PconsFold: improved contact predictions improve protein models.

PubMed

Michel, Mirco; Hayat, Sikander; Skwark, Marcin J; Sander, Chris; Marks, Debora S; Elofsson, Arne

2014-09-01

Recently it has been shown that the quality of protein contact prediction from evolutionary information can be improved significantly if direct and indirect information is separated. Given sufficiently large protein families, the contact predictions contain sufficient information to predict the structure of many protein families. However, since the first studies contact prediction methods have improved. Here, we ask how much the final models are improved if improved contact predictions are used. In a small benchmark of 15 proteins, we show that the TM-scores of top-ranked models are improved by on average 33% using PconsFold compared with the original version of EVfold. In a larger benchmark, we find that the quality is improved with 15-30% when using PconsC in comparison with earlier contact prediction methods. Further, using Rosetta instead of CNS does not significantly improve global model accuracy, but the chemistry of models generated with Rosetta is improved. PconsFold is a fully automated pipeline for ab initio protein structure prediction based on evolutionary information. PconsFold is based on PconsC contact prediction and uses the Rosetta folding protocol. Due to its modularity, the contact prediction tool can be easily exchanged. The source code of PconsFold is available on GitHub at https://www.github.com/ElofssonLab/pcons-fold under the MIT license. PconsC is available from http://c.pcons.net/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Middle-School Science Students' Scientific Modelling Performances Across Content Areas and Within a Learning Progression

NASA Astrophysics Data System (ADS)

Bamberger, Yael M.; Davis, Elizabeth A.

2013-01-01

This paper focuses on students' ability to transfer modelling performances across content areas, taking into consideration their improvement of content knowledge as a result of a model-based instruction. Sixty-five sixth grade students of one science teacher in an urban public school in the Midwestern USA engaged in scientific modelling practices that were incorporated into a curriculum focused on the nature of matter. Concept-process models were embedded in the curriculum, as well as emphasis on meta-modelling knowledge and modelling practices. Pre-post test items that required drawing scientific models of smell, evaporation, and friction were analysed. The level of content understanding was coded and scored, as were the following elements of modelling performance: explanation, comparativeness, abstraction, and labelling. Paired t-tests were conducted to analyse differences in students' pre-post tests scores on content knowledge and on each element of the modelling performances. These are described in terms of the amount of transfer. Students significantly improved in their content knowledge for the smell and the evaporation models, but not for the friction model, which was expected as that topic was not taught during the instruction. However, students significantly improved in some of their modelling performances for all the three models. This improvement serves as evidence that the model-based instruction can help students acquire modelling practices that they can apply in a new content area.

Evaluation of airborne lidar data to predict vegetation Presence/Absence

USGS Publications Warehouse

Palaseanu-Lovejoy, M.; Nayegandhi, A.; Brock, J.; Woodman, R.; Wright, C.W.

2009-01-01

This study evaluates the capabilities of the Experimental Advanced Airborne Research Lidar (EAARL) in delineating vegetation assemblages in Jean Lafitte National Park, Louisiana. Five-meter-resolution grids of bare earth, canopy height, canopy-reflection ratio, and height of median energy were derived from EAARL data acquired in September 2006. Ground-truth data were collected along transects to assess species composition, canopy cover, and ground cover. To decide which model is more accurate, comparisons of general linear models and generalized additive models were conducted using conventional evaluation methods (i.e., sensitivity, specificity, Kappa statistics, and area under the curve) and two new indexes, net reclassification improvement and integrated discrimination improvement. Generalized additive models were superior to general linear models in modeling presence/absence in training vegetation categories, but no statistically significant differences between the two models were achieved in determining the classification accuracy at validation locations using conventional evaluation methods, although statistically significant improvements in net reclassifications were observed. ?? 2009 Coastal Education and Research Foundation.

Human Neural Stem Cell Extracellular Vesicles Improve Recovery in a Porcine Model of Ischemic Stroke

PubMed Central

Webb, Robin L.; Kaiser, Erin E.; Jurgielewicz, Brian J.; Spellicy, Samantha; Scoville, Shelley L.; Thompson, Tyler A.; Swetenburg, Raymond L.; Hess, David C.; West, Franklin D.

2018-01-01

Background and Purpose— Recent work from our group suggests that human neural stem cell–derived extracellular vesicle (NSC EV) treatment improves both tissue and sensorimotor function in a preclinical thromboembolic mouse model of stroke. In this study, NSC EVs were evaluated in a pig ischemic stroke model, where clinically relevant end points were used to assess recovery in a more translational large animal model. Methods— Ischemic stroke was induced by permanent middle cerebral artery occlusion (MCAO), and either NSC EV or PBS treatment was administered intravenously at 2, 14, and 24 hours post-MCAO. NSC EV effects on tissue level recovery were evaluated via magnetic resonance imaging at 1 and 84 days post-MCAO. Effects on functional recovery were also assessed through longitudinal behavior and gait analysis testing. Results— NSC EV treatment was neuroprotective and led to significant improvements at the tissue and functional levels in stroked pigs. NSC EV treatment eliminated intracranial hemorrhage in ischemic lesions in NSC EV pigs (0 of 7) versus control pigs (7 of 8). NSC EV–treated pigs exhibited a significant decrease in cerebral lesion volume and decreased brain swelling relative to control pigs 1-day post-MCAO. NSC EVs significantly reduced edema in treated pigs relative to control pigs, as assessed by improved diffusivity through apparent diffusion coefficient maps. NSC EVs preserved white matter integrity with increased corpus callosum fractional anisotropy values 84 days post-MCAO. Behavior and mobility improvements paralleled structural changes as NSC EV–treated pigs exhibited improved outcomes, including increased exploratory behavior and faster restoration of spatiotemporal gait parameters. Conclusions— This study demonstrated for the first time that in a large animal model novel NSC EVs significantly improved neural tissue preservation and functional levels post-MCAO, suggesting NSC EVs may be a paradigm changing stroke therapeutic. PMID:29650593

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

NASA Astrophysics Data System (ADS)

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K.; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from 50 {× } 5 -fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of r=0.90 and r=0.93 . As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from r=0.51 to r=0.87 respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

NASA Astrophysics Data System (ADS)

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K.; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger ( AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients ( r) from 50 {× } 5-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of r=0.90 and r=0.93. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from r=0.51 to r=0.87 respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity.

PubMed

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from [Formula: see text]-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of [Formula: see text] and [Formula: see text]. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from [Formula: see text] to [Formula: see text] respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Advanced Hydrogen Liquefaction Process

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

Schwartz, Joseph; Kromer, Brian; Neu, Ben

2011-09-28

The project identified and quantified ways to reduce the cost of hydrogen liquefaction, and reduce the cost of hydrogen distribution. The goal was to reduce the power consumption by 20% and then to reduce the capital cost. Optimizing the process, improving process equipment, and improving ortho-para conversion significantly reduced the power consumption of liquefaction, but by less than 20%. Because the efficiency improvement was less than the target, the program was stopped before the capital cost was addressed. These efficiency improvements could provide a benefit to the public to improve the design of future hydrogen liquefiers. The project increased themore » understanding of hydrogen liquefaction by modeling different processes and thoroughly examining ortho-para separation and conversion. The process modeling provided a benefit to the public because the project incorporated para hydrogen into the process modeling software, so liquefaction processes can be modeled more accurately than using only normal hydrogen. Adding catalyst to the first heat exchanger, a simple method to reduce liquefaction power, was identified, analyzed, and quantified. The demonstrated performance of ortho-para separation is sufficient for at least one identified process concept to show reduced power cost when compared to hydrogen liquefaction processes using conventional ortho-para conversion. The impact of improved ortho-para conversion can be significant because ortho para conversion uses about 20-25% of the total liquefaction power, but performance improvement is necessary to realize a substantial benefit. Most of the energy used in liquefaction is for gas compression. Improvements in hydrogen compression will have a significant impact on overall liquefier efficiency. Improvements to turbines, heat exchangers, and other process equipment will have less impact.« less

Dynamic one-dimensional modeling of secondary settling tanks and design impacts of sizing decisions.

PubMed

Li, Ben; Stenstrom, Michael K

2014-03-01

As one of the most significant components in the activated sludge process (ASP), secondary settling tanks (SSTs) can be investigated with mathematical models to optimize design and operation. This paper takes a new look at the one-dimensional (1-D) SST model by analyzing and considering the impacts of numerical problems, especially the process robustness. An improved SST model with Yee-Roe-Davis technique as the PDE solver is proposed and compared with the widely used Takács model to show its improvement in numerical solution quality. The improved and Takács models are coupled with a bioreactor model to reevaluate ASP design basis and several popular control strategies for economic plausibility, contaminant removal efficiency and system robustness. The time-to-failure due to rising sludge blanket during overloading, as a key robustness indicator, is analyzed to demonstrate the differences caused by numerical issues in SST models. The calculated results indicate that the Takács model significantly underestimates time to failure, thus leading to a conservative design. Copyright © 2013 Elsevier Ltd. All rights reserved.

An approximate model for cancellous bone screw fixation.

PubMed

Brown, C J; Sinclair, R A; Day, A; Hess, B; Procter, P

2013-04-01

This paper presents a finite element (FE) model to identify parameters that affect the performance of an improved cancellous bone screw fixation technique, and hence potentially improve fracture treatment. In cancellous bone of low apparent density, it can be difficult to achieve adequate screw fixation and hence provide stable fracture fixation that enables bone healing. Data from predictive FE models indicate that cements can have a significant potential to improve screw holding power in cancellous bone. These FE models are used to demonstrate the key parameters that determine pull-out strength in a variety of screw, bone and cement set-ups, and to compare the effectiveness of different configurations. The paper concludes that significant advantages, up to an order of magnitude, in screw pull-out strength in cancellous bone might be gained by the appropriate use of a currently approved calcium phosphate cement.

Role of socioeconomic status measures in long-term mortality risk prediction after myocardial infarction.

PubMed

Molshatzki, Noa; Drory, Yaacov; Myers, Vicki; Goldbourt, Uri; Benyamini, Yael; Steinberg, David M; Gerber, Yariv

2011-07-01

The relationship of risk factors to outcomes has traditionally been assessed by measures of association such as odds ratio or hazard ratio and their statistical significance from an adjusted model. However, a strong, highly significant association does not guarantee a gain in stratification capacity. Using recently developed model performance indices, we evaluated the incremental discriminatory power of individual and neighborhood socioeconomic status (SES) measures after myocardial infarction (MI). Consecutive patients aged ≤65 years (N=1178) discharged from 8 hospitals in central Israel after incident MI in 1992 to 1993 were followed-up through 2005. A basic model (demographic variables, traditional cardiovascular risk factors, and disease severity indicators) was compared with an extended model including SES measures (education, income, employment, living with a steady partner, and neighborhood SES) in terms of Harrell c statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). During the 13-year follow-up, 326 (28%) patients died. Cox proportional hazards models showed that all SES measures were significantly and independently associated with mortality. Furthermore, compared with the basic model, the extended model yielded substantial gains (all P<0.001) in c statistic (0.723 to 0.757), NRI (15.2%), IDI (5.9%), and relative IDI (32%). Improvement was observed both for sensitivity (classification of events) and specificity (classification of nonevents). This study illustrates the additional insights that can be gained from considering the IDI and NRI measures of model performance and suggests that, among community patients with incident MI, incorporating SES measures into a clinical-based model substantially improves long-term mortality risk prediction.

Dynamic physiological modeling for functional diffuse optical tomography

PubMed Central

Diamond, Solomon Gilbert; Huppert, Theodore J.; Kolehmainen, Ville; Franceschini, Maria Angela; Kaipio, Jari P.; Arridge, Simon R.; Boas, David A.

2009-01-01

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n = 10, P < 0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis. PMID:16242967

A conceptual model to empower software requirements conflict detection and resolution with rule-based reasoning

NASA Astrophysics Data System (ADS)

Ahmad, Sabrina; Jalil, Intan Ermahani A.; Ahmad, Sharifah Sakinah Syed

2016-08-01

It is seldom technical issues which impede the process of eliciting software requirements. The involvement of multiple stakeholders usually leads to conflicts and therefore the need of conflict detection and resolution effort is crucial. This paper presents a conceptual model to further improve current efforts. Hence, this paper forwards an improved conceptual model to assist the conflict detection and resolution effort which extends the model ability and improves overall performance. The significant of the new model is to empower the automation of conflicts detection and its severity level with rule-based reasoning.

Sivelestat sodium hydrate improves post-traumatic knee osteoarthritis through nuclear factor-κB in a rat model.

PubMed

Yu, Xiaofeng; Zhao, Lijun; Yu, Zhiping; Yu, Changzheng; Bi, Jianfei; Sun, Binglong; Cong, Haibo

2017-08-01

As a specific inhibitor of neutrophil elastase, sivelestat sodium hydrate has primarily been used in the treatment of acute lung injury caused by various factors since its approval in 2002. Sivelestat sodium hydrate also improves post-traumatic knee osteoarthritis (KOA), although its underlying mechanisms of action have yet to be elucidated. The aim of the current study was to determine if sivelestat sodium hydrate improves post-traumatic KOA through nuclear factor (NF)-κB in a rat model. Treatment with sivelestat sodium hydrate significantly inhibited the induction of structural changes and significantly increased the vertical episode count and ipsilateral static weight bearing of the joint in KOA rats (all P<0.01). Sivelestat sodium hydrate significantly inhibited tumor necrosis factor-α and interleukin-6 production, serum nitrite levels, inducible nitric oxide synthase protein expression and high mobility group box 1 (HMGB1) secretion in KOA rats compared with the model group (all P<0.01). Sivelestat sodium hydrate also significantly suppressed p50/p65 DNA binding activity and NF-κB and phosphorylated inhibitor of κB protein expression in the joints of KOA rats compared with the model group (all P<0.01). These results suggest that sivelestat sodium hydrate improves post-traumatic KOA through HMGB1 and NF-κB in rats.

Sivelestat sodium hydrate improves post-traumatic knee osteoarthritis through nuclear factor-κB in a rat model

PubMed Central

Yu, Xiaofeng; Zhao, Lijun; Yu, Zhiping; Yu, Changzheng; Bi, Jianfei; Sun, Binglong; Cong, Haibo

2017-01-01

As a specific inhibitor of neutrophil elastase, sivelestat sodium hydrate has primarily been used in the treatment of acute lung injury caused by various factors since its approval in 2002. Sivelestat sodium hydrate also improves post-traumatic knee osteoarthritis (KOA), although its underlying mechanisms of action have yet to be elucidated. The aim of the current study was to determine if sivelestat sodium hydrate improves post-traumatic KOA through nuclear factor (NF)-κB in a rat model. Treatment with sivelestat sodium hydrate significantly inhibited the induction of structural changes and significantly increased the vertical episode count and ipsilateral static weight bearing of the joint in KOA rats (all P<0.01). Sivelestat sodium hydrate significantly inhibited tumor necrosis factor-α and interleukin-6 production, serum nitrite levels, inducible nitric oxide synthase protein expression and high mobility group box 1 (HMGB1) secretion in KOA rats compared with the model group (all P<0.01). Sivelestat sodium hydrate also significantly suppressed p50/p65 DNA binding activity and NF-κB and phosphorylated inhibitor of κB protein expression in the joints of KOA rats compared with the model group (all P<0.01). These results suggest that sivelestat sodium hydrate improves post-traumatic KOA through HMGB1 and NF-κB in rats. PMID:28810618

Constructing an adaptive care model for the management of disease-related symptoms throughout the course of multiple sclerosis--performance improvement CME.

PubMed

Miller, Aaron E; Cohen, Bruce A; Krieger, Stephen C; Markowitz, Clyde E; Mattson, David H; Tselentis, Helen N

2014-01-01

Symptom management remains a challenging clinical aspect of MS. To design a performance improvement continuing medical education (PI CME) activity for better clinical management of multiple sclerosis (MS)-related depression, fatigue, mobility impairment/falls, and spasticity. Ten volunteer MS centers participated in a three-stage PI CME model: A) baseline assessment; B) practice improvement CME intervention; C) reassessment. Expert faculty developed performance measures and activity intervention tools. Designated MS center champions reviewed patient charts and entered data into an online database. Stage C data were collected eight weeks after implementation of the intervention and compared with Stage A baseline data to measure change in performance. Aggregate data from the 10 participating MS centers (405 patient charts) revealed performance improvements in the assessment of all four MS-related symptoms. Statistically significant improvements were found in the documented assessment of mobility impairment/falls (p=0.003) and spasticity (p<0.001). For documentation of care plans, statistically significant improvements were reported for fatigue (p=0.007) and mobility impairment/falls (p=0.040); non-significant changes were noted for depression and spasticity. Our PI CME interventions demonstrated performance improvement in the management of MS-related symptoms. This PI CME model (available at www.achlpicme.org/ms/toolkit) offers a new perspective on enhancing symptom management in patients with MS.

Follow on Research for Multi-Utility Technology Test Bed Aircraft at NASA Dryden Flight Research Center (FY13 Progress Report)

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2013-01-01

Modern aircraft employ a significant fraction of their weight in composite materials to reduce weight and improve performance. Aircraft aeroservoelastic models are typically characterized by significant levels of model parameter uncertainty due to the composite manufacturing process. Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of Multi Utility Technology Test-bed (MUTT) aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of MUTT aircraft. The ground vibration test-validated structural dynamic finite element model of the MUTT aircraft is created in this study. The structural dynamic finite element model of MUTT aircraft is improved using the in-house Multi-disciplinary Design, Analysis, and Optimization tool. In this study, two different weight configurations of MUTT aircraft have been improved simultaneously in a single model tuning procedure.

Aerothermal modeling. Executive summary

NASA Technical Reports Server (NTRS)

Kenworthy, M. K.; Correa, S. M.; Burrus, D. L.

1983-01-01

One of the significant ways in which the performance level of aircraft turbine engines has been improved is by the use of advanced materials and cooling concepts that allow a significant increase in turbine inlet temperature level, with attendant thermodynamic cycle benefits. Further cycle improvements have been achieved with higher pressure ratio compressors. The higher turbine inlet temperatures and compressor pressure ratios with corresponding higher temperature cooling air has created a very hostile environment for the hot section components. To provide the technology needed to reduce the hot section maintenance costs, NASA has initiated the Hot Section Technology (HOST) program. One key element of this overall program is the Aerothermal Modeling Program. The overall objective of his program is to evolve and validate improved analysis methods for use in the design of aircraft turbine engine combustors. The use of such combustor analysis capabilities can be expected to provide significant improvement in the life and durability characteristics of both combustor and turbine components.

Remotely-sensed, nocturnal, dew point correlates with malaria transmission in Southern Province, Zambia: a time-series study

PubMed Central

2014-01-01

Background Plasmodium falciparum transmission has decreased significantly in Zambia in the last decade. The malaria transmission is influenced by environmental variables. Incorporation of environmental variables in models of malaria transmission likely improves model fit and predicts probable trends in malaria disease. This work is based on the hypothesis that remotely-sensed environmental factors, including nocturnal dew point, are associated with malaria transmission and sustain foci of transmission during the low transmission season in the Southern Province of Zambia. Methods Thirty-eight rural health centres in Southern Province, Zambia were divided into three zones based on transmission patterns. Correlations between weekly malaria cases and remotely-sensed nocturnal dew point, nocturnal land surface temperature as well as vegetation indices and rainfall were evaluated in time-series analyses from 2012 week 19 to 2013 week 36. Zonal as well as clinic-based, multivariate, autoregressive, integrated, moving average (ARIMAX) models implementing environmental variables were developed to model transmission in 2011 week 19 to 2012 week 18 and forecast transmission in 2013 week 37 to week 41. Results During the dry, low transmission season significantly higher vegetation indices, nocturnal land surface temperature and nocturnal dew point were associated with the areas of higher transmission. Environmental variables improved ARIMAX models. Dew point and normalized differentiated vegetation index were significant predictors and improved all zonal transmission models. In the high-transmission zone, this was also seen for land surface temperature. Clinic models were improved by adding dew point and land surface temperature as well as normalized differentiated vegetation index. The mean average error of prediction for ARIMAX models ranged from 0.7 to 33.5%. Forecasts of malaria incidence were valid for three out of five rural health centres; however, with poor results at the zonal level. Conclusions In this study, the fit of ARIMAX models improves when environmental variables are included. There is a significant association of remotely-sensed nocturnal dew point with malaria transmission. Interestingly, dew point might be one of the factors sustaining malaria transmission in areas of general aridity during the dry season. PMID:24927747

Remotely-sensed, nocturnal, dew point correlates with malaria transmission in Southern Province, Zambia: a time-series study.

PubMed

Nygren, David; Stoyanov, Cristina; Lewold, Clemens; Månsson, Fredrik; Miller, John; Kamanga, Aniset; Shiff, Clive J

2014-06-13

Plasmodium falciparum transmission has decreased significantly in Zambia in the last decade. The malaria transmission is influenced by environmental variables. Incorporation of environmental variables in models of malaria transmission likely improves model fit and predicts probable trends in malaria disease. This work is based on the hypothesis that remotely-sensed environmental factors, including nocturnal dew point, are associated with malaria transmission and sustain foci of transmission during the low transmission season in the Southern Province of Zambia. Thirty-eight rural health centres in Southern Province, Zambia were divided into three zones based on transmission patterns. Correlations between weekly malaria cases and remotely-sensed nocturnal dew point, nocturnal land surface temperature as well as vegetation indices and rainfall were evaluated in time-series analyses from 2012 week 19 to 2013 week 36. Zonal as well as clinic-based, multivariate, autoregressive, integrated, moving average (ARIMAX) models implementing environmental variables were developed to model transmission in 2011 week 19 to 2012 week 18 and forecast transmission in 2013 week 37 to week 41. During the dry, low transmission season significantly higher vegetation indices, nocturnal land surface temperature and nocturnal dew point were associated with the areas of higher transmission. Environmental variables improved ARIMAX models. Dew point and normalized differentiated vegetation index were significant predictors and improved all zonal transmission models. In the high-transmission zone, this was also seen for land surface temperature. Clinic models were improved by adding dew point and land surface temperature as well as normalized differentiated vegetation index. The mean average error of prediction for ARIMAX models ranged from 0.7 to 33.5%. Forecasts of malaria incidence were valid for three out of five rural health centres; however, with poor results at the zonal level. In this study, the fit of ARIMAX models improves when environmental variables are included. There is a significant association of remotely-sensed nocturnal dew point with malaria transmission. Interestingly, dew point might be one of the factors sustaining malaria transmission in areas of general aridity during the dry season.

Do treatment improvements in PTSD severity affect substance use outcomes? A secondary analysis from a randomized clinical trial in NIDA's Clinical Trials Network.

PubMed

Hien, Denise A; Jiang, Huiping; Campbell, Aimee N C; Hu, Mei-Chen; Miele, Gloria M; Cohen, Lisa R; Brigham, Gregory S; Capstick, Carrie; Kulaga, Agatha; Robinson, James; Suarez-Morales, Lourdes; Nunes, Edward V

2010-01-01

The purpose of the analysis was to examine the temporal course of improvement in symptoms of posttraumatic stress disorder (PTSD) and substance use disorder among women in outpatient substance abuse treatment. Participants were 353 women randomly assigned to 12 sessions of either trauma-focused or health education group treatment. PTSD and substance use assessments were conducted during treatment and posttreatment at 1 week and after 3, 6, and 12 months. A continuous Markov model was fit on four defined response categories (nonresponse, substance use response, PTSD response, or global response [improvement in both PTSD and substance use]) to investigate the temporal association between improvement in PTSD and substance use symptom severity during the study's treatment phase. A generalized linear model was applied to test this relationship over the follow-up period. Subjects exhibiting nonresponse, substance use response, or global response tended to maintain original classification; subjects exhibiting PTSD response were significantly more likely to transition to global response over time, indicating maintained PTSD improvement was associated with subsequent substance use improvement. Trauma-focused treatment was significantly more effective than health education in achieving substance use improvement, but only among those who were heavy substance users at baseline and had achieved significant PTSD reductions. PTSD severity reductions were more likely to be associated with substance use improvement, with minimal evidence of substance use symptom reduction improving PTSD symptoms. Results support the self-medication model of coping with PTSD symptoms and an empirical basis for integrated interventions for improved substance use outcomes in patients with severe symptoms.

Diagnosing the impact of alternative calibration strategies on coupled hydrologic models

NASA Astrophysics Data System (ADS)

Smith, T. J.; Perera, C.; Corrigan, C.

2017-12-01

Hydrologic models represent a significant tool for understanding, predicting, and responding to the impacts of water on society and society on water resources and, as such, are used extensively in water resources planning and management. Given this important role, the validity and fidelity of hydrologic models is imperative. While extensive focus has been paid to improving hydrologic models through better process representation, better parameter estimation, and better uncertainty quantification, significant challenges remain. In this study, we explore a number of competing model calibration scenarios for simple, coupled snowmelt-runoff models to better understand the sensitivity / variability of parameterizations and its impact on model performance, robustness, fidelity, and transferability. Our analysis highlights the sensitivity of coupled snowmelt-runoff model parameterizations to alterations in calibration approach, underscores the concept of information content in hydrologic modeling, and provides insight into potential strategies for improving model robustness / fidelity.

Filtering data from the collaborative initial glaucoma treatment study for improved identification of glaucoma progression.

PubMed

Schell, Greggory J; Lavieri, Mariel S; Stein, Joshua D; Musch, David C

2013-12-21

Open-angle glaucoma (OAG) is a prevalent, degenerate ocular disease which can lead to blindness without proper clinical management. The tests used to assess disease progression are susceptible to process and measurement noise. The aim of this study was to develop a methodology which accounts for the inherent noise in the data and improve significant disease progression identification. Longitudinal observations from the Collaborative Initial Glaucoma Treatment Study (CIGTS) were used to parameterize and validate a Kalman filter model and logistic regression function. The Kalman filter estimates the true value of biomarkers associated with OAG and forecasts future values of these variables. We develop two logistic regression models via generalized estimating equations (GEE) for calculating the probability of experiencing significant OAG progression: one model based on the raw measurements from CIGTS and another model based on the Kalman filter estimates of the CIGTS data. Receiver operating characteristic (ROC) curves and associated area under the ROC curve (AUC) estimates are calculated using cross-fold validation. The logistic regression model developed using Kalman filter estimates as data input achieves higher sensitivity and specificity than the model developed using raw measurements. The mean AUC for the Kalman filter-based model is 0.961 while the mean AUC for the raw measurements model is 0.889. Hence, using the probability function generated via Kalman filter estimates and GEE for logistic regression, we are able to more accurately classify patients and instances as experiencing significant OAG progression. A Kalman filter approach for estimating the true value of OAG biomarkers resulted in data input which improved the accuracy of a logistic regression classification model compared to a model using raw measurements as input. This methodology accounts for process and measurement noise to enable improved discrimination between progression and nonprogression in chronic diseases.

Bayesian logistic regression approaches to predict incorrect DRG assignment.

PubMed

Suleiman, Mani; Demirhan, Haydar; Boyd, Leanne; Girosi, Federico; Aksakalli, Vural

2018-05-07

Episodes of care involving similar diagnoses and treatments and requiring similar levels of resource utilisation are grouped to the same Diagnosis-Related Group (DRG). In jurisdictions which implement DRG based payment systems, DRGs are a major determinant of funding for inpatient care. Hence, service providers often dedicate auditing staff to the task of checking that episodes have been coded to the correct DRG. The use of statistical models to estimate an episode's probability of DRG error can significantly improve the efficiency of clinical coding audits. This study implements Bayesian logistic regression models with weakly informative prior distributions to estimate the likelihood that episodes require a DRG revision, comparing these models with each other and to classical maximum likelihood estimates. All Bayesian approaches had more stable model parameters than maximum likelihood. The best performing Bayesian model improved overall classification per- formance by 6% compared to maximum likelihood, with a 34% gain compared to random classification, respectively. We found that the original DRG, coder and the day of coding all have a significant effect on the likelihood of DRG error. Use of Bayesian approaches has improved model parameter stability and classification accuracy. This method has already lead to improved audit efficiency in an operational capacity.

Thirty Years of Improving the NCEP Global Forecast System

NASA Astrophysics Data System (ADS)

White, G. H.; Manikin, G.; Yang, F.

2014-12-01

Current eight day forecasts by the NCEP Global Forecast System are as accurate as five day forecasts 30 years ago. This revolution in weather forecasting reflects increases in computer power, improvements in the assimilation of observations, especially satellite data, improvements in model physics, improvements in observations and international cooperation and competition. One important component has been and is the diagnosis, evaluation and reduction of systematic errors. The effect of proposed improvements in the GFS on systematic errors is one component of the thorough testing of such improvements by the Global Climate and Weather Modeling Branch. Examples of reductions in systematic errors in zonal mean temperatures and winds and other fields will be presented. One challenge in evaluating systematic errors is uncertainty in what reality is. Model initial states can be regarded as the best overall depiction of the atmosphere, but can be misleading in areas of few observations or for fields not well observed such as humidity or precipitation over the oceans. Verification of model physics is particularly difficult. The Environmental Modeling Center emphasizes the evaluation of systematic biases against observations. Recently EMC has placed greater emphasis on synoptic evaluation and on precipitation, 2-meter temperatures and dew points and 10 meter winds. A weekly EMC map discussion reviews the performance of many models over the United States and has helped diagnose and alleviate significant systematic errors in the GFS, including a near surface summertime evening cold wet bias over the eastern US and a multi-week period when the GFS persistently developed bogus tropical storms off Central America. The GFS exhibits a wet bias for light rain and a dry bias for moderate to heavy rain over the continental United States. Significant changes to the GFS are scheduled to be implemented in the fall of 2014. These include higher resolution, improved physics and improvements to the assimilation. These changes significantly improve the tropospheric flow and reduce a tropical upper tropospheric warm bias. One important error remaining is the failure of the GFS to maintain deep convection over Indonesia and in the tropical west Pacific. This and other current systematic errors will be presented.

Systematic Review of Programs Treating High-Need and High-Cost People With Multiple Chronic Diseases or Disabilities in the United States, 2008–2014

PubMed Central

Bleich, Sara N.; Sherrod, Cheryl; Chiang, Anne; Boyd, Cynthia; Wolff, Jennifer; DuGoff, Eva; Salzberg, Claudia; Anderson, Keely; Leff, Bruce

2015-01-01

Introduction Finding ways to provide better and less expensive health care for people with multiple chronic conditions or disability is a pressing concern. The purpose of this systematic review was to evaluate different approaches for caring for this high-need and high-cost population. Methods We searched Medline for articles published from May 31, 2008, through June 10, 2014, for relevant studies. Articles were considered eligible for this review if they met the following criteria: included people with multiple chronic conditions (behavioral or mental health) or disabilities (2 or more); addressed 1 or more of clinical outcomes, health care use and spending, or patient satisfaction; and compared results from an intervention group with a comparison group or baseline measurements. We extracted information on program characteristics, participant characteristics, and significant (positive and negative) clinical findings, patient satisfaction, and health care use outcomes. For each outcome, the number of significant and positive results was tabulated. Results Twenty-seven studies were included across 5 models of care. Of the 3 studies reporting patient satisfaction outcomes, 2 reported significant improvements; both were randomized controlled trials (RCTs). Of the 14 studies reporting clinical outcomes, 12 reported improvements (8 were RCTs). Of the 13 studies reporting health care use and spending outcomes, 12 reported significant improvements (2 were RCTs). Two models of care — care and case management and disease management — reported improvements in all 3 outcomes. For care and case management models, most improvements were related to health care use. For the disease management models, most improvements were related to clinical outcomes. Conclusions Care and case management as well as disease management may be promising models of care for people with multiple chronic conditions or disabilities. More research and consistent methods are needed to understand the most appropriate care for these high-need and high-cost patients. PMID:26564013

Systematic Review of Programs Treating High-Need and High-Cost People With Multiple Chronic Diseases or Disabilities in the United States, 2008-2014.

PubMed

Bleich, Sara N; Sherrod, Cheryl; Chiang, Anne; Boyd, Cynthia; Wolff, Jennifer; DuGoff, Eva; Chang, Eva; Salzberg, Claudia; Anderson, Keely; Leff, Bruce; Anderson, Gerard

2015-11-12

Finding ways to provide better and less expensive health care for people with multiple chronic conditions or disability is a pressing concern. The purpose of this systematic review was to evaluate different approaches for caring for this high-need and high-cost population. We searched Medline for articles published from May 31, 2008, through June 10, 2014, for relevant studies. Articles were considered eligible for this review if they met the following criteria: included people with multiple chronic conditions (behavioral or mental health) or disabilities (2 or more); addressed 1 or more of clinical outcomes, health care use and spending, or patient satisfaction; and compared results from an intervention group with a comparison group or baseline measurements. We extracted information on program characteristics, participant characteristics, and significant (positive and negative) clinical findings, patient satisfaction, and health care use outcomes. For each outcome, the number of significant and positive results was tabulated. Twenty-seven studies were included across 5 models of care. Of the 3 studies reporting patient satisfaction outcomes, 2 reported significant improvements; both were randomized controlled trials (RCTs). Of the 14 studies reporting clinical outcomes, 12 reported improvements (8 were RCTs). Of the 13 studies reporting health care use and spending outcomes, 12 reported significant improvements (2 were RCTs). Two models of care - care and case management and disease management - reported improvements in all 3 outcomes. For care and case management models, most improvements were related to health care use. For the disease management models, most improvements were related to clinical outcomes. Care and case management as well as disease management may be promising models of care for people with multiple chronic conditions or disabilities. More research and consistent methods are needed to understand the most appropriate care for these high-need and high-cost patients.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2004-12-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2005-01-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Galantamine improves olfactory learning in the Ts65Dn mouse model of Down syndrome

PubMed Central

Simoes de Souza, Fabio M.; Busquet, Nicolas; Blatner, Megan; Maclean, Kenneth N.; Restrepo, Diego

2011-01-01

Down syndrome (DS) is the most common form of congenital intellectual disability. Although DS involves multiple disturbances in various tissues, there is little doubt that in terms of quality of life cognitive impairment is the most serious facet and there is no effective treatment for this aspect of the syndrome. The Ts65Dn mouse model of DS recapitulates multiple aspects of DS including cognitive impairment. Here the Ts65Dn mouse model of DS was evaluated in an associative learning paradigm based on olfactory cues. In contrast to disomic controls, trisomic mice exhibited significant deficits in olfactory learning. Treatment of trisomic mice with the acetylcholinesterase inhibitor galantamine resulted in a significant improvement in olfactory learning. Collectively, our study indicates that olfactory learning can be a sensitive tool for evaluating deficits in associative learning in mouse models of DS and that galantamine has therapeutic potential for improving cognitive abilities. PMID:22355654

Galantamine improves olfactory learning in the Ts65Dn mouse model of Down syndrome.

PubMed

de Souza, Fabio M Simoes; Busquet, Nicolas; Blatner, Megan; Maclean, Kenneth N; Restrepo, Diego

2011-01-01

Down syndrome (DS) is the most common form of congenital intellectual disability. Although DS involves multiple disturbances in various tissues, there is little doubt that in terms of quality of life cognitive impairment is the most serious facet and there is no effective treatment for this aspect of the syndrome. The Ts65Dn mouse model of DS recapitulates multiple aspects of DS including cognitive impairment. Here the Ts65Dn mouse model of DS was evaluated in an associative learning paradigm based on olfactory cues. In contrast to disomic controls, trisomic mice exhibited significant deficits in olfactory learning. Treatment of trisomic mice with the acetylcholinesterase inhibitor galantamine resulted in a significant improvement in olfactory learning. Collectively, our study indicates that olfactory learning can be a sensitive tool for evaluating deficits in associative learning in mouse models of DS and that galantamine has therapeutic potential for improving cognitive abilities.

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

DOE PAGES

Ling, Julia; Kurzawski, Andrew; Templeton, Jeremy

2016-10-18

There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data. A novel neural network architecture is proposed which uses a multiplicative layer with an invariant tensor basis to embed Galilean invariance into the predicted anisotropy tensor. It is demonstrated that this neural network architecture provides improved prediction accuracy compared with a generic neural network architecture that does not embed this invariance property.more » Furthermore, the Reynolds stress anisotropy predictions of this invariant neural network are propagated through to the velocity field for two test cases. For both test cases, significant improvement versus baseline RANS linear eddy viscosity and nonlinear eddy viscosity models is demonstrated.« less

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

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

Ling, Julia; Kurzawski, Andrew; Templeton, Jeremy

There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data. A novel neural network architecture is proposed which uses a multiplicative layer with an invariant tensor basis to embed Galilean invariance into the predicted anisotropy tensor. It is demonstrated that this neural network architecture provides improved prediction accuracy compared with a generic neural network architecture that does not embed this invariance property.more » Furthermore, the Reynolds stress anisotropy predictions of this invariant neural network are propagated through to the velocity field for two test cases. For both test cases, significant improvement versus baseline RANS linear eddy viscosity and nonlinear eddy viscosity models is demonstrated.« less

Particle-gas dynamics in the protoplanetary nebula

NASA Technical Reports Server (NTRS)

Cuzzi, Jeffrey N.; Champney, Joelle M.; Dobrovolskis, Anthony R.

1991-01-01

In the past year we made significant progress in improving our fundamental understanding of the physics of particle-gas dynamics in the protoplanetary nebula. Having brought our code to a state of fairly robust functionality, we devoted significant effort to optimizing it for running long cases. We optimized the code for vectorization to the extent that it now runs eight times faster than before. The following subject areas are covered: physical improvements to the model; numerical results; Reynolds averaging of fluid equations; and modeling of turbulence and viscosity.

Innovative integrative bedside teaching model improves tutors’ self-assessments of teaching skills and attitudes

PubMed Central

Gat, Itai; Pessach-Gelblum, Liat; Givati, Gili; Haim, Nadav; Paluch-Shimon, Shani; Unterman, Avraham; Bar-Shavit, Yochay; Grabler, Galit; Sagi, Doron; Achiron, Anat; Ziv, Amitai

2016-01-01

Introduction Patient bedside is the ideal setting for teaching physical examination, medical interviewing, and interpersonal skills. Herein we describe a novel model for bedside teaching (BST) practiced during tutor training workshop and its resulting effect on practitioners’ self assessment of teaching skills and perceptions. Methods One-day tutor training workshop included theoretical knowledge supplementation regarding tutors’ roles as well as implementing practical tools for clinical education, mainly BST model. The model, which emphasizes simultaneous clinical and communication teaching in a stepwise approach, was practiced by consecutive simulations with a gradual escalation of difficulty and adjusted instruction approaches. Pre- and post-workshop-adjusted questionnaires using a Likert scale of 1 to 4 were completed by participants and compared. Results Analysis was based on 25 out of 48 participants who completed both questionnaires. Significantly improved teaching skills were demonstrated upon workshop completion (mean 3.3, SD 0.5) compared with pre-training (mean 2.6, SD 0.6; p<0.001) with significant increase in most examined parameters. Significantly improved tutor's roles internalization was demonstrated after training completion (mean 3.7, SD 0.3) compared with pre-workshop (mean 3.5 SD 0.5; p=0.002). Discussion Successful BST involves combination of clinical and communication skills. BST model practiced during the workshop may contribute to improved teaching skills in this challenging environment. PMID:26894587

AERONET Version 3 Release: Providing Significant Improvements for Multi-Decadal Global Aerosol Database and Near Real-Time Validation

NASA Technical Reports Server (NTRS)

Holben, Brent; Slutsker, Ilya; Giles, David; Eck, Thomas; Smirnov, Alexander; Sinyuk, Aliaksandr; Schafer, Joel; Sorokin, Mikhail; Rodriguez, Jon; Kraft, Jason;

The Incorporation and Initialization of Cloud Water/ice in AN Operational Forecast Model

NASA Astrophysics Data System (ADS)

Zhao, Qingyun

Quantitative precipitation forecasts have been one of the weakest aspects of numerical weather prediction models. Theoretical studies show that the errors in precipitation calculation can arise from three sources: errors in the large-scale forecasts of primary variables, errors in the crude treatment of condensation/evaporation and precipitation processes, and errors in the model initial conditions. A new precipitation parameterization scheme has been developed to investigate the forecast value of improved precipitation physics via the introduction of cloud water and cloud ice into a numerical prediction model. The main feature of this scheme is the explicit calculation of cloud water and cloud ice in both the convective and stratiform precipitation parameterization. This scheme has been applied to the eta model at the National Meteorological Center. Four extensive tests have been performed. The statistical results showed a significant improvement in the model precipitation forecasts. Diagnostic studies suggest that the inclusion of cloud ice is important in transferring water vapor to precipitation and in the enhancement of latent heat release; the latter subsequently affects the vertical motion field significantly. Since three-dimensional cloud data is absent from the analysis/assimilation system for most numerical models, a method has been proposed to incorporate observed precipitation and nephanalysis data into the data assimilation system to obtain the initial cloud field for the eta model. In this scheme, the initial moisture and vertical motion fields are also improved at the same time as cloud initialization. The physical initialization is performed in a dynamical initialization framework that uses the Newtonian dynamical relaxation method to nudge the model's wind and mass fields toward analyses during a 12-hour data assimilation period. Results from a case study showed that a realistic cloud field was produced by this method at the end of the data assimilation period. Precipitation forecasts have been significantly improved as a result of the improved initial cloud, moisture and vertical motion fields.

Use of cerebrospinal fluid flow rates measured by phase-contrast MR to predict outcome of ventriculoperitoneal shunting for idiopathic normal-pressure hydrocephalus.

PubMed

Dixon, Geoffrey R; Friedman, Jonathan A; Luetmer, Patrick H; Quast, Lynn M; McClelland, Robyn L; Petersen, Ronald C; Maher, Cormac O; Ebersold, Michael J

2002-06-01

To determine whether favorable clinical response and magnitude of improvement are associated with increased aqueductal cerebrospinal fluid (CSF) flow rates in patients who undergo ventriculoperitoneal shunting (VPS) for idiopathic normal-pressure hydrocephalus (NPH). Between January 1995 and June 2000, 49 patients (14 men and 35 women; mean age, 72.9 years; range, 54-88 years) underwent magnetic resonance quantification of aqueductal CSF flow followed by VPS for presumed idiopathic NPH at the Mayo Clinic, Rochester, Minn. Logistic regression models for the odds of any improvement in score as a function of aqueductal CSF flow and separate models for any improvement in gait, incontinence, cognition, and total score were constructed. Forty-two patients (86%) had improvement in gait at postoperative follow-up (mean, 10 months). Of the 32 patients with incontinence, 27 (69%) improved. Of the 36 patients with cognitive impairment, 16 (44%) improved. In univariate and fully adjusted models, increased CSF flow through the aqueduct was not significantly associated with improvement or the magnitude of improvement in gait, cognition, or incontinence. Thirty-six patients underwent high-volume lumbar puncture preoperatively, of whom 5 (14%) had no response. The aqueductal CSF flow rates of these 5 patients were significantly higher than those of the patients who improved after lumbar puncture. Postoperative complications occurred in 15 patients. The aqueductal CSF flow rates in these 15 patients were not significantly different from those of patients who experienced no complications. Among patients who underwent VPS for the treatment of NPH, measurement of CSF flow through the cerebral aqueduct did not reliably predict which patients would improve after shunting or the magnitude of improvement.

Can Video Self-Modeling Improve Affected Limb Reach and Grasp Ability in Stroke Patients?

PubMed

Steel, Kylie Ann; Mudie, Kurt; Sandoval, Remi; Anderson, David; Dogramaci, Sera; Rehmanjan, Mohammad; Birznieks, Ingvars

2018-01-01

The authors examined whether feedforward video self-modeling (FF VSM) would improve control over the affected limb, movement self-confidence, movement self-consciousness, and well-being in 18 stroke survivors. Participants completed a cup transport task and 2 questionnaires related to psychological processes pre- and postintervention. Pretest video footage of the unaffected limb performing the task was edited to create a best-of or mirror-reversed training DVD, creating the illusion that patients were performing proficiently with the affected limb. The training yielded significant improvements for the forward movement of the affected limb compared to the unaffected limb. Significant improvements were also seen in movement self-confidence, movement self-consciousness, and well-being. FF VSM appears to be a viable way to improve motor ability in populations with movement disorders.

Improvements and validation of the erythropoiesis control model for bed rest simulation

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1977-01-01

The most significant improvement in the model is the explicit formulation of separate elements representing erythropoietin production and red cell production. Other modifications include bone marrow time-delays, capability to shift oxyhemoglobin affinity and an algorithm for entering experimental data as time-varying driving functions. An area of model development is suggested by applying the model to simulating onset, diagnosis and treatment of a hematologic disorder. Recommendations for further improvements in the model and suggestions for experimental application are also discussed. A detailed analysis of the hematologic response to bed rest including simulation of the recent Baylor Medical College bed rest studies is also presented.

Improving the realism of hydrologic model through multivariate parameter estimation

NASA Astrophysics Data System (ADS)

Rakovec, Oldrich; Kumar, Rohini; Attinger, Sabine; Samaniego, Luis

2017-04-01

Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains. Rakovec, O., Kumar, R., Attinger, S. and Samaniego, L. (2016): Improving the realism of hydrologic model functioning through multivariate parameter estimation. Water Resour. Res., 52, http://dx.doi.org/10.1002/2016WR019430

Towards improved storm surge models in the northern Bay of Bengal

NASA Astrophysics Data System (ADS)

Krien, Y.; Testut, L.; Islam, A. K. M. S.; Bertin, X.; Durand, F.; Mayet, C.; Tazkia, A. R.; Becker, M.; Calmant, S.; Papa, F.; Ballu, V.; Shum, C. K.; Khan, Z. H.

2017-03-01

The northern Bay of Bengal is home to some of the deadliest cyclones recorded during the last decades. Storm surge models developed for this region significantly improved in recent years, but they still fail to predict patterns of coastal flooding with sufficient accuracy. In the present paper, we make use of a state-of-the art numerical modeling system with improved bathymetric and topographic data to identify the strengths, weaknesses, and to suggest areas for improvement of current storm surge models in this area. The new model is found to perform relatively well in reproducing waves characteristics and maximum water levels for the two extreme cyclones studied here: Phailin (2013) and Sidr (2007). The wave setup turns out to be small compared to the wind-driven surge, although it still plays a significant role for inland flooding. Relatively large tide-surge interactions mainly due to shallow water effects are also evidenced by the model. These findings plead in favor of further efforts to improve the representation of the bathymetry, especially in the nearshore area, and the implementation of models including tides and radiation stresses explicitly. The main limit of the model is its inability to predict the detailed patterns of coastal flooding satisfactorily. The reason lies mainly in the fact that topographic data also need to be further improved. In particular, a good knowledge of embankments characteristics (crest elevation and their condition) is found to be of primary importance to represent inland flooding correctly. Public authorities should take urgent action to ensure that better data are available to the scientific community, so that state-of-the-art storm surge models reaching a sufficiently high level of confidence can be used for emergency preparedness and to implement mitigation strategies in the northern Bay of Bengal.

Towards improving the representation of beaching in oil spill models: a case study.

PubMed

Samaras, Achilleas G; De Dominicis, Michela; Archetti, Renata; Lamberti, Alberto; Pinardi, Nadia

2014-11-15

Oil-shoreline interaction (or "beaching" as commonly referred to in literature) is an issue of major concern in oil spill modeling, due to the significant environmental, social and economic importance of coastal areas. The present work studies the improvement of the representation of beaching brought by the introduction of the Oil Holding Capacity approach to estimate oil concentration on coast, along with new approaches for coast type assignment to shoreline segments and the calculation of permanent oil attachment to the coast. The above were tested for the Lebanon oil spill of 2006, using a modified version of the open-source oil spill model MEDSLIK-II. The modified model results were found to be in good agreement with field observations for the specific case study, and their comparison with the original model results denote the significant improvement in the fate of beached oil brought by the proposed changes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Discovery learning model with geogebra assisted for improvement mathematical visual thinking ability

NASA Astrophysics Data System (ADS)

Juandi, D.; Priatna, N.

2018-05-01

The main goal of this study is to improve the mathematical visual thinking ability of high school student through implementation the Discovery Learning Model with Geogebra Assisted. This objective can be achieved through study used quasi-experimental method, with non-random pretest-posttest control design. The sample subject of this research consist of 62 senior school student grade XI in one of school in Bandung district. The required data will be collected through documentation, observation, written tests, interviews, daily journals, and student worksheets. The results of this study are: 1) Improvement students Mathematical Visual Thinking Ability who obtain learning with applied the Discovery Learning Model with Geogebra assisted is significantly higher than students who obtain conventional learning; 2) There is a difference in the improvement of students’ Mathematical Visual Thinking ability between groups based on prior knowledge mathematical abilities (high, medium, and low) who obtained the treatment. 3) The Mathematical Visual Thinking Ability improvement of the high group is significantly higher than in the medium and low groups. 4) The quality of improvement ability of high and low prior knowledge is moderate category, in while the quality of improvement ability in the high category achieved by student with medium prior knowledge.

COMPASS: A computational model to predict changes in MMSE scores 24-months after initial assessment of Alzheimer's disease.

PubMed

Zhu, Fan; Panwar, Bharat; Dodge, Hiroko H; Li, Hongdong; Hampstead, Benjamin M; Albin, Roger L; Paulson, Henry L; Guan, Yuanfang

2016-10-05

We present COMPASS, a COmputational Model to Predict the development of Alzheimer's diSease Spectrum, to model Alzheimer's disease (AD) progression. This was the best-performing method in recent crowdsourcing benchmark study, DREAM Alzheimer's Disease Big Data challenge to predict changes in Mini-Mental State Examination (MMSE) scores over 24-months using standardized data. In the present study, we conducted three additional analyses beyond the DREAM challenge question to improve the clinical contribution of our approach, including: (1) adding pre-validated baseline cognitive composite scores of ADNI-MEM and ADNI-EF, (2) identifying subjects with significant declines in MMSE scores, and (3) incorporating SNPs of top 10 genes connected to APOE identified from functional-relationship network. For (1) above, we significantly improved predictive accuracy, especially for the Mild Cognitive Impairment (MCI) group. For (2), we achieved an area under ROC of 0.814 in predicting significant MMSE decline: our model has 100% precision at 5% recall, and 91% accuracy at 10% recall. For (3), "genetic only" model has Pearson's correlation of 0.15 to predict progression in the MCI group. Even though addition of this limited genetic model to COMPASS did not improve prediction of progression of MCI group, the predictive ability of SNP information extended beyond well-known APOE allele.

Effect of Higher Order Thinking Laboratory on the Improvement of Critical and Creative Thinking Skills

NASA Astrophysics Data System (ADS)

Setiawan, A.; Malik, A.; Suhandi, A.; Permanasari, A.

2018-02-01

This research was based on the need for improving critical and creative thinking skills of student in the 21 -st century. In this research, we have implemented HOT-Lab model for topic of force. The model was characterized by problem solving and higher order thinking development through real laboratory activities. This research used a quasy experiment method with pre-test post-test control group design. Samples of this research were 60 students of Physics Education Program of Teacher Educatuon Institution in Bandung. The samples were divided into 2 classes, experiment class (HOT-lab model) and control class (verification lab model). Research instruments were essay tests for creative and critical thinking skills measurements. The results revealed that both the models have improved student’s creative and critical thinking skills. However, the improvement of the experiment class was significantly higher than that of the control class, as indicated by the average of normalized gains (N-gain) for critical thinking skills of 60.18 and 29.30 and for creative thinking skills of 70.71 and 29.40, respectively for the experimental class and the control class. In addition, there is no significant correlation between the improvement of critical thinking skills and creative thinking skills in both the classes.

System Dynamics Model and Simulation of Employee Work-Family Conflict in the Construction Industry

PubMed Central

Wu, Guangdong; Duan, Kaifeng; Zuo, Jian; Yang, Jianlin; Wen, Shiping

2016-01-01

The construction industry is a demanding work environment where employees’ work-family conflict is particularly prominent. This conflict has a significant impact on job and family satisfaction and performance of employees. In order to analyze the dynamic evolution of construction industry employee’s work-family conflict between work and family domains, this paper constructs a bi-directional dynamic model framework of work-family conflict by referring to the relevant literature. Consequently, a system dynamics model of employee’s work-family conflict in the construction industry is established, and a simulation is conducted. The simulation results indicate that construction industry employees experience work interference with family conflict (WIFC) levels which are significantly greater than the family interference with work conflict (FIWC) levels. This study also revealed that improving work flexibility and organizational support can have a positive impact on the satisfaction and performance of construction industry employees from a work and family perspective. Furthermore, improving family support can only significantly improve employee job satisfaction. PMID:27801857

System Dynamics Model and Simulation of Employee Work-Family Conflict in the Construction Industry.

PubMed

Wu, Guangdong; Duan, Kaifeng; Zuo, Jian; Yang, Jianlin; Wen, Shiping

2016-10-28

The construction industry is a demanding work environment where employees' work-family conflict is particularly prominent. This conflict has a significant impact on job and family satisfaction and performance of employees. In order to analyze the dynamic evolution of construction industry employee's work-family conflict between work and family domains, this paper constructs a bi-directional dynamic model framework of work-family conflict by referring to the relevant literature. Consequently, a system dynamics model of employee's work-family conflict in the construction industry is established, and a simulation is conducted. The simulation results indicate that construction industry employees experience work interference with family conflict (WIFC) levels which are significantly greater than the family interference with work conflict (FIWC) levels. This study also revealed that improving work flexibility and organizational support can have a positive impact on the satisfaction and performance of construction industry employees from a work and family perspective. Furthermore, improving family support can only significantly improve employee job satisfaction.

Improvements to the nuclear model code GNASH for cross section calculations at higher energies

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

Young, P.G.; Chadwick, M.B.

1994-05-01

The nuclear model code GNASH, which in the past has been used predominantly for incident particle energies below 20 MeV, has been modified extensively for calculations at higher energies. The model extensions and improvements are described in this paper, and their significance is illustrated by comparing calculations with experimental data for incident energies up to 160 MeV.

A Theory-Based Model for Understanding Faculty Intention to Use Students Ratings to Improve Teaching in a Health Sciences Institution in Puerto Rico

ERIC Educational Resources Information Center

Collazo, Andrés A.

2018-01-01

A model derived from the theory of planned behavior was empirically assessed for understanding faculty intention to use student ratings for teaching improvement. A sample of 175 professors participated in the study. The model was statistically significant and had a very large explanatory power. Instrumental attitude, affective attitude, perceived…

Building mental models by dissecting physical models.

PubMed

Srivastava, Anveshna

2016-01-01

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to ensure focused learning; models that are too constrained require less supervision, but can be constructed mechanically, with little to no conceptual engagement. We propose "model-dissection" as an alternative to "model-building," whereby instructors could make efficient use of supervisory resources, while simultaneously promoting focused learning. We report empirical results from a study conducted with biology undergraduate students, where we demonstrate that asking them to "dissect" out specific conceptual structures from an already built 3D physical model leads to a significant improvement in performance than asking them to build the 3D model from simpler components. Using questionnaires to measure understanding both before and after model-based interventions for two cohorts of students, we find that both the "builders" and the "dissectors" improve in the post-test, but it is the latter group who show statistically significant improvement. These results, in addition to the intrinsic time-efficiency of "model dissection," suggest that it could be a valuable pedagogical tool. © 2015 The International Union of Biochemistry and Molecular Biology.

Contribution of village cooperation unit in improving farmers incomes

NASA Astrophysics Data System (ADS)

Sibuea, M. B.; Sibuea, F. A.

2018-02-01

One of the government and private efforts to improve people’s welfare particularly to improve farmer’s income is to activate the Village Cooperation Unit (KUD). The objective of research was to know the efficiency level of farming organized by farmers together with cooperative. Theoretically some social economic variables have been known influences the rate of farmer’s income, therefore three social variables, such us the level of cooperation services, members participation and friendship among farmers with cooperation were studied. List of questions divided into forty family’s leader members of KUD which become samples. Analysis models were used production function of Cob-Douglass and Output Input Ratio models. It was concluded that level of participation and friendship partially were significantly to the income’s rate meanwhile variable of cooperation services level were not significant. Simultaneously, three factors gave very significant contribution, where R-square was 0.97 so that very significant. It’s also concluded that the biggest contribution given by the friendship level. Efficiency level or farming efforts of the farmers is very well and feasible with the average of OIR rate 19.23. This research recommended that this effort could be improved from friendship process among institution since the contribution was significantly improving the farmer’s income.

Representation of the Community Earth System Model (CESM1) CAM4-chem within the Chemistry-Climate Model Initiative (CCMI)

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

Tilmes, Simone; Lamarque, Jean -Francois; Emmons, Louisa K.

The Community Earth System Model (CESM1) CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low-top model that reaches up to approximately 40 km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. We summarize the performance ofmore » the three reference simulations suggested by CCMI, with a focus on the last 15 years of the simulation when most observations are available. Comparisons with selected data sets are employed to demonstrate the general performance of the model. We highlight new data sets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20 % of values from available observations for most regions. In particular, the trend and magnitude of surface ozone is much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. In conclusion, all experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.« less

Representation of the Community Earth System Model (CESM1) CAM4-chem within the Chemistry-Climate Model Initiative (CCMI)

DOE PAGES

Tilmes, Simone; Lamarque, Jean -Francois; Emmons, Louisa K.; ...

2016-05-20

The Community Earth System Model (CESM1) CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low-top model that reaches up to approximately 40 km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. We summarize the performance ofmore » the three reference simulations suggested by CCMI, with a focus on the last 15 years of the simulation when most observations are available. Comparisons with selected data sets are employed to demonstrate the general performance of the model. We highlight new data sets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20 % of values from available observations for most regions. In particular, the trend and magnitude of surface ozone is much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. In conclusion, all experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.« less

Development of a two-fluid drag law for clustered particles using direct numerical simulation and validation through experiments

NASA Astrophysics Data System (ADS)

Abbasi Baharanchi, Ahmadreza

This dissertation focused on development and utilization of numerical and experimental approaches to improve the CFD modeling of fluidization flow of cohesive micron size particles. The specific objectives of this research were: (1) Developing a cluster prediction mechanism applicable to Two-Fluid Modeling (TFM) of gas-solid systems (2) Developing more accurate drag models for Two-Fluid Modeling (TFM) of gas-solid fluidization flow with the presence of cohesive interparticle forces (3) using the developed model to explore the improvement of accuracy of TFM in simulation of fluidization flow of cohesive powders (4) Understanding the causes and influential factor which led to improvements and quantification of improvements (5) Gathering data from a fast fluidization flow and use these data for benchmark validations. Simulation results with two developed cluster-aware drag models showed that cluster prediction could effectively influence the results in both the first and second cluster-aware models. It was proven that improvement of accuracy of TFM modeling using three versions of the first hybrid model was significant and the best improvements were obtained by using the smallest values of the switch parameter which led to capturing the smallest chances of cluster prediction. In the case of the second hybrid model, dependence of critical model parameter on only Reynolds number led to the fact that improvement of accuracy was significant only in dense section of the fluidized bed. This finding may suggest that a more sophisticated particle resolved DNS model, which can span wide range of solid volume fraction, can be used in the formulation of the cluster-aware drag model. The results of experiment suing high speed imaging indicated the presence of particle clusters in the fluidization flow of FCC inside the riser of FIU-CFB facility. In addition, pressure data was successfully captured along the fluidization column of the facility and used as benchmark validation data for the second hybrid model developed in the present dissertation. It was shown the second hybrid model could predict the pressure data in the dense section of the fluidization column with better accuracy.

Leukocyte and platelet depletion improves blood flow and function in a renal transplant model.

PubMed

Yates, Phillip J; Hosgood, Sarah A; Nicholson, Michael L

2012-01-01

Donation after cardiac death (DCD) donors are an important source of organs for transplantation. Due to warm and cold ischemic injury, DCD kidneys undergo a significant reperfusion insult when transplanted. This is manifested clinically as a high incidence of delayed graft function (DGF) and primary non-function (PNF). The importance of leukocytes in the generation of reperfusion injury is pivotal. Using an ex vivo porcine model of kidney transplantation, the effects of reperfusion with leukocyte and platelet depleted blood (LDB) and whole blood (WB) on renal blood flow and function were compared. Hemodynamic measurements were recorded, and biochemical, hematological, and histologic samples taken at set time-points. Reperfusion with LDB improved renal blood flow significantly compared with WB reperfusion. In addition, there was a significant improvement in creatinine clearance and renal oxygen consumption, but not fractional excretion of sodium, acid-base homeostasis, urinary nitric oxide (NO), or 8-isoprostane levels. This study represents a good model for the initial reperfusion period in renal transplantation. Improvement in only some functional markers and neither urinary NO nor 8-isoprostane levels indicates that improved blood flow alone is not sufficient to reverse the severe ischemic insult endured by DCD kidneys. Copyright © 2012 Elsevier Inc. All rights reserved.

Application of a theoretical model to evaluate COPD disease management.

PubMed

Lemmens, Karin M M; Nieboer, Anna P; Rutten-Van Mölken, Maureen P M H; van Schayck, Constant P; Asin, Javier D; Dirven, Jos A M; Huijsman, Robbert

2010-03-26

Disease management programmes are heterogeneous in nature and often lack a theoretical basis. An evaluation model has been developed in which theoretically driven inquiries link disease management interventions to outcomes. The aim of this study is to methodically evaluate the impact of a disease management programme for patients with chronic obstructive pulmonary disease (COPD) on process, intermediate and final outcomes of care in a general practice setting. A quasi-experimental research was performed with 12-months follow-up of 189 COPD patients in primary care in the Netherlands. The programme included patient education, protocolised assessment and treatment of COPD, structural follow-up and coordination by practice nurses at 3, 6 and 12 months. Data on intermediate outcomes (knowledge, psychosocial mediators, self-efficacy and behaviour) and final outcomes (dyspnoea, quality of life, measured by the CRQ and CCQ, and patient experiences) were obtained from questionnaires and electronic registries. Implementation of the programme was associated with significant improvements in dyspnoea (p < 0.001) and patient experiences (p < 0.001). No significant improvement was found in mean quality of life scores. Improvements were found in several intermediate outcomes, including investment beliefs (p < 0.05), disease-specific knowledge (p < 0.01; p < 0.001) and medication compliance (p < 0.01). Overall, process improvement was established. The model showed associations between significantly improved intermediate outcomes and improvements in quality of life and dyspnoea. The application of a theory-driven model enhances the design and evaluation of disease management programmes aimed at improving health outcomes. This study supports the notion that a theoretical approach strengthens the evaluation designs of complex interventions. Moreover, it provides prudent evidence that the implementation of COPD disease management programmes can positively influence outcomes of care.

Application of a theoretical model to evaluate COPD disease management

PubMed Central

2010-01-01

Background Disease management programmes are heterogeneous in nature and often lack a theoretical basis. An evaluation model has been developed in which theoretically driven inquiries link disease management interventions to outcomes. The aim of this study is to methodically evaluate the impact of a disease management programme for patients with chronic obstructive pulmonary disease (COPD) on process, intermediate and final outcomes of care in a general practice setting. Methods A quasi-experimental research was performed with 12-months follow-up of 189 COPD patients in primary care in the Netherlands. The programme included patient education, protocolised assessment and treatment of COPD, structural follow-up and coordination by practice nurses at 3, 6 and 12 months. Data on intermediate outcomes (knowledge, psychosocial mediators, self-efficacy and behaviour) and final outcomes (dyspnoea, quality of life, measured by the CRQ and CCQ, and patient experiences) were obtained from questionnaires and electronic registries. Results Implementation of the programme was associated with significant improvements in dyspnoea (p < 0.001) and patient experiences (p < 0.001). No significant improvement was found in mean quality of life scores. Improvements were found in several intermediate outcomes, including investment beliefs (p < 0.05), disease-specific knowledge (p < 0.01; p < 0.001) and medication compliance (p < 0.01). Overall, process improvement was established. The model showed associations between significantly improved intermediate outcomes and improvements in quality of life and dyspnoea. Conclusions The application of a theory-driven model enhances the design and evaluation of disease management programmes aimed at improving health outcomes. This study supports the notion that a theoretical approach strengthens the evaluation designs of complex interventions. Moreover, it provides prudent evidence that the implementation of COPD disease management programmes can positively influence outcomes of care. PMID:20346135

Curcumin improves the therapeutic efficacy of Listeria(at)-Mage-b vaccine in correlation with improved T-cell responses in blood of a triple-negative breast cancer model 4T1.

PubMed

Singh, Manisha; Ramos, Ilyssa; Asafu-Adjei, Denise; Quispe-Tintaya, Wilber; Chandra, Dinesh; Jahangir, Arthee; Zang, Xingxing; Aggarwal, Bharat B; Gravekamp, Claudia

2013-08-01

Success of cancer vaccination is strongly hampered by immune suppression in the tumor microenvironment (TME). Interleukin (IL)-6 is particularly and highly produced by triple-negative breast cancer (TNBC) cells, and has been considered as an important contributor to immune suppression in the TME. Therefore, we hypothesized that IL-6 reduction may improve efficacy of vaccination against TNBC cancer through improved T-cell responses. To prove this hypothesis, we investigated the effect of curcumin, an inhibitor of IL-6 production, on vaccination of a highly attenuated Listeria monocytogenes (Listeria(at)), encoding tumor-associated antigens (TAA) Mage-b in a TNBC model 4T1. Two therapeutic vaccination strategies with Listeria(at)-Mage-b and curcumin were tested. The first immunization strategy involved all Listeria(at)-Mage-b vaccinations and curcumin after tumor development. As curcumin has been consumed all over the world, the second immunization strategy involved curcumin before and all therapeutic vaccinations with Listeria(at)-Mage-b after tumor development. Here, we demonstrate that curcumin significantly improves therapeutic efficacy of Listeria(at)-Mage-b with both immunization strategies particularly against metastases in a TNBC model (4T1). The combination therapy was slightly but significantly more effective against the metastases when curcumin was administered before compared to after tumor development. With curcumin before tumor development in the combination therapy, the production of IL-6 was significantly decreased and IL-12 increased by myeloid-derived suppressor cells (MDSC), in correlation with improved CD4 and CD8 T-cell responses in blood. Our study suggests that curcumin improves the efficacy of Listeria(at)-Mage-b vaccine against metastases in TNBC model 4T1 through reversal of tumor-induced immune suppression.

