, Luc

2013-01-01

Background Studies relating long-term exposure to persistent organochlorine pollutants (POPs) with endocrine activities (endocrine disrupting chemicals) on circulating levels of steroid hormones have been limited to a small number of hormones and reported conflicting results. Objective We examined the relationship between serum concentrations of dehydroepiandrosterone, dehydroepiandrosterone sulphate, androstenedione, androstenediol, testosterone, free and bioavailable testosterone, dihydrotestosterone, estrone, estrone sulphate, estradiol, sex-hormone binding globulin, follicle-stimulating hormone, and luteinizing hormone as a function of level of exposure to three POPs known to interfere with hormone-regulated processes in different way: dichlorodiphenyl dichloroethene (DDE), polychlorinated biphenyl (PCB) congener 153, and chlordecone. Methods We collected fasting, morning serum samples from 277 healthy, non obese, middle-aged men from the French West Indies. Steroid hormones were determined by gas chromatography-mass spectrometry, except for dehydroepiandrosterone sulphate, which was determined by immunological assay, as were the concentrations of sex-hormone binding globulin, follicle-stimulating hormone and luteinizing hormone. Associations were assessed by multiple linear regression analysis, controlling for confounding factors, in a backward elimination procedure, in multiple bootstrap samples. Results DDE exposure was negatively associated to dihydrotestosterone level and positively associated to luteinizing hormone level. PCB 153 was positively associated to androstenedione and estrone levels. No association was found for chlordecone. Conclusions These results suggested that the endocrine response pattern, estimated by determining blood levels of steroid hormones, varies depending on the POPs studied, possibly reflecting differences in the modes of action generally attributed to these compounds. It remains to be investigated whether this response pattern is predictive of the subsequent occurrence of disease. PMID:23785499

Plasma signaling proteins in persons at genetic risk for Alzheimer disease: influence of APOE genotype.

PubMed

Ringman, John M; Elashoff, David; Geschwind, Daniel H; Welsh, Brian T; Gylys, Karen H; Lee, Cathy; Cummings, Jeffrey L; Cole, Greg M

2012-06-01

To study the effect of familial Alzheimer disease (FAD) mutations and APOE genotype on plasma signaling protein levels. Cross-sectional comparison of plasma levels of 77 proteins measured using multiplex immune assays. A tertiary referral dementia research center. Thirty-three persons from families harboring PSEN1 or APP mutations, aged 19 to 59 years. Protein levels were compared between FAD mutation carriers (MCs) and noncarriers (NCs) and among APOE genotype groups, using multiple linear regression models. Twenty-one participants were FAD MCs and 12 were NCs. Six had the APOE ε2/3, 6 had the ε3/4, and 21 had the ε3/3 genotype. Levels of 17 proteins differed among APOE genotype groups, and there were significant interactions between age and APOE genotype for 12 proteins. Plasma levels of apolipoprotein E and superoxide dismutase 1 were highest in the ε2 carriers, lowest in ε4 carriers, and intermediate in the ε3 carriers. Levels of multiple interleukins showed the opposite pattern and, among the ε4 carriers, demonstrated significant negative correlations with age. Although there were no significant differences between FAD MCs and NCs, there were interactions between mutation status and APOE genotype for 13 proteins. We found different patterns of inflammatory markers in young and middle-aged persons among APOE genotype groups. The APOE ε4 carriers had the lowest levels of apolipoprotein E. Young ε4 carriers have increased inflammatory markers that diminish with age. We demonstrated altered inflammatory responses in young and middle adulthood in ε4 carriers that may relate to AD risk later in life.

Factors affecting variability in the urinary biomarker 1,6-hexamethylene diamine in workers exposed to 1,6-hexamethylene diisocyanate.

PubMed

Gaines, Linda G T; Fent, Kenneth W; Flack, Sheila L; Thomasen, Jennifer M; Whittaker, Stephen G; Nylander-French, Leena A

2011-01-01

Although urinary 1,6-hexamethylene diamine (HDA) is a useful biomarker of exposure to 1,6-hexamethylene diisocyanate (HDI), a large degree of unexplained intra- and inter-individual variability exists between estimated HDI exposure and urine HDA levels. We investigated the effect of individual and workplace factors on urine HDA levels using quantitative dermal and inhalation exposure data derived from a survey of automotive spray painters exposed to HDI. Painters' dermal and breathing-zone HDI-exposures were monitored over an entire workday for up to three separate workdays, spaced approximately one month apart. One urine sample was collected before the start of work with HDI-containing paints, and multiple samples were collected throughout the workday. Using mixed effects multiple linear regression modeling, coverall use resulted in significantly lower HDA levels (p = 0.12), and weekday contributed to significant variability in HDA levels (p = 0.056). We also investigated differences in urine HDA levels stratified by dichotomous and classification covariates using analysis of variance. Use of coveralls (p = 0.05), respirator type worn (p = 0.06), smoker status (p = 0.12), paint-booth type (p = 0.02), and more than one painter at the shop (p = 0.10) were all found to significantly affect urine HDA levels adjusted for creatinine concentration. Coverall use remained significant (p = 0.10), even after adjusting for respirator type. These results indicate that the variation in urine HDA level is mainly due to workplace factors and that appropriate dermal and inhalation protection is required to prevent HDI exposure.

Socio-economic factors associated with infant mortality in Italy: an ecological study.

PubMed

Dallolio, Laura; Di Gregori, Valentina; Lenzi, Jacopo; Franchino, Giuseppe; Calugi, Simona; Domenighetti, Gianfranco; Fantini, Maria Pia

2012-08-16

One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Associations between infant mortality rates in the 20 Italian regions (2006-2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15-64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = -0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = -0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels.

Trends in bullying victimization by gender among U.S. high school students.

PubMed

Pontes, Nancy M H; Ayres, Cynthia G; Lewandowski, Carla; Pontes, Manuel C F

2018-06-01

This research used four consecutive waves of data from the National Youth Risk Behavior Survey (YRBS) conducted by the Centers for Disease Control (CDC), to estimate linear time trends by gender in the prevalence of school and electronic bullying victimization among U.S. high school students (N = 61,042). Dependent variables were student self-reported school bullying victimization and electronic bullying victimization during the previous 12 months. Independent variables used to estimate multiple logistic regression models by gender were survey year, race/ethnicity, and grade level. Results showed the prevalence of school bullying increased significantly among females from 2009 (21.2%) to 2015 (24.8%), linear trend OR = 1.08 [1.04, 1.12]; and decreased significantly among males from 2009 (18.7%) to 2015 (15.8%), linear trend OR = 0.93 [0.89, 0.98]. Prevalence of electronic bullying was unchanged between 2011 to 2015 among both male and female students. Asian race, relative to White race, was associated with significantly lower rates of both school and electronic bullying victimization among females, but not males. The incidence of school and electronic bullying victimization was significantly lower among Black and Hispanic students, but not among multiple-race students, regardless of student gender. Healthy People 2020 set a goal to reduce school bullying victimization 10% by 2019. As of 2015, school bullying victimization decreased significantly among males (16% decrease); it significantly increased among females (17% increase). Future research should explore underlying factors related to these divergent trends, and develop effective strategies to reverse the alarming rise in female school bullying victimization. © 2018 Wiley Periodicals, Inc.

[Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015].

PubMed

Du, Z; Zhang, J; Lu, J X; Lu, L P

2018-05-10

Objective: To analyze the distribution characteristics of bacillary dysentery in Beijing during 2004-2015 and evaluate the influence of meteorological factors on the temporal and spatial distribution of bacillary dysentery. Methods: The incidence data of bacterial dysentery and meteorological data in Beijing from 2004 to 2015 were collected. Descriptive epidemiological analysis was conducted to study the distribution characteristics of bacterial dysentery. Linear correlation analysis and multiple linear regression analysis were carried out to investigate the relationship between the incidence of bacillary dysentery and average precipitation, average air temperature, sunshine hours, average wind speed, average air pressure, gale and rain days. Results: A total of 280 704 cases of bacterial dysentery, including 36 deaths, were reported from 2004 to 2015 in Beijing, the average annual incidence was 130.15/100 000. The annual incidence peak was mainly between May and October, the cases occurred during this period accounted for 80.75 % of the total, and the incidence was highest in age group 0 year. The population distribution showed that most cases were children outside child care settings and students, and the sex ratio of the cases was 1.22∶1. The reported incidence of bacillary dysentery was positively associated with average precipitation, average air temperature and rain days with the correlation coefficients of 0.931, 0.878 and 0.888, but it was negatively associated with the average pressure, the correlation coefficient was -0.820. Multiple linear regression equation for fitting analysis of bacillary dysentery and meteorological factors was Y =3.792+0.162 X (1). Conclusion: The reported incidence of bacillary dysentery in Beijing was much higher than national level. The annual incidence peak was during July to August, and the average precipitation was an important meteorological factor influencing the incidence of bacillary dysentery.

Plasma adiponectin concentrations are associated with dietary glycemic index in Malaysian patients with type 2 diabetes.

PubMed

Loh, Beng-In; Sathyasuryan, Daniel Robert; Mohamed, Hamid Jan Jan

2013-01-01

Adiponectin, an adipocyte-derived hormone has been implicated in the control of blood glucose and chronic inflammation in type 2 diabetes. However, limited studies have evaluated dietary factors on plasma adiponectin levels, especially among type 2 diabetic patients in Malaysia. The aim of this study was to investigate the influence of dietary glycemic index on plasma adiponectin concentrations in patients with type 2 diabetes. A cross-sectional study was conducted in 305 type 2 diabetic patients aged 19-75 years from the Penang General Hospital, Malaysia. Socio-demographic information was collected using a standard questionnaire while dietary details were determined by using a pre-validated semi-quantitative food frequency questionnaire. Anthropometry measurement included weight, height, BMI and waist circumference. Plasma adiponectin concentrations were measured using a commercial ELISA kit. Data were analyzed using multiple linear regression. After multivariate adjustment, dietary glycemic index was inversely associated with plasma adiponectin concentrations (β =-0.272, 95% CI -0.262, - 0.094; p<0.001). It was found that in individuals who consumed 1 unit of foods containing high dietary glycemic index that plasma adiponectin level reduced by 0.3 μg/mL. Thirty two percent (31.9%) of the variation in adiponectin concentrations was explained by age, sex, race, smoking status, BMI, waist circumference, HDL-C, triglycerides, magnesium, fiber and dietary glycemic index according to the multiple linear regression model (R2=0.319). These results support the hypothesis that dietary glycemic index influences plasma adiponectin concentrations in patients with type 2 diabetes. Controlled clinical trials are required to confirm our findings and to elucidate the underlying mechanism.

Anxiety and Depression Are More Prevalent in Patients with Graves' Disease than in Patients with Nodular Goitre

PubMed Central

Bové, Kira Bang; Watt, Torquil; Vogel, Asmus; Hegedüs, Laszlo; Bjoerner, Jakob Bue; Groenvold, Mogens; Bonnema, Steen Joop; Rasmussen, Åse Krogh; Feldt-Rasmussen, Ulla

2014-01-01

Background and Objective Graves' disease has been associated with an increased psychiatric morbidity. It is unclarified whether this relates to Graves' disease or chronic disease per se. The aim of our study was to estimate the prevalence of anxiety and depression symptoms in patients with Graves' disease compared to patients with another chronic thyroid disease, nodular goitre, and to investigate determinants of anxiety and depression in Graves' disease. Methods 157 cross-sectionally sampled patients with Graves' disease, 17 newly diagnosed, 140 treated, and 251 controls with nodular goitre completed the Hospital Anxiety and Depression Scale (HADS). The differences in the mean HADS scores between the groups were analysed using multiple linear regression, controlling for socio-demographic variables. HADS scores were also analysed dichotomized: a score >10 indicating probable ‘anxiety’/probable ‘depression’. Determinants of anxiety and depression symptoms in Graves' disease were examined using multiple linear regression. Results In Graves' disease levels of anxiety (p = 0.008) and depression (p = 0.014) were significantly higher than in controls. The prevalence of depression was 10% in Graves' disease versus 4% in nodular goitre (p = 0.038), anxiety was 18 versus 13% (p = 0.131). Symptoms of anxiety (p = 0.04) and depression (p = 0.01) increased with comorbidity. Anxiety symptoms increased with duration of Graves' disease (p = 0.04). Neither thyroid function nor autoantibody levels were associated with anxiety and depression symptoms. Conclusions Anxiety and depression symptoms were more severe in Graves' disease than in nodular goitre. Symptoms were positively correlated to comorbidity and duration of Graves' disease but neither to thyroid function nor thyroid autoimmunity. PMID:25538899

Use of cardiopulmonary exercise testing to assess early ventilatory changes related to occupational particulate matter

PubMed Central

Chao, T.P.; Sperandio, E.F.; Ostolin, T.L.V.P.; Almeida, V.R.; Romiti, M.; Gagliardi, A.R.T.; Arantes, R.L.; Dourado, V.Z.

2018-01-01

Spirometry has been used as the main strategy for assessing ventilatory changes related to occupational exposure to particulate matter (OEPM). However, in some cases, as one of its limitations, it may not be sensitive enough to show abnormalities before extensive damage, as seen in restrictive lung diseases. Therefore, we hypothesized that cardiopulmonary exercise testing (CPET) may be better than spirometry to detect early ventilatory impairment caused by OEPM. We selected 135 male workers with at least one year of exposure. After collection of self-reported socioeconomic status, educational level, and cardiovascular risk data, participants underwent spirometry, CPET, body composition assessment (bioelectrical impedance), and triaxial accelerometry (for level of physical activity in daily life). CPET was performed using a ramp protocol on a treadmill. Metabolic, cardiovascular, ventilatory, and submaximal relationships were measured. We compared 52 exposed to 83 non-exposed workers. Multiple linear regressions were developed using spirometry and CPET variables as outcomes and OEPM as the main predictor, and adjusted by the main covariates. Our results showed that OEPM was associated with significant reductions in peak minute ventilation, peak tidal volume, and breathing reserve index. Exposed participants presented shallower slope of ΔVT/ΔlnV̇E (breathing pattern), i.e., increased tachypneic breathing pattern. The OEPM explained 7.4% of the ΔVT/ΔlnV̇E variability. We found no significant influence of spirometric indices after multiple linear regressions. We conclude that CPET might be a more sensitive feature of assessing early pulmonary impairment related to OEPM. Our cross-sectional results suggested that CPET is a promising tool for the screening of asymptomatic male workers. PMID:29590255

Periodontal status affects C-reactive protein and lipids in patients with stable heart disease from a tertiary care cardiovascular clinic.

