Advances in the Study of Moving Sediments and Evolving Seabeds

NASA Astrophysics Data System (ADS)

Davies, Alan G.; Thorne, Peter D.

2008-01-01

Sands and mud are continually being transported around the world’s coastal seas due to the action of tides, wind and waves. The transport of these sediments modifies the boundary between the land and the sea, changing and reshaping its form. Sometimes the nearshore bathymetry evolves slowly over long time periods, at other times more rapidly due to natural episodic events or the introduction of manmade structures at the shoreline. For over half a century we have been trying to understand the physics of sediment transport processes and formulate predictive models. Although significant progress has been made, our capability to forecast the future behaviour of the coastal zone from basic principles is still relatively poor. However, innovative acoustic techniques for studying the fundamentals of sediment movement experimentally are now providing new insights, and it is expected that such observations, coupled with developing theoretical works, will allow us to take further steps towards the goal of predicting the evolution of coastlines and coastal bathymetry. This paper presents an overview of our existing predictive capabilities, primarily in the field of non-cohesive sediment transport, and highlights how new acoustic techniques are enabling our modelling efforts to achieve greater sophistication and accuracy. The paper is aimed at coastal scientists and managers seeking to understand how detailed physical studies can contribute to the improvement of coastal area models and, hence, inform coastal zone management strategies.

Prognostic Classifier Based on Genome-Wide DNA Methylation Profiling in Well-Differentiated Thyroid Tumors.

PubMed

Bisarro Dos Reis, Mariana; Barros-Filho, Mateus Camargo; Marchi, Fábio Albuquerque; Beltrami, Caroline Moraes; Kuasne, Hellen; Pinto, Clóvis Antônio Lopes; Ambatipudi, Srikant; Herceg, Zdenko; Kowalski, Luiz Paulo; Rogatto, Silvia Regina

2017-11-01

Even though the majority of well-differentiated thyroid carcinoma (WDTC) is indolent, a number of cases display an aggressive behavior. Cumulative evidence suggests that the deregulation of DNA methylation has the potential to point out molecular markers associated with worse prognosis. To identify a prognostic epigenetic signature in thyroid cancer. Genome-wide DNA methylation assays (450k platform, Illumina) were performed in a cohort of 50 nonneoplastic thyroid tissues (NTs), 17 benign thyroid lesions (BTLs), and 74 thyroid carcinomas (60 papillary, 8 follicular, 2 Hürthle cell, 1 poorly differentiated, and 3 anaplastic). A prognostic classifier for WDTC was developed via diagonal linear discriminant analysis. The results were compared with The Cancer Genome Atlas (TCGA) database. A specific epigenetic profile was detected according to each histological subtype. BTLs and follicular carcinomas showed a greater number of methylated CpG in comparison with NTs, whereas hypomethylation was predominant in papillary and undifferentiated carcinomas. A prognostic classifier based on 21 DNA methylation probes was able to predict poor outcome in patients with WDTC (sensitivity 63%, specificity 92% for internal data; sensitivity 64%, specificity 88% for TCGA data). High-risk score based on the classifier was considered an independent factor of poor outcome (Cox regression, P < 0.001). The methylation profile of thyroid lesions exhibited a specific signature according to the histological subtype. A meaningful algorithm composed of 21 probes was capable of predicting the recurrence in WDTC. Copyright © 2017 Endocrine Society

EEG-based time and spatial interpretation of activation areas for relaxation and words writing between poor and capable dyslexic children.

PubMed

Mohamad, N B; Lee, Khuan Y; Mansor, W; Mahmoodin, Z; Fadzal, C W N F C W; Amirin, S

2015-01-01

Symptoms of dyslexia such as difficulties with accurate and/or fluent word recognition, and/or poor spelling as well as decoding abilities, are easily misinterpreted as laziness and defiance amongst school children. Indeed, 37.9% of 699 school dropouts and failures are diagnosed as dyslexic. Currently, Screening for dyslexia relies heavily on therapists, whom are few and subjective, yet objective methods are still unavailable. EEG has long been a popular method to study the cognitive processes in human such as language processing and motor activity. However, its interpretation is limited to time and frequency domain, without visual information, which is still useful. Here, our research intends to illustrate an EEG-based time and spatial interpretation of activated brain areas for the poor and capable dyslexic during the state of relaxation and words writing, being the first attempt ever reported. From the 2D distribution of EEG spectral at the activation areas and its progress with time, it is observed that capable dyslexics are able to relax compared to poor dyslexics. During the state of words writing, neural activities are found higher on the right hemisphere than the left hemisphere of the capable dyslexics, which suggests a neurobiological compensation pathway in the right hemisphere, during reading and writing, which is not observed in the poor dyslexics.

Machine learning for outcome prediction of acute ischemic stroke post intra-arterial therapy.

PubMed

Asadi, Hamed; Dowling, Richard; Yan, Bernard; Mitchell, Peter

2014-01-01

Stroke is a major cause of death and disability. Accurately predicting stroke outcome from a set of predictive variables may identify high-risk patients and guide treatment approaches, leading to decreased morbidity. Logistic regression models allow for the identification and validation of predictive variables. However, advanced machine learning algorithms offer an alternative, in particular, for large-scale multi-institutional data, with the advantage of easily incorporating newly available data to improve prediction performance. Our aim was to design and compare different machine learning methods, capable of predicting the outcome of endovascular intervention in acute anterior circulation ischaemic stroke. We conducted a retrospective study of a prospectively collected database of acute ischaemic stroke treated by endovascular intervention. Using SPSS®, MATLAB®, and Rapidminer®, classical statistics as well as artificial neural network and support vector algorithms were applied to design a supervised machine capable of classifying these predictors into potential good and poor outcomes. These algorithms were trained, validated and tested using randomly divided data. We included 107 consecutive acute anterior circulation ischaemic stroke patients treated by endovascular technique. Sixty-six were male and the mean age of 65.3. All the available demographic, procedural and clinical factors were included into the models. The final confusion matrix of the neural network, demonstrated an overall congruency of ∼ 80% between the target and output classes, with favourable receiving operative characteristics. However, after optimisation, the support vector machine had a relatively better performance, with a root mean squared error of 2.064 (SD: ± 0.408). We showed promising accuracy of outcome prediction, using supervised machine learning algorithms, with potential for incorporation of larger multicenter datasets, likely further improving prediction. Finally, we propose that a robust machine learning system can potentially optimise the selection process for endovascular versus medical treatment in the management of acute stroke.

Novel composites for wing and fuselage applications

NASA Technical Reports Server (NTRS)

Sobel, L. H.; Buttitta, C.; Suarez, J. A.

1995-01-01

Probabilistic predictions based on the IPACS code are presented for the material and structural response of unnotched and notched, IM6/3501-6 Gr/Ep laminates. Comparisons of predicted and measured modulus and strength distributions are given for unnotched unidirectional, cross-ply and quasi-isotropic laminates. The predicted modulus distributions were found to correlate well with the test results for all three unnotched laminates. Correlations of strength distributions for the unnotched laminates are judged good for the unidirectional laminate and fair for the cross-ply laminate, whereas the strength correlation for the quasi-isotropic laminate is judged poor because IPACS did not have a progressive failure capability at the time this work was performed. The report also presents probabilistic and structural reliability analysis predictions for the strain concentration factor (SCF) for an open-hole, quasi-isotropic laminate subjected to longitudinal tension. A special procedure was developed to adapt IPACS for the structural reliability analysis. The reliability results show the importance of identifying the most significant random variables upon which the SCF depends, and of having accurate scatter values for these variables.

Effective moisture penetration depth model for residential buildings: Sensitivity analysis and guidance on model inputs

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

Woods, Jason; Winkler, Jon

Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less

Effective moisture penetration depth model for residential buildings: Sensitivity analysis and guidance on model inputs

DOE PAGES

Woods, Jason; Winkler, Jon

2018-01-31

Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less

Statistical Analysis on the Mechanical Properties of Magnesium Alloys

PubMed Central

Liu, Ruoyu; Jiang, Xianquan; Zhang, Hongju; Zhang, Dingfei; Wang, Jingfeng; Pan, Fusheng

2017-01-01

Knowledge of statistical characteristics of mechanical properties is very important for the practical application of structural materials. Unfortunately, the scatter characteristics of magnesium alloys for mechanical performance remain poorly understood until now. In this study, the mechanical reliability of magnesium alloys is systematically estimated using Weibull statistical analysis. Interestingly, the Weibull modulus, m, of strength for magnesium alloys is as high as that for aluminum and steels, confirming the very high reliability of magnesium alloys. The high predictability in the tensile strength of magnesium alloys represents the capability of preventing catastrophic premature failure during service, which is essential for safety and reliability assessment. PMID:29113116

Development of a five-year mortality model in systemic sclerosis patients by different analytical approaches.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; Cappiello, Francesca; Chawla, Nitesh V; Vonk, Madelon C; Carreira, Patricia E; Allanore, Yannick; Popa-Diaconu, D A; Cossu, Marta; Bertolotti, Francesca; Ferraccioli, Gianfranco; Mazzone, Antonino; Scorza, Raffaella

2010-01-01

Systemic sclerosis (SSc) is a multiorgan disease with high mortality rates. Several clinical features have been associated with poor survival in different populations of SSc patients, but no clear and reproducible prognostic model to assess individual survival prediction in scleroderma patients has ever been developed. We used Cox regression and three data mining-based classifiers (Naïve Bayes Classifier [NBC], Random Forests [RND-F] and logistic regression [Log-Reg]) to develop a robust and reproducible 5-year prognostic model. All the models were built and internally validated by means of 5-fold cross-validation on a population of 558 Italian SSc patients. Their predictive ability and capability of generalisation was then tested on an independent population of 356 patients recruited from 5 external centres and finally compared to the predictions made by two SSc domain experts on the same population. The NBC outperformed the Cox-based classifier and the other data mining algorithms after internal cross-validation (area under receiving operator characteristic curve, AUROC: NBC=0.759; RND-F=0.736; Log-Reg=0.754 and Cox= 0.724). The NBC had also a remarkable and better trade-off between sensitivity and specificity (e.g. Balanced accuracy, BA) than the Cox-based classifier, when tested on an independent population of SSc patients (BA: NBC=0.769, Cox=0.622). The NBC was also superior to domain experts in predicting 5-year survival in this population (AUROC=0.829 vs. AUROC=0.788 and BA=0.769 vs. BA=0.67). We provide a model to make consistent 5-year prognostic predictions in SSc patients. Its internal validity, as well as capability of generalisation and reduced uncertainty compared to human experts support its use at bedside. Available at: http://www.nd.edu/~nchawla/survival.xls.

Development of low-cost meteorological observation system based on wireless network for poor-visibility occurred by snowstorm

NASA Astrophysics Data System (ADS)

Kobayashi, Y.; Watanabe, K.; Imai, M.; Watanabe, K.; Naruse, N.; Takahashi, Y.

2016-12-01

Hyper-densely monitoring for poor-visibility occurred by snowstorm is needed to make an alert system, because the snowstorm is difficult to predict from the observation only at a representative point. There are some problems in the previous approaches for the poor-visibility monitoring using video analyses or visibility meters; these require a wired network monitoring (a large amount of data: 10MB/sec at least) and the system cost is high (10,000 at each point). Thus, the risk of poor-visibility has been mainly measured at specific point such as airport and mountain pass, and estimated by simulation two dimensionally. To predict it two dimensionally and accurately, we have developed a low-cost meteorological system to observe the snowstorm hyper-densely. We have developed a low-cost visibility meter which works as the reduced intensity of semiconducting laser light when snow particles block off. Our developed system also has a capability of extending a hyper-densely observation in real-time on wireless network using Zigbee; A/D conversion and wireless data sent from temperature and illuminance sensors. We use a semiconducting laser chip (5) for the light source and a reflection mechanism by the use of three mirrors so as to send the light to a non-sensitive illuminance sensor directly. Thus, our visibility detecting system ($500) becomes much cheaper than previous one. We have checked the correlation between the reduced intensity taken by our system and the visibility recorded by conventional video camera. The value for the correlation coefficient was -0.67, which indicates a strong correlation. It means that our developed system is practical. In conclusion, we have developed low-cost meteorological detecting system to observe poor-visibility occurred by snowstorm, having a potential of hyper-densely monitoring on wireless network, and have made sure the practicability.

Unreliable gut feelings can lead to correct decisions: the somatic marker hypothesis in non-linear decision chains.

PubMed

Bedia, Manuel G; Di Paolo, Ezequiel

2012-01-01

Dual-process approaches of decision-making examine the interaction between affective/intuitive and deliberative processes underlying value judgment. From this perspective, decisions are supported by a combination of relatively explicit capabilities for abstract reasoning and relatively implicit evolved domain-general as well as learned domain-specific affective responses. One such approach, the somatic markers hypothesis (SMH), expresses these implicit processes as a system of evolved primary emotions supplemented by associations between affect and experience that accrue over lifetime, or somatic markers. In this view, somatic markers are useful only if their local capability to predict the value of an action is above a baseline equal to the predictive capability of the combined rational and primary emotional subsystems. We argue that decision-making has often been conceived of as a linear process: the effect of decision sequences is additive, local utility is cumulative, and there is no strong environmental feedback. This widespread assumption can have consequences for answering questions regarding the relative weight between the systems and their interaction within a cognitive architecture. We introduce a mathematical formalization of the SMH and study it in situations of dynamic, non-linear decision chains using a discrete-time stochastic model. We find, contrary to expectations, that decision-making events can interact non-additively with the environment in apparently paradoxical ways. We find that in non-lethal situations, primary emotions are represented globally over and above their local weight, showing a tendency for overcautiousness in situated decision chains. We also show that because they tend to counteract this trend, poorly attuned somatic markers that by themselves do not locally enhance decision-making, can still produce an overall positive effect. This result has developmental and evolutionary implications since, by promoting exploratory behavior, somatic markers would seem to be beneficial even at early stages when experiential attunement is poor. Although the model is formulated in terms of the SMH, the implications apply to dual systems theories in general since it makes minimal assumptions about the nature of the processes involved.

Unreliable Gut Feelings Can Lead to Correct Decisions: The Somatic Marker Hypothesis in Non-Linear Decision Chains

PubMed Central

Bedia, Manuel G.; Di Paolo, Ezequiel

2012-01-01

Dual-process approaches of decision-making examine the interaction between affective/intuitive and deliberative processes underlying value judgment. From this perspective, decisions are supported by a combination of relatively explicit capabilities for abstract reasoning and relatively implicit evolved domain-general as well as learned domain-specific affective responses. One such approach, the somatic markers hypothesis (SMH), expresses these implicit processes as a system of evolved primary emotions supplemented by associations between affect and experience that accrue over lifetime, or somatic markers. In this view, somatic markers are useful only if their local capability to predict the value of an action is above a baseline equal to the predictive capability of the combined rational and primary emotional subsystems. We argue that decision-making has often been conceived of as a linear process: the effect of decision sequences is additive, local utility is cumulative, and there is no strong environmental feedback. This widespread assumption can have consequences for answering questions regarding the relative weight between the systems and their interaction within a cognitive architecture. We introduce a mathematical formalization of the SMH and study it in situations of dynamic, non-linear decision chains using a discrete-time stochastic model. We find, contrary to expectations, that decision-making events can interact non-additively with the environment in apparently paradoxical ways. We find that in non-lethal situations, primary emotions are represented globally over and above their local weight, showing a tendency for overcautiousness in situated decision chains. We also show that because they tend to counteract this trend, poorly attuned somatic markers that by themselves do not locally enhance decision-making, can still produce an overall positive effect. This result has developmental and evolutionary implications since, by promoting exploratory behavior, somatic markers would seem to be beneficial even at early stages when experiential attunement is poor. Although the model is formulated in terms of the SMH, the implications apply to dual systems theories in general since it makes minimal assumptions about the nature of the processes involved. PMID:23087655

Race, gender, class, and sexual orientation: intersecting axes of inequality and self-rated health in Canada

PubMed Central

2011-01-01

Background Intersectionality theory, a way of understanding social inequalities by race, gender, class, and sexuality that emphasizes their mutually constitutive natures, possesses potential to uncover and explicate previously unknown health inequalities. In this paper, the intersectionality principles of "directionality," "simultaneity," "multiplicativity," and "multiple jeopardy" are applied to inequalities in self-rated health by race, gender, class, and sexual orientation in a Canadian sample. Methods The Canadian Community Health Survey 2.1 (N = 90,310) provided nationally representative data that enabled binary logistic regression modeling on fair/poor self-rated health in two analytical stages. The additive stage involved regressing self-rated health on race, gender, class, and sexual orientation singly and then as a set. The intersectional stage involved consideration of two-way and three-way interaction terms between the inequality variables added to the full additive model created in the previous stage. Results From an additive perspective, poor self-rated health outcomes were reported by respondents claiming Aboriginal, Asian, or South Asian affiliations, lower class respondents, and bisexual respondents. However, each axis of inequality interacted significantly with at least one other: multiple jeopardy pertained to poor homosexuals and to South Asian women who were at unexpectedly high risks of fair/poor self-rated health and mitigating effects were experienced by poor women and by poor Asian Canadians who were less likely than expected to report fair/poor health. Conclusions Although a variety of intersections between race, gender, class, and sexual orientation were associated with especially high risks of fair/poor self-rated health, they were not all consistent with the predictions of intersectionality theory. I conclude that an intersectionality theory well suited for explicating health inequalities in Canada should be capable of accommodating axis intersections of multiple kinds and qualities. PMID:21241506

Toward a US National Air Quality Forecast Capability: Current and Planned Capabilities

EPA Science Inventory

As mandated by Congress, NOAA is establishing a US national air quality forecast capability. This capability is being built with EPA, to provide air quality forecast information with enough accuracy and lead-time so that people can take actions to limit harmful effects of poor a...

Analysis and simulation of wireless signal propagation applying geostatistical interpolation techniques

NASA Astrophysics Data System (ADS)

Kolyaie, S.; Yaghooti, M.; Majidi, G.

2011-12-01

This paper is a part of an ongoing research to examine the capability of geostatistical analysis for mobile networks coverage prediction, simulation and tuning. Mobile network coverage predictions are used to find network coverage gaps and areas with poor serviceability. They are essential data for engineering and management in order to make better decision regarding rollout, planning and optimisation of mobile networks.The objective of this research is to evaluate different interpolation techniques in coverage prediction. In method presented here, raw data collected from drive testing a sample of roads in study area is analysed and various continuous surfaces are created using different interpolation methods. Two general interpolation methods are used in this paper with different variables; first, Inverse Distance Weighting (IDW) with various powers and number of neighbours and second, ordinary kriging with Gaussian, spherical, circular and exponential semivariogram models with different number of neighbours. For the result comparison, we have used check points coming from the same drive test data. Prediction values for check points are extracted from each surface and the differences with actual value are computed. The output of this research helps finding an optimised and accurate model for coverage prediction.

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

What can we learn about the dynamics of DO-events from studying the high resolution ice core records?

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2017-04-01

The causes for and possible predictions of rapid climate changes are poorly understood. The most pronounced changes observed, beside the glacial terminations, are the Dansgaard-Oeschger events. Present day general circulation climate models simulating glacial conditions are not capable of reproducing these rapid shifts. It is thus not known if they are due to bifurcations in the structural stability of the climate or if they are induced by stochastic fluctuations. By analyzing a high resolution ice core record we exclude the bifurcation scenario, which strongly suggests that they are noise induced and thus have very limited predictability. Ref: Peter Ditlevsen, "Tipping points in the climate system", in Nonlinear and Stochastic Climate Dynamics, Cambridge University Press (C. Franzke and T. O'Kane, eds.) (2016) P. D. Ditlevsen and S. Johnsen, "Tipping points: Early warning and wishful thinking", Geophys. Res. Lett., 37, L19703, 2010

Mortality, morbidity and refractoriness prediction in status epilepticus: Comparison of STESS and EMSE scores.

PubMed

Giovannini, Giada; Monti, Giulia; Tondelli, Manuela; Marudi, Andrea; Valzania, Franco; Leitinger, Markus; Trinka, Eugen; Meletti, Stefano

2017-03-01

Status epilepticus (SE) is a neurological emergency, characterized by high short-term morbidity and mortality. We evaluated and compared two scores that have been developed to evaluate status epilepticus prognosis: STESS (Status Epilepticus Severity Score) and EMSE (Epidemiology based Mortality score in Status Epilepticus). A prospective observational study was performed on consecutive patients with SE admitted between September 2013 and August 2015. Demographics, clinical variables, STESS-3 and -4, and EMSE-64 scores were calculated for each patient at baseline. SE drug response, 30-day mortality and morbidity were the outcomes measure. 162 episodes of SE were observed: 69% had a STESS ≥3; 34% had a STESS ≥4; 51% patients had an EMSE ≥64. The 30-days mortality was 31.5%: EMSE-64 showed greater negative predictive value (NPV) (97.5%), positive predictive value (PPV) (59.8%) and accuracy in the prediction of death than STESS-3 and STESS-4 (p<0.001). At 30 days, the clinical condition had deteriorated in 59% of the cases: EMSE-64 showed greater NPV (71.3%), PPV (87.8%) and accuracy than STESS-3 and STESS-4 (p<0.001) in the prediction of this outcome. In 23% of all cases, status epilepticus proved refractory to non-anaesthetic treatment. All three scales showed a high NPV (EMSE-64: 87.3%; STESS-4: 89.4%; STESS-3: 87.5%) but a low PPV (EMSE-64: 40.9%; STESS-4: 52.9%; STESS-3: 32%) for the prediction of refractoriness to first and second line drugs. This means that accuracy for the prediction of refractoriness was equally poor for all scales. EMSE-64 appears superior to STESS-3 and STESS-4 in the prediction of 30-days mortality and morbidity. All scales showed poor accuracy in the prediction of response to first and second line antiepileptic drugs. At present, there are no reliable scores capable of predicting treatment responsiveness. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Improving National Capability in Biogeochemical Flux Modelling: the UK Environmental Virtual Observatory (EVOp)

NASA Astrophysics Data System (ADS)

Johnes, P.; Greene, S.; Freer, J. E.; Bloomfield, J.; Macleod, K.; Reaney, S. M.; Odoni, N. A.

2012-12-01

The best outcomes from watershed management arise where policy and mitigation efforts are underpinned by strong science evidence, but there are major resourcing problems associated with the scale of monitoring needed to effectively characterise the sources rates and impacts of nutrient enrichment nationally. The challenge is to increase national capability in predictive modelling of nutrient flux to waters, securing an effective mechanism for transferring knowledge and management tools from data-rich to data-poor regions. The inadequacy of existing tools and approaches to address these challenges provided the motivation for the Environmental Virtual Observatory programme (EVOp), an innovation from the UK Natural Environment Research Council (NERC). EVOp is exploring the use of a cloud-based infrastructure in catchment science, developing an exemplar to explore N and P fluxes to inland and coastal waters in the UK from grid to catchment and national scale. EVOp is bringing together for the first time national data sets, models and uncertainty analysis into cloud computing environments to explore and benchmark current predictive capability for national scale biogeochemical modelling. The objective is to develop national biogeochemical modelling capability, capitalising on extensive national investment in the development of science understanding and modelling tools to support integrated catchment management, and supporting knowledge transfer from data rich to data poor regions, The AERC export coefficient model (Johnes et al., 2007) has been adapted to function within the EVOp cloud environment, and on a geoclimatic basis, using a range of high resolution, geo-referenced digital datasets as an initial demonstration of the enhanced national capacity for N and P flux modelling using cloud computing infrastructure. Geoclimatic regions are landscape units displaying homogenous or quasi-homogenous functional behaviour in terms of process controls on N and P cycling, underpin this approach (Johnes & Butterfield, 2002). Ten regions have been defined across the UK using GIS manipulation of spatial data describing hydrogeology, runoff, topographical slope and soil parent material. The export coefficient model operates within this regional modelling framework, providing mapped, tabulated and statistical outputs at scales from 1km2 grid scale to river catchment, WFD river basin district, major coastal drainage units to the North Sea, North Atlantic and English Channel, to the international reporting units defined under OSPAR, the International Convention for the protection of the marine environment of the North-East Atlantic. Here the geoclimatic modelling framework is presented together with modelled fluxes for N and P for each scale of reporting unit, together with scenario analysis applied at regional scale and mapped at national scale. The ways in which the results can be used to further explore the primary drivers for spatial variation and identify waterbodies at risk, especially in unmonitored and data-poor catchments are discussed, and the technical and computational support of a cloud-based infrastructure is evaluated as a mechanism to explore potential water quality impacts of future mitigation strategies applied at catchment to national scale.

Tutorial: Neural networks and their potential application in nuclear power plants

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

Uhrig, R.E.

A neural network is a data processing system consisting of a number of simple, highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks have emerged in the past few years as an area of unusual opportunity for research, development and application to a variety of real world problems. Indeed, neural networks exhibit characteristics and capabilities not provided by any other technology. Examples include reading Japanese Kanjimore » characters and human handwriting, reading a typewritten manuscript aloud, compensating for alignment errors in robots, interpreting very noise'' signals (e.g. electroencephalograms), modeling complex systems that cannot be modelled mathematically, and predicting whether proposed loans will be good or fail. This paper presents a brief tutorial on neural networks and describes research on the potential applications to nuclear power plants.« less

Balance decrements are associated with age-related muscle property changes.

PubMed

Hasson, Christopher J; van Emmerik, Richard E A; Caldwell, Graham E

2014-08-01

In this study, a comprehensive evaluation of static and dynamic balance abilities was performed in young and older adults and regression analysis was used to test whether age-related variations in individual ankle muscle mechanical properties could explain differences in balance performance. The mechanical properties included estimates of the maximal isometric force capability, force-length, force-velocity, and series elastic properties of the dorsiflexors and individual plantarflexor muscles (gastrocnemius and soleus). As expected, the older adults performed more poorly on most balance tasks. Muscular maximal isometric force, optimal fiber length, tendon slack length, and velocity-dependent force capabilities accounted for up to 60% of the age-related variation in performance on the static and dynamic balance tests. In general, the plantarflexors had a stronger predictive role than the dorsiflexors. Plantarflexor stiffness was strongly related to general balance performance, particularly in quiet stance; but this effect did not depend on age. Together, these results suggest that age-related differences in balance performance are explained in part by alterations in muscular mechanical properties.

Predicting the payload capability of cable logging systems including the effect of partial suspension

Treesearch

Gary D. Falk

1981-01-01

A systematic procedure for predicting the payload capability of running, live, and standing skylines is presented. Three hand-held calculator programs are used to predict payload capability that includes the effect of partial suspension. The programs allow for predictions for downhill yarding and for yarding away from the yarder. The equations and basic principles...

Support vector regression to predict porosity and permeability: Effect of sample size

NASA Astrophysics Data System (ADS)

Al-Anazi, A. F.; Gates, I. D.

2012-02-01

Porosity and permeability are key petrophysical parameters obtained from laboratory core analysis. Cores, obtained from drilled wells, are often few in number for most oil and gas fields. Porosity and permeability correlations based on conventional techniques such as linear regression or neural networks trained with core and geophysical logs suffer poor generalization to wells with only geophysical logs. The generalization problem of correlation models often becomes pronounced when the training sample size is small. This is attributed to the underlying assumption that conventional techniques employing the empirical risk minimization (ERM) inductive principle converge asymptotically to the true risk values as the number of samples increases. In small sample size estimation problems, the available training samples must span the complexity of the parameter space so that the model is able both to match the available training samples reasonably well and to generalize to new data. This is achieved using the structural risk minimization (SRM) inductive principle by matching the capability of the model to the available training data. One method that uses SRM is support vector regression (SVR) network. In this research, the capability of SVR to predict porosity and permeability in a heterogeneous sandstone reservoir under the effect of small sample size is evaluated. Particularly, the impact of Vapnik's ɛ-insensitivity loss function and least-modulus loss function on generalization performance was empirically investigated. The results are compared to the multilayer perception (MLP) neural network, a widely used regression method, which operates under the ERM principle. The mean square error and correlation coefficients were used to measure the quality of predictions. The results demonstrate that SVR yields consistently better predictions of the porosity and permeability with small sample size than the MLP method. Also, the performance of SVR depends on both kernel function type and loss functions used.

A new method for the prediction of combustion instability

NASA Astrophysics Data System (ADS)

Flanagan, Steven Meville

This dissertation presents a new approach to the prediction of combustion instability in solid rocket motors. Previous attempts at developing computational tools to solve this problem have been largely unsuccessful, showing very poor agreement with experimental results and having little or no predictive capability. This is due primarily to deficiencies in the linear stability theory upon which these efforts have been based. Recent advances in linear instability theory by Flandro have demonstrated the importance of including unsteady rotational effects, previously considered negligible. Previous versions of the theory also neglected corrections to the unsteady flow field of the first order in the mean flow Mach number. This research explores the stability implications of extending the solution to include these corrections. Also, the corrected linear stability theory based upon a rotational unsteady flow field extended to first order in mean flow Mach number has been implemented in two computer programs developed for the Macintosh platform. A quasi one-dimensional version of the program has been developed which is based upon an approximate solution to the cavity acoustics problem. The three-dimensional program applies Greens's Function Discretization (GFD) to the solution for the acoustic mode shapes and frequency. GFD is a recently developed numerical method for finding fully three dimensional solutions for this class of problems. The analysis of complex motor geometries, previously a tedious and time consuming task, has also been greatly simplified through the development of a drawing package designed specifically to facilitate the specification of typical motor geometries. The combination of the drawing package, improved acoustic solutions, and new analysis, results in a tool which is capable of producing more accurate and meaningful predictions than have been possible in the past.

Capabilities and Contributions of Unwed Fathers

ERIC Educational Resources Information Center

Lerman, Robert I.

2010-01-01

Young, minority, and poorly educated fathers in fragile families have little capacity to support their children financially and are hard-pressed to maintain stability in raising those children. In this article, Robert Lerman examines the capabilities and contributions of unwed fathers, how their capabilities and contributions fall short of those…

A method of predicting the energy-absorption capability of composite subfloor beams

NASA Technical Reports Server (NTRS)

Farley, Gary L.

1987-01-01

A simple method of predicting the energy-absorption capability of composite subfloor beam structure was developed. The method is based upon the weighted sum of the energy-absorption capability of constituent elements of a subfloor beam. An empirical data base of energy absorption results from circular and square cross section tube specimens were used in the prediction capability. The procedure is applicable to a wide range of subfloor beam structure. The procedure was demonstrated on three subfloor beam concepts. Agreement between test and prediction was within seven percent for all three cases.

Novel surgical performance evaluation approximates Standardized Incidence Ratio with high accuracy at simple means.

PubMed

Gabbay, Itay E; Gabbay, Uri

2013-01-01

Excess adverse events may be attributable to poor surgical performance but also to case-mix, which is controlled through the Standardized Incidence Ratio (SIR). SIR calculations can be complicated, resource consuming, and unfeasible in some settings. This article suggests a novel method for SIR approximation. In order to evaluate a potential SIR surrogate measure we predefined acceptance criteria. We developed a new measure - Approximate Risk Index (ARI). "Number Needed for Event" (NNE) is the theoretical number of patients needed "to produce" one adverse event. ARI is defined as the quotient of the group of patients needed for no observed events Ge by total patients treated Ga. Our evaluation compared 2500 surgical units and over 3 million heterogeneous risk surgical patients that were induced through a computerized simulation. Surgical unit's data were computed for SIR and ARI to evaluate compliance with the predefined criteria. Approximation was evaluated by correlation analysis and performance prediction capability by Receiver Operating Characteristics (ROC) analysis. ARI strongly correlates with SIR (r(2) = 0.87, p < 0.05). ARI prediction of excessive risk revealed excellent ROC (Area Under the Curve > 0.9) 87% sensitivity and 91% specificity. ARI provides good approximation of SIR and excellent prediction capability. ARI is simple and cost-effective as it requires thorough risk evaluation of only the adverse events patients. ARI can provide a crucial screening and performance evaluation quality control tool. The ARI method may suit other clinical and epidemiological settings where relatively small fraction of the entire population is affected. Copyright © 2013 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

Lucero, E.; Russo, T. A.; Zentner, M.; May, J.; Nguy-Robertson, A. L.

2016-12-01

Reservoirs serve multiple functions and are vital for storage, electricity generation, and flood control. For many areas, traditional ground-based reservoir measurements may not be available or data dissemination may be problematic. Consistent monitoring of reservoir levels in data-poor areas can be achieved through remote sensing, providing information to researchers and the international community. Estimates of trends and relative reservoir volume can be used to identify water supply vulnerability, anticipate low power generation, and predict flood risk. Image processing with automated cloud computing provides opportunities to study multiple geographic areas in near real-time. We demonstrate the prediction capability of a cloud environment for identifying water trends at reservoirs in the US, and then apply the method to data-poor areas in North Korea, Iran, Azerbaijan, Zambia, and India. The Google Earth Engine cloud platform hosts remote sensing data and can be used to automate reservoir level estimation with multispectral imagery. We combine automated cloud-based analysis from Landsat image classification to identify reservoir surface area trends and radar altimetry to identify reservoir level trends. The study estimates water level trends using three years of data from four domestic reservoirs to validate the remote sensing method, and five foreign reservoirs to demonstrate the method application. We report correlations between ground-based reservoir level measurements in the US and our remote sensing methods, and correlations between the cloud analysis and altimetry data for reservoirs in data-poor areas. The availability of regular satellite imagery and an automated, near real-time application method provides the necessary datasets for further temporal analysis, reservoir modeling, and flood forecasting. All statements of fact, analysis, or opinion are those of the author and do not reflect the official policy or position of the Department of Defense or any of its components or the U.S. Government

Unfavorable polysomnographic sleep patterns predict poor sleep and poor psychological functioning 3 years later in patients with restless legs syndrome.