C-reactive protein and serum creatinine, but not haemoglobin A1c, are independent predictors of coronary heart disease risk in non-diabetic Chinese.

PubMed

Salim, Agus; Tai, E Shyong; Tan, Vincent Y; Welsh, Alan H; Liew, Reginald; Naidoo, Nasheen; Wu, Yi; Yuan, Jian-Min; Koh, Woon P; van Dam, Rob M

2016-08-01

In western populations, high-sensitivity C-reactive protein (hsCRP), and to a lesser degree serum creatinine and haemoglobin A1c, predict risk of coronary heart disease (CHD). However, data on Asian populations that are increasingly affected by CHD are sparse and it is not clear whether these biomarkers can be used to improve CHD risk classification. We conducted a nested case-control study within the Singapore Chinese Health Study cohort, with incident 'hard' CHD (myocardial infarction or CHD death) as an outcome. We used data from 965 men (298 cases, 667 controls) and 528 women (143 cases, 385 controls) to examine the utility of hsCRP, serum creatinine and haemoglobin A1c in improving the prediction of CHD risk over and above traditional risk factors for CHD included in the ATP III model. For each sex, the performance of models with only traditional risk factors used in the ATP III model was compared with models with the biomarkers added using weighted Cox proportional hazards analysis. The impact of adding these biomarkers was assessed using the net reclassification improvement index. For men, loge hsCRP (hazard ratio 1.25, 95% confidence interval: 1.05; 1.49) and loge serum creatinine (hazard ratio 4.82, 95% confidence interval: 2.10; 11.04) showed statistically significantly associations with CHD risk when added to the ATP III model. We did not observe a significant association between loge haemoglobin A1c and CHD risk (hazard ratio 1.83, 95% confidence interval: 0.21; 16.06). Adding hsCRP and serum creatinine to the ATP III model improved risk classification in men with a net gain of 6.3% of cases (p-value = 0.001) being reclassified to a higher risk category, while it did not significantly reduce the accuracy of classification for non-cases. For women, squared hsCRP was borderline significantly (hazard ratio 1.01, 95% confidence interval: 1.00; 1.03) and squared serum creatinine was significantly (hazard ratio 1.81, 95% confidence interval: 1.49; 2.21) associated with CHD risk. However, the association between squared haemoglobin A1c and CHD risk was not significant (hazard ratio 1.05, 95% confidence interval: 0.99; 1.12). The addition of hsCRP and serum creatinine to the ATP III model resulted in 3.7% of future cases being reclassified to a higher risk category (p-value = 0.025), while it did not significantly reduce the accuracy of classification for non-cases. Adding hsCRP and serum creatinine, but not haemoglobin A1c, to traditional risk factors improved CHD risk prediction among non-diabetic Singaporean Chinese. The improved risk estimates will allow better identification of individuals at high risk of CHD than existing risk calculators such as the ATP III model. © The European Society of Cardiology 2016.

An Improved K-Epsilon Model for Near-Wall Turbulence and Comparison with Direct Numerical Simulation

NASA Technical Reports Server (NTRS)

Shih, T. H.

1990-01-01

An improved k-epsilon model for low Reynolds number turbulence near a wall is presented. The near-wall asymptotic behavior of the eddy viscosity and the pressure transport term in the turbulent kinetic energy equation is analyzed. Based on this analysis, a modified eddy viscosity model, having correct near-wall behavior, is suggested, and a model for the pressure transport term in the k-equation is proposed. In addition, a modeled dissipation rate equation is reformulated. Fully developed channel flows were used for model testing. The calculations using various k-epsilon models are compared with direct numerical simulations. The results show that the present k-epsilon model performs well in predicting the behavior of near-wall turbulence. Significant improvement over previous k-epsilon models is obtained.

Improving Climate and Achievement in a Troubled Urban High School through the Talent Development Model.

ERIC Educational Resources Information Center

McPartland, James; Balfanz, Robert; Jordan, Will; Legters, Nettie

1998-01-01

A case study of a large nonselective urban high school in Baltimore (Maryland) describes the design and implementation of a comprehensive package of school reforms, the Talent Development Model with Career Academies. Qualitative and quantitative evidence is provided on significant improvements in school climate, student attendance, promotion…

Using the Madeline Hunter Direct Instruction Model to Improve Outcomes Assessments in Marketing Programs

ERIC Educational Resources Information Center

Steward, Michelle D.; Martin, Gregory S.; Burns, Alvin C.; Bush, Ronald F.

2010-01-01

This study introduces marketing educators to the Madeline Hunter Direct Instruction Model (HDIM) as an approach to significantly and substantially improve student learning through course-embedded assessment. The effectiveness of the method is illustrated in three different marketing courses taught by three different marketing professors. The…

Modelling the physics in iterative reconstruction for transmission computed tomography

PubMed Central

Nuyts, Johan; De Man, Bruno; Fessler, Jeffrey A.; Zbijewski, Wojciech; Beekman, Freek J.

2013-01-01

There is an increasing interest in iterative reconstruction (IR) as a key tool to improve quality and increase applicability of X-ray CT imaging. IR has the ability to significantly reduce patient dose, it provides the flexibility to reconstruct images from arbitrary X-ray system geometries and it allows to include detailed models of photon transport and detection physics, to accurately correct for a wide variety of image degrading effects. This paper reviews discretisation issues and modelling of finite spatial resolution, Compton scatter in the scanned object, data noise and the energy spectrum. Widespread implementation of IR with highly accurate model-based correction, however, still requires significant effort. In addition, new hardware will provide new opportunities and challenges to improve CT with new modelling. PMID:23739261

How to improve an un-alterable model forecast? A sequential data assimilation based error updating approach

NASA Astrophysics Data System (ADS)

Gragne, A. S.; Sharma, A.; Mehrotra, R.; Alfredsen, K. T.

2012-12-01

Accuracy of reservoir inflow forecasts is instrumental for maximizing value of water resources and influences operation of hydropower reservoirs significantly. Improving hourly reservoir inflow forecasts over a 24 hours lead-time is considered with the day-ahead (Elspot) market of the Nordic exchange market in perspectives. The procedure presented comprises of an error model added on top of an un-alterable constant parameter conceptual model, and a sequential data assimilation routine. The structure of the error model was investigated using freely available software for detecting mathematical relationships in a given dataset (EUREQA) and adopted to contain minimum complexity for computational reasons. As new streamflow data become available the extra information manifested in the discrepancies between measurements and conceptual model outputs are extracted and assimilated into the forecasting system recursively using Sequential Monte Carlo technique. Besides improving forecast skills significantly, the probabilistic inflow forecasts provided by the present approach entrains suitable information for reducing uncertainty in decision making processes related to hydropower systems operation. The potential of the current procedure for improving accuracy of inflow forecasts at lead-times unto 24 hours and its reliability in different seasons of the year will be illustrated and discussed thoroughly.

Health Blief Model-based intervention to improve nutritional behavior among elderly women.

PubMed

Iranagh, Jamileh Amirzadeh; Rahman, Hejar Abdul; Motalebi, Seyedeh Ameneh

2016-06-01

Nutrition is a determinant factor of health in elderly people. Independent living in elderly people can be maintained or enhanced by improvement of nutritional behavior. Hence, the present study was conducted to determine the impact of Health Belief Model (HBM)-based intervention on the nutritional behavior of elderly women. Cluster-random sampling was used to assess the sample of this clinical trial study. The participants of this study attended a 12-week nutrition education program consisting of two (2) sessions per week. There was also a follow-up for another three (3) months. Smart PLS 3.5 and SPSS 19 were used for structural equation modeling, determination of model fitness, and hypotheses testing. The findings indicate that intervention had a significant effect on knowledge improvement as well as the behavior of elderly women. The model explained 5 to 70% of the variance in nutritional behavior. In addition, nutritional behavior was positively affected by the HBM constructs comprised of perceived susceptibility, self-efficacy, perceived benefits, and barriers after the intervention program. The results of this study show that HBM-based educational intervention has a significant effect in improving nutritional knowledge and behavior among elderly women.

Individualized Physical 3-dimensional Kidney Tumor Models Constructed From 3-dimensional Printers Result in Improved Trainee Anatomic Understanding.

PubMed

Knoedler, Margaret; Feibus, Allison H; Lange, Andrew; Maddox, Michael M; Ledet, Elisa; Thomas, Raju; Silberstein, Jonathan L

2015-06-01

To evaluate the effect of 3-dimensionally (3D) printed physical renal models with enhancing masses on medical trainee characterization, localization, and understanding of renal malignancy. Proprietary software was used to import standard computed tomography (CT) cross-sectional imaging into 3D printers to create physical models of renal units with enhancing renal lesions in situ. Six different models were printed from a transparent plastic resin; the normal parenchyma was printed in a clear, translucent plastic, with a red hue delineating the suspicious renal lesion. Medical students, who had completed their first year of training, were given an overview and tasked with completion of RENAL nephrometry scores, separately using CT imaging and 3D models. Trainees were also asked to complete a questionnaire about their experience. Variability between trainees was assessed by intraclass correlation coefficients (ICCs), and kappa statistics were used to compare the trainee to experts. Overall trainee nephrometry score accuracy was significantly improved with the 3D model vs CT scan (P <.01). Furthermore, 3 of the 4 components of the nephrometry score (radius, nearness to collecting system, and location) showed significant improvement (P <.001) using the models. There was also more consistent agreement among trainees when using the 3D models compared with CT scans to assess the nephrometry score (intraclass correlation coefficient, 0.28 for CT scan vs 0.72 for 3D models). Qualitative evaluation with questionnaires filled out by the trainees further confirmed that the 3D models improved their ability to understand and conceptualize the renal mass. Physical 3D models using readily available printing techniques improve trainees' understanding and characterization of individual patients' enhancing renal lesions. Published by Elsevier Inc.

Improving the accuracy of macromolecular structure refinement at 7 Å resolution.

PubMed

Brunger, Axel T; Adams, Paul D; Fromme, Petra; Fromme, Raimund; Levitt, Michael; Schröder, Gunnar F

2012-06-06

In X-ray crystallography, molecular replacement and subsequent refinement is challenging at low resolution. We compared refinement methods using synchrotron diffraction data of photosystem I at 7.4 Å resolution, starting from different initial models with increasing deviations from the known high-resolution structure. Standard refinement spoiled the initial models, moving them further away from the true structure and leading to high R(free)-values. In contrast, DEN refinement improved even the most distant starting model as judged by R(free), atomic root-mean-square differences to the true structure, significance of features not included in the initial model, and connectivity of electron density. The best protocol was DEN refinement with initial segmented rigid-body refinement. For the most distant initial model, the fraction of atoms within 2 Å of the true structure improved from 24% to 60%. We also found a significant correlation between R(free) values and the accuracy of the model, suggesting that R(free) is useful even at low resolution. Copyright © 2012 Elsevier Ltd. All rights reserved.

Improving Estimates and Forecasts of Lake Carbon Pools and Fluxes Using Data Assimilation

NASA Astrophysics Data System (ADS)

Zwart, J. A.; Hararuk, O.; Prairie, Y.; Solomon, C.; Jones, S.

2017-12-01

Lakes are biogeochemical hotspots on the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. Observations and models of lake carbon pools and fluxes are rarely explicitly combined through data assimilation despite significant use of this technique in other fields with great success. Data assimilation adds value to both observations and models by constraining models with observations of the system and by leveraging knowledge of the system formalized by the model to objectively fill information gaps. In this analysis, we highlight the utility of data assimilation in lake carbon cycling research by using the Ensemble Kalman Filter to combine simple lake carbon models with observations of lake carbon pools. We demonstrate the use of data assimilation to improve a model's representation of lake carbon dynamics, to reduce uncertainty in estimates of lake carbon pools and fluxes, and to improve the accuracy of carbon pool size estimates relative to estimates derived from observations alone. Data assimilation techniques should be embraced as valuable tools for lake biogeochemists interested in learning about ecosystem dynamics and forecasting ecosystem states and processes.

Improved spatial accuracy of functional maps in the rat olfactory bulb using supervised machine learning approach.

PubMed

Murphy, Matthew C; Poplawsky, Alexander J; Vazquez, Alberto L; Chan, Kevin C; Kim, Seong-Gi; Fukuda, Mitsuhiro

2016-08-15

Functional MRI (fMRI) is a popular and important tool for noninvasive mapping of neural activity. As fMRI measures the hemodynamic response, the resulting activation maps do not perfectly reflect the underlying neural activity. The purpose of this work was to design a data-driven model to improve the spatial accuracy of fMRI maps in the rat olfactory bulb. This system is an ideal choice for this investigation since the bulb circuit is well characterized, allowing for an accurate definition of activity patterns in order to train the model. We generated models for both cerebral blood volume weighted (CBVw) and blood oxygen level dependent (BOLD) fMRI data. The results indicate that the spatial accuracy of the activation maps is either significantly improved or at worst not significantly different when using the learned models compared to a conventional general linear model approach, particularly for BOLD images and activity patterns involving deep layers of the bulb. Furthermore, the activation maps computed by CBVw and BOLD data show increased agreement when using the learned models, lending more confidence to their accuracy. The models presented here could have an immediate impact on studies of the olfactory bulb, but perhaps more importantly, demonstrate the potential for similar flexible, data-driven models to improve the quality of activation maps calculated using fMRI data. Copyright © 2016 Elsevier Inc. All rights reserved.

Short note: the experimental geopotential model XGM2016

NASA Astrophysics Data System (ADS)

Pail, R.; Fecher, T.; Barnes, D.; Factor, J. F.; Holmes, S. A.; Gruber, T.; Zingerle, P.

2018-04-01

As a precursor study for the upcoming combined Earth Gravitational Model 2020 (EGM2020), the Experimental Gravity Field Model XGM2016, parameterized as a spherical harmonic series up to degree and order 719, is computed. XGM2016 shares the same combination methodology as its predecessor model GOCO05c (Fecher et al. in Surv Geophys 38(3): 571-590, 2017. doi: 10.1007/s10712-016-9406-y). The main difference between these models is that XGM2016 is supported by an improved terrestrial data set of 15^' × 15^' gravity anomaly area-means provided by the United States National Geospatial-Intelligence Agency (NGA), resulting in significant upgrades compared to existing combined gravity field models, especially in continental areas such as South America, Africa, parts of Asia, and Antarctica. A combination strategy of relative regional weighting provides for improved performance in near-coastal ocean regions, including regions where the altimetric data are mostly unchanged from previous models. Comparing cumulative height anomalies, from both EGM2008 and XGM2016 at degree/order 719, yields differences of 26 cm in Africa and 40 cm in South America. These differences result from including additional information of satellite data, as well as from the improved ground data in these regions. XGM2016 also yields a smoother Mean Dynamic Topography with significantly reduced artifacts, which indicates an improved modeling of the ocean areas.

CRAC2 model description

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

Ritchie, L.T.; Alpert, D.J.; Burke, R.P.

1984-03-01

The CRAC2 computer code is a revised version of CRAC (Calculation of Reactor Accident Consequences) which was developed for the Reactor Safety Study. This document provides an overview of the CRAC2 code and a description of each of the models used. Significant improvements incorporated into CRAC2 include an improved weather sequence sampling technique, a new evacuation model, and new output capabilities. In addition, refinements have been made to the atmospheric transport and deposition model. Details of the modeling differences between CRAC2 and CRAC are emphasized in the model descriptions.

A cross-national analysis of how economic inequality predicts biodiversity loss.

PubMed

Holland, Tim G; Peterson, Garry D; Gonzalez, Andrew

2009-10-01

We used socioeconomic models that included economic inequality to predict biodiversity loss, measured as the proportion of threatened plant and vertebrate species, across 50 countries. Our main goal was to evaluate whether economic inequality, measured as the Gini index of income distribution, improved the explanatory power of our statistical models. We compared four models that included the following: only population density, economic footprint (i.e., the size of the economy relative to the country area), economic footprint and income inequality (Gini index), and an index of environmental governance. We also tested the environmental Kuznets curve hypothesis, but it was not supported by the data. Statistical comparisons of the models revealed that the model including both economic footprint and inequality was the best predictor of threatened species. It significantly outperformed population density alone and the environmental governance model according to the Akaike information criterion. Inequality was a significant predictor of biodiversity loss and significantly improved the fit of our models. These results confirm that socioeconomic inequality is an important factor to consider when predicting rates of anthropogenic biodiversity loss.

Are We on the Right Track: Can Our Understanding of Abscission in Model Systems Promote or Derail Making Improvements in Less Studied Crops?

PubMed Central

Patterson, Sara E.; Bolivar-Medina, Jenny L.; Falbel, Tanya G.; Hedtcke, Janet L.; Nevarez-McBride, Danielle; Maule, Andrew F.; Zalapa, Juan E.

2016-01-01

As the world population grows and resources and climate conditions change, crop improvement continues to be one of the most important challenges for agriculturalists. The yield and quality of many crops is affected by abscission or shattering, and environmental stresses often hasten or alter the abscission process. Understanding this process can not only lead to genetic improvement, but also changes in cultural practices and management that will contribute to higher yields, improved quality and greater sustainability. As plant scientists, we have learned significant amounts about this process through the study of model plants such as Arabidopsis, tomato, rice, and maize. While these model systems have provided significant valuable information, we are sometimes challenged to use this knowledge effectively as variables including the economic value of the crop, the uniformity of the crop, ploidy levels, flowering and crossing mechanisms, ethylene responses, cultural requirements, responses to changes in environment, and cellular and tissue specific morphological differences can significantly influence outcomes. The value of genomic resources for lesser-studied crops such as cranberries and grapes and the orphan crop fonio will also be considered. PMID:26858730

Are We on the Right Track: Can Our Understanding of Abscission in Model Systems Promote or Derail Making Improvements in Less Studied Crops?

PubMed

Patterson, Sara E; Bolivar-Medina, Jenny L; Falbel, Tanya G; Hedtcke, Janet L; Nevarez-McBride, Danielle; Maule, Andrew F; Zalapa, Juan E

2015-01-01

As the world population grows and resources and climate conditions change, crop improvement continues to be one of the most important challenges for agriculturalists. The yield and quality of many crops is affected by abscission or shattering, and environmental stresses often hasten or alter the abscission process. Understanding this process can not only lead to genetic improvement, but also changes in cultural practices and management that will contribute to higher yields, improved quality and greater sustainability. As plant scientists, we have learned significant amounts about this process through the study of model plants such as Arabidopsis, tomato, rice, and maize. While these model systems have provided significant valuable information, we are sometimes challenged to use this knowledge effectively as variables including the economic value of the crop, the uniformity of the crop, ploidy levels, flowering and crossing mechanisms, ethylene responses, cultural requirements, responses to changes in environment, and cellular and tissue specific morphological differences can significantly influence outcomes. The value of genomic resources for lesser-studied crops such as cranberries and grapes and the orphan crop fonio will also be considered.

Effects of Land Use Land Cover (LULC) and Climate on Simulation of Phosphorus loading in the Southeast United States Region

NASA Astrophysics Data System (ADS)

Jima, T. G.; Roberts, A.

2013-12-01

Quality of coastal and freshwater resources in the Southeastern United States is threatened due to Eutrophication as a result of excessive nutrients, and phosphorus is acknowledged as one of the major limiting nutrients. In areas with much non-point source (NPS) pollution, land use land cover and climate have been found to have significant impact on water quality. Landscape metrics applied in catchment and riparian stream based nutrient export models are known to significantly improve nutrient prediction. The regional SPARROW (Spatially Referenced Regression On Watershed attributes), which predicts Total Phosphorus has been developed by the Southeastern United States regions USGS, as part of the National Water Quality Assessment (NAWQA) program and the model accuracy was found to be 67%. However, landscape composition and configuration metrics which play a significant role in the source, transport and delivery of the nutrient have not been incorporated in the model. Including these matrices in the models parameterization will improve the models accuracy and improve decision making process for mitigating and managing NPS phosphorus in the region. The National Land Cover Data 2001 raster data will be used (since the base line is 2002) for the region (with 8321 watersheds ) with fragstats 4.1 and ArcGIS Desktop 10.1 for the analysis of landscape matrices, buffers and creating map layers. The result will be imported to the Southeast SPARROW model and will be analyzed. Resulting statistical significance and model accuracy will be assessed and predictions for those areas with no water quality monitoring station will be made.

Improved nurse job satisfaction and job retention with the transition from a "mandatory consultation" model to a "semiclosed" surgical intensive care unit: a 1-year prospective evaluation.

PubMed

Haut, Elliott R; Sicoutris, Corinna P; Meredith, Denise M; Sonnad, Seema S; Reilly, Patrick M; Schwab, C William; Hanson, C William; Gracias, Vicente H

2006-02-01

The change from a "mandatory consultation" to a "semiclosed" surgical intensive care unit (SICU) model will impact nurses considerably. We hypothesize that nurse job satisfaction, job turnover rates, and hospital costs for temporary agency nurses will improve and these improvements will be more dramatic in SICU sections with greater involvement of a dedicated surgical critical care service (SCCS). Prospective longitudinal survey. Tertiary-care university hospital. SICU staff nurses. Change from mandatory consultation to semiclosed SICU. We surveyed SICU nurses during the year-long transition to a semiclosed SICU service (five time points, 3-month intervals). The first four surveys included ten questions on nurse job satisfaction. The final survey included two additional questions. All questions were on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Nurse job turnover rates and money spent on agency nurses were compared over time; 503 of a possible 914 surveys were completed (55% overall return rate). Nurse job satisfaction scores significantly improved over time for all questions (p < .05). Hospital spending on agency nurses decreased significantly (p = .0098). The yearly nurse job turnover rate dropped from 25% to 16% (p = .15). The scores for both year-end statements ("I am more satisfied with my job now than 1 year ago" and "The SCCS management of all orders has improved my job satisfaction") were significantly higher in sections with greater SCCS involvement (p = .0070 and p < .0001). Nurse job satisfaction improved significantly with the transition to a semiclosed SICU. This higher satisfaction was associated with a significant decrease in spending on temporary agency nurses and a trend toward increased staff nurse job retention. SICU sections with greater SCCS involvement had more dramatic improvements. This semiclosed SICU model may help retain SICU nurses in a competitive job market in which experienced nurses are in short supply.

Incorporating Single-nucleotide Polymorphisms Into the Lyman Model to Improve Prediction of Radiation Pneumonitis

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

Tucker, Susan L., E-mail: sltucker@mdanderson.org; Li Minghuan; Xu Ting

2013-01-01

Purpose: To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-{beta}, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials: Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGF{beta}, TNF{alpha}, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk ofmore » severe (grade {>=}3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results: Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGF{beta}, VEGF, TNF{alpha}, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGF{beta}, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions: This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.« less

Towards an Improved Represenation of Reservoirs and Water Management in a Land Surface-Hydrology Model

NASA Astrophysics Data System (ADS)

Yassin, F.; Anis, M. R.; Razavi, S.; Wheater, H. S.

2017-12-01

Water management through reservoirs, diversions, and irrigation have significantly changed river flow regimes and basin-wide energy and water balance cycles. Failure to represent these effects limits the performance of land surface-hydrology models not only for streamflow prediction but also for the estimation of soil moisture, evapotranspiration, and feedbacks to the atmosphere. Despite recent research to improve the representation of water management in land surface models, there remains a need to develop improved modeling approaches that work in complex and highly regulated basins such as the 406,000 km2 Saskatchewan River Basin (SaskRB). A particular challenge for regional and global application is a lack of local information on reservoir operational management. To this end, we implemented a reservoir operation, water abstraction, and irrigation algorithm in the MESH land surface-hydrology model and tested it over the SaskRB. MESH is Environment Canada's Land Surface-hydrology modeling system that couples Canadian Land Surface Scheme (CLASS) with hydrological routing model. The implemented reservoir algorithm uses an inflow-outflow relationship that accounts for the physical characteristics of reservoirs (e.g., storage-area-elevation relationships) and includes simplified operational characteristics based on local information (e.g., monthly target volume and release under limited, normal, and flood storage zone). The irrigation algorithm uses the difference between actual and potential evapotranspiration to estimate irrigation water demand. This irrigation demand is supplied from the neighboring reservoirs/diversion in the river system. We calibrated the model enabled with the new reservoir and irrigation modules in a multi-objective optimization setting. Results showed that the reservoir and irrigation modules significantly improved the MESH model performance in generating streamflow and evapotranspiration across the SaskRB and that this our approach provides a basis for improved large scale hydrological modelling.

Effect of Progesterone on Cerebral Vasospasm and Neurobehavioral Outcomes in a Rodent Model of Subarachnoid Hemorrhage.

PubMed

Turan, Nefize; Miller, Brandon A; Huie, J Russell; Heider, Robert A; Wang, Jun; Wali, Bushra; Yousuf, Seema; Ferguson, Adam R; Sayeed, Iqbal; Stein, Donald G; Pradilla, Gustavo

2018-02-01

Subarachnoid hemorrhage (SAH) induces widespread inflammation leading to cellular injury, vasospasm, and ischemia. Evidence suggests that progesterone (PROG) can improve functional recovery in acute brain injury owing to its anti-inflammatory and neuroprotective properties, which could also be beneficial in SAH. We hypothesized that PROG treatment attenuates inflammation-mediated cerebral vasospasm and microglial activation, improves synaptic connectivity, and ameliorates functional recovery after SAH. We investigated the effect of PROG in a cisternal SAH model in adult male C57BL/6 mice. Neurobehavioral outcomes were evaluated using rotarod latency and grip strength tests. Basilar artery perimeter, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid glutamate receptor 1 (GluR1)/synaptophysin colocalization, and Iba-1 immunoreactivity were quantified histologically. PROG (8 mg/kg) significantly improved rotarod latency at day 6 and grip strength at day 9. PROG-treated mice had significantly reduced basilar artery vasospasm at 24 hours. GluR1/synaptophysin colocalization, indicative of synaptic GluR1, was significantly reduced in the SAH+Vehicle group at 24 hours, and PROG treatment significantly attenuated this reduction. PROG treatment significantly reduced microglial cell activation and proliferation in cerebellum and cortex but not in the brainstem at 10 days. PROG treatment ameliorated cerebral vasospasm, reduced microglial activation, restored synaptic GluR1 localization, and improved neurobehavioral performance in a murine model of SAH. These results provide a rationale for further translational testing of PROG therapy in SAH. Copyright © 2017 Elsevier Inc. All rights reserved.

Effectiveness of Japanese SHARE model in improving Taiwanese healthcare personnel's preference for cancer truth telling.

PubMed

Tang, Woung-Ru; Chen, Kuan-Yu; Hsu, Sheng-Hui; Juang, Yeong-Yuh; Chiu, Shin-Che; Hsiao, Shu-Chun; Fujimori, Maiko; Fang, Chun-Kai

2014-03-01

Communication skills training (CST) based on the Japanese SHARE model of family-centered truth telling in Asian countries has been adopted in Taiwan. However, its effectiveness in Taiwan has only been preliminarily verified. This study aimed to test the effect of SHARE model-centered CST on Taiwanese healthcare providers' truth-telling preference, to determine the effect size, and to compare the effect of 1-day and 2-day CST programs on participants' truth-telling preference. For this one-group, pretest-posttest study, 10 CST programs were conducted from August 2010 to November 2011 under certified facilitators and with standard patients. Participants (257 healthcare personnel from northern, central, southern, and eastern Taiwan) chose the 1-day (n = 94) or 2-day (n = 163) CST program as convenient. Participants' self-reported truth-telling preference was measured before and immediately after CST programs, with CST program assessment afterward. The CST programs significantly improved healthcare personnel's truth-telling preference (mean pretest and posttest scores ± standard deviation (SD): 263.8 ± 27.0 vs. 281.8 ± 22.9, p < 0.001). The CST programs effected a significant, large (d = 0.91) improvement in overall truth-telling preference and significantly improved method of disclosure, emotional support, and additional information (p < 0.001). Participation in 1-day or 2-day CST programs did not significantly affect participants' truth-telling preference (p > 0.05) except for the setting subscale. Most participants were satisfied with the CST programs (93.8%) and were willing to recommend them to colleagues (98.5%). The SHARE model-centered CST programs significantly improved Taiwanese healthcare personnel's truth-telling preference. Future studies should objectively assess participants' truth-telling preference, for example, by cancer patients, their families, and other medical team personnel and at longer times after CST programs. Copyright © 2013 John Wiley & Sons, Ltd.

Does box model training improve surgical dexterity and economy of movement during virtual reality laparoscopy? A randomised trial.

PubMed

Clevin, Lotte; Grantcharov, Teodor P

2008-01-01

Laparoscopic box model trainers have been used in training curricula for a long time, however data on their impact on skills acquisition is still limited. Our aim was to validate a low cost box model trainer as a tool for the training of skills relevant to laparoscopic surgery. Randomised, controlled trial (Canadian Task Force Classification I). University Hospital. Sixteen gynaecologic residents with limited laparoscopic experience were randomised to a group that received a structured box model training curriculum, and a control group. Performance before and after the training was assessed in a virtual reality laparoscopic trainer (LapSim and was based on objective parameters, registered by the computer system (time, error, and economy of motion scores). Group A showed significantly greater improvement in all performance parameters compared with the control group: economy of movement (p=0.001), time (p=0.001) and tissue damage (p=0.036), confirming the positive impact of box-trainer curriculum on laparoscopic skills acquisition. Structured laparoscopic skill training on a low cost box model trainer improves performance as assessed using the VR system. Trainees who used the box model trainer showed significant improvement compared to the control group. Box model trainers are valid tools for laparoscopic skills training and should be implemented in the comprehensive training curricula in gynaecology.

Improved CFD Model to Predict Flow and Temperature Distributions in a Blast Furnace Hearth

NASA Astrophysics Data System (ADS)

Komiyama, Keisuke M.; Guo, Bao-Yu; Zughbi, Habib; Zulli, Paul; Yu, Ai-Bing

2014-10-01

The campaign life of a blast furnace is limited by the erosion of hearth refractories. Flow and temperature distributions of the liquid iron have a significant influence on the erosion mechanism. In this work, an improved three-dimensional computational fluid dynamics model is developed to simulate the flow and heat transfer phenomena in the hearth of BlueScope's Port Kembla No. 5 Blast Furnace. Model improvements feature more justified input parameters in turbulence modeling, buoyancy modeling, wall boundary conditions, material properties, and modeling of the solidification of iron. The model is validated by comparing the calculated temperatures with the thermocouple data available, where agreements are established within ±3 pct. The flow distribution in the hearth is discussed for intact and eroded hearth profiles, for sitting and floating coke bed states. It is shown that natural convection affects the flow in several ways: for example, the formation of (a) stagnant zones preventing hearth bottom from eroding or (b) the downward jetting of molten liquid promoting side wall erosion, or (c) at times, a vortex-like peripheral flow, promoting the "elephant foot" type erosion. A significant influence of coke bed permeability on the macroscopic flow pattern and the refractory temperature is observed.

[Nicorandil improves cognitive dysfunction in mice with streptozotocin-induced diabetes].

PubMed

Yan, Wen-Hui; Zhang, Chun-Xi; Xing, Tong; Gong, Xue; Yang, Yu-Xuan; Li, Yi-Nuo; Liu, Xuan; Ayijiang, Jiamaliding; Yu, Ye; Zhang, Meng; Chen, Li-Na

2018-04-20

To observe the protective effects of potassium channel opener nicorandil against cognitive dysfunction in mice with streptozotocin (STZ)-induced diabetes. C57BL/6J mouse models of type 1 diabetes mellitus (T1DM) were established by intraperitoneal injection of STZ and received daily treatment with intragastric administration of nicorandil or saline (model group) for 4 consecutive weeks, with normal C57BL/6J mice serving as control. Fasting blood glucose level was recorded every week and Morris water maze was used to evaluate the cognitive behavior of the mice in the 4th week. At the end of the experiment, the mice were sacrificed to observe the ultrastructural changes in the hippocampus and pancreas under transmission electron microscopy; the contents of glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) in the hippocampus and SOD activity and MDA level in the brain tissue were determined. Compared with the control group, the model group showed significantly increased fasting blood glucose (P<0.001), significantly prolonged escape latency (P<0.05) and increased swimming distance (P<0.01) with ultrastructural damage of pancreatic β cells and in the hippocampus; GIP and GLP-1 contents in the hippocampus (P<0.01) and SOD activity in the brain were significantly decreased (P<0.05) and MDA content was significantly increased in the model group (P<0.05). Compared with the model group, nicorandil treatment did not cause significant changes in fasting blood glucose, but significantly reduced the swimming distance (P<0.05); nicorandil did not improve the ultrastructural changes in pancreatic β cells but obviously improved the ultrastructures of hippocampal neurons and synapses. Nicorandil also significantly increased the contents of GIP and GLP-1 in the hippocampus (P<0.05), enhanced SOD activity (P<0.05) and decreased MDA level (P<0.01) in the brain tissue. Nicorandil improves cognitive dysfunction in mice with STZ-induced diabetes by increasing GIP and GLP-1 contents in the hippocampus and promoting antioxidation to relieve hippocampal injury.

Cardiac rehabilitation using the Family-Centered Empowerment Model versus home-based cardiac rehabilitation in patients with myocardial infarction: a randomised controlled trial

PubMed Central

Vahedian-Azimi, Amir; Hajiesmaieli, Mohammadreza; Kangasniemi, Mari; Alhani, Fatemah; Jelvehmoghaddam, Hosseinali; Fathi, Mohammad; Farzanegan, Behrooz; Ardehali, Seyed H; Hatamian, Sevak; Gahremani, Mehdi; Mosavinasab, Seyed M M; Rostami, Zohreh; Madani, Seyed J; Izadi, Morteza

2016-01-01

Objective To determine if a hybrid cardiac rehabilitation (CR) programme using the Family-Centered Empowerment Model (FCEM) as compared with standard CR will improve patient quality of life, perceived stress and state anxiety of patients with myocardial infarction (MI). Methods We conducted a randomised controlled trial in which patients received either standard home CR or CR using the FCEM strategy. Patient empowerment was measured with FCEM questionnaires preintervention and postintervention for a total of 9 assessments. Quality of life, perceived stress, and state and trait anxiety were assessed using the 36-Item Short Form Health Survey (SF-36), the 14-item Perceived Stress, and the 20-item State and 20-item Trait Anxiety questionnaires, respectively. Results 70 patients were randomised. Baseline characteristics were similar. Ejection fraction was significantly higher in the intervention group at measurements 2 (p=0.01) and 3 (p=0.001). Exercise tolerance measured as walking distance was significantly improved in the intervention group throughout the study. The quality of life results in the FCEM group showed significant improvement both within the group over time (p<0.0001) and when compared with control (p<0.0001). Similarly, the perceived stress and state anxiety results showed significant improvement both within the FCEM group over time (p<0.0001) and when compared with control (p<0.0001). No significant difference was found either within or between groups for trait anxiety. Conclusions The family-centred empowerment model may be an effective hybrid cardiac rehabilitation method for improving the physical and mental health of patients post-MI; however, further study is needed to validate these findings. Clinical Trials.gov identifier NCT02402582. Trial registration number NCT02402582. PMID:27110376

Dark matter, constrained minimal supersymmetric standard model, and lattice QCD.

PubMed

Giedt, Joel; Thomas, Anthony W; Young, Ross D

2009-11-13

Recent lattice measurements have given accurate estimates of the quark condensates in the proton. We use these results to significantly improve the dark matter predictions in benchmark models within the constrained minimal supersymmetric standard model. The predicted spin-independent cross sections are at least an order of magnitude smaller than previously suggested and our results have significant consequences for dark matter searches.

Process Correlation Analysis Model for Process Improvement Identification

PubMed Central

Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data. PMID:24977170

Process correlation analysis model for process improvement identification.

PubMed

Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

Validation of X1 motorcycle model in industrial plant layout by using WITNESSTM simulation software

NASA Astrophysics Data System (ADS)

Hamzas, M. F. M. A.; Bareduan, S. A.; Zakaria, M. Z.; Tan, W. J.; Zairi, S.

2017-09-01

This paper demonstrates a case study on simulation, modelling and analysis for X1 Motorcycles Model. In this research, a motorcycle assembly plant has been selected as a main place of research study. Simulation techniques by using Witness software were applied to evaluate the performance of the existing manufacturing system. The main objective is to validate the data and find out the significant impact on the overall performance of the system for future improvement. The process of validation starts when the layout of the assembly line was identified. All components are evaluated to validate whether the data is significance for future improvement. Machine and labor statistics are among the parameters that were evaluated for process improvement. Average total cycle time for given workstations is used as criterion for comparison of possible variants. From the simulation process, the data used are appropriate and meet the criteria for two-sided assembly line problems.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

PubMed Central

Schoppe, Oliver; King, Andrew J.; Schnupp, Jan W.H.; Harper, Nicol S.

2016-01-01

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear–nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too. PMID:26758822

Evaluating an online pharmaceutical education system for pharmacy interns in critical care settings.

PubMed

Yeh, Yu-Ting; Chen, Hsiang-Yin; Cheng, Kuei-Ju; Hou, Ssu-An; Yen, Yu-Hsuan; Liu, Chien-Tsai

2014-02-01

Incorporating electronic learning (eLearning) system into professional experimental programs such as pharmacy internships is a challenge. However, none of the current systems can fully support the unique needs of clinical pharmacy internship. In this study we enhanced a commercial eLearning system for clinical pharmacy internship (The Clinical Pharmacy Internship eLearning System, CPIES). The KAP questionnaire was used to evaluate the performance of group A with the traditional teaching model and group B with the CPIES teaching model. The CPIES teaching model showed significant improvement in interns' knowledge and practice (p = 0.002 and 0.031, respectively). The traditional teaching model only demonstrated significant improvement in practice (p = 0.011). Moreover, professionalism, such as attitudes on cooperating with other health professionals, is developed by learning from a good mentor. The on-line teaching and traditional teaching methods should undoubtedly be blended in a complete teaching model in order to improve learners' professional knowledge, facilitate correct attitude, and influence good practice. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Gravity model improvement using GEOS 3 /GEM 9 and 10/. [and Seasat altimetry data

NASA Technical Reports Server (NTRS)

Lerch, F. J.; Wagner, C. A.; Klosko, S. M.; Laubscher, R. E.

1979-01-01

Although errors in previous gravity models have produced large uncertainties in the orbital position of GEOS 3, significant improvement has been obtained with new geopotential solutions, Goddard Earth Model (GEM) 9 and 10. The GEM 9 and 10 solutions for the potential coefficients and station coordinates are presented along with a discussion of the new techniques employed. Also presented and discussed are solutions for three fundamental geodetic reference parameters, viz. the mean radius of the earth, the gravitational constant, and mean equatorial gravity. Evaluation of the gravity field is examined together with evaluation of GEM 9 and 10 for orbit determination accuracy. The major objectives of GEM 9 and 10 are achieved. GEOS 3 orbital accuracies from these models are about 1 m in their radial components for 5-day arc lengths. Both models yield significantly improved results over GEM solutions when compared to surface gravimetry, Skylab and GEOS 3 altimetry, and highly accurate BE-C (Beacon Explorer-C) laser ranges. The new values of the parameters discussed are given.

Medical student mental health 3.0: improving student wellness through curricular changes.

PubMed

Slavin, Stuart J; Schindler, Debra L; Chibnall, John T

2014-04-01

Medical education can have significant negative effects on the well-being of medical students. To date, efforts to improve student mental health have focused largely on improving access to mental health providers, reducing the stigma and other barriers to mental health treatment, and implementing ancillary wellness programs. Still, new and innovative models that build on these efforts by directly addressing the root causes of stress that lie within the curriculum itself are needed to properly promote student wellness. In this article, the authors present a new paradigm for improving medical student mental health, by describing an integrated, multifaceted, preclinical curricular change program implemented through the Office of Curricular Affairs at the Saint Louis University School of Medicine starting in the 2009-2010 academic year. The authors found that significant but efficient changes to course content, contact hours, scheduling, grading, electives, learning communities, and required resilience/mindfulness experiences were associated with significantly lower levels of depression symptoms, anxiety symptoms, and stress, and significantly higher levels of community cohesion, in medical students who participated in the expanded wellness program compared with those who preceded its implementation. The authors discuss the utility and relevance of such curricular changes as an overlooked component of change models for improving medical student mental health.

Overview and Evaluation of the Community Multiscale Air ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In late 2016 or early 2017, CMAQ version 5.2 will be released. This new version of CMAQ will contain important updates from the current CMAQv5.1 modeling system, along with several instrumented versions of the model (e.g. decoupled direct method and sulfur tracking). Some specific model updates include the implementation of a new wind-blown dust treatment in CMAQv5.2, a significant improvement over the treatment in v5.1 which can severely overestimate wind-blown dust under certain conditions. Several other major updates to the modeling system include an update to the calculation of aerosols; implementation of full halogen chemistry (CMAQv5.1 contains a partial implementation of halogen chemistry); the new carbon bond 6 (CB6) chemical mechanism; updates to cloud model in CMAQ; and a new lightning assimilation scheme for the WRF model which significant improves the placement and timing of convective precipitation in the WRF precipitation fields. Numerous other updates to the modeling system will also be available in v5.2.

Accuracy Analysis of a Box-wing Theoretical SRP Model

NASA Astrophysics Data System (ADS)

Wang, Xiaoya; Hu, Xiaogong; Zhao, Qunhe; Guo, Rui

2016-07-01

For Beidou satellite navigation system (BDS) a high accuracy SRP model is necessary for high precise applications especially with Global BDS establishment in future. The BDS accuracy for broadcast ephemeris need be improved. So, a box-wing theoretical SRP model with fine structure and adding conical shadow factor of earth and moon were established. We verified this SRP model by the GPS Block IIF satellites. The calculation was done with the data of PRN 1, 24, 25, 27 satellites. The results show that the physical SRP model for POD and forecast for GPS IIF satellite has higher accuracy with respect to Bern empirical model. The 3D-RMS of orbit is about 20 centimeters. The POD accuracy for both models is similar but the prediction accuracy with the physical SRP model is more than doubled. We tested 1-day 3-day and 7-day orbit prediction. The longer is the prediction arc length, the more significant is the improvement. The orbit prediction accuracy with the physical SRP model for 1-day, 3-day and 7-day arc length are 0.4m, 2.0m, 10.0m respectively. But they are 0.9m, 5.5m and 30m with Bern empirical model respectively. We apply this means to the BDS and give out a SRP model for Beidou satellites. Then we test and verify the model with Beidou data of one month only for test. Initial results show the model is good but needs more data for verification and improvement. The orbit residual RMS is similar to that with our empirical force model which only estimate the force for along track, across track direction and y-bias. But the orbit overlap and SLR observation evaluation show some improvement. The remaining empirical force is reduced significantly for present Beidou constellation.

Modeling the Surface Water-Groundwater Interaction in Arid and Semi-Arid Regions Impacted by Agricultural Activities

NASA Astrophysics Data System (ADS)

Tian, Y.; Wu, B.; Zheng, Y.

2013-12-01

In many semi-arid and arid regions, interaction between surface water and groundwater plays an important role in the eco-hydrological system. The interaction is often complicated by agricultural activities such as surface water diversion, groundwater pumping, and irrigation. In existing surface water-groundwater integrated models, simulation of the interaction is often simplified, which could introduce significant simulation uncertainty under certain circumstance. In this study, GSFLOW, a USGS model coupling PRMS and MODFLOW, was improved to better characterize the surface water-groundwater interaction. The practices of water diversion from rivers, groundwater pumping and irrigation are explicitly simulated. In addition, the original kinematic wave routing method was replaced by a dynamic wave routing method. The improved model was then applied in Zhangye Basin (the midstream part of Heihe River Baisn), China, where the famous 'Silk Road' came through. It is a typical semi-arid region of the western China, with extensive agriculture in its oasis. The model was established and calibrated using the data in 2000-2008. A series of numerical experiments were conducted to evaluate the effect of those improvements. It has been demonstrated that with the improvements, the observed streamflow and groundwater level were better reproduced by the model. The improvements have a significant impact on the simulation of multiple fluxes associated with the interaction, such as groundwater discharge, riverbed seepage, infiltration, etc. Human activities were proved to be key elements of the water cycle in the study area. The study results have important implications to the water resources modeling and management in semi-arid and arid basins.

Does probabilistic modelling of linkage disequilibrium evolution improve the accuracy of QTL location in animal pedigree?

PubMed

Cierco-Ayrolles, Christine; Dejean, Sébastien; Legarra, Andrés; Gilbert, Hélène; Druet, Tom; Ytournel, Florence; Estivals, Delphine; Oumouhou, Naïma; Mangin, Brigitte

2010-10-22

Since 2001, the use of more and more dense maps has made researchers aware that combining linkage and linkage disequilibrium enhances the feasibility of fine-mapping genes of interest. So, various method types have been derived to include concepts of population genetics in the analyses. One major drawback of many of these methods is their computational cost, which is very significant when many markers are considered. Recent advances in technology, such as SNP genotyping, have made it possible to deal with huge amount of data. Thus the challenge that remains is to find accurate and efficient methods that are not too time consuming. The study reported here specifically focuses on the half-sib family animal design. Our objective was to determine whether modelling of linkage disequilibrium evolution improved the mapping accuracy of a quantitative trait locus of agricultural interest in these populations. We compared two methods of fine-mapping. The first one was an association analysis. In this method, we did not model linkage disequilibrium evolution. Therefore, the modelling of the evolution of linkage disequilibrium was a deterministic process; it was complete at time 0 and remained complete during the following generations. In the second method, the modelling of the evolution of population allele frequencies was derived from a Wright-Fisher model. We simulated a wide range of scenarios adapted to animal populations and compared these two methods for each scenario. Our results indicated that the improvement produced by probabilistic modelling of linkage disequilibrium evolution was not significant. Both methods led to similar results concerning the location accuracy of quantitative trait loci which appeared to be mainly improved by using four flanking markers instead of two. Therefore, in animal half-sib designs, modelling linkage disequilibrium evolution using a Wright-Fisher model does not significantly improve the accuracy of the QTL location when compared to a simpler method assuming complete and constant linkage between the QTL and the marker alleles. Finally, given the high marker density available nowadays, the simpler method should be preferred as it gives accurate results in a reasonable computing time.

Quantification of the multi-streaming effect in redshift space distortion

NASA Astrophysics Data System (ADS)

Zheng, Yi; Zhang, Pengjie; Oh, Minji

2017-05-01

Both multi-streaming (random motion) and bulk motion cause the Finger-of-God (FoG) effect in redshift space distortion (RSD). We apply a direct measurement of the multi-streaming effect in RSD from simulations, proving that it induces an additional, non-negligible FoG damping to the redshift space density power spectrum. We show that, including the multi-streaming effect, the RSD modelling is significantly improved. We also provide a theoretical explanation based on halo model for the measured effect, including a fitting formula with one to two free parameters. The improved understanding of FoG helps break the fσ8-σv degeneracy in RSD cosmology, and has the potential of significantly improving cosmological constraints.

Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.

New features to the night sky radiance model illumina: Hyperspectral support, improved obstacles and cloud reflection

NASA Astrophysics Data System (ADS)

Aubé, M.; Simoneau, A.

2018-05-01

Illumina is one of the most physically detailed artificial night sky brightness model to date. It has been in continuous development since 2005 [1]. In 2016-17, many improvements were made to the Illumina code including an overhead cloud scheme, an improved blocking scheme for subgrid obstacles (trees and buildings), and most importantly, a full hyperspectral modeling approach. Code optimization resulted in significant reduction in execution time enabling users to run the model on standard personal computers for some applications. After describing the new schemes introduced in the model, we give some examples of applications for a peri-urban and a rural site both located inside the International Dark Sky reserve of Mont-Mégantic (QC, Canada).

Evaluation of Industry Standard Turbulence Models on an Axisymmetric Supersonic Compression Corner

NASA Technical Reports Server (NTRS)

DeBonis, James R.

2015-01-01

Reynolds-averaged Navier-Stokes computations of a shock-wave/boundary-layer interaction (SWBLI) created by a Mach 2.85 flow over an axisymmetric 30-degree compression corner were carried out. The objectives were to evaluate four turbulence models commonly used in industry, for SWBLIs, and to evaluate the suitability of this test case for use in further turbulence model benchmarking. The Spalart-Allmaras model, Menter's Baseline and Shear Stress Transport models, and a low-Reynolds number k- model were evaluated. Results indicate that the models do not accurately predict the separation location; with the SST model predicting the separation onset too early and the other models predicting the onset too late. Overall the Spalart-Allmaras model did the best job in matching the experimental data. However there is significant room for improvement, most notably in the prediction of the turbulent shear stress. Density data showed that the simulations did not accurately predict the thermal boundary layer upstream of the SWBLI. The effect of turbulent Prandtl number and wall temperature were studied in an attempt to improve this prediction and understand their effects on the interaction. The data showed that both parameters can significantly affect the separation size and location, but did not improve the agreement with the experiment. This case proved challenging to compute and should provide a good test for future turbulence modeling work.

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

Yu, V; Nguyen, D; Tran, A

Purpose: To develop and clinically implement 4π radiotherapy, an inverse optimization platform that maximally utilizes non-coplanar intensity modulated radiotherapy (IMRT) beams to significantly improve critical organ sparing. Methods: A 3D scanner was used to digitize the human and phantom subject surfaces, which were positioned in the computer assisted design (CAD) model of a TrueBeam machine to create a virtual geometrical model, based on which, the feasible beam space was calculated for different tumor locations. Beamlets were computed for all feasible beams using convolution/superposition. A column generation algorithm was employed to optimize patient specific beam orientations and fluence maps. Optimal routingmore » through all selected beams were calculated by a level set method. The resultant plans were converted to XML files and delivered to phantoms in the TrueBeam developer mode. Finally, 4π plans were recomputed in Eclipse and manually delivered to recurrent GBM patients. Results: Compared to IMRT utilizing manually selected beams and volumetric modulated arc therapy plans, markedly improved dosimetry was observed using 4π for the brain, head and neck, liver, lung, and prostate patients. The improvements were due to significantly improved conformality and reduced high dose spillage to organs mediolateral to the PTV. The virtual geometrical model was experimentally validated. Safety margins with 99.9% confidence in collision avoidance were included to the model based model accuracy estimates determined via 300 physical machine to phantom distance measurements. Automated delivery in the developer mode was completed in 10 minutes and collision free. Manual 4 π treatment on the GBM cases resulted in significant brainstem sparing and took 35–45 minutes including multiple images, which showed submillimeter cranial intrafractional motion. Conclusion: The mathematical modeling utilized in 4π is accurate to create and guide highly complex non-coplanar IMRT treatments that consistently and significantly outperform human-operator-created plans. Deliverability of such plans is clinically demonstrated. This work is funded by Varian Medical Systems and the NSF Graduate Research Fellowship DGE-1144087.« less

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

Simpson, L.; Britt, J.; Birkmire, R.

ITN Energy Systems, Inc., and Global Solar Energy, Inc., assisted by NREL's PV Manufacturing R&D program, have continued to advance CIGS production technology by developing trajectory-oriented predictive/control models, fault-tolerance control, control platform development, in-situ sensors, and process improvements. Modeling activities included developing physics-based and empirical models for CIGS and sputter-deposition processing, implementing model-based control, and applying predictive models to the construction of new evaporation sources and for control. Model-based control is enabled by implementing reduced or empirical models into a control platform. Reliability improvement activities include implementing preventive maintenance schedules; detecting failed sensors/equipment and reconfiguring to tinue processing; and systematicmore » development of fault prevention and reconfiguration strategies for the full range of CIGS PV production deposition processes. In-situ sensor development activities have resulted in improved control and indicated the potential for enhanced process status monitoring and control of the deposition processes. Substantial process improvements have been made, including significant improvement in CIGS uniformity, thickness control, efficiency, yield, and throughput. In large measure, these gains have been driven by process optimization, which in turn have been enabled by control and reliability improvements due to this PV Manufacturing R&D program.« less

A Review of Mathematical Models for Leukemia and Lymphoma

PubMed Central

Clapp, Geoffrey; Levy, Doron

2014-01-01

Recently, there has been significant activity in the mathematical community, aimed at developing quantitative tools for studying leukemia and lymphoma. Mathematical models have been applied to evaluate existing therapies and to suggest novel therapies. This article reviews the recent contributions of mathematical modeling to leukemia and lymphoma research. These developments suggest that mathematical modeling has great potential in this field. Collaboration between mathematicians, clinicians, and experimentalists can significantly improve leukemia and lymphoma therapy. PMID:26744598

Anharmonic Normal Mode Analysis of Elastic Network Model Improves the Modeling of Atomic Fluctuations in Protein Crystal Structures

PubMed Central

Zheng, Wenjun

2010-01-01

Abstract Protein conformational dynamics, despite its significant anharmonicity, has been widely explored by normal mode analysis (NMA) based on atomic or coarse-grained potential functions. To account for the anharmonic aspects of protein dynamics, this study proposes, and has performed, an anharmonic NMA (ANMA) based on the Cα-only elastic network models, which assume elastic interactions between pairs of residues whose Cα atoms or heavy atoms are within a cutoff distance. The key step of ANMA is to sample an anharmonic potential function along the directions of eigenvectors of the lowest normal modes to determine the mean-squared fluctuations along these directions. ANMA was evaluated based on the modeling of anisotropic displacement parameters (ADPs) from a list of 83 high-resolution protein crystal structures. Significant improvement was found in the modeling of ADPs by ANMA compared with standard NMA. Further improvement in the modeling of ADPs is attained if the interactions between a protein and its crystalline environment are taken into account. In addition, this study has determined the optimal cutoff distances for ADP modeling based on elastic network models, and these agree well with the peaks of the statistical distributions of distances between Cα atoms or heavy atoms derived from a large set of protein crystal structures. PMID:20550915

Improved Intraseasonal Variability in the NASA GEOS AGCM with 2-moment Microphysics and a Shallow Cumulus Parameterization

NASA Technical Reports Server (NTRS)

Arnold, Nathan; Barahona, Donifan; Achuthavarier, Deepthi

2017-01-01

Weather and climate models have long struggled to realistically simulate the Madden-Julian Oscillation (MJO). Here we present a significant improvement in MJO simulation in NASA's GEOS atmospheric model with the implementation of 2-moment microphysics and the UW shallow cumulus parameterization. Comparing ten-year runs (2007-2016) with the old (1mom) and updated (2mom+shlw) model physics, the updated model has increased intra-seasonal variance with increased coherence. Surface fluxes and OLR are found to vary more realistically with precipitation, and a moisture budget suggests that changes in rain reevaporation and the cloud longwave feedback help support heavy precipitation. Preliminary results also show improved MJO hindcast skill.

Critical analysis of 3-D organoid in vitro cell culture models for high-throughput drug candidate toxicity assessments.

PubMed

Astashkina, Anna; Grainger, David W

2014-04-01

Drug failure due to toxicity indicators remains among the primary reasons for staggering drug attrition rates during clinical studies and post-marketing surveillance. Broader validation and use of next-generation 3-D improved cell culture models are expected to improve predictive power and effectiveness of drug toxicological predictions. However, after decades of promising research significant gaps remain in our collective ability to extract quality human toxicity information from in vitro data using 3-D cell and tissue models. Issues, challenges and future directions for the field to improve drug assay predictive power and reliability of 3-D models are reviewed. Copyright © 2014 Elsevier B.V. All rights reserved.

WAM: an improved algorithm for modelling antibodies on the WEB.

PubMed

Whitelegg, N R; Rees, A R

2000-12-01

An improved antibody modelling algorithm has been developed which incorporates significant improvements to the earlier versions developed by Martin et al. (1989, 1991), Pedersen et al. (1992) and Rees et al. (1996) and known as AbM (Oxford Molecular). The new algorithm, WAM (for Web Antibody Modelling), has been launched as an online modelling service and is located at URL http://antibody.bath.ac.uk. Here we provide a summary only of the important features of WAM. Readers interested in further details are directed to the website, which gives extensive background information on the methods employed. A brief description of the rationale behind some of the newer methodology (specifically, the knowledge-based screens) is also given.

Medium- and Long-term Prediction of LOD Change by the Leap-step Autoregressive Model

NASA Astrophysics Data System (ADS)

Wang, Qijie

2015-08-01

The accuracy of medium- and long-term prediction of length of day (LOD) change base on combined least-square and autoregressive (LS+AR) deteriorates gradually. Leap-step autoregressive (LSAR) model can significantly reduce the edge effect of the observation sequence. Especially, LSAR model greatly improves the resolution of signals’ low-frequency components. Therefore, it can improve the efficiency of prediction. In this work, LSAR is used to forecast the LOD change. The LOD series from EOP 08 C04 provided by IERS is modeled by both the LSAR and AR models. The results of the two models are analyzed and compared. When the prediction length is between 10-30 days, the accuracy improvement is less than 10%. When the prediction length amounts to above 30 day, the accuracy improved obviously, with the maximum being around 19%. The results show that the LSAR model has higher prediction accuracy and stability in medium- and long-term prediction.

Comparison of Individualized Covert Modeling, Self-Control Desensitization, and Study Skills Training for Alleviation of Test Anxiety.

ERIC Educational Resources Information Center

Harris, Gina; Johhson, Suzanne Bennett

1980-01-01

Individualized covert modeling and self-control desensitization substantially reduced self-reported test anxiety. However, the individualized covert modeling group was the only treatment group that showed significant improvement in academic performance. (Author)

Improvement of Reynolds-Stress and Triple-Product Lag Models

NASA Technical Reports Server (NTRS)

Olsen, Michael E.; Lillard, Randolph P.

2017-01-01

The Reynolds-stress and triple product Lag models were created with a normal stress distribution which was denied by a 4:3:2 distribution of streamwise, spanwise and wall normal stresses, and a ratio of r(sub w) = 0.3k in the log layer region of high Reynolds number flat plate flow, which implies R11(+)= [4/(9/2)*.3] approximately 2.96. More recent measurements show a more complex picture of the log layer region at high Reynolds numbers. The first cut at improving these models along with the direction for future refinements is described. Comparison with recent high Reynolds number data shows areas where further work is needed, but also shows inclusion of the modeled turbulent transport terms improve the prediction where they influence the solution. Additional work is needed to make the model better match experiment, but there is significant improvement in many of the details of the log layer behavior.

Current target acquisition methodology in force on force simulations

NASA Astrophysics Data System (ADS)

Hixson, Jonathan G.; Miller, Brian; Mazz, John P.

2017-05-01

The U.S. Army RDECOM CERDEC NVESD MSD's target acquisition models have been used for many years by the military community in force on force simulations for training, testing, and analysis. There have been significant improvements to these models over the past few years. The significant improvements are the transition of ACQUIRE TTP-TAS (ACQUIRE Targeting Task Performance Target Angular Size) methodology for all imaging sensors and the development of new discrimination criteria for urban environments and humans. This paper is intended to provide an overview of the current target acquisition modeling approach and provide data for the new discrimination tasks. This paper will discuss advances and changes to the models and methodologies used to: (1) design and compare sensors' performance, (2) predict expected target acquisition performance in the field, (3) predict target acquisition performance for combat simulations, and (4) how to conduct model data validation for combat simulations.

Predicting significant torso trauma.

PubMed

Nirula, Ram; Talmor, Daniel; Brasel, Karen

2005-07-01

Identification of motor vehicle crash (MVC) characteristics associated with thoracoabdominal injury would advance the development of automatic crash notification systems (ACNS) by improving triage and response times. Our objective was to determine the relationships between MVC characteristics and thoracoabdominal trauma to develop a torso injury probability model. Drivers involved in crashes from 1993 to 2001 within the National Automotive Sampling System were reviewed. Relationships between torso injury and MVC characteristics were assessed using multivariate logistic regression. Receiver operating characteristic curves were used to compare the model to current ACNS models. There were a total of 56,466 drivers. Age, ejection, braking, avoidance, velocity, restraints, passenger-side impact, rollover, and vehicle weight and type were associated with injury (p < 0.05). The area under the receiver operating characteristic curve (83.9) was significantly greater than current ACNS models. We have developed a thoracoabdominal injury probability model that may improve patient triage when used with ACNS.

Advanced scatter search approach and its application in a sequencing problem of mixed-model assembly lines in a case company

NASA Astrophysics Data System (ADS)

Liu, Qiong; Wang, Wen-xi; Zhu, Ke-ren; Zhang, Chao-yong; Rao, Yun-qing

2014-11-01

Mixed-model assembly line sequencing is significant in reducing the production time and overall cost of production. To improve production efficiency, a mathematical model aiming simultaneously to minimize overtime, idle time and total set-up costs is developed. To obtain high-quality and stable solutions, an advanced scatter search approach is proposed. In the proposed algorithm, a new diversification generation method based on a genetic algorithm is presented to generate a set of potentially diverse and high-quality initial solutions. Many methods, including reference set update, subset generation, solution combination and improvement methods, are designed to maintain the diversification of populations and to obtain high-quality ideal solutions. The proposed model and algorithm are applied and validated in a case company. The results indicate that the proposed advanced scatter search approach is significant for mixed-model assembly line sequencing in this company.

A small business worksite wellness model for improving health behaviors.

PubMed

Merrill, Ray M

2013-08-01

To evaluate the effectiveness of a wellness program delivered by WellSteps, LLC, aimed at improving employee health behaviors in small companies that lack the resources to independently develop and manage a wellness program. Analyses are based on 618 employees from five diverse companies that completed an initial personal health assessment. Exercise and dietary behaviors significantly improved across the five companies. Significant improvements in health perception and life satisfaction also resulted and were associated with improvements in health behaviors. Three of the five companies, each with fewer than 50 employees, were most effective in influencing positive health behaviors, health perceptions, and life satisfaction. The worksite wellness program effectively improved health behaviors, health perceptions, and life satisfaction.

A new predictive model for continuous positive airway pressure in the treatment of obstructive sleep apnea.

PubMed

Ebben, Matthew R; Narizhnaya, Mariya; Krieger, Ana C

2017-05-01

Numerous mathematical formulas have been developed to determine continuous positive airway pressure (CPAP) without an in-laboratory titration study. Recent studies have shown that style of CPAP mask can affect the optimal pressure requirement. However, none of the current models take mask style into account. Therefore, the goal of this study was to develop new predictive models of CPAP that take into account the style of mask interface. Data from 200 subjects with attended CPAP titrations during overnight polysomnograms using nasal masks and 132 subjects using oronasal masks were randomized and split into either a model development or validation group. Predictive models were then created in each model development group and the accuracy of the models was then tested in the model validation groups. The correlation between our new oronasal model and laboratory determined optimal CPAP was significant, r = 0.61, p < 0.001. Our nasal formula was also significantly related to laboratory determined optimal CPAP, r = 0.35, p < 0.001. The oronasal model created in our study significantly outperformed the original CPAP predictive model developed by Miljeteig and Hoffstein, z = 1.99, p < 0.05. The predictive performance of our new nasal model did not differ significantly from Miljeteig and Hoffstein's original model, z = -0.16, p < 0.90. The best predictors for the nasal mask group were AHI, lowest SaO2, and neck size, whereas the top predictors in the oronasal group were AHI and lowest SaO2. Our data show that predictive models of CPAP that take into account mask style can significantly improve the formula's accuracy. Most of the past models likely focused on model development with nasal masks (mask style used for model development was not typically reported in previous investigations) and are not well suited for patients using an oronasal interface. Our new oronasal CPAP prediction equation produced significantly improved performance compared to the well-known Miljeteig and Hoffstein formula in patients titrated on CPAP with an oronasal mask and was also significantly related to laboratory determined optimal CPAP.

Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

NASA Astrophysics Data System (ADS)

Langlois, A.; Royer, A.; Derksen, C.; Montpetit, B.; Dupont, F.; GoïTa, K.

2012-12-01

Satellite-passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two-step iteration method compared to standalone simulations with the snow model.

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

Minimizing the total harmonic distortion for a 3 kW, 20 kHz ac to dc converter using SPICE

NASA Technical Reports Server (NTRS)

Lollar, Louis F.; Kapustka, Robert E.

1988-01-01

This paper describes the SPICE model of a transformer-rectified-filter (TRF) circuit and the Micro-CAP (Microcomputer Circuit Analysis Program) model and their application. The models were used to develop an actual circuit with reduced input current THD. The SPICE analysis consistently predicted the THD improvements in actual circuits as various designs were attempted. In an effort to predict and verify load regulation, the incorporation of saturable inductor models significantly improved the fidelity of the TRF circuit output voltage.

On central-difference and upwind schemes

NASA Technical Reports Server (NTRS)

Swanson, R. C.; Turkel, Eli

1990-01-01

A class of numerical dissipation models for central-difference schemes constructed with second- and fourth-difference terms is considered. The notion of matrix dissipation associated with upwind schemes is used to establish improved shock capturing capability for these models. In addition, conditions are given that guarantee that such dissipation models produce a Total Variation Diminishing (TVD) scheme. Appropriate switches for this type of model to ensure satisfaction of the TVD property are presented. Significant improvements in the accuracy of a central-difference scheme are demonstrated by computing both inviscid and viscous transonic airfoil flows.

Filling the Gaps: The Synergistic Application of Satellite Data for the Volcanic Ash Threat to Aviation

NASA Technical Reports Server (NTRS)

Murray, John; Vernier, Jean-Paul; Fairlie, T. Duncan; Pavolonis, Michael; Krotkov, Nickolay A.; Lindsay, Francis; Haynes, John

2013-01-01

Although significant progress has been made in recent years, estimating volcanic ash concentration for the full extent of the airspace affected by volcanic ash remains a challenge. No single satellite, airborne or ground observing system currently exists which can sufficiently inform dispersion models to provide the degree of accuracy required to use them with a high degree of confidence for routing aircraft in and near volcanic ash. Toward this end, the detection and characterization of volcanic ash in the atmosphere may be substantially improved by integrating a wider array of observing systems and advancements in trajectory and dispersion modeling to help solve this problem. The qualitative aspect of this effort has advanced significantly in the past decade due to the increase of highly complementary observational and model data currently available. Satellite observations, especially when coupled with trajectory and dispersion models can provide a very accurate picture of the 3-dimensional location of ash clouds. The accurate estimate of the mass loading at various locations throughout the entire plume, however improving, remains elusive. This paper examines the capabilities of various satellite observation systems and postulates that model-based volcanic ash concentration maps and forecasts might be significantly improved if the various extant satellite capabilities are used together with independent, accurate mass loading data from other observing systems available to calibrate (tune) ash concentration retrievals from the satellite systems.