PubMed

Flores, Manuela F; Montenegro, Marlon M; Furtado, Mariana V; Polanczyk, Carisi A; Rösing, Cassiano K; Haas, Alex N

2014-04-01

There are scarce data on the impact of the periodontal condition in the control of biomarkers in patients with cardiovascular disease (CVD). The aim of this study is to assess whether periodontal inflammation and tissue breakdown are associated with C-reactive protein (CRP) and lipids in patients with stable heart disease. This cross-sectional study included 93 patients with stable coronary artery disease (57 males; mean age: 63.5 ± 9.8 years) who were in outpatient care for at least 6 months. After applying a structured questionnaire, periodontal examinations were performed by two calibrated periodontists in six sites per tooth at all teeth. Blood samples were collected from patients on the day of periodontal examination to determine levels of CRP, lipids, and glycated hemoglobin. Multiple linear regression models were fitted to evaluate the association among different periodontal and blood parameters controlling for sex, body mass index, glycated hemoglobin, use of oral hypoglycemic drugs, and smoking. Overall, the sample presented high levels of periodontal inflammation and tissue breakdown. Unadjusted mean concentrations of triglycerides (TGs), very-low-density lipoprotein cholesterol, and glucose were significantly higher in individuals with severe periodontitis. When multiple linear regression models were applied, number of teeth with clinical attachment loss ≥6 mm and presence of severe periodontitis were significantly associated with higher CRP concentrations. Bleeding on probing was significantly associated with TGs, total cholesterol, and non-high-density lipoprotein cholesterol. In this sample of patients with stable CVD, current periodontal inflammation and tissue breakdown are associated with cardiovascular inflammatory markers, such as CRP and lipid profile.

Translating plasma and whole blood fatty acid compositional data into the sum of eicosapentaenoic and docosahexaenoic acid in erythrocytes.

PubMed

Stark, Ken D; Aristizabal Henao, Juan J; Metherel, Adam H; Pilote, Louise

2016-01-01

Specific blood levels of eicosapentaenoic plus docosahexaenoic acid (EPA+DHA, wt% of total) in erythrocytes or "the omega-3 index" have been recommended for cardio-protection, but fatty acids are often measured in different blood fractions. The ability to estimate the % of EPA+DHA in erythrocytes from the fatty acid composition of other blood fractions would enable clinical assessments of omega-3 status when erythrocyte fractions are not available and increase the ability to compare blood levels of omega-3 fatty acids across clinical studies. The fatty acid composition of baseline plasma, erythrocytes and whole blood samples from participants (n=1104) in a prospective, multicenter study examining acute coronary syndrome were determined. The ability to predict the % of EPA+DHA in erythrocytes from other blood fractions were examined using bivariate and multiple linear regression modelling. Concordance analysis was also used to compare the actual erythrocytes EPA+DHA values to values estimated from other blood fractions. EPA+DHA in erythrocytes was significantly (p<0.001) correlated EPA+DHA in plasma (r(2)=0.54) and whole blood (r(2)=0.79). Using multiple linear regression to predict EPA+DHA in erythrocytes resulted in stronger coefficients of determination in both plasma (R(2)=0.70) and whole blood (R(2)=0.84). Concordance analyses indicated agreement between actual and estimated EPA+DHA in erythrocytes, although estimating from plasma fatty acids appears to require translation by categorization rather than by translation as continuous data. This study shows that the fatty acid composition of different blood fractions can be used to estimate erythrocyte EPA+DHA in a population with acute coronary syndrome. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling the effects of AADT on predicting multiple-vehicle crashes at urban and suburban signalized intersections.

PubMed

Chen, Chen; Xie, Yuanchang

2016-06-01

Annual Average Daily Traffic (AADT) is often considered as a main covariate for predicting crash frequencies at urban and suburban intersections. A linear functional form is typically assumed for the Safety Performance Function (SPF) to describe the relationship between the natural logarithm of expected crash frequency and covariates derived from AADTs. Such a linearity assumption has been questioned by many researchers. This study applies Generalized Additive Models (GAMs) and Piecewise Linear Negative Binomial (PLNB) regression models to fit intersection crash data. Various covariates derived from minor-and major-approach AADTs are considered. Three different dependent variables are modeled, which are total multiple-vehicle crashes, rear-end crashes, and angle crashes. The modeling results suggest that a nonlinear functional form may be more appropriate. Also, the results show that it is important to take into consideration the joint safety effects of multiple covariates. Additionally, it is found that the ratio of minor to major-approach AADT has a varying impact on intersection safety and deserves further investigations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

Multiplicity fluctuation analysis of target residues in nucleus-emulsion collisions at a few hundred MeV/nucleon

NASA Astrophysics Data System (ADS)

Zhang, Dong-Hai; Chen, Yan-Ling; Wang, Guo-Rong; Li, Wang-Dong; Wang, Qing; Yao, Ji-Jie; Zhou, Jian-Guo; Zheng, Su-Hua; Xu, Li-Ling; Miao, Hui-Feng; Wang, Peng

2014-07-01

Multiplicity fluctuation of the target evaporated fragments emitted in 290 MeV/u 12C-AgBr, 400 MeV/u 12C-AgBr, 400 MeV/u 20Ne-AgBr and 500 MeV/u 56Fe-AgBr interactions is investigated using the scaled factorial moment method in two-dimensional normal phase space and cumulative variable space, respectively. It is found that in normal phase space the scaled factorial moment (ln) increases linearly with the increase of the divided number of phase space (lnM)for lower q-value and increases linearly with the increase of lnM, and then becomes saturated or decreased for a higher q-value. In cumulative variable space ln decreases linearly with increase of lnM. This indicates that no evidence of non-statistical multiplicity fluctuation is observed in our data sets. So, any fluctuation indicated in the results of normal variable space analysis is totally caused by the non-uniformity of the single-particle density distribution.

Extending the eigCG algorithm to nonsymmetric Lanczos for linear systems with multiple right-hand sides

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

Abdel-Rehim, A M; Stathopoulos, Andreas; Orginos, Kostas

2014-08-01

The technique that was used to build the EigCG algorithm for sparse symmetric linear systems is extended to the nonsymmetric case using the BiCG algorithm. We show that, similarly to the symmetric case, we can build an algorithm that is capable of computing a few smallest magnitude eigenvalues and their corresponding left and right eigenvectors of a nonsymmetric matrix using only a small window of the BiCG residuals while simultaneously solving a linear system with that matrix. For a system with multiple right-hand sides, we give an algorithm that computes incrementally more eigenvalues while solving the first few systems andmore » then uses the computed eigenvectors to deflate BiCGStab for the remaining systems. Our experiments on various test problems, including Lattice QCD, show the remarkable ability of EigBiCG to compute spectral approximations with accuracy comparable to that of the unrestarted, nonsymmetric Lanczos. Furthermore, our incremental EigBiCG followed by appropriately restarted and deflated BiCGStab provides a competitive method for systems with multiple right-hand sides.« less

An enhanced export coefficient based optimization model for supporting agricultural nonpoint source pollution mitigation under uncertainty.

PubMed

Rong, Qiangqiang; Cai, Yanpeng; Chen, Bing; Yue, Wencong; Yin, Xin'an; Tan, Qian

2017-02-15

In this research, an export coefficient based dual inexact two-stage stochastic credibility constrained programming (ECDITSCCP) model was developed through integrating an improved export coefficient model (ECM), interval linear programming (ILP), fuzzy credibility constrained programming (FCCP) and a fuzzy expected value equation within a general two stage programming (TSP) framework. The proposed ECDITSCCP model can effectively address multiple uncertainties expressed as random variables, fuzzy numbers, pure and dual intervals. Also, the model can provide a direct linkage between pre-regulated management policies and the associated economic implications. Moreover, the solutions under multiple credibility levels can be obtained for providing potential decision alternatives for decision makers. The proposed model was then applied to identify optimal land use structures for agricultural NPS pollution mitigation in a representative upstream subcatchment of the Miyun Reservoir watershed in north China. Optimal solutions of the model were successfully obtained, indicating desired land use patterns and nutrient discharge schemes to get a maximum agricultural system benefits under a limited discharge permit. Also, numerous results under multiple credibility levels could provide policy makers with several options, which could help get an appropriate balance between system benefits and pollution mitigation. The developed ECDITSCCP model can be effectively applied to addressing the uncertain information in agricultural systems and shows great applicability to the land use adjustment for agricultural NPS pollution mitigation. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of Regression Methods to Compute Atmospheric Pressure and Earth Tidal Coefficients in Water Level Associated with Wenchuan Earthquake of 12 May 2008

NASA Astrophysics Data System (ADS)

He, Anhua; Singh, Ramesh P.; Sun, Zhaohua; Ye, Qing; Zhao, Gang

2016-07-01

The earth tide, atmospheric pressure, precipitation and earthquake fluctuations, especially earthquake greatly impacts water well levels, thus anomalous co-seismic changes in ground water levels have been observed. In this paper, we have used four different models, simple linear regression (SLR), multiple linear regression (MLR), principal component analysis (PCA) and partial least squares (PLS) to compute the atmospheric pressure and earth tidal effects on water level. Furthermore, we have used the Akaike information criterion (AIC) to study the performance of various models. Based on the lowest AIC and sum of squares for error values, the best estimate of the effects of atmospheric pressure and earth tide on water level is found using the MLR model. However, MLR model does not provide multicollinearity between inputs, as a result the atmospheric pressure and earth tidal response coefficients fail to reflect the mechanisms associated with the groundwater level fluctuations. On the premise of solving serious multicollinearity of inputs, PLS model shows the minimum AIC value. The atmospheric pressure and earth tidal response coefficients show close response with the observation using PLS model. The atmospheric pressure and the earth tidal response coefficients are found to be sensitive to the stress-strain state using the observed data for the period 1 April-8 June 2008 of Chuan 03# well. The transient enhancement of porosity of rock mass around Chuan 03# well associated with the Wenchuan earthquake (Mw = 7.9 of 12 May 2008) that has taken its original pre-seismic level after 13 days indicates that the co-seismic sharp rise of water well could be induced by static stress change, rather than development of new fractures.

An Investigation of the Fit of Linear Regression Models to Data from an SAT[R] Validity Study. Research Report 2011-3

ERIC Educational Resources Information Center

Kobrin, Jennifer L.; Sinharay, Sandip; Haberman, Shelby J.; Chajewski, Michael

2011-01-01

This study examined the adequacy of a multiple linear regression model for predicting first-year college grade point average (FYGPA) using SAT[R] scores and high school grade point average (HSGPA). A variety of techniques, both graphical and statistical, were used to examine if it is possible to improve on the linear regression model. The results…

Preliminary development and validation of an Australian community participation questionnaire: types of participation and associations with distress in a coastal community.

PubMed

Berry, Helen Louise; Rodgers, Bryan; Dear, Keith B G

2007-04-01

Participating in the social and civic life of communities is protectively associated with the onset and course of physical and mental disorders, and is considered important in achieving health promotion goals. Despite its importance in health research, there is no systematically developed measure of community participation. Our aim was to undertake the preliminary development of a community participation questionnaire, including validating it against an external reference, general psychological distress. Participants were 963 randomly selected community members, aged 19-97, from coastal New South Wales, Australia, who completed an anonymous postal survey. There were 14 types of community participation, most of which were characterised by personal involvement, initiative and effort. Frequency of participation varied across types and between women and men. Based on multiple linear regression analyses, controlling for socio-demographic factors, nine types of participation were independently and significantly associated with general psychological distress. Unexpectedly, for two of these, "expressing opinions publicly" and "political protest", higher levels of participation were associated with higher levels of distress. The other seven were: contact with immediate household, extended family, friends, and neighbours; participating in organised community activities; taking an active interest in current affairs; and religious observance. We called these the "Big 7". Higher levels of participation in the Big 7 were associated with lower levels of distress. Participating in an increasing number of the Big 7 types of participation was strongly associated in linear fashion with decreasing distress.

[Factors influencing glucose metabolism in young obese subjects with obstructive sleep apnea hypopnea syndrome].

PubMed

Gu, C J; Li, Q Y; Li, M; Zhou, J; Du, J; Yi, H H; Feng, J; Zhou, L N; Wang, Q

2016-05-17

To explore the factors influencing glucose metabolism in young obese subjects with obstructive sleep apnea hypopnea syndrome (OSAHS). A total of 106 young obese subjects[18-44 years old, body mass index (BMI) ≥30 kg/m(2)]were enrolled and divided into two groups based on full-night polysomnography (PSG), OSAHS group[apnea hypopnea index (AHI) ≥5 events/h]and non-OSAHS group (AHI<5 events/h). Oral glucose tolerance-insulin releasing test (OGTT-IRT) was performed and serum glycosylated hemoglobin A1 (HbA1c) levels were measured after an overnight fast. Homeostasis model assessment-IR (HOMA-IR), Matsuda insulin sensitivity index (MI), homeostasis model assessment-β (HOMA-β), the early phase insulinogenic index (ΔI(30)/ΔG(30)), total area under the curve of insulin in 180 minutes (AUC-I180) and oral disposition index (DIo) were calculated to evaluate insulin resistance and pancreatic β cell function. Stepwise multiple linear regressions were conducted to determine the independent linear correlation of glucose measurements with PSG parameters. Prevalence of diabetes was higher in OSAHS than in non-OSAHS group (22.0% vs 4.3%, P=0.009). OGTT 0, 30, 60 min glucose and HbA1c levels were higher in OSAHS group than those in non-OASHS group (all P<0.05). DIo were lower in OSAHS group than those in non-OASHS group (P=0.024), HOMA-IR, MI, HOMA-β, ΔI(30)/ΔG(30), and AUC-I(180) were similar between two groups (all P>0.05). In stepwise multiple linear regressions, OGTT 0, 30 and 60 min glucose were positively correlated with oxygen desaturation index (ODI) (β=0.243, 0.273 and 0.371 respectively, all P<0.05). HOMA-β was negatively correlated with AHI (β=-0.243, P=0.011). DIo was negatively correlated with ODI (β=-0.234, P=0.031). OSAHS worsens glucose metabolism and compensatory pancreatic β-cell function in young obese subjects, which could probably be attributed to sleep apnea related oxygen desaturation during sleep.