PubMed

Brand, Serge; Beck, Johannes; Hatzinger, Martin; Savic, Mirjana; Holsboer-Trachsler, Edith

2011-01-01

Amongst the variety of disorders affecting sleep, restless legs syndrome (RLS) merits particular attention. Little is known about long-term outcomes for sleep or psychological functioning following a diagnosis of RLS. The aim of the present study was thus to evaluate sleep and psychological functioning at a 3-year follow-up and based on polysomnographic measurements. Thirty-eight patients (18 female and 20 male patients; mean age: 56.06, SD = 12.07) with RLS and sleep electroencephalographic recordings were followed-up 33 months later. Participants completed a series of self-rating questionnaires related to sleep and psychological functioning. Additionally, they completed a sleep log for 7 consecutive days. Age, male gender, increased light sleep (S1, S2) and sleep onset latency, along with low sleep efficiency, predicted psychological functioning and sleep 33 months later. Specifically, sleep fragmentation predicted poor psychological functioning, and both sleep fragmentation and light sleep predicted poor sleep. In patients with RLS, irrespective of medication or duration of treatment, poor objective sleep patterns at diagnosis predicted both poor psychological functioning and poor sleep about 3 years after diagnosis. The pattern of results suggests the need for more thorough medical and psychotherapeutic treatment and monitoring of patients with RLS. © 2010 S. Karger AG, Basel.

Validation of the SEPHIS Program for the Modeling of the HM Process

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

Kyser, E.A.

The SEPHIS computer program is currently being used to evaluate the effect of all process variables on the criticality safety of the HM 1st Uranium Cycle process in H Canyon. The objective of its use has three main purposes. (1) To provide a better technical basis for those process variables that do not have any realistic effect on the criticality safety of the process. (2) To qualitatively study those conditions that have been previously recognized to affect the nuclear safety of the process or additional conditions that modeling has indicated may pose a criticality safety issue. (3) To judge themore » adequacy of existing or future neutron monitors locations in the detection of the initial stages of reflux for specific scenarios.Although SEPHIS generally over-predicts the distribution of uranium to the organic phase, it is a capable simulation tool as long as the user recognizes its biases and takes special care when using the program for scenarios where the prediction bias is non-conservative. The temperature coefficient used by SEPHIS is poor at predicting effect of temperature on uranium extraction for the 7.5 percent TBP used in the HM process. Therefore, SEPHIS should not be used to study temperature related scenarios. However, within normal operating temperatures when other process variables are being studied, it may be used. Care must be is given to understanding the prediction bias and its effect on any conclusion for the particular scenario that is under consideration. Uranium extraction with aluminum nitrate is over-predicted worse than for nitric acid systems. However, the extraction section of the 1A bank has sufficient excess capability that these errors, while relatively large, still allow SEPHIS to be used to develop reasonable qualitative assessments for reflux scenarios. However, high losses to the 1AW stream cannot be modeled by SEPHIS.« less

Longitudinal Stability and Predictors of Poor Oral Comprehenders and Poor Decoders

PubMed Central

Elwér, Åsa; Keenan, Janice M.; Olson, Richard K.; Byrne, Brian; Samuelsson, Stefan

2012-01-01

Two groups of 4th grade children were selected from a population sample (N= 926) to either be Poor Oral Comprehenders (poor oral comprehension but normal word decoding), or Poor Decoders (poor decoding but normal oral comprehension). By examining both groups in the same study with varied cognitive and literacy predictors, and examining them both retrospectively and prospectively, we could assess how distinctive and stable the predictors of each deficit are. Predictors were assessed retrospectively at preschool, at the end of kindergarten, 1st, and 2nd grades. Group effects were significant at all test occasions, including those for preschool vocabulary (worse in poor oral comprehenders) and rapid naming (RAN) (worse in poor decoders). Preschool RAN and Vocabulary prospectively predicted grade 4 group membership (77–79% correct classification) within the selected samples. Reselection in preschool of at-risk poor decoder and poor oral comprehender subgroups based on these variables led to significant but relatively weak prediction of subtype membership at grade 4. Implications of the predictive stability of our results for identification and intervention of these important subgroups are discussed. PMID:23528975

Constitutive Equation with Varying Parameters for Superplastic Flow Behavior

NASA Astrophysics Data System (ADS)

Guan, Zhiping; Ren, Mingwen; Jia, Hongjie; Zhao, Po; Ma, Pinkui

2014-03-01

In this study, constitutive equations for superplastic materials with an extra large elongation were investigated through mechanical analysis. From the view of phenomenology, firstly, some traditional empirical constitutive relations were standardized by restricting some strain paths and parameter conditions, and the coefficients in these relations were strictly given new mechanical definitions. Subsequently, a new, general constitutive equation with varying parameters was theoretically deduced based on the general mechanical equation of state. The superplastic tension test data of Zn-5%Al alloy at 340 °C under strain rates, velocities, and loads were employed for building a new constitutive equation and examining its validity. Analysis results indicated that the constitutive equation with varying parameters could characterize superplastic flow behavior in practical superplastic forming with high prediction accuracy and without any restriction of strain path or deformation condition, showing good industrial or scientific interest. On the contrary, those empirical equations have low prediction capabilities due to constant parameters and poor applicability because of the limit of special strain path or parameter conditions based on strict phenomenology.

Ford Class Aircraft Carrier: Poor Outcomes Are the Predictable Consequences of the Prevalent Acquisition Culture

DTIC Science & Technology

2015-10-01

FORD CLASS AIRCRAFT CARRIER Poor Outcomes Are the Predictable Consequences of the Prevalent Acquisition Culture...2. REPORT TYPE 3. DATES COVERED 00-00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Ford Class Aircraft Carrier: Poor Outcomes Are the Predictable...This Study The Navy set ambitious goals for the Ford -class program, including an array of new technologies and design features that were intended

Self-care behavior of type 2 diabetes mellitus patients in Bandar Abbas in 2015.

PubMed

Karimi, Fatemeh; Abedini, Sedigheh; Mohseni, Shokrollah

2017-11-01

Diabetes self-care helps to control the blood sugar which, in turn, results in a better state of health. However, more than 50% of diabetic patients do not have self-care capabilities. To determine type 2 diabetes self-care capabilities among patients visiting a Bandar Abbas diabetes clinic in 2016. The present descriptive-analytical research was of a cross-sectional type. The sample was comprised of 120 patients afflicted with type 2 diabetes, who had been selected through the simple randomized sampling method. The data collection instrument was a questionnaire comprised of two sections: demographic information, and a summary of patients' diabetes self-care activities. A 7-point Likert scale was used for the rating. The final score would be interpreted as any of the three levels: good (acceptable) (75-100), moderate (50-74) and poor (below 50). The data entered SPSS version 18.0 for the required statistical analyses. The mean age of the sample was 51.88±10.12 years. Of the 120 subjects, 86 were female (71.7%) and 34 were male (28.3%). The findings revealed that the self-care capability of 83 subjects (69.2%) was poor; capability of 28 subjects was moderate (23.3%) and the same score of good/acceptable in 9 subjects (7.5%). The results of the present research indicate that a large number of diabetic patients have a poor self-care capability. Due to the key role of such activities in a diabetic patient's life, it is suggested to include educational programs to increase the level of self-care capabilities among these patients.

Testing the hindlimb-strength hypothesis: non-aerial locomotion by Chiroptera is not constrained by the dimensions of the femur or tibia.

PubMed

Riskin, Daniel K; Bertram, John E A; Hermanson, John W

2005-04-01

In the evolution of flight bats appear to have suffered a trade-off; they have become poor crawlers relative to terrestrial mammals. Capable walking does occur in a few disparate taxa, including the vampire bats, but the vast majority of bats are able only to shuffle awkwardly along the ground, and the morphological bases of differences in crawling ability are not currently understood. One widely cited hypothesis suggests that the femora of most bats are too weak to withstand the compressive forces that occur during terrestrial locomotion, and that the vampire bats can walk because they possess more robust hindlimb skeletons. We tested a prediction of the hindlimb-strength hypothesis: that during locomotion, the forces produced by the hindlimbs of vampire bats should be larger than those produced by the legs of poorly crawling bats. Using force plates we compared the hindlimb forces produced by two species of vampire bats that walk well, Desmodus rotundus (N=8) and Diaemus youngi (N=2), to the hindlimb forces produced during over-ground shuffling by a similarly sized bat that is a poor walker (Pteronotus parnellii; N=6). Peak hindlimb forces produced by P. parnellii were larger (ANOVA; P<0.05; N=65) and more variable (93.5+/-36.6% body weight, mean +/- s.d.) than those of D. rotundus (69.3+/-8.1%) or D. youngi (75.0+/-6.2%). Interestingly, the vertical components of peak force were equivalent among species (P>0.6), indicating similar roles for support of body weight by the hindlimbs in the three species. We also used a simple engineering model of bending stress to evaluate the support capabilities of the hindlimb skeleton from the dimensions of 113 museum specimens in 50 species. We found that the hindlimb bones of vampires are not built to withstand larger forces than those of species that crawl poorly. Our results show that the legs of poorly crawling bats should be able to withstand the forces produced during coordinated crawling of the type used by the agile vampires, and this indicates that some mechanism other than hindlimb bone thickness, such as myology of the pectoral girdle, limits the ability of most bats to crawl.

Validation of an Algorithm to Predict the Likelihood of an 8/8 HLA-Matched Unrelated Donor at Search Initiation.

PubMed

Davis, Eric; Devlin, Sean; Cooper, Candice; Nhaissi, Melissa; Paulson, Jennifer; Wells, Deborah; Scaradavou, Andromachi; Giralt, Sergio; Papadopoulos, Esperanza; Kernan, Nancy A; Byam, Courtney; Barker, Juliet N

2018-05-01

A strategy to rapidly determine if a matched unrelated donor (URD) can be secured for allograft recipients is needed. We sought to validate the accuracy of (1) HapLogic match predictions and (2) a resultant novel Search Prognosis (SP) patient categorization that could predict 8/8 HLA-matched URD(s) likelihood at search initiation. Patient prognosis categories at search initiation were correlated with URD confirmatory typing results. HapLogic-based SP categorizations accurately predicted the likelihood of an 8/8 HLA-match in 830 patients (1530 donors tested). Sixty percent of patients had 8/8 URD(s) identified. Patient SP categories (217 very good, 104 good, 178 fair, 33 poor, 153 very poor, 145 futile) were associated with a marked progressive decrease in 8/8 URD identification and transplantation. Very good to good categories were highly predictive of identifying and receiving an 8/8 URD regardless of ancestry. Europeans in fair/poor categories were more likely to identify and receive an 8/8 URD compared with non-Europeans. In all ancestries very poor and futile categories predicted no 8/8 URDs. HapLogic permits URD search results to be predicted once patient HLA typing and ancestry is obtained, dramatically improving search efficiency. Poor, very poor, andfutile searches can be immediately recognized, thereby facilitating prompt pursuit of alternative donors. Copyright © 2017 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

On the Conditioning of Machine-Learning-Assisted Turbulence Modeling

NASA Astrophysics Data System (ADS)

Wu, Jinlong; Sun, Rui; Wang, Qiqi; Xiao, Heng

2017-11-01

Recently, several researchers have demonstrated that machine learning techniques can be used to improve the RANS modeled Reynolds stress by training on available database of high fidelity simulations. However, obtaining improved mean velocity field remains an unsolved challenge, restricting the predictive capability of current machine-learning-assisted turbulence modeling approaches. In this work we define a condition number to evaluate the model conditioning of data-driven turbulence modeling approaches, and propose a stability-oriented machine learning framework to model Reynolds stress. Two canonical flows, the flow in a square duct and the flow over periodic hills, are investigated to demonstrate the predictive capability of the proposed framework. The satisfactory prediction performance of mean velocity field for both flows demonstrates the predictive capability of the proposed framework for machine-learning-assisted turbulence modeling. With showing the capability of improving the prediction of mean flow field, the proposed stability-oriented machine learning framework bridges the gap between the existing machine-learning-assisted turbulence modeling approaches and the demand of predictive capability of turbulence models in real applications.

A Review and Analysis of Remote Sensing Capability for Air Quality Measurements as a Potential Decision Support Tool Conducted by the NASA DEVELOP Program

NASA Technical Reports Server (NTRS)

Ross, A.; Richards, A.; Keith, K.; Frew, C.; Boseck, J.; Sutton, S.; Watts, C.; Rickman, D.

2007-01-01

This project focused on a comprehensive utilization of air quality model products as decision support tools (DST) needed for public health applications. A review of past and future air quality measurement methods and their uncertainty, along with the relationship of air quality to national and global public health, is vital. This project described current and future NASA satellite remote sensing and ground sensing capabilities and the potential for using these sensors to enhance the prediction, prevention, and control of public health effects that result from poor air quality. The qualitative uncertainty of current satellite remotely sensed air quality, the ground-based remotely sensed air quality, the air quality/public health model, and the decision making process is evaluated in this study. Current peer-reviewed literature suggests that remotely sensed air quality parameters correlate well with ground-based sensor data. A satellite remote-sensed and ground-sensed data complement is needed to enhance the models/tools used by policy makers for the protection of national and global public health communities

Application of Machine Learning to Predict Dietary Lapses During Weight Loss.

PubMed

Goldstein, Stephanie P; Zhang, Fengqing; Thomas, John G; Butryn, Meghan L; Herbert, James D; Forman, Evan M

2018-05-01

Individuals who adhere to dietary guidelines provided during weight loss interventions tend to be more successful with weight control. Any deviation from dietary guidelines can be referred to as a "lapse." There is a growing body of research showing that lapses are predictable using a variety of physiological, environmental, and psychological indicators. With recent technological advancements, it may be possible to assess these triggers and predict dietary lapses in real time. The current study sought to use machine learning techniques to predict lapses and evaluate the utility of combining both group- and individual-level data to enhance lapse prediction. The current study trained and tested a machine learning algorithm capable of predicting dietary lapses from a behavioral weight loss program among adults with overweight/obesity (n = 12). Participants were asked to follow a weight control diet for 6 weeks and complete ecological momentary assessment (EMA; repeated brief surveys delivered via smartphone) regarding dietary lapses and relevant triggers. WEKA decision trees were used to predict lapses with an accuracy of 0.72 for the group of participants. However, generalization of the group algorithm to each individual was poor, and as such, group- and individual-level data were combined to improve prediction. The findings suggest that 4 weeks of individual data collection is recommended to attain optimal model performance. The predictive algorithm could be utilized to provide in-the-moment interventions to prevent dietary lapses and therefore enhance weight losses. Furthermore, methods in the current study could be translated to other types of health behavior lapses.

Circulating tumor cells (CTCs) in malignant pleural mesothelioma (MPM).

PubMed

Yoneda, Kazue; Tanaka, Fumihiro; Kondo, Nobuyuki; Hashimoto, Masaki; Takuwa, Teruhisa; Matsumoto, Seiji; Okumura, Yoshitomo; Tsubota, Noriaki; Sato, Ayuko; Tsujimura, Tohru; Kuribayashi, Kozo; Fukuoka, Kazuya; Tabata, Chiharu; Nakano, Takashi; Hasegawa, Seiki

2014-12-01

To investigate the diagnostic and prognostic value of circulating tumor cells (CTCs), a potential surrogate of micrometastasis, in malignant pleural mesothelioma (MPM). We prospectively evaluated CTCs in 7.5 mL of peripheral blood sampled from patients with a suspicion of MPM. A semiautomated system was used to capture CTCs with an antibody against the epithelial cell adhesion molecule. Of 136 eligible patients, 32 were finally diagnosed with nonmalignant diseases (NM), and 104 had MPM. CTCs were detected in 32.7 % (34 of 104) of MPM patients but in only 9.4 % (3 of 32) of NM patients (P = 0.011). The CTC count was significantly higher in MPM patients than in NM patients (P = 0.007), and a receiver operating characteristic (ROC) curve analysis showed an insufficient capability of the CTC test in discrimination between MPM and NM, with an area under ROC curve of 0.623 (95 % confidence interval, 0.523-0.723; P = 0.036). Among MPM patients, CTCs were more frequently detected in patients with epithelioid subtype (39.7 %, 31 of 78) than in those with nonepithelioid subtypes (11.5 %, 3 of 26; P = 0.016). Positive CTCs (CTC count ≥ 1) were a significant factor to predict a poor prognosis among epithelioid patients (median overall survival, 22.3 months for positive CTCs vs. 12.6 months for negative CTCs; P = 0.004) and not in nonepithelioid patients (P = 0.649). A multivariate analysis showed that positive CTCs were a significant and independent factor to predict a poor prognosis (hazard ratio, 2.904; 95 % confidence interval, 1.530-5.511; P = 0.001) for epithelioid MPM patients. CTC was a promising marker in diagnosis and prediction of prognosis in MPM, especially in epithelioid MPM.

Longitudinal Analysis of Vaginal Microbiome Dynamics in Women with Recurrent Bacterial Vaginosis: Recognition of the Conversion Process

PubMed Central

Lambert, Janet A.; John, Susan; Sobel, Jack D.; Akins, Robert A.

2013-01-01

Bacterial vaginosis (BV) affects ∼30% of women of reproductive age, has a high rate of recurrence, and is associated with miscarriage, preterm birth, and increased risk of acquiring other sexually transmitted infections, including HIV-1. Little is known of the daily changes in the vaginal bacterial composition as it progresses from treatment to recurrence, or whether any of these might be useful in its prediction or an understanding of its causes. We used phylogenetic branch-inclusive quantitative PCR (PB-qPCR) and Lactobacillus blocked/unblocked qPCR (Lb-qPCR) to characterize longitudinal changes in the vaginal microbiota in sequential vaginal self-swabs from five women with recurrent BV, from diagnosis through remission to recurrence. Both patients with acute BV samples dominated by G. vaginalis recurred during the study with similar profiles, whereas the three patients with acute BV samples dominated by other anaerobes did not recur or recurred to an intermediate Nugent score. L. iners dominated remission phases, with intermittent days of abnormal microbial profiles typically associated with menses. The exception was a newly discovered phenomenon, a sustained period of abnormal profiles, termed conversion, which preceded symptomatic acute BV. Species known to have antagonistic activity towards Lactobacillus were detected in pre-conversion samples, possibly contributing to the decline in Lactobacillus. Lb-qPCR scores define two categories of response in the initial post-treatment visit samples; scores <5 may correspond with poor response to treatment or rapid recurrence, whereas scores >8 may predict delayed or no recurrence. Amsel criteria or Nugent scores did not have this potential predictive capability. Larger studies are warranted to evaluate the prognostic potential of detecting conversion and poor Lb-qPCR scores at the post-treatment visit of recurrent BV patients. PMID:24376552

A Method to Predict the Thickness of Poorly-Bonded Material Along Spray and Spray-Layer Boundaries in Cold Spray Deposition

NASA Astrophysics Data System (ADS)

Li, Yangfan; Hamada, Yukitaka; Otobe, Katsunori; Ando, Teiichi

2017-02-01

Multi-traverse CS provides a unique means for the production of thick coatings and bulk materials from powders. However, the material along spray and spray-layer boundaries is often poorly bonded as it is laid by the leading and trailing peripheries of the spray that carry powder particles with insufficient kinetic energy. For the same reason, the splats in the very first layer deposited on the substrate may not be bonded well either. A mathematical spray model was developed based on an axisymmetric Gaussian mass flow rate distribution and a stepped deposition yield to predict the thickness of such poorly-bonded layers in multi-traverse CS deposition. The predicted thickness of poorly-bonded layers in a multi-traverse Cu coating falls in the range of experimental values. The model also predicts that the material that contains poorly bonded splats could exceed 20% of the total volume of the coating.

Specific regions of the brain are capable of fructose metabolism.

PubMed

Oppelt, Sarah A; Zhang, Wanming; Tolan, Dean R

2017-02-15

High fructose consumption in the Western diet correlates with disease states such as obesity and metabolic syndrome complications, including type II diabetes, chronic kidney disease, and non-alcoholic fatty acid liver disease. Liver and kidneys are responsible for metabolism of 40-60% of ingested fructose, while the physiological fate of the remaining fructose remains poorly understood. The primary metabolic pathway for fructose includes the fructose-transporting solute-like carrier transport proteins 2a (SLC2a or GLUT), including GLUT5 and GLUT9, ketohexokinase (KHK), and aldolase. Bioinformatic analysis of gene expression encoding these proteins (glut5, glut9, khk, and aldoC, respectively) identifies other organs capable of this fructose metabolism. This analysis predicts brain, lymphoreticular tissue, placenta, and reproductive tissues as possible additional organs for fructose metabolism. While expression of these genes is highest in liver, the brain is predicted to have expression levels of these genes similar to kidney. RNA in situ hybridization of coronal slices of adult mouse brains validate the in silico expression of glut5, glut9, khk, and aldoC, and show expression across many regions of the brain, with the most notable expression in the cerebellum, hippocampus, cortex, and olfactory bulb. Dissected samples of these brain regions show KHK and aldolase enzyme activity 5-10 times the concentration of that in liver. Furthermore, rates of fructose oxidation in these brain regions are 15-150 times that of liver slices, confirming the bioinformatics prediction and in situ hybridization data. This suggests that previously unappreciated regions across the brain can use fructose, in addition to glucose, for energy production. Copyright © 2016 Elsevier B.V. All rights reserved.

Specific regions of the brain are capable of fructose metabolism

PubMed Central

Oppelt, Sarah A.; Zhang, Wanming; Tolan, Dean R.

2017-01-01

High fructose consumption in the Western diet correlates with disease states such as obesity and metabolic syndrome complications, including type II diabetes, chronic kidney disease, and nonalcoholic fatty acid liver disease. Liver and kidneys are responsible for metabolism of 40–60% of ingested fructose, while the physiological fate of the remaining fructose remains poorly understood. The primary metabolic pathway for fructose includes the fructose-transporting solute-like carrier transport proteins 2a (SLC2a or GLUT), including GLUT5 and GLUT9, ketohexokinase (KHK), and aldolase. Bioinformatic analysis of gene expression encoding these proteins (glut5, glut9, khk, and aldoC, respectively) identifies other organs capable of this fructose metabolism. This analysis predicts brain, lymphoreticular tissue, placenta, and reproductive tissues as possible additional organs for fructose metabolism. While expression of these genes is highest in liver, the brain is predicted to have expression levels of these genes similar to kidney. RNA in situ hybridization of coronal slices of adult mouse brains validate the in silico expression of glut5, glut9, khk, and aldoC, and show expression across many regions of the brain, with the most notable expression in the cerebellum, hippocampus, cortex, and olfactory bulb. Dissected samples of these brain regions show KHK and aldolase enzyme activity 5–10 times the concentration of that in liver. Furthermore, rates of fructose oxidation in these brain regions are 15–150 times that of liver slices, confirming the bioinformatics prediction and in situ hybridization data. This suggests that previously unappreciated regions across the brain can use fructose, in addition to glucose, for energy production. PMID:28034722

Enumerating bone marrow blasts from nonerythroid cellularity improves outcome prediction in myelodysplastic syndromes and permits a better definition of the intermediate risk category of the Revised International Prognostic Scoring System (IPSS-R).

PubMed

Calvo, Xavier; Arenillas, Leonor; Luño, Elisa; Senent, Leonor; Arnan, Montserrat; Ramos, Fernando; Pedro, Carme; Tormo, Mar; Montoro, Julia; Díez-Campelo, María; Blanco, María Laura; Arrizabalaga, Beatriz; Xicoy, Blanca; Bonanad, Santiago; Jerez, Andrés; Nomdedeu, Meritxell; Ferrer, Ana; Sanz, Guillermo F; Florensa, Lourdes

2017-07-01

The Revised International Prognostic Scoring System (IPSS-R) has been recognized as the score with the best outcome prediction capability in MDS, but this brought new concerns about the accurate prognostication of patients classified into the intermediate risk category. The correct enumeration of blasts is essential in prognostication of MDS. Recent data evidenced that considering blasts from nonerythroid cellularity (NECs) improves outcome prediction in the context of IPSS and WHO classification. We assessed the percentage of blasts from total nucleated cells (TNCs) and NECs in 3924 MDS patients from the GESMD, 498 of whom were MDS with erythroid predominance (MDS-E). We assessed if calculating IPSS-R by enumerating blasts from NECs improves prognostication of MDS. Twenty-four percent of patients classified into the intermediate category were reclassified into higher-risk categories and showed shorter overall survival (OS) and time to AML evolution than those who remained into the intermediate one. Likewise, a better distribution of patients was observed, since lower-risk patients showed longer survivals than previously whereas higher-risk ones maintained the outcome expected in this poor prognostic group (median OS < 20 months). Furthermore, our approach was particularly useful for detecting patients at risk of dying with AML. Regarding MDS-E, 51% patients classified into the intermediate category were reclassified into higher-risk ones and showed shorter OS and time to AML. In this subgroup of MDS, IPSS-R was capable of splitting our series in five groups with significant differences in OS only when blasts were assessed from NECs. In conclusion, our easy-applicable approach improves prognostic assessment of MDS patients. © 2017 Wiley Periodicals, Inc.

Biome-scale nitrogen fixation strategies selected by climatic constraints on nitrogen cycle.

PubMed

Sheffer, Efrat; Batterman, Sarah A; Levin, Simon A; Hedin, Lars O

2015-11-23

Dinitrogen fixation by plants (in symbiosis with root bacteria) is a major source of new nitrogen for land ecosystems(1). A long-standing puzzle(2) is that trees capable of nitrogen fixation are abundant in nitrogen-rich tropical forests, but absent or restricted to early successional stages in nitrogen-poor extra-tropical forests. This biome-scale pattern presents an evolutionary paradox(3), given that the physiological cost(4) of nitrogen fixation predicts the opposite pattern: fixers should be out-competed by non-fixers in nitrogen-rich conditions, but competitively superior in nitrogen-poor soils. Here we evaluate whether this paradox can be explained by the existence of different fixation strategies in tropical versus extra-tropical trees: facultative fixers (capable of downregulating fixation(5,6) by sanctioning mutualistic bacteria(7)) are common in the tropics, whereas obligate fixers (less able to downregulate fixation) dominate at higher latitudes. Using a game-theoretic approach, we assess the ecological and evolutionary conditions under which these fixation strategies emerge, and examine their dependence on climate-driven differences in the nitrogen cycle. We show that in the tropics, transient soil nitrogen deficits following disturbance and rapid tree growth favour a facultative strategy and the coexistence of fixers and non-fixers. In contrast, sustained nitrogen deficits following disturbance in extra-tropical forests favour an obligate fixation strategy, and cause fixers to be excluded in late successional stages. We conclude that biome-scale differences in the abundance of nitrogen fixers can be explained by the interaction between individual plant strategies and climatic constraints on the nitrogen cycle over evolutionary time.

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

NASA Astrophysics Data System (ADS)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

Amoxapine Demonstrates Incomplete Inhibition of β-Glucuronidase Activity from Human Gut Microbiota.

PubMed

Yang, Wei; Wei, Bin; Yan, Ru

2018-01-01

Amoxapine has been demonstrated to be a potent inhibitor of Escherichia coli β-glucuronidase. This study aims to explore the factors causing unsatisfactory efficacy of amoxapine in alleviating CPT-11-induced gastrointestinal toxicity in mice and to predict the outcomes in humans. Amoxapine (100 µM) exhibited poor and varied inhibition on β-glucuronidase activity in gut microbiota from 10 healthy individuals and their pool (pool, 11.9%; individuals, 3.6%-54.4%) with IC 50 >100 µM and potent inhibition toward E. coli β-glucuronidase (IC 50 = 0.34 µM). p-Nitrophenol formation from p-nitrophenyl-β-D-glucuronide by pooled and individual gut microbiota fitted classical Michaelis-Menten kinetics, showing similar affinity (K m = 113-189 µM) but varied catalytic capability (V max = 53-556 nmol/h/mg). Interestingly, amoxapine showed distinct inhibitory effects (8.7%-100%) toward β-glucuronidases of 13 bacterial isolates (including four Enterococcus, three Streptococcus, two Escherichia, and two Staphylococcus strains; gus genes belonging to OTU1, 2 or 21) regardless of their genetic similarity or bacterial origin. In addition, amoxapine inhibited the growth of pooled and individual gut microbiota at a high concentration (6.3%-30.8%, 200 µM). Taken together, these findings partly explain the unsatisfactory efficacy of amoxapine in alleviating CPT-11-induced toxicity and predict a poor outcome of β-glucuronidase inhibition in humans, highlighting the necessity of using a human gut microbiota community for drug screening.

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.

A mechanistic model for electricity consumption on dairy farms: definition, validation, and demonstration.

PubMed

Upton, J; Murphy, M; Shalloo, L; Groot Koerkamp, P W G; De Boer, I J M

2014-01-01

Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat tariff. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Does the sensorimotor system minimize prediction error or select the most likely prediction during object lifting?

PubMed Central

McGregor, Heather R.; Pun, Henry C. H.; Buckingham, Gavin; Gribble, Paul L.

2016-01-01

The human sensorimotor system is routinely capable of making accurate predictions about an object's weight, which allows for energetically efficient lifts and prevents objects from being dropped. Often, however, poor predictions arise when the weight of an object can vary and sensory cues about object weight are sparse (e.g., picking up an opaque water bottle). The question arises, what strategies does the sensorimotor system use to make weight predictions when one is dealing with an object whose weight may vary? For example, does the sensorimotor system use a strategy that minimizes prediction error (minimal squared error) or one that selects the weight that is most likely to be correct (maximum a posteriori)? In this study we dissociated the predictions of these two strategies by having participants lift an object whose weight varied according to a skewed probability distribution. We found, using a small range of weight uncertainty, that four indexes of sensorimotor prediction (grip force rate, grip force, load force rate, and load force) were consistent with a feedforward strategy that minimizes the square of prediction errors. These findings match research in the visuomotor system, suggesting parallels in underlying processes. We interpret our findings within a Bayesian framework and discuss the potential benefits of using a minimal squared error strategy. NEW & NOTEWORTHY Using a novel experimental model of object lifting, we tested whether the sensorimotor system models the weight of objects by minimizing lifting errors or by selecting the statistically most likely weight. We found that the sensorimotor system minimizes the square of prediction errors for object lifting. This parallels the results of studies that investigated visually guided reaching, suggesting an overlap in the underlying mechanisms between tasks that involve different sensory systems. PMID:27760821

The Hurricane-Flood-Landslide Continuum

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Burkardt, Nina; Golden, Joseph H.; Halverson, Jeffrey B.; Huffman, George J.; Larsen, Matthew C.; McGinley, John A.; Updike, Randall G.; Verdin, James P.; Wieczorek, Gerald F.

2005-01-01

In August 2004, representatives from NOAA, NASA, the USGS, and other government agencies convened in San Juan, Puerto Rim for a workshop to discuss a proposed research project called the Hurricane-Flood-Landslide Continuum (HFLC). The essence of the HFLC is to develop and integrate tools across disciplines to enable the issuance of regional guidance products for floods and landslides associated with major tropical rain systems, with sufficient lead time that local emergency managers can protect vulnerable populations and infrastructure. All three lead agencies are independently developing precipitation-flood-debris flow forecasting technologies, and all have a history of work on natural hazards both domestically and overseas. NOM has the capability to provide tracking and prediction of storm rainfall, trajectory and landfall and is developing flood probability and magnTtude capabilities. The USGS has the capability to evaluate the ambient stability of natural and man-made landforms, to assess landslide susceptibilities for those landforms, and to establish probabilities for initiation of landslides and debris flows. Additionally, the USGS has well-developed operational capacity for real-time monitoring and reporting of streamflow across distributed networks of automated gaging stations (http://water.usgs.gov/waterwatch/). NASA has the capability to provide sophisticated algorithms for satellite remote sensing of precipitation, land use, and in the future, soil moisture. The Workshop sought to initiate discussion among three agencies regarding their specific and highly complimentary capabilities. The fundamental goal of the Workshop was to establish a framework that will leverage the strengths of each agency. Once a prototype system is developed for example, in relatively data-rich Puerto Rim, it could be adapted for use in data-poor, low-infrastructure regions such as the Dominican Republic or Haiti. This paper provides an overview of the Workshop s goals, presentations and recommendations with respect to the development of the HFLC.

OBSERVATIONS OF BINARY STARS WITH THE DIFFERENTIAL SPECKLE SURVEY INSTRUMENT. V. TOWARD AN EMPIRICAL METAL-POOR MASS–LUMINOSITY RELATION

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

Horch, Elliott P.; Van Altena, William F.; Demarque, Pierre

2015-05-15

In an effort to better understand the details of the stellar structure and evolution of metal-poor stars, the Gemini North telescope was used on two occasions to take speckle imaging data of a sample of known spectroscopic binary stars and other nearby stars in order to search for and resolve close companions. The observations were obtained using the Differential Speckle Survey Instrument, which takes data in two filters simultaneously. The results presented here are of 90 observations of 23 systems in which one or more companions was detected, and six stars where no companion was detected to the limit ofmore » the camera capabilities at Gemini. In the case of the binary and multiple stars, these results are then further analyzed to make first orbit determinations in five cases, and orbit refinements in four other cases. The mass information is derived, and since the systems span a range in metallicity, a study is presented that compares our results with the expected trend in total mass as derived from the most recent Yale isochrones as a function of metal abundance. These data suggest that metal-poor main-sequence stars are less massive at a given color than their solar-metallicity analogues in a manner consistent with that predicted from the theory.« less

Prognostic value of resident clinical performance ratings.

PubMed

Williams, Reed G; Dunnington, Gary L

2004-10-01

This study investigated the concurrent and predictive validity of end-of-rotation (EOR) clinical performance ratings. Surgeon EOR ratings of residents were collected and compared with end-of-year (EOY) progress decisions and to EOR and EOY confidential judgments of resident ability to provide patient care without direct supervision. Eighty percent to 85% of EOR ratings were Excellent or Very Good. Five percent or fewer were Fair or Poor. Almost all residents receiving Excellent or Very Good EOR ratings also received positive EOR judgments about ability to provide patient care without direct supervision. Residents rated Fair or Poor received negative EOR judgments about ability to provide patient care without direct supervision. As the cumulative percent of Good, Fair, and Poor EOR ratings increased, the number of residents promoted without stipulations at the end of the year decreased and the percentage of faculty members who judged the residents capable of providing effective patient care without direct supervision at the end of the year declined. All residents receiving 40% or more EOR ratings below Very Good had stipulations associated with their promotion. Despite use of descriptive anchors on the scale, clinical performance ratings have no direct meaning. Their meaning needs to be established in the same manner as is done in setting normal values for diagnostic tests, ie, by establishing the relationship between EOR ratings and practice outcomes.