Thermal comfort modelling of body temperature and psychological variations of a human exercising in an outdoor environment

NASA Astrophysics Data System (ADS)

Vanos, Jennifer K.; Warland, Jon S.; Gillespie, Terry J.; Kenny, Natasha A.

2012-01-01

Human thermal comfort assessments pertaining to exercise while in outdoor environments can improve urban and recreational planning. The current study applied a simple four-segment skin temperature approach to the COMFA (COMfort FormulA) outdoor energy balance model. Comparative results of measured mean skin temperature ( {{bar{T}}}nolimits_{{Msk}} ) with predicted {{bar{T}}}nolimits_{{sk}} indicate that the model accurately predicted {{bar{T}}}nolimits_{{sk}} , showing significantly strong agreement ( r = 0.859, P < 0.01) during outdoor exercise (cycling and running). The combined 5-min mean variation of the {{bar{T}}}nolimits_{{sk}} RMSE was 1.5°C, with separate cycling and running giving RMSE of 1.4°C and 1.6°C, respectively, and no significant difference in residuals. Subjects' actual thermal sensation (ATS) votes displayed significant strong rank correlation with budget scores calculated using both measured and predicted {{bar{T}}}nolimits_{{sk}} ( r s = 0.507 and 0.517, respectively, P < 0.01). These results show improved predictive strength of ATS of subjects as compared to the original and updated COMFA models. This psychological improvement, plus {{bar{T}}}nolimits_{{sk}} and T c validations, enables better application to a variety of outdoor spaces. This model can be used in future research studying linkages between thermal discomfort, subsequent decreases in physical activity, and negative health trends.

Fermentation of Saccharomyces cerevisiae - Combining kinetic modeling and optimization techniques points out avenues to effective process design.

PubMed

Scheiblauer, Johannes; Scheiner, Stefan; Joksch, Martin; Kavsek, Barbara

2018-09-14

A combined experimental/theoretical approach is presented, for improving the predictability of Saccharomyces cerevisiae fermentations. In particular, a mathematical model was developed explicitly taking into account the main mechanisms of the fermentation process, allowing for continuous computation of key process variables, including the biomass concentration and the respiratory quotient (RQ). For model calibration and experimental validation, batch and fed-batch fermentations were carried out. Comparison of the model-predicted biomass concentrations and RQ developments with the corresponding experimentally recorded values shows a remarkably good agreement for both batch and fed-batch processes, confirming the adequacy of the model. Furthermore, sensitivity studies were performed, in order to identify model parameters whose variations have significant effects on the model predictions: our model responds with significant sensitivity to the variations of only six parameters. These studies provide a valuable basis for model reduction, as also demonstrated in this paper. Finally, optimization-based parametric studies demonstrate how our model can be utilized for improving the efficiency of Saccharomyces cerevisiae fermentations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Using anthropomorphic avatars resembling sedentary older individuals as models to enhance self-efficacy and adherence to physical activity: psychophysiological correlates.

PubMed

Ruiz, Jorge G; Andrade, Allen D; Anam, Ramankumar; Aguiar, Rudxandra; Sun, Huaping; Roos, Bernard A

2012-01-01

The prevalence of obesity and associated health complications are currently at unprecedented levels. Physical activity in this population can improve patient outcomes. Virtual reality (VR) self-modeling may improve self-efficacy and adherence to physical activity. We conducted a comparative study of 30 participants randomized to 3 versions of a 3D avatar-based VR intervention about exercise: virtual representation of the self exercising condition; virtual representation of other person exercising and control condition. Participants in the virtual representation of the self group significantly increased their levels of physical activity. The improvement in physical activity for participants in the visual representation of other person exercising was marginal. The improvement for the control group was not significant. However, the effect sizes for comparing the pre and post intervention physical activity levels were quite large for all three groups. We did not find any group difference in the improvements of physical activity levels and self-efficacy among sedentary, overweight or obese individuals.

TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis

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

Krafft, S; The University of Texas Graduate School of Biomedical Sciences, Houston, TX; Briere, T

2015-06-15

Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. Amore » total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP NTCP modeling is warranted. This work was supported by the Rosalie B. Hite Fellowship in Cancer research awarded to SPK.« less

Effect of nutrition education intervention based on Pender's Health Promotion Model in improving the frequency and nutrient intake of breakfast consumption among female Iranian students.

PubMed

Dehdari, Tahereh; Rahimi, Tahereh; Aryaeian, Naheed; Gohari, Mahmood Reza

2014-03-01

To determine the effectiveness of nutrition education intervention based on Pender's Health Promotion Model in improving the frequency and nutrient intake of breakfast consumption among female Iranian students. The quasi-experimental study based on Pender's Health Promotion Model was conducted during April-June 2011. Information (data) was collected by self-administered questionnaire. In addition, a 3 d breakfast record was analysed. P < 0·05 was considered significant. Two middle schools in average-income areas of Qom, Iran. One hundred female middle-school students. There was a significant reduction in immediate competing demands and preferences, perceived barriers and negative activity-related affect constructs in the experimental group after education compared with the control group. In addition, perceived benefit, perceived self-efficacy, positive activity-related affect, interpersonal influences, situational influences, commitment to a plan of action, frequency and intakes of macronutrients and most micronutrients of breakfast consumption were also significantly higher in the experimental group compared with the control group after the nutrition education intervention. Constructs of Pender's Health Promotion Model provide a suitable source for designing strategies and content of a nutrition education intervention for improving the frequency and nutrient intake of breakfast consumption among female students.

Bone marrow mesenchymal stem cells combined with minocycline improve spinal cord injury in a rat model

PubMed Central

Chen, Dayong; Zeng, Wei; Fu, Yunfeng; Gao, Meng; Lv, Guohua

2015-01-01

The aims of this study were to assess that the effects of bone marrow mesenchymal stem cells (BMSCs) combination with minocycline improve spinal cord injury (SCI) in rat model. In the present study, the Wistar rats were randomly divided into five groups: control group, SCI group, BMSCs group, Minocycline group and BMSCs + minocycline group. Basso, Beattie and Bresnahan (BBB) test and MPO activity were used to assess the effect of combination therapy on locomotion and neutrophil infiltration. Inflammation factors, VEGF and BDNF expression, caspase-3 activation, phosphorylation-p38MAPK, proNGF, p75NTR and RhoA expressions were estimated using commercial kits or western blot, respectively. BBB scores were significantly increased and MPO activity was significantly undermined by combination therapy. In addition, combination therapy significantly decreased inflammation factors in SCI rats. Results from western blot showed that combination therapy significantly up-regulated the protein of VEGF and BDNF expression and down-regulated the protein of phosphorylation-p38MAPK, proNGF, p75NTR and RhoA expressions in SCI rats. Combination therapy stimulation also suppressed the caspase-3 activation in SCI rats. These results demonstrated that the effects of bone marrow mesenchymal stem cells combination with minocycline improve SCI in rat model. PMID:26722382

Refinement of Generalized Born Implicit Solvation Parameters for Nucleic Acids and their Complexes with Proteins

PubMed Central

Nguyen, Hai; Pérez, Alberto; Bermeo, Sherry; Simmerling, Carlos

2016-01-01

The Generalized Born (GB) implicit solvent model has undergone significant improvements in accuracy for modeling of proteins and small molecules. However, GB still remains a less widely explored option for nucleic acid simulations, in part because fast GB models are often unable to maintain stable nucleic acid structures, or they introduce structural bias in proteins, leading to difficulty in application of GB models in simulations of protein-nucleic acid complexes. Recently, GB-neck2 was developed to improve the behavior of protein simulations. In an effort to create a more accurate model for nucleic acids, a similar procedure to the development of GB-neck2 is described here for nucleic acids. The resulting parameter set significantly reduces absolute and relative energy error relative to Poisson Boltzmann for both nucleic acids and nucleic acid-protein complexes, when compared to its predecessor GB-neck model. This improvement in solvation energy calculation translates to increased structural stability for simulations of DNA and RNA duplexes, quadruplexes, and protein-nucleic acid complexes. The GB-neck2 model also enables successful folding of small DNA and RNA hairpins to near native structures as determined from comparison with experiment. The functional form and all required parameters are provided here and also implemented in the AMBER software. PMID:26574454

The potential for improving remote primary productivity estimates through subsurface chlorophyll and irradiance measurement

NASA Astrophysics Data System (ADS)

Jacox, Michael G.; Edwards, Christopher A.; Kahru, Mati; Rudnick, Daniel L.; Kudela, Raphael M.

2015-02-01

A 26-year record of depth integrated primary productivity (PP) in the Southern California Current System (SCCS) is analyzed with the goal of improving satellite net primary productivity (PP) estimates. Modest improvements in PP model performance are achieved by tuning existing algorithms for the SCCS, particularly by parameterizing carbon fixation rate in the vertically generalized production model as a function of surface chlorophyll concentration and distance from shore. Much larger improvements are enabled by improving the accuracy of subsurface chlorophyll and light profiles. In a simple vertically resolved production model for the SCCS (VRPM-SC), substitution of in situ surface data for remote sensing estimates offers only marginal improvements in model r2 (from 0.54 to 0.56) and total log10 root mean squared difference (from 0.22 to 0.21), while inclusion of in situ chlorophyll and light profiles improves these metrics to 0.77 and 0.15, respectively. Autonomous underwater gliders, capable of measuring subsurface properties on long-term, long-range deployments, significantly improve PP model fidelity in the SCCS. We suggest their use (and that of other autonomous profilers such as Argo floats) in conjunction with satellites as a way forward for large-scale improvements in PP estimation.

Central or Peripheral Delivery of an Adenosine A1 Receptor Agonist Improves Mechanical Allodynia in a Mouse Model of Painful Diabetic Neuropathy

PubMed Central

Katz, N. K.; Ryals, J. M.; Wright, D. E.

2014-01-01

Diabetic peripheral neuropathy is a common complication of diabetes mellitus, and a significant proportion of individuals suffer debilitating pain that significantly affects their quality of life. Unfortunately, symptomatic treatment options have limited efficacy, and often carry significant risk of systemic adverse effects. Activation of the adenosine A1 receptor (A1R) by the analgesic small molecule adenosine has been shown to have antinociceptive benefits in models of inflammatory and neuropathic pain. The current study used a mouse model of painful diabetic neuropathy to determine the effect of diabetes on endogenous adenosine production, and if central or peripheral delivery of adenosine receptor agonists could alleviate signs of mechanical allodynia in diabetic mice. Diabetes was induced using streptozocin in male A/J mice. Mechanical withdrawal thresholds were measured weekly to characterize neuropathy phenotype. Hydrolysis of AMP into adenosine by ectonucleotidases was determined in the dorsal root ganglia (DRG) and spinal cord at 8-weeks post-induction of diabetes. AMP, adenosine and the specific A1R agonist, N6-cyclopentyladenosine (CPA), were administered both centrally (intrathecal) and peripherally (intraplantar) to determine the effect of activation of adenosine receptors on mechanical allodynia in diabetic mice. Eight weeks post-induction, diabetic mice displayed significantly decreased hydrolysis of extracellular AMP in the DRG; at this same time, diabetic mice displayed significantly decreased mechanical withdrawal thresholds compared to nondiabetic controls. Central delivery AMP, adenosine and CPA significantly improved mechanical withdrawal thresholds in diabetic mice. Surprisingly, peripheral delivery of CPA also improved mechanical allodynia in diabetic mice. This study provides new evidence that diabetes significantly affects endogenous AMP hydrolysis, suggesting that altered adenosine production could contribute to the development of painful diabetic neuropathy. Moreover, central and peripheral activation of A1R significantly improved mechanical sensitivity, warranting further investigation into this important antinociceptive pathway as a novel therapeutic option for the treatment of painful diabetic neuropathy. PMID:25451280

Generator Dynamic Model Validation and Parameter Calibration Using Phasor Measurements at the Point of Connection

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

Huang, Zhenyu; Du, Pengwei; Kosterev, Dmitry

2013-05-01

Disturbance data recorded by phasor measurement units (PMU) offers opportunities to improve the integrity of dynamic models. However, manually tuning parameters through play-back events demands significant efforts and engineering experiences. In this paper, a calibration method using the extended Kalman filter (EKF) technique is proposed. The formulation of EKF with parameter calibration is discussed. Case studies are presented to demonstrate its validity. The proposed calibration method is cost-effective, complementary to traditional equipment testing for improving dynamic model quality.

Parametrization of turbulence models using 3DVAR data assimilation in laboratory conditions

NASA Astrophysics Data System (ADS)

Olbert, A. I.; Nash, S.; Ragnoli, E.; Hartnett, M.

2013-12-01

In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ɛ model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ɛ model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. Such analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows. This research further demonstrates how 3DVAR can be utilized to identify and quantify shortcomings of the numerical model and consequently to improve forecasting by correct parameterization of the turbulence models. Such improvements may greatly benefit physical oceanography in terms of understanding and monitoring of coastal systems and the engineering sector through applications in coastal structure design, marine renewable energy and pollutant transport.

Numerical optimization of composite hip endoprostheses under different loading conditions

NASA Technical Reports Server (NTRS)

Blake, T. A.; Davy, D. T.; Saravanos, D. A.; Hopkins, D. A.

1992-01-01

The optimization of composite hip implants was investigated. Emphasis was placed on the effect of shape and material tailoring of the implant to improve the implant-bone interaction. A variety of loading conditions were investigated to better understand the relationship between loading and optimization outcome. Comparisons of the initial and optimal models with more complex 3D finite element models were performed. The results indicate that design improvements made using this method result in similar improvements in the 3D models. Although the optimization outcomes were significantly affected by the choice of loading conditions, certain trends were observed that were independent of the applied loading.

Quantification of the multi-streaming effect in redshift space distortion

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

Zheng, Yi; Oh, Minji; Zhang, Pengjie, E-mail: yizheng@kasi.re.kr, E-mail: zhangpj@sjtu.edu.cn, E-mail: minjioh@kasi.re.kr

Both multi-streaming (random motion) and bulk motion cause the Finger-of-God (FoG) effect in redshift space distortion (RSD). We apply a direct measurement of the multi-streaming effect in RSD from simulations, proving that it induces an additional, non-negligible FoG damping to the redshift space density power spectrum. We show that, including the multi-streaming effect, the RSD modelling is significantly improved. We also provide a theoretical explanation based on halo model for the measured effect, including a fitting formula with one to two free parameters. The improved understanding of FoG helps break the f σ{sub 8}−σ {sub v} degeneracy in RSD cosmology,more » and has the potential of significantly improving cosmological constraints.« less

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

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

Defraene, Gilles, E-mail: gilles.defraene@uzleuven.be; Van den Bergh, Laura; Al-Mamgani, Abrahim

2012-03-01

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including themore » most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions: Comparable prediction models were obtained with LKB, RS, and logistic NTCP models. Including clinical factors improved the predictive power of all models significantly.« less

Assessment of Arctic and Antarctic Sea Ice Predictability in CMIP5 Decadal Hindcasts

NASA Technical Reports Server (NTRS)

Yang, Chao-Yuan; Liu, Jiping (Inventor); Hu, Yongyun; Horton, Radley M.; Chen, Liqi; Cheng, Xiao

2016-01-01

This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea ice. We analyze decadal hindcasts/predictions of 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Decadal hindcasts exhibit a large multimodel spread in the simulated sea ice extent, with some models deviating significantly from the observations as the predicted ice extent quickly drifts away from the initial constraint. The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Sea ice extent in the North Pacific has better predictive skill than that in the North Atlantic (particularly at a lead time of 3-7 years), but there is a reemerging predictive skill in the North Atlantic at a lead time of 6-8 years. In contrast to the Arctic, Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales, and there is no obvious improvement linking the areal extent of significant predictive skill to lead time increase. This might be because nearly all the models predict a retreating Antarctic sea ice cover, opposite to the observations. For the Arctic, the predictive skill of the multi-model ensemble mean outperforms most models and the persistence prediction at longer timescales, which is not the case for the Antarctic. Overall, for the Arctic, initialized decadal hindcasts show improved predictive skill compared to uninitialized simulations, although this improvement is not present in the Antarctic.

A mechanistic diagnosis of the simulation of soil CO2 efflux of the ACME Land Model

NASA Astrophysics Data System (ADS)

Liang, J.; Ricciuto, D. M.; Wang, G.; Gu, L.; Hanson, P. J.; Mayes, M. A.

2017-12-01

Accurate simulation of the CO2 efflux from soils (i.e., soil respiration) to the atmosphere is critical to project global biogeochemical cycles and the magnitude of climate change in Earth system models (ESMs). Currently, the simulated soil respiration by ESMs still have a large uncertainty. In this study, a mechanistic diagnosis of soil respiration in the Accelerated Climate Model for Energy (ACME) Land Model (ALM) was conducted using long-term observations at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the central U.S. The results showed that the ALM default run significantly underestimated annual soil respiration and gross primary production (GPP), while incorrectly estimating soil water potential. Improved simulations of soil water potential with site-specific data significantly improved the modeled annual soil respiration, primarily because annual GPP was simultaneously improved. Therefore, accurate simulations of soil water potential must be carefully calibrated in ESMs. Despite improved annual soil respiration, the ALM continued to underestimate soil respiration during peak growing seasons, and to overestimate soil respiration during non-peak growing seasons. Simulations involving increased GPP during peak growing seasons increased soil respiration, while neither improved plant phenology nor increased temperature sensitivity affected the simulation of soil respiration during non-peak growing seasons. One potential reason for the overestimation of the soil respiration during non-peak growing seasons may be that the current model structure is substrate-limited, while microbial dormancy under stress may cause the system to become decomposer-limited. Further studies with more microbial data are required to provide adequate representation of soil respiration and to understand the underlying reasons for inaccurate model simulations.

Predicting undergraduates' intentions to improve oral health behaviors: the importance of self-identity--a pilot study.

PubMed

Dumitrescu, Alexandrina L; Duţă, Carmen; Dogaru, Carmen Beatrice; Manolescu, Bogdan

2013-08-01

The purpose of this study was to explore the predictive ability of factors associated with the Theory of Planned Behavior (TPB) on oral health behaviors. The participants of this descriptive, cross-sectional study were 179 first year medical students at the Carol Davila University of Medicine and Pharmacy that completed a questionnaire assessing TPB variables, self-identity and their current oral hygiene behaviors. Significant differences in self-identity regarding the toothbrushing behavior and reason for the dental visit were observed (p < 0.0001). When participants were classified in 2 groups according to their levels of self-identity, significant differences were found according to their age, toothbrushing frequency, attitudes, perceived behavioral control and intention for improving oral hygiene (p < 0.0001). Self-identity had a statistically significant positive correlation with affective attitudes, cognitive attitudes, subjective norms, perceived behavioral control and intention for improving oral hygiene. Hierarchical multiple regressions for toothbrushing frequency revealed that the TPB factors and self-identity explained 31% and 35% from the intention to improving behaviors, the coefficients for self-identity being significant. The structural equation model revealed the effect of self-identity on intention on improving oral health behaviors and the effect of past-behavior on self-identity. The findings revealed the value of the extended TPB model as a predictor of intention to improve oral health behaviors. Dental educators should focus on issues of students' self-identity as a person concerned by their oral health.

Fuel thermal conductivity (FTHCON). Status report. [PWR; BWR

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

Hagrman, D. L.

1979-02-01

An improvement of the fuel thermal conductivity subcode is described which is part of the fuel rod behavior modeling task performed at EG and G Idaho, Inc. The original version was published in the Materials Properties (MATPRO) Handbook, Section A-2 (Fuel Thermal Conductivity). The improved version incorporates data which were not included in the previous work and omits some previously used data which are believed to come from cracked specimens. The models for the effect of porosity on thermal conductivity and for the electronic contribution to thermal coductivity have been completely revised in order to place these models on amore » more mechanistic basis. As a result of modeling improvements the standard error of the model with respect to its data base has been significantly reduced.« less

Passage relevance models for genomics search.

PubMed

Urbain, Jay; Frieder, Ophir; Goharian, Nazli

2009-03-19

We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of topics, concepts, terms, and document are represented as potential functions within a Markov Random Field. The probability of a passage being relevant to a biologist's information need is represented as the joint distribution across all potential functions. Relevance model feedback of top ranked passages is used to improve distributional estimates of query concepts and topics in context, and a dimensional indexing strategy is used for efficient aggregation of concept and term statistics. By integrating multiple sources of evidence including dependencies between topics, concepts, and terms, we seek to improve genomics literature passage retrieval precision. Using this model, we are able to demonstrate statistically significant improvements in retrieval precision using a large genomics literature corpus.

Optimal decision making modeling for copper-matte Peirce-Smith converting process by means of data mining

NASA Astrophysics Data System (ADS)

Song, Yanpo; Peng, Xiaoqi; Tang, Ying; Hu, Zhikun

2013-07-01

To improve the operation level of copper converter, the approach to optimal decision making modeling for coppermatte converting process based on data mining is studied: in view of the characteristics of the process data, such as containing noise, small sample size and so on, a new robust improved ANN (artificial neural network) modeling method is proposed; taking into account the application purpose of decision making model, three new evaluation indexes named support, confidence and relative confidence are proposed; using real production data and the methods mentioned above, optimal decision making model for blowing time of S1 period (the 1st slag producing period) are developed. Simulation results show that this model can significantly improve the converting quality of S1 period, increase the optimal probability from about 70% to about 85%.

Bone mass improved effect of icariin for postmenopausal osteoporosis in ovariectomy-induced rats: a meta-analysis and systematic review.

PubMed

Xu, Jin-Hai; Yao, Min; Ye, Jie; Wang, Guo-Dong; Wang, Jing; Cui, Xue-Jun; Mo, Wen

2016-10-01

Ovariectomy (OVX)-induced rats are the most frequently used animal model to research postmenopausal osteoporosis. Our objective was to summarize and critically assess the bone mass improved effect of icariin (ICA) for treatment of postmenopausal osteoporosis in an OVX-induced rat model. The PUBMED, EMBASE, and Chinese databases were searched from their inception date to February 2015. Two reviewers independently selected animal studies that evaluated the bone mass improved effect of ICA compared with control in OVX-induced rats. Extracted data were analyzed by RevMan statistical software, and the methodological quality of each study was assessed. Seven studies with adequate randomization were included in the systematic review. Overall, ICA seemed to significantly improve bone mass as assessed using the bone mineral density (seven studies, n = 169; weighted mean difference, 0.02; 95% CI, 0.01-0.02, I = 77%, P < 0.00001) using a random-effects model. There is no significant difference between ICA and estrogen (E) (six studies, n = 128; weighted mean difference, 0.00; 95% CI, -0.00 to 0.01, I = 54%, P = 0.01). Bone mass improved effect of ICA for postmenopausal osteoporosis was observed in OVX-induced rats. Assessment of the methodological quality of studies involving OVX-induced animal models is required, and good methodological quality should be valued in systematic reviews of animal studies.

An improved model for computing the trajectories of conductive particles in roll-type electrostatic separator for recycling metals from WEEE.

PubMed

Wu, Jiang; Li, Jia; Xu, Zhenming

2009-08-15

Electrostatic separation presents an effective and environmentally friendly way for recycling metals and nonmetals from ground waste electrical and electronic equipment (WEEE). For this process, the trajectory of conductive particle is significant and some models have been established. However, the results of previous researches are limited by some simplifying assumptions and lead to a notable discrepancy between the model prediction and the experimental results. In the present research, a roll-type corona-electrostatic separator and ground printed circuit board (PCB) wastes were used to investigate the trajectory of the conductive particle. Two factors, the air drag force and the different charging situation, were introduced into the improved model. Their effects were analyzed and an improved model for the theoretical trajectory of conductive particle was established. Compared with the previous one, the improved model shows a good agreement with the experimental results. It provides a positive guidance for designing of separator and makes a progress for recycling the metals and nonmetals from WEEE.

Voluntary wheel running improves recovery from a moderate spinal cord injury.

PubMed

Engesser-Cesar, Christie; Anderson, Aileen J; Basso, D Michele; Edgerton, V R; Cotman, Carl W

2005-01-01

Recently, locomotor training has been shown to improve overground locomotion in patients with spinal cord injury (SCI). This has triggered renewed interest in the role of exercise in rehabilitation after SCI. However, there are no mouse models for voluntary exercise and recovery of function following SCI. Here, we report voluntary wheel running improves recovery from a SCI in mice. C57Bl/10 female mice received a 60-kdyne T9 contusion injury with an IH impactor after 3 weeks of voluntary wheel running or 3 weeks of standard single housing conditions. Following a 7-day recovery period, running mice were returned to their running wheels. Weekly open-field behavior measured locomotor recovery using the Basso, Beattie and Bresnahan (BBB) locomotor rating scale and the Basso Mouse Scale (BMS) locomotor rating scale, a scale recently developed specifically for mice. Initial experiments using standard rung wheels show that wheel running impaired recovery, but subsequent experiments using a modified flat-surface wheel show improved recovery with exercise. By 14 days post SCI, the modified flat-surface running group had significantly higher BBB and BMS scores than the sedentary group. A repeated measures ANOVA shows locomotor recovery of modified flat-surface running mice was significantly improved compared to sedentary animals (p < 0.05). Locomotor assessment using a ladder beam task also shows a significant improvement in the modified flat-surface runners (p < 0.05). Finally, fibronectin staining shows no significant difference in lesion size between the two groups. These data represent the first mouse model showing voluntary exercise improves recovery after SCI.

Annular mode changes in the CMIP5 simulations

NASA Astrophysics Data System (ADS)

Gillett, N. P.; Fyfe, J. C.

2013-03-01

We investigate simulated changes in the annular modes in historical and RCP 4.5 scenario simulations of 37 models from the fifth Coupled Model Intercomparison Project (CMIP5), a much larger ensemble of models than has previously been used to investigate annular mode trends, with improved resolution and forcings. The CMIP5 models on average simulate increases in the Northern Annular Mode (NAM) and Southern Annular Mode (SAM) in every season by 2100, and no CMIP5 model simulates a significant decrease in either the NAM or SAM in any season. No significant increase in the NAM or North Atlantic Oscillation (NAO) is simulated in response to volcanic aerosol, and no significant NAM or NAO response to solar irradiance variations is simulated. The CMIP5 models simulate a significant negative SAM response to volcanic aerosol in MAM and JJA, and a significant positive SAM response to solar irradiance variations in MAM, JJA and DJF.

Progress Toward Improving Jet Noise Predictions in Hot Jets

NASA Technical Reports Server (NTRS)

Khavaran, Abbas; Kenzakowski, Donald C.

2007-01-01

An acoustic analogy methodology for improving noise predictions in hot round jets is presented. Past approaches have often neglected the impact of temperature fluctuations on the predicted sound spectral density, which could be significant for heated jets, and this has yielded noticeable acoustic under-predictions in such cases. The governing acoustic equations adopted here are a set of linearized, inhomogeneous Euler equations. These equations are combined into a single third order linear wave operator when the base flow is considered as a locally parallel mean flow. The remaining second-order fluctuations are regarded as the equivalent sources of sound and are modeled. It is shown that the hot jet effect may be introduced primarily through a fluctuating velocity/enthalpy term. Modeling this additional source requires specialized inputs from a RANS-based flowfield simulation. The information is supplied using an extension to a baseline two equation turbulence model that predicts total enthalpy variance in addition to the standard parameters. Preliminary application of this model to a series of unheated and heated subsonic jets shows significant improvement in the acoustic predictions at the 90 degree observer angle.

Formoterol, a long-acting β2 adrenergic agonist, improves cognitive function and promotes dendritic complexity in a mouse model of Down syndrome.

PubMed

Dang, Van; Medina, Brian; Das, Devsmita; Moghadam, Sarah; Martin, Kara J; Lin, Bill; Naik, Priyanka; Patel, Devan; Nosheny, Rachel; Wesson Ashford, John; Salehi, Ahmad

2014-02-01

Down syndrome is associated with significant failure in cognitive function. Our previous investigation revealed age-dependent degeneration of locus coeruleus, a major player in contextual learning, in the Ts65Dn mouse model of Down syndrome. We studied whether drugs already available for use in humans can be used to improve cognitive function in these mice. We studied the status of β adrenergic signaling in the dentate gyrus of the Ts65Dn mouse model of Down syndrome. Furthermore, we used fear conditioning to study learning and memory in these mice. Postmortem analyses included the analysis of synaptic density, dendritic arborization, and neurogenesis. We found significant atrophy of dentate gyrus and failure of β adrenergic signaling in the hippocampus of Ts65Dn mice. Our behavioral analyses revealed that formoterol, a long-acting β2 adrenergic receptor agonist, caused significant improvement in the cognitive function in Ts65Dn mice. Postmortem analyses revealed that the use of formoterol was associated with a significant improvement in the synaptic density and increased complexity of newly born dentate granule neurons in the hippocampus of Ts65Dn mice. Our data suggest that targeting β2 adrenergic receptors is an effective strategy for restoring synaptic plasticity and cognitive function in these mice. Considering its widespread use in humans and positive effects on cognition in Ts65Dn mice, formoterol or similar β2 adrenergic receptor agonists with ability to cross the blood brain barrier might be attractive candidates for clinical trials to improve cognitive function in individuals with Down syndrome. Published by Elsevier Inc.

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico.

PubMed

Johansson, Michael A; Reich, Nicholas G; Hota, Aditi; Brownstein, John S; Santillana, Mauricio

2016-09-26

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model.

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico

PubMed Central

Johansson, Michael A.; Reich, Nicholas G.; Hota, Aditi; Brownstein, John S.; Santillana, Mauricio

2016-01-01

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model. PMID:27665707

Improving the Validity of Activity of Daily Living Dependency Risk Assessment

PubMed Central

Clark, Daniel O.; Stump, Timothy E.; Tu, Wanzhu; Miller, Douglas K.

2015-01-01

Objectives Efforts to prevent activity of daily living (ADL) dependency may be improved through models that assess older adults’ dependency risk. We evaluated whether cognition and gait speed measures improve the predictive validity of interview-based models. Method Participants were 8,095 self-respondents in the 2006 Health and Retirement Survey who were aged 65 years or over and independent in five ADLs. Incident ADL dependency was determined from the 2008 interview. Models were developed using random 2/3rd cohorts and validated in the remaining 1/3rd. Results Compared to a c-statistic of 0.79 in the best interview model, the model including cognitive measures had c-statistics of 0.82 and 0.80 while the best fitting gait speed model had c-statistics of 0.83 and 0.79 in the development and validation cohorts, respectively. Conclusion Two relatively brief models, one that requires an in-person assessment and one that does not, had excellent validity for predicting incident ADL dependency but did not significantly improve the predictive validity of the best fitting interview-based models. PMID:24652867

How Interplanetary Scintillation Data Can Improve Modeling of Coronal Mass Ejection Propagation

NASA Astrophysics Data System (ADS)

Taktakishvili, A.; Mays, M. L.; Manoharan, P. K.; Rastaetter, L.; Kuznetsova, M. M.

2017-12-01

Coronal mass ejections (CMEs) can have a significant impact on the Earth's magnetosphere-ionosphere system and cause widespread anomalies for satellites from geosynchronous to low-Earth orbit and produce effects such as geomagnetically induced currents. At the NASA/GSFC Community Coordinated Modeling Center we have been using ensemble modeling of CMEs since 2012. In this presnetation we demonstrate that using of interplanetary scintillation (IPS) observations from the Ooty Radio Telescope facility in India can help to track CME propagaion and improve ensemble forecasting of CMEs. The observations of the solar wind density and velocity using IPS from hundreds of distant sources in ensemble modeling of CMEs can be a game-changing improvement of the current state of the art in CME forecasting.

Reducing RN Vacancy Rate: A Nursing Recruitment Office Process Improvement Project.

PubMed

Hisgen, Stephanie A; Page, Nancy E; Thornlow, Deirdre K; Merwin, Elizabeth I

2018-06-01

The aim of this study was to reduce the RN vacancy rate at an academic medical center by improving the hiring process in the Nursing Recruitment Office. Inability to fill RN positions can lead to higher vacancy rates and negatively impact staff and patient satisfaction, quality outcomes, and the organization's bottom line. The Model for Improvement was used to design and implement a process improvement project to improve the hiring process from time of interview through the position being filled. Number of days to interview and check references decreased significantly, but no change in overall time to hire and time to fill positions was noted. RN vacancy rate also decreased significantly. Nurse manager satisfaction with the hiring process increased significantly. Redesigning the recruitment process supported operational efficiencies of the organization related to RN recruitment.

Model Update of a Micro Air Vehicle (MAV) Flexible Wing Frame with Uncertainty Quantification

NASA Technical Reports Server (NTRS)

Reaves, Mercedes C.; Horta, Lucas G.; Waszak, Martin R.; Morgan, Benjamin G.

2004-01-01

This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.

High-precision radiometric tracking for planetary approach and encounter in the inner solar system

NASA Technical Reports Server (NTRS)

Christensen, C. S.; Thurman, S. W.; Davidson, J. M.; Finger, M. H.; Folkner, W. M.

1989-01-01

The benefits of improved radiometric tracking data have been studied for planetary approach within the inner Solar System using the Mars Rover Sample Return trajectory as a model. It was found that the benefit of improved data to approach and encounter navigation was highly dependent on the a priori uncertainties assumed for several non-estimated parameters, including those for frame-tie, Earth orientation, troposphere delay, and station locations. With these errors at their current levels, navigational performance was found to be insensitive to enhancements in data accuracy. However, when expected improvements in these errors are modeled, performance with current-accuracy data significantly improves, with substantial further improvements possible with enhancements in data accuracy.

Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement.

PubMed

Buonaccorsi, Giovanni A; Roberts, Caleb; Cheung, Sue; Watson, Yvonne; O'Connor, James P B; Davies, Karen; Jackson, Alan; Jayson, Gordon C; Parker, Geoff J M

2006-09-01

The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.

TU-D-207B-02: Delta-Radiomics: The Prognostic Value of Therapy-Induced Changes in Radiomics Features for Stage III Non-Small Cell Lung Cancer Patients

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

Fave, X; Court, L; UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX

Purpose: To determine how radiomics features change during radiation therapy and whether those changes (delta-radiomics features) can improve prognostic models built with clinical factors. Methods: 62 radiomics features, including histogram, co-occurrence, run-length, gray-tone difference, and shape features, were calculated from pretreatment and weekly intra-treatment CTs for 107 stage III NSCLC patients (5–9 images per patient). Image preprocessing for each feature was determined using the set of pretreatment images: bit-depth resample and/or a smoothing filter were tested for their impact on volume-correlation and significance of each feature in univariate cox regression models to maximize their information content. Next, the optimized featuresmore » were calculated from the intratreatment images and tested in linear mixed-effects models to determine which features changed significantly with dose-fraction. The slopes in these significant features were defined as delta-radiomics features. To test their prognostic potential multivariate cox regression models were fitted, first using only clinical features and then clinical+delta-radiomics features for overall-survival, local-recurrence, and distant-metastases. Leave-one-out cross validation was used for model-fitting and patient predictions. Concordance indices(c-index) and p-values for the log-rank test with patients stratified at the median were calculated. Results: Approximately one-half of the 62 optimized features required no preprocessing, one-fourth required smoothing, and one-fourth required smoothing and resampling. From these, 54 changed significantly during treatment. For overall-survival, the c-index improved from 0.52 for clinical factors alone to 0.62 for clinical+delta-radiomics features. For distant-metastases, the c-index improved from 0.53 to 0.58, while for local-recurrence it did not improve. Patient stratification significantly improved (p-value<0.05) for overallsurvival and distant-metastases when delta-radiomics features were included. The delta-radiomics versions of autocorrelation, kurtosis, and compactness were selected most frequently in leave-one-out iterations. Conclusion: Weekly changes in radiomics features can potentially be used to evaluate treatment response and predict patient outcomes. High-risk patients could be recommended for dose escalation or consolidation chemotherapy. This project was funded in part by grants from the National Cancer Institute (NCI) and the Cancer Prevention Research Institute of Texas (CPRIT).« less

Probiotics improve survival of septic rats by suppressing conditioned pathogens in ascites

PubMed Central

Liu, Da-Quan; Gao, Qiao-Ying; Liu, Hong-Bin; Li, Dong-Hua; Wu, Shang-Wei

2013-01-01

AIM: To investigate the benefits of probiotics treatment in septic rats. METHODS: The septic rats were induced by cecal ligation and puncture. The animals of control, septic model and probiotics treated groups were treated with vehicle and mixed probiotics, respectively. The mixture of probiotics included Bifidobacterium longum, Lactobacillus bulgaricus and Streptococcus thermophilus. We observed the survival of septic rats using different amounts of mixed probiotics. We also detected the bacterial population in ascites and blood of experimental sepsis using cultivation and real-time polymerase chain reaction. The severity of mucosal inflammation in colonic tissues was determined. RESULTS: Probiotics treatment improved survival of the rats significantly and this effect was dose dependent. The survival rate was 30% for vehicle-treated septic model group. However, 1 and 1/4 doses of probiotics treatment increased survival rate significantly compared with septic model group (80% and 55% vs 30%, P < 0.05). The total viable counts of bacteria in ascites decreased significantly in probiotics treated group compared with septic model group (5.20 ± 0.57 vs 9.81 ± 0.67, P < 0.05). The total positive rate of hemoculture decreased significantly in probiotics treated group compared with septic model group (33.3% vs 100.0%, P < 0.05). The population of Escherichia coli and Staphylococcus aureus in ascites of probiotics treated group were decreased significantly compared with that of septic model group (3.93 ± 0.73 vs 8.80 ± 0.83, P < 0.05; 2.80 ± 1.04 vs 5.39 ± 1.21, P < 0.05). With probiotics treatment, there was a decrease in the scores of inflammatory cell infiltration into the intestinal mucosa in septic animals (1.50 ± 0.25 vs 2.88 ± 0.14, P < 0.01). CONCLUSION: Escherichia coli and Staphylococcus aureus may be primary pathogens in septic rats. Probiotics improve survival of septic rats by suppressing these conditioned pathogens. PMID:23840152

The effect of the introduction of a case-mix-based funding model of rehabilitation for severe stroke: an Australian experience.

PubMed

Brock, Kim A; Vale, Stephen J; Cotton, Susan M

2007-07-01

To compare resource use of, and outcomes for, rehabilitation for severe stroke before and after the implementation of the Casemix and Rehabilitation Funding Tree case-mix-based funding model. Prospective, observational cohort study. Eight inpatient rehabilitation centers in Australia. Consecutive sample of 609 patients with severe stroke. Not applicable. Rehabilitation length of stay (LOS), discharge destination, and FIM instrument motor score at discharge. The average rehabilitation LOS changed significantly between the preimplementation year and the implementation year (Mann-Whitney U, P=.001). There were no significant differences in discharge destination. FIM motor score at discharge showed significant reduction in improvement (Mann-Whitney U, P=.001) between the preimplementation year and the implementation year. There were no significant correlations between LOS in rehabilitation and gain in function for either the preimplementation year (Spearman rho, P=.07) or the implementation year (P=.15). The change in funding model was associated with a decrease in inpatient costs and with an associated increase in disability at discharge. Our results suggest that the rate of improvement in severe stroke is variable; also, they support the use of funding models for stroke rehabilitation that allow flexibility in resource allocation.

Genetic variants in SLC22A17 and SLC22A7 are associated with anthracycline-induced cardiotoxicity in children.

PubMed

Visscher, Henk; Rassekh, S Rod; Sandor, George S; Caron, Huib N; van Dalen, Elvira C; Kremer, Leontien C; van der Pal, Helena J; Rogers, Paul C; Rieder, Michael J; Carleton, Bruce C; Hayden, Michael R; Ross, Colin J

2015-01-01

To identify novel variants associated with anthracycline-induced cardiotoxicity and to assess these in a genotype-guided risk prediction model. Two cohorts treated for childhood cancer (n = 344 and 218, respectively) were genotyped for 4578 SNPs in drug ADME and toxicity genes. Significant associations were identified in SLC22A17 (rs4982753; p = 0.0078) and SLC22A7 (rs4149178; p = 0.0034), with replication in the second cohort (p = 0.0071 and 0.047, respectively). Additional evidence was found for SULT2B1 and several genes related to oxidative stress. Adding the SLC22 variants to the prediction model improved its discriminative ability (AUC 0.78 vs 0.75 [p = 0.029]). Two novel variants in SLC22A17 and SLC22A7 were significantly associated with anthracycline-induced cardiotoxicity and improved a genotype-guided risk prediction model, which could improve patient risk stratification.

A low-cost approach for rapidly creating demonstration models for hands-on learning

NASA Astrophysics Data System (ADS)

Kinzli, Kristoph-Dietrich; Kunberger, Tanya; O'Neill, Robert; Badir, Ashraf

2018-01-01

Demonstration models allow students to readily grasp theory and relate difficult concepts and equations to real life. However drawbacks of using these demonstration models are that they are can be costly to purchase from vendors or take a significant amount of time to build. These two limiting factors can pose a significant obstacle for adding demonstrations to the curriculum. This article presents an assignment to overcome these obstacles, which has resulted in 36 demonstration models being added to the curriculum. The article also presents the results of student performance on course objectives as a result of the developed models being used in the classroom. Overall, significant improvement in student learning outcomes, due to the addition of demonstration models, has been observed.

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

Simpson, L.

ITN Energy Systems, Inc., and Global Solar Energy, Inc., with the assistance of NREL's PV Manufacturing R&D program, have continued the advancement of CIGS production technology through the development of trajectory-oriented predictive/control models, fault-tolerance control, control-platform development, in-situ sensors, and process improvements. Modeling activities to date include the development of physics-based and empirical models for CIGS and sputter-deposition processing, implementation of model-based control, and application of predictive models to the construction of new evaporation sources and for control. Model-based control is enabled through implementation of reduced or empirical models into a control platform. Reliability improvement activities include implementation of preventivemore » maintenance schedules; detection of failed sensors/equipment and reconfiguration to continue processing; and systematic development of fault prevention and reconfiguration strategies for the full range of CIGS PV production deposition processes. In-situ sensor development activities have resulted in improved control and indicated the potential for enhanced process status monitoring and control of the deposition processes. Substantial process improvements have been made, including significant improvement in CIGS uniformity, thickness control, efficiency, yield, and throughput. In large measure, these gains have been driven by process optimization, which, in turn, have been enabled by control and reliability improvements due to this PV Manufacturing R&D program. This has resulted in substantial improvements of flexible CIGS PV module performance and efficiency.« less

Assimilation of Terrestrial Water Storage from GRACE in a Snow-Dominated Basin

NASA Technical Reports Server (NTRS)

Forman, Barton A.; Reichle, R. H.; Rodell, M.

2011-01-01

Terrestrial water storage (TWS) information derived from Gravity Recovery and Climate Experiment (GRACE) measurements is assimilated into a land surface model over the Mackenzie River basin located in northwest Canada. Assimilation is conducted using an ensemble Kalman smoother (EnKS). Model estimates with and without assimilation are compared against independent observational data sets of snow water equivalent (SWE) and runoff. For SWE, modest improvements in mean difference (MD) and root mean squared difference (RMSD) are achieved as a result of the assimilation. No significant differences in temporal correlations of SWE resulted. Runoff statistics of MD remain relatively unchanged while RMSD statistics, in general, are improved in most of the sub-basins. Temporal correlations are degraded within the most upstream sub-basin, but are, in general, improved at the downstream locations, which are more representative of an integrated basin response. GRACE assimilation using an EnKS offers improvements in hydrologic state/flux estimation, though comparisons with observed runoff would be enhanced by the use of river routing and lake storage routines within the prognostic land surface model. Further, GRACE hydrology products would benefit from the inclusion of better constrained models of post-glacial rebound, which significantly affects GRACE estimates of interannual hydrologic variability in the Mackenzie River basin.

AP214, an analogue of α-melanocyte-stimulating hormone, ameliorates sepsis-induced acute kidney injury and mortality

PubMed Central

Doi, Kent; Hu, Xuzhen; Yuen, Peter S.T.; Leelahavanichkul, Asada; Yasuda, Hideo; Kim, Soo Mi; Schnermann, Jürgen; Jonassen, Thomas E.N.; Frøkiær, Jørgen; Nielsen, Søren; Star, Robert A.

2008-01-01

Sepsis remains a serious problem in critically ill patients with the mortality increasing to over half when there is attendant acute kidney injury. α-Melanocyte-stimulating hormone is a potent anti-inflammatory cytokine that inhibits many forms of inflammation including that with acute kidney injury. We tested whether a new α-melanocyte-stimulating hormone analogue (AP214), which has increased binding affinity to melanocortin receptors, improves sepsis-induced kidney injury and mortality using a cecal ligation and puncture mouse model. In the lethal cecal ligation-puncture model of sepsis, severe hypotension and bradycardia resulted and AP214 attenuated acute kidney injury of the lethal model with a bell-shaped dose-response curve. An optimum AP214 dose reduced acute kidney injury even when it was administered 6 hr after surgery and it significantly improved blood pressure and heart rate. AP214 reduced serum TNF-α and IL-10 levels with a bell-shaped dose-response curve. Additionally; NF-κB activation in the kidney and spleen, and splenocyte apoptosis were decreased by the treatment. AP214 significantly improved survival in both lethal and sublethal models. We have shown that AP214 improves hemodynamic failure, acute kidney injury, mortality and splenocyte apoptosis attenuating pro- and anti-inflammatory actions due to sepsis. PMID:18354376

A numerical study of wave-current interaction through surface and bottom stresses: Coastal ocean response to Hurricane Fran of 1996

NASA Astrophysics Data System (ADS)

Xie, L.; Pietrafesa, L. J.; Wu, K.

2003-02-01

A three-dimensional wave-current coupled modeling system is used to examine the influence of waves on coastal currents and sea level. This coupled modeling system consists of the wave model-WAM (Cycle 4) and the Princeton Ocean Model (POM). The results from this study show that it is important to incorporate surface wave effects into coastal storm surge and circulation models. Specifically, we find that (1) storm surge models without coupled surface waves generally under estimate not only the peak surge but also the coastal water level drop which can also cause substantial impact on the coastal environment, (2) introducing wave-induced surface stress effect into storm surge models can significantly improve storm surge prediction, (3) incorporating wave-induced bottom stress into the coupled wave-current model further improves storm surge prediction, and (4) calibration of the wave module according to minimum error in significant wave height does not necessarily result in an optimum wave module in a wave-current coupled system for current and storm surge prediction.

Using Data From Ontario's Episode-Based Funding Model to Assess Quality of Chemotherapy.

PubMed

Kaizer, Leonard; Simanovski, Vicky; Lalonde, Carlin; Tariq, Huma; Blais, Irene; Evans, William K

2016-10-01

A new episode-based funding model for ambulatory systemic therapy was implemented in Ontario, Canada on April 1, 2014, after a comprehensive knowledge transfer and exchange strategy with providers and administrators. An analysis of the data from the first year of the new funding model provided an opportunity to assess the quality of chemotherapy, which was not possible under the old funding model. Options for chemotherapy regimens given with adjuvant/curative intent or palliative intent were informed by input from disease site groups. Bundles were developed and priced to enable evidence-informed best practice. Analysis of systemic therapy utilization after model implementation was performed to assess the concordance rate of the treatments chosen with recommended practice. The actual number of cycles of treatment delivered was also compared with expert recommendations. Significant improvement compared with baseline was seen in the proportion of adjuvant/curative regimens that aligned with disease site group-recommended options (98% v 90%). Similar improvement was seen for palliative regimens (94% v 89%). However, overall, the number of cycles of adjuvant/curative therapy delivered was lower than recommended best practice in 57.5% of patients. There was significant variation by disease site and between facilities. Linking funding to quality, supported by knowledge transfer and exchange, resulted in a rapid improvement in the quality of systemic treatment in Ontario. This analysis has also identified further opportunities for improvement and the need for model refinement.

Impact of the single point of access referral system to reduce waiting times and improve clinical outcomes in an assistive technology service.

PubMed

Hosking, Jonathan; Gibson, Colin

2016-07-01

The introduction of a single point referral system that prioritises clients depending on case complexity and overcomes the need for re-admittance to a waiting list via a review system has been shown to significantly reduce maximum waiting times for a Posture and Mobility (Special Seating) Service from 102.0 ± 24.33 weeks to 19.2 ± 8.57 weeks (p = 0.015). Using this service model linear regression revealed a statistically significant improvement in the performance outcome of prescribed seating solutions with shorter Episode of Care completion times (p = 0.023). In addition, the number of Episodes of Care completed per annum was significantly related to the Episode of Care completion time (p = 0.019). In conclusion, it is recommended that it may be advantageous to apply this service model to other assistive technology services in order to reduce waiting times and to improve clinical outcomes.

Flight assessment of the onboard propulsion system model for the Performance Seeking Control algorithm on an F-15 aircraft

NASA Technical Reports Server (NTRS)

Orme, John S.; Schkolnik, Gerard S.

1995-01-01

Performance Seeking Control (PSC), an onboard, adaptive, real-time optimization algorithm, relies upon an onboard propulsion system model. Flight results illustrated propulsion system performance improvements as calculated by the model. These improvements were subject to uncertainty arising from modeling error. Thus to quantify uncertainty in the PSC performance improvements, modeling accuracy must be assessed. A flight test approach to verify PSC-predicted increases in thrust (FNP) and absolute levels of fan stall margin is developed and applied to flight test data. Application of the excess thrust technique shows that increases of FNP agree to within 3 percent of full-scale measurements for most conditions. Accuracy to these levels is significant because uncertainty bands may now be applied to the performance improvements provided by PSC. Assessment of PSC fan stall margin modeling accuracy was completed with analysis of in-flight stall tests. Results indicate that the model overestimates the stall margin by between 5 to 10 percent. Because PSC achieves performance gains by using available stall margin, this overestimation may represent performance improvements to be recovered with increased modeling accuracy. Assessment of thrust and stall margin modeling accuracy provides a critical piece for a comprehensive understanding of PSC's capabilities and limitations.

Improving inflow forecasting into hydropower reservoirs through a complementary modelling framework

NASA Astrophysics Data System (ADS)

Gragne, A. S.; Sharma, A.; Mehrotra, R.; Alfredsen, K.

2014-10-01

Accuracy of reservoir inflow forecasts is instrumental for maximizing the value of water resources and benefits gained through hydropower generation. Improving hourly reservoir inflow forecasts over a 24 h lead-time is considered within the day-ahead (Elspot) market of the Nordic exchange market. We present here a new approach for issuing hourly reservoir inflow forecasts that aims to improve on existing forecasting models that are in place operationally, without needing to modify the pre-existing approach, but instead formulating an additive or complementary model that is independent and captures the structure the existing model may be missing. Besides improving forecast skills of operational models, the approach estimates the uncertainty in the complementary model structure and produces probabilistic inflow forecasts that entrain suitable information for reducing uncertainty in the decision-making processes in hydropower systems operation. The procedure presented comprises an error model added on top of an un-alterable constant parameter conceptual model, the models being demonstrated with reference to the 207 km2 Krinsvatn catchment in central Norway. The structure of the error model is established based on attributes of the residual time series from the conceptual model. Deterministic and probabilistic evaluations revealed an overall significant improvement in forecast accuracy for lead-times up to 17 h. Season based evaluations indicated that the improvement in inflow forecasts varies across seasons and inflow forecasts in autumn and spring are less successful with the 95% prediction interval bracketing less than 95% of the observations for lead-times beyond 17 h.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.

PubMed

Morote, Juan; Del Amo, Jokin; Borque, Angel; Ars, Elisabet; Hernández, Carlos; Herranz, Felipe; Arruza, Antonio; Llarena, Roberto; Planas, Jacques; Viso, María J; Palou, Joan; Raventós, Carles X; Tejedor, Diego; Artieda, Marta; Simón, Laureano; Martínez, Antonio; Rioja, Luis A

2010-08-01

Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information. Copyright (c) 2010 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

The Real World Significance of Performance Prediction

ERIC Educational Resources Information Center

Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

2012-01-01

In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

PubMed

Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

2010-06-01

The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it was possible to interchange certain descriptors (i.e. molecular weight and melting point) without incurring a loss of model quality. Such synergy suggested that a model constructed from discrete terms in an equation may not be the most appropriate way of representing mechanistic understandings of skin absorption.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI

NASA Astrophysics Data System (ADS)

Pei, Linmin; Reza, Syed M. S.; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M.

2017-03-01

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. To model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI.

PubMed

Pei, Linmin; Reza, Syed M S; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M

2017-02-11

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. In order to model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

An improved car-following model considering headway changes with memory

NASA Astrophysics Data System (ADS)

Yu, Shaowei; Shi, Zhongke

2015-03-01

To describe car-following behaviors in complex situations better, increase roadway traffic mobility and minimize cars' fuel consumptions, the linkage between headway changes with memory and car-following behaviors was explored with the field car-following data by using the gray correlation analysis method, and then an improved car-following model considering headway changes with memory on a single lane was proposed based on the full velocity difference model. Some numerical simulations were carried out by employing the improved car-following model to explore how headway changes with memory affected each car's velocity, acceleration, headway and fuel consumptions. The research results show that headway changes with memory have significant effects on car-following behaviors and fuel consumptions and that considering headway changes with memory in designing the adaptive cruise control strategy can improve the traffic flow stability and minimize cars' fuel consumptions.

A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014

PubMed Central

Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian

2015-01-01

This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001), migration route (OR = 0.993, p < 0.01), river (OR = 0.861, p < 0.001), lake(OR = 0.992, p < 0.001), road (OR = 0.906, p < 0.001), railway (OR = 0.980, p < 0.001), temperature (OR = 1.170, p < 0.01), precipitation (OR = 0.615, p < 0.001) and relative humidity (OR = 1.337, p < 0.001). The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446

Towards improving software security by using simulation to inform requirements and conceptual design

DOE PAGES

Nutaro, James J.; Allgood, Glenn O.; Kuruganti, Teja

2015-06-17

We illustrate the use of modeling and simulation early in the system life-cycle to improve security and reduce costs. The models that we develop for this illustration are inspired by problems in reliability analysis and supervisory control, for which similar models are used to quantify failure probabilities and rates. In the context of security, we propose that models of this general type can be used to understand trades between risk and cost while writing system requirements and during conceptual design, and thereby significantly reduce the need for expensive security corrections after a system enters operation

An Operations Concept for Integrated Model-Centric Engineering at JPL

NASA Technical Reports Server (NTRS)

Bayer, Todd J.; Cooney, Lauren A.; Delp, Christopher L.; Dutenhoffer, Chelsea A.; Gostelow, Roli D.; Ingham, Michel D.; Jenkins, J. Steven; Smith, Brian S.

2010-01-01

As JPL's missions grow more complex, the need for improved systems engineering processes is becoming clear. Of significant promise in this regard is the move toward a more integrated and model-centric approach to mission conception, design, implementation and operations. The Integrated Model-Centric Engineering (IMCE) Initiative, now underway at JPL, seeks to lay the groundwork for these improvements. This paper will report progress on three fronts: articulating JPL's need for IMCE; characterizing the enterprise into which IMCE capabilities will be deployed; and constructing an operations concept for a flight project development in an integrated model-centric environment.

Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

NASA Astrophysics Data System (ADS)

Yang, Bin

2017-07-01

Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately

Cardiorespiratory fitness and classification of risk of cardiovascular disease mortality.

PubMed

Gupta, Sachin; Rohatgi, Anand; Ayers, Colby R; Willis, Benjamin L; Haskell, William L; Khera, Amit; Drazner, Mark H; de Lemos, James A; Berry, Jarett D

2011-04-05

Cardiorespiratory fitness (fitness) is associated with cardiovascular disease (CVD) mortality. However, the extent to which fitness improves risk classification when added to traditional risk factors is unclear. Fitness was measured by the Balke protocol in 66 371 subjects without prior CVD enrolled in the Cooper Center Longitudinal Study between 1970 and 2006; follow-up was extended through 2006. Cox proportional hazards models were used to estimate the risk of CVD mortality with a traditional risk factor model (age, sex, systolic blood pressure, diabetes mellitus, total cholesterol, and smoking) with and without the addition of fitness. The net reclassification improvement and integrated discrimination improvement were calculated at 10 and 25 years. Ten-year risk estimates for CVD mortality were categorized as <1%, 1% to <5%, and ≥5%, and 25-year risk estimates were categorized as <8%, 8% to 30%, and ≥30%. During a median follow-up period of 16 years, there were 1621 CVD deaths. The addition of fitness to the traditional risk factor model resulted in reclassification of 10.7% of the men, with significant net reclassification improvement at both 10 years (net reclassification improvement=0.121) and 25 years (net reclassification improvement=0.041) (P<0.001 for both). The integrated discrimination improvement was 0.010 at 10 years (P<0.001), and the relative integrated discrimination improvement was 29%. Similar findings were observed for women at 25 years. A single measurement of fitness significantly improves classification of both short-term (10-year) and long-term (25-year) risk for CVD mortality when added to traditional risk factors.

Liver graft preservation using perfluorocarbon improves the outcomes of simulated donation after cardiac death liver transplantation in rats.

PubMed

Okumura, Shinya; Uemura, Tadahiro; Zhao, Xiangdong; Masano, Yuki; Tsuruyama, Tatsuaki; Fujimoto, Yasuhiro; Iida, Taku; Yagi, Shintaro; Bezinover, Dmitri; Spiess, Bruce; Kaido, Toshimi; Uemoto, Shinji

2017-09-01

The outcomes of liver transplantation (LT) from donation after cardiac death (DCD) donors remain poor due to severe warm ischemia injury. Perfluorocarbon (PFC) is a novel compound with high oxygen carrying capacity. In the present study, a rat model simulating DCD LT was used, and the impact of improved graft oxygenation provided by PFC addition on liver ischemia/reperfusion injury (IRI) and survival after DCD LT was investigated. Orthotopic liver transplants were performed in male Lewis rats, using DCD liver grafts preserved with cold University of Wisconsin (UW) solution in the control group and preserved with cold oxygenated UW solution with addition of 20% PFC in the PFC group. For experiment I, in a 30-minute donor warm ischemia model, postoperative graft injury was analyzed at 3 and 6 hours after transplantation. For experiment II, in a 50-minute donor warm ischemia model, the postoperative survival was assessed. For experiment I, the levels of serum aspartate aminotransferase, alanine aminotransferase, hyaluronic acid, malondialdehyde, and several inflammatory cytokines were significantly lower in the PFC group. The hepatic expression levels of tumor necrosis factor α and interleukin 6 were significantly lower, and the expression level of heme oxygenase 1 was significantly higher in the PFC group. Histological analysis showed significantly less necrosis and apoptosis in the PFC group. Sinusoidal endothelial cells and microvilli of the bile canaliculi were well preserved in the PFC group. For experiment II, the postoperative survival rate was significantly improved in the PFC group. In conclusion, graft preservation with PFC attenuated liver IRI and improved postoperative survival. This graft preservation protocol might be a new therapeutic option to improve the outcomes of DCD LT. Liver Transplantation 23 1171-1185 2017 AASLD. © 2017 by the American Association for the Study of Liver Diseases.

Baryon spectra and antiparticle-to-particle ratios from the improved AMPT model

NASA Astrophysics Data System (ADS)

He, Yuncun; Lin, Zi-Wei

2018-02-01

The current version of a multi-phase transport (AMPT) model with string melting can reasonably describe the dN/dy yields, pT spectra and anisotropic flows of pions and kaons at low pT in heavy ion collisions at RHIC and LHC energies, although it failed to reproduce the dN/dy and pT spectra of baryons. In this work, we improve the quark coalescence mechanism in AMPT by removing the forced separate number conservations of mesons, baryons and antibaryons in each event. We find that the improved AMPT model can better describe the yields at midrapidity, the pT spectra and elliptic flow of low-pT baryons in comparison with the experimental data. Antiparticle-to-particle ratios of strange baryons are also significantly improved.

More than Anecdotes: Fishers’ Ecological Knowledge Can Fill Gaps for Ecosystem Modeling

PubMed Central

Bevilacqua, Ana Helena V.; Carvalho, Adriana R.; Angelini, Ronaldo; Christensen, Villy

2016-01-01

Background Ecosystem modeling applied to fisheries remains hampered by a lack of local information. Fishers’ knowledge could fill this gap, improving participation in and the management of fisheries. Methodology The same fishing area was modeled using two approaches: based on fishers’ knowledge and based on scientific information. For the former, the data was collected by interviews through the Delphi methodology, and for the latter, the data was gathered from the literature. Agreement between the attributes generated by the fishers’ knowledge model and scientific model is discussed and explored, aiming to improve data availability, the ecosystem model, and fisheries management. Principal Findings The ecosystem attributes produced from the fishers’ knowledge model were consistent with the ecosystem attributes produced by the scientific model, and elaborated using only the scientific data from literature. Conclusions/Significance This study provides evidence that fishers’ knowledge may suitably complement scientific data, and may improve the modeling tools for the research and management of fisheries. PMID:27196131

Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression.

PubMed

Ashrafi, Parivash; Sun, Yi; Davey, Neil; Adams, Roderick G; Wilkinson, Simon C; Moss, Gary Patrick

2018-03-01

The aim of this study was to investigate how to improve predictions from Gaussian Process models by optimising the model hyperparameters. Optimisation methods, including Grid Search, Conjugate Gradient, Random Search, Evolutionary Algorithm and Hyper-prior, were evaluated and applied to previously published data. Data sets were also altered in a structured manner to reduce their size, which retained the range, or 'chemical space' of the key descriptors to assess the effect of the data range on model quality. The Hyper-prior Smoothbox kernel results in the best models for the majority of data sets, and they exhibited significantly better performance than benchmark quantitative structure-permeability relationship (QSPR) models. When the data sets were systematically reduced in size, the different optimisation methods generally retained their statistical quality, whereas benchmark QSPR models performed poorly. The design of the data set, and possibly also the approach to validation of the model, is critical in the development of improved models. The size of the data set, if carefully controlled, was not generally a significant factor for these models and that models of excellent statistical quality could be produced from substantially smaller data sets. © 2018 Royal Pharmaceutical Society.

Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement

PubMed Central

Xu, Dong; Zhang, Jian; Roy, Ambrish; Zhang, Yang

2011-01-01

I-TASSER is an automated pipeline for protein tertiary structure prediction using multiple threading alignments and iterative structure assembly simulations. In CASP9 experiments, two new algorithms, QUARK and FG-MD, were added to the I-TASSER pipeline for improving the structural modeling accuracy. QUARK is a de novo structure prediction algorithm used for structure modeling of proteins that lack detectable template structures. For distantly homologous targets, QUARK models are found useful as a reference structure for selecting good threading alignments and guiding the I-TASSER structure assembly simulations. FG-MD is an atomic-level structural refinement program that uses structural fragments collected from the PDB structures to guide molecular dynamics simulation and improve the local structure of predicted model, including hydrogen-bonding networks, torsion angles and steric clashes. Despite considerable progress in both the template-based and template-free structure modeling, significant improvements on protein target classification, domain parsing, model selection, and ab initio folding of beta-proteins are still needed to further improve the I-TASSER pipeline. PMID:22069036

How to Use Value-Added Analysis to Improve Student Learning: A Field Guide for School and District Leaders

ERIC Educational Resources Information Center

Kennedy, Kate; Peters, Mary; Thomas, Mike

2012-01-01

Value-added analysis is the most robust, statistically significant method available for helping educators quantify student progress over time. This powerful tool also reveals tangible strategies for improving instruction. Built around the work of Battelle for Kids, this book provides a field-tested continuous improvement model for using…

Improving Earth/Prediction Models to Improve Network Processing

NASA Astrophysics Data System (ADS)

Wagner, G. S.

2017-12-01

The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.

A hybrid health service accreditation program model incorporating mandated standards and continuous improvement: interview study of multiple stakeholders in Australian health care.

PubMed

Greenfield, David; Hinchcliff, Reece; Hogden, Anne; Mumford, Virginia; Debono, Deborah; Pawsey, Marjorie; Westbrook, Johanna; Braithwaite, Jeffrey

2016-07-01

The study aim was to investigate the understandings and concerns of stakeholders regarding the evolution of health service accreditation programs in Australia. Stakeholder representatives from programs in the primary, acute and aged care sectors participated in semi-structured interviews. Across 2011-12 there were 47 group and individual interviews involving 258 participants. Interviews lasted, on average, 1 h, and were digitally recorded and transcribed. Transcriptions were analysed using textual referencing software. Four significant issues were considered to have directed the evolution of accreditation programs: altering underlying program philosophies; shifting of program content focus and details; different surveying expectations and experiences and the influence of external contextual factors upon accreditation programs. Three accreditation program models were noted by participants: regulatory compliance; continuous quality improvement and a hybrid model, incorporating elements of these two. Respondents noted the compatibility or incommensurability of the first two models. Participation in a program was reportedly experienced as ranging on a survey continuum from "malicious compliance" to "performance audits" to "quality improvement journeys". Wider contextual factors, in particular, political and community expectations, and associated media reporting, were considered significant influences on the operation and evolution of programs. A hybrid accreditation model was noted to have evolved. The hybrid model promotes minimum standards and continuous quality improvement, through examining the structure and processes of organisations and the outcomes of care. The hybrid model appears to be directing organisational and professional attention to enhance their safety cultures. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Usefulness of the addition of beta-2-microglobulin, cystatin C and C-reactive protein to an established risk factors model to improve mortality risk prediction in patients undergoing coronary angiography.

