On the self-serving function of an academic wooden leg: test anxiety as a self-handicapping strategy.

PubMed

Smith, C W; Snyder, D R; Handelsman, M M

1982-02-01

The present study investigated the hypothesis that psychological symptoms may serve a self-protective function by providing an alternative explanation for potential failure in evaluating situations. It was hypothesized that highly test-anxious subjects would report anxiety symptoms in a pattern that reflected strategic presentation of symptoms; more specifically, it was predicted that greater reported anxiety should result when anxiety was a viable explanation for poor performance on an intelligence test and that lower reported anxiety should result when anxiety was not a viable explanation for poor performance. Analysis of state measures of self-reported anxiety supported these predictions. Further analysis indicated that when anxiety was not a viable explanation for poor test performance, high test-anxiety subjects reported reduced effort as an alternative self-protective strategy. These results are discussed in terms of traditional models of symptoms as self-protective strategies, current social psychological models of symptoms, and in reference to recent theory and research about the nature and treatment of test anxiety.

Dysglycemia, Glycemic Variability, and Outcome After Cardiac Arrest and Temperature Management at 33°C and 36°C.

PubMed

Borgquist, Ola; Wise, Matt P; Nielsen, Niklas; Al-Subaie, Nawaf; Cranshaw, Julius; Cronberg, Tobias; Glover, Guy; Hassager, Christian; Kjaergaard, Jesper; Kuiper, Michael; Smid, Ondrej; Walden, Andrew; Friberg, Hans

2017-08-01

Dysglycemia and glycemic variability are associated with poor outcomes in critically ill patients. Targeted temperature management alters blood glucose homeostasis. We investigated the association between blood glucose concentrations and glycemic variability and the neurologic outcomes of patients randomized to targeted temperature management at 33°C or 36°C after cardiac arrest. Post hoc analysis of the multicenter TTM-trial. Primary outcome of this analysis was neurologic outcome after 6 months, referred to as "Cerebral Performance Category." Thirty-six sites in Europe and Australia. All 939 patients with out-of-hospital cardiac arrest of presumed cardiac cause that had been included in the TTM-trial. Targeted temperature management at 33°C or 36°C. Nonparametric tests as well as multiple logistic regression and mixed effects logistic regression models were used. Median glucose concentrations on hospital admission differed significantly between Cerebral Performance Category outcomes (p < 0.0001). Hyper- and hypoglycemia were associated with poor neurologic outcome (p = 0.001 and p = 0.054). In the multiple logistic regression models, the median glycemic level was an independent predictor of poor Cerebral Performance Category (Cerebral Performance Category, 3-5) with an odds ratio (OR) of 1.13 in the adjusted model (p = 0.008; 95% CI, 1.03-1.24). It was also a predictor in the mixed model, which served as a sensitivity analysis to adjust for the multiple time points. The proportion of hyperglycemia was higher in the 33°C group compared with the 36°C group. Higher blood glucose levels at admission and during the first 36 hours, and higher glycemic variability, were associated with poor neurologic outcome and death. More patients in the 33°C treatment arm had hyperglycemia.

Making Schools the Model for Healthier Environments Toolkit: What It Is

ERIC Educational Resources Information Center

Robert Wood Johnson Foundation, 2012

2012-01-01

Healthy students perform better. Poor nutrition and inadequate physical activity can affect not only academic achievement, but also other factors such as absenteeism, classroom behavior, ability to concentrate, self-esteem, cognitive performance, and test scores. This toolkit provides information to help make schools the model for healthier…

Not self-focused attention but negative beliefs affect poor social performance in social anxiety: an investigation of pathways in the social anxiety-social rejection relationship.

PubMed

Voncken, Marisol J; Dijk, Corine; de Jong, Peter J; Roelofs, Jeffrey

2010-10-01

Patients with social anxiety disorder (SAD) not only fear negative evaluation but are indeed less likeable than people without SAD. Previous research shows social performance to mediate this social anxiety-social rejection relationship. This study studied two pathways hypothesized to lead to poor social performance in social anxiety: increased self-focused attention and negative beliefs. State social anxiety was experimentally manipulated in high and low-blushing-fearful individuals by letting half of the participants believe that they blushed intensely during a 5 min getting-acquainted interaction with two confederates. Participants rated their state social anxiety, self-focused attention, and level of negative beliefs. Two confederates and two video-observers rated subsequently likeability (i.e., social rejection) and social performance of the participants. In both groups, the social anxiety-social rejection relationship was present. Although state social anxiety was related to heightened self-focused attention and negative beliefs, only negative beliefs were associated with relatively poor social performance. In contrast to current SAD models, self-focused attention did not play a key-role in poor social performance but seemed to function as a by-product of state social anxiety. Beliefs of being negatively evaluated seem to elicit changes in behavioral repertoire resulting in a poor social performance and subsequent rejection. Copyright 2010 Elsevier Ltd. All rights reserved.

Born Small for Gestational Age and Poor School Performance - How Small Is Too Small?

PubMed

Lindström, Linda; Wikström, Anna-Karin; Bergman, Eva; Lundgren, Maria

2017-01-01

To assess the relationship between severity of small for gestational age (SGA) and the risk of poor school performance, and to investigate whether adult stature modifies this risk. 1,088,980 Swedish children born at term between 1973 and 1988 were categorized into severe SGA (less than -3 standard deviations (SD) of expected birth weight), moderate SGA (-2.01 to -3 SD), mild SGA (-1.01 to -2 SD), and appropriate for gestational age (-1 to 0.99 SD). The risk of poor school performance at the time of graduation from compulsory school (grades <10th percentile) was calculated using unconditional logistic regression models and adjusted for socio-economic factors. In a sub-analysis, we stratified boys by adult stature, and adjusted for maternal but not paternal height. All SGA groups were significantly associated with an increased risk of poor school performance, with adjusted odds ratios and 95% confidence intervals ranging from 1.85 (1.65-2.07) for severe SGA to 1.25 (1.22-1.28) for mild SGA. In the sub-analysis, all birth weight groups were associated with an increased risk of poor school performance among boys with short stature compared to those with non-short stature. Mild SGA is associated with a significantly increased risk of poor school performance, and the risk increases with severity of SGA. Further, this risk diminishes after adequate catch-up growth. © 2017 S. Karger AG, Basel.

Forgotten forests--issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study.

PubMed

Särkinen, Tiina; Iganci, João R V; Linares-Palomino, Reynaldo; Simon, Marcelo F; Prado, Darién E

2011-11-24

South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF) biome using herbarium data of habitat specialist species. Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1) poor spatial resolution, and (2) poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM) approach where georeferenced herbarium data is used in conjunction with bioclimatic data. Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in biome mapping, and could be particularly useful for mapping poorly known, fragmented, or degraded vegetation. We wish to highlight that biome delimitation is not an exact science, and that transparency is needed on how biomes are used as study units in macroevolutionary and ecological research.

Forgotten forests - issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study

PubMed Central

2011-01-01

Background South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF) biome using herbarium data of habitat specialist species. Results Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1) poor spatial resolution, and (2) poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM) approach where georeferenced herbarium data is used in conjunction with bioclimatic data. Conclusions Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in biome mapping, and could be particularly useful for mapping poorly known, fragmented, or degraded vegetation. We wish to highlight that biome delimitation is not an exact science, and that transparency is needed on how biomes are used as study units in macroevolutionary and ecological research. PMID:22115315

External validation of a prediction model for surgical site infection after thoracolumbar spine surgery in a Western European cohort.

PubMed

Janssen, Daniël M C; van Kuijk, Sander M J; d'Aumerie, Boudewijn B; Willems, Paul C

2018-05-16

A prediction model for surgical site infection (SSI) after spine surgery was developed in 2014 by Lee et al. This model was developed to compute an individual estimate of the probability of SSI after spine surgery based on the patient's comorbidity profile and invasiveness of surgery. Before any prediction model can be validly implemented in daily medical practice, it should be externally validated to assess how the prediction model performs in patients sampled independently from the derivation cohort. We included 898 consecutive patients who underwent instrumented thoracolumbar spine surgery. To quantify overall performance using Nagelkerke's R 2 statistic, the discriminative ability was quantified as the area under the receiver operating characteristic curve (AUC). We computed the calibration slope of the calibration plot, to judge prediction accuracy. Sixty patients developed an SSI. The overall performance of the prediction model in our population was poor: Nagelkerke's R 2 was 0.01. The AUC was 0.61 (95% confidence interval (CI) 0.54-0.68). The estimated slope of the calibration plot was 0.52. The previously published prediction model showed poor performance in our academic external validation cohort. To predict SSI after instrumented thoracolumbar spine surgery for the present population, a better fitting prediction model should be developed.

Impact of the revised International Prognostic Scoring System, cytogenetics and monosomal karyotype on outcome after allogeneic stem cell transplantation for myelodysplastic syndromes and secondary acute myeloid leukemia evolving from myelodysplastic syndromes: a retrospective multicenter study of the European Society of Blood and Marrow Transplantation

PubMed Central

Koenecke, Christian; Göhring, Gudrun; de Wreede, Liesbeth C.; van Biezen, Anja; Scheid, Christof; Volin, Liisa; Maertens, Johan; Finke, Jürgen; Schaap, Nicolaas; Robin, Marie; Passweg, Jakob; Cornelissen, Jan; Beelen, Dietrich; Heuser, Michael; de Witte, Theo; Kröger, Nicolaus

2015-01-01

The aim of this study was to determine the impact of the revised 5-group International Prognostic Scoring System cytogenetic classification on outcome after allogeneic stem cell transplantation in patients with myelodysplastic syndromes or secondary acute myeloid leukemia who were reported to the European Society for Blood and Marrow Transplantation database. A total of 903 patients had sufficient cytogenetic information available at stem cell transplantation to be classified according to the 5-group classification. Poor and very poor risk according to this classification was an independent predictor of shorter relapse-free survival (hazard ratio 1.40 and 2.14), overall survival (hazard ratio 1.38 and 2.14), and significantly higher cumulative incidence of relapse (hazard ratio 1.64 and 2.76), compared to patients with very good, good or intermediate risk. When comparing the predictive performance of a series of Cox models both for relapse-free survival and for overall survival, a model with simplified 5-group cytogenetics (merging very good, good and intermediate cytogenetics) performed best. Furthermore, monosomal karyotype is an additional negative predictor for outcome within patients of the poor, but not the very poor risk group of the 5-group classification. The revised International Prognostic Scoring System cytogenetic classification allows patients with myelodysplastic syndromes to be separated into three groups with clearly different outcomes after stem cell transplantation. Poor and very poor risk cytogenetics were strong predictors of poor patient outcome. The new cytogenetic classification added value to prediction of patient outcome compared to prediction models using only traditional risk factors or the 3-group International Prognostic Scoring System cytogenetic classification. PMID:25552702

β-decay studies of r-process nuclei at NSCL

NASA Astrophysics Data System (ADS)

Pereira, J.; Aprahamian, A.; Arndt, O.; Becerril, A.; Elliot, T.; Estrade, A.; Galaviz, D.; Hennrich, S.; Hosmer, P.; Schnorrenberger, L.; Kessler, R.; Kratz, K.-L.; Lorusso, G.; Mantica, P. F.; Matos, M.; Montes, F.; Pfeiffer, B.; Quinn, M.; Santi, P.; Schatz, H.; Schertz, F.; Smith, E.; Tomlin, B. E.; Walters, W. B.; Wöhr, A.

2008-06-01

Observed neutron-capture elemental abundances in metal-poor stars, along with ongoing analysis of the extremely metal-poor Eu-enriched sub-class provide new guidance for astrophysical models aimed at finding the r-process sites. The present paper emphasizes the importance of nuclear physics parameters entering in these models, particularly β-decay properties of neutron-rich nuclei. In this context, several r-process motivated β-decay experiments performed at the National Superconducting Cyclotron Laboratory (NSCL) are presented, including a summary of results and impact on model calculations.

Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study.

PubMed

Zammit, Andrea R; Hall, Charles B; Lipton, Richard B; Katz, Mindy J; Muniz-Terrera, Graciela

2018-05-01

The aim of this study was to identify natural subgroups of older adults based on cognitive performance, and to establish each subgroup's characteristics based on demographic factors, physical function, psychosocial well-being, and comorbidity. We applied latent class (LC) modeling to identify subgroups in baseline assessments of 1345 Einstein Aging Study (EAS) participants free of dementia. The EAS is a community-dwelling cohort study of 70+ year-old adults living in the Bronx, NY. We used 10 neurocognitive tests and 3 covariates (age, sex, education) to identify latent subgroups. We used goodness-of-fit statistics to identify the optimal class solution and assess model adequacy. We also validated our model using two-fold split-half cross-validation. The sample had a mean age of 78.0 (SD=5.4) and a mean of 13.6 years of education (SD=3.5). A 9-class solution based on cognitive performance at baseline was the best-fitting model. We characterized the 9 identified classes as (i) disadvantaged, (ii) poor language, (iii) poor episodic memory and fluency, (iv) poor processing speed and executive function, (v) low average, (vi) high average, (vii) average, (viii) poor executive and poor working memory, (ix) elite. The cross validation indicated stable class assignment with the exception of the average and high average classes. LC modeling in a community sample of older adults revealed 9 cognitive subgroups. Assignment of subgroups was reliable and associated with external validators. Future work will test the predictive validity of these groups for outcomes such as Alzheimer's disease, vascular dementia and death, as well as markers of biological pathways that contribute to cognitive decline. (JINS, 2018, 24, 511-523).

A framework for streamflow prediction in the world's most severely data-limited regions: Test of applicability and performance in a poorly-gauged region of China

NASA Astrophysics Data System (ADS)

Alipour, M. H.; Kibler, Kelly M.

2018-02-01

A framework methodology is proposed for streamflow prediction in poorly-gauged rivers located within large-scale regions of sparse hydrometeorologic observation. A multi-criteria model evaluation is developed to select models that balance runoff efficiency with selection of accurate parameter values. Sparse observed data are supplemented by uncertain or low-resolution information, incorporated as 'soft' data, to estimate parameter values a priori. Model performance is tested in two catchments within a data-poor region of southwestern China, and results are compared to models selected using alternative calibration methods. While all models perform consistently with respect to runoff efficiency (NSE range of 0.67-0.78), models selected using the proposed multi-objective method may incorporate more representative parameter values than those selected by traditional calibration. Notably, parameter values estimated by the proposed method resonate with direct estimates of catchment subsurface storage capacity (parameter residuals of 20 and 61 mm for maximum soil moisture capacity (Cmax), and 0.91 and 0.48 for soil moisture distribution shape factor (B); where a parameter residual is equal to the centroid of a soft parameter value minus the calibrated parameter value). A model more traditionally calibrated to observed data only (single-objective model) estimates a much lower soil moisture capacity (residuals of Cmax = 475 and 518 mm and B = 1.24 and 0.7). A constrained single-objective model also underestimates maximum soil moisture capacity relative to a priori estimates (residuals of Cmax = 246 and 289 mm). The proposed method may allow managers to more confidently transfer calibrated models to ungauged catchments for streamflow predictions, even in the world's most data-limited regions.

Identifying Medical Students Likely to Exhibit Poor Professionalism and Knowledge During Internship

PubMed Central

Durning, Steven J.; Cohen, Daniel L.; Cruess, David; Jackson, Jeffrey L.

2007-01-01

CONTEXT Identifying medical students who will perform poorly during residency is difficult. OBJECTIVE Determine whether commonly available data predicts low performance ratings during internship by residency program directors. DESIGN Prospective cohort involving medical school data from graduates of the Uniformed Services University (USU), surveys about experiences at USU, and ratings of their performance during internship by their program directors. SETTING Uniformed Services University. PARTICIPANTS One thousand sixty-nine graduates between 1993 and 2002. MAIN OUTCOME MEASURE(S) Residency program directors completed an 18-item survey assessing intern performance. Factor analysis of these items collapsed to 2 domains: knowledge and professionalism. These domains were scored and performance dichotomized at the 10th percentile. RESULTS Many variables showed a univariate relationship with ratings in the bottom 10% of both domains. Multivariable logistic regression modeling revealed that grades earned during the third year predicted low ratings in both knowledge (odds ratio [OR] = 4.9; 95%CI = 2.7–9.2) and professionalism (OR = 7.3; 95%CI = 4.1–13.0). USMLE step 1 scores (OR = 1.03; 95%CI = 1.01–1.05) predicted knowledge but not professionalism. The remaining variables were not independently predictive of performance ratings. The predictive ability for the knowledge and professionalism models was modest (respective area under ROC curves = 0.735 and 0.725). CONCLUSIONS A strong association exists between the third year GPA and internship ratings by program directors in professionalism and knowledge. In combination with third year grades, either the USMLE step 1 or step 2 scores predict poor knowledge ratings. Despite a wealth of available markers and a large data set, predicting poor performance during internship remains difficult. PMID:17952512

The simplest acquisition protocol is sometimes the best protocol: performing and learning a 1:2 bimanual coordination task.

PubMed

Panzer, Stefan; Kennedy, Deanna; Wang, Chaoyi; Shea, Charles H

2018-02-01

An experiment was conducted to determine if the performance and learning of a multi-frequency (1:2) coordination pattern between the limbs are enhanced when a model is provided prior to each acquisition trial. Research has indicated very effective performance of a wide variety of bimanual coordination tasks when Lissajous plots with goal templates are provided, but this research has also found that participants become dependent on this information and perform quite poorly when it is withdrawn. The present experiment was designed to test three forms of modeling (Lissajous with template, Lissajous without template, and limb model), but in each situations, the model was presented prior to practice and not available during the performance of the task. This was done to decrease dependency on the model and increase the development of an internal reference of correctness that could be applied on test trials. A control condition was also collected, where a metronome was used to guide the movement. Following less than 7 min of practice, participants in the three modeling conditions performed the first test block very effectively; however, performance of the control condition was quite poor. Note that Test 1 was performed under the same conditions as used during acquisition. Test 2 was conducted with no augmented information provided prior to or during the performance of the task. Only participants in the limb model condition were able to maintain performance on Test 2. The findings suggest that a very simple intuitive display can provide the necessary information to form an effective internal representation of the coordination pattern which can be used guide performance when the augmented display is withdrawn.

Modeling and simulation of continuous wave velocity radar based on third-order DPLL

NASA Astrophysics Data System (ADS)

Di, Yan; Zhu, Chen; Hong, Ma

2015-02-01

Second-order digital phase-locked-loop (DPLL) is widely used in traditional Continuous wave (CW) velocity radar with poor performance in high dynamic conditions. Using the third-order DPLL can improve the performance. Firstly, the echo signal model of CW radar is given. Secondly, theoretical derivations of the tracking performance in different velocity conditions are given. Finally, simulation model of CW radar is established based on Simulink tool. Tracking performance of the two kinds of DPLL in different acceleration and jerk conditions is studied by this model. The results show that third-order PLL has better performance in high dynamic conditions. This model provides a platform for further research of CW radar.

A Bayesian modification to the Jelinski-Moranda software reliability growth model

NASA Technical Reports Server (NTRS)

Littlewood, B.; Sofer, A.

1983-01-01

The Jelinski-Moranda (JM) model for software reliability was examined. It is suggested that a major reason for the poor results given by this model is the poor performance of the maximum likelihood method (ML) of parameter estimation. A reparameterization and Bayesian analysis, involving a slight modelling change, are proposed. It is shown that this new Bayesian-Jelinski-Moranda model (BJM) is mathematically quite tractable, and several metrics of interest to practitioners are obtained. The BJM and JM models are compared by using several sets of real software failure data collected and in all cases the BJM model gives superior reliability predictions. A change in the assumption which underlay both models to present the debugging process more accurately is discussed.

A coupled hydrological-hydraulic flood inundation model calibrated using post-event measurements and integrated uncertainty analysis in a poorly gauged Mediterranean basin

NASA Astrophysics Data System (ADS)

Hdeib, Rouya; Abdallah, Chadi; Moussa, Roger; Colin, Francois

2017-04-01

Developing flood inundation maps of defined exceedance probabilities is required to provide information on the flood hazard and the associated risk. A methodology has been developed to model flood inundation in poorly gauged basins, where reliable information on the hydrological characteristics of floods are uncertain and partially captured by the traditional rain-gauge networks. Flood inundation is performed through coupling a hydrological rainfall-runoff (RR) model (HEC-HMS) with a hydraulic model (HEC-RAS). The RR model is calibrated against the January 2013 flood event in the Awali River basin, Lebanon (300 km2), whose flood peak discharge was estimated by post-event measurements. The resulting flows of the RR model are defined as boundary conditions of the hydraulic model, which is run to generate the corresponding water surface profiles and calibrated against 20 post-event surveyed cross sections after the January-2013 flood event. An uncertainty analysis is performed to assess the results of the models. Consequently, the coupled flood inundation model is simulated with design storms and flood inundation maps are generated of defined exceedance probabilities. The peak discharges estimated by the simulated RR model were in close agreement with the results from different empirical and statistical methods. This methodology can be extended to other poorly gauged basins facing common stage-gauge failure or characterized by floods with a stage exceeding the gauge measurement level, or higher than that defined by the rating curve.

Inter-comparison of time series models of lake levels predicted by several modeling strategies

NASA Astrophysics Data System (ADS)

Khatibi, R.; Ghorbani, M. A.; Naghipour, L.; Jothiprakash, V.; Fathima, T. A.; Fazelifard, M. H.

2014-04-01

Five modeling strategies are employed to analyze water level time series of six lakes with different physical characteristics such as shape, size, altitude and range of variations. The models comprise chaos theory, Auto-Regressive Integrated Moving Average (ARIMA) - treated for seasonality and hence SARIMA, Artificial Neural Networks (ANN), Gene Expression Programming (GEP) and Multiple Linear Regression (MLR). Each is formulated on a different premise with different underlying assumptions. Chaos theory is elaborated in a greater detail as it is customary to identify the existence of chaotic signals by a number of techniques (e.g. average mutual information and false nearest neighbors) and future values are predicted using the Nonlinear Local Prediction (NLP) technique. This paper takes a critical view of past inter-comparison studies seeking a superior performance, against which it is reported that (i) the performances of all five modeling strategies vary from good to poor, hampering the recommendation of a clear-cut predictive model; (ii) the performances of the datasets of two cases are consistently better with all five modeling strategies; (iii) in other cases, their performances are poor but the results can still be fit-for-purpose; (iv) the simultaneous good performances of NLP and SARIMA pull their underlying assumptions to different ends, which cannot be reconciled. A number of arguments are presented including the culture of pluralism, according to which the various modeling strategies facilitate an insight into the data from different vantages.

Physical performance and frailty in chronic kidney disease.

PubMed

Reese, Peter P; Cappola, Anne R; Shults, Justine; Townsend, Raymond R; Gadegbeku, Crystal A; Anderson, Cheryl; Baker, Joshua F; Carlow, Dean; Sulik, Michael J; Lo, Joan C; Go, Alan S; Ky, Bonnie; Mariani, Laura; Feldman, Harold I; Leonard, Mary B

2013-01-01

Poor physical performance and frailty are associated with elevated risks of death and disability. Chronic kidney disease (CKD) is also strongly associated with these outcomes. The risks of poor physical performance and frailty among CKD patients, however, are not well established. We measured the Short Physical Performance Battery (SPPB; a summary test of gait speed, chair raises and balance; range 0-12) and the five elements of frailty among 1,111 Chronic Renal Insufficiency Cohort participants. Adjusting for demographics and multiple comorbidities, we fit a linear regression model for the outcome of SPPB score and an ordinal logistic regression model for frailty status. Median (interquartile range, IQR) age was 65 (57-71) years, median estimated glomerular filtration rate (eGFR) for non-dialysis patients was 49 (36-62) ml/min/1.73 m(2), and median SPPB score was 9 (7-10). Seven percent of participants were frail and 43% were pre-frail. Compared with the SPPB score for eGFR >60 ml/min/1.73 m(2), the SPPB was 0.51 points lower for eGFR 30-59; 0.61 points lower for eGFR 15-29, and 1.75 points lower for eGFR <15 (p < 0.01 for all comparisons). eGFR 30-59 (odds ratio, OR 1.45; p = 0.024), eGFR 15-29 (OR 2.02; p = 0.002) and eGFR <15 (OR 4.83; p < 0.001) were associated with worse frailty status compared with eGFR >60 ml/min/1.73 m(2). CKD severity was associated with poor physical performance and frailty in a graded fashion. Future trials should determine if outcomes for CKD patients with frailty and poor physical performance are improved by targeted interventions. © 2013 S. Karger AG, Basel.

Item Response Theory Models for Performance Decline during Testing

ERIC Educational Resources Information Center

Jin, Kuan-Yu; Wang, Wen-Chung

2014-01-01

Sometimes, test-takers may not be able to attempt all items to the best of their ability (with full effort) due to personal factors (e.g., low motivation) or testing conditions (e.g., time limit), resulting in poor performances on certain items, especially those located toward the end of a test. Standard item response theory (IRT) models fail to…

Stream ecological condition modeling at the reach and the hydrologic unit (HUC) scale: A look at model performance and mapping

EPA Science Inventory

The National Hydrography and updated Watershed Boundary Datasets provide a ready-made framework for hydrographic modeling. Determining particular stream reaches or watersheds in poor ecological condition across large regions is an essential goal for monitoring and management. T...

A MODE-OF-ACTION-BASED QSAR APPROACH TO IMPROVE UNDERSTANDING OF DEVELOPMENTAL TOXICITY

EPA Science Inventory

QSAR models of developmental toxicity (devtox) have met with limited regulatory acceptance due to the use of ill-defined endpoints, lack of biological interpretability, and poor model performance. More generally, the lack of biological inference of many QSAR models is often due t...

The contribution of attentional lapses to individual differences in visual working memory capacity.

PubMed

Adam, Kirsten C S; Mance, Irida; Fukuda, Keisuke; Vogel, Edward K

2015-08-01

Attentional control and working memory capacity are important cognitive abilities that substantially vary between individuals. Although much is known about how attentional control and working memory capacity relate to each other and to constructs like fluid intelligence, little is known about how trial-by-trial fluctuations in attentional engagement impact trial-by-trial working memory performance. Here, we employ a novel whole-report memory task that allowed us to distinguish between varying levels of attentional engagement in humans performing a working memory task. By characterizing low-performance trials, we can distinguish between models in which working memory performance failures are caused by either (1) complete lapses of attention or (2) variations in attentional control. We found that performance failures increase with set-size and strongly predict working memory capacity. Performance variability was best modeled by an attentional control model of attention, not a lapse model. We examined neural signatures of performance failures by measuring EEG activity while participants performed the whole-report task. The number of items correctly recalled in the memory task was predicted by frontal theta power, with decreased frontal theta power associated with poor performance on the task. In addition, we found that poor performance was not explained by failures of sensory encoding; the P1/N1 response and ocular artifact rates were equivalent for high- and low-performance trials. In all, we propose that attentional lapses alone cannot explain individual differences in working memory performance. Instead, we find that graded fluctuations in attentional control better explain the trial-by-trial differences in working memory that we observe.

The Contribution of Attentional Lapses to Individual Differences in Visual Working Memory Capacity

PubMed Central

Adam, Kirsten C. S.; Mance, Irida; Fukuda, Keisuke; Vogel, Edward K.

2015-01-01

Attentional control and working memory capacity are important cognitive abilities that substantially vary between individuals. Although much is known about how attentional control and working memory capacity relate to each other and to constructs like fluid intelligence, little is known about how trial-by-trial fluctuations in attentional engagement impact trial-by-trial working memory performance. Here, we employ a novel whole-report memory task that allowed us to distinguish between varying levels of attentional engagement in humans performing a working memory task. By characterizing low-performance trials, we can distinguish between models in which working memory performance failures are caused by either (1) complete lapses of attention or (2) variations in attentional control. We found that performance failures increase with set-size and strongly predict working memory capacity. Performance variability was best modeled by an attentional control model of attention, not a lapse model. We examined neural signatures of performance failures by measuring EEG activity while participants performed the whole-report task. The number of items correctly recalled in the memory task was predicted by frontal theta power, with decreased frontal theta power associated with poor performance on the task. In addition, we found that poor performance was not explained by failures of sensory encoding; the P1/N1 response and ocular artifact rates were equivalent for high- and low-performance trials. In all, we propose that attentional lapses alone cannot explain individual differences in working memory performance. Instead, we find that graded fluctuations in attentional control better explain the trial-by-trial differences in working memory that we observe. PMID:25811710

Short-term Wind Forecasting at Wind Farms using WRF-LES and Actuator Disk Model

NASA Astrophysics Data System (ADS)

Kirkil, Gokhan

2017-04-01

Short-term wind forecasts are obtained for a wind farm on a mountainous terrain using WRF-LES. Multi-scale simulations are also performed using different PBL parameterizations. Turbines are parameterized using Actuator Disc Model. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Complex topography of the study area affects model performance, especially the accuracy of wind forecasts were poor for cross valley-mountain flows. By means of LES, we gain new knowledge about the sources of spatial and temporal variability of wind fluctuations such as the configuration of wind turbines.

Effect of exposure to good vs poor medical trainee performance on attending physician ratings of subsequent performances.

PubMed

Yeates, Peter; O'Neill, Paul; Mann, Karen; Eva, Kevin W

2012-12-05

Competency-based models of education require assessments to be based on individuals' capacity to perform, yet the nature of human judgment may fundamentally limit the extent to which such assessment is accurately possible. To determine whether recent observations of the Mini Clinical Evaluation Exercise (Mini-CEX) performance of postgraduate year 1 physicians influence raters' scores of subsequent performances, consistent with either anchoring bias (scores biased similar to previous experience) or contrast bias (scores biased away from previous experience). Internet-based randomized, blinded experiment using videos of Mini-CEX assessments of postgraduate year 1 trainees interviewing new internal medicine patients. Participants were 41 attending physicians from England and Wales experienced with the Mini-CEX, with 20 watching and scoring 3 good trainee performances and 21 watching and scoring 3 poor performances. All then watched and scored the same 3 borderline video performances. The study was completed between July and November 2011. The primary outcome was scores assigned to the borderline videos, using a 6-point Likert scale (anchors included: 1, well below expectations; 3, borderline; 6, well above expectations). Associations were tested in a multivariable analysis that included participants' sex, years of practice, and the stringency index (within-group z score of initial 3 ratings). The mean rating scores assigned by physicians who viewed borderline video performances following exposure to good performances was 2.7 (95% CI, 2.4-3.0) vs 3.4 (95% CI, 3.1-3.7) following exposure to poor performances (difference of 0.67 [95% CI, 0.28-1.07]; P = .001). Borderline videos were categorized as consistent with failing scores in 33 of 60 assessments (55%) in those exposed to good performances and in 15 of 63 assessments (24%) in those exposed to poor performances (P < .001). They were categorized as consistent with passing scores in 5 of 60 assessments (8.3%) in those exposed to good performances compared with 25 of 63 assessments (39.5%) in those exposed to poor performances (P < .001). Sex and years of attending practice were not associated with scores. The priming condition (good vs poor performances) and the stringency index jointly accounted for 45% of the observed variation in raters' scores for the borderline videos (P < .001). In an experimental setting, attending physicians exposed to videos of good medical trainee performances rated subsequent borderline performances lower than those who had been exposed to poor performances, consistent with a contrast bias.

Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models

NASA Astrophysics Data System (ADS)

Kim, Go-Un; Seo, Kyong-Hwan

2018-01-01

A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

Improving Learner Handovers in Medical Education.

PubMed

Warm, Eric J; Englander, Robert; Pereira, Anne; Barach, Paul

2017-07-01

Multiple studies have demonstrated that the information included in the Medical Student Performance Evaluation fails to reliably predict medical students' future performance. This faulty transfer of information can lead to harm when poorly prepared students fail out of residency or, worse, are shuttled through the medical education system without an honest accounting of their performance. Such poor learner handovers likely arise from two root causes: (1) the absence of agreed-on outcomes of training and/or accepted assessments of those outcomes, and (2) the lack of standardized ways to communicate the results of those assessments. To improve the current learner handover situation, an authentic, shared mental model of competency is needed; high-quality tools to assess that competency must be developed and tested; and transparent, reliable, and safe ways to communicate this information must be created.To achieve these goals, the authors propose using a learner handover process modeled after a patient handover process. The CLASS model includes a description of the learner's Competency attainment, a summary of the Learner's performance, an Action list and statement of Situational awareness, and Synthesis by the receiving program. This model also includes coaching oriented towards improvement along the continuum of education and care. Just as studies have evaluated patient handover models using metrics that matter most to patients, studies must evaluate this learner handover model using metrics that matter most to providers, patients, and learners.

Profiling outcomes of ambulatory care: casemix affects perceived performance.

PubMed

Berlowitz, D R; Ash, A S; Hickey, E C; Kader, B; Friedman, R; Moskowitz, M A

1998-06-01

The authors explored the role of casemix adjustment when profiling outcomes of ambulatory care. The authors reviewed the medical records of 656 patients with hypertension, diabetes, or chronic obstructive pulmonary disease (COPD) receiving care at one of three Department of Veterans Affairs medical centers. Outcomes included measures of physiological control for hypertension and diabetes, and of exacerbations for COPD. Predictors of poor outcomes, including physical examination findings, symptoms, and comorbidities, were identified and entered into regression models. Observed minus expected performance was described for each site, both before and after casemix adjustment. Risk-adjustment models were developed that were clinically plausible and had good performance properties. Differences existed among the three sites in the severity of the patients being cared for. For example, the percentage of patients expected to have poor blood pressure control were 35% at site 1, 37% at site 2, and 44% at site 3 (P < 0.01). Casemix-adjusted measures of performance were different from unadjusted measures. Sites that were outliers (P < 0.05) with one approach had observed performance no different from expected with another approach. Casemix adjustment models can be developed for outpatient medical conditions. Sites differ in the severity of patients they treat, and adjusting for these differences can alter judgments of site performance. Casemix adjustment is necessary when profiling outpatient medical conditions.

No food for thought: Food insecurity is related to poor mental health and lower academic performance among students in California's public university system.

PubMed

Martinez, Suzanna M; Frongillo, Edward A; Leung, Cindy; Ritchie, Lorrene

2018-06-01

This study examined the relationships between food insecurity, mental health, and academic performance among college students in a California public university system ( N = 8705). Structural equation modeling was performed to examine a direct path from food insecurity to student grade point average and an indirect path through mental health, controlling for demographic characteristics. Food insecurity was related to lower student grade point average directly and indirectly through poor mental health. These findings support the need for future interventions and policy on the importance of providing students with the basic needs to succeed both academically and in the future.

Sensitivity to gaze-contingent contrast increments in naturalistic movies: An exploratory report and model comparison

PubMed Central

Wallis, Thomas S. A.; Dorr, Michael; Bex, Peter J.

2015-01-01

Sensitivity to luminance contrast is a prerequisite for all but the simplest visual systems. To examine contrast increment detection performance in a way that approximates the natural environmental input of the human visual system, we presented contrast increments gaze-contingently within naturalistic video freely viewed by observers. A band-limited contrast increment was applied to a local region of the video relative to the observer's current gaze point, and the observer made a forced-choice response to the location of the target (≈25,000 trials across five observers). We present exploratory analyses showing that performance improved as a function of the magnitude of the increment and depended on the direction of eye movements relative to the target location, the timing of eye movements relative to target presentation, and the spatiotemporal image structure at the target location. Contrast discrimination performance can be modeled by assuming that the underlying contrast response is an accelerating nonlinearity (arising from a nonlinear transducer or gain control). We implemented one such model and examined the posterior over model parameters, estimated using Markov-chain Monte Carlo methods. The parameters were poorly constrained by our data; parameters constrained using strong priors taken from previous research showed poor cross-validated prediction performance. Atheoretical logistic regression models were better constrained and provided similar prediction performance to the nonlinear transducer model. Finally, we explored the properties of an extended logistic regression that incorporates both eye movement and image content features. Models of contrast transduction may be better constrained by incorporating data from both artificial and natural contrast perception settings. PMID:26057546

REMO poor man's reanalysis

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Poor Performance Among Trainees in a Dutch Postgraduate GP Training Program.

PubMed

Vermeulen, Margit I; Kuyvenhoven, Marijke M; de Groot, Esther; Zuithoff, Nicolaas Pa; Pieters, Honore M; van der Graaf, Yolanda; Damoiseaux, Roger Amj

2016-06-01

Poor performance among trainees is an important issue, for patient safety and economic reasons. While early identification might enhance remediation measures, we explored the frequency, nature, and risk factors of poor performance in a Dutch postgraduate general practitioner (GP) training program. All trainees who started the GP training between 2005 and 2007 were included. Multivariate logistic regression analysis was applied to examine associations between individual characteristics; early assessments of competencies and knowledge, training process characteristics (eg, illness, maternal leave), and the outcome poor performance; sub-analyses were performed for each year. A total of 215 trainees started the 3-year GP program, and 49 (22.8%) exhibited poor performance (in one or more years). In the first and second years, problem areas among poor performers were equally distributed across the roles of "medical expert," "communicator," and "professional." In the third year, shortcomings in "professionalism" were the most common problem. Increasing age was a risk factor for poor performance as were insufficient scores in communication and knowledge. Poor performance in the previous year was a risk factor for poor performance in the second and third years; OR=4.20 (CI=1.31--13.47) and OR=5.40 (CI=1.58--18.47), respectively. Poor performance is prevalent but primarily occurring within a single training year. This finding suggests that trainees are capable of solving trainee problems. Increasing age, insufficient assessment scores early in the training, and poor performance in a previous year constitute risk factors for poor performance.

Black-white disparity in physical performance among older women with newly diagnosed non-metastatic breast cancer: Exploring the role of inflammation and physical activity.

PubMed

Owusu, Cynthia; Schluchter, Mark; Koroukian, Siran M; Schmitz, Kathryn H; Berger, Nathan A

2018-04-23

To examine racial differences in physical performance among older women with newly diagnosed non-metastatic breast cancer and identify clinical, behavioral and biological factors that might contribute to such disparities. This is a cross-sectional study of women aged ≥65 years with newly diagnosed stage I-III breast cancer recruited from ambulatory oncology clinics at an academic center, between September 2010 and August 2015. Participants completed a Comprehensive Geriatric Assessment and laboratory testing for biomarkers of inflammation [interleukin-6 (IL6)] prior to receiving systemic treatment for cancer. The primary outcome was poor physical performance, defined as scoring ≤7 on the Short Physical Performance Battery, Yes or No. Logistic regression analyses were undertaken. Among 135 women with mean age of 74.8 years (SD = 6.9), 31% were African-American (AA), and 33% had poor physical performance. Controlling for age, education, comorbidities and geriatric syndromes, participants with poor physical performance were more likely to be AA [versus (vs.) Non-Hispanic Whites (NHW)], odds ratio (OR) = 3.10, 95% confidence interval (CI) = 1.18-8.15. Controlling further for physical activity (PA) attenuated the racial disparity in physical performance (OR = 2.50, CI = 0.91-6.84). Lastly, controlling for IL6 further diminished the racial disparity in physical performance (OR = 1.93, CI = 0.67-5.56). In adjusted models, PA and IL6 explained 29% and 38%, respectively, of the racial disparity in poor physical performance. Among older women with newly diagnosed non-metastatic breast cancer, poor physical performance was prevalent and AA were disproportionately affected. Less engagement in physical activity and subclinical inflammation partly contributed to this disparity. Copyright © 2018 Elsevier Inc. All rights reserved.

Performativity in School Management and Leadership in Botswana

ERIC Educational Resources Information Center

Pansiri, Nkobi Owen

2011-01-01

The thesis of this article is that the uncritical adoption of Western models of education management and leadership policies results in poor performance in schools in disadvantaged communities in developing countries. The argument shows that this has led to the institutionalization of generic education policies that are not contingent to the…

Self-Esteem and Adolescent Problems: Modeling Reciprocal Effects.

ERIC Educational Resources Information Center

Rosenberg, Morris; And Others

1989-01-01

Explores the reciprocal relationships between self-esteem and the following three problems of youth: (1) juvenile delinquency; (2) poor school performance; and (3) psychological depression. Findings include the following: (1) low self-esteem fosters delinquency, which may enhance self-esteem; (2) school performance affects self-esteem; and (3)…

Country of birth, parental background and self-rated health among adolescents: a population-based study.

PubMed

Lindström, Martin; Modén, Birgit; Rosvall, Maria

2014-12-01

The aim of this study was to investigate differences according to country of birth and parental country of birth, in relation to poor self-rated health (SRH), in Swedish adolescents. The Scania public health survey among children and adolescents, conducted in 2012, is a cross-sectional study including most pupils in grade 9 (15 years old), including in 32 of 33 municipalities. The participation rate was 83% (9,791 of 11,735). We performed logistic regressions to investigate the association between the students' country of birth, parental country of birth and poor SRH. Boys born outside Europe had an odds ratio (OR) 2.1 (1.6-2.8) of poor SRH in the unadjusted model, which was reduced to 0.7 (0.4-1.3) in the multiple model, as compared to boys born in Sweden with both or one parent born in Sweden. Boys born in Europe had an OR 0.4 (0.2-0.9) of poor SRH, after multiple adjustments. Girls born in Sweden with both parents born abroad, and girls born outside of Europe had significantly lower ORs of poor SRH in the multiple model. In particular, adjustment for socio-demographic and psychosocial factors reduced the ORs of poor SRH among boys, but did so to a lesser extent among girls. Differences in socio-demographic and psychosocial factors explained the higher odds of poor SRH among boys born outside of Europe. Girls born in Sweden with both parents born abroad, and girls born outside Europe, had significantly lower ORs of poor SRH. Our results indicate that there are gender differences in the factors behind poor self-rated health, according to the country-related background of adolescents in Sweden. © 2014 the Nordic Societies of Public Health.

[Two-level logistic modeling analysis on the factors that influence birth in hospitals in poor rural areas of Sichuan province].

PubMed

Yu, Chuan; Li, Xiao-song

2008-11-01

To identify the determinants of birth in hospitals in the poor rural areas. A questionnaire survey in eight poor counties in Sichuan province was conducted. Multilevel logistic regression analysis was performed to identify the factors that influenced birth in hospitals. Hospitals delivered 61.4% of babies in the selected counties. Education, eligibility to poverty relief, numbers of pre-natal examinations and abnormalities found in pre-natal examinations had a significant impact on birth in hospitals. Education of women and medical relief in the poor rural areas need to be strengthened to increase the proportion of babies delivered in hospitals in the poor rural areas. Systematic management of pregnant women and increased pre-natal examinations could also contribute to hospital delivery of babies.

The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?

NASA Technical Reports Server (NTRS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.; Or, Dani; Best, Martin J.; Johnson, Helen R.; Balsamo, Gianpaolo; Boone, Aaron; Cuntz, Matthais; Decharme, Bertrand;

Aztec Middle College: High School Alternatives in Community Colleges

ERIC Educational Resources Information Center

Olsen, Lynette

2010-01-01

The traditional high school model derived from the factory deficit model of the early 1900s has left many students, mainly minorities and/or low socioeconomic students, disenfranchised. This is evident in the poor school performance and high dropout rates of such students. Whereas the factory deficit model was created to promote only a few high…

Model Error Budgets

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

2008-01-01

An error budget is a commonly used tool in design of complex aerospace systems. It represents system performance requirements in terms of allowable errors and flows these down through a hierarchical structure to lower assemblies and components. The requirements may simply be 'allocated' based upon heuristics or experience, or they may be designed through use of physics-based models. This paper presents a basis for developing an error budget for models of the system, as opposed to the system itself. The need for model error budgets arises when system models are a principle design agent as is increasingly more common for poorly testable high performance space systems.

Depressive and anxiety disorders on-the-job: the importance of job characteristics for good work functioning in persons with depressive and anxiety disorders.

PubMed

Plaisier, Inger; de Graaf, Ron; de Bruijn, Jeanne; Smit, Johannes; van Dyck, Richard; Beekman, Aartjan; Penninx, Brenda

2012-12-30

This study examines the importance of job characteristics on absence and on-the-job performance in a large group of employees with diagnosed depressive and anxiety disorders. In a sample of 1522 employees (1129 persons with and 393 persons without psychopathology) participating in Netherlands Study of Depression and Anxiety (NESDA, n=2981) we examined associations between job characteristics and work functioning (absenteeism and work performance) in multinominal logistic regression models. Job characteristics were working hours, psychosocial working conditions and occupational status. As expected, depressed and anxious patients were at significantly elevated risk for absenteeism and poor work performance. In analyses adjusted for psychopathology, absenteeism and poor performance were significantly lower among persons reporting high job support, high job control, less working hours, self-employed and high skilled jobs. Associations were comparable between persons with and without psychopathology. High job support, high job control and reduced working hours were partially related to work functioning in both workers with- and without-psychopathology. Since depressed and anxious employees are at a substantially increased risk for absenteeism and poor work performance, strategies that improve job support and feelings of control at work may be especially helpful to prevent poor work functioning in this at-risk group of employees. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Software reliability perspectives

NASA Technical Reports Server (NTRS)

Wilson, Larry; Shen, Wenhui

1987-01-01

Software which is used in life critical functions must be known to be highly reliable before installation. This requires a strong testing program to estimate the reliability, since neither formal methods, software engineering nor fault tolerant methods can guarantee perfection. Prior to the final testing software goes through a debugging period and many models have been developed to try to estimate reliability from the debugging data. However, the existing models are poorly validated and often give poor performance. This paper emphasizes the fact that part of their failures can be attributed to the random nature of the debugging data given to these models as input, and it poses the problem of correcting this defect as an area of future research.

A Multi-Step Pathway Connecting Short Sleep Duration to Daytime Somnolence, Reduced Attention, and Poor Academic Performance: An Exploratory Cross-Sectional Study in Teenagers

PubMed Central

Perez-Lloret, Santiago; Videla, Alejandro J.; Richaudeau, Alba; Vigo, Daniel; Rossi, Malco; Cardinali, Daniel P.; Perez-Chada, Daniel

2013-01-01

Background: A multi-step causality pathway connecting short sleep duration to daytime somnolence and sleepiness leading to reduced attention and poor academic performance as the final result can be envisaged. However this hypothesis has never been explored. Objective: To explore consecutive correlations between sleep duration, daytime somnolence, attention levels, and academic performance in a sample of school-aged teenagers. Methods: We carried out a survey assessing sleep duration and daytime somnolence using the Pediatric Daytime Sleepiness Scale (PDSS). Sleep duration variables included week-days' total sleep time, usual bedtimes, and absolute weekdayto-weekend sleep time difference. Attention was assessed by d2 test and by the coding subtest from the WISC-IV scale. Academic performance was obtained from literature and math grades. Structural equation modeling was used to assess the independent relationships between these variables, while controlling for confounding effects of other variables, in one single model. Standardized regression weights (SWR) for relationships between these variables are reported. Results: Study sample included 1,194 teenagers (mean age: 15 years; range: 13-17 y). Sleep duration was inversely associated with daytime somnolence (SWR = -0.36, p < 0.01) while sleepiness was negatively associated with attention (SWR = -0.13, p < 0.01). Attention scores correlated positively with academic results (SWR = 0.18, p < 0.01). Daytime somnolence correlated negatively with academic achievements (SWR = -0.16, p < 0.01). The model offered an acceptable fit according to usual measures (RMSEA = 0.0548, CFI = 0.874, NFI = 0.838). A Sobel test confirmed that short sleep duration influenced attention through daytime somnolence (p < 0.02), which in turn influenced academic achievements through reduced attention (p < 0.002). Conclusions: Poor academic achievements correlated with reduced attention, which in turn was related to daytime somnolence. Somnolence correlated with short sleep duration. Citation: Perez-Lloret S; Videla AJ; Richaudeau A; Vigo D; Rossi M; Cardinali DP; Perez-Chada D. A multi-step pathway connecting short sleep duration to daytime somnolence, reduced attention, and poor academic performance: an exploratory cross-sectional study in teenagers. J Clin Sleep Med 2013;9(5):469-473. PMID:23674938

Measuring the usefulness of hidden units in Boltzmann machines with mutual information.

PubMed

Berglund, Mathias; Raiko, Tapani; Cho, Kyunghyun

2015-04-01

Restricted Boltzmann machines (RBMs) and deep Boltzmann machines (DBMs) are important models in deep learning, but it is often difficult to measure their performance in general, or measure the importance of individual hidden units in specific. We propose to use mutual information to measure the usefulness of individual hidden units in Boltzmann machines. The measure is fast to compute, and serves as an upper bound for the information the neuron can pass on, enabling detection of a particular kind of poor training results. We confirm experimentally that the proposed measure indicates how much the performance of the model drops when some of the units of an RBM are pruned away. We demonstrate the usefulness of the measure for early detection of poor training in DBMs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study.

PubMed

Miao, Hui; Hartman, Mikael; Bhoo-Pathy, Nirmala; Lee, Soo-Chin; Taib, Nur Aishah; Tan, Ern-Yu; Chan, Patrick; Moons, Karel G M; Wong, Hoong-Seam; Goh, Jeremy; Rahim, Siti Mastura; Yip, Cheng-Har; Verkooijen, Helena M

2014-01-01

In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.

Phonological working memory in German children with poor reading and spelling abilities.

PubMed

Steinbrink, Claudia; Klatte, Maria

2008-11-01

Deficits in verbal short-term memory have been identified as one factor underlying reading and spelling disorders. However, the nature of this deficit is still unclear. It has been proposed that poor readers make less use of phonological coding, especially if the task can be solved through visual strategies. In the framework of Baddeley's phonological loop model, this study examined serial recall performance in German second-grade children with poor vs good reading and spelling abilities. Children were presented with four-item lists of common nouns for immediate serial recall. Word length and phonological similarity as well as presentation modality (visual vs auditory) and type of recall (visual vs verbal) were varied as within-subject factors in a mixed design. Word length and phonological similarity effects did not differ between groups, thus indicating equal use of phonological coding and rehearsal in poor and good readers. However, in all conditions, except the one that combined visual presentation and visual recall, overall performance was significantly lower in poor readers. The results suggest that the poor readers' difficulties do not arise from an avoidance of the phonological loop, but from its inefficient use. An alternative account referring to unstable phonological representations in long-term memory is discussed. Copyright (c) 2007 John Wiley & Sons, Ltd.

Academic performance in adolescents with delayed sleep phase.

PubMed

Sivertsen, Børge; Glozier, Nick; Harvey, Allison G; Hysing, Mari

2015-09-01

Delayed sleep phase (DSP) in adolescence has been linked to reduced academic performance, but there are few population-based studies examining this association using validated sleep measures and objective outcomes. The youth@hordaland-survey, a large population-based study from Norway conducted in 2012, surveyed 8347 high-school students aged 16-19 years (54% girls). DSP was assessed by self-report sleep measures, and it was operationalized according to the International Classification of Sleep Disorders - Second Edition. School performance (grade point average, GPA) was obtained from official administrative registries, and it was linked individually to health data. DSP was associated with increased odds for poor school performance. After adjusting for age and gender, DSP was associated with a threefold increased odds of poor GPA (lowest quartile) [odds ratio (OR) = 2.95; 95% confidence interval (CI): 2.03-4.30], and adjustment for sociodemographics and lifestyle factors did not, or only slightly, attenuate this association. Adjustment for nonattendance at school reduced the association substantially, and in the fully adjusted model, the effect of DSP on poor academic performance was reduced to a non-significant level. Mediation analyses confirmed both direct and significant indirect effects of DSP on school performance based on school absence, daytime sleepiness, and sleep duration. Poor academic performance may reflect an independent effect of underlying circadian disruption, which in part could be mediated by school attendance, as well as daytime sleepiness and short sleep duration. This suggests that careful assessment of sleep is warranted in addressing educational difficulties. Copyright © 2015 Elsevier B.V. All rights reserved.

From approach to inhibition: the influence of power on responses to poor performers.

PubMed

Ferguson, Amanda J; Ormiston, Margaret E; Moon, Henry

2010-03-01

This article examines how relative differences in power affect responses to poor performers in organizations. We predicted that higher power individuals would engage in approach-related behaviors, whereas lower power individuals would be inhibited when responding to poor performers. Results from a scenario study and a field study generally supported this prediction, indicating that power was positively related to training or confronting a poor performer and negatively related to compensating for or rejecting a poor performer. A second scenario study investigated the effect of the interaction of power and emotion on individual responses to poor performers. Results showed that the type of emotion expressed moderated the effect of power on inhibition-related responses. We discuss implications for managing poor performers with relative power differences. 2010 APA, all rights reserved

Why Study Time Does Not Predict Grade Point Average across College Students: Implications of Deliberate Practice for Academic Performance

ERIC Educational Resources Information Center

Plant, E. Ashby; Ericsson, K. Anders; Hill, Len; Asberg, Kia

2005-01-01

The current work draws upon the theoretical framework of deliberate practice in order to clarify why the amount of study by college students is a poor predictor of academic performance. A model was proposed where performance in college, both cumulatively and for a current semester, was jointly determined by previous knowledge and skills as well as…

Children's school performance: impact of general and oral health.

PubMed

Blumenshine, Stephanie L; Vann, William F; Gizlice, Ziya; Lee, Jessica Y

2008-01-01

The purpose of this study was to examine: a) the sociodemographic and health factors associated with poor school performance among North Carolina children; and b) the impact of poor oral health status on school performance while controlling for other health and sociodemographic factors. We used data from the 2005 Child Health Assessment and Monitoring Program, a follow-back telephone survey to the Behavioral Risk Factor Surveillance System involving parents/guardians of children 0 to 17. This project includes sections on oral health and school performance. Our principal outcome variable was school performance and our major explanatory variable was children's oral health status, based upon parental report. Our sample consisted of 2,871 school children, weighted to reflect the North Carolina census. Bivariate analysis revealed that sex, race, parental education, low socioeconomic status, poor general health, poor oral health, and the interaction of poor oral health and general health were significantly related to school performance (P < 0.05). Logistic regression analysis demonstrates the effects of poor oral health and general health on school performance. Children with both poor oral health and general health were 2.3 times more likely to report poor school performance. Children with either poor oral health or general health were only 1.4 times more likely to report poor school performance. Our results show that children who have both poor oral health and general health are more likely to have poor school performance. Our findings suggest that the improvement of children's oral health may be a vehicle to improve their educational experience.

Portuguese School Libraries Evaluation Model: An Analysis of Primary Schools' Results for the "Reading and Literacy" Domain

ERIC Educational Resources Information Center

Martins, Jorge Tiago; Martins, Rosa Maria

2012-01-01

This paper reports the implementation results of the Portuguese School Libraries Evaluation Model, more specifically the results of primary schools self-evaluation of their libraries' reading promotion and information literacy development activities. School libraries that rated their performance as either "Excellent" or "Poor"…

The effects of competition on efficiency of electricity generation: A post-PURPA analysis

NASA Astrophysics Data System (ADS)

Jordan, Paula Faye

1998-10-01

The central issue of this research is the effects increased market competition has on production efficiency. Specifically, the research focuses upon measuring the relative level of efficiency in the generation of electricity in 1978 and 1993. It is hypothesized that the Public Utilities Regulatory Policy Act (PURPA), passed by Congress in 1978, made progress toward achieving its legislative intent of increasing competition, and therefore increased efficiency, in the generation of electricity. The methodology used to measure levels of efficiency in this research is the stochastic statistical estimator with the functional form of the translog production function. The models are then estimated using the maximum likelihood estimating technique using plant level data of coal generating units in the U.S. for 1978 and 1993. Results from the estimation of these models indicate that: (a) For the technical efficiency measures, the 1978 data set out performed the 1993 data set for the OTE and OTE of Fuel measures; (b) the 1993 data set was relatively more efficient in the OTE of Capital and the OTE of Labor when compared to the 1978 data set; (c) The 1993 observations indicated a relatively greater level of efficiency over 1978 in the OAE, OAE of Fuel, and OAE of Capital measures; (d) The OAE of Labor measure findings supported the 1978 observations as more efficient when compared to the 1993 set of observations; (e) When looking at the top and bottom ranked sites within each data set, the results indicated that sites which were top or poor performers for the technical and allocative efficiency measures tended to be a top or poor performer for the overall, fuel, and capital measures. The sites that appeared as a top or poor performer of labor measures within the technical and allocative groups were often unique and didn't necessarily appear as a top or poor performer in the other efficiency measures.

Combined Effect of Contraction Ratio and Chamber Pressure on the Performance of a Gaseous Hydrogen-Liquid-Oxygen Combustor for a Given Propellant Weight Flow and Oxidant-Fuel Ratio

NASA Technical Reports Server (NTRS)

Hersch, Martin

1961-01-01

The effect of contraction ratio and chamber pressure on the combustion performance of a gaseous-hydrogen-liquid-oxygen combustor was investigated analytically and experimentally. The experiment was conducted with a "two-dimensional" gaseous-hydrogen-liquid-oxygen engine of about 150-pound thrust. The contraction ratio was varied from 1.5 to 6 by changing the nozzle throat area. This variation resulted in a chamber pressure variation of about 25 to 120 pounds per square inch. The experimental results were corrected for heat transfer to the engine walls and momentum pressure losses. The experimental performance, as evaluated in terms of characteristic exhaust velocity, was 98 percent of theoretical at contraction ratios greater than 3 but decreased very rapidly at smaller contraction ratios. The heat-transfer rate increased with increasing contraction ratio and chamber pressure; it was about 1 Btu per square inch per second at a contraction ratio of 1.5 and increased to about 3 at a contraction ratio of 6. The combined effects of contraction-ratio and chamber-pressure changes on performance were investigated analytically with a mixing model and a vaporization model. The mixing model predicted very poor mixing at contraction ratios below 3 and almost perfect mixing at higher contraction ratios. The performance predicted by the vaporization model was very close to 100 percent for all contraction ratios. From these results, it was concluded that the performance was limited by poor mixing at low contraction ratios and chamber pressures.

Prevention of and dealing with poor performance: an interview study about how professional associations aim to support healthcare professionals.

PubMed

Weenink, Jan-Willem; Kool, Rudolf B; Hesselink, Gijs; Bartels, Ronald H; Westert, Gert P

2017-10-01

To explore how professional associations of nine healthcare professions aim to support professionals to prevent and deal with poor performance. Qualitative interview study. The Netherlands. Representatives of professional associations for dentists, general practitioners, medical specialists, midwives, nurses, pharmacists, physiotherapists, psychologists and psychotherapists. During nine face-to-face semi-structured interviews we asked how associations aim to support professionals in prevention of and dealing with poor performance. Following the first interview, we monitored new initiatives in support over a 2.5-year period, after which we conducted a second interview. Interviews were analysed using thematic analysis. Available policy and support regarding poor performance. Three themes emerged from our data (i.e. elaborating on professional performance, performance insight and dealing with poor performance) for which we identified a total of 10 categories of support. Support concerned professional codes, guidelines and codes of conduct, quality registers, individual performance assessment, peer consultation, practice evaluation, helpdesk and expert counselling, a protocol for dealing with poor performance, a place for support and to report poor performance, and internal disciplinary procedures. This study provides an overview of support given to nine healthcare professions by their associations regarding poor performance, and identifies gaps that associations could follow up on, such as clarifying what to do when confronted with a poorly performing colleague, supporting professionals that poorly perform, and developing methods for individual performance assessment to gain performance insight. A next step would be to evaluate the use and effect of different types of support. © The Author 2017. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Toward the establishment of standardized in vitro tests for lipid-based formulations, part 1: method parameterization and comparison of in vitro digestion profiles across a range of representative formulations.

PubMed

Williams, Hywel D; Sassene, Philip; Kleberg, Karen; Bakala-N'Goma, Jean-Claude; Calderone, Marilyn; Jannin, Vincent; Igonin, Annabel; Partheil, Anette; Marchaud, Delphine; Jule, Eduardo; Vertommen, Jan; Maio, Mario; Blundell, Ross; Benameur, Hassan; Carrière, Frédéric; Müllertz, Anette; Porter, Christopher J H; Pouton, Colin W

2012-09-01

The Lipid Formulation Classification System Consortium is an industry-academia collaboration, established to develop standardized in vitro methods for the assessment of lipid-based formulations (LBFs). In this first publication, baseline conditions for the conduct of digestion tests are suggested and a series of eight model LBFs are described to probe test performance across different formulation types. Digestion experiments were performed in vitro using a pH-stat apparatus and danazol employed as a model poorly water-soluble drug. LBF digestion (rate and extent) and drug solubilization patterns on digestion were examined. To evaluate cross-site reproducibility, experiments were conducted at two sites and highly consistent results were obtained. In a further refinement, bench-top centrifugation was explored as a higher throughput approach to separation of the products of digestion (and compared with ultracentrifugation), and conditions under which this method was acceptable were defined. Drug solubilization was highly dependent on LBF composition, but poorly correlated with simple performance indicators such as dispersion efficiency, confirming the utility of the digestion model as a means of formulation differentiation. Copyright © 2012 Wiley Periodicals, Inc.

Using brain imaging to extract the structure of complex events at the rational time band.

PubMed

Anderson, John R; Qin, Yulin

2008-09-01

A functional magnetic resonance imaging (fMRI) study was performed in which participants performed a complex series of mental calculations that spanned about 2 min. An Adaptive Control of Thought--Rational (ACT-R) model [Anderson, J. R. How can the human mind occur in the physical universe? New York: Oxford University Press, 2007] was developed that successfully fit the distribution of latencies. This model generated predictions for the fMRI signal in six brain regions that have been associated with modules in the ACT-R theory. The model's predictions were confirmed for a fusiform region that reflects the visual module, for a prefrontal region that reflects the retrieval module, and for an anterior cingulate region that reflects the goal module. In addition, the only significant deviations to the motor region that reflects the manual module were anticipatory hand movements. In contrast, the predictions were relatively poor for a parietal region that reflects an imaginal module and for a caudate region that reflects the procedural module. Possible explanations of these poor fits are discussed. In addition, exploratory analyses were performed to find regions that might correspond to the predictions of the modules.

Neurologic examination at 24–48 hours predicts functional outcomes in basilar artery occlusion stroke

PubMed Central

Rangaraju, Srikant; Jovin, Tudor G.; Frankel, Michael; Schonewille, Wouter J.; Algra, Ale; Kappelle, L. Jaap; Nogueira, Raul G.

2016-01-01

Background and Purpose Accurate long-term outcome prognostication in basilar artery occlusion (BAO) strokes may guide clinical management in the subacute stage. We determine the prognostic value of the follow-up neurologic examination using the NIH stroke scale (NIHSS) and identify 24–48 hours NIHSS risk categories in BAO patients. Methods Participants of an observational registry of radiologically-confirmed acute BAO (BASICS) with prospectively collected 24–48 hours NIHSS and 1-month modified Rankin Scale (mRS) scores were included. Uni- and multivariable modeling were performed to identify independent predictors of poor outcome. Predictive powers of baseline and 24–48 hour NIHSS for poor outcome (mRS 4–6) and 1-month mortality were determined by Receiver Operating Characteristic analyses. Classification and regression tree (CART) analysis was performed to identify risk groups. Results 376 of 619 BASICS participants were included of whom 65.4% had poor outcome. In multivariable analyses, 24–48 hours NIHSS (OR=1.28 [1.21–1.35]), history of minor stroke (OR=2.64 [1.04–6.74], time to treatment >6 hours (OR=3.07 [1.35–6.99]) and age (OR 1.02 [0.99–1.04] were retained in the final model as predictors of poor outcome. Prognostic power of 24–48 hours NIHSS was higher than baseline NIHSS for 1-month poor outcome (AUC 0.92 vs. 0.75) and mortality (AUC 0.85 vs. 0.72). CART analysis identified five 24–48 hour NIHSS risk categories with poor outcome rates of 9.4% (NIHSS 0–4), 36% (NIHSS 5–11), 84.3% (NIHSS 12–22), 96.1% (NIHSS 23–27) and 100% (NIHSS≥28). Conclusion 24–48 hour NIHSS accurately predicts 1-month poor outcome and mortality and represents a clinically valuable prognostic tool for the care of BAO patients. PMID:27586683

A Study of a High Performing, High Poverty Elementary School on the Texas-Mexico Border

ERIC Educational Resources Information Center

Lopez, Cynthia Iris

2012-01-01

Transforming low performing schools to ensure the academic success of Hispanic children situated in poverty remains an educational challenge. External factors impacting student learning are often targeted as the main reasons for poor academic achievement, thereby advancing the culturally deficit model. This study is about an elementary school that…

5 CFR 9701.408 - Developing performance and addressing poor performance.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Developing performance and addressing poor performance. (a) Subject to budgetary and other organizational... 5 Administrative Personnel 3 2011-01-01 2011-01-01 false Developing performance and addressing poor performance. 9701.408 Section 9701.408 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY...

Predicting Survival of De Novo Metastatic Breast Cancer in Asian Women: Systematic Review and Validation Study

PubMed Central

Miao, Hui; Hartman, Mikael; Bhoo-Pathy, Nirmala; Lee, Soo-Chin; Taib, Nur Aishah; Tan, Ern-Yu; Chan, Patrick; Moons, Karel G. M.; Wong, Hoong-Seam; Goh, Jeremy; Rahim, Siti Mastura; Yip, Cheng-Har; Verkooijen, Helena M.

2014-01-01

Background In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. Materials and Methods We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). Results We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48–0.53) to 0.63 (95% CI, 0.60–0.66). Conclusion The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making. PMID:24695692

Prediction Models for 30-Day Mortality and Complications After Total Knee and Hip Arthroplasties for Veteran Health Administration Patients With Osteoarthritis.

PubMed

Harris, Alex Hs; Kuo, Alfred C; Bowe, Thomas; Gupta, Shalini; Nordin, David; Giori, Nicholas J

2018-05-01

Statistical models to preoperatively predict patients' risk of death and major complications after total joint arthroplasty (TJA) could improve the quality of preoperative management and informed consent. Although risk models for TJA exist, they have limitations including poor transparency and/or unknown or poor performance. Thus, it is currently impossible to know how well currently available models predict short-term complications after TJA, or if newly developed models are more accurate. We sought to develop and conduct cross-validation of predictive risk models, and report details and performance metrics as benchmarks. Over 90 preoperative variables were used as candidate predictors of death and major complications within 30 days for Veterans Health Administration patients with osteoarthritis who underwent TJA. Data were split into 3 samples-for selection of model tuning parameters, model development, and cross-validation. C-indexes (discrimination) and calibration plots were produced. A total of 70,569 patients diagnosed with osteoarthritis who received primary TJA were included. C-statistics and bootstrapped confidence intervals for the cross-validation of the boosted regression models were highest for cardiac complications (0.75; 0.71-0.79) and 30-day mortality (0.73; 0.66-0.79) and lowest for deep vein thrombosis (0.59; 0.55-0.64) and return to the operating room (0.60; 0.57-0.63). Moderately accurate predictive models of 30-day mortality and cardiac complications after TJA in Veterans Health Administration patients were developed and internally cross-validated. By reporting model coefficients and performance metrics, other model developers can test these models on new samples and have a procedure and indication-specific benchmark to surpass. Published by Elsevier Inc.