Menstrual cycle length: a surrogate measure of reproductive health capable of improving the accuracy of biochemical/sonographical ovarian reserve test in estimating the reproductive chances of women referred to ART.

PubMed

Gizzo, Salvatore; Andrisani, Alessandra; Noventa, Marco; Quaranta, Michela; Esposito, Federica; Armanini, Decio; Gangemi, Michele; Nardelli, Giovanni B; Litta, Pietro; D'Antona, Donato; Ambrosini, Guido

2015-04-10

Aim of the study was to investigate whether menstrual cycle length may be considered as a surrogate measure of reproductive health, improving the accuracy of biochemical/sonographical ovarian reserve test in estimating the reproductive chances of women referred to ART. A retrospective-observational-study in Padua' public tertiary level Centre was conducted. A total of 455 normo-ovulatory infertile women scheduled for their first fresh non-donor IVF/ICSI treatment. The mean menstrual cycle length (MCL) during the preceding 6 months was calculated by physicians on the basis of information contained in our electronic database (first day of menstrual cycle collected every month by telephonic communication by single patients). We evaluated the relations between MCL, ovarian response to stimulation protocol, oocytes fertilization ratio, ovarian sensitivity index (OSI) and pregnancy rate in different cohorts of patients according to the class of age and the estimated ovarian reserve. In women younger than 35 years, MCL over 31 days may be associated with an increased risk of OHSS and with a good OSI. In women older than 35 years, and particularly than 40 years, MCL shortening may be considered as a marker of ovarian aging and may be associated with poor ovarian response, low OSI and reduced fertilization rate. When AMH serum value is lower than 1.1 ng/ml in patients older than 40 years, MCL may help Clinicians discriminate real from expected poor responders. Considering the pool of normoresponders, MCL was not correlated with pregnancy rate while a positive association was found with patients' age. MCL diary is more predictive than chronological age in estimating ovarian biological age and response to COH and it is more predictive than AMH in discriminating expected from real poor responders. In women older than 35 years MCL shortening may be considered as a marker of ovarian aging while chronological age remains most accurate parameter in predicting pregnancy.

Neurophysiological prediction of neurological good and poor outcome in post-anoxic coma.

PubMed

Grippo, A; Carrai, R; Scarpino, M; Spalletti, M; Lanzo, G; Cossu, C; Peris, A; Valente, S; Amantini, A

2017-06-01

Investigation of the utility of association between electroencephalogram (EEG) and somatosensory-evoked potentials (SEPs) for the prediction of neurological outcome in comatose patients resuscitated after cardiac arrest (CA) treated with therapeutic hypothermia, according to different recording times after CA. Glasgow Coma Scale, EEG and SEPs performed at 12, 24 and 48-72 h after CA were assessed in 200 patients. Outcome was evaluated by Cerebral Performance Category 6 months after CA. Within 12 h after CA, grade 1 EEG predicted good outcome and bilaterally absent (BA) SEPs predicted poor outcome. Because grade 1 EEG and BA-SEPs were never found in the same patient, the recording of both EEG and SEPs allows us to correctly prognosticate a greater number of patients with respect to the use of a single test within 12 h after CA. At 48-72 h after CA, both grade 2 EEG and BA-SEPs predicted poor outcome with FPR=0.0%. When these neurophysiological patterns are both present in the same patient, they confirm and strengthen their prognostic value, but because they also occurred independently in eight patients, poor outcome is predictable in a greater number of patients. The combination of EEG/SEP findings allows prediction of good and poor outcome (within 12 h after CA) and of poor outcome (after 48-72 h). Recording of EEG and SEPs in the same patients allows always an increase in the number of cases correctly classified, and an increase of the reliability of prognostication in a single patient due to concordance of patterns. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Poor outcome prediction by burst suppression ratio in adults with post-anoxic coma without hypothermia.

PubMed

Yang, Qinglin; Su, Yingying; Hussain, Mohammed; Chen, Weibi; Ye, Hong; Gao, Daiquan; Tian, Fei

2014-05-01

Burst suppression ratio (BSR) is a quantitative electroencephalography (qEEG) parameter. The purpose of our study was to compare the accuracy of BSR when compared to other EEG parameters in predicting poor outcomes in adults who sustained post-anoxic coma while not being subjected to therapeutic hypothermia. EEG was registered and recorded at least once within 7 days of post-anoxic coma onset. Electrodes were placed according to the international 10-20 system, using a 16-channel layout. Each EEG expert scored raw EEG using a grading scale adapted from Young and scored amplitude-integrated electroencephalography tracings, in addition to obtaining qEEG parameters defined as BSR with a defined threshold. Glasgow outcome scales of 1 and 2 at 3 months, determined by two blinded neurologists, were defined as poor outcome. Sixty patients with Glasgow coma scale score of 8 or less after anoxic accident were included. The sensitivity (97.1%), specificity (73.3%), positive predictive value (82.5%), and negative prediction value (95.0%) of BSR in predicting poor outcome were higher than other EEG variables. BSR1 and BSR2 were reliable in predicting death (area under the curve > 0.8, P < 0.05), with the respective cutoff points being 39.8% and 61.6%. BSR1 was reliable in predicting poor outcome (area under the curve  =  0.820, P < 0.05) with a cutoff point of 23.9%. BSR1 was also an independent predictor of increased risk of death (odds ratio  =  1.042, 95% confidence intervals: 1.012-1.073, P  =  0.006). BSR may be a better predictor in prognosticating poor outcomes in patients with post-anoxic coma who do not undergo therapeutic hypothermia when compared to other qEEG parameters.

A Man-Machine System for Contemporary Counseling Practice: Diagnosis and Prediction.

ERIC Educational Resources Information Center

Roach, Arthur J.

This paper looks at present and future capabilities for diagnosis and prediction in computer-based guidance efforts and reviews the problems and potentials which will accompany the implementation of such capabilities. In addition to necessary procedural refinement in prediction, future developments in computer-based educational and career…

Effective Use of New Communication Technologies.

ERIC Educational Resources Information Center

Fauley, Franz E.

Until the last two or three years, three forces inhibited the acceptance of computer-assisted instruction (CAI). These were the fear on the part of traditional trainers of displacement by machines, the poor quality of existing courseware and limited capability of accompanying hardware, and the poor price and performance characteristics of existing…

Building spatially-explicit model predictions for ecological condition of streams in the Pacific Northwest: An assessment of landscape variables, models, endpoints and prediction scale

EPA Science Inventory

While large-scale, randomized surveys estimate the percentage of a region’s streams in poor ecological condition, identifying particular stream reaches or watersheds in poor condition is an equally important goal for monitoring and management. We built predictive models of strea...

A variable capacitance based modeling and power capability predicting method for ultracapacitor

NASA Astrophysics Data System (ADS)

Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

2018-01-01

Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

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.

Breast cancer prognosis by combinatorial analysis of gene expression data.

PubMed

Alexe, Gabriela; Alexe, Sorin; Axelrod, David E; Bonates, Tibérius O; Lozina, Irina I; Reiss, Michael; Hammer, Peter L

2006-01-01

The potential of applying data analysis tools to microarray data for diagnosis and prognosis is illustrated on the recent breast cancer dataset of van 't Veer and coworkers. We re-examine that dataset using the novel technique of logical analysis of data (LAD), with the double objective of discovering patterns characteristic for cases with good or poor outcome, using them for accurate and justifiable predictions; and deriving novel information about the role of genes, the existence of special classes of cases, and other factors. Data were analyzed using the combinatorics and optimization-based method of LAD, recently shown to provide highly accurate diagnostic and prognostic systems in cardiology, cancer proteomics, hematology, pulmonology, and other disciplines. LAD identified a subset of 17 of the 25,000 genes, capable of fully distinguishing between patients with poor, respectively good prognoses. An extensive list of 'patterns' or 'combinatorial biomarkers' (that is, combinations of genes and limitations on their expression levels) was generated, and 40 patterns were used to create a prognostic system, shown to have 100% and 92.9% weighted accuracy on the training and test sets, respectively. The prognostic system uses fewer genes than other methods, and has similar or better accuracy than those reported in other studies. Out of the 17 genes identified by LAD, three (respectively, five) were shown to play a significant role in determining poor (respectively, good) prognosis. Two new classes of patients (described by similar sets of covering patterns, gene expression ranges, and clinical features) were discovered. As a by-product of the study, it is shown that the training and the test sets of van 't Veer have differing characteristics. The study shows that LAD provides an accurate and fully explanatory prognostic system for breast cancer using genomic data (that is, a system that, in addition to predicting good or poor prognosis, provides an individualized explanation of the reasons for that prognosis for each patient). Moreover, the LAD model provides valuable insights into the roles of individual and combinatorial biomarkers, allows the discovery of new classes of patients, and generates a vast library of biomedical research hypotheses.

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

A Deep Space Orbit Determination Software: Overview and Event Prediction Capability

NASA Astrophysics Data System (ADS)

Kim, Youngkwang; Park, Sang-Young; Lee, Eunji; Kim, Minsik

2017-06-01

This paper presents an overview of deep space orbit determination software (DSODS), as well as validation and verification results on its event prediction capabilities. DSODS was developed in the MATLAB object-oriented programming environment to support the Korea Pathfinder Lunar Orbiter (KPLO) mission. DSODS has three major capabilities: celestial event prediction for spacecraft, orbit determination with deep space network (DSN) tracking data, and DSN tracking data simulation. To achieve its functionality requirements, DSODS consists of four modules: orbit propagation (OP), event prediction (EP), data simulation (DS), and orbit determination (OD) modules. This paper explains the highest-level data flows between modules in event prediction, orbit determination, and tracking data simulation processes. Furthermore, to address the event prediction capability of DSODS, this paper introduces OP and EP modules. The role of the OP module is to handle time and coordinate system conversions, to propagate spacecraft trajectories, and to handle the ephemerides of spacecraft and celestial bodies. Currently, the OP module utilizes the General Mission Analysis Tool (GMAT) as a third-party software component for highfidelity deep space propagation, as well as time and coordinate system conversions. The role of the EP module is to predict celestial events, including eclipses, and ground station visibilities, and this paper presents the functionality requirements of the EP module. The validation and verification results show that, for most cases, event prediction errors were less than 10 millisec when compared with flight proven mission analysis tools such as GMAT and Systems Tool Kit (STK). Thus, we conclude that DSODS is capable of predicting events for the KPLO in real mission applications.

Eye movement sequence generation in humans: Motor or goal updating?

PubMed Central

Quaia, Christian; Joiner, Wilsaan M.; FitzGibbon, Edmond J.; Optican, Lance M.; Smith, Maurice A.

2011-01-01

Saccadic eye movements are often grouped in pre-programmed sequences. The mechanism underlying the generation of each saccade in a sequence is currently poorly understood. Broadly speaking, two alternative schemes are possible: first, after each saccade the retinotopic location of the next target could be estimated, and an appropriate saccade could be generated. We call this the goal updating hypothesis. Alternatively, multiple motor plans could be pre-computed, and they could then be updated after each movement. We call this the motor updating hypothesis. We used McLaughlin’s intra-saccadic step paradigm to artificially create a condition under which these two hypotheses make discriminable predictions. We found that in human subjects, when sequences of two saccades are planned, the motor updating hypothesis predicts the landing position of the second saccade in two-saccade sequences much better than the goal updating hypothesis. This finding suggests that the human saccadic system is capable of executing sequences of saccades to multiple targets by planning multiple motor commands, which are then updated by serial subtraction of ongoing motor output. PMID:21191134

A dynamic feedforward neural network based on gaussian particle swarm optimization and its application for predictive control.

PubMed

Han, Min; Fan, Jianchao; Wang, Jun

2011-09-01

A dynamic feedforward neural network (DFNN) is proposed for predictive control, whose adaptive parameters are adjusted by using Gaussian particle swarm optimization (GPSO) in the training process. Adaptive time-delay operators are added in the DFNN to improve its generalization for poorly known nonlinear dynamic systems with long time delays. Furthermore, GPSO adopts a chaotic map with Gaussian function to balance the exploration and exploitation capabilities of particles, which improves the computational efficiency without compromising the performance of the DFNN. The stability of the particle dynamics is analyzed, based on the robust stability theory, without any restrictive assumption. A stability condition for the GPSO+DFNN model is derived, which ensures a satisfactory global search and quick convergence, without the need for gradients. The particle velocity ranges could change adaptively during the optimization process. The results of a comparative study show that the performance of the proposed algorithm can compete with selected algorithms on benchmark problems. Additional simulation results demonstrate the effectiveness and accuracy of the proposed combination algorithm in identifying and controlling nonlinear systems with long time delays.

Beyond Phonology: Visual Processes Predict Alphanumeric and Nonalphanumeric Rapid Naming in Poor Early Readers

ERIC Educational Resources Information Center

Kruk, Richard S.; Luther Ruban, Cassia

2018-01-01

Visual processes in Grade 1 were examined for their predictive influences in nonalphanumeric and alphanumeric rapid naming (RAN) in 51 poor early and 69 typical readers. In a lagged design, children were followed longitudinally from Grade 1 to Grade 3 over 5 testing occasions. RAN outcomes in early Grade 2 were predicted by speeded and nonspeeded…

A reinforcement sensitivity model of affective and behavioral dysregulation in marijuana use and associated problems.

PubMed

Emery, Noah N; Simons, Jeffrey S

2017-08-01

This study tested a model linking sensitivity to punishment (SP) and reward (SR) to marijuana use and problems via affect lability and poor control. A 6-month prospective design was used in a sample of 2,270 young-adults (64% female). The hypothesized SP × SR interaction did not predict affect lability or poor control, but did predict use likelihood at baseline. At low levels of SR, SP was associated with an increased likelihood of abstaining, which was attenuated as SR increased. SP and SR displayed positive main effects on both affect lability and poor control. Affect lability and poor control, in turn, mediated effects on the marijuana outcomes. Poor control predicted both increased marijuana use and, controlling for use level, greater intensity of problems. Affect lability predicted greater intensity of problems, but was not associated with use level. There were few prospective effects. SR consistently predicted greater marijuana use and problems. SP however, exhibited both risk and protective pathways. Results indicate that SP is associated with a decreased likelihood of marijuana use. However, once use is initiated SP is associated with increased risk of problems, in part, due to its effects on both affect and behavioral dysregulation. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

3D Protein structure prediction with genetic tabu search algorithm

PubMed Central

2010-01-01

Background Protein structure prediction (PSP) has important applications in different fields, such as drug design, disease prediction, and so on. In protein structure prediction, there are two important issues. The first one is the design of the structure model and the second one is the design of the optimization technology. Because of the complexity of the realistic protein structure, the structure model adopted in this paper is a simplified model, which is called off-lattice AB model. After the structure model is assumed, optimization technology is needed for searching the best conformation of a protein sequence based on the assumed structure model. However, PSP is an NP-hard problem even if the simplest model is assumed. Thus, many algorithms have been developed to solve the global optimization problem. In this paper, a hybrid algorithm, which combines genetic algorithm (GA) and tabu search (TS) algorithm, is developed to complete this task. Results In order to develop an efficient optimization algorithm, several improved strategies are developed for the proposed genetic tabu search algorithm. The combined use of these strategies can improve the efficiency of the algorithm. In these strategies, tabu search introduced into the crossover and mutation operators can improve the local search capability, the adoption of variable population size strategy can maintain the diversity of the population, and the ranking selection strategy can improve the possibility of an individual with low energy value entering into next generation. Experiments are performed with Fibonacci sequences and real protein sequences. Experimental results show that the lowest energy obtained by the proposed GATS algorithm is lower than that obtained by previous methods. Conclusions The hybrid algorithm has the advantages from both genetic algorithm and tabu search algorithm. It makes use of the advantage of multiple search points in genetic algorithm, and can overcome poor hill-climbing capability in the conventional genetic algorithm by using the flexible memory functions of TS. Compared with some previous algorithms, GATS algorithm has better performance in global optimization and can predict 3D protein structure more effectively. PMID:20522256

A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

NASA Astrophysics Data System (ADS)

Coyne, Kevin Anthony

The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional branching events and provide a better representation of the IDAC cognitive model. An operator decision-making engine capable of responding to dynamic changes in situational context was implemented. The IDAC human performance model was fully integrated with a detailed nuclear plant model in order to realistically simulate plant accident scenarios. Finally, the improved ADS-IDAC model was calibrated, validated, and updated using actual nuclear plant crew performance data. This research led to the following general conclusions: (1) A relatively small number of branching rules are capable of efficiently capturing a wide spectrum of crew-to-crew variabilities. (2) Compared to traditional static risk assessment methods, ADS-IDAC can provide a more realistic and integrated assessment of human error events by directly determining the effect of operator behaviors on plant thermal hydraulic parameters. (3) The ADS-IDAC approach provides an efficient framework for capturing actual operator performance data such as timing of operator actions, mental models, and decision-making activities.

Bipartite design of a self-fibrillating protein copolymer with nanopatterned peptide display capabilities.

PubMed

Bruning, Marc; Kreplak, Laurent; Leopoldseder, Sonja; Müller, Shirley A; Ringler, Philippe; Duchesne, Laurence; Fernig, David G; Engel, Andreas; Ucurum-Fotiadis, Zöhre; Mayans, Olga

2010-11-10

The development of biomatrices for technological and biomedical applications employs self-assembled scaffolds built from short peptidic motifs. However, biopolymers composed of protein domains would offer more varied molecular frames to introduce finer and more complex functionalities in bioreactive scaffolds using bottom-up approaches. Yet, the rules governing the three-dimensional organization of protein architectures in nature are complex and poorly understood. As a result, the synthetic fabrication of ordered protein association into polymers poses major challenges to bioengineering. We have now fabricated a self-assembling protein nanofiber with predictable morphologies and amenable to bottom-up customization, where features supporting function and assembly are spatially segregated. The design was inspired by the cross-linking of titin filaments by telethonin in the muscle sarcomere. The resulting fiber is a two-protein system that has nanopatterned peptide display capabilities as shown by the recruitment of functionalized gold nanoparticles at regular intervals of ∼ 5 nm, yielding a semiregular linear array over micrometers. This polymer promises the uncomplicated display of biologically active motifs to selectively bind and organize matter in the fine nanoscale. Further, its conceptual design has high potential for controlled plurifunctionalization.

Predicting crash-relevant violations at stop sign-controlled intersections for the development of an intersection driver assistance system.

PubMed

Scanlon, John M; Sherony, Rini; Gabler, Hampton C

2016-09-01

Intersection crashes resulted in over 5,000 fatalities in the United States in 2014. Intersection Advanced Driver Assistance Systems (I-ADAS) are active safety systems that seek to help drivers safely traverse intersections. I-ADAS uses onboard sensors to detect oncoming vehicles and, in the event of an imminent crash, can either alert the driver or take autonomous evasive action. The objective of this study was to develop and evaluate a predictive model for detecting whether a stop sign violation was imminent. Passenger vehicle intersection approaches were extracted from a data set of typical driver behavior (100-Car Naturalistic Driving Study) and violations (event data recorders downloaded from real-world crashes) and were assigned weighting factors based on real-world frequency. A k-fold cross-validation procedure was then used to develop and evaluate 3 hypothetical stop sign warning algorithms (i.e., early, intermediate, and delayed) for detecting an impending violation during the intersection approach. Violation detection models were developed using logistic regression models that evaluate likelihood of a violation at various locations along the intersection approach. Two potential indicators of driver intent to stop-that is, required deceleration parameter (RDP) and brake application-were used to develop the predictive models. The earliest violation detection opportunity was then evaluated for each detection algorithm in order to (1) evaluate the violation detection accuracy and (2) compare braking demand versus maximum braking capabilities. A total of 38 violating and 658 nonviolating approaches were used in the analysis. All 3 algorithms were able to detect a violation at some point during the intersection approach. The early detection algorithm, as designed, was able to detect violations earlier than all other algorithms during the intersection approach but gave false alarms for 22.3% of approaches. In contrast, the delayed detection algorithm sacrificed some time for detecting violations but was able to substantially reduce false alarms to only 3.3% of all nonviolating approaches. Given good surface conditions (maximum braking capabilities = 0.8 g) and maximum effort, most drivers (55.3-71.1%) would be able to stop the vehicle regardless of the detection algorithm. However, given poor surface conditions (maximum braking capabilities = 0.4 g), few drivers (10.5-26.3%) would be able to stop the vehicle. Automatic emergency braking (AEB) would allow for early braking prior to driver reaction. If equipped with an AEB system, the results suggest that, even for the poor surface conditions scenario, over one half (55.3-65.8%) of the vehicles could have been stopped. This study demonstrates the potential of I-ADAS to incorporate a stop sign violation detection algorithm. Repeating the analysis on a larger, more extensive data set will allow for the development of a more comprehensive algorithm to further validate the findings.

A method for testing whether model predictions fall within a prescribed factor of true values, with an application to pesticide leaching

USGS Publications Warehouse

Parrish, Rudolph S.; Smith, Charles N.

1990-01-01

A quantitative method is described for testing whether model predictions fall within a specified factor of true values. The technique is based on classical theory for confidence regions on unknown population parameters and can be related to hypothesis testing in both univariate and multivariate situations. A capability index is defined that can be used as a measure of predictive capability of a model, and its properties are discussed. The testing approach and the capability index should facilitate model validation efforts and permit comparisons among competing models. An example is given for a pesticide leaching model that predicts chemical concentrations in the soil profile.

New smoke predictions for Alaska in NOAA’s National Air Quality Forecast Capability

NASA Astrophysics Data System (ADS)

Davidson, P. M.; Ruminski, M.; Draxler, R.; Kondragunta, S.; Zeng, J.; Rolph, G.; Stajner, I.; Manikin, G.

2009-12-01

Smoke from wildfire is an important component of fine particle pollution, which is responsible for tens of thousands of premature deaths each year in the US. In Alaska, wildfire smoke is the leading cause of poor air quality in summer. Smoke forecast guidance helps air quality forecasters and the public take steps to limit exposure to airborne particulate matter. A new smoke forecast guidance tool, built by a cross-NOAA team, leverages efforts of NOAA’s partners at the USFS on wildfire emissions information, and with EPA, in coordinating with state/local air quality forecasters. Required operational deployment criteria, in categories of objective verification, subjective feedback, and production readiness, have been demonstrated in experimental testing during 2008-2009, for addition to the operational products in NOAA's National Air Quality Forecast Capability. The Alaska smoke forecast tool is an adaptation of NOAA’s smoke predictions implemented operationally for the lower 48 states (CONUS) in 2007. The tool integrates satellite information on location of wildfires with weather (North American mesoscale model) and smoke dispersion (HYSPLIT) models to produce daily predictions of smoke transport for Alaska, in binary and graphical formats. Hour-by hour predictions at 12km grid resolution of smoke at the surface and in the column are provided each day by 13 UTC, extending through midnight next day. Forecast accuracy and reliability are monitored against benchmark criteria for accuracy and reliability. While wildfire activity in the CONUS is year-round, the intense wildfire activity in AK is limited to the summer. Initial experimental testing during summer 2008 was hindered by unusually limited wildfire activity and very cloudy conditions. In contrast, heavier than average wildfire activity during summer 2009 provided a representative basis (more than 60 days of wildfire smoke) for demonstrating required prediction accuracy. A new satellite observation product was developed for routine near-real time verification of these predictions. The footprint of the predicted smoke from identified fires is verified with satellite observations of the spatial extent of smoke aerosols (5km resolution). Based on geostationary aerosol optical depth measurements that provide good time resolution of the horizontal spatial extent of the plumes, these observations do not yield quantitative concentrations of smoke particles at the surface. Predicted surface smoke concentrations are consistent with the limited number of in situ observations of total fine particle mass from all sources; however they are much higher than predicted for most CONUS fires. To assess uncertainty associated with fire emissions estimates, sensitivity analyses are in progress.

EBUS-STAT Subscore Analysis to Predict the Efficacy and Assess the Validity of Virtual Reality Simulation for EBUS-TBNA Training Among Experienced Bronchoscopists.

PubMed

Scarlata, Simone; Palermo, Patrizio; Candoli, Piero; Tofani, Ariela; Petitti, Tommasangelo; Corbetta, Lorenzo

2017-04-01

Linear endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) represents a pivotal innovation in interventional pulmonology; determining the best approach to guarantee systematic and efficient training is expected to become a main issue in the forthcoming years. Virtual reality simulators have been proposed as potential EBUS-TBNA training instruments, to avoid unskilled beginners practicing directly in real-life settings. A validated and perfected simulation program could be used before allowing beginners to practice on patients. Our goal was to test the reliability of the EBUS-Skills and Task Assessment Tool (STAT) and its subscores for measuring the competence of experienced bronchoscopists approaching EBUS-guided TBNA, using only the virtual reality simulator as both a training and an assessment tool. Fifteen experienced bronchoscopists, with poor or no experience in EBUS-TBNA, participated in this study. They were all administered the Italian version of the EBUS-STAT evaluation tool, during a high-fidelity virtual reality simulation. This was followed by a single 7-hour theoretical and practical (on simulators) session on EBUS-TBNA, at the end of which their skills were reassessed by EBUS-STAT. An overall, significant improvement in EBUS-TBNA skills was observed, thereby confirming that (a) virtual reality simulation can facilitate practical learning among practitioners, and (b) EBUS-STAT is capable of detecting these improvements. The test's overall ability to detect differences was negatively influenced by the minimal variation of the scores relating to items 1 and 2, was not influenced by the training, and improved significantly when the 2 items were not considered. Apart from these 2 items, all the remaining subscores were equally capable of revealing improvements in the learner. Lastly, we found that trainees with presimulation EBUS-STAT scores above 79 did not show any significant improvement after virtual reality training, suggesting that this score represents a cutoff value capable of predicting the likelihood that simulation can be beneficial. Virtual reality simulation is capable of providing a practical learning tool for practitioners with previous experience in flexible bronchoscopy, and the EBUS-STAT questionnaire is capable of detecting these changes. A pretraining EBUS-STAT score below 79 is a good indicator of those candidates who will benefit from the simulation training. Further studies are needed to verify whether a modified version of the questionnaire would be capable of improving its performance among experienced bronchoscopists.

Core solidification and dynamo evolution in a mantle-stripped planetesimal

NASA Astrophysics Data System (ADS)

Scheinberg, A.; Elkins-Tanton, L. T.; Schubert, G.; Bercovici, D.

2016-01-01

The physical processes active during the crystallization of a low-pressure, low-gravity planetesimal core are poorly understood but have implications for asteroidal magnetic fields and large-scale asteroidal structure. We consider a core with only a thin silicate shell, which could be analogous to some M-type asteroids including Psyche, and use a parameterized thermal model to predict a solidification timeline and the resulting chemical profile upon complete solidification. We then explore the potential strength and longevity of a dynamo in the planetesimal's early history. We find that cumulate inner core solidification would be capable of sustaining a dynamo during solidification, but less power would be available for a dynamo in an inward dendritic solidification scenario. We also model and suggest limits on crystal settling and compaction of a possible cumulate inner core.

Multi-pathway Kinase Signatures of Multipotent Stromal Cells are Predictive for Osteogenic Differentiation

PubMed Central

Platt, Manu O.; Wilder, Catera L.; Wells, Alan; Griffith, Linda G.; Lauffenburger, Douglas A.

2010-01-01

Bone marrow-derived multi-potent stromal cells (MSCs) offer great promise for regenerating tissue. While certain transcription factors have been identified in association with tendency toward particular MSC differentiation phenotypes, the regulatory network of key receptor-mediated signaling pathways activated by extracellular ligands that induce various differentiation responses remain poorly understood. Attempts to predict differentiation fate tendencies from individual pathways in isolation are problematic due to the complex pathway interactions inherent in signaling networks. Accordingly, we have undertaken a multi-variate systems approach integrating experimental measurement of multiple kinase pathway activities and osteogenic differentiation in MSCs, together with computational analysis to elucidate quantitative combinations of kinase signals predictive of cell behavior across diverse contexts. In particular, for culture on polymeric biomaterials surfaces presenting tethered epidermal growth factor (tEGF), type-I collagen, neither, or both, we have found that a partial least-squares regression model yields successful prediction of phenotypic behavior on the basis of two principal components comprising the weighted sums of 8 intracellular phosphoproteins: p-EGFR, p-Akt, p-ERK1/2, p-Hsp27, p-c-jun, p-GSK3α/β, p-p38, and p-STAT3. This combination provides strongest predictive capability for 21-day differentiated phenotype status when calculated from day-7 signal measurements (99%); day-4 (88%) and day-14 (89%) signal measurements are also significantly predictive, indicating a broad time-frame during MSC osteogenesis wherein multiple pathways and states of the kinase signaling network are quantitatively integrated to regulate gene expression, cell processes, and ultimately, cell fate. PMID:19750537

Building a Predictive Capability for Decision-Making that Supports MultiPEM

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

Carmichael, Joshua Daniel

Multi-phenomenological explosion monitoring (multiPEM) is a developing science that uses multiple geophysical signatures of explosions to better identify and characterize their sources. MultiPEM researchers seek to integrate explosion signatures together to provide stronger detection, parameter estimation, or screening capabilities between different sources or processes. This talk will address forming a predictive capability for screening waveform explosion signatures to support multiPEM.

Modeling of adipose/blood partition coefficient for environmental chemicals.

PubMed

Papadaki, K C; Karakitsios, S P; Sarigiannis, D A

2017-12-01

A Quantitative Structure Activity Relationship (QSAR) model was developed in order to predict the adipose/blood partition coefficient of environmental chemical compounds. The first step of QSAR modeling was the collection of inputs. Input data included the experimental values of adipose/blood partition coefficient and two sets of molecular descriptors for 67 organic chemical compounds; a) the descriptors from Linear Free Energy Relationship (LFER) and b) the PaDEL descriptors. The datasets were split to training and prediction set and were analysed using two statistical methods; Genetic Algorithm based Multiple Linear Regression (GA-MLR) and Artificial Neural Networks (ANN). The models with LFER and PaDEL descriptors, coupled with ANN, produced satisfying performance results. The fitting performance (R 2 ) of the models, using LFER and PaDEL descriptors, was 0.94 and 0.96, respectively. The Applicability Domain (AD) of the models was assessed and then the models were applied to a large number of chemical compounds with unknown values of adipose/blood partition coefficient. In conclusion, the proposed models were checked for fitting, validity and applicability. It was demonstrated that they are stable, reliable and capable to predict the values of adipose/blood partition coefficient of "data poor" chemical compounds that fall within the applicability domain. Copyright © 2017. Published by Elsevier Ltd.

Transperineal ultrasound compared to evacuation proctography for diagnosing enteroceles and intussusceptions.

PubMed

Weemhoff, M; Kluivers, K B; Govaert, B; Evers, J L H; Kessels, A G H; Baeten, C G

2013-03-01

This study concerns the level of agreement between transperineal ultrasound and evacuation proctography for diagnosing enteroceles and intussusceptions. In a prospective observational study, 50 consecutive women who were planned to have an evacuation proctography underwent transperineal ultrasound too. Sensitivity, specificity, positive (PPV) and negative predictive value, as well as the positive and negative likelihood ratio of transperineal ultrasound were assessed in comparison to evacuation proctography. To determine the interobserver agreement of transperineal ultrasound, the quadratic weighted kappa was calculated. Furthermore, receiver operating characteristic curves were generated to show the diagnostic capability of transperineal ultrasound. For diagnosing intussusceptions (PPV 1.00), a positive finding on transperineal ultrasound was predictive of an abnormal evacuation proctography. Sensitivity of transperineal ultrasound was poor for intussusceptions (0.25). For diagnosing enteroceles, the positive likelihood ratio was 2.10 and the negative likelihood ratio, 0.85. There are many false-positive findings of enteroceles on ultrasonography (PPV 0.29). The interobserver agreement of the two ultrasonographers assessed as the quadratic weighted kappa of diagnosing enteroceles was 0.44 and that of diagnosing intussusceptions was 0.23. An intussusception on ultrasound is predictive of an abnormal evacuation proctography. For diagnosing enteroceles, the diagnostic quality of transperineal ultrasound was limited compared to evacuation proctography.

Online and offline inferential and textual processing of poor comprehenders: Evidence from a probing method.

PubMed

Yeari, Menahem; Elentok, Shiri; Schiff, Rachel

2017-03-01

Numerous studies have demonstrated that poor inferential processing underlies the specific deficit of poor comprehenders. However, it is still not clear why poor comprehenders have difficulties in generating inferences while reading and whether this impairment is general or specific to one or more types of inferences. The current study employed an online probing method to examine the spontaneous immediate activation of two inference types-forward-predictive inferences and backward-explanatory inferences-during reading. In addition, we examined the ability of poor comprehenders to retain, suppress, and reactivate text information (relevant for inferencing) in working memory. The participants, 10- to 12-year-old good and poor comprehenders, read short narratives and name inference or text word probes following a predictive, intervening, or bridging sentence. Comparing the size of probe-naming facilitations revealed that poor comprehenders generate predictive inferences, albeit more slowly than good comprehenders, and generate explanatory inferences to a lesser extent than good comprehenders. Moreover, we found that this inferior inferential processing is presumably a result of poor retention and reactivation of inference-evoking text information during reading. Finally, poorer reading comprehension was associated with higher activation of information when it was less relevant following the intervening sentences. Taken together, the current findings demonstrate the manner in which poor regulation of relevant and less relevant information during reading underlies the specific comprehension difficulties experienced by poor comprehenders. Copyright © 2016 Elsevier Inc. All rights reserved.