PubMed

Nead, Kevin T; Zhou, Margaret J; Caceres, Roxanne Diaz; Sharp, Stephen J; Wehner, Mackenzie R; Olin, Jeffrey W; Cooke, John P; Leeper, Nicholas J

2013-03-15

Evidence-based therapies are available to reduce the risk for death from cardiovascular disease, yet many patients go untreated. Novel methods are needed to identify those at highest risk for cardiovascular death. In this study, the biomarkers β2-microglobulin, cystatin C, and C-reactive protein were measured at baseline in a cohort of participants who underwent coronary angiography. Adjusted Cox proportional-hazards models were used to determine whether the biomarkers predicted all-cause and cardiovascular mortality. Additionally, improvements in risk reclassification and discrimination were evaluated by calculating the net reclassification improvement, C-index, and integrated discrimination improvement with the addition of the biomarkers to a baseline model of risk factors for cardiovascular disease and death. During a median follow-up period of 5.6 years, there were 78 deaths among 470 participants. All biomarkers independently predicted future all-cause and cardiovascular mortality. A significant improvement in risk reclassification was observed for all-cause (net reclassification improvement 35.8%, p = 0.004) and cardiovascular (net reclassification improvement 61.9%, p = 0.008) mortality compared to the baseline risk factors model. Additionally, there was significantly increased risk discrimination with C-indexes of 0.777 (change in C-index 0.057, 95% confidence interval 0.016 to 0.097) and 0.826 (change in C-index 0.071, 95% confidence interval 0.010 to 0.133) for all-cause and cardiovascular mortality, respectively. Improvements in risk discrimination were further supported using the integrated discrimination improvement index. In conclusion, this study provides evidence that β2-microglobulin, cystatin C, and C-reactive protein predict mortality and improve risk reclassification and discrimination for a high-risk cohort of patients who undergo coronary angiography. Copyright © 2013 Elsevier Inc. All rights reserved.

Centers for medicare and medicaid services: using an episode-based payment model to improve oncology care.

PubMed

Kline, Ronald M; Bazell, Carol; Smith, Erin; Schumacher, Heidi; Rajkumar, Rahul; Conway, Patrick H

2015-03-01

Cancer is a medically complex and expensive disease with costs projected to rise further as new treatment options increase and the United States population ages. Studies showing significant regional variation in oncology quality and costs and model tests demonstrating cost savings without adverse outcomes suggest there are opportunities to create a system of oncology care in the US that delivers higher quality care at lower cost. The Centers for Medicare and Medicaid Services (CMS) have designed an episode-based payment model centered around 6 month periods of chemotherapy treatment. Monthly per-patient care management payments will be made to practices to support practice transformation, including additional patient services and specific infrastructure enhancements. Quarterly reporting of quality metrics will drive continuous quality improvement and the adoption of best practices among participants. Practices achieving cost savings will also be eligible for performance-based payments. Savings are expected through improved care coordination and appropriately aligned payment incentives, resulting in decreased avoidable emergency department visits and hospitalizations and more efficient and evidence-based use of imaging, laboratory tests, and therapeutic agents, as well as improved end of life care. New therapies and better supportive care have significantly improved cancer survival in recent decades. This has come at a high cost, with cancer therapy consuming $124 billion in 2010. CMS has designed an episode-based model of oncology care that incorporates elements from several successful model tests. By providing care management and performance based payments in conjunction with quality metrics and a rapid learning environment, it is hoped that this model will demonstrate how oncology care in the US can transform into a high value, high quality system. Copyright © 2015 by American Society of Clinical Oncology.

Effect of roughness formulation on the performance of a coupled wave, hydrodynamic, and sediment transport model

USGS Publications Warehouse

Ganju, Neil K.; Sherwood, Christopher R.

2010-01-01

A variety of algorithms are available for parameterizing the hydrodynamic bottom roughness associated with grain size, saltation, bedforms, and wave–current interaction in coastal ocean models. These parameterizations give rise to spatially and temporally variable bottom-drag coefficients that ostensibly provide better representations of physical processes than uniform and constant coefficients. However, few studies have been performed to determine whether improved representation of these variable bottom roughness components translates into measurable improvements in model skill. We test the hypothesis that improved representation of variable bottom roughness improves performance with respect to near-bed circulation, bottom stresses, or turbulence dissipation. The inner shelf south of Martha’s Vineyard, Massachusetts, is the site of sorted grain-size features which exhibit sharp alongshore variations in grain size and ripple geometry over gentle bathymetric relief; this area provides a suitable testing ground for roughness parameterizations. We first establish the skill of a nested regional model for currents, waves, stresses, and turbulent quantities using a uniform and constant roughness; we then gauge model skill with various parameterization of roughness, which account for the influence of the wave-boundary layer, grain size, saltation, and rippled bedforms. We find that commonly used representations of ripple-induced roughness, when combined with a wave–current interaction routine, do not significantly improve skill for circulation, and significantly decrease skill with respect to stresses and turbulence dissipation. Ripple orientation with respect to dominant currents and ripple shape may be responsible for complicating a straightforward estimate of the roughness contribution from ripples. In addition, sediment-induced stratification may be responsible for lower stresses than predicted by the wave–current interaction model.

Significant and Sustained Reduction in Chemotherapy Errors Through Improvement Science.

PubMed

Weiss, Brian D; Scott, Melissa; Demmel, Kathleen; Kotagal, Uma R; Perentesis, John P; Walsh, Kathleen E

2017-04-01

A majority of children with cancer are now cured with highly complex chemotherapy regimens incorporating multiple drugs and demanding monitoring schedules. The risk for error is high, and errors can occur at any stage in the process, from order generation to pharmacy formulation to bedside drug administration. Our objective was to describe a program to eliminate errors in chemotherapy use among children. To increase reporting of chemotherapy errors, we supplemented the hospital reporting system with a new chemotherapy near-miss reporting system. After the model for improvement, we then implemented several interventions, including a daily chemotherapy huddle, improvements to the preparation and delivery of intravenous therapy, headphones for clinicians ordering chemotherapy, and standards for chemotherapy administration throughout the hospital. Twenty-two months into the project, we saw a centerline shift in our U chart of chemotherapy errors that reached the patient from a baseline rate of 3.8 to 1.9 per 1,000 doses. This shift has been sustained for > 4 years. In Poisson regression analyses, we found an initial increase in error rates, followed by a significant decline in errors after 16 months of improvement work ( P < .001). After the model for improvement, our improvement efforts were associated with significant reductions in chemotherapy errors that reached the patient. Key drivers for our success included error vigilance through a huddle, standardization, and minimization of interruptions during ordering.

Multiple model analysis with discriminatory data collection (MMA-DDC): A new method for improving measurement selection

NASA Astrophysics Data System (ADS)

Kikuchi, C.; Ferre, P. A.; Vrugt, J. A.

2011-12-01

Hydrologic models are developed, tested, and refined based on the ability of those models to explain available hydrologic data. The optimization of model performance based upon mismatch between model outputs and real world observations has been extensively studied. However, identification of plausible models is sensitive not only to the models themselves - including model structure and model parameters - but also to the location, timing, type, and number of observations used in model calibration. Therefore, careful selection of hydrologic observations has the potential to significantly improve the performance of hydrologic models. In this research, we seek to reduce prediction uncertainty through optimization of the data collection process. A new tool - multiple model analysis with discriminatory data collection (MMA-DDC) - was developed to address this challenge. In this approach, multiple hydrologic models are developed and treated as competing hypotheses. Potential new data are then evaluated on their ability to discriminate between competing hypotheses. MMA-DDC is well-suited for use in recursive mode, in which new observations are continuously used in the optimization of subsequent observations. This new approach was applied to a synthetic solute transport experiment, in which ranges of parameter values constitute the multiple hydrologic models, and model predictions are calculated using likelihood-weighted model averaging. MMA-DDC was used to determine the optimal location, timing, number, and type of new observations. From comparison with an exhaustive search of all possible observation sequences, we find that MMA-DDC consistently selects observations which lead to the highest reduction in model prediction uncertainty. We conclude that using MMA-DDC to evaluate potential observations may significantly improve the performance of hydrologic models while reducing the cost associated with collecting new data.

Improving the Accuracy of Satellite Sea Surface Temperature Measurements by Explicitly Accounting for the Bulk-Skin Temperature Difference

NASA Technical Reports Server (NTRS)

Wick, Gary A.; Emery, William J.; Castro, Sandra L.; Lindstrom, Eric (Technical Monitor)

2002-01-01

The focus of this research was to determine whether the accuracy of satellite measurements of sea surface temperature (SST) could be improved by explicitly accounting for the complex temperature gradients at the surface of the ocean associated with the cool skin and diurnal warm layers. To achieve this goal, work was performed in two different major areas. The first centered on the development and deployment of low-cost infrared radiometers to enable the direct validation of satellite measurements of skin temperature. The second involved a modeling and data analysis effort whereby modeled near-surface temperature profiles were integrated into the retrieval of bulk SST estimates from existing satellite data. Under the first work area, two different seagoing infrared radiometers were designed and fabricated and the first of these was deployed on research ships during two major experiments. Analyses of these data contributed significantly to the Ph.D. thesis of one graduate student and these results are currently being converted into a journal publication. The results of the second portion of work demonstrated that, with presently available models and heat flux estimates, accuracy improvements in SST retrievals associated with better physical treatment of the near-surface layer were partially balanced by uncertainties in the models and extra required input data. While no significant accuracy improvement was observed in this experiment, the results are very encouraging for future applications where improved models and coincident environmental data will be available. These results are included in a manuscript undergoing final review with the Journal of Atmospheric and Oceanic Technology.

Numerical simulations and observations of surface wave fields under an extreme tropical cyclone

USGS Publications Warehouse

Fan, Y.; Ginis, I.; Hara, T.; Wright, C.W.; Walsh, E.J.

2009-01-01

The performance of the wave model WAVEWATCH III under a very strong, category 5, tropical cyclone wind forcing is investigated with different drag coefficient parameterizations and ocean current inputs. The model results are compared with field observations of the surface wave spectra from an airborne scanning radar altimeter, National Data Buoy Center (NDBC) time series, and satellite altimeter measurements in Hurricane Ivan (2004). The results suggest that the model with the original drag coefficient parameterization tends to overestimate the significant wave height and the dominant wavelength and produces a wave spectrum with narrower directional spreading. When an improved drag parameterization is introduced and the wave-current interaction is included, the model yields an improved forecast of significant wave height, but underestimates the dominant wavelength. When the hurricane moves over a preexisting mesoscale ocean feature, such as the Loop Current in the Gulf of Mexico or a warm-and cold-core ring, the current associated with the feature can accelerate or decelerate the wave propagation and significantly modulate the wave spectrum. ?? 2009 American Meteorological Society.

Improvement of radiology services based on the process management approach.

PubMed

Amaral, Creusa Sayuri Tahara; Rozenfeld, Henrique; Costa, Janaina Mascarenhas Hornos; Magon, Maria de Fátima de Andrade; Mascarenhas, Yvone Maria

2011-06-01

The health sector requires continuous investments to ensure the improvement of products and services from a technological standpoint, the use of new materials, equipment and tools, and the application of process management methods. Methods associated with the process management approach, such as the development of reference models of business processes, can provide significant innovations in the health sector and respond to the current market trend for modern management in this sector (Gunderman et al. (2008) [4]). This article proposes a process model for diagnostic medical X-ray imaging, from which it derives a primary reference model and describes how this information leads to gains in quality and improvements. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Io's Magnetospheric Interaction: An MHD Model with Day-Night Asymmetry

NASA Technical Reports Server (NTRS)

Kabin, K.; Combi, M. R.; Gombosi, T. I.; DeZeeuw, D. L.; Hansen, K. C.; Powell, K. G.

2001-01-01

In this paper we present the results of all improved three-dimensional MHD model for Io's interaction with Jupiter's magnetosphere. We have included the day-night asymmetry into the spatial distribution of our mass-loading, which allowed us to reproduce several smaller features or the Galileo December 1995 data set. The calculation is performed using our newly modified description of the pick-up processes that accounts for the effects of the corotational electric field existing in the Jovian magnetosphere. This change in the formulation of the source terms for the MHD equations resulted in significant improvements in the comparison with the Galileo measurements. We briefly discuss the limitations of our model and possible future improvements.

The use of an exclusion-based risk-assessment model for venous thrombosis improves uptake of appropriate thromboprophylaxis in hospitalized medical patients.

PubMed

Bagot, C; Gohil, S; Perrott, R; Barsam, S; Patel, R K; Arya, R

2010-08-01

Venous thromboembolism is a common condition in hospitalized medical patients. Numerous studies have demonstrated that low molecular weight heparin significantly reduces this risk but, despite this, the use of thromboprophylaxis remains poor. To evaluate the use of an exclusion based risk-assessment model (RAM) for venous thrombosis in improving the uptake of appropriate thromboprophylaxis in hospitalized medical patients. A survey with a subsequent audit cycle of three separate audits over 36 months. 497 hospitalized patients with acute medical conditions on general medical wards were audited at a secondary care centre in London, UK. The survey and subsequent audits were performed by reviewing the notes and medication charts of medical patients, prior to the launch of the RAM and at 12, 28 and 36 months following its introduction. Prior to launching the RAM, 49% of hospitalized medical patients received appropriate thromboprophylaxis. This did not change 12 months after the RAM was introduced but increased significantly to 71% following formal education of the health care professionals involved in thromboprophylaxis prescription. This improvement was maintained as demonstrated by a subsequent audit 8 months later (75.9%). The introduction of a simple exclusion-based RAM for venous thrombosis in medical patients significantly improved delivery of thromboprophylaxis. The successful uptake of the RAM appears to have been dependent on direct education of those health carers involved in its use. A similar exclusion-based model used nationally could have a significant impact on the burden of VTE currently experienced in the UK.

Recreational benefits of urban forests: explaining visitors' willingness to pay in the context of the theory of planned behavior.

PubMed

Bernath, Katrin; Roschewitz, Anna

2008-11-01

The extension of contingent valuation models with an attitude-behavior based framework has been proposed in order to improve the descriptive and predictive ability of the models. This study examines the potential of the theory of planned behavior to explain willingness to pay (WTP) in a contingent valuation survey of the recreational benefits of the Zurich city forests. Two aspects of WTP responses, protest votes and bid levels, were analyzed separately. In both steps, models with and without the psychological predictors proposed by the theory of planned behavior were compared. Whereas the inclusion of the psychological predictors significantly improved explanations of protest votes, their ability to improve the performance of the model explaining bid levels was limited. The results indicate that the interpretation of bid levels as behavioral intention may not be appropriate and that the potential of the theory of planned behavior to improve contingent valuation models depends on which aspect of WTP responses is examined.

Application of a sub-specialties management model improves quality control in a central sterile supply department.

PubMed

Wang, Li; Cai, Xuejiao; Cheng, Ping

2018-05-30

The management of medical devices is crucial to safe, high-quality surgical care, but has received little attention in the medical literature. This study explored the effect of a sub-specialties management model in the Central Sterile Supply Department (CSSD). A traditional routine management model (control) was applied from September 2015 through April 2016, and a newly developed sub-specialties management model (observation) was applied from July 2016 through February 2017. Health personnel from various clinical departments were randomly selected to participate as the control (n = 86) and observation (n = 90) groups, respectively. The groups were compared for rates of personnel satisfaction, complaints regarding device errors, and damage of medical devices. The satisfaction score of the observation group (95.8 ± 1.2) was significantly higher than that of the control (90.2 ± 2.3; P = 0.000). The rate of complaints of the observation group (3.3%) was significantly lower than that of the control (11.6%; P = 0.035). The quality control regarding recycle and packing was significantly higher during the observation period than the control period, which favorably influenced the scores for satisfaction. The rate of damage to specialist medical devices during the observation period (0.40%) was lower than during the control period (0.61%; P = 0.003). The theoretical knowledge and practical skills of the CSSD professionals improved after application of the sub-specialties management model. A management model that considers the requirements of specialist medical devices can improve quality control in the CSSD.

APPLICATION OF A MICROSCALE EMISSION FACTOR MODEL FOR PARTICULATE MATTER (MICROFACPM) IN CONJUNCTION WITH CALINE4-MODEL

EPA Science Inventory

The United States Environmental Protection Agency's (EPA) National Exposure Research Laboratory is developing improved methods for modeling the pollutant sources through the air pathway to human exposure in significant microenvironments of exposure. As a part of this project, w...

Merging bioreactor technology with 3D hepatocyte-fibroblast culturing approaches: Improved in vitro models for toxicological applications.

PubMed

Leite, Sofia B; Teixeira, Ana P; Miranda, Joana P; Tostões, Rui M; Clemente, João J; Sousa, Marcos F; Carrondo, Manuel J T; Alves, Paula M

2011-06-01

During the last years an increasing number of in vitro models have been developed for drug screening and toxicity testing. Primary cultures of hepatocytes are, by far, the model of choice for those high-throughput studies but their spontaneous dedifferentiation after some time in culture hinders long-term studies. Thus, novel cell culture systems allowing extended hepatocyte maintenance and more predictive long term in vitro studies are required. It has been shown that hepatocytes functionality can be improved and extended in time when cultured as 3D-cell aggregates in environmental controlled stirred bioreactors. In this work, aiming at further improving hepatocytes functionality in such 3D cellular structures, co-cultures with fibroblasts were performed. An inoculum concentration of 1.2×10(5) cell/mL and a 1:2 hepatocyte:mouse embryonic fibroblast ratio allowed to improve significantly the albumin secretion rate and both ECOD (phase I) and UGT (phase II) enzymatic activities in 3D co-cultures, as compared to the routinely used 2D hepatocyte monocultures. Significant improvements were also observed in relation to 3D monocultures of hepatocytes. Furthermore, hepatocytes were able to respond to the addition of beta-Naphtoflavone by increasing ECOD activity showing CYP1A inducibility. The dependence of CYP activity on oxygen concentration was also observed. In summary, the improved hepatocyte specific functions during long term incubation of 3D co-cultures of hepatocytes with fibroblasts indicate that this system is a promising in vitro model for long term toxicological studies. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling the probability of arsenic in groundwater in New England as a tool for exposure assessment.

PubMed

Ayotte, Joseph D; Nolan, Bernard T; Nuckols, John R; Cantor, Kenneth P; Robinson, Gilpin R; Baris, Dalsu; Hayes, Laura; Karagas, Margaret; Bress, William; Silverman, Debra T; Lubin, Jay H

2006-06-01

We developed a process-based model to predict the probability of arsenic exceeding 5 microg/L in drinking water wells in New England bedrock aquifers. The model is being used for exposure assessment in an epidemiologic study of bladder cancer. One important study hypothesis that may explain increased bladder cancer risk is elevated concentrations of inorganic arsenic in drinking water. In eastern New England, 20-30% of private wells exceed the arsenic drinking water standard of 10 micrograms per liter. Our predictive model significantly improves the understanding of factors associated with arsenic contamination in New England. Specific rock types, high arsenic concentrations in stream sediments, geochemical factors related to areas of Pleistocene marine inundation and proximity to intrusive granitic plutons, and hydrologic and landscape variables relating to groundwater residence time increase the probability of arsenic occurrence in groundwater. Previous studies suggest that arsenic in bedrock groundwater may be partly from past arsenical pesticide use. Variables representing historic agricultural inputs do not improve the model, indicating that this source does not significantly contribute to current arsenic concentrations. Due to the complexity of the fractured bedrock aquifers in the region, well depth and related variables also are not significant predictors.

Short-Period, Anelastic and Anisotropic, Waveform-Based 3D Middle East Model to Improve Nuclear Explosion Monitoring

DTIC Science & Technology

2014-08-30

initial wave speed model, M00, was used while model iteration 13, M13 , was used within. This expansion of the model does not significantly alter the...total misfit between M13 and M14. The increase in events, stations, and ray-based path coverage is displayed in Figure 4. Expanding the model domain

Protein simulation using coarse-grained two-bead multipole force field with polarizable water models.

PubMed

Li, Min; Zhang, John Z H

2017-02-14

A recently developed two-bead multipole force field (TMFF) is employed in coarse-grained (CG) molecular dynamics (MD) simulation of proteins in combination with polarizable CG water models, the Martini polarizable water model, and modified big multipole water model. Significant improvement in simulated structures and dynamics of proteins is observed in terms of both the root-mean-square deviations (RMSDs) of the structures and residue root-mean-square fluctuations (RMSFs) from the native ones in the present simulation compared with the simulation result with Martini's non-polarizable water model. Our result shows that TMFF simulation using CG water models gives much stable secondary structures of proteins without the need for adding extra interaction potentials to constrain the secondary structures. Our result also shows that by increasing the MD time step from 2 fs to 6 fs, the RMSD and RMSF results are still in excellent agreement with those from all-atom simulations. The current study demonstrated clearly that the application of TMFF together with a polarizable CG water model significantly improves the accuracy and efficiency for CG simulation of proteins.

Protein simulation using coarse-grained two-bead multipole force field with polarizable water models

NASA Astrophysics Data System (ADS)

Li, Min; Zhang, John Z. H.

2017-02-01

A recently developed two-bead multipole force field (TMFF) is employed in coarse-grained (CG) molecular dynamics (MD) simulation of proteins in combination with polarizable CG water models, the Martini polarizable water model, and modified big multipole water model. Significant improvement in simulated structures and dynamics of proteins is observed in terms of both the root-mean-square deviations (RMSDs) of the structures and residue root-mean-square fluctuations (RMSFs) from the native ones in the present simulation compared with the simulation result with Martini's non-polarizable water model. Our result shows that TMFF simulation using CG water models gives much stable secondary structures of proteins without the need for adding extra interaction potentials to constrain the secondary structures. Our result also shows that by increasing the MD time step from 2 fs to 6 fs, the RMSD and RMSF results are still in excellent agreement with those from all-atom simulations. The current study demonstrated clearly that the application of TMFF together with a polarizable CG water model significantly improves the accuracy and efficiency for CG simulation of proteins.

Enhancing performance of P300-Speller under mental workload by incorporating dual-task data during classifier training.

PubMed

Chen, Yuqian; Ke, Yufeng; Meng, Guifang; Jiang, Jin; Qi, Hongzhi; Jiao, Xuejun; Xu, Minpeng; Zhou, Peng; He, Feng; Ming, Dong

2017-12-01

As one of the most important brain-computer interface (BCI) paradigms, P300-Speller was shown to be significantly impaired once applied in practical situations due to effects of mental workload. This study aims to provide a new method of building training models to enhance performance of P300-Speller under mental workload. Three experiment conditions based on row-column P300-Speller paradigm were performed including speller-only, 3-back-speller and mental-arithmetic-speller. Data under dual-task conditions were introduced to speller-only data respectively to build new training models. Then performance of classifiers with different models was compared under the same testing condition. The results showed that when tasks of imported training data and testing data were the same, character recognition accuracies and round accuracies of P300-Speller with mixed-data training models significantly improved (FDR, p < 0.005). When they were different, performance significantly improved when tested on mental-arithmetic-speller (FDR, p < 0.05) while the improvement was modest when tested on n-back-speller (FDR, p < 0.1). The analysis of ERPs revealed that ERP difference between training data and testing data was significantly diminished when the dual-task data was introduced to training data (FDR, p < 0.05). The new method of training classifier on mixed data proved to be effective in enhancing performance of P300-Speller under mental workload, confirmed the feasibility to build a universal training model and overcome the effects of mental workload in its practical applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Self-Shadowing of a Spacecraft in the Computation of Surface Forces. An Example in Planetary Geodesy

NASA Astrophysics Data System (ADS)

Balmino, G.; Marty, J. C.

2018-03-01

We describe in details the algorithms used in modelling the self-shadowing between spacecraft components, which appears when computing the surface forces as precisely as possible and especially when moving parts are involved. This becomes necessary in planetary geodesy inverse problems using more and more precise orbital information to derive fundamental parameters of geophysical interest. Examples are given with two Mars orbiters, which show significant improvement on drag and solar radiation pressure model multiplying factors, a prerequisite for improving in turn the determination of other global models.

The effect of two kinds of role playing on self-evaluation of improved assertiveness.

PubMed

Kipper, D A

1992-03-01

The study investigated the "differential effect of role-playing enactments" hypothesis through self-evaluations of improvement in assertiveness by participants in an assertive training program. Twenty-two nonassertive Israeli students were trained in two groups: mimetic-replications (action modeling, n = 12) and spontaneous (self-produced action, n = 10) role-playing interventions. Comparisons of their scores on the Self-Expression College Scale (CSES) before and after the training showed that both groups significantly improved their self-evaluations, but the mimetic-replication group did better. In particular, this group scored significantly higher on the CSES first factor (the willingness to take risks in situations that involved other, significant persons).

Modeling coverage gaps in haplotype frequencies via Bayesian inference to improve stem cell donor selection.

PubMed

Louzoun, Yoram; Alter, Idan; Gragert, Loren; Albrecht, Mark; Maiers, Martin

2018-05-01

Regardless of sampling depth, accurate genotype imputation is limited in regions of high polymorphism which often have a heavy-tailed haplotype frequency distribution. Many rare haplotypes are thus unobserved. Statistical methods to improve imputation by extending reference haplotype distributions using linkage disequilibrium patterns that relate allele and haplotype frequencies have not yet been explored. In the field of unrelated stem cell transplantation, imputation of highly polymorphic human leukocyte antigen (HLA) genes has an important application in identifying the best-matched stem cell donor when searching large registries totaling over 28,000,000 donors worldwide. Despite these large registry sizes, a significant proportion of searched patients present novel HLA haplotypes. Supporting this observation, HLA population genetic models have indicated that many extant HLA haplotypes remain unobserved. The absent haplotypes are a significant cause of error in haplotype matching. We have applied a Bayesian inference methodology for extending haplotype frequency distributions, using a model where new haplotypes are created by recombination of observed alleles. Applications of this joint probability model offer significant improvement in frequency distribution estimates over the best existing alternative methods, as we illustrate using five-locus HLA frequency data from the National Marrow Donor Program registry. Transplant matching algorithms and disease association studies involving phasing and imputation of rare variants may benefit from this statistical inference framework.

Improving Safe Sleep Modeling in the Hospital through Policy Implementation.

PubMed

Heitmann, Rachel; Nilles, Ester K; Jeans, Ashley; Moreland, Jackie; Clarke, Chris; McDonald, Morgan F; Warren, Michael D

2017-11-01

Introduction Sleep-related infant deaths are major contributors to Tennessee's high infant mortality rate. The purpose of this initiative was to evaluate the impact of policy-based efforts to improve modeling of safe sleep practices by health care providers in hospital settings across Tennessee. Methods Safe sleep policies were developed and implemented at 71 hospitals in Tennessee. Policies, at minimum, were required to address staff training on the American Academy of Pediatrics' safe sleep recommendations, correct modeling of infant safe sleep practices, and parent education. Hospital data on process measures related to training and results of crib audits were compiled for analysis. Results The overall observance of infants who were found with any risk factors for unsafe sleep decreased 45.6% (p ≤ 0.001) from the first crib audit to the last crib audit. Significant decreases were noted for specific risk factors, including infants found asleep not on their back, with a toy or object in the crib, and not sleeping in a crib. Significant improvements were observed at hospitals where printed materials or video were utilized for training staff compared to face-to-face training. Discussion Statewide implementation of the hospital policy intervention resulted in significant reductions in infants found in unsafe sleep situations. The most common risk factors for sleep-related infant deaths can be modeled in hospitals. This effort has the potential to reduce sleep-related infant deaths and ultimately infant mortality.

Pan-Arctic River Discharge: Where Can We Improve Monitoring of Future Change?

NASA Astrophysics Data System (ADS)

Bring, A.; Shiklomanov, A. I.; Lammers, R. B.

2016-12-01

The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flow to detect, observe and understand changes and provide adaptation information. There has however been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change, and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.

Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

PubMed Central

Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614

Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

PubMed

Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

Comparison of Different Attitude Correction Models for ZY-3 Satellite Imagery

NASA Astrophysics Data System (ADS)

Song, Wenping; Liu, Shijie; Tong, Xiaohua; Niu, Changling; Ye, Zhen; Zhang, Han; Jin, Yanmin

2018-04-01

ZY-3 satellite, launched in 2012, is the first civilian high resolution stereo mapping satellite of China. This paper analyzed the positioning errors of ZY-3 satellite imagery and conducted compensation for geo-position accuracy improvement using different correction models, including attitude quaternion correction, attitude angle offset correction, and attitude angle linear correction. The experimental results revealed that there exist systematic errors with ZY-3 attitude observations and the positioning accuracy can be improved after attitude correction with aid of ground controls. There is no significant difference between the results of attitude quaternion correction method and the attitude angle correction method. However, the attitude angle offset correction model produced steady improvement than the linear correction model when limited ground control points are available for single scene.

Using Flux Site Observations to Calibrate Root System Architecture Stencils for Water Uptake of Plant Functional Types in Land Surface Models.

NASA Astrophysics Data System (ADS)

Bouda, M.

2017-12-01

Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, RSA has not been included because of its three-dimensional complexity, which makes RSA modelling generally too computationally costly. This work builds upon the recently introduced "RSA stencil," a process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA in response to heterogeneous soil moisture profiles. In validations using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, the RSA stencil predicts plant water potentials within 2% of the outputs of full 3D models, despite its trivial computational cost. In transient simulations, the RSA stencil yields improved predictions of water uptake and soil moisture profiles compared to a 1D model based on root fraction alone. Here I show how the RSA stencil can be calibrated to time-series observations of soil moisture and transpiration to yield a water uptake PFT definition for use in terrestrial models. This model-data integration exercise aims to improve LSM predictions of soil moisture dynamics and, under water-limiting conditions, surface fluxes. These improvements can be expected to significantly impact predictions of downstream variables, including surface fluxes, climate-vegetation feedbacks and soil nutrient cycling.

Accurate and dynamic predictive model for better prediction in medicine and healthcare.

PubMed

Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

2018-05-01

Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

An improved Multimodel Approach for Global Sea Surface Temperature Forecasts

NASA Astrophysics Data System (ADS)

Khan, M. Z. K.; Mehrotra, R.; Sharma, A.

2014-12-01

The concept of ensemble combinations for formulating improved climate forecasts has gained popularity in recent years. However, many climate models share similar physics or modeling processes, which may lead to similar (or strongly correlated) forecasts. Recent approaches for combining forecasts that take into consideration differences in model accuracy over space and time have either ignored the similarity of forecast among the models or followed a pairwise dynamic combination approach. Here we present a basis for combining model predictions, illustrating the improvements that can be achieved if procedures for factoring in inter-model dependence are utilised. The utility of the approach is demonstrated by combining sea surface temperature (SST) forecasts from five climate models over a period of 1960-2005. The variable of interest, the monthly global sea surface temperature anomalies (SSTA) at a 50´50 latitude-longitude grid, is predicted three months in advance to demonstrate the utility of the proposed algorithm. Results indicate that the proposed approach offers consistent and significant improvements for majority of grid points compared to the case where the dependence among the models is ignored. Therefore, the proposed approach of combining multiple models by taking into account the existing interdependence, provides an attractive alternative to obtain improved climate forecast. In addition, an approach to combine seasonal forecasts from multiple climate models with varying periods of availability is also demonstrated.

Informatics Approach to Improving Surgical Skills Training

ERIC Educational Resources Information Center

Islam, Gazi

2013-01-01

Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of…

Improving collaborative learning in online software engineering education

NASA Astrophysics Data System (ADS)

Neill, Colin J.; DeFranco, Joanna F.; Sangwan, Raghvinder S.

2017-11-01

Team projects are commonplace in software engineering education. They address a key educational objective, provide students critical experience relevant to their future careers, allow instructors to set problems of greater scale and complexity than could be tackled individually, and are a vehicle for socially constructed learning. While all student teams experience challenges, those in fully online programmes must also deal with remote working, asynchronous coordination, and computer-mediated communications all of which contribute to greater social distance between team members. We have developed a facilitation framework to aid team collaboration and have demonstrated its efficacy, in prior research, with respect to team performance and outcomes. Those studies indicated, however, that despite experiencing improved project outcomes, students working in effective software engineering teams did not experience significantly improved individual achievement. To address this deficiency we implemented theoretically grounded refinements to the collaboration model based upon peer-tutoring research. Our results indicate a modest, but statistically significant (p = .08), improvement in individual achievement using this refined model.

Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes

USGS Publications Warehouse

Williamson, Tanja N.; Taylor, Charles J.; Newson, Jeremy K.

2013-01-01

The Water Availability Tool for Environmental Resources (WATER) is a TOPMODEL-based hydrologic model that depends on spatially accurate soils data to function in diverse terranes. In Kentucky, this includes mountainous regions, karstic plateau, and alluvial plains. Soils data are critical because they quantify the space to store water, as well as how water moves through the soil to the stream during storm events. We compared how the model performs using two different sources of soils data--Soil Survey Geographic Database (SSURGO) and State Soil Geographic Database laboratory data (STATSGO)--for 21 basins ranging in size from 17 to 1564 km2. Model results were consistently better when SSURGO data were used, likely due to the higher field capacity, porosity, and available-water holding capacity, which cause the model to store more soil-water in the landscape and improve streamflow estimates for both low- and high-flow conditions. In addition, there were significant differences in the conductivity multiplier and scaling parameter values that describe how water moves vertically and laterally, respectively, as quantified by TOPMODEL. We also evaluated whether partitioning areas that drain to streams via sinkholes in karstic basins as separate hydrologic modeling units (HMUs) improved model performance. There were significant differences between HMUs in properties that control soil-water storage in the model, although the effect of partitioning these HMUs on streamflow simulation was inconclusive.

Two-year follow-up of outcomes related to scarring and distress in children with severe burns.

PubMed

Wurzer, Paul; Forbes, Abigail A; Hundeshagen, Gabriel; Andersen, Clark R; Epperson, Kathryn M; Meyer, Walter J; Kamolz, Lars P; Branski, Ludwik K; Suman, Oscar E; Herndon, David N; Finnerty, Celeste C

2017-08-01

We assessed the perception of scarring and distress by pediatric burn survivors with burns covering more than one-third of total body surface area (TBSA) for up to 2 years post-burn. Children with severe burns were admitted to our hospital between 2004 and 2012, and consented to this IRB-approved-study. Subjects completed at least one Scars Problems and/or Distress questionnaire between discharge and 24 months post burn. Outcomes were modeled with generalized estimating equations or using mixed linear models. Significance was accepted at p < 0.01. Responses of 167 children with a mean age of 7 ± 5 years and burns covering an average 54 ± 14% of TBSA were analyzed. Significant improvements over the 2-year period were seen in reduction of pain, itching, sleeping disturbance, tightness, range of motion, and strength (p < 0.01). There was a significantly increased persistent desire to hide the scarred body areas over time (p < 0.01). The perception of mouth scarring, inability to portray accurate facial expressions, and skin coloration did not improve over the follow-up period. According to self-assessment questionnaires, severely burned children exhibit significant improvements in their overall perception of scarring and distress. However, these patients remain self-conscious with respect to their body image even 2 years after burn injury. Implications for Rehabilitation According to self-assessment questionnaires, severely burned children perceive significant improvements in scarring and distress during the first 2 years post burn. Significant improvements were seen in reduction of pain, itching, sleeping disturbances, tightness, range of motion, and strength (p < 0.01). Burn care providers should improve the treatment of burns surrounding the mouth that with result in scarring, and develop strategies to prevent skin discoloration. Careful evaluation of pain and sleeping disorders during the first year post burn are warranted to improve the patient rehabilitation. Overall, significantly more female patients expressed a persistent desire to hide their scarred body areas. The rehabilitation team should provide access to wigs or other aids to pediatric burn survivors to address these needs.

Improving Air Quality Forecasts with AURA Observations

NASA Technical Reports Server (NTRS)

Newchurch, M. J.; Biazer, A.; Khan, M.; Koshak, W. J.; Nair, U.; Fuller, K.; Wang, L.; Parker, Y.; Williams, R.; Liu, X.

2008-01-01

Past studies have identified model initial and boundary conditions as sources of reducible errors in air-quality simulations. In particular, improving the initial condition improves the accuracy of short-term forecasts as it allows for the impact of local emissions to be realized by the model and improving boundary conditions improves long range transport through the model domain, especially in recirculating anticyclones. During the August 2006 period, we use AURA/OMI ozone measurements along with MODIS and CALIPSO aerosol observations to improve the initial and boundary conditions of ozone and Particulate Matter. Assessment of the model by comparison of the control run and satellite assimilation run to the IONS06 network of ozonesonde observations, which comprise the densest ozone sounding campaign ever conducted in North America, to AURA/TES ozone profile measurements, and to the EPA ground network of ozone and PM measurements will show significant improvement in the CMAQ calculations that use AURA initial and boundary conditions. Further analyses of lightning occurrences from ground and satellite observations and AURA/OMI NO2 column abundances will identify the lightning NOx signal evident in OMI measurements and suggest pathways for incorporating the lightning and NO2 data into the CMAQ simulations.

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes. Sensitivity study of the model indicated that southern and south-west part of the city have shown improvement and small patches of growth are also observed in the north western part of the city.The study highlights the growing importance of socio economic factors and geo-computational modeling approach on changing LULC of newly growing cities of modern India.

Improving Rice Modeling Success Rate with Ternary Non-structural Fertilizer Response Model.

PubMed

Li, Juan; Zhang, Mingqing; Chen, Fang; Yao, Baoquan

2018-06-13

Fertilizer response modelling is an important technical approach to realize metrological fertilization on rice. With the goal of solving the problems of a low success rate of a ternary quadratic polynomial model (TPFM) and to expand the model's applicability, this paper established a ternary non-structural fertilizer response model (TNFM) based on the experimental results from N, P and K fertilized rice fields. Our research results showed that the TNFM significantly improved the modelling success rate by addressing problems arising from setting the bias and multicollinearity in a TPFM. The results from 88 rice field trials in China indicated that the proportion of typical TNFMs that satisfy the general fertilizer response law of plant nutrition was 40.9%, while the analogous proportion of TPFMs was only 26.1%. The recommended fertilization showed a significant positive linear correlation between the two models, and the parameters N 0 , P 0 and K 0 that estimated the value of soil supplying nutrient equivalents can be used as better indicators of yield potential in plots where no N or P or K fertilizer was applied. The theoretical analysis showed that the new model has a higher fitting accuracy and a wider application range.

The effects of speech production and vocabulary training on different components of spoken language performance.

PubMed

Paatsch, Louise E; Blamey, Peter J; Sarant, Julia Z; Bow, Catherine P

2006-01-01

A group of 21 hard-of-hearing and deaf children attending primary school were trained by their teachers on the production of selected consonants and on the meanings of selected words. Speech production, vocabulary knowledge, reading aloud, and speech perception measures were obtained before and after each type of training. The speech production training produced a small but significant improvement in the percentage of consonants correctly produced in words. The vocabulary training improved knowledge of word meanings substantially. Performance on speech perception and reading aloud were significantly improved by both types of training. These results were in accord with the predictions of a mathematical model put forward to describe the relationships between speech perception, speech production, and language measures in children (Paatsch, Blamey, Sarant, Martin, & Bow, 2004). These training data demonstrate that the relationships between the measures are causal. In other words, improvements in speech production and vocabulary performance produced by training will carry over into predictable improvements in speech perception and reading scores. Furthermore, the model will help educators identify the most effective methods of improving receptive and expressive spoken language for individual children who are deaf or hard of hearing.

Scaling depth-induced wave-breaking in two-dimensional spectral wave models

NASA Astrophysics Data System (ADS)

Salmon, J. E.; Holthuijsen, L. H.; Zijlema, M.; van Vledder, G. Ph.; Pietrzak, J. D.

2015-03-01

Wave breaking in shallow water is still poorly understood and needs to be better parameterized in 2D spectral wave models. Significant wave heights over horizontal bathymetries are typically under-predicted in locally generated wave conditions and over-predicted in non-locally generated conditions. A joint scaling dependent on both local bottom slope and normalized wave number is presented and is shown to resolve these issues. Compared to the 12 wave breaking parameterizations considered in this study, this joint scaling demonstrates significant improvements, up to ∼50% error reduction, over 1D horizontal bathymetries for both locally and non-locally generated waves. In order to account for the inherent differences between uni-directional (1D) and directionally spread (2D) wave conditions, an extension of the wave breaking dissipation models is presented. By including the effects of wave directionality, rms-errors for the significant wave height are reduced for the best performing parameterizations in conditions with strong directional spreading. With this extension, our joint scaling improves modeling skill for significant wave heights over a verification data set of 11 different 1D laboratory bathymetries, 3 shallow lakes and 4 coastal sites. The corresponding averaged normalized rms-error for significant wave height in the 2D cases varied between 8% and 27%. In comparison, using the default setting with a constant scaling, as used in most presently operating 2D spectral wave models, gave equivalent errors between 15% and 38%.

Improving real-time inflow forecasting into hydropower reservoirs through a complementary modelling framework

NASA Astrophysics Data System (ADS)

Gragne, A. S.; Sharma, A.; Mehrotra, R.; Alfredsen, K.

2015-08-01

Accuracy of reservoir inflow forecasts is instrumental for maximizing the value of water resources and benefits gained through hydropower generation. Improving hourly reservoir inflow forecasts over a 24 h lead time is considered within the day-ahead (Elspot) market of the Nordic exchange market. A complementary modelling framework presents an approach for improving real-time forecasting without needing to modify the pre-existing forecasting model, but instead formulating an independent additive or complementary model that captures the structure the existing operational model may be missing. We present here the application of this principle for issuing improved hourly inflow forecasts into hydropower reservoirs over extended lead times, and the parameter estimation procedure reformulated to deal with bias, persistence and heteroscedasticity. The procedure presented comprises an error model added on top of an unalterable constant parameter conceptual model. This procedure is applied in the 207 km2 Krinsvatn catchment in central Norway. The structure of the error model is established based on attributes of the residual time series from the conceptual model. Besides improving forecast skills of operational models, the approach estimates the uncertainty in the complementary model structure and produces probabilistic inflow forecasts that entrain suitable information for reducing uncertainty in the decision-making processes in hydropower systems operation. Deterministic and probabilistic evaluations revealed an overall significant improvement in forecast accuracy for lead times up to 17 h. Evaluation of the percentage of observations bracketed in the forecasted 95 % confidence interval indicated that the degree of success in containing 95 % of the observations varies across seasons and hydrologic years.

NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems

NASA Technical Reports Server (NTRS)

Marks, Virginia B. (Compiler); Keckler, Claude R. (Compiler)

1994-01-01

Although significant advances have been made in modeling and controlling flexible systems, there remains a need for improvements in model accuracy and in control performance. The finite element models of flexible systems are unduly complex and are almost intractable to optimum parameter estimation for refinement using experimental data. Distributed parameter or continuum modeling offers some advantages and some challenges in both modeling and control. Continuum models often result in a significantly reduced number of model parameters, thereby enabling optimum parameter estimation. The dynamic equations of motion of continuum models provide the advantage of allowing the embedding of the control system dynamics, thus forming a complete set of system dynamics. There is also increased insight provided by the continuum model approach.

Advances in Projection Moire Interferometry Development for Large Wind Tunnel Applications

NASA Technical Reports Server (NTRS)

Fleming, Gary A.; Soto, Hector L.; South, Bruce W.; Bartram, Scott M.

1999-01-01

An instrument development program aimed at using Projection Moire Interferometry (PMI) for acquiring model deformation measurements in large wind tunnels was begun at NASA Langley Research Center in 1996. Various improvements to the initial prototype PMI systems have been made throughout this development effort. This paper documents several of the most significant improvements to the optical hardware and image processing software, and addresses system implementation issues for large wind tunnel applications. The improvements have increased both measurement accuracy and instrument efficiency, promoting the routine use of PMI for model deformation measurements in production wind tunnel tests.

Extended charge banking model of dual path shocks for implantable cardioverter defibrillators

PubMed Central

Dosdall, Derek J; Sweeney, James D

2008-01-01

Background Single path defibrillation shock methods have been improved through the use of the Charge Banking Model of defibrillation, which predicts the response of the heart to shocks as a simple resistor-capacitor (RC) circuit. While dual path defibrillation configurations have significantly reduced defibrillation thresholds, improvements to dual path defibrillation techniques have been limited to experimental observations without a practical model to aid in improving dual path defibrillation techniques. Methods The Charge Banking Model has been extended into a new Extended Charge Banking Model of defibrillation that represents small sections of the heart as separate RC circuits, uses a weighting factor based on published defibrillation shock field gradient measures, and implements a critical mass criteria to predict the relative efficacy of single and dual path defibrillation shocks. Results The new model reproduced the results from several published experimental protocols that demonstrated the relative efficacy of dual path defibrillation shocks. The model predicts that time between phases or pulses of dual path defibrillation shock configurations should be minimized to maximize shock efficacy. Discussion Through this approach the Extended Charge Banking Model predictions may be used to improve dual path and multi-pulse defibrillation techniques, which have been shown experimentally to lower defibrillation thresholds substantially. The new model may be a useful tool to help in further improving dual path and multiple pulse defibrillation techniques by predicting optimal pulse durations and shock timing parameters. PMID:18673561

An Evaluation of Understandability of Patient Journey Models in Mental Health.

PubMed

Percival, Jennifer; McGregor, Carolyn

2016-07-28

There is a significant trend toward implementing health information technology to reduce administrative costs and improve patient care. Unfortunately, little awareness exists of the challenges of integrating information systems with existing clinical practice. The systematic integration of clinical processes with information system and health information technology can benefit the patients, staff, and the delivery of care. This paper presents a comparison of the degree of understandability of patient journey models. In particular, the authors demonstrate the value of a relatively new patient journey modeling technique called the Patient Journey Modeling Architecture (PaJMa) when compared with traditional manufacturing based process modeling tools. The paper also presents results from a small pilot case study that compared the usability of 5 modeling approaches in a mental health care environment. Five business process modeling techniques were used to represent a selected patient journey. A mix of both qualitative and quantitative methods was used to evaluate these models. Techniques included a focus group and survey to measure usability of the various models. The preliminary evaluation of the usability of the 5 modeling techniques has shown increased staff understanding of the representation of their processes and activities when presented with the models. Improved individual role identification throughout the models was also observed. The extended version of the PaJMa methodology provided the most clarity of information flows for clinicians. The extended version of PaJMa provided a significant improvement in the ease of interpretation for clinicians and increased the engagement with the modeling process. The use of color and its effectiveness in distinguishing the representation of roles was a key feature of the framework not present in other modeling approaches. Future research should focus on extending the pilot case study to a more diversified group of clinicians and health care support workers.

Thermal modelling using discrete vasculature for thermal therapy: a review

PubMed Central

Kok, H.P.; Gellermann, J.; van den Berg, C.A.T.; Stauffer, P.R.; Hand, J.W.; Crezee, J.

2013-01-01

Reliable temperature information during clinical hyperthermia and thermal ablation is essential for adequate treatment control, but conventional temperature measurements do not provide 3D temperature information. Treatment planning is a very useful tool to improve treatment quality and substantial progress has been made over the last decade. Thermal modelling is a very important and challenging aspect of hyperthermia treatment planning. Various thermal models have been developed for this purpose, with varying complexity. Since blood perfusion is such an important factor in thermal redistribution of energy in in vivo tissue, thermal simulations are most accurately performed by modelling discrete vasculature. This review describes the progress in thermal modelling with discrete vasculature for the purpose of hyperthermia treatment planning and thermal ablation. There has been significant progress in thermal modelling with discrete vasculature. Recent developments have made real-time simulations possible, which can provide feedback during treatment for improved therapy. Future clinical application of thermal modelling with discrete vasculature in hyperthermia treatment planning is expected to further improve treatment quality. PMID:23738700

Improved Propulsion Modeling for Low-Thrust Trajectory Optimization

NASA Technical Reports Server (NTRS)

Knittel, Jeremy M.; Englander, Jacob A.; Ozimek, Martin T.; Atchison, Justin A.; Gould, Julian J.

2017-01-01

Low-thrust trajectory design is tightly coupled with spacecraft systems design. In particular, the propulsion and power characteristics of a low-thrust spacecraft are major drivers in the design of the optimal trajectory. Accurate modeling of the power and propulsion behavior is essential for meaningful low-thrust trajectory optimization. In this work, we discuss new techniques to improve the accuracy of propulsion modeling in low-thrust trajectory optimization while maintaining the smooth derivatives that are necessary for a gradient-based optimizer. The resulting model is significantly more realistic than the industry standard and performs well inside an optimizer. A variety of deep-space trajectory examples are presented.

IMPROVING CHEMICAL TRANSPORT MODEL PREDICTIONS OF ORGANIC AEROSOL: MEASUREMENT AND SIMULATION OF SEMIVOLATILE ORGANIC EMISSIONS FROM MOBILE AND NON-MOBILE SOURCES

EPA Science Inventory

Organic material contributes a significant fraction of PM_2.5 mass across all regions of the United States, but state-of-the-art chemical transport models often substantially underpredict measured organic aerosol concentrations. Recent revisions to these models that...

Do Three-dimensional Visualization and Three-dimensional Printing Improve Hepatic Segment Anatomy Teaching? A Randomized Controlled Study.

PubMed

Kong, Xiangxue; Nie, Lanying; Zhang, Huijian; Wang, Zhanglin; Ye, Qiang; Tang, Lei; Li, Jianyi; Huang, Wenhua

2016-01-01

Hepatic segment anatomy is difficult for medical students to learn. Three-dimensional visualization (3DV) is a useful tool in anatomy teaching, but current models do not capture haptic qualities. However, three-dimensional printing (3DP) can produce highly accurate complex physical models. Therefore, in this study we aimed to develop a novel 3DP hepatic segment model and compare the teaching effectiveness of a 3DV model, a 3DP model, and a traditional anatomical atlas. A healthy candidate (female, 50-years old) was recruited and scanned with computed tomography. After three-dimensional (3D) reconstruction, the computed 3D images of the hepatic structures were obtained. The parenchyma model was divided into 8 hepatic segments to produce the 3DV hepatic segment model. The computed 3DP model was designed by removing the surrounding parenchyma and leaving the segmental partitions. Then, 6 experts evaluated the 3DV and 3DP models using a 5-point Likert scale. A randomized controlled trial was conducted to evaluate the educational effectiveness of these models compared with that of the traditional anatomical atlas. The 3DP model successfully displayed the hepatic segment structures with partitions. All experts agreed or strongly agreed that the 3D models provided good realism for anatomical instruction, with no significant differences between the 3DV and 3DP models in each index (p > 0.05). Additionally, the teaching effects show that the 3DV and 3DP models were significantly better than traditional anatomical atlas in the first and second examinations (p < 0.05). Between the first and second examinations, only the traditional method group had significant declines (p < 0.05). A novel 3DP hepatic segment model was successfully developed. Both the 3DV and 3DP models could improve anatomy teaching significantly. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Electro-acupuncture stimulation acts on the basal ganglia output pathway to ameliorate motor impairment in Parkinsonian model rats.

PubMed

Jia, Jun; Li, Bo; Sun, Zuo-Li; Yu, Fen; Wang, Xuan; Wang, Xiao-Min

2010-04-01

The role of electro-acupuncture (EA) stimulation on motor symptoms in Parkinson's disease (PD) has not been well studied. In a rat hemiparkinsonian model induced by unilateral transection of the medial forebrain bundle (MFB), EA stimulation improved motor impairment in a frequency-dependent manner. Whereas EA stimulation at a low frequency (2 Hz) had no effect, EA stimulation at a high frequency (100 Hz) significantly improved motor coordination. However, neither low nor high EA stimulation could significantly enhance dopamine levels in the striatum. EA stimulation at 100 Hz normalized the MFB lesion-induced increase in midbrain GABA content, but it had no effect on GABA content in the globus pallidus. These results suggest that high-frequency EA stimulation improves motor impairment in MFB-lesioned rats by increasing GABAergic inhibition in the output structure of the basal ganglia.

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies.

PubMed

Davis, Michael J; Janke, Robert

2018-01-04

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies

NASA Astrophysics Data System (ADS)

Davis, Michael J.; Janke, Robert

2018-05-01

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

Factors influencing job satisfaction among registered nurses: a questionnaire survey in Mashhad, Iran.

PubMed

Atefi, Narges; Lim Abdullah, Khatijah; Wong, Li Ping; Mazlom, Reza

2015-05-01

Job satisfaction is a critical factor in health care. Strong empirical evidence supports a causal relationship between job satisfaction, patient safety and quality of care. To determine the level of nurses' job satisfaction and its associated factors. A stratified random sample of 421 registered nurses working at a large hospital in Mashhad, Iran was surveyed. The results showed that autonomy, task requirement and work interaction had scores higher than their respective median on the subscales. There were significant differences between demographic characteristics and the autonomy, task requirement, work interaction, salary, work condition, professional development, supportive nursing management, decision making, professional status subscales and mean total job satisfaction. In univariate analysis, young age, being female and being married were significantly associated with a higher level of job satisfaction. The adjusted R(2) for this model was 0.14, indicating that the model explained 14% of the variability. The regression model was highly significant, F (4298) = 13.194, P < 0.001. The authors emphasise that the human resources policies and incentives need to be re-visited. Efforts undertaken to improve working conditions, supportive nursing management, improved professional status, professional development and increased salaries are some of the ways for nurse managers to improve job satisfaction. © 2013 John Wiley & Sons Ltd.

Analysis of variance to assess statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Joe, Cody; Lee, Colin; Besio, Walter G

2017-07-01

Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.

Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes

PubMed Central

Parker, Joel S.; Mullins, Michael; Cheang, Maggie C.U.; Leung, Samuel; Voduc, David; Vickery, Tammi; Davies, Sherri; Fauron, Christiane; He, Xiaping; Hu, Zhiyuan; Quackenbush, John F.; Stijleman, Inge J.; Palazzo, Juan; Marron, J.S.; Nobel, Andrew B.; Mardis, Elaine; Nielsen, Torsten O.; Ellis, Matthew J.; Perou, Charles M.; Bernard, Philip S.

2009-01-01

Purpose To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression–based “intrinsic” subtypes luminal A, luminal B, HER2-enriched, and basal-like. Methods A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen. Results The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for the combined model (subtype and tumor size) was a significant improvement on either the clinicopathologic model or subtype model alone. The intrinsic subtype model predicted neoadjuvant chemotherapy efficacy with a negative predictive value for pCR of 97%. Conclusion Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer. The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers. The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy. PMID:19204204

Effects of gemfibrozil on outcome after permanent middle cerebral artery occlusion in mice

PubMed Central

Guo, Qingmin; Wang, Guangming; Liu, Xiaowei; Namura, Shobu

2009-01-01

Fibrates are lipid lowering drugs and found as ligands for peroxisome proliferator-activated receptors (PPARs). A clinical study has shown that one type of fibrate gemfibrozil reduces stroke incidence in men. However, it remains unknown whether gemfibrozil improves outcome after stroke. We hypothesized that prophylactic administration of gemfibrozil improves outcome after ischemic stroke. In this study, we measured the impact of gemfibrozil in two permanent middle cerebral artery occlusion (MCAO) models in young adult male mice on normal diet. First, we tested gemfibrozil in a filamentous MCAO model. Pretreatment with gemfibrozil (30 mg/kg) for 7 days moderately but significantly reduced infarct size at 24 h after MCAO. A higher dose (120 mg/kg) did not attenuate infarct size. Rather, it tended to increase brain swelling. Second, we tested in a distal MCAO model. Gemfibrozil (30 mg/kg) for 7 days before and after stroke significantly attenuated cortical lesion size at 7 days after MCAO. Cortical blood flow measured by laser speckle imaging was improved by gemfibrozil in the ischemic hemisphere. In non-stroke animals gemfibrozil also altered gene expression levels of PPARs in both the aorta and brain in organ specific manners; however, endothelial nitric oxide synthase (eNOS) was not significantly affected. These findings suggested the possibility that the observed infarct reductions and cortical blood flow improvements in ischemic brains were not through eNOS-mediated mechanisms. Further investigations may be meritorious to examine whether prophylactic usage of gemfibrozil against stroke is beneficial. PMID:19427843

Effects of gemfibrozil on outcome after permanent middle cerebral artery occlusion in mice.

PubMed

Guo, Qingmin; Wang, Guangming; Liu, Xiaowei; Namura, Shobu

2009-07-07

Fibrates are lipid lowering drugs and found as ligands for peroxisome proliferator-activated receptors (PPARs). A clinical study has shown that one type of fibrate gemfibrozil reduces stroke incidence in men. However, it remains unknown whether gemfibrozil improves outcome after stroke. We hypothesized that prophylactic administration of gemfibrozil improves outcome after ischemic stroke. In this study, we measured the impact of gemfibrozil in two permanent middle cerebral artery occlusion (MCAO) models in young adult male mice on normal diet. First, we tested gemfibrozil in a filamentous MCAO model. Pretreatment with gemfibrozil (30 mg/kg) for 7 days moderately but significantly reduced infarct size at 24 h after MCAO. A higher dose (120 mg/kg) did not attenuate infarct size. Rather, it tended to increase brain swelling. Second, we tested in a distal MCAO model. Gemfibrozil (30 mg/kg) for 7 days before and after stroke significantly attenuated cortical lesion size at 7 days after MCAO. Cortical blood flow measured by laser speckle imaging was improved by gemfibrozil in the ischemic hemisphere. In non-stroke animals gemfibrozil also altered gene expression levels of PPARs in both the aorta and brain in organ specific manners; however, endothelial nitric oxide synthase (eNOS) was not significantly affected. These findings suggested the possibility that the observed infarct reductions and cortical blood flow improvements in ischemic brains were not through eNOS-mediated mechanisms. Further investigations may be meritorious to examine whether prophylactic usage of gemfibrozil against stroke is beneficial.

A 4.5 km resolution Arctic Ocean simulation with the global multi-resolution model FESOM 1.4

NASA Astrophysics Data System (ADS)

Wang, Qiang; Wekerle, Claudia; Danilov, Sergey; Wang, Xuezhu; Jung, Thomas

2018-04-01

In the framework of developing a global modeling system which can facilitate modeling studies on Arctic Ocean and high- to midlatitude linkage, we evaluate the Arctic Ocean simulated by the multi-resolution Finite Element Sea ice-Ocean Model (FESOM). To explore the value of using high horizontal resolution for Arctic Ocean modeling, we use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 km vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer, in terms of both Atlantic Water (AW) mean state and variability. The deepening and thickening bias of the AW layer, a common issue found in coarse-resolution simulations, is significantly alleviated by using higher resolution. The topographic steering of the AW is stronger and the seasonal and interannual temperature variability along the ocean bottom topography is enhanced in the high-resolution simulation. The high resolution also improves the ocean surface circulation, mainly through a better representation of the narrow straits in the Canadian Arctic Archipelago (CAA). The representation of CAA throughflow not only influences the release of water masses through the other gateways but also the circulation pathways inside the Arctic Ocean. However, the mean state and variability of Arctic freshwater content and the variability of freshwater transport through the Arctic gateways appear not to be very sensitive to the increase in resolution employed here. By highlighting the issues that are independent of model resolution, we address that other efforts including the improvement of parameterizations are still required.

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

Haywood, Jim M.; Jones, Andy; Dunstone, Nick

Despite the fact that the southern hemisphere contains a far greater proportion of dark ocean than the northern hemisphere, the total amount of sunlight reflected from the hemispheres is equal. However, the majority of climate models do not adequately represent this equivalence. Here we examine the impact of equilibrating hemispheric albedos by various idealised methods in a comprehensive coupled climate model and find significant improvements in what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases almost vanish over all continental land areas, the penetration of monsoon rainfall across the Sahel and the west African monsoon “jump”more » become well represented, and indicators of hurricane frequency are significantly improved. The results appear not to be model specific, implying that hemispheric albedo equivalence may provide a fundamental constraint for climate models that must be satisfied if the dynamics driving these processes, in particular the strength of the Hadley cell, are to be adequately represented. Cross-equatorial energy transport is implicated as a crucial component that must be accurately modelled in coupled general circulation models. The results also suggest that the commonly used practice of prescribing sea-surface temperatures in models provides a less accurate represention of precipitation than constraining the hemispheric albedos.« less

Modeling of near-wall turbulence

NASA Technical Reports Server (NTRS)

Shih, T. H.; Mansour, N. N.

1990-01-01

An improved k-epsilon model and a second order closure model is presented for low Reynolds number turbulence near a wall. For the k-epsilon model, a modified form of the eddy viscosity having correct asymptotic near wall behavior is suggested, and a model for the pressure diffusion term in the turbulent kinetic energy equation is proposed. For the second order closure model, the existing models are modified for the Reynolds stress equations to have proper near wall behavior. A dissipation rate equation for the turbulent kinetic energy is also reformulated. The proposed models satisfy realizability and will not produce unphysical behavior. Fully developed channel flows are used for model testing. The calculations are compared with direct numerical simulations. It is shown that the present models, both the k-epsilon model and the second order closure model, perform well in predicting the behavior of the near wall turbulence. Significant improvements over previous models are obtained.

AIR QUALITY MODELING AT NEIGHBORHOOD SCALES TO IMPROVE HUMAN EXPOSURE ASSESSMENT

EPA Science Inventory

Air quality modeling is an integral component of risk assessment and of subsequent development of effective and efficient management of air quality. Urban areas introduce of fresh sources of pollutants into regional background producing significant spatial variability of the co...

Paeoniflorin improves cardiac function and decreases adverse postinfarction left ventricular remodeling in a rat model of acute myocardial infarction.

PubMed

Chen, Hengwen; Dong, Yan; He, Xuanhui; Li, Jun; Wang, Jie

2018-01-01

Paeoniflorin (PF) is the active component of Paeonia lactiflora Pall. or Paeonia veitchii Lynch. This study was, therefore, aimed to evaluate the improvement and mechanism of the PF on ventricular remodeling in rats with acute myocardial infarction (AMI). In this study, AMI model was established by ligating the anterior descending coronary artery in Wistar rats. After 4 weeks gavage of PF, the apparent signs and the left ventricle weight index of Wistar rats were observed. The left ventricular ejection fraction (LVEF) was evaluated by Doppler ultrasonography. Changes in cardiac morphology were observed by pathologic examination, and apoptosis was observed by the terminal deoxynucleotidyl transferase dUTP nick end labeling assay. In addition, enzyme-linked immunosorbent assay was used to detect the expression of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) interleukin-10 (IL-10) and brain natriuretic peptide (BNP). Immunohistochemistry and Western blot method were applied to detect Caspase-3 and Caspase-9. Compared with the model control, the survival conditions of rats in all treatment groups were generally improved after PF treatment. LVEF was significantly increased, and both left ventricular end-diastolic inner diameter and left ventricular end-systolic inner diameter were significantly reduced. Moreover, pathologic examination showed that the myocardium degeneration of the rats treated with PF was decreased, including neater arrangement, more complete myofilament, more uniform gap and less interstitial collagen fibers. Furthermore, the mitochondrial structure of cardiomyocytes was significantly improved. The ultrastructure was clear, and the arrangement of myofilament was more regular. Also, the expression of Caspase-3 and Caspase-9 was inhibited, and apoptosis was obviously reduced in the PF treatment groups. BNP, TNF-α and IL-6 were also decreased and IL-10 was increased in the treated rats. PF could significantly improve the LVEF of rats. It decreased adverse left ventricular remodeling after myocardial infarction in rat models. The potential mechanism could be that PF decreased and inhibited BNP, TNF-α and IL-6, increased IL-10 and further inhibited the expression of Caspase-3 and Caspase-9, thus promoting ventricular remodeling.

Effect of Qingnao tablet on blood viscosity of rat model of blood stasis induced by epinephrine

NASA Astrophysics Data System (ADS)

Xie, Guoqi; Hao, Shaojun; Ma, Zhenzhen; Liu, Xiaobin; Li, Jun; Li, Wenjun; Zhang, Zhengchen

2018-04-01

To establish a rat model of blood stasis with adrenaline (Adr) subcutaneous injection and ice bath stimulation. The effects of different doses on the blood viscosity of blood stasis model rats were observed. The rats were randomly divided into 6 groups: blank control group (no model), model group, positive control group, high, middle and low dose group. The whole blood viscosity and plasma viscosity were detected by blood viscosity instrument. Compared with the blank group, model group, high shear, low shear whole blood viscosity and plasma viscosity were significantly increased, TT PT significantly shortened, APTT was significantly prolonged, FIB increased significantly, indicating that the model was successful. Compared with the model group, can significantly reduce the Naoluotong group (cut, low cut). Qingnaopian high dose group (low cut), middle dose group (cut, low shear blood viscosity) (P<0.01), Can significantly reduce Naoluotong qingnaopian group, high dose group (P<0.01), plasma viscosity decreased qingnaopian plasma viscosity in low dose group (P<0.05). Conclusion: qingnaopian could improve the blood rheology of blood stasis mice abnormal index, decrease the blood viscosity, blood stasis has certain hemostatic effect.

Tezosentan, a Novel Endothelin Receptor Antagonist, Markedly Reduces Rat Hepatic Ischemia and Reperfusion Injury in Three Different Models

PubMed Central

Farmer, Douglas G.; Kaldas, Fady; Anselmo, Dean; Katori, Masamichi; Shen, Xiu-Da; Lassman, Charles; Kaldas, Marian; Clozel, Martine; Busuttil, Ronald W.; Kupiec-Weglinski, Jerzy

2010-01-01

This study investigated the effects of dual endothelin (ET) receptor blockade in rat models of liver ischemia and reperfusion injury (IRI). Three models of IRI were used: (1) in vivo total hepatic warm ischemia with portal shunting for 60 minutes with control (saline) and treatment groups (15 mg/kg tezosentan intravenously prior to reperfusion), (2) ex vivo hepatic perfusion after 24 hours of cold storage in University of Wisconsin solution with control and treatment groups (10 mg/kg tezosentan in the perfusate), and (3) syngeneic liver transplantation (LT) after 24 hours of cold storage in University of Wisconsin solution with control and treatment groups (10 mg/kg tezosentan intravenously prior to reperfusion). Tezosentan treatment significantly improved serum transaminase and histology after IRI in all 3 models. This correlated with reduced vascular resistance, improved bile production, and an improved oxygen extraction ratio. Treatment led to a reduction in neutrophil infiltration and interleukin-1 beta and macrophage inflammatory protein 2 production. A reduction in endothelial cell injury as measured by purine nucleoside phosphorylase was seen. Survival after LT was significantly increased with tezosentan treatment (90% versus 50%). In conclusion, this is the first investigation to examine dual receptor ET blockade in 3 models of hepatic IRI and the first to use the parenterally administered agent tezosentan. The results demonstrate that in both warm and cold IRI tezosentan administration improves sinusoidal hemodynamics and is associated with improved tissue oxygenation and reduced endothelial cell damage. In addition, reduced tissue inflammation, injury, and leukocyte chemotactic signaling were seen. These results provide compelling data for the further investigation of the use of tezosentan in hepatic IRI. PMID:19025917

Electroencephalography Based Fusion Two-Dimensional (2D)-Convolution Neural Networks (CNN) Model for Emotion Recognition System.