Abdominal girth and vertebral column length can adjust spinal anesthesia for lower limb surgery, a prospective, observational study.

PubMed

Zhou, Qing-he; Zhu, Bo; Wei, Chang-na; Yan, Min

2016-03-24

Studies have shown that abdominal girth and vertebral column length have high predictive value for spinal spread after administering a dose of plain bupivacaine. we designed a study to identify the specific correlations between abdominal girth, vertebral column length and a 0.5% dosage of plain bupivacaine, which should provide a minimum upper block level (T12) and a suitable upper block level (T10) for lower limb surgeries. A suitable dose of 0.5% plain bupivacaine was administered intrathecally between the L3 and L4 vertebrae for lower limb surgeries. If the upper cephalad spread of the patient by loss of pinprick discrimination was T12 or T10, the patient was enrolled in this study. Five patient variables and intrathecal plain bupivacaine dose were recorded. Linear regression and multiple regression analyses were performed. Totals of 111 patients and 121 patients who lost pinprick discrimination at T12 and T10, respectively, were analyzed in this study. Linear regression analysis showed that only abdominal girth and plain bupivacaine dose were strongly correlated (r =-0.827 for T12, r = -0.806 for T10; both p < 0.0001). Multiple linear regression analysis showed that both abdominal girth and vertebral column length were the key determinants of plain bupivacaine dose (both p < 0.0001). R(2) was 0.874 and 0.860 for the loss of pinprick discrimination at T12 and T10, respectively. Our data indicated that vertebral column length and abdominal girth were strongly correlated with the dosage of intrathecal plain bupivacaine for the loss of pinprick discrimination at T12 and T10. The two regression equations were YT12 = 3.547 + 0.045X1-0.044X2 and YT10 = 3.848 + 0.047X1- 0.046X2 (Y, 0.5% plain bupivacaine volume; X1, vertebral column length;and X 2, abdominal girth), which can accurately predict the minimum and suitable intrathecal bupivacaine dose for lower limb surgery to a great extent, separately.

Noise limitations in optical linear algebra processors.

PubMed

Batsell, S G; Jong, T L; Walkup, J F; Krile, T F

1990-05-10

A general statistical noise model is presented for optical linear algebra processors. A statistical analysis which includes device noise, the multiplication process, and the addition operation is undertaken. We focus on those processes which are architecturally independent. Finally, experimental results which verify the analytical predictions are also presented.

Precision pharmacology for Alzheimer's disease.

PubMed

Hampel, Harald; Vergallo, Andrea; Aguilar, Lisi Flores; Benda, Norbert; Broich, Karl; Cuello, A Claudio; Cummings, Jeffrey; Dubois, Bruno; Federoff, Howard J; Fiandaca, Massimo; Genthon, Remy; Haberkamp, Marion; Karran, Eric; Mapstone, Mark; Perry, George; Schneider, Lon S; Welikovitch, Lindsay A; Woodcock, Janet; Baldacci, Filippo; Lista, Simone

2018-04-01

The complex multifactorial nature of polygenic Alzheimer's disease (AD) presents significant challenges for drug development. AD pathophysiology is progressing in a non-linear dynamic fashion across multiple systems levels - from molecules to organ systems - and through adaptation, to compensation, and decompensation to systems failure. Adaptation and compensation maintain homeostasis: a dynamic equilibrium resulting from the dynamic non-linear interaction between genome, epigenome, and environment. An individual vulnerability to stressors exists on the basis of individual triggers, drivers, and thresholds accounting for the initiation and failure of adaptive and compensatory responses. Consequently, the distinct pattern of AD pathophysiology in space and time must be investigated on the basis of the individual biological makeup. This requires the implementation of systems biology and neurophysiology to facilitate Precision Medicine (PM) and Precision Pharmacology (PP). The regulation of several processes at multiple levels of complexity from gene expression to cellular cycle to tissue repair and system-wide network activation has different time delays (temporal scale) according to the affected systems (spatial scale). The initial failure might originate and occur at every level potentially affecting the whole dynamic interrelated systems within an organism. Unraveling the spatial and temporal dynamics of non-linear pathophysiological mechanisms across the continuum of hierarchical self-organized systems levels and from systems homeostasis to systems failure is key to understand AD. Measuring and, possibly, controlling space- and time-scaled adaptive and compensatory responses occurring during AD will represent a crucial step to achieve the capacity to substantially modify the disease course and progression at the best suitable timepoints, thus counteracting disrupting critical pathophysiological inputs. This approach will provide the conceptual basis for effective disease-modifying pathway-based targeted therapies. PP is based on an exploratory and integrative strategy to complex diseases such as brain proteinopathies including AD, aimed at identifying simultaneous aberrant molecular pathways and predicting their temporal impact on the systems levels. The depiction of pathway-based molecular signatures of complex diseases contributes to the accurate and mechanistic stratification of distinct subcohorts of individuals at the earliest compensatory stage when treatment intervention may reverse, stop, or delay the disease. In addition, individualized drug selection may optimize treatment safety by decreasing risk and amplitude of side effects and adverse reactions. From a methodological point of view, comprehensive "omics"-based biomarkers will guide the exploration of spatio-temporal systems-wide morpho-functional shifts along the continuum of AD pathophysiology, from adaptation to irreversible failure. The Alzheimer Precision Medicine Initiative (APMI) and the APMI cohort program (APMI-CP) have commenced to facilitate a paradigm shift towards effective drug discovery and development in AD. Copyright © 2018 Elsevier Ltd. All rights reserved.

Vector Adaptive/Predictive Encoding Of Speech

NASA Technical Reports Server (NTRS)

Chen, Juin-Hwey; Gersho, Allen

1989-01-01

Vector adaptive/predictive technique for digital encoding of speech signals yields decoded speech of very good quality after transmission at coding rate of 9.6 kb/s and of reasonably good quality at 4.8 kb/s. Requires 3 to 4 million multiplications and additions per second. Combines advantages of adaptive/predictive coding, and code-excited linear prediction, yielding speech of high quality but requires 600 million multiplications and additions per second at encoding rate of 4.8 kb/s. Vector adaptive/predictive coding technique bridges gaps in performance and complexity between adaptive/predictive coding and code-excited linear prediction.

FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2011-03-01

We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

Estimation of perceptible water vapor of atmosphere using artificial neural network, support vector machine and multiple linear regression algorithm and their comparative study

NASA Astrophysics Data System (ADS)

Shastri, Niket; Pathak, Kamlesh

2018-05-01

The water vapor content in atmosphere plays very important role in climate. In this paper the application of GPS signal in meteorology is discussed, which is useful technique that is used to estimate the perceptible water vapor of atmosphere. In this paper various algorithms like artificial neural network, support vector machine and multiple linear regression are use to predict perceptible water vapor. The comparative studies in terms of root mean square error and mean absolute errors are also carried out for all the algorithms.

Multiple Cylinder Free-Piston Stirling Machinery

NASA Astrophysics Data System (ADS)

Berchowitz, David M.; Kwon, Yong-Rak

In order to improve the specific power of piston-cylinder type machinery, there is a point in capacity or power where an advantage accrues with increasing number of piston-cylinder assemblies. In the case of Stirling machinery where primary energy is transferred across the casing wall of the machine, this consideration is even more important. This is due primarily to the difference in scaling of basic power and the required heat transfer. Heat transfer is found to be progressively limited as the size of the machine increases. Multiple cylinder machines tend to preserve the surface area to volume ratio at more favorable levels. In addition, the spring effect of the working gas in the so-called alpha configuration is often sufficient to provide a high frequency resonance point that improves the specific power. There are a number of possible multiple cylinder configurations. The simplest is an opposed pair of piston-displacer machines (beta configuration). A three-cylinder machine requires stepped pistons to obtain proper volume phase relationships. Four to six cylinder configurations are also possible. A small demonstrator inline four cylinder alpha machine has been built to demonstrate both cooling operation and power generation. Data from this machine verifies theoretical expectations and is used to extrapolate the performance of future machines. Vibration levels are discussed and it is argued that some multiple cylinder machines have no linear component to the casing vibration but may have a nutating couple. Example applications are discussed ranging from general purpose coolers, computer cooling, exhaust heat power extraction and some high power engines.

Working memory span in mild cognitive impairment. Influence of processing speed and cognitive reserve.

PubMed

Facal, David; Juncos-Rabadán, Onésimo; Pereiro, Arturo X; Lojo-Seoane, Cristina

2014-04-01

Mild cognitive impairment (MCI) often includes episodic memory impairment, but can also involve other types of cognitive decline. Although previous studies have shown poorer performance of MCI patients in working memory (WM) span tasks, different MCI subgroups were not studied. In the present exploratory study, 145 participants underwent extensive cognitive evaluation, which included three different WM span tasks, and were classified into the following groups: multiple-domain amnestic MCI (mda-MCI), single-domain amnestic MCI (sda-MCI), and controls. General linear model was conducted by considering the WM span tasks as the within-subject factor; the group (mda-MCI, sda-MCI, and controls) as the inter-subject factor; and processing speed, vocabulary and age as covariates. Multiple linear regression models were also used to test the influence of processing speed, vocabulary, and other cognitive reserve (CR) proxies. Results indicate different levels of impairment of WM, with more severe impairment in mda-MCI patients. The differences were still present when processing resources and CR were controlled. Between-group differences can be understood as a manifestation of the greater severity and widespread memory impairment in mda-MCI patients and may contribute to a better understanding of continuum from normal controls to mda-MCI patients. Processing speed and CR have a limited influence on WM scores, reducing but not removing differences between groups.

Modeling daily soil temperature over diverse climate conditions in Iran—a comparison of multiple linear regression and support vector regression techniques

NASA Astrophysics Data System (ADS)

Delbari, Masoomeh; Sharifazari, Salman; Mohammadi, Ehsan

2018-02-01

The knowledge of soil temperature at different depths is important for agricultural industry and for understanding climate change. The aim of this study is to evaluate the performance of a support vector regression (SVR)-based model in estimating daily soil temperature at 10, 30 and 100 cm depth at different climate conditions over Iran. The obtained results were compared to those obtained from a more classical multiple linear regression (MLR) model. The correlation sensitivity for the input combinations and periodicity effect were also investigated. Climatic data used as inputs to the models were minimum and maximum air temperature, solar radiation, relative humidity, dew point, and the atmospheric pressure (reduced to see level), collected from five synoptic stations Kerman, Ahvaz, Tabriz, Saghez, and Rasht located respectively in the hyper-arid, arid, semi-arid, Mediterranean, and hyper-humid climate conditions. According to the results, the performance of both MLR and SVR models was quite well at surface layer, i.e., 10-cm depth. However, SVR performed better than MLR in estimating soil temperature at deeper layers especially 100 cm depth. Moreover, both models performed better in humid climate condition than arid and hyper-arid areas. Further, adding a periodicity component into the modeling process considerably improved the models' performance especially in the case of SVR.

Psychosocial issues on-orbit: results from two space station programs

NASA Astrophysics Data System (ADS)

Kanas, N. A.; Salnitskiy, V. P.; Ritsher, J. B.; Gushin, V. I.; Weiss, D. S.; Saylor, S. A.; Marmar, C. R.

PURPOSE Psychosocial issues affecting people working in isolated and confined environments such as spacecraft can jeopardize mental health and mission safety Our team has completed two large NASA-funded studies involving missions to the Mir and International Space Stations where crewmembers were on-orbit for four to seven months Combining these two datasets allows us to generalize across these two settings and maximize statistical power in testing our hypotheses This paper presents results from three sets of hypotheses concerning possible changes in mood and social climate over time displacement of negative emotions to outside monitoring personnel and the task and support roles of the leader METHODS The combined sample of 216 participants included 13 American astronauts 17 Russian cosmonauts and 150 U S and 36 Russian mission control personnel Subjects completed a weekly questionnaire that included items from the Profile of Mood States the Group Environment Scale and the Work Environment Scale producing 20 subscale scores The analytic strategy included piecewise linear regression and general linear modeling and it accounted for the effects of multiple observations per person and multiple analyses RESULTS There was little evidence to suggest that universal changes in levels of mood and group climate occurred among astronauts and cosmonauts over time Although a few individuals experienced decrements in the second half of the mission the majority did not However there was evidence that subjects displaced negative emotions to outside

Analysis of methods to estimate spring flows in a karst aquifer

USGS Publications Warehouse

Sepulveda, N.