Predictive modeling capabilities from incident powder and laser to mechanical properties for laser directed energy deposition

NASA Astrophysics Data System (ADS)

Shin, Yung C.; Bailey, Neil; Katinas, Christopher; Tan, Wenda

2018-05-01

This paper presents an overview of vertically integrated comprehensive predictive modeling capabilities for directed energy deposition processes, which have been developed at Purdue University. The overall predictive models consist of vertically integrated several modules, including powder flow model, molten pool model, microstructure prediction model and residual stress model, which can be used for predicting mechanical properties of additively manufactured parts by directed energy deposition processes with blown powder as well as other additive manufacturing processes. Critical governing equations of each model and how various modules are connected are illustrated. Various illustrative results along with corresponding experimental validation results are presented to illustrate the capabilities and fidelity of the models. The good correlations with experimental results prove the integrated models can be used to design the metal additive manufacturing processes and predict the resultant microstructure and mechanical properties.

Predictive modeling capabilities from incident powder and laser to mechanical properties for laser directed energy deposition

NASA Astrophysics Data System (ADS)

Shin, Yung C.; Bailey, Neil; Katinas, Christopher; Tan, Wenda

2018-01-01

This paper presents an overview of vertically integrated comprehensive predictive modeling capabilities for directed energy deposition processes, which have been developed at Purdue University. The overall predictive models consist of vertically integrated several modules, including powder flow model, molten pool model, microstructure prediction model and residual stress model, which can be used for predicting mechanical properties of additively manufactured parts by directed energy deposition processes with blown powder as well as other additive manufacturing processes. Critical governing equations of each model and how various modules are connected are illustrated. Various illustrative results along with corresponding experimental validation results are presented to illustrate the capabilities and fidelity of the models. The good correlations with experimental results prove the integrated models can be used to design the metal additive manufacturing processes and predict the resultant microstructure and mechanical properties.

Predicting Risk for Suicide: A Preliminary Examination of Non-Suicidal Self-Injury and the Acquired Capability Construct in a College Sample.

PubMed

Brackman, Emily H; Morris, Blair W; Andover, Margaret S

2016-01-01

The interpersonal psychological theory of suicide provides a useful framework for considering the relationship between non-suicidal self-injury and suicide. Researchers propose that NSSI increases acquired capability for suicide. We predicted that both NSSI frequency and the IPTS acquired capability construct (decreased fear of death and increased pain tolerance) would separately interact with suicidal ideation to predict suicide attempts. Undergraduate students (N = 113) completed self-report questionnaires, and a subsample (n = 66) also completed a pain sensitivity task. NSSI frequency significantly moderated the association between suicidal ideation and suicide attempts. However, in a separate model, acquired capability did not moderate this relationship. Our understanding of the relationship between suicidal ideation and suicidal behavior can be enhanced by factors associated with NSSI that are distinct from the acquired capability construct.

Motor testing at 1 year improves the prediction of motor and mental outcome at 2 years after perinatal hypoxic-ischaemic encephalopathy.

PubMed

van Schie, Petra E M; Becher, Jules G; Dallmeijer, Annet J; Barkhof, Frederik; Van Weissenbruch, Mirjam M; Vermeulen, R Jeroen

2010-01-01

To investigate the predictive value of motor testing at 1 year for motor and mental outcome at 2 years after perinatal hypoxic-ischaemic encephalopathy (HIE) in term neonates. Motor and mental outcome at 2 years was assessed with the Bayley Scales of Infant Development, 2nd edition (BSID-II) in 32 surviving children (20 males, 12 females; mean gestational age 40.2 wk, SD 1.4; mean birthweight 3217g, SD 435) participating in a prospective cohort study of HIE. The predictive value of three motor tests (Alberta Infant Motor Scale [AIMS], BSID-II, and the Neurological Optimality Score [NOS]) at 1 year was analysed, in addition to predictions based on neonatal Sarnat staging and magnetic resonance imaging (MRI). Poor motor test results were defined as an AIMS z-score of <-2, a psychomotor developmental index of the BSID-II of <70, or a NOS of <26. Poor motor and poor mental outcome at 2 years was defined as a psychomotor developmental index or mental developmental index of the BSID-II of <70. Twelve children, all with Sarnat grade II, had a poor motor outcome and 12 children, of whom one had Sarnat grade I, had a poor mental outcome at 2 years. Nine children had cerebral palsy, of whom five had quadriplegia, three had dyskinesia, and one had hemiplegia. Poor motor tests at 1 year increased the probability of a poor motor outcome from 71% (range 92 to 100%), and a poor mental outcome from 59% (range 77 to 100%) in children with Sarnat grade II and abnormal MRI, assessed with the AIMS and BSID-II or NOS respectively. Additional motor testing at 1 year improves the prediction of motor and mental outcome at 2 years in children with Sarnat grade II and abnormal MRI.

Early EEG for outcome prediction of postanoxic coma: prospective cohort study with cost-minimization analysis.

PubMed

Sondag, Lotte; Ruijter, Barry J; Tjepkema-Cloostermans, Marleen C; Beishuizen, Albertus; Bosch, Frank H; van Til, Janine A; van Putten, Michel J A M; Hofmeijer, Jeannette

2017-05-15

We recently showed that electroencephalography (EEG) patterns within the first 24 hours robustly contribute to multimodal prediction of poor or good neurological outcome of comatose patients after cardiac arrest. Here, we confirm these results and present a cost-minimization analysis. Early prognosis contributes to communication between doctors and family, and may prevent inappropriate treatment. A prospective cohort study including 430 subsequent comatose patients after cardiac arrest was conducted at intensive care units of two teaching hospitals. Continuous EEG was started within 12 hours after cardiac arrest and continued up to 3 days. EEG patterns were visually classified as unfavorable (isoelectric, low-voltage, or burst suppression with identical bursts) or favorable (continuous patterns) at 12 and 24 hours after cardiac arrest. Outcome at 6 months was classified as good (cerebral performance category (CPC) 1 or 2) or poor (CPC 3, 4, or 5). Predictive values of EEG measures and cost-consequences from a hospital perspective were investigated, assuming EEG-based decision- making about withdrawal of life-sustaining treatment in the case of a poor predicted outcome. Poor outcome occurred in 197 patients (51% of those included in the analyses). Unfavorable EEG patterns at 24 hours predicted a poor outcome with specificity of 100% (95% CI 98-100%) and sensitivity of 29% (95% CI 22-36%). Favorable patterns at 12 hours predicted good outcome with specificity of 88% (95% CI 81-93%) and sensitivity of 51% (95% CI 42-60%). Treatment withdrawal based on an unfavorable EEG pattern at 24 hours resulted in a reduced mean ICU length of stay without increased mortality in the long term. This gave small cost reductions, depending on the timing of withdrawal. Early EEG contributes to reliable prediction of good or poor outcome of postanoxic coma and may lead to reduced length of ICU stay. In turn, this may bring small cost reductions.

Evaluation of pyritic mine tailings as a plant growth substrate.

PubMed

Roseby, Stuart J; Kopittke, Peter M; Mulligan, David R; Menzies, Neal W

2017-10-01

At the Kidston gold mine, Australia, the direct establishment of vegetation on tailings was considered as an alternative to the use of a waste rock cover. The tailings acid/base account was used to predict plant growth limitation by acidity, and thus methods capable of identifying tailings that would acidify to pH 4.5 or lower were sought. Total S was found to be poorly correlated with acid-generating sulfide, and total C was poorly correlated with acid-neutralizing carbonate, precluding the use of readily determined total S and C as predictors of net acid generation. Therefore, the selected approach used assessment of sulfide content as a predictor of acid generation, and carbonate content as a measure of the acid-neutralizing capacity available at pH 5 and above. Using this approach, the majority of tailings (67%) were found to be non-acid generating. However, areas of potentially acid-generating tailings were randomly distributed across the dam, and could only be located by intensive sampling. The limitations imposed by the large sample numbers, and costly analysis of sulfide and carbonate, make it impractical to identify and ameliorate acid-generating areas prior to vegetation establishment. However, as only a small proportion of the tailings will acidify, a strategy of re-treating acid areas following oxidation is suggested. The findings of the present study will assist in the selection of appropriate methods for the prediction of net acid generation, particularly where more conservative measurements are required to allow vegetation to be established directly in tailings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predictors of Poor Seizure Control in Children Managed at a Tertiary Care Hospital of Eastern Nepal

PubMed Central

POUDEL, Prakash; CHITLANGIA, Mohit; POKHAREL, Rita

2016-01-01

Objective Various factors have been claimed to predict outcome of afebrile seizures in children. This study was aimed to find out the predictors of poor seizure control in children at a resource limited setting. Materials & Methods This prospective study was done from July 1st, 2009 to January 31st, 2012 at B.P. Koirala Institute of Health Sciences, Nepal. Children (1 month-20 yr of age) with afebrile seizures presenting to pediatric neurology clinic were studied. Significant predictors on bivariate analysis were further analyzed with binary logistic model to find out the true predictors. Positive predictive values (PPVs) and negative predictive values (NPVs) for the true predictors were calculated. Results Out of 256 patients (male: female ratio 3:2) with afebrile seizures followed up for median duration of 27 (IQR 12-50) months, seizure was poorly controlled in 20% patients. Three factors predicted poor seizure control. They were frequent (≥1 per month) seizures at onset (OR 12.76, 95% CI 1.44-112.73, PPV 25%, NPV 98%); remote symptomatic etiology (OR 3.56, 95% CI 1.04-12.17, PPV 36%, NPV 92%); and need of more than one anticonvulsant drug (polytherapy) (OR 12.83, 95% CI 5.50-29.9, PPV 56%, NPV 96%). The strongest predictor was need of polytherapy. When all three factors were present, PPV and NPV for prediction of poor seizure control were 70% and 90% respectively. Conclusion Frequent seizures at onset, remote symptomatic etiology of seizure and need of polytherapy were associated with poor seizure control in children with afebrile seizures. PMID:27375756

The Earth Science Vision

NASA Technical Reports Server (NTRS)

Schoeberl, Mark; Rychekewkitsch, Michael; Andrucyk, Dennis; McConaughy, Gail; Meeson, Blanche; Hildebrand, Peter; Einaudi, Franco (Technical Monitor)

2000-01-01

NASA's Earth Science Enterprise's long range vision is to enable the development of a national proactive environmental predictive capability through targeted scientific research and technological innovation. Proactive environmental prediction means the prediction of environmental events and their secondary consequences. These consequences range from disasters and disease outbreak to improved food production and reduced transportation, energy and insurance costs. The economic advantage of this predictive capability will greatly outweigh the cost of development. Developing this predictive capability requires a greatly improved understanding of the earth system and the interaction of the various components of that system. It also requires a change in our approach to gathering data about the earth and a change in our current methodology in processing that data including its delivery to the customers. And, most importantly, it requires a renewed partnership between NASA and its sister agencies. We identify six application themes that summarize the potential of proactive environmental prediction. We also identify four technology themes that articulate our approach to implementing proactive environmental prediction.

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

Breaking through barriers: using technology to address executive function weaknesses and improve student achievement.

PubMed

Schwartz, David M

2014-01-01

Assistive technologies provide significant capabilities for improving student achievement. Improved accessibility, cost, and diversity of applications make integration of technology a powerful tool to compensate for executive function weaknesses and deficits and their impact on student performance, learning, and achievement. These tools can be used to compensate for decreased working memory, poor time management, poor planning and organization, poor initiation, and decreased memory. Assistive technology provides mechanisms to assist students with diverse strengths and weaknesses in mastering core curricular concepts.

Prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy: a systematic review and external validation study.

PubMed

Hilkens, N A; Algra, A; Greving, J P

2016-01-01

ESSENTIALS: Prediction models may help to identify patients at high risk of bleeding on antiplatelet therapy. We identified existing prediction models for bleeding and validated them in patients with cerebral ischemia. Five prediction models were identified, all of which had some methodological shortcomings. Performance in patients with cerebral ischemia was poor. Background Antiplatelet therapy is widely used in secondary prevention after a transient ischemic attack (TIA) or ischemic stroke. Bleeding is the main adverse effect of antiplatelet therapy and is potentially life threatening. Identification of patients at increased risk of bleeding may help target antiplatelet therapy. This study sought to identify existing prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy and evaluate their performance in patients with cerebral ischemia. We systematically searched PubMed and Embase for existing prediction models up to December 2014. The methodological quality of the included studies was assessed with the CHARMS checklist. Prediction models were externally validated in the European Stroke Prevention Study 2, comprising 6602 patients with a TIA or ischemic stroke. We assessed discrimination and calibration of included prediction models. Five prediction models were identified, of which two were developed in patients with previous cerebral ischemia. Three studies assessed major bleeding, one studied intracerebral hemorrhage and one gastrointestinal bleeding. None of the studies met all criteria of good quality. External validation showed poor discriminative performance, with c-statistics ranging from 0.53 to 0.64 and poor calibration. A limited number of prediction models is available that predict intracranial hemorrhage or major bleeding in patients on antiplatelet therapy. The methodological quality of the models varied, but was generally low. Predictive performance in patients with cerebral ischemia was poor. In order to reliably predict the risk of bleeding in patients with cerebral ischemia, development of a prediction model according to current methodological standards is needed. © 2015 International Society on Thrombosis and Haemostasis.

Energy-absorption capability of composite tubes and beams. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Farley, Gary L.; Jones, Robert M.

1989-01-01

In this study the objective was to develop a method of predicting the energy-absorption capability of composite subfloor beam structures. Before it is possible to develop such an analysis capability, an in-depth understanding of the crushing process of composite materials must be achieved. Many variables affect the crushing process of composite structures, such as the constituent materials' mechanical properties, specimen geometry, and crushing speed. A comprehensive experimental evaluation of tube specimens was conducted to develop insight into how composite structural elements crush and what are the controlling mechanisms. In this study the four characteristic crushing modes, transverse shearing, brittle fracturing, lamina bending, and local buckling were identified and the mechanisms that control the crushing process defined. An in-depth understanding was developed of how material properties affect energy-absorption capability. For example, an increase in fiber and matrix stiffness and failure strain can, depending upon the configuration of the tube, increase energy-absorption capability. An analysis to predict the energy-absorption capability of composite tube specimens was developed and verified. Good agreement between experiment and prediction was obtained.

"I Want to Help Girls Like Me": An Exploration of the Educational Aspirations of Teenage Girls in Kolkata Slums

ERIC Educational Resources Information Center

Ipe, Rebecca

2016-01-01

This qualitative study used participatory visual research in order to develop an understanding of the educational experiences of urban poor adolescent girls in Kolkata and to elicit their capabilities. The sample comprised urban poor girls who were undergoing formal education at a religious, philanthropic primary school in Kolkata. Findings from…

The Reciprocal Influence of Callous-Unemotional Traits, Oppositional Defiant Disorder and Parenting Practices in Preschoolers.

PubMed

Brown, Caitlin A; Granero, Roser; Ezpeleta, Lourdes

2017-04-01

The present study investigates reciprocal associations between positive parenting, parental monitoring, CU traits, and ODD in children assessed at age 3 and again at age 6. Data were collected from a sample of preschoolers (N = 419; 51.58 % female) through diagnostic interviews and questionnaires answered by parents and teachers. Structural equation modeling revealed a bidirectional relationship between poor monitoring and ODD, with poor monitoring at age 3 predicting ODD at age 6 (β = 0.11, p < 0.05), and ODD at age 3 predicting poor monitoring at age 6 (β = 0.10, p < 0.05). While poor monitoring at age 3 predicted CU traits at age 6 (β = 0.11, p < 0.05), CU traits at age 3 predicted positive parenting (β = 0.09, p < 0.05) and ODD (β = 0.13, p < 0.05) at age 6. Results have important implications for early targeted parenting interventions for CU traits and ODD.

Prediction of Poor Ovarian response by Biochemical and Biophysical Markers: A Logistic Regression Model.

PubMed

Jaiswar, S P; Natu, S M; Sujata; Sankhwar, P L; Manjari, Gupta

2015-12-01

To study correlation between ovarian reserve with biophysical markers (antral follicle count and ovarian volume) and biochemical markers (S. FSH, S. Inhibin B, and S. AMH) and use these markers to predict poor ovarian response to ovarian induction. This is a prospective observational study. One hundred infertile women attending the Obst & Gynae Dept, KGMU were recruited. Blood samples were collected on day 2/day 3 for assessment of S. FSH, S. Inhibin B, and S. AMH and TVS were done for antral follicle count and ovarian volume. Clomephene citrate 100 mg 1OD was given from day 2 to 6, and patients were followed up with serial USG measurements. The numbers of dominant follicles (> or = 14 mm) at the time of hCG administration were counted. Patients with <3 follicles in the 1st cycle were subjected to the 2nd cycle of clomephene 100 mg 1OD from day 2 to day 6 with Inj HMG 150 IU given i.m. starting from day 8 and every alternate day until at least one leading follicle attained ≥18 mm. Development of <3 follicles at end of the 2nd cycle was considered as poor response. Univariate analyses showed that s. inhibin B presented the highest (ROCAUC = 0.862) discriminating potential for predicting poor ovarian response, In multivariate logistic regression model, the variables age, FSH, AMH, INHIBIN B, and AFC remained significant, and the resulting model showed a predicted accuracy of 84.4 %. A derived multimarker computation by a logistic regression model for predicting poor ovarian response was obtained through this study. Thus, potential poor responders could be identified easily, and appropriate ovarian stimulation protocol could be devised for such pts.

Selective Laser Sintering of Porous Silica Enabled by Carbon Additive.

PubMed

Chang, Shuai; Li, Liqun; Lu, Li; Fuh, Jerry Ying Hsi

2017-11-16

The aim of this study is to investigate the possibility of a freeform fabrication of porous ceramic parts through selective laser sintering (SLS). SLS was proposed to manufacture ceramic green parts because this additive manufacturing technique can be used to fabricate three-dimensional objects directly without a mold, and the technique has the capability of generating porous ceramics with controlled porosity. However, ceramic printing has not yet fully achieved its 3D fabrication capabilities without using polymer binder. Except for the limitations of high melting point, brittleness, and low thermal shock resistance from ceramic material properties, the key obstacle lies in the very poor absorptivity of oxide ceramics to fiber laser, which is widely installed in commercial SLS equipment. An alternative solution to overcome the poor laser absorptivity via improving material compositions is presented in this study. The positive effect of carbon additive on the absorptivity of silica powder to fiber laser is discussed. To investigate the capabilities of the SLS process, 3D porous silica structures were successfully prepared and characterized.

Can somatosensory and visual evoked potentials predict neurological outcome during targeted temperature management in post cardiac arrest patients?

PubMed

Choi, Seung Pill; Park, Kyu Nam; Wee, Jung Hee; Park, Jeong Ho; Youn, Chun Song; Kim, Han Joon; Oh, Sang Hoon; Oh, Yoon Sang; Kim, Soo Hyun; Oh, Joo Suk

2017-10-01

In cardiac arrest patients treated with targeted temperature management (TTM), it is not certain if somatosensory evoked potentials (SEPs) and visual evoked potentials (VEPs) can predict neurological outcomes during TTM. The aim of this study was to investigate the prognostic value of SEPs and VEPs during TTM and after rewarming. This retrospective cohort study included comatose patients resuscitated from cardiac arrest and treated with TTM between March 2007 and July 2015. SEPs and VEPs were recorded during TTM and after rewarming in these patients. Neurological outcome was assessed at discharge by the Cerebral Performance Category (CPC) Scale. In total, 115 patients were included. A total of 175 SEPs and 150 VEPs were performed. Five SEPs during treated with TTM and nine SEPs after rewarming were excluded from outcome prediction by SEPs due to an indeterminable N20 response because of technical error. Using 80 SEPs and 85 VEPs during treated with TTM, absent SEPs yielded a sensitivity of 58% and a specificity of 100% for poor outcome (CPC 3-5), and absent VEPs predicted poor neurological outcome with a sensitivity of 44% and a specificity of 96%. The AUC of combination of SEPs and VEPs was superior to either test alone (0.788 for absent SEPs and 0.713 for absent VEPs compared with 0.838 for the combination). After rewarming, absent SEPs and absent VEPs predicted poor neurological outcome with a specificity of 100%. When SEPs and VEPs were combined, VEPs slightly increased the prognostic accuracy of SEPs alone. Although one patient with absent VEP during treated with TTM had a good neurological outcome, none of the patients with good neurological outcome had an absent VEP after rewarming. Absent SEPs could predict poor neurological outcome during TTM as well as after rewarming. Absent VEPs may predict poor neurological outcome in both periods and VEPs may provide additional prognostic value in outcome prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

Studies on adaptation to complete dentures. Part II: Oral stereognosis and tactile sensibility.

PubMed

Müller, F; Link, I; Fuhr, K; Utz, K H

1995-10-01

High oral perception is thought to contribute to poor adaptation to new dentures. The aim of this study was to evaluate the oral stereognosis and tactile sensibility in edentate subjects and relate these to patient age and capability of adaptation to new prostheses. A total of 67 patients were provided with new complete dentures 2-3 weeks before the experiment. In 54 subjects, the oral stereognosis was evaluated by 12 different test-pieces, which were placed unseen on the tongue and had to be recognized. In 38 patients, the oral tactile sensibility was determined in the premolar area using copper foils. The capability of adaptation was evaluated by a questionnaire. Denture retention was assessed by clinical examination. The number of correctly identified test-pieces and the average identification time were related to the age, but no relation was found to patients' capability of adaptation. The tactile sensibility was found to be impaired with age and diminished capability of adaptation. Both adaptation and oral tactile sensibility were significantly lower in subjects with poor lower-denture retention. In conclusion, the results cannot support a relationship between high oral stereognosis and adaptation problems. However, good denture retention facilitates the adaptation process.

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.

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).

Southern Ocean bottom water characteristics in CMIP5 models

NASA Astrophysics Data System (ADS)

Heuzé, CéLine; Heywood, Karen J.; Stevens, David P.; Ridley, Jeff K.

2013-04-01

Southern Ocean deep water properties and formation processes in climate models are indicative of their capability to simulate future climate, heat and carbon uptake, and sea level rise. Southern Ocean temperature and density averaged over 1986-2005 from 15 CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models are compared with an observed climatology, focusing on bottom water. Bottom properties are reasonably accurate for half the models. Ten models create dense water on the Antarctic shelf, but it mixes with lighter water and is not exported as bottom water as in reality. Instead, most models create deep water by open ocean deep convection, a process occurring rarely in reality. Models with extensive deep convection are those with strong seasonality in sea ice. Optimum bottom properties occur in models with deep convection in the Weddell and Ross Gyres. Bottom Water formation processes are poorly represented in ocean models and are a key challenge for improving climate predictions.

Zooming in on neutrino oscillations with DUNE

NASA Astrophysics Data System (ADS)

Srivastava, Rahul; Ternes, Christoph A.; Tórtola, Mariam; Valle, José W. F.

2018-05-01

We examine the capabilities of the DUNE experiment as a probe of the neutrino mixing paradigm. Taking the current status of neutrino oscillations and the design specifications of DUNE, we determine the experiment's potential to probe the structure of neutrino mixing and C P violation. We focus on the poorly determined parameters θ23 and δC P and consider both two and seven years of run. We take various benchmarks as our true values, such as the current preferred values of θ23 and δC P, as well as several theory-motivated choices. We determine quantitatively DUNE's potential to perform a precision measurement of θ23, as well as to test the C P violation hypothesis in a model-independent way. We find that, after running for seven years, DUNE will make a substantial step in the precise determination of these parameters, bringing to quantitative test the predictions of various theories of neutrino mixing.

Traditional and emerging molecular markers in neuroblastoma prognosis: the good, the bad and the ugly.

PubMed

Poremba, C; Hero, B; Goertz, H G; Scheel, C; Wai, D; Schaefer, K L; Christiansen, H; Berthold, F; Juergens, H; Boecker, W; Dockhorn-Dworniczak, B

2001-01-01

Neuroblastomas (NB) are a heterogeneous group of childhood tumours with a wide range of likelihood for tumour progression. As traditional parameters do not ensure completely accurate prognostic grouping, new molecular markers are needed for assessing the individual patient's prognosis more precisely. 133 NB of all stages were analysed in blind-trial fashion for telomerase activity (TA), expression of surviving, and MYCN status. These data were correlated with other traditional prognostic indicators and disease outcome. TA is a powerful independent prognostic marker for all stages and is capable of differentiating between good and poor outcome in putative "favourable" clinical or biological subgroups of NB patients. High surviving expression is associated with an adverse outcome, but is more difficult to interprete than TA because survivin expression needs to be accurately quantified to be of predictive value. We propose an extended progression model for NB including emerging prognostic markers, with emphasis on telomerase activity.

Impact of airway morphological changes on pulmonary flows in scoliosis

NASA Astrophysics Data System (ADS)

Farrell, James; Garrido, Enrique; Valluri, Prashant

2016-11-01

The relationship between thoracic deformity in scoliosis and lung function is poorly understood. In a pilot study, we reviewed computed tomography (CT) routine scans of patients undergoing scoliosis surgery. The CT scans were processed to segment the anatomy of the airways, lung and spine. A three-dimensional model was created to study the anatomical relationship. Preliminary analysis showed significant airway morphological differences depending on the anterior position of the spine. A computational fluid dynamics (CFD) study was also conducted on the airway geometry using the inspiratory scans. The CFD model assuming non-compliant airway walls was capable of showing pressure drops in areas of high airway resistance, but was unable to predict regional ventilation differences. Our results indicate a dependence between the dynamic deformation of the airway during breathing and lung function. Dynamic structural deformation must therefore be incorporated within any modelling approaches to guide clinicians on the decision to perform surgical correction of the scoliosis.

Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural networks, and functional trees methods

NASA Astrophysics Data System (ADS)

Pham, Binh Thai; Tien Bui, Dieu; Pourghasemi, Hamid Reza; Indra, Prakash; Dholakia, M. B.

2017-04-01

The objective of this study is to make a comparison of the prediction performance of three techniques, Functional Trees (FT), Multilayer Perceptron Neural Networks (MLP Neural Nets), and Naïve Bayes (NB) for landslide susceptibility assessment at the Uttarakhand Area (India). Firstly, a landslide inventory map with 430 landslide locations in the study area was constructed from various sources. Landslide locations were then randomly split into two parts (i) 70 % landslide locations being used for training models (ii) 30 % landslide locations being employed for validation process. Secondly, a total of eleven landslide conditioning factors including slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to lineaments, distance to rivers, and rainfall were used in the analysis to elucidate the spatial relationship between these factors and landslide occurrences. Feature selection of Linear Support Vector Machine (LSVM) algorithm was employed to assess the prediction capability of these conditioning factors on landslide models. Subsequently, the NB, MLP Neural Nets, and FT models were constructed using training dataset. Finally, success rate and predictive rate curves were employed to validate and compare the predictive capability of three used models. Overall, all the three models performed very well for landslide susceptibility assessment. Out of these models, the MLP Neural Nets and the FT models had almost the same predictive capability whereas the MLP Neural Nets (AUC = 0.850) was slightly better than the FT model (AUC = 0.849). The NB model (AUC = 0.838) had the lowest predictive capability compared to other models. Landslide susceptibility maps were final developed using these three models. These maps would be helpful to planners and engineers for the development activities and land-use planning.

Added value of delayed computed tomography angiography in primary intracranial hemorrhage and hematoma size for predicting spot sign.

PubMed

Wu, Te Chang; Chen, Tai Yuan; Shiue, Yow Ling; Chen, Jeon Hor; Hsieh, Tsyh-Jyi; Ko, Ching Chung; Lin, Ching Po

2018-04-01

Background The computed tomography angiography (CTA) spot sign represents active contrast extravasation within acute primary intracerebral hemorrhage (ICH) and is an independent predictor of hematoma expansion (HE) and poor clinical outcomes. The spot sign could be detected on first-pass CTA (fpCTA) or delayed CTA (dCTA). Purpose To investigate the additional benefits of dCTA spot sign in primary ICH and hematoma size for predicting spot sign. Material and Methods This is a retrospective study of 100 patients who underwent non-contrast CT (NCCT) and CTA within 24 h of onset of primary ICH. The presence of spot sign on fpCTA or dCTA, and hematoma size on NCCT were recorded. The spot sign on fpCTA or dCTA for predicting significant HE, in-hospital mortality, and poor clinical outcomes (mRS ≥ 4) are calculated. The hematoma size for prediction of CTA spot sign was also analyzed. Results Only the spot sign on dCTA could predict high risk of significant HE and poor clinical outcomes as on fpCTA ( P < 0.05). With dCTA, there is increased sensitivity and negative predictive value (NPV) for predicting significant HE, in-hospital mortality, and poor clinical outcomes. The XY value (product of the two maximum perpendicular axial dimensions) is the best predictor (area under the curve [AUC] = 0.82) for predicting spot sign on fpCTA or dCTA in the absence of intraventricular and subarachnoid hemorrhage. Conclusion This study clarifies that dCTA imaging could improve predictive performance of CTA in primary ICH. Furthermore, the XY value is the best predictor for CTA spot sign.

ECOSAR model performance with a large test set of industrial chemicals.

PubMed

Reuschenbach, Peter; Silvani, Maurizio; Dammann, Martina; Warnecke, Dietmar; Knacker, Thomas

2008-05-01

The widely used ECOSAR computer programme for QSAR prediction of chemical toxicity towards aquatic organisms was evaluated by using large data sets of industrial chemicals with varying molecular structures. Experimentally derived toxicity data covering acute effects on fish, Daphnia and green algae growth inhibition of in total more than 1,000 randomly selected substances were compared to the prediction results of the ECOSAR programme in order (1) to assess the capability of ECOSAR to correctly classify the chemicals into defined classes of aquatic toxicity according to rules of EU regulation and (2) to determine the number of correct predictions within tolerance factors from 2 to 1,000. Regarding ecotoxicity classification, 65% (fish), 52% (Daphnia) and 49% (algae) of the substances were correctly predicted into the classes "not harmful", "harmful", "toxic" and "very toxic". At all trophic levels about 20% of the chemicals were underestimated in their toxicity. The class of "not harmful" substances (experimental LC/EC(50)>100 mg l(-1)) represents nearly half of the whole data set. The percentages for correct predictions of toxic effects on fish, Daphnia and algae growth inhibition were 69%, 64% and 60%, respectively, when a tolerance factor of 10 was allowed. Focussing on those experimental results which were verified by analytically measured concentrations, the predictability for Daphnia and algae toxicity was improved by approximately three percentage points, whereas for fish no improvement was determined. The calculated correlation coefficients demonstrated poor correlation when the complete data set was taken, but showed good results for some of the ECOSAR chemical classes. The results are discussed in the context of literature data on the performance of ECOSAR and other QSAR models.

Is decision-making ability related to food choice and facets of eating behaviour in adolescents?

PubMed

Macchi, Rosemarie; MacKew, Laura; Davis, Caroline

2017-09-01

To test the prediction that poor decision-making would predict poor eating-related behaviours, which in turn would relate to elevated body mass index (BMI) percentile. Associations among decision-making ability, eating behaviours, and BMI percentile were examined in a sample of 311 healthy male and female adolescents, aged 14-18 years. Structural equation modelling was used to test the proposed relationships. The predicted model was a good fit to the data and all paths between latent and indicator variables were significant. Impulsive responding significantly predicted poor food choice and overeating. No significant relationships emerged between eating-related variables and BMI percentile. Findings from this study extend the existing research in adults and offer a more comprehensive understanding of factors that may contribute to eating behaviours and weight status in teenagers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Elevated platelet count as predictor of recurrence in rectal cancer patients undergoing preoperative chemoradiotherapy followed by surgery.

PubMed

Toiyama, Yuji; Inoue, Yasuhiro; Kawamura, Mikio; Kawamoto, Aya; Okugawa, Yoshinaga; Hiro, Jyunichiro; Saigusa, Susumu; Tanaka, Koji; Mohri, Yasuhiko; Kusunoki, Masato

2015-02-01

The impact of systemic inflammatory response (SIR) on prognostic and predictive outcome in rectal cancer after neoadjuvant chemoradiotherapy (CRT) has not been fully investigated. This retrospective study enrolled 89 patients with locally advanced rectal cancer who underwent neoadjuvant CRT and for whom platelet (PLT) counts and SIR status [neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR)] were available. Both clinical values of PLT and SIR status in rectal cancer patients were investigated. Elevated PLT, NLR, PLR, and pathologic TNM stage III [ypN(+)] were associated with significantly poor overall survival (OS). Elevated PLT, NLR, and ypN(+) were shown to independently predict OS. Elevated PLT and ypN(+) significantly predicted poor disease-free survival (DFS). Elevated PLT was identified as the only independent predictor of DFS. PLT counts are a promising pre-CRT biomarker for predicting recurrence and poor prognosis in rectal cancer.

Poverty and behavior problems trajectories from 1.5 to 8 years of age: Is the gap widening between poor and non-poor children?

PubMed

Mazza, Julia Rachel S E; Boivin, Michel; Tremblay, Richard E; Michel, Gregory; Salla, Julie; Lambert, Jean; Zunzunegui, Maria Victoria; Côté, Sylvana M

2016-08-01

Poverty has been associated with high levels of behavior problems across childhood, yet patterns of associations over time remain understudied. This study aims: (a) to examine whether poverty predicts changes in behavior problems between 1.5 and 8 years of age; (b) to estimate potential selection bias for the observed associations. We used the 1998-2006 waves of the Quebec Longitudinal Study of Child Development (N = 2120). Main outcomes were maternal ratings of hyperactivity, opposition and physical aggression from 1.5 to 8 years of age. Linear mixed-effects models were used to assess the longitudinal association between poverty and behavior problems. Models were re-estimated adjusting for wave nonresponse and using multiple imputation to account for attrition. Poverty predicted higher levels of behavior problems between 1.5 and 8 years of age. Poverty predicted hyperactivity and opposition in a time dependent manner. Hyperactivity [Bpoverty*age = 0.052; CI 95 % (0.002; 0.101)] and opposition [Bpoverty*age = 0.049; CI 95 % (0.018; 0.079)] increased at a faster rate up to age 5 years, and then decreased at a slower rate for poor than non-poor children. Physical aggression decreased at a steady rate over time for all children [Bpoverty*age = -0.030; p = 0.064). Estimates remained similar when accounting for attrition. Poverty predicted higher levels of behavior problems between 1.5 and 8 years of age. The difference between poor and non-poor children was stable over time for physical aggression, but increased with age for hyperactivity and opposition. Attrition among poor children did not compromise the validity of results.