PubMed

Kwon, Yea-Hoon; Shin, Sae-Byuk; Kim, Shin-Dug

2018-04-30

The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN) model and to suggest an overall method to classify emotion based on multimodal data. We improved classification performance by combining electroencephalogram (EEG) and galvanic skin response (GSR) signals. GSR signals are preprocessed using by the zero-crossing rate. Sufficient EEG feature extraction can be obtained through CNN. Therefore, we propose a suitable CNN model for feature extraction by tuning hyper parameters in convolution filters. The EEG signal is preprocessed prior to convolution by a wavelet transform while considering time and frequency simultaneously. We use a database for emotion analysis using the physiological signals open dataset to verify the proposed process, achieving 73.4% accuracy, showing significant performance improvement over the current best practice models.

Can theoretical intervention improve hand hygiene behavior among nurses?

PubMed Central

Baghaei, Rahim; Sharifian, Elham; Kamran, Aziz

2016-01-01

Background Hand washing is the best strategy to prevent known nosocomial infections but the nurses’ hand hygiene is estimated to be poor in Iran. Objective This study aimed to determine the effectiveness of BASNEF (Behavior, Attitude, Subjective Norms, and Enabling Factors) model on hand hygiene adherence education. Methods This controlled quasi-experimental study was conducted on 70 hemodialysis unit nurses (35 case and 35 control) in the health and educational centers of the University of Medical Sciences of Urmia, Iran. To collect the data, a six-part validated and reliable questionnaire was used. The data were analyzed using SPSS version18, using Wilcoxon, Mann–Whitney, chi-square, and Fisher’s exact tests. The significance level was considered P<0.05. Results The mean age was 38.4±8.1 years for the intervention group and 40.2±8.0 years for the control group. There was no significant difference between the two groups for any demographic variables. Also, before the intervention, there was no significant difference between the two groups for any components of the BASNEF model. Post-intervention, the attitude, subjective norms, enabling factors, and intention improved significantly in the intervention group (P<0.001), but hand hygiene behavior did not show any significant change in the intervention group (P=0.16). Conclusion Despite the improving attitudes and intention, the intervention had no significant effect on hand hygiene behavior among the studied nurses. PMID:27366106

Can theoretical intervention improve hand hygiene behavior among nurses?

PubMed

Baghaei, Rahim; Sharifian, Elham; Kamran, Aziz

2016-01-01

Hand washing is the best strategy to prevent known nosocomial infections but the nurses' hand hygiene is estimated to be poor in Iran. This study aimed to determine the effectiveness of BASNEF (Behavior, Attitude, Subjective Norms, and Enabling Factors) model on hand hygiene adherence education. This controlled quasi-experimental study was conducted on 70 hemodialysis unit nurses (35 case and 35 control) in the health and educational centers of the University of Medical Sciences of Urmia, Iran. To collect the data, a six-part validated and reliable questionnaire was used. The data were analyzed using SPSS version18, using Wilcoxon, Mann-Whitney, chi-square, and Fisher's exact tests. The significance level was considered P<0.05. The mean age was 38.4±8.1 years for the intervention group and 40.2±8.0 years for the control group. There was no significant difference between the two groups for any demographic variables. Also, before the intervention, there was no significant difference between the two groups for any components of the BASNEF model. Post-intervention, the attitude, subjective norms, enabling factors, and intention improved significantly in the intervention group (P<0.001), but hand hygiene behavior did not show any significant change in the intervention group (P=0.16). Despite the improving attitudes and intention, the intervention had no significant effect on hand hygiene behavior among the studied nurses.

Optimum outlier model for potential improvement of environmental cleaning and disinfection.

PubMed

Rupp, Mark E; Huerta, Tomas; Cavalieri, R J; Lyden, Elizabeth; Van Schooneveld, Trevor; Carling, Philip; Smith, Philip W

2014-06-01

The effectiveness and efficiency of 17 housekeepers in terminal cleaning 292 hospital rooms was evaluated through adenosine triphosphate detection. A subgroup of housekeepers was identified who were significantly more effective and efficient than their coworkers. These optimum outliers may be used in performance improvement to optimize environmental cleaning.

P-wave characteristics on routine preoperative electrocardiogram improve prediction of new-onset postoperative atrial fibrillation in cardiac surgery.

PubMed

Wong, Jim K; Lobato, Robert L; Pinesett, Andre; Maxwell, Bryan G; Mora-Mangano, Christina T; Perez, Marco V

2014-12-01

To test the hypothesis that including preoperative electrocardiogram (ECG) characteristics with clinical variables significantly improves the new-onset postoperative atrial fibrillation prediction model. Retrospective analysis. Single-center university hospital. Five hundred twenty-six patients, ≥ 18 years of age, who underwent coronary artery bypass grafting, aortic valve replacement, mitral valve replacement/repair, or a combination of valve surgery and coronary artery bypass grafting requiring cardiopulmonary bypass. Retrospective review of medical records. Baseline characteristics and cardiopulmonary bypass times were collected. Digitally-measured timing and voltages from preoperative electrocardiograms were extracted. Postoperative atrial fibrillation was defined as atrial fibrillation requiring therapeutic intervention. Two hundred eight (39.5%) patients developed postoperative atrial fibrillation. Clinical predictors were age, ejection fraction<55%, history of atrial fibrillation, history of cerebral vascular event, and valvular surgery. Three ECG parameters associated with postoperative atrial fibrillation were observed: Premature atrial contraction, p-wave index, and p-frontal axis. Adding electrocardiogram variables to the prediction model with only clinical predictors significantly improved the area under the receiver operating characteristic curve, from 0.71 to 0.78 (p<0.01). Overall net reclassification improvement was 0.059 (p = 0.09). Among those who developed postoperative atrial fibrillation, the net reclassification improvement was 0.063 (p = 0.03). Several p-wave characteristics are independently associated with postoperative atrial fibrillation. Addition of these parameters improves the postoperative atrial fibrillation prediction model. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

NASA Astrophysics Data System (ADS)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

Valproic acid treatment attenuates caspase-3 activation and improves survival after lethal burn injury in a rodent model.

PubMed

Luo, Hong-Min; Hu, Sen; Bai, Hui-Ying; Wang, Hai-Bin; Du, Ming-Hua; Lin, Zhi-Long; Ma, Li; Wang, Huan; Lv, Yi; Sheng, Zhi-Yong

2014-01-01

Burn injury may result in multiple organ dysfunction partially because of apoptotic cell death. The authors have previously shown that valproic acid (VPA) improves survival in a dog burn model. The aim of this study is to examine whether a VPA improves survival in a rodent burn model and whether this was because of inhibition of cell apoptosis. Rats were subjected to third-degree 55% TBSA burns and randomized to treatment with a VPA (300 mg/kg) or normal saline. One group of animals was monitored for 12 hours for survival analysis; another group was killed at 6 hours after injury, and brains, hearts, and blood samples were harvested for examination. Plasma creatine kinase (CK)-MB activities and neuron-specific enolase (NSE) levels were measured to evaluate the cardiac and brain damages. The effects of a VPA on acetylation of histone H3 and caspase-3 activation were also evaluated. Major burn injury resulted in a significant decrease in the acetylation of histone H3, and there was an increase in plasma CK-MB activities, NSE concentrations, and tissue levels of activated caspase-3. A VPA treatment significantly increased the acetylation of histone H3 and survival of the animals after major burn injury. In addition, a VPA treatment significantly attenuated the plasma CK-MB activities, an NSE concentrations, and inhibited caspase-3 activation after major burn injury. These results indicate that a VPA can attenuate cardiac and brain injury, and can improve survival in a rodent model of lethal burn injury. These protective effects may be mediated in part through the inhibition of caspase-3 activation.

Parametrized modified gravity and the CMB bispectrum

NASA Astrophysics Data System (ADS)

Di Valentino, Eleonora; Melchiorri, Alessandro; Salvatelli, Valentina; Silvestri, Alessandra

2012-09-01

We forecast the constraints on modified theories of gravity from the cosmic microwave background (CMB) anisotropies bispectrum that arises from correlations between lensing and the Integrated Sachs-Wolfe effect. In models of modified gravity the evolution of the metric potentials is generally altered and the contribution to the CMB bispectrum signal can differ significantly from the one expected in the standard cosmological model. We adopt a parametrized approach and focus on three different classes of models: Linder’s growth index, Chameleon-type models, and f(R) theories. We show that the constraints on the parameters of the models will significantly improve with future CMB bispectrum measurements.

Schwann Cells Transplantation Improves Locomotor Recovery in Rat Models with Spinal Cord Injury: a Systematic Review and Meta-Analysis.

PubMed

Yang, Lei; Ge, Yingbin; Tang, Jian; Yuan, Jinxia; Ge, Dawei; Chen, Hongtao; Zhang, Hongxiu; Cao, Xiaojian

2015-01-01

Schwann cells (SCs) which were demonstrated to be responsible for axonal myelination and ensheathing are widely studied and commonly used for cell transplantation to treat spinal cord injury (SCI). We performed this meta-analysis to summarize the effects of SCs versus controls for locomotor recovery in rat models of traumatic SCI. Studies of the BBB scores after transplantation of SCs were searched out from Pubmed, Cochrane Library Medline databases and analyzed by Review Manager 5.2.5. Thirteen randomized controlled animal trials were selected with 283 rats enrolled. The studies were divided to different subgroups by different models of SCI, different cell doses for transplantation, different sources of SCs and different transplantation ways. The pooled results of this meta-analysis suggested that SCs transplantation cannot significantly improve the locomotor recovery at a short time after intervention (1 week after transplantation) in both impacted and hemi-sected SCI models. However, at a longer time after intervention (3, 5-7 and over 8 weeks after transplantation), significant improvement of BBB score emerged in SCs groups compared with control groups. Subgroup analyses revealed that SCs transplantation can significantly promote locomotor recovery regardless of in high or low doses of cells, from different sources (isolated from sciatic nerves or differentiated from bone marrow stromal cells(BMSCs)) and with or without scaffolding. SCs seem to demonstrate substantial beneficial effects on locomotor recovery in a widely-used animal models of SCI. © 2015 The Author(s) Published by S. Karger AG, Basel.

An online psychological intervention can improve the sexual satisfaction of men following treatment for localized prostate cancer: outcomes of a Randomised Controlled Trial evaluating My Road Ahead.

PubMed

Wootten, Addie C; Meyer, Denny; Abbott, Jo-Anne M; Chisholm, Katherine; Austin, David W; Klein, Britt; McCabe, Marita; Murphy, Declan G; Costello, Anthony J

2017-07-01

Prostate cancer treatment often results in significant psycho-sexual challenges for men following treatment; however, many men report difficulty in accessing appropriate care. A randomized controlled trial was undertaken to assess the efficacy of a 10-week self-guided online psychological intervention called My Road Ahead (MRA) for men with localized prostate cancer in improving sexual satisfaction. Participants were randomized to 1 of 3 conditions MRA alone or MRA plus online forum, or forum access alone. Pre, post, and follow-up assessments of overall sexual satisfaction were conducted. Mixed models and structural equation modeling were used to analyze the data. One hundred forty-two men (mean age 61 y; SD = 7) participated. The majority of participants had undergone radical prostatectomy (88%) and all men had received treatment for localized prostate cancer. Significant differences were obtained for the 3 groups (P = .026) and a significant improvement in total sexual satisfaction was observed only for participants who were allocated to MRA + forum with a large effect size (P = .004, partial η 2  = 0.256). Structural equation modeling indicated that increases in sexual function, masculine self-esteem, and sexual confidence contributed significantly to overall sexual satisfaction for the MRA + forum plus forum condition. This study is the first, to our knowledge, that has evaluated a self-guided online psychological intervention tailored to the specific needs of men with prostate cancer. The findings indicate the potential for MRA to deliver support that men may not otherwise receive and also highlight the importance of psychological intervention to facilitate improved sexual outcomes. Copyright © 2016 John Wiley & Sons, Ltd.

Establishment and outcomes of a model primary care pharmacy service system.

PubMed

Carmichael, Jannet M; Alvarez, Autumn; Chaput, Ryan; DiMaggio, Jennifer; Magallon, Heather; Mambourg, Scott

2004-03-01

The establishment and outcomes of a model primary care pharmacy service system are described. A primary care pharmacy practice model was established at a government health care facility in March 1996. The original objective was to establish a primary pharmacy practice model that would demonstrate improved patient outcomes and maximize the pharmacist's contributions to drug therapy. Since its inception, many improvements have been realized and supported by advanced computer and automated systems, expanded disease state management practices, and unique practitioner and administrative support. Many outcomes studies have been performed on the pharmacist-initiated and -managed clinics, leading to improved patient care and conveying the quality-conscious and cost-effective role pharmacists can play as independent practitioners in this environment. These activities demonstrate cutting-edge leadership in health-system pharmacy. Redesign has been used to improve consistent access to a medication expert and has significantly improved the quality of patient care while easing physicians' workload without increasing health care costs. A system using pharmacists as independent practitioners to promote primary care has achieved high-quality and cost-effective patient care.

The effectiveness of collaborative problem based physics learning (CPBPL) model to improve student’s self-confidence on physics learning

NASA Astrophysics Data System (ADS)

Prahani, B. K.; Suprapto, N.; Suliyanah; Lestari, N. A.; Jauhariyah, M. N. R.; Admoko, S.; Wahyuni, S.

2018-03-01

In the previous research, Collaborative Problem Based Physic Learning (CPBPL) model has been developed to improve student’s science process skills, collaborative problem solving, and self-confidence on physics learning. This research is aimed to analyze the effectiveness of CPBPL model towards the improvement of student’s self-confidence on physics learning. This research implemented quasi experimental design on 140 senior high school students who were divided into 4 groups. Data collection was conducted through questionnaire, observation, and interview. Self-confidence measurement was conducted through Self-Confidence Evaluation Sheet (SCES). The data was analyzed using Wilcoxon test, n-gain, and Kruskal Wallis test. Result shows that: (1) There is a significant score improvement on student’s self-confidence on physics learning (α=5%), (2) n-gain value student’s self-confidence on physics learning is high, and (3) n-gain average student’s self-confidence on physics learning was consistent throughout all groups. It can be concluded that CPBPL model is effective to improve student’s self-confidence on physics learning.

A Novel Feed-Forward Modeling System Leads to Sustained Improvements in Attention and Academic Performance.

PubMed

McDermott, Ashley F; Rose, Maya; Norris, Troy; Gordon, Eric

2016-01-28

This study tested a novel feed-forward modeling (FFM) system as a nonpharmacological intervention for the treatment of ADHD children and the training of cognitive skills that improve academic performance. This study implemented a randomized, controlled, parallel design comparing this FFM with a nonpharmacological community care intervention. Improvements were measured on parent- and clinician-rated scales of ADHD symptomatology and on academic performance tests completed by the participant. Participants were followed for 3 months after training. Participants in the FFM training group showed significant improvements in ADHD symptomatology and academic performance, while the control group did not. Improvements from FFM were sustained 3 months later. The FFM appeared to be an effective intervention for the treatment of ADHD and improving academic performance. This FFM training intervention shows promise as a first-line treatment for ADHD while improving academic performance. © The Author(s) 2016.

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

PubMed

Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L

2018-02-01

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Improving risk classification of critical illness with biomarkers: a simulation study

PubMed Central

Seymour, Christopher W.; Cooke, Colin R.; Wang, Zheyu; Kerr, Kathleen F.; Yealy, Donald M.; Angus, Derek C.; Rea, Thomas D.; Kahn, Jeremy M.; Pepe, Margaret S.

2012-01-01

Purpose Optimal triage of patients at risk of critical illness requires accurate risk prediction, yet little data exists on the performance criteria required of a potential biomarker to be clinically useful. Materials and Methods We studied an adult cohort of non-arrest, non-trauma emergency medical services encounters transported to a hospital from 2002–2006. We simulated hypothetical biomarkers increasingly associated with critical illness during hospitalization, and determined the biomarker strength and sample size necessary to improve risk classification beyond a best clinical model. Results Of 57,647 encounters, 3,121 (5.4%) were hospitalized with critical illness and 54,526 (94.6%) without critical illness. The addition of a moderate strength biomarker (odds ratio=3.0 for critical illness) to a clinical model improved discrimination (c-statistic 0.85 vs. 0.8, p<0.01), reclassification (net reclassification improvement=0.15, 95%CI: 0.13,0.18), and increased the proportion of cases in the highest risk categoryby+8.6% (95%CI: 7.5,10.8%). Introducing correlation between the biomarker and physiological variables in the clinical risk score did not modify the results. Statistically significant changes in net reclassification required a sample size of at least 1000 subjects. Conclusions Clinical models for triage of critical illness could be significantly improved by incorporating biomarkers, yet, substantial sample sizes and biomarker strength may be required. PMID:23566734

The effect of various parameters of large scale radio propagation models on improving performance mobile communications

NASA Astrophysics Data System (ADS)

Pinem, M.; Fauzi, R.

2018-02-01

One technique for ensuring continuity of wireless communication services and keeping a smooth transition on mobile communication networks is the soft handover technique. In the Soft Handover (SHO) technique the inclusion and reduction of Base Station from the set of active sets is determined by initiation triggers. One of the initiation triggers is based on the strong reception signal. In this paper we observed the influence of parameters of large-scale radio propagation models to improve the performance of mobile communications. The observation parameters for characterizing the performance of the specified mobile system are Drop Call, Radio Link Degradation Rate and Average Size of Active Set (AS). The simulated results show that the increase in altitude of Base Station (BS) Antenna and Mobile Station (MS) Antenna contributes to the improvement of signal power reception level so as to improve Radio Link quality and increase the average size of Active Set and reduce the average Drop Call rate. It was also found that Hata’s propagation model contributed significantly to improvements in system performance parameters compared to Okumura’s propagation model and Lee’s propagation model.

Improving Crop Productions Using the Irrigation & Crop Production Model Under Drought

NASA Astrophysics Data System (ADS)

Shin, Y.; Lee, T.; Lee, S. H.; Kim, J.; Jang, W.; Park, S.

2017-12-01

We aimed to improve crop productions by providing optimal irrigation water amounts (IWAs) for various soils and crops using the Irrigation & Crop Production (ICP) model under various hydro-climatic regions. We selected the Little Washita (LW 13/21) and Bangdong-ri sites in Oklahoma (United States of America) and Chuncheon (Republic of Korea) for the synthetic studies. Our results showed that the ICP model performed well for improving crop productions by providing optimal IWAs during the study period (2000 to 2016). Crop productions were significantly affected by the solar radiation and precipitation, but the maximum and minimum temperature showed less impact on crop productions. When we considerd that the weather variables cannot be adjusted by artifical activities, irrigation might be the only solution for improving crop productions under drought. Also, the presence of shallow ground water (SGW) table depths higlhy influences on crop production. Although certainties exist in the synthetic studies, our results showed the robustness of the ICP model for improving crop productions under the drought condition. Thus, the ICP model can contribute to efficient water management plans under drought in regions at where water availability is limited.

A supply chain model to improve the beef quality distribution using investment analysis: A case study

NASA Astrophysics Data System (ADS)

Lupita, Alessandra; Rangkuti, Sabrina Heriza; Sutopo, Wahyudi; Hisjam, Muh.

2017-11-01

There are significant differences related to the quality and price of the beef commodity in traditional market and modern market in Indonesia. Those are caused by very different treatments of the commodity. The different treatments are in the slaughter lines, the transportation from the abattoir to the outlet, the display system, and the control system. If the problem is not solved by the Government, the gap will result a great loss of the consumer regarding to the quality and sustainability of traditional traders business because of the declining interest in purchasing beef in the traditional markets. This article aims to improve the quality of beef in traditional markets. This study proposed A Supply Chain Model that involves the schemes of investment and government incentive for improving the distribution system. The supply chain model is can be formulated using the Mix Integer Linear Programming (MILP) and solved using the IBM®ILOG®CPLEX software. The results show that the proposed model can be used to determine the priority of programs for improving the quality and sustainability business of traditional beef merchants. By using the models, The Government can make a decision to consider incentives for improving the condition.

An improved gravity model for Mars: Goddard Mars Model 1

NASA Technical Reports Server (NTRS)

Smith, D. E.; Lerch, F. J.; Nerem, R. S.; Zuber, M. T.; Patel, G. B.; Fricke, S. K.; Lemoine, F. G.

1993-01-01

Doppler tracking data of three orbiting spacecraft have been reanalyzed to develop a new gravitational field model for the planet Mars, Goddard Mars Model 1 (GMM-1). This model employs nearly all available data, consisting of approximately 1100 days of S band tracking data collected by NASA's Deep Space Network from the Mariner 9 and Viking 1 and Viking 2 spacecraft, in seven different orbits, between 1971 and 1979. GMM-1 is complete to spherical harmonic degree and order 50, which corresponds to a half-wavelength spatial resolution of 200-300 km where the data permit. GMM-1 represents satellite orbits with considerably better accuracy than previous Mars gravity models and shows greater resolution of identifiable geological structures. The notable improvement in GMM-1 over previous models is a consequence of several factors: improved computational capabilities, the use of otpimum weighting and least squares collocation solution techniques which stabilized the behavior of the solution at high degree and order, and the use of longer satellite arcs than employed in previous solutions that were made possible by improved force and measurement models. The inclusion of X band tracking data from the 379-km altitude, nnear-polar orbiting Mars Observer spacecraft should provide a significant improvement over GMM-1, particularly at high latitudes where current data poorly resolve the gravitational signature of the planet.

An improved gravity model for Mars: Goddard Mars Model-1 (GMM-1)

NASA Technical Reports Server (NTRS)

Smith, D. E.; Lerch, F. J.; Nerem, R. S.; Zuber, M. T.; Patel, G. B.; Fricke, S. K.; Lemoine, F. G.

1993-01-01

Doppler tracking data of three orbiting spacecraft have been reanalyzed to develop a new gravitational field model for the planet Mars, GMM-1 (Goddard Mars Model-1). This model employs nearly all available data, consisting of approximately 1100 days of S-bank tracking data collected by NASA's Deep Space Network from the Mariner 9, and Viking 1 and Viking 2 spacecraft, in seven different orbits, between 1971 and 1979. GMM-1 is complete to spherical harmonic degree and order 50, which corresponds to a half-wavelength spatial resolution of 200-300 km where the data permit. GMM-1 represents satellite orbits with considerably better accuracy than previous Mars gravity models and shows greater resolution of identifiable geological structures. The notable improvement in GMM-1 over previous models is a consequence of several factors: improved computational capabilities, the use of optimum weighting and least-squares collocation solution techniques which stabilized the behavior of the solution at high degree and order, and the use of longer satellite arcs than employed in previous solutions that were made possible by improved force and measurement models. The inclusion of X-band tracking data from the 379-km altitude, near-polar orbiting Mars Observer spacecraft should provide a significant improvement over GMM-1, particularly at high latitudes where current data poorly resolves the gravitational signature of the planet.

Fusion of mobile in situ and satellite remote sensing observations of chemical release emissions to improve disaster response

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

Leifer, Ira; Melton, Christopher; Frash, Jason

Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and space-based remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response. Understanding urban atmospheric transport in the Los Angeles Basin, where topographic influences on transport patterns are significant, was improved by leveraging the Aliso Canyon leak as an atmospheric tracer. Plume characterization data was collected by the AutoMObile trace Gas (AMOG) Surveyor, a commuter carmore » modified for science. Mobile surface in situ CH 4 and winds were measured by AMOG Surveyor under Santa Ana conditions to estimate an emission rate of 365±30% Gg yr -1. Vertical profiles were collected by AMOG Surveyor by leveraging local topography for vertical profiling to identify the planetary boundary layer at ~700 m. Topography significantly constrained plume dispersion by up to a factor of two. The observed plume trajectory was used to validate satellite aerosol optical depth-inferred atmospheric transport, which suggested the plume first was driven offshore, but then veered back towards land. Numerical long-range transport model predictions confirm this interpretation. Lastly, this study demonstrated a novel application of satellite aerosol remote sensing for disaster response.« less

Multipayer patient-centered medical home implementation guided by the chronic care model.

PubMed

Gabbay, Robert A; Bailit, Michael H; Mauger, David T; Wagner, Edward H; Siminerio, Linda

2011-06-01

A unique statewide multipayer ini Pennsylvania was undertaken to implement the Patient-Centered Medical Home (PCMH) guided by the Chronic Care Model (CCM) with diabetes as an initial target disease. This project represents the first broad-scale CCM implementation with payment reform across a diverse range of practice organizations and one of the largest PCMH multipayer initiatives. Practices implemented the CCM and PCMH through regional Breakthrough Series learning collaboratives, supported by Improving Performance in Practice (IPIP) practice coaches, with required monthly quality reporting enhanced by multipayer infrastructure payments. Some 105 practices, representing 382 primary care providers, were engaged in the four regional collaboratives. The practices from the Southeast region of Pennsylvania focused on diabetes patients (n = 10,016). During the first intervention year (May 2008-May 2009), all practices achieved at least Level 1 National Committee for Quality Assurance (NCQA) Physician Practice Connections Patient-Centered Medical Home (PPC-PCMH) recognition. There was significant improvement in the percentage of patients who had evidence-based complications screening and who were on therapies to reduce morbidity and mortality (statins, angiotensin-converting enzyme inhibitors). In addition, there were small but statistically significant improvements in key clinical parameters for blood pressure and cholesterol levels, with the greatest absolute improvement in the highest-risk patients. Transforming primary care delivery through implementation of the PCMH and CCM supported by multipayer infrastructure payments holds significant promise to improve diabetes care.

Fusion of mobile in situ and satellite remote sensing observations of chemical release emissions to improve disaster response

DOE PAGES

Leifer, Ira; Melton, Christopher; Frash, Jason; ...

2016-09-22

Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and space-based remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response. Understanding urban atmospheric transport in the Los Angeles Basin, where topographic influences on transport patterns are significant, was improved by leveraging the Aliso Canyon leak as an atmospheric tracer. Plume characterization data was collected by the AutoMObile trace Gas (AMOG) Surveyor, a commuter carmore » modified for science. Mobile surface in situ CH 4 and winds were measured by AMOG Surveyor under Santa Ana conditions to estimate an emission rate of 365±30% Gg yr -1. Vertical profiles were collected by AMOG Surveyor by leveraging local topography for vertical profiling to identify the planetary boundary layer at ~700 m. Topography significantly constrained plume dispersion by up to a factor of two. The observed plume trajectory was used to validate satellite aerosol optical depth-inferred atmospheric transport, which suggested the plume first was driven offshore, but then veered back towards land. Numerical long-range transport model predictions confirm this interpretation. Lastly, this study demonstrated a novel application of satellite aerosol remote sensing for disaster response.« less

Effect of desvenlafaxine 50 mg and 100 mg on energy and lassitude in patients with major depressive disorder: A pooled analysis.

PubMed

Lam, Raymond W; Wajsbrot, Dalia B; Meier, Ellen; Pappadopulos, Elizabeth; Mackell, Joan A; Boucher, Matthieu

2017-09-01

Nine randomized, double-blind, placebo-controlled studies of major depressive disorder were pooled to evaluate the effects of desvenlafaxine 50- and 100-mg/d on energy and lassitude in adults with major depressive disorder ( n=4279). Changes from baseline to endpoint in 17-item Hamilton Rating Scale for Depression (HAM-D 17 ) Work and Activities, Retardation, and Somatic Symptoms General items, HAM-D 17 psychomotor retardation factor, and Montgomery-Åsberg Depression Rating Scale Lassitude item were analyzed with a mixed model for repeated measures analysis of variance. Associations between residual energy measures and functional impairment, based on the Sheehan Disability Scale, were modeled using stepwise multiple linear regression. Improvement from baseline was significantly greater for both desvenlafaxine doses versus placebo on all energy symptom outcomes at week 8 (all p⩽0.005). Both early improvement in HAM-D 17 psychomotor retardation at week 2 and residual energy symptoms at week 8 were associated with Sheehan Disability Scale total score at week 8 (all p⩽0.001). Among Sheehan Disability Scale remitters and responders, the HAM-D 17 psychomotor retardation score at week 8 was significantly lower with desvenlafaxine (both doses) than placebo. Desvenlafaxine 50 and 100 mg/d significantly improved energy and lassitude symptoms in patients with major depressive disorder. Both early improvement in energy and fewer residual energy symptoms were associated with functional improvement.

Impact of sequential proton density fat fraction for quantification of hepatic steatosis in nonalcoholic fatty liver disease.

PubMed

Idilman, Ilkay S; Keskin, Onur; Elhan, Atilla Halil; Idilman, Ramazan; Karcaaltincaba, Musturay

2014-05-01

To determine the utility of sequential MRI-estimated proton density fat fraction (MRI-PDFF) for quantification of the longitudinal changes in liver fat content in individuals with nonalcoholic fatty liver disease (NAFLD). A total of 18 consecutive individuals (M/F: 10/8, mean age: 47.7±9.8 years) diagnosed with NAFLD, who underwent sequential PDFF calculations for the quantification of hepatic steatosis at two different time points, were included in the study. All patients underwent T1-independent volumetric multi-echo gradient-echo imaging with T2* correction and spectral fat modeling. A close correlation for quantification of hepatic steatosis between the initial MRI-PDFF and liver biopsy was observed (rs=0.758, p<0.001). The median interval between two sequential MRI-PDFF measurements was 184 days. From baseline to the end of the follow-up period, serum GGT level and homeostasis model assessment score were significantly improved (p=0.015, p=0.006, respectively), whereas BMI, serum AST, and ALT levels were slightly decreased. MRI-PDFFs were significantly improved (p=0.004). A good correlation between two sequential MRI-PDFF calculations was observed (rs=0.714, p=0.001). With linear regression analyses, only delta serum ALT levels had a significant effect on delta MRI-PDFF calculations (r2=38.6%, p=0.006). At least 5.9% improvement in MRI-PDFF is needed to achieve a normalized abnormal ALT level. The improvement of MRI-PDFF score was associated with the improvement of biochemical parameters in patients who had improvement in delta MRI-PDFF (p<0.05). MRI-PDFF can be used for the quantification of the longitudinal changes of hepatic steatosis. The changes in serum ALT levels significantly reflected changes in MRI-PDFF in patients with NAFLD.

Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains

PubMed Central

Harrison, Kenneth W.; Tian, Yudong; Peters-Lidard, Christa D.; Ringerud, Sarah; Kumar, Sujay V.

2018-01-01

Better estimation of land surface microwave emissivity promises to improve over-land precipitation retrievals in the GPM era. Forward models of land microwave emissivity are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square-difference (RMSD) of about 0.013, or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the microwave emissivity model alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared to joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy. PMID:29795962

Improved Short-Term Clock Prediction Method for Real-Time Positioning.

PubMed

Lv, Yifei; Dai, Zhiqiang; Zhao, Qile; Yang, Sheng; Zhou, Jinning; Liu, Jingnan

2017-06-06

The application of real-time precise point positioning (PPP) requires real-time precise orbit and clock products that should be predicted within a short time to compensate for the communication delay or data gap. Unlike orbit correction, clock correction is difficult to model and predict. The widely used linear model hardly fits long periodic trends with a small data set and exhibits significant accuracy degradation in real-time prediction when a large data set is used. This study proposes a new prediction model for maintaining short-term satellite clocks to meet the high-precision requirements of real-time clocks and provide clock extrapolation without interrupting the real-time data stream. Fast Fourier transform (FFT) is used to analyze the linear prediction residuals of real-time clocks. The periodic terms obtained through FFT are adopted in the sliding window prediction to achieve a significant improvement in short-term prediction accuracy. This study also analyzes and compares the accuracy of short-term forecasts (less than 3 h) by using different length observations. Experimental results obtained from International GNSS Service (IGS) final products and our own real-time clocks show that the 3-h prediction accuracy is better than 0.85 ns. The new model can replace IGS ultra-rapid products in the application of real-time PPP. It is also found that there is a positive correlation between the prediction accuracy and the short-term stability of on-board clocks. Compared with the accuracy of the traditional linear model, the accuracy of the static PPP using the new model of the 2-h prediction clock in N, E, and U directions is improved by about 50%. Furthermore, the static PPP accuracy of 2-h clock products is better than 0.1 m. When an interruption occurs in the real-time model, the accuracy of the kinematic PPP solution using 1-h clock prediction product is better than 0.2 m, without significant accuracy degradation. This model is of practical significance because it solves the problems of interruption and delay in data broadcast in real-time clock estimation and can meet the requirements of real-time PPP.

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

USGS Publications Warehouse

Zimmermann, N.E.; Edwards, T.C.; Moisen, Gretchen G.; Frescino, T.S.; Blackard, J.A.

2007-01-01

1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. 5. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. ?? 2007 The Authors.

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

PubMed Central

ZIMMERMANN, N E; EDWARDS, T C; MOISEN, G G; FRESCINO, T S; BLACKARD, J A

2007-01-01

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. PMID:18642470

Massive metrology using fast e-beam technology improves OPC model accuracy by >2x at faster turnaround time

NASA Astrophysics Data System (ADS)

Zhao, Qian; Wang, Lei; Wang, Jazer; Wang, ChangAn; Shi, Hong-Fei; Guerrero, James; Feng, Mu; Zhang, Qiang; Liang, Jiao; Guo, Yunbo; Zhang, Chen; Wallow, Tom; Rio, David; Wang, Lester; Wang, Alvin; Wang, Jen-Shiang; Gronlund, Keith; Lang, Jun; Koh, Kar Kit; Zhang, Dong Qing; Zhang, Hongxin; Krishnamurthy, Subramanian; Fei, Ray; Lin, Chiawen; Fang, Wei; Wang, Fei

2018-03-01

Classical SEM metrology, CD-SEM, uses low data rate and extensive frame-averaging technique to achieve high-quality SEM imaging for high-precision metrology. The drawbacks include prolonged data collection time and larger photoresist shrinkage due to excess electron dosage. This paper will introduce a novel e-beam metrology system based on a high data rate, large probe current, and ultra-low noise electron optics design. At the same level of metrology precision, this high speed e-beam metrology system could significantly shorten data collection time and reduce electron dosage. In this work, the data collection speed is higher than 7,000 images per hr. Moreover, a novel large field of view (LFOV) capability at high resolution was enabled by an advanced electron deflection system design. The area coverage by LFOV is >100x larger than classical SEM. Superior metrology precision throughout the whole image has been achieved, and high quality metrology data could be extracted from full field. This new capability on metrology will further improve metrology data collection speed to support the need for large volume of metrology data from OPC model calibration of next generation technology. The shrinking EPE (Edge Placement Error) budget places more stringent requirement on OPC model accuracy, which is increasingly limited by metrology errors. In the current practice of metrology data collection and data processing to model calibration flow, CD-SEM throughput becomes a bottleneck that limits the amount of metrology measurements available for OPC model calibration, impacting pattern coverage and model accuracy especially for 2D pattern prediction. To address the trade-off in metrology sampling and model accuracy constrained by the cycle time requirement, this paper employs the high speed e-beam metrology system and a new computational software solution to take full advantage of the large volume data and significantly reduce both systematic and random metrology errors. The new computational software enables users to generate large quantity of highly accurate EP (Edge Placement) gauges and significantly improve design pattern coverage with up to 5X gain in model prediction accuracy on complex 2D patterns. Overall, this work showed >2x improvement in OPC model accuracy at a faster model turn-around time.

Clinical implementation of a knowledge based planning tool for prostate VMAT.

PubMed

Powis, Richard; Bird, Andrew; Brennan, Matthew; Hinks, Susan; Newman, Hannah; Reed, Katie; Sage, John; Webster, Gareth

2017-05-08

A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency. A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as "optimal" and "sub-optimal" by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly. Plans identified as "sub-optimal" in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as "optimal" observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed. The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data.

Selection of proper candidates with resected pathological stage IIIA-N2 non-small cell lung cancer for postoperative radiotherapy

PubMed Central

Hui, Zhouguang; Dai, Honghai; Liang, Jun; Lv, Jima; Zhou, Zongmei; Feng, Qinfu; Xiao, Zefen; Chen, Dongfu; Zhang, Hongxing; Yin, Weibo; Wang, Luhua

2015-01-01

Background To establish a prediction model in selecting fit patients with resected pIIIA-N2 non-small cell lung cancer (NSCLC) for postoperative radiotherapy (PORT), and evaluate the model in clinical practice. Methods Between January 2003 and December 2005, 221 patients with resected pIIIA-N2 NSCLC were retrospectively analyzed. The effect of PORT on overall survival (OS) of patients with different clinicopathological factors was evaluated and the results were used to establish a prediction model to select patients fit for PORT. Results Compared with the control, PORT significantly improved the OS of patients with a smoking index ≤400 (P = 0.033), cN2 (P = 0.003), pT3 (P = 0.014), squamous cell carcinoma (SCC) (P = 0.013), or ≥4 positive nodes (P = 0.025). Patients were divided from zero to all five factors into low, middle, and high PORT index (PORT-I) groups (scored 0–1, 2, and 3–5, respectively). PORT did not improve OS (3-year, P = 0.531), disease free survival (DFS) (P = 0.358), or loco-regional recurrence free survival (LRFS) (P = 0.412) in the low PORT-I group. PORT significantly improved OS (P = 0.033), and tended to improve DFS (P = 0.064), but not LRFS (P = 0.287) in the middle PORT-I group. PORT could significantly improve OS (P = 0.000), DFS (P = 0.000), and LRFS (P = 0.006) in the high PORT-I group. Conclusion The prediction model is valuable in selecting patients with resected pIIIA-N2 NSCLC fit for PORT. PORT is strongly recommended for patients with three or more of the five factors of smoking index ≤400, cN2, pT3, SCC, and ≥4 positive nodes. PMID:26273382

Friendship Network and Dental Brushing Behavior among Middle School Students: An Agent Based Modeling Approach.

PubMed

Sadeghipour, Maryam; Khoshnevisan, Mohammad Hossein; Jafari, Afshin; Shariatpanahi, Seyed Peyman

2017-01-01

By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals' dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network's nodes' in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students' brushing frequency was demonstrated by simulation results.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, J.; Madsen, H.; Jensen, K. H.; Refsgaard, J. C.

2015-08-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both stream flow and groundwater modeling. The Colored Noise Kalman filter (ColKF) and the Separate bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman Filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved stream flow modeling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modeling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behavior and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, Jørn; Madsen, Henrik; Høgh Jensen, Karsten; Refsgaard, Jens Christian

2016-05-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment-scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both streamflow and groundwater modelling. The coloured noise Kalman filter (ColKF) and the separate-bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved streamflow modelling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modelling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behaviour and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Model-based sensor-less wavefront aberration correction in optical coherence tomography.

PubMed

Verstraete, Hans R G W; Wahls, Sander; Kalkman, Jeroen; Verhaegen, Michel

2015-12-15

Several sensor-less wavefront aberration correction methods that correct nonlinear wavefront aberrations by maximizing the optical coherence tomography (OCT) signal are tested on an OCT setup. A conventional coordinate search method is compared to two model-based optimization methods. The first model-based method takes advantage of the well-known optimization algorithm (NEWUOA) and utilizes a quadratic model. The second model-based method (DONE) is new and utilizes a random multidimensional Fourier-basis expansion. The model-based algorithms achieve lower wavefront errors with up to ten times fewer measurements. Furthermore, the newly proposed DONE method outperforms the NEWUOA method significantly. The DONE algorithm is tested on OCT images and shows a significantly improved image quality.

Modeling the effect of shroud contact and friction dampers on the mistuned response of turbopumps

NASA Technical Reports Server (NTRS)

Griffin, Jerry H.; Yang, M.-T.

1994-01-01

The contract has been revised. Under the revised scope of work a reduced order model has been developed that can be used to predict the steady-state response of mistuned bladed disks. The approach has been implemented in a computer code, LMCC. It is concluded that: the reduced order model displays structural fidelity comparable to that of a finite element model of an entire bladed disk system with significantly improved computational efficiency; and, when the disk is stiff, both the finite element model and LMCC predict significantly more amplitude variation than was predicted by earlier models. This second result may have important practical ramifications, especially in the case of integrally bladed disks.

Confronting the surface temperature cold bias in AGCMs over the Tibetan Plateau and improving climate simulations

NASA Astrophysics Data System (ADS)

Wu, G. X.; Liu, Y.; Bao, Q.; Chen, X.; Li, J.

2017-12-01

One of the mid-term progresses of the NSFC- Key Research Program "Land-air Coupling over the Tibetan Plateau and Its Climate Impact " is presented. The elevated heating in summer and cooling in winter of the Tibetan Plateau significantly regulate the seasonal change of the atmospheric circulation and exert remarkable impacts on world climate. Recent studies have demonstrated that the majority of the Phase-5 Coupled Model Inter-comparison Project (CMIP5) models underestimate annual and seasonal mean surface air temperatures (Ta) over the Tibetan Plateau (TP). In addition, more than half of the models underestimate annual and seasonal mean surface temperatures (Ts) over the TP. These cold biases are larger over the western TP. By decomposing the Ts bias using the surface energy budget equation, it was demonstrated that this TP's cold bias can be attributed to various factors, in which the stronger bias in surface albedo (a-) and the weaker bias in clear-sky downward Longwave radiation (DLR) play the most significant roles. Since a- and DLR are respectively affected by snow coverage fraction at the ground surface and water vapor content in the atmosphere, these results then imply that the cold bias over the TP is caused by too large snow coverage fraction and too less water vapor content over the TP in the models. The FAMIL AGCM model developed at LASG also suffers from the similar cold bias over the TP. By introducing the 3D- Radiative Transfer Parameterization Over Mountains/Snow (Liou, 2013) into the model, the total solar radiation reaching the ground surface is increased during the daytime, resulting in more snowmelt and less snow coverage. Accordingly, surface albedo is decreased on the sunny side of the mountains, and the surface cold bias over mountain areas is decreased. It is shown that the improvement is sensitive to the model resolution: increased the horizontal resolution of Community Land Model version 4.0 (CLM 4.0) from nearly 200km (1.9o×2.5o) to about 25km (0.23o×0.31o) can significantly improve the parameterization effect and accuracy, with more notably improvement appearing in Spring. It is demonstrated that, by stimulating a Rossby wave and strengthen the precipitation in subtropical frontal zone of East Asia, the decrement of clod bias over the TP can greatly improve the climate simulations of the model.

Two-dimensional Mathematical Model of Oil-bearing Materials in Extrusion-type Transportation over Rectangular Screw Core

NASA Astrophysics Data System (ADS)

Gukasyan, A. V.; Koshevoy, E. P.; Kosachev, V. S.

2018-05-01

A comparative analysis of alternative models for plastic flow in extrusive transportation of oil-bearing materials was conducted; the research was directed at determining the function describing the screw core throughput capacity of the press (extruder). Transition from a one-dimensional model to a two-dimensional model significantly improves the mathematical model and allows using two-dimensional rheological models determining the throughput of the screw core.

An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

NASA Astrophysics Data System (ADS)

Chang, You-Soon; Zhang, Shaoqing; Rosati, Anthony; Vecchi, Gabriel A.; Yang, Xiaosong

2018-03-01

An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, "observations" drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the "identical" twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.

Strategies to implement maternal vaccination: A comparison between standing orders for midwife delivery, a hospital based maternal immunisation service and primary care.

PubMed

Krishnaswamy, Sushena; Wallace, Euan M; Buttery, Jim; Giles, Michelle L

2018-03-20

Maternal vaccination is a safe and effective strategy to reduce maternal and neonatal morbidity and mortality from pertussis and influenza. However, despite recommendations for maternal vaccination since 2010, uptake remains suboptimal. Barriers to uptake have been studied widely and include lack of integration of vaccination into routine pregnancy care and access to vaccination services. Standing orders for administration of vaccines without the need for a physician review or prescription have been demonstrated to improve uptake as part of multi-model interventions to increase antenatal influenza and post-partum pertussis vaccination. Monash Health is a university-affiliated, public healthcare network in Melbourne, Australia providing maternity services across three hospitals. In this study we compared three different immunisation models - an immunisation nurse-led immunisation service, standing orders for midwife-administered pertussis vaccination within pregnancy care clinics, and delivery by general practitioners in primary care. Uptake of maternal pertussis vaccine was measured as recorded in the state-wide perinatal data collection tool. Uptake improved significantly at all three hospitals over the study period with the most significant change (39% to 91%, p < .001) noted at the hospital where standing orders were introduced. Our study highlights the diversity of immunisation service models available in maternity care settings. We demonstrated significant improvement in uptake of maternal pertussis vaccination with introduction of midwife-administered vaccination but each maternity service should consider the model best suited to their needs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Retrieval of LAI and leaf chlorophyll content from remote sensing data by agronomy mechanism knowledge to solve the ill-posed inverse problem

NASA Astrophysics Data System (ADS)

Li, Zhenhai; Nie, Chenwei; Yang, Guijun; Xu, Xingang; Jin, Xiuliang; Gu, Xiaohe

2014-10-01

Leaf area index (LAI) and LCC, as the two most important crop growth variables, are major considerations in management decisions, agricultural planning and policy making. Estimation of canopy biophysical variables from remote sensing data was investigated using a radiative transfer model. However, the ill-posed problem is unavoidable for the unique solution of the inverse problem and the uncertainty of measurements and model assumptions. This study focused on the use of agronomy mechanism knowledge to restrict and remove the ill-posed inversion results. For this purpose, the inversion results obtained using the PROSAIL model alone (NAMK) and linked with agronomic mechanism knowledge (AMK) were compared. The results showed that AMK did not significantly improve the accuracy of LAI inversion. LAI was estimated with high accuracy, and there was no significant improvement after considering AMK. The validation results of the determination coefficient (R2) and the corresponding root mean square error (RMSE) between measured LAI and estimated LAI were 0.635 and 1.022 for NAMK, and 0.637 and 0.999 for AMK, respectively. LCC estimation was significantly improved with agronomy mechanism knowledge; the R2 and RMSE values were 0.377 and 14.495 μg cm-2 for NAMK, and 0.503 and 10.661 μg cm-2 for AMK, respectively. Results of the comparison demonstrated the need for agronomy mechanism knowledge in radiative transfer model inversion.

Engagement with the auditory processing system during targeted auditory cognitive training mediates changes in cognitive outcomes in individuals with schizophrenia.

PubMed

Biagianti, Bruno; Fisher, Melissa; Neilands, Torsten B; Loewy, Rachel; Vinogradov, Sophia

2016-11-01

Individuals with schizophrenia who engage in targeted cognitive training (TCT) of the auditory system show generalized cognitive improvements. The high degree of variability in cognitive gains maybe due to individual differences in the level of engagement of the underlying neural system target. 131 individuals with schizophrenia underwent 40 hours of TCT. We identified target engagement of auditory system processing efficiency by modeling subject-specific trajectories of auditory processing speed (APS) over time. Lowess analysis, mixed models repeated measures analysis, and latent growth curve modeling were used to examine whether APS trajectories were moderated by age and illness duration, and mediated improvements in cognitive outcome measures. We observed significant improvements in APS from baseline to 20 hours of training (initial change), followed by a flat APS trajectory (plateau) at subsequent time-points. Participants showed interindividual variability in the steepness of the initial APS change and in the APS plateau achieved and sustained between 20 and 40 hours. We found that participants who achieved the fastest APS plateau, showed the greatest transfer effects to untrained cognitive domains. There is a significant association between an individual's ability to generate and sustain auditory processing efficiency and their degree of cognitive improvement after TCT, independent of baseline neurocognition. APS plateau may therefore represent a behavioral measure of target engagement mediating treatment response. Future studies should examine the optimal plateau of auditory processing efficiency required to induce significant cognitive improvements, in the context of interindividual differences in neural plasticity and sensory system efficiency that characterize schizophrenia. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Model Studies on the Effectiveness of MBBR Reactors for the Restoration of Small Water Reservoirs

NASA Astrophysics Data System (ADS)

Nowak, Agata; Mazur, Robert; Panek, Ewa; Chmist, Joanna

2018-02-01

The authors present the Moving Bed Biofilm Reactor (MBBR) model with a quasi-continuous flow for small water reservoir restoration, characterized by high concentrations of organic pollutants. To determine the efficiency of wastewater treatment the laboratory analysis of physic-chemical parameters were conducted for the model on a semi-technical scale of 1:3. Wastewater treatment process was carried out in 24 h for 1 m3 for raw sewage. The startup period was 2 weeks for all biofilters (biological beds). Approximately 50% reduction in COD and BOD5 was obtained on average for the studied bioreactors. Significant improvements were achieved in theclarity of the treated wastewater, with the reduction of suspension by 60%. The oxygen profile has improved significantly in 7 to 9 hours of the process, and a diametric reduction in the oxidative reduction potential was recorded. A preliminary model of biological treatment effectiveness was determined based on the conducted studies. In final stages, the operation mode was set in real conditions of polluted water reservoirs.

On use of the multistage dose-response model for assessing laboratory animal carcinogenicity

PubMed Central

Nitcheva, Daniella; Piegorsch, Walter W.; West, R. Webster

2007-01-01

We explore how well a statistical multistage model describes dose-response patterns in laboratory animal carcinogenicity experiments from a large database of quantal response data. The data are collected from the U.S. EPA’s publicly available IRIS data warehouse and examined statistically to determine how often higher-order values in the multistage predictor yield significant improvements in explanatory power over lower-order values. Our results suggest that the addition of a second-order parameter to the model only improves the fit about 20% of the time, while adding even higher-order terms apparently does not contribute to the fit at all, at least with the study designs we captured in the IRIS database. Also included is an examination of statistical tests for assessing significance of higher-order terms in a multistage dose-response model. It is noted that bootstrap testing methodology appears to offer greater stability for performing the hypothesis tests than a more-common, but possibly unstable, “Wald” test. PMID:17490794

Condylar position analysis with a new electronic condylar position measuring instrument E-CPM: influence of different examiners and a working bite on reproducibility.

PubMed

Vahle-Hinz, K; Rybczynski, A; Jakstat, H; Ahlers, M O

2009-01-01

Condylar position analysis facilitates a quantitative comparison of the condylar position with and without a bite record, different records and changed influencing factors. Handling by the examiner when positioning the model is a significant factor with regard to the accuracy of the examination. Measurement accuracy could be improved when positioning the models by using special working bites, hence the objective of the experiments described in this study consisted in examining the extent to which the measuring results are influenced by different examiners and by using working bites. In the first trial, one examiner performed ten measurements without and with an interposed working bite for five model pairs in each case. In the second trial, nine examiners (three specialized dentists, three dental assistants, three students) performed ten measurements in each case without and with an interposed working bite. The three-dimensional position was read digitally with the E-CPM (Gamma Dental, Klosterneuburg/Vienna, Austria), recorded by means of spreadsheet software (Microsoft Excel) and diagnostic software (CMDfact, CMD3D module, dentaConcept, Hamburg), and evaluated with graphing software (Sigma Plot, Systat Software, USA). In the first trial, it was shown that the reproducibility of mounting was improved markedly (p <0.01) by using bite records in the form of working bites. In the second trial, it was shown that the mean error increased significantly (p <0.01) when several examiners performed the measurements compared with the results of one examiner alone. No significantly different results occurred (p < 0.01) in the comparison of the different groups of examiners with different educational and training backgrounds. This applied for the mounting methods without and with working bite. On the other hand, the reproducibility of mounting improved distinctly (p<0.01) in every group of examiners when working bites were used. Reproducibility of condylar position analysis was improved significantly by mounting the models with special working bites. This applied for operators of different professional background (dentists, dental assistants and dental students), while there were no significant differences between results of the three groups.

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Xu, Xiaofeng; Yuan, Fengming; Hanson, Paul J.; Wullschleger, Stan D.; Thornton, Peter E.; Riley, William J.; Song, Xia; Graham, David E.; Song, Changchun; Tian, Hanqin

2016-06-01

Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data-model and model-model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land-atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate-carbon cycle feedbacks.

Westerly wind bursts simulated in CAM4 and CCSM4

NASA Astrophysics Data System (ADS)

Lian, Tao; Tang, Youmin; Zhou, Lei; Islam, Siraj Ul; Zhang, Chan; Li, Xiaojing; Ling, Zheng

2018-02-01

The equatorial westerly wind bursts (WWBs) play an important role in modulating and predicting the El Niño-Southern Oscillation (ENSO). In this study, the ability of the Community Atmospheric Model version 4 (CAM4) and the Community Climate System Model version 4 (CCSM4) in simulating WWBs is systematically evaluated. Many characteristics of WWBs, including their longitude distributions, durations, zonal extensions, variabilities at seasonal, intraseasonal, and interannual timescales, as well as their relations with the Madden-Julian Oscillation (MJO) and ENSO, are discussed. Generally speaking, these characteristics of WWBs can be successfully reproduced by CAM4, owning to the improvement of the deep convection in the model. In CCSM4, significant bias such as the lack of the equatorial Pacific WWBs in boreal spring season and the weak modulation by a strong MJO are found. Our findings confirm the fact that the WWBs are greatly modulated by the surface temperature. It's also suggested that improving the air-sea coupling in CCSM4 may improve model performance in simulating WWBs, and may further improve the predictability of ENSO in the coupled model.

An Empirical Correction Method for Improving off-Axes Response Prediction in Component Type Flight Mechanics Helicopter Models

NASA Technical Reports Server (NTRS)

Mansur, M. Hossein; Tischler, Mark B.

1997-01-01

Historically, component-type flight mechanics simulation models of helicopters have been unable to satisfactorily predict the roll response to pitch stick input and the pitch response to roll stick input off-axes responses. In the study presented here, simple first-order low-pass filtering of the elemental lift and drag forces was considered as a means of improving the correlation. The method was applied to a blade-element model of the AH-64 APache, and responses of the modified model were compared with flight data in hover and forward flight. Results indicate that significant improvement in the off-axes responses can be achieved in hover. In forward flight, however, the best correlation in the longitudinal and lateral off-axes responses required different values of the filter time constant for each axis. A compromise value was selected and was shown to result in good overall improvement in the off-axes responses. The paper describes both the method and the model used for its implementation, and presents results obtained at hover and in forward flight.

Lifted worm algorithm for the Ising model

NASA Astrophysics Data System (ADS)

Elçi, Eren Metin; Grimm, Jens; Ding, Lijie; Nasrawi, Abrahim; Garoni, Timothy M.; Deng, Youjin

2018-04-01

We design an irreversible worm algorithm for the zero-field ferromagnetic Ising model by using the lifting technique. We study the dynamic critical behavior of an energylike observable on both the complete graph and toroidal grids, and compare our findings with reversible algorithms such as the Prokof'ev-Svistunov worm algorithm. Our results show that the lifted worm algorithm improves the dynamic exponent of the energylike observable on the complete graph and leads to a significant constant improvement on toroidal grids.

Testing the standard model by precision measurement of the weak charges of quarks.

PubMed

Young, R D; Carlini, R D; Thomas, A W; Roche, J

2007-09-21

In a global analysis of the latest parity-violating electron scattering measurements on nuclear targets, we demonstrate a significant improvement in the experimental knowledge of the weak neutral-current lepton-quark interactions at low energy. The precision of this new result, combined with earlier atomic parity-violation measurements, places tight constraints on the size of possible contributions from physics beyond the standard model. Consequently, this result improves the lower-bound on the scale of relevant new physics to approximately 1 TeV.

Modeling the probability of arsenic in groundwater in New England as a tool for exposure assessment

USGS Publications Warehouse

Ayotte, J.D.; Nolan, B.T.; Nuckols, J.R.; Cantor, K.P.; Robinson, G.R.; Baris, D.; Hayes, L.; Karagas, M.; Bress, W.; Silverman, D.T.; Lubin, J.H.

2006-01-01

We developed a process-based model to predict the probability of arsenic exceeding 5 ??g/L in drinking water wells in New England bedrock aquifers. The model is being used for exposure assessment in an epidemiologic study of bladder cancer. One important study hypothesis that may explain increased bladder cancer risk is elevated concentrations of inorganic arsenic in drinking water. In eastern New England, 20-30% of private wells exceed the arsenic drinking water standard of 10 micrograms per liter. Our predictive model significantly improves the understanding of factors associated with arsenic contamination in New England. Specific rock types, high arsenic concentrations in stream sediments, geochemical factors related to areas of Pleistocene marine inundation and proximity to intrusive granitic plutons, and hydrologic and landscape variables relating to groundwater residence time increase the probability of arsenic occurrence in groundwater. Previous studies suggest that arsenic in bedrock groundwater may be partly from past arsenical pesticide use. Variables representing historic agricultural inputs do not improve the model, indicating that this source does not significantly contribute to current arsenic concentrations. Due to the complexity of the fractured bedrock aquifers in the region, well depth and related variables also are not significant predictors. ?? 2006 American Chemical Society.

The Effect of a Multi-Strategy Program on Developing Social Behaviors Based on Pender’s Health Promotion Model to Prevent Loneliness of Old Women Referred to Gonabad Urban Health Centers

PubMed Central

Alaviani, Mehri; Khosravan, Shahla; Alami, Ali; Moshki, Mahdi

2015-01-01

Background Loneliness is one of the most significant problems during aging. This research has been done to determine the effect of a multi-strategy program based on Pender’s Health Promotion model to prevent loneliness of elderly women by improving social relationships. Methods In this quasi-experimental study done in 2013 from January to November, 150 old women suffering medium loneliness referred to Gonabad urban Health Centers were enrolled. Data were gathered using Russell’s UCLA loneliness questionnaire and the questionnaires based on Pender’s Health Promotion Model about loneliness. The results were analyzed by descriptive statistics and Chi-square, T-pair, and independent-T tests through SPSS, version 20. Results Loneliness decreased significantly in the interventional group compared to the control group (P<0.00). In addition, mean scores related to variables of Health Promotion Model (received benefits and barriers, self-efficacy, interpersonal effectives of loneliness) in both groups were significantly different before and after the study (P<0.05). Conclusion Constructs of Pender’s Health Promotion Model can be used as a framework for planning interventions in order to anticipate, improve and modify related behaviors related to loneliness in old women.   PMID:26005693

Using television shows to teach communication skills in internal medicine residency.

PubMed

Wong, Roger Y; Saber, Sadra S; Ma, Irene; Roberts, J Mark

2009-02-03

To address evidence-based effective communication skills in the formal academic half day curriculum of our core internal medicine residency program, we designed and delivered an interactive session using excerpts taken from medically-themed television shows. We selected two excerpts from the television show House, and one from Gray's Anatomy and featured them in conjunction with a brief didactic presentation of the Kalamazoo consensus statement on doctor-patient communication. To assess the efficacy of this approach a set of standardized questions were given to our residents once at the beginning and once at the completion of the session. Our residents indicated that their understanding of an evidence-based model of effective communication such as the Kalamazoo model, and their comfort levels in applying such model in clinical practice increased significantly. Furthermore, residents' understanding levels of the seven essential competencies listed in the Kalamazoo model also improved significantly. Finally, the residents reported that their comfort levels in three challenging clinical scenarios presented to them improved significantly. We used popular television shows to teach residents in our core internal medicine residency program about effective communication skills with a focus on the Kalamazoo's model. The results of the subjective assessment of this approach indicated that it was successful in accomplishing our objectives.

Quantifying second generation ethanol inhibition: Design of Experiments approach and kinetic model development.

PubMed

Schneiderman, Steven J; Johnson, Roger W; Menkhaus, Todd J; Gilcrease, Patrick C

2015-03-01

While softwoods represent a potential feedstock for second generation ethanol production, compounds present in their hydrolysates can inhibit fermentation. In this study, a novel Design of Experiments (DoE) approach was used to identify significant inhibitory effects on Saccharomyces cerevisiae D5A for the purpose of guiding kinetic model development. Although acetic acid, furfural and 5-hydroxymethyl furfural (HMF) were present at potentially inhibitory levels, initial factorial experiments only identified ethanol as a significant rate inhibitor. It was hypothesized that high ethanol levels masked the effects of other inhibitors, and a subsequent factorial design without ethanol found significant effects for all other compounds. When these non-ethanol effects were accounted for in the kinetic model, R¯(2) was significantly improved over an ethanol-inhibition only model (R¯(2)=0.80 vs. 0.76). In conclusion, when ethanol masking effects are removed, DoE is a valuable tool to identify significant non-ethanol inhibitors and guide kinetic model development. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rolling scheduling of electric power system with wind power based on improved NNIA algorithm

NASA Astrophysics Data System (ADS)

Xu, Q. S.; Luo, C. J.; Yang, D. J.; Fan, Y. H.; Sang, Z. X.; Lei, H.

2017-11-01

This paper puts forth a rolling modification strategy for day-ahead scheduling of electric power system with wind power, which takes the operation cost increment of unit and curtailed wind power of power grid as double modification functions. Additionally, an improved Nondominated Neighbor Immune Algorithm (NNIA) is proposed for solution. The proposed rolling scheduling model has further improved the operation cost of system in the intra-day generation process, enhanced the system’s accommodation capacity of wind power, and modified the key transmission section power flow in a rolling manner to satisfy the security constraint of power grid. The improved NNIA algorithm has defined an antibody preference relation model based on equal incremental rate, regulation deviation constraints and maximum & minimum technical outputs of units. The model can noticeably guide the direction of antibody evolution, and significantly speed up the process of algorithm convergence to final solution, and enhance the local search capability.

Communication and well-being outcomes of a hybrid service delivery model of intensive impairment-based treatment for aphasia in the hospital setting: a pilot study.

PubMed

Wenke, Rachel; Cardell, Elizabeth; Lawrie, Melissa; Gunning, Dana

2018-06-01

This pilot study aimed to evaluate the effects of an intensive hybrid service delivery model (i.e., combining face-to-face individual, computer and group therapy) on communication and well-being for people with aphasia (PWA) in the hospital setting. The study explored two different intensities of the hybrid model, 4 h/week (Hybrid-4) and 8 h/week (Hybrid-8) both for 8 weeks. Participants ranging from 1 month to 5 years post-onset were allocated using matched-pair randomisation to receive either Hybrid-4 (n = 5) or Hybrid-8 (n = 4) and assessed using a comprehensive language battery by a blinded assessor, as well as selected activity, participation and well-being measures before, immediately after and 4-week post-treatment. All participants in Hybrid-4 and three out of four participants in Hybrid-8 demonstrated clinically significant improvement to measures of language impairment immediately post-treatment, with the majority also demonstrating maintenance effects 4-week post-treatment. Clinically significant improvements to activity, participation and well-being measures were also observed across participants in both groups. Findings support the potential benefit of employing an intensive hybrid service model and suggest that both 4 and 8 h per week of impairment-based treatment for 8 weeks may result in improvements in communication and well-being for some PWA across different stages of recovery. Implications for rehabilitation The present findings help bridge the gap between what evidence suggests is effective intensity of rehabilitation for aphasia and what can be practically delivered in real-world hospital settings. Findings support the potential clinical value of employing a hybrid service model (using computer, group and individual therapy) to deliver intensive rehabilitation to people with aphasia in the hospital setting, and suggest that clinically significant improvements to communication and well-being can result when the model is delivered at either 4 or 8 h per week. The current study highlights that people with aphasia in the early stages of aphasia recovery can potentially benefit from intensive impairment-based hybrid models of intervention.

Quality Improvement in Acute Ischemic Stroke Care in Taiwan: The Breakthrough Collaborative in Stroke

PubMed Central

Chern, Chang-Ming; Lee, Tsong-Hai; Tang, Sung-Chun; Tsai, Li-Kai; Liao, Hsun-Hsiang; Chang, Hang; LaBresh, Kenneth A.; Lin, Hung-Jung; Chiou, Hung-Yi; Chiu, Hou-Chang; Lien, Li-Ming

2016-01-01

In the management of acute ischemic stroke, guideline adherence is often suboptimal, particularly for intravenous thrombolysis or anticoagulation for atrial fibrillation. We sought to improve stroke care quality via a collaborative model, the Breakthrough Series (BTS)-Stroke activity, in a nationwide, multi-center activity in Taiwan. A BTS Collaborative, a short-term learning system for a large number of multidisciplinary teams from hospitals, was applied to enhance acute ischemic stroke care quality. Twenty-four hospitals participated in and submitted data for this stroke quality improvement campaign in 2010–2011. Totally, 14 stroke quality measures, adopted from the Get With The Guideline (GWTG)-Stroke program, were used to evaluate the performance and outcome of the ischemic stroke patients. Data for a one-year period from 24 hospitals with 13,181 acute ischemic stroke patients were analyzed. In 14 hospitals, most stroke quality measures improved significantly during the BTS-activity compared with a pre-BTS-Stroke activity period (2006–08). The rate of intravenous thrombolysis increased from 1.2% to 4.6%, door-to-needle time ≤60 minutes improved from 7.1% to 50.8%, symptomatic hemorrhage after intravenous thrombolysis decreased from 11.0% to 5.6%, and anticoagulation therapy for atrial fibrillation increased from 32.1% to 64.1%. The yearly composite measures of five stroke quality measures revealed significant improvements from 2006 to 2011 (75% to 86.3%, p<0.001). The quarterly composite measures also improved significantly during the BTS-Stroke activity. In conclusion, a BTS collaborative model is associated with improved guideline adherence for patients with acute ischemic stroke. GWTG-Stroke recommendations can be successfully applied in countries besides the United States. PMID:27487190

Quality Improvement in Acute Ischemic Stroke Care in Taiwan: The Breakthrough Collaborative in Stroke.