2009-01-01

Hydraulically and statistically based methods were analyzed to identify the most reliable method to predict spring flows in a karst aquifer. Measured water levels at nearby observation wells, measured spring pool altitudes, and the distance between observation wells and the spring pool were the parameters used to match measured spring flows. Measured spring flows at six Upper Floridan aquifer springs in central Florida were used to assess the reliability of these methods to predict spring flows. Hydraulically based methods involved the application of the Theis, Hantush-Jacob, and Darcy-Weisbach equations, whereas the statistically based methods were the multiple linear regressions and the technology of artificial neural networks (ANNs). Root mean square errors between measured and predicted spring flows using the Darcy-Weisbach method ranged between 5% and 15% of the measured flows, lower than the 7% to 27% range for the Theis or Hantush-Jacob methods. Flows at all springs were estimated to be turbulent based on the Reynolds number derived from the Darcy-Weisbach equation for conduit flow. The multiple linear regression and the Darcy-Weisbach methods had similar spring flow prediction capabilities. The ANNs provided the lowest residuals between measured and predicted spring flows, ranging from 1.6% to 5.3% of the measured flows. The model prediction efficiency criteria also indicated that the ANNs were the most accurate method predicting spring flows in a karst aquifer. ?? 2008 National Ground Water Association.

Analysis of methods to estimate spring flows in a karst aquifer.

PubMed

Sepúlveda, Nicasio

2009-01-01

Hydraulically and statistically based methods were analyzed to identify the most reliable method to predict spring flows in a karst aquifer. Measured water levels at nearby observation wells, measured spring pool altitudes, and the distance between observation wells and the spring pool were the parameters used to match measured spring flows. Measured spring flows at six Upper Floridan aquifer springs in central Florida were used to assess the reliability of these methods to predict spring flows. Hydraulically based methods involved the application of the Theis, Hantush-Jacob, and Darcy-Weisbach equations, whereas the statistically based methods were the multiple linear regressions and the technology of artificial neural networks (ANNs). Root mean square errors between measured and predicted spring flows using the Darcy-Weisbach method ranged between 5% and 15% of the measured flows, lower than the 7% to 27% range for the Theis or Hantush-Jacob methods. Flows at all springs were estimated to be turbulent based on the Reynolds number derived from the Darcy-Weisbach equation for conduit flow. The multiple linear regression and the Darcy-Weisbach methods had similar spring flow prediction capabilities. The ANNs provided the lowest residuals between measured and predicted spring flows, ranging from 1.6% to 5.3% of the measured flows. The model prediction efficiency criteria also indicated that the ANNs were the most accurate method predicting spring flows in a karst aquifer.

Hemoglobin levels and prevalence of anemia in pregnant women assisted in primary health care services, before and after fortification of flour.

PubMed

Araújo, Claudia Regina Marchiori Antunes; Uchimura, Taqueco Teruya; Fujimori, Elizabeth; Nishida, Fernanda Shizue; Veloso, Giovanna Batista Leite; Szarfarc, Sophia Cornblutz

2013-06-01

We evaluated hemoglobin-Hb levels and prevalence of anemia in pregnant women before and after fortification of flour. It was developed a study to evaluate intervention, of the type before and after, with independent population samples. Study was conducted in primary health care services in Maringá, PR. We assessed 366 and 419 medical records, Before and After implementation of fortification. Pregnant women with Hb < 11g/dL were considered anemic. Data were submitted to multiple linear regression analysis. There was low prevalence of anemia affecting 12.3% and 9.4% pregnant women Before and After fortification (p > 0.05), but the Group After the fortification had higher Hb levels (p < 0.05). Hb levels associated with Group, gestational age, previous pregnancy number, employment and marital status (p < 0.05). Although the fortification of flour may have had role in increasing the mean hemoglobin, we need consider the contribution of other variables not investigated.

Nondeducibility-Based Analysis of Cyber-Physical Systems

NASA Astrophysics Data System (ADS)

Gamage, Thoshitha; McMillin, Bruce

Controlling information flow in a cyber-physical system (CPS) is challenging because cyber domain decisions and actions manifest themselves as visible changes in the physical domain. This paper presents a nondeducibility-based observability analysis for CPSs. In many CPSs, the capacity of a low-level (LL) observer to deduce high-level (HL) actions ranges from limited to none. However, a collaborative set of observers strategically located in a network may be able to deduce all the HL actions. This paper models a distributed power electronics control device network using a simple DC circuit in order to understand the effect of multiple observers in a CPS. The analysis reveals that the number of observers required to deduce all the HL actions in a system increases linearly with the number of configurable units. A simple definition of nondeducibility based on the uniqueness of low-level projections is also presented. This definition is used to show that a system with two security domain levels could be considered “nondeducibility secure” if no unique LL projections exist.

MABE multibeam accelerator

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

Hasti, D.E.; Ramirez, J.J.; Coleman, P.D.

1985-01-01

The Megamp Accelerator and Beam Experiment (MABE) was the technology development testbed for the multiple beam, linear induction accelerator approach for Hermes III, a new 20 MeV, 0.8 MA, 40 ns accelerator being developed at Sandia for gamma-ray simulation. Experimental studies of a high-current, single-beam accelerator (8 MeV, 80 kA), and a nine-beam injector (1.4 MeV, 25 kA/beam) have been completed, and experiments on a nine-beam linear induction accelerator are in progress. A two-beam linear induction accelerator is designed and will be built as a gamma-ray simulator to be used in parallel with Hermes III. The MABE pulsed power systemmore » and accelerator for the multiple beam experiments is described. Results from these experiments and the two-beam design are discussed. 11 refs., 6 figs.« less

A multiple linear regression analysis of hot corrosion attack on a series of nickel base turbine alloys

NASA Technical Reports Server (NTRS)

Barrett, C. A.

1985-01-01

Multiple linear regression analysis was used to determine an equation for estimating hot corrosion attack for a series of Ni base cast turbine alloys. The U transform (i.e., 1/sin (% A/100) to the 1/2) was shown to give the best estimate of the dependent variable, y. A complete second degree equation is described for the centered" weight chemistries for the elements Cr, Al, Ti, Mo, W, Cb, Ta, and Co. In addition linear terms for the minor elements C, B, and Zr were added for a basic 47 term equation. The best reduced equation was determined by the stepwise selection method with essentially 13 terms. The Cr term was found to be the most important accounting for 60 percent of the explained variability hot corrosion attack.

The Utility of a Syndemic Framework in Understanding Chronic Disease Management Among HIV-Infected and Type 2 Diabetic Men Who Have Sex with Men.

PubMed

Byg, Blaire; Bazzi, Angela Robertson; Funk, Danielle; James, Bonface; Potter, Jennifer

2016-12-01

Syndemic theory posits that epidemics of multiple physical and psychosocial problems co-occur among disadvantaged groups due to adverse social conditions. Although sexual minority populations are often stigmatized and vulnerable to multiple health problems, the syndemic perspective has been underutilized in understanding chronic disease. To assess the potential utility of this perspective in understanding the management of co-occurring HIV and Type 2 diabetes, we used linear regression to examine glycemic control (A1c) among men who have sex with men (MSM) with both HIV and Type 2 diabetes (n = 88). Bivariable linear regression explored potential syndemic correlates of inadequate glycemic control. Compared to those with adequate glycemic control (A1c ≤ 7.5 %), more men with inadequate glycemic control (A1c > 7.5 %) had hypertension (70 vs. 46 %, p = 0.034), high triglycerides (93 vs. 61 %, p = 0.002), depression (67 vs. 39 %, p = 0.018), current substance abuse (15 vs. 2 %, p = 0.014), and detectable levels of HIV (i.e., viral load ≥75 copies per ml blood; 30 vs. 10 %, p = 0.019). In multivariable regression controlling for age, the factors that were independently associated with higher A1c were high triglycerides, substance use, and detectable HIV viral load, suggesting that chronic disease management among MSM is complex and challenging for patients and providers. Findings also suggest that syndemic theory can be a clarifying lens for understanding chronic disease management among sexual minority stigmatized populations. Interventions targeting single conditions may be inadequate when multiple conditions co-occur; thus, research using a syndemic framework may be helpful in identifying intervention strategies that target multiple co-occurring conditions.

[Spectral features analysis of Pinus massoniana with pest of Dendrolimus punctatus Walker and levels detection].

PubMed

Xu, Zhang-Hua; Liu, Jian; Yu, Kun-Yong; Gong, Cong-Hong; Xie, Wan-Jun; Tang, Meng-Ya; Lai, Ri-Wen; Li, Zeng-Lu

2013-02-01

Taking 51 field measured hyperspectral data with different pest levels in Yanping, Fujian Province as objects, the spectral reflectance and first derivative features of 4 levels of healthy, mild, moderate and severe insect pest were analyzed. On the basis of 7 detecting parameters construction, the pest level detecting models were built. The results showed that (1) the spectral reflectance of Pinus massoniana with pests were significantly lower than that of healthy state, and the higher the pest level, the lower the reflectance; (2) with the increase in pest level, the spectral reflectance curves' "green peak" and "red valley" of Pinus massoniana gradually disappeared, and the red edge was leveleds (3) the pest led to spectral "green peak" red shift, red edge position blue shift, but the changes in "red valley" and near-infrared position were complicated; (4) CARI, RES, REA and REDVI were highly relevant to pest levels, and the correlations between REP, RERVI, RENDVI and pest level were weak; (5) the multiple linear regression model with the variables of the 7 detection parameters could effectively detect the pest levels of Dendrolimus punctatus Walker, with both the estimation rate and accuracy above 0.85.

C-reactive protein and reactive oxygen metabolites in subjects with metabolic syndrome.

PubMed

Kotani, K; Sakane, N

2012-01-01

This cross-sectional study investigated the correlation between diacron reactive oxygen metabolites (d-ROMs) and high-sensitivity C-reactive protein (hs-CRP) in subjects with or without metabolic syndrome. Cardiometabolic risk factors, d-ROMs and hs-CRP were determined in 457 women: 123 with metabolic syndrome and 334 without metabolic syndrome. The correlation between d-ROMs and hs-CRP levels was compared between the two groups. The group with metabolic syndrome had significantly higher d-ROMs and hs-CRP levels than the group without metabolic syndrome. While the d-ROMs level was significantly and positively correlated with the hs-CRP level in both groups, the correlation level between the two groups was significantly different. Multiple linear regression analysis adjusted for other cardiometabolic risk factors also showed significant positive correlation between dROMs and hs-CRP levels in both groups. Subjects with metabolic syndrome may have a closer relationship between inflammation and oxidative stress than subjects without metabolic syndrome, possibly reflecting their increased predisposition to atherosclerosis. Further studies are necessary to confirm the observed relationship.

Clinically Practical Approach for Screening of Low Muscularity Using Electronic Linear Measures on Computed Tomography Images in Critically Ill Patients.

PubMed

Avrutin, Egor; Moisey, Lesley L; Zhang, Roselyn; Khattab, Jenna; Todd, Emma; Premji, Tahira; Kozar, Rosemary; Heyland, Daren K; Mourtzakis, Marina

2017-12-06

Computed tomography (CT) scans performed during routine hospital care offer the opportunity to quantify skeletal muscle and predict mortality and morbidity in intensive care unit (ICU) patients. Existing methods of muscle cross-sectional area (CSA) quantification require specialized software, training, and time commitment that may not be feasible in a clinical setting. In this article, we explore a new screening method to identify patients with low muscle mass. We analyzed 145 scans of elderly ICU patients (≥65 years old) using a combination of measures obtained with a digital ruler, commonly found on hospital radiological software. The psoas and paraspinal muscle groups at the level of the third lumbar vertebra (L3) were evaluated by using 2 linear measures each and compared with an established method of CT image analysis of total muscle CSA in the L3 region. There was a strong association between linear measures of psoas and paraspinal muscle groups and total L3 muscle CSA (R 2 = 0.745, P < 0.001). Linear measures, age, and sex were included as covariates in a multiple logistic regression to predict those with low muscle mass; receiver operating characteristic (ROC) area under the curve (AUC) of the combined psoas and paraspinal linear index model was 0.920. Intraclass correlation coefficients (ICCs) were used to evaluate intrarater and interrater reliability, resulting in scores of 0.979 (95% CI: 0.940-0.992) and 0.937 (95% CI: 0.828-0.978), respectively. A digital ruler can reliably predict L3 muscle CSA, and these linear measures may be used to identify critically ill patients with low muscularity who are at risk for worse clinical outcomes. © 2017 American Society for Parenteral and Enteral Nutrition.

Pre-diagnostic blood immune markers, incidence and progression of B-cell lymphoma and multiple myeloma: Univariate and functionally informed multivariate analyses.