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...

Phonology and Handedness in Primary School: Predictions of the Right Shift Theory

ERIC Educational Resources Information Center

Smythe, Pamela; Annett, Marian

2006-01-01

Background: The right shift (RS) theory of handedness suggests that poor phonology may occur in the general population as a risk associated with absence of an agent of left cerebral speech, the hypothesised RS + gene. The theory predicts that poor phonology is associated with reduced bias to right-handedness. Methods: A representative cohort of…

Computational Analysis of Advanced Shape-Memory Alloy Devices Through a Robust Modeling Framework

NASA Astrophysics Data System (ADS)

Scalet, Giulia; Conti, Michele; Auricchio, Ferdinando

2017-06-01

Shape-memory alloys (SMA) provide significant advantages in various industrial fields, but their manufacturing and commercialization are currently hindered. This is attributed mainly to the poor knowledge of material behavior and the lack of standards in its mechanical characterization. SMA products are usually developed by trial-and-error testing to address specific design requirements, thus increasing costs and time. The development of simulation tools offers a possible solution to assist engineers and designers and allows to better understand SMA transformation phenomena. Accordingly, the purpose of the present paper is to numerically analyze and predict the response of spring-like actuators and septal occluders, which are industrial components exploiting the shape-memory and pseudoelastic properties of SMAs, respectively. The methodology includes two main stages: the implementation of the three-dimensional phenomenological model known as Souza- Auricchio model and the finite element modeling of the device. A discussion about the steps of each stage, as parameter identification and model generalizations, is provided. Validation results are presented through a comparison with the results of a performed experimental campaign. The framework proves good prediction capabilities and allows to reduce the number of experimental tests in the future.

A hybrid degradation tendency measurement method for mechanical equipment based on moving window and Grey-Markov model

NASA Astrophysics Data System (ADS)

Jiang, Wei; Zhou, Jianzhong; Zheng, Yang; Liu, Han

2017-11-01

Accurate degradation tendency measurement is vital for the secure operation of mechanical equipment. However, the existing techniques and methodologies for degradation measurement still face challenges, such as lack of appropriate degradation indicator, insufficient accuracy, and poor capability to track the data fluctuation. To solve these problems, a hybrid degradation tendency measurement method for mechanical equipment based on a moving window and Grey-Markov model is proposed in this paper. In the proposed method, a 1D normalized degradation index based on multi-feature fusion is designed to assess the extent of degradation. Subsequently, the moving window algorithm is integrated with the Grey-Markov model for the dynamic update of the model. Two key parameters, namely the step size and the number of states, contribute to the adaptive modeling and multi-step prediction. Finally, three types of combination prediction models are established to measure the degradation trend of equipment. The effectiveness of the proposed method is validated with a case study on the health monitoring of turbine engines. Experimental results show that the proposed method has better performance, in terms of both measuring accuracy and data fluctuation tracing, in comparison with other conventional methods.

An inexpensive and portable drill rig for bedrock groundwater studies in headwater catchments

Treesearch

C. Gabrielli; J.J. McDonnell

2011-01-01

Bedrock groundwater dynamics in headwater catchments are poorly understood and poorly characterized. Here, we present an inexpensive and portable bedrock drilling system designed for use in remote locations. Our system is capable of drilling bedrock wells up to 11 m deep and 38 mm in diameter in a wide range of bedrock types. The drill consists of a lawn mower engine...

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

Casella, Amanda J.; Hylden, Laura R.; Campbell, Emily L.

Knowledge of real-time solution properties and composition is a necessity for any spent nuclear fuel reprocessing method. Metal-ligand speciation in aqueous solutions derived from the dissolved commercial spent fuel is highly dependent upon the acid concentration/pH, which influences extraction efficiency and the resulting speciation in the organic phase. Spectroscopic process monitoring capabilities, incorporated in a counter current centrifugal contactor bank, provide a pathway for on-line real-time measurement of solution pH. The spectroscopic techniques are process-friendly and can be easily configured for on-line applications, while classic potentiometric pH measurements require frequent calibration/maintenance and have poor long-term stability in aggressive chemical andmore » radiation environments. Our research is focused on developing a general method for on-line determination of pH of aqueous solutions through chemometric analysis of Raman spectra. Interpretive quantitative models have been developed and validated under the range of chemical composition and pH using a lactic acid/lactate buffer system. The developed model was applied to spectra obtained on-line during solvent extractions performed in a centrifugal contactor bank. The model predicted the pH within 11% for pH > 2, thus demonstrating that this technique could provide the capability of monitoring pH on-line in applications such as nuclear fuel reprocessing.« less

Phytoremediation of landfill leachate.

PubMed

Jones, D L; Williamson, K L; Owen, A G

2006-01-01

Leachate emissions from landfill sites are of concern, primarily due to their toxic impact when released unchecked into the environment, and the potential for landfill sites to generate leachate for many hundreds of years following closure. Consequently, economically and environmentally sustainable disposal options are a priority in waste management. One potential option is the use of soil-plant based remediation schemes. In many cases, using either trees (including short rotation coppice) or grassland, phytoremediation of leachate has been successful. However, there are a significant number of examples where phytoremediation has failed. Typically, this failure can be ascribed to excessive leachate application and poor management due to a fundamental lack of understanding of the plant-soil system. On balance, with careful management, phytoremediation can be viewed as a sustainable, cost effective and environmentally sound option which is capable of treating 250m(3)ha(-1)yr(-1). However, these schemes have a requirement for large land areas and must be capable of responding to changes in leachate quality and quantity, problems of scheme establishment and maintenance, continual environmental monitoring and seasonal patterns of plant growth. Although the fundamental underpinning science is well understood, further work is required to create long-term predictive remediation models, full environmental impact assessments, a complete life-cycle analysis and economic analyses for a wide range of landfill scenarios.

A Comparison of Vibration and Oil Debris Gear Damage Detection Methods Applied to Pitting Damage

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.

2000-01-01

Helicopter Health Usage Monitoring Systems (HUMS) must provide reliable, real-time performance monitoring of helicopter operating parameters to prevent damage of flight critical components. Helicopter transmission diagnostics are an important part of a helicopter HUMS. In order to improve the reliability of transmission diagnostics, many researchers propose combining two technologies, vibration and oil monitoring, using data fusion and intelligent systems. Some benefits of combining multiple sensors to make decisions include improved detection capabilities and increased probability the event is detected. However, if the sensors are inaccurate, or the features extracted from the sensors are poor predictors of transmission health, integration of these sensors will decrease the accuracy of damage prediction. For this reason, one must verify the individual integrity of vibration and oil analysis methods prior to integrating the two technologies. This research focuses on comparing the capability of two vibration algorithms, FM4 and NA4, and a commercially available on-line oil debris monitor to detect pitting damage on spur gears in the NASA Glenn Research Center Spur Gear Fatigue Test Rig. Results from this research indicate that the rate of change of debris mass measured by the oil debris monitor is comparable to the vibration algorithms in detecting gear pitting damage.

The NASA/USDA Reservoir and Lake Monitor: Present and Future Capabilities and Water Resources Applications

NASA Astrophysics Data System (ADS)

Birkett, C. M.; Beckley, B. D.; Reynolds, C. A.; Brakenridge, G. R.; Ricko, M.

2013-12-01

The USDA/NASA Global Reservoir and Lake Monitor (GRLM) provides satellite-based surface water level products for large reservoirs and lakes around the world. It utilizes a suite of NASA/CNES and ESA radar altimetry data sets and outputs near real time and archival products via a web interface. Several stakeholders utilize the products for applications that focus on water resources management and natural hazards mitigation, particularly in arid and semi-arid regions. The satellite data sets prove particularly useful in un-gauged or poorly gauged basins where in situ data is sparse. Here, we present water-level product examples based on data from the NASA/CNES Jason-2/OSTM mission, and the new ISRO/CNES SARAL mission. We also demonstrate product application from the viewpoint of various end users who have interests ranging from crop production and fisheries, to regional security and climate change. In the current phase of the program the team is also looking to the potential of additional lake/reservoir products such as areal extent (NASA/MODIS), lake volume variations (combined altimetry/imagery), and model-derived water levels, that will enhance the GRLM via improved observation and prediction, and provide a more global lake basin monitoring capability. Surface water level variations for Lake Nasser.

High Fidelity Ion Beam Simulation of High Dose Neutron Irradiation

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

Was, Gary; Wirth, Brian; Motta, Athur

The objective of this proposal is to demonstrate the capability to predict the evolution of microstructure and properties of structural materials in-reactor and at high doses, using ion irradiation as a surrogate for reactor irradiations. “Properties” includes both physical properties (irradiated microstructure) and the mechanical properties of the material. Demonstration of the capability to predict properties has two components. One is ion irradiation of a set of alloys to yield an irradiated microstructure and corresponding mechanical behavior that are substantially the same as results from neutron exposure in the appropriate reactor environment. Second is the capability to predict the irradiatedmore » microstructure and corresponding mechanical behavior on the basis of improved models, validated against both ion and reactor irradiations and verified against ion irradiations. Taken together, achievement of these objectives will yield an enhanced capability for simulating the behavior of materials in reactor irradiations.« less

Developmental Course of Impulsivity and Capability from Age 10 to Age 25 as Related to Trajectory of Suicide Attempt in a Community Cohort

ERIC Educational Resources Information Center

Kasen, Stephanie; Cohen, Patricia; Chen, Henian

2011-01-01

Hierarchical linear models were used to examine trajectories of impulsivity and capability between ages 10 and 25 in relation to suicide attempt in 770 youths followed longitudinally: intercepts were set at age 17. The impulsivity measure assessed features of urgency (e.g., poor control, quick provocation, and disregard for external constraints);…

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

DOE PAGES

Lewis, John R.; Zhang, Adah; Anderson-Cook, Christine Michaela

2017-10-29

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X) of some underlying causal model producing the observables or responses (Y = g ( X) + error). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research inmore » which inverse predictions, along with an assessment of predictive capability, are desired.« less

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

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

Lewis, John R.; Zhang, Adah; Anderson-Cook, Christine Michaela

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X) of some underlying causal model producing the observables or responses (Y = g ( X) + error). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research inmore » which inverse predictions, along with an assessment of predictive capability, are desired.« less

Evaluation of prediction capability, robustness, and sensitivity in non-linear landslide susceptibility models, Guantánamo, Cuba

NASA Astrophysics Data System (ADS)

Melchiorre, C.; Castellanos Abella, E. A.; van Westen, C. J.; Matteucci, M.

2011-04-01

This paper describes a procedure for landslide susceptibility assessment based on artificial neural networks, and focuses on the estimation of the prediction capability, robustness, and sensitivity of susceptibility models. The study is carried out in the Guantanamo Province of Cuba, where 186 landslides were mapped using photo-interpretation. Twelve conditioning factors were mapped including geomorphology, geology, soils, landuse, slope angle, slope direction, internal relief, drainage density, distance from roads and faults, rainfall intensity, and ground peak acceleration. A methodology was used that subdivided the database in 3 subsets. A training set was used for updating the weights. A validation set was used to stop the training procedure when the network started losing generalization capability, and a test set was used to calculate the performance of the network. A 10-fold cross-validation was performed in order to show that the results are repeatable. The prediction capability, the robustness analysis, and the sensitivity analysis were tested on 10 mutually exclusive datasets. The results show that by means of artificial neural networks it is possible to obtain models with high prediction capability and high robustness, and that an exploration of the effect of the individual variables is possible, even if they are considered as a black-box model.

Toward a Public Toxicogenomics Capability for Supporting Predictive Toxicology: Survey of Current Resources and Chemical Indexing of Experiments in GEO and ArrayExpress

EPA Science Inventory

A publicly available toxicogenomics capability for supporting predictive toxicology and meta-analysis depends on availability of gene expression data for chemical treatment scenarios, the ability to locate and aggregate such information by chemical, and broad data coverage within...

Wind tunnel wall effects in a linear oscillating cascade

NASA Technical Reports Server (NTRS)

Buffum, Daniel H.; Fleeter, Sanford

1991-01-01

Experiments in a linear oscillating cascade reveal that the wind tunnel walls enclosing the airfoils have, in some cases, a detrimental effect on the oscillating cascade aerodynamics. In a subsonic flow field, biconvex airfoils are driven simultaneously in harmonic, torsion-mode oscillations for a range of interblade phase angle values. It is found that the cascade dynamic periodicity - the airfoil to airfoil variation in unsteady surface pressure - is good for some values of interblade phase angle but poor for others. Correlation of the unsteady pressure data with oscillating flat plate cascade predictions is generally good for conditions where the periodicity is good and poor where the periodicity is poor. Calculations based upon linearized unsteady aerodynamic theory indicate that pressure waves reflected from the wind tunnel walls are responsible for the cases where there is poor periodicity and poor correlation with the predictions.

High Tumor Volume to Fetal Weight Ratio Is Associated with Worse Fetal Outcomes and Increased Maternal Risk in Fetuses with Sacrococcygeal Teratoma.

PubMed

Gebb, Juliana S; Khalek, Nahla; Qamar, Huma; Johnson, Mark P; Oliver, Edward R; Coleman, Beverly G; Peranteau, William H; Hedrick, Holly L; Flake, Alan W; Adzick, N Scott; Moldenhauer, Julie S

2018-03-01

Tumor volume to fetal weight ratio (TFR) > 0.12 before 24 weeks has been associated with poor outcome in fetuses with sacrococcygeal teratoma (SCT). We evaluated TFR in predicting poor fetal outcome and increased maternal operative risk in our cohort of SCT pregnancies. This is a retrospective, single-center review of fetuses seen with SCT from 1997 to 2015. Patients who chose termination of pregnancy (TOP), delivered elsewhere, or had initial evaluation at > 24 weeks were excluded. Receiver operating characteristic (ROC) analysis determined the optimal TFR to predict poor fetal outcome and increased maternal operative risk. Poor fetal outcome included fetal demise, neonatal demise, or fetal deterioration warranting open fetal surgery or delivery < 32 weeks. Increased maternal operative risk included cases necessitating open fetal surgery, classical cesarean delivery, or ex utero intrapartum treatment (EXIT). Of 139 pregnancies with SCT, 27 chose TOP, 14 delivered elsewhere, and 40 had initial evaluation at > 24 weeks. Thus, 58 fetuses were reviewed. ROC analysis revealed that at ≤24 weeks, TFR > 0.095 was predictive of poor fetal outcome and TFR > 0.12 was predictive of increased maternal operative risk. This study supports the use of TFR at ≤24 weeks for risk stratification of pregnancies with SCT. © 2018 S. Karger AG, Basel.

Circulating basal anti-Müllerian hormone levels as predictor of ovarian response in women undergoing ovarian stimulation for in vitro fertilization.

PubMed

Nardo, Luciano G; Gelbaya, Tarek A; Wilkinson, Hannah; Roberts, Stephen A; Yates, Allen; Pemberton, Phil; Laing, Ian

2009-11-01

To evaluate the clinical value of basal anti-Müllerian hormone (AMH) measurements compared with other available determinants, apart from chronologic age, in the prediction of ovarian response to gonadotrophin stimulation. Prospective cohort study. Tertiary referral center for reproductive medicine and an IVF unit. Women undergoing their first cycle of controlled ovarian hyperstimulation (COH) for in vitro fertilization (IVF). Basal levels of FSH and AMH as well as antral follicle count (AFC) were measured in 165 subjects. All patients were followed prospectively and their cycle outcomes recorded. Predictive value of FSH, AMH, and AFC for extremes of ovarian response to stimulation. Out of the 165 women, 134 were defined as normal responders, 15 as poor responders, and 16 as high responders. Subjects in the poor response group were significantly older then those in the other two groups. Anti-Müllerian hormone levels and AFC were markedly raised in the high responders and decreased in the poor responders. Compared with FSH and AFC, AMH performed better in the prediction of excessive response to ovarian stimulation-AMH area under receiver operating characteristic curve (ROC(AUC)) 0.81, FSH ROC(AUC) 0.66, AFC ROC(AUC) 0.69. For poor response, AMH (ROC(AUC) 0.88) was a significantly better predictor than FSH (ROC(AUC) 0.63) but not AFC (ROC(AUC) 0.81). AMH prediction of ovarian response was independent of age and PCOS. Anti-Müllerian hormone cutoffs of >3.75 ng/mL and <1.0 ng/mL would have modest sensitivity and specificity in predicting the extremes of response. Circulating AMH has the ability to predict excessive and poor response to stimulation with exogenous gonadotrophins. Overall, this biomarker is superior to basal FSH and AFC, and has the potential to be incorporated in to work-up protocols to predict patient's ovarian response to treatment and to individualize strategies aiming at reducing the cancellation rate and the iatrogenic complications of COH.

Towards cheminformatics-based estimation of drug therapeutic index: Predicting the protective index of anticonvulsants using a new quantitative structure-index relationship approach.

PubMed

Chen, Shangying; Zhang, Peng; Liu, Xin; Qin, Chu; Tao, Lin; Zhang, Cheng; Yang, Sheng Yong; Chen, Yu Zong; Chui, Wai Keung

2016-06-01

The overall efficacy and safety profile of a new drug is partially evaluated by the therapeutic index in clinical studies and by the protective index (PI) in preclinical studies. In-silico predictive methods may facilitate the assessment of these indicators. Although QSAR and QSTR models can be used for predicting PI, their predictive capability has not been evaluated. To test this capability, we developed QSAR and QSTR models for predicting the activity and toxicity of anticonvulsants at accuracy levels above the literature-reported threshold (LT) of good QSAR models as tested by both the internal 5-fold cross validation and external validation method. These models showed significantly compromised PI predictive capability due to the cumulative errors of the QSAR and QSTR models. Therefore, in this investigation a new quantitative structure-index relationship (QSIR) model was devised and it showed improved PI predictive capability that superseded the LT of good QSAR models. The QSAR, QSTR and QSIR models were developed using support vector regression (SVR) method with the parameters optimized by using the greedy search method. The molecular descriptors relevant to the prediction of anticonvulsant activities, toxicities and PIs were analyzed by a recursive feature elimination method. The selected molecular descriptors are primarily associated with the drug-like, pharmacological and toxicological features and those used in the published anticonvulsant QSAR and QSTR models. This study suggested that QSIR is useful for estimating the therapeutic index of drug candidates. Copyright © 2016. Published by Elsevier Inc.

Shuttle Entry Imaging Using Infrared Thermography

NASA Technical Reports Server (NTRS)

Horvath, Thomas; Berry, Scott; Alter, Stephen; Blanchard, Robert; Schwartz, Richard; Ross, Martin; Tack, Steve

2007-01-01

During the Columbia Accident Investigation, imaging teams supporting debris shedding analysis were hampered by poor entry image quality and the general lack of information on optical signatures associated with a nominal Shuttle entry. After the accident, recommendations were made to NASA management to develop and maintain a state-of-the-art imagery database for Shuttle engineering performance assessments and to improve entry imaging capability to support anomaly and contingency analysis during a mission. As a result, the Space Shuttle Program sponsored an observation campaign to qualitatively characterize a nominal Shuttle entry over the widest possible Mach number range. The initial objectives focused on an assessment of capability to identify/resolve debris liberated from the Shuttle during entry, characterization of potential anomalous events associated with RCS jet firings and unusual phenomenon associated with the plasma trail. The aeroheating technical community viewed the Space Shuttle Program sponsored activity as an opportunity to influence the observation objectives and incrementally demonstrate key elements of a quantitative spatially resolved temperature measurement capability over a series of flights. One long-term desire of the Shuttle engineering community is to calibrate boundary layer transition prediction methodologies that are presently part of the Shuttle damage assessment process using flight data provided by a controlled Shuttle flight experiment. Quantitative global imaging may offer a complementary method of data collection to more traditional methods such as surface thermocouples. This paper reviews the process used by the engineering community to influence data collection methods and analysis of global infrared images of the Shuttle obtained during hypersonic entry. Emphasis is placed upon airborne imaging assets sponsored by the Shuttle program during Return to Flight. Visual and IR entry imagery were obtained with available airborne imaging platforms used within DoD along with agency assets developed and optimized for use during Shuttle ascent to demonstrate capability (i.e., tracking, acquisition of multispectral data, spatial resolution) and identify system limitations (i.e., radiance modeling, saturation) using state-of-the-art imaging instrumentation and communication systems. Global infrared intensity data have been transformed to temperature by comparison to Shuttle flight thermocouple data. Reasonable agreement is found between the flight thermography images and numerical prediction. A discussion of lessons learned and potential application to a potential Shuttle boundary layer transition flight test is presented.

Value of neutrophil-to-lymphocyte ratio for predicting lung cancer prognosis: A meta-analysis of 7,219 patients.

PubMed

Yu, Yu; Qian, Lei; Cui, Jiuwei

2017-09-01

Current evidence suggests that the neutrophil-to-lymphocyte ratio (NLR) may be a biomarker for poor prognosis in lung cancer, although this association remains controversial. Therefore, a meta-analysis was performed to evaluate the association between NLR and lung cancer outcome. A systematic literature search was performed through the PubMed, Embase and Cochrane Library databases (until July 30, 2016), to identify studies evaluating the association between NLR and overall survival (OS) and/or progression-free survival (PFS) among patients with lung cancer. Based on the results of this search, data from 18 studies involving 7,219 patients with lung cancer were evaluated. The pooled hazard ratio (HR) suggested that elevated pretreatment NLR predicted poor OS [HR=1.46, 95% confidence interval (CI): 1.30-1.64] and poor PFS (HR=1.42, 95% CI: 1.15-1.75) among patients with lung cancer. Subgroup analysis revealed that the prognostic value of NLR for predicting poor OS increased among patients who underwent surgery (HR=1.50, 95% CI: 1.21-1.84) or patients with early-stage disease (HR=1.64, 95% CI: 1.37-1.97). An NLR cut-off value of ≥4 significantly predicted poor OS (HR=1.56, 95% CI: 1.31-1.85) and PFS (HR=1.54, 95% CI: 1.13-1.82), particularly in the cases of small-cell lung cancer. Thus, the results of the present meta-analysis suggested that an elevated pretreatment NLR (e.g., ≥4) may be considered as a biomarker for poor prognosis in patients with lung cancer.

A correlational approach to predicting operator status

NASA Technical Reports Server (NTRS)

Shingledecker, Clark A.

1988-01-01

This paper discusses a research approach for identifying and validating candidate physiological and behavioral parameters which can be used to predict the performance capabilities of aircrew and other system operators. In this methodology, concurrent and advance correlations are computed between predictor values and criterion performance measures. Continuous performance and sleep loss are used as stressors to promote performance variation. Preliminary data are presented which suggest dependence of prediction capability on the resource allocation policy of the operator.

Blend sign predicts poor outcome in patients with intracerebral hemorrhage.

PubMed

Li, Qi; Yang, Wen-Song; Wang, Xing-Chen; Cao, Du; Zhu, Dan; Lv, Fa-Jin; Liu, Yang; Yuan, Liang; Zhang, Gang; Xiong, Xin; Li, Rui; Hu, Yun-Xin; Qin, Xin-Yue; Xie, Peng

2017-01-01

Blend sign has been recently described as a novel imaging marker that predicts hematoma expansion. The purpose of our study was to investigate the prognostic value of CT blend sign in patients with ICH. Patients with intracerebral hemorrhage who underwent baseline CT scan within 6 hours were included. The presence of blend sign on admission nonenhanced CT was independently assessed by two readers. The functional outcome was assessed by using the modified Rankin Scale (mRS) at 90 days. Blend sign was identified in 40 of 238 (16.8%) patients on admission CT scan. The proportion of patients with a poor functional outcome was significantly higher in patients with blend sign than those without blend sign (75.0% versus 47.5%, P = 0.001). The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, admission GCS score, baseline hematoma volume and presence of blend sign on baseline CT independently predict poor functional outcome at 90 days. The CT blend sign independently predicts poor outcome in patients with ICH (odds ratio 3.61, 95% confidence interval [1.47-8.89];p = 0.005). Early identification of blend sign is useful in prognostic stratification and may serve as a potential therapeutic target for prospective interventional studies.

Mothers' early depressive symptoms and children's first-grade adjustment: a transactional analysis of child withdrawal as a mediator.

PubMed

Yan, Ni; Dix, Theodore

2014-05-01

The depression-inhibition hypothesis suggests that mothers' depressive symptoms undermine development because they lead children to withdraw from social contact. To test this, this study examined whether poor first-grade adjustment among children of mothers with depressive symptoms is mediated by the emergence of child withdrawal in early development. Based on 1,364 dyads, four waves of data spanning from 24 months to first grade (7 years) were used to examine paths by which children's withdrawal mediates relations between mothers' early depressive symptoms and three first-grade outcomes: social competence, academic performance, and externalizing behavior problems. Structural equation modeling revealed three principal paths. First, direct relations were observed: Mothers' depressive symptoms predicted early child withdrawal and increases in child withdrawal over time, which predicted poor first-grade adjustment. Second, reciprocal relations were observed: Mothers' depressive symptoms predicted child withdrawal, which predicted increases in depressive symptoms. Third, relations via mother-child mutual responsiveness were observed: Depression-related increases in child withdrawal predicted declines in mutual responsiveness, which predicted poor first-grade adjustment. The findings suggest that, due to its interdependence with maternal depression and low mother-child mutual responsiveness over time, child withdrawal may play an important role in the poor first-grade adjustment of children whose mothers are high in depressive symptoms. © 2013 The Authors. Journal of Child Psychology and Psychiatry. © 2013 Association for Child and Adolescent Mental Health.

NOAA Climate Program Office Contributions to National ESPC

NASA Astrophysics Data System (ADS)

Higgins, W.; Huang, J.; Mariotti, A.; Archambault, H. M.; Barrie, D.; Lucas, S. E.; Mathis, J. T.; Legler, D. M.; Pulwarty, R. S.; Nierenberg, C.; Jones, H.; Cortinas, J. V., Jr.; Carman, J.

2016-12-01

NOAA is one of five federal agencies (DOD, DOE, NASA, NOAA, and NSF) which signed an updated charter in 2016 to partner on the National Earth System Prediction Capability (ESPC). Situated within NOAA's Office of Oceanic and Atmospheric Research (OAR), NOAA Climate Program Office (CPO) programs contribute significantly to the National ESPC goals and activities. This presentation will provide an overview of CPO contributions to National ESPC. First, we will discuss selected CPO research and transition activities that directly benefit the ESPC coupled model prediction capability, including The North American Multi-Model Ensemble (NMME) seasonal prediction system The Subseasonal Experiment (SubX) project to test real-time subseasonal ensemble prediction systems. Improvements to the NOAA operational Climate Forecast System (CFS), including software infrastructure and data assimilation. Next, we will show how CPO's foundational research activities are advancing future ESPC capabilities. Highlights will include: The Tropical Pacific Observing System (TPOS) to provide the basis for predicting climate on subseasonal to decadal timescales. Subseasonal-to-Seasonal (S2S) processes and predictability studies to improve understanding, modeling and prediction of the MJO. An Arctic Research Program to address urgent needs for advancing monitoring and prediction capabilities in this major area of concern. Advances towards building an experimental multi-decadal prediction system through studies on the Atlantic Meridional Overturning Circulation (AMOC). Finally, CPO has embraced Integrated Information Systems (IIS's) that build on the innovation of programs such as the National Integrated Drought Information System (NIDIS) to develop and deliver end to end environmental information for key societal challenges (e.g. extreme heat; coastal flooding). These contributions will help the National ESPC better understand and address societal needs and decision support requirements.

USM3D Analysis of Low Boom Configuration

NASA Technical Reports Server (NTRS)

Carter, Melissa B.; Campbell, Richard L.; Nayani, Sudheer N.

2011-01-01

In the past few years considerable improvement was made in NASA's in house boom prediction capability. As part of this improved capability, the USM3D Navier-Stokes flow solver, when combined with a suitable unstructured grid, went from accurately predicting boom signatures at 1 body length to 10 body lengths. Since that time, the research emphasis has shifted from analysis to the design of supersonic configurations with boom signature mitigation In order to design an aircraft, the techniques for accurately predicting boom and drag need to be determined. This paper compares CFD results with the wind tunnel experimental results conducted on a Gulfstream reduced boom and drag configuration. Two different wind-tunnel models were designed and tested for drag and boom data. The goal of this study was to assess USM3D capability for predicting both boom and drag characteristics. Overall, USM3D coupled with a grid that was sheared and stretched was able to reasonably predict boom signature. The computational drag polar matched the experimental results for a lift coefficient above 0.1 despite some mismatch in the predicted lift-curve slope.

Towards predicting the encoding capability of MR fingerprinting sequences.

PubMed

Sommer, K; Amthor, T; Doneva, M; Koken, P; Meineke, J; Börnert, P

2017-09-01

Sequence optimization and appropriate sequence selection is still an unmet need in magnetic resonance fingerprinting (MRF). The main challenge in MRF sequence design is the lack of an appropriate measure of the sequence's encoding capability. To find such a measure, three different candidates for judging the encoding capability have been investigated: local and global dot-product-based measures judging dictionary entry similarity as well as a Monte Carlo method that evaluates the noise propagation properties of an MRF sequence. Consistency of these measures for different sequence lengths as well as the capability to predict actual sequence performance in both phantom and in vivo measurements was analyzed. While the dot-product-based measures yielded inconsistent results for different sequence lengths, the Monte Carlo method was in a good agreement with phantom experiments. In particular, the Monte Carlo method could accurately predict the performance of different flip angle patterns in actual measurements. The proposed Monte Carlo method provides an appropriate measure of MRF sequence encoding capability and may be used for sequence optimization. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Suitability of Commercial Transport Media for Biological Pathogens under Nonideal Conditions

DTIC Science & Technology

2011-01-01

microscopy (see supplemental data available online at doi:10.1155/2dl/463096), which showed the increase in recovery was the result of sporulation of...both nutrient poor, promoted sporulation [20]. Lower temper- atures inhibited B. anthracis Sterne sporulation , which in turn resulted in a rapid loss...for microorganisms capable of sporulation in nutrient-poor transport media. Unfortunately, if a sample slowly converts from the vegetative to the

Moving toward an Empowering Setting in a First Grade Classroom Serving Primarily Working Class and Working Poor Latina/o Children: An Exploratory Analysis

ERIC Educational Resources Information Center

Silva, Janelle M.; Langhout, Regina Day

2016-01-01

Empowering settings are important places for people to develop leadership skills in order to enact social change. Yet, due to socio-cultural constructions of childhood in the US, especially constructions around working class and working poor children of Color, they are often not seen as capable or competent change agents, or in need of being in…

An Assessment of Current Fan Noise Prediction Capability

NASA Technical Reports Server (NTRS)

Envia, Edmane; Woodward, Richard P.; Elliott, David M.; Fite, E. Brian; Hughes, Christopher E.; Podboy, Gary G.; Sutliff, Daniel L.

2008-01-01

In this paper, the results of an extensive assessment exercise carried out to establish the current state of the art for predicting fan noise at NASA are presented. Representative codes in the empirical, analytical, and computational categories were exercised and assessed against a set of benchmark acoustic data obtained from wind tunnel tests of three model scale fans. The chosen codes were ANOPP, representing an empirical capability, RSI, representing an analytical capability, and LINFLUX, representing a computational aeroacoustics capability. The selected benchmark fans cover a wide range of fan pressure ratios and fan tip speeds, and are representative of modern turbofan engine designs. The assessment results indicate that the ANOPP code can predict fan noise spectrum to within 4 dB of the measurement uncertainty band on a third-octave basis for the low and moderate tip speed fans except at extreme aft emission angles. The RSI code can predict fan broadband noise spectrum to within 1.5 dB of experimental uncertainty band provided the rotor-only contribution is taken into account. The LINFLUX code can predict interaction tone power levels to within experimental uncertainties at low and moderate fan tip speeds, but could deviate by as much as 6.5 dB outside the experimental uncertainty band at the highest tip speeds in some case.

Developing a predictive tropospheric ozone model for Tabriz

NASA Astrophysics Data System (ADS)

Khatibi, Rahman; Naghipour, Leila; Ghorbani, Mohammad A.; Smith, Michael S.; Karimi, Vahid; Farhoudi, Reza; Delafrouz, Hadi; Arvanaghi, Hadi

2013-04-01

Predictive ozone models are becoming indispensable tools by providing a capability for pollution alerts to serve people who are vulnerable to the risks. We have developed a tropospheric ozone prediction capability for Tabriz, Iran, by using the following five modeling strategies: three regression-type methods: Multiple Linear Regression (MLR), Artificial Neural Networks (ANNs), and Gene Expression Programming (GEP); and two auto-regression-type models: Nonlinear Local Prediction (NLP) to implement chaos theory and Auto-Regressive Integrated Moving Average (ARIMA) models. The regression-type modeling strategies explain the data in terms of: temperature, solar radiation, dew point temperature, and wind speed, by regressing present ozone values to their past values. The ozone time series are available at various time intervals, including hourly intervals, from August 2010 to March 2011. The results for MLR, ANN and GEP models are not overly good but those produced by NLP and ARIMA are promising for the establishing a forecasting capability.

Fire spread probabilities for experimental beds composed of mixedwood boreal forest fuels

Treesearch

M.B. Dickinson; E.A. Johnson; R. Artiaga

2013-01-01

Although fuel characteristics are assumed to have an important impact on fire regimes through their effects on extinction dynamics, limited capabilities exist for predicting whether a fire will spread in mixedwood boreal forest surface fuels. To improve predictive capabilities, we conducted 347 no-wind, laboratory test burns in surface fuels collected from the mixed-...

Evaluating the habitat capability model for Merriam's turkeys

Treesearch

Mark A. Rumble; Stanley H. Anderson

1995-01-01

Habitat capability (HABCAP) models for wildlife assist land managers in predicting the consequences of their management decisions. Models must be tested and refined prior to using them in management planning. We tested the predicted patterns of habitat selection of the R2 HABCAP model using observed patterns of habitats selected by radio-marked Merriam’s turkey (

Comparing the utility of the theory of planned behavior between boys and girls for predicting snack food consumption: implications for practice.