PubMed

Hsieh, Fang-I; Jeng, Jiann-Shing; Chern, Chang-Ming; Lee, Tsong-Hai; Tang, Sung-Chun; Tsai, Li-Kai; Liao, Hsun-Hsiang; Chang, Hang; LaBresh, Kenneth A; Lin, Hung-Jung; Chiou, Hung-Yi; Chiu, Hou-Chang; Lien, Li-Ming

2016-01-01

In the management of acute ischemic stroke, guideline adherence is often suboptimal, particularly for intravenous thrombolysis or anticoagulation for atrial fibrillation. We sought to improve stroke care quality via a collaborative model, the Breakthrough Series (BTS)-Stroke activity, in a nationwide, multi-center activity in Taiwan. A BTS Collaborative, a short-term learning system for a large number of multidisciplinary teams from hospitals, was applied to enhance acute ischemic stroke care quality. Twenty-four hospitals participated in and submitted data for this stroke quality improvement campaign in 2010-2011. Totally, 14 stroke quality measures, adopted from the Get With The Guideline (GWTG)-Stroke program, were used to evaluate the performance and outcome of the ischemic stroke patients. Data for a one-year period from 24 hospitals with 13,181 acute ischemic stroke patients were analyzed. In 14 hospitals, most stroke quality measures improved significantly during the BTS-activity compared with a pre-BTS-Stroke activity period (2006-08). The rate of intravenous thrombolysis increased from 1.2% to 4.6%, door-to-needle time ≤60 minutes improved from 7.1% to 50.8%, symptomatic hemorrhage after intravenous thrombolysis decreased from 11.0% to 5.6%, and anticoagulation therapy for atrial fibrillation increased from 32.1% to 64.1%. The yearly composite measures of five stroke quality measures revealed significant improvements from 2006 to 2011 (75% to 86.3%, p<0.001). The quarterly composite measures also improved significantly during the BTS-Stroke activity. In conclusion, a BTS collaborative model is associated with improved guideline adherence for patients with acute ischemic stroke. GWTG-Stroke recommendations can be successfully applied in countries besides the United States.

Stabilization of surface-immobilized enzymes using grafted polymers

NASA Astrophysics Data System (ADS)

Moskovitz, Yevgeny; Srebnik, Simcha

2004-03-01

Vast research efforts focus on improving the biocompatibility and biofunctionality of surfaces for artificial implants and organs. A relatively successful approach involves grafting of polymer (usually PEG) on the artificial surface, which significantly improves its biocompatibility. In addition, positioning enzymes on or in the vicinity of the surface can significantly enhance bioseparation processes. However, the catalytic activity of the anchored enzyme is often drastically impaired by the nonnatural environment, leading to loss of activity and denaturation. We study protein adsorption and stabilization by grafted polymers using a mean-field lattice model. The model protein is designed as a compact HP with a specific bulk conformation reproducing a catalytic cleft of natural enzymes. Using hydrophilic grafted polymers of tailored length and density, we show that the conformation as well as hydrophobic and active centers of the model enzyme can be restored. This research is inspired by the problem of biocompatibility and biofunctionality of surfaces for artificial implants and organs.

Statistical significance of the rich-club phenomenon in complex networks

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing

2008-04-01

We propose that the rich-club phenomenon in complex networks should be defined in the spirit of bootstrapping, in which a null model is adopted to assess the statistical significance of the rich-club detected. Our method can serve as a definition of the rich-club phenomenon and is applied to analyze three real networks and three model networks. The results show significant improvement compared with previously reported results. We report a dilemma with an exceptional example, showing that there does not exist an omnipotent definition for the rich-club phenomenon.

Ion-source modeling and improved performance of the CAMS high-intensity Cs-sputter ion source

NASA Astrophysics Data System (ADS)

Brown, T. A.; Roberts, M. L.; Southon, J. R.

2000-10-01

The interior of the high-intensity Cs-sputter source used in routine operations at the Center for Accelerator Mass Spectrometry (CAMS) has been computer modeled using the program NEDLab, with the aim of improving negative ion output. Space charge effects on ion trajectories within the source were modeled through a successive iteration process involving the calculation of ion trajectories through Poisson-equation-determined electric fields, followed by calculation of modified electric fields incorporating the charge distribution from the previously calculated ion trajectories. The program has several additional features that are useful in ion source modeling: (1) averaging of space charge distributions over successive iterations to suppress instabilities, (2) Child's Law modeling of space charge limited ion emission from surfaces, and (3) emission of particular ion groups with a thermal energy distribution and at randomized angles. The results of the modeling effort indicated that significant modification of the interior geometry of the source would double Cs + ion production from our spherical ionizer and produce a significant increase in negative ion output from the source. The results of the implementation of the new geometry were found to be consistent with the model results.

Trehalose Improves Cognition in the Transgenic Tg2576 Mouse Model of Alzheimer's Disease.

PubMed

Portbury, Stuart D; Hare, Dominic J; Sgambelloni, Charlotte; Perronnes, Kali; Portbury, Ashley J; Finkelstein, David I; Adlard, Paul A

2017-01-01

This study assessed the therapeutic utility of the autophagy enhancing stable disaccharide trehalose in the Tg2576 transgenic mouse model of Alzheimer's disease (AD) via an oral gavage of a 2% trehalose solution for 31 days. Furthermore, as AD is a neurodegenerative condition in which the transition metals, iron, copper, and zinc, are understood to be intricately involved in the cellular cascades leading to the defining pathologies of the disease, we sought to determine any parallel impact of trehalose treatment on metal levels. Trehalose treatment significantly improved performance in the Morris water maze, consistent with enhanced learning and memory. The improvement was not associated with significant modulation of full length amyloid-β protein precursor or other amyloid-β fragments. Trehalose had no effect on autophagy as assessed by western blot of the LC3-1 to LC3-2 protein ratio, and no alteration in biometals that might account for the improved cognition was observed. Biochemical analysis revealed a significant increase in the hippocampus of both synaptophysin, a synaptic vesicle protein and surrogate marker of synapses, and doublecortin, a reliable marker of neurogenesis. The growth factor progranulin was also significantly increased in the hippocampus and cortex with trehalose treatment. This study suggests that trehalose might invoke a suite of neuroprotective mechanisms that can contribute to improved cognitive performance in AD that are independent of more classical trehalose-mediated pathways, such as Aβ reduction and activation of autophagy. Thus, trehalose may have utility as a potential AD therapeutic, with conceivable implications for the treatment of other neurodegenerative disorders.

IEEE Computer Society/Software Engineering Institute Watts S. Humphrey Software Process Achievement Award 2016: Raytheon Integrated Defense Systems Design for Six Sigma Team

DTIC Science & Technology

2017-04-01

notice for non -US Government use and distribution. External use: This material may be reproduced in its entirety, without modification, and freely...Combinatorial Design Methods 4 2.1 Identification of Significant Improvement Opportunity 4 2.2 Methodology Development 4 2.3 Piloting...11 3 Process Performance Modeling and Analysis 13 3.1 Identification of Significant Improvement Opportunity 13 3.2 Methodology Development 13 3.3

Improved interpretation of satellite altimeter data using genetic algorithms

NASA Technical Reports Server (NTRS)

Messa, Kenneth; Lybanon, Matthew

1992-01-01

Genetic algorithms (GA) are optimization techniques that are based on the mechanics of evolution and natural selection. They take advantage of the power of cumulative selection, in which successive incremental improvements in a solution structure become the basis for continued development. A GA is an iterative procedure that maintains a 'population' of 'organisms' (candidate solutions). Through successive 'generations' (iterations) the population as a whole improves in simulation of Darwin's 'survival of the fittest'. GA's have been shown to be successful where noise significantly reduces the ability of other search techniques to work effectively. Satellite altimetry provides useful information about oceanographic phenomena. It provides rapid global coverage of the oceans and is not as severely hampered by cloud cover as infrared imagery. Despite these and other benefits, several factors lead to significant difficulty in interpretation. The GA approach to the improved interpretation of satellite data involves the representation of the ocean surface model as a string of parameters or coefficients from the model. The GA searches in parallel, a population of such representations (organisms) to obtain the individual that is best suited to 'survive', that is, the fittest as measured with respect to some 'fitness' function. The fittest organism is the one that best represents the ocean surface model with respect to the altimeter data.

Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

NASA Astrophysics Data System (ADS)

Zhu, Shijia; Wang, Yadong

2015-12-01

Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

A Hyaluronan-Based Injectable Hydrogel Improves the Survival and Integration of Stem Cell Progeny following Transplantation.

PubMed

Ballios, Brian G; Cooke, Michael J; Donaldson, Laura; Coles, Brenda L K; Morshead, Cindi M; van der Kooy, Derek; Shoichet, Molly S

2015-06-09

The utility of stem cells and their progeny in adult transplantation models has been limited by poor survival and integration. We designed an injectable and bioresorbable hydrogel blend of hyaluronan and methylcellulose (HAMC) and tested it with two cell types in two animal models, thereby gaining an understanding of its general applicability for enhanced cell distribution, survival, integration, and functional repair relative to conventional cell delivery in saline. HAMC improves cell survival and integration of retinal stem cell (RSC)-derived rods in the retina. The pro-survival mechanism of HAMC is ascribed to the interaction of the CD44 receptor with HA. Transient disruption of the retinal outer limiting membrane, combined with HAMC delivery, results in significantly improved rod survival and visual function. HAMC also improves the distribution, viability, and functional repair of neural stem and progenitor cells (NSCs). The HAMC delivery system improves cell transplantation efficacy in two CNS models, suggesting broad applicability. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Recent Improvements in Semi-Span Testing at the National Transonic Facility (Invited)

NASA Technical Reports Server (NTRS)

Gatlin, G. M.; Tomek, W. G.; Payne, F. M.; Griffiths, R. C.

2006-01-01

Three wind tunnel investigations of a commercial transport, high-lift, semi-span configuration have recently been conducted in the National Transonic Facility at the NASA Langley Research Center. Throughout the course of these investigations multiple improvements have been developed in the facility semi-span test capability. The primary purpose of the investigations was to assess Reynolds number scale effects on a modern commercial transport configuration up to full-scale flight test conditions (Reynolds numbers on the order of 27 million). The tests included longitudinal aerodynamic studies at subsonic takeoff and landing conditions across a range of Reynolds numbers from that available in conventional wind tunnels up to flight conditions. The purpose of this paper is to discuss lessons learned and improvements incorporated into the semi-span testing process. Topics addressed include enhanced thermal stabilization and moisture reduction procedures, assessments and improvements in model sealing techniques, compensation of model reference dimensions due to test temperature, significantly improved semi-span model access capability, and assessments of data repeatability.

Police Mental Health Partnership project: Police Ambulance Crisis Emergency Response (PACER) model development.

PubMed

Huppert, David; Griffiths, Matthew

2015-10-01

To review internationally recognized models of police interactions with people experiencing mental health crises that are sometimes complex and associated with adverse experience for the person in crisis, their family and emergency service personnel. To develop, implement and review a partnership model trial between mental health and emergency services that offers alternative response pathways with improved outcomes in care. Three unique models of police and mental health partnership in the USA were reviewed and used to develop the PACER (Police Ambulance Crisis Emergency Response) model. A three month trial of the model was implemented and evaluated. Significant improvements in response times, the interactions with and the outcomes for people in crisis were some of the benefits shown when compared with usual services. The pilot showed that a partnership involving mental health and police services in Melbourne, Australia could be replicated based on international models. Initial data supported improvements compared with usual care. Further data collection regarding usual care and this new model is required to confirm observed benefits. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Historical background and design evolution of the transonic aircraft technology supercritical wing

NASA Technical Reports Server (NTRS)

Ayers, T. G.; Hallissy, J. B.

1981-01-01

Two dimensional wind tunnel test results obtained for supercritical airfoils indicated that substantial improvements in aircraft performance at high subsonic speeds could be achieved by shaping the airfoil to improve the supercritical flow above the upper surface. Significant increases in the drag divergence Mach number, the maximum lift coefficient for buffer onset, and the Mach number for buffet onset at a given lift coefficient were demonstrated for the supercritical airfoil, as compared with a NACA 6 series airfoil of comparable thickness. These trends were corroborated by results from three dimensional wind tunnel and flight tests. Because these indicated extensions of the buffet boundaries could provide significant improvements in the maneuverability of a fighter airplane, an exploratory wind tunnel investigation was initiated which demonstrated that significant aerodynamic improvements could be achieved from the direct substitution of a supercritical airfoil on a variable wing sweep multimission airplane model.

Impact of the Local Public Hospital Reform on the Efficiency of Medium-Sized Hospitals in Japan: An Improved Slacks-Based Measure Data Envelopment Analysis Approach.

PubMed

Zhang, Xing; Tone, Kaoru; Lu, Yingzhe

2018-04-01

To assess the change in efficiency and total factor productivity (TFP) of the local public hospitals in Japan after the local public hospital reform launched in late 2007, which was aimed at improving the financial capability and operational efficiency of hospitals. Secondary data were collected from the Ministry of Internal Affairs and Communications on 213 eligible medium-sized hospitals, each operating 100-400 beds from FY2006 to FY2011. The improved slacks-based measure nonoriented data envelopment analysis models (Quasi-Max SBM nonoriented DEA models) were used to estimate dynamic efficiency score and Malmquist Index. The dynamic efficiency measure indicated an efficiency gain in the first several years of the reform and then was followed by a decrease. Malmquist Index analysis showed a significant decline in the TFP between 2006 and 2011. The financial improvement of medium-sized hospitals was not associated with enhancement of efficiency. Hospital efficiency was not significantly different among ownership structure and law-application system groups, but it was significantly affected by hospital location. The results indicate a need for region-tailored health care policies and for a more comprehensive reform to overcome the systemic constraints that might contribute to the decline of the TFP. © Health Research and Educational Trust.

Effect of multimedia information sequencing on educational outcome in orthodontic training.

PubMed

Aly, Medhat; Willems, Guy; Van Den Noortgate, Wim; Elen, Jan

2012-08-01

The aim of this research was to compare the effectiveness of hierarchical sequencing (HS) versus elaboration sequencing (ES) models in improving educational outcome of clinical knowledge when using instructional multimedia programs in postgraduate orthodontic training. Twenty-four postgraduate and 24 undergraduate dental students participated in this study. The postgraduates were following an orthodontic speciality training programme. The undergraduates were fourth- and fifth-year dental students. Twelve instructional multimedia modules were developed, six logically sequenced (LS) discussing six different orthodontic topics. Another six modules on identical topics were sequenced according to one macro-sequencing (MS) model. The implemented MS model was either HS or ES. The only difference between LS and MS modules was the adopted sequencing model. All participants were assigned into consistent pairs of students and were randomly divided into a test and a control group. In each pair, one student studied the LS module (control group) while the other studied the MS version (test group). Pre- and post-evaluation tests of each pair of participants were performed to measure knowledge, understanding and application of each participant with regard to the discussed topic. A multilevel analysis was conducted to assess the estimated effect of the different sequencing models. The level of significance was set at 0.05. At baseline, no significant differences (P > 0.05) were found in pre-test scores between groups. The HS model showed a significant effect on the scores achieved (P = 0.05). The test group showed a significantly higher estimated probability of correct answers to the questions (P = 0.003) when applying the HS model. The HS model may improve educational outcome when using instructional multimedia programs in postgraduate orthodontic training.

Otago Exercise Program in the United States: Comparison of 2 Implementation Models.

PubMed

Shubert, Tiffany E; Smith, Matthew L; Goto, Lavina; Jiang, Luohua; Ory, Marcia G

2017-02-01

The Otago Exercise Program (OEP) is an evidence-based fall prevention program delivered by a physical therapist in 6 visits over a year. Despite documented effectiveness, there has been limited adoption of the OEP by physical therapists in the United States. To facilitate dissemination, 2 models have been developed: (1) the US OEP provided by a physical therapist or physical therapist assistant in the home or outpatient setting and (2) the community OEP provided by a non–physical therapist and a physical therapist consultant. It is unknown whether such modifications result in similar outcomes. The aims of this study were to identify the components of these 2 models, to compare participant characteristics for those components reached by each model, and to examine outcome changes by model and between models. This was a translational cohort study with physical therapists implementing the US OEP and trained providers implementing the community OEP. Data for physical performance, sociodemographic characteristics, and self-perception of function were collected at baseline and at 8 weeks. Participants in the community OEP were significantly younger and reported more falls compared with those in US OEP. Both sites reported significant improvements in most physical and self-reported measures of function, with larger effect sizes reported by the community OEP for the Timed “Up & Go” Test. There was no significant difference in improvements in outcome measures between sites. This was an evaluation of a translational research project with limited control over delivery processes. The sample was 96% white, which may limit application to a more diverse population. Alternative, less expensive implementation models of the OEP can achieve results similar to those achieved with traditional methods, especially improvements in Timed “Up & Go” Test scores. The data suggest that the action of doing the exercises may be the essential element of the OEP, providing opportunities to develop and test new delivery models to ensure that the best outcomes are achieved by participants. © 2017 American Physical Therapy Association

The effect of educational intervention based on an Ecological-social model on consuming fruit and vegetables in women in Ilam.

PubMed

Shafiei, Leili; Taymoori, Parvaneh; Maleki, Afshin; Sayehmiri, Kourosh

2017-12-01

The effect of instructional models on the changing behavior of consuming fruit and vegetables in the prevention of diseases caused by consumption of foods including rice, contaminated with toxic metals, has not been investigated in Iran yet. To compare an Ecological-social model (ECO) group and Control group in increasing fruit and vegetable consumption. This research involved implementation of a six-month randomized controlled educational interventionist program into a group of Ecological-social framework along with a control group, totally summing up to 160 women between 18 and 50 years of age in Ilam, Iran in 2014. The questionnaire included knowledge, social support construct (immediate family, relatives, friends, colleagues and neighbors.) and fruit and vegetable intake in both groups before and after the intervention was examined. Data were analyzed by SPSS version 16 using the signed ranks test, and repeated measures analysis of variance analysis, and confidence interval of 95% were employed. The results of the signed ranks test showed a significant increase in social support in the intervention group (p<0.001). This test showed a significant increase in fruit and vegetable consumption and a significant increase in the number of women using healthy rice (p<0.001), and a significant reduction in the number of women consuming unhealthy rice in the intervention group (p<0.001), that determines dietary intake improvement after the intervention compared with before the intervention (p<0.01). However, this improvement was not observed in the control group. The results showed that ECO plays an effective role in improving fruit and vegetable consumption in women. Therefore, this model was implemented as a health protocol through health-care centers to conduct the prevention of complications resulting from the use of food contaminated with toxic metals.

Cost-Effectiveness of a Technology-Facilitated Depression Care Management Adoption Model in Safety-Net Primary Care Patients with Type 2 Diabetes.

PubMed

Hay, Joel W; Lee, Pey-Jiuan; Jin, Haomiao; Guterman, Jeffrey J; Gross-Schulman, Sandra; Ell, Kathleen; Wu, Shinyi

2018-05-01

The Diabetes-Depression Care-Management Adoption Trial is a translational study of safety-net primary care predominantly Hispanic/Latino patients with type 2 diabetes in collaboration with the Los Angeles County Department of Health Services. To evaluate the cost-effectiveness of an information and communication technology (ICT)-facilitated depression care management program. Cost-effectiveness of the ICT-facilitated care (TC) delivery model was evaluated relative to a usual care (UC) and a supported care (SC) model. TC added automated low-intensity periodic depression assessment calls to patients. Patient-reported outcomes included the 12-Item Short Form Health Survey converted into quality-adjusted life-years (QALYs) and the 9-Item Patient Health Questionnaire-calculated depression-free days (DFDs). Costs and outcomes data were collected over a 24-month period (-6 to 0 months baseline, 0 to 18 months study intervention). A sample of 1406 patients (484 in UC, 480 in SC, and 442 in TC) was enrolled in the nonrandomized trial. TC had a significant improvement in DFDs (17.3; P = 0.011) and significantly greater 12-Item Short Form Health Survey utility improvement (2.1%; P = 0.031) compared with UC. Medical costs were statistically significantly lower for TC (-$2328; P = 0.001) relative to UC but not significantly lower than for SC. TC had more than a 50% probability of being cost-effective relative to SC at willingness-to-pay thresholds of more than $50,000/QALY. An ICT-facilitated depression care (TC) delivery model improved QALYs, DFDs, and medical costs. It was cost-effective compared with SC and dominant compared with UC. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

DeMO: An Ontology for Discrete-event Modeling and Simulation.

PubMed

Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

2011-09-01

Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community.

DeMO: An Ontology for Discrete-event Modeling and Simulation

PubMed Central

Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

2011-01-01

Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community. PMID:22919114

A review of failure models for unidirectional ceramic matrix composites under monotonic loads

NASA Technical Reports Server (NTRS)

Tripp, David E.; Hemann, John H.; Gyekenyesi, John P.

1989-01-01

Ceramic matrix composites offer significant potential for improving the performance of turbine engines. In order to achieve their potential, however, improvements in design methodology are needed. In the past most components using structural ceramic matrix composites were designed by trial and error since the emphasis of feasibility demonstration minimized the development of mathematical models. To understand the key parameters controlling response and the mechanics of failure, the development of structural failure models is required. A review of short term failure models with potential for ceramic matrix composite laminates under monotonic loads is presented. Phenomenological, semi-empirical, shear-lag, fracture mechanics, damage mechanics, and statistical models for the fast fracture analysis of continuous fiber unidirectional ceramic matrix composites under monotonic loads are surveyed.

The Generalized Born solvation model: What is it?

NASA Astrophysics Data System (ADS)

Onufriev, Alexey

2004-03-01

Implicit solvation models provide, for many applications, an effective way of describing the electrostatic effects of aqueous solvation. Here we outline the main approximations behind the popular Generalized Born solvation model. We show how its accuracy, relative to the Poisson-Boltzmann treatment, can be significantly improved in a computationally inexpensive manner to make the model useful in the studies of large-scale conformational transitions at the atomic level. The improved model is tested in a molecular dynamics simulation of folding of a 46-residue (three helix bundle) protein. Starting from an extended structure at 450K, the protein folds to the lowest energy conformation within 6 ns of simulation time, and the predicted structure differs from the native one by 2.4 A (backbone RMSD).

Crustal tracers in the atmosphere and ocean: Relating their concentrations, fluxes, and ages

NASA Astrophysics Data System (ADS)

Han, Qin

Crustal tracers are important sources of key limiting nutrients (e.g., iron) in remote ocean regions where they have a large impact on global biogeochemical cycles. However, the atmospheric delivery of bio-available iron to oceans via mineral dust aerosol deposition is poorly constrained. This dissertation aims to improve understanding and model representation of oceanic dust deposition and to provide soluble iron flux maps by testing observations of crustal tracer concentrations and solubilities against predictions from two conceptual solubility models. First, we assemble a database of ocean surface dissolved Al and incorporate Al cycling into the global Biogeochemical Elemental Cycling (BEC) model. The observed Al concentrations show clear basin-scale differences that are useful for constraining dust deposition. The dynamic mixed layer depth and Al residence time in the BEC model significantly improve the simulated dissolved Al field. Some of the remaining model-data discrepancies appear related to the neglect of aerosol size, age, and air mass characteristics in estimating tracer solubility. Next, we develop the Mass-Age Tracking method (MAT) to efficiently and accurately estimate the mass-weighted age of tracers. We apply MAT to four sizes of desert dust aerosol and simulate, for the first time, global distributions of aerosol age in the atmosphere and at deposition. These dust size and age distributions at deposition, together with independent information on air mass acidity, allow us to test two simple yet plausible models for predicting the dissolution of mineral dust iron and aluminum during atmospheric transport. These models represent aerosol solubility as controlled (1) by a diffusive process leaching nutrients from the dust into equilibrium with the liquid water coating or (2) by a process that continually dissolves nutrients in proportion to the particle surface area. The surface-controlled model better captures the spatial pattern of observed solubility in the Atlantic. Neither model improves previous estimates of the solubility in the Pacific, nor do they significantly improve the global BEC simulation of dissolved iron or aluminum.

Oleanolic Acid Ameliorates Aβ25-35 Injection-induced Spatial Learning and Memory Deficit in Alzheimer's Disease Model Rats.

PubMed

Wang, Kai; Sun, Weiming; Zhang, Linlin; Guo, Wei; Xu, Jiachun; Liu, Shuang; Zhou, Zhen; Zhang, Yulian

2018-05-24

Abnormal amyloid β (Aβ) accumulation and deposition in hippocampus is an essential process in Alzheimer's disease (AD). To investigate whether Oleanolic acid (OA) could improve learning and memory deficit and its possible mechanism. Forty-five SD rats were randomly divided into sham operation group, model group, and OA group. AD models by injection of Aβ25-35 were built. Morris water maze (MWM) was applied to investigate learning and memory, transmission electron microscope (TEM) to observe the ultrastructure of synapse, western blot to the key targets of synapse, electrophysiology for long-term potentiation (LTP), and Ca2+ concentration in synapse was also measured. The latency time in model group was significantly longer than that in sham operation group (P=0.0001<0.05); while it was significantly shorter in the OA group than that in model group (P=0.0001<0.05); compared with model group, the times of cross-platform in OA group significantly increased (P = 0.0001 <0.05). TEM results showed OA couldalleviate neuron damage and synapses changes induced by Aβ25-35. The expression of CaMKII, PKC, NMDAR2B, BDNF, TrkB, and CREB protein were significantly improved by OA; the concentration of Ca2+ were significantly lower and the slope and amplitude of f-EPSP increased in OA group. OA could ameliorate Aβ-induced spatial learning and memory loss of AD rats, and the mechanism might be involved with maintaining synaptic integrity to restore synaptic plasticity and increasing the NMDAR2B protein, CaMKII and PKC protein in postsynaptic density (PSD), reducing synaptic Ca2+ concentration, enhancing LTP by up-regulating BDNF, TrkB, CREB proteins. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Multi-objective optimization in quantum parameter estimation

NASA Astrophysics Data System (ADS)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

Teacher coaching supported by formative assessment for improving classroom practices.

PubMed

Fabiano, Gregory A; Reddy, Linda A; Dudek, Christopher M

2018-06-01

The present study is a wait-list controlled, randomized study investigating a teacher coaching approach that emphasizes formative assessment and visual performance feedback to enhance elementary school teachers' classroom practices. The coaching model targeted instructional and behavioral management practices as measured by the Classroom Strategies Assessment System (CSAS) Observer and Teacher Forms. The sample included 89 general education teachers, stratified by grade level, and randomly assigned to 1 of 2 conditions: (a) immediate coaching, or (b) waitlist control. Results indicated that, relative to the waitlist control, teachers in immediate coaching demonstrated significantly greater improvements in observations of behavior management strategy use but not for observations of instructional strategy use. Observer- and teacher-completed ratings of behavioral management strategy use at postassessment were significantly improved by both raters; ratings of instructional strategy use were significantly improved for teacher but not observer ratings. A brief coaching intervention improved teachers' use of observed behavior management strategies and self-reported use of behavior management and instructional strategies. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

Fisk, William J.

The evidence of health benefits of particle filtration in homes and commercial buildings is reviewed. Prior reviews of papers published before 2000 are summarized. The results of 16 more recent intervention studies are compiled and analyzed. Also, reviewed are four studies that modeled health benefits of using filtration to reduce indoor exposures to particles from outdoors. Prior reviews generally concluded that particle filtration is, at best, a source of small improvements in allergy and asthma health effects; however, many early studies had weak designs. A majority of recent intervention studies employed strong designs and more of these studies report statisticallymore » significant improvements in health symptoms or objective health outcomes, particularly for subjects with allergies or asthma. The percent age improvement in health outcomes is typically modest, for example, 7percent to 25percent. Delivery of filtered air to the breathing zone of sleeping allergic or asthmatic persons may be more consistently effective in improving health than room air filtration. Notable are two studies that report statistically significant improvements, with filtration, in markers that predict future adverse coronary events. From modeling, the largest potential benefits of indoor particle filtration may be reductions in morbidity and mortality from reducing indoor exposures to particles from outdoor air.« less

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

Fisk, William J.

The evidence of health benefits of particle filtration in homes and commercial buildings is reviewed. Prior reviews of papers published before 2000 are summarized. The results of 16 more recent intervention studies are compiled and analyzed. Also reviewed are four studies that modeled health benefits of using filtration to reduce indoor exposures to particles from outdoors. Prior reviews generally concluded that particle filtration is, at best, a source of small improvements in allergy and asthma health effects; however, many early studies had weak designs. A majority of recent intervention studies employed strong designs and more of these studies report statisticallymore » significant improvements in health symptoms or objective health outcomes, particularly for subjects with allergies or asthma. The percentage improvement in health outcomes is typically modest, e.g., 7percent to 25percent. Delivery of filtered air to the breathing zone of sleeping allergic or asthmatic persons may be more consistently effective in improving health than room air filtration. Notable are two studies that report statistically significant improvements, with filtration, in markers that predict future adverse coronary events. From modeling, the largest potential benefits of indoor particle filtration may be reductions in morbidity and mortality from reducing indoor exposures to particles from outdoor air.« less

Antenatal Saireito (TJ-114) Can Improve Pulmonary Hypoplasia and Pulmonary Vascular Remodeling in Nitrofen-Induced Congenital Diaphragmatic Hernia.

PubMed

Hirako, Shima; Tsuda, Hiroyuki; Kotani, Tomomi; Sumigama, Seiji; Mano, Yukio; Nakano, Tomoko; Imai, Kenji; Li, Hua; Toyokuni, Shinya; Kikkawa, Fumitaka

2016-09-01

Congenital diaphragmatic hernia (CDH) can induce lung hypoplasia and pulmonary hypertension and is associated with high mortality. The purpose of this study is to examine the efficacy and safety of antenatal Saireito (TJ-114), a traditional Japanese herbal medicine, in a rat CDH model. Sprague-Dawley rats were exposed to an herbicide (nitrofen, 100 mg) on embryonic day 9 (E9) to induce CDH, and antenatal Saireito (2000 mg/kg/day) was orally administered from E10 to E20. On E21, fetuses were delivered. Antenatal Saireito significantly decreased the incidence of CDH (p < 0.01), increased lung volume (p < 0.01), improved alveolarization and pulmonary artery remodeling using histological analysis, and improved respiratory function using gasometric analysis (pH; p < 0.05, and PCO2 ; p < 0.01). In addition, antenatal Saireito significantly decreased endothelin-1 and endothelin receptor A expression in the pulmonary arteries. Taken together, our results demonstrated that antenatal Saireito can improve fetal pulmonary hypoplasia and pulmonary vascular remodeling and, as a result, can improve respiratory function in a rat CDH model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman Filter

PubMed Central

Han, Houzeng; Xu, Tianhe; Wang, Jian

2016-01-01

Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD) operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC) algorithm is implemented by integrating PPP with inertial navigation system (INS) using an Extended Kalman filter (EKF). The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies of the height component are improved by 30.36%, 16.95% and 24.07% for three different convergence times, i.e., 60, 50 and 30 min, respectively. It shows that the ambiguity-fixed horizontal positioning accuracy has been significantly improved. When compared with the conventional PPP solution, it can be seen that position accuracies are improved by 19.51%, 61.11% and 23.53% for the north, east and height components, respectively, after one hour convergence through the troposphere constraint fixed PPP/INS with adaptive covariance model. PMID:27399721

Improving and Evaluating Nested Sampling Algorithm for Marginal Likelihood Estimation

NASA Astrophysics Data System (ADS)

Ye, M.; Zeng, X.; Wu, J.; Wang, D.; Liu, J.

2016-12-01

With the growing impacts of climate change and human activities on the cycle of water resources, an increasing number of researches focus on the quantification of modeling uncertainty. Bayesian model averaging (BMA) provides a popular framework for quantifying conceptual model and parameter uncertainty. The ensemble prediction is generated by combining each plausible model's prediction, and each model is attached with a model weight which is determined by model's prior weight and marginal likelihood. Thus, the estimation of model's marginal likelihood is crucial for reliable and accurate BMA prediction. Nested sampling estimator (NSE) is a new proposed method for marginal likelihood estimation. The process of NSE is accomplished by searching the parameters' space from low likelihood area to high likelihood area gradually, and this evolution is finished iteratively via local sampling procedure. Thus, the efficiency of NSE is dominated by the strength of local sampling procedure. Currently, Metropolis-Hasting (M-H) algorithm is often used for local sampling. However, M-H is not an efficient sampling algorithm for high-dimensional or complicated parameter space. For improving the efficiency of NSE, it could be ideal to incorporate the robust and efficient sampling algorithm - DREAMzs into the local sampling of NSE. The comparison results demonstrated that the improved NSE could improve the efficiency of marginal likelihood estimation significantly. However, both improved and original NSEs suffer from heavy instability. In addition, the heavy computation cost of huge number of model executions is overcome by using an adaptive sparse grid surrogates.

Effect of Internet-Based Cognitive Apprenticeship Model (i-CAM) on Statistics Learning among Postgraduate Students.

PubMed

Saadati, Farzaneh; Ahmad Tarmizi, Rohani; Mohd Ayub, Ahmad Fauzi; Abu Bakar, Kamariah

2015-01-01

Because students' ability to use statistics, which is mathematical in nature, is one of the concerns of educators, embedding within an e-learning system the pedagogical characteristics of learning is 'value added' because it facilitates the conventional method of learning mathematics. Many researchers emphasize the effectiveness of cognitive apprenticeship in learning and problem solving in the workplace. In a cognitive apprenticeship learning model, skills are learned within a community of practitioners through observation of modelling and then practice plus coaching. This study utilized an internet-based Cognitive Apprenticeship Model (i-CAM) in three phases and evaluated its effectiveness for improving statistics problem-solving performance among postgraduate students. The results showed that, when compared to the conventional mathematics learning model, the i-CAM could significantly promote students' problem-solving performance at the end of each phase. In addition, the combination of the differences in students' test scores were considered to be statistically significant after controlling for the pre-test scores. The findings conveyed in this paper confirmed the considerable value of i-CAM in the improvement of statistics learning for non-specialized postgraduate students.

Improving evapotranspiration processes in distrubing hydrological models using Remote Sensing derived ET products.

NASA Astrophysics Data System (ADS)

Abitew, T. A.; van Griensven, A.; Bauwens, W.

2015-12-01

Evapotranspiration is the main process in hydrology (on average around 60%), though has not received as much attention in the evaluation and calibration of hydrological models. In this study, Remote Sensing (RS) derived Evapotranspiration (ET) is used to improve the spatially distributed processes of ET of SWAT model application in the upper Mara basin (Kenya) and the Blue Nile basin (Ethiopia). The RS derived ET data is obtained from recently compiled global datasets (continuously monthly data at 1 km resolution from MOD16NBI,SSEBop,ALEXI,CMRSET models) and from regionally applied Energy Balance Models (for several cloud free days). The RS-RT data is used in different forms: Method 1) to evaluate spatially distributed evapotransiration model resultsMethod 2) to calibrate the evotranspiration processes in hydrological modelMethod 3) to bias-correct the evapotranpiration in hydrological model during simulation after changing the SWAT codesAn inter-comparison of the RS-ET products shows that at present there is a significant bias, but at the same time an agreement on the spatial variability of ET. The ensemble mean of different ET products seems the most realistic estimation and was further used in this study.The results show that:Method 1) the spatially mapped evapotranspiration of hydrological models shows clear differences when compared to RS derived evapotranspiration (low correlations). Especially evapotranspiration in forested areas is strongly underestimated compared to other land covers.Method 2) Calibration allows to improve the correlations between the RS and hydrological model results to some extent.Method 3) Bias-corrections are efficient in producing (sesonal or annual) evapotranspiration maps from hydrological models which are very similar to the patterns obtained from RS data.Though the bias-correction is very efficient, it is advised to improve the model results by better representing the ET processes by improved plant/crop computations, improved agricultural management practices or by providing improved meteorological data.

Global and Regional 3D Tomography for Improved Seismic Event Location and Uncertainty in Explosion Monitoring

NASA Astrophysics Data System (ADS)

Downey, N.; Begnaud, M. L.; Hipp, J. R.; Ballard, S.; Young, C. S.; Encarnacao, A. V.

2017-12-01

The SALSA3D global 3D velocity model of the Earth was developed to improve the accuracy and precision of seismic travel time predictions for a wide suite of regional and teleseismic phases. Recently, the global SALSA3D model was updated to include additional body wave phases including mantle phases, core phases, reflections off the core-mantle boundary and underside reflections off the surface of the Earth. We show that this update improves travel time predictions and leads directly to significant improvements in the accuracy and precision of seismic event locations as compared to locations computed using standard 1D velocity models like ak135, or 2½D models like RSTT. A key feature of our inversions is that path-specific model uncertainty of travel time predictions are calculated using the full 3D model covariance matrix computed during tomography, which results in more realistic uncertainty ellipses that directly reflect tomographic data coverage. Application of this method can also be done at a regional scale: we present a velocity model with uncertainty obtained using data obtained from the University of Utah Seismograph Stations. These results show a reduction in travel-time residuals for re-located events compared with those obtained using previously published models.

Polarized BRDF for coatings based on three-component assumption

NASA Astrophysics Data System (ADS)

Liu, Hong; Zhu, Jingping; Wang, Kai; Xu, Rong

2017-02-01

A pBRDF(polarized bidirectional reflection distribution function) model for coatings is given based on three-component reflection assumption in order to improve the polarized scattering simulation capability for space objects. In this model, the specular reflection is given based on microfacet theory, the multiple reflection and volume scattering are given separately according to experimental results. The polarization of specular reflection is considered from Fresnel's law, and both multiple reflection and volume scattering are assumed depolarized. Simulation and measurement results of two satellite coating samples SR107 and S781 are given to validate that the pBRDF modeling accuracy can be significantly improved by the three-component model given in this paper.

Improved estimation of PM2.5 using Lagrangian satellite-measured aerosol optical depth

NASA Astrophysics Data System (ADS)

Olivas Saunders, Rolando

Suspended particulate matter (aerosols) with aerodynamic diameters less than 2.5 mum (PM2.5) has negative effects on human health, plays an important role in climate change and also causes the corrosion of structures by acid deposition. Accurate estimates of PM2.5 concentrations are thus relevant in air quality, epidemiology, cloud microphysics and climate forcing studies. Aerosol optical depth (AOD) retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument has been used as an empirical predictor to estimate ground-level concentrations of PM2.5 . These estimates usually have large uncertainties and errors. The main objective of this work is to assess the value of using upwind (Lagrangian) MODIS-AOD as predictors in empirical models of PM2.5. The upwind locations of the Lagrangian AOD were estimated using modeled backward air trajectories. Since the specification of an arrival elevation is somewhat arbitrary, trajectories were calculated to arrive at four different elevations at ten measurement sites within the continental United States. A systematic examination revealed trajectory model calculations to be sensitive to starting elevation. With a 500 m difference in starting elevation, the 48-hr mean horizontal separation of trajectory endpoints was 326 km. When the difference in starting elevation was doubled and tripled to 1000 m and 1500m, the mean horizontal separation of trajectory endpoints approximately doubled and tripled to 627 km and 886 km, respectively. A seasonal dependence of this sensitivity was also found: the smallest mean horizontal separation of trajectory endpoints was exhibited during the summer and the largest separations during the winter. A daily average AOD product was generated and coupled to the trajectory model in order to determine AOD values upwind of the measurement sites during the period 2003-2007. Empirical models that included in situ AOD and upwind AOD as predictors of PM2.5 were generated by multivariate linear regressions using the least squares method. The multivariate models showed improved performance over the single variable regression (PM2.5 and in situ AOD) models. The statistical significance of the improvement of the multivariate models over the single variable regression models was tested using the extra sum of squares principle. In many cases, even when the R-squared was high for the multivariate models, the improvement over the single models was not statistically significant. The R-squared of these multivariate models varied with respect to seasons, with the best performance occurring during the summer months. A set of seasonal categorical variables was included in the regressions to exploit this variability. The multivariate regression models that included these categorical seasonal variables performed better than the models that didn't account for seasonal variability. Furthermore, 71% of these regressions exhibited improvement over the single variable models that was statistically significant at a 95% confidence level.

Population pharmacokinetics of busulfan in pediatric and young adult patients undergoing hematopoietic cell transplant: a model-based dosing algorithm for personalized therapy and implementation into routine clinical use.

PubMed

Long-Boyle, Janel R; Savic, Rada; Yan, Shirley; Bartelink, Imke; Musick, Lisa; French, Deborah; Law, Jason; Horn, Biljana; Cowan, Morton J; Dvorak, Christopher C

2015-04-01

Population pharmacokinetic (PK) studies of busulfan in children have shown that individualized model-based algorithms provide improved targeted busulfan therapy when compared with conventional dose guidelines. The adoption of population PK models into routine clinical practice has been hampered by the tendency of pharmacologists to develop complex models too impractical for clinicians to use. The authors aimed to develop a population PK model for busulfan in children that can reliably achieve therapeutic exposure (concentration at steady state) and implement a simple model-based tool for the initial dosing of busulfan in children undergoing hematopoietic cell transplantation. Model development was conducted using retrospective data available in 90 pediatric and young adult patients who had undergone hematopoietic cell transplantation with busulfan conditioning. Busulfan drug levels and potential covariates influencing drug exposure were analyzed using the nonlinear mixed effects modeling software, NONMEM. The final population PK model was implemented into a clinician-friendly Microsoft Excel-based tool and used to recommend initial doses of busulfan in a group of 21 pediatric patients prospectively dosed based on the population PK model. Modeling of busulfan time-concentration data indicates that busulfan clearance displays nonlinearity in children, decreasing up to approximately 20% between the concentrations of 250-2000 ng/mL. Important patient-specific covariates found to significantly impact busulfan clearance were actual body weight and age. The percentage of individuals achieving a therapeutic concentration at steady state was significantly higher in subjects receiving initial doses based on the population PK model (81%) than in historical controls dosed on conventional guidelines (52%) (P = 0.02). When compared with the conventional dosing guidelines, the model-based algorithm demonstrates significant improvement for providing targeted busulfan therapy in children and young adults.

A multiobjective response surface approach for improved water quality planning in lakes and reservoirs

NASA Astrophysics Data System (ADS)

Castelletti, A.; Pianosi, F.; Soncini-Sessa, R.; Antenucci, J. P.

2010-06-01

Improved data collection techniques as well as increasing computing power are opening up new opportunities for the development of sophisticated models that can accurately reproduce hydrodynamic and biochemical conditions of water bodies. While increasing model complexity is considered a virtue for scientific purposes, it is a definite disadvantage for management (engineering) purposes, as it limits the model applicability to what-if analysis over a few, a priori defined interventions. In the recent past, this has become a significant limitation, particularly considering recent advances in water quality rehabilitation technologies (e.g., mixers or oxygenators) for which many design parameters have to be decided. In this paper, a novel approach toward integrating science-oriented and engineering-oriented models and improving water quality planning is presented. It is based on the use of a few appropriately designed simulations of a complex process-based model to iteratively identify the multidimensional function (response surface) that maps the rehabilitation interventions into the objective function. On the basis of the response surface (RS), a greater number of interventions can be quickly evaluated and the corresponding Pareto front can be approximated. Interesting points on the front are then selected and the corresponding interventions are simulated using the original process-based model, thus obtaining new decision-objective samples to refine the RS approximation. The approach is demonstrated in Googong Reservoir (Australia), which is periodically affected by high concentrations of manganese and cyanobacteria. Results indicate that significant improvements could be observed by simply changing the location of the two mixers installed in 2007. Furthermore, it also suggests the best location for an additional pair of mixers.

The impact of equilibrating hemispheric albedos on tropical performance in the HadGEM2-ES coupled climate model

DOE PAGES

Haywood, Jim M.; Jones, Andy; Dunstone, Nick; ...

2016-01-14

Despite the fact that the southern hemisphere contains a far greater proportion of dark ocean than the northern hemisphere, the total amount of sunlight reflected from the hemispheres is equal. However, the majority of climate models do not adequately represent this equivalence. Here we examine the impact of equilibrating hemispheric albedos by various idealised methods in a comprehensive coupled climate model and find significant improvements in what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases almost vanish over all continental land areas, the penetration of monsoon rainfall across the Sahel and the west African monsoon “jump”more » become well represented, and indicators of hurricane frequency are significantly improved. The results appear not to be model specific, implying that hemispheric albedo equivalence may provide a fundamental constraint for climate models that must be satisfied if the dynamics driving these processes, in particular the strength of the Hadley cell, are to be adequately represented. Cross-equatorial energy transport is implicated as a crucial component that must be accurately modelled in coupled general circulation models. The results also suggest that the commonly used practice of prescribing sea-surface temperatures in models provides a less accurate represention of precipitation than constraining the hemispheric albedos.« less

Epoxide pathways improve model predictions of isoprene markers and reveal key role of acidity in aerosol formation

EPA Science Inventory

Isoprene significantly contributes to organic aerosol in the southeastern United States where biogenic hydrocarbons mix with anthropogenic emissions. In this work, the Community Multiscale Air Quality model is updated to predict isoprene aerosol from epoxides produced under both ...

Computer-Based Enhancements for the Improvement of Learning.

ERIC Educational Resources Information Center

Tennyson, Robert D.

The third of four symposium papers argues that, if instructional methods are to improve learning, they must have two aspects: a direct trace to a specific learning process, and empirical support that demonstrates their significance. Focusing on the tracing process, the paper presents an information processing model of learning that can be used by…

Next Generation Waveform Based Three-Dimensional Models and Metrics to Improve Nuclear Explosion Monitoring in the Middle East (Postprint)

DTIC Science & Technology

2011-12-30

improvements also significantly increase anomaly strength while sharpening the anomaly edges to create stronger and more pronounced tectonic structures. The...continental deformation and crustal thickening is occurring, the wave speeds are substantially slower. This Asian north-to-south, fast-to-slow wave speed

A Caveat Note on Tuning in the Development of Coupled Climate Models

NASA Astrophysics Data System (ADS)

Dommenget, Dietmar; Rezny, Michael

2018-01-01

State-of-the-art coupled general circulation models (CGCMs) have substantial errors in their simulations of climate. In particular, these errors can lead to large uncertainties in the simulated climate response (both globally and regionally) to a doubling of CO2. Currently, tuning of the parameterization schemes in CGCMs is a significant part of the developed. It is not clear whether such tuning actually improves models. The tuning process is (in general) neither documented, nor reproducible. Alternative methods such as flux correcting are not used nor is it clear if such methods would perform better. In this study, ensembles of perturbed physics experiments are performed with the Globally Resolved Energy Balance (GREB) model to test the impact of tuning. The work illustrates that tuning has, in average, limited skill given the complexity of the system, the limited computing resources, and the limited observations to optimize parameters. While tuning may improve model performance (such as reproducing observed past climate), it will not get closer to the "true" physics nor will it significantly improve future climate change projections. Tuning will introduce artificial compensating error interactions between submodels that will hamper further model development. In turn, flux corrections do perform well in most, but not all aspects. A main advantage of flux correction is that it is much cheaper, simpler, more transparent, and it does not introduce artificial error interactions between submodels. These GREB model experiments should be considered as a pilot study to motivate further CGCM studies that address the issues of model tuning.

Treatment with docosahexaenoic acid after hypoxia–ischemia improves forepaw placing in a rat model of perinatal hypoxia-ischemia

PubMed Central

Berman, Deborah R; Liu, YiQing; Barks, John; Mozurkewich, Ellen

2010-01-01

Objective Docosahexaenoic acid (DHA) is a dietary fatty acid with neuroprotective properties. We hypothesized that DHA treatment after hypoxia-ischemia (HI) would improve function and reduce brain volume loss in a perinatal rat model. Study design Seven-day-old Wistar rat pups from 7 litters (N=84) underwent right carotid ligation, followed by 8% O2 for 90 minutes. Fifteen minutes after HI, pups were divided into 3 treatment groups (intraperitoneal injections of DHA 1, 2.5 or 5 mg/kg) and 2 control groups (25% albumin or saline). At 14 days, rats underwent vibrissae-stimulated forepaw placing testing, and bilateral regional volumes were calculated for cortex, striatum, hippocampus, and hemisphere. Results Post HI treatment with DHA significantly improved vibrissae forepaw placing (complete responses: 8.5±2 treatment vs. 7.4±2 controls; normal=10; p = 0.032, t-test). Post injury DHA treatment did not attenuate brain volume loss in any region. Conclusion Post-hypoxia-ischemia DHA treatment significantly improves functional outcome. PMID:20691409

Iron overload cardiomyopathy: from diagnosis to management.

PubMed

Díez-López, Carles; Comín-Colet, Josep; González-Costello, José

2018-05-01

Iron overload cardiomyopathy (IOC) is an important predictor of prognosis in a significant number of patients with hereditary hemochromatosis and hematologic diseases. Its prevalence is increasing because of improved treatment strategies, which significantly improve life expectancy. We will review diagnosis, treatment, and recent findings in the field. The development of preclinical translational disease models during the last years have helped our understanding of specific disease pathophysiological pathways that might eventually change the outcomes of these patients. IOC is an overlooked disease because of the progressive silent disease pattern and the lack of physicians' expertise. It mainly affects patients with hemochromatosis and hematologic diseases and its prevalence is expected to increase with the improvement in life expectancy of hematologic disorders. Early diagnosis of IOC in patients at risk by means of biochemical parameters and cardiac imaging can lead to early treatment and improved prognosis. The mainstay of treatment of IOC is conventional heart failure treatment, combined with phlebotomies or iron chelation in the context of anemia. The development of preclinical models has provided a comprehensive look into specific pathophysiological pathways with potential treatment strategies that must be sustained by future randomized trials.

Electronic and mechanical improvement of the receiving terminal of a free-space microwave power transmission system

NASA Technical Reports Server (NTRS)

Brown, W. C.

1977-01-01

Significant advancements were made in a number of areas: improved efficiency of basic receiving element at low power density levels, improved resolution and confidence in efficiency measurements mathematical modelling and computer simulation of the receiving element and the design, construction, and testing of an environmentally protected two-plane construction suitable for low cost, highly automated construction of large receiving arrays.

Efficacy of a Process Improvement Intervention on Delivery of HIV Services to Offenders: A Multisite Trial

PubMed Central

Shafer, Michael S.; Dembo, Richard; del Mar Vega-Debién, Graciela; Pankow, Jennifer; Duvall, Jamieson L.; Belenko, Steven; Frisman, Linda K.; Visher, Christy A.; Pich, Michele; Patterson, Yvonne

2014-01-01

Objectives. We tested a modified Network for the Improvement of Addiction Treatment (NIATx) process improvement model to implement improved HIV services (prevention, testing, and linkage to treatment) for offenders under correctional supervision. Methods. As part of the Criminal Justice Drug Abuse Treatment Studies, Phase 2, the HIV Services and Treatment Implementation in Corrections study conducted 14 cluster-randomized trials in 2011 to 2013 at 9 US sites, where one correctional facility received training in HIV services and coaching in a modified NIATx model and the other received only HIV training. The outcome measure was the odds of successful delivery of an HIV service. Results. The results were significant at the .05 level, and the point estimate for the odds ratio was 2.14. Although overall the results were heterogeneous, the experiments that focused on implementing HIV prevention interventions had a 95% confidence interval that exceeded the no-difference point. Conclusions. Our results demonstrate that a modified NIATx process improvement model can effectively implement improved rates of delivery of some types of HIV services in correctional environments. PMID:25322311

Efficacy of a process improvement intervention on delivery of HIV services to offenders: a multisite trial.

PubMed

Pearson, Frank S; Shafer, Michael S; Dembo, Richard; Del Mar Vega-Debién, Graciela; Pankow, Jennifer; Duvall, Jamieson L; Belenko, Steven; Frisman, Linda K; Visher, Christy A; Pich, Michele; Patterson, Yvonne

2014-12-01

We tested a modified Network for the Improvement of Addiction Treatment (NIATx) process improvement model to implement improved HIV services (prevention, testing, and linkage to treatment) for offenders under correctional supervision. As part of the Criminal Justice Drug Abuse Treatment Studies, Phase 2, the HIV Services and Treatment Implementation in Corrections study conducted 14 cluster-randomized trials in 2011 to 2013 at 9 US sites, where one correctional facility received training in HIV services and coaching in a modified NIATx model and the other received only HIV training. The outcome measure was the odds of successful delivery of an HIV service. The results were significant at the .05 level, and the point estimate for the odds ratio was 2.14. Although overall the results were heterogeneous, the experiments that focused on implementing HIV prevention interventions had a 95% confidence interval that exceeded the no-difference point. Our results demonstrate that a modified NIATx process improvement model can effectively implement improved rates of delivery of some types of HIV services in correctional environments.

Developing and Testing a Model to Predict Outcomes of Organizational Change

PubMed Central

Gustafson, David H; Sainfort, François; Eichler, Mary; Adams, Laura; Bisognano, Maureen; Steudel, Harold

2003-01-01

Objective To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. PMID:12785571

Social Cognitive Constructs Did Not Mediate the BEAT Cancer Intervention Effects on Objective Physical Activity Behavior Based on Multivariable Path Analysis.

PubMed

Rogers, Laura Q; Courneya, Kerry S; Anton, Phillip M; Hopkins-Price, Patricia; Verhulst, Steven; Robbs, Randall S; Vicari, Sandra K; McAuley, Edward

2017-04-01

Most breast cancer survivors do not meet physical activity recommendations. Understanding mediators of physical activity behavior change can improve interventions designed to increase physical activity in this at-risk population. Study aims were to determine the 3-month Better Exercise Adherence after Treatment for Cancer (BEAT Cancer) behavior change intervention effects on social cognitive theory constructs and the mediating role of any changes on the increase in accelerometer-measured physical activity previously reported. Post-treatment breast cancer survivors (N = 222) were randomized to BEAT Cancer or usual care. Assessments occurred at baseline, 3 months (M3), and 6 months (M6). Adjusted linear mixed model analysis of variance determined intervention effects on walking self-efficacy, outcome expectations, goal setting, and perceived barrier interference at M3. Path analysis determined mediation of intervention effects on physical activity at M6 by changes in social cognitive constructs during the intervention (i.e., baseline to M3). BEAT Cancer significantly improved self-efficacy, goals, negative outcome expectations, and barriers. Total path analysis model explained 24 % of the variance in M6 physical activity. There were significant paths from randomized intervention group to self-efficacy (β = 0.15, p < .05) and barriers (β = -0.22, p < .01). Barriers demonstrated a borderline significant association with M6 physical activity (β = -0.24, p = .05). No statistically significant indirect effects were found. Although BEAT Cancer significantly improved social cognitive constructs, no significant indirect effects on physical activity improvements 3 months post-intervention were observed (NCT00929617).

Human Umbilical Cord-Derived Mesenchymal Stromal Cells Improve Left Ventricular Function, Perfusion, and Remodeling in a Porcine Model of Chronic Myocardial Ischemia

PubMed Central

Liu, Chuan-Bin; Huang, He; Sun, Ping; Ma, Shi-Ze; Liu, An-Heng; Xue, Jian; Fu, Jin-Hui; Liang, Yu-Qian; Liu, Bing; Wu, Dong-Ying

2016-01-01

Stem cell therapy has emerged as a new strategy for treatment of ischemic heart disease. Although umbilical cord-derived mesenchymal stromal cells (UC-MSCs) have been used preferentially in the acute ischemia model, data for the chronic ischemia model are lacking. In this study, we investigated the effect of UC-MSCs originated from Wharton’s jelly in the treatment of chronic myocardial ischemia in a porcine model induced by ameroid constrictor. Four weeks after ameroid constrictor placement, the surviving animals were divided randomly into two groups to undergo saline injection (n = 6) or UC-MSC transplantation (n = 6) through the left main coronary artery. Two additional intravenous administrations of UC-MSCs were performed in the following 2 weeks to enhance therapeutic effect. Cardiac function and perfusion were examined just before and at 4 weeks after intracoronary transplantation. The results showed that pigs with UC-MSC transplantation exhibited significantly greater left ventricular ejection fraction compared with control animals (61.3% ± 1.3% vs. 50.3% ± 2.0%, p < .05). The systolic thickening fraction in the infarcted left ventricular wall was also improved (41.2% ± 3.3% vs. 46.2% ± 2.3%, p < .01). Additionally, the administration of UC-MSCs promoted collateral development and myocardial perfusion. The indices of fibrosis and apoptosis were also significantly reduced. Immunofluorescence staining showed clusters of CM-DiI-labeled cells in the border zone, some of which expressed von Willebrand factor. These results suggest that UC-MSC treatment improves left ventricular function, perfusion, and remodeling in a porcine model with chronic myocardial ischemia. Significance Ischemic heart disease is the leading cause of death worldwide. Many patients with chronic myocardial ischemia are not suitable for surgery and have no effective drug treatment; they are called “no-option” patients. This study finds that umbilical cord-derived mesenchymal stromal cells transplanted by intracoronary delivery combined with two intravenous administrations was safe and could significantly improve left ventricular function, perfusion, and remodeling in a large-animal model of chronic myocardial ischemia, which provides a new choice for the no-option patients. In addition, this study used clinical-grade mesenchymal stem cells with delivery and assessment methods commonly used clinically to facilitate further clinical transformation. PMID:27334487

Placental Mesenchymal Stromal Cells Rescue Ambulation in Ovine Myelomeningocele

PubMed Central

Brown, Erin G.; Lankford, Lee; Keller, Benjamin A.; Pivetti, Christopher D.; Sitkin, Nicole A.; Beattie, Michael S.; Bresnahan, Jacqueline C.; Farmer, Diana L.

2015-01-01

Myelomeningocele (MMC)—commonly known as spina bifida—is a congenital birth defect that causes lifelong paralysis, incontinence, musculoskeletal deformities, and severe cognitive disabilities. The recent landmark Management of Myelomeningocele Study (MOMS) demonstrated for the first time in humans that in utero surgical repair of the MMC defect improves lower limb motor function, suggesting a capacity for improved neurologic outcomes in this disorder. However, functional recovery was incomplete, and 58% of the treated children were unable to walk independently at 30 months of age. In the present study, we demonstrate that using early gestation human placenta-derived mesenchymal stromal cells (PMSCs) to augment in utero repair of MMC results in significant and consistent improvement in neurologic function at birth in the rigorous fetal ovine model of MMC. In vitro, human PMSCs express characteristic MSC markers and trilineage differentiation potential. Protein array assays and enzyme-linked immunosorbent assay show that PMSCs secrete a variety of immunomodulatory and angiogenic cytokines. Compared with adult bone marrow MSCs, PMSCs secrete significantly higher levels of brain-derived neurotrophic factor and hepatocyte growth factor, both of which have known neuroprotective capabilities. In vivo, functional and histopathologic analysis demonstrated that human PMSCs mediate a significant, clinically relevant improvement in motor function in MMC lambs and increase the preservation of large neurons within the spinal cord. These preclinical results in the well-established fetal ovine model of MMC provide promising early support for translating in utero stem cell therapy for MMC into clinical application for patients. Significance This study presents placenta-derived mesenchymal stromal cell (PMSC) treatment as a potential therapy for myelomeningocele (MMC). Application of PMSCs can augment current in utero surgical repair in the well-established and rigorously applied fetal lamb model of MMC. Treatment with human PMSCs significantly and dramatically improved neurologic function and preserved spinal cord neuron density in experimental animals. Sixty-seven percent of the PMSC-treated lambs were able to ambulate independently, with two exhibiting no motor deficits whatsoever. In contrast, none of the lambs treated with the vehicle alone were capable of ambulation. The locomotor rescue demonstrated in PMSC-treated lambs indicates great promise for future clinical trials to improve paralysis in children afflicted with MMC. PMID:25911465

A time dependent mixing model to close PDF equations for transport in heterogeneous aquifers

NASA Astrophysics Data System (ADS)

Schüler, L.; Suciu, N.; Knabner, P.; Attinger, S.

2016-10-01

Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the concentration variance, used in moment methods. The mixing model, describing the transport of the PDF in concentration space, is essential for both methods. Finding a satisfactory mixing model is still an open question and due to the rather elaborate PDF methods, a difficult undertaking. Both the PDF equation and the concentration variance equation depend on the same mixing model. This connection is used to find and test an improved mixing model for the much easier to handle concentration variance. Subsequently, this mixing model is transferred to the PDF equation and tested. The newly proposed mixing model yields significantly improved results for both variance modelling and PDF modelling.

Stochastic models for atomic clocks

NASA Technical Reports Server (NTRS)

Barnes, J. A.; Jones, R. H.; Tryon, P. V.; Allan, D. W.

1983-01-01

For the atomic clocks used in the National Bureau of Standards Time Scales, an adequate model is the superposition of white FM, random walk FM, and linear frequency drift for times longer than about one minute. The model was tested on several clocks using maximum likelihood techniques for parameter estimation and the residuals were acceptably random. Conventional diagnostics indicate that additional model elements contribute no significant improvement to the model even at the expense of the added model complexity.

The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

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

Finley, Cathy

2014-04-30

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements inmore » wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.« less

Network model of project "Lean Production"

NASA Astrophysics Data System (ADS)

Khisamova, E. D.

2018-05-01

Economical production implies primarily new approaches to culture of management and organization of production and offers a set of tools and techniques that allows reducing losses significantly and making the process cheaper and faster. Economical production tools are simple solutions that allow one to see opportunities for improvement of all aspects of the business, to reduce losses significantly, to constantly improve the whole spectrum of business processes, to increase significantly the transparency and manageability of the organization, to take advantage of the potential of each employee of the company, to increase competitiveness, and to obtain significant economic benefits without making large financial expenditures. Each of economical production tools solves a specific part of the problems, and only application of their combination will allow one to solve the problem or minimize it to acceptable values. The research of the governance process project "Lean Production" permitted studying the methods and tools of lean production and developing measures for their improvement.

The importance of topography controlled sub-grid process heterogeneity in distributed hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, R. C.; Samaniego, L.; Mai, J.; Kumar, R.; Thober, S.; Zink, M.; Schäfer, D.; Savenije, H. H. G.; Hrachowitz, M.

2015-12-01

Heterogeneity of landscape features like terrain, soil, and vegetation properties affect the partitioning of water and energy. However, it remains unclear to which extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated in the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge based model constraints reduces model uncertainty; and (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both, the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as overall measure for model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 % respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. Besides, it was shown that suitable semi-quantitative prior constraints in combination with the transfer function based regularization approach of mHM, can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Samaniego, Luis; Mai, Juliane; Kumar, Rohini; Thober, Stephan; Zink, Matthias; Schäfer, David; Savenije, Hubert H. G.; Hrachowitz, Markus

2016-03-01

Heterogeneity of landscape features like terrain, soil, and vegetation properties affects the partitioning of water and energy. However, it remains unclear to what extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated into the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge-based model constraints reduces model uncertainty, and whether (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge-based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as an overall measure of model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 %, respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. In addition, it was shown that suitable semi-quantitative prior constraints in combination with the transfer-function-based regularization approach of mHM can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

Resveratrol Improves Cell Cycle Arrest in Chronic Prostatitis Rats, by C-kit/SCF Suppression.

PubMed

He, Yi; Zeng, Huizhi; Yu, Yang; Zhang, Jiashu; Zeng, Xiaona; Gong, Fengtao; Liu, Qi; Yang, Bo

2017-08-01

Chronic prostatitis (CP) with complex pathogenesis is difficult for treatment. c-kit has been associated with the control of cell proliferation of prostate cells. This study aims to evaluate the role of resveratrol, an activator of Sirt1, in regulating the expression of c-kit in CP and investigate the consequent effects on cell cycle. Rat model of CP was established through subcutaneous injections of diphtheria-pertussis-tetanus vaccine and subsequently treated with resveratrol. Hematoxylin and eosin staining was performed to identify the histopathological changes in prostates. Western blotting and immunohistochemical staining examined the expression level of c-kit, stem cell factor (SCF), Sirt1, and cell cycle-associated proteins. The model group exhibited severe diffuse chronic inflammation, characterized by leukocyte infiltration and papillary frond protrusion into the gland cavities, and a notable increase in prostatic epithelial height. Gland lumen diameter was also significantly smaller; the activity of c-kit/SCF in the CP rats was increased significantly compared to the control group. Meanwhile, the cell cycle proteins are dysregulated significantly in CP rats. Resveratrol treatment significantly improved these factors by Sirt1 activation. Dysregulation of cell cycle was involved in the pathological processes of CP, which was improved after resveratrol treatment by the downregulation of c-kit/SCF by activating Sirt1.

A pilot study of parent education intervention improves early childhood development among toddlers with sickle cell disease.

PubMed

Fields, Melanie E; Hoyt-Drazen, Catherine; Abel, Regina; Rodeghier, Mark J; Yarboi, Janet M; Compas, Bruce E; King, Allison A

2016-12-01

Young children with sickle cell disease (SCD) are at risk for cognitive delay. In addition to biologic risk factors associated with SCD, environmental factors contribute to cognitive dysfunction within this cohort. We completed a single-arm, prospective cohort study. Children with SCD between the ages of 3 and 36 months and their caregivers were followed between October 2010 and December 2013. The aim was to describe the role of a home visitation model, the home environment, and socioeconomic status in the development of young children with SCD. Primary outcome measures were the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III) and the Home Observation for Measurement of the Environment (HOME). We hypothesized that the home visitation model, Parents as Teachers ® (PAT), would encourage positive parent-child interactions and improve cognitive outcomes. Thirty-five participants had at least two PAT visits and BSID-III assessments. Mean scores within all five subtests of the BSID-III improved between enrollment and exit, with significant changes within cognitive (P = 0.016) and expressive language (EL) domains (P = 0.002). Multivariate modeling found the HOME score associated with the exit results of the cognitive domain. We report longitudinal results of the first home visitation program within the early childhood SCD population and show significant improvement in cognitive and EL development. Additionally, home environment was a significant predictor of cognitive development. Randomized controlled trials to test the impact of interventions targeting the home environment are warranted for this vulnerable population. © 2016 Wiley Periodicals, Inc.

A stepwise under-prepared osteotomy technique improves primary stability in shallow-placed implants: a preliminary study for simultaneous vertical ridge augmentation.