Four dimensional data assimilation (FDDA) impacts on WRF performance in simulating inversion layer structure and distributions of CMAQ-simulated winter ozone concentrations in Uintah Basin

NASA Astrophysics Data System (ADS)

Tran, Trang; Tran, Huy; Mansfield, Marc; Lyman, Seth; Crosman, Erik

2018-03-01

Four-dimensional data assimilation (FDDA) was applied in WRF-CMAQ model sensitivity tests to study the impact of observational and analysis nudging on model performance in simulating inversion layers and O3 concentration distributions within the Uintah Basin, Utah, U.S.A. in winter 2013. Observational nudging substantially improved WRF model performance in simulating surface wind fields, correcting a 10 °C warm surface temperature bias, correcting overestimation of the planetary boundary layer height (PBLH) and correcting underestimation of inversion strengths produced by regular WRF model physics without nudging. However, the combined effects of poor performance of WRF meteorological model physical parameterization schemes in simulating low clouds, and warm and moist biases in the temperature and moisture initialization and subsequent simulation fields, likely amplified the overestimation of warm clouds during inversion days when observational nudging was applied, impacting the resulting O3 photochemical formation in the chemistry model. To reduce the impact of a moist bias in the simulations on warm cloud formation, nudging with the analysis water mixing ratio above the planetary boundary layer (PBL) was applied. However, due to poor analysis vertical temperature profiles, applying analysis nudging also increased the errors in the modeled inversion layer vertical structure compared to observational nudging. Combining both observational and analysis nudging methods resulted in unrealistically extreme stratified stability that trapped pollutants at the lowest elevations at the center of the Uintah Basin and yielded the worst WRF performance in simulating inversion layer structure among the four sensitivity tests. The results of this study illustrate the importance of carefully considering the representativeness and quality of the observational and model analysis data sets when applying nudging techniques within stable PBLs, and the need to evaluate model results on a basin-wide scale.

Modelling Errors in Automatic Speech Recognition for Dysarthric Speakers

NASA Astrophysics Data System (ADS)

Caballero Morales, Santiago Omar; Cox, Stephen J.

2009-12-01

Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited phonemic repertoire decrease speech recognition accuracy, making conventional speaker adaptation algorithms perform poorly on dysarthric speakers. In this work, rather than adapting the acoustic models, we model the errors made by the speaker and attempt to correct them. For this task, two techniques have been developed: (1) a set of "metamodels" that incorporate a model of the speaker's phonetic confusion matrix into the ASR process; (2) a cascade of weighted finite-state transducers at the confusion matrix, word, and language levels. Both techniques attempt to correct the errors made at the phonetic level and make use of a language model to find the best estimate of the correct word sequence. Our experiments show that both techniques outperform standard adaptation techniques.

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution.

PubMed

Harrison, Xavier A

2015-01-01

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels), I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed poorly when models contained <5 levels of the random intercept term, especially for estimating variance components, and this effect appeared independent of total sample size. These results suggest that OLRE are a useful tool for modelling overdispersion in Binomial data, but that they do not perform well in all circumstances and researchers should take care to verify the robustness of parameter estimates of OLRE models.

On the effects of improved cross-section representation in one dimensional flow routing models applied to ephemeral rivers

USDA-ARS?s Scientific Manuscript database

Flash floods are an important component of the semi-arid hydrological cycle, and provide the potential for groundwater recharge as well as posing a dangerous natural hazard. A number of catchment models have been applied to flash flood prediction; however, in general they perform poorly. This study ...

A STUDY OF LONGITUDINAL PATTERNS OF FAILURE AMONG HIGH SCHOOL DROP-OUTS AND POORLY PERFORMING GRADUATES.

ERIC Educational Resources Information Center

STOLLER, DAVID S.

THE RELATIONSHIP BETWEEN PATTERNS OF POOR PERFORMANCE AND SIGNIFICANT DISTINGUISHING FACTORS WHICH MIGHT IDENTIFY DROPOUTS IS EXPLORED. DATA WERE OBTAINED ON 270 STUDENTS (FROM A PARENT POPULATION OF 2,500) WHO WERE POOR PERFORMERS (POOR PERFORMANCE BEING DEFINED AS THREE "D'S" OR "F'S" IN HIGH SCHOOL). THE VAST MAJORITY OF…

Improved simulation of poorly drained forests using Biome-BGC.

PubMed

Bond-Lamberty, Ben; Gower, Stith T; Ahl, Douglas E

2007-05-01

Forested wetlands and peatlands are important in boreal and terrestrial biogeochemical cycling, but most general-purpose forest process models are designed and parameterized for upland systems. We describe changes made to Biome-BGC, an ecophysiological process model, that improve its ability to simulate poorly drained forests. Model changes allowed for: (1) lateral water inflow from a surrounding watershed, and variable surface and subsurface drainage; (2) adverse effects of anoxic soil on decomposition and nutrient mineralization; (3) closure of leaf stomata in flooded soils; and (4) growth of nonvascular plants (i.e., bryophytes). Bryophytes were treated as ectohydric broadleaf evergreen plants with zero stomatal conductance, whose cuticular conductance to CO(2) was dependent on plant water content. Individual model changes were parameterized with published data, and ecosystem-level model performance was assessed by comparing simulated output to field data from the northern BOREAS site in Manitoba, Canada. The simulation of the poorly drained forest model exhibited reduced decomposition and vascular plant growth (-90%) compared with that of the well-drained forest model; the integrated bryophyte photosynthetic response accorded well with published data. Simulated net primary production, biomass and soil carbon accumulation broadly agreed with field measurements, although simulated net primary production was higher than observed data in well-drained stands. Simulated net primary production in the poorly drained forest was most sensitive to oxygen restriction on soil processes, and secondarily to stomatal closure in flooded conditions. The modified Biome-BGC remains unable to simulate true wetlands that are subject to prolonged flooding, because it does not track organic soil formation, water table changes, soil redox potential or anaerobic processes.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment

NASA Astrophysics Data System (ADS)

De Kauwe, M. G.; Medlyn, B.; Walker, A.; Zaehle, S.; Pendall, E.; Norby, R. J.

2017-12-01

Multifactor experiments are often advocated as important for advancing models, yet to date, such models have only been tested against single-factor experiments. We applied 10 models to the multifactor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions: comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO2-induced water savings to extend the growing season length. Observed interactive (CO2 × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

A Comparison of Three Programming Models for Adaptive Applications

NASA Technical Reports Server (NTRS)

Shan, Hong-Zhang; Singh, Jaswinder Pal; Oliker, Leonid; Biswa, Rupak; Kwak, Dochan (Technical Monitor)

2000-01-01

We study the performance and programming effort for two major classes of adaptive applications under three leading parallel programming models. We find that all three models can achieve scalable performance on the state-of-the-art multiprocessor machines. The basic parallel algorithms needed for different programming models to deliver their best performance are similar, but the implementations differ greatly, far beyond the fact of using explicit messages versus implicit loads/stores. Compared with MPI and SHMEM, CC-SAS (cache-coherent shared address space) provides substantial ease of programming at the conceptual and program orchestration level, which often leads to the performance gain. However it may also suffer from the poor spatial locality of physically distributed shared data on large number of processors. Our CC-SAS implementation of the PARMETIS partitioner itself runs faster than in the other two programming models, and generates more balanced result for our application.

Slug to churn transition analysis using wire-mesh sensor

NASA Astrophysics Data System (ADS)

H. F. Velasco, P.; Ortiz-Vidal, L. E.; Rocha, D. M.; Rodriguez, O. M. H.

2016-06-01

A comparison between some theoretical slug to churn flow-pattern transition models and experimental data is performed. The flow-pattern database considers vertical upward air-water flow at standard temperature and pressure for 50 mm and 32 mm ID pipes. A briefly description of the models and its phenomenology is presented. In general, the performance of the transition models is poor. We found that new experimental studies describing objectively both stable and unstable slug flow-pattern are required. In this sense, the Wire Mesh Sensor (WMS) can assist to that aim. The potential of the WMS is outlined.

Predictors of Poor School Readiness in Children Without Developmental Delay at Age 2

PubMed Central

Dudovitz, Rebecca N.; Coker, Tumaini R.; Barnert, Elizabeth S.; Biely, Christopher; Li, Ning; Szilagyi, Peter G.; Larson, Kandyce; Halfon, Neal; Zimmerman, Frederick J.; Chung, Paul J.

2016-01-01

BACKGROUND AND OBJECTIVES: Current recommendations emphasize developmental screening and surveillance to identify developmental delays (DDs) for referral to early intervention (EI) services. Many young children without DDs, however, are at high risk for poor developmental and behavioral outcomes by school entry but are ineligible for EI. We developed models for 2-year-olds without DD that predict, at kindergarten entry, poor academic performance and high problem behaviors. METHODS: Data from the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B), were used for this study. The analytic sample excluded children likely eligible for EI because of DDs or very low birth weight. Dependent variables included low academic scores and high problem behaviors at the kindergarten wave. Regression models were developed by using candidate predictors feasibly obtainable during typical 2-year well-child visits. Models were cross-validated internally on randomly selected subsamples. RESULTS: Approximately 24% of all 2-year-old children were ineligible for EI at 2 years of age but still had poor academic or behavioral outcomes at school entry. Prediction models each contain 9 variables, almost entirely parental, social, or economic. Four variables were associated with both academic and behavioral risk: parental education below bachelor’s degree, little/no shared reading at home, food insecurity, and fair/poor parental health. Areas under the receiver-operating characteristic curve were 0.76 for academic risk and 0.71 for behavioral risk. Adding the mental scale score from the Bayley Short Form–Research Edition did not improve areas under the receiver-operating characteristic curve for either model. CONCLUSIONS: Among children ineligible for EI services, a small set of clinically available variables at age 2 years predicted academic and behavioral outcomes at school entry. PMID:27432845

Rethinking Remediation: A Model to Support the Detailed Diagnosis of Clinicians' Performance Problems and the Development of Effective Remediation Plans.

PubMed

Prescott-Clements, Linda; Voller, Vicky; Bell, Mark; Nestors, Natasha; van der Vleuten, Cees P M

2017-01-01

The successful remediation of clinicians demonstrating poor performance in the workplace is essential to ensure the provision of safe patient care. Clinicians may develop performance problems for numerous reasons, including health, personal factors, the workplace environment, or outdated knowledge/skills. Performance problems are often complex involving multifactorial issues, encompassing knowledge, skills, and professional behaviors. It is important that (where possible and appropriate) clinicians are supported through effective remediation to return them to safe clinical practice. A review of the literature demonstrated that research into remediation is in its infancy, with little known about the effectiveness of remediation programs currently. Current strategies for the development of remediation programs are mostly "intuitive"; a few draw upon established theories to inform their approach. Similarly, although it has been established that identification of the nature/scope of performance problems through assessment is an essential first step within remediation, the need for a more widespread "diagnosis" of why the problems exist is emerging. These reasons for poor performance, particularly in the context of experienced practicing clinicians, are likely to have an impact on the potential success of remediation and should be considered within the "diagnosis." A new model for diagnosing the performance problems of the clinicians has been developed, using behavioral change theories to explore known barriers to successful remediation, such as insight, motivation, attitude, self-efficacy, and the working environment, in addition to addressing known deficits regarding knowledge and skills. This novel approach is described in this article. An initial feasibility study has demonstrated the acceptability and practical implementation of our model.

Alkyl polyglucoside vs. ethoxylated surfactant-based microemulsions as vehicles for two poorly water-soluble drugs: physicochemical characterization and in vivo skin performance.

PubMed

Pajić, Nataša Z Bubić; Todosijević, Marija N; Vuleta, Gordana M; Cekić, Nebojša D; Dobričić, Vladimir D; Vučen, Sonja R; Čalija, Bojan R; Lukić, Milica Ž; Ilić, Tanja M; Savić, Snežana D

2017-12-20

Two types of biocompatible surfactants were evaluated for their capability to formulate skin-friendly/non-irritant microemulsions as vehicles for two poorly water-soluble model drugs differing in properties and concentrations: alkyl polyglucosides (decyl glucoside and caprylyl/capryl glucoside) and ethoxylated surfactants (glycereth-7-caprylate/ caprate and polysorbate 80). Phase behavior, structural inversion and microemulsion solubilization potential for sertaconazole nitrate and adapalene were found to be highly dependent on the surfactants structure and HLB value. Performed characterization (polarized light microscopy, pH, electrical conductivity, rheological, FTIR and DSC measurements) indicated a formulation containing glycereth- 7-caprylate/caprate as suitable for incorporation of both drugs, whereas alkyl polyglucoside-based systems did not exhibit satisfying solubilization capacity for sertaconazole nitrate. Further, monitored parameters were strongly affected by sertaconazole nitrate incorporation, while they remained almost unchanged in adapalene-loaded vehicles. In addition, results of the in vivo skin performance study supported acceptable tolerability for all investigated formulations, suggesting selected microemulsions as promising carriers worth exploring further for effective skin delivery of model drugs.

Making ecological models adequate

USGS Publications Warehouse

Getz, Wayne M.; Marshall, Charles R.; Carlson, Colin J.; Giuggioli, Luca; Ryan, Sadie J.; Romañach, Stephanie; Boettiger, Carl; Chamberlain, Samuel D.; Larsen, Laurel; D'Odorico, Paolo; O'Sullivan, David

2018-01-01

Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a model's ability to predict ecological systems’ responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management.

Poor oral health including active caries in 187 UK professional male football players: clinical dental examination performed by dentists.

PubMed

Needleman, Ian; Ashley, Paul; Meehan, Lyndon; Petrie, Aviva; Weiler, Richard; McNally, Steve; Ayer, Chris; Hanna, Rob; Hunt, Ian; Kell, Steven; Ridgewell, Paul; Taylor, Russell

2016-01-01

The few studies that have assessed oral health in professional/elite football suggest poor oral health with minimal data on impact on performance. The aim of this research was to determine oral health in a representative sample of professional footballers in the UK and investigate possible determinants of oral health and self-reported impact on well-being, training and performance. Clinical oral health examination of senior squad players using standard methods and outcomes carried out at club training facilities. Questionnaire data were also collected. 8 teams were included, 5 Premier League, 2 Championship and 1 League One. 6 dentists examined 187 players who represented >90% of each senior squad. Oral health was poor: 37% players had active dental caries, 53% dental erosion and 5% moderate-severe irreversible periodontal disease. 45% were bothered by their oral health, 20% reported an impact on their quality of life and 7% on training or performance. Despite attendance for dental check-ups, oral health deteriorated with age. This is the first large, representative sample study in professional football. Oral health of professional footballers is poor, and this impacts on well-being and performance. Successful strategies to promote oral health within professional football are urgently needed, and research should investigate models based on best evidence for behaviour change and implementation science. Furthermore, this study provides strong evidence to support oral health screening within professional football. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

On the importance of geological data for hydraulic tomography analysis: Laboratory sandbox study

NASA Astrophysics Data System (ADS)

Zhao, Zhanfeng; Illman, Walter A.; Berg, Steven J.

2016-11-01

This paper investigates the importance of geological data in Hydraulic Tomography (HT) through sandbox experiments. In particular, four groundwater models with homogeneous geological units constructed with borehole data of varying accuracy are jointly calibrated with multiple pumping test data of two different pumping and observation densities. The results are compared to those from a geostatistical inverse model. Model calibration and validation performances are quantitatively assessed using drawdown scatterplots. We find that accurate and inaccurate geological models can be well calibrated, despite the estimated K values for the poor geological models being quite different from the actual values. Model validation results reveal that inaccurate geological models yield poor drawdown predictions, but using more calibration data improves its predictive capability. Moreover, model comparisons among a highly parameterized geostatistical and layer-based geological models show that, (1) as the number of pumping tests and monitoring locations are reduced, the performance gap between the approaches decreases, and (2) a simplified geological model with a fewer number of layers is more reliable than the one based on the wrong description of stratigraphy. Finally, using a geological model as prior information in geostatistical inverse models results in the preservation of geological features, especially in areas where drawdown data are not available. Overall, our sandbox results emphasize the importance of incorporating geological data in HT surveys when data from pumping tests is sparse. These findings have important implications for field applications of HT where well distances are large.

School violence, mental health, and educational performance in Uganda.

PubMed

Devries, Karen M; Child, Jennifer C; Allen, Elizabeth; Walakira, Eddy; Parkes, Jenny; Naker, Dipak

2014-01-01

Violence against children from school staff is anecdotally common in low- and middle-income countries, but data on prevalence and associations with mental health and educational outcomes are lacking. We report data from a cross-sectional survey conducted in June and July 2012 in Luwero District, Uganda. Forty-two primary schools representing 80% of students in the district were randomly selected; 100% agreed to participate. The International Society for the Prevention of Child Abuse and Neglect Child Abuse Screening Tool-Child Institutional; Strengths and Difficulties Questionnaire; and reading, spelling, and math tests were administered. We present descriptive statistics and logistic regression models, accounting for the complex sampling scheme used in the survey. We surveyed 3706 students and 577 school staff members; 93.3% (SE 1.0%) of boys and 94.2% (SE 1.6%) of girls attending primary school reported lifetime experience of physical violence from a school staff member, and >50% reported experience in the past week. Past-week physical violence was associated with increased odds of poor mental health and, for girls, double the odds of poor educational performance (adjusted odds ratio = 1.78, 95% confidence interval = 1.19-2.66). For boys, significant interactions were present. Despite a ban on corporal punishment in Ugandan schools since 1997, the use of violence against students is widespread and associated with poor mental health and educational performance. School violence may be an important but overlooked contributor to disease burden and poor educational performance in low- and middle-income settings.

A Proposed Habitat Management Plan for Yellow-Billed Cuckoos in California

Treesearch

Stephen A. Laymon; Mary D. Halterman

1989-01-01

The California Wildlife-Habitat Relationship (WHR) system was tested for birds breeding in the Valley-Foothill Riparian habitat along California's Sacramento and South Fork Kern rivers. The model performed poorly with 33 pct and 21 pct correct predictions respectively at the two locations. Changes to the model for 60 species on the Sacramento River and 66 species...

Adults with Poor Reading Skills: How Lexical Knowledge Interacts with Scores on Standardized Reading Comprehension Tests

ERIC Educational Resources Information Center

McKoon, Gai; Ratcliff, Roger

2016-01-01

Millions of adults in the United States lack the necessary literacy skills for most living wage jobs. For students from adult learning classes, we used a lexical decision task to measure their knowledge of words and we used a decision-making model (Ratcliff's, 1978, diffusion model) to abstract the mechanisms underlying their performance from…

Clinical value of the VMI supplemental tests: a modified replication study.

PubMed

Avi-Itzhak, Tamara; Obler, Doris Richard

2008-10-01

To carry out a modified replication of the study performed by Kulp and Sortor evaluating the clinical value of the information provided by Beery's visual-motor supplemental tests of Visual Perception (VP) and Motor Coordination (MC) in normally developed children. The objectives were to (a) estimate the correlations among the three tests scores; (b) assess the predictive power of the VP and MC scores in explaining the variance in Visual-Motor Integration (VMI) scores; and (c) examine whether poor performance on the VMI is related to poor performance on VP or MC. METHODS.: A convenience sample of 71 children ages 4 and 5 years (M = 4.62 +/- 0.43) participated in the study. The supplemental tests significantly (F = 9.59; dF = 2; p < or = 0. 001) explained 22% of the variance in VMI performance. Only VP was significantly related to VMI (beta = 0.39; T = 3.49) accounting for the total amount of explained variance. Using the study population norms, 11 children (16% of total sample) did poorly on the VMI; of those 11, 73% did poorly on the VP, and none did poorly on the MC. None of these 11 did poorly on both the VP and MC. Nine percent of total sample who did poorly on the VP performed within the norm on the VMI. Thirteen percent who performed poorly on the MC performed within the norm on the VMI. Using the VMI published norms, 14 children (20% of total sample) who did poorly on the VP performed within the norm on the VMI. Forty-eight percent who did poorly on MC performed within the norm on the VMI. Findings supported Kulp and Sortor's conclusions that each area should be individually evaluated during visual-perceptual assessment of children regardless of performance on the VMI.

How does workaholism affect worker health and performance? The mediating role of coping.

PubMed

Shimazu, Akihito; Schaufeli, Wilmar B; Taris, Toon W

2010-06-01

The underlying mechanisms connecting workaholism on the one hand and ill-health and performance on the other hand have to date hardly been examined empirically. The aim was to study the mediating role of coping (i.e., active coping and emotional discharge) in the relationship between workaholism, ill-health (i.e., psychological distress and physical complaints), and job performance. A theory-based model was tested among 757 employees of a Japanese construction machinery company. Workaholism was positively related to active coping, which was, in its turn, negatively associated with ill-health and positively with job performance. Workaholism was also positively related to emotional discharge, which was positively associated with ill-health. In addition, workaholism was positively and directly related to ill-health, whereas it was not significantly related to job performance. Workaholism is associated with both active coping and emotional discharge. Active coping leads to better health and performance, whereas emotional discharge leads to poor health. In addition, workaholism coincides with poor health. Since the costs for workaholics themselves (in terms of ill-health) are high, workaholism has on average adverse effects on health and performance.

Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran.

PubMed

Azadi, Sama; Karimi-Jashni, Ayoub

2016-02-01

Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verified to predict mean Seasonal Municipal Solid Waste Generation (SMSWG) rate. The accuracy of the proposed models is illustrated through a case study of 20 cities located in Fars Province, Iran. Four performance measures, MAE, MAPE, RMSE and R were used to evaluate the performance of these models. The MLR, as a conventional model, showed poor prediction performance. On the other hand, the results indicated that the ANN model, as a non-linear model, has a higher predictive accuracy when it comes to prediction of the mean SMSWG rate. As a result, in order to develop a more cost-effective strategy for waste management in the future, the ANN model could be used to predict the mean SMSWG rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

A critical evaluation of various turbulence models as applied to internal fluid flows

NASA Technical Reports Server (NTRS)

Nallasamy, M.

1985-01-01

Models employed in the computation of turbulent flows are described and their application to internal flows is evaluated by examining the predictions of various turbulence models in selected flow configurations. The main conclusions are: (1) the k-epsilon model is used in a majority of all the two-dimensional flow calculations reported in the literature; (2) modified forms of the k-epsilon model improve the performance for flows with streamline curvature and heat transfer; (3) for flows with swirl, the k-epsilon model performs rather poorly; the algebraic stress model performs better in this case; and (4) for flows with regions of secondary flow (noncircular duct flows), the algebraic stress model performs fairly well for fully developed flow, for developing flow, the algebraic stress model performance is not good; a Reynolds stress model should be used. False diffusion and inlet boundary conditions are discussed. Countergradient transport and its implications in turbulence modeling is mentioned. Two examples of recirculating flow predictions obtained using PHOENICS code are discussed. The vortex method, large eddy simulation (modeling of subgrid scale Reynolds stresses), and direct simulation, are considered. Some recommendations for improving the model performance are made. The need for detailed experimental data in flows with strong curvature is emphasized.

Albendazole nanocrystals with improved pharmacokinetic performance in mice.

PubMed

Paredes, Alejandro J; Bruni, Sergio Sánchez; Allemandi, Daniel; Lanusse, Carlos; Palma, Santiago D

2018-02-01

Albendazole (ABZ) is a broad-spectrum antiparasitic agent with poor aqueous solubility, which leads to poor/erratic bioavailability and therapeutic failures. Here, we aimed to produce a novel formulation of ABZ nanocrystals (ABZNC) and assess its pharmacokinetic performance in mice. Results/methodology: ABZNC were prepared by high-pressure homogenization and spray-drying processes. Redispersion capacity and solid yield were measured in order to obtain an optimized product. The final particle size was 415.69±7.40 nm and the solid yield was 72.32%. The pharmacokinetic parameters obtained in a mice model for ABZNC were enhanced (p < 0.05) with respect to the control formulation. ABZNC with improved pharmacokinetic behavior were produced by a simple, inexpensive and potentially scalable methodology.

Towards reliable ET estimates in the semi-arid Júcar region in Spain.

NASA Astrophysics Data System (ADS)

Brenner, Johannes; Zink, Matthias; Schrön, Martin; Thober, Stephan; Rakovec, Oldrich; Cuntz, Matthias; Merz, Ralf; Samaniego, Luis

2017-04-01

Current research indicated the potential for improving evapotranspiration (ET) estimates in state-of-the-art hydrologic models such as the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). Most models exhibit deficiencies to estimate the ET flux in semi-arid regions. Possible reasons for poor performance may be related to the low resolution of the forcings, the estimation of the PET, which is in most cases based on temperature only, the joint estimation of the transpiration and evaporation through the Feddes equation, poor process parameterizations, among others. In this study, we aim at sequential hypothesis-based experiments to uncover the main reasons of these deficiencies at the Júcar basin in Spain. We plan the following experiments: 1) Use the high resolution meteorological forcing (P and T) provided by local authorities to estimate its effects on ET and streamflow. 2) Use local ET measurements at seven eddy covariance stations to estimate evaporation related parameters. 3) Test the influence of the PET formulations (Hargreaves-Samani, Priestley-Taylor, Penman-Montheith). 4) Estimate evaporation and transpiration separately based on equations proposed by Bohn and Vivoni (2016) 5) Incorporate local soil moisture measurements to re-estimate ET and soil moisture related parameters. We set-up mHM for seven eddy-covariance sites at the local scale (100 × 100 m2). This resolution was chosen because it is representative for the footprint of the latent heat estimation at the eddy-covariance station. In the second experiment, for example, a parameter set is to be found as a compromised solution between ET measured at local stations and the streamflow observations at eight sub-basins of the Júcar river. Preliminary results indicate that higher model performance regarding streamflow can be achieved using local high-resolution meteorology. ET performance is, however, still deficient. On the contrary, using ET site calibrations alone increase performance in ET but yields in poor performance in streamflow. Results suggest the need of multi-variable, simultaneous calibration schemes to reliable estimate ET and streamflow in the Júcar basin. Penman-Montheith appears to be the best performing PET formulation. Experiments 4 and 5 should reveal the benefits of separating evaporation from bare soil and transpiration in semi-arid regions using mHM. Further research in this direction is foreseen by incorporating neutron counts from Cosmic Ray Neutron Sensing technology in the calibration/validation procedure of mHM.

[Excessive Daytime Sleepiness, Poor Quality Sleep, and Low Academic Performance in Medical Students].

PubMed

Machado-Duque, Manuel Enrique; Echeverri Chabur, Jorge Enrique; Machado-Alba, Jorge Enrique

2015-01-01

Quality of sleep and excessive daytime sleepiness (EDS) affect cognitive ability and performance of medical students. This study attempts to determine the prevalence of EDS, sleep quality, and assess their association with poor academic performance in this population. A descriptive, observational study was conducted on a random sample of 217 medical students from the Universidad Tecnológica de Pereira, who completed the Pittsburgh Sleep Quality Index (PSQI) questionnaire and the Epworth sleepiness scale. Sociodemographic, clinic and academic variables were also measured. Multivariate analyses for poor academic performance were performed. The included students had a mean age of 21.7±3.3 years, of whom 59.4% were men. Almost half (49.8%) had EDS criteria, and 79.3% were poor sleepers (PSQI ≥ 5), while 43.3% had poor academic performance during the last semester. The bivariate analysis showed that having used tobacco or alcohol until intoxicated, fairly bad subjective sleep quality, sleep efficiency < 65%, and being a poor sleeper were associated with increased risk of low performance. Sleep efficiency < 65% was statistically associated with poor academic performance (P=.024; OR = 4.23; 95% CI, 1.12-15.42) in the multivariate analysis. A poor sleep quality determined by low efficiency was related to poor academic achievement at the end of semester in medical students. Copyright © 2015 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Modeling of the jack rabbit series of experiments with a temperature based reactive burn model

NASA Astrophysics Data System (ADS)

Desbiens, Nicolas

2017-01-01

The Jack Rabbit experiments, performed by Lawrence Livermore National Laboratory, focus on detonation wave corner turning and shock desensitization. Indeed, while important for safety or charge design, the behaviour of explosives in these regimes is poorly understood. In this paper, our temperature based reactive burn model is calibrated for LX-17 and compared to the Jack Rabbit data. It is shown that our model can reproduce the corner turning and shock desensitization behaviour of four out of the five experiments.

[Nursing Workforce Characteristics and Control of Diabetes Mellitus in Primary Care: a Multilevel Analysis].

PubMed

Parro Moreno, Ana; Santiago Pérez, M Isolina; Abraira Santos, Victor; Aréjula Torres, José Luis Aréjula Torres; Díaz Holgado, Antonio; Gandarillas Grande, Ana; Morales Asencio, José Miguel; Serrano Gallardo, Pilar

2016-03-04

Nurse activity is determined by the characteristics of nursing staff. The objective was to determine the impact of Primary Health Care (PHC) nursing workforce characteristics on the control of Diabetes Mellitus (DM) in adults. Cross-sectional analytical study. Administrative and clinical registries and questionnaire PES-Nursing Work Index from PHC nurses. Participants 44.214 diabetic patients in two health zones within the Community of Madrid, North-West Zone (NWZ) with higher socioeconomic situation and South-West Zone (SWZ) with lower socioeconomic situation, and their 507 reference nurses. Analyses were performed to multivariate multilevel logistic regression models. Poor DM control (figures equal or higher than 7% HbA1c). The prevalence of poor DM control was 40.1% [CI95%: 38.2-42.1]. There was a risk of 25% more of poor control if the patient changed centre and of 27% if changed of doctor-nurse pair. In the multilevel multivariate regression models: in SWZ increasing the ratio of patients over 65 years per nurse increased the poor control (OR=1.00008 [CI95%:1.00006-1.001]); and higher proportion of patients whose Hb1Ac was not measured at the centre contributed to poor DM control (OR=5.1 [CI95%:1.6-15.6]). In two models for health zone, the economic immigration condition increased poor control, in SWZ (OR=1.3 [CI95%:1.03-1.7]); and in NWZ (OR=1.29 [CI95%:1.03-1.6]). Higher 65 years old patients ratio per nurse, economic immigration condition and a higher proportion of patients whose Hb1Ac was not measured contribute to worse DM control.

Heat transfer enhancement in a lithium-ion cell through improved material-level thermal transport

NASA Astrophysics Data System (ADS)

Vishwakarma, Vivek; Waghela, Chirag; Wei, Zi; Prasher, Ravi; Nagpure, Shrikant C.; Li, Jianlin; Liu, Fuqiang; Daniel, Claus; Jain, Ankur

2015-12-01

While Li-ion cells offer excellent electrochemical performance for several applications including electric vehicles, they also exhibit poor thermal transport characteristics, resulting in reduced performance, overheating and thermal runaway. Inadequate heat removal from Li-ion cells originates from poor thermal conductivity within the cell. This paper identifies the rate-limiting material-level process that dominates overall thermal conduction in a Li-ion cell. Results indicate that thermal characteristics of a Li-ion cell are largely dominated by heat transfer across the cathode-separator interface rather than heat transfer through the materials themselves. This interfacial thermal resistance contributes around 88% of total thermal resistance in the cell. Measured value of interfacial resistance is close to that obtained from theoretical models that account for weak adhesion and large acoustic mismatch between cathode and separator. Further, to address this problem, an amine-based chemical bridging of the interface is carried out. This is shown to result in in four-times lower interfacial thermal resistance without deterioration in electrochemical performance, thereby increasing effective thermal conductivity by three-fold. This improvement is expected to reduce peak temperature rise during operation by 60%. By identifying and addressing the material-level root cause of poor thermal transport in Li-ion cells, this work may contributes towards improved thermal performance of Li-ion cells.

A multi-step pathway connecting short sleep duration to daytime somnolence, reduced attention, and poor academic performance: an exploratory cross-sectional study in teenagers.

PubMed

Perez-Lloret, Santiago; Videla, Alejandro J; Richaudeau, Alba; Vigo, Daniel; Rossi, Malco; Cardinali, Daniel P; Perez-Chada, Daniel

2013-05-15

A multi-step causality pathway connecting short sleep duration to daytime somnolence and sleepiness leading to reduced attention and poor academic performance as the final result can be envisaged. However this hypothesis has never been explored. To explore consecutive correlations between sleep duration, daytime somnolence, attention levels, and academic performance in a sample of school-aged teenagers. We carried out a survey assessing sleep duration and daytime somnolence using the Pediatric Daytime Sleepiness Scale (PDSS). Sleep duration variables included week-days' total sleep time, usual bedtimes, and absolute weekday to-weekend sleep time difference. Attention was assessed by d2 test and by the coding subtest from the WISC-IV scale. Academic performance was obtained from literature and math grades. Structural equation modeling was used to assess the independent relationships between these variables, while controlling for confounding effects of other variables, in one single model. Standardized regression weights (SWR) for relationships between these variables are reported. Study sample included 1,194 teenagers (mean age: 15 years; range: 13-17 y). Sleep duration was inversely associated with daytime somnolence (SWR = -0.36, p < 0.01) while sleepiness was negatively associated with attention (SWR = -0.13, p < 0.01). Attention scores correlated positively with academic results (SWR = 0.18, p < 0.01). Daytime somnolence correlated negatively with academic achievements (SWR = -0.16, p < 0.01). The model offered an acceptable fit according to usual measures (RMSEA = 0.0548, CFI = 0.874, NFI = 0.838). A Sobel test confirmed that short sleep duration influenced attention through daytime somnolence (p < 0.02), which in turn influenced academic achievements through reduced attention (p < 0.002). Poor academic achievements correlated with reduced attention, which in turn was related to daytime somnolence. Somnolence correlated with short sleep duration.

Performance of time-varying predictors in multilevel models under an assumption of fixed or random effects.

PubMed

Baird, Rachel; Maxwell, Scott E

2016-06-01

Time-varying predictors in multilevel models are a useful tool for longitudinal research, whether they are the research variable of interest or they are controlling for variance to allow greater power for other variables. However, standard recommendations to fix the effect of time-varying predictors may make an assumption that is unlikely to hold in reality and may influence results. A simulation study illustrates that treating the time-varying predictor as fixed may allow analyses to converge, but the analyses have poor coverage of the true fixed effect when the time-varying predictor has a random effect in reality. A second simulation study shows that treating the time-varying predictor as random may have poor convergence, except when allowing negative variance estimates. Although negative variance estimates are uninterpretable, results of the simulation show that estimates of the fixed effect of the time-varying predictor are as accurate for these cases as for cases with positive variance estimates, and that treating the time-varying predictor as random and allowing negative variance estimates performs well whether the time-varying predictor is fixed or random in reality. Because of the difficulty of interpreting negative variance estimates, 2 procedures are suggested for selection between fixed-effect and random-effect models: comparing between fixed-effect and constrained random-effect models with a likelihood ratio test or fitting a fixed-effect model when an unconstrained random-effect model produces negative variance estimates. The performance of these 2 procedures is compared. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Cubature/ Unscented/ Sigma Point Kalman Filtering with Angular Measurement Models

DTIC Science & Technology

2015-07-06

Cubature/ Unscented/ Sigma Point Kalman Filtering with Angular Measurement Models David Frederic Crouse Naval Research Laboratory 4555 Overlook Ave...measurement and process non- linearities, such as the cubature Kalman filter , can perform ex- tremely poorly in many applications involving angular... Kalman filtering is a realization of the best linear unbiased estimator (BLUE) that evaluates certain integrals for expected values using different forms

A Test of the California Wildlife-Habitat Relationship System for Breeding Birds in Valley-Foothill Riparian Habitat

Treesearch

Stephen A. Laymon

1989-01-01

The California Wildlife-Habitat Relationship (WHR) system was tested for birds breeding in the Valley-Foothill Riparian habitat along California's Sacramento and South Fork Kern rivers. The model performed poorly with 33 pct and 21 pct correct predictions respectively at the two locations. Changes to the model for 60 species on the Sacramento River and 66 species...

Real-time validation of the Dst Predictor model

USGS Publications Warehouse

McCollough, James P.; Young, Shawn L.; Rigler, E. Joshua; Simpson, Hal A.

2015-01-01

The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor.  Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and specification and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efficiencies of-64.6and-43.1, respectively).

The PMS project: Poor man's supercomputer

NASA Astrophysics Data System (ADS)

Csikor, F.; Fodor, Z.; Hegedüs, P.; Horváth, V. K.; Katz, S. D.; Piróth, A.

2001-02-01

We briefly describe the Poor Man's Supercomputer (PMS) project carried out at Eötvös University, Budapest. The goal was to construct a cost effective, scalable, fast parallel computer to perform numerical calculations of physical problems that can be implemented on a lattice with nearest neighbour interactions. To this end we developed the PMS architecture using PC components and designed a special, low cost communication hardware and the driver software for Linux OS. Our first implementation of PMS includes 32 nodes (PMS1). The performance of PMS1 was tested by Lattice Gauge Theory simulations. Using pure SU(3) gauge theory or the bosonic part of the minimal supersymmetric extention of the standard model (MSSM) on PMS1 we obtained 3 / Mflops and 0.60 / Mflops price-to-sustained performance ratio for double and single precision operations, respectively. The design of the special hardware and the communication driver are freely available upon request for non-profit organizations.

Elucidating Poor Decision-Making in a Rat Gambling Task

PubMed Central

Seriès, Peggy; Marchand, Alain R.; Dellu-Hagedorn, Françoise

2013-01-01

Although poor decision-making is a hallmark of psychiatric conditions such as attention deficit/hyperactivity disorder, pathological gambling or substance abuse, a fraction of healthy individuals exhibit similar poor decision-making performances in everyday life and specific laboratory tasks such as the Iowa Gambling Task. These particular individuals may provide information on risk factors or common endophenotypes of these mental disorders. In a rodent version of the Iowa gambling task – the Rat Gambling Task (RGT), we identified a population of poor decision makers, and assessed how these rats scored for several behavioral traits relevant to executive disorders: risk taking, reward seeking, behavioral inflexibility, and several aspects of impulsivity. First, we found that poor decision-making could not be well predicted by single behavioral and cognitive characteristics when considered separately. By contrast, a combination of independent traits in the same individual, namely risk taking, reward seeking, behavioral inflexibility, as well as motor impulsivity, was highly predictive of poor decision-making. Second, using a reinforcement-learning model of the RGT, we confirmed that only the combination of extreme scores on these traits could induce maladaptive decision-making. Third, the model suggested that a combination of these behavioral traits results in an inaccurate representation of rewards and penalties and inefficient learning of the environment. Poor decision-making appears as a consequence of the over-valuation of high-reward-high-risk options in the task. Such a specific psychological profile could greatly impair clinically healthy individuals in decision-making tasks and may predispose to mental disorders with similar symptoms. PMID:24339988

Elucidating poor decision-making in a rat gambling task.

PubMed

Rivalan, Marion; Valton, Vincent; Seriès, Peggy; Marchand, Alain R; Dellu-Hagedorn, Françoise

2013-01-01

Although poor decision-making is a hallmark of psychiatric conditions such as attention deficit/hyperactivity disorder, pathological gambling or substance abuse, a fraction of healthy individuals exhibit similar poor decision-making performances in everyday life and specific laboratory tasks such as the Iowa Gambling Task. These particular individuals may provide information on risk factors or common endophenotypes of these mental disorders. In a rodent version of the Iowa gambling task--the Rat Gambling Task (RGT), we identified a population of poor decision makers, and assessed how these rats scored for several behavioral traits relevant to executive disorders: risk taking, reward seeking, behavioral inflexibility, and several aspects of impulsivity. First, we found that poor decision-making could not be well predicted by single behavioral and cognitive characteristics when considered separately. By contrast, a combination of independent traits in the same individual, namely risk taking, reward seeking, behavioral inflexibility, as well as motor impulsivity, was highly predictive of poor decision-making. Second, using a reinforcement-learning model of the RGT, we confirmed that only the combination of extreme scores on these traits could induce maladaptive decision-making. Third, the model suggested that a combination of these behavioral traits results in an inaccurate representation of rewards and penalties and inefficient learning of the environment. Poor decision-making appears as a consequence of the over-valuation of high-reward-high-risk options in the task. Such a specific psychological profile could greatly impair clinically healthy individuals in decision-making tasks and may predispose to mental disorders with similar symptoms.

Field Validation of Habitat Suitability Models for Vulnerable Marine Ecosystems in the South Pacific Ocean: Implications for the use of Broad-scale Models in Fisheries Management

NASA Astrophysics Data System (ADS)

Anderson, O. F.; Guinotte, J. M.; Clark, M. R.; Rowden, A. A.; Mormede, S.; Davies, A. J.; Bowden, D.

2016-02-01

Spatial management of vulnerable marine ecosystems requires accurate knowledge of their distribution. Predictive habitat suitability modelling, using species presence data and a suite of environmental predictor variables, has emerged as a useful tool for inferring distributions outside of known areas. However, validation of model predictions is typically performed with non-independent data. In this study, we describe the results of habitat suitability models constructed for four deep-sea reef-forming coral species across a large region of the South Pacific Ocean using MaxEnt and Boosted Regression Tree modelling approaches. In order to validate model predictions we conducted a photographic survey on a set of seamounts in an un-sampled area east of New Zealand. The likelihood of habitat suitable for reef forming corals on these seamounts was predicted to be variable, but very high in some regions, particularly where levels of aragonite saturation, dissolved oxygen, and particulate organic carbon were optimal. However, the observed frequency of coral occurrence in analyses of survey photographic data was much lower than expected, and patterns of observed versus predicted coral distribution were not highly correlated. The poor performance of these broad-scale models is attributed to lack of recorded species absences to inform the models, low precision of global bathymetry models, and lack of data on the geomorphology and substrate of the seamounts at scales appropriate to the modelled taxa. This demonstrates the need to use caution when interpreting and applying broad-scale, presence-only model results for fisheries management and conservation planning in data poor areas of the deep sea. Future improvements in the predictive performance of broad-scale models will rely on the continued advancement in modelling of environmental predictor variables, refinements in modelling approaches to deal with missing or biased inputs, and incorporation of true absence data.

32 CFR 776.77 - Related investigations and actions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... omissions by covered attorneys may constitute professional misconduct, criminal misconduct, poor performance... to appropriate civil authority. (c) Poor performance of duty is properly addressed by the covered USG... criminal conduct or poor performance of duty involving covered attorneys. When, however, investigations...

Quality Lies in the Eyes of the Beholder: A Mismatch between Student Evaluation and Peer Observation of Teaching

ERIC Educational Resources Information Center

Hassan, Salochana; Wium, Wouter

2014-01-01

The study described in this article was prompted by the poor performance of students in an "at risk subject" in a science faculty at a university in South Africa. Teacher performance could contribute to poor performance among students, therefore the performance of one of the science teachers whose students were performing poorly was…

Sleep quantity, quality, and insomnia symptoms of medical students during clinical years. Relationship with stress and academic performance.

PubMed

Alsaggaf, Mohammed A; Wali, Siraj O; Merdad, Roah A; Merdad, Leena A

2016-02-01

To determine sleep habits and sleep quality in medical students during their clinical years using validated measures; and to investigate associations with academic performance and psychological stress. In this cross-sectional study, medical students (n=320) were randomly selected from a list of all enrolled clinical-year students in a Saudi medical school from 2011-2012. Students filled a questionnaire including demographic and lifestyle factors, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Perceived Stress Scale. Students acquired on average, 5.8 hours of sleep each night, with an average bedtime at 01:53. Approximately 8% reported acquiring sleep during the day, and not during nighttime. Poor sleep quality was present in 30%, excessive daytime sleepiness (EDS) in 40%, and insomnia symptoms in 33% of students. Multivariable regression models revealed significant associations between stress, poor sleep quality, and EDS. Poorer academic performance and stress were associated with symptoms of insomnia. Sleep deprivation, poor sleep quality, and EDS are common among clinical years medical students. High levels of stress and the pressure of maintaining grade point averages may be influencing their quality of sleep.

Validation of a new mortality risk prediction model for people 65 years and older in northwest Russia: The Crystal risk score.

PubMed

Turusheva, Anna; Frolova, Elena; Bert, Vaes; Hegendoerfer, Eralda; Degryse, Jean-Marie

2017-07-01

Prediction models help to make decisions about further management in clinical practice. This study aims to develop a mortality risk score based on previously identified risk predictors and to perform internal and external validations. In a population-based prospective cohort study of 611 community-dwelling individuals aged 65+ in St. Petersburg (Russia), all-cause mortality risks over 2.5 years follow-up were determined based on the results obtained from anthropometry, medical history, physical performance tests, spirometry and laboratory tests. C-statistic, risk reclassification analysis, integrated discrimination improvement analysis, decision curves analysis, internal validation and external validation were performed. Older adults were at higher risk for mortality [HR (95%CI)=4.54 (3.73-5.52)] when two or more of the following components were present: poor physical performance, low muscle mass, poor lung function, and anemia. If anemia was combined with high C-reactive protein (CRP) and high B-type natriuretic peptide (BNP) was added the HR (95%CI) was slightly higher (5.81 (4.73-7.14)) even after adjusting for age, sex and comorbidities. Our models were validated in an external population of adults 80+. The extended model had a better predictive capacity for cardiovascular mortality [HR (95%CI)=5.05 (2.23-11.44)] compared to the baseline model [HR (95%CI)=2.17 (1.18-4.00)] in the external population. We developed and validated a new risk prediction score that may be used to identify older adults at higher risk for mortality in Russia. Additional studies need to determine which targeted interventions improve the outcomes of these at-risk individuals. Copyright © 2017 Elsevier B.V. All rights reserved.

Using Brain Imaging to Extract the Structure of Complex Events at the Rational Time Band

PubMed Central

Anderson, John R.; Qin, Yulin

2017-01-01

A functional magnetic resonance imaging (fMRI) study was performed in which participants performed a complex series of mental calculations that spanned about 2 min. An Adaptive Control of Thought—Rational (ACT-R) model [Anderson, J. R. How can the human mind occur in the physical universe? New York: Oxford University Press, 2007] was developed that successfully fit the distribution of latencies. This model generated predictions for the fMRI signal in six brain regions that have been associated with modules in the ACT-R theory. The model’s predictions were confirmed for a fusiform region that reflects the visual module, for a prefrontal region that reflects the retrieval module, and for an anterior cingulate region that reflects the goal module. In addition, the only significant deviations to the motor region that reflects the manual module were anticipatory hand movements. In contrast, the predictions were relatively poor for a parietal region that reflects an imaginal module and for a caudate region that reflects the procedural module. Possible explanations of these poor fits are discussed. In addition, exploratory analyses were performed to find regions that might correspond to the predictions of the modules. PMID:18345979

Effect of visual media use on school performance: a prospective study.

PubMed

Sharif, Iman; Wills, Thomas A; Sargent, James D

2010-01-01

To identify mechanisms for the impact of visual media use on adolescents' school performance. We conducted a 24-month, four-wave longitudinal telephone study of a national sample of 6,486 youth aged 10 to 14 years. Exposure measures: latent construct for screen exposure time (weekday time spent viewing television/playing videogames, presence of television in bedroom) and variables for movie content (proportion of PG-13 and R movies viewed). self- and parent reports of grades in school. Effects of media exposures on change in school performance between baseline and 24 months were assessed using structural equation modeling. Information about hypothesized mediators (substance use, sensation seeking, and school problem behavior) was obtained at baseline and at the 16-month follow-up. Adjusted for baseline school performance, baseline levels of mediators, and a range of covariates, both screen exposure time and media content had adverse effects on change in school performance. Screen exposure had an indirect effect on poor school performance through increased sensation seeking. Viewing more PG-13 and R-rated movies had indirect effects on poor school performance mediated through increases in substance use and sensation seeking. R-rated viewing also had an indirect effect on poor school performance through increased school behavior problems. The effect sizes of exposure time and content on the intermediate variables and ultimately on school performance were similar to those for previously recognized determinants of these mediators, including household income, parenting style, and adolescents' self-control. These aspects of visual media use adversely affect school performance by increasing sensation seeking, substance use, and school problem behavior. Copyright 2010 Society for Adolescent Medicine. Published by Elsevier Inc. All rights reserved.

Effect of Visual Media Use on School Performance: A Prospective Study1

PubMed Central

Sharif, Iman; Wills, Thomas A.; Sargent, James D.

2009-01-01

Purpose To identify mechanisms for the impact of visual media use on adolescents' school performance. Methods We conducted a 24-month, four-wave longitudinal telephone study of a national sample of 6,486 youth aged 10-14 years. Exposure Measures: Latent construct for screen exposure time (weekday time spent viewing television/playing videogames, presence of television in bedroom) and variables for movie content (proportion of PG13 and R movies viewed). Outcome Measure: Self and parent reports of grades in school. Effects of media exposures on change in school performance between baseline and 24 months were assessed using structural equation modeling. Information about hypothesized mediators (substance use, sensation-seeking, and school problem behavior) was obtained at baseline and at the16-month follow-up. Results Adjusted for baseline school performance, baseline levels of mediators, and a range of covariates, both screen exposure time and media content had adverse effects on change in school performance. Screen exposure had an indirect effect on poor school performance through increased sensation-seeking. Viewing more PG-13 and R-rated movies had indirect effects on poor school performance mediated through increases in substance use and sensation-seeking. R-rated viewing also had an indirect effect on poor school performance through increased school behavior problems. The effect sizes of exposure time and content on the intermediate variables and ultimately on school performance were similar to those for previously recognized determinants of these mediators – including household income, parenting style, and adolescents' self-control. Conclusions These aspects of visual media use adversely affect school performance by increasing sensation-seeking, substance use and school problem behavior. PMID:20123258

Preoperative predictive model for acute kidney injury after elective cardiac surgery: a prospective multicentre cohort study.

PubMed

Callejas, Raquel; Panadero, Alfredo; Vives, Marc; Duque, Paula; Echarri, Gemma; Monedero, Pablo

2018-05-11

Predictive models of CS-AKI include emergency surgery and patients with haemodynamic instability. Our objective was to evaluate the performance of validated predictive models (Thakar and Demirjian) in elective cardiac surgery and to propose a better score in the case of poor performance. A prospective, multicentre, observational study was designed. Data were collected from 942 patients undergoing cardiac surgery, after excluding emergency surgery and patients with an intraaortic balloon pump. The main outcome measure was CS-AKI defined by the composite of requiring dialysis or doubling baseline creatinine values. Both models showed poor discrimination in elective surgery (Thakar's model, AUROC = 0.57, 95% CI = 0.50-0.64 and Demirjian's model, AUROC= 0.64, 95% CI = 0.58-0.71). We generated a new model whose significant independent predictors were: anaemia, age, hypertension, obesity, congestive heart failure, previous cardiac surgery and type of surgery. It classifies patients with scores 0-3 as low risk (< 5%), scores 4-7 as medium risk (up to 15%) and scores > 8 as high risk (>30%) of developing CS-AKI with a statistically significant correlation (p <0.001). Our model reflects acceptable discriminatory ability (AUC = 0.72, 95% CI = 0.66-0.78) which is significantly better than Thakar and Demirjian's models (p<0.01). We developed a new simple predictive model of CS-AKI in elective surgery based on available preoperative information. Our new model is easy to calculate and can be an effective tool for communicating risk to patients and guiding decision-making in the perioperative period. The study requires external validation.

5 CFR 362.207 - Withdrawal and readmission.

Code of Federal Regulations, 2010 CFR

2010-01-01

... withdraws from the Program for reasons that are not related to misconduct, poor performance, or suitability... misconduct, poor performance, or suitability, as determined by the agency, he/she will not be readmitted to... are not related to misconduct, poor performance, or suitability, he/she may petition the employing...

Enabling Process Improvement and Control in Higher Education Management

ERIC Educational Resources Information Center

Bell, Gary; Warwick, Jon; Kennedy, Mike

2009-01-01

The emergence of "managerialism" in the governance and direction of UK higher education (HE) institutions has been led by government demands for greater accountability in the quality and cost of universities. There is emerging anecdotal evidence indicating that the estimation performance of HE spreadsheets and regression models are poor.…

Long-Term Memory for a Common Object.

ERIC Educational Resources Information Center

Nickerson, Raymond S.; Adams, Marilyn Jager

1979-01-01

Five experiments investigated how completely and accurately adults remember the visual details of the common United States penny. Subjects had to draw a penny from unaided recall and select the correct representation of a penny. Performance was poor on all tasks. Implications for long-term memory models were discussed. (Author/RD)

A Model of Differential Amygdala Activation in Psychopathy

ERIC Educational Resources Information Center

Moul, Caroline; Killcross, Simon; Dadds, Mark R.

2012-01-01

This article introduces a novel hypothesis regarding amygdala function in psychopathy. The first part of this article introduces the concept of psychopathy and describes the main cognitive and affective impairments demonstrated by this population; that is, a deficit in fear-recognition, lower conditioned fear responses and poor performance in…

Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks

PubMed Central

Khan, Komal Saifullah; Tariq, Muhammad

2014-01-01

Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models. PMID:25421739

A rational model for maximizing the effects of therapeutic relationship regulation in personality disorders with poor metacognition and over-regulation of affects.

PubMed

Dimaggio, Giancarlo; Carcione, Antonino; Salvatore, Giampaolo; Semerari, Antonio; Nicolò, Giuseppe

2010-11-01

The therapeutic relationship plays a key role in personality disorder (PD) psychotherapy. Some aspects of therapeutic relationship regulation appear important for treatment of PD clients, including those with constricted relational schemas, poor metacognition, and over-regulation of affects described here. AIM.: To propose a rational model for how and when to work on the therapeutic relationship by treating the underlying personality pathology. Formalize a step-by-step procedure for performing operations such as validation of clients' experiences, creating a sense of sharedness, assessing the quality of the therapeutic relationship in order to prevent and repair ruptures in the alliance, self-disclosing by the therapist, and metacommunication on the basis of clients' responses to treatment. We discuss the implications of this model for further research into the PD therapy process. 2010 The British Psychological Society.

GPS/GLONASS Combined Precise Point Positioning with Receiver Clock Modeling

PubMed Central

Wang, Fuhong; Chen, Xinghan; Guo, Fei

2015-01-01

Research has demonstrated that receiver clock modeling can reduce the correlation coefficients among the parameters of receiver clock bias, station height and zenith tropospheric delay. This paper introduces the receiver clock modeling to GPS/GLONASS combined precise point positioning (PPP), aiming to better separate the receiver clock bias and station coordinates and therefore improve positioning accuracy. Firstly, the basic mathematic models including the GPS/GLONASS observation equations, stochastic model, and receiver clock model are briefly introduced. Then datasets from several IGS stations equipped with high-stability atomic clocks are used for kinematic PPP tests. To investigate the performance of PPP, including the positioning accuracy and convergence time, a week of (1–7 January 2014) GPS/GLONASS data retrieved from these IGS stations are processed with different schemes. The results indicate that the positioning accuracy as well as convergence time can benefit from the receiver clock modeling. This is particularly pronounced for the vertical component. Statistic RMSs show that the average improvement of three-dimensional positioning accuracy reaches up to 30%–40%. Sometimes, it even reaches over 60% for specific stations. Compared to the GPS-only PPP, solutions of the GPS/GLONASS combined PPP are much better no matter if the receiver clock offsets are modeled or not, indicating that the positioning accuracy and reliability are significantly improved with the additional GLONASS satellites in the case of insufficient number of GPS satellites or poor geometry conditions. In addition to the receiver clock modeling, the impacts of different inter-system timing bias (ISB) models are investigated. For the case of a sufficient number of satellites with fairly good geometry, the PPP performances are not seriously affected by the ISB model due to the low correlation between the ISB and the other parameters. However, the refinement of ISB model weakens the correlation between coordinates and ISB estimates and finally enhance the PPP performance in the case of poor observation conditions. PMID:26134106

The association of students requiring remediation in the internal medicine clerkship with poor performance during internship.

PubMed

Hemann, Brian A; Durning, Steven J; Kelly, William F; Dong, Ting; Pangaro, Louis N; Hemmer, Paul A

2015-04-01

To determine whether the Uniformed Services University (USU) system of workplace performance assessment for students in the internal medicine clerkship at the USU continues to be a sensitive predictor of subsequent poor performance during internship, when compared with assessments in other USU third year clerkships. Utilizing Program Director survey results from 2007 through 2011 and U.S. Medical Licensing Examination (USMLE) Step 3 examination results as the outcomes of interest, we compared performance during internship for students who had less than passing performance in the internal medicine clerkship and required remediation, against students whose performance in the internal medicine clerkship was successful. We further analyzed internship ratings for students who received less than passing grades during the same time period on other third year clerkships such as general surgery, pediatrics, obstetrics and gynecology, family medicine, and psychiatry to evaluate whether poor performance on other individual clerkships were associated with future poor performance at the internship level. Results for this recent cohort of graduates were compared with previously published findings. The overall survey response rate for this 5 year cohort was 81% (689/853). Students who received a less than passing grade in the internal medicine clerkship and required further remediation were 4.5 times more likely to be given poor ratings in the domain of medical expertise and 18.7 times more likely to demonstrate poor professionalism during internship. Further, students requiring internal medicine remediation were 8.5 times more likely to fail USMLE Step 3. No other individual clerkship showed any statistically significant associations with performance at the intern level. On the other hand, 40% of students who successfully remediated and did graduate were not identified during internship as having poor performance. Unsuccessful clinical performance which requires remediation in the third year internal medicine clerkship at Uniformed Services University of the Health Sciences continues to be strongly associated with poor performance at the internship level. No significant associations existed between any of the other clerkships and poor performance during internship and Step 3 failure. The strength of this association with the internal medicine clerkship is most likely because of an increased level of sensitivity in detecting poor performance. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Detecting Human Hydrologic Alteration from Diversion Hydropower Requires Universal Flow Prediction Tools: A Proposed Framework for Flow Prediction in Poorly-gauged, Regulated Rivers

NASA Astrophysics Data System (ADS)

Kibler, K. M.; Alipour, M.

2016-12-01

Achieving the universal energy access Sustainable Development Goal will require great investment in renewable energy infrastructure in the developing world. Much growth in the renewable sector will come from new hydropower projects, including small and diversion hydropower in remote and mountainous regions. Yet, human impacts to hydrological systems from diversion hydropower are poorly described. Diversion hydropower is often implemented in ungauged rivers, thus detection of impact requires flow analysis tools suited to prediction in poorly-gauged and human-altered catchments. We conduct a comprehensive analysis of hydrologic alteration in 32 rivers developed with diversion hydropower in southwestern China. As flow data are sparse, we devise an approach for estimating streamflow during pre- and post-development periods, drawing upon a decade of research into prediction in ungauged basins. We apply a rainfall-runoff model, parameterized and forced exclusively with global-scale data, in hydrologically-similar gauged and ungauged catchments. Uncertain "soft" data are incorporated through fuzzy numbers and confidence-based weighting, and a multi-criteria objective function is applied to evaluate model performance. Testing indicates that the proposed framework returns superior performance (NSE = 0.77) as compared to models parameterized by rote calibration (NSE = 0.62). Confident that the models are providing `the right answer for the right reasons', our analysis of hydrologic alteration based on simulated flows indicates statistically significant hydrologic effects of diversion hydropower across many rivers. Mean annual flows, 7-day minimum and 7-day maximum flows decreased. Frequency and duration of flow exceeding Q25 decreased while duration of flows sustained below the Q75 increased substantially. Hydrograph rise and fall rates and flow constancy increased. The proposed methodology may be applied to improve diversion hydropower design in data-limited regions.

Improving Flood Prediction By the Assimilation of Satellite Soil Moisture in Poorly Monitored Catchments.

NASA Astrophysics Data System (ADS)

Alvarez-Garreton, C. D.; Ryu, D.; Western, A. W.; Crow, W. T.; Su, C. H.; Robertson, D. E.

2014-12-01

Flood prediction in poorly monitored catchments is among the greatest challenges faced by hydrologists. To address this challenge, an increasing number of studies in the last decade have explored methods to integrate various existing observations from ground and satellites. One approach in particular, is the assimilation of satellite soil moisture (SM-DA) into rainfall-runoff models. The rationale is that satellite soil moisture (SSM) can be used to correct model soil water states, enabling more accurate prediction of catchment response to precipitation and thus better streamflow. However, there is still no consensus on the most effective SM-DA scheme and how this might depend on catchment scale, climate characteristics, runoff mechanisms, model and SSM products used, etc. In this work, an operational SM-DA scheme was set up in the poorly monitored, large (>40,000 km2), semi-arid Warrego catchment situated in eastern Australia. We assimilated passive and active SSM products into the probability distributed model (PDM) using an ensemble Kalman filter. We explored factors influencing the SM-DA framework, including relatively new techniques to remove model-observation bias, estimate observation errors and represent model errors. Furthermore, we explored the advantages of accounting for the spatial distribution of forcing and channel routing processes within the catchment by implementing and comparing lumped and semi-distributed model setups. Flood prediction is improved by SM-DA (Figure), with a 30% reduction of the average root-mean-squared difference of the ensemble prediction, a 20% reduction of the false alarm ratio and a 40% increase of the ensemble mean Nash-Sutcliffe efficiency. SM-DA skill does not significantly change with different observation error assumptions, but the skill strongly depends on the observational bias correction technique used, and more importantly, on the performance of the open-loop model before assimilation. Our findings imply that proper pre-processing of SSM is important for the efficacy of the SM-DA and assimilation performance is critically affected by the quality of model calibration. We therefore recommend focusing efforts on these two factors, while further evaluating the trade-offs between model complexity and data availability.

Two-cation competition in ionic-liquid-modified electrolytes for lithium ion batteries.

PubMed

Lee, Sang-Young; Yong, Hyun Hang; Lee, Young Joo; Kim, Seok Koo; Ahn, Soonho

2005-07-21

It is a common observation that when ionic liquids are added to electrolytes the performances of lithium ion cells become poor, while the thermal safeties of the electrolytes might be improved. In this study, this behavior is investigated based on the kinetics of ionic diffusion. As a model ionic liquid, we chose butyldimethylimidazolium hexafluorophosphate (BDMIPF(6)). The common solvent was propylene carbonate (PC), and lithium hexafluorophosphate (LiPF(6)) was selected as the lithium conducting salt. Ionic diffusion coefficients are estimated by using a pulsed field gradient NMR technique. From a basic study on the model electrolytes (BDMIPF(6) in PC, LiPF(6) in PC, and BDMIPF(6) + LiPF(6) in PC), it was found that the BDMI(+) from BDMIPF(6) shows larger diffusion coefficients than the Li(+) from LiPF(6). However, the anionic (PF(6)(-)) diffusion coefficients present little difference between the model electrolytes. The higher diffusion coefficient of BDMI(+) than that of Li(+) suggests that the poor C-rate performance of lithium ion cells containing ionic liquids as an electrolyte component can be attributed to the two-cation competition between Li(+) and BDMI(+).

Sensitivity of Rainfall-runoff Model Parametrization and Performance to Potential Evaporation Inputs

NASA Astrophysics Data System (ADS)

Jayathilake, D. I.; Smith, T. J.

2017-12-01

Many watersheds of interest are confronted with insufficient data and poor process understanding. Therefore, understanding the relative importance of input data types and the impact of different qualities on model performance, parameterization, and fidelity is critically important to improving hydrologic models. In this paper, the change in model parameterization and performance are explored with respect to four different potential evapotranspiration (PET) products of varying quality. For each PET product, two widely used, conceptual rainfall-runoff models are calibrated with multiple objective functions to a sample of 20 basins included in the MOPEX data set and analyzed to understand how model behavior varied. Model results are further analyzed by classifying catchments as energy- or water-limited using the Budyko framework. The results demonstrated that model fit was largely unaffected by the quality of the PET inputs. However, model parameterizations were clearly sensitive to PET inputs, as their production parameters adjusted to counterbalance input errors. Despite this, changes in model robustness were not observed for either model across the four PET products, although robustness was affected by model structure.

Migraine and cognitive function: Baseline findings from the Brazilian Longitudinal Study of Adult Health: ELSA-Brasil.

PubMed

Pellegrino Baena, Cristina; Goulart, Alessandra Carvalho; Santos, Itamar de Souza; Suemoto, Claudia Kimie; Lotufo, Paulo Andrade; Bensenor, Isabela Judith

2017-01-01

Background The association between migraine and cognitive performance is unclear. We analyzed whether migraine is associated with cognitive performance among participants of the Brazilian Longitudinal Study of Adult Health, ELSA-Brasil. Methods Cross-sectional analysis, including participants with complete information about migraine and aura at baseline. Headache status (no headaches, non-migraine headaches, migraine without aura and migraine with aura), based on the International Headache Society classification, was used as the dependent variable in the multilinear regression models, using the category "no headache" as reference. Cognitive performance was measured with the Consortium to Establish a Registry for Alzheimer's Disease word list memory test (CERAD-WLMT), the semantic fluency test (SFT), and the Trail Making Test version B (TMTB). Z-scores for each cognitive test and a composite global score were created and analyzed as dependent variables. Multivariate models were adjusted for age, gender, education, race, coronary heart disease, heart failure, hypertension, diabetes, dyslipidemia, body mass index, smoking, alcohol use, physical activity, depression, and anxiety. In women, the models were further adjusted for hormone replacement therapy. Results We analyzed 4208 participants. Of these, 19% presented migraine without aura and 10.3% presented migraine with aura. All migraine headaches were associated with poor cognitive performance (linear coefficient β; 95% CI) at TMTB -0.083 (-0.160; -0.008) and poorer global z-score -0.077 (-0.152; -0.002). Also, migraine without aura was associated with poor cognitive performance at TMTB -0.084 (-0.160, -0.008 and global z-score -0.077 (-0.152; -0.002). Conclusion In participants of the ELSA-study, all migraine headaches and migraine without aura were significantly and independently associated with poorer cognitive performance.

Managing Your Team's Weakest Link.

PubMed

Hills, Laura

2015-01-01

Do you have a poor-performing employee on your medical practice team? If so, you're not alone. Unfortunately, this is a problem that many medical practice managers face. This article describes the best strategies for managing your team's weakest link. It explores common yet very difficult circumstances that cause low employee performance and that test the patience, heart, and skills of a practice manager. It guides readers through a process of self-discovery to determine whether their negative biases or grudges may be causing employees to perform poorly. It suggests several possible other reasons for weak employee performance, including problems with the job, practice, leadership, communication, and fit between the employee and the job. This article also suggests the best strategy for communicating concerns about performance to the weakest-link employee. It offers guidance to practice managers about protecting their time and energy when handling a poor performer. It provides a simple formula for calculating the cost of a low-performing employee, 10 possible personal reasons for the employee's poor work performance, specific questions to ask to uncover the reasons for poor performance, and an eight-rule strategy for confronting poor performance effectively. Finally, this article offers practice managers a practical strategy for handling resistance from their weakest link, illustrated with a sample dialogue.

Measurements of evaporation from a mine void lake and testing of modelling approaches

NASA Astrophysics Data System (ADS)

McJannet, David; Hawdon, Aaron; Van Niel, Tom; Boadle, Dave; Baker, Brett; Trefry, Mike; Rea, Iain

2017-12-01

Pit lakes often form in the void that remains after open cut mining operations cease. As pit lakes fill, hydrological and geochemical processes interact and these need to be understood for appropriate management actions to be implemented. Evaporation is important in the evolution of pit lakes as it acts to concentrate various constituents, controls water level and changes the thermal characteristics of the water body. Despite its importance, evaporation from pit lakes is poorly understood. To address this, we used an automated floating evaporation pan and undertook measurements at a pit lake over a 12 month period. We also developed a new procedure for correcting floating pan evaporation estimates to lake evaporation estimates based on surface temperature differences. Total annual evaporation was 2690 mm and reflected the strong radiation inputs, high temperatures and low humidity experienced in this region. Measurements were used to test the performance of evaporation estimates derived using both pan coefficient and aerodynamic modelling techniques. Daily and monthly evaporation estimates were poorly reproduced using pan coefficient techniques and their use is not recommended for such environments. Aerodynamic modelling was undertaken using a range of input datasets that may be available to those who manage pit lake systems. Excellent model performance was achieved using over-water or local over-land meteorological observations, particularly when the sheltering effects of the pit were considered. Model performance was reduced when off-site data were utilised and differences between local and off-site vapor pressure and wind speed were found to be the major cause.