PubMed

Branscum, Paul; Sharma, Manoj

2014-01-01

The purpose of this study was to use the theory of planned behavior to explain two types of snack food consumption among boys and girls (girls n = 98; boys n = 69), which may have implications for future theory-based health promotion interventions. Between genders, there was a significant difference for calorie-dense/nutrient-poor snacks (p = .002), but no difference for fruit and vegetable snacks. Using stepwise multiple regression, attitudes, perceived behavioral control, and subjective norms accounted for a large amount of the variance of intentions (girls = 43.3%; boys = 55.9%); however, for girls, subjective norms accounted for the most variance, whereas for boys, attitudes accounted for the most variance. Calories from calorie-dense/nutrient-poor snacks and fruit and vegetable snacks were also predicted by intentions. For boys, intentions predicted 6.4% of the variance for fruit and vegetable snacks (p = .03) but was not significant for calorie-dense/nutrient-poor snacks, whereas for girls, intentions predicted 6.0% of the variance for fruit and vegetable snacks (p = .007), and 7.2% of the variance for calorie-dense/nutrient-poor snacks (p = .004). Results suggest that the theory of planned behavior is a useful framework for predicting snack foods among children; however, there are important differences between genders that should be considered in future health promotion interventions.

Assessment of CFD capability for prediction of hypersonic shock interactions

NASA Astrophysics Data System (ADS)

Knight, Doyle; Longo, José; Drikakis, Dimitris; Gaitonde, Datta; Lani, Andrea; Nompelis, Ioannis; Reimann, Bodo; Walpot, Louis

2012-01-01

The aerothermodynamic loadings associated with shock wave boundary layer interactions (shock interactions) must be carefully considered in the design of hypersonic air vehicles. The capability of Computational Fluid Dynamics (CFD) software to accurately predict hypersonic shock wave laminar boundary layer interactions is examined. A series of independent computations performed by researchers in the US and Europe are presented for two generic configurations (double cone and cylinder) and compared with experimental data. The results illustrate the current capabilities and limitations of modern CFD methods for these flows.

Subjective Sleep Quality in Women With Divorce Histories: The Role of Intimate Partner Victimization.

PubMed

Newton, Tamara L; Burns, Vicki Ellison; Miller, James J; Fernandez-Botran, G Rafael

2016-05-01

A marital status of divorced or separated, as opposed to married, predicts increased risk of health problems, but not for all persons. Focusing on one established health risk that has been linked with divorce--poor subjective sleep quality--the present cross-sectional study examined whether a history of physical intimate partner victimization (IPV) helps identify divorced women at potentially greater risk of health problems. Community midlife women with divorce histories, all of whom were free of current IPV, reported on their past month sleep quality and lifetime IPV. The predicted odds of poor sleep quality were significantly greater for women with, versus without, IPV histories. This held after adjusting for socioemotional, medical, or sociodemographic risks. A dose-response relationship between IPV chronicity and poor quality sleep was observed. IPV history may help identify divorced women at increased risk of poor quality sleep and, more broadly, poor health. © The Author(s) 2015.

The role of ovarian reserve markers in prediction of clinical pregnancy.

PubMed

Zebitay, Ali G; Cetin, Orkun; Verit, Fatma F; Keskin, Seda; Sakar, M Nafi; Karahuseyinoglu, Sercin; Ilhan, Gulsah; Sahmay, Sezai

2017-05-01

To evaluate the role of ovarian reserve markers in the prediction of clinical pregnancy and embryo transfer accomplishment among poor responder IVF applicants. 304 female poor responder IVF applicants were included in this prospective cohort study conducted at the IVF-unit. Antral follicle count, FSH, LH, E2, AMH and IVF outcomes were compared in pregnant and non-pregnant groups as well as in ET vs. non-ET groups. The number of retrieved oocytes was significantly correlated positively with AMH and AFC, and negatively with FSH and age. Quartiles of FSH and AFC were similar to the rate of pregnancy. Quartiles of AMH (<25%/25-75% and <25%/>75%) were statistically significant. Mean serum levels for AMH were significantly lower in the non-ET group. Our findings seem to indicate that day 3 AMH values can predict ET accomplishment with a sensitivity of 96% and a specificity of 35%. Quartiles of AMH <25% (< 0.21 ng/mL) can predict the IVF results among poor responder IVF applicants. Impact statement Various cut-off values have been determined for day 3 serum AMH values. These values help to determine the groups that are expected to give normal, high or low response to stimulation and decide the treatment options. In contrast to other groups of patients, poor responders cannot reach the embryo transfer stage for several reasons. These are; absence of a mature oocyte after oocyte pick-up, fertilisation failure without male factor or poor embryo quality. In the present study; a cut-off value of 0.33 ng/mL for the prediction of ET accomplishment in poor responder patients was determined with a sensitivity of 96%. Additionally, clinical pregnancy could not be achieved under the value of 0.21 ng/mL day 3 AMH values. It is important to clarify the embryo transfer success of poor responder patients prior to expected treatment success. Pre-treatment counselling for these patients would lessen the disappointment that may develop after treatment. The cost-effectiveness of treatments below these AMH values can be determined by further studies.

Selective Laser Sintering of Porous Silica Enabled by Carbon Additive

PubMed Central

Chang, Shuai; Li, Liqun; Lu, Li

2017-01-01

The aim of this study is to investigate the possibility of a freeform fabrication of porous ceramic parts through selective laser sintering (SLS). SLS was proposed to manufacture ceramic green parts because this additive manufacturing technique can be used to fabricate three-dimensional objects directly without a mold, and the technique has the capability of generating porous ceramics with controlled porosity. However, ceramic printing has not yet fully achieved its 3D fabrication capabilities without using polymer binder. Except for the limitations of high melting point, brittleness, and low thermal shock resistance from ceramic material properties, the key obstacle lies in the very poor absorptivity of oxide ceramics to fiber laser, which is widely installed in commercial SLS equipment. An alternative solution to overcome the poor laser absorptivity via improving material compositions is presented in this study. The positive effect of carbon additive on the absorptivity of silica powder to fiber laser is discussed. To investigate the capabilities of the SLS process, 3D porous silica structures were successfully prepared and characterized. PMID:29144425

MnO2-GO double-shelled sulfur (S@MnO2@GO) as a cathode for Li-S batteries with improved rate capability and cyclic performance

NASA Astrophysics Data System (ADS)

Huang, Xingkang; Shi, Keying; Yang, Joseph; Mao, George; Chen, Junhong

2017-07-01

Sulfur cathodes have attracted much attention recently because of their high energy density and power density. However, sulfur possesses very poor electrical conductivity, and lithium polysulfides, resulting from the lithiation of sulfur, are prone to dissolving into electrolytes, which leads to the loss of active materials and poor cyclic performance of the sulfur cathodes. Here we report an MnO2-graphene oxide (GO) double-shelled sulfur (S@MnO2@GO) with improved rate capability and cyclic performance, in which we propose a new reaction using sulfur-reducing KMnO4 to produce MnO2 that covers the surface of the excess sulfur in situ. The resulting MnO2 with honeycomb-like morphology provides excellent voids for storing polysulfides. The outermost GO was assembled to block the open pores of MnO2, thereby minimizing the opportunity for polysulfides to leach into the electrolytes. The GO significantly improved the electrical conductivity of the sulfur cathode, and the S@MnO2@GO exhibited excellent rate capability and long cycle life.

Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions

PubMed Central

Hosey, Chelsea M; Benet, Leslie Z

2015-01-01

The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor™ or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72±9%, 49±10%, and 66±7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74±7%, 85±2%, and 73±8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly, respectively when the permeability rate is determined in vitro. PMID:25816851

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.

Accuracy of angiogenic biomarkers at ⩽20weeks' gestation in predicting the risk of pre-eclampsia: A WHO multicentre study.

PubMed

Widmer, Mariana; Cuesta, Cristina; Khan, Khalid S; Conde-Agudelo, Agustin; Carroli, Guillermo; Fusey, Shalini; Karumanchi, S Ananth; Lapaire, Olav; Lumbiganon, Pisake; Sequeira, Evan; Zavaleta, Nelly; Frusca, Tiziana; Gülmezoglu, A Metin; Lindheimer, Marshall D

2015-10-01

To assess the accuracy of angiogenic biomarkers to predict pre-eclampsia. Prospective multicentre study. From 2006 to 2009, 5121 pregnant women with risk factors for pre-eclampsia (nulliparity, diabetes, previous pre-eclampsia, chronic hypertension) from Argentina, Colombia, Peru, India, Italy, Kenya, Switzerland and Thailand had their serum tested for sFlt-1, PlGF and sEng levels and their urine for PlGF levels at ⩽20, 23-27 and 32-35weeks' gestation (index tests, results blinded from carers). Women were monitored for signs of pre-eclampsia, diagnosed by systolic blood pressure ⩾140mmHg and/or diastolic blood pressure ⩾90mmHg, and proteinuria (protein/creatinine ratio ⩾0.3, protein ⩾1g/l, or one dipstick measurement ⩾2+) appearing after 20weeks' gestation. Early pre-eclampsia was defined when these signs appeared ⩽34weeks' gestation. Pre-eclampsia. Pre-eclampsia was diagnosed in 198 of 5121 women tested (3.9%) of whom 47 (0.9%) developed it early. The median maternal serum concentrations of index tests were significantly altered in women who subsequently developed pre-eclampsia than in those who did not. However, the area under receiver operating characteristics curve at ⩽20weeks' gestation were closer to 0.5 than to 1.0 for all biomarkers both for predicting any pre-eclampsia or at ⩽34weeks' gestation. The corresponding sensitivity, specificity and likelihood ratios were poor. Multivariable models combining sEng with clinical features slightly improved the prediction capability. Angiogenic biomarkers in first half of pregnancy do not perform well enough in predicting the later development of pre-eclampsia. Copyright © 2015. Published by Elsevier B.V.

Nutrition screening tools: does one size fit all? A systematic review of screening tools for the hospital setting.

PubMed

van Bokhorst-de van der Schueren, Marian A E; Guaitoli, Patrícia Realino; Jansma, Elise P; de Vet, Henrica C W

2014-02-01

Numerous nutrition screening tools for the hospital setting have been developed. The aim of this systematic review is to study construct or criterion validity and predictive validity of nutrition screening tools for the general hospital setting. A systematic review of English, French, German, Spanish, Portuguese and Dutch articles identified via MEDLINE, Cinahl and EMBASE (from inception to the 2nd of February 2012). Additional studies were identified by checking reference lists of identified manuscripts. Search terms included key words for malnutrition, screening or assessment instruments, and terms for hospital setting and adults. Data were extracted independently by 2 authors. Only studies expressing the (construct, criterion or predictive) validity of a tool were included. 83 studies (32 screening tools) were identified: 42 studies on construct or criterion validity versus a reference method and 51 studies on predictive validity on outcome (i.e. length of stay, mortality or complications). None of the tools performed consistently well to establish the patients' nutritional status. For the elderly, MNA performed fair to good, for the adults MUST performed fair to good. SGA, NRS-2002 and MUST performed well in predicting outcome in approximately half of the studies reviewed in adults, but not in older patients. Not one single screening or assessment tool is capable of adequate nutrition screening as well as predicting poor nutrition related outcome. Development of new tools seems redundant and will most probably not lead to new insights. New studies comparing different tools within one patient population are required. Copyright © 2013 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Predicting nutrient responses to mitigation at catchment to national scale: the UK research platform (Invited)

NASA Astrophysics Data System (ADS)

Johnes, P.

2013-12-01

Nutrient enrichment of waters from land-based and atmospheric sources presents a significant management challenge, requiring effective stakeholder engagement and policy development, properly underpinned by robust scientific evidence. The challenge is complex, raising significant questions about the specific sources, apportionment and pathways that determine nutrient enrichment and the key priorities for effective management and policy intervention. This paper presents outputs from 4 major UK research programmes: the Defra Demonstration Test Catchments programme (DTC), the Environment Agency's Catchment Sensitive Farming monitoring and evaluation programme (CSF), Natural Resources Wales Welsh Catchment Initiative (WCI) and the NERC Environmental Virtual Observatory programme (EVOp). Funded to meet this challenge, they are delivering new understanding of the rates and sources of pollutant fluxes from land to water, their impacts on ecosystem goods and services, and likely trends under future climate and land use change from field to national scale. DTC, a 12m investment by the UK Government, has set up long-term, high resolution research platforms equipped with novel telemetered sensor networks to monitor stream ecosystem responses to on-farm mitigation measures at a representative scale for catchment management. Ecosystem structural and functional responses and bulk hydrochemistry are also being monitored using standard protocols. CSF has set up long-term, enhanced monitoring in 8 priority catchments, with monthly monitoring in a further 72 English catchments and 6 Welsh priority catchments, to identify shifts in pollutant flux to waters resulting from mitigation measures in priority areas and farming sectors. CSF and WCI have contributed to >50 million of targeted farm improvements to date, representing a significant shift in farming practice. Each programme has generated detailed evidence on stream ecosystem responses to targeted mitigation. However, to provide effective underpinning for policy the major challenge has been to upscale this knowledge beyond these data-rich systems and identify the dominant contributing areas and priorities for management intervention to control nutrient flux and ecological impacts in data-poor systems which are located downstream from existing monitoring infrastructure or are in unmonitored catchments in remote locations. EVOp has directly addressed this challenge, developing a cloud computing enabled National Biogeochemical Modelling Framework to support ensemble modelling, knowledge capture and transfer from DTC, CSF, WCI and data-rich research catchments. This platform provides opportunities for further development of national biogeochemical modelling capability, allowing upscaled predictions from plot to catchment and national scale, enabling knowledge transfer from data-rich to data-poor areas. This paper presents initial findings from these research platforms, identifying the key priorities for action emerging from our national scale scenario analysis, and future research directions to further improve understanding, prediction and management capability in nutrient enriched waters and their catchments under changing climate and land use.

Reconsidering the logic of World Federation of Neurosurgical Societies grading in patients with severe subarachnoid hemorrhage.

PubMed

Fung, Christian; Inglin, Fabienne; Murek, Michael; Balmer, Mathias; Abu-Isa, Janine; Z'Graggen, Werner J; Ozdoba, Christoph; Gralla, Jan; Jakob, Stephan M; Takala, Jukka; Beck, Jürgen; Raabe, Andreas

2016-02-01

Current data show a favorable outcome in up to 50% of patients with World Federation of Neurosurgical Societies (WFNS) Grade V subarachnoid hemorrhage (SAH) and a rather poor prediction of worst cases. Thus, the usefulness of the current WFNS grading system for identifying the worst scenarios for clinical studies and for making treatment decisions is limited. One reason for this lack of differentiation is the use of "negative" or "silent" diagnostic signs as part of the WFNS Grade V definition. The authors therefore reevaluated the WFNS scale by using "positive" clinical signs and the logic of the Glasgow Coma Scale as a progressive herniation score. The authors performed a retrospective analysis of 182 patients with SAH who had poor grades on the WFNS scale. Patients were graded according to the original WFNS scale and additionally according to a modified classification, the WFNS herniation (hWFNS) scale (Grade IV, no clinical signs of herniation; Grade V, clinical signs of herniation). The prediction of poor outcome was compared between these two grading systems. The positive predictive values of Grade V for poor outcome were 74.3% (OR 3.79, 95% CI 1.94-7.54) for WFNS Grade V and 85.7% (OR 8.27, 95% CI 3.78-19.47) for hWFNS Grade V. With respect to mortality, the positive predictive values were 68.3% (OR 3.9, 95% CI 2.01-7.69) for WFNS Grade V and 77.9% (OR 6.22, 95% CI 3.07-13.14) for hWFNS Grade V. Limiting WFNS Grade V to the positive clinical signs of the Glasgow Coma Scale such as flexion, extension, and pupillary abnormalities instead of including "no motor response" increases the prediction of mortality and poor outcome in patients with severe SAH.

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

Mental health status, aggression, and poor driving distinguish traffic offenders from non-offenders but health status predicts driving behavior in both groups

PubMed Central

Abdoli, Nasrin; Farnia, Vahid; Delavar, Ali; Dortaj, Fariborz; Esmaeili, Alireza; Farrokhi, Noorali; Karami, Majid; Shakeri, Jalal; Holsboer-Trachsler, Edith; Brand, Serge

2015-01-01

Background In Iran, traffic accidents and deaths from traffic accidents are among the highest in the world, and generally, driver behavior rather than technical failures or environmental conditions are responsible for traffic accidents. In a previous study, we showed that among young Iranian male traffic offenders, poor mental health status, along with aggression, predicted poor driving behavior. The aims of the present study were twofold, to determine whether this pattern could be replicated among non-traffic offenders, and to compare the mental health status, aggression, and driving behavior of male traffic offenders and non-offenders. Methods A total of 850 male drivers (mean age =34.25 years, standard deviation =10.44) from Kermanshah (Iran) took part in the study. Of these, 443 were offenders (52.1%) and 407 (47.9%) were non-offenders with lowest driving penalty scores applying for attaining an international driving license. Participants completed a questionnaire booklet covering socio-demographic variables, traits of aggression, health status, and driving behavior. Results Compared to non-offenders, offenders reported higher aggression, poorer mental health status, and worse driving behavior. Among non-offenders, multiple regression indicated that poor health status, but not aggression, independently predicted poor driving behavior. Conclusion Compared to non-offenders, offenders reported higher aggression, poorer health status and driving behavior. Further, the predictive power of poorer mental health status, but not aggression, for driving behavior was replicated for male non-offenders. PMID:26300646

Drought Predictability and Prediction in a Changing Climate: Assessing Current Predictive Knowledge and Capabilities, User Requirements and Research Priorities

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2011-01-01

Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g., on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well. In order to make progress on these issues, the WCRP drought information group (DIG), with the support of WCRP, the Catalan Institute of Climate Sciences, the La Caixa Foundation, the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the National Science Foundation, has organized a workshop to focus on: 1. User requirements for drought prediction information on sub-seasonal to centennial time scales 2. Current understanding of the mechanisms and predictability of drought on sub-seasonal to centennial time scales 3. Current drought prediction/projection capabilities on sub-seasonal to centennial time scales 4. Advancing regional drought prediction capabilities for variables and scales most relevant to user needs on sub-seasonal to centennial time scales. This introductory talk provides an overview of these goals, and outlines the occurrence and mechanisms of drought world-wide.

1 H MR spectroscopy in cervical carcinoma using external phase array body coil at 3.0 Tesla: Prediction of poor prognostic human papillomavirus genotypes.

PubMed

Lin, Gigin; Lai, Chyong-Huey; Tsai, Shang-Yueh; Lin, Yu-Chun; Huang, Yu-Ting; Wu, Ren-Chin; Yang, Lan-Yan; Lu, Hsin-Ying; Chao, Angel; Wang, Chiun-Chieh; Ng, Koon-Kwan; Ng, Shu-Hang; Chou, Hung-Hsueh; Yen, Tzu-Chen; Hung, Ji-Hong

2017-03-01

To assess the clinical value of proton ( 1 H) MR spectroscopy in cervical carcinomas, in the prediction of poor prognostic human papillomavirus (HPV) genotypes as well as persistent disease following concurrent chemoradiotherapy (CCRT). 1 H MR spectroscopy using external phase array coil was performed in 52 consecutive cervical cancer patients at 3 Tesla (T). Poor prognostic HPV genotypes (alpha-7 species or absence of HPV infection) and persistent cervical carcinoma after CCRT were recorded. Statistical significance was calculated with the Mann-Whitney two-sided nonparametric test and areas under the receiver operating characteristics curve (AUC) analysis. A 4.3-fold (P = 0.032) increased level of methyl resonance at 0.9 ppm was found in the poor prognostic HPV genotypes, mainly attributed to the presence of HPV18, with a sensitivity of 75%, a specificity of 81%, and an AUC of 0.76. Poor prognostic HPV genotypes were more frequently observed in patients with adeno-/adenosquamous carcinoma (Chi-square, P < 0.0001). In prediction of the four patients with persistent disease after CCRT, elevated methyl resonance demonstrated a sensitivity of 100%, a specificity of 74%, and an AUC of 0.82. 1 H MR spectroscopy at 3T can be used to depict the elevated lipid resonance levels in cervical carcinomas, as well as help to predict the poor prognostic HPV genotypes and persistent disease following CCRT. Further large studies with longer follow up times are warranted to validate our initial findings. 1 J. Magn. Reson. Imaging 2017;45:899-907. © 2016 International Society for Magnetic Resonance in Medicine.

A fibre optic, four channel comparative photometer

NASA Technical Reports Server (NTRS)

Walker, E. N.

1988-01-01

Development of a four channel comparative photometer is described. Tests have shown that it is stable from night to night and is capable of working in very poor sky conditions. Even when the sky conditions are so poor that stars are barely visible, light curves can still be obtained with an r.m.s. value of 0.0016 mag., provided that integration times that are long compared with the transparancy changes are possible.

Orbital Debris Modeling

NASA Technical Reports Server (NTRS)

Liou, J. C.

2012-01-01

Presentation outlne: (1) The NASA Orbital Debris (OD) Engineering Model -- A mathematical model capable of predicting OD impact risks for the ISS and other critical space assets (2) The NASA OD Evolutionary Model -- A physical model capable of predicting future debris environment based on user-specified scenarios (3) The NASA Standard Satellite Breakup Model -- A model describing the outcome of a satellite breakup (explosion or collision)

Capability of ischemia-modified albumin to predict serious cardiac outcomes in the short term among patients with potential acute coronary syndrome.

PubMed

Worster, Andrew; Devereaux, P J; Heels-Ansdell, Diane; Guyatt, Gordon H; Opie, John; Mookadam, Farouk; Hill, Stephen A

2005-06-21

Ischemia-modified albumin (IMA) has been suggested as a marker of cardiac ischemia. Little, however, is known about its capacity to predict short-term serious cardiac outcomes (death, myocardial infarction, congestive heart failure, serious arrhythmia, or refractory ischemic cardiac pain) in patients arriving at the emergency department with symptoms that may indicate cardiac ischemia. We screened 546 patients over a 4-week period, of whom 189 fulfilled our entry criteria by presenting to an emergency department with potential cardiac-ischemia symptoms within 6 hours after chest pain, seeing an emergency physician who chose to order a troponin I test, and having no serious cardiac outcome before the troponin result became available. We followed the study patients for 72 hours to determine if any experienced a serious cardiac outcome. We calculated the likelihood ratios (LRs) of IMA findings predicting serious cardiac outcomes that could not be diagnosed at presentation with current techniques. Of the 189 patients, 24 had a serious cardiac outcome within 72 hours after their arrival at the emergency department. The likelihood ratios for IMA measurement within 6 hours after chest pain predicting a serious cardiac outcome within the next 72 hours were 1.35 (95% confidence interval [CI] 0.315-5.79) for IMA < or = 80 U/mL and 0.98 (95% CI 0.86- 1.11) for IMA > 80 U/mL. These data suggest that in patients presenting with chest pain who have not yet experienced a serious cardiac event, IMA is a poor predictor of serious cardiac outcomes in the short term.

Can high resolution 3D topographic surveys provide reliable grain size estimates in gravel bed rivers?

NASA Astrophysics Data System (ADS)

Pearson, E.; Smith, M. W.; Klaar, M. J.; Brown, L. E.

2017-09-01

High resolution topographic surveys such as those provided by Structure-from-Motion (SfM) contain a wealth of information that is not always exploited in the generation of Digital Elevation Models (DEMs). In particular, several authors have related sub-metre scale topographic variability (or 'surface roughness') to sediment grain size by deriving empirical relationships between the two. In fluvial applications, such relationships permit rapid analysis of the spatial distribution of grain size over entire river reaches, providing improved data to drive three-dimensional hydraulic models, allowing rapid geomorphic monitoring of sub-reach river restoration projects, and enabling more robust characterisation of riverbed habitats. However, comparison of previously published roughness-grain-size relationships shows substantial variability between field sites. Using a combination of over 300 laboratory and field-based SfM surveys, we demonstrate the influence of inherent survey error, irregularity of natural gravels, particle shape, grain packing structure, sorting, and form roughness on roughness-grain-size relationships. Roughness analysis from SfM datasets can accurately predict the diameter of smooth hemispheres, though natural, irregular gravels result in a higher roughness value for a given diameter and different grain shapes yield different relationships. A suite of empirical relationships is presented as a decision tree which improves predictions of grain size. By accounting for differences in patch facies, large improvements in D50 prediction are possible. SfM is capable of providing accurate grain size estimates, although further refinement is needed for poorly sorted gravel patches, for which c-axis percentiles are better predicted than b-axis percentiles.

Predictors of emotional distress a year or more after diagnosis of cancer: A systematic review of the literature.

PubMed

Cook, Sharon A; Salmon, Peter; Hayes, Gemma; Byrne, Angela; Fisher, Peter L

2018-03-01

Why some people recover emotionally after diagnosis and treatment of cancer and others do not is poorly understood. To identify factors around the time of diagnosis that predict longer-term distress is a necessary step in developing interventions to reduce patients' vulnerability. This review identified the demographic, clinical, social, and psychological factors available at or within 3 months of diagnosis that are reliable predictors of emotional distress at least 12 months later. A systematic search of literature for prospective studies addressing our research question and predicting a range of distress outcomes was conducted. Thirty-nine papers (reporting 36 studies) were subjected to narrative synthesis of the evidence. There was no consistent evidence that demographic, clinical, or social factors reliably predicted longer-term distress. Of the psychological factors examined, only baseline distress (significant in 26 of 30 relevant papers; 24 of 28 studies) and neuroticism (significant in all 5 papers/studies that examined it) consistently predicted longer-term distress. The heterogeneity of included studies, particularly in populations studied and methodology, precluded meta-analytic techniques. This review supports current clinical guidance advising early assessment of distress as a marker of vulnerability to persistent problems. Additionally, neuroticism is also indicated as a useful marker of vulnerability. However, the review also highlights that more sophisticated research designs, capable of identifying the psychological processes that underlie the association between these marker variables and persistent distress, are needed before more effective early interventions can be developed. © 2018 The Authors. Psycho-Oncology Published by John Wiley & Sons Ltd.

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.

Representation of Vegetation and Other Nonerodible Elements in Aeolian Shear Stress Partitioning Models for Predicting Transport Threshold

NASA Technical Reports Server (NTRS)

King, James; Nickling, William G.; Gillies, John A.

2005-01-01

The presence of nonerodible elements is well understood to be a reducing factor for soil erosion by wind, but the limits of its protection of the surface and erosion threshold prediction are complicated by the varying geometry, spatial organization, and density of the elements. The predictive capabilities of the most recent models for estimating wind driven particle fluxes are reduced because of the poor representation of the effectiveness of vegetation to reduce wind erosion. Two approaches have been taken to account for roughness effects on sediment transport thresholds. Marticorena and Bergametti (1995) in their dust emission model parameterize the effect of roughness on threshold with the assumption that there is a relationship between roughness density and the aerodynamic roughness length of a surface. Raupach et al. (1993) offer a different approach based on physical modeling of wake development behind individual roughness elements and the partition of the surface stress and the total stress over a roughened surface. A comparison between the models shows the partitioning approach to be a good framework to explain the effect of roughness on entrainment of sediment by wind. Both models provided very good agreement for wind tunnel experiments using solid objects on a nonerodible surface. However, the Marticorena and Bergametti (1995) approach displays a scaling dependency when the difference between the roughness length of the surface and the overall roughness length is too great, while the Raupach et al. (1993) model's predictions perform better owing to the incorporation of the roughness geometry and the alterations to the flow they can cause.

The prediction of disability by self-reported physical frailty components of the Tilburg Frailty Indicator (TFI).

PubMed

Gobbens, R J J; van Assen, M A L M; Schalk, M J D

2014-01-01

Disability is an important health outcome for older persons; it is associated with impaired quality of life, future hospitalization, and mortality. Disability also places a high burden on health care professionals and health care systems. Disability is regarded as an adverse outcome of physical frailty. The main objective of this study was to assess the predictive validity of the eight individual self-reported components of the physical frailty subscale of the TFI for activities of daily living (ADL) and instrumental activities of daily living (IADL) disability. This longitudinal study was carried out with a sample of Dutch citizens. At baseline the sample consisted at 429 people aged 65 years and older and a subset of all respondents participated again two and a half years later (N=355, 83% response rate). The respondents completed a web-based questionnaire comprising the TFI and the Groningen Activity Restriction Scale (GARS) for measuring disability. Five components together (unintentional weakness, weakness, poor endurance, slowness, low physical activity), referring to the phenotype of Fried et al., predicted disability, even after controlling for previous disability and other background characteristics. The other three components of the physical frailty subscale of the TFI (poor balance, poor hearing, poor vision) together did not predict disability. Low physical activity predicted both total and ADL disability, and slowness both total and IADL disability. In conclusion, self-report assessment using the physical subscale of the TFI aids the prediction of future ADL and IADL disability in older persons two and a half years later. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Blend sign predicts poor outcome in patients with intracerebral hemorrhage

PubMed Central

Cao, Du; Zhu, Dan; Lv, Fa-Jin; Liu, Yang; Yuan, Liang; Zhang, Gang; Xiong, Xin; Li, Rui; Hu, Yun-Xin; Qin, Xin-Yue; Xie, Peng

2017-01-01

Introduction Blend sign has been recently described as a novel imaging marker that predicts hematoma expansion. The purpose of our study was to investigate the prognostic value of CT blend sign in patients with ICH. Objectives and methods Patients with intracerebral hemorrhage who underwent baseline CT scan within 6 hours were included. The presence of blend sign on admission nonenhanced CT was independently assessed by two readers. The functional outcome was assessed by using the modified Rankin Scale (mRS) at 90 days. Results Blend sign was identified in 40 of 238 (16.8%) patients on admission CT scan. The proportion of patients with a poor functional outcome was significantly higher in patients with blend sign than those without blend sign (75.0% versus 47.5%, P = 0.001). The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, admission GCS score, baseline hematoma volume and presence of blend sign on baseline CT independently predict poor functional outcome at 90 days. The CT blend sign independently predicts poor outcome in patients with ICH (odds ratio 3.61, 95% confidence interval [1.47–8.89];p = 0.005). Conclusions Early identification of blend sign is useful in prognostic stratification and may serve as a potential therapeutic target for prospective interventional studies. PMID:28829797

Predicting contraceptive vigilance in adolescent females: a projective method for assessing ego development.

PubMed

Speier, P L; Mélèse-D'Hospital, I A; Tschann, J M; Moore, P J; Adler, N E

1997-01-01

To test the hypothesis that ego development would predict contraceptive use. Problems in ego development were defined in terms of three factors: (1) realism, (2) complexity, and (3) discontinuity. Forty-one respondents aged 14-17 years were selected from a group of 233 adolescents who were administered a projective pregnancy scenario and participated in a 12-month follow-up. Twenty of these adolescents were randomly selected from the group determined to be effective contraceptive users, while 21 were randomly selected from the group of poor contraceptors. Chi-square test revealed a significant association (p < .0005) between the composite ego maturity (EM) measure and contraceptive outcome (chi 2 = 13.82, with df-1). Low scores on the ego maturity measure predicted poor contraceptive use. EM was unrelated to age but was associated with race (chi 2 = 7.535, .025 < p < .05). However, EM predicted contraceptive use when controlling for the effects of race. A simple, time-efficient projective pregnancy scenario is an effective way of determining adolescent females at risk for poor contraceptive effectiveness and, therefore, untimely pregnancy. These stories are analyzed using factors related to the ego development of the adolescent. Subjects who scored lower on this measure have poor contraceptive effectiveness while subjects with higher levels demonstrated effective contraception use, at 1-year follow-up.

Provocative work experiences predict the acquired capability for suicide in physicians.

PubMed

Fink-Miller, Erin L

2015-09-30

The interpersonal psychological theory of suicidal behavior (IPTS) offers a potential means to explain suicide in physicians. The IPTS posits three necessary and sufficient precursors to death by suicide: thwarted belongingness, perceived burdensomeness, and acquired capability. The present study sought to examine whether provocative work experiences unique to physicians (e.g., placing sutures, withdrawing life support) would predict levels of acquired capability, while controlling for gender and painful and provocative experiences outside the work environment. Data were obtained from 376 of 7723 recruited physicians. Study measures included the Acquired Capability for Suicide Scale, the Interpersonal Needs Questionnaire, the Painful and Provocative Events Scale, and the Life Events Scale-Medical Doctors Version. Painful and provocative events outside of work predicted acquired capability (β=0.23, t=3.82, p<0.001, f(2)=0.09) as did provocative work experiences (β=0.12, t=2.05, p<0.05, f(2)=0.07). This represents the first study assessing the potential impact of unique work experiences on suicidality in physicians. Limitations include over-representation of Caucasian participants, limited representation from various specialties of medicine, and lack of information regarding individual differences. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Comprehensive Micromechanics-Analysis Code - Version 4.0

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Bednarcyk, B. A.

2005-01-01

Version 4.0 of the Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC) has been developed as an improved means of computational simulation of advanced composite materials. The previous version of MAC/GMC was described in "Comprehensive Micromechanics-Analysis Code" (LEW-16870), NASA Tech Briefs, Vol. 24, No. 6 (June 2000), page 38. To recapitulate: MAC/GMC is a computer program that predicts the elastic and inelastic thermomechanical responses of continuous and discontinuous composite materials with arbitrary internal microstructures and reinforcement shapes. The predictive capability of MAC/GMC rests on a model known as the generalized method of cells (GMC) - a continuum-based model of micromechanics that provides closed-form expressions for the macroscopic response of a composite material in terms of the properties, sizes, shapes, and responses of the individual constituents or phases that make up the material. Enhancements in version 4.0 include a capability for modeling thermomechanically and electromagnetically coupled ("smart") materials; a more-accurate (high-fidelity) version of the GMC; a capability to simulate discontinuous plies within a laminate; additional constitutive models of materials; expanded yield-surface-analysis capabilities; and expanded failure-analysis and life-prediction capabilities on both the microscopic and macroscopic scales.

Factors associated with poor sleep during menopause: results from the Midlife Women's Health Study.