PubMed

Vermeulen, Roel; Saberi Hosnijeh, Fatemeh; Bodinier, Barbara; Portengen, Lützen; Liquet, Benoît; Garrido-Manriquez, Javiera; Lokhorst, Henk; Bergdahl, Ingvar A; Kyrtopoulos, Soterios A; Johansson, Ann-Sofie; Georgiadis, Panagiotis; Melin, Beatrice; Palli, Domenico; Krogh, Vittorio; Panico, Salvatore; Sacerdote, Carlotta; Tumino, Rosario; Vineis, Paolo; Castagné, Raphaële; Chadeau-Hyam, Marc; Botsivali, Maria; Chatziioannou, Aristotelis; Valavanis, Ioannis; Kleinjans, Jos C S; de Kok, Theo M C M; Keun, Hector C; Athersuch, Toby J; Kelly, Rachel; Lenner, Per; Hallmans, Goran; Stephanou, Euripides G; Myridakis, Antonis; Kogevinas, Manolis; Fazzo, Lucia; De Santis, Marco; Comba, Pietro; Bendinelli, Benedetta; Kiviranta, Hannu; Rantakokko, Panu; Airaksinen, Riikka; Ruokojarvi, Paivi; Gilthorpe, Mark; Fleming, Sarah; Fleming, Thomas; Tu, Yu-Kang; Lundh, Thomas; Chien, Kuo-Liong; Chen, Wei J; Lee, Wen-Chung; Kate Hsiao, Chuhsing; Kuo, Po-Hsiu; Hung, Hung; Liao, Shu-Fen

2018-04-18

Recent prospective studies have shown that dysregulation of the immune system may precede the development of B-cell lymphomas (BCL) in immunocompetent individuals. However, to date, the studies were restricted to a few immune markers, which were considered separately. Using a nested case-control study within two European prospective cohorts, we measured plasma levels of 28 immune markers in samples collected a median of 6 years before diagnosis (range 2.01-15.97) in 268 incident cases of BCL (including multiple myeloma [MM]) and matched controls. Linear mixed models and partial least square analyses were used to analyze the association between levels of immune marker and the incidence of BCL and its main histological subtypes and to investigate potential biomarkers predictive of the time to diagnosis. Linear mixed model analyses identified associations linking lower levels of fibroblast growth factor-2 (FGF-2 p = 7.2 × 10 -4 ) and transforming growth factor alpha (TGF-α, p = 6.5 × 10 -5 ) and BCL incidence. Analyses stratified by histological subtypes identified inverse associations for MM subtype including FGF-2 (p = 7.8 × 10 -7 ), TGF-α (p = 4.08 × 10 -5 ), fractalkine (p = 1.12 × 10 -3 ), monocyte chemotactic protein-3 (p = 1.36 × 10 -4 ), macrophage inflammatory protein 1-alpha (p = 4.6 × 10 -4 ) and vascular endothelial growth factor (p = 4.23 × 10 -5 ). Our results also provided marginal support for already reported associations between chemokines and diffuse large BCL (DLBCL) and cytokines and chronic lymphocytic leukemia (CLL). Case-only analyses showed that Granulocyte-macrophage colony stimulating factor levels were consistently higher closer to diagnosis, which provides further evidence of its role in tumor progression. In conclusion, our study suggests a role of growth-factors in the incidence of MM and of chemokine and cytokine regulation in DLBCL and CLL. © 2018 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

Leptin but not adiponectin is related to type 2 diabetes mellitus in obese adolescents.

PubMed

Reinehr, Thomas; Woelfle, Joachim; Wiegand, Susanna; Karges, Beate; Meissner, Thomas; Nagl, Katrin; Holl, Reinhard W

2016-06-01

Adipokines have been suggested to be involved in the development of type 2 diabetes mellitus (T2DM). However, studies in humans are controversial and analyzes at the onset of disease are scarce. We compared adiponectin and leptin levels between 74 predominately Caucasian adolescents with T2DM and 74 body mass index (BMI)-, age-, and gender-matched controls without T2DM. Adiponectin and leptin were correlated to age, BMI, hemoglobin A1c (HbA1c), blood pressure, and lipids. Adolescents with T2DM showed significant lower leptin levels as compared with controls (18 ± 12 vs. 37 ± 23 ng/mL, p < 0.001), whereas the adiponectin levels did not differ between the adolescents with and without T2DM (5.0 ± 2.5 vs. 4.9 ± 2.5 µg/mL, p = 0.833). The associations between adiponectin and high-density lipoprotein (HDL) cholesterol (r = 0.42), systolic (r = -0.15), and diastolic blood pressure (r = -0.20) were stronger as the associations of leptin to these parameters (all r < 0.07). In multiple linear regression analysis, leptin was significantly and positively associated with BMI [β-coefficient: 1.3 (95% confidence interval (95% CI): ±0.5), p < 0.001] and female sex [β-coefficient: 9.7 (95% CI: ±6.7), p = 0.005], and negatively with age [β-coefficient: -2.3 (95% CI: ±2.1), p < 0.001] and HbA1c [β-coefficient -3.1 (95% CI: ±2.1), p = 0.011]. Adiponectin was not significantly associated with BMI, HbA1c, age, or gender in multiple linear regression analysis. Because adiponectin levels did not differ between obese adolescents with and without T2DM, hypoadiponectinemia as observed in obesity seems not to be involved in the genesis of T2DM. The relative hypoleptinemia in obese adolescents with T2DM as compared with obese adolescents without T2DM may contribute to the development of T2DM. Future longitudinal studies in humans are necessary to prove this hypothesis. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Simultaneous multiple non-crossing quantile regression estimation using kernel constraints

PubMed Central

Liu, Yufeng; Wu, Yichao

2011-01-01

Quantile regression (QR) is a very useful statistical tool for learning the relationship between the response variable and covariates. For many applications, one often needs to estimate multiple conditional quantile functions of the response variable given covariates. Although one can estimate multiple quantiles separately, it is of great interest to estimate them simultaneously. One advantage of simultaneous estimation is that multiple quantiles can share strength among them to gain better estimation accuracy than individually estimated quantile functions. Another important advantage of joint estimation is the feasibility of incorporating simultaneous non-crossing constraints of QR functions. In this paper, we propose a new kernel-based multiple QR estimation technique, namely simultaneous non-crossing quantile regression (SNQR). We use kernel representations for QR functions and apply constraints on the kernel coefficients to avoid crossing. Both unregularised and regularised SNQR techniques are considered. Asymptotic properties such as asymptotic normality of linear SNQR and oracle properties of the sparse linear SNQR are developed. Our numerical results demonstrate the competitive performance of our SNQR over the original individual QR estimation. PMID:22190842

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

Sources of variation for indoor nitrogen dioxide in rural residences of Ethiopia

PubMed Central

2009-01-01

Background Unprocessed biomass fuel is the primary source of indoor air pollution (IAP) in developing countries. The use of biomass fuel has been linked with acute respiratory infections. This study assesses sources of variations associated with the level of indoor nitrogen dioxide (NO2). Materials and methods This study examines household factors affecting the level of indoor pollution by measuring NO2. Repeated measurements of NO2 were made using a passive diffusive sampler. A Saltzman colorimetric method using a spectrometer calibrated at 540 nm was employed to analyze the mass of NO2 on the collection filter that was then subjected to a mass transfer equation to calculate the level of NO2 for the 24 hours of sampling duration. Structured questionnaire was used to collect data on fuel use characteristics. Data entry and cleaning was done in EPI INFO version 6.04, while data was analyzed using SPSS version 15.0. Analysis of variance, multiple linear regression and linear mixed model were used to isolate determining factors contributing to the variation of NO2 concentration. Results A total of 17,215 air samples were fully analyzed during the study period. Wood and crop were principal source of household energy. Biomass fuel characteristics were strongly related to indoor NO2 concentration in one-way analysis of variance. There was variation in repeated measurements of indoor NO2 over time. In a linear mixed model regression analysis, highland setting, wet season, cooking, use of fire events at least twice a day, frequency of cooked food items, and interaction between ecology and season were predictors of indoor NO2 concentration. The volume of the housing unit and the presence of kitchen showed little relevance in the level of NO2 concentration. Conclusion Agro-ecology, season, purpose of fire events, frequency of fire activities, frequency of cooking and physical conditions of housing are predictors of NO2 concentration. Improved kitchen conditions and ventilation are highly recommended. PMID:19922645

MAGDM linear-programming models with distinct uncertain preference structures.

PubMed

Xu, Zeshui S; Chen, Jian

2008-10-01

Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.

On Performance of Linear Multiuser Detectors for Wireless Multimedia Applications

NASA Astrophysics Data System (ADS)

Agarwal, Rekha; Reddy, B. V. R.; Bindu, E.; Nayak, Pinki

In this paper, performance of different multi-rate schemes in DS-CDMA system is evaluated. The analysis of multirate linear multiuser detectors with multiprocessing gain is analyzed for synchronous Code Division Multiple Access (CDMA) systems. Variable data rate is achieved by varying the processing gain. Our conclusion is that bit error rate for multirate and single rate systems can be made same with a tradeoff with number of users in linear multiuser detectors.

Sampled-Data Kalman Filtering and Multiple Model Adaptive Estimation for Infinite-Dimensional Continuous-Time Systems

DTIC Science & Technology

2007-03-01

mathematical frame- 1-6 work of linear algebra and functional analysis [122, 33], while Kalman-Bucy filtering [96, 32] is an especially important...Engineering, Air Force Institute of Technology (AU), Wright- Patterson AFB, Ohio, March 2002. 85. Hoffman, Kenneth and Ray Kunze. Linear Algebra (Second Edition...Engineering, Air Force Institute of Technology (AU), Wright- Patterson AFB, Ohio, December 1989. 189. Strang, Gilbert. Linear Algebra and Its Applications

Analysis of the Multiple-Solution Response of a Flexible Rotor Supported on Non-Linear Squeeze Film Dampers

NASA Astrophysics Data System (ADS)

ZHU, C. S.; ROBB, D. A.; EWINS, D. J.

2002-05-01

The multiple-solution response of rotors supported on squeeze film dampers is a typical non-linear phenomenon. The behaviour of the multiple-solution response in a flexible rotor supported on two identical squeeze film dampers with centralizing springs is studied by three methods: synchronous circular centred-orbit motion solution, numerical integration method and slow acceleration method using the assumption of a short bearing and cavitated oil film; the differences of computational results obtained by the three different methods are compared in this paper. It is shown that there are three basic forms for the multiple-solution response in the flexible rotor system supported on the squeeze film dampers, which are the resonant, isolated bifurcation and swallowtail bifurcation multiple solutions. In the multiple-solution speed regions, the rotor motion may be subsynchronous, super-subsynchronous, almost-periodic and even chaotic, besides synchronous circular centred, even if the gravity effect is not considered. The assumption of synchronous circular centred-orbit motion for the journal and rotor around the static deflection line can be used only in some special cases; the steady state numerical integration method is very useful, but time consuming. Using the slow acceleration method, not only can the multiple-solution speed regions be detected, but also the non-synchronous response regions.

Longitudinal patterns and predictors of multiple health risk behaviors among adolescents: The TRAILS study.

PubMed

de Winter, Andrea F; Visser, Leenke; Verhulst, Frank C; Vollebergh, Wilma A M; Reijneveld, Sijmen A

2016-03-01

Most studies on multiple health risk behaviors among adolescents have cross-sectionally studied a limited number of health behaviors or determinants. To examine the prevalence, longitudinal patterns and predictors of individual and multiple health risk behaviors among adolescents. Eight health risk behaviors (no regular consumption of fruit, vegetables or breakfast, overweight or obesity, physical inactivity, smoking, alcohol use and cannabis use) were assessed in a prospective population study (second and third wave). Participants were assessed in three waves between ages 10 and 17 (2001-2008; n=2230). Multiple linear regression was used to assess the influence of gender, self-control, parental health risk behaviors, parental monitoring and socioeconomic factors on the number of health risk behaviors adjusted for preceding multiple health risk behaviors (analysis: 2013-2014). Rates of >5 health risk behaviors were high: 3.6% at age 13.5 and 10.2% at age 16. Smoking at age 13.5 was frequently associated with health risk behaviors at age 16. No regular consumption of fruit, vegetables and breakfast, overweight or obesity, physical inactivity and smoking predicted the co-occurrence of health risk behaviors at follow-up. Significant predictors of the development of multiple health risk behaviors were adolescents' levels of self-control, socioeconomic status and maternal smoking. Multiple health risk behaviors are common among adolescents. Individual and social factors predict changes in multiple health risk behaviors, showing that prevention targeting multiple risk behaviors is needed. Special attention should be paid to adolescents with low self-control and families with low socioeconomic status or a mother who smokes. Copyright © 2015 Elsevier Inc. All rights reserved.

Genomic prediction based on data from three layer lines using non-linear regression models.

PubMed

Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L

2014-11-06

Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional occurrence of large negative accuracies when the evaluated line was not included in the training dataset. Furthermore, when using a multi-line training dataset, non-linear models provided information on the genotype data that was complementary to the linear models, which indicates that the underlying data distributions of the three studied lines were indeed heterogeneous.

Large-region acoustic source mapping using a movable array and sparse covariance fitting.

PubMed

Zhao, Shengkui; Tuna, Cagdas; Nguyen, Thi Ngoc Tho; Jones, Douglas L

2017-01-01

Large-region acoustic source mapping is important for city-scale noise monitoring. Approaches using a single-position measurement scheme to scan large regions using small arrays cannot provide clean acoustic source maps, while deploying large arrays spanning the entire region of interest is prohibitively expensive. A multiple-position measurement scheme is applied to scan large regions at multiple spatial positions using a movable array of small size. Based on the multiple-position measurement scheme, a sparse-constrained multiple-position vectorized covariance matrix fitting approach is presented. In the proposed approach, the overall sample covariance matrix of the incoherent virtual array is first estimated using the multiple-position array data and then vectorized using the Khatri-Rao (KR) product. A linear model is then constructed for fitting the vectorized covariance matrix and a sparse-constrained reconstruction algorithm is proposed for recovering source powers from the model. The user parameter settings are discussed. The proposed approach is tested on a 30 m × 40 m region and a 60 m × 40 m region using simulated and measured data. Much cleaner acoustic source maps and lower sound pressure level errors are obtained compared to the beamforming approaches and the previous sparse approach [Zhao, Tuna, Nguyen, and Jones, Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP) (2016)].

Experimental and analytical investigations of longitudinal combustion instability in a continuously variable resonance combustor (CVRC)

NASA Astrophysics Data System (ADS)

Yu, Yen Ching

An analytical model based on linearized Euler equations (LEE) is developed and used in conjunction with a validating experiment to study combustion instability. The LEE model features mean flow effects, entropy waves, adaptability for more physically-realistic boundary conditions, and is generalized for multiple-domain conditions. The model calculates spatial modes, resonant frequencies and linear growth rates of the overall system. The predicted resonant frequencies and spatially-resolved mode shapes agree with the experimental data from a longitudinally-unstable model rocket combustor to within 7%. Different gaseous fuels (methane, ethylene, and hydrogen) were tested under fixed geometry. Tests with hydrogen were stable, whereas ethylene, methane, and JP-8 were increasingly unstable. A novel method for obtaining large amounts of stability data under variable resonance conditions in a single test was demonstrated. The continuously variable resonance combustor (CVRC) incorporates a traversing choked axial oxidizer inlet to vary the overall combustion system resonance. The CVRC experiment successfully demonstrates different level of instability, transitions between stability levels, and identifies the most stable and unstable geometric combination. Pressure oscillation amplitudes ranged from less than 10% of mean pressure to greater than 60%. At low amplitudes, measured resonant frequency changed with inlet location but at high amplitude the measured resonance frequency matched the frequency of the combustion chamber. As the system transitions from linear to non-linear instability, the higher harmonics of the fundamental resonant mode appear nearly simultaneously. Transient, high-amplitude, broadband noise, at lower frequencies (on the order of 200 Hz) are also observed. Conversely, as the system transitions back to a more linear stability regime, the higher harmonics disappear sequentially, led by the highest order. Good agreements between analytical and experimental results are attained by treating the experiment as quasi-stationary. The stability characteristics from the high frequency measurements are further analyzed using filtered pressure traces, spectrograms, power spectral density plots, and oscillation decrements. Future works recommended include: direct measurements, such as chemiluminescence or high-speed imaging to examine the unsteady combustion processes; three-way comparisons between the acoustic-based, linear Euler-based, and non-linear Euler/RANS model; use the high fidelity computation to investigate the forcing terms modeled in the acoustic-based model.