Developmental programming: the concept, large animal models, and the key role of uteroplacental vascular development.

PubMed

Reynolds, L P; Borowicz, P P; Caton, J S; Vonnahme, K A; Luther, J S; Hammer, C J; Maddock Carlin, K R; Grazul-Bilska, A T; Redmer, D A

2010-04-01

Developmental programming refers to the programming of various bodily systems and processes by a stressor of the maternal system during pregnancy or during the neonatal period. Such stressors include nutritional stress, multiple pregnancy (i.e., increased numbers of fetuses in the gravid uterus), environmental stress (e.g., high environmental temperature, high altitude, prenatal steroid exposure), gynecological immaturity, and maternal or fetal genotype. Programming refers to impaired function of numerous bodily systems or processes, leading to poor growth, altered body composition, metabolic dysfunction, and poor productivity (e.g., poor growth, reproductive dysfunction) of the offspring throughout their lifespan and even across generations. A key component of developmental programming seems to be placental dysfunction, leading to altered fetal growth and development. We discuss various large animal models of developmental programming and how they have and will continue to contribute to our understanding of the mechanisms underlying altered placental function and developmental programming, and, further, how large animal models also will be critical to the identification and application of therapeutic strategies that will alleviate the negative consequences of developmental programming to improve offspring performance in livestock production and human medicine.

Developing a Tool for Measuring the Decision-Making Competence of Older Adults

PubMed Central

Finucane, Melissa L.; Gullion, Christina M.

2010-01-01

The authors evaluated the reliability and validity of a tool for measuring older adults’ decision-making competence (DMC). Two-hundred-five younger adults (25-45 years), 208 young-older adults (65-74 years), and 198 old-older adults (75-97 years) made judgments and decisions related to health, finance, and nutrition. Reliable indices of comprehension, dimension weighting, and cognitive reflection were developed. Unlike previous research, the authors were able to compare old-older with young-older adults’ performance. As hypothesized, old-older adults performed more poorly than young-older adults; both groups of older adults performed more poorly than younger adults. Hierarchical regression analyses showed that a large amount of variance in decision performance across age groups (including mean trends) could be accounted for by social variables, health measures, basic cognitive skills, attitudinal measures, and numeracy. Structural equation modeling revealed significant pathways from three exogenous latent factors (crystallized intelligence, other cognitive abilities, and age) to the endogenous DMC latent factor. Further research is needed to validate the meaning of performance on these tasks for real-life decision making. PMID:20545413

Strategic adaptation to performance objectives in a dual-task setting.

PubMed

Janssen, Christian P; Brumby, Duncan P

2010-11-01

How do people interleave attention when multitasking? One dominant account is that the completion of a subtask serves as a cue to switch tasks. But what happens if switching solely at subtask boundaries led to poor performance? We report a study in which participants manually dialed a UK-style telephone number while driving a simulated vehicle. If the driver were to exclusively return his or her attention to driving after completing a subtask (i.e., using the single break in the xxxxx-xxxxxx representational structure of the number), then we would expect to see a relatively poor driving performance. In contrast, our results show that drivers choose to return attention to steering control before the natural subtask boundary. A computational modeling analysis shows that drivers had to adopt this strategy to meet the required performance objective of maintaining an acceptable lateral position in the road while dialing. Taken together these results support the idea that people can strategically control the allocation of attention in multitask settings to meet specific performance criteria. Copyright © 2010 Cognitive Science Society, Inc.

Lipid correction model of carbon stable isotopes for a cosmopolitan predator, spiny dogfish Squalus acanthias.

PubMed

Reum, J C P

2011-12-01

Three lipid correction models were evaluated for liver and white dorsal muscle from Squalus acanthias. For muscle, all three models performed well, based on the Akaike Information Criterion value corrected for small sample sizes (AIC(c) ), and predicted similar lipid corrections to δ(13) C that were up to 2.8 ‰ higher than those predicted using previously published models based on multispecies data. For liver, which possessed higher bulk C:N values compared to that of white muscle, all three models performed poorly and lipid-corrected δ(13) C values were best approximated by simply adding 5.74 ‰ to bulk δ(13) C values. © 2011 The Author. Journal of Fish Biology © 2011 The Fisheries Society of the British Isles.

Enhanced performance of macrophage-encapsulated nanoparticle albumin-bound-paclitaxel in hypo-perfused cancer lesions

NASA Astrophysics Data System (ADS)

Leonard, Fransisca; Curtis, Louis T.; Yesantharao, Pooja; Tanei, Tomonori; Alexander, Jenolyn F.; Wu, Min; Lowengrub, John; Liu, Xuewu; Ferrari, Mauro; Yokoi, Kenji; Frieboes, Hermann B.; Godin, Biana

2016-06-01

Hypovascularization in tumors such as liver metastases originating from breast and other organs correlates with poor chemotherapeutic response and higher mortality. Poor prognosis is linked to impaired transport of both low- and high-molecular weight drugs into the lesions and to high washout rate. Nanoparticle albumin-bound-paclitaxel (nAb-PTX) has demonstrated benefits in clinical trials when compared to paclitaxel and docetaxel. However, its therapeutic efficacy for breast cancer liver metastasis is disappointing. As macrophages are the most abundant cells in the liver tumor microenvironment, we design a multistage system employing macrophages to deliver drugs into hypovascularized metastatic lesions, and perform in vitro, in vivo, and in silico evaluation. The system encapsulates nAb-PTX into nanoporous biocompatible and biodegradable multistage vectors (MSV), thus promoting nAb-PTX retention in macrophages. We develop a 3D in vitro model to simulate clinically observed hypo-perfused tumor lesions surrounded by macrophages. This model enables evaluation of nAb-PTX and MSV-nab PTX efficacy as a function of transport barriers. Addition of macrophages to this system significantly increases MSV-nAb-PTX efficacy, revealing the role of macrophages in drug transport. In the in vivo model, a significant increase in macrophage number, as compared to unaffected liver, is observed in mice, confirming the in vitro findings. Further, a mathematical model linking drug release and retention from macrophages is implemented to project MSV-nAb-PTX efficacy in a clinical setting. Based on macrophage presence detected via liver tumor imaging and biopsy, the proposed experimental/computational approach could enable prediction of MSV-nab PTX performance to treat metastatic cancer in the liver.Hypovascularization in tumors such as liver metastases originating from breast and other organs correlates with poor chemotherapeutic response and higher mortality. Poor prognosis is linked to impaired transport of both low- and high-molecular weight drugs into the lesions and to high washout rate. Nanoparticle albumin-bound-paclitaxel (nAb-PTX) has demonstrated benefits in clinical trials when compared to paclitaxel and docetaxel. However, its therapeutic efficacy for breast cancer liver metastasis is disappointing. As macrophages are the most abundant cells in the liver tumor microenvironment, we design a multistage system employing macrophages to deliver drugs into hypovascularized metastatic lesions, and perform in vitro, in vivo, and in silico evaluation. The system encapsulates nAb-PTX into nanoporous biocompatible and biodegradable multistage vectors (MSV), thus promoting nAb-PTX retention in macrophages. We develop a 3D in vitro model to simulate clinically observed hypo-perfused tumor lesions surrounded by macrophages. This model enables evaluation of nAb-PTX and MSV-nab PTX efficacy as a function of transport barriers. Addition of macrophages to this system significantly increases MSV-nAb-PTX efficacy, revealing the role of macrophages in drug transport. In the in vivo model, a significant increase in macrophage number, as compared to unaffected liver, is observed in mice, confirming the in vitro findings. Further, a mathematical model linking drug release and retention from macrophages is implemented to project MSV-nAb-PTX efficacy in a clinical setting. Based on macrophage presence detected via liver tumor imaging and biopsy, the proposed experimental/computational approach could enable prediction of MSV-nab PTX performance to treat metastatic cancer in the liver. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr07796f

Parallel But Not Equivalent: Challenges and Solutions for Repeated Assessment of Cognition over Time

PubMed Central

Gross, Alden L.; Inouye, Sharon K.; Rebok, George W.; Brandt, Jason; Crane, Paul K.; Parisi, Jeanine M.; Tommet, Doug; Bandeen-Roche, Karen; Carlson, Michelle C.; Jones, Richard N.

2013-01-01

Objective Analyses of individual differences in change may be unintentionally biased when versions of a neuropsychological test used at different follow-ups are not of equivalent difficulty. This study’s objective was to compare mean, linear, and equipercentile equating methods and demonstrate their utility in longitudinal research. Study Design and Setting The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE, N=1,401) study is a longitudinal randomized trial of cognitive training. The Alzheimer’s Disease Neuroimaging Initiative (ADNI, n=819) is an observational cohort study. Nonequivalent alternate versions of the Auditory Verbal Learning Test (AVLT) were administered in both studies. Results Using visual displays, raw and mean-equated AVLT scores in both studies showed obvious nonlinear trajectories in reference groups that should show minimal change, poor equivalence over time (ps≤0.001), and raw scores demonstrated poor fits in models of within-person change (RMSEAs>0.12). Linear and equipercentile equating produced more similar means in reference groups (ps≥0.09) and performed better in growth models (RMSEAs<0.05). Conclusion Equipercentile equating is the preferred equating method because it accommodates tests more difficult than a reference test at different percentiles of performance and performs well in models of within-person trajectory. The method has broad applications in both clinical and research settings to enhance the ability to use nonequivalent test forms. PMID:22540849

Does adding clinical data to administrative data improve agreement among hospital quality measures?

PubMed

Hanchate, Amresh D; Stolzmann, Kelly L; Rosen, Amy K; Fink, Aaron S; Shwartz, Michael; Ash, Arlene S; Abdulkerim, Hassen; Pugh, Mary Jo V; Shokeen, Priti; Borzecki, Ann

2017-09-01

Hospital performance measures based on patient mortality and readmission have indicated modest rates of agreement. We examined if combining clinical data on laboratory tests and vital signs with administrative data leads to improved agreement with each other, and with other measures of hospital performance in the nation's largest integrated health care system. We used patient-level administrative and clinical data, and hospital-level data on quality indicators, for 2007-2010 from the Veterans Health Administration (VA). For patients admitted for acute myocardial infarction (AMI), heart failure (HF) and pneumonia we examined changes in hospital performance on 30-d mortality and 30-d readmission rates as a result of adding clinical data to administrative data. We evaluated whether this enhancement yielded improved measures of hospital quality, based on concordance with other hospital quality indicators. For 30-d mortality, data enhancement improved model performance, and significantly changed hospital performance profiles; for 30-d readmission, the impact was modest. Concordance between enhanced measures of both outcomes, and with other hospital quality measures - including Joint Commission process measures, VA Surgical Quality Improvement Program (VASQIP) mortality and morbidity, and case volume - remained poor. Adding laboratory tests and vital signs to measure hospital performance on mortality and readmission did not improve the poor rates of agreement across hospital quality indicators in the VA. Efforts to improve risk adjustment models should continue; however, evidence of validation should precede their use as reliable measures of quality. Published by Elsevier Inc.

Polymer brushes in explicit poor solvents studied using a new variant of the bond fluctuation model

NASA Astrophysics Data System (ADS)

Jentzsch, Christoph; Sommer, Jens-Uwe

2014-09-01

Using a variant of the Bond Fluctuation Model which improves its parallel efficiency in particular running on graphic cards we perform large scale simulations of polymer brushes in poor explicit solvent. Grafting density, solvent quality, and chain length are varied. Different morphological structures in particular octopus micelles are observed for low grafting densities. We reconsider the theoretical model for octopus micelles proposed by Williams using scaling arguments with the relevant scaling variable being σ/σc, and with the characteristic grafting density given by σc ˜ N-4/3. We find that octopus micelles only grow laterally, but not in height and we propose an extension of the model by assuming a cylindrical shape instead of a spherical geometry for the micelle-core. We show that the scaling variable σ/σc can be applied to master plots for the averaged height of the brush, the size of the micelles, and the number of chains per micelle. The exponents in the corresponding power law relations for the grafting density and chain length are in agreement with the model for flat cylindrical micelles. We also investigate the surface roughness and find that polymer brushes in explicit poor solvent at grafting densities higher than the stretching transition are flat and surface rippling can only be observed close to the stretching transition.

The upside down world of diabetes care medical economics and what we might do to improve it.

PubMed

Harlan, David M; Hirsch, Irl B

2017-04-01

Increasingly over the past generation, the American healthcare delivery system has received consistently poor marks with regard to public health outcomes and costs. This review by two seasoned diabetes care providers is intended to shed light on the fundamental flaws we believe to underlie that poor performance, and suggest options for better outcomes and cost efficiencies. Despite major advances in diabetes management medications and tools, overall public health with regard to diabetes outcomes remains poor. Efforts focused on controlling costs appear to be exacerbating the problem. For chronic diseases like diabetes, fee-for-service care models are fundamentally flawed and predictably fail. We suggest that a major overhaul of the medical economics underlying diabetes care can improve patient outcomes and decrease costs.

Contribution of organizational strategy to verbal learning and memory in adults with attention-deficit/hyperactivity disorder.

PubMed

Roth, Robert M; Wishart, Heather A; Flashman, Laura A; Riordan, Henry J; Huey, Leighton; Saykin, Andrew J

2004-01-01

Statistical mediation modeling was used to test the hypothesis that poor use of a semantic organizational strategy contributes to verbal learning and memory deficits in adults with attention-deficit/hyperactivity disorder (ADHD). Comparison of 28 adults with ADHD and 34 healthy controls revealed lower performance by the ADHD group on tests of verbal learning and memory, sustained attention, and use of semantic organization during encoding. Mediation modeling indicated that state anxiety, but not semantic organization, significantly contributed to the prediction of both learning and delayed recall in the ADHD group. The pattern of findings suggests that decreased verbal learning and memory in adult ADHD is due in part to situational anxiety and not to poor use of organizational strategies during encoding. ((c) 2004 APA, all rights reserved)

The importance of understanding: Model space moderates goal specificity effects.

PubMed

Kistner, Saskia; Burns, Bruce D; Vollmeyer, Regina; Kortenkamp, Ulrich

2016-01-01

The three-space theory of problem solving predicts that the quality of a learner's model and the goal specificity of a task interact on knowledge acquisition. In Experiment 1 participants used a computer simulation of a lever system to learn about torques. They either had to test hypotheses (nonspecific goal), or to produce given values for variables (specific goal). In the good- but not in the poor-model condition they saw torque depicted as an area. Results revealed the predicted interaction. A nonspecific goal only resulted in better learning when a good model of torques was provided. In Experiment 2 participants learned to manipulate the inputs of a system to control its outputs. A nonspecific goal to explore the system helped performance when compared to a specific goal to reach certain values when participants were given a good model, but not when given a poor model that suggested the wrong hypothesis space. Our findings support the three-space theory. They emphasize the importance of understanding for problem solving and stress the need to study underlying processes.

Comparison of genetic algorithms with conjugate gradient methods

NASA Technical Reports Server (NTRS)

Bosworth, J. L.; Foo, N. Y.; Zeigler, B. P.

1972-01-01

Genetic algorithms for mathematical function optimization are modeled on search strategies employed in natural adaptation. Comparisons of genetic algorithms with conjugate gradient methods, which were made on an IBM 1800 digital computer, show that genetic algorithms display superior performance over gradient methods for functions which are poorly behaved mathematically, for multimodal functions, and for functions obscured by additive random noise. Genetic methods offer performance comparable to gradient methods for many of the standard functions.

Iron nutrition and premenopausal women: effects of poor iron status on physical and neuropsychological performance.

PubMed

McClung, James P; Murray-Kolb, Laura E

2013-01-01

Iron is a nutritionally essential trace element that functions through incorporation into proteins and enzymes, many of which contribute to physical and neuropsychological performance. Poor iron status, including iron deficiency (ID; diminished iron stores) and iron deficiency anemia (IDA; poor iron stores and diminished hemoglobin), affects billions of people worldwide. This review focuses on physical and neuropsychological outcomes associated with ID and IDA in premenopausal women, as the prevalence of ID and IDA is often greater in premenopausal women than other population demographics. Recent studies addressing the physiological effects of poor iron status on physical performance, including work productivity, voluntary activity, and athletic performance, are addressed. Similarly, the effects of iron status on neurological performance, including cognition, affect, and behavior, are summarized. Nutritional countermeasures for the prevention of poor iron status and the restoration of decrements in performance outcomes are described.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment.

PubMed

De Kauwe, Martin G; Medlyn, Belinda E; Walker, Anthony P; Zaehle, Sönke; Asao, Shinichi; Guenet, Bertrand; Harper, Anna B; Hickler, Thomas; Jain, Atul K; Luo, Yiqi; Lu, Xingjie; Luus, Kristina; Parton, William J; Shu, Shijie; Wang, Ying-Ping; Werner, Christian; Xia, Jianyang; Pendall, Elise; Morgan, Jack A; Ryan, Edmund M; Carrillo, Yolima; Dijkstra, Feike A; Zelikova, Tamara J; Norby, Richard J

2017-09-01

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2  yr -1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO 2 -induced water savings to extend the growing season length. Observed interactive (CO 2  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change. © 2017 John Wiley & Sons Ltd.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

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

De Kauwe, Martin G.; Medlyn, Belinda E.; Walker, Anthony P.

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1). Comparison with data highlighted model failures particularlymore » in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2-induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.« less

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

DOE PAGES

De Kauwe, Martin G.; Medlyn, Belinda E.; Walker, Anthony P.; ...

2017-02-01

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1). Comparison with data highlighted model failures particularlymore » in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2-induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.« less

A driver-adaptive stability control strategy for sport utility vehicles

NASA Astrophysics Data System (ADS)

Zhu, Shenjin; He, Yuping

2017-08-01

Conventional vehicle stability control (VSC) systems are designed for average drivers. For a driver with a good driving skill, the VSC systems may be redundant; for a driver with a poor driving skill, the VSC intervention may be inadequate. To increase safety of sport utility vehicles (SUVs), this paper proposes a novel driver-adaptive VSC (DAVSC) strategy based on scaling the target yaw rate commanded by the driver. The DAVSC system is adaptive to drivers' driving skills. More control effort would be exerted for drivers with poor driving skills, and vice versa. A sliding mode control (SMC)-based differential braking (DB) controller is designed using a three degrees of freedom (DOF) yaw-plane model. An eight DOF nonlinear yaw-roll model is used to simulate the SUV dynamics. Two driver models, namely longitudinal and lateral, are used to 'drive' the virtual SUV. By integrating the virtual SUV, the DB controller, and the driver models, the performance of the DAVSC system is investigated. The simulations demonstrate the effectiveness of the DAVSC strategy.

Cognitive architectures and language acquisition: a case study in pronoun comprehension.

PubMed

VAN Rij, Jacolien; VAN Rijn, Hedderik; Hendriks, Petra

2010-06-01

In this paper we discuss a computational cognitive model of children's poor performance on pronoun interpretation (the so-called Delay of Principle B Effect, or DPBE). This cognitive model is based on a theoretical account that attributes the DPBE to children's inability as hearers to also take into account the speaker's perspective. The cognitive model predicts that child hearers are unable to do so because their speed of linguistic processing is too limited to perform this second step in interpretation. We tested this hypothesis empirically in a psycholinguistic study, in which we slowed down the speech rate to give children more time for interpretation, and in a computational simulation study. The results of the two studies confirm the predictions of our model. Moreover, these studies show that embedding a theory of linguistic competence in a cognitive architecture allows for the generation of detailed and testable predictions with respect to linguistic performance.

Private sector, for-profit health providers in low and middle income countries: can they reach the poor at scale?

PubMed

Tung, Elizabeth; Bennett, Sara

2014-06-24

The bottom of the pyramid concept suggests that profit can be made in providing goods and services to poor people, when high volume is combined with low margins. To-date there has been very limited empirical evidence from the health sector concerning the scope and potential for such bottom of the pyramid models. This paper analyzes private for-profit (PFP) providers currently offering services to the poor on a large scale, and assesses the future prospects of bottom of the pyramid models in health. We searched published and grey literature and databases to identify PFP companies that provided more than 40,000 outpatient visits per year, or who covered 15% or more of a particular type of service in their country. For each included provider, we searched for additional information on location, target market, business model and performance, including quality of care. Only 10 large scale PFP providers were identified. The majority of these were in South Asia and most provided specialized services such as eye care. The characteristics of the business models of these firms were found to be similar to non-profit providers studied by other analysts (such as Bhattacharya 2010). They pursued social rather than traditional marketing, partnerships with government, low cost/high volume services and cross-subsidization between different market segments. There was a lack of reliable data concerning these providers. There is very limited evidence to support the notion that large scale bottom of the pyramid models in health offer good prospects for extending services to the poor in the future. In order to be successful PFP providers often require partnerships with government or support from social health insurance schemes. Nonetheless, more reliable and independent data on such schemes is needed.

Private sector, for-profit health providers in low and middle income countries: can they reach the poor at scale?

PubMed Central

2014-01-01

Background The bottom of the pyramid concept suggests that profit can be made in providing goods and services to poor people, when high volume is combined with low margins. To-date there has been very limited empirical evidence from the health sector concerning the scope and potential for such bottom of the pyramid models. This paper analyzes private for-profit (PFP) providers currently offering services to the poor on a large scale, and assesses the future prospects of bottom of the pyramid models in health. Methods We searched published and grey literature and databases to identify PFP companies that provided more than 40,000 outpatient visits per year, or who covered 15% or more of a particular type of service in their country. For each included provider, we searched for additional information on location, target market, business model and performance, including quality of care. Results Only 10 large scale PFP providers were identified. The majority of these were in South Asia and most provided specialized services such as eye care. The characteristics of the business models of these firms were found to be similar to non-profit providers studied by other analysts (such as Bhattacharya 2010). They pursued social rather than traditional marketing, partnerships with government, low cost/high volume services and cross-subsidization between different market segments. There was a lack of reliable data concerning these providers. Conclusions There is very limited evidence to support the notion that large scale bottom of the pyramid models in health offer good prospects for extending services to the poor in the future. In order to be successful PFP providers often require partnerships with government or support from social health insurance schemes. Nonetheless, more reliable and independent data on such schemes is needed. PMID:24961496

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

PubMed

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (p<0.005) and correlated with independently identified visual EEG patterns such as generalized periodic discharges (p<0.02). Receiver operating characteristic (ROC) analysis confirmed the predictive value of lower state space velocity for poor clinical outcome after cardiac arrest (AUC 80.8, 70% sensitivity, 15% false positive rate). Model-based quantitative EEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

The Model Human Processor and the Older Adult: Parameter Estimation and Validation Within a Mobile Phone Task

PubMed Central

Jastrzembski, Tiffany S.; Charness, Neil

2009-01-01

The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; Mage = 20) and older (N = 20; Mage = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.99) and produced equivalent fits to previously validated younger adult models. Critical path analyses highlighted points of poor design as a function of cognitive workload, hardware/software design, and user characteristics. The findings demonstrate that estimated older adult information processing parameters are valid for modeling purposes, can help designers understand age-related performance using existing interfaces, and may support the development of age-sensitive technologies. PMID:18194048

The Model Human Processor and the older adult: parameter estimation and validation within a mobile phone task.

PubMed

Jastrzembski, Tiffany S; Charness, Neil

2007-12-01

The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; M-sub(age) = 20) and older (N = 20; M-sub(age) = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.99) and produced equivalent fits to previously validated younger adult models. Critical path analyses highlighted points of poor design as a function of cognitive workload, hardware/software design, and user characteristics. The findings demonstrate that estimated older adult information processing parameters are valid for modeling purposes, can help designers understand age-related performance using existing interfaces, and may support the development of age-sensitive technologies.

A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method

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

Huang, Shengzhi; Ming, Bo; Huang, Qiang

It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecastingmore » models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.« less

Understanding words, understanding numbers: an exploration of the mathematical profiles of poor comprehenders.

PubMed

Pimperton, Hannah; Nation, Kate

2010-06-01

Poor comprehenders are children who show significant deficits in their reading comprehension performance, despite average, or above-average word reading ability. To date, there have been no in-depth studies of the mathematical performance profiles of such children. This study aimed to explore the mathematical profiles of poor comprehenders. Given that language impairment is associated with difficulties with mathematics, and that poor comprehenders tend to have oral language weaknesses, we hypothesized that poor comprehenders would show relative weaknesses in aspects of mathematical performance. From a sample of 109 children aged 7-8 years, we selected 14 poor comprehenders and 14 controls with age-appropriate reading comprehension ability. The groups were matched on non-verbal ability, multiple measures of reading accuracy, and chronological age. We compared the performance of the group of poor comprehenders with that of the matched controls on two standardized measures of mathematical ability, one measuring procedural arithmetic prowess and the other tapping higher-level mathematical reasoning. Although there were no group differences in performance on the arithmetic measure, the poor comprehenders showed significantly lower scores than the controls on the mathematical reasoning task. The poor comprehenders exhibited impaired verbal ability relative to controls, with these differences in verbal ability associated with the group differences found on the test of mathematical reasoning. Poor comprehenders' deficits are not limited to the domain of literacy; their underlying profile of impairments also seems to selectively impact on certain components of mathematical ability.

Heat transfer enhancement in a lithium-ion cell through improved material-level thermal transport

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

Vishwakarma, Vivek; Waghela, Chirag; Wei, Zi

2016-09-25

We report that while Li-ion cells offer excellent electrochemical performance for several applications including electric vehicles, they also exhibit poor thermal transport characteristics, resulting in reduced performance, overheating and thermal runaway. Inadequate heat removal from Li-ion cells originates from poor thermal conductivity within the cell. This paper identifies the rate-limiting material-level process that dominates overall thermal conduction in a Li-ion cell. Results indicate that thermal characteristics of a Li-ion cell are largely dominated by heat transfer across the cathode-separator interface rather than heat transfer through the materials themselves. This interfacial thermal resistance contributes around 88% of total thermal resistance inmore » the cell. Measured value of interfacial resistance is close to that obtained from theoretical models that account for weak adhesion and large acoustic mismatch between cathode and separator. Further, to address this problem, an amine-based chemical bridging of the interface is carried out. This is shown to result in in four-times lower interfacial thermal resistance without deterioration in electrochemical performance, thereby increasing effective thermal conductivity by three-fold. This improvement is expected to reduce peak temperature rise during operation by 60%. Finally, by identifying and addressing the material-level root cause of poor thermal transport in Li-ion cells, this work may contribute towards improved thermal performance of Li-ion cells.« less

Cigarette smoking in a student sample: neurocognitive and clinical correlates.

PubMed

Dinn, Wayne M; Aycicegi, Ayse; Harris, Catherine L

2004-01-01

Why do adolescents begin to smoke in the face of profound health risks and aggressive antismoking campaigns? The present study tested predictions based on two theoretical models of tobacco use in young adults: (1) the self-medication model; and (2) the orbitofrontal/disinhibition model. Investigators speculated that a significant number of smokers were self-medicating since nicotine possesses mood-elevating and hedonic properties. The self-medication model predicts that smokers will demonstrate increased rates of psychopathology relative to nonsmokers. Similarly, researchers have suggested that individuals with attention-deficit/hyperactivity disorder (ADHD) employ nicotine to enhance cognitive function. The ADHD/self-medication model predicts that smokers will perform poorly on tests of executive function and report a greater number of ADHD symptoms. A considerable body of research indicates that tobacco use is associated with several related personality traits including extraversion, impulsivity, risk taking, sensation seeking, novelty seeking, and antisocial personality features. Antisocial behavior and related personality traits as well as tobacco use may reflect, in part, a failure to effectively employ reward and punishment cues to guide behavior. This failure may reflect orbitofrontal dysfunction. The orbitofrontal/disinhibition model predicts that smokers will perform poorly on neurocognitive tasks considered sensitive to orbitofrontal dysfunction and will obtain significantly higher scores on measures of behavioral disinhibition and antisocial personality relative to nonsmokers. To test these predictions, we administered a battery of neuropsychological tests, clinical scales, and personality questionnaires to university student smokers and nonsmokers. Results did not support the self-medication model or the ADHD/self-medication model; however, findings were consistent with the orbitofrontal/disinhibition model.

Sibling care, school performance, and depression among adolescent caretakers in Cambodia.

PubMed

Yi, Siyan; Poudel, Krishna C; Yasuoka, Junko; Palmer, Paula H; Yi, Songky; Yanagisawa, Satoko; Jimba, Masamine

2012-06-01

In many resource-poor countries, home-based care for young children is crucial. Yet little has been known about the negative impacts of sibling caretaking on mental health conditions of adolescent student caretakers. This study explored associations between sibling caretaking, school performance, and depression among 1943 students randomly selected from 11 junior high and high schools in Cambodia. The Asian Adolescent Depression Scale was used to measure depressive symptoms. In bivariate analyses, we used χ(2) test or Fisher's exact test for categorical variables and t-test or one-way analysis of variance for continuous variables. Multiple linear regression models were then constructed. Of total, 60.1% of our participants took care of their younger sibling(s) regularly during the past one year. The number of siblings under their care ranged from one to nine, and the time they spent for sibling care ranged from one to 10h per day. After adjustment, increased levels of depressive symptoms remained significantly associated among boys with sibling caretaking (p<0.001), as well as poor school performance (p=0.001) and perceived likelihood of dropping out of school in the near future (p=0.002). Among girls, increased levels of depressive symptoms retained their significant association with sibling caretaking (p<0.001); also poor school performance (p<0.001). Sibling care responsibility might have negative impact on school performance and the mental health condition of adolescent caretakers. Copyright © 2012 Elsevier B.V. All rights reserved.

The Relationship of Reduced Peripheral Nerve Function and Diabetes With Physical Performance in Older White and Black Adults

PubMed Central

Strotmeyer, Elsa S.; de Rekeneire, Nathalie; Schwartz, Ann V.; Faulkner, Kimberly A.; Resnick, Helaine E.; Goodpaster, Bret H.; Shorr, Ronald I.; Vinik, Aaron I.; Harris, Tamara B.; Newman, Anne B.

2008-01-01

OBJECTIVE—Poor peripheral nerve function is prevalent in diabetes and older populations, and it has great potential to contribute to poor physical performance. RESEARCH DESIGN AND METHODS—Cross-sectional analyses were done for the Health, Aging, and Body Composition (Health ABC) Study participants (n = 2,364; 48% men; 38% black; aged 73–82 years). Sensory and motor peripheral nerve function in legs/feet was assessed by 10- and 1.4-g monofilament perception, vibration detection, and peroneal motor nerve conduction amplitude and velocity. The Health ABC lower-extremity performance battery was a supplemented version of the Established Populations for the Epidemiologic Studies of the Elderly battery (chair stands, standing balance, and 6-m walk), adding increased stand duration, single foot stand, and narrow walk. RESULTS—Diabetic participants had fewer chair stands (0.34 vs. 0.36 stands/s), shorter standing balance time (0.69 vs. 0.75 ratio), slower usual walking speed (1.11 vs. 1.14 m/s), slower narrow walking speed (0.80 vs. 0.90 m/s), and lower performance battery score (6.43 vs. 6.93) (all P < 0.05). Peripheral nerve function was associated with each physical performance measure independently. After addition of peripheral nerve function in fully adjusted models, diabetes remained significantly related to a lower performance battery score and slower narrow walking speed but not to chair stands, standing balance, or usual walking speed. CONCLUSIONS—Poor peripheral nerve function accounts for a portion of worse physical performance in diabetes and may be directly associated with physical performance in older diabetic and nondiabetic adults. The impact of peripheral nerve function on incident disability should be evaluated in older adults. PMID:18535192

Balancing Model Performance and Simplicity to Predict Postoperative Primary Care Blood Pressure Elevation.

PubMed

Schonberger, Robert B; Dai, Feng; Brandt, Cynthia A; Burg, Matthew M

2015-09-01

Because of uncertainty regarding the reliability of perioperative blood pressures and traditional notions downplaying the role of anesthesiologists in longitudinal patient care, there is no consensus for anesthesiologists to recommend postoperative primary care blood pressure follow-up for patients presenting for surgery with an increased blood pressure. The decision of whom to refer should ideally be based on a predictive model that balances performance with ease-of-use. If an acceptable decision rule was developed, a new practice paradigm integrating the surgical encounter into broader public health efforts could be tested, with the goal of reducing long-term morbidity from hypertension among surgical patients. Using national data from US veterans receiving surgical care, we determined the prevalence of poorly controlled outpatient clinic blood pressures ≥140/90 mm Hg, based on the mean of up to 4 readings in the year after surgery. Four increasingly complex logistic regression models were assessed to predict this outcome. The first included the mean of 2 preoperative blood pressure readings; other models progressively added a broad array of demographic and clinical data. After internal validation, the C-statistics and the Net Reclassification Index between the simplest and most complex models were assessed. The performance characteristics of several simple blood pressure referral thresholds were then calculated. Among 215,621 patients, poorly controlled outpatient clinic blood pressure was present postoperatively in 25.7% (95% confidence interval [CI], 25.5%-25.9%) including 14.2% (95% CI, 13.9%-14.6%) of patients lacking a hypertension history. The most complex prediction model demonstrated statistically significant, but clinically marginal, improvement in discrimination over a model based on preoperative blood pressure alone (C-statistic, 0.736 [95% CI, 0.734-0.739] vs 0.721 [95% CI, 0.718-0.723]; P for difference <0.0001). The Net Reclassification Index was 0.088 (95% CI, 0.082-0.093); P < 0.0001. A preoperative blood pressure threshold ≥150/95 mm Hg, calculated as the mean of 2 readings, identified patients more likely than not to demonstrate outpatient clinic blood pressures in the hypertensive range. Four of 5 patients not meeting this criterion were indeed found to be normotensive during outpatient clinic follow-up (positive predictive value, 51.5%; 95% CI, 51.0-52.0; negative predictive value, 79.6%; 95% CI, 79.4-79.7). In a national cohort of surgical patients, poorly controlled postoperative clinic blood pressure was present in >1 of 4 patients (95% CI, 25.5%-25.9%). Predictive modeling based on the mean of 2 preoperative blood pressure measurements performed nearly as well as more complicated models and may provide acceptable predictive performance to guide postoperative referral decisions. Future studies of the feasibility and efficacy of such referrals are needed to assess possible beneficial effects on long-term cardiovascular morbidity.

Balancing Model Performance and Simplicity to Predict Postoperative Primary Care Blood Pressure Elevation

PubMed Central

Schonberger, Robert B.; Dai, Feng; Brandt, Cynthia A.; Burg, Matthew M.

2015-01-01

Background Because of uncertainty regarding the reliability of perioperative blood pressures and traditional notions downplaying the role of anesthesiologists in longitudinal patient care, there is no consensus for anesthesiologists to recommend postoperative primary care blood pressure follow-up for patients presenting for surgery with an elevated blood pressure. The decision of whom to refer should ideally be based on a predictive model that balances performance with ease-of-use. If an acceptable decision-rule were developed, a new practice paradigm integrating the surgical encounter into broader public health efforts could be tested, with the goal of reducing long-term morbidity from hypertension among surgical patients. Methods Using national data from United States veterans receiving surgical care, we determined the prevalence of poorly controlled outpatient clinic blood pressures ≥ 140/90mmHg, based on the mean of up to four readings in the year after surgery. Four increasingly complex logistic regression models were assessed to predict this outcome. The first included the mean of two preoperative blood pressure readings; other models progressively added a broad array of demographic and clinical data. After internal validation, the C-statistics and the Net Reclassification Index between the simplest and most complex models were assessed. The performance characteristics of several simple blood pressure referral thresholds were then calculated. Results Among 215,621 patients, poorly controlled outpatient clinic blood pressure was present postoperatively in 25.7% (95%CI 25.5%-25.9%) including 14.2% (95%CI 13.9%-14.6%) of patients lacking a prior hypertension history. The most complex prediction model demonstrated statistically significant, but clinically marginal, improvement in discrimination over a model based on preoperative blood pressure alone (C-statistic 0.736 (95% CI 0.734-0.739) vs 0.721 (95% CI 0.718-0.723); p for difference <0.0001). The Net Reclassification Index was 0.088 (95%CI 0.082-0.093), p < 0.0001. A preoperative blood pressure threshold ≥ 150/95mmHg, calculated as the mean of two readings, identified patients more likely than not to demonstrate outpatient clinic blood pressures in the hypertensive range. Four of five patients not meeting this criterion were indeed found to be normotensive during outpatient clinic follow-up (Positive Predictive Value 51.5%, 95% CI 51.0-52.0; Negative Predictive Value 79.6%, 95% CI 79.4-79.7). Conclusions In a national cohort of surgical patients, poorly controlled postoperative clinic blood pressure was present in more than 1 of 4 patients (95%CI 25.5%-25.9%). Predictive modeling based on the mean of two preoperative blood pressure measurements performed nearly as well as more complicated models and may provide acceptable predictive performance to guide postoperative referral decisions. Future studies of the feasibility and efficacy of such referrals are needed to assess possible beneficial effects on long-term cardiovascular morbidity. PMID:26214552

Improving regression-model-based streamwater constituent load estimates derived from serially correlated data

USGS Publications Warehouse

Aulenbach, Brent T.

2013-01-01

A regression-model based approach is a commonly used, efficient method for estimating streamwater constituent load when there is a relationship between streamwater constituent concentration and continuous variables such as streamwater discharge, season and time. A subsetting experiment using a 30-year dataset of daily suspended sediment observations from the Mississippi River at Thebes, Illinois, was performed to determine optimal sampling frequency, model calibration period length, and regression model methodology, as well as to determine the effect of serial correlation of model residuals on load estimate precision. Two regression-based methods were used to estimate streamwater loads, the Adjusted Maximum Likelihood Estimator (AMLE), and the composite method, a hybrid load estimation approach. While both methods accurately and precisely estimated loads at the model’s calibration period time scale, precisions were progressively worse at shorter reporting periods, from annually to monthly. Serial correlation in model residuals resulted in observed AMLE precision to be significantly worse than the model calculated standard errors of prediction. The composite method effectively improved upon AMLE loads for shorter reporting periods, but required a sampling interval of at least 15-days or shorter, when the serial correlations in the observed load residuals were greater than 0.15. AMLE precision was better at shorter sampling intervals and when using the shortest model calibration periods, such that the regression models better fit the temporal changes in the concentration–discharge relationship. The models with the largest errors typically had poor high flow sampling coverage resulting in unrepresentative models. Increasing sampling frequency and/or targeted high flow sampling are more efficient approaches to ensure sufficient sampling and to avoid poorly performing models, than increasing calibration period length.

Floating lipid beads for the improvement of bioavailability of poorly soluble basic drugs: in-vitro optimization and in-vivo performance in humans.

PubMed

Abouelatta, Samar M; Aboelwafa, Ahmed A; Khalil, Rawia M; ElGazayerly, Omaima N

2015-01-01

The challenge in developing oral drug delivery systems of poorly soluble basic drugs is primarily due to their pH dependent solubility. Cinnarizine (CNZ), a model for a poorly soluble basic drug, has pH dependent solubility; where it dissolves readily at low pH in the stomach and exhibits a very low solubility at pH values greater than 4. It is also characterized by a short half life of 3-6h, which requires frequent daily administration resulting in poor patient compliance. In an attempt to solve these problems, extended release floating lipid beads were formulated. A 2(4) full factorial design was utilized for optimization of the effects of various independent variables; lipid:drug ratio, % Pluronic F-127, % Sterotex, and Gelucire 43/01:Gelucire 50/13 ratio, on the loading efficiency and release of CNZ from the lipid beads. In-vivo pharmacokinetic study of the optimized CNZ-lipid beads compared to Stugeron® (reference standard) was performed in healthy human volunteers. A promising approach for enhancing the bioavailability of the poorly soluble basic drug, CNZ, utilizing novel and simple floating lipid beads was successfully developed. Zero order release profile of CNZ was achieved for 12h. Mean AUC0-24 and AUC0-∞ of the optimized CNZ-loaded lipid beads were 4.23 and 6.04 times that of Stugeron® tablets respectively. Copyright © 2014 Elsevier B.V. All rights reserved.

The impact of ethnicity and self-reported health on psychological well-being: a comparative study of Kurdish-born and Swedish-born people.

PubMed

Taloyan, Marina; Sundquist, Jan; Al-Windi, Ahmad

2008-01-01

Although immigrants generally have poorer health and higher psychological distress than the native population, information on Kurdish immigrants' psychological well-being is limited. The aims of the study were to examine the association between ethnicity and poor psychological well-being, and to assess the relationships between socio-demographic characteristics, self-reported health, somatic pain, gastrointestinal complaints and poor psychological well-being. Immigrants with self-reported Kurdish ethnicity (men, n=111; women, n=86) in Sweden from the national sample of immigrants aged 27-60 and 1407 Swedes (1996) were studied. Unconditional logistic regression was performed using the Stata Software program. In the logistic model adjusted for age, sex, employment and self-reported health, the odds ratio for Kurdish-born subjects for having poor psychological well-being is twice as high as for Swedish-born subjects. Subjects with poor self-reported health had more than a threefold higher odds ratio for having poor psychological well-being compared with those with good self-reported health. Furthermore, being female, having somatic pain and recurrent gastrointestinal complaints regardless of ethnicity increased the odds for having poor psychological well-being. Being Kurdish-born and/or reporting poor health in addition to age, female gender, somatic pain and recurrent gastrointestinal complaints is significantly and independently related to poor psychological well-being even when adjusted for all confounders.

Teamwork and Literacy: Learning from a Skills-Poor Position.

ERIC Educational Resources Information Center

Hart-Landsberg, Sylvia; Reder, Stephen

A study examined the roles of literacy and teamwork in an automotive parts manufacturing company that was restructuring to implement a "high-performance" model of team organization, worker responsibility for quality control, and a pay-for-knowledge compensation system. The study focused on the formal and informal educational practices from which…

Owned vertical integration and health care: promise and performance.

PubMed

Walston, S L; Kimberly, J R; Burns, L R

1996-01-01

This article examines the alleged benefits and actual outcomes of vertical integration in the health sector and compares them to those observed in other sectors of the economy. This article concludes that the organizational models on which these arrangements are based may be poorly adapted to the current environment in health care.

The relationship between corporate environmental performance and environmental disclosure: an empirical study in China.

PubMed

Meng, X H; Zeng, S X; Shi, Jonathan J; Qi, G Y; Zhang, Z B

2014-12-01

Based on a content analysis of 533 Chinese listed companies, this study examines how corporate environmental performance affects not only the level of detail of a company's environmental disclosures, but also what information is disclosed. The results show that (1) both poor and good performers have more disclosure than the median (i.e., "mixed") performers, which provides empirical evidence to support a nonlinear relationship between corporate environmental performance and environmental disclosure; (2) poor performers disclose more soft information on environmental performance than good performers, and good performers disclose more solid information; and (3) although poor performers increase disclosure after being exposed as environmental violators, they avoid disclosing negative environmental information, such as the violation and the associated penalties. This study provides additional evidence for a nonlinear relationship between environmental performance and disclosure in emerging markets, and suggests environmental disclosure may not be a valid signal to differentiate good performers from poor performers in contemporary China. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structural adaptations to diverse fighting styles in sexually selected weapons

PubMed Central

McCullough, Erin L.; Tobalske, Bret W.; Emlen, Douglas J.

2014-01-01

The shapes of sexually selected weapons differ widely among species, but the drivers of this diversity remain poorly understood. Existing explanations suggest weapon shapes reflect structural adaptations to different fighting styles, yet explicit tests of this hypothesis are lacking. We constructed finite element models of the horns of different rhinoceros beetle species to test whether functional specializations for increased performance under species-specific fighting styles could have contributed to the diversification of weapon form. We find that horns are both stronger and stiffer in response to species-typical fighting loads and that they perform more poorly under atypical fighting loads, which suggests weapons are structurally adapted to meet the functional demands of fighting. Our research establishes a critical link between weapon form and function, revealing one way male–male competition can drive the diversification of animal weapons. PMID:25201949

Structural adaptations to diverse fighting styles in sexually selected weapons.

PubMed

McCullough, Erin L; Tobalske, Bret W; Emlen, Douglas J

2014-10-07

The shapes of sexually selected weapons differ widely among species, but the drivers of this diversity remain poorly understood. Existing explanations suggest weapon shapes reflect structural adaptations to different fighting styles, yet explicit tests of this hypothesis are lacking. We constructed finite element models of the horns of different rhinoceros beetle species to test whether functional specializations for increased performance under species-specific fighting styles could have contributed to the diversification of weapon form. We find that horns are both stronger and stiffer in response to species-typical fighting loads and that they perform more poorly under atypical fighting loads, which suggests weapons are structurally adapted to meet the functional demands of fighting. Our research establishes a critical link between weapon form and function, revealing one way male-male competition can drive the diversification of animal weapons.

Children's comprehension skill and the understanding of nominal metaphors.

PubMed

Seigneuric, Alix; Megherbi, Hakima; Bueno, Steve; Lebahar, Julie; Bianco, Maryse

2016-10-01

According to Levorato and Cacciari's global elaboration model, understanding figurative language is explained by the same processes and background knowledge that are required for literal language. In this study, we investigated the relation between children's comprehension skill and the ability to understand referential nominal metaphors. Two groups of poor versus good comprehenders (8- to 10-year-olds) matched for word reading and vocabulary skills were invited to identify the referent of nouns used metaphorically or literally in short texts. Compared with good comprehenders, performance of poor comprehenders showed a substantial decrease in the metaphoric condition. Moreover, their performance was strongly affected by the degree of semantic incongruence between the terms of the nominal metaphor. These findings are discussed in relation to several factors, in particular the ability to use contextual information and semantic processing. Copyright © 2016 Elsevier Inc. All rights reserved.

Regulated compensated donation in Pakistan and Iran.

PubMed

Rizvi, Adibul Hasan S; Naqvi, Anwar S A; Zafar, Naqi M; Ahmed, Ejaz

2009-04-01

Paid living unrelated kidney donor transplantation has flourished in Pakistan and Iran. This review discusses the dynamics and consequences of organ trade in Pakistan and of a regulated paid donor model in Iran on transplant activities in these countries. In 2007, over 2500 renal transplants were performed in Pakistan, where more than 70% were from socioeconomic disadvantaged kidney vendors. More than half of recipients were foreigners who paid US$20,000-30,000. Recipients of vendor kidneys had poor outcome and high infectious complications. Regulated paid donor kidney transplant in Iran number around 1500 per year and constitute 70% of the total transplants. Graft survival rates are similar to those for living related donors. The donors are paid US$1200 and additional monies are negotiated between the recipient-donor pair. This model claims to have abolished waiting lists, although many poor patients wait for deceased donors. In both countries, recipients are relatively rich and vendors are the poor of the society who sell kidneys for quick money or to repay debts. Paid donation, regulated or commercial, leads to coercion and exploitation of the poor and benefits the rich. This situation has forestalled deceased donor program and hence other solid-organ transplants. The way forward is to promote deceased donors by making transplant available to all who need it.

Potential role of combined FDG PET/CT & contrast enhancement MRI in a rectal carcinoma model with nodal metastases characterized by a poor FDG-avidity.

PubMed

Farace, Paolo; Conti, Giamaica; Merigo, Flavia; Tambalo, Stefano; Marzola, Pasquina; Sbarbati, Andrea; Quarta, Carmelo; D'Ambrosio, Daniela; Chondrogiannis, Sotirios; Nanni, Cristina; Rubello, Domenico

2012-04-01

To investigate the additional role of MRI contrast enhancement (CE) in the primary tumor and the FDG uptake at PET in the lymph-node metastases. A model of colorectal cancer induced by orthotopic HT-29 cells microinjection, producing pelvic lymph node metastases, was assessed using CE-MRI and FDG-PET. Histology and GLUT-1 immunohistochemistry were performed on primary tumors and iliac lymph nodes. Primary tumors were characterized by low FDG-uptake but high CE-MRI, particularly at tumor periphery. Undetectable FDG-uptake characterized the metastatic lymph-nodes. Histology revealed large stromal bundles at tumor periphery and a dense network of stromal fibers and neoplastic cells in the inner portion of the tumors. Both primary tumors and positive lymph nodes showed poor GLUT-1 staining. Our data support the complementary role of MRI-CE and FDG PET in some types of carcinomas characterized by abundant cancer-associated stroma and poor FDG avidity consequent to poor GLUT-1 transported. In these tumors FDG-PET alone may be not completely adequate to obtain an adequate tumor radiotherapy planning, and a combination with dual CE-MRI is strongly recommended. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Computational assessment of press-fit acetabular implant fixation: the effect of implant design, interference fit, bone quality, and frictional properties.

PubMed

Janssen, D; Zwartelé, R E; Doets, H C; Verdonschot, N

2010-01-01

Patients suffering from rheumatoid arthritis typically have a poor subchondral bone quality, endangering implant fixation. Using finite element analysis (FEA) an investigation was made to find whether a press-fit acetabular implant with a polar clearance would reduce interfacial micromotions and improve fixation compared with a standard hemispherical design. In addition, the effects of interference fit, friction, and implant material were analysed. Cups were introduced into an FEA model of a human pelvis with simulated subchondral bone plasticity. The models were loaded with a loading configuration simulating two cycles of normal walking, during which contact stresses and interfacial micromotions were monitored. Subsequently, a lever-out simulation was performed to assess the fixation strength of the various cases. A flattened cup with good bone quality produced the lowest interfacial micromotions. Poor bone decreased the fixation strength regardless of the geometry of the cup. Increasing the interference fit of the flattened cup compensated for the loss of fixation strength caused by poor bone quality. In conclusion, a flattened cup did not significantly improve implant fixation over a hemispherical cup in the case of poor bone quality. However, implant fixation can be optimized by increasing interference fit and avoiding inferior frictional properties and low-stiffness implants.

Determining team cognition from delay analysis using cross recurrence plot.

PubMed

Hajari, Nasim; Cheng, Irene; Bin Zheng; Basu, Anup

2016-08-01

Team cognition is an important factor in evaluating and determining team performance. Forming a team with good shared cognition is even more crucial for laparoscopic surgery applications. In this study, we analyzed the eye tracking data of two surgeons during a laparoscopic simulation operation, then performed Cross Recurrence Analysis (CRA) on the recorded data to study the delay behaviour for good performer and poor performer teams. Dual eye tracking data for twenty two dyad teams were recorded during a laparoscopic task and then the teams were divided into good performer and poor performer teams based on the task times. Eventually we studied the delay between two team members for good and poor performer teams. The results indicated that the good performer teams show a smaller delay comparing to poor performer teams. This study is compatible with gaze overlap analysis between team members and therefore it is a good evidence of shared cognition between team members.

Adaptation of a Biomarker-Based Sepsis Mortality Risk Stratification Tool for Pediatric Acute Respiratory Distress Syndrome.

PubMed

Yehya, Nadir; Wong, Hector R

2018-01-01

The original Pediatric Sepsis Biomarker Risk Model and revised (Pediatric Sepsis Biomarker Risk Model-II) biomarker-based risk prediction models have demonstrated utility for estimating baseline 28-day mortality risk in pediatric sepsis. Given the paucity of prediction tools in pediatric acute respiratory distress syndrome, and given the overlapping pathophysiology between sepsis and acute respiratory distress syndrome, we tested the utility of Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II for mortality prediction in a cohort of pediatric acute respiratory distress syndrome, with an a priori plan to revise the model if these existing models performed poorly. Prospective observational cohort study. University affiliated PICU. Mechanically ventilated children with acute respiratory distress syndrome. Blood collection within 24 hours of acute respiratory distress syndrome onset and biomarker measurements. In 152 children with acute respiratory distress syndrome, Pediatric Sepsis Biomarker Risk Model performed poorly and Pediatric Sepsis Biomarker Risk Model-II performed modestly (areas under receiver operating characteristic curve of 0.61 and 0.76, respectively). Therefore, we randomly selected 80% of the cohort (n = 122) to rederive a risk prediction model for pediatric acute respiratory distress syndrome. We used classification and regression tree methodology, considering the Pediatric Sepsis Biomarker Risk Model biomarkers in addition to variables relevant to acute respiratory distress syndrome. The final model was comprised of three biomarkers and age, and more accurately estimated baseline mortality risk (area under receiver operating characteristic curve 0.85, p < 0.001 and p = 0.053 compared with Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II, respectively). The model was tested in the remaining 20% of subjects (n = 30) and demonstrated similar test characteristics. A validated, biomarker-based risk stratification tool designed for pediatric sepsis was adapted for use in pediatric acute respiratory distress syndrome. The newly derived Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model demonstrates good test characteristics internally and requires external validation in a larger cohort. Tools such as Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model have the potential to provide improved risk stratification and prognostic enrichment for future trials in pediatric acute respiratory distress syndrome.

A priori testing of subgrid-scale models for large-eddy simulation of the atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Juneja, Anurag; Brasseur, James G.

1996-11-01

Subgrid-scale models are generally developed assuming homogeneous isotropic turbulence with the filter cutoff lying in the inertial range. In the surface layer and capping inversion regions of the atmospheric boundary layer, the turbulence is strongly anisotropic and, in general, influenced by both buoyancy and shear. Furthermore, the integral scale motions are under-resolved in these regions. Herein we perform direct numerical simulations of shear and buoyancy-generated homogeneous anisotropic turbulence to compute and analyze the actual subgrid-resolved-scale (SGS-RS) dynamics as the filter cutoff moves into the energy-containing scales. These are compared with the SGS-RS dynamics predicted by Smagorinsky-based models with a focus on motivating improved closures. We find that, in general, the underlying assumption of such models, that the anisotropic part of the subgrid stress tensor be aligned with the resolved strain rate tensor, is a poor approximation. Similarly, we find poor alignment between the actual and predicted stress divergence, and find low correlations between the actual and modeled subgrid-scale contribution to the pressure and pressure gradient. Details will be given in the talk.

Stratospheric wind errors, initial states and forecast skill in the GLAS general circulation model

NASA Technical Reports Server (NTRS)

Tenenbaum, J.

1983-01-01

Relations between stratospheric wind errors, initial states and 500 mb skill are investigated using the GLAS general circulation model initialized with FGGE data. Erroneous stratospheric winds are seen in all current general circulation models, appearing also as weak shear above the subtropical jet and as cold polar stratospheres. In this study it is shown that the more anticyclonic large-scale flows are correlated with large forecast stratospheric winds. In addition, it is found that for North America the resulting errors are correlated with initial state jet stream accelerations while for East Asia the forecast winds are correlated with initial state jet strength. Using 500 mb skill scores over Europe at day 5 to measure forecast performance, it is found that both poor forecast skill and excessive stratospheric winds are correlated with more anticyclonic large-scale flows over North America. It is hypothesized that the resulting erroneous kinetic energy contributes to the poor forecast skill, and that the problem is caused by a failure in the modeling of the stratospheric energy cycle in current general circulation models independent of vertical resolution.

On the predictability of land surface fluxes from meteorological variables

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.

2018-01-01

Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appear to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that are used by LSMs for predicting land surface fluxes, by interrogating FLUXNET data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, with no explicit vegetation or soil properties, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We reanalyse previously published LSM simulations and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

The association of neighbourhood and individual social capital with consistent self-rated health: a longitudinal study in Brazilian pregnant and postpartum women

PubMed Central

2013-01-01

Background Social conditions, social relationships and neighbourhood environment, the components of social capital, are important determinants of health. The objective of this study was to investigate the association of neighbourhood and individual social capital with consistent self-rated health in women between the first trimester of pregnancy and six months postpartum. Methods A multilevel cohort study in 34 neighbourhoods was performed on 685 Brazilian women recruited at antenatal units in two cities in the State of Rio de Janeiro, Brazil. Self-rated health (SRH) was assessed in the 1st trimester of pregnancy (baseline) and six months after childbirth (follow-up). The participants were divided into two groups: 1. Good SRH – good SRH at baseline and follow-up, and, 2. Poor SRH – poor SRH at baseline and follow-up. Exploratory variables collected at baseline included neighbourhood social capital (neighbourhood-level variable), individual social capital (social support and social networks), demographic and socioeconomic characteristics, health-related behaviours and self-reported diseases. A hierarchical binomial multilevel analysis was performed to test the association between neighbourhood and individual social capital and SRH, adjusted for covariates. Results The Good SRH group reported higher scores of social support and social networks than the Poor SRH group. Although low neighbourhood social capital was associated with poor SRH in crude analysis, the association was not significant when individual socio-demographic variables were included in the model. In the final model, women reporting poor SRH both at baseline and follow-up had lower levels of social support (positive social interaction) [OR 0.82 (95% CI: 0.73-0.90)] and a lower likelihood of friendship social networks [OR 0.61 (95% CI: 0.37-0.99)] than the Good SRH group. The characteristics that remained associated with poor SRH were low level of schooling, Black and Brown ethnicity, more children, urinary infection and water plumbing outside the house. Conclusions Low individual social capital during pregnancy, considered here as social support and social network, was independently associated with poor SRH in women whereas neighbourhood social capital did not affect women’s SRH during pregnancy and the months thereafter. From pregnancy and up to six months postpartum, the effect of individual social capital explained better the consistency of SRH over time than neighbourhood social capital. PMID:23324161

The association of neighbourhood and individual social capital with consistent self-rated health: a longitudinal study in Brazilian pregnant and postpartum women.

PubMed

Lamarca, Gabriela A; do C Leal, Maria; Sheiham, Aubrey; Vettore, Mario V

2013-01-16

Social conditions, social relationships and neighbourhood environment, the components of social capital, are important determinants of health. The objective of this study was to investigate the association of neighbourhood and individual social capital with consistent self-rated health in women between the first trimester of pregnancy and six months postpartum. A multilevel cohort study in 34 neighbourhoods was performed on 685 Brazilian women recruited at antenatal units in two cities in the State of Rio de Janeiro, Brazil. Self-rated health (SRH) was assessed in the 1st trimester of pregnancy (baseline) and six months after childbirth (follow-up). The participants were divided into two groups: 1. Good SRH--good SRH at baseline and follow-up, and, 2. Poor SRH--poor SRH at baseline and follow-up. Exploratory variables collected at baseline included neighbourhood social capital (neighbourhood-level variable), individual social capital (social support and social networks), demographic and socioeconomic characteristics, health-related behaviours and self-reported diseases. A hierarchical binomial multilevel analysis was performed to test the association between neighbourhood and individual social capital and SRH, adjusted for covariates. The Good SRH group reported higher scores of social support and social networks than the Poor SRH group. Although low neighbourhood social capital was associated with poor SRH in crude analysis, the association was not significant when individual socio-demographic variables were included in the model. In the final model, women reporting poor SRH both at baseline and follow-up had lower levels of social support (positive social interaction) [OR 0.82 (95% CI: 0.73-0.90)] and a lower likelihood of friendship social networks [OR 0.61 (95% CI: 0.37-0.99)] than the Good SRH group. The characteristics that remained associated with poor SRH were low level of schooling, Black and Brown ethnicity, more children, urinary infection and water plumbing outside the house. Low individual social capital during pregnancy, considered here as social support and social network, was independently associated with poor SRH in women whereas neighbourhood social capital did not affect women's SRH during pregnancy and the months thereafter. From pregnancy and up to six months postpartum, the effect of individual social capital explained better the consistency of SRH over time than neighbourhood social capital.

A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools

PubMed Central

2012-01-01

Background We introduce the linguistic annotation of a corpus of 97 full-text biomedical publications, known as the Colorado Richly Annotated Full Text (CRAFT) corpus. We further assess the performance of existing tools for performing sentence splitting, tokenization, syntactic parsing, and named entity recognition on this corpus. Results Many biomedical natural language processing systems demonstrated large differences between their previously published results and their performance on the CRAFT corpus when tested with the publicly available models or rule sets. Trainable systems differed widely with respect to their ability to build high-performing models based on this data. Conclusions The finding that some systems were able to train high-performing models based on this corpus is additional evidence, beyond high inter-annotator agreement, that the quality of the CRAFT corpus is high. The overall poor performance of various systems indicates that considerable work needs to be done to enable natural language processing systems to work well when the input is full-text journal articles. The CRAFT corpus provides a valuable resource to the biomedical natural language processing community for evaluation and training of new models for biomedical full text publications. PMID:22901054

Early detection of poor adherers to statins: applying individualized surveillance to pay for performance.

PubMed

Zimolzak, Andrew J; Spettell, Claire M; Fernandes, Joaquim; Fusaro, Vincent A; Palmer, Nathan P; Saria, Suchi; Kohane, Isaac S; Jonikas, Magdalena A; Mandl, Kenneth D

2013-01-01

Medication nonadherence costs $300 billion annually in the US. Medicare Advantage plans have a financial incentive to increase medication adherence among members because the Centers for Medicare and Medicaid Services (CMS) now awards substantive bonus payments to such plans, based in part on population adherence to chronic medications. We sought to build an individualized surveillance model that detects early which beneficiaries will fall below the CMS adherence threshold. This was a retrospective study of over 210,000 beneficiaries initiating statins, in a database of private insurance claims, from 2008-2011. A logistic regression model was constructed to use statin adherence from initiation to day 90 to predict beneficiaries who would not meet the CMS measure of proportion of days covered 0.8 or above, from day 91 to 365. The model controlled for 15 additional characteristics. In a sensitivity analysis, we varied the number of days of adherence data used for prediction. Lower adherence in the first 90 days was the strongest predictor of one-year nonadherence, with an odds ratio of 25.0 (95% confidence interval 23.7-26.5) for poor adherence at one year. The model had an area under the receiver operating characteristic curve of 0.80. Sensitivity analysis revealed that predictions of comparable accuracy could be made only 40 days after statin initiation. When members with 30-day supplies for their first statin fill had predictions made at 40 days, and members with 90-day supplies for their first fill had predictions made at 100 days, poor adherence could be predicted with 86% positive predictive value. To preserve their Medicare Star ratings, plan managers should identify or develop effective programs to improve adherence. An individualized surveillance approach can be used to target members who would most benefit, recognizing the tradeoff between improved model performance over time and the advantage of earlier detection.

Prognostic indicators of poor short-term outcome of physiotherapy intervention in women with stress urinary incontinence.

PubMed

Hendriks, Erik J M; Kessels, Alfons G H; de Vet, Henrica C W; Bernards, Arnold T M; de Bie, Rob A

2010-03-01

To identify prognostic indicators independently associated with poor outcome of physiotherapy intervention in women with primary or recurrent stress urinary incontinence (stress UI). A prospective cohort study was performed in physiotherapy practices in primary care to identify prognostic indicators 12 weeks after initiation of physiotherapy intervention. Patients were referred by general practitioners or urogynecologists. Risk factors for stress UI were examined as potential prognostic indicators of poor outcome. The primary outcomes were defined as poor outcome on the binary Leakage Severity scale (LS scale) and the binary global perceived effectiveness (GPE) score. Two hundred sixty-seven women, with a mean age of 47.7 (SD = 8.3), with stress UI for at least 6 months were included. At 12 weeks, 43% and 59% of the women were considered recovered on the binary LS scale and the binary GPE score, respectively. Prognostic indicators associated with poor outcome included 11 indicators based on the binary LS scale and 8 based on the binary GPE score. The prognostic indicators shared by both models show that poor recovery was associated with women with severe stress UI, POP-Q stage > II, poor outcome of physiotherapy intervention for a previous UI episode, prolonged second stage of labor, BMI > 30, high psychological distress, and poor physical health. This study provides robust evidence of clinically meaningful prognostic indicators of poor short-term outcome. These findings need to be confirmed by replication studies. (c) 2009 Wiley-Liss, Inc.

An investigation of the measurement properties of the Spot-the-Word test in a community sample.

PubMed

Mackinnon, Andrew; Christensen, Helen

2007-12-01

Intellectual ability is assessed with the Spot-the-Word (STW) test (A. Baddeley, H. Emslie, & I. Nimmo Smith, 1993) by asking respondents to identify a word in a word-nonword item pair. Results in moderate-sized samples suggest this ability is resistant to decline due to dementia. The authors used a 3-parameter item response theory model to investigate the measurement properties of the STW in a large community-dwelling sample (n=2,480) 60 to 64 years of age. A number of poorly performing items were identified. Substantial guessing was present; however, the number of words correctly identified was found to be an accurate index of ability. Performance was moderately related to a number of tests of cognitive performance and was effectively unrelated to visual acuity and to physical or mental health status. The STW is a promising test of ability that, in the future, may be refined by the deletion or replacement of poorly functioning items.

Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

NASA Astrophysics Data System (ADS)

Jothiprakash, V.; Magar, R. B.

2012-07-01

SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

Metabolic syndrome correlates poorly with cognitive performance in stroke-free community-dwelling older adults: a population-based, cross-sectional study in rural Ecuador.

PubMed

Del Brutto, Oscar H; Mera, Robertino M; Zambrano, Mauricio

2016-04-01

Studies investigating a possible correlation between metabolic syndrome and cognitive decline have been inconsistent. To determine whether metabolic syndrome or each of its components correlate with cognitive performance in community-dwelling older adults in rural Ecuador. Stroke-free Atahualpa residents aged ≥60 years were identified during a door-to-door survey. Metabolic syndrome was defined according to the International Diabetes Federation criteria. Cognition was evaluated by the use of the Montreal Cognitive Assessment (MoCA). Multivariate logistic regression models estimated the association between metabolic syndrome and each of its components with cognitive performance. A total of 212 persons (mean age: 69.2 ± 7.2 years, 64 % women) were enrolled. Of these, 120 (57 %) had metabolic syndrome. Mean scores in the MoCA were 18.2 ± 4.6 for persons with and 19 ± 4.7 for those without metabolic syndrome. In fully adjusted logistic models, MoCA scores were not associated with metabolic syndrome (p = 0.101). After testing individual components of metabolic syndrome with the MoCA score, we found that only hypertriglyceridemia was independently associated with the MoCA score (p = 0.009). This population-based study showed a poor correlation of metabolic syndrome with cognitive performance after adjusting for relevant confounders. Of the individual components of metabolic syndrome, only hypertriglyceridemia correlated with worse cognitive performance.

Association of tic disorders with poor academic performance in central Spain: a population-based study.

PubMed

Cubo, Esther; Trejo, José; Ausín, Vanesa; Sáez, Sara; Delgado, Vanesa; Macarrón, Jesus; Cordero, José; Louis, Elan D; Kompoliti, Katie; Benito-León, Julián

2013-07-01

To analyze the association between tic disorders and poor academic performance in school-aged children. This was a cross-sectional, observational study conducted in a randomly selected sample of mainstream school-aged children (aged 6-16 years). The sampling frame included different types of schools and educational levels. Children with poor academic performance (eg, repeating a grade, special needs), and tic disorders (defined based on Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision criteria) were identified. Children with and without tics and children with and without poor academic performance were compared in terms of clinical features (ie, medical history and neurologic and psychiatric comorbidities), school, and environmental characteristics. Logistic regression analyses were performed using school performance (dependent variable) and tic disorders (independent variable), after adjusting for confounding variables. The study cohort comprised 1867 children (mean age, 10.9 + 2.9 years; 1007 males [53.9%]). Tics were present in 162 children (8.6%), and poor academic performance was noted in 223 (11.9%). Overall poor academic performance was associated with age (OR, 1.71; P < .0001), television viewing (OR, 5.33; P = .04), attention deficit hyperactivity disorder (OR, 1.38; P < .0001), and family history of school dysfunction (OR, 2.43; P = .02) and was negatively associated with higher IQ score (OR, 0.90; P < .0001) and tic disorders (OR, 0.29; P = .01). After adjusting for other covariates, the presence of tic disorders was not associated with poor academic performance in our cohort. Early academic support and modification of environmental characteristics are needed for children at higher risk for school dysfunction, to enhance academic performance. Copyright © 2013 Mosby, Inc. All rights reserved.