PubMed

Smith, Rebecca L; Flaws, Jodi A; Mahoney, Megan M

2018-05-01

Poor sleep is one of the most common problems reported during menopause, and is known to vary throughout the menopause transition. The objective of this study was to describe the dynamics of poor sleep among participants of the Midlife Women's Health Study and to identify risk factors associated with poor sleep during the menopausal transition. Annual responses to surveys that included questions about the frequency of sleep disturbances and insomnia were analyzed to determine the likelihood of persistent poor sleep throughout the menopausal transition and the correlation of responses to the different sleep-related questions, including frequency of restless sleep during the first year of the study. Responses to questions about a large number of potential risk factors were used to identify risk factors for poor sleep. Poor sleep in premenopause was not predictive of poor sleep in perimenopause, and poor sleep in perimenopause was not predictive of poor sleep in postmenopause. Frequencies of each of the measures of poor sleep were highly correlated. For all sleep outcomes, high frequency of depression was related to a high frequency of poor sleep. Vasomotor symptoms were also significantly related with a higher frequency of all poor sleep outcomes. A history of smoking was also associated with higher frequencies of insomnia and sleep disturbances. The risk factors identified for poor sleep, depression and vasomotor symptoms, were consistently associated with poor sleep throughout the menopausal transition. The likelihood of these risk factors changed from premenopause, through perimenopause, and into postmenopause, however, which could explain changes in sleep difficulties across the menopausal transition. Treatment of these risk factors should be considered when addressing sleep difficulties in menopausal women. Copyright © 2018 Elsevier B.V. All rights reserved.

Investigating the Interaction Between Sleep Symptoms of Arousal and Acquired Capability in Predicting Suicidality.

PubMed

Hochard, Kevin D; Heym, Nadja; Townsend, Ellen

2017-06-01

Heightened arousal significantly interacts with acquired capability to predict suicidality. We explore this interaction with insomnia and nightmares independently of waking state arousal symptoms, and test predictions of the Interpersonal Theory of Suicide (IPTS) and Escape Theory in relation to these sleep arousal symptoms. Findings from our e-survey (n = 540) supported the IPTS over models of Suicide as Escape. Sleep-specific measurements of arousal (insomnia and nightmares) showed no main effect, yet interacted with acquired capability to predict increased suicidality. The explained variance in suicidality by the interaction (1%-2%) using sleep-specific measures was comparable to variance explained by interactions previously reported in the literature using measurements composed of a mix of waking and sleep state arousal symptoms. Similarly, when entrapment (inability to escape) was included in models, main effects of sleep symptoms arousal were not detected yet interacted with entrapment to predict suicidality. We discuss findings in relation to treatment options suggesting that sleep-specific interventions be considered for the long-term management of at-risk individuals. © 2016 The American Association of Suicidology.

STRAPS v1.0: Evaluating a methodology for predicting electron impact ionisation mass spectra for the aerosol mass spectrometer

NASA Astrophysics Data System (ADS)

Topping, David; Allan, James; Alfarra, Rami; Aumont, Bernard

2017-04-01

Our ability to model the chemical and thermodynamic processes that lead to secondary organic aerosol (SOA) formation is thought to be hampered by the complexity of the system. While there are fundamental models now available that can simulate the tens of thousands of reactions thought to take place, validation against experiments is highly challenging. Techniques capable of identifying individual molecules such as chromatography are generally only capable of quantifying a subset of the material present, making it unsuitable for a carbon budget analysis. Integrative analytical methods such as the Aerosol Mass Spectrometer (AMS) are capable of quantifying all mass, but because of their inability to isolate individual molecules, comparisons have been limited to simple data products such as total organic mass and O:C ratio. More detailed comparisons could be made if more of the mass spectral information could be used, but because a discrete inversion of AMS data is not possible, this activity requires a system of predicting mass spectra based on molecular composition. In this proof of concept study, the ability to train supervised methods to predict electron impact ionisation (EI) mass spectra for the AMS is evaluated. Supervised Training Regression for the Arbitrary Prediction of Spectra (STRAPS), is not built from first principles. A methodology is constructed whereby the presence of specific mass-to-charge ratio (m/z) channels are fit as a function of molecular structure before the relative peak height for each channel is similarly fit using a range of regression methods. The widely-used AMS mass spectral database is used as a basis for this, using unit mass resolution spectra of laboratory standards. Key to the fitting process is choice of structural information, or molecular fingerprint. Initial results suggest the generic public 'MACCS' fingerprints provide the most accurate trained model when combined with both decision trees and random forests with median cosine angles of 0.94-.0.97 between modelled and measured spectra. There is some sensitivity to choice of fingerprint, but most sensitivity is in choice of regression technique. Support Vector Machines perform the worst, with median values of 0.78-0.85 and lower ranges approaching 0.4 depending on the fingerprint used. More detailed analysis of modelled versus mass spectra demonstrates important composition dependent sensitivities on a compound-by-compound basis. This is further demonstrated when we apply the trained methods to a model α-pinene SOA system, using output from the GECKO-A model. This shows that use of a generic fingerprint referred to as 'FP4' and one designed for vapour pressure predictions ('Nanoolal') give plausible mass spectra, whilst the use of the MACCS keys perform poorly in this application, demonstrating the need for evaluating model performance against other SOA systems rather than existing laboratory databases on single compounds.

Interactive contributions of self-regulation deficits and social motivation to psychopathology: Unraveling divergent pathways to aggressive behavior and depressive symptoms

PubMed Central

RUDOLPH, KAREN D.; TROOP-GORDON, WENDY; LLEWELLYN, NICOLE

2015-01-01

Poor self-regulation has been implicated as a significant risk factor for the development of multiple forms of psychopathology. This research examined the proposition that self-regulation deficits differentially predict aggressive behavior and depressive symptoms, depending on children’s social approach versus avoidance motivation. A prospective, multiple-informant approach was used to test this hypothesis in 419 children (M age = 8.92, SD = 0.36). Parents rated children’s inhibitory control. Children completed measures of social approach–avoidance motivation and depressive symptoms. Teachers rated children’s aggressive behavior. As anticipated, poor inhibitory control predicted aggressive behavior in boys with high but not low approach motivation and low but not high avoidance motivation, whereas poor inhibitory control predicted depressive symptoms in girls with high but not low avoidance motivation. This research supports several complementary theoretical models of psychopathology and provides insight into the differential contributions of poor self-regulation to maladaptive developmental outcomes. The findings suggest the need for targeted intervention programs that consider heterogeneity among children with self-regulatory deficits. PMID:23627953

Developmental Course of Impulsivity and Capability from Age 10 to Age 25 as Related to Trajectory of Suicide Attempt in a Community Cohort

PubMed Central

Kasen, Stephanie; Cohen, Patricia; Chen, Henian

2011-01-01

Hierarchical linear models were used to examine trajectories of impulsivity and capability between ages 10 and 25 in relation to suicide attempt in 770 youths followed longitudinally: intercepts were set at age 17. The impulsivity measure assessed features of urgency (e.g., poor control, quick provocation, and disregard for external constraints); the capability measure assessed aspects of self-esteem and mastery. Compared to nonattempters, attempters reported significantly higher impulsivity levels with less age-related decline, and significantly lower capability levels with less age-related increase. Independent of other risks, suicide attempt was related significantly to higher impulsivity between ages 10 and 25, especially during the younger years, and lower capability. Implications of those findings for further suicidal behavior and preventive/intervention efforts are discussed. PMID:21342218

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

2015-01-01

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacity-building applications that extend numerical weather prediction to developing countries are intended to provide near real-time applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weather-related hazards, or impacts that local weather events may have during the recovery phase.

An Infrared Census of DUST in Nearby Galaxies with Spitzer (DUSTiNGS). IV. Discovery of High-redshift AGB Analogs

NASA Astrophysics Data System (ADS)

Boyer, M. L.; McQuinn, K. B. W.; Groenewegen, M. A. T.; Zijlstra, A. A.; Whitelock, P. A.; van Loon, J. Th.; Sonneborn, G.; Sloan, G. C.; Skillman, E. D.; Meixner, M.; McDonald, I.; Jones, O. C.; Javadi, A.; Gehrz, R. D.; Britavskiy, N.; Bonanos, A. Z.

2017-12-01

The survey for DUST in Nearby Galaxies with Spitzer (DUSTiNGS) identified several candidate Asymptotic Giant Branch (AGB) stars in nearby dwarf galaxies and showed that dust can form even in very metal-poor systems ({\\boldsymbol{Z}}∼ 0.008 {Z}ȯ ). Here, we present a follow-up survey with WFC3/IR on the Hubble Space Telescope (HST), using filters that are capable of distinguishing carbon-rich (C-type) stars from oxygen-rich (M-type) stars: F127M, F139M, and F153M. We include six star-forming DUSTiNGS galaxies (NGC 147, IC 10, Pegasus dIrr, Sextans B, Sextans A, and Sag DIG), all more metal-poor than the Magellanic Clouds and spanning 1 dex in metallicity. We double the number of dusty AGB stars known in these galaxies and find that most are carbon rich. We also find 26 dusty M-type stars, mostly in IC 10. Given the large dust excess and tight spatial distribution of these M-type stars, they are most likely on the upper end of the AGB mass range (stars undergoing Hot Bottom Burning). Theoretical models do not predict significant dust production in metal-poor M-type stars, but we see evidence for dust excess around M-type stars even in the most metal-poor galaxies in our sample (12+{log}({{O}}/{{H}})=7.26{--}7.50). The low metallicities and inferred high stellar masses (up to ∼10 {M}ȯ ) suggest that AGB stars can produce dust very early in the evolution of galaxies (∼30 Myr after they form), and may contribute significantly to the dust reservoirs seen in high-redshift galaxies. Based on observations made with the NASA/ESA Hubble Space Telescope at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with program GO-14073.

Applications of LANCE Data at SPoRT

NASA Technical Reports Server (NTRS)

Molthan, Andrew

2014-01-01

Short term Prediction Research and Transition (SPoRT) Center: Mission: Apply NASA and NOAA measurement systems and unique Earth science research to improve the accuracy of short term weather prediction at the regional/local scale. Goals: Evaluate and assess the utility of NASA and NOAA Earth science data and products and unique research capabilities to address operational weather forecast problems; Provide an environment which enables the development and testing of new capabilities to improve short term weather forecasts on a regional scale; Help ensure successful transition of new capabilities to operational weather entities for the benefit of society

Aircraft noise prediction program user's manual

NASA Technical Reports Server (NTRS)

Gillian, R. E.

1982-01-01

The Aircraft Noise Prediction Program (ANOPP) predicts aircraft noise with the best methods available. This manual is designed to give the user an understanding of the capabilities of ANOPP and to show how to formulate problems and obtain solutions by using these capabilities. Sections within the manual document basic ANOPP concepts, ANOPP usage, ANOPP functional modules, ANOPP control statement procedure library, and ANOPP permanent data base. appendixes to the manual include information on preparing job decks for the operating systems in use, error diagnostics and recovery techniques, and a glossary of ANOPP terms.

Evaluation of a habitat capability model for nongame birds in the Black Hills, South Dakota

Treesearch

Todd R. Mills; Mark A. Rumble; Lester D. Flake

1996-01-01

Habitat models, used to predict consequences of land management decisions on wildlife, can have considerable economic effect on management decisions. The Black Hills National Forest uses such a habitat capability model (HABCAP), but its accuracy is largely unknown. We tested this model’s predictive accuracy for nongame birds in 13 vegetative structural stages of...

Poor People, Black Faces: The Portrayal of Poverty in Economics Textbooks.

ERIC Educational Resources Information Center

Clawson, Rosalee A.

2002-01-01

Examined the portrayal of poverty in economics textbooks, investigating whether poverty would be predicted as a black problem. Results found evidence that black faces were overwhelmingly portrayed among the contemporary poor, yet Blacks were not portrayed among the Great Depression era poor and nor were they used to illustrate the popular Social…

Design of the Next Generation Aircraft Noise Prediction Program: ANOPP2

NASA Technical Reports Server (NTRS)

Lopes, Leonard V., Dr.; Burley, Casey L.

2011-01-01

The requirements, constraints, and design of NASA's next generation Aircraft NOise Prediction Program (ANOPP2) are introduced. Similar to its predecessor (ANOPP), ANOPP2 provides the U.S. Government with an independent aircraft system noise prediction capability that can be used as a stand-alone program or within larger trade studies that include performance, emissions, and fuel burn. The ANOPP2 framework is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. ANOPP2 integrates noise prediction and propagation methods, including those found in ANOPP, into a unified system that is compatible for use within general aircraft analysis software. The design of the system is described in terms of its functionality and capability to perform predictions accounting for distributed sources, installation effects, and propagation through a non-uniform atmosphere including refraction and the influence of terrain. The philosophy of mixed fidelity noise prediction through the use of nested Ffowcs Williams and Hawkings surfaces is presented and specific issues associated with its implementation are identified. Demonstrations for a conventional twin-aisle and an unconventional hybrid wing body aircraft configuration are presented to show the feasibility and capabilities of the system. Isolated model-scale jet noise predictions are also presented using high-fidelity and reduced order models, further demonstrating ANOPP2's ability to provide predictions for model-scale test configurations.

Good phonetic errors in poor spellers are associated with right-handedness and possible weak utilisation of visuospatial abilities.

PubMed

Eglinton, Elizabeth; Annett, Marian

2008-06-01

Poor spellers in normal schools, who were not poor readers, were studied for handedness, visuospatial and other cognitive abilities in order to explore contrasts between poor spellers with and without good phonology. It was predicted by the right shift (RS) theory of handedness and cerebral dominance that those with good phonology would have strong bias to dextrality and relative weakness of the right hemisphere, while those without good phonology would have reduced bias to dextrality and relative weakness of the left hemisphere. Poor spellers with good phonetic equivalent spelling errors (GFEs) included fewer left-handers (2.4%) than poor spellers without GFEs (24.4%). Differences for hand skill were as predicted. Tests of visuospatial processing found no differences between the groups in levels of ability, but there was a marked difference in pattern of correlations between visuospatial test scores and homophonic word discrimination. Whereas good spellers (GS) and poor spellers without GFEs showed positive correlations between word discrimination and visuospatial ability, there were no significant correlations for poor spellers with GFEs. The differences for handedness and possibly for the utilisation of visuospatial skills suggest that surface dyslexics differ from phonological dyslexics in cerebral specialisation and perhaps in the quality of inter-hemispheric relations.

Performance and comparison of self-reported STI symptoms among high-risk populations - MSM, sex workers, persons living with HIV/AIDS - in El Salvador.

PubMed

Shah, Neha S; Kim, Evelyn; de Maria Hernández Ayala, Flor; Guardado Escobar, Maria Elena; Nieto, Ana Isabel; Kim, Andrea A; Paz-Bailey, Gabriela

2014-12-01

Resource-limited countries have limited laboratory capability and rely on syndromic management to diagnose sexually transmitted infections (STIs). We aimed to estimate the sensitivity, specificity and positive predictive value (PPV) of STI syndromic management when used as a screening method within a study setting. Men who have sex with men (MSM), female sex workers (FSWs) and people living with HIV/AIDS (PLWHA) participated in a behavioural surveillance study. Data were obtained on demographics, sexual behaviours, STI history and service utilisation. Biological specimens were tested for genital inflammatory infections (Neisseria gonorrhoeae [GC], Chlamydia trachomatis [CT], Mycoplasma genitalium [MG], Trichomonas vaginalis [TV]) and genital ulcerative infection (syphilis and Herpes simplex virus-2). There was a high prevalence of Herpes simplex virus-2 (MSM 48.1%, FSW 82.0% and PLWHA 84.4%). Most participants reported no ulcerative symptoms and the majority of men reported no inflammatory symptoms. Sensitivity and PPV were poor for inflammatory infections among PLWHA and MSM. Sensitivity in FSWs for inflammatory infections was 75%. For ulcerative infections, sensitivity was poor, but specificity and PPV were high. Reliance on self-reported symptoms may not be an effective screening strategy for these populations. STI prevention studies should focus on symptom recognition and consider routine screening and referral for high-risk populations. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Acoustic Prediction State of the Art Assessment

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2007-01-01

The acoustic assessment task for both the Subsonic Fixed Wing and the Supersonic projects under NASA s Fundamental Aeronautics Program was designed to assess the current state-of-the-art in noise prediction capability and to establish baselines for gauging future progress. The documentation of our current capabilities included quantifying the differences between predictions of noise from computer codes and measurements of noise from experimental tests. Quantifying the accuracy of both the computed and experimental results further enhanced the credibility of the assessment. This presentation gives sample results from codes representative of NASA s capabilities in aircraft noise prediction both for systems and components. These include semi-empirical, statistical, analytical, and numerical codes. System level results are shown for both aircraft and engines. Component level results are shown for a landing gear prototype, for fan broadband noise, for jet noise from a subsonic round nozzle, and for propulsion airframe aeroacoustic interactions. Additional results are shown for modeling of the acoustic behavior of duct acoustic lining and the attenuation of sound in lined ducts with flow.

Action Imitation at 1.5 Years Is Better than Pointing Gesture in Predicting Late Development of Language Production at 3 Years of Age

ERIC Educational Resources Information Center

Zambrana, Imac M.; Ystrom, Eivind; Schjolberg, Synnve; Pons, Francisco

2013-01-01

This study examined whether poor pointing gestures and imitative actions at 18 months of age uniquely predicted late language production at 36 months, beyond the role of poor language at 18 months of age. Data from the Norwegian Mother and Child Cohort Study were utilized. Maternal reports of the children's nonverbal skills and language were…

Brief report: Poor self-regulation as a predictor of individual differences in adaptive functioning in young children with autism spectrum disorder.

PubMed

Uljarević, Mirko; Hedley, Darren; Nevill, Rose; Evans, David W; Cai, Ru Ying; Butter, Eric; Mulick, James A

2018-04-06

The present study examined the link between poor self-regulation (measured by the child behavior checklist dysregulated profile [DP]) and core autism symptoms, as well as with developmental level, in a sample of 107 children with autism spectrum disorder (ASD) aged 19-46 months. We further examined the utility of DP in predicting individual differences in adaptive functioning, relative to the influence of ASD severity, chronological age (CA), and developmental level. Poor self-regulation was unrelated to CA, developmental level, and severity of ADOS-2 restricted and repetitive behaviors, but was associated with lower ADOS-2 social affect severity. Hierarchical regression identified poor self-regulation as a unique independent predictor of adaptive behavior, with more severe dysregulation predicting poorer adaptive functioning. Results highlight the importance of early identification of deficits in self-regulation, and more specifically, of the utility of DP, when designing individually tailored treatments for young children with ASD. Autism Res 2018. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. This study explored the relationship between poor self-regulation and age, verbal and non-verbal developmental level, severity of autism symptoms and adaptive functioning in 107 children with autism under 4 years of age. Poor self-regulation was unrelated to age, developmental level, and severity of restricted and repetitive behaviors but was associated with lower social affect severity. Importantly, more severe self-regulation deficits predicted poorer adaptive functioning. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.

How well do parental and peer relationships in adolescence predict health in adulthood?

PubMed

Landstedt, Evelina; Hammarström, Anne; Winefield, Helen

2015-07-01

Although health effects of social relationships are well-researched, long-term health consequences of adolescent family as well as peer relationships are poorly understood. The aim of the study was to explore the prospective importance of parental and peer social relationships in adolescence on internalising and functional somatic symptoms in adulthood. Data were drawn from four waves of the Northern Swedish Cohort Study, response rate 94.3%, N=1001. Outcome variables were internalising and functional somatic symptoms at the ages of 21, 30 and 42. Relationship variables at age 16 were poor parental contact and three indicators of poor peer relationships. Associations were assessed in multivariate ordinal logistic regressions with adjustment for confounders and baseline health. Results show that the main relationships-related predictors of adult internalising symptoms were self-rated poor peer relationships in terms of spending time alone during after-school hours and poor parental relationship. Functional somatic symptoms on the other hand were most strongly associated with poor parental contact and not being happy with classmates at age 16. The quality of parental and peer relationships in adolescence predicts adult mental and functional somatic health as much as 26 years later, even when accounting for confounders and adolescent symptomatology. This study extends past research by exploring how both adolescent parental and peer relationships (self-reported as well as teacher reported) predict adult self-reported health. © 2015 the Nordic Societies of Public Health.

The application of improved NeuroEvolution of Augmenting Topologies neural network in Marcellus Shale lithofacies prediction

NASA Astrophysics Data System (ADS)

Wang, Guochang; Cheng, Guojian; Carr, Timothy R.

2013-04-01

The organic-rich Marcellus Shale was deposited in a foreland basin during Middle Devonian. In terms of mineral composition and organic matter richness, we define seven mudrock lithofacies: three organic-rich lithofacies and four organic-poor lithofacies. The 3D lithofacies model is very helpful to determine geologic and engineering sweet spots, and consequently useful for designing horizontal well trajectories and stimulation strategies. The NeuroEvolution of Augmenting Topologies (NEAT) is relatively new idea in the design of neural networks, and shed light on classification (i.e., Marcellus Shale lithofacies prediction). We have successfully enhanced the capability and efficiency of NEAT in three aspects. First, we introduced two new attributes of node gene, the node location and recurrent connection (RCC), to increase the calculation efficiency. Second, we evolved the population size from an initial small value to big, instead of using the constant value, which saves time and computer memory, especially for complex learning tasks. Third, in multiclass pattern recognition problems, we combined feature selection of input variables and modular neural network to automatically select input variables and optimize network topology for each binary classifier. These improvements were tested and verified by true if an odd number of its arguments are true and false otherwise (XOR) experiments, and were powerful for classification.

The Chemistry of Shocked High-energy Materials: Connecting Atomistic Simulations to Experiments

NASA Astrophysics Data System (ADS)

Islam, Md Mahbubul; Strachan, Alejandro

2017-06-01

A comprehensive atomistic-level understanding of the physics and chemistry of shocked high energy (HE) materials is crucial for designing safe and efficient explosives. Advances in the ultrafast spectroscopy and laser shocks enabled the study of shock-induced chemistry at extreme conditions occurring at picosecond timescales. Despite this progress experiments are not without limitations and do not enable a direct characterization of chemical reactions. At the same time, large-scale reactive molecular dynamics (MD) simulations are capable of providing description of the shocked-induced chemistry but the uncertainties resulting from the use of approximate descriptions of atomistic interactions remain poorly quantified. We use ReaxFF MD simulations to investigate the shock and temperature induced chemical decomposition mechanisms of polyvinyl nitrate, RDX, and nitromethane. The effect of various shock pressures on reaction initiation mechanisms is investigated for all three materials. We performed spectral analysis from atomistic velocities at different shock pressures to enable direct comparison with experiments. The simulations predict volume-increasing reactions at the shock-to-detonation transitions and the shock vs. particle velocity data are in good agreement with available experimental data. The ReaxFF MD simulations validated against experiments enabled prediction of reaction kinetics of shocked materials, and interpretation of experimental spectroscopy data via assignment of the spectral peaks to dictate various reaction pathways at extreme conditions.

An Approach to Flooding Inundation Combining the Streamflow Prediction Tool (SPT) and Downscaled Soil Moisture

NASA Astrophysics Data System (ADS)

Cotterman, K. A.; Follum, M. L.; Pradhan, N. R.; Niemann, J. D.

2017-12-01

Flooding impacts numerous aspects of society, from localized flash floods to continental-scale flood events. Many numerical flood models focus solely on riverine flooding, with some capable of capturing both localized and continental-scale flood events. However, these models neglect flooding away from channels that are related to excessive ponding, typically found in areas with flat terrain and poorly draining soils. In order to obtain a holistic view of flooding, we combine flood results from the Streamflow Prediction Tool (SPT), a riverine flood model, with soil moisture downscaling techniques to determine if a better representation of flooding is obtained. This allows for a more holistic understanding of potential flood prone areas, increasing the opportunity for more accurate warnings and evacuations during flooding conditions. Thirty-five years of near-global historical streamflow is reconstructed with continental-scale flow routing of runoff from global land surface models. Elevation data was also obtained worldwide, to establish a relationship between topographic attributes and soil moisture patterns. Derived soil moisture data is validated against observed soil moisture, increasing confidence in the ability to accurately capture soil moisture patterns. Potential flooding situations can be examined worldwide, with this study focusing on the United States, Central America, and the Philippines.

BIOFILTRATION OF VOLATILE POLLUTANTS: Fundamental Mechanisms for Improved Design, Long-term Operation, Prediction, and Implementation

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

Davison,Brian H.

2000-12-31

Biofiltration systems can be used for treatment of volatile organic compounds (VOCs); however, the systems are poorly understood and are normally operated as ''black boxes''. Common operational problems associated with biofilters include fouling, deactivation, and overgrowth, all of which make them ineffective for continuous, long-term use. The objective of this investigation was to develop generic methods for long-term stable operation, in particular by using selective limitation of supplemental nutrients while maintaining high activity. As part of this effort, we have provided a deeper fundamental understanding of the important biological and transport mechanisms in biodestruction of sparingly soluble VOCs and havemore » extended this approach and mathematical models to additional systems of high priority EM relevance--direct degradation and cometabolic degradation of priority pollutants such as BTEX and chlorinated organics. Innovative aspects of this project included development of a user-friendly two-dimensional predictive model/program for MS Windows 95/98/2000 to elucidate mass transfer and kinetic limitations in these systems, isolation of a unique microorganism capable of using sparingly soluble organic and chloroorganic VOCs as its sole carbon and energy source, and making long-term growth possible by successfully decoupling growth and degradation metabolisms in operating trickle bed bioreactors.« less

Advancements in engineering turbulence modeling

NASA Technical Reports Server (NTRS)

Shih, T.-H.

1991-01-01

Some new developments in two-equation models and second order closure models are presented. Two-equation models (k-epsilon models) have been widely used in computational fluid dynamics (CFD) for engineering problems. Most of low-Reynolds number two-equation models contain some wall-distance damping functions to account for the effect of wall on turbulence. However, this often causes the confusion and difficulties in computing flows with complex geometry and also needs an ad hoc treatment near the separation and reattachment points. A set of modified two-equation models is proposed to remove the aforementioned shortcomings. The calculations using various two-equation models are compared with direct numerical simulations of channel flow and flat boundary layers. Development of a second order closure model is also discussed with emphasis on the modeling of pressure related correlation terms and dissipation rates in the second moment equations. All the existing models poorly predict the normal stresses near the wall and fail to predict the 3-D effect of mean flow on the turbulence (e.g. decrease in the shear stress caused by the cross flow in the boundary layer). The newly developed second order near-wall turbulence model is described and is capable of capturing the near-wall behavior of turbulence as well as the effect of 3-D mean flow on the turbulence.

Reverse Engineering Crosswind Limits - A New Flight Test Technique?

NASA Technical Reports Server (NTRS)

Asher, Troy A.; Willliams, Timothy L.; Strovers, Brian K.

2013-01-01

During modification of a Gulfstream III test bed aircraft for an experimental flap project, all roll spoiler hardware had to be removed to accommodate the test article. In addition to evaluating the effects on performance and flying qualities resulting from the modification, the test team had to determine crosswind limits for an airplane previously certified with roll spoilers. Predictions for the modified aircraft indicated the maximum amount of steady state sideslip available during the approach and landing phase would be limited by aileron authority rather than by rudder. Operating out of a location that tends to be very windy, an arbitrary and conservative wind limit would have either been overly restrictive or potentially unsafe if chosen poorly. When determining a crosswind limit, how much reserve roll authority was necessary? Would the aircraft, as configured, have suitable handling qualities for long-term use as a flying test bed? To answer these questions, the test team combined two typical flight test techniques into a new maneuver called the sideslip-to-bank maneuver, and was able to gather flying qualities data, evaluate aircraft response and measure trends for various crosswind scenarios. This paper will describe the research conducted, the maneuver, flight conditions, predictions, and results from this in-flight evaluation of crosswind capability.

Dynamic and Thermal Turbulent Time Scale Modelling for Homogeneous Shear Flows

NASA Technical Reports Server (NTRS)

Schwab, John R.; Lakshminarayana, Budugur

1994-01-01

A new turbulence model, based upon dynamic and thermal turbulent time scale transport equations, is developed and applied to homogeneous shear flows with constant velocity and temperature gradients. The new model comprises transport equations for k, the turbulent kinetic energy; tau, the dynamic time scale; k(sub theta), the fluctuating temperature variance; and tau(sub theta), the thermal time scale. It offers conceptually parallel modeling of the dynamic and thermal turbulence at the two equation level, and eliminates the customary prescription of an empirical turbulent Prandtl number, Pr(sub t), thus permitting a more generalized prediction capability for turbulent heat transfer in complex flows and geometries. The new model also incorporates constitutive relations, based upon invariant theory, that allow the effects of nonequilibrium to modify the primary coefficients for the turbulent shear stress and heat flux. Predictions of the new model, along with those from two other similar models, are compared with experimental data for decaying homogeneous dynamic and thermal turbulence, homogeneous turbulence with constant temperature gradient, and homogeneous turbulence with constant temperature gradient and constant velocity gradient. The new model offers improvement in agreement with the data for most cases considered in this work, although it was no better than the other models for several cases where all the models performed poorly.

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

DOE PAGES

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

2017-04-26

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Small molecule PZL318: forming fluorescent nanoparticles capable of tracing their interactions with cancer cells and activated platelets, slowing tumor growth and inhibiting thrombosis

PubMed Central

Li, Shan; Wang, Yuji; Wang, Feng; Wang, Yaonan; Zhang, Xiaoyi; Zhao, Ming; Feng, Qiqi; Wu, Jianhui; Zhao, Shurui; Wu, Wei; Peng, Shiqi

2015-01-01

Low selectivity of chemotherapy correlates with poor outcomes of cancer patients. To improve this issue, a novel agent, N-(1-[3-methoxycarbonyl-4-hydroxyphenyl]-β-carboline-3-carbonyl)-Trp-Lys-OBzl (PZL318), was reported here. The transmission electron microscopy, scanning electron microscopy, and atomic force microscopy images demonstrated that PZL318 can form nanoparticles. Fluorescent and confocal images visualized that PZL318 formed fluorescent nanoparticles capable of targeting cancer cells and tracing their interactions with cancer cells. In vitro, 40 μM of PZL318 inhibited the proliferation of tumorigenic cells, but not nontumorigenic cells. In vivo, 10 nmol/kg of PZL318 slowed the tumor growth of S180 mice and alleviated the thrombosis of ferric chloride-treated ICR mice, while 100 μmol/kg of PZL318 did not injure healthy mice and they exhibited no liver toxicity. By analyzing Fourier transform–mass spectrometry and rotating-frame Overhauser spectroscopy (ROESY) two-dimensional nuclear magnetic resonance spectra, the chemical mechanism of PZL318-forming trimers and nanoparticles was explored. By using mesoscale simulation, a nanoparticle of 3.01 nm in diameter was predicted containing 13 trimers. Scavenging free radicals, downregulating sP-selectin expression and intercalating toward DNA were correlated with the antitumor mechanism of PZL318. PMID:26345234

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

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

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Semi-Major Axis Knowledge and GPS Orbit Determination

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell; Schiesser, Emil R.; Bauer, F. (Technical Monitor)

2000-01-01

In recent years spacecraft designers have increasingly sought to use onboard Global Positioning System receivers for orbit determination. The superb positioning accuracy of GPS has tended to focus more attention on the system's capability to determine the spacecraft's location at a particular epoch than on accurate orbit determination, per se. The determination of orbit plane orientation and orbit shape to acceptable levels is less challenging than the determination of orbital period or semi-major axis. It is necessary to address semi-major axis mission requirements and the GPS receiver capability for orbital maneuver targeting and other operations that require trajectory prediction. Failure to determine semi-major axis accurately can result in a solution that may not be usable for targeting the execution of orbit adjustment and rendezvous maneuvers. Simple formulas, charts, and rules of thumb relating position, velocity, and semi-major axis are useful in design and analysis of GPS receivers for near circular orbit operations, including rendezvous and formation flying missions. Space Shuttle flights of a number of different GPS receivers, including a mix of unfiltered and filtered solution data and Standard and Precise Positioning Service modes, have been accomplished. These results indicate that semi-major axis is often not determined very accurately, due to a poor velocity solution and a lack of proper filtering to provide good radial and speed error correlation.

Semi-Major Axis Knowledge and GPS Orbit Determination

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell; Schiesser, Emil R.; Bauer, F. (Technical Monitor)

2000-01-01

In recent years spacecraft designers have increasingly sought to use onboard Global Positioning System receivers for orbit determination. The superb positioning accuracy of GPS has tended to focus more attention on the system's capability to determine the spacecraft's location at a particular epoch than on accurate orbit determination, per se. The determination of orbit plane orientation and orbit shape to acceptable levels is less challenging than the determination of orbital period or semi-major axis. It is necessary to address semi-major axis mission requirements and the GPS receiver capability for orbital maneuver targeting and other operations that require trajectory prediction. Failure to determine semi-major axis accurately can result in a solution that may not be usable for targeting the execution of orbit adjustment and rendezvous maneuvers. Simple formulas, charts, and rules of thumb relating position, velocity, and semi-major axis are useful in design and analysis of GPS receivers for near circular orbit operations, including rendezvous and formation flying missions. Space Shuttle flights of a number of different GPS receivers, including a mix of unfiltered and filtered solution data and Standard and Precise Positioning, Service modes, have been accomplished. These results indicate that semi-major axis is often not determined very accurately, due to a poor velocity solution and a lack of proper filtering to provide good radial and speed error correlation.

Phytoremediation of landfill leachate

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

Jones, D.L.; Williamson, K.L.; Owen, A.G.