Photon-Z mixing the Weinberg-Salam model: Effective charges and the a = -3 gauge

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

Baulieu, L.; Coquereaux, R.

1982-04-15

We study some properties of the Weinberg-Salam model connected with the photon-Z mixing. We solve the linear Dyson-Schwinger equations between full and 1PI boson propagators. The task is made easier, by the two-point function Ward identities that we derive to all orders and in any gauge. Some aspects of the renormalization of the model are also discussed. We display the exact mass-dependent one-loop two-point functions involving the photon and Z field in any linear xi-gauge. The special gauge a = xi/sup -1/ = -3 is shown to play a peculiar role. In this gauge, the Z field is multiplicatively renormalizablemore » (at the one-loop level), and one can construct both electric and weak effective charges of the theory from the photon and Z propagators, with a very simple expression similar to that of the QED Petermann, Stueckelberg, Gell-Mann and Low charge.« less

Assessing exposure to violence using multiple informants: application of hierarchical linear model.

PubMed

Kuo, M; Mohler, B; Raudenbush, S L; Earls, F J

2000-11-01

The present study assesses the effects of demographic risk factors on children's exposure to violence (ETV) and how these effects vary by informants. Data on exposure to violence of 9-, 12-, and 15-year-olds were collected from both child participants (N = 1880) and parents (N = 1776), as part of the assessment of the Project on Human Development in Chicago Neighborhoods (PHDCN). A two-level hierarchical linear model (HLM) with multivariate outcomes was employed to analyze information obtained from these two different groups of informants. The findings indicate that parents generally report less ETV than do their children and that associations of age, gender, and parent education with ETV are stronger in the self-reports than in the parent reports. The findings support a multivariate approach when information obtained from different sources is being integrated. The application of HLM allows an assessment of interactions between risk factors and informants and uses all available data, including data from one informant when data from the other informant is missing.

Internal resonance and low frequency vibration energy harvesting

NASA Astrophysics Data System (ADS)

Yang, Wei; Towfighian, Shahrzad

2017-09-01

A nonlinear vibration energy harvester with internal resonance is presented. The proposed harvester consists of two cantilevers, each with a permanent magnet on its tip. One cantilever has a piezoelectric layer at its base. When magnetic force is applied this two degrees-of-freedom nonlinear vibration system shows the internal resonance phenomenon that broadens the frequency bandwidth compared to a linear system. Three coupled partial differential equations are obtained to predict the dynamic behavior of the nonlinear energy harvester. The perturbation method of multiple scales is used to solve equations. Results from experiments done at different vibration levels with varying distances between the magnets validate the mathematical model. Experiments and simulations show the design outperforms the linear system by doubling the frequency bandwidth. Output voltage for frequency response is studied for different system parameters. The optimal load resistance is obtained for the maximum power in the internal resonance case. The results demonstrate that a design combining internal resonance and magnetic nonlinearity improves the efficiency of energy harvesting.

Is It the Intervention or the Students? Using Linear Regression to Control for Student Characteristics in Undergraduate STEM Education Research

PubMed Central

Theobald, Roddy; Freeman, Scott

2014-01-01

Although researchers in undergraduate science, technology, engineering, and mathematics education are currently using several methods to analyze learning gains from pre- and posttest data, the most commonly used approaches have significant shortcomings. Chief among these is the inability to distinguish whether differences in learning gains are due to the effect of an instructional intervention or to differences in student characteristics when students cannot be assigned to control and treatment groups at random. Using pre- and posttest scores from an introductory biology course, we illustrate how the methods currently in wide use can lead to erroneous conclusions, and how multiple linear regression offers an effective framework for distinguishing the impact of an instructional intervention from the impact of student characteristics on test score gains. In general, we recommend that researchers always use student-level regression models that control for possible differences in student ability and preparation to estimate the effect of any nonrandomized instructional intervention on student performance. PMID:24591502

Is it the intervention or the students? using linear regression to control for student characteristics in undergraduate STEM education research.

PubMed

Theobald, Roddy; Freeman, Scott

2014-01-01

Although researchers in undergraduate science, technology, engineering, and mathematics education are currently using several methods to analyze learning gains from pre- and posttest data, the most commonly used approaches have significant shortcomings. Chief among these is the inability to distinguish whether differences in learning gains are due to the effect of an instructional intervention or to differences in student characteristics when students cannot be assigned to control and treatment groups at random. Using pre- and posttest scores from an introductory biology course, we illustrate how the methods currently in wide use can lead to erroneous conclusions, and how multiple linear regression offers an effective framework for distinguishing the impact of an instructional intervention from the impact of student characteristics on test score gains. In general, we recommend that researchers always use student-level regression models that control for possible differences in student ability and preparation to estimate the effect of any nonrandomized instructional intervention on student performance.

Serum osteocalcin is significantly related to indices of obesity and lipid profile in Malaysian men.

PubMed

Chin, Kok-Yong; Ima-Nirwana, Soelaiman; Mohamed, Isa Naina; Ahmad, Fairus; Ramli, Elvy Suhana Mohd; Aminuddin, Amilia; Ngah, Wan Zurinah Wan

2014-01-01

Recent studies revealed a possible reciprocal relationship between the skeletal system and obesity and lipid metabolism, mediated by osteocalcin, an osteoblast-specific protein. This study aimed to validate the relationship between serum osteocalcin and indices of obesity and lipid parameters in a group of Malaysian men. A total of 373 men from the Malaysian Aging Male Study were included in the analysis. Data on subjects' demography, body mass index (BMI), body fat (BF) mass, waist circumference (WC), serum osteocalcin and fasting lipid levels were collected. Bioelectrical impendence (BIA) method was used to estimate BF. Multiple linear and binary logistic regression analyses were performed to analyze the association between serum osteocalcin and the aforementioned variables, with adjustment for age, ethnicity and BMI. Multiple regression results indicated that weight, BMI, BF mass, BF %, WC were significantly and negatively associated with serum osteocalcin (p < 0.001). There was a significant positive association between serum osteocalcin and high density lipoprotein (HDL) cholesterol (p = 0.032). Binary logistic results indicated that subjects with low serum osteocalcin level were more likely to be associated with high BMI (obese and overweight), high BF%, high WC and low HDL cholesterol (p < 0.05). Subjects with high osteocalcin level also demonstrated high total cholesterol level (p < 0.05) but this association was probably driven by high HDL level. These variables were not associated with serum C-terminal of telopeptide crosslinks in the subjects (p > 0.05). Serum osteocalcin is associated with indices of obesity and HDL level in men. These relationships should be validated by a longitudinal study, with comprehensive hormone profile testing.

The Association of Free Testosterone Levels in Men and Lifestyle Factors and Chronic Disease Status: A North Texas Healthy Heart Study.

PubMed

Cardarelli, Roberto; Singh, Meharvan; Meyer, Jason; Balyakina, Elizabeth; Perez, Oscar; King, Michael

2014-07-01

Hypogonadism is highly prevalent in men older than 45 years and is associated with an increased risk of chronic diseases, including obesity, metabolic syndrome, diabetes, and cardiovascular disease. The objective of this study was to determine whether lifestyle factors such as smoking, diet, and exercise are associated with reduced testosterone levels. In this cross-sectional study, 147 men older than 44 years were recruited from a collaborative network of primary care clinics in the Dallas/Fort Worth, Texas, metropolitan area. Free testosterone levels were measured in plasma samples via an enzyme-linked immunosorbent assay-based method, and analyzed by simple and multiple linear regression in relationship to age, race/ethnicity, smoking, diet, exercise, obesity, diabetes, hypertension, and dyslipidemia. The participants had a mean free testosterone level of 3.1 ng/mL (standard deviation [SD] = 1.5) and mean age of 56.8 years (SD = 7.9). In simple regression analysis, free testosterone levels were associated with increased age (β = -0.04; P = .02), diet (β = -0.49; P = .05), diabetes (β = -0.9; P = .003), and hypertension (β = -0.55; P = .03) but not with race/ethnicity, smoking, exercise, obesity, or dyslipidemia. In multiple regression analysis, free testosterone values were significantly associated only with age (β = -0.05; P = .01) and diet (β = -0.72; P = .01). This study implicates diet, in addition to advanced age as a possible risk factor in the development of reduced testosterone levels. © The Author(s) 2014.

Method development towards qualitative and semi-quantitative analysis of multiple pesticides from food surfaces and extracts by desorption electrospray ionization mass spectrometry as a preselective tool for food control.

PubMed

Gerbig, Stefanie; Stern, Gerold; Brunn, Hubertus E; Düring, Rolf-Alexander; Spengler, Bernhard; Schulz, Sabine

2017-03-01

Direct analysis of fruit and vegetable surfaces is an important tool for in situ detection of food contaminants such as pesticides. We tested three different ways to prepare samples for the qualitative desorption electrospray ionization mass spectrometry (DESI-MS) analysis of 32 pesticides found on nine authentic fruits collected from food control. Best recovery rates for topically applied pesticides (88%) were found by analyzing the surface of a glass slide which had been rubbed against the surface of the food. Pesticide concentration in all samples was at or below the maximum residue level allowed. In addition to the high sensitivity of the method for qualitative analysis, quantitative or, at least, semi-quantitative information is needed in food control. We developed a DESI-MS method for the simultaneous determination of linear calibration curves of multiple pesticides of the same chemical class using normalization to one internal standard (ISTD). The method was first optimized for food extracts and subsequently evaluated for the quantification of pesticides in three authentic food extracts. Next, pesticides and the ISTD were applied directly onto food surfaces, and the corresponding calibration curves were obtained. The determination of linear calibration curves was still feasible, as demonstrated for three different food surfaces. This proof-of-principle method was used to simultaneously quantify two pesticides on an authentic sample, showing that the method developed could serve as a fast and simple preselective tool for disclosure of pesticide regulation violations. Graphical Abstract Multiple pesticide residues were detected and quantified in-situ from an authentic set of food items and extracts in a proof of principle study.

[Association between hours of television watched, physical activity, sleep and excess weight among young adults].

PubMed

Martínez-Moyá, María; Navarrete-Muñoz, Eva M; García de la Hera, Manuela; Giménez-Monzo, Daniel; González-Palacios, Sandra; Valera-Gran, Desirée; Sempere-Orts, María; Vioque, Jesús

2014-01-01

To explore the association between excess weight or body mass index (BMI) and the time spent watching television, self-reported physical activity and sleep duration in a young adult population. We analyzed cross-sectional baseline data of 1,135 participants (17-35 years old) from the project Dieta, salud y antropometría en población universitaria (Diet, Health and Anthrompmetric Variables in Univeristy Students). Information about time spent watching television, sleep duration, self-reported physical activity and self-reported height and weight was provided by a baseline questionnaire. BMI was calculated as kg/m(2) and excess of weight was defined as ≥25. We used multiple logistic regression to explore the association between excess weight (no/yes) and independent variables, and multiple linear regression for BMI. The prevalence of excess weight was 13.7% (11.2% were overweight and 2.5% were obese). A significant positive association was found between excess weight and a greater amount of time spent watching television. Participants who reported watching television >2h a day had a higher risk of excess weight than those who watched television ≤1h a day (OR=2.13; 95%CI: 1.37-3.36; p-trend: 0.002). A lower level of physical activity was associated with an increased risk of excess weight, although the association was statistically significant only in multiple linear regression (p=0.037). No association was observed with sleep duration. A greater number of hours spent watching television and lower physical activity were significantly associated with a higher BMI in young adults. Both factors are potentially modifiable with preventive strategies. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Ten years of helicopter emergency medical services in Germany: do we still need the helicopter rescue in multiple traumatised patients?