Poor Performance in Mathematics: Is There a Basis for a Self-Worth Explanation for Women?

ERIC Educational Resources Information Center

Thompson, Ted; Dinnel, Dale L.

2007-01-01

The self-worth theory of achievement motivation holds that in situations in which poor performance is likely to reveal low ability, certain students (known as self-worth protective students) intentionally withdraw effort in order to avoid the negative implications of poor performance in terms of damage to self-worth. In this study, evidence of…

Who Are the Low-Performing Students? PISA in Focus. No. 60

ERIC Educational Resources Information Center

OECD Publishing, 2016

2016-01-01

Far too many students around the world are trapped in a vicious cycle of poor performance and demotivation that leads only to more bad marks and further disengagement from school. Students who perform poorly at age 15 face a high risk of dropping out of school altogether. By the time they become young adults, poor proficiency in numeracy and…

Physical activity and cohabitation status moderate the link between diabetes mellitus and cognitive performance in a community-dwelling elderly population in Germany

PubMed Central

Buchmann, Nikolaus; Tegeler, Christina; Steinhagen-Thiessen, Elisabeth

2017-01-01

Aims/Hypothesis The increasing number of people with dementia and cognitive impairments makes it essential to detect and prevent modifiable risk factors of dementia. This study focuses on type 2 diabetes mellitus, especially on undiagnosed cases and their increased risk of cognitive impairment. Furthermore, the potential of physical activity and social integration to moderate the relation between diabetes and cognitive impairment is assessed. Methods We used cross-sectional data from 1299 participants of the Berlin Aging Study II (BASE-II) aged between 60 to 84 years and performed logistic regression models to analyze the association of diabetes status, physical activity, and cohabitation status with poor cognitive performance. Cognitive performance was measured with the Consortium to Establish a Registry for Alzheimer's Disease (CERAD)-Plus test battery. Results Undiagnosed diabetes (odds ratio (OR) = 2.12, p = 0.031), physical inactivity (OR = 1.43, p = 0.008) and non-cohabiting (OR = 1.58, p = 0.002) were associated with an increased likelihood of poor cognitive performance. The highest odds were observed in participants who suffered from undiagnosed or insulin-dependent diabetes and, in addition, were inactive (undiagnosed diabetes: OR = 3.44, p = 0.003; insulin-dependent diabetes: OR = 6.19, p = 0.019) or lived alone (undiagnosed diabetes: OR = 4.46, p = 0.006; insulin-dependent diabetes: OR = 6.46 p = 0.052). Physical activity and cohabiting appeared to be beneficial. Conclusions/Interpretation Physical activity and cohabitation status moderate the link between diabetes mellitus and cognitive performance. Special attention should be paid to undiagnosed and insulin-dependent diabetes cases, which have a particularly high risk of poor cognitive performance. PMID:29073237

Violence exposure, sleep disturbance, and poor academic performance in middle school.

PubMed

Lepore, Stephen J; Kliewer, Wendy

2013-11-01

Violence has been linked to poor academic outcomes in youth, but there is little understanding of the mechanisms underlying this relation. This longitudinal survey study investigated whether sleep disturbance potentially mediates the associations between academic achievement and two forms of violence exposure--community violence and peer victimization-- in 498 seventh-grade youth. Structural equation models showed that community violence was associated with lower grade point average (GPA) directly and indirectly via sleep problems, whereas peer victimization was associated with lower GPA just indirectly via sleep problems. The structural models controlled for potential confounds, including depressive symptoms, intrusive thoughts and absenteeism. The findings suggest that failing grades and sleepiness in school may be signs that youth are exposed to violence. Interventions to improve sleep hygiene and reduce violence exposure may help to improve academic outcomes for youth.

Advancing land surface model development with satellite-based Earth observations

NASA Astrophysics Data System (ADS)

Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

2017-04-01

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

Users matter : multi-agent systems model of high performance computing cluster users.

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

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

Design of maintainable drains for earth retaining structures : final report and design guide.

DOT National Transportation Integrated Search

2017-04-01

Poor drainage is by far the most common cause of poor performance for earth retention systems. Poor performance includes burdensome serviceability problems that can progress to outright failure of the earth retention system if not addressed. : A comm...

Comparison of APACHE III, APACHE IV, SAPS 3, and MPM0III and Influence of Resuscitation Status on Model Performance

PubMed Central

Gajic, Ognjen; Afessa, Bekele

2012-01-01

Background: There are few comparisons among the most recent versions of the major adult ICU prognostic systems (APACHE [Acute Physiology and Chronic Health Evaluation] IV, Simplified Acute Physiology Score [SAPS] 3, Mortality Probability Model [MPM]0III). Only MPM0III includes resuscitation status as a predictor. Methods: We assessed the discrimination, calibration, and overall performance of the models in 2,596 patients in three ICUs at our tertiary referral center in 2006. For APACHE and SAPS, the analyses were repeated with and without inclusion of resuscitation status as a predictor variable. Results: Of the 2,596 patients studied, 283 (10.9%) died before hospital discharge. The areas under the curve (95% CI) of the models for prediction of hospital mortality were 0.868 (0.854-0.880), 0.861 (0.847-0.874), 0.801 (0.785-0.816), and 0.721 (0.704-0.738) for APACHE III, APACHE IV, SAPS 3, and MPM0III, respectively. The Hosmer-Lemeshow statistics for the models were 33.7, 31.0, 36.6, and 21.8 for APACHE III, APACHE IV, SAPS 3, and MPM0III, respectively. Each of the Hosmer-Lemeshow statistics generated P values < .05, indicating poor calibration. Brier scores for the models were 0.0771, 0.0749, 0.0890, and 0.0932, respectively. There were no significant differences between the discriminative ability or the calibration of APACHE or SAPS with and without “do not resuscitate” status. Conclusions: APACHE III and IV had similar discriminatory capability and both were better than SAPS 3, which was better than MPM0III. The calibrations of the models studied were poor. Overall, models with more predictor variables performed better than those with fewer. The addition of resuscitation status did not improve APACHE III or IV or SAPS 3 prediction. PMID:22499827

Hindcasting of decadal‐timescale estuarine bathymetric change with a tidal‐timescale model

USGS Publications Warehouse

Ganju, Neil K.; Schoellhamer, David H.; Jaffe, Bruce E.

2009-01-01

Hindcasting decadal-timescale bathymetric change in estuaries is prone to error due to limited data for initial conditions, boundary forcing, and calibration; computational limitations further hinder efforts. We developed and calibrated a tidal-timescale model to bathymetric change in Suisun Bay, California, over the 1867–1887 period. A general, multiple-timescale calibration ensured robustness over all timescales; two input reduction methods, the morphological hydrograph and the morphological acceleration factor, were applied at the decadal timescale. The model was calibrated to net bathymetric change in the entire basin; average error for bathymetric change over individual depth ranges was 37%. On a model cell-by-cell basis, performance for spatial amplitude correlation was poor over the majority of the domain, though spatial phase correlation was better, with 61% of the domain correctly indicated as erosional or depositional. Poor agreement was likely caused by the specification of initial bed composition, which was unknown during the 1867–1887 period. Cross-sectional bathymetric change between channels and flats, driven primarily by wind wave resuspension, was modeled with higher skill than longitudinal change, which is driven in part by gravitational circulation. The accelerated response of depth may have prevented gravitational circulation from being represented properly. As performance criteria became more stringent in a spatial sense, the error of the model increased. While these methods are useful for estimating basin-scale sedimentation changes, they may not be suitable for predicting specific locations of erosion or deposition. They do, however, provide a foundation for realistic estuarine geomorphic modeling applications.

Development of self-control in children aged 3 to 9 years: Perspective from a dual-systems model

PubMed Central

Tao, Ting; Wang, Ligang; Fan, Chunlei; Gao, Wenbin

2014-01-01

The current study tested a set of interrelated theoretical propositions based on a dual-systems model of self-control. Data were collected from 2135 children aged 3 to 9 years. The results suggest that (a) there was positive growth in good self-control, whereas poor control remained relatively stable; and (b) girls performed better than boys on tests of good self-control. The results are discussed in terms of their implications for a dual-systems model of self-control theory and future empirical work. PMID:25501669

Montmorillonite-lipid hybrid carriers for ionizable and neutral poorly water-soluble drugs: Formulation, characterization and in vitro lipolysis studies.

PubMed

Dening, Tahnee J; Rao, Shasha; Thomas, Nicky; Prestidge, Clive A

2017-06-30

Lipid-based formulations (LBFs) are a popular strategy for enhancing the gastrointestinal solubilization and absorption of poorly water-soluble drugs. In light of this, montmorillonite-lipid hybrid (MLH) particles, composed of medium-chain triglycerides, lecithin and montmorillonite clay platelets, have been developed as a novel solid-state LBF. Owing to the unique charge properties of montmorillonite, whereby the clay platelet surfaces carry a permanent negative charge and the platelet edges carry a pH-dependent charge, three model poorly water-soluble drugs with different charge properties; blonanserin (weak base, pKa 7.7), ibuprofen (weak acid, pKa 4.5) and fenofibrate (neutral), were formulated as MLH particles and their performance during biorelevant in vitro lipolysis at pH 7.5 was investigated. For blonanserin, drug solubilization during in vitro lipolysis was significantly reduced 3.4-fold and 3.2-fold for MLH particles in comparison to a control lipid solution and silica-lipid hybrid (SLH) particles, respectively. It was hypothesized that strong electrostatic interactions between the anionic montmorillonite platelet surfaces and cationic blonanserin molecules were responsible for the inferior performance of MLH particles. In contrast, no significant influence on drug solubilization was observed for ibuprofen- and fenofibrate-loaded MLH particles. The results of the current study indicate that whilst MLH particles are a promising novel formulation strategy for poorly water-soluble drugs, drug ionization tendency and the potential for drug-clay interactions must be taken into consideration to ensure an appropriate performance. Copyright © 2017 Elsevier B.V. All rights reserved.

A new framework to enhance the interpretation of external validation studies of clinical prediction models.

PubMed

Debray, Thomas P A; Vergouwe, Yvonne; Koffijberg, Hendrik; Nieboer, Daan; Steyerberg, Ewout W; Moons, Karel G M

2015-03-01

It is widely acknowledged that the performance of diagnostic and prognostic prediction models should be assessed in external validation studies with independent data from "different but related" samples as compared with that of the development sample. We developed a framework of methodological steps and statistical methods for analyzing and enhancing the interpretation of results from external validation studies of prediction models. We propose to quantify the degree of relatedness between development and validation samples on a scale ranging from reproducibility to transportability by evaluating their corresponding case-mix differences. We subsequently assess the models' performance in the validation sample and interpret the performance in view of the case-mix differences. Finally, we may adjust the model to the validation setting. We illustrate this three-step framework with a prediction model for diagnosing deep venous thrombosis using three validation samples with varying case mix. While one external validation sample merely assessed the model's reproducibility, two other samples rather assessed model transportability. The performance in all validation samples was adequate, and the model did not require extensive updating to correct for miscalibration or poor fit to the validation settings. The proposed framework enhances the interpretation of findings at external validation of prediction models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Evaluating simplified methods for liquefaction assessment for loss estimation

NASA Astrophysics Data System (ADS)

Kongar, Indranil; Rossetto, Tiziana; Giovinazzi, Sonia

2017-06-01

Currently, some catastrophe models used by the insurance industry account for liquefaction by applying a simple factor to shaking-induced losses. The factor is based only on local liquefaction susceptibility and this highlights the need for a more sophisticated approach to incorporating the effects of liquefaction in loss models. This study compares 11 unique models, each based on one of three principal simplified liquefaction assessment methods: liquefaction potential index (LPI) calculated from shear-wave velocity, the HAZUS software method and a method created specifically to make use of USGS remote sensing data. Data from the September 2010 Darfield and February 2011 Christchurch earthquakes in New Zealand are used to compare observed liquefaction occurrences to forecasts from these models using binary classification performance measures. The analysis shows that the best-performing model is the LPI calculated using known shear-wave velocity profiles, which correctly forecasts 78 % of sites where liquefaction occurred and 80 % of sites where liquefaction did not occur, when the threshold is set at 7. However, these data may not always be available to insurers. The next best model is also based on LPI but uses shear-wave velocity profiles simulated from the combination of USGS VS30 data and empirical functions that relate VS30 to average shear-wave velocities at shallower depths. This model correctly forecasts 58 % of sites where liquefaction occurred and 84 % of sites where liquefaction did not occur, when the threshold is set at 4. These scores increase to 78 and 86 %, respectively, when forecasts are based on liquefaction probabilities that are empirically related to the same values of LPI. This model is potentially more useful for insurance since the input data are publicly available. HAZUS models, which are commonly used in studies where no local model is available, perform poorly and incorrectly forecast 87 % of sites where liquefaction occurred, even at optimal thresholds. This paper also considers two models (HAZUS and EPOLLS) for estimation of the scale of liquefaction in terms of permanent ground deformation but finds that both models perform poorly, with correlations between observations and forecasts lower than 0.4 in all cases. Therefore these models potentially provide negligible additional value to loss estimation analysis outside of the regions for which they have been developed.

Turbulence modeling in simulation of gas-turbine flow and heat transfer.

PubMed

Brereton, G; Shih, T I

2001-05-01

The popular k-epsilon type two-equation turbulence models, which are calibrated by experimental data from simple shear flows, are analyzed for their ability to predict flows involving shear and an extra strain--flow with shear and rotation and flow with shear and streamline curvature. The analysis is based on comparisons between model predictions and those from measurements and large-eddy simulations of homogenous flows involving shear and an extra strain, either from rotation or from streamline curvature. Parameters are identified, which show the conditions under which performance of k-epsilon type models can be expected to be poor.

Comparison between a model-based and a conventional pyramid sensor reconstructor.

PubMed

Korkiakoski, Visa; Vérinaud, Christophe; Le Louarn, Miska; Conan, Rodolphe

2007-08-20

A model of a non-modulated pyramid wavefront sensor (P-WFS) based on Fourier optics has been presented. Linearizations of the model represented as Jacobian matrices are used to improve the P-WFS phase estimates. It has been shown in simulations that a linear approximation of the P-WFS is sufficient in closed-loop adaptive optics. Also a method to compute model-based synthetic P-WFS command matrices is shown, and its performance is compared to the conventional calibration. It was observed that in poor visibility the new calibration is better than the conventional.

Predicting NonInertial Effects with Algebraic Stress Models which Account for Dissipation Rate Anisotropies

NASA Technical Reports Server (NTRS)

Jongen, T.; Machiels, L.; Gatski, T. B.

1997-01-01

Three types of turbulence models which account for rotational effects in noninertial frames of reference are evaluated for the case of incompressible, fully developed rotating turbulent channel flow. The different types of models are a Coriolis-modified eddy-viscosity model, a realizable algebraic stress model, and an algebraic stress model which accounts for dissipation rate anisotropies. A direct numerical simulation of a rotating channel flow is used for the turbulent model validation. This simulation differs from previous studies in that significantly higher rotation numbers are investigated. Flows at these higher rotation numbers are characterized by a relaminarization on the cyclonic or suction side of the channel, and a linear velocity profile on the anticyclonic or pressure side of the channel. The predictive performance of the three types of models are examined in detail, and formulation deficiencies are identified which cause poor predictive performance for some of the models. Criteria are identified which allow for accurate prediction of such flows by algebraic stress models and their corresponding Reynolds stress formulations.

Parent-child attachment, academic performance and the process of high-school dropout: a narrative review.

PubMed

Ramsdal, Gro; Bergvik, Svein; Wynn, Rolf

2015-01-01

Poor academic performance is a strong predictor of school dropout. Researchers have tried to disentangle variables influencing academic performance. However, studies on preschool and early care variables are seldom examined when explaining the school dropout process. We reviewed the literature on the relationship between caregiver-child attachment and academic performance, including attachment studies from preschool years, seeking out potential contributions to academic performance and the dropout process. The review was organized according to a model of four main mediating hypotheses: the attachment-teaching hypothesis, the social network hypothesis, the attachment-cooperation hypothesis, and the attachment self-regulation hypothesis. The results of the review are summed up in a model. There is some support for all four hypotheses. The review indicates that attachment and early care contribute substantially to dropout and graduation processes. Mediation effects should be given far more attention in future research.

Understanding and optimizing the dual excipient functionality of sodium lauryl sulfate in tablet formulation of poorly water soluble drug: wetting and lubrication.

PubMed

Aljaberi, Ahmad; Chatterji, Ashish; Dong, Zedong; Shah, Navnit H; Malick, Waseem; Singhal, Dharmendra; Sandhu, Harpreet K

2013-01-01

To evaluate and optimize sodium lauryl sulfate (SLS) and magnesium stearate (Mg.St) levels, with respect to dissolution and compaction, in a high dose, poorly soluble drug tablet formulation. A model poorly soluble drug was formulated using high shear aqueous granulation. A D-optimal design was used to evaluate and model the effect of granulation conditions, size of milling screen, SLS and Mg.St levels on tablet compaction and ejection. The compaction profiles were generated using a Presster(©) compaction simulator. Dissolution of the kernels was performed using a USP dissolution apparatus II and intrinsic dissolution was determined using a stationary disk system. Unlike kernels dissolution which failed to discriminate between tablets prepared with various SLS contents, the intrinsic dissolution rate showed that a SLS level of 0.57% was sufficient to achieve the required release profile while having minimal effect on compaction. The formulation factors that affect tablet compaction and ejection were identified and satisfactorily modeled. The design space of best factor setting to achieve optimal compaction and ejection properties was successfully constructed by RSM analysis. A systematic study design helped identify the critical factors and provided means to optimize the functionality of key excipient to design robust drug product.

Association between overweight/obesity and academic performance in South Korean adolescents.

PubMed

Kim, Jong-Hyuck; So, Wi-Young

2013-12-01

The purpose of this study was to examine the relationship between academic performance and obesity/overweight among South Korean adolescents. Our data set included 72,399 adolescents in grades 7-12 who had participated in the 5th Korea Youth Risk Behaviour Web-based Survey (KYRBWS-V) in 2009. We assessed the association between academic performance and body mass index (BMI), using multivariate logistic regression analysis after adjusting for covariates such as age, parents' education level, economic status, mental stress experienced, sleep duration, frequency of muscle-strengthening exercises, smoking and drinking behaviour, and vigorous and moderate physical activity (PA). For boys, being overweight (compared with being of normal weight) had a significantly greater odds of poor academic performance (OR=1.182, 95% Cl 1.052-1.329, p=0.005). Obese boys had 1.182 (1.048-1.332, p=0.006), 1.461 (1.294-1.648, p<0.001), and 1.443(1.256-1.657, p<0.001) greater odds of having average, poor, and very poor performance, respectively. In the analysis for girls, overweight girls had 1.314 (1.124-1.536, p<0.001) and 1.296 (1.084-1.548, p=0.004) greater odds of having poor and very poor academic performance, respectively. Finally, obese girls had 1.374 (1.098-1.718, p=0.005), 1.672 (1.339-2.089, p<0.001), and 1.887 (1.478-2.409, p<0.001) greater odds of having average, poor, or very poor academic performance, respectively. Thus, overweight/obesity was negatively associated with academic performance in both boys and girls. The results of this study indicate that adolescents would benefit from weight management to prevent obesity and, possibly, improve academic performance.

A Model of Planning for School Improvement and Obstacles to Implementation.

ERIC Educational Resources Information Center

Taylor, Dianne L.; Tashakkori, Abbas; Crone-Koshel, Linda

2001-01-01

Reports results of two separate but related studies: The first involves the use of a rubric to evaluate improvement plans from low-performing schools; the second involves a sample of teacher and administrator perceptions of their involvement in improvement planning. Finds poor-quality plans in evaluation study to be related to teacher-involvement…

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

Treesearch

Jakob Zscheischler; Simone Fatichi; Sebastian Wolf; Peter D. Blanken; Gil Bohrer; Ken Clark; Ankur R. Desai; David Hollinger; Trevor Keenan; Kimberly A. Novick; Sonia I. Seneviratne

2016-01-01

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their...

Never Good Enough: The Educational Journey of a Vietnamese American Woman

ERIC Educational Resources Information Center

Nguyen, Annie T.

2014-01-01

In this article, author Annie Nguyen describes her personal encounters with the "Model Minority Myth" as a young Vietnamese American in a doctoral program. This myth assumes that all Asian Americans are inherently smart and high achieving, which is problematic when in fact there are many Asian American individuals who perform poorly.…

The Effect of Exposure Duration on Visual Character Identification in Single, Whole, and Partial Report

ERIC Educational Resources Information Center

Petersen, Anders; Andersen, Tobias S.

2012-01-01

The psychometric function of single-letter identification is typically described as a function of stimulus intensity. However, the effect of stimulus exposure duration on letter identification remains poorly described. This is surprising because the effect of exposure duration has played a central role in modeling performance in whole and partial…

Attitude determination using an adaptive multiple model filtering Scheme

NASA Technical Reports Server (NTRS)

Lam, Quang; Ray, Surendra N.

1995-01-01

Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown quantities such as spacecraft dynamics parameters, gyro biases, dynamic disturbances, or environment variations.

Quantitative computed tomography-based predictions of vertebral strength in anterior bending.

PubMed

Buckley, Jenni M; Cheng, Liu; Loo, Kenneth; Slyfield, Craig; Xu, Zheng

2007-04-20

This study examined the ability of QCT-based structural assessment techniques to predict vertebral strength in anterior bending. The purpose of this study was to compare the abilities of QCT-based bone mineral density (BMD), mechanics of solids models (MOS), e.g., bending rigidity, and finite element analyses (FE) to predict the strength of isolated vertebral bodies under anterior bending boundary conditions. Although the relative performance of QCT-based structural measures is well established for uniform compression, the ability of these techniques to predict vertebral strength under nonuniform loading conditions has not yet been established. Thirty human thoracic vertebrae from 30 donors (T9-T10, 20 female, 10 male; 87 +/- 5 years of age) were QCT scanned and destructively tested in anterior bending using an industrial robot arm. The QCT scans were processed to generate specimen-specific FE models as well as trabecular bone mineral density (tBMD), integral bone mineral density (iBMD), and MOS measures, such as axial and bending rigidities. Vertebral strength in anterior bending was poorly to moderately predicted by QCT-based BMD and MOS measures (R2 = 0.14-0.22). QCT-based FE models were better strength predictors (R2 = 0.34-0.40); however, their predictive performance was not statistically different from MOS bending rigidity (P > 0.05). Our results suggest that the poor clinical performance of noninvasive structural measures may be due to their inability to predict vertebral strength under bending loads. While their performance was not statistically better than MOS bending rigidities, QCT-based FE models were moderate predictors of both compressive and bending loads at failure, suggesting that this technique has the potential for strength prediction under nonuniform loads. The current FE modeling strategy is insufficient, however, and significant modifications must be made to better mimic whole bone elastic and inelastic material behavior.

Attitude determination using an adaptive multiple model filtering Scheme

NASA Astrophysics Data System (ADS)

Lam, Quang; Ray, Surendra N.

1995-05-01

Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown quantities such as spacecraft dynamics parameters, gyro biases, dynamic disturbances, or environment variations.

Image analysis of the AXAF VETA-I x ray mirror

NASA Technical Reports Server (NTRS)

Freeman, Mark D.; Hughes, John P; Vanspeybroeck, L.; Weisskopf, M.; Bilbro, J.

1992-01-01

Initial core scan data of the VETA-I x-ray mirror proved disappointing, showing considerable unpredicted image structure and poor measured FWHM. 2-D core scans were performed, providing important insight into the nature of the distortion. Image deconvolutions using a ray traced model PSF was performed successfully to reinforce our conclusion regarding the origin of the astigmatism. A mechanical correction was made to the optical structure, and the mirror was tested successfully (FWHM 0.22 arcsec) as a result.

Mars approach navigation using Doppler and range measurements to surface beacons and orbiting spacecraft

NASA Technical Reports Server (NTRS)

Thurman, Sam W.; Estefan, Jeffrey A.

1991-01-01

Approximate analytical models are developed and used to construct an error covariance analysis for investigating the range of orbit determination accuracies which might be achieved for typical Mars approach trajectories. The sensitivity or orbit determination accuracy to beacon/orbiter position errors and to small spacecraft force modeling errors is also investigated. The results indicate that the orbit determination performance obtained from both Doppler and range data is a strong function of the inclination of the approach trajectory to the Martian equator, for surface beacons, and for orbiters, the inclination relative to the orbital plane. Large variations in performance were also observed for different approach velocity magnitudes; Doppler data in particular were found to perform poorly in determining the downtrack (along the direction of flight) component of spacecraft position. In addition, it was found that small spacecraft acceleration modeling errors can induce large errors in the Doppler-derived downtrack position estimate.

The effect of observing novice and expert performance on acquisition of surgical skills on a robotic platform

PubMed Central

Harris, David J.; Vine, Samuel J.; Wilson, Mark R.; McGrath, John S.; LeBel, Marie-Eve

2017-01-01

Background Observational learning plays an important role in surgical skills training, following the traditional model of learning from expertise. Recent findings have, however, highlighted the benefit of observing not only expert performance but also error-strewn performance. The aim of this study was to determine which model (novice vs. expert) would lead to the greatest benefits when learning robotically assisted surgical skills. Methods 120 medical students with no prior experience of robotically-assisted surgery completed a ring-carrying training task on three occasions; baseline, post-intervention and at one-week follow-up. The observation intervention consisted of a video model performing the ring-carrying task, with participants randomly assigned to view an expert model, a novice model, a mixed expert/novice model or no observation (control group). Participants were assessed for task performance and surgical instrument control. Results There were significant group differences post-intervention, with expert and novice observation groups outperforming the control group, but there were no clear group differences at a retention test one week later. There was no difference in performance between the expert-observing and error-observing groups. Conclusions Similar benefits were found when observing the traditional expert model or the error-strewn model, suggesting that viewing poor performance may be as beneficial as viewing expertise in the early acquisition of robotic surgical skills. Further work is required to understand, then inform, the optimal curriculum design when utilising observational learning in surgical training. PMID:29141046

Use of Latent Class Analysis to define groups based on validity, cognition, and emotional functioning.

PubMed

Morin, Ruth T; Axelrod, Bradley N

Latent Class Analysis (LCA) was used to classify a heterogeneous sample of neuropsychology data. In particular, we used measures of performance validity, symptom validity, cognition, and emotional functioning to assess and describe latent groups of functioning in these areas. A data-set of 680 neuropsychological evaluation protocols was analyzed using a LCA. Data were collected from evaluations performed for clinical purposes at an urban medical center. A four-class model emerged as the best fitting model of latent classes. The resulting classes were distinct based on measures of performance validity and symptom validity. Class A performed poorly on both performance and symptom validity measures. Class B had intact performance validity and heightened symptom reporting. The remaining two Classes performed adequately on both performance and symptom validity measures, differing only in cognitive and emotional functioning. In general, performance invalidity was associated with worse cognitive performance, while symptom invalidity was associated with elevated emotional distress. LCA appears useful in identifying groups within a heterogeneous sample with distinct performance patterns. Further, the orthogonal nature of performance and symptom validities is supported.

Highly specific reasons for nonadherence to antiretroviral therapy: results from the German adherence study.

PubMed

Boretzki, Johanna; Wolf, Eva; Wiese, Carmen; Noe, Sebastian; Balogh, Annamaria; Meurer, Anja; Krznaric, Ivanka; Zink, Alexander; Lersch, Christian; Spinner, Christoph D

2017-01-01

Reasons for and frequency of nonadherence to antiretroviral therapy (ART) may have changed due to pharmacological improvements. In addition, the importance of known non-pharmacologic reasons for nonadherence is unclear. We performed a cross-sectional, noninterventional, multicenter study to identify current reasons for nonadherence. Patients were categorized by physicians into the following adherence groups: good, unstable, or poor adherence. Co-variables of interest included age, sex, time since HIV diagnosis, ART duration, current ART regimen, HIV transmission route, comorbidity, HIV-1 RNA viral load (VL), and CD4 cell count. Patients self-reported the number of missed doses and provided their specific reasons for nonadherent behavior. Statistical analyses were performed using Fisher's extended exact test, Kruskal-Wallis test, and logistic regression models. Our study assessed 215 participants with good (n=162), unstable (n=36), and poor adherence (n=17). Compared to patients with good adherence, patients with unstable and poor adherence reported more often to have missed at least one dose during the last week (good 11% vs unstable 47% vs poor 63%, p <0.001). Physicians' adherence assessment was concordant with patients' self-reports of missed doses during the last week (no vs one or more) in 81% cases. Similarly, we found a strong association of physicians' assessment with viral suppression. Logistic regression analysis showed that "reduced adherence" - defined as unstable or poor - was significantly associated with patients <30 years old, intravenous drug use, history of acquired immune deficiency syndrome (AIDS), and psychiatric disorders ( p <0.05). Univariate analyses showed that specific reasons, such as questioning the efficacy/dosing of ART, HIV stigma, interactive toxicity beliefs regarding alcohol and/or party drugs, and dissatisfaction with regimen complexity, correlated with unstable or poor adherence ( p <0.05). Identification of factors associated with poor adherence helps in identifying patients with a higher risk for nonadherence. Reasons for nonadherence should be directly addressed in every patient, because they are common and constitute possible adherence intervention points.

Performance on a Clinical Quadriceps Activation Battery Is Related to a Laboratory Measure of Activation and Recovery After Total Knee Arthroplasty.

PubMed

Bade, Michael; Struessel, Tamara; Paxton, Roger; Winters, Joshua; Baym, Carol; Stevens-Lapsley, Jennifer

2018-01-01

To determine the relation between performance on a clinical quadriceps activation battery with (1) activation measured by doublet interpolation and (2) recovery of quadriceps strength and functional performance after total knee arthroplasty (TKA). Planned secondary analysis of a randomized controlled trial. University research laboratory. Patients (N=162; mean age, 63±7y; 89 women) undergoing TKA. Patients were classified as high (quadriceps activation battery ≥4/6) or low (quadriceps activation battery ≤3/6) based on performance on the quadriceps activation battery measured 4 days after TKA. Differences between groups in activation and recovery at 1, 2, 3, 6, and 12 months after TKA were compared using a repeated-measures maximum likelihood model. The low quadriceps activation battery group demonstrated poorer quadriceps activation via doublet interpolation (P=.01), greater quadriceps strength loss (P=.01), and greater functional performance decline (all P<.001) at 1 month after TKA compared with the high quadriceps activation battery group. Differences between low and high quadriceps activation battery groups on all measures did not persist at 3 and 12 months (all P>.05). Poor performance on the quadriceps activation battery early after TKA is related to poor quadriceps activation and poor recovery in the early postoperative period. Patients in the low quadriceps activation battery group took 3 months to recover to the same level as the high quadriceps activation battery group. The quadriceps activation battery may be useful in identifying individuals who need specific interventions to target activation deficits or different care pathways in the early postoperative period to speed recovery after TKA. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Assessing the effectiveness of a hybrid-flipped model of learning on fluid mechanics instruction: overall course performance, homework, and far- and near-transfer of learning

NASA Astrophysics Data System (ADS)

Harrison, David J.; Saito, Laurel; Markee, Nancy; Herzog, Serge

2017-11-01

To examine the impact of a hybrid-flipped model utilising active learning techniques, the researchers inverted one section of an undergraduate fluid mechanics course, reduced seat time, and engaged in active learning sessions in the classroom. We compared this model to the traditional section on four performance measures. We employed a propensity score method entailing a two-stage regression analysis that considered eight covariates to address the potential bias of treatment selection. First, we estimated the probability score based on the eight covariates, and second, we used the inverse of the probability score as a regression weight on the performance of learners who did not select into the hybrid course. Results suggest that enrolment in the hybrid-flipped section had a marginally significant negative impact on the total course score and a significant negative impact on homework performance, possibly because of poor video usage by the hybrid-flipped learners. Suggested considerations are also discussed.

Doctors' stress responses and poor communication performance in simulated bad-news consultations.

PubMed

Brown, Rhonda; Dunn, Stewart; Byrnes, Karen; Morris, Richard; Heinrich, Paul; Shaw, Joanne

2009-11-01

No studies have previously evaluated factors associated with high stress levels and poor communication performance in breaking bad news (BBN) consultations. This study determined factors that were most strongly related to doctors' stress responses and poor communication performance during a simulated BBN task. In 2007, the authors recruited 24 doctors comprising 12 novices (i.e., interns/residents with 1-3 years' experience) and 12 experts (i.e., registrars, medical/radiation oncologists, or cancer surgeons, with more than 4 years' experience). Doctors participated in simulated BBN consultations and a number of control tasks. Five-minute-epoch heart rate (HR), HR variability, and communication performance were assessed in all participants. Subjects also completed a short questionnaire asking about their prior experience BBN, perceived stress, psychological distress (i.e., anxiety, depression), fatigue, and burnout. High stress responses were related to inexperience with BBN, fatigue, and giving bad versus good news. Poor communication performance in the consultation was related to high burnout and fatigue scores. These results suggest that BBN was a stressful experience for doctors even in a simulated encounter, especially for those who were inexperienced and/or fatigued. Poor communication performance was related to burnout and fatigue, but not inexperience with BBN. These results likely indicate that burnout and fatigue contributed to stress and poor work performance in some doctors during the simulated BBN task.

[Attrition and poor performance in general practice training: age, competence and knowledge play a role].

PubMed

Vermeulen, Margit I; Kuyvenhoven, Marijke M; Zuithoff, N P A Peter; van der Graaf, Yolanda; Pieters, H M Ron

2011-01-01

To investigate which determinants are related to poor performance and forced attrition in the first year residency in general practice (GP). Observational retrospective cohort study. We collected data relating to personal characteristics such as age, sex and clinical experience from residents who started the GP training in Utrecht, the Netherlands, in the period March 2005-August 2007. We also collected competence scores from the domains 'medical expertise', 'doctor-patient communication' and 'professionalism', as well as scores on a national GP knowledge test. The outcome measures were 'poor performance' and 'forced attrition'. Multivariate logistic regression was used to analyse correlations between personal characteristics, competence scores on the 3 domains and knowledge scores in the first trimester on the one hand and poor performance or forced attrition on the other. 215 residents started the GP training. In the first trimester a quarter of the residents had an insufficient score in 1 or more of the domains. Competence scores were mutually correlated, but did not correlate with the knowledge score. 18 residents showed poor performance and 3 were forced to stop their training. Poor performance and forced attrition were correlated with age (adjusted odds ratio (OR): 1.1; 95% CI: 1.0-1.3), insufficient knowledge (adjusted OR: 8.9; 3.0-26.3) and medical expertise (adjusted OR: 2.1; 1.1-4.0) at the beginning of the training. Age, insufficient knowledge of general practice, and insufficient competence in the domain of 'medical expertise' at the beginning of the training are risk factors for poor performance by residents and attrition from their GP training.

Evaluating the Performance of the ff99SB Force Field Based on NMR Scalar Coupling Data

PubMed Central

Wickstrom, Lauren; Okur, Asim; Simmerling, Carlos

2009-01-01

Abstract Force-field validation is essential for the identification of weaknesses in current models and the development of more accurate models of biomolecules. NMR coupling and relaxation methods have been used to effectively diagnose the strengths and weaknesses of many existing force fields. Studies using the ff99SB force field have shown excellent agreement between experimental and calculated order parameters and residual dipolar calculations. However, recent studies have suggested that ff99SB demonstrates poor agreement with J-coupling constants for short polyalanines. We performed extensive replica-exchange molecular-dynamics simulations on Ala3 and Ala5 in TIP3P and TIP4P-Ew solvent models. Our results suggest that the performance of ff99SB is among the best of currently available models. In addition, scalar coupling constants derived from simulations in the TIP4P-Ew model show a slight improvement over those obtained using the TIP3P model. Despite the overall excellent agreement, the data suggest areas for possible improvement. PMID:19651043

Performance Metrics for Monitoring Parallel Program Executions

NASA Technical Reports Server (NTRS)

Sarukkai, Sekkar R.; Gotwais, Jacob K.; Yan, Jerry; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

Existing tools for debugging performance of parallel programs either provide graphical representations of program execution or profiles of program executions. However, for performance debugging tools to be useful, such information has to be augmented with information that highlights the cause of poor program performance. Identifying the cause of poor performance necessitates the need for not only determining the significance of various performance problems on the execution time of the program, but also needs to consider the effect of interprocessor communications of individual source level data structures. In this paper, we present a suite of normalized indices which provide a convenient mechanism for focusing on a region of code with poor performance and highlights the cause of the problem in terms of processors, procedures and data structure interactions. All the indices are generated from trace files augmented with data structure information.. Further, we show with the help of examples from the NAS benchmark suite that the indices help in detecting potential cause of poor performance, based on augmented execution traces obtained by monitoring the program.

Strategic parenting, birth order, and school performance.

PubMed

Hotz, V Joseph; Pantano, Juan

2015-10-01

Fueled by new evidence, there has been renewed interest about the effects of birth order on human capital accumulation. The underlying causal mechanisms for such effects remain unsettled. We consider a model in which parents impose more stringent disciplinary environments in response to their earlier-born children's poor performance in school in order to deter such outcomes for their later-born offspring. We provide robust empirical evidence that school performance of children in the National Longitudinal Study Children (NLSY-C) declines with birth order as does the stringency of their parents' disciplinary restrictions. When asked how they will respond if a child brought home bad grades, parents state that they would be less likely to punish their later-born children. Taken together, these patterns are consistent with a reputation model of strategic parenting.

Strategic parenting, birth order, and school performance

PubMed Central

Pantano, Juan

2015-01-01

Fueled by new evidence, there has been renewed interest about the effects of birth order on human capital accumulation. The underlying causal mechanisms for such effects remain unsettled. We consider a model in which parents impose more stringent disciplinary environments in response to their earlier-born children’s poor performance in school in order to deter such outcomes for their later-born offspring. We provide robust empirical evidence that school performance of children in the National Longitudinal Study Children (NLSY-C) declines with birth order as does the stringency of their parents’ disciplinary restrictions. When asked how they will respond if a child brought home bad grades, parents state that they would be less likely to punish their later-born children. Taken together, these patterns are consistent with a reputation model of strategic parenting. PMID:26366045

Anatomy of a system accident: the crash of Avianca Flight 052.

PubMed

Helmreich, R L

1994-01-01

On January 25, 1990, Avianca Flight 052 crashed after running out of fuel following a missed approach to New York's John F. Kennedy Airport. Weather was poor on the East Coast of the United States that day, and the flight had experienced several holding patterns enroute from Medellín, Colombia, to New York. The accident is analyzed in terms of Helmreich and Foushee's (1993) model of crew performance and Reason's (1990) model of latent pathogens in system operations.

Anatomy of a system accident: The crash of Avianca Flight 052

NASA Technical Reports Server (NTRS)

Helmreich, Robert L.

1994-01-01

On January 25, 1990, Avianca Flight 052 crashed after running out of fuel following a missed approach to New York's John F. Kennedy Airport. Weather was poor on the East Coast of the United States that day, and the flight had experienced several holding patterns enroute from Medellin, Colombia, to New York. The accident is analyzed in terms of Helmreich and Foushee's (1993) model of crew performance and Reason's (1990) model of latent pathogens in system operations.

Seizures, refractory status epilepticus, and depolarization block as endogenous brain activities

NASA Astrophysics Data System (ADS)

El Houssaini, Kenza; Ivanov, Anton I.; Bernard, Christophe; Jirsa, Viktor K.

2015-01-01

Epilepsy, refractory status epilepticus, and depolarization block are pathological brain activities whose mechanisms are poorly understood. Using a generic mathematical model of seizure activity, we show that these activities coexist under certain conditions spanning the range of possible brain activities. We perform a detailed bifurcation analysis and predict strategies to escape from some of the pathological states. Experimental results using rodent data provide support of the model, highlighting the concept that these pathological activities belong to the endogenous repertoire of brain activities.

The Unsteady Temperature Field in a Turbine Blade Cooling Channel

DTIC Science & Technology

2003-03-01

SYB) 39-1 The Unsteady Temperature Field in a Turbine Blade Cooling Channel T . Arts Von Karman Institute for Fluid Dynamics 72, chausse de Waterloo...wall coordinates (y+ and T +) are used for this purpose: ν = − ρ−= τ+τ + uyy q TT uCT wall wall p (1) (SYB) 39...poor performance of the Baldwin-Lomax model and, up to some extent, of the standard k-ε model (Fig. 5). 0 5 10 15 20 25 1 10 100 1000 10000 Y+ T

Sleep quantity, quality, and insomnia symptoms of medical students during clinical years

PubMed Central

Alsaggaf, Mohammed A.; Wali, Siraj O.; Merdad, Roah A.; Merdad, Leena A.

2016-01-01

Objectives: To determine sleep habits and sleep quality in medical students during their clinical years using validated measures; and to investigate associations with academic performance and psychological stress. Methods: In this cross-sectional study, medical students (n=320) were randomly selected from a list of all enrolled clinical-year students in a Saudi medical school from 2011-2012. Students filled a questionnaire including demographic and lifestyle factors, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Perceived Stress Scale. Results: Students acquired on average, 5.8 hours of sleep each night, with an average bedtime at 01:53. Approximately 8% reported acquiring sleep during the day, and not during nighttime. Poor sleep quality was present in 30%, excessive daytime sleepiness (EDS) in 40%, and insomnia symptoms in 33% of students. Multivariable regression models revealed significant associations between stress, poor sleep quality, and EDS. Poorer academic performance and stress were associated with symptoms of insomnia. Conclusion: Sleep deprivation, poor sleep quality, and EDS are common among clinical years medical students. High levels of stress and the pressure of maintaining grade point averages may be influencing their quality of sleep. PMID:26837401

Large eddy simulation of spanwise rotating turbulent channel flow with dynamic variants of eddy viscosity model

NASA Astrophysics Data System (ADS)

Jiang, Zhou; Xia, Zhenhua; Shi, Yipeng; Chen, Shiyi

2018-04-01

A fully developed spanwise rotating turbulent channel flow has been numerically investigated utilizing large-eddy simulation. Our focus is to assess the performances of the dynamic variants of eddy viscosity models, including dynamic Vreman's model (DVM), dynamic wall adapting local eddy viscosity (DWALE) model, dynamic σ (Dσ ) model, and the dynamic volumetric strain-stretching (DVSS) model, in this canonical flow. The results with dynamic Smagorinsky model (DSM) and direct numerical simulations (DNS) are used as references. Our results show that the DVM has a wrong asymptotic behavior in the near wall region, while the other three models can correctly predict it. In the high rotation case, the DWALE can get reliable mean velocity profile, but the turbulence intensities in the wall-normal and spanwise directions show clear deviations from DNS data. DVSS exhibits poor predictions on both the mean velocity profile and turbulence intensities. In all three cases, Dσ performs the best.

The performance of fine-grained and coarse-grained elastic network models and its dependence on various factors.

PubMed

Na, Hyuntae; Song, Guang

2015-07-01

In a recent work we developed a method for deriving accurate simplified models that capture the essentials of conventional all-atom NMA and identified two best simplified models: ssNMA and eANM, both of which have a significantly higher correlation with NMA in mean square fluctuation calculations than existing elastic network models such as ANM and ANMr2, a variant of ANM that uses the inverse of the squared separation distances as spring constants. Here, we examine closely how the performance of these elastic network models depends on various factors, namely, the presence of hydrogen atoms in the model, the quality of input structures, and the effect of crystal packing. The study reveals the strengths and limitations of these models. Our results indicate that ssNMA and eANM are the best fine-grained elastic network models but their performance is sensitive to the quality of input structures. When the quality of input structures is poor, ANMr2 is a good alternative for computing mean-square fluctuations while ANM model is a good alternative for obtaining normal modes. © 2015 Wiley Periodicals, Inc.

Interannual Tropical Rainfall Variability in General Circulation Model Simulations Associated with the Atmospheric Model Intercomparison Project.

NASA Astrophysics Data System (ADS)

Sperber, K. R.; Palmer, T. N.

1996-11-01

The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall variability was also best reproduced. However, for all regions the skill was less than that of the ECMWF model.The relationships of the all-India and Sahel rainfall/SST teleconnections with horizontal resolution, convection scheme closure, and numerics have been evaluated. Models with resolution T42 performed more poorly than lower-resolution models. The higher resolution models were predominantly spectral. At low resolution, spectral versus gridpoint numerics performed with nearly equal verisimilitude. At low resolution, moisture convergence closure was slightly more preferable than other convective closure techniques. At high resolution, the models that used moisture convergence closure performed very poorly, suggesting that moisture convergence may be problematic for models with horizontal resolution T42.

An Approach to 3d Digital Modeling of Surfaces with Poor Texture by Range Imaging Techniques. `SHAPE from Stereo' VS. `SHAPE from Silhouette' in Digitizing Jorge Oteiza's Sculptures

NASA Astrophysics Data System (ADS)

García Fernández, J.; Álvaro Tordesillas, A.; Barba, S.

2015-02-01

Despite eminent development of digital range imaging techniques, difficulties persist in the virtualization of objects with poor radiometric information, in other words, objects consisting of homogeneous colours (totally white, black, etc.), repetitive patterns, translucence, or materials with specular reflection. This is the case for much of the Jorge Oteiza's works, particularly in the sculpture collection of the Museo Fundación Jorge Oteiza (Navarra, Spain). The present study intend to analyse and asses the performance of two digital 3D-modeling methods based on imaging techniques, facing cultural heritage in singular cases, determined by radiometric characteristics as mentioned: Shape from Silhouette and Shape from Stereo. On the other hand, the text proposes the definition of a documentation workflow and presents the results of its application in the collection of sculptures created by Oteiza.

Optimal firing rate estimation

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

Annealed Importance Sampling Reversible Jump MCMC algorithms

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

Karagiannis, Georgios; Andrieu, Christophe

2013-03-20

It will soon be 20 years since reversible jump Markov chain Monte Carlo (RJ-MCMC) algorithms have been proposed. They have significantly extended the scope of Markov chain Monte Carlo simulation methods, offering the promise to be able to routinely tackle transdimensional sampling problems, as encountered in Bayesian model selection problems for example, in a principled and flexible fashion. Their practical efficient implementation, however, still remains a challenge. A particular difficulty encountered in practice is in the choice of the dimension matching variables (both their nature and their distribution) and the reversible transformations which allow one to define the one-to-one mappingsmore » underpinning the design of these algorithms. Indeed, even seemingly sensible choices can lead to algorithms with very poor performance. The focus of this paper is the development and performance evaluation of a method, annealed importance sampling RJ-MCMC (aisRJ), which addresses this problem by mitigating the sensitivity of RJ-MCMC algorithms to the aforementioned poor design. As we shall see the algorithm can be understood as being an “exact approximation” of an idealized MCMC algorithm that would sample from the model probabilities directly in a model selection set-up. Such an idealized algorithm may have good theoretical convergence properties, but typically cannot be implemented, and our algorithms can approximate the performance of such idealized algorithms to an arbitrary degree while not introducing any bias for any degree of approximation. Our approach combines the dimension matching ideas of RJ-MCMC with annealed importance sampling and its Markov chain Monte Carlo implementation. We illustrate the performance of the algorithm with numerical simulations which indicate that, although the approach may at first appear computationally involved, it is in fact competitive.« less

Twin Screw Extruder Production of MTTP Decoy Flares SERDP WP-1240

DTIC Science & Technology

2005-12-01

5 3. Carnauba Wax ( wax from palm tree exudate, a common ingredient in high quality car polish) Hazards of the remaining formulations were...1. Microsere 5866, a microcrystalline wax derived from refining petroleum 2. Elvax 250, poly(ethylene-co-vinyl acetate) (hot glue ingredient...5866 Poor performance when 1-gm sample ignited Elvax 250 Poor performance when 1-gm sample ignited Carnuba Wax Poor performance when 1-gm sample

External validation and clinical utility of a prediction model for 6-month mortality in patients undergoing hemodialysis for end-stage kidney disease.

PubMed

Forzley, Brian; Er, Lee; Chiu, Helen Hl; Djurdjev, Ognjenka; Martinusen, Dan; Carson, Rachel C; Hargrove, Gaylene; Levin, Adeera; Karim, Mohamud

2018-02-01

End-stage kidney disease is associated with poor prognosis. Health care professionals must be prepared to address end-of-life issues and identify those at high risk for dying. A 6-month mortality prediction model for patients on dialysis derived in the United States is used but has not been externally validated. We aimed to assess the external validity and clinical utility in an independent cohort in Canada. We examined the performance of the published 6-month mortality prediction model, using discrimination, calibration, and decision curve analyses. Data were derived from a cohort of 374 prevalent dialysis patients in two regions of British Columbia, Canada, which included serum albumin, age, peripheral vascular disease, dementia, and answers to the "the surprise question" ("Would I be surprised if this patient died within the next year?"). The observed mortality in the validation cohort was 11.5% at 6 months. The prediction model had reasonable discrimination (c-stat = 0.70) but poor calibration (calibration-in-the-large = -0.53 (95% confidence interval: -0.88, -0.18); calibration slope = 0.57 (95% confidence interval: 0.31, 0.83)) in our data. Decision curve analysis showed the model only has added value in guiding clinical decision in a small range of threshold probabilities: 8%-20%. Despite reasonable discrimination, the prediction model has poor calibration in this external study cohort; thus, it may have limited clinical utility in settings outside of where it was derived. Decision curve analysis clarifies limitations in clinical utility not apparent by receiver operating characteristic curve analysis. This study highlights the importance of external validation of prediction models prior to routine use in clinical practice.

Evidence that communication impairment in schizophrenia is associated with generalized poor task performance.

PubMed

Merrill, Anne M; Karcher, Nicole R; Cicero, David C; Becker, Theresa M; Docherty, Anna R; Kerns, John G

2017-03-01

People with schizophrenia exhibit wide-ranging cognitive deficits, including slower processing speed and decreased cognitive control. Disorganized speech symptoms, such as communication impairment, have been associated with poor cognitive control task performance (e.g., goal maintenance and working memory). Whether communication impairment is associated with poorer performance on a broader range of non-cognitive control measures is unclear. In the current study, people with schizophrenia (n =51) and non-psychiatric controls (n =26) completed speech interviews allowing for reliable quantitative assessment of communication impairment. Participants also completed multiple goal maintenance and working memory tasks. In addition, we also examined (a) simple measures of processing speed involving highly automatic prepotent responses and (b) a non-cognitive control measure of general task performance. Schizophrenia communication impairment was significantly associated with poor performance in all cognitive domains, with the largest association found with processing speed (r s =-0.52). Further, communication impairment was also associated with the non-cognitive control measure of poor general task performance (r s =-0.43). In contrast, alogia, a negative speech symptom, and positive symptoms were less if at all related to cognitive task performance. Overall, this study suggests that communication impairment in schizophrenia may be associated with relatively generalized poor cognitive task performance. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Cochlear-implant spatial selectivity with monopolar, bipolar and tripolar stimulation.

PubMed

Zhu, Ziyan; Tang, Qing; Zeng, Fan-Gang; Guan, Tian; Ye, Datian

2012-01-01

Sharp spatial selectivity is critical to auditory performance, particularly in pitch-related tasks. Most contemporary cochlear implants have employed monopolar stimulation that produces broad electric fields, which presumably contribute to poor pitch and pitch-related performance by implant users. Bipolar or tripolar stimulation can generate focused electric fields but requires higher current to reach threshold and, more interestingly, has not produced any apparent improvement in cochlear-implant performance. The present study addressed this dilemma by measuring psychophysical and physiological spatial selectivity with both broad and focused stimulations in the same cohort of subjects. Different current levels were adjusted by systematically measuring loudness growth for each stimulus, each stimulation mode, and in each subject. Both psychophysical and physiological measures showed that, although focused stimulation produced significantly sharper spatial tuning than monopolar stimulation, it could shift the tuning position or even split the tuning tips. The altered tuning with focused stimulation is interpreted as a result of poor electrode-to-neuron interface in the cochlea, and is suggested to be mainly responsible for the lack of consistent improvement in implant performance. A linear model could satisfactorily quantify the psychophysical and physiological data and derive the tuning width. Significant correlation was found between the individual physiological and psychophysical tuning widths, and the correlation was improved by log-linearly transforming the physiological data to predict the psychophysical data. Because the physiological measure took only one-tenth of the time of the psychophysical measure, the present model is of high clinical significance in terms of predicting and improving cochlear-implant performance. Copyright © 2011 Elsevier B.V. All rights reserved.

Cochlear Implant Spatial Selectivity with Monopolar, Bipolar and Tripolar Stimulation

PubMed Central

Zhu, Ziyan; Tang, Qing; Zeng, Fan-Gang; Guan, Tian; Ye, Datian

2011-01-01

Sharp spatial selectivity is critical to auditory performance, particularly in pitch related tasks. Most contemporary cochlear implants have employed monopolar stimulation that produces broad electric fields, which presumably contribute to poor pitch and pitch-related performance by implant users. Bipolar or tripolar stimulation can generate focused electric fields but requires higher current to reach threshold and, more interestingly, has not produced any apparent improvement in cochlear implant performance. The present study addressed this dilemma by measuring psychophysical and physiological spatial selectivity with both broad and focused stimulations in the same cohort of subjects. Different current levels were adjusted by systematically measuring loudness growth for each stimulus, each stimulation mode, and in each subject. Both psychophysical and physiological measures showed that, although focused stimulation produced significantly sharper spatial tuning than monopolar stimulation, it could shift the tuning position or even split the tuning tips. The altered tuning with focused stimulation is interpreted as a result of poor electrode-to-neuron interface in the cochlea, and is suggested to be mainly responsible for the lack of consistent improvement in implant performance. A linear model could satisfactorily quantify the psychophysical and physiological data and derive the tuning width. Significant correlation was found between the individual physiological and psychophysical tuning widths, and the correlation was improved by log-linearly transforming the physiological data to predict the psychophysical data. Because the physiological measure took only one-tenth of the time of the psychophysical measure, the present model is of high clinical significance in terms of predicting and improving cochlear implant performance. PMID:22138630

Lifespan Aging and Belief Reasoning: Influences of Executive Function and Social Cue Decoding

ERIC Educational Resources Information Center

Phillips, Louise H.; Bull, Rebecca; Allen, Roy; Insch, Pauline; Burr, Kirsty; Ogg, Will

2011-01-01

Older adults often perform poorly on Theory of Mind (ToM) tests that require understanding of others' beliefs and intentions. The course and specificity of age changes in belief reasoning across the adult lifespan is unclear, as is the cause of the age effects. Cognitive and neuropsychological models predict that two types of processing might…

Sources, Properties, Aging, and Anthropogenic Influences on OA and SOA over the Southeast US and the Amazon duing SOAS, DC3, SEAC4RS, and GoAmazon

EPA Science Inventory

The SE US and the Amazon have large sources of biogenic VOCs, varying anthropogenic pollution impacts, and often poor organic aerosol (OA) model performance. Recent results on the sources, properties, aging, and impact of anthropogenic pollution on OA and secondary OA (SOA) over ...

Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility

NASA Astrophysics Data System (ADS)

Tuba, Zoltán; Bottyán, Zsolt

2018-04-01

Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.

20 CFR 658.604 - Assessment and evaluation of program performance data.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., whether overall or relative to a particular program activity, indicate poor program performance does not... that a State agency's performance is poor that the data may raise a presumption (prima facie case) that... performance data. 658.604 Section 658.604 Employees' Benefits EMPLOYMENT AND TRAINING ADMINISTRATION...

The health belief model and determinants of oral hygiene practices and beliefs in preteen children: a pilot study.

PubMed

Walker, Kimberly; Jackson, Richard

2015-01-01

There is limited understanding of children's behavioral decisions for practicing good oral hygiene. The purpose of this study was to identify factors that may motivate children to practice good oral hygiene. Guided by the Health Belief Model (HBM), eight focus groups of 42 American children (second through fifth graders) were interviewed concerning their histories with caries, perceived confidence in brushing, self-perceived susceptibility and vulnerability for caries and/or poor oral health, and perceived benefits and barriers to practicing oral hygiene. Most children equated good oral health as being central to their overall health; however, some viewed poor oral health as occurring only in the elderly while others believed poor oral health could begin at any age. Children cited esthetic appearance of teeth and the desire to please others by brushing without reminders as motivators of good oral hygiene. The greatest barriers to performing oral hygiene were a perceived lack of time and limited access to toothbrushes and dentifrice when away. To motivate children in this age range, emphasis should be placed on the positive aspects of maintaining good oral hygiene for its contribution to appearance and its implication for an overall healthy body and self-image.

Poor Executive Functions among Children with Moderate-into-Severe Asthma: Evidence from WCST Performance.

PubMed

Taha, Haitham

2017-01-01

Executive functions (EFs) measures of 27 asthmatic children, with general learning difficulties, were tested by using the Wisconsin card sorting test (WCST), and were compared to the performances of 30 non-asthmatic children with general learning difficulties. The results revealed that the asthmatic group has poor performance through all the WCST psychometric parameters and especially the perseverative errors one. The results were discussed in light of the postulation that poor EFs could be associated with the learning difficulties of asthmatic children. Neurophysiological framework has been suggested to explain the etiology of poor EFs among children with moderate into severe asthma.

Long working hours and health in Europe: Gender and welfare state differences in a context of economic crisis.

PubMed

Artazcoz, Lucía; Cortès, Imma; Benavides, Fernando G; Escribà-Agüir, Vicenta; Bartoll, Xavier; Vargas, Hernán; Borrell, Carme

2016-07-01

This article examines the relationship between moderately long working hours and health status in Europe. A cross-sectional study based on data from the 2010 European Working Conditions Survey (13,518 men and 9381 women) was performed. Working moderately long hours was consistently associated with poor health status and poor psychological wellbeing in countries with traditional family models, in both sexes in Liberal countries and primarily among women in Continental and Southern European countries. A combination of economic vulnerability, increasing labour market deregulation and work overload related to the combination of job and domestic work could explain these findings. Copyright © 2016 Elsevier Ltd. All rights reserved.

CtBP2 overexpression promotes tumor cell proliferation and invasion in gastric cancer and is associated with poor prognosis.

PubMed

Dai, Faxiang; Xuan, Yi; Jin, Jie-Jie; Yu, Shengjia; Long, Zi-Wen; Cai, Hong; Liu, Xiao-Wen; Zhou, Ye; Wang, Ya-Nong; Chen, Zhong; Huang, Hua

2017-04-25

C-terminal binding protein-2 (CtBP2), a transcriptional corepressor, has been reported to correlate with tumorigenesis and progression and predict a poor prognosis in several human cancers. However, few studies on CtBP2 in gastric cancer (GC) have been performed. In this research, we evaluated the correlations between CtBP2 expression and the clinicopathological characteristics, as well as prognosis of GC patients. The effects of silencing CtBP2 expression on GC cells biology activity were also assessed. The results showed that CtBP2 was overexpressed in GC tissues and closely correlated with poor differentiation, advanced tumor stage and poor prognosis in GC patients. CtBP2 induced epithelial-to-mesenchymal transition (EMT) and repressed PTEN to increase proliferation rate, migration, and invasion in GC cells. Silencing CtBP2 inhibited GC growth in nude mice model. In conclusion, CtBP2 is overexpressed in GC and may accelerate GC tumorigenesis and metastasis, which could represent an independent prognostic marker and promising therapeutic target for GC.

Common Characteristics of Good and Poorly Performing PCC Pavements

DOT National Transportation Integrated Search

1998-01-01

This report documents the analysis and findings of a study to identify the site conditions and design/construction features of concrete pavements (JPCP, JRCP, CRCP) that lead to good performance and those that lead to poor performance. Data from Long...

Common Characteristics of Good and Poorly Performing AC Pavements

DOT National Transportation Integrated Search

1999-12-01

This report documents the analysis and findings of a study to identify the site conditions and design/construction features of : flexible pavements that lead to good performance and those that lead to poor performance. Data from the Long Term Pavemen...

Early Prediction of Intensive Care Unit-Acquired Weakness: A Multicenter External Validation Study.

PubMed

Witteveen, Esther; Wieske, Luuk; Sommers, Juultje; Spijkstra, Jan-Jaap; de Waard, Monique C; Endeman, Henrik; Rijkenberg, Saskia; de Ruijter, Wouter; Sleeswijk, Mengalvio; Verhamme, Camiel; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

2018-01-01

An early diagnosis of intensive care unit-acquired weakness (ICU-AW) is often not possible due to impaired consciousness. To avoid a diagnostic delay, we previously developed a prediction model, based on single-center data from 212 patients (development cohort), to predict ICU-AW at 2 days after ICU admission. The objective of this study was to investigate the external validity of the original prediction model in a new, multicenter cohort and, if necessary, to update the model. Newly admitted ICU patients who were mechanically ventilated at 48 hours after ICU admission were included. Predictors were prospectively recorded, and the outcome ICU-AW was defined by an average Medical Research Council score <4. In the validation cohort, consisting of 349 patients, we analyzed performance of the original prediction model by assessment of calibration and discrimination. Additionally, we updated the model in this validation cohort. Finally, we evaluated a new prediction model based on all patients of the development and validation cohort. Of 349 analyzed patients in the validation cohort, 190 (54%) developed ICU-AW. Both model calibration and discrimination of the original model were poor in the validation cohort. The area under the receiver operating characteristics curve (AUC-ROC) was 0.60 (95% confidence interval [CI]: 0.54-0.66). Model updating methods improved calibration but not discrimination. The new prediction model, based on all patients of the development and validation cohort (total of 536 patients) had a fair discrimination, AUC-ROC: 0.70 (95% CI: 0.66-0.75). The previously developed prediction model for ICU-AW showed poor performance in a new independent multicenter validation cohort. Model updating methods improved calibration but not discrimination. The newly derived prediction model showed fair discrimination. This indicates that early prediction of ICU-AW is still challenging and needs further attention.

Correlation between stressors and academic performance in second year medical students.

PubMed

Nuallaong, Winitra

2011-12-01

The present study aimed to find which type of stressors correlating to academic performance in second year medical students. One-hundred and eighty three second year medical students of Thammasat University participated in a three-week cross-sectional study. The self-report questionnaire consisted of Thai stress test, stress factors and examination grades referring academic performance were applied in the present study. Females felt stress more than males in severe, high, and medium level of stress. There was no low level of stress and no correlation between stress level and the entrance programs. Academic performance found relating to 1) fear of doing a mistake, 2) feeling of competition or comparison, 3) unilateral headache, 4) worrying, and 5) poor concentration. Students with poor concentration had significantly decreasing grade in the second year (p < 0.01). Interestingly, worrying, feeling of competition or comparison, and fear of doing a mistake correlated to increasing grade in some terms (p < 0.05). Specifically to poor concentration, there were medium linear association with fatigue, poor memory, feeling confused, feeling sad, feeling angry or irritable, changing appetite, and headache from stress (p < 0.01). Poor concentration was the only stressor significantly correlated with poorer academic performance. Poor concentration also correlated with physical, cognitive, and financial problems. The recommendation is to keep watching those issues in order to early detect problem about academic performance.

Biomechanical factors associated with mandibular cantilevers: analysis with three-dimensional finite element models.

PubMed

Gonda, Tomoya; Yasuda, Daiisa; Ikebe, Kazunori; Maeda, Yoshinobu

2014-01-01

Although the risks of using a cantilever to treat missing teeth have been described, the mechanisms remain unclear. This study aimed to reveal these mechanisms from a biomechanical perspective. The effects of various implant sites, number of implants, and superstructural connections on stress distribution in the marginal bone were analyzed with three-dimensional finite element models based on mandibular computed tomography data. Forces from the masseter, temporalis, and internal pterygoid were applied as vectors. Two three-dimensional finite element models were created with the edentulous mandible showing severe and relatively modest residual ridge resorption. Cantilevers of the premolar and molar were simulated in the superstructures in the models. The following conditions were also included as factors in the models to investigate changes: poor bone quality, shortened dental arch, posterior occlusion, lateral occlusion, double force of the masseter, and short implant. Multiple linear regression analysis with a forced-entry method was performed with stress values as the objective variable and the factors as the explanatory variable. When bone mass was high, stress around the implant caused by differences in implantation sites was reduced. When bone mass was low, the presence of a cantilever was a possible risk factor. The stress around the implant increased significantly if bone quality was poor or if increased force (eg, bruxism) was applied. The addition of a cantilever to the superstructure increased stress around implants. When large muscle forces were applied to a superstructure with cantilevers or if bone quality was poor, stress around the implants increased.

Disciplinary processes and the management of poor performance among UK nurses: bad apple or systemic failure? A scoping study.

PubMed

Traynor, Michael; Stone, Katie; Cook, Hannah; Gould, Dinah; Maben, Jill

2014-03-01

The rise of managerialism within healthcare systems has been noted globally. This paper uses the findings of a scoping study to investigate the management of poor performance among nurses and midwives in the United Kingdom within this context. The management of poor performance among clinicians in the NHS has been seen as a significant policy problem. There has been a profound shift in the distribution of power between professional and managerial groups in many health systems globally. We examined literature published between 2000 and 10 to explore aspects of poor performance and its management. We used Web of Science, CINAHL, MEDLINE, British Nursing Index, HMIC, Cochrane Library and PubMed. Empirical data are limited but indicate that nurses and midwives are the clinical groups most likely to be suspended and that poor performance is often represented as an individual deficit. A focus on the individual as a source of trouble can serve as a distraction from more complex systematic problems. © 2013 John Wiley & Sons Ltd.

Does poor school performance cause later psychosocial problems among children in foster care? Evidence from national longitudinal registry data.

PubMed

Forsman, Hilma; Brännström, Lars; Vinnerljung, Bo; Hjern, Anders

2016-07-01

Research has shown that children in foster care are a high-risk group for adverse economic, social and health related outcomes in young adulthood. Children's poor school performance has been identified as a major risk factor for these poor later life outcomes. Aiming to support the design of effective intervention strategies, this study examines the hypothesized causal effect of foster children's poor school performance on subsequent psychosocial problems, here conceptualized as economic hardship, illicit drug use, and mental health problems, in young adulthood. Using the potential outcomes approach, longitudinal register data on more than 7500 Swedish foster children born 1973-1978 were analyzed by means of doubly robust treatment-effect estimators. The results show that poor school performance has a negative impact on later psychosocial problems net of observed background attributes and potential selection on unobservables, suggesting that the estimated effects allow for causal interpretations. Promotion of school performance may thus be a viable intervention path for policymakers and practitioners interested in improving foster children's overall life chances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relationship between Poor Sleep and Daytime Cognitive Performance in Young Adults with Autism

ERIC Educational Resources Information Center

Limoges, Elyse; Bolduc, Christianne; Berthiaume, Claude; Mottron, Laurent; Godbout, Roger

2013-01-01

Poor sleep is a common feature in autism even though patients themselves do not necessarily complain. The impact of poor sleep on daytime cognitive functioning in autism is not well-known and we therefore investigated whether sleep in autism correlates with daytime cognitive performance. A battery of non-verbal tasks was administered, in the…

SEM-PLS Analysis of Inhibiting Factors of Cost Performance for Large Construction Projects in Malaysia: Perspective of Clients and Consultants

PubMed Central

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R 2 value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun. PMID:24693227

SEM-PLS analysis of inhibiting factors of cost performance for large construction projects in Malaysia: perspective of clients and consultants.

PubMed

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R(2) value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun.

A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

PubMed

Halliday, Drew W R; MacDonald, Stuart W S; Scherf, K Suzanne; Sherf, Suzanne K; Tanaka, James W

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

A Reciprocal Model of Face Recognition and Autistic Traits: Evidence from an Individual Differences Perspective

PubMed Central

Halliday, Drew W. R.; MacDonald, Stuart W. S.; Sherf, Suzanne K.; Tanaka, James W.