PubMed

Ueno, Daisuke; Nakamura, Kei; Kojima, Kousuke; Toyoshima, Takeshi; Tanaka, Hideaki; Ueda, Kazuhiko; Koyano, Kiyoshi; Kodama, Toshiro

2018-04-01

Simultaneous vertical ridge augmentation (VRA) can reduce treatment procedures and surgery time, but the concomitant reduction in primary stability (PS) of a shallow-placed implant imparts risk to its prognosis. Although several studies have reported improvements in PS, there is little information from any simultaneous VRA model. This study aimed to evaluate whether tapered implants with stepwise under-prepared osteotomy could improve the PS of shallow-placed implants in an in vitro model of simultaneous VRA. Tapered implants (Straumann ® Bone Level Tapered implant; BLT) and hybrid implants (Straumann ® Bone Level implant; BL) were investigated in this study. A total of 80 osteotomies of different depths (4, 6, 8, 10 mm) were created in rigid polyurethane foam blocks, and each BLT and BL was inserted by either standard (BLT-S, BL-S) or a stepwise under-prepared (BLT-U, BL-U) osteotomy protocol. The PS was evaluated by measuring maximum insertion torque (IT), implant stability quotient (ISQ), and removal torque (RT). The significance level was set at P < 0.05. There were no significant differences in IT, ISQ or RT when comparing BLT-S and BL-S or BLT-U and BL-U at placement depths of 6 and 8 mm. When comparison was made between osteotomy protocols, IT was significantly greater in BLT-U than in BLT-S at all placement depths. A stepwise under-prepared osteotomy protocol improves initial stability of a tapered implant even in a shallow-placed implant model. BLT-U could be a useful protocol for simultaneous VRA.

Patient flow improvement for an ophthalmic specialist outpatient clinic with aid of discrete event simulation and design of experiment.

PubMed

Pan, Chong; Zhang, Dali; Kon, Audrey Wan Mei; Wai, Charity Sue Lea; Ang, Woo Boon

2015-06-01

Continuous improvement in process efficiency for specialist outpatient clinic (SOC) systems is increasingly being demanded due to the growth of the patient population in Singapore. In this paper, we propose a discrete event simulation (DES) model to represent the patient and information flow in an ophthalmic SOC system in the Singapore National Eye Centre (SNEC). Different improvement strategies to reduce the turnaround time for patients in the SOC were proposed and evaluated with the aid of the DES model and the Design of Experiment (DOE). Two strategies for better patient appointment scheduling and one strategy for dilation-free examination are estimated to have a significant impact on turnaround time for patients. One of the improvement strategies has been implemented in the actual SOC system in the SNEC with promising improvement reported.

Chemical data assimilation of geostationary aerosol optical depth and PM surface observations on regional aerosol modeling over the Korean Peninsula during KORUS-AQ campaign

NASA Astrophysics Data System (ADS)

Jung, J.; Choi, Y.; Souri, A.; Jeon, W.

2017-12-01

Particle matter(PM) has played a significantly deleterious role in affecting human health and climate. Recently, continuous high concentrations of PM in Korea attracted public attention to this critical issue, and the Korea-United States Air Quality Study(KORUS-AQ) campaign in 2016 was conducted to investigate the causes. For this study, we adjusted the initial conditions in the chemical transport model(CTM) to improve its performance over Korean Peninsula during KORUS-AQ period, using the campaign data to evaluate our model performance. We used the Optimal Interpolation(OI) approach and used hourly surface air quality measurement data from the Air Quality Monitoring Station(AQMS) by NIER and the aerosol optical depth(AOD) measured by a GOCI sensor from the geostationary orbit onboard the Communication Ocean and Meteorological Satellite(COMS). The AOD at 550nm has a 6km spatial resolution and broad coverage over East Asia. After assimilating the surface air quality observation data, the model accuracy significantly improved compared to base model result (without assimilation). It reported very high correlation value (0.98) and considerably decreased mean bias. Especially, it well captured some high peaks which was underpredicted by the base model. To assimilate satellite data, we applied AOD scaling factors to quantify each specie's contribution to total PM concentration and find-mode fraction(FMF) to define vertical distribution. Finally, the improvement showed fairly good agreement.

Probabilistic models of eukaryotic evolution: time for integration

PubMed Central

Lartillot, Nicolas

2015-01-01

In spite of substantial work and recent progress, a global and fully resolved picture of the macroevolutionary history of eukaryotes is still under construction. This concerns not only the phylogenetic relations among major groups, but also the general characteristics of the underlying macroevolutionary processes, including the patterns of gene family evolution associated with endosymbioses, as well as their impact on the sequence evolutionary process. All these questions raise formidable methodological challenges, calling for a more powerful statistical paradigm. In this direction, model-based probabilistic approaches have played an increasingly important role. In particular, improved models of sequence evolution accounting for heterogeneities across sites and across lineages have led to significant, although insufficient, improvement in phylogenetic accuracy. More recently, one main trend has been to move away from simple parametric models and stepwise approaches, towards integrative models explicitly considering the intricate interplay between multiple levels of macroevolutionary processes. Such integrative models are in their infancy, and their application to the phylogeny of eukaryotes still requires substantial improvement of the underlying models, as well as additional computational developments. PMID:26323768

A pilot study of modified cognitive-behavioral therapy for childhood traumatic grief (CBT-CTG).

PubMed

Cohen, Judith A; Mannarino, Anthony P; Staron, Virginia R

2006-12-01

This pilot study evaluated outcomes for a modified 12-session protocol of cognitive-behavioral therapy for childhood traumatic grief (CBT-CTG) conducted between March 2004 and October 2005. CTG is an emerging condition characterized by a combination of posttraumatic stress and unresolved grief symptoms. This two-module treatment model consisting of sequential trauma- and grief-focused components was shortened from a previously presented 16-session protocol. Thirty-nine children ages 6 to 17 years old with CTG and their parents received the modified 12-session protocol of CBT-CTG. CTG and posttraumatic stress disorder (PTSD) symptoms were assessed at pretreatment, after the trauma-focused module, and after the grief-focused module (at posttreatment). Child depression, anxiety, and behavioral symptoms, as well as parental depression and PTSD symptoms, were assessed at pre- and posttreatment. Children reported significant improvement in CTG, PTSD, depression, and anxiety, and parents reported significant improvement in children's PTSD, internalizing and total behavior problems, and their personal PTSD symptoms. Although PTSD significantly improved only during the trauma-focused module of treatment, CTG improved significantly during both trauma- and grief-focused modules of treatment. Child satisfaction and parent satisfaction for this treatment protocol were also high. These findings suggest that the shortened CBT-CTG protocol, which is similar in the number of sessions to what many community child bereavement programs offer, may be acceptable and efficacious for this population. The CBT-CTG model requires further evaluation in randomized, controlled treatment trials.

Improvement of Systematic Bias of mean state and the intraseasonal variability of CFSv2 through superparameterization and revised cloud-convection-radiation parameterization

NASA Astrophysics Data System (ADS)

Mukhopadhyay, P.; Phani Murali Krishna, R.; Goswami, Bidyut B.; Abhik, S.; Ganai, Malay; Mahakur, M.; Khairoutdinov, Marat; Dudhia, Jimmy

2016-05-01

Inspite of significant improvement in numerical model physics, resolution and numerics, the general circulation models (GCMs) find it difficult to simulate realistic seasonal and intraseasonal variabilities over global tropics and particularly over Indian summer monsoon (ISM) region. The bias is mainly attributed to the improper representation of physical processes. Among all the processes, the cloud and convective processes appear to play a major role in modulating model bias. In recent times, NCEP CFSv2 model is being adopted under Monsoon Mission for dynamical monsoon forecast over Indian region. The analyses of climate free run of CFSv2 in two resolutions namely at T126 and T382, show largely similar bias in simulating seasonal rainfall, in capturing the intraseasonal variability at different scales over the global tropics and also in capturing tropical waves. Thus, the biases of CFSv2 indicate a deficiency in model's parameterization of cloud and convective processes. Keeping this in background and also for the need to improve the model fidelity, two approaches have been adopted. Firstly, in the superparameterization, 32 cloud resolving models each with a horizontal resolution of 4 km are embedded in each GCM (CFSv2) grid and the conventional sub-grid scale convective parameterization is deactivated. This is done to demonstrate the role of resolving cloud processes which otherwise remain unresolved. The superparameterized CFSv2 (SP-CFS) is developed on a coarser version T62. The model is integrated for six and half years in climate free run mode being initialised from 16 May 2008. The analyses reveal that SP-CFS simulates a significantly improved mean state as compared to default CFS. The systematic bias of lesser rainfall over Indian land mass, colder troposphere has substantially been improved. Most importantly the convectively coupled equatorial waves and the eastward propagating MJO has been found to be simulated with more fidelity in SP-CFS. The reason of such betterment in model mean state has been found to be due to the systematic improvement in moisture field, temperature profile and moist instability. The model also has better simulated the cloud and rainfall relation. This initiative demonstrates the role of cloud processes on the mean state of coupled GCM. As the superparameterization approach is computationally expensive, so in another approach, the conventional Simplified Arakawa Schubert (SAS) scheme is replaced by a revised SAS scheme (RSAS) and also the old and simplified cloud scheme of Zhao-Karr (1997) has been replaced by WSM6 in CFSV2 (hereafter CFS-CR). The primary objective of such modifications is to improve the distribution of convective rain in the model by using RSAS and the grid-scale or the large scale nonconvective rain by WSM6. The WSM6 computes the tendency of six class (water vapour, cloud water, ice, snow, graupel, rain water) hydrometeors at each of the model grid and contributes in the low, middle and high cloud fraction. By incorporating WSM6, for the first time in a global climate model, we are able to show a reasonable simulation of cloud ice and cloud liquid water distribution vertically and spatially as compared to Cloudsat observations. The CFS-CR has also showed improvement in simulating annual rainfall cycle and intraseasonal variability over the ISM region. These improvements in CFS-CR are likely to be associated with improvement of the convective and stratiform rainfall distribution in the model. These initiatives clearly address a long standing issue of resolving the cloud processes in climate model and demonstrate that the improved cloud and convective process paramterizations can eventually reduce the systematic bias and improve the model fidelity.

On the combinatorics of sparsification.

PubMed

Huang, Fenix Wd; Reidys, Christian M

2012-10-22

We study the sparsification of dynamic programming based on folding algorithms of RNA structures. Sparsification is a method that improves significantly the computation of minimum free energy (mfe) RNA structures. We provide a quantitative analysis of the sparsification of a particular decomposition rule, Λ∗. This rule splits an interval of RNA secondary and pseudoknot structures of fixed topological genus. Key for quantifying sparsifications is the size of the so called candidate sets. Here we assume mfe-structures to be specifically distributed (see Assumption 1) within arbitrary and irreducible RNA secondary and pseudoknot structures of fixed topological genus. We then present a combinatorial framework which allows by means of probabilities of irreducible sub-structures to obtain the expectation of the Λ∗-candidate set w.r.t. a uniformly random input sequence. We compute these expectations for arc-based energy models via energy-filtered generating functions (GF) in case of RNA secondary structures as well as RNA pseudoknot structures. Furthermore, for RNA secondary structures we also analyze a simplified loop-based energy model. Our combinatorial analysis is then compared to the expected number of Λ∗-candidates obtained from the folding mfe-structures. In case of the mfe-folding of RNA secondary structures with a simplified loop-based energy model our results imply that sparsification provides a significant, constant improvement of 91% (theory) to be compared to an 96% (experimental, simplified arc-based model) reduction. However, we do not observe a linear factor improvement. Finally, in case of the "full" loop-energy model we can report a reduction of 98% (experiment). Sparsification was initially attributed a linear factor improvement. This conclusion was based on the so called polymer-zeta property, which stems from interpreting polymer chains as self-avoiding walks. Subsequent findings however reveal that the O(n) improvement is not correct. The combinatorial analysis presented here shows that, assuming a specific distribution (see Assumption 1), of mfe-structures within irreducible and arbitrary structures, the expected number of Λ∗-candidates is Θ(n2). However, the constant reduction is quite significant, being in the range of 96%. We furthermore show an analogous result for the sparsification of the Λ∗-decomposition rule for RNA pseudoknotted structures of genus one. Finally we observe that the effect of sparsification is sensitive to the employed energy model.

Effects of pediatric asthma care coordination in underserved communities on parent perceptions of care and asthma-management confidence.

PubMed

Janevic, Mary R; Baptist, Alan P; Bryant-Stephens, Tyra; Lara, Marielena; Persky, Victoria; Ramos-Valencia, Gilberto; Uyeda, Kimberly; Hazan, Rebecca; Garrity, Ashley; Malveaux, Floyd J

2017-06-01

Disparities by race and socioeconomic status persist in pediatric asthma morbidity, mortality, and treatment. Improving parent/provider communication and parents' asthma-management confidence may result in better asthma control in vulnerable populations. The Merck Childhood Asthma Network, Inc. funded an initiative to implement medical-social care coordination to improve asthma outcomes at sites in four low-income, urban communities (Los Angeles, CA; Philadelphia, PA; Chicago, IL; and San Juan, PR.) As part of a cross-site evaluation of this effort, pre- post-program changes in parents' reports of asthma care and management were assessed. Across sites, 805 parents or other caregivers responded to a baseline survey that was repeated one year later following their child's participation in care coordination. Parents' asthma-management confidence, as well as their perceptions of provider access, trust, and communication, were measured with Likert scales. Linear mixed models were used to assess improvement in these variables, across and within sites, adjusting for sociodemographics. Pooled across sites, the adjusted mean estimate for all outcomes showed a significant improvement (p <.05) from baseline to follow-up. Knowledge and Between-Provider Communication improved significantly (p <.05) within all four sites; Access improved significantly in Chicago, Philadelphia, and Puerto Rico; Trust improved significantly in Chicago, Los Angeles, and Philadelphia; and Patient-Provider Communication improved significantly in Philadelphia only. Pediatric asthma care coordination, as implemented variously in diverse settings, was associated with improvement in parents' perceptions of asthma care and self-reported asthma-management knowledge and confidence. This positive impact on parents may help sustain care coordination's impact on children.

Improved simulation of river water and groundwater exchange in an alluvial plain using the SWAT model

USDA-ARS?s Scientific Manuscript database

Hydrological interaction between surface and subsurface water systems has a significant impact on water quality, ecosystems and biogeochemistry cycling of both systems. Distributed models have been developed to simulate this function, but they require detailed spatial inputs and extensive computati...

Difficulties associated with predicting forage intake by grazing beef cows

USDA-ARS?s Scientific Manuscript database

The current National Research Council (NRC) model is based on a single equation that relates dry matter intake (DMI) to metabolic size and net energy density of the diet offered and was a significant improvement over previous models. However, observed DMI by grazing animals can be conceptualized by...

APPLICATION OF A MICROSCALE EMISSION FACTOR MODEL FOR PARTICULATE MATTER (MICROFACPM) TO CALCULATE VEHICLE GENERATED CONTRIBUTION PM 2.5 EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's (EPA) National Exposure Research Laboratory is developing improved methods for modeling the source through the air pathway to human exposure in significant microenvironments of exposure. As a part of this project, we develope...

Model-Driven Development for PDS4 Software and Services

NASA Astrophysics Data System (ADS)

Hughes, J. S.; Crichton, D. J.; Algermissen, S. S.; Cayanan, M. D.; Joyner, R. S.; Hardman, S. H.; Padams, J. H.

2018-04-01

PDS4 data product labels provide the information necessary for processing the referenced digital object. However, significantly more information is available in the PDS4 Information Model. This additional information is made available for use, by both software and services, to configure, promote resiliency, and improve interoperability.

Guidelines for Implementing NCHRP 1-37A M-E Design Procedures in Ohio : Volume 4 -- MEPDG Models Validation & Recalibration

DOT National Transportation Integrated Search

2009-11-01

The development of the Mechanistic-Empirical Pavement Design Guide (MEPDG) under National Cooperative Highway Research Program (NCHRP) projects 1-37A and 1-40D has significantly improved the ability of pavement designers to model and simulate the eff...

Improving the simulation of convective dust storms in regional-to-global models

EPA Science Inventory

Convective dust storms have significant impacts on atmospheric conditions and air quality and are a major source of dust uplift in summertime. However, regional-to-global models generally do not accurately simulate these storms, a limitation that can be attributed to (1) using a ...

Molecular modeling and redesign of alginate lyase from Pseudomonas aeruginosa for accelerating CRPA biofilm degradation.

PubMed

Cho, Hoon; Huang, Xiaoqin; Lan Piao, Yu; Eun Kim, Da; Yeon Lee, So; Jeong Yoon, Eun; Hee Park, So; Lee, Kyoung; Ho Jang, Chul; Zhan, Chang-Guo

2016-12-01

Administration of an efficient alginate lyase (AlgL) or AlgL mutant may be a promising therapeutic strategy for treatment of cystic fibrosis patients with Pseudomonas aeruginosa infections. Nevertheless, the catalytic activity of wild-type AlgL is not sufficiently high. It is highly desired to design and discover an AlgL mutant with significantly improved catalytic efficiency against alginate substrates. For the purpose of identifying an AlgL mutant with significantly improved catalytic activity, in this study, we first constructed and validated a structural model of AlgL interacting with substrate, providing a better understanding of the interactions between AlgL and its substrate. Based on the modeling insights, further enzyme redesign and experimental testing led to discovery of AlgL mutants, including the K197D/K321A mutant, with significantly improved catalytic activities against alginate and acetylated alginate in ciprofloxacin-resistant P. aeruginosa (CRPA) biofilms. Further anti-biofilm activity assays have confirmed that the K197D/K321A mutant with piperacillin/tazobactam is indeed effective in degrading the CRPA biofilms. Co-administration of the potent mutant AlgL and an antibiotic (such as a nebulizer) could be effective for therapeutic treatment of CRPA-infected patients with cystic fibrosis. Proteins 2016; 84:1875-1887. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Is the maturity of hospitals' quality improvement systems associated with measures of quality and patient safety?

PubMed Central

2011-01-01

Background Previous research addressed the development of a classification scheme for quality improvement systems in European hospitals. In this study we explore associations between the 'maturity' of the hospitals' quality improvement system and clinical outcomes. Methods The maturity classification scheme was developed based on survey results from 389 hospitals in eight European countries. We matched the hospitals from the Spanish sample (113 hospitals) with those hospitals participating in a nation-wide, voluntary hospital performance initiative. We then compared sample distributions and explored associations between the 'maturity' of the hospitals' quality improvement system and a range of composite outcomes measures, such as adjusted hospital-wide mortality, -readmission, -complication and -length of stay indices. Statistical analysis includes bivariate correlations for parametrically and non-parametrically distributed data, multiple robust regression models and bootstrapping techniques to obtain confidence-intervals for the correlation and regression estimates. Results Overall, 43 hospitals were included. Compared to the original sample of 113, this sample was characterized by a higher representation of university hospitals. Maturity of the quality improvement system was similar, although the matched sample showed less variability. Analysis of associations between the quality improvement system and hospital-wide outcomes suggests significant correlations for the indicator adjusted hospital complications, borderline significance for adjusted hospital readmissions and non-significance for the adjusted hospital mortality and length of stay indicators. These results are confirmed by the bootstrap estimates of the robust regression model after adjusting for hospital characteristics. Conclusions We assessed associations between hospitals' quality improvement systems and clinical outcomes. From this data it seems that having a more developed quality improvement system is associated with lower rates of adjusted hospital complications. A number of methodological and logistic hurdles remain to link hospital quality improvement systems to outcomes. Further research should aim at identifying the latent dimensions of quality improvement systems that predict quality and safety outcomes. Such research would add pertinent knowledge regarding the implementation of organizational strategies related with quality of care outcomes. PMID:22185479

Providing High-Quality Support Services to Home-Based Child Care: A Conceptual Model and Literature Review

ERIC Educational Resources Information Center

Bromer, Juliet; Korfmacher, Jon

2017-01-01

Research Findings: Home-based child care accounts for a significant proportion of nonparental child care arrangements for young children in the United States. Yet the early care and education field lacks clear models or pathways for how to improve quality in these settings. The conceptual model presented here articulates the components of…

Model Design for Military Advisors

DTIC Science & Technology

2013-05-02

needs of their counterpart. This paper explores one area that would significantly improve advising outcomes; using advising models to match the...more specific. This paper develops three dominate models for advisors; the Stoic Acquaintance, the General Manger, and the Entertainer which can...then outcomes related to the individual counterpart’s developmental needs will be more predictable and specific. This paper will focus only on

The necessary burden of involving stakeholders in agent-based modelling for education and decision-making

NASA Astrophysics Data System (ADS)

Bommel, P.; Bautista Solís, P.; Leclerc, G.

2016-12-01

We implemented a participatory process with water stakeholders for improving resilience to drought at watershed scale, and for reducing water pollution disputes in drought prone Northwestern Costa Rica. The purpose is to facilitate co-management in a rural watershed impacted by recurrent droughts related to ENSO. The process involved designing "ContaMiCuenca", a hybrid agent-based model where users can specify the decisions of their agents. We followed a Companion Modeling approach (www.commod.org) and organized 10 workshops that included research techniques such as participatory diagnostics, actor-resources-interaction and UML diagrams, multi-agents model design, and interactive simulation sessions. We collectively assessed the main water issues in the watershed, prioritized their importance, defined the objectives of the process, and pilot-tested ContaMiCuenca for environmental education with adults and children. Simulation sessions resulted in debates about the need to improve the model accuracy, arguably more relevant for decision-making. This helped identify sensible knowledge gaps in the groundwater pollution and aquifer dynamics that need to be addressed in order to improve our collective learning. Significant mismatches among participants expectations, objectives, and agendas considerably slowed down the participatory process. The main issue may originate in participants expecting technical solutions from a positivist science, as constantly promoted in the region by dole-out initiatives, which is incompatible with the constructivist stance of participatory modellers. This requires much closer interaction of community members with modellers, which may be hard to attain in the current research practice and institutional context. Nevertheless, overcoming these constraints is necessary for a true involvement of water stakeholders to achieve community-based decisions that facilitate integrated water management. Our findings provide significant guidance for improving the trans-generational engagement of stakeholders in participatory modeling processes in a context of limited technical skills and information, research expectative mismatches, and poor multi-stakeholder interaction for decision-making.

Assessments on GOCE-based Gravity Field Model Comparisons with Terrestrial Data Using Wavelet Decomposition and Spectral Enhancement Approaches

NASA Astrophysics Data System (ADS)

Erol, Serdar; Serkan Isık, Mustafa; Erol, Bihter

2016-04-01

The recent Earth gravity field satellite missions data lead significant improvement in Global Geopotential Models in terms of both accuracy and resolution. However the improvement in accuracy is not the same everywhere in the Earth and therefore quantifying the level of improvement locally is necessary using the independent data. The validations of the level-3 products from the gravity field satellite missions, independently from the estimation procedures of these products, are possible using various arbitrary data sets, as such the terrestrial gravity observations, astrogeodetic vertical deflections, GPS/leveling data, the stationary sea surface topography. Quantifying the quality of the gravity field functionals via recent products has significant importance for determination of the regional geoid modeling, base on the satellite and terrestrial data fusion with an optimal algorithm, beside the statistical reporting the improvement rates depending on spatial location. In the validations, the errors and the systematic differences between the data and varying spectral content of the compared signals should be considered in order to have comparable results. In this manner this study compares the performance of Wavelet decomposition and spectral enhancement techniques in validation of the GOCE/GRACE based Earth gravity field models using GPS/leveling and terrestrial gravity data in Turkey. The terrestrial validation data are filtered using Wavelet decomposition technique and the numerical results from varying levels of decomposition are compared with the results which are derived using the spectral enhancement approach with contribution of an ultra-high resolution Earth gravity field model. The tests include the GO-DIR-R5, GO-TIM-R5, GOCO05S, EIGEN-6C4 and EGM2008 global models. The conclusion discuss the superiority and drawbacks of both concepts as well as reporting the performance of tested gravity field models with an estimate of their contribution to modeling the geoid in Turkish territory.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Impact of single-point GPS integrated water vapor estimates on short-range WRF model forecasts over southern India

NASA Astrophysics Data System (ADS)

Kumar, Prashant; Gopalan, Kaushik; Shukla, Bipasha Paul; Shyam, Abhineet

2017-11-01

Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (November-December, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of ˜10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments.

An improved model for the Earth's gravity field

NASA Technical Reports Server (NTRS)

Tapley, B. D.; Shum, C. K.; Yuan, D. N.; Ries, J. C.; Schutz, B. E.

1989-01-01

An improved model for the Earth's gravity field, TEG-1, was determined using data sets from fourteen satellites, spanning the inclination ranges from 15 to 115 deg, and global surface gravity anomaly data. The satellite measurements include laser ranging data, Doppler range-rate data, and satellite-to-ocean radar altimeter data measurements, which include the direct height measurement and the differenced measurements at ground track crossings (crossover measurements). Also determined was another gravity field model, TEG-1S, which included all the data sets in TEG-1 with the exception of direct altimeter data. The effort has included an intense scrutiny of the gravity field solution methodology. The estimated parameters included geopotential coefficients complete to degree and order 50 with selected higher order coefficients, ocean and solid Earth tide parameters, Doppler tracking station coordinates and the quasi-stationary sea surface topography. Extensive error analysis and calibration of the formal covariance matrix indicate that the gravity field model is a significant improvement over previous models and can be used for general applications in geodesy.

Potential for Metabolomics-Based Markers of Exposure:Encouraging Evidence from Studies using Model Organisms

EPA Science Inventory

Genomic techniques (transcriptomics, proteomics, and metabolomics) have the potential to significantly improve the way chemical risk is managed in the 21st century. Indeed, a significant amount of research has been devoted to the use of these techniques to screen chemicals for h...

Evaluation of a Childhood Obesity Prevention Online Training Certificate Program for Community Family Educators.

PubMed

Eck, Kaitlyn; Alleman, Gayle Povis; Quick, Virginia; Martin-Biggers, Jennifer; Hongu, Nobuko; Byrd-Bredbenner, Carol

2016-12-01

Community family educators have the opportunity to incorporate childhood obesity prevention concepts in their programming with families of young children, but often lack formal health and nutrition education. The purpose of this feasibility study was to create an online training certificate program for community family educators and assess the program's effectiveness at improving participant's knowledge, attitudes, and intended and actual behaviors related to healthy lifestyles. Community family educators (n = 68) completed an online pretest, viewed 13 brief videos (8-15 min) focused on childhood obesity related topics and took mini-knowledge self-checks after each video followed by an online posttest. At posttest, paired t tests showed participants' childhood obesity prevention related knowledge (i.e., nutrition, physical activity, screen time and sleep) improved significantly (p < 0.001). Participants' attitudes toward parenting behaviors related to feeding practices, family meals, physical activity, screen time control and parent modeling significantly (p < 0.05) improved. Improvements also were seen in participants' intentions to promote obesity prevention behaviors (i.e., age appropriate portions sizes, adequate physically active, and parental role modeling). Furthermore, changes in personal health behaviors at posttest revealed participants had significantly (p < 0.05) greater dietary restraint, improvements in sleep quality, and reductions of use of electronic devices during meals and snacks. Overall, participants were very satisfied with the training program, felt comfortable with skills acquired, and enjoyed the program. Findings suggest this online training program is a feasible and effective method for improving community family educators' knowledge, attitudes, and intentions for obesity-prevention related parenting practices.

Cellular track model for study of heavy ion beams

NASA Technical Reports Server (NTRS)

Shinn, Judy L.; Katz, Robert; Cucinotta, Francis A.; Wilson, John W.; Ngo, Duc M.

1993-01-01

Track theory is combined with a realistic model of a heavy ion beam to study the effects of nuclear fragmentation on cell survival and biological effectiveness. The effects of secondary reaction products are studied as a function of depth in a water column. Good agreement is found with experimental results for the survival of human T-l cells exposed to monoenergetic carbon, neon, and argon beams under aerobic and hypoxia conditions. The present calculation, which includes the effect of target fragmentation, is a significant improvement over an earlier calculation because of the use of a vastly improved beam model with no change in the track theory or cellular response parameters.

Tandospirone reduces wasting and improves cardiac function in experimental cancer cachexia.

PubMed

Elkina, Yulia; Palus, Sandra; Tschirner, Anika; Hartmann, Kai; von Haehling, Stephan; Doehner, Wolfram; Mayer, Ulrike; Coats, Andrew J S; Beadle, John; Anker, Stefan D; Springer, Jochen

2013-12-10

Cancer cachexia is thought to be the cause of >20% of cancer related deaths. Symptoms of cancer cachexia patients include depression and anorexia significantly worsening their quality of life. Moreover, in rodent models of cancer cachexia atrophy of the heart has been shown to impair cardiac function. Here, we characterize the effects of the antidepressant and anxiolytic drug tandospirone on wasting, cardiac function and survival in experimental cancer cachexia. The well-established Yoshida hepatoma rat model was used and tumor-bearing rats were treated with 1mg/kg/d (LD), 10mg/kg/d (HD) tandospirone or placebo. Weight, body composition (NMR), cardiac function (echocardiography), activity and food intake were assessed. Noradrenalin and cortisol were measured in plasma and caspase activity in skeletal muscle. Ten mg/kg/d tandospirone decreased the loss of body weight (p=0.0003) compared to placebo animals, mainly due to preservation of muscle mass (p<0.001), while 1mg/kg/d tandospirone was not effective. Locomotor activity (p=0.0007) and food intake (p=0.0001) were increased by HD tandospirone. The weight (p=0.0277) and function of heart (left ventricular mass, fractional shortening, stroke volume, ejection fraction, all p<0.05) were significantly improved. In the HD tandospirone group, plasma levels of noradrenalin and cortisol were significantly reduced by 49% and 52%, respectively, which may have contributed to the lower caspase activity in the gastrocnemius muscle. Most importantly, HD tandospirone significantly improved survival compared to placebo rats (HR: 0.34; 95% CI: 0.13-0.86; p=0.0495). Tandospirone showed significant beneficial effects in the Yoshida hepatoma cancer cachexia model and should be further examined as a prospective drug for this syndrome. © 2013.

Impact of Land Use/Land Cover Conditions on WRF Model Evaluation for Heat Island Assessment

NASA Astrophysics Data System (ADS)

Bhati, S.; Mohan, M.

2017-12-01

Urban heat island effect has been assessed using Weather Research and Forecasting model (WRF v3.5) focusing on air temperature and surface skin temperature in the sub-tropical urban Indian megacity of Delhi. Impact of urbanization related changes in land use/land cover (LULC) on model outputs has been analyzed. Four simulations have been carried out with different types of LULC data viz. (1) USGS , (2) MODIS, (3) user-modified USGS and (4) user modified land use data coupled with urban canopy model (UCM) for incorporation of canopy features. Heat island intensities have been estimated based on these simulations and subsequently compared with those derived from in-situ and satellite observations. There is a significant improvement in model performance with modification of LULC and inclusion of UCM. Overall, RMSEs for near surface temperature improved from 6.3°C to 3.9°C and index of agreement for mean urban heat island intensities (UHI) improved from 0.4 to 0.7 with modified land use coupled with UCM. In general, model is able to capture the magnitude of UHI as well as high UHI zones well. The study highlights the importance of appropriate and updated representation of landuse-landcover and urban canopies for improving predictive capabilities of the mesoscale models.

Flexible Fabrics with High Thermal Conductivity for Advanced Spacesuits

NASA Technical Reports Server (NTRS)

Trevino, Luis A.; Bue, Grant; Orndoff, Evelyne; Kesterson, Matt; Connel, John W.; Smith, Joseph G., Jr.; Southward, Robin E.; Working, Dennis; Watson, Kent A.; Delozier, Donovan M.

2006-01-01

This paper describes the effort and accomplishments for developing flexible fabrics with high thermal conductivity (FFHTC) for spacesuits to improve thermal performance, lower weight and reduce complexity. Commercial and additional space exploration applications that require substantial performance enhancements in removal and transport of heat away from equipment as well as from the human body can benefit from this technology. Improvements in thermal conductivity were achieved through the use of modified polymers containing thermally conductive additives. The objective of the FFHTC effort is to significantly improve the thermal conductivity of the liquid cooled ventilation garment by improving the thermal conductivity of the subcomponents (i.e., fabric and plastic tubes). This paper presents the initial system modeling studies, including a detailed liquid cooling garment model incorporated into the Wissler human thermal regulatory model, to quantify the necessary improvements in thermal conductivity and garment geometries needed to affect system performance. In addition, preliminary results of thermal conductivity improvements of the polymer components of the liquid cooled ventilation garment are presented. By improving thermal garment performance, major technology drivers will be addressed for lightweight, high thermal conductivity, flexible materials for spacesuits that are strategic technical challenges of the Exploration

Modeling and analysis of the DSS-14 antenna control system

NASA Technical Reports Server (NTRS)

Gawronski, W.; Bartos, R.

1996-01-01

An improvement of pointing precision of the DSS-14 antenna is planned for the near future. In order to analyze the improvement limits and to design new controllers, a precise model of the antenna and the servo is developed, including a finite element model of the antenna structure and detailed models of the hydraulic drives and electronic parts. The DSS-14 antenna control system has two modes of operation: computer mode and precision mode. The principal goal of this investigation is to develop the model of the computer mode and to evaluate its performance. The DSS-14 antenna computer model consists of the antenna structure and drives in azimuth and elevation. For this model, the position servo loop is derived, and simulations of the closed-loop antenna dynamics are presented. The model is significantly different from that for the 34-m beam-waveguide antennas.

Extending the Solvation-Layer Interface Condition Continum Electrostatic Model to a Linearized Poisson-Boltzmann Solvent.

PubMed

Molavi Tabrizi, Amirhossein; Goossens, Spencer; Mehdizadeh Rahimi, Ali; Cooper, Christopher D; Knepley, Matthew G; Bardhan, Jaydeep P

2017-06-13

We extend the linearized Poisson-Boltzmann (LPB) continuum electrostatic model for molecular solvation to address charge-hydration asymmetry. Our new solvation-layer interface condition (SLIC)/LPB corrects for first-shell response by perturbing the traditional continuum-theory interface conditions at the protein-solvent and the Stern-layer interfaces. We also present a GPU-accelerated treecode implementation capable of simulating large proteins, and our results demonstrate that the new model exhibits significant accuracy improvements over traditional LPB models, while reducing the number of fitting parameters from dozens (atomic radii) to just five parameters, which have physical meanings related to first-shell water behavior at an uncharged interface. In particular, atom radii in the SLIC model are not optimized but uniformly scaled from their Lennard-Jones radii. Compared to explicit-solvent free-energy calculations of individual atoms in small molecules, SLIC/LPB is significantly more accurate than standard parametrizations (RMS error 0.55 kcal/mol for SLIC, compared to RMS error of 3.05 kcal/mol for standard LPB). On parametrizing the electrostatic model with a simple nonpolar component for total molecular solvation free energies, our model predicts octanol/water transfer free energies with an RMS error 1.07 kcal/mol. A more detailed assessment illustrates that standard continuum electrostatic models reproduce total charging free energies via a compensation of significant errors in atomic self-energies; this finding offers a window into improving the accuracy of Generalized-Born theories and other coarse-grained models. Most remarkably, the SLIC model also reproduces positive charging free energies for atoms in hydrophobic groups, whereas standard PB models are unable to generate positive charging free energies regardless of the parametrized radii. The GPU-accelerated solver is freely available online, as is a MATLAB implementation.

Developing models of how cognitive improvements change functioning: Mediation, moderation and moderated mediation

PubMed Central

Wykes, Til; Reeder, Clare; Huddy, Vyv; Taylor, Rumina; Wood, Helen; Ghirasim, Natalia; Kontis, Dimitrios; Landau, Sabine

2012-01-01

Background Cognitive remediation (CRT) affects functioning but the extent and type of cognitive improvements necessary are unknown. Aim To develop and test models of how cognitive improvement transfers to work behaviour using the data from a current service. Method Participants (N49) with a support worker and a paid or voluntary job were offered CRT in a Phase 2 single group design with three assessments: baseline, post therapy and follow-up. Working memory, cognitive flexibility, planning and work outcomes were assessed. Results Three models were tested (mediation — cognitive improvements drive functioning improvement; moderation — post treatment cognitive level affects the impact of CRT on functioning; moderated mediation — cognition drives functioning improvements only after a certain level is achieved). There was evidence of mediation (planning improvement associated with improved work quality). There was no evidence that cognitive flexibility (total Wisconsin Card Sorting Test errors) and working memory (Wechsler Adult Intelligence Scale III digit span) mediated work functioning despite significant effects. There was some evidence of moderated mediation for planning improvement if participants had poorer memory and/or made fewer WCST errors. The total CRT effect on work quality was d = 0.55, but the indirect (planning-mediated CRT effect) was d = 0.082 Conclusion Planning improvements led to better work quality but only accounted for a small proportion of the total effect on work outcome. Other specific and non-specific effects of CRT and the work programme are likely to account for some of the remaining effect. This is the first time complex models have been tested and future Phase 3 studies need to further test mediation and moderated mediation models. PMID:22503640

Hierarchical Probabilistic Inference of the Color-Magnitude Diagram and Shrinkage of Stellar Distance Uncertainties

NASA Astrophysics Data System (ADS)

Leistedt, Boris; Hogg, David W.

2017-12-01

We present a hierarchical probabilistic model for improving geometric stellar distance estimates using color-magnitude information. This is achieved with a data-driven model of the color-magnitude diagram, not relying on stellar models but instead on the relative abundances of stars in color-magnitude cells, which are inferred from very noisy magnitudes and parallaxes. While the resulting noise-deconvolved color-magnitude diagram can be useful for a range of applications, we focus on deriving improved stellar distance estimates relying on both parallax and photometric information. We demonstrate the efficiency of this approach on the 1.4 million stars of the Gaia TGAS sample that also have AAVSO Photometric All Sky Survey magnitudes. Our hierarchical model has 4 million parameters in total, most of which are marginalized out numerically or analytically. We find that distance estimates are significantly improved for the noisiest parallaxes and densest regions of the color-magnitude diagram. In particular, the average distance signal-to-noise ratio (S/N) and uncertainty improve by 19% and 36%, respectively, with 8% of the objects improving in S/N by a factor greater than 2. This computationally efficient approach fully accounts for both parallax and photometric noise and is a first step toward a full hierarchical probabilistic model of the Gaia data.

Mitigation of bone loss with ultrasound induced dynamic mechanical signals in an OVX induced rat model of osteopenia.

PubMed

Ferreri, Suzanne L; Talish, Roger; Trandafir, Titi; Qin, Yi-Xian

2011-05-01

This study tests the hypothesis that an ultrasound generated dynamic mechanical signal can attenuate bone loss in an estrogen deficient model of osteopenia. Eighty-four 16-week-old Sprague-Dawley rats were divided into six groups: baseline control, age-matched control, ovariectomy (OVX) control, OVX+5mW/cm(2) ultrasound (US), OVX+30mW/cm(2) US and OVX+100mW/cm(2) US. Low intensity pulsed ultrasound (LIPUS) was delivered transdermally at the L4/L5 vertebrae, using gel-coupled plane wave US transducers. The signal, characterized by 200μs pulses of 1.5MHz sine waves repeating at 1kHz with spatial-averaged temporal-averaged (SATA) intensities of 5, 30 or 100mW/cm(2), was applied 20 min/day, 5 days/week for 4 weeks. OVX treatment reduced bone volume fraction 40% and compromised microstructure at 4 weeks. LIPUS treatment, however, significantly increased BV/TV (+33%) compared to OVX controls for the 100mW/cm(2) treated group. SMI and Tb.N showed significant improvements compared with OVX for the 100mW/cm(2) treated group and Tb.Th was significantly improved in the 30 and 100mW/cm(2) treated groups. Improvements in bone's microstructural characteristics with 100mW/cm(2) US treatment translated into improved load bearing characteristics, including a significant 42% increase in apparent level elastic modulus compared to OVX controls. Significant improvement of trabecular mechanical strength was also observed in the treated animals, e.g., principal compressive stress (represent bone's ability to resist loads) was significantly higher compared to OVX controls. Histomorphometric analysis also showed that treatment with 100mW/cm(2) US resulted in a 76% improvement in MS/BS. In addition, measures of bone quantity and quality at the femoral metaphysis suggest that LIPUS is site specific. This study indicates that localized ultrasound treatment, delivered at specific intensities, has beneficial effects on intact bone and may represent a novel intervention for bone loss. Copyright © 2011 Elsevier Inc. All rights reserved.

Mitigation of Bone Loss with Ultrasound Induced Dynamic Mechanical Signals in an OVX Induced Rat Model of Osteopenia

PubMed Central

Ferreri, Suzanne L.; Talish, Roger; Trandafir, Titi; Qin, Yi-Xian

2011-01-01

This study tests the hypothesis that an ultrasound generated dynamic mechanical signal can attenuate bone loss in an estrogen deficient model of osteopenia. Eighty-four, sixteen week old Sprague-Dawley rats were divided into six groups: baseline control, age-matched control, ovariectomy (OVX) OVX control, OVX + 5 mW/cm2 ultrasound (US), OVX + 30 mW/cm2 US and OVX + 100 mW/cm2 US. Low intensity pulsed ultrasound (LIPUS) was delivered transdermally at the L4/L5 vertebrae, using gelcoupled plane wave US transducers. The signal, characterized by 200μs pulses of 1.5 MHz sine waves repeating at 1 kHz with spatial-averaged temporal-averaged (SATA) intensities of 5, 30 or 100mW/cm2, was applied 20 min/day, 5 days/week for 4 weeks. OVX treatment reduced bone volume fraction 40% and compromised microstructure at 4 weeks. LIPUS treatment, however, significantly increased BV/TV 33% compared to OVX controls for the 100mW/cm2 treated group. SMI, and Tb.N showed significant improvements compared with OVX for the 100mW/cm2 treated group and Tb.Th was significantly improved in the 30 and 100mW/cm2 treated groups. Improvements in bone’s microstructural characteristics with 100mW/cm2 US treatment translated into improved load bearing characteristics, including a significant, 42% increase in apparent level Elastic Modulus compared to OVX controls. Significant improvement of trabecular mechanical strength is also observed in the treated animals, e.g., principal compressive stress (represent bone’s ability to resist loads) was significantly higher compared to OVX controls. Histomorphometric analysis also showed that treatment with 100mW/cm2 US resulted in a 76% improvement in MS/BS. In addition, measures of bone quantity and quality at the femoral metaphysis suggest that LIPUS is site specific. This study indicates that ultrasound, delivered at specific intensities, has beneficial effects on intact bone and may represent a novel intervention for bone loss. PMID:21241838

Geopotential models of the Earth from satellite tracking, altimeter and surface gravity observations: GEM-T3 and GEM-T3S

NASA Technical Reports Server (NTRS)

Lerch, F. J.; Nerem, R. S.; Putney, B. H.; Felsentreger, T. L.; Sanchez, B. V.; Klosko, S. M.; Patel, G. B.; Williamson, R. G.; Chinn, D. S.; Chan, J. C.

1992-01-01

Improved models of the Earth's gravitational field have been developed from conventional tracking data and from a combination of satellite tracking, satellite altimeter and surface gravimetric data. This combination model represents a significant improvement in the modeling of the gravity field at half-wavelengths of 300 km and longer. Both models are complete to degree and order 50. The Goddard Earth Model-T3 (GEM-T3) provides more accurate computation of satellite orbital effects as well as giving superior geoidal representation from that achieved in any previous GEM. A description of the models, their development and an assessment of their accuracy is presented. The GEM-T3 model used altimeter data from previous satellite missions in estimating the orbits, geoid, and dynamic height fields. Other satellite tracking data are largely the same as was used to develop GEM-T2, but contain certain important improvements in data treatment and expanded laser tracking coverage. Over 1300 arcs of tracking data from 31 different satellites have been used in the solution. Reliable estimates of the model uncertainties via error calibration and optimal data weighting techniques are discussed.

A new enhanced index tracking model in portfolio optimization with sum weighted approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

Tree biomass in the Swiss landscape: nationwide modelling for improved accounting for forest and non-forest trees.

PubMed

Price, B; Gomez, A; Mathys, L; Gardi, O; Schellenberger, A; Ginzler, C; Thürig, E

2017-03-01

Trees outside forest (TOF) can perform a variety of social, economic and ecological functions including carbon sequestration. However, detailed quantification of tree biomass is usually limited to forest areas. Taking advantage of structural information available from stereo aerial imagery and airborne laser scanning (ALS), this research models tree biomass using national forest inventory data and linear least-square regression and applies the model both inside and outside of forest to create a nationwide model for tree biomass (above ground and below ground). Validation of the tree biomass model against TOF data within settlement areas shows relatively low model performance (R 2 of 0.44) but still a considerable improvement on current biomass estimates used for greenhouse gas inventory and carbon accounting. We demonstrate an efficient and easily implementable approach to modelling tree biomass across a large heterogeneous nationwide area. The model offers significant opportunity for improved estimates on land use combination categories (CC) where tree biomass has either not been included or only roughly estimated until now. The ALS biomass model also offers the advantage of providing greater spatial resolution and greater within CC spatial variability compared to the current nationwide estimates.

Tailor-made heart simulation predicts the effect of cardiac resynchronization therapy in a canine model of heart failure.

PubMed

Panthee, Nirmal; Okada, Jun-ichi; Washio, Takumi; Mochizuki, Youhei; Suzuki, Ryohei; Koyama, Hidekazu; Ono, Minoru; Hisada, Toshiaki; Sugiura, Seiryo

2016-07-01

Despite extensive studies on clinical indices for the selection of patient candidates for cardiac resynchronization therapy (CRT), approximately 30% of selected patients do not respond to this therapy. Herein, we examined whether CRT simulations based on individualized realistic three-dimensional heart models can predict the therapeutic effect of CRT in a canine model of heart failure with left bundle branch block. In four canine models of failing heart with dyssynchrony, individualized three-dimensional heart models reproducing the electromechanical activity of each animal were created based on the computer tomographic images. CRT simulations were performed for 25 patterns of three ventricular pacing lead positions. Lead positions producing the best and the worst therapeutic effects were selected in each model. The validity of predictions was tested in acute experiments in which hearts were paced from the sites identified by simulations. We found significant correlations between the experimentally observed improvement in ejection fraction (EF) and the predicted improvements in ejection fraction (P<0.01) or the maximum value of the derivative of left ventricular pressure (P<0.01). The optimal lead positions produced better outcomes compared with the worst positioning in all dogs studied, although there were significant variations in responses. Variations in ventricular wall thickness among the dogs may have contributed to these responses. Thus CRT simulations using the individualized three-dimensional heart models can predict acute hemodynamic improvement, and help determine the optimal positions of the pacing lead. Copyright © 2016 Elsevier B.V. All rights reserved.

THR-18, a 18-mer peptide derived from PAI-1, is neuroprotective and improves thrombolysis by tPA in rat stroke models.

PubMed

Krakovsky, M; Polianski, V; Nimrod, A; Higazi, A; Leker, R R; Lamensdorf, I

2011-11-01

The thrombolytic treatment of stroke is limited by a narrow therapeutic time window and is associated with significant adverse side effects. To improve this situation, the modulation of tissue-type plasminogen activator (tPA) activity by a synthetic plasminogen activator inhibitor-1-derived 18-mer peptide (THR-18) was examined in two models of stroke in rats. In the first model (thromboembolic), stroke was induced by intra-carotid injection of micro-clots to rats, and tPA (6 mg/kg) was intravenously infused for 30 minutes with or without THR-18 (1 mg/kg) at 4 hours post-induction. In the second model [transient middle cerebral artery occlusion (tMCAO)], stroke was induced for 2 hours by a transient mechanical occlusion. tPA and/or THR-18 (0.02, 0.1, and 1 mg/kg) were intravenously infused for 60 minutes at the time of reperfusion. In the thromboembolic model, cerebral blood flow, measured before and up to 5.5 hours post-induction, revealed that tPA administration caused reperfusion of flow at 30 minutes post-infusion. Later on, an additional increase in reperfusion was seen in the tPA+THR-18 group, and not with tPA alone. In both models, the frequency of intracranial hemorrhage in the tPA-treated group was found to be significantly higher than the control, and this tPA effect was attenuated by THR-18. In the thromboembolic study, infarct size and brain edema were similar in the control and tPA-treated rats. However, the combination of tPA and THR-18 caused a statistically significant reduction in both parameters (infarct size 17.8 versus 25.0%, brain edema 5 versus 8%, tPA+THR-18 versus control, respectively). In the tMCAO mechanical model, infarct size and brain edema were both increased by tPA treatment as compared to the control group, and this increase was markedly diminished by THR-18 co-administration. Neurobehavioral assessment of the tMCAO animals performed at 72 hours post-stroke induction revealed significant improvements (P<0.05-0.01) in neuroscores in all groups of animals treated with peptide-tPA, as compared to the tPA monotherapy group. A significant (P<0.05) improvement in the neurological outcome was also seen in the THR-18 monoterapy group, as compared to the control animals, thus demonstrating a clear neuroprotective effect by the peptide on its own. The results support the use of THR-18 together with tPA in the thrombolytic therapy of stroke, in order to achieve better patency, less tPA-induced damage, and possibly a widening of tPA therapeutic time window.

Vehicle Modeling for Future Generation Transportation Simulation

DOT National Transportation Integrated Search

2009-05-10

Recent development of inter-vehicular wireless communication technologies have motivated many innovative applications aiming at significantly increasing traffic throughput and improving highway safety. Powerful traffic simulation is an indispensable ...

Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market.

PubMed

Kim, Taegu; Hong, Jungsik; Kang, Pilsung

2017-01-01

Accurate box office forecasting models are developed by considering competition and word-of-mouth (WOM) effects in addition to screening-related information. Nationality, genre, ratings, and distributors of motion pictures running concurrently with the target motion picture are used to describe the competition, whereas the numbers of informative, positive, and negative mentions posted on social network services (SNS) are used to gauge the atmosphere spread by WOM. Among these candidate variables, only significant variables are selected by genetic algorithm (GA), based on which machine learning algorithms are trained to build forecasting models. The forecasts are combined to improve forecasting performance. Experimental results on the Korean film market show that the forecasting accuracy in early screening periods can be significantly improved by considering competition. In addition, WOM has a stronger influence on total box office forecasting. Considering both competition and WOM improves forecasting performance to a larger extent than when only one of them is considered.

Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market

PubMed Central

Kim, Taegu; Hong, Jungsik

2017-01-01

Accurate box office forecasting models are developed by considering competition and word-of-mouth (WOM) effects in addition to screening-related information. Nationality, genre, ratings, and distributors of motion pictures running concurrently with the target motion picture are used to describe the competition, whereas the numbers of informative, positive, and negative mentions posted on social network services (SNS) are used to gauge the atmosphere spread by WOM. Among these candidate variables, only significant variables are selected by genetic algorithm (GA), based on which machine learning algorithms are trained to build forecasting models. The forecasts are combined to improve forecasting performance. Experimental results on the Korean film market show that the forecasting accuracy in early screening periods can be significantly improved by considering competition. In addition, WOM has a stronger influence on total box office forecasting. Considering both competition and WOM improves forecasting performance to a larger extent than when only one of them is considered. PMID:28819355

Improved hurricane forecasting from a variational bogus and ozone data assimilation (BODA) scheme: case study

NASA Astrophysics Data System (ADS)

Liu, Yin; Zhang, Wei

2016-12-01

This study develops a proper way to incorporate Atmospheric Infrared Sounder (AIRS) ozone data into the bogus data assimilation (BDA) initialization scheme for improving hurricane prediction. First, the observation operator at some model levels with the highest correlation coefficients is established to assimilate AIRS ozone data based on the correlation between total column ozone and potential vorticity (PV) ranging from 400 to 50 hPa level. Second, AIRS ozone data act as an augmentation to a BDA procedure using a four-dimensional variational (4D-Var) data assimilation system. Case studies of several hurricanes are performed to demonstrate the effectiveness of the bogus and ozone data assimilation (BODA) scheme. The statistical result indicates that assimilating AIRS ozone data at 4, 5, or 6 model levels can produce a significant improvement in hurricane track and intensity prediction, with reasonable computation time for the hurricane initialization. Moreover, a detailed analysis of how BODA scheme affects hurricane prediction is conducted for Hurricane Earl (2010). It is found that the new scheme developed in this study generates significant adjustments in the initial conditions (ICs) from the lower levels to the upper levels, compared with the BDA scheme. With the BODA scheme, hurricane development is found to be much more sensitive to the number of ozone data assimilation levels. In particular, the experiment with the assimilation of AIRS ozone data at proper number of model levels shows great capabilities in reproducing the intensity and intensity changes of Hurricane Earl, as well as improve the track prediction. These results suggest that AIRS ozone data convey valuable meteorological information in the upper troposphere, which can be assimilated into a numerical model to improve hurricane initialization when the low-level bogus data are included.

State-of-the-art satellite laser range modeling for geodetic and oceanographic applications

NASA Technical Reports Server (NTRS)

Klosko, Steve M.; Smith, David E.

1993-01-01

Significant improvements have been made in the modeling and accuracy of Satellite Laser Range (SLR) data since the launch of LAGEOS in 1976. Some of these include: improved models of the static geopotential, solid-Earth and ocean tides, more advanced atmospheric drag models, and the adoption of the J2000 reference system with improved nutation and precession. Site positioning using SLR systems currently yield approximately 2 cm static and 5 mm/y kinematic descriptions of the geocentric location of these sites. Incorporation of a large set of observations from advanced Satellite Laser Ranging (SLR) tracking systems have directly made major contributions to the gravitational fields and in advancing the state-of-the-art in precision orbit determination. SLR is the baseline tracking system for the altimeter bearing TOPEX/Poseidon and ERS-1 satellites and thus, will play an important role in providing the Conventional Terrestrial Reference Frame for instantaneously locating the geocentric position of the ocean surface over time, in providing an unchanging range standard for altimeter range calibration, and for improving the geoid models to separate gravitational from ocean circulation signals seen in the sea surface. Nevertheless, despite the unprecedented improvements in the accuracy of the models used to support orbit reduction of laser observations, there still remain systematic unmodeled effects which limit the full exploitation of modern SLR data.

Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts

USGS Publications Warehouse

Almanaseer, Naser; Sankarasubramanian, A.; Bales, Jerad

2014-01-01

Recent studies have found a significant association between climatic variability and basin hydroclimatology, particularly groundwater levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly timescales. Three modeling schemes are considered at the beginning of January to predict winter (January, February, and March) and spring (April, May, and June) streamflow and groundwater for the selected sites within the Flint River Basin. The first scheme (model 1) is a null model and is developed using PCR for every streamflow and groundwater site using previous 3-month observations (October, November, and December) available at that particular site as predictors. Modeling schemes 2 and 3 are developed using PCR and CCA, respectively, to evaluate the role of precipitation forecasts in improving monthly and seasonal groundwater predictions. Modeling scheme 3, which employs a CCA approach, is developed for each site by considering observed groundwater levels from nearby sites as predictands. The performance of these three schemes is evaluated using two metrics (correlation coefficient and relative RMS error) by developing groundwater-level forecasts based on leave-five-out cross-validation. Results from the research reported in this paper show that using precipitation forecasts in climate models improves the ability to predict the interannual variability of winter and spring streamflow and groundwater levels over the basin. However, significant conditional bias exists in all the three modeling schemes, which indicates the need to consider improved modeling schemes as well as the availability of longer time-series of observed hydroclimatic information over the basin.

A Model of Cooperative Education--"Group Leader Training Program" for Industry Employees

ERIC Educational Resources Information Center

Arslan, Ridvan; Kus, Abdil; Mumcu, Haldun; Uzaslan, N. Tufan

2008-01-01

Studies on continuous education and alteration are highly significant in order to improve the technical and social abilities of the industry employees. Generally, these kinds of educational facilities are carried on in the range of in-house training. Besides in-house training, it is also possible to improve the abilities of the employees with the…

The First Non-Dispersive High-Resolution Spectroscopy of an X-ray-bright Galaxy Cluster

NASA Astrophysics Data System (ADS)

Yamaguchi, Hiroya; Hitomi Collaboration

2018-06-01

The Hitomi X-ray Observatory was equipped with the Soft X-ray Spectrometer (SXS), an X-ray microcalorimeter that achieved an energy resolution of 5 eV (@0.5-10 keV) for extended objects. This offered an unprecedented benchmark of atomic modeling and database for hot collisional plasmas, revealing both successes and challenges in the current atomic codes that are widely used by the X-ray astronomy community. I will review the Hitomi observations of the brightest part of the Perseus Cluster, whose X-ray spectrum is dominated by thermal emission from the intra-cluster medium (ICM). The SXS successfully measured the turbulent velocities and metal abundances of the ICM, which radically altered our understanding of the dynamics and chemical enrichment in this object. At the same time, the high-resolution X-ray data led to significant improvement in the atomic models, such as AtomDB and SPEX -- I will briefly overview how this improvement was made. Nevertheless, there are still significant discrepancies among the public atomic models, causing systematic uncertainties in measurements of the temperature, abundance, and degree of the resonance scattering. Requirements for future improvements will be summarized in this context.

An Evaluation of Understandability of Patient Journey Models in Mental Health

PubMed Central

2016-01-01

Background There is a significant trend toward implementing health information technology to reduce administrative costs and improve patient care. Unfortunately, little awareness exists of the challenges of integrating information systems with existing clinical practice. The systematic integration of clinical processes with information system and health information technology can benefit the patients, staff, and the delivery of care. Objectives This paper presents a comparison of the degree of understandability of patient journey models. In particular, the authors demonstrate the value of a relatively new patient journey modeling technique called the Patient Journey Modeling Architecture (PaJMa) when compared with traditional manufacturing based process modeling tools. The paper also presents results from a small pilot case study that compared the usability of 5 modeling approaches in a mental health care environment. Method Five business process modeling techniques were used to represent a selected patient journey. A mix of both qualitative and quantitative methods was used to evaluate these models. Techniques included a focus group and survey to measure usability of the various models. Results The preliminary evaluation of the usability of the 5 modeling techniques has shown increased staff understanding of the representation of their processes and activities when presented with the models. Improved individual role identification throughout the models was also observed. The extended version of the PaJMa methodology provided the most clarity of information flows for clinicians. Conclusions The extended version of PaJMa provided a significant improvement in the ease of interpretation for clinicians and increased the engagement with the modeling process. The use of color and its effectiveness in distinguishing the representation of roles was a key feature of the framework not present in other modeling approaches. Future research should focus on extending the pilot case study to a more diversified group of clinicians and health care support workers. PMID:27471006

Modeling the viscosity of polydisperse suspensions: Improvements in prediction of limiting behavior

NASA Astrophysics Data System (ADS)

Mwasame, Paul M.; Wagner, Norman J.; Beris, Antony N.

2016-06-01

The present study develops a fully consistent extension of the approach pioneered by Farris ["Prediction of the viscosity of multimodal suspensions from unimodal viscosity data," Trans. Soc. Rheol. 12, 281-301 (1968)] to describe the viscosity of polydisperse suspensions significantly improving upon our previous model [P. M. Mwasame, N. J. Wagner, and A. N. Beris, "Modeling the effects of polydispersity on the viscosity of noncolloidal hard sphere suspensions," J. Rheol. 60, 225-240 (2016)]. The new model captures the Farris limit of large size differences between consecutive particle size classes in a suspension. Moreover, the new model includes a further generalization that enables its application to real, complex suspensions that deviate from ideal non-colloidal suspension behavior. The capability of the new model to predict the viscosity of complex suspensions is illustrated by comparison against experimental data.

Badhwar - O'Neill 2014 Galactic Cosmic Ray Flux Model Description

NASA Technical Reports Server (NTRS)

O'Neill, P. M.; Golge, S.; Slaba, T. C.

2014-01-01

The Badhwar-O'Neill (BON) Galactic Cosmic Ray (GCR) model is based on GCR measurements from particle detectors. The model has mainly been used by NASA to certify microelectronic systems and the analysis of radiation health risks to astronauts in space missions. The BON14 model numerically solves the Fokker-Planck differential equation to account for particle transport in the heliosphere due to diffusion, convection, and adiabatic deceleration under the assumption of a spherically symmetric heliosphere. The model also incorporates an empirical time delay function to account for the lag of the solar activity to reach the boundary of the heliosphere. This technical paper describes the most recent improvements in parameter fits to the BON model (BON14). Using a comprehensive measurement database, it is shown that BON14 is significantly improved over the previous version, BON11.

Models of ovarian cancer metastasis: Murine models

PubMed Central

Šale, Sanja; Orsulic, Sandra

2008-01-01

Mice have mainly been used in ovarian cancer research as immunodeficient hosts for cell lines derived from the primary tumors and ascites of ovarian cancer patients. These xenograft models have provided a valuable system for pre-clinical trials, however, the genetic complexity of human tumors has precluded the understanding of key events that drive metastatic dissemination. Recently developed immunocompetent, genetically defined mouse models of epithelial ovarian cancer represent significant improvements in the modeling of metastatic disease. PMID:19337569

Bayesian parameter estimation of a k-ε model for accurate jet-in-crossflow simulations

DOE PAGES

Ray, Jaideep; Lefantzi, Sophia; Arunajatesan, Srinivasan; ...

2016-05-31

Reynolds-averaged Navier–Stokes models are not very accurate for high-Reynolds-number compressible jet-in-crossflow interactions. The inaccuracy arises from the use of inappropriate model parameters and model-form errors in the Reynolds-averaged Navier–Stokes model. In this study, the hypothesis is pursued that Reynolds-averaged Navier–Stokes predictions can be significantly improved by using parameters inferred from experimental measurements of a supersonic jet interacting with a transonic crossflow.

An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

PubMed Central

Churchill, Nathan W.; Spring, Robyn; Afshin-Pour, Babak; Dong, Fan; Strother, Stephen C.

2015-01-01

BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the “pipeline”) significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard “fixed” preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets. PMID:26161667

Statistical analysis of the factors that influenced the mechanical properties improvement of cassava starch films

NASA Astrophysics Data System (ADS)

Monteiro, Mayra; Oliveira, Victor; Santos, Francisco; Barros Neto, Eduardo; Silva, Karyn; Silva, Rayane; Henrique, João; Chibério, Abimaelle

2017-08-01

In order to obtain cassava starch films with improved mechanical properties in relation to the synthetic polymer in the packaging production, a complete factorial design 23 was carried out in order to investigate which factor significantly influences the tensile strength of the biofilm. The factors to be investigated were cassava starch, glycerol and modified clay contents. Modified bentonite clay was used as a filling material of the biofilm. Glycerol was the plasticizer used to thermoplastify cassava starch. The factorial analysis suggested a regression model capable of predicting the optimal mechanical property of the cassava starch film from the maximization of the tensile strength. The reliability of the regression model was tested by the correlation established with the experimental data through the following statistical analyse: Pareto graph. The modified clay was the factor of greater statistical significance on the observed response variable, being the factor that contributed most to the improvement of the mechanical property of the starch film. The factorial experiments showed that the interaction of glycerol with both modified clay and cassava starch was significant for the reduction of biofilm ductility. Modified clay and cassava starch contributed to the maximization of biofilm ductility, while glycerol contributed to the minimization.

Phase Behavior Modeling of Asphaltene Precipitation for Heavy Crudes: A Promising Tool Along with Experimental Data

NASA Astrophysics Data System (ADS)

Tavakkoli, M.; Kharrat, R.; Masihi, M.; Ghazanfari, M. H.; Fadaei, S.

2012-12-01

Thermodynamic modeling is known as a promising tool for phase behavior modeling of asphaltene precipitation under different conditions such as pressure depletion and CO2 injection. In this work, a thermodynamic approach is used for modeling the phase behavior of asphaltene precipitation. The precipitated asphaltene phase is represented by an improved solid model, while the oil and gas phases are modeled with an equation of state. The PR-EOS was used to perform flash calculations. Then, the onset point and the amount of precipitated asphaltene were predicted. A computer code based on an improved solid model has been developed and used for predicting asphaltene precipitation data for one of Iranian heavy crudes, under pressure depletion and CO2 injection conditions. A significant improvement has been observed in predicting the asphaltene precipitation data under gas injection conditions. Especially for the maximum value of asphaltene precipitation and for the trend of the curve after the peak point, good agreement was observed. For gas injection conditions, comparison of the thermodynamic micellization model and the improved solid model showed that the thermodynamic micellization model cannot predict the maximum of precipitation as well as the improved solid model. The non-isothermal improved solid model has been used for predicting asphaltene precipitation data under pressure depletion conditions. The pressure depletion tests were done at different levels of temperature and pressure, and the parameters of a non-isothermal model were tuned using three onset pressures at three different temperatures for the considered crude. The results showed that the model is highly sensitive to the amount of solid molar volume along with the interaction coefficient parameter between the asphaltene component and light hydrocarbon components. Using a non-isothermal improved solid model, the asphaltene phase envelope was developed. It has been revealed that at high temperatures, an increase in the temperature results in a lower amount of asphaltene precipitation and also it causes the convergence of lower and upper boundaries of the asphaltene phase envelope. This work illustrates successful application of a non-isothermal improved solid model for developing the asphaltene phase envelope of heavy crude which can be helpful for monitoring and controlling of asphaltene precipitation through the wellbore and surface facilities during heavy oil production.

Xenon improves neurological outcome and reduces secondary injury following trauma in an in vivo model of traumatic brain injury

PubMed Central

Luh, Clara; Gruss, Marco; Radyushkin, Konstantin; Hirnet, Tobias; Werner, Christian; Engelhard, Kristin; Franks, Nicholas P; Thal, Serge C; Dickinson, Robert

2015-01-01

Objectives To determine the neuroprotective efficacy of the inert gas xenon following traumatic brain injury, and to determine whether application of xenon has a clinically relevant therapeutic time window. Design Controlled animal study. Setting University research laboratory. Subjects Male C57BL/6N mice (n=196) Interventions 75% xenon, 50% xenon or 30% xenon, with 25% oxygen (balance nitrogen) treatment following mechanical brain lesion by controlled cortical impact. Measurements & Main Results Outcome following trauma was measured using: 1) functional neurological outcome score, 2) histological measurement of contusion volume, 3) analysis of locomotor function and gait. Our study shows that xenon-treatment improves outcome following traumatic brain injury. Neurological outcome scores were significantly (p<0.05) better in xenon-treated groups in the early phase (24 hours) and up to 4 days after injury. Contusion volume was significantly (p<0.05) reduced in the xenon-treated groups. Xenon treatment significantly (p<0.05) reduced contusion volume when xenon was given 15 minutes after injury or when treatment was delayed 1 hour or 3 hours after injury. Neurological outcome was significantly (p<0.05) improved when xenon treatment was given 15 minutes or 1 hour after injury. Improvements in locomotor function (p<0.05) were observed in the xenon-treated group, 1 month after trauma. Conclusions These results show for the first time that xenon improves neurological outcome and reduces contusion volume following traumatic brain injury in mice. In this model, xenon application has a therapeutic time window of up to at least 3 hours. These findings support the idea that xenon may be of benefit as a neuroprotective treatment in brain trauma patients. PMID:25188549

Xenon improves neurologic outcome and reduces secondary injury following trauma in an in vivo model of traumatic brain injury.