PubMed

Andruszkow, Hagen; Hildebrand, Frank; Lefering, Rolf; Pape, Hans-Christoph; Hoffmann, Reinhard; Schweigkofler, Uwe

2014-10-01

Helicopter emergency medical service (HEMS) has been established in the preclinical treatment of multiple traumatised patients despite an ongoing controversy towards the potential benefit. Celebrating the 20th anniversary of TraumaRegister DGU(®) of the German Trauma Society (DGU) the presented study intended to provide an overview of HEMS rescue in Germany over the last 10 years analysing the potential beneficial impact of a nationwide helicopter rescue in multiple traumatised patients. We analysed TraumaRegister DGU(®) including multiple traumatised patients (ISS ≥ 16) between 2002 and 2012. In-hospital mortality was defined as main outcome. An adjusted, multivariate regression with 13 confounders was performed to evaluate the potential survival benefit. 42,788 patients were included in the present study. 14,275 (33.4%) patients were rescued by HEMS and 28,513 (66.6%) by GEMS. Overall, 66.8% (n=28,569) patients were transported to a level I trauma centre and 28.2% (n=12,052) to a level II trauma centre. Patients rescued by HEMS sustained a higher injury severity compared to GEMS (ISS HEMS: 29.5 ± 12.6 vs. 27.5 ± 11.8). Helicopter rescue teams performed more on-scene interventions, and mission times were increased in HEMS rescue (HEMS: 77.2 ± 28.7 min. vs. GEMS: 60.9 ± 26.9 min.). Linear regression analysis revealed that the frequency of HEMS rescue has decreased significantly between 2002 and 2012. In case of transportation to level I trauma centres a decrease of 1.7% per year was noted (p<0.001) while a decline of 1.6% per year (p<0.001) was measured for level II trauma centre admissions. According to multivariate logistic regression HEMS was proven a positive independent survival predictor between 2002 and 2012 (OR 0.863; 95%-CI 0.800-0.930; Nagelkerkes-R(2) 0.539) with only little differences between each year. This study was able to prove an independent survival benefit of HEMS in multiple traumatised patients during the last 10 years. Despite this fact, a constant decline of HEMS rescue missions was found in multiple trauma patients due to unknown reasons. We concluded that HEMS should be used more often in case of trauma in order to guarantee the proven benefit for multiple traumatised patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dendritic cell immunotherapy followed by cART interruption during HIV-1 infection induces plasma protein markers of cellular immunity and neutrophil recruitment

PubMed Central

Cooper, Jason D.; Tomasik, Jakub; Bahn, Sabine; Aerts, Joeri L.; Osterhaus, Albert D. M. E.; Gruters, Rob A.; Andeweg, Arno C.

2018-01-01

Objectives To characterize the host response to dendritic cell-based immunotherapy and subsequent combined antiretroviral therapy (cART) interruption in HIV-1-infected individuals at the plasma protein level. Design An autologous dendritic cell (DC) therapeutic vaccine was administered to HIV-infected individuals, stable on cART. The effect of vaccination was evaluated at the plasma protein level during the period preceding cART interruption, during analytical therapy interruption and at viral reactivation. Healthy controls and post-exposure prophylactically treated healthy individuals were included as controls. Methods Plasma marker (‘analyte’) levels including cytokines, chemokines, growth factors, and hormones were measured in trial participants and control plasma samples using a multiplex immunoassay. Analyte levels were analysed using principle component analysis, cluster analysis and limma. Blood neutrophil counts were analysed using linear regression. Results Plasma analyte levels of HIV-infected individuals are markedly different from those of healthy controls and HIV-negative individuals receiving post-exposure prophylaxis. Viral reactivation following cART interruption also affects multiple analytes, but cART interruption itself only has only a minor effect. We find that Thyroxine-Binding Globulin (TBG) levels and late-stage neutrophil numbers correlate with the time off cART after DC vaccination. Furthermore, analysis shows that cART alters several regulators of blood glucose levels, including C-peptide, chromogranin-A and leptin. HIV reactivation is associated with the upregulation of CXCR3 ligands. Conclusions Chronic HIV infection leads to a change in multiple plasma analyte levels, as does virus reactivation after cART interruption. Furthermore, we find evidence for the involvement of TBG and neutrophils in the response to DC-vaccination in the setting of HIV-infection. PMID:29389978

Dendritic cell immunotherapy followed by cART interruption during HIV-1 infection induces plasma protein markers of cellular immunity and neutrophil recruitment.

PubMed

van den Ham, Henk-Jan; Cooper, Jason D; Tomasik, Jakub; Bahn, Sabine; Aerts, Joeri L; Osterhaus, Albert D M E; Gruters, Rob A; Andeweg, Arno C

2018-01-01

To characterize the host response to dendritic cell-based immunotherapy and subsequent combined antiretroviral therapy (cART) interruption in HIV-1-infected individuals at the plasma protein level. An autologous dendritic cell (DC) therapeutic vaccine was administered to HIV-infected individuals, stable on cART. The effect of vaccination was evaluated at the plasma protein level during the period preceding cART interruption, during analytical therapy interruption and at viral reactivation. Healthy controls and post-exposure prophylactically treated healthy individuals were included as controls. Plasma marker ('analyte') levels including cytokines, chemokines, growth factors, and hormones were measured in trial participants and control plasma samples using a multiplex immunoassay. Analyte levels were analysed using principle component analysis, cluster analysis and limma. Blood neutrophil counts were analysed using linear regression. Plasma analyte levels of HIV-infected individuals are markedly different from those of healthy controls and HIV-negative individuals receiving post-exposure prophylaxis. Viral reactivation following cART interruption also affects multiple analytes, but cART interruption itself only has only a minor effect. We find that Thyroxine-Binding Globulin (TBG) levels and late-stage neutrophil numbers correlate with the time off cART after DC vaccination. Furthermore, analysis shows that cART alters several regulators of blood glucose levels, including C-peptide, chromogranin-A and leptin. HIV reactivation is associated with the upregulation of CXCR3 ligands. Chronic HIV infection leads to a change in multiple plasma analyte levels, as does virus reactivation after cART interruption. Furthermore, we find evidence for the involvement of TBG and neutrophils in the response to DC-vaccination in the setting of HIV-infection.

Quasilinear Line Broadened Model for Energetic Particle Transport

NASA Astrophysics Data System (ADS)

Ghantous, Katy; Gorelenkov, Nikolai; Berk, Herbert

2011-10-01

We present a self-consistent quasi-linear model that describes wave-particle interaction in toroidal geometry and computes fast ion transport during TAE mode evolution. The model bridges the gap between single mode resonances, where it predicts the analytically expected saturation levels, and the case of multiple modes overlapping, where particles diffuse across phase space. Results are presented in the large aspect ratio limit where analytic expressions are used for Fourier harmonics of the power exchange between waves and particles, . Implemention of a more realistic mode structure calculated by NOVAK code are also presented. This work is funded by DOE contract DE-AC02-09CH11466.

Mapping of fluoride endemic areas and correlation studies of fluoride with other quality parameters of drinking water of Veppanapalli block of Dharmapuri district in Tamil Nadu.

PubMed

Karthikeyan, G; Sundarraj, A Shunmuga; Elango, K P

2003-10-01

193 drinking water samples from water sources of 27 panchayats of Veppanapalli block of Dharmapuri district of Tamil Nadu were analysed for chemical quality parameters. Based on the fluoride content of the water sources, fluoride maps differentiating regions with high / low fluoride levels were prepared using Isopleth mapping technique. The interdependence among the important chemical quality parameters were assessed using correlation studies. The experimental results of the application of linear and multiple regression equations on the influence of hardness, alkalinity, total dissolved solids and pH on fluoride are discussed.

Auger heating of carriers in {GaAs}/{AlAs} heterostructures

NASA Astrophysics Data System (ADS)

Borri, P.; Ceccherini, S.; Gurioli, M.; Bogani, F.

1997-07-01

The photoluminescence of {GaAs}/{AlAs} multiple quantum wells structures under optical ps excitation is investigated for carrier densities in the range 10 18-4 × 10 19 cm -3 with frequency and time-resolved spectroscopic techniques. The measurements give a direct evidence of the occurrence in the sample of carrier heating. This energy up-conversion gives rise to photoluminescence from the states near the Fermi level whose intensity and time evolution depend on the carrier density in a strongly non-linear way. The observed behaviour can be explained introducing in the carrier dynamics an up-conversion mechanism due to Auger-like processes.

Communicative participation restrictions in multiple sclerosis: associated variables and correlation with social functioning.

PubMed

Yorkston, Kathryn M; Baylor, Carolyn; Amtmann, Dagmar

2014-01-01

Individuals with multiple sclerosis (MS) are at risk for communication problems that may restrict their ability to take participation in important life roles such as maintenance of relationships, work, or household management. The aim of this project is to examine selected demographic and symptom-related variables that may contribute to participation restrictions. This examination is intended to aid clinicians in predicting who might be at risk for such restrictions and what variables may be targeted in interventions. Community-dwelling adults with MS (n=216) completed a survey either online or using paper forms. The survey included the 46-item version of the Communicative Participation Item Bank, demographics (age, sex, living situation, employment status, education, and time since onset of diagnosis of MS), and self-reported symptom-related variables (physical activity, emotional problems, fatigue, pain, speech severity, and cognitive/communication skills). In order to identify predictors of restrictions in communicative participation, these variables were entered into a backwards stepwise multiple linear regression analysis. Five variables (cognitive/communication skills, speech severity, speech usage, physical activity, and education) were statistically significant predictors of communication participation. In order to examine the relationship of communicative participation and social role variables, bivariate Spearman correlations were conducted. Results suggest only a fair to moderate relationship between communicative participation and measures of social roles. Communicative participation is a complex construct associated with a number of self-reported variables. Clinicians should be alert to risk factors for reduced communicative participation including reduced cognitive and speech skills, lower levels of speech usage, limitations in physical activities and higher levels of education. The reader will be able to: (a) describe the factors that may restrict participation in individuals with multiple sclerosis; (b) list measures of social functioning that may be pertinent in adults with multiple sclerosis; (c) discuss factors that can be used to predict communicative participation in multiple sclerosis. Copyright © 2014 Elsevier Inc. All rights reserved.

Do Productive Activities Reduce Inflammation in Later Life? Multiple Roles, Frequency of Activities, and C-Reactive Protein

PubMed Central

Kim, Seoyoun; Ferraro, Kenneth F.

2014-01-01

Purpose of the Study: The study investigates whether productive activities by older adults reduce bodily inflammation, as indicated by C-reactive protein (CRP), a biomeasure associated with the risk of cardiovascular diseases. Design and Methods: The study uses a representative survey of adults aged 57–85 from the National Social Life, Health, and Aging Project (N = 1,790). Linear regression models were used to analyze the effects of multiple roles (employment, volunteering, attending meetings, and caregiving) and the frequency of activity within each role on log values of CRP concentration (mg/L) drawn from assayed blood samples. Results: Number of roles for productive activities was associated with lower levels of CRP net of chronic conditions, lifestyle factors, and socioeconomic resources. When specific types of activity were examined, volunteering manifested the strongest association with lower levels of inflammation, particularly in the 70+ group. There was no evidence that frequent engagement in volunteer activity was associated with heightened inflammation. Implications: Productive activities—and frequent volunteering in particular—may protect individuals from inflammation that is associated with increased risk of hypertension and cardiovascular disease. PMID:23969258

Multiscale imaging of bone microdamage

PubMed Central

Poundarik, Atharva A.; Vashishth, Deepak

2015-01-01

Bone is a structural and hierarchical composite that exhibits remarkable ability to sustain complex mechanical loading and resist fracture. Bone quality encompasses various attributes of bone matrix from the quality of its material components (type-I collagen, mineral and non-collagenous matrix proteins) and cancellous microarchitecture, to the nature and extent of bone microdamage. Microdamage, produced during loading, manifests in multiple forms across the scales of hierarchy in bone and functions to dissipate energy and avert fracture. Microdamage formation is a key determinant of bone quality, and through a range of biological and physical mechanisms, accumulates with age and disease. Accumulated microdamage in bone decreases bone strength and increases bone’s propensity to fracture. Thus, a thorough assessment of microdamage, across the hierarchical levels of bone, is crucial to better understand bone quality and bone fracture. This review article details multiple imaging modalities that have been used to study and characterize microdamage; from bulk staining techniques originally developed by Harold Frost to assess linear microcracks, to atomic force microscopy, a modality that revealed mechanistic insights into the formation diffuse damage at the ultrastructural level in bone. New automated techniques using imaging modalities such as microcomputed tomography are also presented for a comprehensive overview. PMID:25664772

A cytokine immunosensor for Multiple Sclerosis detection based upon label-free electrochemical impedance spectroscopy using electroplated printed circuit board electrodes.

PubMed

Bhavsar, Kinjal; Fairchild, Aaron; Alonas, Eric; Bishop, Daniel K; La Belle, Jeffrey T; Sweeney, James; Alford, T L; Joshi, Lokesh

2009-10-15

A biosensor for the serum cytokine, Interleukin-12 (IL-12), based upon a label-free electrochemical impedance spectroscopy (EIS) monitoring approach is described. Overexpression of IL-12 has been correlated to the diagnosis of Multiple Sclerosis (MS). An immunosensor has been fabricated by electroplating gold onto a disposable printed circuit board (PCB) electrode and immobilizing anti-IL-12 monoclonal antibodies (MAb) onto the surface of the electrode. This approach yields a robust sensor that facilitates reproducible mass fabrication and easy alteration of the electrode shape. Results indicate that this novel PCB sensor can detect IL-12 at physiological levels, <100 fM with f-values of 0.05 (typically <0.0001) in a label-free and rapid manner. A linear (with respect to log concentration) detectable range was achieved. Detection in a complex biological solution is also explored; however, significant loss of dynamic range is noted in the 100% complex solution. The cost effective approach described here can be used potentially for diagnosis of diseases (like MS) with known biomarkers in body fluids and for monitoring physiological levels of biomolecules with healthcare, food, and environmental relevance.

Seasonal Sea-Level Variations in San Francisco Bay in Response to Atmospheric Forcing, 1980

USGS Publications Warehouse

Wang, Jingyuan; Cheng, R.T.; Smith, P.C.

1997-01-01

The seasonal response of sea level in San Francisco Bay (SFB) to atmospheric forcing during 1980 is investigated. The relations between sea-level data from the Northern Reach, Central Bay and South Bay, and forcing by local wind stresses, sea level pressure (SLP), runoff and the large scale sea level pressure field are examined in detail. The analyses show that the sea-level elevations and slopes respond to the along-shore wind stress T(V) at most times of the year, and to the cross-shore wind stress T(N) during two transition periods in spring and autumn. River runoff raises the sea-level elevation during winter. It is shown that winter precipitation in the SFB area is mainly attributed to the atmospheric circulation associated with the Alcutian Low, which transports the warm, moist air into the Bay area. A multiple linear regression model is employed to estimate the independent contributions of barometric pressure and wind stress to adjusted sea level. These calculations have a simple dynamical interpretation which confirms the importance of along-shore wind to both sea level and north-south slope within the Bay.