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals. PMID:24853862

CAUSES OF POOR SEALANT PERFORMANCE IN SOIL-GAS- RESISTANT FOUNDATIONS

EPA Science Inventory

The paper discusses causes of poor sealant performance in soil-gas-resistant foundations. ealants for radon-resistant foundation construction must seal the gap between concrete sections. odern sealants have such low permeability that seal performance depends only on the permeabil...

Poor school performance.

PubMed

Karande, Sunil; Kulkarni, Madhuri

2005-11-01

Education is one of the most important aspects of human resource development. Poor school performance not only results in the child having a low self-esteem, but also causes significant stress to the parents. There are many reasons for children to under perform at school, such as, medical problems, below average intelligence, specific learning disability, attention deficit hyperactivity disorder, emotional problems, poor socio-cultural home environment, psychiatric disorders and even environmental causes. The information provided by the parents, classroom teacher and school counselor about the child's academic difficulties guides the pediatrician to form an initial diagnosis. However, a multidisciplinary evaluation by an ophthalmologist, otolaryngologist, counselor, clinical psychologist, special educator, and child psychiatrist is usually necessary before making the final diagnosis. It is important to find the reason(s) for a child's poor school performance and come up with a treatment plan early so that the child can perform up to full potential.

Management of a water distribution network by coupling GIS and hydraulic modeling: a case study of Chetouane in Algeria

NASA Astrophysics Data System (ADS)

Abdelbaki, Chérifa; Benchaib, Mohamed Mouâd; Benziada, Salim; Mahmoudi, Hacène; Goosen, Mattheus

2017-06-01

For more effective management of water distribution network in an arid region, Mapinfo GIS (8.0) software was coupled with a hydraulic model (EPANET 2.0) and applied to a case study region, Chetouane, situated in the north-west of Algeria. The area is characterized not only by water scarcity but also by poor water management practices. The results showed that a combination of GIS and modeling permits network operators to better analyze malfunctions with a resulting more rapid response as well as facilitating in an improved understanding of the work performed on the network. The grouping of GIS and modeling as an operating tool allows managers to diagnosis a network, to study solutions of problems and to predict future situations. The later can assist them in making informed decisions to ensure an acceptable performance level for optimal network operation.

[Predictive model based multimetric index of macroinvertebrates for river health assessment].

PubMed

Chen, Kai; Yu, Hai Yan; Zhang, Ji Wei; Wang, Bei Xin; Chen, Qiu Wen

2017-06-18

Improving the stability of integrity of biotic index (IBI; i.e., multi-metric indices, MMI) across temporal and spatial scales is one of the most important issues in water ecosystem integrity bioassessment and water environment management. Using datasets of field-based macroinvertebrate and physicochemical variables and GIS-based natural predictors (e.g., geomorphology and climate) and land use variables collected at 227 river sites from 2004 to 2011 across the Zhejiang Province, China, we used random forests (RF) to adjust the effects of natural variations at temporal and spatial scales on macroinvertebrate metrics. We then developed natural variations adjusted (predictive) and unadjusted (null) MMIs and compared performance between them. The core me-trics selected for predictive and null MMIs were different from each other, and natural variations within core metrics in predictive MMI explained by RF models ranged between 11.4% and 61.2%. The predictive MMI was more precise and accurate, but less responsive and sensitive than null MMI. The multivariate nearest-neighbor test determined that 9 test sites and 1 most degraded site were flagged outside of the environmental space of the reference site network. We found that combination of predictive MMI developed by using predictive model and the nearest-neighbor test performed best and decreased risks of inferring type I (designating a water body as being in poor biological condition, when it was actually in good condition) and type II (designating a water body as being in good biological condition, when it was actually in poor condition) errors. Our results provided an effective method to improve the stability and performance of integrity of biotic index.

SU-D-204-03: Comparison of Patient Positioning Methods Through Modeling of Acute Rectal Toxicity in Intensity Modulated Radiation Therapy for Prostate Cancer. Does Quality of Data Matter More Than the Quantity?

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

Liu, X; Fatyga, M; Vora, S

Purpose: To determine if differences in patient positioning methods have an impact on the incidence and modeling of grade >=2 acute rectal toxicity in prostate cancer patients who were treated with Intensity Modulated Radiation Therapy (IMRT). Methods: We compared two databases of patients treated with radiation therapy for prostate cancer: a database of 79 patients who were treated with 7 field IMRT and daily image guided positioning based on implanted gold markers (IGRTdb), and a database of 302 patients who were treated with 5 field IMRT and daily positioning using a trans-abdominal ultrasound system (USdb). Complete planning dosimetry was availablemore » for IGRTdb patients while limited planning dosimetry, recorded at the time of planning, was available for USdb patients. We fit Lyman-Kutcher-Burman (LKB) model to IGRTdb only, and Univariate Logistic Regression (ULR) NTCP model to both databases. We perform Receiver Operating Characteristics analysis to determine the predictive power of NTCP models. Results: The incidence of grade >= 2 acute rectal toxicity in IGRTdb was 20%, while the incidence in USdb was 54%. Fits of both LKB and ULR models yielded predictive NTCP models for IGRTdb patients with Area Under the Curve (AUC) in the 0.63 – 0.67 range. Extrapolation of the ULR model from IGRTdb to planning dosimetry in USdb predicts that the incidence of acute rectal toxicity in USdb should not exceed 40%. Fits of the ULR model to the USdb do not yield predictive NTCP models and their AUC is consistent with AUC = 0.5. Conclusion: Accuracy of a patient positioning system affects clinically observed toxicity rates and the quality of NTCP models that can be derived from toxicity data. Poor correlation between planned and clinically delivered dosimetry may lead to erroneous or poorly performing NTCP models, even if the number of patients in a database is large.« less

Association between Facebook dependence and poor sleep quality: a study in a sample of undergraduate students in Peru.

PubMed

Wolniczak, Isabella; Cáceres-DelAguila, José Alonso; Palma-Ardiles, Gabriela; Arroyo, Karen J; Solís-Visscher, Rodrigo; Paredes-Yauri, Stephania; Mego-Aquije, Karina; Bernabe-Ortiz, Antonio

2013-01-01

Internet can accelerate information exchange. Social networks are the most accessed especially Facebook. This kind of networks might create dependency with several negative consequences in people's life. The aim of this study was to assess potential association between Facebook dependence and poor sleep quality. A cross sectional study was performed enrolling undergraduate students of the Universidad Peruana de Ciencias Aplicadas, Lima, Peru. The Internet Addiction Questionnaire, adapted to the Facebook case, and the Pittsburgh Sleep Quality Index, were used. A global score of 6 or greater was defined as the cutoff to determine poor sleep quality. Generalized linear model were used to determine prevalence ratios (PR) and 95% confidence intervals (95%CI). A total of 418 students were analyzed; of them, 322 (77.0%) were women, with a mean age of 20.1 (SD: 2.5) years. Facebook dependence was found in 8.6% (95% CI: 5.9%-11.3%), whereas poor sleep quality was present in 55.0% (95% CI: 50.2%-59.8%). A significant association between Facebook dependence and poor sleep quality mainly explained by daytime dysfunction was found (PR = 1.31; IC95%: 1.04-1.67) after adjusting for age, sex and years in the faculty. There is a relationship between Facebook dependence and poor quality of sleep. More than half of students reported poor sleep quality. Strategies to moderate the use of this social network and to improve sleep quality in this population are needed.

Memory binding and white matter integrity in familial Alzheimer’s disease

PubMed Central

Saarimäki, Heini; Bastin, Mark E.; Londoño, Ana C.; Pettit, Lewis; Lopera, Francisco; Della Sala, Sergio; Abrahams, Sharon

2015-01-01

Binding information in short-term and long-term memory are functions sensitive to Alzheimer’s disease. They have been found to be affected in patients who meet criteria for familial Alzheimer’s disease due to the mutation E280A of the PSEN1 gene. However, only short-term memory binding has been found to be affected in asymptomatic carriers of this mutation. The neural correlates of this dissociation are poorly understood. The present study used diffusion tensor magnetic resonance imaging to investigate whether the integrity of white matter structures could offer an account. A sample of 19 patients with familial Alzheimer’s disease, 18 asymptomatic carriers and 21 non-carrier controls underwent diffusion tensor magnetic resonance imaging, neuropsychological and memory binding assessment. The short-term memory binding task required participants to detect changes across two consecutive screens displaying arrays of shapes, colours, or shape-colour bindings. The long-term memory binding task was a Paired Associates Learning Test. Performance on these tasks were entered into regression models. Relative to controls, patients with familial Alzheimer’s disease performed poorly on both memory binding tasks. Asymptomatic carriers differed from controls only in the short-term memory binding task. White matter integrity explained poor memory binding performance only in patients with familial Alzheimer’s disease. White matter water diffusion metrics from the frontal lobe accounted for poor performance on both memory binding tasks. Dissociations were found in the genu of corpus callosum which accounted for short-term memory binding impairments and in the hippocampal part of cingulum bundle which accounted for long-term memory binding deficits. The results indicate that white matter structures in the frontal and temporal lobes are vulnerable to the early stages of familial Alzheimer’s disease and their damage is associated with impairments in two memory binding functions known to be markers for Alzheimer’s disease. PMID:25762465

Memory binding and white matter integrity in familial Alzheimer's disease.

PubMed

Parra, Mario A; Saarimäki, Heini; Bastin, Mark E; Londoño, Ana C; Pettit, Lewis; Lopera, Francisco; Della Sala, Sergio; Abrahams, Sharon

2015-05-01

Binding information in short-term and long-term memory are functions sensitive to Alzheimer's disease. They have been found to be affected in patients who meet criteria for familial Alzheimer's disease due to the mutation E280A of the PSEN1 gene. However, only short-term memory binding has been found to be affected in asymptomatic carriers of this mutation. The neural correlates of this dissociation are poorly understood. The present study used diffusion tensor magnetic resonance imaging to investigate whether the integrity of white matter structures could offer an account. A sample of 19 patients with familial Alzheimer's disease, 18 asymptomatic carriers and 21 non-carrier controls underwent diffusion tensor magnetic resonance imaging, neuropsychological and memory binding assessment. The short-term memory binding task required participants to detect changes across two consecutive screens displaying arrays of shapes, colours, or shape-colour bindings. The long-term memory binding task was a Paired Associates Learning Test. Performance on these tasks were entered into regression models. Relative to controls, patients with familial Alzheimer's disease performed poorly on both memory binding tasks. Asymptomatic carriers differed from controls only in the short-term memory binding task. White matter integrity explained poor memory binding performance only in patients with familial Alzheimer's disease. White matter water diffusion metrics from the frontal lobe accounted for poor performance on both memory binding tasks. Dissociations were found in the genu of corpus callosum which accounted for short-term memory binding impairments and in the hippocampal part of cingulum bundle which accounted for long-term memory binding deficits. The results indicate that white matter structures in the frontal and temporal lobes are vulnerable to the early stages of familial Alzheimer's disease and their damage is associated with impairments in two memory binding functions known to be markers for Alzheimer's disease. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Can patients with schizophrenia have good mentalizing skills? Disentangling heterogeneity of theory of mind.

PubMed

Bechi, Margherita; Bosia, Marta; Agostoni, Giulia; Spangaro, Marco; Buonocore, Mariachiara; Bianchi, Laura; Cocchi, Federica; Guglielmino, Carmelo; Mastromatteo, Antonella Rita; Cavallaro, Roberto

2018-06-07

Theory of Mind (ToM) is a multifaceted construct that involves mental states attribution in social interactions. Patients with schizophrenia are impaired in ToM abilities, but recent studies showed that a non-negligible number of patients perform within normal ranges or close to normal, whereas other patients are very impaired in ToM tasks. The present study aims to comprehensively analyze differences between patients with "poor" and "fair" mentalizing abilities, as identified through a median-split procedure on mental state attribution task, and healthy controls, as well as to explore the role of clinical, demographical, and neurocognitive predictors of ToM performance within groups. One hundred twenty-two patients with schizophrenia and 67 healthy controls were assessed for ToM, attention, and executive functioning. In addition, patients' daily functioning and psychopathological profiles were also rated. "Fair" mentalizers perform significantly better than "poor" mentalizers on cognitive abilities and quality of life and they differ from healthy controls in neurocognition and cognitive ToM performance, even though the global ToM performance is similar. Furthermore, regression models showed distinct contributing factors in each sub group: ToM is related to neurocognitive abilities and education in healthy subjects, while it is mainly associated with attention in "fair" group and it is related to clinical variables and executive functions in "poor" mentalizers. Although preliminary, these data shed new light on the heterogeneity of ToM deficit among patients with schizophrenia and could reflect on daily clinical practice, as they are important to develop individualized step-by-step rehabilitative programs. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Effect of Sipjeondaebo-Tang on Cancer-Induced Anorexia and Cachexia in CT-26 Tumor-Bearing Mice

PubMed Central

Jung, Ki Yong; Woo, Sang-Mi; Jun, Chan-Yong; Park, Jong Hyeong; Shin, Yong Cheol; Ko, Seong-Gyu

2014-01-01

Cancer-associated anorexia and cachexia are a multifactorial condition described by a loss of body weight and muscle with anorexia, asthenia, and anemia. Moreover, they correlate with a high mortality rate, poor response to chemotherapy, poor performance status, and poor quality of life. Cancer cachexia is regulated by proinflammatory cytokines such as interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), and tumor necrosis factor-α (TNF-α). In addition, glucagon like peptide-1 (GIP-1), peptide YY (PYY), ghrelin, and leptin plays a crucial role in food intake. In this study, we investigated the therapeutic effects of one of the traditional herbal medicines, Sipjeondaebo-tang (Juzen-taiho-to in Japanese; SJDBT), on cancer anorexia and cachexia in a fundamental mouse cancer anorexia/cachexia model, CT-26 tumor-bearing mice. SJDBT was more significantly effective in a treatment model where it was treated after anorexia and cachexia than in a prevention model where it was treated before anorexia and cachexia on the basis of parameters such as weights of muscles and whole body and food intakes. Moreover, SJDBT inhibited a production of IL-6, MCP-1, PYY, and GLP-1 and ameliorated cancer-induced anemia. Therefore, our in vivo studies provide evidence on the role of SJDBT in cancer-associated anorexia and cachexia, thereby suggesting that SJDBT may be useful for treating cancer-associated anorexia and cachexia. PMID:24963216

Effect of Sipjeondaebo-tang on cancer-induced anorexia and cachexia in CT-26 tumor-bearing mice.

PubMed

Choi, Youn Kyung; Jung, Ki Yong; Woo, Sang-Mi; Yun, Yee Jin; Jun, Chan-Yong; Park, Jong Hyeong; Shin, Yong Cheol; Cho, Sung-Gook; Ko, Seong-Gyu

2014-01-01

Cancer-associated anorexia and cachexia are a multifactorial condition described by a loss of body weight and muscle with anorexia, asthenia, and anemia. Moreover, they correlate with a high mortality rate, poor response to chemotherapy, poor performance status, and poor quality of life. Cancer cachexia is regulated by proinflammatory cytokines such as interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), and tumor necrosis factor- α (TNF- α). In addition, glucagon like peptide-1 (GIP-1), peptide YY (PYY), ghrelin, and leptin plays a crucial role in food intake. In this study, we investigated the therapeutic effects of one of the traditional herbal medicines, Sipjeondaebo-tang (Juzen-taiho-to in Japanese; SJDBT), on cancer anorexia and cachexia in a fundamental mouse cancer anorexia/cachexia model, CT-26 tumor-bearing mice. SJDBT was more significantly effective in a treatment model where it was treated after anorexia and cachexia than in a prevention model where it was treated before anorexia and cachexia on the basis of parameters such as weights of muscles and whole body and food intakes. Moreover, SJDBT inhibited a production of IL-6, MCP-1, PYY, and GLP-1 and ameliorated cancer-induced anemia. Therefore, our in vivo studies provide evidence on the role of SJDBT in cancer-associated anorexia and cachexia, thereby suggesting that SJDBT may be useful for treating cancer-associated anorexia and cachexia.

Goodness of fit of probability distributions for sightings as species approach extinction.

PubMed

Vogel, Richard M; Hosking, Jonathan R M; Elphick, Chris S; Roberts, David L; Reed, J Michael

2009-04-01

Estimating the probability that a species is extinct and the timing of extinctions is useful in biological fields ranging from paleoecology to conservation biology. Various statistical methods have been introduced to infer the time of extinction and extinction probability from a series of individual sightings. There is little evidence, however, as to which of these models provide adequate fit to actual sighting records. We use L-moment diagrams and probability plot correlation coefficient (PPCC) hypothesis tests to evaluate the goodness of fit of various probabilistic models to sighting data collected for a set of North American and Hawaiian bird populations that have either gone extinct, or are suspected of having gone extinct, during the past 150 years. For our data, the uniform, truncated exponential, and generalized Pareto models performed moderately well, but the Weibull model performed poorly. Of the acceptable models, the uniform distribution performed best based on PPCC goodness of fit comparisons and sequential Bonferroni-type tests. Further analyses using field significance tests suggest that although the uniform distribution is the best of those considered, additional work remains to evaluate the truncated exponential model more fully. The methods we present here provide a framework for evaluating subsequent models.

Requirements model for an e-Health awareness portal

NASA Astrophysics Data System (ADS)

Hussain, Azham; Mkpojiogu, Emmanuel O. C.; Nawi, Mohd Nasrun M.

2016-08-01

Requirements engineering is at the heart and foundation of software engineering process. Poor quality requirements inevitably lead to poor quality software solutions. Also, poor requirement modeling is tantamount to designing a poor quality product. So, quality assured requirements development collaborates fine with usable products in giving the software product the needed quality it demands. In the light of the foregoing, the requirements for an e-Ebola Awareness Portal were modeled with a good attention given to these software engineering concerns. The requirements for the e-Health Awareness Portal are modeled as a contribution to the fight against Ebola and helps in the fulfillment of the United Nation's Millennium Development Goal No. 6. In this study requirements were modeled using UML 2.0 modeling technique.

Mental state attribution in schizophrenia: what distinguishes patients with "poor" from patients with "fair" mentalising skills?

PubMed

Brüne, M; Schaub, D

2012-07-01

Although many patients with schizophrenia are impaired in mental states attribution abilities, a significant number perform within normal or near-normal ranges in mental state attribution tasks. No studies have analysed cognitive or behavioural differences between patients with - to some extent - preserved mental state attribution skills and those with poor mentalising abilities. To examine characteristics of "poor" and "fair" mentalisers, 58 patients with schizophrenia performed a mental state attribution task, a test of general intelligence, and two executive functioning tests. "Poor" and "fair" mentalising skills were defined according to a median-split procedure; the median score in the patient group was also within two standard deviations of the control group. In addition, patients' social behavioural skills and psychopathological profiles were rated. Patients performing within normal or near normal ranges on the mental state attribution task had fewer social behavioural abnormalities than patients with poor mentalising abilities (even when controlled for intelligence), but did not differ in executive functioning. Fair mental state performers showed less disorganisation and excitement symptoms than poor performers. The degree of disorganisation mediated the influence of mental state attribution on social behavioural skills. Schizophrenia patients with (partially) preserved mentalising skills have fewer behavioural problems in the social domain than patients with poor mentalising abilities. Conceptual disorganisation mediates the prediction of social behavioural skills through mentalising skills, suggesting that disorganised patients may require special attention regarding social-cognitive skills training. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

More than just nickels and dimes: a cross-national analysis of working poverty in affluent democracies.

PubMed

Brady, David; Fullerton, Andrew S; Cross, Jennifer Moren

2010-01-01

Despite its centrality to contemporary inequality, working poverty is often popularly discussed but rarely studied by sociologists. Using the Luxembourg Income Study (2009), we analyze whether an individual is working poor across 18 affluent democracies circa 2000. We demonstrate that working poverty does not simply mirror overall poverty and that there is greater cross-national variation in working than overall poverty. We then examine four explanations for working poverty: demographic characteristics, economic performance, unified theory, and welfare generosity. We utilize Heckman probit models to jointly model the likelihood of employment and poverty among the employed. Our analyses provide the least support for the economic performance explanation. There is modest support for unified theory as unionization reduces working poverty in some models. However, most of these effects appear to be mediated by welfare generosity. More substantial evidence exists for the demographic characteristics and welfare generosity explanations. An individual's likelihood of being working poor can be explained by (a) a lack of multiple earners or other adults in one's household, low education, single motherhood, having children and youth; and (b) the generosity of the welfare state in which he or she resides. Also, welfare generosity does not undermine employment and reduces working poverty even among demographically vulnerable groups. Ultimately, we encourage a greater role for the welfare state in debates about working poverty.

Hybrid quantum and molecular mechanics embedded cluster models for chemistry on silicon and silicon carbide surfaces

NASA Astrophysics Data System (ADS)

Shoemaker, James Richard

Fabrication of silicon carbide (SiC) semiconductor devices are of interest for aerospace applications because of their high-temperature tolerance. Growth of an insulating SiO2 layer on SiC by oxidation is a poorly understood process, and sometimes produces interface defects that degrade device performance. Accurate theoretical models of surface chemistry, using quantum mechanics (QM), do not exist because of the huge computational cost of solving Schrodinger's equation for a molecular cluster large enough to represent a surface. Molecular mechanics (MM), which describes a molecule as a collection of atoms interacting through classical potentials, is a fast computational method, good at predicting molecular structure, but cannot accurately model chemical reactions. A new hybrid QM/MM computational method for surface chemistry was developed and applied to silicon and SiC surfaces. The addition of MM steric constraints was shown to have a large effect on the energetics of O atom adsorption on SiC. Adsorption of O atoms on Si-terminated SiC(111) favors above surface sites, in contrast to Si(111), but favors subsurface adsorption sites on C- terminated SiC(111). This difference, and the energetics of C atom etching via CO2 desorption, can explain the observed poor performance of SiC devices in which insulating layers were grown on C-terminated surfaces.

Efficiency, equity and feasibility of strategies to identify the poor: an application to premium exemptions under National Health Insurance in Ghana.

PubMed

Jehu-Appiah, Caroline; Aryeetey, Genevieve; Spaan, Ernst; Agyepong, Irene; Baltussen, Rob

2010-05-01

This paper outlines the potential strategies to identify the poor, and assesses their feasibility, efficiency and equity. Analyses are illustrated for the case of premium exemptions under National Health Insurance (NHI) in Ghana. A literature search in Medline search was performed to identify strategies to identify the poor. Models were developed including information on demography and poverty, and costs and errors of in- and exclusion of these strategies in two regions in Ghana. Proxy means testing (PMT), participatory welfare ranking (PWR), and geographic targeting (GT) are potentially useful strategies to identify the poor, and vary in terms of their efficiency, equity and feasibility. Costs to exempt one poor individual range between US$11.63 and US$66.67, and strategies may exclude up to 25% of the poor. Feasibility of strategies is dependent on their aptness in rural/urban settings, and administrative capacity to implement. A decision framework summarizes the above information to guide policy making. We recommend PMT as an optimal strategy in relative low poverty incidence urbanized settings, PWR as an optimal strategy in relative low poverty incidence rural settings, and GT as an optimal strategy in high incidence poverty settings. This paper holds important lessons not only for NHI in Ghana but also for other countries implementing exemption policies. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Detection of selective sweeps in structured populations: a comparison of recent methods.

PubMed

Vatsiou, Alexandra I; Bazin, Eric; Gaggiotti, Oscar E

2016-01-01

Identifying genomic regions targeted by positive selection has been a long-standing interest of evolutionary biologists. This objective was difficult to achieve until the recent emergence of next-generation sequencing, which is fostering the development of large-scale catalogues of genetic variation for increasing number of species. Several statistical methods have been recently developed to analyse these rich data sets, but there is still a poor understanding of the conditions under which these methods produce reliable results. This study aims at filling this gap by assessing the performance of genome-scan methods that consider explicitly the physical linkage among SNPs surrounding a selected variant. Our study compares the performance of seven recent methods for the detection of selective sweeps (iHS, nSL, EHHST, xp-EHH, XP-EHHST, XPCLR and hapFLK). We use an individual-based simulation approach to investigate the power and accuracy of these methods under a wide range of population models under both hard and soft sweeps. Our results indicate that XPCLR and hapFLK perform best and can detect soft sweeps under simple population structure scenarios if migration rate is low. All methods perform poorly with moderate-to-high migration rates, or with weak selection and very poorly under a hierarchical population structure. Finally, no single method is able to detect both starting and nearly completed selective sweeps. However, combining several methods (XPCLR or hapFLK with iHS or nSL) can greatly increase the power to pinpoint the selected region. © 2015 John Wiley & Sons Ltd.

Characterization of identification errors and uses in localization of poor modal correlation

NASA Astrophysics Data System (ADS)

Martin, Guillaume; Balmes, Etienne; Chancelier, Thierry

2017-05-01

While modal identification is a mature subject, very few studies address the characterization of errors associated with components of a mode shape. This is particularly important in test/analysis correlation procedures, where the Modal Assurance Criterion is used to pair modes and to localize at which sensors discrepancies occur. Poor correlation is usually attributed to modeling errors, but clearly identification errors also occur. In particular with 3D Scanning Laser Doppler Vibrometer measurement, many transfer functions are measured. As a result individual validation of each measurement cannot be performed manually in a reasonable time frame and a notable fraction of measurements is expected to be fairly noisy leading to poor identification of the associated mode shape components. The paper first addresses measurements and introduces multiple criteria. The error measures the difference between test and synthesized transfer functions around each resonance and can be used to localize poorly identified modal components. For intermediate error values, diagnostic of the origin of the error is needed. The level evaluates the transfer function amplitude in the vicinity of a given mode and can be used to eliminate sensors with low responses. A Noise Over Signal indicator, product of error and level, is then shown to be relevant to detect poorly excited modes and errors due to modal property shifts between test batches. Finally, a contribution is introduced to evaluate the visibility of a mode in each transfer. Using tests on a drum brake component, these indicators are shown to provide relevant insight into the quality of measurements. In a second part, test/analysis correlation is addressed with a focus on the localization of sources of poor mode shape correlation. The MACCo algorithm, which sorts sensors by the impact of their removal on a MAC computation, is shown to be particularly relevant. Combined with the error it avoids keeping erroneous modal components. Applied after removal of poor modal components, it provides spatial maps of poor correlation, which help localizing mode shape correlation errors and thus prepare the selection of model changes in updating procedures.

Context Switching with Multiple Register Windows: A RISC Performance Study

NASA Technical Reports Server (NTRS)

Konsek, Marion B.; Reed, Daniel A.; Watcharawittayakul, Wittaya

1987-01-01

Although previous studies have shown that a large file of overlapping register windows can greatly reduce procedure call/return overhead, the effects of register windows in a multiprogramming environment are poorly understood. This paper investigates the performance of multiprogrammed, reduced instruction set computers (RISCs) as a function of window management strategy. Using an analytic model that reflects context switch and procedure call overheads, we analyze the performance of simple, linearly self-recursive programs. For more complex programs, we present the results of a simulation study. These studies show that a simple strategy that saves all windows prior to a context switch, but restores only a single window following a context switch, performs near optimally.

Low Cerebral Blood Volume Identifies Poor Outcome in Stent Retriever Thrombectomy

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

Protto, Sara, E-mail: sara.protto@pshp.fi; Pienimäki, Juha-Pekka; Seppänen, Janne

BackgroundMechanical thrombectomy (MT) is an efficient treatment of acute stroke caused by large-vessel occlusion. We evaluated the factors predicting poor clinical outcome (3-month modified Rankin Scale, mRS >2) although MT performed with modern stent retrievers.MethodsWe prospectively collected the clinical and imaging data of 105 consecutive anterior circulation stroke patients who underwent MT after multimodal CT imaging. Patients with occlusion of the internal carotid artery and/or middle cerebral artery up to the M2 segment were included. We recorded baseline clinical, procedural and imaging variables, technical outcome, 24-h imaging outcome and the clinical outcome. Differences between the groups were studied with appropriatemore » statistical tests and binary logistic regression analysis.ResultsLow cerebral blood volume Alberta stroke program early CT score (CBV-ASPECTS) was associated with poor clinical outcome (median 7 vs. 9, p = 0.01). Lower collateral score (CS) significantly predicted poor outcome in regression modelling with CS = 0 increasing the odds of poor outcome 4.4-fold compared to CS = 3 (95% CI 1.27–15.5, p = 0.02). Lower CBV-ASPECTS significantly predicted poor clinical outcome among those with moderate or severe stroke (OR 0.82, 95% CI 0.68–1, p = 0.05) or poor collateral circulation (CS 0–1, OR 0.66, 95% CI 0.48–0.90, p = 0.009) but not among those with mild strokes or good collaterals.ConclusionsCBV-ASPECTS estimating infarct core is a significant predictor of poor clinical outcome among anterior circulation stroke patients treated with MT, especially in the setting of poor collateral circulation and/or moderate or severe stroke.« less

Slow Physical Growth, Delayed Reflex Ontogeny, and Permanent Behavioral as Well as Cognitive Impairments in Rats Following Intra-generational Protein Malnutrition

PubMed Central

Naik, Aijaz A.; Patro, Ishan K.; Patro, Nisha

2015-01-01

Environmental stressors including protein malnutrition (PMN) during pre-, neo- and post-natal age have been documented to affect cognitive development and cause increased susceptibility to neuropsychiatric disorders. Most studies have addressed either of the three windows and that does not emulate the clinical conditions of intra-uterine growth restriction (IUGR). Such data fail to provide a complete picture of the behavioral alterations in the F1 generation. The present study thus addresses the larger window from gestation to F1 generation, a new model of intra-generational PMN. Naive Sprague Dawley (SD) dams pre-gestationally switched to LP (8% protein) or HP (20% protein) diets for 45 days were bred and maintained throughout gestation on same diets. Pups born (HP/LP dams) were maintained on the respective diets post-weaningly. The present study aimed to show the sex specific differences in the neurobehavioral evolution and behavioral phenotype of the HP/LP F1 generation pups. A battery of neurodevelopmental reflex tests, behavioral (Open field and forelimb gripstrength test), and cognitive [Elevated plus maze (EPM) and Morris water maze (MWM)] assays were performed. A decelerated growth curve with significantly restricted body and brain weight, delays in apparition of neuro-reflexes and poor performance in the LP group rats was recorded. Intra-generational PMN induced poor habituation-with-time in novel environment exploration, low anxiety and hyperactive like profile in open field test in young and adult rats. The study revealed poor forelimb neuromuscular strength in LP F1 pups till adulthood. Group occupancy plots in MWM test revealed hyperactivity with poor learning, impaired memory retention and integration, thus modeling the signs of early onset Alzehemier phenotype. In addition, a gender specific effect of LP diet with severity in males and favoring female sex was also noticed. PMID:26696810

Creation of a Prognostic Index for Spine Metastasis to Stratify Survival in Patients Treated With Spinal Stereotactic Radiosurgery: Secondary Analysis of Mature Prospective Trials

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

Tang, Chad; Hess, Kenneth; Bishop, Andrew J.

Purpose: There exists uncertainty in the prognosis of patients following spinal metastasis treatment. We sought to create a scoring system that stratifies patients based on overall survival. Methods and Materials: Patients enrolled in 2 prospective trials investigating stereotactic spine radiation surgery (SSRS) for spinal metastasis with ≥3-year follow-up were analyzed. A multivariate Cox regression model was used to create a survival model. Pretreatment variables included were race, sex, age, performance status, tumor histology, extent of vertebrae involvement, previous therapy at the SSRS site, disease burden, and timing of diagnosis and metastasis. Four survival groups were generated based on the model-derivedmore » survival score. Results: Median follow-up in the 206 patients included in this analysis was 70 months (range: 37-133 months). Seven variables were selected: female sex (hazard ratio [HR] = 0.7, P=.02), Karnofsky performance score (HR = 0.8 per 10-point increase above 60, P=.007), previous surgery at the SSRS site (HR = 0.7, P=.02), previous radiation at the SSRS site (HR = 1.8, P=.001), the SSRS site as the only site of metastatic disease (HR = 0.5, P=.01), number of organ systems involved outside of bone (HR = 1.4 per involved system, P<.001), and >5 year interval from initial diagnosis to detection of spine metastasis (HR = 0.5, P<.001). The median survival among all patients was 25.5 months and was significantly different among survival groups (in group 1 [excellent prognosis], median survival was not reached; group 2 reached 32.4 months; group 3 reached 22.2 months; and group 4 [poor prognosis] reached 9.1 months; P<.001). Pretreatment symptom burden was significantly higher in the patient group with poor survival than in the group with excellent survival (all metrics, P<.05). Conclusions: We developed the prognostic index for spinal metastases (PRISM) model, a new model that identified patient subgroups with poor and excellent prognoses.« less

Assessment of an ensemble seasonal streamflow forecasting system for Australia

NASA Astrophysics Data System (ADS)

Bennett, James C.; Wang, Quan J.; Robertson, David E.; Schepen, Andrew; Li, Ming; Michael, Kelvin

2017-11-01

Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean-land-atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall-runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall-runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall-runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.

Dual Pathways from Reactive Aggression to Depressive Symptoms in Children: Further Examination of the Failure Model.

PubMed

Evans, Spencer C; Fite, Paula J

2018-04-13

The failure model posits that peer rejection and poor academic performance are dual pathways in the association between early aggressive behavior and subsequent depressive symptoms. We examined this model using an accelerated longitudinal design while also incorporating proactive and reactive aggression and gender moderation. Children in 1st, 3rd, and 5th grades (n = 912; ages 6-12; 48% female) were rated three times annually by their primary teachers on measures of proactive and reactive aggression, peer rejection, academic performance, and depressive symptoms. Using Bayesian cross-classified estimation to account for nested and planned-missing data, path models were estimated to examine whether early reactive aggression predicted subsequent peer rejection and academic performance, and whether these, in turn, predicted subsequent depressive symptoms. From 1st to 3rd grade, reactive aggression predicted peer rejection (not academic performance), proactive aggression predicted academic performance (not peer rejection), and academic performance and peer rejection both predicted depressive symptoms. From 3rd to 5th grade, however, neither peer rejection nor academic performance predicted subsequent depressive symptoms. Results were not moderated by gender. Overall, these findings provide mixed and limited support for the failure model among school-age children. Early reactive aggression may be a key risk factor for social problems, whereas proactive aggression may be linked to improved academic functioning. The "dual pathways" of peer rejection and academic performance may operate during early but not later elementary school. Limitations and implications are discussed.

Poor Gait Performance and Prediction of Dementia: Results From a Meta-Analysis.

PubMed

Beauchet, Olivier; Annweiler, Cédric; Callisaya, Michele L; De Cock, Anne-Marie; Helbostad, Jorunn L; Kressig, Reto W; Srikanth, Velandai; Steinmetz, Jean-Paul; Blumen, Helena M; Verghese, Joe; Allali, Gilles

2016-06-01

Poor gait performance predicts risk of developing dementia. No structured critical evaluation has been conducted to study this association yet. The aim of this meta-analysis was to systematically examine the association of poor gait performance with incidence of dementia. An English and French Medline search was conducted in June 2015, with no limit of date, using the medical subject headings terms "Gait" OR "Gait Disorders, Neurologic" OR "Gait Apraxia" OR "Gait Ataxia" AND "Dementia" OR "Frontotemporal Dementia" OR "Dementia, Multi-Infarct" OR "Dementia, Vascular" OR "Alzheimer Disease" OR "Lewy Body Disease" OR "Frontotemporal Dementia With Motor Neuron Disease" (Supplementary Concept). Poor gait performance was defined by standardized tests of walking, and dementia was diagnosed according to international consensus criteria. Four etiologies of dementia were identified: any dementia, Alzheimer disease (AD), vascular dementia (VaD), and non-AD (ie, pooling VaD, mixed dementias, and other dementias). Fixed effects meta-analyses were performed on the estimates in order to generate summary values. Of the 796 identified abstracts, 12 (1.5%) were included in this systematic review and meta-analysis. Poor gait performance predicted dementia [pooled hazard ratio (HR) combined with relative risk and odds ratio = 1.53 with P < .001 for any dementia, pooled HR = 1.79 with P < .001 for VaD, HR = 1.89 with P value < .001 for non-AD]. Findings were weaker for predicting AD (HR = 1.03 with P value = .004). This meta-analysis provides evidence that poor gait performance predicts dementia. This association depends on the type of dementia; poor gait performance is a stronger predictor of non-AD dementias than AD. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Interactions between Arctic sea ice drift, concentration and thickness modeled by NEMO-LIM3 at different resolutions

NASA Astrophysics Data System (ADS)

Docquier, David; Massonnet, François; Raulier, Jonathan; Lecomte, Olivier; Fichefet, Thierry

2016-04-01

Sea ice concentration and thickness have substantially decreased in the Arctic since the beginning of the satellite era. As a result, mechanical strength has decreased allowing more fracturing and leading to increased sea ice drift. However, recent studies have highlighted that the interplay between sea ice thermodynamics and dynamics is poorly represented in contemporary global climate model (GCM) simulations. Thus, the considerable inter-model spread in terms of future sea ice extent projections could be reduced by better understanding the interactions between drift, concentration and thickness. This study focuses on the results coming from the global coupled ocean-sea ice model NEMO-LIM3 between 1979 and 2012. Three different simulations are forced by the Drakkar Forcing Set (DFS) 5.2 and run on the global tripolar ORCA grid at spatial resolutions of 0.25, 1° and 2°. The relation between modeled sea ice drift, concentration and thickness is further analyzed, compared to observations and discussed in the framework of the above-mentioned poor representation. It is proposed as a process-based metric for evaluating model performance. This study forms part of the EU Horizon 2020 PRIMAVERA project aiming at developing a new generation of advanced and well-evaluated high-resolution GCMs.

A Systematic Approach to the Study of Accelerated weathering of Building Joint Sealants

Treesearch

Christopher C. White; Donald L. Hunston; Kar Tean Tan; James J. Filliben; Adam L. Pintar; Greg Schueneman

2012-01-01

An accurate service life prediction model is needed for building joint sealants in order to greatly reduce the time to market of a new product and reduce the risk of introducing a poorly performing product into the marketplace. A stepping stone to the success of this effort is the precise control of environmental variables in a laboratory accelerated test apparatus in...

Robust Adaptive Control Using a Filtering Action

DTIC Science & Technology

2009-09-01

research performed on this class of control systems , sensitivity to external disturbances and modeling errors together with poor transient response...dissertation, we address the problems of designing a class of Adaptive Control systems which yield fast adaptation, thus good transient response, and...unable to stabilize the system . Although this approach requires more knowledge about the system in order to control it, it is still attractive in cases

Diagnosing Expertise: Human Capital, Decision Making, and Performance among Physicians

PubMed Central

Currie, Janet; MacLeod, W. Bentley

2017-01-01

Expert performance is often evaluated assuming that good experts have good outcomes. We examine expertise in medicine and develop a model that allows for two dimensions of physician performance: decision making and procedural skill. Better procedural skill increases the use of intensive procedures for everyone, while better decision making results in a reallocation of procedures from fewer low-risk to high-risk cases. We show that poor diagnosticians can be identified using administrative data and that improving decision making improves birth outcomes by reducing C-section rates at the bottom of the risk distribution and increasing them at the top of the distribution. PMID:29276336

Feedforward object-vision models only tolerate small image variations compared to human

PubMed Central

Ghodrati, Masoud; Farzmahdi, Amirhossein; Rajaei, Karim; Ebrahimpour, Reza; Khaligh-Razavi, Seyed-Mahdi

2014-01-01

Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modeling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well in image categorization under more complex image variations. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e., briefly presented masked stimuli with complex image variations), human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modeling. We show that this approach is not of significant help in solving the computational crux of object recognition (i.e., invariant object recognition) when the identity-preserving image variations become more complex. PMID:25100986

Review of Methods for Buildings Energy Performance Modelling

NASA Astrophysics Data System (ADS)

Krstić, Hrvoje; Teni, Mihaela

2017-10-01

Research presented in this paper gives a brief review of methods used for buildings energy performance modelling. This paper gives also a comprehensive review of the advantages and disadvantages of available methods as well as the input parameters used for modelling buildings energy performance. European Directive EPBD obliges the implementation of energy certification procedure which gives an insight on buildings energy performance via exiting energy certificate databases. Some of the methods for buildings energy performance modelling mentioned in this paper are developed by employing data sets of buildings which have already undergone an energy certification procedure. Such database is used in this paper where the majority of buildings in the database have already gone under some form of partial retrofitting - replacement of windows or installation of thermal insulation but still have poor energy performance. The case study presented in this paper utilizes energy certificates database obtained from residential units in Croatia (over 400 buildings) in order to determine the dependence between buildings energy performance and variables from database by using statistical dependencies tests. Building energy performance in database is presented with building energy efficiency rate (from A+ to G) which is based on specific annual energy needs for heating for referential climatic data [kWh/(m2a)]. Independent variables in database are surfaces and volume of the conditioned part of the building, building shape factor, energy used for heating, CO2 emission, building age and year of reconstruction. Research results presented in this paper give an insight in possibilities of methods used for buildings energy performance modelling. Further on it gives an analysis of dependencies between buildings energy performance as a dependent variable and independent variables from the database. Presented results could be used for development of new building energy performance predictive model.

Potential role of maternal lineage in the thoroughbred breeding strategy.

PubMed

Lin, Xiang; Zhou, Shi; Wen, Li; Davie, Allan; Yao, Xinkui; Liu, Wujun; Zhang, Yong

2015-05-05

Many studies have focused on identifying the genes or single nucleotide polymorphisms associated with the athletic ability of thoroughbreds, but few have considered differences in maternal and paternal heritability of athletic ability. Herein, we report on our association study of career race performances of 675 Australian thoroughbreds with their pedigrees. Racing performance data (prize money per start) were collected from the Bloodhound database. The performance of all horses was categorised as either poor or elite athletic achievement. Then, 675 foals were divided by their parents' performance (elite or poor) into four groups: (1) elite dams and elite sires; (2) elite dams and poor sires; (3) poor dams and elite sires; and (4) poor dams and poor sires. The performance of foals was then compared between the four groups. The results show that the heritability of race performance between dams and foals (r = 0.141, P < 0.001) is much higher than that between sires and foals (r = 0.035, P = 0.366), and that this difference is statistically significant (P < 0.05). We also examined the effect of the child-bearing age of dams and sires on the ratio of elite foals. We found a strong correlation between the number of elite foals and dams' child-bearing age (r = -0.105, P < 0.001), with the ratio of elite offspring reaching a high level between a child-bearing age of 8 and 11 years (χ2 = 14.31, d.f. = 1, P < 0.001). These findings suggest that the maternal line may play an important role in the selective breeding of athletic performance in thoroughbreds.

Non-compliance to the continuous ambulatory peritoneal dialysis procedure increases the risk of peritonitis.

PubMed

Mawar, Shashi; Gupta, Sanjay; Mahajan, Sandeep

2012-08-01

Peritonitis in patients on continuous ambulatory peritoneal dialysis (CAPD) is the leading cause of technique failure. Information on the impact of non-compliance in performing CAPD exchange on peritonitis is limited. We aimed to find the prevalence of non-compliance to the CAPD procedure and its influence on the incidence of peritonitis. This observational study included 30 adult patients undergoing CAPD. The CAPD exchange procedure was observed at home and assessed as per the structured checklist and categorized into poor, average and good compliance. The compliance was correlated with the episodes of peritonitis in previous 1 year. The patients' mean age was 52 ± 13 years and the mean duration of CAPD was 2.1 ± 0.9 years. Only 16.5% of patients were good performers, while 67% were average performers, and 16.5% were poor performers. The technique skill was similar across all the steps of the procedure. The most common improperly performed steps were: not putting on a face mask in 68%, not flushing the tubing system in 60%, and not washing hands in 24%. Poor adherence to procedure was independent of age, gender, education and duration of dialysis. Ten episodes of peritonitis occurred in 5 patients over 1-year period. Peritonitis occurred in 60% of poor performers, whereas fully compliant patients had no peritonitis. Also 40% of the poorly compliant patients had multiple episodes of peritonitis. Poor compliance in performing the CAPD procedure is a modifiable risk factor for peritonitis. Adherence to recommended aseptic technique is the cornerstone of peritonitis prevention.

Perceptions of good medical practice in the NHS: a survey of senior health professionals.

PubMed

Hutchinson, A; Williams, M; Meadows, K; Barbour, R S; Jones, R

1999-12-01

To categorize senior health professionals' experience with poor medical practice in hospitals and in general practice, to describe perceptions which senior NHS staff have of good medical practice, and to describe how problems of poor medical practice are currently managed. A postal questionnaire survey. The questionnaire sought perceptions of good medical practice, asked participants to characterise deviations from good practice, and to describe experience with managing poor performance at the time of the introduction of the General Medical Council (GMC) performance procedures. A range of NHS settings in the UK: hospital trusts, health authorities/boards, local medical committees, community health councils. Senior health professionals involved in the management of medical professional performance. Perceptions of what constitutes good medical practice. Most respondents considered that persistent problems related to clinical practice (diagnosis, management, and outcome and prescribing) would require local management and, possibly, referral to the GMC performance procedures. Informal mechanisms, including informal discussion, education, training, and work shifting, were the most usual means of handling a doctor whose performance was poor. Many took a less serious view of deficiencies in performance on manner and attitude and communication, although consultation skills rather than technical skills comprised the greatest number of complaints about doctors. Senior NHS professionals seem reluctant to consider persistently poor consultation skills in the same critical light as they do persistently poor technical practice. These attitudes may need to change with the implementation of clinical governance and updated guidance from the GMC on what constitutes good medical practice.

Multivariate Analysis of Seismic Field Data

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

Alam, M. Kathleen

1999-06-01

This report includes the details of the model building procedure and prediction of seismic field data. Principal Components Regression, a multivariate analysis technique, was used to model seismic data collected as two pieces of equipment were cycled on and off. Models built that included only the two pieces of equipment of interest had trouble predicting data containing signals not included in the model. Evidence for poor predictions came from the prediction curves as well as spectral F-ratio plots. Once the extraneous signals were included in the model, predictions improved dramatically. While Principal Components Regression performed well for the present datamore » sets, the present data analysis suggests further work will be needed to develop more robust modeling methods as the data become more complex.« less

Modelling invasion for a habitat generalist and a specialist plant species

USGS Publications Warehouse

Evangelista, P.H.; Kumar, S.; Stohlgren, T.J.; Jarnevich, C.S.; Crall, A.W.; Norman, J. B.; Barnett, D.T.

2008-01-01

Predicting suitable habitat and the potential distribution of invasive species is a high priority for resource managers and systems ecologists. Most models are designed to identify habitat characteristics that define the ecological niche of a species with little consideration to individual species' traits. We tested five commonly used modelling methods on two invasive plant species, the habitat generalist Bromus tectorum and habitat specialist Tamarix chinensis, to compare model performances, evaluate predictability, and relate results to distribution traits associated with each species. Most of the tested models performed similarly for each species; however, the generalist species proved to be more difficult to predict than the specialist species. The highest area under the receiver-operating characteristic curve values with independent validation data sets of B. tectorum and T. chinensis was 0.503 and 0.885, respectively. Similarly, a confusion matrix for B. tectorum had the highest overall accuracy of 55%, while the overall accuracy for T. chinensis was 85%. Models for the generalist species had varying performances, poor evaluations, and inconsistent results. This may be a result of a generalist's capability to persist in a wide range of environmental conditions that are not easily defined by the data, independent variables or model design. Models for the specialist species had consistently strong performances, high evaluations, and similar results among different model applications. This is likely a consequence of the specialist's requirement for explicit environmental resources and ecological barriers that are easily defined by predictive models. Although defining new invaders as generalist or specialist species can be challenging, model performances and evaluations may provide valuable information on a species' potential invasiveness.

The application of dummy noise adaptive Kalman filter in underwater navigation

NASA Astrophysics Data System (ADS)

Li, Song; Zhang, Chun-Hua; Luan, Jingde

2011-10-01

The track of underwater target is easy to be affected by the various by the various factors, which will cause poor performance in Kalman filter with the error in the state and measure model. In order to solve the situation, a method is provided with dummy noise compensative technology. Dummy noise is added to state and measure model artificially, and then the question can be solved by the adaptive Kalman filter with unknown time-changed statistical character. The simulation result of underwater navigation proves the algorithm is effective.

An Evaluation of the Performance Diagnostic Checklist-Human Services to Assess an Employee Performance Problem in a Center-Based Autism Treatment Facility

ERIC Educational Resources Information Center

Ditzian, Kyle; Wilder, David A.; King, Allison; Tanz, Jeanine

2015-01-01

The Performance Diagnostic Checklist-Human Services (PDC-HS) is an informant-based tool designed to assess the environmental variables that contribute to poor employee performance in human services settings. We administered the PDC-HS to 3 supervisors to assess the variables that contributed to poor performance by 4 staff members when securing…

Standard & Poor's "Return on Resources" Measure of School Performance. Issue Brief. Volume 1, Issue 1

ERIC Educational Resources Information Center

Reeder, Brian

2004-01-01

Standard & Poors (S&P) uses a measure they call a Performance Cost Index (PCI) as their measure of a school or district?s ?Return on Resources?. The Performance Cost Index is defined as the average cost per measured ?unit? of student performance. In its simplest form, the Performance Cost Index is calculated as per student expenditures divided by…

Numerical Ergonomics Analysis in Operation Environment of CNC Machine

NASA Astrophysics Data System (ADS)

Wong, S. F.; Yang, Z. X.

2010-05-01

The performance of operator will be affected by different operation environments [1]. Moreover, poor operation environment may cause health problems of the operator [2]. Physical and psychological considerations are two main factors that will affect the performance of operator under different conditions of operation environment. In this paper, applying scientific and systematic methods find out the pivot elements in the field of physical and psychological factors. There are five main factors including light, temperature, noise, air flow and space that are analyzed. A numerical ergonomics model has been built up regarding the analysis results which can support to advance the design of operation environment. Moreover, the output of numerical ergonomic model can provide the safe, comfortable, more productive conditions for the operator.

An experimental investigation of hingeless helicopter rotor-body stability in hover

NASA Technical Reports Server (NTRS)

Bousman, W. G.

1978-01-01

Model tests of a 1.62 m diameter rotor were performed to investigate the aeromechanical stability of coupled rotor-body systems in hover. Experimental measurements were made of modal frequencies and damping over a wide range of rotor speeds. Good data were obtained for the frequencies of the rotor lead-lag regressing mode. The quality of the damping measurements of the body modes was poor due to nonlinear damping in the gimbal ball bearings. Simulated vacuum testing was performed using substitute blades of tantalum that reduced the effective lock number to 0.2% of the model scale value while keeping the blade inertia constant. The experimental data were compared with theoretical predictions, and the correlation was in general very good.

A tissue-engineered subcutaneous pancreatic cancer model for antitumor drug evaluation.

PubMed

He, Qingyi; Wang, Xiaohui; Zhang, Xing; Han, Huifang; Han, Baosan; Xu, Jianzhong; Tang, Kanglai; Fu, Zhiren; Yin, Hao

2013-01-01

The traditional xenograft subcutaneous pancreatic cancer model is notorious for its low incidence of tumor formation, inconsistent results for the chemotherapeutic effects of drug molecules of interest, and a poor predictive capability for the clinical efficacy of novel drugs. These drawbacks are attributed to a variety of factors, including inoculation of heterogeneous tumor cells from patients with different pathological histories, and use of poorly defined Matrigel(®). In this study, we aimed to tissue-engineer a pancreatic cancer model that could readily cultivate a pancreatic tumor derived from highly homogenous CD24(+)CD44(+) pancreatic cancer stem cells delivered by a well defined electrospun scaffold of poly(glycolide-co-trimethylene carbonate) and gelatin. The scaffold supported in vitro tumorigenesis from CD24(+)CD44(+) cancer stem cells for up to 7 days without inducing apoptosis. Moreover, CD24(+)CD44(+) cancer stem cells delivered by the scaffold grew into a native-like mature pancreatic tumor within 8 weeks in vivo and exhibited accelerated tumorigenesis as well as a higher incidence of tumor formation than the traditional model. In the scaffold model, we discovered that oxaliplatin-gemcitabine (OXA-GEM), a chemotherapeutic regimen, induced tumor regression whereas gemcitabine alone only capped tumor growth. The mechanistic study attributed the superior antitumorigenic performance of OXA-GEM to its ability to induce apoptosis of CD24(+)CD44(+) cancer stem cells. Compared with the traditional model, the scaffold model demonstrated a higher incidence of tumor formation and accelerated tumor growth. Use of a tiny population of highly homogenous CD24(+)CD44(+) cancer stem cells delivered by a well defined scaffold greatly reduces the variability associated with the traditional model, which uses a heterogeneous tumor cell population and poorly defined Matrigel. The scaffold model is a robust platform for investigating the antitumorigenesis mechanism of novel chemotherapeutic drugs with a special focus on cancer stem cells.

Air-liquid interface exposure to aerosols of poorly soluble nanomaterials induces different biological activation levels compared to exposure to suspensions.

PubMed

Loret, Thomas; Peyret, Emmanuel; Dubreuil, Marielle; Aguerre-Chariol, Olivier; Bressot, Christophe; le Bihan, Olivier; Amodeo, Tanguy; Trouiller, Bénédicte; Braun, Anne; Egles, Christophe; Lacroix, Ghislaine

2016-11-03

Recently, much progress has been made to develop more physiologic in vitro models of the respiratory system and improve in vitro simulation of particle exposure through inhalation. Nevertheless, the field of nanotoxicology still suffers from a lack of relevant in vitro models and exposure methods to predict accurately the effects observed in vivo, especially after respiratory exposure. In this context, the aim of our study was to evaluate if exposing pulmonary cells at the air-liquid interface to aerosols of inhalable and poorly soluble nanomaterials generates different toxicity patterns and/or biological activation levels compared to classic submerged exposures to suspensions. Three nano-TiO 2 and one nano-CeO 2 were used. An exposure system was set up using VitroCell® devices to expose pulmonary cells at the air-liquid interface to aerosols. A549 alveolar cells in monocultures or in co-cultures with THP-1 macrophages were exposed to aerosols in inserts or to suspensions in inserts and in plates. Submerged exposures in inserts were performed, using similar culture conditions and exposure kinetics to the air-liquid interface, to provide accurate comparisons between the methods. Exposure in plates using classical culture and exposure conditions was performed to provide comparable results with classical submerged exposure studies. The biological activity of the cells (inflammation, cell viability, oxidative stress) was assessed at 24 h and comparisons of the nanomaterial toxicities between exposure methods were performed. Deposited doses of nanomaterials achieved using our aerosol exposure system were sufficient to observe adverse effects. Co-cultures were more sensitive than monocultures and biological responses were usually observed at lower doses at the air-liquid interface than in submerged conditions. Nevertheless, the general ranking of the nanomaterials according to their toxicity was similar across the different exposure methods used. We showed that exposure of cells at the air-liquid interface represents a valid and sensitive method to assess the toxicity of several poorly soluble nanomaterials. We underlined the importance of the cellular model used and offer the possibility to deal with low deposition doses by using more sensitive and physiologic cellular models. This brings perspectives towards the use of relevant in vitro methods of exposure to assess nanomaterial toxicity.

High dimensional biological data retrieval optimization with NoSQL technology.

PubMed

Wang, Shicai; Pandis, Ioannis; Wu, Chao; He, Sijin; Johnson, David; Emam, Ibrahim; Guitton, Florian; Guo, Yike

2014-01-01

High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating tranSMART's implementation to a more scalable solution for Big Data.

High dimensional biological data retrieval optimization with NoSQL technology

PubMed Central

2014-01-01

Background High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating tranSMART's implementation to a more scalable solution for Big Data. PMID:25435347

Human performance modeling for system of systems analytics: combat performance-shaping factors.

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

Lawton, Craig R.; Miller, Dwight Peter

The US military has identified Human Performance Modeling (HPM) as a significant requirement and challenge of future systems modeling and analysis initiatives. To support this goal, Sandia National Laboratories (SNL) has undertaken a program of HPM as an integral augmentation to its system-of-system (SoS) analytics capabilities. The previous effort, reported in SAND2005-6569, evaluated the effects of soldier cognitive fatigue on SoS performance. The current effort began with a very broad survey of any performance-shaping factors (PSFs) that also might affect soldiers performance in combat situations. The work included consideration of three different approaches to cognition modeling and how appropriate theymore » would be for application to SoS analytics. This bulk of this report categorizes 47 PSFs into three groups (internal, external, and task-related) and provides brief descriptions of how each affects combat performance, according to the literature. The PSFs were then assembled into a matrix with 22 representative military tasks and assigned one of four levels of estimated negative impact on task performance, based on the literature. Blank versions of the matrix were then sent to two ex-military subject-matter experts to be filled out based on their personal experiences. Data analysis was performed to identify the consensus most influential PSFs. Results indicate that combat-related injury, cognitive fatigue, inadequate training, physical fatigue, thirst, stress, poor perceptual processing, and presence of chemical agents are among the PSFs with the most negative impact on combat performance.« less

Job satisfaction and its modeling among township health center employees: a quantitative study in poor rural China.

PubMed

Liu, Jun A; Wang, Qi; Lu, Zu X

2010-05-10

Job satisfaction is important to staff management of township health centers (THCs), as it is associated with organizational performance, quality of care and employee retention. The purpose of this study was to measure job satisfaction level of THC employees in poor rural China and to identify relevant features in order to provide policy advice on human resource development of health service institutions in poor regions. A self-completion questionnaire was used to assess the job satisfaction and relevant features (response rate: 90.5%) among 172 employees (i.e., clinic doctors, medico-technical workers and public health workers) of 17 THCs in Anhui and Xinjiang provinces of China. The study covered a time period of two months in 2007. The mean staff job satisfaction scored 83.3, which was in the category of "somewhat satisfied" on a scale ranging from 0 (extremely dissatisfied) to 100 (extremely satisfied) by employing Likert's transformation formula. Exploratory factor analysis (EFA) revealed eight domains involved in modeling of job satisfaction, among which, the caregivers were more satisfied with job significance (88.2), job competency (87.9) and teamwork (87.7), as compared with work reward (72.9) and working conditions (79.7). Mean job satisfaction in Xinjiang (89.7) was higher than that in Anhui (75.5). Employees of THCs have moderate job satisfactions in poor areas, which need to be raised further by improving their working conditions and reward.

Non-LTE line formation of Fe in late-type stars - III. 3D non-LTE analysis of metal-poor stars

NASA Astrophysics Data System (ADS)

Amarsi, A. M.; Lind, K.; Asplund, M.; Barklem, P. S.; Collet, R.

2016-12-01

As one of the most important elements in astronomy, iron abundance determinations need to be as accurate as possible. We investigate the accuracy of spectroscopic iron abundance analyses using archetypal metal-poor stars. We perform detailed 3D non-LTE radiative transfer calculations based on 3D hydrodynamic STAGGER model atmospheres, and employ a new model atom that includes new quantum-mechanical neutral hydrogen collisional rate coefficients. With the exception of the red giant HD122563, we find that the 3D non-LTE models achieve Fe I/Fe II excitation and ionization balance as well as not having any trends with equivalent width to within modelling uncertainties of 0.05 dex, all without having to invoke any microturbulent broadening; for HD122563 we predict that the current best parallax-based surface gravity is overestimated by 0.5 dex. Using a 3D non-LTE analysis, we infer iron abundances from the 3D model atmospheres that are roughly 0.1 dex higher than corresponding abundances from 1D MARCS model atmospheres; these differences go in the same direction as the non-LTE effects themselves. We make available grids of departure coefficients, equivalent widths and abundance corrections, calculated on 1D MARCS model atmospheres and horizontally and temporally averaged 3D STAGGER model atmospheres.

Leisure-Time Physical Activity and Academic Performance: Cross-Lagged Associations from Adolescence to Young Adulthood

PubMed Central

Aaltonen, Sari; Latvala, Antti; Rose, Richard J.; Kujala, Urho M.; Kaprio, Jaakko; Silventoinen, Karri

2016-01-01

Physical activity and academic performance are positively associated, but the direction of the association is poorly understood. This longitudinal study examined the direction and magnitude of the associations between leisure-time physical activity and academic performance throughout adolescence and young adulthood. The participants were Finnish twins (from 2,859 to 4,190 individuals/study wave) and their families. In a cross-lagged path model, higher academic performance at ages 12, 14 and 17 predicted higher leisure-time physical activity at subsequent time-points (standardized path coefficient at age 14: 0.07 (p < 0.001), age 17: 0.12 (p < 0.001) and age 24: 0.06 (p < 0.05)), whereas physical activity did not predict future academic performance. A cross-lagged model of co-twin differences suggested that academic performance and subsequent physical activity were not associated due to the environmental factors shared by co-twins. Our findings suggest that better academic performance in adolescence modestly predicts more frequent leisure-time physical activity in late adolescence and young adulthood. PMID:27976699

Leisure-Time Physical Activity and Academic Performance: Cross-Lagged Associations from Adolescence to Young Adulthood.

PubMed

Aaltonen, Sari; Latvala, Antti; Rose, Richard J; Kujala, Urho M; Kaprio, Jaakko; Silventoinen, Karri

2016-12-15

Physical activity and academic performance are positively associated, but the direction of the association is poorly understood. This longitudinal study examined the direction and magnitude of the associations between leisure-time physical activity and academic performance throughout adolescence and young adulthood. The participants were Finnish twins (from 2,859 to 4,190 individuals/study wave) and their families. In a cross-lagged path model, higher academic performance at ages 12, 14 and 17 predicted higher leisure-time physical activity at subsequent time-points (standardized path coefficient at age 14: 0.07 (p < 0.001), age 17: 0.12 (p < 0.001) and age 24: 0.06 (p < 0.05)), whereas physical activity did not predict future academic performance. A cross-lagged model of co-twin differences suggested that academic performance and subsequent physical activity were not associated due to the environmental factors shared by co-twins. Our findings suggest that better academic performance in adolescence modestly predicts more frequent leisure-time physical activity in late adolescence and young adulthood.

Simulation analysis of capacity and performance improvement in wastewater treatment plants: Case study of Alexandria eastern plant

NASA Astrophysics Data System (ADS)

Moursy, Aly; Sorour, Mohamed T.; Moustafa, Medhat; Elbarqi, Walid; Fayd, Mai; Elreedy, Ahmed

2018-05-01

This study concerns the upgrading of a real domestic wastewater treatment plant (WWTP) supported by simulation. The main aims of this work are to: (1) decide between two technologies to improve WWTP capacity and its nitrogen removal efficiency; membrane bioreactor (MBR) and integrated fixed film activated sludge (IFAS), and (2) perform a cost estimation analysis for the two proposed solutions. The model used was calibrated based on data from the existing WWTP, namely, Eastern plant and located in Alexandria, Egypt. The activated sludge model No. 1 (ASM1) was considered in the model analysis by GPS-X 7 software. Steady-state analysis revealed that high performances corresponded to high compliance with Egyptian standards were achieved by the two techniques; however, MBR was better. Nonetheless, the two systems showed poor nitrogen removal efficiency according to the current situation, which reveals that the plant needs a modification to add an anaerobic treatment unit before the aerobic zone.

Analysis of Free Modeling Predictions by RBO Aleph in CASP11

PubMed Central

Mabrouk, Mahmoud; Werner, Tim; Schneider, Michael; Putz, Ines; Brock, Oliver

2015-01-01

The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue–residue contact prediction by EPC-map and contact–guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. PMID:26492194

20 CFR 632.23 - Termination and corrective action of a CAP and/or Master Plan.

Code of Federal Regulations, 2010 CFR

2010-04-01

... substantiates serious management, fiscal and/or performance problems, information from the Inspector General or gained through incident reports of poor performance, serious administrative problems and/or inability to... termination: (1) Poor performance and inability to meet Federal standards related to such debt collection...

Prognostic indicators associated with early mortality of wild raptors admitted to a wildlife rehabilitation centre in Spain.

PubMed

Molina-López, Rafael A; Casal, Jordi; Darwich, Laila

2015-03-01

Assessment of the prognostic indicators of wildlife casualties is critical in wildlife rehabilitation practice, to optimize the use of economical resources, and to protect animal welfare. Few studies have been conducted in this field. To identify the prognostic indicators associated with raptor mortality during the first week of hospitalization. Complete medical records of 1722 wild raptor cases admitted to a wildlife rehabilitation centre from 1995 to 2007 were used. Regression models were created to determine mortality-related factors for different variables (order, sex, body condition (BC), clinical signs, and available haematological and biochemical parameters). In the bivariate analysis, the presence of nervous (OR = 11.9, 95%CI:5.1-27.6) or musculoskeletal (OR = 12.1, 95%CI:5.8-25.3) signs, a poor BC (OR = 32.9, 95%CI:19-81.2), and low values of packed cell volume (PCV), haemoglobin or total solids (TS), were all associated with early mortality. After adjusting variables in the multivariate model, BC was excluded due to co-linearity with other variables, and alteration of the nervous system was the only significant risk factor (OR = 4.0; 95%CI:1.9-8.8). In species specific analysis, poor prognosis was related to neurological signs in Athene noctua, poor BC in Strix aluco, trauma in Acciptiter nisus and Tyto alba, low PCV in Buteo buteo and Falco tinnunculus and low TS in Falco tinnunculus. Raptors with a poor BC, low values of PCV and those presenting with neurological signs, had the highest risk of dying in the first days of admittance. Thus, either medical care or humane euthanasia for poor prognosis should be performed to address animal welfare.

Sleep problems are associated with poor outcomes in remedial teaching programmes: a preliminary study.

PubMed

Blunden, Sarah L; Chervin, Ron D

2008-05-01

Problematic behaviour and deficient academic performance have been reported in children with sleep problems, but whether sleep problems are common among children presenting with primary behavioural and performance concerns in remedial programmes is not well studied. We studied this possibility in 80 Australian school children aged 6-15 years and then compared 15 of these children from mainstream schools to 15 demographically matched children in specialist behavioural programmes for problematic behaviour and academic difficulties. Parents completed the Child Behaviour Checklist and the Sleep Disorders Scale for Children. Questionnaires assessed behaviour, academic performance and symptoms of diverse sleep disorders, expressed as T-scores (mean (SD) = 50 (10)). Teachers rated students' academic performance (A, B, C, D, E). When compared with the 15 controls, the 15 index children had significantly more sleep problems, in addition to parental concerns about school performance. In the total sample (n = 80), poor sleep including symptoms of daytime sleepiness, parasomnias, behavioural sleep problems and combined sleep problems was associated with poor academic performance and daytime behavioural issues. This preliminary study suggests that children in remedial school programmes may have poor sleep compared with those in mainstream schools. Sleep problems were associated with problematic behaviour and poor academic performance. If sleep disturbances worsen daytime behaviour, then diagnosis and treatment of underlying sleep disorders could offer a novel therapeutic opportunity.

Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

NASA Astrophysics Data System (ADS)

Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

Educational attainment in poor comprehenders

PubMed Central

Ricketts, Jessie; Sperring, Rachael; Nation, Kate

2014-01-01

To date, only one study has investigated educational attainment in poor (reading) comprehenders, providing evidence of poor performance on national UK school tests at age 11 years relative to peers (Cain and Oakhill, 2006). In the present study, we adopted a longitudinal approach, tracking attainment on such tests from 11 years to the end of compulsory schooling in the UK (age 16 years). We aimed to investigate the proposal that educational weaknesses (defined as poor performance on national assessments) might become more pronounced over time, as the curriculum places increasing demands on reading comprehension. Participants comprised 15 poor comprehenders and 15 controls; groups were matched for chronological age, nonverbal reasoning ability and decoding skill. Children were identified at age 9 years using standardized measures of nonverbal reasoning, decoding and reading comprehension. These measures, along with a measure of oral vocabulary knowledge, were repeated at age 11 years. Data on educational attainment were collected from all participants (n = 30) at age 11 and from a subgroup (n = 21) at 16 years. Compared to controls, educational attainment in poor comprehenders was lower at ages 11 and 16 years, an effect that was significant at 11 years. When poor comprehenders were compared to national performance levels, they showed significantly lower performance at both time points. Low educational attainment was not evident for all poor comprehenders. Nonetheless, our findings point to a link between reading comprehension difficulties in mid to late childhood and poor educational outcomes at ages 11 and 16 years. At these ages, pupils in the UK are making key transitions: they move from primary to secondary schools at 11, and out of compulsory schooling at 16. PMID:24904464

Association between overweight and obesity with school performance in secondary students in Merida, Mexico.

PubMed

Salazar-Rendón, Juan Carlos; Méndez, Nina; Azcorra, Hugo

2018-01-01

Some studies have found a negative relationship between obesity and school performance in scholars. However, this topic has not been studied in depth in Mexico. The aim of this study was to analyze the association between overweight and obesity with school performance in secondary school students from Merida. Weight and height were measured, and body mass index was calculated in a sample of 566 secondary students in Merida. Nutritional status was classified in normal weight (-2-<+1 standard deviation [SD]), overweight (+1-<2 SD) and obesity (> + 2 SD) according to the World Health Organization criteria. The scores in language, mathematics and sciences were used as indicators of school performance. Good performance was considered when the scores were ≥8 points, and poor performance when scores were <8 points. Logistic regression models were used to analyse the association between the variables. The 44% of the sample met the criteria for overweight and obesity. After adjusting for school grade, type of school, number of absences, and Mayan surnames, we found that girls classified as obese had a significant risk of a poor performance in mathematics (odds ratio [OR]: 3.07; 95% confidence interval [CI]: 1.39-6.80) and language (OR: 2.55; 95% CI: 1.14-5.71) compared with those with healthy weight. Our results suggest that obesity represents a risk of having a lower school performance in girls but not in boys. Copyright: © 2018 Permanyer.

Association between Self-Reported Academic Performance and Risky Sexual Behavior among Ugandan University Students- A Cross Sectional Study

PubMed Central

Mehra, Devika; Kyagaba, Emmanuel; Östergren, Per-Olof; Agardh, Anette

2014-01-01

Little is known about the association between self-reported academic performance and risky sexual behaviors and if this differs by gender, among university students. Academic performance can create psychological pressure in young students. Poor academic performance might thus potentially contribute to risky sexual behavior among university students. The aim of this study was to investigate the association between self-reported academic performance and risky sexual behaviors, and whether gender affects this relationship among Ugandan university students. In 2010, 1,954 students participated in a cross-sectional survey, conducted at Mbarara University of Science and Technology in southwestern Uganda (72% response rate). Multivariate logistic regression analysis was used for the analysis. 1,179 (60.3%) students in our study sample reported having debuted sexually. Of these 440 (42.2%) used condoms inconsistently with new sexual partners, and 344 (33.6%) had had multiple sexual partners. We found a statistically significant association between poor academic performance and inconsistent condom use with a new sex partner and this association remained significant even after adjusting for all the potential confounders. There was no such association detected regarding multiple sexual partners. We also found that gender modified the effect of poor academic performance on inconsistent condom use. Females, who were poor academic performers, were found to be at a higher risk of inconsistent condom use than their male counterparts. Interventions should be designed to provide extra support to poor academic performers, which may improve their performance and self-esteem, which in turn might reduce their risky sexual behaviors. PMID:24999121

Association between self-reported academic performance and risky sexual behavior among Ugandan university students- a cross sectional study.

PubMed

Mehra, Devika; Kyagaba, Emmanuel; Ostergren, Per-Olof; Agardh, Anette

2014-04-16

Little is known about the association between self-reported academic performance and risky sexual behaviors and if this differs by gender, among university students. Academic performance can create psychological pressure in young students. Poor academic performance might thus potentially contribute to risky sexual behavior among university students. The aim of this study was to investigate the association between self-reported academic performance and risky sexual behaviors, and whether gender affects this relationship among Ugandan university students. In 2010, 1,954 students participated in a cross-sectional survey, conducted at Mbarara University of Science and Technology in southwestern Uganda (72% response rate). Multivariate logistic regression analysis was used for the analysis. 1,179 (60.3%) students in our study sample reported having debuted sexually. Of these 440 (42.2%) used condoms inconsistently with new sexual partners, and 344 (33.6%) had had multiple sexual partners. We found a statistically significant association between poor academic performance and inconsistent condom use with a new sex partner and this association remained significant even after adjusting for all the potential confounders. There was no such association detected regarding multiple sexual partners. We also found that gender modified the effect of poor academic performance on inconsistent condom use. Females, who were poor academic performers, were found to be at a higher risk of inconsistent condom use than their male counterparts. Interventions should be designed to provide extra support to poor academic performers, which may improve their performance and self-esteem, which in turn might reduce their risky sexual behaviors.

The role of objective cognitive dysfunction in subjective cognitive complaints after stroke.

PubMed

van Rijsbergen, M W A; Mark, R E; Kop, W J; de Kort, P L M; Sitskoorn, M M

2017-03-01

Objective cognitive performance (OCP) is often impaired in patients post-stroke but the consequences of OCP for patient-reported subjective cognitive complaints (SCC) are poorly understood. We performed a detailed analysis on the association between post-stroke OCP and SCC. Assessments of OCP and SCC were obtained in 208 patients 3 months after stroke. OCP was evaluated using conventional and ecologically valid neuropsychological tests. Levels of SCC were measured using the CheckList for Cognitive and Emotional (CLCE) consequences following stroke inventory. Multivariate hierarchical regression analyses were used to evaluate the association of OCP with CLCE scores adjusting for age, sex and intelligence quotient. Analyses were performed to examine the global extent of OCP dysfunction (based on the total number of impaired neuropsychological tests, i.e. objective cognitive impairment index) and for each OCP test separately using the raw neuropsychological (sub)test scores. The objective cognitive impairment index for global OCP was positively correlated with the CLCE score (Spearman's rho = 0.22, P = 0.003), which remained significant in multivariate adjusted models (β = 0.25, P = 0.01). Results for the separate neuropsychological tests indicated that only one task (the ecologically valid Rivermead Behavioural Memory Test) was independently associated with the CLCE in multivariate adjusted models (β = -0.34, P < 0.001). Objective neuropsychological test performance, as measured by the global dysfunction index or an ecologically valid memory task, was associated with SCC. These data suggest that cumulative deficits in multiple cognitive domains contribute to subjectively experienced poor cognitive abilities in daily life in patients post-stroke. © 2016 EAN.

Effect of hydrotalcite-like compounds on the aqueous solubility of some poorly water-soluble drugs.

PubMed

Ambrogi, Valeria; Fardella, Giuseppe; Grandolini, Giuliano; Nocchetti, Morena; Perioli, Luana

2003-07-01

A new approach of improving drug dissolution properties is described. This method exploits the property of a carrier owing to the hydrotalcite-type anionic clays (HTlc). HTlc is an inorganic layered solid that lodges anionic compounds among its layers. As HTlc dissolves at acidic pH values (pH < 4), the anions intercalated among the layers are promptly released in the medium. In this article some nonsteroidal antiinflammatory drugs were chosen as models of poorly water-soluble drugs. They were intercalated in HTlc and solubility measurements in acidic medium were performed. A remarkable improvement of drug solubility was observed especially in the case of indomethacin. Copyright 2003 Wiley-Liss, Inc. and the American Pharmacists Association

Bayesian analysis of input uncertainty in hydrological modeling: 2. Application

NASA Astrophysics Data System (ADS)

Kavetski, Dmitri; Kuczera, George; Franks, Stewart W.

2006-03-01

The Bayesian total error analysis (BATEA) methodology directly addresses both input and output errors in hydrological modeling, requiring the modeler to make explicit, rather than implicit, assumptions about the likely extent of data uncertainty. This study considers a BATEA assessment of two North American catchments: (1) French Broad River and (2) Potomac basins. It assesses the performance of the conceptual Variable Infiltration Capacity (VIC) model with and without accounting for input (precipitation) uncertainty. The results show the considerable effects of precipitation errors on the predicted hydrographs (especially the prediction limits) and on the calibrated parameters. In addition, the performance of BATEA in the presence of severe model errors is analyzed. While BATEA allows a very direct treatment of input uncertainty and yields some limited insight into model errors, it requires the specification of valid error models, which are currently poorly understood and require further work. Moreover, it leads to computationally challenging highly dimensional problems. For some types of models, including the VIC implemented using robust numerical methods, the computational cost of BATEA can be reduced using Newton-type methods.

Assessing groundwater policy with coupled economic-groundwater hydrologic modeling

NASA Astrophysics Data System (ADS)

Mulligan, Kevin B.; Brown, Casey; Yang, Yi-Chen E.; Ahlfeld, David P.

2014-03-01

This study explores groundwater management policies and the effect of modeling assumptions on the projected performance of those policies. The study compares an optimal economic allocation for groundwater use subject to streamflow constraints, achieved by a central planner with perfect foresight, with a uniform tax on groundwater use and a uniform quota on groundwater use. The policies are compared with two modeling approaches, the Optimal Control Model (OCM) and the Multi-Agent System Simulation (MASS). The economic decision models are coupled with a physically based representation of the aquifer using a calibrated MODFLOW groundwater model. The results indicate that uniformly applied policies perform poorly when simulated with more realistic, heterogeneous, myopic, and self-interested agents. In particular, the effects of the physical heterogeneity of the basin and the agents undercut the perceived benefits of policy instruments assessed with simple, single-cell groundwater modeling. This study demonstrates the results of coupling realistic hydrogeology and human behavior models to assess groundwater management policies. The Republican River Basin, which overlies a portion of the Ogallala aquifer in the High Plains of the United States, is used as a case study for this analysis.

Cognitive control components and speech symptoms in people with schizophrenia.

PubMed

Becker, Theresa M; Cicero, David C; Cowan, Nelson; Kerns, John G

2012-03-30

Previous schizophrenia research suggests poor cognitive control is associated with schizophrenia speech symptoms. However, cognitive control is a broad construct. Two important cognitive control components are poor goal maintenance and poor verbal working memory storage. In the current research, people with schizophrenia (n=45) performed three cognitive tasks that varied in their goal maintenance and verbal working memory storage demands. Speech symptoms were assessed using clinical rating scales, ratings of disorganized speech from typed transcripts, and self-reported disorganization. Overall, alogia was associated with both goal maintenance and verbal working memory tasks. Objectively rated disorganized speech was associated with poor goal maintenance and with a task that included both goal maintenance and verbal working memory storage demands. In contrast, self-reported disorganization was unrelated to either amount of objectively rated disorganized speech or to cognitive control task performance, instead being associated with negative mood symptoms. Overall, our results suggest that alogia is associated with both poor goal maintenance and poor verbal working memory storage and that disorganized speech is associated with poor goal maintenance. In addition, patients' own assessment of their disorganization is related to negative mood, but perhaps not to objective disorganized speech or to cognitive control task performance. Published by Elsevier Ireland Ltd.

Encoding of speech sounds at auditory brainstem level in good and poor hearing aid performers.

PubMed

Shetty, Hemanth Narayan; Puttabasappa, Manjula

Hearing aids are prescribed to alleviate loss of audibility. It has been reported that about 31% of hearing aid users reject their own hearing aid because of annoyance towards background noise. The reason for dissatisfaction can be located anywhere from the hearing aid microphone till the integrity of neurons along the auditory pathway. To measure spectra from the output of hearing aid at the ear canal level and frequency following response recorded at the auditory brainstem from individuals with hearing impairment. A total of sixty participants having moderate sensorineural hearing impairment with age range from 15 to 65 years were involved. Each participant was classified as either Good or Poor Hearing aid Performers based on acceptable noise level measure. Stimuli /da/ and /si/ were presented through loudspeaker at 65dB SPL. At the ear canal, the spectra were measured in the unaided and aided conditions. At auditory brainstem, frequency following response were recorded to the same stimuli from the participants. Spectrum measured in each condition at ear canal was same in good hearing aid performers and poor hearing aid performers. At brainstem level, better F 0 encoding; F 0 and F 1 energies were significantly higher in good hearing aid performers than in poor hearing aid performers. Though the hearing aid spectra were almost same between good hearing aid performers and poor hearing aid performers, subtle physiological variations exist at the auditory brainstem. The result of the present study suggests that neural encoding of speech sound at the brainstem level might be mediated distinctly in good hearing aid performers from that of poor hearing aid performers. Thus, it can be inferred that subtle physiological changes are evident at the auditory brainstem in a person who is willing to accept noise from those who are not willing to accept noise. Copyright © 2016 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

Numerical Study On Propulsion Performance Of The Parabolic Laser Thruster With Elongate Cylinder Nozzle

NASA Astrophysics Data System (ADS)

Cheng, Fuqiang; Hong, Yanji; Li, Qian; Wen, Ming

2011-11-01

Laser thrusters with a single nozzle, e.g. parabolic or conical, failed to constrict the flow field of high pressure effectively, resulting in poor propulsive performance. Under the condition of air-breathing mode, parabolic thruster models with an elongate cylinder nozzle were studied numerically by building a physical computation model. Initially, to verify the computation model, the influence of cylinder length on the momentum coupling coefficient was computed and compared with the experiments, which shows a good congruence. A model of diameter 20 mm and cylindrical length 80 mm obtains about 627.7 N/MW at single pulse energy density 1.5 J/cm2. Then, the influence of expanding angle of the parabolic nozzle on propulsion performance was gained for different laser pulse energies, and the evolution process of the flow field was analyzed. The results show: as the expanding angel increases, the momentum coupling coefficient increases remarkably at first and descends relative slowly after reaching a peak value; moreover, the peak positions stay constant around 33° with little variation when laser energy differs.

Optimizing modality selection for image-guided procedures: an analysis of the challenges to ultrasound guidance.

PubMed

Beland, Michael D; Sternick, Laura A; Baird, Grayson L; Dupuy, Damian E; Cronan, John J; Mayo-Smith, William W

2016-04-01

Selection of the most appropriate modality for image guidance is essential for procedural success. We identified specific factors contributing to failure of ultrasound-guided procedures that were subsequently performed using CT guidance. This single-center, retrospective study included 164 patients who underwent a CT-guided biopsy, aspiration/drainage, or ablation after initially having the same procedure attempted unsuccessfully with ultrasound guidance. Review of the procedure images, reports, biopsy results, and clinical follow-up was performed and the reasons for inability to perform the procedure with ultrasound guidance were recorded. Patient cross-sectional area and depth to target were calculated. Differences in area and depth were compared using general linear modeling. Depth as a predictor of an unfavorable body habitus designation was modeled using logistic regression. US guidance was successful in the vast majority of cases (97%). Of the 164 procedures, there were 92 (56%) biopsies, 63 (38%) aspirations/drainages, and 9 (5%) ablations. The most common reason for procedure failure was poor acoustic window (83/164, 51%). Other reasons included target lesion being poorly discerned from adjacent tissue (61/164, 37%), adjacent bowel gas (34/164, 21%), body habitus (27/164, 16%), and gas-containing collection (22/164, 13%). Within the biopsy subgroup, patients for whom body habitus was a limiting factor were found to have on average a larger cross-sectional area and lesion depth relative to patients whose body habitus was not a complicating factor (p < 0.0001 and p = 0.0009). Poor acoustic window was the most common reason for procedural failure with ultrasound guidance. In addition, as lesion depth increased, the odds that body habitus would limit the procedure also increased. If preliminary imaging suggests a limited sonographic window, particularly for deeper lesions, proceeding directly to CT guidance should be considered.

[Correlations Between Joint Proprioception, Muscle Strength, and Functional Ability in Patients with Knee Osteoarthritis].

PubMed

Chen, Yoa; Yu, Yong; He, Cheng-qi

2015-11-01

To establish correlations between joint proprioception, muscle flexion and extension peak torque, and functional ability in patients with knee osteoarthritis (OA). Fifty-six patients with symptomatic knee OA were recruited in this study. Both proprioceptive acuity and muscle strength were measured using the isomed-2000 isokinetic dynamometer. Proprioceptive acuity was evaluated by establishing the joint motion detection threshold (JMDT). Muscle strength was evaluated by Max torque (Nm) and Max torque/weight (Nm/ kg). Functional ability was assessed by the Western Ontario and McMaster Universities Osteoarthritis Index physical function (WOMAC-PF) questionnaire. Correlational analyses were performed between proprioception, muscle strength, and functional ability. A multiple stepwise regression model was established, with WOMAC-PF as dependent variable and patient age, body mass index (BMI), visual analogue scale (VAS)-score, mean grade for Kellgren-Lawrance of both knees, mean strength for quadriceps and hamstring muscles of both knees, and mean JMDT of both knees as independent variables. Poor proprioception (high JMDT) was negatively correlated with muscle strength (P<0.05). There was no significant correlation between knee proprioception (high JMDT) and joint pain (WOMAC pain score), and between knee proprioception (high JMDT) and joint stiffness (WOMAC stiffness score). Poor proprioception (high JMDT) was correlated with limitation in functional ability (WOMAC physical function score r=0.659, P<0.05). WOMAC score was correlated with poor muscle strength (quadriceps muscle strength r = -0.511, P<0.05, hamstring muscle strength r = -0.408, P<0.05). The multiple stepwise regression model showed that high JMDT C standard partial regression coefficient (B) = 0.385, P<0.50 and high VAS-scale score (B=0.347, P<0.05) were significant predictors of WOMAC-PF score. Patients with poor proprioception is associated with poor muscle strength and limitation in functional ability. Patients with symptomatic OA of knees commonly endure with moderate to considerable dysfunction, which is associated with poor proprioception (high JMDT) and high VAS-scale score.

A Longitudinal Examination of the Persistence of Late Emerging Reading Disabilities.

PubMed

Etmanskie, Jill M; Partanen, Marita; Siegel, Linda S

2016-01-01

There are some children who encounter unexpected reading difficulties in the fourth grade. This phenomenon has been described as late emerging reading disabilities (LERD). Using Grade 4 as a starting point, this study examined the reading development of 964 children between kindergarten and Grade 7. The results showed that 72.0% of children had typical reading performance in Grade 4, whereas there was 0.7% with poor word reading, 12.6% with poor reading comprehension, 2.5% with poor word reading and comprehension, and 12.2% with borderline performance. We also showed that there were similar proportions of children who had early versus late emerging reading difficulties; however, most of the late emerging poor readers recovered by Grade 7. Furthermore, our study showed that poor comprehenders showed poorer performance than typical readers on word reading, pseudoword decoding, and spelling between Grade 1 and Grade 7 and poorer performance on a working memory task in kindergarten. Overall, this study showed that most children recover from late emerging reading problems and that working memory may be an early indicator for reading comprehension difficulties. © Hammill Institute on Disabilities 2014.

Linking in situ LAI and fine resolution remote sensing data to map reference LAI over cropland and grassland using geostatistical regression method

NASA Astrophysics Data System (ADS)

He, Yaqian; Bo, Yanchen; Chai, Leilei; Liu, Xiaolong; Li, Aihua

2016-08-01

Leaf Area Index (LAI) is an important parameter of vegetation structure. A number of moderate resolution LAI products have been produced in urgent need of large scale vegetation monitoring. High resolution LAI reference maps are necessary to validate these LAI products. This study used a geostatistical regression (GR) method to estimate LAI reference maps by linking in situ LAI and Landsat TM/ETM+ and SPOT-HRV data over two cropland and two grassland sites. To explore the discrepancies of employing different vegetation indices (VIs) on estimating LAI reference maps, this study established the GR models for different VIs, including difference vegetation index (DVI), normalized difference vegetation index (NDVI), and ratio vegetation index (RVI). To further assess the performance of the GR model, the results from the GR and Reduced Major Axis (RMA) models were compared. The results show that the performance of the GR model varies between the cropland and grassland sites. At the cropland sites, the GR model based on DVI provides the best estimation, while at the grassland sites, the GR model based on DVI performs poorly. Compared to the RMA model, the GR model improves the accuracy of reference LAI maps in terms of root mean square errors (RMSE) and bias.

Social inequality in dynamic balance performance in an early old age Spanish population: the role of health and lifestyle associated factors.

PubMed

Rodríguez López, Santiago; Nilsson, Charlotte; Lund, Rikke; Montero, Pilar; Fernández-Ballesteros, Rocío; Avlund, Kirsten

2012-01-01

This study investigates the association between socioeconomic status (SES) and dynamic balance performance and whether lifestyle factors explained any possible associations. A total of 448 nondisabled individuals, age-range 54-75 years and enrolled in the Active Aging Longitudinal Study of Spain in 2006, constituted the study population. Baseline data of this cross-sectional study were obtained by personal interviews and objective measures of balance performance. The present study shows an educational gradient in poor dynamic balance, where individuals with no formal education had higher risk of poor balance, also after adjustment for age, gender, obesity and physical activity. In addition, obesity and sedentary physical activity were related to poor dynamic balance. The findings suggest an independent effect of both SES and behavioral factors on poor balance performance in the older Spanish population. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Phasic dopamine release in the rat nucleus accumbens predicts approach and avoidance performance

PubMed Central

Gentry, Ronny N.; Lee, Brian; Roesch, Matthew R.

2016-01-01

Dopamine (DA) is critical for reward processing, but significantly less is known about its role in punishment avoidance. Using a combined approach-avoidance task, we measured phasic DA release in the nucleus accumbens (NAc) of rats during presentation of cues that predicted reward, punishment or neutral outcomes and investigated individual differences based on avoidance performance. Here we show that DA release within a single microenvironment is higher for reward and avoidance cues compared with neutral cues and positively correlated with poor avoidance behaviour. We found that DA release delineates trial-type during sessions with good avoidance but is non-selective during poor avoidance, with high release correlating with poor performance. These data demonstrate that phasic DA is released during cued approach and avoidance within the same microenvironment and abnormal processing of value signals is correlated with poor performance. PMID:27786172

A novel use of structural equation models to examine factors associated with prediabetes among adults aged 50 years and older: National Health and Nutrition Examination Survey 2001-2006.

PubMed

Bardenheier, Barbara H; Bullard, Kai McKeever; Caspersen, Carl J; Cheng, Yiling J; Gregg, Edward W; Geiss, Linda S

2013-09-01

To use structural modeling to test a hypothesized model of causal pathways related with prediabetes among older adults in the U.S. Cross-sectional study of 2,230 older adults (≥ 50 years) without diabetes included in the morning fasting sample of the 2001-2006 National Health and Nutrition Examination Surveys. Demographic data included age, income, marital status, race/ethnicity, and education. Behavioral data included physical activity (metabolic equivalent hours per week for vigorous or moderate muscle strengthening, walking/biking, and house/yard work), and poor diet (refined grains, red meat, added sugars, solid fats, and high-fat dairy). Structural-equation modeling was performed to examine the interrelationships among these variables with family history of diabetes, high blood pressure, BMI, large waist (waist circumference: women, ≥ 35 inches; men, ≥ 40 inches), triglycerides ≥ 200 mg/dL, and total and HDL (≥ 60 mg/dL) cholesterol. After dropping BMI and total cholesterol, our best-fit model included three single factors: socioeconomic position (SEP), physical activity, and poor diet. Large waist had the strongest direct effect on prediabetes (0.279), followed by male sex (0.270), SEP (-0.157), high blood pressure (0.122), family history of diabetes (0.070), and age (0.033). Physical activity had direct effects on HDL (0.137), triglycerides (-0.136), high blood pressure (-0.132), and large waist (-0.067); poor diet had direct effects on large waist (0.146) and triglycerides (0.148). Our results confirmed that, while including factors known to be associated with high risk of developing prediabetes, large waist circumference had the strongest direct effect. The direct effect of SEP on prediabetes suggests mediation by some unmeasured factor(s).

A Public-Private Partnership Develops and Externally Validates a 30-Day Hospital Readmission Risk Prediction Model

PubMed Central

Choudhry, Shahid A.; Li, Jing; Davis, Darcy; Erdmann, Cole; Sikka, Rishi; Sutariya, Bharat

2013-01-01

Introduction: Preventing the occurrence of hospital readmissions is needed to improve quality of care and foster population health across the care continuum. Hospitals are being held accountable for improving transitions of care to avert unnecessary readmissions. Advocate Health Care in Chicago and Cerner (ACC) collaborated to develop all-cause, 30-day hospital readmission risk prediction models to identify patients that need interventional resources. Ideally, prediction models should encompass several qualities: they should have high predictive ability; use reliable and clinically relevant data; use vigorous performance metrics to assess the models; be validated in populations where they are applied; and be scalable in heterogeneous populations. However, a systematic review of prediction models for hospital readmission risk determined that most performed poorly (average C-statistic of 0.66) and efforts to improve their performance are needed for widespread usage. Methods: The ACC team incorporated electronic health record data, utilized a mixed-method approach to evaluate risk factors, and externally validated their prediction models for generalizability. Inclusion and exclusion criteria were applied on the patient cohort and then split for derivation and internal validation. Stepwise logistic regression was performed to develop two predictive models: one for admission and one for discharge. The prediction models were assessed for discrimination ability, calibration, overall performance, and then externally validated. Results: The ACC Admission and Discharge Models demonstrated modest discrimination ability during derivation, internal and external validation post-recalibration (C-statistic of 0.76 and 0.78, respectively), and reasonable model fit during external validation for utility in heterogeneous populations. Conclusions: The ACC Admission and Discharge Models embody the design qualities of ideal prediction models. The ACC plans to continue its partnership to further improve and develop valuable clinical models. PMID:24224068

Perception of Overweight Is Associated with Poor Academic Performance in US Adolescents

ERIC Educational Resources Information Center

Florin, Todd A.; Shults, Justine; Stettler, Nicolas

2011-01-01

Background: To improve understanding of the mechanisms affecting the relationship between adolescent obesity and poor academic performance, we examined the association of overweight or perceived weight status with academic achievement. Methods: We performed a cross-sectional study of 14-17-year-olds (N = 11,012) from the nationally representative…

Deterioration in Teachers' Performance: Causes and Some Remedies

ERIC Educational Resources Information Center

Yariv, Eliezer

2011-01-01

Why do teachers become poor performers? In semi-structured interviews, forty elementary school principals in Israel described the personal story of one poor-performing staff member. Half of the problematic teachers were veteran teachers who faced a marked internal and external shift in mid-career. The seeds of their problems were probably planted…

Association between Facebook Dependence and Poor Sleep Quality: A Study in a Sample of Undergraduate Students in Peru

PubMed Central

Wolniczak, Isabella; Cáceres-DelAguila, José Alonso; Palma-Ardiles, Gabriela; Arroyo, Karen J.; Solís-Visscher, Rodrigo; Paredes-Yauri, Stephania; Mego-Aquije, Karina; Bernabe-Ortiz, Antonio

2013-01-01

Objectives Internet can accelerate information exchange. Social networks are the most accessed especially Facebook. This kind of networks might create dependency with several negative consequences in people’s life. The aim of this study was to assess potential association between Facebook dependence and poor sleep quality. Methodology/Principal Findings A cross sectional study was performed enrolling undergraduate students of the Universidad Peruana de Ciencias Aplicadas, Lima, Peru. The Internet Addiction Questionnaire, adapted to the Facebook case, and the Pittsburgh Sleep Quality Index, were used. A global score of 6 or greater was defined as the cutoff to determine poor sleep quality. Generalized linear model were used to determine prevalence ratios (PR) and 95% confidence intervals (95%CI). A total of 418 students were analyzed; of them, 322 (77.0%) were women, with a mean age of 20.1 (SD: 2.5) years. Facebook dependence was found in 8.6% (95% CI: 5.9%–11.3%), whereas poor sleep quality was present in 55.0% (95% CI: 50.2%–59.8%). A significant association between Facebook dependence and poor sleep quality mainly explained by daytime dysfunction was found (PR = 1.31; IC95%: 1.04–1.67) after adjusting for age, sex and years in the faculty. Conclusions There is a relationship between Facebook dependence and poor quality of sleep. More than half of students reported poor sleep quality. Strategies to moderate the use of this social network and to improve sleep quality in this population are needed. PMID:23554978

Low intake of vegetables, high intake of confectionary, and unhealthy eating habits are associated with poor sleep quality among middle-aged female Japanese workers.

PubMed

Katagiri, Ryoko; Asakura, Keiko; Kobayashi, Satomi; Suga, Hitomi; Sasaki, Satoshi

2014-01-01

Although workers with poor sleep quality are reported to have problems with work performance, few studies have assessed the association between dietary factors and sleep quality using validated indexes. Here, we examined this association using information acquired from validated questionnaires. A total of 3,129 female workers aged 34 to 65 years were analyzed. Dietary intake was assessed using a self-administered diet history questionnaire (DHQ), and subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The relationship between the intake of several food groups and nutrients and sleep quality was examined using multivariable logistic regression models. The effect of eating habits on sleep quality was also examined. Poor sleep quality was associated with low intake of vegetables (p for trend 0.002) and fish (p for trend 0.04) and high intake of confectionary (p for trend 0.004) and noodles (p for trend 0.03) after adjustment for potential confounding factors (age, body mass index, physical activity, depression score, employment status, alcohol intake and smoking status). Poor sleep quality was also significantly and positively associated with consumption of energy drinks and sugar-sweetened beverages, skipping breakfast, and eating irregularly. In addition, poor sleep quality was significantly associated with high carbohydrate intake (p for trend 0.03). A low intake of vegetables and fish, high intake of confectionary and noodles and unhealthy eating habits were independently associated with poor sleep quality. Poor sleep quality was also associated with high carbohydrate intake in free-living Japanese middle-aged female workers.

Exercising upper respiratory videoendoscopic evaluation of 100 nonracing performance horses with abnormal respiratory noise and/or poor performance.

PubMed

Davidson, E J; Martin, B B; Boston, R C; Parente, E J

2011-01-01

Although well documented in racehorses, there is paucity in the literature regarding the prevalence of dynamic upper airway abnormalities in nonracing performance horses. To describe upper airway function of nonracing performance horses with abnormal respiratory noise and/or poor performance via exercising upper airway videoendoscopy. Medical records of nonracing performance horses admitted for exercising evaluation with a chief complaint of abnormal respiratory noise and/or poor performance were reviewed. All horses had video recordings of resting and exercising upper airway endoscopy. Relationships between horse demographics, resting endoscopic findings, treadmill intensity and implementation of head and neck flexion during exercise with exercising endoscopic findings were examined. Dynamic upper airway obstructions were observed in 72% of examinations. Head and neck flexion was necessary to obtain a diagnosis in 21 horses. Pharyngeal wall collapse was the most prevalent upper airway abnormality, observed in 31% of the examinations. Complex abnormalities were noted in 27% of the examinations. Resting laryngeal dysfunction was significantly associated with dynamic arytenoid collapse and the odds of detecting intermittent dorsal displacement of the soft palate (DDSP) during exercise in horses with resting DDSP was only 7.7%. Exercising endoscopic observations were different from the resting observations in 54% of examinations. Dynamic upper airway obstructions were common in nonracing performance horses with respiratory noise and/or poor performance. Resting endoscopy was only helpful in determining exercising abnormalities with recurrent laryngeal neuropathy. This study emphasises the importance of exercising endoscopic evaluation in nonracing performance horses with abnormal respiratory noise and/or poor performance for accurate assessment of dynamic upper airway function. © 2010 EVJ Ltd.

Great expectations: top-down attention modulates the costs of clutter and eccentricity.

PubMed

Steelman, Kelly S; McCarley, Jason S; Wickens, Christopher D

2013-12-01

An experiment and modeling effort examined interactions between bottom-up and top-down attentional control in visual alert detection. Participants performed a manual tracking task while monitoring peripheral display channels for alerts of varying salience, eccentricity, and spatial expectancy. Spatial expectancy modulated the influence of salience and eccentricity; alerts in low-probability locations engendered higher miss rates, longer detection times, and larger costs of visual clutter and eccentricity, indicating that top-down attentional control offset the costs of poor bottom-up stimulus quality. Data were compared to the predictions of a computational model of scanning and noticing that incorporates bottom-up and top-down sources of attentional control. The model accounted well for the overall pattern of miss rates and response times, predicting each of the observed main effects and interactions. Empirical results suggest that designers should expect the costs of poor bottom-up visibility to be greater for low expectancy signals, and that the placement of alerts within a display should be determined based on the combination of alert expectancy and response priority. Model fits suggest that the current model can serve as a useful tool for exploring a design space as a precursor to empirical data collection and for generating hypotheses for future experiments. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Comparative Assessment of Particulate Air Pollution Exposure from Municipal Solid Waste Incinerator Emissions

PubMed Central

Ashworth, Danielle C.; Fuller, Gary W.; Toledano, Mireille B.; Font, Anna; Elliott, Paul; Hansell, Anna L.; de Hoogh, Kees

2013-01-01

Background. Research to date on health effects associated with incineration has found limited evidence of health risks, but many previous studies have been constrained by poor exposure assessment. This paper provides a comparative assessment of atmospheric dispersion modelling and distance from source (a commonly used proxy for exposure) as exposure assessment methods for pollutants released from incinerators. Methods. Distance from source and the atmospheric dispersion model ADMS-Urban were used to characterise ambient exposures to particulates from two municipal solid waste incinerators (MSWIs) in the UK. Additionally an exploration of the sensitivity of the dispersion model simulations to input parameters was performed. Results. The model output indicated extremely low ground level concentrations of PM10, with maximum concentrations of <0.01 μg/m3. Proximity and modelled PM10 concentrations for both MSWIs at postcode level were highly correlated when using continuous measures (Spearman correlation coefficients ~ 0.7) but showed poor agreement for categorical measures (deciles or quintiles, Cohen's kappa coefficients ≤ 0.5). Conclusion. To provide the most appropriate estimate of ambient exposure from MSWIs, it is essential that incinerator characteristics, magnitude of emissions, and surrounding meteorological and topographical conditions are considered. Reducing exposure misclassification is particularly important in environmental epidemiology to aid detection of low-level risks. PMID:23935644

Performance of DS/SSMA (Direct-Sequence Spread-Spectrum Multiple-Access) Communications in Impulsive Channels.

DTIC Science & Technology

1986-11-01

mother and my brother. Their support and encouragement made this research exciting and enjoyable. I am grateful to my advisor, Professor H. Vincent Poor...the model. The m! M A variance of a random variable with density given by (A. 1) is a2 KmC 2 2A(I+l’)• (A.2) With the variance of the random variable

N Reasons Why Production-Rules are Insufficient Models for Expert System Knowledge Representation Schemes

DTIC Science & Technology

1991-02-01

3 2.2 Hybrid Rule/Fact Schemas .............................................................. 3 3 THE LIMITATIONS OF RULE BASED KNOWLEDGE...or hybrid rule/fact schemas. 2 UNCLASSIFIED .WA UNCLASSIFIED ERL-0520-RR 2.1 Propositional Logic The simplest form of production-rules are based upon...requirements which may lead to poor system performance. 2.2 Hybrid Rule/Fact Schemas Hybrid rule/fact relationships (also known as Predicate Calculus ) have

In use performance of catalytic converters on properly maintained high mileage vehicles

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

Sabourin, M.A.; Larson, R.E.; Donahue, K.S.

1986-01-01

A test program to evaluate the performance of catalytic converters from fifty-six 1981 and 1982 model year high mileage properly maintained in-use vehicles (from 21 engine families) was performed by the Certification Division of the Office of Mobile Sources (EPA). The program is called the Catalyst Change Program. All program vehicles were screened for proper maintenance and for mileages that ranged from 35,000 to 60,000 miles. Among vehicles belonging to 21 high sales volume and high technology engine and emission control system designs tested, poor catalyst performance was determined to be a significant contributor to emissions failure of properly-maintained vehiclesmore » at or near their warranted useful life mileage.« less

Galactic evolution of copper in the light of NLTE computations

NASA Astrophysics Data System (ADS)

Andrievsky, S.; Bonifacio, P.; Caffau, E.; Korotin, S.; Spite, M.; Spite, F.; Sbordone, L.; Zhukova, A. V.

2018-01-01

We have developed a model atom for Cu with which we perform statistical equilibrium computations that allow us to compute the line formation of Cu I lines in stellar atmospheres without assuming local thermodynamic equilibrium (LTE). We validate this model atom by reproducing the observed line profiles of the Sun, Procyon and 11 metal-poor stars. Our sample of stars includes both dwarfs and giants. Over a wide range of stellar parameters, we obtain excellent agreement among different Cu I lines. The 11 metal-poor stars have iron abundances in the range - 4.2 ≤ [Fe/H] ≤ -1.4, the weighted mean of the [Cu/Fe] ratios is -0.22 dex, with a scatter of -0.15 dex. This is very different from the results from LTE analysis (the difference between NLTE and LTE abundances reaches 1 dex) and in spite of the small size of our sample, it prompts for a revision of the Galactic evolution of Cu.

Assimilation of Sea Color Data Into A Three Dimensional Biogeochemical Model: Sensitivity Experiments

NASA Astrophysics Data System (ADS)

Echevin, V.; Levy, M.; Memery, L.

The assimilation of two dimensional sea color data fields into a 3 dimensional coupled dynamical-biogeochemical model is performed using a 4DVAR algorithm. The biogeochemical model includes description of nitrates, ammonium, phytoplancton, zooplancton, detritus and dissolved organic matter. A subset of the biogeochemical model poorly known parameters (for example,phytoplancton growth, mortality,grazing) are optimized by minimizing a cost function measuring misfit between the observations and the model trajectory. Twin experiments are performed with an eddy resolving model of 5 km resolution in an academic configuration. Starting from oligotrophic conditions, an initially unstable baroclinic anticyclone splits into several eddies. Strong vertical velocities advect nitrates into the euphotic zone and generate a phytoplancton bloom. Biogeochemical parameters are perturbed to generate surface pseudo-observations of chlorophyll,which are assimilated in the model in order to retrieve the correct parameter perturbations. The impact of the type of measurement (quasi-instantaneous, daily mean, weekly mean) onto the retrieved set of parameters is analysed. Impacts of additional subsurface measurements and of errors in the circulation are also presented.

Assessment of recovery in older patients hospitalized with different diagnoses and functional levels, evaluated with and without geriatric assessment.

PubMed

Abrahamsen, Jenny Foss; Haugland, Cathrine; Ranhoff, Anette Hylen

2016-01-01

The objective of the present study was to investigate 1) the role of different admission diagnoses and 2) the degree of functional loss, on the rate of recovery of older patients after acute hospitalization. Furthermore, to compare the predictive value of simple assessments that can be carried out in a hospital lacking geriatric service, with assessments including geriatric screening tests. Prospective, observational cohort study, including 961community dwelling patients aged ≥ 70 years, transferred from medical, cardiac, pulmonary and orthopedic acute hospital departments to intermediate care in nursing home. Functional assessment with Barthel index (BI) was performed at admission to the nursing home and further geriatric assessment tests was performed during the first week. Logistic regression models with and without geriatric assessment were compared concerning the patients having 1) slow recovery (nursing home stay up to 2 months before return home) or, 2) poor recovery (dead or still in nursing home at 2 months). Slow recovery was independently associated with a diagnosis of non-vertebral fracture, BI subgroups 50-79 and <50, and, in the model including geriatric assessment, also with cognitive impairment. Poor recovery was more complex, and independently associated both with BI < 50, receiving home care before admission, higher age, admission with a non-vertebral fracture, and in the geriatric assessment model, cognitive impairment. Geriatric assessment is optimal for determining the recovery potential of older patients after acute hospitalization. As some hospitals lack geriatric services and ability to perform geriatric screening tests, a simpler assessment based on admission diagnoses and ADL function (BI), gives good information regarding the possible rehabilitation time and possibility to return home.

Wearable Technology for Global Surgical Teleproctoring.

PubMed

Datta, Néha; MacQueen, Ian T; Schroeder, Alexander D; Wilson, Jessica J; Espinoza, Juan C; Wagner, Justin P; Filipi, Charles J; Chen, David C

2015-01-01

In underserved communities around the world, inguinal hernias represent a significant burden of surgically-treatable disease. With traditional models of international surgical assistance limited to mission trips, a standardized framework to strengthen local healthcare systems is lacking. We established a surgical education model using web-based tools and wearable technology to allow for long-term proctoring and assessment in a resource-poor setting. This is a feasibility study examining wearable technology and web-based performance rating tools for long-term proctoring in an international setting. Using the Lichtenstein inguinal hernia repair as the index surgical procedure, local surgeons in Paraguay and Brazil were trained in person by visiting international expert trainers using a formal, standardized teaching protocol. Surgeries were captured in real-time using Google Glass and transmitted wirelessly to an online video stream, permitting real-time observation and proctoring by mentoring surgeon experts in remote locations around the world. A system for ongoing remote evaluation and support by experienced surgeons was established using the Lichtenstein-specific Operative Performance Rating Scale. Data were collected from 4 sequential training operations for surgeons trained in both Paraguay and Brazil. With continuous internet connectivity, live streaming of the surgeries was successful. The Operative Performance Rating Scale was immediately used after each operation. Both surgeons demonstrated proficiency at the completion of the fourth case. A sustainable model for surgical training and proctoring to empower local surgeons in resource-poor locations and "train trainers" is feasible with wearable technology and web-based communication. Capacity building by maximizing use of local resources and expertise offers a long-term solution to reducing the global burden of surgically-treatable disease. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Low-impact falls: demands on a system of trauma management, prediction of outcome, and influence of comorbidities.

PubMed

Kennedy, R L; Grant, P T; Blackwell, D

2001-10-01

Falls from a low height are an extremely common source of injury, the severity of which is often underestimated. As a result, low fall patients are usually not transferred to Level I trauma centers. There are surprisingly few systematic data relating to the demands made on systems of trauma care by patients with low falls. This study addresses this issue using information from a comprehensive national trauma database. The performance of TRISS methodology, and the factors associated with prolonged hospital stay, in low fall patients is also examined. The study included 31,419 patients. Patients with low falls (< 2 m) were compared with those suffering high falls (> or = 2 m), motor vehicle crashes, assault, sports injuries, and a group with unclassified injuries. Probability of survival was estimated using TRISS, and its performance in different types of injury was assessed using measures of discrimination and calibration. The influence of coexistent medical conditions on mortality and length of stay was investigated using logistic regression. Low falls accounted for 45.5% of all admissions, and 43.9% of the total bed days. The low fall group was older (mean age, 61.6 years), and predominantly female (62.5%) in contrast to the other groups (both p < 0.001). There were fewer severely injured patients than in all of the other groups except sports injuries. The area under the receiver operating characteristic curve for TRISS applied to low falls (0.874) was less than that for high falls (0.969), motor vehicle crashes (0.973), assaults (0.960), sports (1.000), and unclassified injuries (0.965). Also, the calibration of the TRISS model was poor for patients with low falls. A logistic regression model derived from a training set of 5,000 patients gave slightly improved discrimination and markedly improved calibration when compared with TRISS. Although there was a strong relationship between the number of coexistent medical conditions and the risk of dying after a low fall, including data on comorbidities in a predictive model did not improve performance. Prolonged stay (defined as greater than the 90th centile, 23 days) was more likely in women (p < 0.005), or with advanced age (p < 0.001) or low initial calculated probability of survival (p < 0.001). Cardiovascular and central nervous system diseases and diabetes were associated with longer hospital stay (all p < 0.001). A logistic regression model using TRISS variables and comorbidity data gave poor prediction of prolonged stay. There was considerable variation in the length of stay between institutions. Patients with low falls make considerable demands on a system of trauma care. TRISS methodology performs less well in this group than with other types of injury. Chronic medical conditions are associated with increased mortality and more prolonged stay after a low fall. Between-institutional variation in length of stay was considerable and this, along with the poor performance of predictive models derived from routinely collected clinical data, make it unlikely that length of stay could be used as a measure of institutional performance. More robust audit measures for patients with low falls are required.

Differences in Performance Among Test Statistics for Assessing Phylogenomic Model Adequacy.

PubMed

Duchêne, David A; Duchêne, Sebastian; Ho, Simon Y W

2018-05-18

Statistical phylogenetic analyses of genomic data depend on models of nucleotide or amino acid substitution. The adequacy of these substitution models can be assessed using a number of test statistics, allowing the model to be rejected when it is found to provide a poor description of the evolutionary process. A potentially valuable use of model-adequacy test statistics is to identify when data sets are likely to produce unreliable phylogenetic estimates, but their differences in performance are rarely explored. We performed a comprehensive simulation study to identify test statistics that are sensitive to some of the most commonly cited sources of phylogenetic estimation error. Our results show that, for many test statistics, traditional thresholds for assessing model adequacy can fail to reject the model when the phylogenetic inferences are inaccurate and imprecise. This is particularly problematic when analysing loci that have few variable informative sites. We propose new thresholds for assessing substitution model adequacy and demonstrate their effectiveness in analyses of three phylogenomic data sets. These thresholds lead to frequent rejection of the model for loci that yield topological inferences that are imprecise and are likely to be inaccurate. We also propose the use of a summary statistic that provides a practical assessment of overall model adequacy. Our approach offers a promising means of enhancing model choice in genome-scale data sets, potentially leading to improvements in the reliability of phylogenomic inference.

Species distribution models: A comparison of statistical approaches for livestock and disease epidemics.

PubMed

Hollings, Tracey; Robinson, Andrew; van Andel, Mary; Jewell, Chris; Burgman, Mark

2017-01-01

In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning.

Species distribution models: A comparison of statistical approaches for livestock and disease epidemics

PubMed Central

Robinson, Andrew; van Andel, Mary; Jewell, Chris; Burgman, Mark

2017-01-01

In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning. PMID:28837685

Gender Roles and Physical Function in Older Adults: Cross-Sectional Analysis of the International Mobility in Aging Study (IMIAS).

PubMed

Ahmed, Tamer; Vafaei, Afshin; Auais, Mohammad; Guralnik, Jack; Zunzunegui, Maria Victoria

2016-01-01

To examine the relationships between physical function and gender-stereotyped traits and whether these relationships are modified by sex or social context. A total of 1995 community-dwelling older adults from the International Mobility in Aging Study (IMIAS) aged 65 to 74 years were recruited in Natal (Brazil), Manizales (Colombia), Tirana (Albania), Kingston (Ontario, Canada), and Saint-Hyacinthe (Quebec, Canada). We performed a cross-sectional analysis. Study outcomes were mobility disability, defined as having difficulty in walking 400 meters without assistance or climbing a flight of stairs without resting, and low physical performance, defined as a score < 8 on the Short Physical Performance Battery. The 12-item Bem Sex Role Inventory (BSRI) was used to classify participants into four gender roles (Masculine, Feminine, Androgynous, and Undifferentiated) using site-specific medians of femininity and masculinity as cut-off points. Poisson regression models were used to estimate prevalence rate ratios (PRR) of mobility disability and poor physical performance according to gender roles. In models adjusted for sex, marital status, education, income, and research site, when comparing to the androgynous role, we found higher prevalence of mobility disability and poor physical performance among participants endorsing the feminine role (PRR = 1.20, 95% confidence interval (CI) 1.03-1.39 and PRR = 1.37, CI 1.01-1.88, respectively) or the undifferentiated role (PRR = 1.23, 95% CI 1.07-1.42 and PRR = 1.58, CI 1.18-2.12, respectively). Participants classified as masculine did not differ from androgynous participants in prevalence rates of mobility disability or low physical performance. None of the multiplicative interactions by sex and research site were significant. Feminine and undifferentiated gender roles are independent risk factors for mobility disability and low physical performance in older adults. Longitudinal research is needed to assess the mediation pathways through which gender-stereotyped traits influence functional limitations and to investigate the longitudinal nature of these relationships.

Sarcopenia Screened by the SARC-F Questionnaire and Physical Performances of Elderly Women: A Cross-Sectional Study.

PubMed

Rolland, Yves; Dupuy, Charlotte; Abellan Van Kan, Gabor; Cesari, Matteo; Vellas, Bruno; Faruch, Marie; Dray, Cedric; de Souto Barreto, Philipe

2017-10-01

Screening for sarcopenia in daily practice can be challenging. Our objective was to explore whether the SARC-F questionnaire is a valid screening tool for sarcopenia (defined by the Foundation for the National Institutes of Health [FNIH] criteria). Moreover, we evaluated the physical performance of older women according to the SARC-F questionnaire. Cross-sectional study. Data from the Toulouse and Lyon EPIDémiologie de l'OStéoporose study (EPIDOS) on 3025 women living in the community (mean age: 80.5 ± 3.9 years), without a previous history of hip fracture, were assessed. The SARC-F self-report questionnaire score ranges from 0 to 10: a score ≥4 defines sarcopenia. The FNIH criteria uses handgrip strength (GS) and appendicular lean mass (ALM; assessed by DXA) divided by body mass index (BMI) to define sarcopenia. Outcome measures were the following performance-based tests: knee-extension strength, 6-m gait speed, and a repeated chair-stand test. The associations of sarcopenia with performance-based tests was examined using bootstrap multiple linear-regression models; adjusted R 2 determined the percentage variation for each outcome explained by the model. Prevalence of sarcopenia was 16.7% (n = 504) according to the SARC-F questionnaire and 1.8% (n = 49) using the FNIH criteria. Sensibility and specificity of the SARC-F to diagnose sarcopenia (defined by FNIH criteria) were 34% and 85%, respectively. Sarcopenic women defined by SARC-F had significantly lower physical performance than nonsarcopenic women. The SARC-F improved the ability to predict poor physical performance. The validity of the SARC-F questionnaire to screen for sarcopenia, when compared with the FNIH criteria, was limited. However, sarcopenia defined by the SARC-F questionnaire substantially improved the predictive value of clinical characteristics of patients to predict poor physical performance. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Physical Function, Hyperuricemia, and Gout in Older Adults.

PubMed

Burke, Bridget Teevan; Köttgen, Anna; Law, Andrew; Windham, Beverly Gwen; Segev, Dorry; Baer, Alan N; Coresh, Josef; McAdams-DeMarco, Mara A

2015-12-01

Gout prevalence is high in older adults and those affected are at risk of physical disability, yet it is unclear whether they have worse physical function. We studied gout, hyperuricemia, and physical function in 5,819 older adults (age ≥65 years) attending the 2011-2013 Atherosclerosis Risk in Communities Study visit, a prospective US population-based cohort. Differences in lower extremity function (Short Physical Performance Battery [SPPB] and 4-meter walking speed) and upper extremity function (grip strength) by gout status and by hyperuricemia prevalence were estimated in adjusted ordinal logistic regression (SPPB) and linear regression (walking speed and grip strength) models. Lower scores or times signify worse function. The prevalence of poor physical performance (first quartile) by gout and hyperuricemia was estimated using adjusted modified Poisson regression. Ten percent of participants reported a history of gout and 21% had hyperuricemia. There was no difference in grip strength by history of gout (P = 0.77). Participants with gout performed worse on the SPPB test; they had 0.77 times (95% confidence interval [95% CI] 0.65, 0.90, P = 0.001) the prevalence odds of a 1-unit increase in SPPB score and were 1.18 times (95% CI 1.07, 1.32, P = 0.002) more likely to have poor SPPB performance. Participants with a history of gout had slower walking speed (mean difference -0.03; 95% CI -0.05, -0.01, P < 0.001) and were 1.19 times (95% CI 1.06, 1.34, P = 0.003) more likely to have poor walking speed. Similarly, SPPB score and walking speed, but not grip strength, were worse in participants with hyperuricemia. Older adults with gout and hyperuricemia are more likely to have worse lower extremity, but not upper extremity, function. © 2015, American College of Rheumatology.

On the predictive information criteria for model determination in seismic hazard analysis

NASA Astrophysics Data System (ADS)

Varini, Elisa; Rotondi, Renata

2016-04-01

Many statistical tools have been developed for evaluating, understanding, and comparing models, from both frequentist and Bayesian perspectives. In particular, the problem of model selection can be addressed according to whether the primary goal is explanation or, alternatively, prediction. In the former case, the criteria for model selection are defined over the parameter space whose physical interpretation can be difficult; in the latter case, they are defined over the space of the observations, which has a more direct physical meaning. In the frequentist approaches, model selection is generally based on an asymptotic approximation which may be poor for small data sets (e.g. the F-test, the Kolmogorov-Smirnov test, etc.); moreover, these methods often apply under specific assumptions on models (e.g. models have to be nested in the likelihood ratio test). In the Bayesian context, among the criteria for explanation, the ratio of the observed marginal densities for two competing models, named Bayes Factor (BF), is commonly used for both model choice and model averaging (Kass and Raftery, J. Am. Stat. Ass., 1995). But BF does not apply to improper priors and, even when the prior is proper, it is not robust to the specification of the prior. These limitations can be extended to two famous penalized likelihood methods as the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), since they are proved to be approximations of -2log BF . In the perspective that a model is as good as its predictions, the predictive information criteria aim at evaluating the predictive accuracy of Bayesian models or, in other words, at estimating expected out-of-sample prediction error using a bias-correction adjustment of within-sample error (Gelman et al., Stat. Comput., 2014). In particular, the Watanabe criterion is fully Bayesian because it averages the predictive distribution over the posterior distribution of parameters rather than conditioning on a point estimate, but it is hardly applicable to data which are not independent given parameters (Watanabe, J. Mach. Learn. Res., 2010). A solution is given by Ando and Tsay criterion where the joint density may be decomposed into the product of the conditional densities (Ando and Tsay, Int. J. Forecast., 2010). The above mentioned criteria are global summary measures of model performance, but more detailed analysis could be required to discover the reasons for poor global performance. In this latter case, a retrospective predictive analysis is performed on each individual observation. In this study we performed the Bayesian analysis of Italian data sets by four versions of a long-term hazard model known as the stress release model (Vere-Jones, J. Physics Earth, 1978; Bebbington and Harte, Geophys. J. Int., 2003; Varini and Rotondi, Environ. Ecol. Stat., 2015). Then we illustrate the results on their performance evaluated by Bayes Factor, predictive information criteria and retrospective predictive analysis.

Introducing a simple model system for binding studies of known and novel inhibitors of AMPK: a therapeutic target for prostate cancer.

PubMed

Kumar, Rakesh; Maurya, Ranjana; Saran, Shweta

2018-02-23

Prostate cancer (PC) is one of the leading cancers in men, raising a serious health issue worldwide. Due to lack of suitable biomarker, their inhibitors and the platform for testing those inhibitors result in poor prognosis of PC. AMP-activated protein kinase (AMPK) is a highly conserved protein kinase found in eukaryotes that is involved in growth and development, and also acts as a therapeutic target for PC. The aim of the present study is to identify novel potent inhibitors of AMPK and propose a simple cellular model system for understanding its biology. Structural modelling and MD simulations were performed to construct and refine the 3D models of Dictyostelium and human AMPK. Binding mechanisms of different drug compounds were studied by performing molecular docking, molecular dynamics and MM-PBSA methods. Two novel drugs were isolated having higher binding affinity over the known drugs and hydrophobic forces that played a key role during protein-ligand interactions. The study also explored the simple cellular model system for drug screening and understanding the biology of a therapeutic target by performing in vitro experiments.

Detonation failure characterization of non-ideal explosives

NASA Astrophysics Data System (ADS)

Janesheski, Robert S.; Groven, Lori J.; Son, Steven

2012-03-01

Non-ideal explosives are currently poorly characterized, hence limiting the modeling of them. Current characterization requires large-scale testing to obtain steady detonation wave characterization for analysis due to the relatively thick reaction zones. Use of a microwave interferometer applied to small-scale confined transient experiments is being implemented to allow for time resolved characterization of a failing detonation. The microwave interferometer measures the position of a failing detonation wave in a tube that is initiated with a booster charge. Experiments have been performed with ammonium nitrate and various fuel compositions (diesel fuel and mineral oil). It was observed that the failure dynamics are influenced by factors such as chemical composition and confiner thickness. Future work is planned to calibrate models to these small-scale experiments and eventually validate the models with available large scale experiments. This experiment is shown to be repeatable, shows dependence on reactive properties, and can be performed with little required material.

A new RISE-based adaptive control of PKMs: design, stability analysis and experiments

NASA Astrophysics Data System (ADS)

Bennehar, M.; Chemori, A.; Bouri, M.; Jenni, L. F.; Pierrot, F.

2018-03-01

This paper deals with the development of a new adaptive control scheme for parallel kinematic manipulators (PKMs) based on Rrbust integral of the sign of the error (RISE) control theory. Original RISE control law is only based on state feedback and does not take advantage of the modelled dynamics of the manipulator. Consequently, the overall performance of the resulting closed-loop system may be poor compared to modern advanced model-based control strategies. We propose in this work to extend RISE by including the nonlinear dynamics of the PKM in the control loop to improve its overall performance. More precisely, we augment original RISE control scheme with a model-based adaptive control term to account for the inherent nonlinearities in the closed-loop system. To demonstrate the relevance of the proposed controller, real-time experiments are conducted on the Delta robot, a three-degree-of-freedom (3-DOF) PKM.

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.

The impact of covariance misspecification in group-based trajectory models for longitudinal data with non-stationary covariance structure.

PubMed

Davies, Christopher E; Glonek, Gary Fv; Giles, Lynne C

2017-08-01

One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Group-based trajectory models generally assume a certain structure in the covariances between measurements, for example conditional independence, homogeneous variance between groups or stationary variance over time. Violations of these assumptions could be expected to result in poor model performance. We used simulation to investigate the effect of covariance misspecification on misclassification of trajectories in commonly used models under a range of scenarios. To do this we defined a measure of performance relative to the ideal Bayesian correct classification rate. We found that the more complex models generally performed better over a range of scenarios. In particular, incorrectly specified covariance matrices could significantly bias the results but using models with a correct but more complicated than necessary covariance matrix incurred little cost.

Functional Imaging of Audio-Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed

Rinne, Teemu; Muers, Ross S; Salo, Emma; Slater, Heather; Petkov, Christopher I

2017-06-01

The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio-visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio-visual selective attention modulates the primate brain, identify sources for "lost" attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. © The Author 2017. Published by Oxford University Press.

Functional Imaging of Audio–Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed Central

Muers, Ross S.; Salo, Emma; Slater, Heather; Petkov, Christopher I.

2017-01-01

Abstract The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio–visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio–visual selective attention modulates the primate brain, identify sources for “lost” attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. PMID:28419201

Adverse events associated with poor neurological outcome during targeted temperature management and advanced critical care after out-of-hospital cardiac arrest.

PubMed

Kim, Young-Min; Youn, Chun Song; Kim, Soo Hyun; Lee, Byung Kook; Cho, In Soo; Cho, Gyu Chong; Jeung, Kyung Woon; Oh, Sang Hoon; Choi, Seung Pill; Shin, Jong Hwan; Cha, Kyoung-Chul; Oh, Joo Suk; Yim, Hyeon Woo; Park, Kyu Nam

2015-07-22

The aim of this study was to investigate the association of adverse events (AEs) during targeted temperature management (TTM) and other AEs and concomitant treatments during the advanced critical care period with poor neurological outcome at hospital discharge in adult out-of-hospital cardiac arrest (OHCA) patients. This was a retrospective study using Korean Hypothermia Network registry data of adult OHCA patients treated with TTM in 24 teaching hospitals throughout South Korea from 2007 to 2012. Demographic characteristics, resuscitation and post-resuscitation variables, AEs, and concomitant treatments during TTM and the advanced critical care were collected. The primary outcome was poor neurological outcome, defined as a cerebral performance category (CPC) score of 3-5 at hospital discharge. The AEs and concomitant treatments were individually entered into the best multivariable predictive model of poor neurological outcome to evaluate the associations between each variable and outcome. A total of 930 patients, including 704 for whom a complete dataset of AEs and covariates was available for multivariable modeling, were included in the analysis; 476 of these patients exhibited poor neurological outcome [CPC 3 = 50 (7.1%), CPC 4 = 214 (30.4%), and CPC 5 = 212 (30.1%)]. Common AEs included hyperglycemia (45.6%), hypokalemia (31.3%), arrhythmia (21.3%) and hypotension (29%) during cooling, and hypotension (21.6%) during rewarming. Bleeding (5%) during TTM was a rare AE. Common AEs during the advanced critical care included pneumonia (39.6%), myoclonus (21.9%), seizures (21.7%) and hypoglycemia within 72 hours (23%). After adjusting for independent predictors of outcome, cooling- and rewarming-related AEs were not significantly associated with poor neurological outcome. However, sepsis, myoclonus, seizure, hypoglycemia within 72 hours and anticonvulsant use during the advanced critical care were associated with poor neurological outcome [adjusted odds ratios (95% confidence intervals) of 3.12 (1.40-6.97), 3.72 (1.93-7.16), 4.02 (2.04-7.91), 2.03 (1.09-3.78), and 1.69 (1.03-2.77), respectively]. Alternatively, neuromuscular blocker use was inversely associated with poor neurological outcome (0.48 [0.28-0.84]). Cooling- and rewarming-related AEs were not associated with poor neurological outcome at hospital discharge. Sepsis, myoclonus, seizure, hypoglycemia within 72 hours and anticonvulsant use during the advanced critical care period were associated with poor neurological outcome at hospital discharge in our study.

Identification and characterization of poorly differentiated invasive carcinomas in a mouse model of pancreatic neuroendocrine tumorigenesis.

PubMed

Hunter, Karen E; Quick, Marsha L; Sadanandam, Anguraj; Hanahan, Douglas; Joyce, Johanna A

2013-01-01

Pancreatic neuroendocrine tumors (PanNETs) are a relatively rare but clinically challenging tumor type. In particular, high grade, poorly-differentiated PanNETs have the worst patient prognosis, and the underlying mechanisms of disease are poorly understood. In this study we have identified and characterized a previously undescribed class of poorly differentiated PanNETs in the RIP1-Tag2 mouse model. We found that while the majority of tumors in the RIP1-Tag2 model are well-differentiated insulinomas, a subset of tumors had lost multiple markers of beta-cell differentiation and were highly invasive, leading us to term them poorly differentiated invasive carcinomas (PDICs). In addition, we found that these tumors exhibited a high mitotic index, resembling poorly differentiated (PD)-PanNETs in human patients. Interestingly, we identified expression of Id1, an inhibitor of DNA binding gene, and a regulator of differentiation, specifically in PDIC tumor cells by histological analysis. The identification of PDICs in this mouse model provides a unique opportunity to study the pathology and molecular characteristics of PD-PanNETs.

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

Getting off on the Wrong Foot: Longitudinal Effects of Hispanic Students' Stability Attributions Following Poor Initial Test Performance

ERIC Educational Resources Information Center

Cox, Cody B.; Yang, Yan

2012-01-01

Though studies have established that following poor performance, attributions to stable causes affect the performance of minority students, few studies have explored the impact of stability attributions over time. This study explored attributions following initial failure among a predominantly Hispanic student population. We measured students'…

Performance of Seven Seed Sources of Blue Spruce in Central North Dakota

Treesearch

David H. Dawson; Paul O. Rudolf

1966-01-01

Blue spruce (Picea pungens Engelm.) has been planted quite extensively in North Dakota shelterbelts and farmstead windbreaks. Generally survival and growth have been promising, but there is considerable variation in performance of individual trees or plantations. Poorly adapted seed sources have been suspected as one cause for poor performance. There should be...

Assembling nanoparticle coatings to improve the drug delivery performance of lipid based colloids

NASA Astrophysics Data System (ADS)

Simovic, Spomenka; Barnes, Timothy J.; Tan, Angel; Prestidge, Clive A.

2012-02-01

Lipid based colloids (e.g. emulsions and liposomes) are widely used as drug delivery systems, but often suffer from physical instabilities and non-ideal drug encapsulation and delivery performance. We review the application of engineered nanoparticle layers at the interface of lipid colloids to improve their performance as drug delivery systems. In addition we focus on the creation of novel hybrid nanomaterials from nanoparticle-lipid colloid assemblies and their drug delivery applications. Specifically, nanoparticle layers can be engineered to enhance the physical stability of submicron lipid emulsions and liposomes, satbilise encapsulated active ingredients against chemical degradation, control molecular transport and improve the dermal and oral delivery characteristics, i.e. increase absorption, bioavailability and facilitate targeted delivery. It is feasible that hybrid nanomaterials composed of nanoparticles and colloidal lipids are effective encapsulation and delivery systems for both poorly soluble drugs and biological drugs and may form the basis for the next generation of medicines. Additional pre-clinical research including specific animal model studies are required to advance the peptide/protein delivery systems, whereas the silica lipid hybrid systems have now entered human clinical trials for poorly soluble drugs.

Sensorimotor and postural control factors associated with driving safety in a community-dwelling older driver population.

PubMed

Lacherez, Philippe; Wood, Joanne M; Anstey, Kaarin J; Lord, Stephen R

2014-02-01

To establish whether sensorimotor function and balance are associated with on-road driving performance in older adults. The performance of 270 community-living adults aged 70-88 years recruited via the electoral roll was measured on a battery of peripheral sensation, strength, flexibility, reaction time, and balance tests and on a standardized measure of on-road driving performance. Forty-seven participants (17.4%) were classified as unsafe based on their driving assessment. Unsafe driving was associated with reduced peripheral sensation, lower limb weakness, reduced neck range of motion, slow reaction time, and poor balance in univariate analyses. Multivariate logistic regression analysis identified poor vibration sensitivity, reduced quadriceps strength, and increased sway on a foam surface with eyes closed as significant and independent risk factors for unsafe driving. These variables classified participants into safe and unsafe drivers with a sensitivity of 74% and specificity of 70%. A number of sensorimotor and balance measures were associated with driver safety and the multivariate model comprising measures of sensation, strength, and balance was highly predictive of unsafe driving in this sample. These findings highlight important determinants of driver safety and may assist in developing efficacious driver safety strategies for older drivers.

Intercomparison and Evaluation of Global Aerosol Microphysical Properties Among Aerocom Models of a Range of Complexity

NASA Technical Reports Server (NTRS)

Mann, G. W.; Carslaw, K. S.; Reddington, C. L.; Pringle, K. J.; Schulz, M.; Asmi, A.; Spracklen, D. V.; Ridley, D. A.; Woodhouse, M. T.; Lee, L. A.;

Family incivility and job performance: a moderated mediation model of psychological distress and core self-evaluation.

PubMed

Lim, Sandy; Tai, Kenneth

2014-03-01

This study extends the stress literature by exploring the relationship between family incivility and job performance. We examine whether psychological distress mediates the link between family incivility and job performance. We also investigate how core self-evaluation might moderate this mediated relationship. Data from a 2-wave study indicate that psychological distress mediates the relationship between family incivility and job performance. In addition, core self-evaluation moderates the relationship between family incivility and psychological distress but not the relationship between psychological distress and job performance. The results hold while controlling for general job stress, family-to-work conflict, and work-to-family conflict. The findings suggest that family incivility is linked to poor performance at work, and psychological distress and core self-evaluation are key mechanisms in the relationship.