PubMed

Campos-Pires, Rita; Armstrong, Scott P; Sebastiani, Anne; Luh, Clara; Gruss, Marco; Radyushkin, Konstantin; Hirnet, Tobias; Werner, Christian; Engelhard, Kristin; Franks, Nicholas P; Thal, Serge C; Dickinson, Robert

2015-01-01

To determine the neuroprotective efficacy of the inert gas xenon following traumatic brain injury and to determine whether application of xenon has a clinically relevant therapeutic time window. Controlled animal study. University research laboratory. Male C57BL/6N mice (n = 196). Seventy-five percent xenon, 50% xenon, or 30% xenon, with 25% oxygen (balance nitrogen) treatment following mechanical brain lesion by controlled cortical impact. Outcome following trauma was measured using 1) functional neurologic outcome score, 2) histological measurement of contusion volume, and 3) analysis of locomotor function and gait. Our study shows that xenon treatment improves outcome following traumatic brain injury. Neurologic outcome scores were significantly (p < 0.05) better in xenon-treated groups in the early phase (24 hr) and up to 4 days after injury. Contusion volume was significantly (p < 0.05) reduced in the xenon-treated groups. Xenon treatment significantly (p < 0.05) reduced contusion volume when xenon was given 15 minutes after injury or when treatment was delayed 1 or 3 hours after injury. Neurologic outcome was significantly (p < 0.05) improved when xenon treatment was given 15 minutes or 1 hour after injury. Improvements in locomotor function (p < 0.05) were observed in the xenon-treated group, 1 month after trauma. These results show for the first time that xenon improves neurologic outcome and reduces contusion volume following traumatic brain injury in mice. In this model, xenon application has a therapeutic time window of up to at least 3 hours. These findings support the idea that xenon may be of benefit as a neuroprotective treatment in patients with brain trauma.

Bone marrow stem cells assuage radiation-induced damage in a murine model of distraction osteogenesis: A histomorphometric evaluation.

PubMed

Zheutlin, Alexander R; Deshpande, Sagar S; Nelson, Noah S; Kang, Stephen Y; Gallagher, Kathleen K; Polyatskaya, Yekaterina; Rodriguez, Jose J; Donneys, Alexis; Ranganathan, Kavitha; Buchman, Steven R

2016-05-01

The purpose of this study is to determine if intraoperatively placed bone marrow stem cells (BMSCs) will permit successful osteocyte and mature bone regeneration in an isogenic murine model of distraction osteogenesis (DO) following radiation therapy (XRT). Lewis rats were split into three groups, DO only (Control), XRT followed by DO (xDO) and XRT followed by DO with intraoperatively placed BMSCs (xDO-BMSC). Coronal sections from the distraction site were obtained, stained and analyzed via statistical analysis with analysis of variance (ANOVA) and subsequent Tukey or Games-Howell post-hoc tests. Comparison of the xDO-BMSC and xDO groups demonstrated significantly improved osteocyte count (87.15 ± 10.19 vs. 67.88 ± 15.38, P = 0.00), and empty lacunae number (2.18 ± 0.79 vs 12.34 ± 6.61, P = 0.00). Quantitative analysis revealed a significant decrease in immature osteoid volume relative to total volume (P = 0.00) and improved the ratio of mature woven bone to immature osteoid (P = 0.02) in the xDO-BMSC compared with the xDO group. No significant differences were found between the Control and xDO-BMSC groups. In an isogenic murine model of DO, BMSC therapy assuaged XRT-induced cellular depletion, resulting in a significant improvement in histological and histomorphometric outcomes. Copyright © 2016 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Structure of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Criteria for Obsessive–Compulsive Personality Disorder in Patients With Binge Eating Disorder

PubMed Central

Ansell, Emily B; Pinto, Anthony; Edelen, Maria Orlando; Grilo, Carlos M

2013-01-01

Objective To examine 1-, 2-, and 3-factor model structures through confirmatory analytic procedures for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) obsessive–compulsive personality disorder (OCPD) criteria in patients with binge eating disorder (BED). Method Participants were consecutive outpatients (n = 263) with binge eating disorder and were assessed with semi-structured interviews. The 8 OCPD criteria were submitted to confirmatory factor analyses in Mplus Version 4.2 (Los Angeles, CA) in which previously identified factor models of OCPD were compared for fit, theoretical relevance, and parsimony. Nested models were compared for significant improvements in model fit. Results Evaluation of indices of fit in combination with theoretical considerations suggest a multifactorial model is a significant improvement in fit over the current DSM-IV single-factor model of OCPD. Though the data support both 2- and 3-factor models, the 3-factor model is hindered by an underspecified third factor. Conclusion A multifactorial model of OCPD incorporating the factors perfectionism and rigidity represents the best compromise of fit and theory in modelling the structure of OCPD in patients with BED. A third factor representing miserliness may be relevant in BED populations but needs further development. The perfectionism and rigidity factors may represent distinct intrapersonal and interpersonal attempts at control and may have implications for the assessment of OCPD. PMID:19087485

Structure of diagnostic and statistical manual of mental disorders, fourth edition criteria for obsessive-compulsive personality disorder in patients with binge eating disorder.

PubMed

Ansell, Emily B; Pinto, Anthony; Edelen, Maria Orlando; Grilo, Carlos M

2008-12-01

To examine 1-, 2-, and 3-factor model structures through confirmatory analytic procedures for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) obsessive-compulsive personality disorder (OCPD) criteria in patients with binge eating disorder (BED). Participants were consecutive outpatients (n = 263) with binge eating disorder and were assessed with semi-structured interviews. The 8 OCPD criteria were submitted to confirmatory factor analyses in Mplus Version 4.2 (Los Angeles, CA) in which previously identified factor models of OCPD were compared for fit, theoretical relevance, and parsimony. Nested models were compared for significant improvements in model fit. Evaluation of indices of fit in combination with theoretical considerations suggest a multifactorial model is a significant improvement in fit over the current DSM-IV single- factor model of OCPD. Though the data support both 2- and 3-factor models, the 3-factor model is hindered by an underspecified third factor. A multifactorial model of OCPD incorporating the factors perfectionism and rigidity represents the best compromise of fit and theory in modelling the structure of OCPD in patients with BED. A third factor representing miserliness may be relevant in BED populations but needs further development. The perfectionism and rigidity factors may represent distinct intrapersonal and interpersonal attempts at control and may have implications for the assessment of OCPD.

Cost reduction from resolution/improvement of carcinoid syndrome symptoms following treatment with above-standard dose of octreotide LAR.

PubMed

Huynh, Lynn; Totev, Todor; Vekeman, Francis; Neary, Maureen P; Duh, Mei S; Benson, Al B

2017-09-01

To calculate the cost reduction associated with diarrhea/flushing symptom resolution/improvement following treatment with above-standard dose octreotide-LAR from the commercial payor's perspective. Diarrhea and flushing are two major carcinoid syndrome symptoms of neuroendocrine tumor (NET). Previously, a study of NET patients from three US tertiary oncology centers (NET 3-Center Study) demonstrated that dose escalation of octreotide LAR to above-standard dose resolved/improved diarrhea/flushing in 79% of the patients within 1 year. Time course of diarrhea/flushing symptom data were collected from the NET 3-Center Study. Daily healthcare costs were calculated from a commercial claims database analysis. For the patient cohort experiencing any diarrhea/flushing symptom resolution/improvement, their observation period was divided into days of symptom resolution/improvement or no improvement, which were then multiplied by the respective daily healthcare cost and summed over 1 year to yield the blended mean annual cost per patient. For patients who experienced no diarrhea/flushing symptom improvement, mean annual daily healthcare cost of diarrhea/flushing over a 1-year period was calculated. The economic model found that 108 NET patients who experienced diarrhea/flushing symptom resolution/improvement within 1 year had statistically significantly lower mean annual healthcare cost/patient than patients with no symptom improvement, by $14,766 (p = .03). For the sub-set of 85 patients experiencing resolution/improvement of diarrhea, their cost reduction was more pronounced, at $18,740 (p = .01), statistically significantly lower than those with no improvement; outpatient costs accounted for 56% of the cost reduction (p = .02); inpatient costs, emergency department costs, and pharmacy costs accounted for the remaining 44%. The economic model relied on two different sources of data, with some heterogeneity in the prior treatment and disease status of patients. Symptom resolution/improvement of diarrhea/flushing after treatment with an above-standard dose of octreotide-LAR in NET was associated with a statistically significant healthcare cost decrease compared to a scenario of no symptom improvement.

Comment on 'Modeling of Convective-Stratiform Precipitation Processes: Sensitivity to Partitioning Methods' by Matthias Steiner

NASA Technical Reports Server (NTRS)

Lang, Steve; Tao, W.-K.; Simpson, J.; Ferrier, B.

2003-01-01

Despite the obvious notion that the presence of hail or graupel is a good indication of convection, the model results show this does not provide an objective benchmark partly due to the unrealistic presence of small amounts of hail or graupel throughout the anvil in the model but mainly because of the significant amounts of hail or graupel, especially in the tropical TOGA COARE simulation, in the transition zone. Without use of a "transition" category, it is open to debate as how this region should best be defined, as stratiform or as convective. So, the presence of significant hail or graupel contents in this zone significantly degrades its use an objective benchmark for convection. The separation algorithm comparison was done in the context of a cloud-resolving model. These models are widely used and serve a variety of purposes especially with regard to retrieving information that cannot be directly measured by providing synthetic data sets that are consistent and complete. Separation algorithms are regularly applied in these models. However, as with any modeling system, these types 'of models are constantly being improved to overcome any known deficiencies and make them more accurate representations of observed systems. The presence of hail and graupel in the anvil and the bias towards heavy rainfall rates are two such examples of areas that need improvement. Since, both of these can effect the perceived performance of the separation algorithms, the Lang et al. (2003) study did not want to overstate the relative performance of any specific algorithms.

High-School Chemistry Students' Performance and Gender Differences in a Computerized Molecular Modeling Learning Environment

NASA Astrophysics Data System (ADS)

Barnea, Nitza; Dori, Yehudit J.

1999-12-01

Computerized molecular modeling (CMM) contributes to the development of visualization skills via vivid animation of three dimensional representations. Its power to illustrate and explore phenomena in chemistry teaching stems from the convenience and simplicity of building molecules of any size and color in a number of presentation styles. A new CMM-based learning environment for teaching and learning chemistry in Israeli high schools has been designed and implemented. Three tenth grade experimental classes used this discovery CMM approach, while two other classes, who studied the same topic in the customary approach, served as a control group. We investigated the effects of using molecular modeling on students' spatial ability, understanding of new concepts related to geometric and symbolic representations and students' perception of the model concept. Each variable was examined for gender differences. Students of the experimental group performed better than control group students in all three performance aspects. Experimental group students scored higher than the control group students in the achievement test on structure and bonding. Students' spatial ability improved in both groups, but students from the experimental group scored higher. For the average students in the two groups the improvement in all three spatial ability sub-tests —paper folding, card rotation, and cube comparison—was significantly higher for the experimental group. Experimental group students gained better insight into the model concept than the control group and could explain more phenomena with the aid of a variety of models. Hence, CMM helps in particular to improve the examined cognitive aspects of the average student population. In most of the achievement and spatial ability tests no significant differences between the genders were found, but in some aspects of model perception and verbal argumentation differences still exist. Experimental group females improved their model perception more than the control group females in understanding ways to create models and in the role of models as mental structures and prediction tools. Teachers' and students' feedback on the CMM learning environment was found to be positive, as it helped them understand concepts in molecular geometry and bonding. The results of this study suggest that teaching/learning of topics in chemistry that are related to three dimensional structures can be improved by using a discovery approach in a computerized learning environment.

Improved blend and tablet properties of fine pharmaceutical powders via dry particle coating.

PubMed

Huang, Zhonghui; Scicolone, James V; Han, Xi; Davé, Rajesh N

2015-01-30

The improvements in the flow and packing of fine pharmaceutical powder blends due to dry coating of micronized acetaminophen (mAPAP, ∼11μm), a model poorly flowing drug, are quantified. Poor flow and packing density of fine excipients (∼20μm) allowed testing the hypothesis that dry coating of cohesive API may counteract poor flow and packing of fine pharmaceutical powder blends. Further, fine excipients could improve compaction and reduce segregation tendency. It was found that flow function coefficient (FFC) and bulk density enhancements for 10%, 30%, and 60% (w/w), API loading blends with dry coated API are significantly higher than those without coated silica. At the highest API loading, for which coarser excipients were also used as reference, the flow and packing of dry coated mAPAP blends were significantly increased regardless of the excipient particle size, exceeding those of a well compacting excipient, Avicel 102. In addition, tensile strength of tablets with fine excipients was significantly higher, indicating improved compactibility. These results show for the first time that dry coating of fine, cohesive API powder leads to significantly improved flow and packing of high API loading blends consisting of fine excipients, while achieving improved tablet compactibility, suggesting suitability for direct compaction. Copyright © 2014 Elsevier B.V. All rights reserved.

Audio visual speech source separation via improved context dependent association model

NASA Astrophysics Data System (ADS)

Kazemi, Alireza; Boostani, Reza; Sobhanmanesh, Fariborz

2014-12-01

In this paper, we exploit the non-linear relation between a speech source and its associated lip video as a source of extra information to propose an improved audio-visual speech source separation (AVSS) algorithm. The audio-visual association is modeled using a neural associator which estimates the visual lip parameters from a temporal context of acoustic observation frames. We define an objective function based on mean square error (MSE) measure between estimated and target visual parameters. This function is minimized for estimation of the de-mixing vector/filters to separate the relevant source from linear instantaneous or time-domain convolutive mixtures. We have also proposed a hybrid criterion which uses AV coherency together with kurtosis as a non-Gaussianity measure. Experimental results are presented and compared in terms of visually relevant speech detection accuracy and output signal-to-interference ratio (SIR) of source separation. The suggested audio-visual model significantly improves relevant speech classification accuracy compared to existing GMM-based model and the proposed AVSS algorithm improves the speech separation quality compared to reference ICA- and AVSS-based methods.

An improved car-following model with two preceding cars' average speed

NASA Astrophysics Data System (ADS)

Yu, Shao-Wei; Shi, Zhong-Ke

2015-01-01

To better describe cooperative car-following behaviors under intelligent transportation circumstances and increase roadway traffic mobility, the data of three successive following cars at a signalized intersection of Jinan in China were obtained and employed to explore the linkage between two preceding cars' average speed and car-following behaviors. The results indicate that two preceding cars' average velocity has significant effects on the following car's motion. Then an improved car-following model considering two preceding cars' average velocity was proposed and calibrated based on full velocity difference model and some numerical simulations were carried out to study how two preceding cars' average speed affected the starting process and the traffic flow evolution process with an initial small disturbance, the results indicate that the improved car-following model can qualitatively describe the impacts of two preceding cars' average velocity on traffic flow and that taking two preceding cars' average velocity into account in designing the control strategy for the cooperative adaptive cruise control system can improve the stability of traffic flow, suppress the appearance of traffic jams and increase the capacity of signalized intersections.

Microburst vertical wind estimation from horizontal wind measurements

NASA Technical Reports Server (NTRS)

Vicroy, Dan D.

1994-01-01

The vertical wind or downdraft component of a microburst-generated wind shear can significantly degrade airplane performance. Doppler radar and lidar are two sensor technologies being tested to provide flight crews with early warning of the presence of hazardous wind shear. An inherent limitation of Doppler-based sensors is the inability to measure velocities perpendicular to the line of sight, which results in an underestimate of the total wind shear hazard. One solution to the line-of-sight limitation is to use a vertical wind model to estimate the vertical component from the horizontal wind measurement. The objective of this study was to assess the ability of simple vertical wind models to improve the hazard prediction capability of an airborne Doppler sensor in a realistic microburst environment. Both simulation and flight test measurements were used to test the vertical wind models. The results indicate that in the altitude region of interest (at or below 300 m), the simple vertical wind models improved the hazard estimate. The radar simulation study showed that the magnitude of the performance improvement was altitude dependent. The altitude of maximum performance improvement occurred at about 300 m.

Measurement of Nitrogen Hyperfine Structure on the 53 CM (562 MHz) Butyronitrile Line

NASA Astrophysics Data System (ADS)

Dewberry, Christopher T.; Grubbs, Garry S. Grubbs, II; Raphelt, Andrew; Cooke, Stephen A.

2009-06-01

Recent improvements to our cavity-based Fourier transform radiofrequency spectrometer will be presented. Amongst other improvements use of Miteq amp, model AMF-6F-00100400-10-10P (0.1 GHz to 4 GHz, 65 dB gain minimum, 1 dB noise figure maximum) together with shielding from an improved Faraday cage have significantly helped us in this regard. Electromagnetic fields within our near-spherical cavity have been modeled and results will be presented. We have been able to easily resolve the nitrogen hyperfine structure on the ^aQ_{0,-1} transition 1_{1,0} ← 1_{1,1} located at 562 MHz. This result will be discussed.

On improving the performance of nonphotochemical quenching in CP29 light-harvesting antenna complex

NASA Astrophysics Data System (ADS)

Berman, Gennady P.; Nesterov, Alexander I.; Sayre, Richard T.; Still, Susanne

2016-03-01

We model and simulate the performance of charge-transfer in nonphotochemical quenching (NPQ) in the CP29 light-harvesting antenna-complex associated with photosystem II (PSII). The model consists of five discrete excitonic energy states and two sinks, responsible for the potentially damaging processes and charge-transfer channels, respectively. We demonstrate that by varying (i) the parameters of the chlorophyll-based dimer, (ii) the resonant properties of the protein-solvent environment interaction, and (iii) the energy transfer rates to the sinks, one can significantly improve the performance of the NPQ. Our analysis suggests strategies for improving the performance of the NPQ in response to environmental changes, and may stimulate experimental verification.

Development of a Higher Fidelity Model for the Cascade Distillation Subsystem (CDS)

NASA Technical Reports Server (NTRS)

Perry, Bruce; Anderson, Molly

2014-01-01

Significant improvements have been made to the ACM model of the CDS, enabling accurate predictions of dynamic operations with fewer assumptions. The model has been utilized to predict how CDS performance would be impacted by changing operating parameters, revealing performance trade-offs and possibilities for improvement. CDS efficiency is driven by the THP coefficient of performance, which in turn is dependent on heat transfer within the system. Based on the remaining limitations of the simulation, priorities for further model development include: center dot Relaxing the assumption of total condensation center dot Incorporating dynamic simulation capability for the buildup of dissolved inert gasses in condensers center dot Examining CDS operation with more complex feeds center dot Extending heat transfer analysis to all surfaces

A new approach to correct the QT interval for changes in heart rate using a nonparametric regression model in beagle dogs.

PubMed

Watanabe, Hiroyuki; Miyazaki, Hiroyasu

2006-01-01

Over- and/or under-correction of QT intervals for changes in heart rate may lead to misleading conclusions and/or masking the potential of a drug to prolong the QT interval. This study examines a nonparametric regression model (Loess Smoother) to adjust the QT interval for differences in heart rate, with an improved fitness over a wide range of heart rates. 240 sets of (QT, RR) observations collected from each of 8 conscious and non-treated beagle dogs were used as the materials for investigation. The fitness of the nonparametric regression model to the QT-RR relationship was compared with four models (individual linear regression, common linear regression, and Bazett's and Fridericia's correlation models) with reference to Akaike's Information Criterion (AIC). Residuals were visually assessed. The bias-corrected AIC of the nonparametric regression model was the best of the models examined in this study. Although the parametric models did not fit, the nonparametric regression model improved the fitting at both fast and slow heart rates. The nonparametric regression model is the more flexible method compared with the parametric method. The mathematical fit for linear regression models was unsatisfactory at both fast and slow heart rates, while the nonparametric regression model showed significant improvement at all heart rates in beagle dogs.

[Compatible biomass models of natural spruce (Picea asperata)].

PubMed

Wang, Jin Chi; Deng, Hua Feng; Huang, Guo Sheng; Wang, Xue Jun; Zhang, Lu

2017-10-01

By using nonlinear measurement error method, the compatible tree volume and above ground biomass equations were established based on the volume and biomass data of 150 sampling trees of natural spruce (Picea asperata). Two approaches, controlling directly under total aboveground biomass and controlling jointly from level to level, were used to design the compatible system for the total aboveground biomass and the biomass of four components (stem, bark, branch and foliage), and the total ground biomass could be estimated independently or estimated simultaneously in the system. The results showed that the R 2 of the one variable and bivariate compatible tree volume and aboveground biomass equations were all above 0.85, and the maximum value reached 0.99. The prediction effect of the volume equations could be improved significantly when tree height was included as predictor, while it was not significant in biomass estimation. For the compatible biomass systems, the one variable model based on controlling jointly from level to level was better than the model using controlling directly under total above ground biomass, but the bivariate models of the two methods were similar. Comparing the imitative effects of the one variable and bivariate compatible biomass models, the results showed that the increase of explainable variables could significantly improve the fitness of branch and foliage biomass, but had little effect on other components. Besides, there was almost no difference between the two methods of estimation based on the comparison.

A Successful Implementation Strategy to Support Adoption of Decision Making in Mental Health Services.

PubMed

MacDonald-Wilson, Kim L; Hutchison, Shari L; Karpov, Irina; Wittman, Paul; Deegan, Patricia E

2017-04-01

Individual involvement in treatment decisions with providers, often through the use of decision support aids, improves quality of care. This study investigates an implementation strategy to bring decision support to community mental health centers (CMHC). Fifty-two CMHCs implemented a decision support toolkit supported by a 12-month learning collaborative using the Breakthrough Series model. Participation in learning collaborative activities was high, indicating feasibility of the implementation model. Progress by staff in meeting process aims around utilization of components of the toolkit improved significantly over time (p < .0001). Survey responses by individuals in service corroborate successful implementation. Community-based providers were able to successfully implement decision support in mental health services as evidenced by improved process outcomes and sustained practices over 1 year through the structure of the learning collaborative model.

Genetic modifications of pigs for medicine and agriculture

PubMed Central

Whyte, Jeffrey J.; Prather, Randall S.

2011-01-01

SUMMARY Genetically modified swine hold great promise in the fields of agriculture and medicine. Currently, these swine are being used to optimize production of quality meat, to improve our understanding of the biology of disease resistance, and to reduced waste. In the field of biomedicine, swine are anatomically and physiologically analogous to humans. Alterations of key swine genes in disease pathways provide model animals to improve our understanding of the causes and potential treatments of many human genetic disorders. The completed sequencing of the swine genome will significantly enhance the specificity of genetic modifications, and allow for more accurate representations of human disease based on syntenic genes between the two species. Improvements in both methods of gene alteration and efficiency of model animal production are key to enabling routine use of these swine models in medicine and agriculture. PMID:21671302

Impact of a Stochastic Parameterization Scheme on El Nino-Southern Oscillation in the Community Climate System Model

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Berner, J.; Sardeshmukh, P. D.

2017-12-01

Stochastic parameterizations have been used for more than a decade in atmospheric models. They provide a way to represent model uncertainty through representing the variability of unresolved sub-grid processes, and have been shown to have a beneficial effect on the spread and mean state for medium- and extended-range forecasts. There is increasing evidence that stochastic parameterization of unresolved processes can improve the bias in mean and variability, e.g. by introducing a noise-induced drift (nonlinear rectification), and by changing the residence time and structure of flow regimes. We present results showing the impact of including the Stochastically Perturbed Parameterization Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. SPPT results in a significant improvement in the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. We use a Linear Inverse Modelling framework to gain insight into the mechanisms by which SPPT has improved ENSO-variability.

The effectiveness of CPI model to improve positive attitude toward science (PATS) for pre-service physics teacher

NASA Astrophysics Data System (ADS)

Sunarti, T.; Wasis; Madlazim; Suyidno; Prahani, B. K.

2018-03-01

In the previous research, learning material based Construction, Production, and Implementation (CPI) model has been developed to improve scientific literacy and positive attitude toward science for pre-service physics teacher. CPI model has 4 phases, included: 1) Motivation; 2) Construction (Cycle I); 3) Production (Cycle II); and 4) Evaluation. This research is aimed to analyze the effectiveness of CPI model towards the improvement Positive Attitude toward Science (PATS) for pre-service physics teacher. This research used one group pre-test and post-test design on 160 pre-service physics teacher divided into 4 groups at Lambung Mangkurat University and Surabaya State University (Indonesia), academic year 2016/2017. Data collection was conducted through questioner, observation, and interview. Positive attitude toward science for pre-service physics teacher measurement were conducted through Positive Attitude toward Science Evaluation Sheet (PATSES). The data analysis technique was done by using Wilcoxon test and n-gain. The results showed that there was a significant increase in positive attitude toward science for pre-service physics teacher at α = 5%, with n-gain average of high category. Thus, the CPI model is effective for improving positive attitude toward science for pre-service physics teacher.

The Impact of New Payment Models on Quality of Diabetes Care and Outcomes.

PubMed

McGinley, Erin L; Gabbay, Robert A

2016-06-01

Historic changes in healthcare reimbursement and payment models due to the Affordable Care Act in the United States have the potential to transform how providers care for chronic diseases such as diabetes. Payment experimentation has provided insights into how changing incentives for primary care providers can yield improvements in the triple aim: improving patient experience, improving the health of populations, and reducing costs of healthcare. Much of this has involved leveraging widespread adoption of the patient-centered medical home (PCMH) with diabetes often the focus. While evidence is mounting that the PCMH can improve diabetes outcomes, some PCMH demonstrations have displayed mixed results. One of the first large-scale PCMH demonstrations developed around diabetes was conducted by the Commonwealth of Pennsylvania. Different payment models were employed across a series of staggered regional rollouts that provided a case study for the influence of innovative payment models. These learning laboratories provide insights into the role of reimbursement models and changes in how practice transformation is implemented. Ultimately, evolving payment systems focused on the total cost of care, such as Accountable Care Organizations, hold promise to transform diabetes care and produce significant cost savings through the prevention of complications.

Changes in Underlying Determinants Explain Rapid Increases in Child Linear Growth in Alive & Thrive Study Areas between 2010 and 2014 in Bangladesh and Vietnam123

PubMed Central

Headey, Derek; Frongillo, Edward A; Tran, Lan Mai; Rawat, Rahul; Ruel, Marie T; Menon, Purnima

2017-01-01

Background: Child linear growth sometimes improves in both intervention and comparison groups in evaluations of nutrition interventions, possibly because of spillover intervention effects to nonintervention areas or improvements in underlying determinants of nutritional change in both areas. Objective: We aimed to understand what changes in underlying socioeconomic characteristics and behavioral factors are important in explaining improvements in child linear growth. Methods: Baseline (2010) and endline (2014) surveys from the Alive & Thrive impact evaluation were used to identify the underlying determinants of height-for-age z scores (HAZs) among children aged 24–48 mo in Bangladesh (n = 4311) and 24–59 mo in Vietnam (n = 4002). Oaxaca-Blinder regression decompositions were used to examine which underlying determinants contributed to HAZ changes over time. Results: HAZs improved significantly between 2010 and 2014 in Bangladesh (∼0.18 SDs) and Vietnam (0.25 SDs). Underlying determinants improved substantially over time and were larger in Vietnam than in Bangladesh. Multiple regression models revealed significant associations between changes in HAZs and socioeconomic status (SES), food security, maternal education, hygiene, and birth weight in both countries. Changes in HAZs were significantly associated with maternal nutrition knowledge and child dietary diversity in Bangladesh, and with prenatal visits in Vietnam. Improvements in maternal nutrition knowledge in Bangladesh accounted for 20% of the total HAZ change, followed by maternal education (13%), SES (12%), hygiene (10%), and food security (9%). HAZ improvements in Vietnam were accounted for by changes in SES (26%), prenatal visits (25%), hygiene (19%), child birth weight (10%), and maternal education (7%). The decomposition models in both countries performed well, explaining >75% of the HAZ changes. Conclusions: Decomposition is a useful and simple technique for analyzing nonintervention drivers of nutritional change in intervention and comparison areas. Improvements in underlying determinants explained rapid improvements in HAZs between 2010 and 2014 in Bangladesh and Vietnam. PMID:28122930

Changes in Underlying Determinants Explain Rapid Increases in Child Linear Growth in Alive & Thrive Study Areas between 2010 and 2014 in Bangladesh and Vietnam.

PubMed

Nguyen, Phuong Hong; Headey, Derek; Frongillo, Edward A; Tran, Lan Mai; Rawat, Rahul; Ruel, Marie T; Menon, Purnima

2017-03-01

Background: Child linear growth sometimes improves in both intervention and comparison groups in evaluations of nutrition interventions, possibly because of spillover intervention effects to nonintervention areas or improvements in underlying determinants of nutritional change in both areas. Objective: We aimed to understand what changes in underlying socioeconomic characteristics and behavioral factors are important in explaining improvements in child linear growth. Methods: Baseline (2010) and endline (2014) surveys from the Alive & Thrive impact evaluation were used to identify the underlying determinants of height-for-age z scores (HAZs) among children aged 24-48 mo in Bangladesh ( n = 4311) and 24-59 mo in Vietnam ( n = 4002). Oaxaca-Blinder regression decompositions were used to examine which underlying determinants contributed to HAZ changes over time. Results: HAZs improved significantly between 2010 and 2014 in Bangladesh (∼0.18 SDs) and Vietnam (0.25 SDs). Underlying determinants improved substantially over time and were larger in Vietnam than in Bangladesh. Multiple regression models revealed significant associations between changes in HAZs and socioeconomic status (SES), food security, maternal education, hygiene, and birth weight in both countries. Changes in HAZs were significantly associated with maternal nutrition knowledge and child dietary diversity in Bangladesh, and with prenatal visits in Vietnam. Improvements in maternal nutrition knowledge in Bangladesh accounted for 20% of the total HAZ change, followed by maternal education (13%), SES (12%), hygiene (10%), and food security (9%). HAZ improvements in Vietnam were accounted for by changes in SES (26%), prenatal visits (25%), hygiene (19%), child birth weight (10%), and maternal education (7%). The decomposition models in both countries performed well, explaining >75% of the HAZ changes. Conclusions: Decomposition is a useful and simple technique for analyzing nonintervention drivers of nutritional change in intervention and comparison areas. Improvements in underlying determinants explained rapid improvements in HAZs between 2010 and 2014 in Bangladesh and Vietnam.

Collagen Peptides from Crucian Skin Improve Calcium Bioavailability and Structural Characterization by HPLC-ESI-MS/MS.

PubMed

Hou, Tao; Liu, Yanshuang; Guo, Danjun; Li, Bo; He, Hui

2017-10-11

The effects of collagen peptides (CPs), which are derived from crucian skin, were investigated in a retinoic acid-induced bone loss model. The level of serum bone alkaline phosphatase (BALP) in the model group (117.65 ± 4.66 units/L) was significantly higher than those of the other three groups (P < 0.05). After treatment with 600 and 1200 mg of CPs/kg, the level of BALP decreased to 85.26 ± 7.35 and 97.03 ± 7.21 units/L, respectively. After treatment with 600 mg of CPs/kg, the bone calcium content significantly increased by 22% (femur) and 12.38% (tibia) compared to those of the model group. In addition, the bone mineral density in the 600 mg of CPs/kg group was significantly higher (femur, 0.37 ± 0.02 g/cm 2 ; tibia, 0.33 ± 0.02 g/cm 2 ) than in the model group (femur, 0.26 ± 0.01 g/cm 2 ; tibia, 0.23 ± 0.02 g/cm 2 ). The morphology results indicated bone structure improved after the treatment with CPs. Structural characterization demonstrated that Glu, Lys, and Arg play important roles in binding calcium and promoting calcium uptake. Our results indicated that CPs could promote calcium uptake and regulate bone formation.

Adjoint-Based Climate Model Tuning: Application to the Planet Simulator

NASA Astrophysics Data System (ADS)

Lyu, Guokun; Köhl, Armin; Matei, Ion; Stammer, Detlef

2018-01-01

The adjoint method is used to calibrate the medium complexity climate model "Planet Simulator" through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.

Using Neural Networks to Improve the Performance of Radiative Transfer Modeling Used for Geometry Dependent LER Calculations

NASA Astrophysics Data System (ADS)

Fasnacht, Z.; Qin, W.; Haffner, D. P.; Loyola, D. G.; Joiner, J.; Krotkov, N. A.; Vasilkov, A. P.; Spurr, R. J. D.

2017-12-01

In order to estimate surface reflectance used in trace gas retrieval algorithms, radiative transfer models (RTM) such as the Vector Linearized Discrete Ordinate Radiative Transfer Model (VLIDORT) can be used to simulate the top of the atmosphere (TOA) radiances with advanced models of surface properties. With large volumes of satellite data, these model simulations can become computationally expensive. Look up table interpolation can improve the computational cost of the calculations, but the non-linear nature of the radiances requires a dense node structure if interpolation errors are to be minimized. In order to reduce our computational effort and improve the performance of look-up tables, neural networks can be trained to predict these radiances. We investigate the impact of using look-up table interpolation versus a neural network trained using the smart sampling technique, and show that neural networks can speed up calculations and reduce errors while using significantly less memory and RTM calls. In future work we will implement a neural network in operational processing to meet growing demands for reflectance modeling in support of high spatial resolution satellite missions.

Development of a Dynamic, End-to-End Free Piston Stirling Convertor Model

NASA Technical Reports Server (NTRS)

Regan, Timothy F.; Gerber, Scott S.; Roth, Mary Ellen

2004-01-01

A dynamic model for a free-piston Stirling convertor is being developed at the NASA Glenn Research Center. The model is an end-to-end system model that includes the cycle thermodynamics, the dynamics, and electrical aspects of the system. The subsystems of interest are the heat source, the springs, the moving masses, the linear alternator, the controller, and the end-user load. The envisioned use of the model will be in evaluating how changes in a subsystem could affect the operation of the convertor. The model under development will speed the evaluation of improvements to a subsystem and aid in determining areas in which most significant improvements may be found. One of the first uses of the end-toend model will be in the development of controller architectures. Another related area is in evaluating changes to details in the linear alternator.

Development of a Dynamic, End-to-End Free Piston Stirling Convertor Model

NASA Astrophysics Data System (ADS)

Regan, Timothy F.; Gerber, Scott S.; Roth, Mary Ellen

2003-01-01

A dynamic model for a free-piston Stirling convertor is being developed at the NASA Glenn Research Center. The model is an end-to-end system model that includes the cycle thermodynamics, the dynamics, and electrical aspects of the system. The subsystems of interest are the heat source, the springs, the moving masses, the linear alternator, the controller and the end-user load. The envisioned use of the model will be in evaluating how changes in a subsystem could affect the operation of the convertor. The model under development will speed the evaluation of improvements to a subsystem and aid in determining areas in which most significant improvements may be found. One of the first uses of the end-to-end model will be in the development of controller architectures. Another related area is in evaluating changes to details in the linear alternator.

Polar versus Cartesian velocity models for maneuvering target tracking with IMM

NASA Astrophysics Data System (ADS)

Laneuville, Dann

This paper compares various model sets in different IMM filters for the maneuvering target tracking problem. The aim is to see whether we can improve the tracking performance of what is certainly the most widely used model set in the literature for the maneuvering target tracking problem: a Nearly Constant Velocity model and a Nearly Coordinated Turn model. Our new challenger set consists of a mixed Cartesian position and polar velocity state vector to describe the uniform motion segments and is augmented with the turn rate to obtain the second model for the maneuvering segments. This paper also gives a general procedure to discretize up to second order any non-linear continuous time model with linear diffusion. Comparative simulations on an air defence scenario with a 2D radar, show that this new approach improves significantly the tracking performance in this case.

Lung function and pulmonary artery blood flow following prenatal maternal retinoic acid and imatinib in the nitrofen model of congenital diaphragmatic hernia.

PubMed

Burgos, Carmen Mesas; Davey, Marcus G; Riley, John S; Jia, Huimin; Flake, Alan W; Peranteau, William H

2017-12-19

Lung and pulmonary vascular maldevelopment in congenital diaphragmatic hernia (CDH) results in significant morbidity and mortality. Retinoic acid (RA) and imatinib have been shown to improve pulmonary morphology following prenatal administration in the rat nitrofen-induced CDH model. It remains unclear if these changes translate into improved function. We evaluated the effect of prenatal RA and imatinib on postnatal lung function, structure, and pulmonary artery (PA) blood flow in the rat CDH model. Olive oil or nitrofen was administered alone or in combination with RA or imatinib to pregnant rats. Pups were assessed for PA blood flow by ultrasound and pulmonary function/morphology following delivery, intubation, and short-term ventilation. Neither RA nor imatinib had a negative effect on lung and body growth. RA accelerated lung maturation indicated by increased alveoli number and thinner interalveolar septa and was associated with decreased PA resistance and improved oxygenation. With the exception of a decreased PA pulsatility index, no significant changes in morphology and pulmonary function were noted following imatinib. Prenatal treatment with RA but not imatinib was associated with improved pulmonary morphology and function, and decreased pulmonary vascular resistance. This study highlights the potential of prenatal pharmacologic therapies, such as RA, for management of CDH. Copyright © 2017 Elsevier Inc. All rights reserved.

Troposphere gradients from the ECMWF in VLBI analysis

NASA Astrophysics Data System (ADS)

Boehm, Johannes; Schuh, Harald

2007-06-01

Modeling path delays in the neutral atmosphere for the analysis of Very Long Baseline Interferometry (VLBI) observations has been improved significantly in recent years by the use of elevation-dependent mapping functions based on data from numerical weather models. In this paper, we present a fast way of extracting both, hydrostatic and wet, linear horizontal gradients for the troposphere from data of the European Centre for Medium-range Weather Forecasts (ECMWF) model, as it is realized at the Vienna University of Technology on a routine basis for all stations of the International GNSS (Global Navigation Satellite Systems) Service (IGS) and International VLBI Service for Geodesy and Astrometry (IVS) stations. This approach only uses information about the refractivity gradients at the site vertical, but no information from the line-of-sight. VLBI analysis of the CONT02 and CONT05 campaigns, as well as all IVS-R1 and IVS-R4 sessions in the first half of 2006, shows that fixing these a priori gradients improves the repeatability for 74% (40 out of 54) of the VLBI baseline lengths compared to fixing zero or constant a priori gradients, and improves the repeatability for the majority of baselines compared to estimating 24-h offsets for the gradients. Only if 6-h offsets are estimated, the baseline length repeatabilities significantly improve, no matter which a priori gradients are used.

Looking good or doing better? Patterns of decoupling in the implementation of clinical directorates.

PubMed

Mascia, Daniele; Morandi, Federica; Cicchetti, Americo

2014-01-01

The interest toward hospital restructuring has risen significantly in recent years. In spite of its potential benefits, often organizational restructuring in health care produces unexpected consequences. Extant research suggests that institutional theory provides a powerful theoretical lens through which hospital restructuring can be described and explained. According to this perspective, the effectiveness of change is strongly related to the extent to which innovative arrangements, tools, or practices are adopted and implemented within hospitals. Whenever these new arrangements require a substantial modification of internal processes and practices, resistance to implementation emerges and organizational change is likely to become neutralized. This study analyzes how hospital organizations engage in decoupling by adopting but not implementing a new organizational model named clinical directorate. We collected primary data on the diffusion of the clinical directorate model, which was mandated by law in the Italian National Health Service to improve hospital services. We surveyed the adoption and implementation of the clinical directorate model by monitoring the presence of clinical governance tools (measures for the quality improvement of hospital services) within single directorates. In particular, we compared hospitals that adopted the model before (early adopters) or after (later adopters) the mandate was introduced. Hospitals were engaged in decoupling by adopting the new arrangement but not implementing internal practices and tools for quality improvement. The introduction of the law significantly affected the decoupling, with late-adopter hospitals being less likely to implement the adopted model. The present research shows that changes in quality improvement processes may vary in relation to policy makers' interventions aimed at boosting the adoption of new hospital arrangements. Hospital administrators need to be aware and identify the institutional changes that might be driven by law to be able to react consistently with expectations of policymakers.

Does Trabecular Bone Score (TBS) improve the predictive ability of FRAX® for major osteoporotic fractures according to the Japanese Population-Based Osteoporosis (JPOS) cohort study?

PubMed

Tamaki, Junko; Iki, Masayuki; Sato, Yuho; Winzenrieth, Renaud; Kajita, Etsuko; Kagamimori, Sadanobu

2018-02-21

This study examined whether bone microarchitecture determined by Trabecular Bone Score (TBS) is associated with the risk of major osteoporotic fractures independent of FRAX ® in Japanese women. Participants included 1541 women aged ≥ 40 at baseline. Major osteoporotic fractures during a 10-year follow-up period were documented by the Japanese Population-based Osteoporosis Cohort Study. TBS and areal bone mineral density (aBMD) were calculated for the same spinal regions at baseline. To compare the predictive ability of FRAX ® model when used alone versus in combination with TBS, Akaike information criterion (AIC), the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were calculated. We identified 67 events of major osteoporotic fractures. The skeletal sites of the first fracture event were as follows: hip (11), vertebrae (13), radius (42), and humerus (1). The model incorporating FRAX ® [1.35 (95% CI 1.09-1.67) for 1 standard deviation (SD) increase] with TBS [1.46 (95% CI 1.08-1.98) for 1 SD decrease] demonstrated better fit compared to a model consisting of FRAX alone (AIC 528.6 vs 532.7). NRI values for classification accuracy showed significant improvements in the FRAX ® and TBS model, as compared to FRAX ® alone [0.299 (95% CI 0.056-0.541)]. However, there were no significant differences in AUC or IDI between these models. The TBS score is associated with a risk of major osteoporotic fracture independent of FRAX ® score obtained with or without BMD values among Japanese women during a 10-year follow-up period.

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds.

PubMed

Simkovic, Felix; Thomas, Jens M H; Keegan, Ronan M; Winn, Martyn D; Mayans, Olga; Rigden, Daniel J

2016-07-01

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions ('decoys'), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue-residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing.

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds

PubMed Central

Simkovic, Felix; Thomas, Jens M. H.; Keegan, Ronan M.; Winn, Martyn D.; Mayans, Olga; Rigden, Daniel J.

2016-01-01

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions (‘decoys’), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue–residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing. PMID:27437113

Global land-atmosphere coupling associated with cold climate processes

NASA Astrophysics Data System (ADS)

Dutra, Emanuel

This dissertation constitutes an assessment of the role of cold processes, associated with snow cover, in controlling the land-atmosphere coupling. The work was based on model simulations, including offline simulations with the land surface model HTESSEL, and coupled atmosphere simulations with the EC-EARTH climate model. A revised snow scheme was developed and tested in HTESSEL and EC-EARTH. The snow scheme is currently operational at the European Centre for Medium-Range Weather Forecasts integrated forecast system, and in the default configuration of EC-EARTH. The improved representation of the snowpack dynamics in HTESSEL resulted in improvements in the near surface temperature simulations of EC-EARTH. The new snow scheme development was complemented with the option of multi-layer version that showed its potential in modeling thick snowpacks. A key process was the snow thermal insulation that led to significant improvements of the surface water and energy balance components. Similar findings were observed when coupling the snow scheme to lake ice, where lake ice duration was significantly improved. An assessment on the snow cover sensitivity to horizontal resolution, parameterizations and atmospheric forcing within HTESSEL highlighted the role of the atmospheric forcing accuracy and snowpack parameterizations in detriment of horizontal resolution over flat regions. A set of experiments with and without free snow evolution was carried out with EC-EARTH to assess the impact of the interannual variability of snow cover on near surface and soil temperatures. It was found that snow cover interannual variability explained up to 60% of the total interannual variability of near surface temperature over snow covered regions. Although these findings are model dependent, the results showed consistency with previously published work. Furthermore, the detailed validation of the snow dynamics simulations in HTESSEL and EC-EARTH guarantees consistency of the results.

A directional model of tropospheric horizontal gradients in Global Positioning System and its application for particular weather scenarios

NASA Astrophysics Data System (ADS)

Masoumi, Salim; McClusky, Simon; Koulali, Achraf; Tregoning, Paul

2017-04-01

Improper modeling of horizontal tropospheric gradients in GPS analysis induces errors in estimated parameters, with the largest impact on heights and tropospheric zenith delays. The conventional two-axis tilted plane model of horizontal gradients fails to provide an accurate representation of tropospheric gradients under weather conditions with asymmetric horizontal changes of refractivity. A new parametrization of tropospheric gradients whereby an arbitrary number of gradients are estimated as discrete directional wedges is shown via simulations to significantly improve the accuracy of recovered tropospheric zenith delays in asymmetric gradient scenarios. In a case study of an extreme rain event that occurred in September 2002 in southern France, the new directional parametrization is able to isolate the strong gradients in particular azimuths around the GPS stations consistent with the "V" shape spatial pattern of the observed precipitation. In another study of a network of GPS stations in the Sierra Nevada region where highly asymmetric tropospheric gradients are known to exist, the new directional model significantly improves the repeatabilities of the stations in asymmetric gradient situations while causing slightly degraded repeatabilities for the stations in normal symmetric gradient conditions. The average improvement over the entire network is ˜31%, while the improvement for one of the worst affected sites P631 is ˜49% (from 8.5 mm to 4.3 mm) in terms of weighted root-mean-square (WRMS) error and ˜82% (from -1.1 to -0.2) in terms of skewness. At the same station, the use of the directional model changes the estimates of zenith wet delay by 15 mm (˜25%).

A multiple-time-scale turbulence model based on variable partitioning of turbulent kinetic energy spectrum

NASA Technical Reports Server (NTRS)

Kim, S.-W.; Chen, C.-P.

1988-01-01

The paper presents a multiple-time-scale turbulence model of a single point closure and a simplified split-spectrum method. Consideration is given to a class of turbulent boundary layer flows and of separated and/or swirling elliptic turbulent flows. For the separated and/or swirling turbulent flows, the present turbulence model yielded significantly improved computational results over those obtained with the standard k-epsilon turbulence model.

Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy.

PubMed

Vulliemoz, S; Rodionov, R; Carmichael, D W; Thornton, R; Guye, M; Lhatoo, S D; Michel, C M; Duncan, J S; Lemieux, L

2010-02-15

EEG-correlated fMRI (EEG-fMRI) studies can reveal haemodynamic changes associated with Interictal Epileptic Discharges (IED). Methodological improvements are needed to increase sensitivity and specificity for localising the epileptogenic zone. We investigated whether the estimated EEG source activity improved models of the BOLD changes in EEG-fMRI data, compared to conventional < event-related > designs based solely on the visual identification of IED. Ten patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI. EEG Source Imaging (ESI) was performed on intra-fMRI averaged IED to identify the irritative zone. The continuous activity of this estimated IED source (cESI) over the entire recording was used for fMRI analysis (cESI model). The maps of BOLD signal changes explained by cESI were compared to results of the conventional IED-related model. ESI was concordant with non-invasive data in 13/15 different types of IED. The cESI model explained significant additional BOLD variance in regions concordant with video-EEG, structural MRI or, when available, intracranial EEG in 10/15 IED. The cESI model allowed better detection of the BOLD cluster, concordant with intracranial EEG in 4/7 IED, compared to the IED model. In 4 IED types, cESI-related BOLD signal changes were diffuse with a pattern suggestive of contamination of the source signal by artefacts, notably incompletely corrected motion and pulse artefact. In one IED type, there was no significant BOLD change with either model. Continuous EEG source imaging can improve the modelling of BOLD changes related to interictal epileptic activity and this may enhance the localisation of the irritative zone. Copyright 2009 Elsevier Inc. All rights reserved.

Improved Traceability of a Small Satellite Mission Concept to Requirements Using Model Based System Engineering

NASA Technical Reports Server (NTRS)

Reil, Robin L.

2014-01-01

Model Based Systems Engineering (MBSE) has recently been gaining significant support as a means to improve the "traditional" document-based systems engineering (DBSE) approach to engineering complex systems. In the spacecraft design domain, there are many perceived and propose benefits of an MBSE approach, but little analysis has been presented to determine the tangible benefits of such an approach (e.g. time and cost saved, increased product quality). This paper presents direct examples of how developing a small satellite system model can improve traceability of the mission concept to its requirements. A comparison of the processes and approaches for MBSE and DBSE is made using the NASA Ames Research Center SporeSat CubeSat mission as a case study. A model of the SporeSat mission is built using the Systems Modeling Language standard and No Magic's MagicDraw modeling tool. The model incorporates mission concept and requirement information from the mission's original DBSE design efforts. Active dependency relationships are modeled to demonstrate the completeness and consistency of the requirements to the mission concept. Anecdotal information and process-duration metrics are presented for both the MBSE and original DBSE design efforts of SporeSat.

Improved Traceability of Mission Concept to Requirements Using Model Based Systems Engineering

NASA Technical Reports Server (NTRS)

Reil, Robin

2014-01-01

Model Based Systems Engineering (MBSE) has recently been gaining significant support as a means to improve the traditional document-based systems engineering (DBSE) approach to engineering complex systems. In the spacecraft design domain, there are many perceived and propose benefits of an MBSE approach, but little analysis has been presented to determine the tangible benefits of such an approach (e.g. time and cost saved, increased product quality). This thesis presents direct examples of how developing a small satellite system model can improve traceability of the mission concept to its requirements. A comparison of the processes and approaches for MBSE and DBSE is made using the NASA Ames Research Center SporeSat CubeSat mission as a case study. A model of the SporeSat mission is built using the Systems Modeling Language standard and No Magics MagicDraw modeling tool. The model incorporates mission concept and requirement information from the missions original DBSE design efforts. Active dependency relationships are modeled to analyze the completeness and consistency of the requirements to the mission concept. Overall experience and methodology are presented for both the MBSE and original DBSE design efforts of SporeSat.

Using Computational Modeling to Assess the Impact of Clinical Decision Support on Cancer Screening within Community Health Centers

PubMed Central

Carney, Timothy Jay; Morgan, Geoffrey P.; Jones, Josette; McDaniel, Anna M.; Weaver, Michael; Weiner, Bryan; Haggstrom, David A.

2014-01-01

Our conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman’s Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability. PMID:24953241

Are performance measurement systems useful? Perceptions from health care.

PubMed

Demartini, Chiara; Trucco, Sara

2017-01-31

Prior literature identified the use of Performance Measurement Systems (PMS) as crucial in addressing improved processes of care. Moreover, a strategic use of PMS has been found to enhance quality, compared to non-strategic use, although a clear understanding of this linkage is still to be achieved. This paper deals with the test of direct and indirect models related to the link between the strategic use of PMS and the level of improved processes in health care organizations. Indirect models were mediated by the degree of perceived managerial discretion. A PLS analysis on a survey of 97 Italian managers working for health care organizations in the Lombardy region was conducted. The response rate was 77.6%. The strategic use of PMS in health care organizations directly and significantly (p < 0.001) enhances performance in terms of improved processes. Perceived managerial discretion is positively and significantly (p < 0.001) affected by the strategic use of PMS, whereas the mediation effect is non-significant. This study contributes to the literature investigating the design and implementation of a non-financial measurement tool, such as the non-financial information included into a balanced scorecard (BSC), in health care organizations. Managers in health care organizations can benefit from the strategic use of PMS to effectively allocate their time to strategic opportunities and threats, which might arise and affect organizational, output-related performance, such as improving processes.

Development of a Quality Improvement Curriculum in Physician Assistant Studies.

PubMed

Kindratt, Tiffany B; Orcutt, Venetia L

2017-06-01

The purpose of this project was to develop and evaluate a curriculum for physician assistant (PA) students addressing knowledge, skills, and attitudes (KSA) toward quality improvement (QI). Students (N = 77) completed a pretest rating their KSA. A curriculum was developed to improve KSA among didactic and clinical students. Two department-wide QI projects were developed for student participation. Students completed a posttest after completing curriculum components and changes in KSA had been measured. Postcurriculum implementation, QI knowledge, and skills increased significantly in most areas. Large improvements were seen in knowledge of Plan, Do, Study, Act models and life cycles of QI projects (p < .0001). Seven students (20%) participated in department-wide projects. Our curriculum model (1) was effective at improving students' QI knowledge and skills; (2) allowed students to participate in community-based QI projects; and (3) can be used by other PA programs looking to enhance their QI curriculum.

Speech sound discrimination training improves auditory cortex responses in a rat model of autism

PubMed Central

Engineer, Crystal T.; Centanni, Tracy M.; Im, Kwok W.; Kilgard, Michael P.

2014-01-01

Children with autism often have language impairments and degraded cortical responses to speech. Extensive behavioral interventions can improve language outcomes and cortical responses. Prenatal exposure to the antiepileptic drug valproic acid (VPA) increases the risk for autism and language impairment. Prenatal exposure to VPA also causes weaker and delayed auditory cortex responses in rats. In this study, we document speech sound discrimination ability in VPA exposed rats and document the effect of extensive speech training on auditory cortex responses. VPA exposed rats were significantly impaired at consonant, but not vowel, discrimination. Extensive speech training resulted in both stronger and faster anterior auditory field (AAF) responses compared to untrained VPA exposed rats, and restored responses to control levels. This neural response improvement generalized to non-trained sounds. The rodent VPA model of autism may be used to improve the understanding of speech processing in autism and contribute to improving language outcomes. PMID:25140133

Assessment of the impacts of aromatic VOC emissions and yields of SOA on SOA concentrations with the air quality model RAMS-CMAQ

NASA Astrophysics Data System (ADS)

Li, Jialin; Zhang, Meigen; Wu, Fangkun; Sun, Yele; Tang, Guiqian

2017-06-01

The secondary organic aerosol (SOA) concentration is generally underestimated by models. Recent studies suggest that the underprediction is related to underestimations of aromatic volatile organic compound (VOC) emissions and SOA yields in current models. Here, the impacts of these two factors in China were investigated with the regional air quality modeling system RAMS-CMAQ, referring to field observations during the episode from October 14 to November 14, 2014. Comparisons between the observed and modeled SOA of four sensitivity simulation cases indicated the significant impacts of the two underestimated factors on the SOA output. By considering these two aspects, the simulated mean SOA concentrations significantly increased by nearly 4 times with a good representation of the intensively temporal variations of concentrations, which were largely controlled by photochemical processes rather than meteorological conditions. The improvement in SOA compensated for the underestimations by approximately 23.5% and contributed to the mean fraction of SOA to organic aerosol (OA) by increasing the fraction from less than 7% to more than 25%, which was closer to the observed result. These results suggested a more reasonable and more realistic representation of SOA formation in the model after allowing for the two factors. Due to the better simulation of SOA, predictions of OA were correspondingly improved when the correlation coefficient increased from 0.57 to 0.73 and other bias parameters were reduced, which indicated the improved ability of our model to trace the temporal variations of OA. Based on the improved simulation throughout the episode, the mean SOA concentration was obviously higher in eastern China than in the west. The highest concentration appeared in the Sichuan Basin and Pearl River Delta (PRD) areas, with values of 6-11 μg/m3 and 8-17 μg/m3, respectively. Over the wide regions of central and eastern China, the dominant component in SOA was formed from anthropogenic sources (ASOA), generally accounting for more than 60%.

Retiring the Short-Run Aggregate Supply Curve

ERIC Educational Resources Information Center

Elwood, S. Kirk

2010-01-01

The author argues that the aggregate demand/aggregate supply (AD/AS) model is significantly improved--although certainly not perfected--by trimming it of the short-run aggregate supply (SRAS) curve. Problems with the SRAS curve are shown first for the AD/AS model that casts the AD curve as identifying the equilibrium level of output associated…

The MDE Diploma: First International Postgraduate Specialization in Model-Driven Engineering

ERIC Educational Resources Information Center

Cabot, Jordi; Tisi, Massimo

2011-01-01

Model-Driven Engineering (MDE) is changing the way we build, operate, and maintain our software-intensive systems. Several projects using MDE practices are reporting significant improvements in quality and performance but, to be able to handle these projects, software engineers need a set of technical and interpersonal skills that are currently…

77 FR 485 - Wind Plant Performance-Public Meeting on Modeling and Testing Needs for Complex Air Flow...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-05

... modeling needs and experimental validation techniques for complex flow phenomena in and around off- shore... experimental validation. Ultimately, research in this area may lead to significant improvements in wind plant... meeting will consist of an initial plenary session in which invited speakers will survey available...

A Model for Mapping Linkages between Health and Education Agencies To Improve School Health.

ERIC Educational Resources Information Center

St. Leger, Lawrence; Nutbeam, Don

2000-01-01

Reviews the evolution of efforts to develop effective, sustainable school health programs, arguing that efforts were significantly driven by public health priorities and have not adequately accounted for educational perspectives. A model illustrating linkages between different school-based inputs and strategies and long-term health and educational…

Comparison of parathyroid hormone and strontium ranelate in combination with whole-body vibration in a rat model of osteoporosis.

PubMed

Hoffmann, D B; Sehmisch, S; Hofmann, A M; Eimer, C; Komrakova, M; Saul, D; Wassmann, M; Stürmer, K M; Tezval, M

2017-01-01

We investigated the combinatorial effects of whole-body vertical vibration (WBVV) with the primarily osteoanabolic parathyroid hormone (PTH) and the mainly antiresorptive strontium ranelate (SR) in a rat model of osteoporosis. Ovariectomies were performed on 76 three-month-old Sprague-Dawley rats (OVX, n = 76; NON-OVX, n = 12). After 8 weeks, the ovariectomized rats were divided into 6 groups. One group (OVX + PTH) received daily injections of PTH (40 µg/kg body weight/day) for 6 weeks. Another group (OVX + SR) was fed SR-supplemented chow (600 mg/kg body weight/day). Three groups (OVX + VIB, OVX + PTH + VIB, and OVX + SR + VIB) were treated with WBVV twice a day at 70 Hz for 15 min. Two groups (OVX + PTH + VIB, OVX + SR + VIB) were treated additionally with PTH and SR, respectively. The rats were killed at 14 weeks post-ovariectomy. The lumbar vertebrae and femora were removed for biomechanical and morphological assessment. PTH produced statistically significant improvements in biomechanical and structural properties, including bone mineral density (BMD) and trabecular bone quality. In contrast, SR treatment exerted mild effects, with significant effects in cortical thickness only. SR produced no significant improvement in biomechanical properties. WBVV as a single or an adjunctive therapy produced no significant improvements. In conclusion, vibration therapy administered as a single or dual treatment had no significant impact on bones affected by osteoporosis. PTH considerably improved bone quality in osteoporosis cases and is superior to treatment with SR.

Vascular endothelial growth factor receptor-3 is a novel target to improve net ultrafiltration in methylglyoxal-induced peritoneal injury.

PubMed

Terabayashi, Takeshi; Ito, Yasuhiko; Mizuno, Masashi; Suzuki, Yasuhiro; Kinashi, Hiroshi; Sakata, Fumiko; Tomita, Takako; Iguchi, Daiki; Tawada, Mitsuhiro; Nishio, Ryosuke; Maruyama, Shoichi; Imai, Enyu; Matsuo, Seiichi; Takei, Yoshifumi

2015-09-01

Appropriate fluid balance is important for good clinical outcomes and survival in patients on peritoneal dialysis. We recently reported that lymphangiogenesis associated with fibrosis developed in the peritoneal cavity via the transforming growth factor-β1-vascular endothelial growth factor-C (VEGF-C) pathway. We investigated whether VEGF receptor-3 (VEGFR-3), the receptor for VEGF-C and -D, might be a new target to improve net ultrafiltration by using adenovirus-expressing soluble VEGFR-3 (Adeno-sVEGFR-3) in rodent models of peritoneal injury induced by methylglyoxal (MGO). We demonstrated that lymphangiogenesis developed in these MGO models, especially in the diaphragm, indicating that lymphangiogenesis is a common feature in the peritoneal cavity with inflammation and fibrosis. In MGO models, VEGF-D was significantly increased in the diaphragm; however, VEGF-C was not significantly upregulated. Adeno-sVEGFR-3, which was detected on day 50 after administration via tail vein injections, successfully suppressed lymphangiogenesis in the diaphragm and parietal peritoneum in mouse MGO models without significant effects on fibrosis, inflammation, or neoangiogenesis. Drained volume in the peritoneal equilibration test using a 7.5% icodextrin peritoneal dialysis solution (the 7.5% icodextrin peritoneal equilibration test) was improved by Adeno-sVEGFR-3 on day 22 (P<0.05) and day 50 after reduction of inflammation (P<0.01), indicating that the 7.5% icodextrin peritoneal equilibration test identifies changes in lymphangiogenesis. The solute transport rate was not affected by suppression of lymphangiogenesis. In human peritoneal dialysis patients, the dialysate to plasma ratio of creatinine positively correlated with the dialysate VEGF-D concentration (P<0.001). VEGF-D mRNA was significantly higher in the peritoneal membranes of patients with ultrafiltration failure, indicating that VEGF-D is involved in the development of lymphangiogenesis in peritoneal dialysis patients. These results indicate that VEGFR-3 is a new target to improve net ultrafiltration by suppressing lymphatic absorption and that the 7.5% icodextrin peritoneal equilibration test is useful for estimation of lymphatic absorption.

Application of Hellison's Teaching Personal and Social Responsibility Model in physical education to improve self-efficacy for adolescents at risk of dropping-out of school.

PubMed

Escartí, Amparo; Gutiérrez, Melchor; Pascual, Carmina; Marín, Diana

2010-11-01

This study evaluated improvement in self-efficacy and personal and social responsibility among at-risk of dropping-out of school adolescents participating in a program in which Hellison's Teaching Personal and Social Responsibility Model was applied in physical education classes during the course of an academic year. Thirty at-risk adolescents aged 13-14 years old (23 boys, 7 girls) were assigned to an intervention group (12 boys and 3 girls) or a comparison group (11 boys, 4 girls), the latter of which did not participate in the program. Quantitative results showed a significant improvement in the students' self-efficacy for enlisting social resources and in self-efficacy for self-regulated learning. Qualitative results showed an improvement in responsibility behaviors of participants in the intervention group. This suggests that the model could be effective for improving psychological and social development in at-risk adolescents, and that physical education classes may be an appropriate arena for working with these young people.

Land ownership and technology adoption revisited: Improved maize varieties in Ethiopia.

PubMed

Zeng, Di; Alwang, Jeffrey; Norton, George; Jaleta, Moti; Shiferaw, Bekele; Yirga, Chilot

2018-03-01

The lack of land ownership can discourage agricultural technology adoption, yet there is scarce evidence of the impact of land rental contracts on the adoption of improved crop varieties in developing countries. The current study investigates such impact using a nationally representative survey of Ethiopian maize farmers. In contrast to many previous studies, we show in a simple model that cash-renters are as likely to adopt improved maize varieties as owner-operators, while sharecroppers are more likely to adopt given that such varieties are profitable. Empirical analysis reveals a significant impact of sharecropping on improved maize variety adoption, and no significant impact from cash-rental, lending support to the above hypotheses. These results imply that improvements in land rental markets can potentially enhance household welfare through crop variety adoption in agrarian economies where land sales markets are incomplete or missing.

Show and Tell: Video Modeling and Instruction Without Feedback Improves Performance but Is Not Sufficient for Retention of a Complex Voice Motor Skill.

PubMed

Look, Clarisse; McCabe, Patricia; Heard, Robert; Madill, Catherine J

2018-02-02

Modeling and instruction are frequent components of both traditional and technology-assisted voice therapy. This study investigated the value of video modeling and instruction in the early acquisition and short-term retention of a complex voice task without external feedback. Thirty participants were randomized to two conditions and trained to produce a vocal siren over 40 trials. One group received a model and verbal instructions, the other group received a model only. Sirens were analyzed for phonation time, vocal intensity, cepstral peak prominence, peak-to-peak time, and root-mean-square error at five time points. The model and instruction group showed significant improvement on more outcome measures than the model-only group. There was an interaction effect for vocal intensity, which showed that instructions facilitated greater improvement when they were first introduced. However, neither group reproduced the model's siren performance across all parameters or retained the skill 1 day later. Providing verbal instruction with a model appears more beneficial than providing a model only in the prepractice phase of acquiring a complex voice skill. Improved performance was observed; however, the higher level of performance was not retained after 40 trials in both conditions. Other prepractice variables may need to be considered. Findings have implications for traditional and technology-assisted voice therapy. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Efficient preloading of the ventricles by a properly timed atrial contraction underlies stroke work improvement in the acute response to cardiac resynchronization therapy

PubMed Central

Hu, Yuxuan; Gurev, Viatcheslav; Constantino, Jason; Trayanova, Natalia

2013-01-01

Background The acute response to cardiac resynchronization therapy (CRT) has been shown to be due to three mechanisms: resynchronization of ventricular contraction, efficient preloading of the ventricles by a properly timed atrial contraction, and mitral regurgitation reduction. However, the contribution of each of the three mechanisms to the acute response of CRT, specifically stroke work improvement, has not been quantified. Objective The goal of this study was to use an MRI-based anatomically accurate 3D model of failing canine ventricular electromechanics to quantify the contribution of each of the three mechanisms to stroke work improvement and identify the predominant mechanisms. Methods An MRI-based electromechanical model of the failing canine ventricles assembled previously by our group was further developed and modified. Three different protocols were used to dissect the contribution of each of the three mechanisms to stroke work improvement. Results Resynchronization of ventricular contraction did not lead to significant stroke work improvement. Efficient preloading of the ventricles by a properly timed atrial contraction was the predominant mechanism underlying stroke work improvement. Stroke work improvement peaked at an intermediate AV delay, as it allowed ventricular filling by atrial contraction to occur at a low diastolic LV pressure but also provided adequate time for ventricular filling before ventricular contraction. Diminution of mitral regurgitation by CRT led to stroke work worsening instead of improvement. Conclusion Efficient preloading of the ventricles by a properly timed atrial contraction is responsible for significant stroke work improvement in the acute CRT response. PMID:23928177