Normal Theory Two-Stage ML Estimator When Data Are Missing at the Item Level

PubMed Central

Savalei, Victoria; Rhemtulla, Mijke

2017-01-01

In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately handle missing data at the item level. Item-level multiple imputation (MI), however, can handle such missing data straightforwardly. In this article, we develop an analytic approach for dealing with item-level missing data—that is, one that obtains a unique set of parameter estimates directly from the incomplete data set and does not require imputations. The proposed approach is a variant of the two-stage maximum likelihood (TSML) methodology, and it is the analytic equivalent of item-level MI. We compare the new TSML approach to three existing alternatives for handling item-level missing data: scale-level full information maximum likelihood, available-case maximum likelihood, and item-level MI. We find that the TSML approach is the best analytic approach, and its performance is similar to item-level MI. We recommend its implementation in popular software and its further study. PMID:29276371

Normal Theory Two-Stage ML Estimator When Data Are Missing at the Item Level.

PubMed

Savalei, Victoria; Rhemtulla, Mijke

2017-08-01

In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately handle missing data at the item level. Item-level multiple imputation (MI), however, can handle such missing data straightforwardly. In this article, we develop an analytic approach for dealing with item-level missing data-that is, one that obtains a unique set of parameter estimates directly from the incomplete data set and does not require imputations. The proposed approach is a variant of the two-stage maximum likelihood (TSML) methodology, and it is the analytic equivalent of item-level MI. We compare the new TSML approach to three existing alternatives for handling item-level missing data: scale-level full information maximum likelihood, available-case maximum likelihood, and item-level MI. We find that the TSML approach is the best analytic approach, and its performance is similar to item-level MI. We recommend its implementation in popular software and its further study.

Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

NASA Astrophysics Data System (ADS)

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali; Naderi, Mehdi; Dematte, Jose Alexandre M.; Kerry, Ruth

2016-11-01

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014 t h MJ- 1 mm- 1 and 2.08 times less than the estimated mean K (0.030 t h MJ- 1 mm- 1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2 = 0.81, n = 40, p < 0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.

Spatial summation revealed in the earliest visual evoked component C1 and the effect of attention on its linearity.

PubMed

Chen, Juan; Yu, Qing; Zhu, Ziyun; Peng, Yujia; Fang, Fang

2016-01-01

In natural scenes, multiple objects are usually presented simultaneously. How do specific areas of the brain respond to multiple objects based on their responses to each individual object? Previous functional magnetic resonance imaging (fMRI) studies have shown that the activity induced by a multiobject stimulus in the primary visual cortex (V1) can be predicted by the linear or nonlinear sum of the activities induced by its component objects. However, there has been little evidence from electroencephelogram (EEG) studies so far. Here we explored how V1 responded to multiple objects by comparing the EEG signals evoked by a three-grating stimulus with those evoked by its two components (the central grating and 2 flanking gratings). We focused on the earliest visual component C1 (onset latency of ∼50 ms) because it has been shown to reflect the feedforward responses of neurons in V1. We found that when the stimulus was unattended, the amplitude of the C1 evoked by the three-grating stimulus roughly equaled the sum of the amplitudes of the C1s evoked by its two components, regardless of the distances between these gratings. When the stimulus was attended, this linear spatial summation existed only when the three gratings were far apart from each other. When the three gratings were close to each other, the spatial summation became compressed. These results suggest that the earliest visual responses in V1 follow a linear summation rule when attention is not involved and that attention can affect the earliest interactions between multiple objects. Copyright © 2016 the American Physiological Society.

A framework for emissions source apportionment in industrial areas: MM5/CALPUFF in a near-field application.

PubMed

Ghannam, K; El-Fadel, M

2013-02-01

This paper examines the relative source contribution to ground-level concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), and PM10 (particulate matter with an aerodynamic diameter < 10 microm) in a coastal urban area due to emissions from an industrial complex with multiple stacks, quarrying activities, and a nearby highway. For this purpose, an inventory of CO, oxide of nitrogen (NO(x)), and PM10 emissions was coupled with the non-steady-state Mesoscale Model 5/California Puff Dispersion Modeling system to simulate individual source contributions under several spatial and temporal scales. As the contribution of a particular source to ground-level concentrations can be evaluated by simulating this single-source emissions or otherwise total emissions except that source, a set of emission sensitivity simulations was designed to examine if CALPUFF maintains a linear relationship between emission rates and predicted concentrations in cases where emitted plumes overlap and chemical transformations are simulated. Source apportionment revealed that ground-level releases (i.e., highway and quarries) extended over large areas dominated the contribution to exposure levels over elevated point sources, despite the fact that cumulative emissions from point sources are higher. Sensitivity analysis indicated that chemical transformations of NO(x) are insignificant, possibly due to short-range plume transport, with CALPUFF exhibiting a linear response to changes in emission rate. The current paper points to the significance of ground-level emissions in contributing to urban air pollution exposure and questions the viability of the prevailing paradigm of point-source emission reduction, especially that the incremental improvement in air quality associated with this common abatement strategy may not accomplish the desirable benefit in terms of lower exposure with costly emissions capping. The application of atmospheric dispersion models for source apportionment helps in identifying major contributors to regional air pollution. In industrial urban areas where multiple sources with different geometry contribute to emissions, ground-level releases extended over large areas such as roads and quarries often dominate the contribution to ground-level air pollution. Industrial emissions released at elevated stack heights may experience significant dilution, resulting in minor contribution to exposure at ground level. In such contexts, emission reduction, which is invariably the abatement strategy targeting industries at a significant investment in control equipment or process change, may result in minimal return on investment in terms of improvement in air quality at sensitive receptors.

Step-response of a torsional device with multiple discontinuous non-linearities: Formulation of a vibratory experiment

NASA Astrophysics Data System (ADS)

Krak, Michael D.; Dreyer, Jason T.; Singh, Rajendra

2016-03-01

A vehicle clutch damper is intentionally designed to contain multiple discontinuous non-linearities, such as multi-staged springs, clearances, pre-loads, and multi-staged friction elements. The main purpose of this practical torsional device is to transmit a wide range of torque while isolating torsional vibration between an engine and transmission. Improved understanding of the dynamic behavior of the device could be facilitated by laboratory measurement, and thus a refined vibratory experiment is proposed. The experiment is conceptually described as a single degree of freedom non-linear torsional system that is excited by an external step torque. The single torsional inertia (consisting of a shaft and torsion arm) is coupled to ground through parallel production clutch dampers, which are characterized by quasi-static measurements provided by the manufacturer. Other experimental objectives address physical dimensions, system actuation, flexural modes, instrumentation, and signal processing issues. Typical measurements show that the step response of the device is characterized by three distinct non-linear regimes (double-sided impact, single-sided impact, and no-impact). Each regime is directly related to the non-linear features of the device and can be described by peak angular acceleration values. Predictions of a simplified single degree of freedom non-linear model verify that the experiment performs well and as designed. Accordingly, the benchmark measurements could be utilized to validate non-linear models and simulation codes, as well as characterize dynamic parameters of the device including its dissipative properties.

A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation

PubMed Central

Nam, Haewon

2017-01-01

We propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which significantly degrades the image quality. To fill in the metal trace region efficiently, the proposed algorithm uses multiple prior images with residual error compensation in sinogram space. Multiple prior images are generated by applying a recursive active contour (RAC) segmentation algorithm to the pre-corrected image acquired by MAR with linear interpolation, where the number of prior image is controlled by RAC depending on the object complexity. A sinogram basis is then acquired by forward projection of the prior images. The metal trace region of the original sinogram is replaced by the linearly combined sinogram of the prior images. Then, the additional correction in the metal trace region is performed to compensate the residual errors occurred by non-ideal data acquisition condition. The performance of the proposed MAR algorithm is compared with MAR with linear interpolation and the normalized MAR algorithm using simulated and experimental data. The results show that the proposed algorithm outperforms other MAR algorithms, especially when the object is complex with multiple bone objects. PMID:28604794

Multiple degree of freedom object recognition using optical relational graph decision nets

NASA Technical Reports Server (NTRS)

Casasent, David P.; Lee, Andrew J.

1988-01-01

Multiple-degree-of-freedom object recognition concerns objects with no stable rest position with all scale, rotation, and aspect distortions possible. It is assumed that the objects are in a fairly benign background, so that feature extractors are usable. In-plane distortion invariance is provided by use of a polar-log coordinate transform feature space, and out-of-plane distortion invariance is provided by linear discriminant function design. Relational graph decision nets are considered for multiple-degree-of-freedom pattern recognition. The design of Fisher (1936) linear discriminant functions and synthetic discriminant function for use at the nodes of binary and multidecision nets is discussed. Case studies are detailed for two-class and multiclass problems. Simulation results demonstrate the robustness of the processors to quantization of the filter coefficients and to noise.

Correlation between serum 25-hydroxyvitamin D levels and carotid intima-media thickness in a Brazilian population descended from African slaves

PubMed Central

Monteiro, F.C.; Mandarino, N.R.; Santos, E.M.; Santos, A.M.; Salgado, J.V.; Brito, D.J.A.; Salgado, B.J.L.; Lages, J.S.; Castelo Branco, G.; Salgado, N.

2018-01-01

Hypovitaminosis D has been identified as a possible new cardiovascular risk factor. However, the results of studies correlating serum vitamin D levels with markers of subclinical atherosclerosis have been conflicting. The aim of this study was to correlate serum levels of 25-hydroxyvitamin D [25(OH)D] with carotid intima-media thickness (C-IMT) and conventional cardiovascular risk factors in Afro-descendants. A cross-sectional analysis was performed on a sample of 382 individuals from a cohort of descendants of African slaves, inhabitants of “Quilombola” communities, with a mean age of 57.79 ±15.3 years, 54.5% of whom were women. Socio-demographic and clinical data were collected and biochemical tests were performed, including serum levels of 25(OH)D by electrochemiluminescence and urinary albumin excretion, evaluated by the albumin/creatinine ratio (ACR) in a spot urine sample. All participants underwent high-resolution ultrasonography for C-IMT measurement. Hypovitaminosis D was defined as serum 25(OH)D levels <30 ng/mL. The mean serum 25(OH)D levels were 50.4±13.5 ng/mL, with a low prevalence of hypovitaminosis D (4.86%). By simple linear correlation, a significant inverse association between 25(OH)D levels and C-IMT (r=-0.174, P=0.001) was observed. However, after multiple linear regression analysis, the significance of the association between serum levels of 25(OH)D and C-IMT measurement was lost (β=-0.039, P=0.318) and only male gender, age, smoking, systolic blood pressure, glucose and low density lipoprotein (LDL)-cholesterol remained significantly associated with C-IMT. Levels of 25(OH)D were independently and positively associated with HDL-cholesterol and inversely associated with age and ACR. In conclusion, no independent association between 25(OH)D levels and C-IMT was observed in this population. On the other hand, there was an inverse association with albuminuria, a marker of endothelial lesion. PMID:29490002

Correlation between serum 25-hydroxyvitamin D levels and carotid intima-media thickness in a Brazilian population descended from African slaves.

PubMed

Monteiro Júnior, F C; Mandarino, N R; Santos, E M; Santos, A M; Salgado, J V; Brito, D J A; Salgado, B J L; Lages, J S; Castelo Branco, G; Salgado Filho, N

2018-01-01

Hypovitaminosis D has been identified as a possible new cardiovascular risk factor. However, the results of studies correlating serum vitamin D levels with markers of subclinical atherosclerosis have been conflicting. The aim of this study was to correlate serum levels of 25-hydroxyvitamin D [25(OH)D] with carotid intima-media thickness (C-IMT) and conventional cardiovascular risk factors in Afro-descendants. A cross-sectional analysis was performed on a sample of 382 individuals from a cohort of descendants of African slaves, inhabitants of "Quilombola" communities, with a mean age of 57.79 ±15.3 years, 54.5% of whom were women. Socio-demographic and clinical data were collected and biochemical tests were performed, including serum levels of 25(OH)D by electrochemiluminescence and urinary albumin excretion, evaluated by the albumin/creatinine ratio (ACR) in a spot urine sample. All participants underwent high-resolution ultrasonography for C-IMT measurement. Hypovitaminosis D was defined as serum 25(OH)D levels <30 ng/mL. The mean serum 25(OH)D levels were 50.4±13.5 ng/mL, with a low prevalence of hypovitaminosis D (4.86%). By simple linear correlation, a significant inverse association between 25(OH)D levels and C-IMT (r=-0.174, P=0.001) was observed. However, after multiple linear regression analysis, the significance of the association between serum levels of 25(OH)D and C-IMT measurement was lost (β=-0.039, P=0.318) and only male gender, age, smoking, systolic blood pressure, glucose and low density lipoprotein (LDL)-cholesterol remained significantly associated with C-IMT. Levels of 25(OH)D were independently and positively associated with HDL-cholesterol and inversely associated with age and ACR. In conclusion, no independent association between 25(OH)D levels and C-IMT was observed in this population. On the other hand, there was an inverse association with albuminuria, a marker of endothelial lesion.

Moving from Descriptive to Causal Analytics: Case Study of the Health Indicators Warehouse

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

Schryver, Jack C.; Shankar, Mallikarjun; Xu, Songhua

The KDD community has described a multitude of methods for knowledge discovery on large datasets. We consider some of these methods and integrate them into an analyst s workflow that proceeds from the data-centric descriptive level to the model-centric causal level. Examples of the workflow are shown for the Health Indicators Warehouse, which is a public database for community health information that is a potent resource for conducting data science on a medium scale. We demonstrate the potential of HIW as a source of serious visual analytics efforts by showing correlation matrix visualizations, multivariate outlier analysis, multiple linear regression ofmore » Medicare costs, and scatterplot matrices for a broad set of health indicators. We conclude by sketching the first steps toward a causal dependence hypothesis.« less