Combined use of local and global hydrometeorological data with regional and global hydrological models in the Magdalena - Cauca river basin, Colombia

NASA Astrophysics Data System (ADS)

Rodriguez, Erasmo; Sanchez, Ines; Duque, Nicolas; Lopez, Patricia; Kaune, Alexander; Werner, Micha; Arboleda, Pedro

2017-04-01

The Magdalena Cauca Macrobasin (MCMB) in Colombia, with an area of about 257,000 km2, is the largest and most important water resources system in the country. With almost 80% of the Colombian population (46 million people) settled in the basin, it is the main source of water for demands including human consumption, agriculture, hydropower generation, industrial activities and ecosystems. Despite its importance, the basin has witnessed enormous changes in land-cover and extensive deforestation during the last three decades. To make things more complicated, the MCMB currently lacks a set of tools to support planning and decision making processes at scale of the whole watershed. Considering this, the MCMB has been selected as one of the six different regional case studies in the eartH2Observe research project, in which hydrological and meteorological reanalysis products are being validated for the period 1980-2012. The combined use of the hydrological and meteorological reanalysis data, with local hydrometeorological data (precipitation, temperature and streamflow) provided by the National Hydrometeorological Agency (IDEAM), has given us the opportunity to implement and test three hydrological models (VIC, WFLOW and a Water Balance Model based on the Budyko framework) at the basin scale. Additionally, results from the global models in the eartH2Observe hydrological reanalysis have been used to evaluate their performance against the observed streamflow data. This paper discusses the comparison between streamflow observations and simulations from the global hydrological models forced with the WFDEI data, and regional models forced with a combination of observed and meteorological reanalysis data, in the whole domain of the MCMB. For the three regional models analysed results show good performances for some sub-basins and poor performances for others. This can be due to the smoothing of the precipitation fields, interpolated from point daily rainfall data, the effect of horizontal precipitation (not included in the models) and weaknesses in the models structures; for example the poor performance of the VIC model in base flow dominated basins. In order to improve these simulations a strategy based on a hydrological model ensemble is currently being developed in the case study. Results from the global models, show that these consistently tend to overestimate runoff. This may be due to the coarse resolution used (50 km), biases in the ERA-Interim precipitation forcing, and the different partitioning within the global models of the precipitation into evapotranspiration and runoff. It is expected that within the Tier II hydrological reanalysis, where the models will produce outputs at 25 km resolution, some improvements may be identified.

Sleep Quality Prediction From Wearable Data Using Deep Learning.

PubMed

Sathyanarayana, Aarti; Joty, Shafiq; Fernandez-Luque, Luis; Ofli, Ferda; Srivastava, Jaideep; Elmagarmid, Ahmed; Arora, Teresa; Taheri, Shahrad

2016-11-04

The importance of sleep is paramount to health. Insufficient sleep can reduce physical, emotional, and mental well-being and can lead to a multitude of health complications among people with chronic conditions. Physical activity and sleep are highly interrelated health behaviors. Our physical activity during the day (ie, awake time) influences our quality of sleep, and vice versa. The current popularity of wearables for tracking physical activity and sleep, including actigraphy devices, can foster the development of new advanced data analytics. This can help to develop new electronic health (eHealth) applications and provide more insights into sleep science. The objective of this study was to evaluate the feasibility of predicting sleep quality (ie, poor or adequate sleep efficiency) given the physical activity wearable data during awake time. In this study, we focused on predicting good or poor sleep efficiency as an indicator of sleep quality. Actigraphy sensors are wearable medical devices used to study sleep and physical activity patterns. The dataset used in our experiments contained the complete actigraphy data from a subset of 92 adolescents over 1 full week. Physical activity data during awake time was used to create predictive models for sleep quality, in particular, poor or good sleep efficiency. The physical activity data from sleep time was used for the evaluation. We compared the predictive performance of traditional logistic regression with more advanced deep learning methods: multilayer perceptron (MLP), convolutional neural network (CNN), simple Elman-type recurrent neural network (RNN), long short-term memory (LSTM-RNN), and a time-batched version of LSTM-RNN (TB-LSTM). Deep learning models were able to predict the quality of sleep (ie, poor or good sleep efficiency) based on wearable data from awake periods. More specifically, the deep learning methods performed better than traditional logistic regression. “CNN had the highest specificity and sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional logistic regression (0.6463). Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep. ©Aarti Sathyanarayana, Shafiq Joty, Luis Fernandez-Luque, Ferda Ofli, Jaideep Srivastava, Ahmed Elmagarmid, Teresa Arora, Shahrad Taheri. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 04.11.2016.

Sleep Quality Prediction From Wearable Data Using Deep Learning

PubMed Central

Sathyanarayana, Aarti; Joty, Shafiq; Ofli, Ferda; Srivastava, Jaideep; Elmagarmid, Ahmed; Arora, Teresa; Taheri, Shahrad

2016-01-01

Background The importance of sleep is paramount to health. Insufficient sleep can reduce physical, emotional, and mental well-being and can lead to a multitude of health complications among people with chronic conditions. Physical activity and sleep are highly interrelated health behaviors. Our physical activity during the day (ie, awake time) influences our quality of sleep, and vice versa. The current popularity of wearables for tracking physical activity and sleep, including actigraphy devices, can foster the development of new advanced data analytics. This can help to develop new electronic health (eHealth) applications and provide more insights into sleep science. Objective The objective of this study was to evaluate the feasibility of predicting sleep quality (ie, poor or adequate sleep efficiency) given the physical activity wearable data during awake time. In this study, we focused on predicting good or poor sleep efficiency as an indicator of sleep quality. Methods Actigraphy sensors are wearable medical devices used to study sleep and physical activity patterns. The dataset used in our experiments contained the complete actigraphy data from a subset of 92 adolescents over 1 full week. Physical activity data during awake time was used to create predictive models for sleep quality, in particular, poor or good sleep efficiency. The physical activity data from sleep time was used for the evaluation. We compared the predictive performance of traditional logistic regression with more advanced deep learning methods: multilayer perceptron (MLP), convolutional neural network (CNN), simple Elman-type recurrent neural network (RNN), long short-term memory (LSTM-RNN), and a time-batched version of LSTM-RNN (TB-LSTM). Results Deep learning models were able to predict the quality of sleep (ie, poor or good sleep efficiency) based on wearable data from awake periods. More specifically, the deep learning methods performed better than traditional linear regression. CNN had the highest specificity and sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional linear regression (0.6463). Conclusions Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep. PMID:27815231

A mediated modelling approach to promote collaborative learning in Andean rural micro-catchments in Colombia

NASA Astrophysics Data System (ADS)

Gowing, John; Dominguez, Isabel

2013-04-01

In rural catchments of developing countries water-related diseases, due to land use patterns (agriculture and livestock), microbial pollution, inadequate sanitation systems, access to water of poor quality, and lack of institutional support are common problems which disproportionally affect poor and vulnerable people. This research aims at developing a system dynamic model to improve the understanding of the macro and micro factors that influence human health and environmental health in rural micro-catchments in Valle del Cauca, Colombia. In this catchment livelihoods for most people depend on agriculture, particularly coffee. The research uses a mediated modeling approach, in which different stakeholders in modeling sessions, develop a STELLA model that allows them to identify relations between the economic, social and environmental factors and driving forces over the performance of their system. Stakeholders jointly develop the model structure in sessions facilitated by the researcher and the data required is gathered using secondary information from the different relevant institutions and primary information from field surveys that cover socioeconomic and environmental aspects that has not been previously collected by any institution or organization (i.e. household survey, stream water survey, and drinking water survey). Representation and understanding of their system will allow the stakeholders to test the effect of different management strategies in the micro-catchment and their associated socioeconomic, environmental and human health outcomes.

A Model of Fatigue Following Traumatic Brain Injury.

PubMed

Ponsford, Jennie; Schönberger, Michael; Rajaratnam, Shantha M W

2015-01-01

Fatigue is one of the most frequent sequelae of traumatic brain injury (TBI), although its causes are poorly understood. This study investigated the interrelationships between fatigue and sleepiness, vigilance performance, depression, and anxiety, using a structural equation modeling approach. Seventy-two participants with moderate to severe TBI (78% males) were recruited a median of 305 days postinjury. They completed the Fatigue Severity Scale, a vigilance task, the Epworth Sleepiness Scale, and Hospital Anxiety and Depression Scale. A model of the interrelationships between the study variables was developed, tested, and modified with path analysis. The modified model had a good overall fit (χ2 = 1.3, P = .54; comparative fit index = 1.0; root-mean square error of approximation = 0.0; standardized root-mean square residual = 0.02). Most paths in this model were significant (P < .05). Fatigue predicted anxiety, depression, and daytime sleepiness. Depression predicted daytime sleepiness and poor vigilance, whereas anxiety tended to predict reduced daytime sleepiness. This model confirms the complexity of fatigue experience. It supports the hypothesis that fatigue after TBI is a cause, not a consequence, of anxiety, depression, and daytime sleepiness, which, in turn (especially depression), may exacerbate fatigue by affecting cognitive functioning. These findings suggest that to alleviate fatigue, it is important to address each of these factors. However, the findings need to be confirmed with a longitudinal research design.

Orthographic Processing and Visual Sequential Memory in Unexpectedly Poor Spellers

ERIC Educational Resources Information Center

Holmes, Virginia M.; Malone, Aisling M.; Redenbach, Holly

2008-01-01

Does unexpectedly poor spelling in adults result from inferior visual sequential memory? In one experiment, unexpectedly poor spellers performed significantly worse than better spellers in the immediate reproduction of sequences of visual symbols, but in a second experiment, the effect was not replicated. Poor spellers were also no worse at the…

The diagnostic value of specific IgE to Ara h 2 to predict peanut allergy in children is comparable to a validated and updated diagnostic prediction model.

PubMed

Klemans, Rob J B; Otte, Dianne; Knol, Mirjam; Knol, Edward F; Meijer, Yolanda; Gmelig-Meyling, Frits H J; Bruijnzeel-Koomen, Carla A F M; Knulst, André C; Pasmans, Suzanne G M A

2013-01-01

A diagnostic prediction model for peanut allergy in children was recently published, using 6 predictors: sex, age, history, skin prick test, peanut specific immunoglobulin E (sIgE), and total IgE minus peanut sIgE. To validate this model and update it by adding allergic rhinitis, atopic dermatitis, and sIgE to peanut components Ara h 1, 2, 3, and 8 as candidate predictors. To develop a new model based only on sIgE to peanut components. Validation was performed by testing discrimination (diagnostic value) with an area under the receiver operating characteristic curve and calibration (agreement between predicted and observed frequencies of peanut allergy) with the Hosmer-Lemeshow test and a calibration plot. The performance of the (updated) models was similarly analyzed. Validation of the model in 100 patients showed good discrimination (88%) but poor calibration (P < .001). In the updating process, age, history, and additional candidate predictors did not significantly increase discrimination, being 94%, and leaving only 4 predictors of the original model: sex, skin prick test, peanut sIgE, and total IgE minus sIgE. When building a model with sIgE to peanut components, Ara h 2 was the only predictor, with a discriminative ability of 90%. Cutoff values with 100% positive and negative predictive values could be calculated for both the updated model and sIgE to Ara h 2. In this way, the outcome of the food challenge could be predicted with 100% accuracy in 59% (updated model) and 50% (Ara h 2) of the patients. Discrimination of the validated model was good; however, calibration was poor. The discriminative ability of Ara h 2 was almost comparable to that of the updated model, containing 4 predictors. With both models, the need for peanut challenges could be reduced by at least 50%. Copyright © 2012 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

The associations of indoor environment and psychosocial factors on the subjective evaluation of Indoor Air Quality among lower secondary school students: a multilevel analysis.

PubMed

Finell, E; Haverinen-Shaughnessy, U; Tolvanen, A; Laaksonen, S; Karvonen, S; Sund, R; Saaristo, V; Luopa, P; Ståhl, T; Putus, T; Pekkanen, J

2017-03-01

Subjective evaluation of Indoor Air Quality (subjective IAQ) reflects both building-related and psychosocial factors, but their associations have rarely been studied other than on the individual level in occupational settings and their interactions have not been assessed. Therefore, we studied whether schools' observed indoor air problems and psychosocial factors are associated with subjective IAQ and their potential interactions. The analysis was performed with a nationwide sample (N = 195 schools/26946 students) using multilevel modeling. Two datasets were merged: (i) survey data from students, including information on schools' psychosocial environment and subjective IAQ, and (ii) data from school principals, including information on observed indoor air problems. On the student level, school-related stress, poor teacher-student relationship, and whether the student did not easily receive help from school personnel, were significantly associated with poor subjective IAQ. On the school level, observed indoor air problem (standardized β = -0.43) and poor teacher-student relationship (standardized β = -0.22) were significant predictors of poor subjective IAQ. In addition, school-related stress was associated with poor subjective IAQ, but only in schools without observed indoor air problem (standardized β = -0.44). © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Learning to research in first grade: Bridging the transition from narrative to expository texts and tasks

NASA Astrophysics Data System (ADS)

Weise, Richard

Decades of research indicate that students at all academic grade and performance levels perform poorly with informational texts and tasks and particularly with locating assignment-relevant information in expository texts. Students have little understanding of the individual tasks required, the arc of the activity, the hierarchical structure of the information they seek, or how to reconstitute and interpret the information they extract. Poor performance begins with the introduction of textbooks and research assignments in fourth grade and continues into adulthood. However, to date, neither educators nor researchers have substantially addressed this problem. In this quasi-experimental study, we ask if first-grade children can perform essential tasks in identifying, extracting, and integrating assignment-relevant information and if instruction improves their performance. To answer this question, we conducted a 15-week, teacher-led, intervention in two first-grade classrooms in an inner-city Nashville elementary school. We created a computer learning environment (NoteTaker) to facilitate children's creation of a mental model of the research process and a narrative/expository bridge curriculum to support the children's transition from all narrative to all expository texts and tasks. We also created a new scaffolding taxonomy and a reading-to-research model to focus our research. Teachers participated in weekly professional development workshops. The results of this quasi-experimental study indicate that at-risk, first-grade children are able to (a) identify relevant information in an expository text, (b) categorize the information they identify, and (c) justify their choice of category. Children's performance in the first and last tasks significantly improved with instruction, and low-performing readers showed the greatest benefits from instruction. We find that the children's performance in categorizing information depended upon content-specific knowledge that was not taught, as well as on the process knowledge that was taught. We also find that children's narrative reading performance predicted their initial-performance for each assessment measure. We argue that first-grade children are developmentally ready to read expository texts and to learn reading-to-research tasks and that primary-school literacy instruction should not be limited to reading and writing stories.

Helicon thruster plasma modeling: Two-dimensional fluid-dynamics and propulsive performances

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

Ahedo, Eduardo; Navarro-Cavalle, Jaume

2013-04-15

An axisymmetric macroscopic model of the magnetized plasma flow inside the helicon thruster chamber is derived, assuming that the power absorbed from the helicon antenna emission is known. Ionization, confinement, subsonic flows, and production efficiency are discussed in terms of design and operation parameters. Analytical solutions and simple scaling laws for ideal plasma conditions are obtained. The chamber model is then matched with a model of the external magnetic nozzle in order to characterize the whole plasma flow and assess thruster performances. Thermal, electric, and magnetic contributions to thrust are evaluated. The energy balance provides the power conversion between ionsmore » and electrons in chamber and nozzle, and the power distribution among beam power, ionization losses, and wall losses. Thruster efficiency is assessed, and the main causes of inefficiency are identified. The thermodynamic behavior of the collisionless electron population in the nozzle is acknowledged to be poorly known and crucial for a complete plasma expansion and good thrust efficiency.« less

The Advanced Trauma Operative Management course--a two student to one faculty model.

PubMed

Ali, Jameel; Sorvari, Anne; Henry, Sharon; Kortbeek, John; Tremblay, Lorraine

2013-09-01

The internationally recognized Advanced Trauma Operative Management (ATOM) course uses a 1:1 student-to-faculty teaching model. This study examines a two student to one faculty ATOM teaching model. We randomly assigned 16 residents to four experienced ATOM faculty members. Half started with the one-student model and the other half with the two-student model and then switched using the same faculty. Students and faculty completed forms on the educational value of the two models (1 = very poor; 2 = poor; 3 = average; 4 = good; and 5 = excellent) and identified educational preferences and recommendations. We assigned educational values for the 13 procedures as follows: All faculty rated the one-student model as excellent; six members rated the two-student model as excellent, and seven as good. Students rated 50%-75% as excellent and 12%-44% as good for the two-student model, and 56%-81% as excellent and 12%-44% as good for the one-student model. Given resource constraints, all faculty and 88% of students preferred the two-student model. With no resource constraints, 75% of students and 50% of faculty chose the two-student model. All faculty and students rated both models "acceptable." Overall, 81% of students and 50% of faculty rated the two-student model better. All faculty members recommended that the models be optional; 94% of students recommended that they be either optional (50%) or a two-student model (44%). Performing or assisting on each procedure twice was considered an advantage of the two-student model. The two-student teaching model was acceptable and generally preferred in this study. With appropriately trained faculty and students, the two-student model is feasible and should result in less animal usage and possibly wider promulgation. Copyright © 2013 Elsevier Inc. All rights reserved.

Brainstem encephalitis: etiologies, treatment, and predictors of outcome

PubMed Central

Tan, Ik Lin; Mowry, Ellen M.; Steele, Sonya U.; Pardo, Carlos A.; McArthur, Justin C.; Nath, Avindra

2016-01-01

Brainstem encephalitis (BE) is an uncommon condition. We sought to characterize clinical presentations, etiologies, response to treatment, and predictors of outcome. We performed a retrospective review of non–HIV infected patients diagnosed with BE at Johns Hopkins Hospital (January 1997–April 2010). We characterized clinical and paraclinical features, and used regression models to assess associations with poor outcome. BE was diagnosed in 81 patients. An etiology was identified in 58 of 81 (71.6 %) of cases, most of which were confirmed or probable inflammatory/autoimmune conditions. Of the remaining 23 cases in which a specific diagnosis remained undefined, clinical presentation, CSF, neuroimaging studies, and outcomes were similar to the inflammatory/autoimmune group. Brain biopsy identified a specific diagnosis in 7 of 14 patients (50 %). Fifteen patients (18.5 %) either died or had a poor outcome. In multivariate logistic regression models, a higher CSF protein (per 5 mg/dl, OR = 1.11, 95 % CI: 1.03–1.20), a higher CSF glucose (per 5 mg/dl, OR = 1.36, 95 % CI: 1.09–1.70), and higher serum glucose (per 5 mg/dl, OR = 1.27, 95 % CI: 1.06–1.52) were independently associated with increased odds of poor outcome. Inflammatory and non-infectious conditions accounted for most cases of BE. Higher CSF protein and glucose were independently associated with poor outcome. In immunocompetent patients with BE of undefined etiology despite extensive investigation, a trial of immunosuppressive treatment may be warranted, though deterioration clinically or on magnetic resonance imaging should prompt a brain biopsy. PMID:23749332

Income gains predict cognitive functioning longitudinally throughout later childhood in poor children.

PubMed

Raffington, Laurel; Prindle, John J; Shing, Yee Lee

2018-04-26

Alleviating disadvantage in low-income environments predicts higher cognitive abilities during early childhood. It is less established whether family income continues to predict cognitive growth in later childhood or whether there may even be bidirectional dynamics. Notably, living in poverty may moderate income-cognition dynamics. In this study, we investigated longitudinal dynamics over 7 waves of data collection from 1,168 children between the ages of 4.6 and 12 years, 226 (19%) of whom lived in poverty in at least 1 wave, as part of the NICHD Study of Early Child Care and Youth Development. Two sets of dual change-score models evaluated, first, whether a score predicted change from that wave to the next and, second, whether change from 1 wave to the next predicted the following score. As previous comparisons have documented, poor children had substantially lower average starting points and cognitive growth slopes through later childhood. The first set of models showed that income scores did not predict cognitive change. In reverse, child cognitive scores positively predicted income change. We speculated that parents may reduce their work investment, thus reducing income gains, when their children fall behind. Second, income changes continued to positively predict higher cognitive scores at the following wave for poor children only, which suggests that income gains and losses continue to be a leading indicator in time of poor children's cognitive performance in later childhood. This study underlined the need to look at changes in income, allow for poverty moderation, and explore bidirectional income-cognition dynamics in middle childhood. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The impact of insight in a first-episode mania with psychosis population on outcome at 18 months.

PubMed

Smith, Leo T; Shelton, Clare L; Berk, Michael; Hasty, Melissa K; Cotton, Sue M; Henry, Lisa; Daglas, Rothanthi; Gentle, Ellen; McGorry, Patrick D; Macneil, Craig A; Conus, Philippe

2014-01-01

To explore whether poor initial insight during a first episode of mania with psychotic features was predictive of poor psychosocial and clinical outcomes at 18 months. Secondary analysis was performed on data collected during an 8-week RCT comparing the efficacy of olanzapine versus chlorpromazine as an adjunct to lithium, and at 18-month follow-up. 74 participants were divided into three groups (no insight, partial insight, and full insight) according to the insight item from the Young Mania Rating Scale (YMRS). Differences between these three groups were examined at baseline and at 18 months on measures of symptoms (YMRS, HAMD-21, and CGI-S), and social and occupational functioning (SOFAS). Baseline differences between the three groups were determined using general linear models and chi-squared analyses. Group differences from baseline to 18-month follow-up were determined using repeated measures general linear models. At baseline there were significant differences between the three insight groups in terms of mania and functioning, but at 18 months all groups had improved significantly in terms of psychopathology, mania, depression and social and occupational functioning. There were no significant differences between the three groups at study completion with respect to these domains. The study was limited by the lack of availability of a more detailed rating scale for insight, and it did not account for the duration of untreated psychosis (DUI). Poor initial insight during a first episode of mania with psychotic features does not predict poor clinical and psychosocial outcome at 18 months. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

Species delimitation using Bayes factors: simulations and application to the Sceloporus scalaris species group (Squamata: Phrynosomatidae).

PubMed

Grummer, Jared A; Bryson, Robert W; Reeder, Tod W

2014-03-01

Current molecular methods of species delimitation are limited by the types of species delimitation models and scenarios that can be tested. Bayes factors allow for more flexibility in testing non-nested species delimitation models and hypotheses of individual assignment to alternative lineages. Here, we examined the efficacy of Bayes factors in delimiting species through simulations and empirical data from the Sceloporus scalaris species group. Marginal-likelihood scores of competing species delimitation models, from which Bayes factor values were compared, were estimated with four different methods: harmonic mean estimation (HME), smoothed harmonic mean estimation (sHME), path-sampling/thermodynamic integration (PS), and stepping-stone (SS) analysis. We also performed model selection using a posterior simulation-based analog of the Akaike information criterion through Markov chain Monte Carlo analysis (AICM). Bayes factor species delimitation results from the empirical data were then compared with results from the reversible-jump MCMC (rjMCMC) coalescent-based species delimitation method Bayesian Phylogenetics and Phylogeography (BP&P). Simulation results show that HME and sHME perform poorly compared with PS and SS marginal-likelihood estimators when identifying the true species delimitation model. Furthermore, Bayes factor delimitation (BFD) of species showed improved performance when species limits are tested by reassigning individuals between species, as opposed to either lumping or splitting lineages. In the empirical data, BFD through PS and SS analyses, as well as the rjMCMC method, each provide support for the recognition of all scalaris group taxa as independent evolutionary lineages. Bayes factor species delimitation and BP&P also support the recognition of three previously undescribed lineages. In both simulated and empirical data sets, harmonic and smoothed harmonic mean marginal-likelihood estimators provided much higher marginal-likelihood estimates than PS and SS estimators. The AICM displayed poor repeatability in both simulated and empirical data sets, and produced inconsistent model rankings across replicate runs with the empirical data. Our results suggest that species delimitation through the use of Bayes factors with marginal-likelihood estimates via PS or SS analyses provide a useful and complementary alternative to existing species delimitation methods.

Linking Logistics and Operations: A Case Study of World War II Air Power

DTIC Science & Technology

1991-01-01

Weapon System Evaluation Group, 1951, p. 30). The logistic innovation greatly extended the time that combat ships could remain on station and...presented. This Note was produced under the Project AIR FORCE Resource Management and System Acquisition Program in the project "Combat Support C3 Needs...maintenance workload data suggest either unacceptable system performance or excessive costs. The predictive power of these models is so poor as to

Reduced order models for assessing CO 2 impacts in shallow unconfined aquifers

DOE PAGES

Keating, Elizabeth H.; Harp, Dylan H.; Dai, Zhenxue; ...

2016-01-28

Risk assessment studies of potential CO 2 sequestration projects consider many factors, including the possibility of brine and/or CO 2 leakage from the storage reservoir. Detailed multiphase reactive transport simulations have been developed to predict the impact of such leaks on shallow groundwater quality; however, these simulations are computationally expensive and thus difficult to directly embed in a probabilistic risk assessment analysis. Here we present a process for developing computationally fast reduced-order models which emulate key features of the more detailed reactive transport simulations. A large ensemble of simulations that take into account uncertainty in aquifer characteristics and CO 2/brinemore » leakage scenarios were performed. Twelve simulation outputs of interest were used to develop response surfaces (RSs) using a MARS (multivariate adaptive regression splines) algorithm (Milborrow, 2015). A key part of this study is to compare different measures of ROM accuracy. We then show that for some computed outputs, MARS performs very well in matching the simulation data. The capability of the RS to predict simulation outputs for parameter combinations not used in RS development was tested using cross-validation. Again, for some outputs, these results were quite good. For other outputs, however, the method performs relatively poorly. Performance was best for predicting the volume of depressed-pH-plumes, and was relatively poor for predicting organic and trace metal plume volumes. We believe several factors, including the non-linearity of the problem, complexity of the geochemistry, and granularity in the simulation results, contribute to this varied performance. The reduced order models were developed principally to be used in probabilistic performance analysis where a large range of scenarios are considered and ensemble performance is calculated. We demonstrate that they effectively predict the ensemble behavior. But, the performance of the RSs is much less accurate when used to predict time-varying outputs from a single simulation. If an analysis requires only a small number of scenarios to be investigated, computationally expensive physics-based simulations would likely provide more reliable results. Finally, if the aggregate behavior of a large number of realizations is the focus, as will be the case in probabilistic quantitative risk assessment, the methodology presented here is relatively robust.« less

Discrete element modelling of bedload transport

NASA Astrophysics Data System (ADS)

Loyer, A.; Frey, P.

2011-12-01

Discrete element modelling (DEM) has been widely used in solid mechanics and in granular physics. In this type of modelling, each individual particle is taken into account and intergranular interactions are modelled with simple laws (e.g. Coulomb friction). Gravity and contact forces permit to solve the dynamical behaviour of the system. DEM is interesting to model configurations and access to parameters not directly available in laboratory experimentation, hence the term "numerical experimentations" sometimes used to describe DEM. DEM was used to model bedload transport experiments performed at the particle scale with spherical glass beads in a steep and narrow flume. Bedload is the larger material that is transported on the bed on stream channels. It has a great geomorphic impact. Physical processes ruling bedload transport and more generally coarse-particle/fluid systems are poorly known, arguably because granular interactions have been somewhat neglected. An existing DEM code (PFC3D) already computing granular interactions was used. We implemented basic hydrodynamic forces to model the fluid interactions (buoyancy, drag, lift). The idea was to use the minimum number of ingredients to match the experimental results. Experiments were performed with one-size and two-size mixtures of coarse spherical glass beads entrained by a shallow turbulent and supercritical water flow down a steep channel with a mobile bed. The particle diameters were 4 and 6mm, the channel width 6.5mm (about the same width as the coarser particles) and the channel inclination was typically 10%. The water flow rate and the particle rate were kept constant at the upstream entrance and adjusted to obtain bedload transport equilibrium. Flows were filmed from the side by a high-speed camera. Using image processing algorithms made it possible to determine the position, velocity and trajectory of both smaller and coarser particles. Modelled and experimental particle velocity and concentration depth profiles were compared in the case of the one-size mixture. The turbulent fluid velocity profile was prescribed and attached to the variable upper bedline. Provided the upper bedline was calculated with a refined space and time resolution, a fair agreement between DEM and experiments was reached. Experiments with two-size mixtures were designed to study vertical grain size sorting or segregation patterns. Sorting is arguably the reason why the predictive capacity of bedload formulations remains so poor. Modelling of the two-size mixture was also performed and gave promising qualitative results.

Relationship between alcohol consumption, whether linked to other substance use or not, and antiretroviral treatment adherence in HIV+ patients.

PubMed

González-Álvarez, Sara; Madoz-Gúrpide, Agustín; Parro-Torres, Carlos; Hernández-Huerta, Daniel; Ochoa Mangado, Enriqueta

2017-07-14

Hazardous alcohol consumption is a common diagnosis among people living with HIV infection. The relationship between alcohol consumption and poor adherence to antiretroviral therapy has been highlighted in different studies, yet few of them performed a parallel analysis of other substance use. In Spain, alcohol consumption is frequently associated with other substance use, mainly cannabis and cocaine. The aim of this study is to assess the influence of hazardous alcohol consumption both combined with other substances (cocaine, heroin, methadone and/or cannabis) or alone on antiretroviral therapy adherence in our social environment. We performed an observational case-control study including 119 HIV+ individuals. We recruited 40 non-adherent patients, defined by less than 90% compliance according to hospital pharmacy refill data, and corroborated by the Simplified Medication Adherence Questionnaire (SMAQ) and referring professional's opinion. Control cases (n=79) were defined as those patients with similar characteristics but considered adherent according to the same parameters. Data collection took place between May 2013 and September 2015. Statistical analysis was performed using a binary logistic regression model. Our results indicate that alcohol consumption decreases adherence to antiretroviral therapy. The use of methadone represents a statistically significant increased risk of poor adherence. No significant differences were found between adherent and non-adherent groups regarding cocaine, heroin or cannabis use in this study. In summary, the detection of substance use and especially alcohol consumption in HIV+ patients can improve the effectiveness of antiretroviral therapy by identifying and treating at-risk individuals for a poor therapeutic adherence.

Human casualties in earthquakes: Modelling and mitigation

USGS Publications Warehouse

Spence, R.J.S.; So, E.K.M.

2011-01-01

Earthquake risk modelling is needed for the planning of post-event emergency operations, for the development of insurance schemes, for the planning of mitigation measures in the existing building stock, and for the development of appropriate building regulations; in all of these applications estimates of casualty numbers are essential. But there are many questions about casualty estimation which are still poorly understood. These questions relate to the causes and nature of the injuries and deaths, and the extent to which they can be quantified. This paper looks at the evidence on these questions from recent studies. It then reviews casualty estimation models available, and finally compares the performance of some casualty models in making rapid post-event casualty estimates in recent earthquakes.

Novel Hydrogen Production Systems Operative at Thermodynamic Extremes

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

Gunsalus, Robert

2012-11-30

We have employed a suite of molecular, bioinformatics, and biochemical tools to interrogate the thermodynamically limiting steps of H{sub 2} production from fatty acids in syntrophic communities. We also developed a new microbial model system that generates high H{sub 2} concentrations (over 17% of the gas phase) with high H{sub 2} yields of over 3 moles H{sub 2} per mole glucose. Lastly, a systems-based study of biohydrogen production in model anaerobic consortia was performed to begin identifying key regulated steps as a precursor to modeling co-metabolism. The results of these studies significantly expand our ability to predict and model systemsmore » for H{sub 2} production in novel anaerobes that are currently very poorly documented or understood.« less

Why Rural Community Day Secondary Schools Students' Performance in Physical Science Examinations Is Poor in Lilongwe Rural West Education District in Malawi

ERIC Educational Resources Information Center

Mlangeni, Angstone Noel J. Thembachako; Chiotha, Sosten Staphael

2015-01-01

A study was conducted to investigate factors that affect students' poor performance in physical science examinations at Malawi School Certificate of Education and Junior Certificate of Education levels in Community day secondary schools (CDSS) in Lilongwe Rural West Education District in Malawi. Students' performance was collected from schools'…

Is Self-Worth Protection Best Regarded as Intentional Self-Handicapping Behaviour or an Outcome of Choking under Pressure?

ERIC Educational Resources Information Center

Thompson, Ted; Dinnel, Dale L.

2007-01-01

Self-worth protective students characteristically perform poorly when they anticipate that poor performance is likely to reveal low ability, yet perform well in situations that involve little threat to self-worth. The present study sought a further understanding of this variable pattern of achievement, assessing two possibilities: (1) that the…

An exhaustive approach for identification of flood risk hotspots in data poor regions enforcing combined geomorphic and socio-economic indicators

NASA Astrophysics Data System (ADS)

Mohanty, M. P.; Karmakar, S.; Ghosh, S.

2017-12-01

Many countries across the Globe are victims of floods. To monitor them, various sophisticated algorithms and flood models are used by the scientific community. However, there still lies a gap to efficiently mapping flood risk. The limitations being: (i) scarcity of extensive data inputs required for precise flood modeling, (ii) fizzling performance of models in large and complex terrains (iii) high computational cost and time, and (iv) inexpertise in handling model simulations by civic bodies. These factors trigger the necessity of incorporating uncomplicated and inexpensive, yet precise approaches to identify areas at different levels of flood risk. The present study addresses this issue by utilizing various easily available, low cost data in a GIS environment for a large flood prone and data poor region. A set of geomorphic indicators of Digital Elevation Model (DEM) are analysed through linear binary classification, and are used to identify the flood hazard. The performance of these indicators is then investigated using receiver operating characteristics (ROC) curve, whereas the calibration and validation of the derived flood maps are accomplished through a comparison with dynamically coupled 1-D 2-D flood model outputs. A high degree of similarity on flood inundation proves the reliability of the proposed approach in identifying flood hazard. On the other hand, an extensive list of socio-economic indicators is selected to represent the flood vulnerability at a very finer forward sortation level using multivariate Data Envelopment Analysis (DEA). A set of bivariate flood risk maps is derived combining the flood hazard and socio-economic vulnerability maps. Given the acute problem of floods in developing countries, the proposed methodology which may be characterized by low computational cost, lesser data requirement and limited flood modeling complexity may facilitate local authorities and planners for deriving effective flood management strategies.

Effects of nicergoline on age-related decrements in radial maze performance and acetylcholine levels.

PubMed

McArthur, R A; Carfagna, N; Banfi, L; Cavanus, S; Cervini, M A; Fariello, R; Post, C

1997-01-01

The effects of chronic oral administration of nicergoline (5.0 mg/kg; bid) on locomotor activity, eight-arm radial maze performance plus striatal, cortical, and hippocampal acetylcholine (ACh) levels were examined in young and aged Wistar rats. Chronic nicergoline administration did not modify either the locomotor activity or radial maze learning in young rats. Young rats learned the radial maze procedure rapidly and improved their performance throughout the successive training sessions. Radial maze performance in young rats was characterised by very few arm reentries. Aged rats were hypoactive and did not explore or enter the radial maze arms, and consequently performed poorly in the radial maze throughout the training sessions. Nicergoline treatment did not significantly modify locomotor activity in aged rats. Aged rats treated with nicergoline also performed poorly initially but improved with repeated training in the radial maze. This improvement was associated with an increasing number of arms being entered and very few arm reentries. Reduced acetylcholine (ACh) levels were also associated with age. Aged rats had significantly reduced levels of ACh in the straitum and cortex, but not the hippocampus as compared to young rats. Nicergoline treatment did not change ACh levels in young rats, but substantially restored the reduced ACh levels in aged rats. These results indicate that nicergoline is an effective cognitive enhancer in a learning model of age-related deficits and that these results may be related to changes in the cholinergic system.

[Medical Image Registration Method Based on a Semantic Model with Directional Visual Words].

PubMed

Jin, Yufei; Ma, Meng; Yang, Xin

2016-04-01

Medical image registration is very challenging due to the various imaging modality,image quality,wide inter-patients variability,and intra-patient variability with disease progressing of medical images,with strict requirement for robustness.Inspired by semantic model,especially the recent tremendous progress in computer vision tasks under bag-of-visual-word framework,we set up a novel semantic model to match medical images.Since most of medical images have poor contrast,small dynamic range,and involving only intensities and so on,the traditional visual word models do not perform very well.To benefit from the advantages from the relative works,we proposed a novel visual word model named directional visual words,which performs better on medical images.Then we applied this model to do medical registration.In our experiment,the critical anatomical structures were first manually specified by experts.Then we adopted the directional visual word,the strategy of spatial pyramid searching from coarse to fine,and the k-means algorithm to help us locating the positions of the key structures accurately.Sequentially,we shall register corresponding images by the areas around these positions.The results of the experiments which were performed on real cardiac images showed that our method could achieve high registration accuracy in some specific areas.

Factors Affecting the Delivery, Access, and Use of Interventions to Prevent Malaria in Pregnancy in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

PubMed Central

Hill, Jenny; Hoyt, Jenna; van Eijk, Anna Maria; D'Mello-Guyett, Lauren; ter Kuile, Feiko O.; Steketee, Rick; Smith, Helen; Webster, Jayne

2013-01-01

Background Malaria in pregnancy has important consequences for mother and baby. Coverage with the World Health Organization–recommended prevention strategy for pregnant women in sub-Saharan Africa of intermittent preventive treatment in pregnancy (IPTp) and insecticide-treated nets (ITNs) is low. We conducted a systematic review to explore factors affecting delivery, access, and use of IPTp and ITNs among healthcare providers and women. Methods and Results We searched the Malaria in Pregnancy Library and Global Health Database from 1 January 1990 to 23 April 2013, without language restriction. Data extraction was performed by two investigators independently, and data was appraised for quality and content. Data on barriers and facilitators, and the effect of interventions, were explored using content analysis and narrative synthesis. We conducted a meta-analysis of determinants of IPTp and ITN uptake using random effects models, and performed subgroup analysis to evaluate consistency across interventions and study populations, countries, and enrolment sites. We did not perform a meta-ethnography of qualitative data. Ninety-eight articles were included, of which 20 were intervention studies. Key barriers to the provision of IPTp and ITNs were unclear policy and guidance on IPTp; general healthcare system issues, such as stockouts and user fees; health facility issues stemming from poor organisation, leading to poor quality of care; poor healthcare provider performance, including confusion over the timing of each IPTp dose; and women's poor antenatal attendance, affecting IPTp uptake. Key determinants of IPTp coverage were education, knowledge about malaria/IPTp, socio-economic status, parity, and number and timing of antenatal clinic visits. Key determinants of ITN coverage were employment status, education, knowledge about malaria/ITNs, age, and marital status. Predictors showed regional variations. Conclusions Delivery of ITNs through antenatal clinics presents fewer problems than delivery of IPTp. Many obstacles to IPTp delivery are relatively simple barriers that could be resolved in the short term. Other barriers are more entrenched within the overall healthcare system or socio-economic/cultural contexts, and will require medium- to long-term strategies. Please see later in the article for the Editors' Summary PMID:23935459

Fatigue - but not mTBI history, PTSD, or sleep quality - directly contributes to reduced prospective memory performance in Iraq and Afghanistan era Veterans.

PubMed

Rau, Holly K; Hendrickson, Rebecca; Roggenkamp, Hannah C; Peterson, Sarah; Parmenter, Brett; Cook, David G; Peskind, Elaine; Pagulayan, Kathleen F

2017-10-13

Memory problems that affect daily functioning are a frequent complaint among Veterans reporting a history of repetitive mild traumatic brain injury (mTBI), especially in cohorts with comorbid PTSD. Here, we test the degree to which subjective sleep impairment and daytime fatigue account for the association of PTSD and self-reported mTBI history with prospective memory. 82 Veterans with and without personal history of repeated blast-related mTBI during deployment were administered the Clinician Administered PTSD Scale (CAPS), Memory for Intentions Test (MIST), Patient Health Questionnaire-9 (PHQ-9), Neurobehavioral Symptom Inventory (NSI), and the Pittsburgh Sleep Quality Index (PSQI). Relationships between self-reported mTBI, PTSD, self-reported poor sleep and daytime fatigue, and MIST performance were modeled using partial least squares structural equation modeling (PLS-SEM). Reported daytime fatigue was strongly associated with poorer prospective memory performance. Poor subjective sleep quality was strongly and positively associated with reported daytime fatigue, but had no significant direct effect on prospective memory performance. PTSD diagnosis and self-reported mTBI history were only associated with prospective memory via their impact on subjective sleep quality and daytime fatigue. Results suggest that daytime fatigue may be a mediating factor by which both mTBI and PTSD can interfere with prospective memory. Additional attention should be given to complaints of daytime fatigue, independent of subjective sleep quality, in the clinical care of those with a self-reported history of mTBI, and/or PTSD. Further research into whether interventions that decrease daytime fatigue lead to improvement in prospective memory and subjective cognitive functioning is warranted.

An integrative model of the impairments in insight in schizophrenia: emerging research on causal factors and treatments.

PubMed

Vohs, Jenifer L; George, Sunita; Leonhardt, Bethany L; Lysaker, Paul H

2016-10-01

Poor insight, or unawareness of some major aspect of mental illness, is a major barrier to wellness when it interferes with persons seeking out treatment or forming their own understanding of the challenges they face. One barrier to addressing impaired insight is the absence of a comprehensive model of how poor insight develops. To explore this issue we review how poor insight is the result of multiple phenomena which interfere with the construction of narrative accounts of psychiatric challenges, rather than a single social or biological cause. Expert commentary: We propose an integrative model of poor insight in schizophrenia which involves the interaction of symptoms, deficits in neurocognition, social cognition, metacognition, and stigma. Emerging treatments for poor insight including therapies which focus on the development of metacognition are discussed.

Rapid B-rep model preprocessing for immersogeometric analysis using analytic surfaces

PubMed Central

Wang, Chenglong; Xu, Fei; Hsu, Ming-Chen; Krishnamurthy, Adarsh

2017-01-01

Computational fluid dynamics (CFD) simulations of flow over complex objects have been performed traditionally using fluid-domain meshes that conform to the shape of the object. However, creating shape conforming meshes for complicated geometries like automobiles require extensive geometry preprocessing. This process is usually tedious and requires modifying the geometry, including specialized operations such as defeaturing and filling of small gaps. Hsu et al. (2016) developed a novel immersogeometric fluid-flow method that does not require the generation of a boundary-fitted mesh for the fluid domain. However, their method used the NURBS parameterization of the surfaces for generating the surface quadrature points to enforce the boundary conditions, which required the B-rep model to be converted completely to NURBS before analysis can be performed. This conversion usually leads to poorly parameterized NURBS surfaces and can lead to poorly trimmed or missing surface features. In addition, converting simple geometries such as cylinders to NURBS imposes a performance penalty since these geometries have to be dealt with as rational splines. As a result, the geometry has to be inspected again after conversion to ensure analysis compatibility and can increase the computational cost. In this work, we have extended the immersogeometric method to generate surface quadrature points directly using analytic surfaces. We have developed quadrature rules for all four kinds of analytic surfaces: planes, cones, spheres, and toroids. We have also developed methods for performing adaptive quadrature on trimmed analytic surfaces. Since analytic surfaces have frequently been used for constructing solid models, this method is also faster to generate quadrature points on real-world geometries than using only NURBS surfaces. To assess the accuracy of the proposed method, we perform simulations of a benchmark problem of flow over a torpedo shape made of analytic surfaces and compare those to immersogeometric simulations of the same model with NURBS surfaces. We also compare the results of our immersogeometric method with those obtained using boundary-fitted CFD of a tessellated torpedo shape, and quantities of interest such as drag coefficient are in good agreement. Finally, we demonstrate the effectiveness of our immersogeometric method for high-fidelity industrial scale simulations by performing an aerodynamic analysis of a truck that has a large percentage of analytic surfaces. Using analytic surfaces over NURBS avoids unnecessary surface type conversion and significantly reduces model-preprocessing time, while providing the same accuracy for the aerodynamic quantities of interest. PMID:29051678

Influence of hip and knee osteoarthritis on dynamic postural control parameters among older fallers.

PubMed

Mat, Sumaiyah; Ng, Chin Teck; Tan, Maw Pin

2017-03-06

To compare the relationship between postural control and knee and hip osteoarthritis in older adults with and without a history of falls. Fallers were those with ≥ 2 falls or 1 injurious fall over 12 months. Non-fallers were volunteers with no falls in the past year. Radiological evidence of osteoarthritis with no reported symptoms was considered "asymptomatic osteoarthritis", while "symptomatic osteoarthritis" was defined as radiographic osteoarthritis with pain or stiffness. Dynamic postural control was quantified with the limits of stability test measured on a balance platform (Neurocom® Balancemaster, California, USA). Parameters assessed were end-point excursion, maximal excursion, and directional control. A total of 102 older individuals, mean age 73 years (standard deviation 5.7) years were included. The association between falls and poor performance in maximal excursion and directional control was confounded by age and comorbidities. In the same linear equation model with falls, symptomatic osteoarthritis remained independently associated with poor end-point excursion (β-coefficient (95% confidence interval) -6.80 (-12.14 to -1.42)). Poor performance in dynamic postural control (maximal excursion and directional control) among fallers was not accounted for by hip/knee osteoarthritis, but was confounded by old age and comorbidities. Loss of postural control due to hip/knee osteoarthritis is not a risk factor for falls among community-dwelling older adults.

Childhood clumsiness and peer victimization: a case–control study of psychiatric patients

PubMed Central

2013-01-01

Background Poor motor and social skills as well as peer victimization are commonly reported in both ADHD and autism spectrum disorder. Positive relationships between poor motor and poor social skills, and between poor social skills and peer victimization, are well documented, but the relationship between poor motor skills and peer victimization has not been studied in psychiatric populations. Method 277 patients (133 males, 144 females), mean age 31 years, investigated for ADHD or autism spectrum disorder in adulthood and with normal intelligence, were interviewed about childhood peer victimization and examined for gross motor skills. The parents completed a comprehensive questionnaire on childhood problems, the Five to Fifteen. The Five to Fifteen is a validated questionnaire with 181 statements that covers various symptoms in childhood across eight different domains, one of them targeting motor skills. Regression models were used to evaluate the relationship between motor skills and the risk and duration of peer victimization, adjusted for sex and diagnosis. Results Victims were described as more clumsy in childhood than their non-victimized counterparts. A significant independent association was found between reportedly poor childhood gross motor skills and peer victimization (adjusted odds ratio: 2.97 [95% confidence interval: 1.46-6.07], n = 235, p = 0.003). In adulthood, the victimized group performed worse on vertical jumps, a gross motor task, and were lonelier. Other factors that were expected to be associated with peer victimization were not found in this highly selected group. Conclusion Poor gross motor skills constitute a strong and independent risk factor for peer victimization in childhood, regardless of sex, childhood psychiatric care and diagnosis. PMID:23442984

Poor decision-making by chronic marijuana users is associated with decreased functional responsiveness to negative consequences.

PubMed

Wesley, Michael J; Hanlon, Colleen A; Porrino, Linda J

2011-01-30

Chronic marijuana users (MJ Users) perform poorly on the Iowa Gambling Task (IGT), a complex decision-making task in which monetary wins and losses guide strategy development. This functional magnetic resonance imaging (MRI) study sought to determine if the poor performance of MJ Users was related to differences in brain activity while evaluating wins and losses during the strategy development phase of the IGT. MJ Users (16) and Controls (16) performed a modified IGT in an MRI scanner. Performance was tracked and functional activity in response to early wins and losses was examined. While the MJ Users continued to perform poorly at the end of the task, there was no difference in group performance during the initial strategy development phase. During this phase, before the emergence of behavioral differences, Controls exhibited significantly greater activity in response to losses in the anterior cingulate cortex, medial frontal cortex, precuneus, superior parietal lobe, occipital lobe and cerebellum as compared to MJ Users. Furthermore, in Controls, but not MJ Users, the functional response to losses in the anterior cingulate cortex, ventral medial prefrontal cortex and rostral prefrontal cortex positively correlated with performance over time. These data suggest MJ Users are less sensitive to negative feedback during strategy development. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Impact of familiar and unfamiliar settings on cooking task assessments in frail older adults with poor and preserved executive functions.

PubMed

Provencher, Véronique; Demers, Louise; Gagnon, Lise; Gélinas, Isabelle

2012-05-01

Hospitalized frail older patients are usually assessed for their ability to perform some daily living activities in a clinical setting prior to discharge. However, assessments that take place in this unfamiliar environment might not be as representative of their functional performance as assessments at home. This may be related to a decline in some cognitive components, such as executive functions (EF), which enable one to cope with new environments. This study thus aims to compare cooking task performance in familiar and unfamiliar settings in a population of frail older adults with poor and preserved EF. Thirty-seven frail older adults were assigned to one of two groups: poor EF or preserved EF. Participants performed two cooking tasks in familiar and unfamiliar settings, using a counterbalanced design. Their performance was assessed with a reliable tool based on observation of motor and process skills (Assessment of Motor and Process Skills). Thirty-three participants were retained for analysis. They demonstrated significantly better motor skills (F = 5.536; p = 0.025) and process skills (F = 8.149; p = 0.008) in the familiar setting. The difference between settings was particularly marked for process skills in participants with poor EF (F = 16.920; p < 0.001). This study suggests that a home setting may be preferable for a more accurate assessment of cooking task performance in frail older adults, especially those with poor EF. These findings highlight the risk of underestimating frail older adults' performance when assessed in an unfamiliar setting (e.g. hospital), which could lead to inefficient allocation of home care services.

Validating a model that predicts daily growth and feed quality of New Zealand dairy pastures.

PubMed

Woodward, S J

2001-09-01

The Pasture Quality (PQ) model is a simple, mechanistic, dynamical system model that was designed to capture the essential biological processes in grazed grass-clover pasture, and to be optimised to derive improved grazing strategies for New Zealand dairy farms. While the individual processes represented in the model (photosynthesis, tissue growth, flowering, leaf death, decomposition, worms) were based on experimental data, this did not guarantee that the assembled model would accurately predict the behaviour of the system as a whole (i.e., pasture growth and quality). Validation of the whole model was thus a priority, since any strategy derived from the model could impact a farm business in the order of thousands of dollars per annum if adopted. This paper describes the process of defining performance criteria for the model, obtaining suitable data to test the model, and carrying out the validation analysis. The validation process highlighted a number of weaknesses in the model, which will lead to the model being improved. As a result, the model's utility will be enhanced. Furthermore, validation was found to have an unexpected additional benefit, in that despite the model's poor initial performance, support was generated for the model among field scientists involved in the wider project.

Development, current applications and future roles of biorelevant two-stage in vitro testing in drug development.

PubMed

Fiolka, Tom; Dressman, Jennifer

2018-03-01

Various types of two stage in vitro testing have been used in a number of experimental settings. In addition to its application in quality control and for regulatory purposes, two-stage in vitro testing has also been shown to be a valuable technique to evaluate the supersaturation and precipitation behavior of poorly soluble drugs during drug development. The so-called 'transfer model', which is an example of two-stage testing, has provided valuable information about the in vivo performance of poorly soluble, weakly basic drugs by simulating the gastrointestinal drug transit from the stomach into the small intestine with a peristaltic pump. The evolution of the transfer model has resulted in various modifications of the experimental model set-up. Concomitantly, various research groups have developed simplified approaches to two-stage testing to investigate the supersaturation and precipitation behavior of weakly basic drugs without the necessity of using a transfer pump. Given the diversity among the various two-stage test methods available today, a more harmonized approach needs to be taken to optimize the use of two stage testing at different stages of drug development. © 2018 Royal Pharmaceutical Society.

Mental health, sleep quality, drinking motives, and alcohol-related consequences: a path-analytic model.

PubMed

Kenney, Shannon R; Lac, Andrew; Labrie, Joseph W; Hummer, Justin F; Pham, Andy

2013-11-01

Poor mental health, sleep problems, drinking motivations, and high-risk drinking are prevalent among college students. However, research designed to explicate the interrelationships among these health risk behaviors is lacking. This study was designed to assess the direct and indirect influences of poor mental health (a latent factor consisting of depression, anxiety, and stress) to alcohol use and alcohol-related consequences through the mediators of global sleep quality and drinking motives in a comprehensive model. Participants were 1,044 heavy-drinking college students (66.3% female) who completed online surveys. A hybrid structural equation model tested hypotheses involving relations leading from poor mental health to drinking motives and poorer global sleep quality to drinking outcomes. Results showed that poor mental health significantly predicted all four subscales of drinking motivations (social, coping, conformity, and enhancement) as well as poor sleep. Most of the drinking motives and poor sleep were found to explain alcohol use and negative alcohol consequences. Poor sleep predicted alcohol consequences, even after controlling for all other variables in the model. The hypothesized mediational pathways were examined with tests of indirect effects. This is the first study to assess concomitantly the relationships among three vital health-related domains (mental health, sleep behavior, and alcohol risk) in college students. Findings offer important implications for college personnel and interventionists interested in reducing alcohol risk by focusing on alleviating mental health problems and poor sleep quality.

Frequency of and risk factors for poor cognitive performance in hemodialysis patients

USDA-ARS?s Scientific Manuscript database

There are few detailed data on cognition in patients undergoing dialysis. We evaluated the frequency of and risk factors for poor cognitive performance using detailed neurocognitive testing. In this cross-sectional cohort study, 314 hemodialysis patients from 6 Boston-area hemodialysis units underwe...

Confronting Poor Performance.

ERIC Educational Resources Information Center

Dennis, Bruce L.

Responsible and effective administrative leadership requires confronting those members of the teaching staff who are a negative influence on the institution. Importantly, the absence of expressed appreciation for good work can have a devastating impact on a principal's image if he or she suddenly begins to confront poor performances. Actually, the…

What Matters from Admissions? Identifying Success and Risk Among Canadian Dental Students.

PubMed

Plouffe, Rachel A; Hammond, Robert; Goldberg, Harvey A; Chahine, Saad

2018-05-01

The aims of this study were to determine whether different student profiles would emerge in terms of high and low GPA performance in each year of dental school and to investigate the utility of preadmissions variables in predicting performance and performance stability throughout each year of dental school. Data from 11 graduating cohorts (2004-14) at the Schulich School of Medicine & Dentistry, University of Western Ontario, Canada, were collected and analyzed using bivariate correlations, latent profile analysis, and hierarchical generalized linear models (HGLMs). The data analyzed were for 616 students in total (332 males and 284 females). Four models were developed to predict adequate and poor performance throughout each of four dental school years. An additional model was developed to predict student performance stability across time. Two separate student profiles reflecting high and low GPA performance across each year of dental school were identified, and scores on cognitive preadmissions variables differentially predicted the probability of grouping into high and low performance profiles. Students with higher pre-dental GPAs and DAT chemistry were most likely to remain stable in a high-performance group across each year of dental school. Overall, the findings suggest that selection committees should consider pre-dental GPA and DAT chemistry scores as important tools for predicting dental school performance and stability across time. This research is important in determining how to better predict success and failure in various areas of preclinical dentistry courses and to provide low-performing students with adequate academic assistance.

Feature inference with uncertain categorization: Re-assessing Anderson's rational model.

PubMed

Konovalova, Elizaveta; Le Mens, Gaël

2017-09-18

A key function of categories is to help predictions about unobserved features of objects. At the same time, humans are often in situations where the categories of the objects they perceive are uncertain. In an influential paper, Anderson (Psychological Review, 98(3), 409-429, 1991) proposed a rational model for feature inferences with uncertain categorization. A crucial feature of this model is the conditional independence assumption-it assumes that the within category feature correlation is zero. In prior research, this model has been found to provide a poor fit to participants' inferences. This evidence is restricted to task environments inconsistent with the conditional independence assumption. Currently available evidence thus provides little information about how this model would fit participants' inferences in a setting with conditional independence. In four experiments based on a novel paradigm and one experiment based on an existing paradigm, we assess the performance of Anderson's model under conditional independence. We find that this model predicts participants' inferences better than competing models. One model assumes that inferences are based on just the most likely category. The second model is insensitive to categories but sensitive to overall feature correlation. The performance of Anderson's model is evidence that inferences were influenced not only by the more likely category but also by the other candidate category. Our findings suggest that a version of Anderson's model which relaxes the conditional independence assumption will likely perform well in environments characterized by within-category feature correlation.

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

Naulleau, Patrick; Mochi, Iacopo; Goldberg, Kenneth A.

Defect free masks remain one of the most significant challenges facing the commercialization of extreme ultraviolet (EUV) lithography. Progress on this front requires high-performance wavelength-specific metrology of EUV masks, including high-resolution and aerial-image microscopy performed near the 13.5 nm wavelength. Arguably the most cost-effective and rapid path to proliferating this capability is through the development of Fresnel zoneplate-based microscopes. Given the relative obscurity of such systems, however, modeling tools are not necessarily optimized to deal with them and their imaging properties are poorly understood. Here we present a modeling methodology to analyze zoneplate microscopes based on commercially available optical modelingmore » software and use the technique to investigate the imaging performance of an off-axis EUV microscope design. The modeling predicts that superior performance can be achieved by tilting the zoneplate, making it perpendicular to the chief ray at the center of the field, while designing the zoneplate to explicitly work in that tilted plane. Although the examples presented here are in the realm of EUV mask inspection, the methods described and analysis results are broadly applicable to zoneplate microscopes in general, including full-field soft-x-ray microscopes rou tinely used in the synchrotron community.« less

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

Naulleau, Patrick P.; Mochi, Iacopo; Goldberg, Kenneth A.

Defect free masks remain one of the most significant challenges facing the commercialization of extreme ultraviolet (EUV) lithography. Progress on this front requires high-performance wavelength-specific metrology of EUV masks, including high-resolution and aerial-image microscopy performed near the 13.5 nm wavelength. Arguably the most cost-effective and rapid path to proliferating this capability is through the development of Fresnel zoneplate-based microscopes. Given the relative obscurity of such systems, however, modeling tools are not necessarily optimized to deal with them and their imaging properties are poorly understood. Here we present a modeling methodology to analyze zoneplate microscopes based on commercially available optical modelingmore » software and use the technique to investigate the imaging performance of an off-axis EUV microscope design. The modeling predicts that superior performance can be achieved by tilting the zoneplate, making it perpendicular to the chief ray at the center of the field, while designing the zoneplate to explicitly work in that tilted plane. Although the examples presented here are in the realm of EUV mask inspection, the methods described and analysis results are broadly applicable to zoneplate microscopes in general, including full-field soft-x-ray microscopes routinely used in the synchrotron community.« less

Comparing colon cancer outcomes: The impact of low hospital case volume and case-mix adjustment.

PubMed

Fischer, C; Lingsma, H F; van Leersum, N; Tollenaar, R A E M; Wouters, M W; Steyerberg, E W

2015-08-01

When comparing performance across hospitals it is essential to consider the noise caused by low hospital case volume and to perform adequate case-mix adjustment. We aimed to quantify the role of noise and case-mix adjustment on standardized postoperative mortality and anastomotic leakage (AL) rates. We studied 13,120 patients who underwent colon cancer resection in 85 Dutch hospitals. We addressed differences between hospitals in postoperative mortality and AL, using fixed (ignoring noise) and random effects (incorporating noise) logistic regression models with general and additional, disease specific, case-mix adjustment. Adding disease specific variables improved the performance of the case-mix adjustment models for postoperative mortality (c-statistic increased from 0.77 to 0.81). The overall variation in standardized mortality ratios was similar, but some individual hospitals changed considerably. For the standardized AL rates the performance of the adjustment models was poor (c-statistic 0.59 and 0.60) and overall variation was small. Most of the observed variation between hospitals was actually noise. Noise had a larger effect on hospital performance than extended case-mix adjustment, although some individual hospital outcome rates were affected by more detailed case-mix adjustment. To compare outcomes between hospitals it is crucial to consider noise due to low hospital case volume with a random effects model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Stability and performance of notch filter control for unbalance response

NASA Technical Reports Server (NTRS)

Knospe, C. R.

1992-01-01

Many current applications of magnetic bearings for rotating machinery employ notch filters in the feedback control loop to reduce the synchronous forces transmitted through the bearings. The capabilities and limitations of notch filter control are investigated. First, a rigid rotor is examined with some classical root locus techniques. Notch filter control is shown to result in conditional stability whenever complete synchronous attenuation is required. Next, a nondimensional parametric symmetric flexible three mass rotor model is constructed. An examination of this model for several test cases illustrates the limited attenuation possible with notch filters at and near the system critical speeds when the bearing damping is low. The notch filter's alteration of the feedback loop is shown to cause stability problems which limits performance. Poor transient response may also result. A high speed compressor is then examined as a candidate for notch filter control. A collocated 22 mass station model with lead-lag control is used. The analysis confirms the reduction in stability robustness that can occur with notch filter control. It is concluded that other methods of synchronous vibration control yield greater performance without compromising stability.

Analysis of free modeling predictions by RBO aleph in CASP11.

PubMed

Mabrouk, Mahmoud; Werner, Tim; Schneider, Michael; Putz, Ines; Brock, Oliver

2016-09-01

The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue-residue contact prediction by EPC-map and contact-guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. Proteins 2016; 84(Suppl 1):87-104. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Estimating estuarine salt intrusion using an analytical and a full hydrodynamic simulation - a comparison for the Ma Estuary

NASA Astrophysics Data System (ADS)

Nguyen, Duc Anh; Cat Vu, Minh; Willems, Patrick; Monbaliu, Jaak

2017-04-01

Salt intrusion is the most acute problem for irrigation water quality in coastal regions during dry seasons. The use of numerical hydrodynamic models is widespread and has become the prevailing approach to simulate the salinity distribution in an estuary. Despite its power to estimate both spatial and temporal salinity variations along the estuary, this approach also has its drawbacks. The high computational cost and the need for detailed hydrological, bathymetric and tidal datasets, put some limits on the usability in particular case studies. In poor data environments, analytical salt intrusion models are more widely used as they require less data and have a further reduction of the computational effort. There are few studies however where a more comprehensive comparison is made between the performance of a numerical hydrodynamic and an analytical model. In this research the multi-channel Ma Estuary in Vietnam is considered as a case study. Both the analytical and the hydrodynamic simulation approaches have been applied and were found capable to mimic the longitudinal salt distribution along the estuary. The data to construct the MIKE11 model include observations provided by a network of fixed hydrological stations and the cross-section measurements along the estuary. The analytic model is developed in parallel but based on information obtained from the hydrological network only (typical for poor data environment). Note that the two convergence length parameters of this simplified model are usually extracted from topography data including cross-sectional area and width along the estuary. Furthermore, freshwater discharge data are needed but these are gauged further upstream outside of the tidal region and unable to reflect the individual flows entering the multi-channel estuary. In order to tackle the poor data environment limitations, a new approach was needed to calibrate the two estuary geometry parameters of the parsimonious salt intrusion model. Compared to the values based on a field survey for the estuary, the calibrated cross-sectional convergence length values are in very high agreement. By assuming a linear relation between inverses of the individual flows entering the estuary and inverses of the sum of flows gauged further upstream, the individual flows can be assessed. Evaluation on the modeling approaches at high water slack shows that the two modeling approaches have similar results. They explain salinity distribution along the Ma Estuary reasonably well with Nash-Sutcliffe efficiency values at gauging stations along the estuary of 0.50 or higher. These performances demonstrate the predictive power of the simplified salt intrusion model and of the proposed parameter/input estimation approach, even with the poorer data.

The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt.

PubMed

Viboud, Cécile; Sun, Kaiyuan; Gaffey, Robert; Ajelli, Marco; Fumanelli, Laura; Merler, Stefano; Zhang, Qian; Chowell, Gerardo; Simonsen, Lone; Vespignani, Alessandro

2018-03-01

Infectious disease forecasting is gaining traction in the public health community; however, limited systematic comparisons of model performance exist. Here we present the results of a synthetic forecasting challenge inspired by the West African Ebola crisis in 2014-2015 and involving 16 international academic teams and US government agencies, and compare the predictive performance of 8 independent modeling approaches. Challenge participants were invited to predict 140 epidemiological targets across 5 different time points of 4 synthetic Ebola outbreaks, each involving different levels of interventions and "fog of war" in outbreak data made available for predictions. Prediction targets included 1-4 week-ahead case incidences, outbreak size, peak timing, and several natural history parameters. With respect to weekly case incidence targets, ensemble predictions based on a Bayesian average of the 8 participating models outperformed any individual model and did substantially better than a null auto-regressive model. There was no relationship between model complexity and prediction accuracy; however, the top performing models for short-term weekly incidence were reactive models with few parameters, fitted to a short and recent part of the outbreak. Individual model outputs and ensemble predictions improved with data accuracy and availability; by the second time point, just before the peak of the epidemic, estimates of final size were within 20% of the target. The 4th challenge scenario - mirroring an uncontrolled Ebola outbreak with substantial data reporting noise - was poorly predicted by all modeling teams. Overall, this synthetic forecasting challenge provided a deep understanding of model performance under controlled data and epidemiological conditions. We recommend such "peace time" forecasting challenges as key elements to improve coordination and inspire collaboration between modeling groups ahead of the next pandemic threat, and to assess model forecasting accuracy for a variety of known and hypothetical pathogens. Published by Elsevier B.V.

Predicting coin flips: using resampling and hierarchical models to help untangle the NHL's shoot-out.

PubMed

Lopez, Michael J; Schuckers, Michael

2017-05-01

Roughly 14% of regular season National Hockey League games since the 2005-06 season have been decided by a shoot-out, and the resulting allocation of points has impacted play-off races each season. But despite interest from fans, players and league officials, there is little in the way of published research on team or individual shoot-out performance. This manuscript attempts to fill that void. We present both generalised linear mixed model and Bayesian hierarchical model frameworks to model shoot-out outcomes, with results suggesting that there are (i) small but statistically significant talent gaps between shooters, (ii) marginal differences in performance among netminders and (iii) few, if any, predictors of player success after accounting for individual talent. We also provide a resampling strategy to highlight a selection bias with respect to shooter assignment, in which coaches choose their most skilled offensive players early in shoot-out rounds and are less likely to select players with poor past performances. Finally, given that per-shot data for shoot-outs do not currently exist in a single location for public use, we provide both our data and source code for other researchers interested in studying shoot-out outcomes.

Development of a prediction tool for patients presenting with acute cough in primary care: a prognostic study spanning six European countries.

PubMed

Bruyndonckx, Robin; Hens, Niel; Verheij, Theo Jm; Aerts, Marc; Ieven, Margareta; Butler, Christopher C; Little, Paul; Goossens, Herman; Coenen, Samuel

2018-05-01

Accurate prediction of the course of an acute cough episode could curb antibiotic overprescribing, but is still a major challenge in primary care. The authors set out to develop a new prediction rule for poor outcome (re-consultation with new or worsened symptoms, or hospital admission) in adults presenting to primary care with acute cough. Data were collected from 2604 adults presenting to primary care with acute cough or symptoms suggestive of lower respiratory tract infection (LRTI) within the Genomics to combat Resistance against Antibiotics in Community-acquired LRTI in Europe (GRACE; www.grace-lrti.org) Network of Excellence. Important signs and symptoms for the new prediction rule were found by combining random forest and logistic regression modelling. Performance to predict poor outcome in acute cough patients was compared with that of existing prediction rules, using the models' area under the receiver operator characteristic curve (AUC), and any improvement obtained by including additional test results (C-reactive protein [CRP], blood urea nitrogen [BUN], chest radiography, or aetiology) was evaluated using the same methodology. The new prediction rule, included the baseline Risk of poor outcome, Interference with daily activities, number of years stopped Smoking (> or <45 years), severity of Sputum, presence of Crackles, and diastolic blood pressure (> or <85 mmHg) (RISSC85). Though performance of RISSC85 was moderate (sensitivity 62%, specificity 59%, positive predictive value 27%, negative predictive value 86%, AUC 0.63, 95% confidence interval [CI] = 0.61 to 0.67), it outperformed all existing prediction rules used today (highest AUC 0.53, 95% CI = 0.51 to 0.56), and could not be significantly improved by including additional test results (highest AUC 0.64, 95% CI = 0.62 to 0.68). The new prediction rule outperforms all existing alternatives in predicting poor outcome in adult patients presenting to primary care with acute cough and could not be improved by including additional test results. © British Journal of General Practice 2018.

Daylighting performance and thermal implications of skylights vs. south-facing roof monitors

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

Rosenbaum, M.; Coldham, B.

1997-12-31

This paper reports the results of a comparison of skylights vs. south-facing roof monitors for daylighting the north wall zone of a 10,000 ft{sup 2} office building near Manchester, NH. A physical model was constructed and tested. Simultaneously, the building`s annual thermal performance was modeled with Energy-10 hourly simulation software, and its peak heating and cooling load performance was modeled with the Carrier Corp. Hourly Analysis Program (HAP). Apertures were built into the roof of the model, and several skylight and south-facing roof monitor configurations were tested in both clear and overcast conditions. A design goal was to have themore » building be daylit on overcast as well as clear days. This goal was based more on enhancement of the working environment than it was on electrical energy savings. Monitors with overhangs performed poorly in the overcast conditions--it was determined that 2.4 times as much monitor aperture was needed to yield equivalent light levels in overcast conditions. The thermal models showed that the annual heating and cooling energy cost for the building was the same for either strategy, but that peak cooling loads and peak heating loads were lower with the skylit version. The authors concluded that skylights were preferred over monitors in this application, due to similar annual energy costs, lower peak loads, and lower construction cost.« less

Evaluation of undergraduate geologists' problem solving and cognition during field exams using a mixed methods approach

NASA Astrophysics Data System (ADS)

Balliet, Russell N.

Understanding how geologists conduct fieldwork through analysis of problem solving has significant potential impact on field instruction methods. Recent progress has been made in this area but the problem solving behaviors displayed by geologists during fieldwork and the associated underlying cognition remains poorly understood. We present research showing how geology students initiate and develop geologic models as part of the problem solving process. We qualitatively analyzed field notes and interview data from 36 undergraduate geoscientists engaged in field exams while enrolled in a six-week advanced field camp. Eight cognitive frameworks grouped in two broad categories emerged from the data that show how students develop geologic models. Students employ both single and multiple model approaches with varying degrees of success and frequency. The success of any given approach is dependent on the level of students' geologic situational awareness. The development of multiple geologic models leads to a higher rate of success in general, because of the inherent flexibility to accommodate newly collected data. Instructors should continue to teach a multiple model approach until students have the proper geologic skills to ensure a high level of situational awareness and exhibit expert characteristics in the field. In addition, we collected GPS navigation data from students during these field exams in order to understand the relationship between navigation, cognition, and performance. From the analysis of this data we found that over half of all stops are 1-4 minutes long, while very few of students' stops are longer than 9 minutes as the frequency of stops decreases as the duration increases. Regardless of performance or framework, there is an increase in shorter stops and decrease in longer stops from exam one to three, indicating that students changed the way they investigated as the field course progressed. Temporal signatures categorized by performance only show slight differences, but do indicate that there is an increase in very short and longer stops with declining performance. In contrast, higher performance is linked to an increase in short and medium length stops, suggesting that stops 4-14 minutes long are a "sweet spot" for investigation. We speculate that a high percentage of very short stops involve basic field tasks such as locating or data collection and that the decreasing frequency of long stops indicates that there is a relationship between the length of the stop and the complexity of the activities performed during that stop. Students increased experience leads to more efficient stops as they become more competent with field tasks and more versed in the regional geology. The GPS data we collected from these students while they took these notes allowing us to connect the duration of a stop to the types of notes produced during that stop. Note taking species occurred in various frequencies with the most common type being those that focused on lithologic, or lithologic & structural data collection. Stops that produced geologic models, specifically structural models, were much less frequent. The more frequent data collection stops are very short in length (typically 1-4 minutes), while the more complex stops tend to be longer in duration as the note taking gets more complex. Poor performing students had a high proportion of stops where they only collect lithologic data or stops where they don't generate any hypotheses. In contrast, successful students have more structural data and hypothesis generation in their notes. From this analysis we conclude that too much effort spent on stops with only basic data collection leaves less time for the cognitive effort required for model development, eventually leading to poor exam performance. Specifically, a higher frequency of lithologic data stops and lack of structural data leads to the development of incomplete geologic models or lack of comprehensive models altogether. Field instructors often educate their students on good note taking practices and critique the content of their students' field notebooks, and these findings can inform the content of that critique. Students' utilize many different problem solving approaches in the field, but we suggest that instructors continue to advocate a multiple model approach until students are capable of using a single model approach. In this approach students should decrease the number of geologic models they are using as the day progresses to avoid overwhelming themselves with data and hypothesis. Furthermore, field instructors need to work with students on developing their geologic investigation skills further and improving their efficiency. Specifically students need to collect a higher proportion of structural data and develop complete geologic models earlier in the day. (Abstract shortened by UMI.)

Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population.

PubMed

Wei, Fu; Nie, Guanghui; Zhou, Bo; Wang, Liang; Ma, Yifei; Peng, Suwan; Ou, Songfeng; Qin, Jian; Zhang, Li'e; Li, Shu; Zou, Ruosi; Zeng, Xiaoyun; Zhang, Zhiyong; Zou, Yunfeng

2017-08-01

Poor sleep quality is an important symptom of many medical or psychiatric disorders. However, the impact of cooking oil fumes (COFs) on sleep quality has not been studied. This population-based cross-sectional study was conducted to examine the association between COFs of Chinese household cooking and sleep quality. Individual sleep quality assessment was completed in 2197 participants with an average age of 37.52 years, through Pittsburgh Sleep Quality Index (PSQI). Information about their cooking practice were also collected by self-reported questionnaire. As an internal biomarker of COFs, urinary 1-hydroxypyrene (1-HOP) (n = 562) was further measured using high-performance liquid chromatography. Binary logistic regression models were performed to evaluate the association between exposure to COFs and individual sleep quality. We found that, subjective poor kitchen ventilation, preheating oil to smoking, and cooking for over 30 minutes were positively associated with overall poor sleep quality (global PSQI score >5) [odds ratio (OR) = 1.75, 95% confidence interval (CI) = 1.43-2.16; 1.25, (1.03-1.52); 1.42, (1.15-1.76), respectively]. After adjusting for potential confounders, subjective poor kitchen ventilation still tend to increase the risk of long sleep latency, sleep disturbances, and daytime dysfunction [OR = 1.37, 95% CI = 1.09-1.73; 1.91, (1.39-2.61); 1.54, (1.23-1.93), respectively]. Similar results were observed in participants who preheated oil to smoking [OR = 1.36, 95% CI = 1.08-1.72; 1.55, (1.14-2.14); 1.25, (1.02-1.55), respectively] and cooked for over 30 minutes [OR = 1.34, 95% CI = 1.05-1.72; 1.46, (1.03-2.06); 1.36, (1.08-1.72), respectively]. Furthermore, high urinary 1-HOP level was also positively associated with overall poor sleep quality (OR = 2.30, 95% CI = 1.31-4.05). The results indicated that exposure to COFs from Chinese household cooking may be a risk factor for poor sleep quality among middle-aged Chinese population. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reducing failures of working memory with performance feedback.

PubMed

Adam, Kirsten C S; Vogel, Edward K

2016-10-01

Fluctuations in attentional control can lead to failures of working memory (WM), in which the subject is no better than chance at reporting items from a recent display. In three experiments, we used a whole-report measure of visual WM to examine the impact of feedback on the rate of failures. In each experiment, subjects remembered an array of colored items across a blank delay, and then reported the identity of items using a whole-report procedure. In Experiment 1, we gave subjects simple feedback about the number of items they correctly identified at the end of each trial. In Experiment 2, we gave subjects additional information about the cumulative number of items correctly identified within each block. Finally, in Experiment 3, we gave subjects weighted feedback in which poor trials resulted in lost points and consistent successful performance received "streak" points. Surprisingly, simple feedback (Exp. 1) was ineffective at improving average performance or decreasing the rate of poor-performance trials. Simple cumulative feedback (Exp. 2) modestly decreased poor-performance trials (by 7 %). Weighted feedback produced the greatest benefits, decreasing the frequency of poor-performance trials by 28 % relative to baseline performance. This set of results demonstrates the usefulness of whole-report WM measures for investigating the effects of feedback on WM performance. Further, we showed that only a feedback structure that specifically discouraged lapses using negative feedback led to large reductions in WM failures.

Video gamers of League of Legends: The role of passion in abusive use and in performance.

PubMed

Bertran, Enric; Chamarro, Andrés

2016-03-02

There is growing concern about the addictive potential of Massively Multiplayer Online Role Playing Games (MMORPG). The Multiplayer Online Battle Arena (MOBA) is a new genre, poorly studied but very popular, in which performance holds priority over immersion. The aim of the current study was to explore the influence of passion both on abuse and performance, using the dualistic model of passion. A total of 369 participants completed an online questionnaire that included problematic use and the Passion Scale. From players' nicknames, performance statistics were obtained. The results show that harmonious passion is a protector from negative consequences. On the other hand, obsessive passion predicts negative consequences and use of videogames for evasion. Obsessive passion also predicts better performance. These results suggest that distinguishing the two kinds of passion is important because they influence vulnerability to developing maladaptive behaviors and also players' performance.

On-road driving impairments and associated cognitive deficits after stroke.

PubMed

Devos, Hannes; Tant, Mark; Akinwuntan, Abiodun E

2014-01-01

Little is known about the critical on-road driving skills that get affected after a stroke. The purpose of this study was to investigate the key on-road driving impairments and their associated cognitive deficits after a stroke. A second aim was to investigate if lateralization of stroke impacts results of the cognitive and on-road driving tests. In this cross-sectional study, 99 participants with a first-ever stroke who were actively driving prior to stroke underwent a cognitive battery and a standardized road test that evaluated 13 specific on-road driving skills. These on-road driving skills were mapped onto an existing, theoretical framework that categorized the on-road items into hierarchic clusters of operational, tactical, visuo-integrative, and mixed driving skills. The total score on the road test and the on-road decision, made by a certified fitness-to-drive expert, decided the main outcome. The critical on-road driving skills predicting the on-road decision were identified using logistic regression analysis. Linear regression analysis was employed to determine the cognitive impairments leading to poor total on-road scores. Analyses were repeated for right- and left-sided strokes. In all, 37 persons scored poorly on the road test. These participants performed worse in all hierarchic clusters of on-road driving. Performances on the operational cluster and the visuo-integrative cluster best predicted on-road decisions (R(2) = 0.60). 'Lane changing' and 'understanding, insight, and quality of traffic participation' were the critical skill deficits leading to poor performance on the road test (R(2) = 0.65). Divided attention was the main determinant of on-road scores in the total group (R(2) = 0.06). Participants with right-sided stroke performed worse on visual field, visual neglect, visual scanning, visuo-constructive skills, and divided attention compared with those with left-sided stroke. Divided attention was the main determinant of total on-road scores in the right-sided stroke group (R(2) = 0.10). A combination of visual scanning, speed of processing, and executive dysfunction yielded the best model to predict on-road scores in left-sided strokes (R(2) = 0.46). Poor performance in the road test after stroke is determined by critical operational and visuo-integrative driving impairments. Specific and different driving evaluation and training programs are needed for right- and left-sided strokes. © 2014 S. Karger AG, Basel.

77 FR 9876 - Proposed Modification of VOR Federal Airways V-10, V-12, and V-508 in the Vicinity of Olathe, KS

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-21

... (OJC) VOR/DME navigation aid located on the Johnson County Executive Airport, Olathe, KS, due to poor performance of the navigation aid. The OJC VOR/DME performs poorly due to suburban encroachment into the...

12 CFR 367.6 - Causes for exclusion.

Code of Federal Regulations, 2010 CFR

2010-01-01

... default; or (2) The termination of such contract(s) for poor performance; or (3) A violation of the terms of a contract that would have resulted in a default or termination of the contract for poor... lack of integrity, or conspiracy to do the same; (l) The contractor's performance under previous...

Leadership Development: A Lever for System-Wide Educational Change

ERIC Educational Resources Information Center

Naicker, Suraiya R.; Mestry, Raj

2016-01-01

The continuous poor performance of South Africa's learners is detrimental to its developing economy. The need for education change prompted two universities to initiate a system-wide change strategy in a poorly performing school district. The leverage for change was leadership development, involving school principals and district officials. The…

Principals' Perceptions of Barriers to Dismissal of Poor-Performing Teachers

ERIC Educational Resources Information Center

Dandoy, Jason R.

2012-01-01

The purpose of this study is to determine which factors influence items that school principals consider "barriers" to dismissal of "incompetent" or "poor performing" teachers. This study determines if specific characteristics of schools, principals, or a combination of the two can predict the specific barriers cited…

Poorly Performing Physicians: Does the Script Concordance Test Detect Bad Clinical Reasoning?

ERIC Educational Resources Information Center

Goulet, Francois; Jacques, Andre; Gagnon, Robert; Charlin, Bernard; Shabah, Abdo

2010-01-01

Introduction: Evaluation of poorly performing physicians is a worldwide concern for licensing bodies. The College des Medecins du Quebec currently assesses the clinical competence of physicians previously identified with potential clinical competence difficulties through a day-long procedure called the Structured Oral Interview (SOI). Two peer…

Principals' Informal Methods for Appraising Poor-Performing Teachers

ERIC Educational Resources Information Center

Yariv, Eliezer

2009-01-01

Teacher appraisal is never an easy task, especially of teachers experiencing difficulties and failures. Nevertheless it is a requirement for good management, in our schools no less than our corporations. Forty elementary school principals in Israel described the informal methods they use to appraise teachers who are performing poorly. Most…

Data Visualization Saliency Model: A Tool for Evaluating Abstract Data Visualizations

DOE PAGES

Matzen, Laura E.; Haass, Michael J.; Divis, Kristin M.; ...

2017-08-29

Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. One possibility for such a tool is a model of visual saliency for data visualizations. Visual saliency models are typically based on the properties of the human visual cortex and predict which areas of a scene havemore » visual features (e.g. color, luminance, edges) that are likely to draw a viewer's attention. While these models can accurately predict where viewers will look in a natural scene, they typically do not perform well for abstract data visualizations. In this paper, we discuss the reasons for the poor performance of existing saliency models when applied to data visualizations. We introduce the Data Visualization Saliency (DVS) model, a saliency model tailored to address some of these weaknesses, and we test the performance of the DVS model and existing saliency models by comparing the saliency maps produced by the models to eye tracking data obtained from human viewers. In conclusion, we describe how modified saliency models could be used as general tools for assessing the effectiveness of visualizations, including the strengths and weaknesses of this approach.« less

Data Visualization Saliency Model: A Tool for Evaluating Abstract Data Visualizations

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

Matzen, Laura E.; Haass, Michael J.; Divis, Kristin M.

Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. One possibility for such a tool is a model of visual saliency for data visualizations. Visual saliency models are typically based on the properties of the human visual cortex and predict which areas of a scene havemore » visual features (e.g. color, luminance, edges) that are likely to draw a viewer's attention. While these models can accurately predict where viewers will look in a natural scene, they typically do not perform well for abstract data visualizations. In this paper, we discuss the reasons for the poor performance of existing saliency models when applied to data visualizations. We introduce the Data Visualization Saliency (DVS) model, a saliency model tailored to address some of these weaknesses, and we test the performance of the DVS model and existing saliency models by comparing the saliency maps produced by the models to eye tracking data obtained from human viewers. In conclusion, we describe how modified saliency models could be used as general tools for assessing the effectiveness of visualizations, including the strengths and weaknesses of this approach.« less

Active Subspaces for Wind Plant Surrogate Modeling

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

King, Ryan N; Quick, Julian; Dykes, Katherine L

Understanding the uncertainty in wind plant performance is crucial to their cost-effective design and operation. However, conventional approaches to uncertainty quantification (UQ), such as Monte Carlo techniques or surrogate modeling, are often computationally intractable for utility-scale wind plants because of poor congergence rates or the curse of dimensionality. In this paper we demonstrate that wind plant power uncertainty can be well represented with a low-dimensional active subspace, thereby achieving a significant reduction in the dimension of the surrogate modeling problem. We apply the active sub-spaces technique to UQ of plant power output with respect to uncertainty in turbine axial inductionmore » factors, and find a single active subspace direction dominates the sensitivity in power output. When this single active subspace direction is used to construct a quadratic surrogate model, the number of model unknowns can be reduced by up to 3 orders of magnitude without compromising performance on unseen test data. We conclude that the dimension reduction achieved with active subspaces makes surrogate-based UQ approaches tractable for utility-scale wind plants.« less

A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

NASA Astrophysics Data System (ADS)

Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

2018-01-01

Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.

Testing the multidimensionality of the inventory of school motivation in a Dutch student sample.

PubMed

Korpershoek, Hanke; Xu, Kun; Mok, Magdalena Mo Ching; McInerney, Dennis M; van der Werf, Greetje

2015-01-01

A factor analytic and a Rasch measurement approach were applied to evaluate the multidimensional nature of the school motivation construct among more than 7,000 Dutch secondary school students. The Inventory of School Motivation (McInerney and Ali, 2006) was used, which intends to measure four motivation dimensions (mastery, performance, social, and extrinsic motivation), each comprising of two first-order factors. One unidimensional model and three multidimensional models (4-factor, 8-factor, higher order) were fit to the data. Results of both approaches showed that the multidimensional models validly represented the school motivation among Dutch secondary school pupils, whereas model fit of the unidimensional model was poor. The differences in model fit between the three multidimensional models were small, although a different model was favoured by the two approaches. The need for improvement of some of the items and the need to increase measurement precision of several first-order factors are discussed.

Study of G-S/D underlap for enhanced analog performance and RF/circuit analysis of UTB InAs-OI-Si MOSFET using NQS small signal model

NASA Astrophysics Data System (ADS)

Maity, Subir Kumar; Pandit, Soumya

2017-01-01

InGaAs (and its variant) appears to be a promising channel material for high-performance, low-power scaled CMOS applications due to its excellent carrier transport properties. However, MOS transistors made of this suffer from poor electrostatic integrity. In this work, we consider an underlap ultra thin body (UTB) InAs-on-Insulator n-channel MOS transistor, and study the effect of varying the gate-source/drain (G-S/D) underlap length on the analog performance of the device with the help of technology computer-aided design (TCAD) simulation, calibrated with Schrodinger-Poisson solver and experimental results. The underlap technique improves the gate electrostatic integrity which in turn improves the analog performance. We develop a non-quasi-static (NQS) small signal equivalent circuit model of the device which is used for study of the RF performance. With increase of the underlap length, the unity gain cut-off frequency degrades and the maximum oscillation frequency improves beyond a certain value of the underlap length. We further study the gain-frequency response of a common source amplifier using the NQS model, through SPICE simulation and observe that the voltage gain and the gain bandwidth improves.

Poland.

PubMed

1987-09-01

In 1986, Poland's population was 37.5 million and the annual population growth rate was 0.8%. The infant mortality rate was 19.3/1000 and life expectancy stood at 71.6 years. Of the labor force of 17.5 million, 30% were engaged in agriculture, 44% were in industry and commerce, 8% were government employees, and 11% were employed in services. Poland is a communist state. The economy is based on the Soviet model of state ownership of most of the country's productive assets, although the private sector predominates in agriculture. The rights of private farmers are now protected through a 1983 amendment to the constitution. Poland's economy has performed poorly in comparison with other Eastern European economies. The economic growth rate is 5% and inflation averages 20%. Per capita income is US$2000. Industries were centralized following World War II, and this systemic rigidity is considered to have contributed to the economy's poor performance. Another important factor has been low reliance of foreign trade, meaning that Poland's industries have failed to develop competitiveness. The government has committed itself to a so-called second-stage of economic reform, but to date there have been few concrete accomplishments.

Testing the Trower and Chadwick model of paranoia: Is 'poor-me' and 'bad-me' paranoia acting as a defence?

PubMed

Marley, Charles; Jones, Jason; Jones, Christopher A

2017-12-01

The study tested the predicted differences in phenomenology (self-esteem and depression) and insecurity of the subgroups of paranoia proposed by the Trower and Chadwick (1995) model of paranoia. Thirty-two inpatients experiencing persecutory delusions were assigned to either the poor me or bad me paranoid group. Questionnaire assessment of depression and self-esteem were conducted. A Dot Probe task measured detection latency (reaction time) to poor me words, bad me words and neutral words. The poor me and bad me groups displayed the predicted phenomenological differences. The dot probe task did not support the predicted insecurities of the Trower and Chadwick model, but unexpected significant results for the poor me subgroup may offer support for an alternative explanation of paranoia as an unstable phenomenon. Copyright © 2017 Elsevier B.V. All rights reserved.

How do dispersal costs and habitat selection influence realized population connectivity?

PubMed

Burgess, Scott C; Treml, Eric A; Marshall, Dustin J

2012-06-01

Despite the importance of dispersal for population connectivity, dispersal is often costly to the individual. A major impediment to understanding connectivity has been a lack of data combining the movement of individuals and their survival to reproduction in the new habitat (realized connectivity). Although mortality often occurs during dispersal (an immediate cost), in many organisms costs are paid after dispersal (deferred costs). It is unclear how such deferred costs influence the mismatch between dispersal and realized connectivity. Through a series of experiments in the field and laboratory, we estimated both direct and indirect deferred costs in a marine bryozoan (Bugula neritina). We then used the empirical data to parameterize a theoretical model in order to formalize predictions about how dispersal costs influence realized connectivity. Individuals were more likely to colonize poor-quality habitat after prolonged dispersal durations. Individuals that colonized poor-quality habitat performed poorly after colonization because of some property of the habitat (an indirect deferred cost) rather than from prolonged dispersal per se (a direct deferred cost). Our theoretical model predicted that indirect deferred costs could result in nonlinear mismatches between spatial patterns of potential and realized connectivity. The deferred costs of dispersal are likely to be crucial for determining how well patterns of dispersal reflect realized connectivity. Ignoring these deferred costs could lead to inaccurate predictions of spatial population dynamics.

Thermodynamics of Highly Supersaturated Aqueous Solutions of Poorly Water-Soluble Drugs-Impact of a Second Drug on the Solution Phase Behavior and Implications for Combination Products.

PubMed

Trasi, Niraj S; Taylor, Lynne S

2015-08-01

There is increasing interest in formulating combination products that contain two or more drugs. Furthermore, it is also common for different drug products to be taken simultaneously. This raises the possibility of interactions between different drugs that may impact formulation performance. For poorly water-soluble compounds, the supersaturation behavior may be a critical factor in determining the extent of oral absorption. The goal of the current study was to evaluate the maximum achievable supersaturation for several poorly water-soluble compounds alone, and in combination. Model compounds included ritonavir, lopinavir, paclitaxel, felodipine, and diclofenac. The "amorphous solubility" for the pure drugs was determined using different techniques and the change in this solubility was then measured in the presence of differing amounts of a second drug. The results showed that "amorphous solubility" of each component in aqueous solution is substantially decreased by the second component, as long as the two drugs are miscible in the amorphous state. A simple thermodynamic model could be used to predict the changes in solubility as a function of composition. This information is of great value when developing co-amorphous or other supersaturating formulations and should contribute to a broader understanding of drug-drug physicochemical interactions in in vitro assays as well as in the gastrointestinal tract. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Bio-psychosocial factors are associated with pain intensity, physical functioning, and ability to work in female healthcare personnel with recurrent low back pain.

PubMed

Taulaniemi, Annika; Kuusinen, Lotta; Tokola, Kari; Kankaanpää, Markku; Suni, Jaana H

2017-08-31

To investigate associations of various bio-psychosocial factors with bodily pain, physical func-tioning, and ability to work in low back pain. Cross-sectional study. A total of 219 female healthcare workers with recurrent non-specific low back pain. Associations between several physical and psychosocial factors and: (i) bodily pain, (ii) physical functioning and (iii) ability to work were studied. Variables with statistically significant associations (p < 0.05) in bivariate analysis were set within a generalized linear model to analyse their relationship with each dependent variable. In generalized linear model analysis, perceived work-induced lumbar exertion (p < 0.001), multi-site pain (p <0.001) and work-related fear-avoidance beliefs (FAB-W) (p = 0.02) best explained bodily pain. Multi-site pain (p < 0.001), lumbar exertion (p = 0.005), FAB-W (p = 0.01) and physical performance in figure-of-eight running (p = 0.01) and modified push-ups (p = 0.05) best explained physical functioning; FAB-W (p <0.001), lumbar exertion (p = 0.003), depression (p = 0.01) and recovery after work (p = 0.03) best explained work ability. In bivariate analysis lumbar exertion was associated with poor physical performance. FAB-W and work-induced lumbar exertion were associated with levels of pain, physical functioning and ability to work. Poor physical performance capacity was associated with work-induced lumbar exertion. Interventions that aim to reduce fear-avoidance and increase fitness capacity might be beneficial.

Strategic and non-strategic problem gamblers differ on decision-making under risk and ambiguity.

PubMed

Lorains, Felicity K; Dowling, Nicki A; Enticott, Peter G; Bradshaw, John L; Trueblood, Jennifer S; Stout, Julie C

2014-07-01

To analyse problem gamblers' decision-making under conditions of risk and ambiguity, investigate underlying psychological factors associated with their choice behaviour and examine whether decision-making differed in strategic (e.g., sports betting) and non-strategic (e.g., electronic gaming machine) problem gamblers. Cross-sectional study. Out-patient treatment centres and university testing facilities in Victoria, Australia. Thirty-nine problem gamblers and 41 age, gender and estimated IQ-matched controls. Decision-making tasks included the Iowa Gambling Task (IGT) and a loss aversion task. The Prospect Valence Learning (PVL) model was used to provide an explanation of cognitive, motivational and response style factors involved in IGT performance. Overall, problem gamblers performed more poorly than controls on both the IGT (P = 0.04) and the loss aversion task (P = 0.01), and their IGT decisions were associated with heightened attention to gains (P = 0.003) and less consistency (P = 0.002). Strategic problem gamblers did not differ from matched controls on either decision-making task, but non-strategic problem gamblers performed worse on both the IGT (P = 0.006) and the loss aversion task (P = 0.02). Furthermore, we found differences in the PVL model parameters underlying strategic and non-strategic problem gamblers' choices on the IGT. Problem gamblers demonstrated poor decision-making under conditions of risk and ambiguity. Strategic (e.g. sports betting, poker) and non-strategic (e.g. electronic gaming machines) problem gamblers differed in decision-making and the underlying psychological processes associated with their decisions. © 2014 Society for the Study of Addiction.

Lexical and semantic processing in the absence of word reading: evidence from neglect dyslexia.

PubMed

Làdavas, E; Umiltà, C; Mapelli, D

1997-08-01

Nine patients with left-sided neglect and nine matched control patients performed three tasks on horizontal (either normal or mirror-reversed) letter strings. The tasks were: reading aloud, making a lexical decision (word vs non-word), and making a semantic decision (living vs non-living item). Relative to controls, neglect patients performed very poorly in the reading task, whereas they performed nearly normally in the lexical and semantic tasks. This was considered to be a dissociation between direct tasks, rather than a dissociation between explicit and implicit knowledge. The explanation offered for the dissociation is in terms of both a dual-route model for reading aloud and a degraded representation of the letter string.

Lyophilized silica lipid hybrid (SLH) carriers for poorly water-soluble drugs: physicochemical and in vitro pharmaceutical investigations.

PubMed

Yasmin, Rokhsana; Tan, Angel; Bremmell, Kristen E; Prestidge, Clive A

2014-09-01

Lyophilization was investigated to produce a powdery silica-lipid hybrid (SLH) carrier for oral delivery of poorly water-soluble drugs. The silica to lipid ratio, incorporation of cryoprotectant, and lipid loading level were investigated as performance indicators for lyophilized SLH carriers. Celecoxib, a nonsteroidal anti-inflammatory drug, was used as the model poorly soluble moiety to attain desirable physicochemical and in vitro drug solubilization properties. Scanning electron microscopy and confocal fluorescence imaging verified a nanoporous, homogenous internal matrix structures of the lyophilized SLH particles, prepared from submicron triglyceride emulsions and stabilized by porous silica nanoparticles (Aerosil 380), similar to spray-dried SLH. 20-50 wt % of silica in the formulation have shown to produce nonoily SLH agglomerates with complete lipid encapsulation. The incorporation of a cryoprotectant prevented irreversible aggregation of the silica-stabilized droplets during lyophilization, thereby readily redispersing in water to form micrometre-sized particles (<5 μm). The lyophilized SLH produced approximately 1.5-fold and fivefold increased drug solubilization than the pure drug under nondigesting and digesting conditions, respectively. The feasibility of lyophilization for producing nanostructured SLH formulations with desirable lipid loading and drug solubilization properties for enhanced oral delivery of poorly water-soluble therapeutics is confirmed. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Targeted interventions of ultra-poor women in rural Rangpur, Bangladesh: do they make a difference to appropriate cooking practices, food habits and sanitation?

PubMed

Yeasmin, Lubna; Akter, Shamima; Shahidul Islam, A M; Mizanur Rahman, Md; Akashi, Hidechika; Jesmin, Subrina

2014-07-01

This study aimed to assess whether teaching good cooking practices, food habits and sanitation to ultra-poor rural women in four rural communities of Rangpur district, Bangladesh, with a high density of extremely poor households, would improve the overall health of the community. The sample size was 200 respondents combined from the target and control areas. In the target area, twelve in-depth interviews and four focus group discussions were undertaken for knowledge dissemination. Descriptive and mixed-model analyses were performed. The results show that washing hands with soap was 1.35 times more likely in the target than the control group (p<0.01). Further, after intervention, there was a significant improvement in hand-washing behaviour: before cutting vegetables, preparing food, feeding a child and eating, and after defecating and cleaning a baby (p<0.05). Also, the target group was more likely to moderately and briefly boil their vegetables and were 19% less likely to use maximum heat when cooking vegetables than the control group (p<0.01). Improved knowledge and skills training of ultra-poor women reduces the loss of nutrients during food preparation and increases their hygiene through hand-washing in every-day life.

A Prognostic Modeling Approach for Predicting Recurring Maintenance for Shipboard Propulsion Systems

DTIC Science & Technology

2001-06-01

CIT CDT 1 CIP CDP η γ 1γ T T adb (1) Compressor fouling has also been shown to increase vibration , (Ozgur et al (2000) and Tsalavoutas et al) but... vibration increases and secondly is the poor reliability with which performance degradation severity may be assessed. In lieu of these practical...Industrial Gas Turbines” International Gas Turbine and Aeroengine Congress and Exposition, Belgium, June 1990 4. Kurtz, Rainer, Brun, Klaus, and

Bioeffects on an In Vitro Model by Small-Scale Explosives and Shock Wave Overpressure Impacts

DTIC Science & Technology

2017-11-01

still poorly understood, and proper diagnosis and treatment.17 Many TBIs—in particular, mild TBIs (mTBI)—seldom have neuroanatomical abnormalities ...performed for 24 h using 16 processors for time integrated out to 2 ms with 2.8 × 105 cell calculation. All blast simulations were conducted on the US...1. Williamson V, Mulhall E. Invisible wounds: psychological and neurological injuries confront a new generation of veterans. Iraq and Afghanistan

Radiotracer Technology in Mixing Processes for Industrial Applications

PubMed Central

Othman, N.; Kamarudin, S. K.

2014-01-01

Many problems associated with the mixing process remain unsolved and result in poor mixing performance. The residence time distribution (RTD) and the mixing time are the most important parameters that determine the homogenisation that is achieved in the mixing vessel and are discussed in detail in this paper. In addition, this paper reviews the current problems associated with conventional tracers, mathematical models, and computational fluid dynamics simulations involved in radiotracer experiments and hybrid of radiotracer. PMID:24616642

Particular bi-fuel application of spark ignition engines

NASA Astrophysics Data System (ADS)

Raţiu, S.; Alexa, V.; Kiss, I.

2016-02-01

This paper presents a comparative test concerning the operation of a spark-ignition engine, make: Dacia 1300, model: 810.99, fuelled alternatively with gasoline and LPG (Liquefied Petroleum Gas). The tests carried out show, on the one hand, the maintenance of power and torque performances in both engine fuelling cases, for all the engine operation regimes, and, on the other hand, a considerable decrease in CO and HC emissions when using poor mixtures related to LPG fuelling.

Traveling wave electroosmosis: the influence of electrode array geometry.

PubMed

Hrdlička, Jiří; Patel, Niketan S; Snita, Dalimil

2014-07-01

We used a mathematical model describing traveling-wave electroosmotic micropumps to explain their rather poor ability to work against pressure loads. The mathematical model is based upon the Poisson-Nernst-Planck-Navier-Stokes approach, that is, a direct numerical simulation, which allows a detail study of the energy transformations and the charging dynamics of the electric double layers. Using Matlab and COMSOL Multiphysics, we performed a set of extensive parametric studies to determine the dependence of generated electroosmotic flow on the geometric arrangement of the pump. The results suggest that the performance of AC electroosmotic pumps should improve with miniaturization. The AC electroosmosis is likely to be suitable only at submicrometer scale, as the pump's ability to work against pressure load diminishes rapidly when increasing the channel diameter. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Divergence Median-based Geometric Detector with A Weighted Averaging Filter

NASA Astrophysics Data System (ADS)

Hua, Xiaoqiang; Cheng, Yongqiang; Li, Yubo; Wang, Hongqiang; Qin, Yuliang

2018-01-01

To overcome the performance degradation of the classical fast Fourier transform (FFT)-based constant false alarm rate detector with the limited sample data, a divergence median-based geometric detector on the Riemannian manifold of Heimitian positive definite matrices is proposed in this paper. In particular, an autocorrelation matrix is used to model the correlation of sample data. This method of the modeling can avoid the poor Doppler resolution as well as the energy spread of the Doppler filter banks result from the FFT. Moreover, a weighted averaging filter, conceived from the philosophy of the bilateral filtering in image denoising, is proposed and combined within the geometric detection framework. As the weighted averaging filter acts as the clutter suppression, the performance of the geometric detector is improved. Numerical experiments are given to validate the effectiveness of our proposed method.

Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

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

Folkvord, Sigurd; Flatmark, Kjersti; Department of Cancer and Surgery, Norwegian Radium Hospital, Oslo University Hospital

2010-10-01

Purpose: Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials: Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatmentmore » as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results: In the patient population, 73% and 15% were scored as good responders (TRG 1-2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4-5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions: Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.« less

Single-locus species delimitation: a test of the mixed Yule-coalescent model, with an empirical application to Philippine round-leaf bats.

PubMed

Esselstyn, Jacob A; Evans, Ben J; Sedlock, Jodi L; Anwarali Khan, Faisal Ali; Heaney, Lawrence R

2012-09-22

Prospects for a comprehensive inventory of global biodiversity would be greatly improved by automating methods of species delimitation. The general mixed Yule-coalescent (GMYC) was recently proposed as a potential means of increasing the rate of biodiversity exploration. We tested this method with simulated data and applied it to a group of poorly known bats (Hipposideros) from the Philippines. We then used echolocation call characteristics to evaluate the plausibility of species boundaries suggested by GMYC. In our simulations, GMYC performed relatively well (errors in estimated species diversity less than 25%) when the product of the haploid effective population size (N(e)) and speciation rate (SR; per lineage per million years) was less than or equal to 10(5), while interspecific variation in N(e) was twofold or less. However, at higher but also biologically relevant values of N(e) × SR and when N(e) varied tenfold among species, performance was very poor. GMYC analyses of mitochondrial DNA sequences from Philippine Hipposideros suggest actual diversity may be approximately twice the current estimate, and available echolocation call data are mostly consistent with GMYC delimitations. In conclusion, we consider the GMYC model useful under some conditions, but additional information on N(e), SR and/or corroboration from independent character data are needed to allow meaningful interpretation of results.

Advancing haemostasis automation--successful implementation of robotic centrifugation and sample processing in a tertiary service hospital.

PubMed

Sédille-Mostafaie, Nazanin; Engler, Hanna; Lutz, Susanne; Korte, Wolfgang

2013-06-01

Laboratories today face increasing pressure to automate operations due to increasing workloads and the need to reduce expenditure. Few studies to date have focussed on the laboratory automation of preanalytical coagulation specimen processing. In the present study, we examined whether a clinical chemistry automation protocol meets the preanalytical requirements for the analyses of coagulation. During the implementation of laboratory automation, we began to operate a pre- and postanalytical automation system. The preanalytical unit processes blood specimens for chemistry, immunology and coagulation by automated specimen processing. As the production of platelet-poor plasma is highly dependent on optimal centrifugation, we examined specimen handling under different centrifugation conditions in order to produce optimal platelet deficient plasma specimens. To this end, manually processed models centrifuged at 1500 g for 5 and 20 min were compared to an automated centrifugation model at 3000 g for 7 min. For analytical assays that are performed frequently enough to be targets for full automation, Passing-Bablok regression analysis showed close agreement between different centrifugation methods, with a correlation coefficient between 0.98 and 0.99 and a bias between -5% and +6%. For seldom performed assays that do not mandate full automation, the Passing-Bablok regression analysis showed acceptable to poor agreement between different centrifugation methods. A full automation solution is suitable and can be recommended for frequent haemostasis testing.

Marijuana Use Trajectories and Academic Outcomes among College Students

PubMed Central

Suerken, Cynthia K.; Reboussin, Beth A.; Egan, Kathleen L.; Sutfin, Erin L.; Wagoner, Kimberly G.; Spangler, John; Wolfson, Mark

2016-01-01

Background Marijuana is the most commonly used illicit drug by college students. Prior studies have established an association between marijuana use and poor academic performance in college, but research on the frequency of marijuana use over the entire college career is limited. The study objective was to examine the association of marijuana use trajectories on academic outcomes, including senior year enrollment, plans to graduate on time, and GPA. Methods Data were collected from a cohort of 3,146 students from 11 colleges in North Carolina and Virginia at six time points across the college career. Group-based trajectory models were used to characterize longitudinal marijuana use patterns during college. Associations between marijuana trajectory groups and academic outcomes were modeled using random-effects linear and logistic regressions. Results Five marijuana trajectory groups were identified: non-users (69.0%), infrequent users (16.6%), decreasing users (4.7%), increasing users (5.8%), and frequent users (3.9%). Decreasing users and frequent users were more likely to drop out of college and plan to delay graduation when compared to non-users. All marijuana user groups reported lower GPAs, on average, than non-users. Conclusion These results identify marijuana use patterns that put students at risk for poor academic performance in college. Students who use marijuana frequently at the beginning of the college career are especially at risk for lower academic achievement than non-users, suggesting that early intervention is critical. PMID:27020322

Validation of community models: 3. Tracing field lines in heliospheric models

NASA Astrophysics Data System (ADS)

MacNeice, Peter; Elliott, Brian; Acebal, Ariel

2011-10-01

Forecasting hazardous gradual solar energetic particle (SEP) bursts at Earth requires accurately modeling field line connections between Earth and the locations of coronal or interplanetary shocks that accelerate the particles. We test the accuracy of field lines reconstructed using four different models of the ambient coronal and inner heliospheric magnetic field, through which these shocks must propagate, including the coupled Wang-Sheeley-Arge (WSA)/ENLIL model. Evaluating the WSA/ENLIL model performance is important since it is the most sophisticated model currently available to space weather forecasters which can model interplanetary coronal mass ejections and, when coupled with particle acceleration and transport models, will provide a complete model for gradual SEP bursts. Previous studies using a simpler Archimedean spiral approach above 2.5 solar radii have reported poor performance. We test the accuracy of the model field lines connecting Earth to the Sun at the onset times of 15 impulsive SEP bursts, comparing the foot points of these field lines with the locations of surface events believed to be responsible for the SEP bursts. We find the WSA/ENLIL model performance is no better than the simplest spiral model, and the principal source of error is the model's inability to reproduce sufficient low-latitude open flux. This may be due to the model's use of static synoptic magnetograms, which fail to account for transient activity in the low corona, during which reconnection events believed to initiate the SEP acceleration may contribute short-lived open flux at low latitudes. Time-dependent coronal models incorporating these transient events may be needed to significantly improve Earth/Sun field line forecasting.

Development and testing of watershed-scale models for poorly drained soils

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2005-01-01

Watershed-scale hydrology and water quality models were used to evaluate the crrmulative impacts of land use and management practices on dowrzstream hydrology and nitrogen loading of poorly drained watersheds. Field-scale hydrology and nutrient dyyrutmics are predicted by DRAINMOD in both models. In the first model (DRAINMOD-DUFLOW), field-scale predictions are coupled...

Improving the Rank Precision of Population Health Measures for Small Areas with Longitudinal and Joint Outcome Models

PubMed Central

Athens, Jessica K.; Remington, Patrick L.; Gangnon, Ronald E.

2015-01-01

Objectives The University of Wisconsin Population Health Institute has published the County Health Rankings since 2010. These rankings use population-based data to highlight health outcomes and the multiple determinants of these outcomes and to encourage in-depth health assessment for all United States counties. A significant methodological limitation, however, is the uncertainty of rank estimates, particularly for small counties. To address this challenge, we explore the use of longitudinal and pooled outcome data in hierarchical Bayesian models to generate county ranks with greater precision. Methods In our models we used pooled outcome data for three measure groups: (1) Poor physical and poor mental health days; (2) percent of births with low birth weight and fair or poor health prevalence; and (3) age-specific mortality rates for nine age groups. We used the fixed and random effects components of these models to generate posterior samples of rates for each measure. We also used time-series data in longitudinal random effects models for age-specific mortality. Based on the posterior samples from these models, we estimate ranks and rank quartiles for each measure, as well as the probability of a county ranking in its assigned quartile. Rank quartile probabilities for univariate, joint outcome, and/or longitudinal models were compared to assess improvements in rank precision. Results The joint outcome model for poor physical and poor mental health days resulted in improved rank precision, as did the longitudinal model for age-specific mortality rates. Rank precision for low birth weight births and fair/poor health prevalence based on the univariate and joint outcome models were equivalent. Conclusion Incorporating longitudinal or pooled outcome data may improve rank certainty, depending on characteristics of the measures selected. For measures with different determinants, joint modeling neither improved nor degraded rank precision. This approach suggests a simple way to use existing information to improve the precision of small-area measures of population health. PMID:26098858

Use of Polyvinyl Alcohol as a Solubility-Enhancing Polymer for Poorly Water Soluble Drug Delivery (Part 1).

PubMed

Brough, Chris; Miller, Dave A; Keen, Justin M; Kucera, Shawn A; Lubda, Dieter; Williams, Robert O

2016-02-01

Polyvinyl alcohol (PVAL) has not been investigated in a binary formulation as a concentration-enhancing polymer owing to its high melting point/high viscosity and poor organic solubility. Due to the unique attributes of the KinetiSol® dispersing (KSD) technology, PVAL has been enabled for this application and it is the aim of this paper to investigate various grades for improvement of the solubility and bioavailability of poorly water soluble active pharmaceutical ingredients. Solid amorphous dispersions were created with the model drug, itraconazole (ITZ), at a selected drug loading of 20%. Polymer grades were chosen with variation in molecular weight and degree of hydroxylation to determine the effects on performance. Differential scanning calorimetry, powder X-ray diffraction, polarized light microscopy, size exclusion chromatography, and dissolution testing were used to characterize the amorphous dispersions. An in vivo pharmacokinetic study in rats was also conducted to compare the selected formulation to current market formulations of ITZ. The 4-88 grade of PVAL was determined to be effective at enhancing solubility and bioavailability of itraconazole.

A Differential Abundance Analysis of Very Metal-poor Stars

NASA Astrophysics Data System (ADS)

O'Malley, Erin M.; McWilliam, Andrew; Chaboyer, Brian; Thompson, Ian

2017-04-01

We have performed a differential line-by-line chemical abundance analysis, ultimately relative to the Sun, of nine very metal-poor main-sequence (MS) halo stars, near [Fe/H] = -2 dex. Our abundances range from -2.66≤slant [{Fe}/{{H}}]≤slant -1.40 dex with conservative uncertainties of 0.07 dex. We find an average [α/Fe] = 0.34 ± 0.09 dex, typical of the Milky Way. While our spectroscopic atmosphere parameters provide good agreement with Hubble Space Telescope parallaxes, there is significant disagreement with temperature and gravity parameters indicated by observed colors and theoretical isochrones. Although a systematic underestimate of the stellar temperature by a few hundred degrees could explain this difference, it is not supported by current effective temperature studies and would create large uncertainties in the abundance determinations. Both 1D and < 3{{D}}> hydrodynamical models combined with separate 1D non-LTE effects do not yet account for the atmospheres of real metal-poor MS stars, but a fully 3D non-LTE treatment may be able to explain the ionization imbalance found in this work.

Clinical utility of the Conners' Continuous Performance Test-II to detect poor effort in U.S. military personnel following traumatic brain injury.

PubMed

Lange, Rael T; Iverson, Grant L; Brickell, Tracey A; Staver, Tara; Pancholi, Sonal; Bhagwat, Aditya; French, Louis M

2013-06-01

The purpose of this study is to examine the clinical utility of the Conners' Continuous Performance Test (CPT-II) as an embedded marker of poor effort in military personnel undergoing neuropsychological evaluations following traumatic brain injury. Participants were 158 U.S. military service members divided into 3 groups on the basis of brain injury severity and performance (pass/fail) on 2 symptom validity tests: Mild Traumatic Brain Injury (MTBI)-Pass (n = 87), MTBI-Fail (n = 42), and severe traumatic brain injury (STBI)-Pass (n = 29). The MTBI-Fail group performed worse on the majority of CPT-II measures compared with both the MTBI-Pass and STBI-Pass groups. When comparing the MTBI-Fail group and MTBI-Pass groups, the most accurate measure for identifying poor effort was the Commission T score. When selected measures were combined (i.e., Omissions, Commissions, and Perseverations), there was a very small increase in sensitivity (from .26 to .29). When comparing the MTBI-Fail group and STBI-Pass groups, the most accurate measure for identifying poor effort was the Omission and Commissions T score. When selected measures were combined, sensitivity again increased (from .24 to .45). Overall, these results suggest that individual CPT-II measures can be useful for identifying people who are suspected of providing poor effort from those who have provided adequate effort. However, due to low sensitivity and modest negative predictive power values, this measure cannot be used in isolation to detect poor effort, and is largely useful as a test to "rule in," not "rule out" poor effort. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Adrenoleukodystrophy

MedlinePlus

... 10. The most common symptoms are usually behavioral changes such as abnormal withdrawal or aggression, poor memory, and poor school performance. Other symptoms include visual loss, learning disabilities, ...

Simulating Snow in Canadian Boreal Environments with CLASS for ESM-SnowMIP

NASA Astrophysics Data System (ADS)

Wang, L.; Bartlett, P. A.; Derksen, C.; Ireson, A. M.; Essery, R.

2017-12-01

The ability of land surface schemes to provide realistic simulations of snow cover is necessary for accurate representation of energy and water balances in climate models. Historically, this has been particularly challenging in boreal forests, where poor treatment of both snow masking by forests and vegetation-snow interaction has resulted in biases in simulated albedo and snowpack properties, with subsequent effects on both regional temperatures and the snow albedo feedback in coupled simulations. The SnowMIP (Snow Model Intercomparison Project) series of experiments or `MIPs' was initiated in order to provide assessments of the performance of various snow- and land-surface-models at selected locations, in order to understand the primary factors affecting model performance. Here we present preliminary results of simulations conducted for the third such MIP, ESM-SnowMIP (Earth System Model - Snow Model Intercomparison Project), using the Canadian Land Surface Scheme (CLASS) at boreal forest sites in central Saskatchewan. We assess the ability of our latest model version (CLASS 3.6.2) to simulate observed snowpack properties (snow water equivalent, density and depth) and above-canopy albedo over 13 winters. We also examine the sensitivity of these simulations to climate forcing at local and regional scales.

49 CFR 240.309 - Railroad oversight responsibilities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... reported train accidents attributed to poor safety performance by locomotive engineers; (3) The number and... and analysis concerning the administration of its program for responding to detected instances of poor... analysis shall involve: (1) The number and nature of the instances of detected poor safety conduct...

Predicting ecological flow regime at ungaged sites: A comparison of methods

USGS Publications Warehouse

Murphy, Jennifer C.; Knight, Rodney R.; Wolfe, William J.; Gain, W. Scott

2012-01-01

Nineteen ecologically relevant streamflow characteristics were estimated using published rainfall–runoff and regional regression models for six sites with observed daily streamflow records in Kentucky. The regional regression model produced median estimates closer to the observed median for all but two characteristics. The variability of predictions from both models was generally less than the observed variability. The variability of the predictions from the rainfall–runoff model was greater than that from the regional regression model for all but three characteristics. Eight characteristics predicted by the rainfall–runoff model display positive or negative bias across all six sites; biases are not as pronounced for the regional regression model. Results suggest that a rainfall–runoff model calibrated on a single characteristic is less likely to perform well as a predictor of a range of other characteristics (flow regime) when compared with a regional regression model calibrated individually on multiple characteristics used to represent the flow regime. Poor model performance may misrepresent hydrologic conditions, potentially distorting the perceived risk of ecological degradation. Without prior selection of streamflow characteristics, targeted calibration, and error quantification, the widespread application of general hydrologic models to ecological flow studies is problematic. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Integration of membrane distillation into traditional salt farming method: Process development and modelling

NASA Astrophysics Data System (ADS)

Hizam, S.; Bilad, M. R.; Putra, Z. A.

2017-10-01

Farmers still practice the traditional salt farming in many regions, particularly in Indonesia. This archaic method not only produces low yield and poor salt quality, it is also laborious. Furthermore, the farming locations typically have poor access to fresh water and are far away from electricity grid, which restrict upgrade to a more advanced technology for salt production. This paper proposes a new concept of salt harvesting method that improves the salt yield and at the same time facilitates recovery of fresh water from seawater. The new concept integrates solar powered membrane distillation (MD) and photovoltaic cells to drive the pumping. We performed basic solar still experiments to quantify the heat flux received by a pond. The data were used as insight for designing the proposed concept, particularly on operational strategy and the most effective way to integrate MD. After the conceptual design had been developed, we formulated mass and energy balance to estimate the performance of the proposed concept. Based on our data and design, it is expected that the system would improve the yield and quality of the salt production, maximizing fresh water harvesting, and eventually provides economical gain for salt farmers hence improving their quality of life. The key performance can only be measured via experiment using gain output ratio as performance indicator, which will be done in a future study.

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

Oral and Written Expression in Children With Reading Comprehension Difficulties.

PubMed

Carretti, Barbara; Motta, Eleonora; Re, Anna Maria

2016-01-01

Several studies have highlighted that children with reading comprehension difficulties also have problems in tasks that involve telling a story, in writing or verbally. The main differences identified regard poor comprehenders' lower level of coherence in their productions by comparison with good comprehenders. Only one study has compared poor and good comprehenders' performance in both modalities (oral and written), however, to see whether these modalities differently influence poor comprehenders' performance. We qualitatively and quantitatively compared the performance of good and poor comprehenders in oral and written narrative tasks with the aim of shedding light on this issue. Regression analyses were also used to explore the role of working memory and vocabulary in explaining individual differences. Our results showed that the two groups produced narratives of comparable length, with similar percentages of spelling mistakes, whereas they differed in terms of the quality of their narratives, regardless of the modality. These differences were qualified by analyzing the children's use of connective devices, and poor comprehenders were found to use a higher proportion of additive devices than good comprehenders. Regression analyses showed that working memory (particularly the intrusion errors measure) explained a modest part of the qualitative differences in narrative production. Implications for our theoretical understanding of poor comprehenders' profiles and education are discussed. © Hammill Institute on Disabilities 2014.

An evaluation of the predictive performance of distributional models for flora and fauna in north-east New South Wales.

PubMed

Pearce, J; Ferrier, S; Scotts, D

2001-06-01

To use models of species distributions effectively in conservation planning, it is important to determine the predictive accuracy of such models. Extensive modelling of the distribution of vascular plant and vertebrate fauna species within north-east New South Wales has been undertaken by linking field survey data to environmental and geographical predictors using logistic regression. These models have been used in the development of a comprehensive and adequate reserve system within the region. We evaluate the predictive accuracy of models for 153 small reptile, arboreal marsupial, diurnal bird and vascular plant species for which independent evaluation data were available. The predictive performance of each model was evaluated using the relative operating characteristic curve to measure discrimination capacity. Good discrimination ability implies that a model's predictions provide an acceptable index of species occurrence. The discrimination capacity of 89% of the models was significantly better than random, with 70% of the models providing high levels of discrimination. Predictions generated by this type of modelling therefore provide a reasonably sound basis for regional conservation planning. The discrimination ability of models was highest for the less mobile biological groups, particularly the vascular plants and small reptiles. In the case of diurnal birds, poor performing models tended to be for species which occur mainly within specific habitats not well sampled by either the model development or evaluation data, highly mobile species, species that are locally nomadic or those that display very broad habitat requirements. Particular care needs to be exercised when employing models for these types of species in conservation planning.

Performance-based self-esteem and burnout in a cross-sectional study of medical students.

PubMed

Dahlin, M; Joneborg, N; Runeson, B

2007-02-01

To examine levels of burnout among medical students and test the hypothesis that high performance-based self-esteem is associated with burnout. Further to study associations between burnout and self-rated health. Cross-sectional survey, of medical students at 1st, 3rd and 6th year of medical school, N = 342, 59.1% women. Burnout was monitored by the Oldenburg Burnout Inventory (OLBI), comprising Exhaustion and Disengagement dimensions. Performance-based self-esteem (PBSE) was assessed by the PBSE-scale (PBSS) and self-rated health by SRH-5. The response rate was 90.4%. Females were more exhausted than males and sixth year students were most disengaged. High performance-based self-esteem was present in 41.7% of the respondents and poor health in 10.7%. Performance-based self-esteem had significant and moderate correlations with both burnout dimensions. Logistic regression showed a positive association between poor health and Exhaustion. Exhaustion among medical students was significantly associated with poor health, and deserves attention from teachers. Performance-based self-esteem was higher than in other populations and associated with both burnout dimensions, but not with poor health. Further research on study environment and burnout is needed, and the reasons for female students' higher exhaustion levels should be further investigated.

The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

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

Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari

2009-11-15

Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R{sup 2} were used to evaluate performancemore » of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R{sup 2} confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.« less

Can air temperature be used to project influences of climate change on stream temperature?

USGS Publications Warehouse

Arismendi, Ivan; Safeeq, Mohammad; Dunham, Jason B.; Johnson, Sherri L.

2014-01-01

Worldwide, lack of data on stream temperature has motivated the use of regression-based statistical models to predict stream temperatures based on more widely available data on air temperatures. Such models have been widely applied to project responses of stream temperatures under climate change, but the performance of these models has not been fully evaluated. To address this knowledge gap, we examined the performance of two widely used linear and nonlinear regression models that predict stream temperatures based on air temperatures. We evaluated model performance and temporal stability of model parameters in a suite of regulated and unregulated streams with 11–44 years of stream temperature data. Although such models may have validity when predicting stream temperatures within the span of time that corresponds to the data used to develop them, model predictions did not transfer well to other time periods. Validation of model predictions of most recent stream temperatures, based on air temperature–stream temperature relationships from previous time periods often showed poor performance when compared with observed stream temperatures. Overall, model predictions were less robust in regulated streams and they frequently failed in detecting the coldest and warmest temperatures within all sites. In many cases, the magnitude of errors in these predictions falls within a range that equals or exceeds the magnitude of future projections of climate-related changes in stream temperatures reported for the region we studied (between 0.5 and 3.0 °C by 2080). The limited ability of regression-based statistical models to accurately project stream temperatures over time likely stems from the fact that underlying processes at play, namely the heat budgets of air and water, are distinctive in each medium and vary among localities and through time.

Task-sharing or public finance for the expansion of surgical access in rural Ethiopia: an extended cost-effectiveness analysis.

PubMed

Shrime, Mark G; Verguet, Stéphane; Johansson, Kjell Arne; Desalegn, Dawit; Jamison, Dean T; Kruk, Margaret E

2016-07-01

Despite a high burden of surgical disease, access to surgical services in low- and middle-income countries is often limited. In line with the World Health Organization's current focus on universal health coverage and equitable access to care, we examined how policies to expand access to surgery in rural Ethiopia would impact health, impoverishment and equity. An extended cost-effectiveness analysis was performed. Deterministic and stochastic models of surgery in rural Ethiopia were constructed, utilizing pooled estimates of costs and probabilities from national surveys and published literature. Model calibration and validation were performed against published estimates, with sensitivity analyses on model assumptions to check for robustness. Outcomes of interest were the number of deaths averted, the number of cases of poverty averted and the number of cases of catastrophic expenditure averted for each policy, divided across wealth quintiles. Health benefits, financial risk protection and equity appear to be in tension in the expansion of access to surgical care in rural Ethiopia. Health benefits from each of the examined policies accrued primarily to the poor. However, without travel vouchers, many policies also induced impoverishment in the poor while providing financial risk protection to the rich, calling into question the equitable distribution of benefits by these policies. Adding travel vouchers removed the impoverishing effects of a policy but decreased the health benefit that could be bought per dollar spent. These results were robust to sensitivity analyses. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Global-scale regionalization of hydrological model parameters using streamflow data from many small catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; de Roo, Ad; van Dijk, Albert; McVicar, Tim; Miralles, Diego; Schellekens, Jaap; Bruijnzeel, Sampurno; de Jeu, Richard

2015-04-01

Motivated by the lack of large-scale model parameter regionalization studies, a large set of 3328 small catchments (< 10000 km2) around the globe was used to set up and evaluate five model parameterization schemes at global scale. The HBV-light model was chosen because of its parsimony and flexibility to test the schemes. The catchments were calibrated against observed streamflow (Q) using an objective function incorporating both behavioral and goodness-of-fit measures, after which the catchment set was split into subsets of 1215 donor and 2113 evaluation catchments based on the calibration performance. The donor catchments were subsequently used to derive parameter sets that were transferred to similar grid cells based on a similarity measure incorporating climatic and physiographic characteristics, thereby producing parameter maps with global coverage. Overall, there was a lack of suitable donor catchments for mountainous and tropical environments. The schemes with spatially-uniform parameter sets (EXP2 and EXP3) achieved the worst Q estimation performance in the evaluation catchments, emphasizing the importance of parameter regionalization. The direct transfer of calibrated parameter sets from donor catchments to similar grid cells (scheme EXP1) performed best, although there was still a large performance gap between EXP1 and HBV-light calibrated against observed Q. The schemes with parameter sets obtained by simultaneously calibrating clusters of similar donor catchments (NC10 and NC58) performed worse than EXP1. The relatively poor Q estimation performance achieved by two (uncalibrated) macro-scale hydrological models suggests there is considerable merit in regionalizing the parameters of such models. The global HBV-light parameter maps and ancillary data are freely available via http://water.jrc.ec.europa.eu.

Understanding Preclerkship Medical Students' Poor Performance in Prescription Writing.

PubMed

James, Henry; Al Khaja, Khalid A J; Tayem, Yasin I; Veeramuthu, Sindhan; Sequeira, Reginald P

2016-05-01

This study aimed to explore reasons for poor performance in prescription writing stations of the objective structured practical examination (OSPE) and absenteeism in prescription writing sessions among preclerkship medical students at the Arabian Gulf University (AGU) in Manama, Bahrain. This descriptive study was carried out between September 2014 and June 2015 among 157 preclerkship medical students at AGU. Data were collected using focus group discussions and a questionnaire with closed- and open-ended items. All 157 students participated in the study (response rate: 100.0%). The most frequently cited reasons for poor performance in OSPE stations were an inability to select the correct drugs (79.6%), treatment duration (69.4%), drug quantity (69.4%) and drug formulation (68.2%). Additionally, students reported inadequate time for completing the stations (68.8%). During focus group discussions, students reported other reasons for poor performance, including examination stress and the difficulty of the stations. Absenteeism was attributed to the length of each session (55.4%), lack of interest (50.3%), reliance on peers for information (48.4%) and optional attendance policies (47.1%). Repetitive material, large group sessions, unmet student expectations and the proximity of the sessions to summative examinations were also indicated to contribute to absenteeism according to open-ended responses or focus group discussions. This study suggests that AGU medical students perform poorly in prescription writing OSPE stations because of inadequate clinical pharmacology knowledge. Participation in prescription writing sessions needs to be enhanced by addressing the concerns identified in this study. Strategies to improve attendance and performance should take into account the learner-teacher relationship.

The association of snoring and risk of obstructive sleep apnea with poor academic performance among university students.

PubMed

Khassawneh, Basheer Y; Alkhatib, Loiy L; Ibnian, Ali M; Khader, Yousef S

2018-04-20

Subjects with obstructive sleep apnea (OSA) have neurocognitive dysfunction. The aim of this study was to estimate the prevalence of symptoms and risk of OSA among university students and the association with academic performance. A cross-sectional study was conducted at Jordan University of Science and Technology. Students from faculties of engineering, medicine, nursing, pharmacy, and dentistry were asked to participate in this study. The Berlin Sleep Questionnaire was used to report symptoms and risk of OSA. Below average cumulative scores were considered poor academic performance. A total of 777 students (51% female; mean age, 20 years) completed the study questionnaire. According to the study definition, 42 students (5.4%) had high risk for OSA. Snoring was reported by 11% and daytime sleepiness and fatigue by 30%. Compared to female students, male students had more snoring (14.6 vs. 7.6%, p = 0.002) and higher risk for OSA (6.5 vs. 1.6%, p = 0.001). Both self-reported snoring and being at high risk for OSA were associated with poor academic performance (27.9 vs. 11.6% and 23.1 vs. 9.2%, respectively; p < 0.02). After adjusting for confounding factors, the odds ratio of having poor academic performance in students at high risk for OSA was 2.4 (CI 1.11-5.2, p = 0.027). Snoring and OSA were uncommon among university students. However, both were more common among male students and were associated with poor academic performance.

SLP-2 overexpression is associated with tumour distant metastasis and poor prognosis in pulmonary squamous cell carcinoma.

PubMed

Chang, Dong; Ma, Kai; Gong, Min; Cui, Yong; Liu, Zhi-hua; Zhou, Xiao-ge; Zhou, Chuan-nong; Wang, Tian-you

2010-03-01

To investigate the role of stomatin-like protein 2 (SLP-2), a novel cancer-related gene, in pulmonary squamous cell carcinoma (PSCC) and its implications. Immunohistochemical detection of SLP-2 was performed on 96 cases of PSCC with a tissue microarray. SLP-2 was overexpressed in lung cancer compared with normal lung tissue (p <0.001). High-level SLP-2 expression was significantly correlated with distant metastasis (p = 0.025), decreased overall survival (p = 0.018) and disease-free survival (p = 0.017). SLP-2 overexpression was an independent prognostic factor in multivariate analysis using the Cox regression model (p <0.05). SLP-2 overexpression is associated with tumour distant metastasis and poor prognosis in PSCC. SLP-2 could be regarded as a new significant prognostic biomarker for patients with PSCC.

Radiative transfer modelling inside thermal protection system using hybrid homogenization method for a backward Monte Carlo method coupled with Mie theory

NASA Astrophysics Data System (ADS)

Le Foll, S.; André, F.; Delmas, A.; Bouilly, J. M.; Aspa, Y.

2012-06-01

A backward Monte Carlo method for modelling the spectral directional emittance of fibrous media has been developed. It uses Mie theory to calculate the radiative properties of single fibres, modelled as infinite cylinders, and the complex refractive index is computed by a Drude-Lorenz model for the dielectric function. The absorption and scattering coefficient are homogenised over several fibres, but the scattering phase function of a single one is used to determine the scattering direction of energy inside the medium. Sensitivity analysis based on several Monte Carlo results has been performed to estimate coefficients for a Multi-Linear Model (MLM) specifically developed for inverse analysis of experimental data. This model concurs with the Monte Carlo method and is highly computationally efficient. In contrast, the surface emissivity model, which assumes an opaque medium, shows poor agreement with the reference Monte Carlo calculations.

Examining asthma quality of care using a population-based approach

PubMed Central

Klomp, Helena; Lawson, Joshua A.; Cockcroft, Donald W.; Chan, Benjamin T.; Cascagnette, Paul; Gander, Laurie; Jorgenson, Derek

2008-01-01

Background Asthma accounts for considerable burden on health care, but in most cases, asthma can be controlled. Quality-of-care indicators would aid in monitoring asthma management. We describe the quality of asthma care using a set of proposed quality indicators. Methods We performed a retrospective cross-sectional study using health databases in Saskatchewan, a Canadian province with a population of about 1 million people. We assessed 6 quality-of-care indicators among people with asthma: admission to hospital because of asthma; poor asthma control (high use of short-acting β-agonists, admission to hospital because of asthma or death due to asthma); no inhaled corticosteroid use among patients with poor control; at least moderate inhaled corticosteroid use among patients with poor control; high inhaled corticosteroid use and use of another preventer medication among patients with poor control; and any main preventer use among patients with poor control. We calculated crude and adjusted rates with 95% confidence intervals. We tested for differences using the χ2 test for proportions and generalized linear modelling techniques. Results In 2002/03, there were 24 616 people aged 5–54 years with asthma in Saskatchewan, representing a prevalence of 3.8%. Poor symptom control was observed in 18% of patients with asthma. Among those with poor control, 37% were not dispensed any inhaled corticosteroids, and 40% received potentially inadequate doses. Among those with poor control who were dispensed high doses of inhaled corticosteroids, 26% also used another preventer medication. Hospital admissions because of asthma were highest among those aged 6–9 years and females aged 20–44 years. Males and those in adult age groups (predominantly 20–44 years) had worse quality of care for 4 indicators examined. Interpretation Suboptimal asthma management would be improved through increased use of inhaled corticosteroids and preventer medications, and reduced reliance on short-acting β-agonist medications as recommended by consensus guidelines. PMID:18390944

Multi-level modeling of aspects associated with poor mental health in a sample of prehospital emergency professionals.

PubMed

Arial, Marc; Wild, Pascal; Benoit, Damien; Chouaniere, Dominique; Danuser, Brigitta

2011-11-01

The goal of this paper is to investigate the respective influence of work characteristics, the effort-reward ratio, and overcommitment on the poor mental health of out-of-hospital care providers. 333 out-of-hospital care providers answered a questionnaire that included queries on mental health (GHQ-12), demographics, health-related information and work characteristics, questions from the Effort-Reward Imbalance Questionnaire, and items about overcommitment. A two-level multiple regression was performed between mental health (the dependent variable) and the effort-reward ratio, the overcommitment score, weekly number of interventions, percentage of non-prehospital transport of patients out of total missions, gender, and age. Participants were first-level units, and ambulance services were second-level units. We also shadowed ambulance personnel for a total of 416 hr. With cutoff points of 2/3 and 3/4 positive answers on the GHQ-12, the percentages of potential cases with poor mental health were 20% and 15%, respectively. The effort-reward ratio was associated with poor mental health (P < 0.001), irrespective of age or gender. Overcommitment was associated with poor mental health; this association was stronger in women (β = 0.054) than in men (β = 0.020). The percentage of prehospital missions out of total missions was only associated with poor mental health at the individual level. Emergency medical services should pay attention to the way employees perceive their efforts and the rewarding aspects of their work: an imbalance of those aspects is associated with poor mental health. Low perceived esteem appeared particularly associated with poor mental health. This suggests that supervisors of emergency medical services should enhance the value of their employees' work. Employees with overcommitment should also receive appropriate consideration. Preventive measures should target individual perceptions of effort and reward in order to improve mental health in prehospital care providers. Copyright © 2011 Wiley Periodicals, Inc.