Leachate emissions from landfill sites are of concern, primarily due to their toxic impact when released unchecked into the environment, and the potential for landfill sites to generate leachate for many hundreds of years following closure. Consequently, economically and environmentally sustainable disposal options are a priority in waste management. One potential option is the use of soil-plant based remediation schemes. In many cases, using either trees (including short rotation coppice) or grassland, phytoremediation of leachate has been successful. However, there are a significant number of examples where phytoremediation has failed. Typically, this failure can be ascribed to excessive leachate applicationmore » and poor management due to a fundamental lack of understanding of the plant-soil system. On balance, with careful management, phytoremediation can be viewed as a sustainable, cost effective and environmentally sound option which is capable of treating 250 m{sup 3} ha{sup -1} yr{sup -1}. However, these schemes have a requirement for large land areas and must be capable of responding to changes in leachate quality and quantity, problems of scheme establishment and maintenance, continual environmental monitoring and seasonal patterns of plant growth. Although the fundamental underpinning science is well understood, further work is required to create long-term predictive remediation models, full environmental impact assessments, a complete life-cycle analysis and economic analyses for a wide range of landfill scenarios.« less

Prediction of poor outcomes six months following total knee arthroplasty in patients awaiting surgery.

PubMed

Lungu, Eugen; Desmeules, François; Dionne, Clermont E; Belzile, Etienne L; Vendittoli, Pascal-André

2014-09-08

Identification of patients experiencing poor outcomes following total knee arthroplasty (TKA) before the intervention could allow better case selection, patient preparation and, likely, improved outcomes. The objective was to develop a preliminary prediction rule (PR) to identify patients enrolled on surgical wait lists who are at the greatest risk of poor outcomes 6 months after TKA. 141 patients scheduled for TKA were recruited prospectively from the wait lists of 3 hospitals in Quebec City, Canada. Knee pain, stiffness and function were measured 6 months after TKA with the Western Ontario and McMaster Osteoarthritis Index (WOMAC) and participants in the lowest quintile for the WOMAC total score were considered to have a poor outcome. Several variables measured at enrolment on the wait lists (baseline) were considered potential predictors: demographic, socioeconomic, psychosocial, and clinical factors including pain, stiffness and functional status measured with the WOMAC. The prediction rule was built with recursive partitioning. The best prediction was provided by 5 items of the baseline WOMAC. The rule had a sensitivity of 82.1% (95% CI: 66.7-95.8), a specificity of 71.7% (95% CI: 62.8-79.8), a positive predictive value of 41.8% (95% CI: 29.7-55.0), a negative predictive value of 94.2% (95% CI: 87.1-97.5) and positive and negative likelihood ratios of 2.9 (95% CI: 1.8-4.7) and 0.3 (95% CI: 0.1-0.6) respectively. The developed PR is a promising tool to identify patients at risk of worse outcomes 6 months after TKA as it could help improve the management of these patients. Further validation of this rule is however warranted before clinical use.

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

The year without a summer

NASA Astrophysics Data System (ADS)

Luterbacher, J.; Pfister, C.

2015-04-01

The 1815 eruption of Tambora caused an unusually cold summer in much of Europe in 1816. The extreme weather led to poor harvests and malnutrition, but also demonstrated the capability of humans to adapt and help others in worse conditions.

Loss of an Androgen-Inactivating and Isoform-Specific HSD17B4 Splice Form Enables Emergence of Castration-Resistant Prostate Cancer.

PubMed

Ko, Hyun-Kyung; Berk, Michael; Chung, Yoon-Mi; Willard, Belinda; Bareja, Rohan; Rubin, Mark; Sboner, Andrea; Sharifi, Nima

2018-01-16

Castration-resistant prostate cancer (CRPC) requires tumors to engage metabolic mechanisms that allow sustained testosterone and/or dihydrotestosterone to stimulate progression. 17β-Hydroxysteroid dehydrogenase type 4 (17βHSD4), encoded by HSD17B4, is thought to inactivate testosterone and dihydrotestosterone by converting them to their respective inert 17-keto steroids. Counterintuitively, HSD17B4 expression increases in CRPC and predicts poor prognosis. Here, we show that, of five alternative splice forms, only isoform 2 encodes an enzyme capable of testosterone and dihydrotestosterone inactivation. In contrast with other transcripts, functional expression of isoform 2 is specifically suppressed in development of CRPC in patients. Genetically silencing isoform 2 shifts the metabolic balance toward 17β-OH androgens (testosterone and dihydrotestosterone), stimulating androgen receptor (AR) and CRPC development. Our studies specifically implicate HSD17B4 isoform 2 loss in lethal prostate cancer. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Cultivating Healthy Growth and Nutrition through the Gut Microbiota

PubMed Central

Subramanian, Sathish; Blanton, Laura; Frese, Steven A.; Charbonneau, Mark; Mills, David A.; Gordon, Jeffrey I.

2015-01-01

Microbiota assembly is perturbed in children with undernutrition, resulting in persistent microbiota immaturity that is not rescued by current nutritional interventions. Evidence is accumulating that this immaturity is causally related to the pathogenesis of undernutrition and its lingering sequelae. Preclinical models in which human gut communities are replicated in gnotobiotic mice have provided an opportunity to identify and predict the effects of different dietary ingredients on microbiota structure, expressed functions, and host biology. This capacity sets the stage for proof-of-concept tests designed to deliberately shape the developmental trajectory and configurations of microbiota in children representing different geographies, cultural traditions, and states of health. Developing these capabilities for microbial stewardship is timely given the global health burden of childhood undernutrition, the effects of changing eating practices brought about by globalization, and the realization that affordable nutritious foods need to be developed to enhance our capacity to cultivate healthier microbiota in populations at risk for poor nutrition. PMID:25815983

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-07-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Sea-ice floe-size distribution in the context of spontaneous scaling emergence in stochastic systems.

PubMed

Herman, Agnieszka

2010-06-01

Sea-ice floe-size distribution (FSD) in ice-pack covered seas influences many aspects of ocean-atmosphere interactions. However, data concerning FSD in the polar oceans are still sparse and processes shaping the observed FSD properties are poorly understood. Typically, power-law FSDs are assumed although no feasible explanation has been provided neither for this one nor for other properties of the observed distributions. Consequently, no model exists capable of predicting FSD parameters in any particular situation. Here I show that the observed FSDs can be well represented by a truncated Pareto distribution P(x)=x(-1-α) exp[(1-α)/x] , which is an emergent property of a certain group of multiplicative stochastic systems, described by the generalized Lotka-Volterra (GLV) equation. Building upon this recognition, a possibility of developing a simple agent-based GLV-type sea-ice model is considered. Contrary to simple power-law FSDs, GLV gives consistent estimates of the total floe perimeter, as well as floe-area distribution in agreement with observations.

Sea-ice floe-size distribution in the context of spontaneous scaling emergence in stochastic systems

NASA Astrophysics Data System (ADS)

Herman, Agnieszka

2010-06-01

Sea-ice floe-size distribution (FSD) in ice-pack covered seas influences many aspects of ocean-atmosphere interactions. However, data concerning FSD in the polar oceans are still sparse and processes shaping the observed FSD properties are poorly understood. Typically, power-law FSDs are assumed although no feasible explanation has been provided neither for this one nor for other properties of the observed distributions. Consequently, no model exists capable of predicting FSD parameters in any particular situation. Here I show that the observed FSDs can be well represented by a truncated Pareto distribution P(x)=x-1-αexp[(1-α)/x] , which is an emergent property of a certain group of multiplicative stochastic systems, described by the generalized Lotka-Volterra (GLV) equation. Building upon this recognition, a possibility of developing a simple agent-based GLV-type sea-ice model is considered. Contrary to simple power-law FSDs, GLV gives consistent estimates of the total floe perimeter, as well as floe-area distribution in agreement with observations.

Analytical and experimental investigation of aircraft metal structures reinforced with filamentary composites. Phase 1: Concept development and feasibility

NASA Technical Reports Server (NTRS)

Oken, S.; June, R. R.

1971-01-01

The analytical and experimental investigations are described in the first phase of a program to establish the feasibility of reinforcing metal aircraft structures with advanced filamentary composites. The interactions resulting from combining the two types of materials into single assemblies as well as their ability to function structurally were studied. The combinations studied were boron-epoxy reinforced aluminum, boron-epoxy reinforced titanium, and boron-polyimide reinforced titanium. The concepts used unidirectional composites as reinforcement in the primary loading direction and metal for carrying the transverse loads as well as its portion of the primary load. The program established that several realistic concepts could be fabricated, that these concepts could perform to a level that would result in significant weight savings, and that there are means for predicting their capability within a reasonable degree of accuracy. This program also encountered problems related to the application of polyimide systems that resulted in their relatively poor and variable performance.

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

PubMed

Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

2016-04-01

Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

The corporate social responsibility of the pharmaceutical industry: idealism without illusion and realism without resignation.

PubMed

Leisinger, Klaus M

2005-10-01

In recent years society has come to expect more from the "socially-responsible" company and the global HIV/AIDS pandemic in particular has resulted in some critics saying that the "Big Pharma" companies have not been living up to their social responsibilities. Corporate social responsibility can be understood as the socio-economic product of the organizational division of labor in complex modern society. Global poverty and poor health conditions are in the main the responsibilities of the world's national governments and international governmental organizations, which possess society's mandate and appropriate organizational capabilities. Private enterprises have neither the societal mandate nor the organizational capabilities to feed the poor or provide health care to the sick in their home countries or in the developing world. Nevertheless, private enterprises do have responsibilities to society that can be categorized as what they must do, what they ought do, and what they can do.

Predictions of the electro-mechanical response of conductive CNT-polymer composites

NASA Astrophysics Data System (ADS)

Matos, Miguel A. S.; Tagarielli, Vito L.; Baiz-Villafranca, Pedro M.; Pinho, Silvestre T.

2018-05-01

We present finite element simulations to predict the conductivity, elastic response and strain-sensing capability of conductive composites comprising a polymeric matrix and carbon nanotubes. Realistic representative volume elements (RVE) of the microstructure are generated and both constituents are modelled as linear elastic solids, with resistivity independent of strain; the electrical contact between nanotubes is represented by a new element which accounts for quantum tunnelling effects and captures the sensitivity of conductivity to separation. Monte Carlo simulations are conducted and the sensitivity of the predictions to RVE size is explored. Predictions of modulus and conductivity are found in good agreement with published results. The strain-sensing capability of the material is explored for multiaxial strain states.

Material Stream Strategy for Lithium and Inorganics (U)

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

Safarik, Douglas Joseph; Dunn, Paul Stanton; Korzekwa, Deniece Rochelle

Design Agency Responsibilities: Manufacturing Support to meet Stockpile Stewardship goals for maintaining the nuclear stockpile through experimental and predictive modeling capability. Development and maintenance of Manufacturing Science expertise to assess material specifications and performance boundaries, and their relationship to processing parameters. Production Engineering Evaluations with competence in design requirements, material specifications, and manufacturing controls. Maintenance and enhancement of Aging Science expertise to support Stockpile Stewardship predictive science capability.

Progress in Finite Element Modeling of the Lower Extremities

DTIC Science & Technology

2015-06-01

bending and subsequent injury , e.g., the distal tibia motion results in bending of the tibia rather than the tibia rotating about the knee joint...layers, rich anisotropy, and wide variability. Developing a model for predictive injury capability, therefore, needs to be versatile and flexible to... injury capability presents many challenges, the first of which is identifying the types of conditions where injury prediction is needed. Our focus

Assessing Chemical Retention Process Controls in Ponds

NASA Astrophysics Data System (ADS)

Torgersen, T.; Branco, B.; John, B.

2002-05-01

Small ponds are a ubiquitous component of the landscape and have earned a reputation as effective chemical retention devices. The most common characterization of pond chemical retention is the retention coefficient, Ri= ([Ci]inflow-[Ci] outflow)/[Ci]inflow. However, this parameter varies widely in one pond with time and among ponds. We have re-evaluated literature reported (Borden et al., 1998) monthly average retention coefficients for two ponds in North Carolina. Employing a simple first order model that includes water residence time, the first order process responsible for species removal have been separated from the water residence time over which it acts. Assuming the rate constant for species removal is constant within the pond (arguable at least), the annual average rate constant for species removal is generated. Using the annual mean rate constant for species removal and monthly water residence times results in a significantly enhanced predictive capability for Davis Pond during most months of the year. Predictive ability remains poor in Davis Pond during winter/unstratified periods when internal loading of P and N results in low to negative chemical retention. Predictive ability for Piedmont Pond (which has numerous negative chemical retention periods) is improved but not to the same extent as Davis Pond. In Davis Pond, the rate constant for sediment removal (each month) is faster than the rate constant for water and explains the good predictability for sediment retention. However, the removal rate constant for P and N is slower than the removal rate constant for sediment (longer water column residence time for P,N than for sediment). Thus sedimentation is not an overall control on nutrient retention. Additionally, the removal rate constant for P is slower than for TOC (TOC is not the dominate removal process for P) and N is removed slower than P (different in pond controls). For Piedmont Pond, sediment removal rate constants are slower than the removal rate constant for water indicating significant sediment resuspension episodes. It appears that these sediment resuspension events are aperiodic and control the loading and the chemical retention capability of Piedmont Pond for N,P,TOC. These calculated rate constants reflect the differing internal loading processes for each component and suggest means and mechanisms for the use of ponds in water quality management.

Can paediatric early warning scores (PEWS) be used to guide the need for hospital admission and predict significant illness in children presenting to the emergency department? An assessment of PEWS diagnostic accuracy using sensitivity and specificity.

PubMed

Lillitos, Peter J; Hadley, Graeme; Maconochie, Ian

2016-05-01

Designed to detect early deterioration of the hospitalised child, paediatric early warning scores (PEWS) validity in the emergency department (ED) is less validated. We aimed to evaluate sensitivity and specificity of two commonly used PEWS (Brighton and COAST) in predicting hospital admission and, for the first time, significant illness. Retrospective analysis of PEWS data for paediatric ED attendances at St Mary's Hospital, London, UK, in November 2012. Patients with missing data were excluded. Diagnoses were grouped: medical and surgical. To classify diagnoses as significant, established guidelines were used and, where not available, common agreement between three acute paediatricians. 1921 patients were analysed. There were 211 admissions (11%). 1630 attendances were medical (86%) and 273 (14%) surgical. Brighton and COAST PEWS performed similarly. hospital admission: PEWS of ≥3 was specific (93%) but poorly sensitive (32%). The area under the receiver operating curve (AUC) was low at 0.690. Significant illness: for medical illness, PEWS ≥3 was highly specific (96%) but poorly sensitive (44%). The AUC was 0.754 and 0.755 for Brighton and COAST PEWS, respectively. Both scores performed poorly for predicting significant surgical illness (AUC 0.642). PEWS ≥3 performed well in predicting significant respiratory illness: sensitivity 75%, specificity 91%. Both Brighton and COAST PEWS scores performed similarly. A score of ≥3 has good specificity but poor sensitivity for predicting hospital admission and significant illness. Therefore, a high PEWS should be taken seriously but a low score is poor at ruling out the requirement for admission or serious underlying illness. PEWS was better at detecting significant medical illness compared with detecting the need for admission. PEWS performed poorly in detecting significant surgical illness. PEWS may be particularly useful in evaluating respiratory illness in a paediatric ED. 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/

Developmental course of impulsivity and capability from age 10 to age 25 as related to trajectory of suicide attempt in a community cohort.

PubMed

Kasen, Stephanie; Cohen, Patricia; Chen, Henian

2011-04-01

Hierarchical linear models were used to examine trajectories of impulsivity and capability between ages 10 and 25 in relation to suicide attempt in 770 youths followed longitudinally: intercepts were set at age 17. The impulsivity measure assessed features of urgency (e.g., poor control, quick provocation, and disregard for external constraints); the capability measure assessed aspects of self-esteem and mastery. Compared to nonattempters, attempters reported significantly higher impulsivity levels with less age-related decline, and significantly lower capability levels with less age-related increase. Independent of other risks, suicide attempt was related significantly to higher impulsivity between ages 10 and 25, especially during the younger years, and lower capability. Implications of those findings for further suicidal behavior and preventive/intervention efforts are discussed. © 2011 The American Association of Suicidology.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

PubMed

He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A; Watson, David B; Adams, Michael W W; Fields, Matthew W; Alm, Eric J; Hazen, Terry C; Adams, Paul D; Arkin, Adam P; Zhou, Jizhong

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly ( P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as uranium or nitrate increased. These key microbial functional genes could be used to successfully predict environmental contamination and ecosystem functioning. This study represents a significant advance in using functional gene markers to predict the spatial distribution of environmental contaminants and ecosystem functioning toward predictive microbial ecology, which is an ultimate goal of microbial ecology. Copyright © 2018 He et al.

Systematic Evaluation of Wajima Superposition (Steady-State Concentration to Mean Residence Time) in the Estimation of Human Intravenous Pharmacokinetic Profile.

PubMed

Lombardo, Franco; Berellini, Giuliano; Labonte, Laura R; Liang, Guiqing; Kim, Sean

2016-03-01

We present a systematic evaluation of the Wajima superpositioning method to estimate the human intravenous (i.v.) pharmacokinetic (PK) profile based on a set of 54 marketed drugs with diverse structure and range of physicochemical properties. We illustrate the use of average of "best methods" for the prediction of clearance (CL) and volume of distribution at steady state (VDss) as described in our earlier work (Lombardo F, Waters NJ, Argikar UA, et al. J Clin Pharmacol. 2013;53(2):178-191; Lombardo F, Waters NJ, Argikar UA, et al. J Clin Pharmacol. 2013;53(2):167-177). These methods provided much more accurate prediction of human PK parameters, yielding 88% and 70% of the prediction within 2-fold error for VDss and CL, respectively. The prediction of human i.v. profile using Wajima superpositioning of rat, dog, and monkey time-concentration profiles was tested against the observed human i.v. PK using fold error statistics. The results showed that 63% of the compounds yielded a geometric mean of fold error below 2-fold, and an additional 19% yielded a geometric mean of fold error between 2- and 3-fold, leaving only 18% of the compounds with a relatively poor prediction. Our results showed that good superposition was observed in any case, demonstrating the predictive value of the Wajima approach, and that the cause of poor prediction of human i.v. profile was mainly due to the poorly predicted CL value, while VDss prediction had a minor impact on the accuracy of human i.v. profile prediction. Copyright © 2016. Published by Elsevier Inc.

How to avoid the ten most frequent EMS pitfalls

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

Andrews, W.

1982-04-19

It pays to do your homework before investing in an energy management system if you want to avoid the 10 most common pitfalls listed by users, consultants, and manufacturers as: oversimplification, improper maintenance, failure to involve operating personnel, inaccurate savings estimates, failure to include monitoring capability, incompetent or fradulent firms, improper load control, not allowing for a de-bugging period, failure to include manual override, and software problems. The article describes how each of these pitfalls can lead to poor decisions and poor results. (DCK)

A Process for Assessing NASA's Capability in Aircraft Noise Prediction Technology

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2008-01-01

An acoustic assessment is being conducted by NASA that has been designed to assess the current state of the art in NASA s capability to predict aircraft related noise and to establish baselines for gauging future progress in the field. The process for determining NASA s current capabilities includes quantifying the differences between noise predictions and measurements of noise from experimental tests. The computed noise predictions are being obtained from semi-empirical, analytical, statistical, and numerical codes. In addition, errors and uncertainties are being identified and quantified both in the predictions and in the measured data to further enhance the credibility of the assessment. The content of this paper contains preliminary results, since the assessment project has not been fully completed, based on the contributions of many researchers and shows a select sample of the types of results obtained regarding the prediction of aircraft noise at both the system and component levels. The system level results are for engines and aircraft. The component level results are for fan broadband noise, for jet noise from a variety of nozzles, and for airframe noise from flaps and landing gear parts. There are also sample results for sound attenuation in lined ducts with flow and the behavior of acoustic lining in ducts.

Artificial neural network model for ozone concentration estimation and Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Gao, Meng; Yin, Liting; Ning, Jicai

2018-07-01

Air pollution in urban atmosphere directly affects public-health; therefore, it is very essential to predict air pollutant concentrations. Air quality is a complex function of emissions, meteorology and topography, and artificial neural networks (ANNs) provide a sound framework for relating these variables. In this study, we investigated the feasibility of using ANN model with meteorological parameters as input variables to predict ozone concentration in the urban area of Jinan, a metropolis in Northern China. We firstly found that the architecture of network of neurons had little effect on the predicting capability of ANN model. A parsimonious ANN model with 6 routinely monitored meteorological parameters and one temporal covariate (the category of day, i.e. working day, legal holiday and regular weekend) as input variables was identified, where the 7 input variables were selected following the forward selection procedure. Compared with the benchmarking ANN model with 9 meteorological and photochemical parameters as input variables, the predicting capability of the parsimonious ANN model was acceptable. Its predicting capability was also verified in term of warming success ratio during the pollution episodes. Finally, uncertainty and sensitivity analysis were also performed based on Monte Carlo simulations (MCS). It was concluded that the ANN could properly predict the ambient ozone level. Maximum temperature, atmospheric pressure, sunshine duration and maximum wind speed were identified as the predominate input variables significantly influencing the prediction of ambient ozone concentrations.

Harnessing atomistic simulations to predict the rate at which dislocations overcome obstacles

NASA Astrophysics Data System (ADS)

Saroukhani, S.; Nguyen, L. D.; Leung, K. W. K.; Singh, C. V.; Warner, D. H.

2016-05-01

Predicting the rate at which dislocations overcome obstacles is key to understanding the microscopic features that govern the plastic flow of modern alloys. In this spirit, the current manuscript examines the rate at which an edge dislocation overcomes an obstacle in aluminum. Predictions were made using different popular variants of Harmonic Transition State Theory (HTST) and compared to those of direct Molecular Dynamics (MD) simulations. The HTST predictions were found to be grossly inaccurate due to the large entropy barrier associated with the dislocation-obstacle interaction. Considering the importance of finite temperature effects, the utility of the Finite Temperature String (FTS) method was then explored. While this approach was found capable of identifying a prominent reaction tube, it was not capable of computing the free energy profile along the tube. Lastly, the utility of the Transition Interface Sampling (TIS) approach was explored, which does not need a free energy profile and is known to be less reliant on the choice of reaction coordinate. The TIS approach was found capable of accurately predicting the rate, relative to direct MD simulations. This finding was utilized to examine the temperature and load dependence of the dislocation-obstacle interaction in a simple periodic cell configuration. An attractive rate prediction approach combining TST and simple continuum models is identified, and the strain rate sensitivity of individual dislocation obstacle interactions is predicted.

The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

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

Eden, H.F.; Mooers, C.N.K.

1990-06-01

The goal of COPS is to couple a program of regular observations to numerical models, through techniques of data assimilation, in order to provide a predictive capability for the US coastal ocean including the Great Lakes, estuaries, and the entire Exclusive Economic Zone (EEZ). The objectives of the program include: determining the predictability of the coastal ocean and the processes that govern the predictability; developing efficient prediction systems for the coastal ocean based on the assimilation of real-time observations into numerical models; and coupling the predictive systems for the physical behavior of the coastal ocean to predictive systems for biological,more » chemical, and geological processes to achieve an interdisciplinary capability. COPS will provide the basis for effective monitoring and prediction of coastal ocean conditions by optimizing the use of increased scientific understanding, improved observations, advanced computer models, and computer graphics to make the best possible estimates of sea level, currents, temperatures, salinities, and other properties of entire coastal regions.« less

Artificial neural network classifier predicts neuroblastoma patients' outcome.

PubMed

Cangelosi, Davide; Pelassa, Simone; Morini, Martina; Conte, Massimo; Bosco, Maria Carla; Eva, Alessandra; Sementa, Angela Rita; Varesio, Luigi

2016-11-08

More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients' outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease. Multi-layer perceptron (MLP) was trained on the expression values of the 62 probe sets constituting NB-hypo signature to develop a predictive model for neuroblastoma patients' outcome. We utilized the expression data of 100 tumors in a leave-one-out analysis to select and construct the classifier and the expression data of the remaining 82 tumors to test the classifier performance in an external dataset. We utilized the Gene set enrichment analysis (GSEA) to evaluate the enrichment of hypoxia related gene sets in patients predicted with "Poor" or "Good" outcome. We utilized the expression of the 62 probe sets of the NB-Hypo signature in 182 neuroblastoma tumors to develop a MLP classifier predicting patients' outcome (NB-hypo classifier). We trained and validated the classifier in a leave-one-out cross-validation analysis on 100 tumor gene expression profiles. We externally tested the resulting NB-hypo classifier on an independent 82 tumors' set. The NB-hypo classifier predicted the patients' outcome with the remarkable accuracy of 87 %. NB-hypo classifier prediction resulted in 2 % classification error when applied to clinically defined low-intermediate risk neuroblastoma patients. The prediction was 100 % accurate in assessing the death of five low/intermediated risk patients. GSEA of tumor gene expression profile demonstrated the hypoxic status of the tumor in patients with poor prognosis. We developed a robust classifier predicting neuroblastoma patients' outcome with a very low error rate and we provided independent evidence that the poor outcome patients had hypoxic tumors, supporting the potential of using hypoxia as target for neuroblastoma treatment.

Predictors of poor adherence to treatment in inpatients with bipolar and psychotic spectrum disorders.

PubMed

Niolu, Cinzia; Barone, Ylenia; Bianciardi, Emanuela; Ribolsi, Michele; Marchetta, Claudia; Robone, Camilla; Ambrosio, Antonio; Sarchiola, Luca; Reggiardo, Giorgio; Lorenzo, Giorgio Di; Siracusano, Alberto

2015-01-01

The aim of this study was to assess possible predictors of poor adherence in patients with a diagnosis of schizophrenia-spectrum disorders (SD) or bipolar disorder (BD) and to evaluate the roles of attachment style and caregivers as predictive factors of adherence. The sample was composed of 178 voluntarily hospitalized inpatients: 89 diagnosed with BD (I, II), 89 with SD and other schizophrenia-spectrum disorders. All patients enrolled in the study were assessed for adherence, psychopathology, attachment style, presence of caregiver, subjective well-being during pharmacological treatment with neuroleptics, side effects following therapy, subjective attitude towards drugs, global functioning and quality of life. In patients with SD, non-adherence was associated with the absence of a caregiver, fewer years of treatment, poor insight and attitude towards drugs and fearful dimensions of attachment. In patients with BD, poor insight, anxious and social avoidant temperament traits, together with a high sense of self efficacy, were related to non-adherence. Diagnosis, type of medication and side effects were not predictive factors of adherence in either group. Interestingly, some temperament traits and dimensions of attachment predict non-adherence, indicating differences between patients with SD and BD. Considering these predictors of non-adherence and assessing adherence at the time of admission for relapse could be useful to plan an early and tailored “treatment adherence”, along with other therapeutic strategies, for patients using these predictive factors. The role of caregiver proved particularly important in relation to the therapeutic alliance. Attachment style may play a key role in predicting adherence through the therapeutic alliance with both patients and caregivers.

Investigating GAIM-GM’s Capability to Sense Ionospheric Irregularities via Walker Satellite Constellations

DTIC Science & Technology

2015-03-26

aligned along the Earth’s geomagnetic equator [9]. Nava’s method was analyzed under the research of Fenton , who investigated GAIM-GM’s capability to handle...the plasma bubbles without additional inputs. Fenton determined that GAIM-GM handled the evolution of the plasma bubbles poorly [2]. With the results...0 0 2 2 .3 0 Z . 66 Bibliography 1. Space Environment Corporation. Ionospheric Forecast Model Version 4.4a, 2002. 2. Kenneth Fenton . Assessment of

Hopping robot

DOEpatents

Spletzer, Barry L.; Fischer, Gary J.; Marron, Lisa C.; Martinez, Michael A.; Kuehl, Michael A.; Feddema, John T.

2001-01-01

The present invention provides a hopping robot that includes a misfire tolerant linear actuator suitable for long trips, low energy steering and control, reliable low energy righting, miniature low energy fuel control. The present invention provides a robot with hopping mobility, capable of traversing obstacles significant in size relative to the robot and capable of operation on unpredictable terrain over long range. The present invention further provides a hopping robot with misfire-tolerant combustion actuation, and with combustion actuation suitable for use in oxygen-poor environments.

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

Defining Social Class Across Time and Between Groups.

PubMed

Cohen, Dov; Shin, Faith; Liu, Xi; Ondish, Peter; Kraus, Michael W

2017-11-01

We examined changes over four decades and between ethnic groups in how people define their social class. Changes included the increasing importance of income, decreasing importance of occupational prestige, and the demise of the "Victorian bargain," in which poor people who subscribed to conservative sexual and religious norms could think of themselves as middle class. The period also saw changes (among Whites) and continuity (among Black Americans) in subjective status perceptions. For Whites (and particularly poor Whites), their perceptions of enhanced social class were greatly reduced. Poor Whites now view their social class as slightly but significantly lower than their poor Black and Latino counterparts. For Black respondents, a caste-like understanding of social class persisted, as they continued to view their class standing as relatively independent of their achieved education, income, and occupation. Such achievement indicators, however, predicted Black respondents' self-esteem more than they predicted self-esteem for any other group.

Higher leukocyte count predicts 3-month poor outcome of ruptured cerebral aneurysms.

PubMed

Yao, Pei-Sen; Chen, Guo-Rong; Xie, Xue-Ling; Shang-Guan, Huang-Cheng; Gao, Jin-Zhen; Lin, Yuan-Xiang; Zheng, Shu-Fa; Lin, Zhang-Ya; Kang, De-Zhi

2018-04-11

It is not fully established whether leukocyte can predict the poor outcome for ruptured cerebral aneurysms (CA) or not. Here, we retrospectively analyzed the clinical data of 428 patients with ruptured CA between 2010 and 2015. Patients' demographic data, including gender, age, history of smoking, alcohol, hypertension, diabetes and hypercholesterolemia, Hunt-Hess and Fisher grade, occurrence of hydrocephalus, aneurysm location, time to surgery, delayed ischemic neurological deficit (DIND) and peak leukocyte of blood test from day 1 to 3 after aneurysmal rupture were recorded and analyzed. In the multivariable analysis model, gender, Fisher grade, time to surgery and hydrocephalus were not relevant to poor outcome. However, Hunt-Hess grade, DIND and preoperative leukocyte count (>13.84 × 10 9 /L) were significantly associated with adverse outcome. The respective increased risks were 5.2- (OR5.24, 95% CI 1.67-16.50, p = 0.005), 6.2-(OR 6.24, 95% CI 3.55-10.99, p < 0.001) and 10.9-fold (OR 9.35, 95% CI 5.98-19.97, p < 0.001). The study revealed that Hunt-Hess grade, DIND and preoperative leukocyte count (>13.84 × 10 9 /L) were independent risk factors for poor outcome of ruptured CA at 3 months. Higher leukocyte count is a convenient and useful marker to predict 3-month poor outcome for ruptured CA.

Predictive factors for poor prognosis febrile neutropenia.

PubMed

Ahn, Shin; Lee, Yoon-Seon

2012-07-01

Most patients with chemotherapy-induced febrile neutropenia recover rapidly without serious complications. However, it still remains a life-threatening treatment-related toxicity, and is associated with dose reductions and delays of chemotherapeutic agents that may compromise treatment outcomes. Recent developments of risk stratification enabled early discharge with oral antibiotics for low-risk patients. However, even in low-risk patients, medical complications including bacteremia could happen. The authors reviewed recent literature to provide an update on research regarding predictive factors for poor prognosis in patients with febrile neutropenia. Various prognostic factors have been suggested with controversies. Hematological parameters, prophylactic measurements and patient-specific risk factors showed inconsistent results. MASCC risk-index score, which was originally developed to identify low-risk patients, in turn showed that the lower the MASCC score, the poorer the prognosis of febrile neutropenia, with very low levels (<15), the rate of complications was high. Patients with severe sepsis and septic shock commonly had procalcitonin concentration above 2.0 ng/ml, and this level should be considered at high risk of poor prognosis. Lower MASCC score and higher procalcitonin concentration can predict poor outcomes in febrile neutropenia. More research is required with regard to the other factors showing controversies.

Predicting when biliary excretion of parent drug is a major route of elimination in humans.

PubMed

Hosey, Chelsea M; Broccatelli, Fabio; Benet, Leslie Z

2014-09-01

Biliary excretion is an important route of elimination for many drugs, yet measuring the extent of biliary elimination is difficult, invasive, and variable. Biliary elimination has been quantified for few drugs with a limited number of subjects, who are often diseased patients. An accurate prediction of which drugs or new molecular entities are significantly eliminated in the bile may predict potential drug-drug interactions, pharmacokinetics, and toxicities. The Biopharmaceutics Drug Disposition Classification System (BDDCS) characterizes significant routes of drug elimination, identifies potential transporter effects, and is useful in understanding drug-drug interactions. Class 1 and 2 drugs are primarily eliminated in humans via metabolism and will not exhibit significant biliary excretion of parent compound. In contrast, class 3 and 4 drugs are primarily excreted unchanged in the urine or bile. Here, we characterize the significant elimination route of 105 orally administered class 3 and 4 drugs. We introduce and validate a novel model, predicting significant biliary elimination using a simple classification scheme. The model is accurate for 83% of 30 drugs collected after model development. The model corroborates the observation that biliarily eliminated drugs have high molecular weights, while demonstrating the necessity of considering route of administration and extent of metabolism when predicting biliary excretion. Interestingly, a predictor of potential metabolism significantly improves predictions of major elimination routes of poorly metabolized drugs. This model successfully predicts the major elimination route for poorly permeable/poorly metabolized drugs and may be applied prior to human dosing.

Magnetic resonance imaging-detected tumor response for locally advanced rectal cancer predicts survival outcomes: MERCURY experience.

PubMed

Patel, Uday B; Taylor, Fiona; Blomqvist, Lennart; George, Christopher; Evans, Hywel; Tekkis, Paris; Quirke, Philip; Sebag-Montefiore, David; Moran, Brendan; Heald, Richard; Guthrie, Ashley; Bees, Nicola; Swift, Ian; Pennert, Kjell; Brown, Gina

2011-10-01

To assess magnetic resonance imaging (MRI) and pathologic staging after neoadjuvant therapy for rectal cancer in a prospectively enrolled, multicenter study. In a prospective cohort study, 111 patients who had rectal cancer treated by neoadjuvant therapy were assessed for response by MRI and pathology staging by T, N and circumferential resection margin (CRM) status. Tumor regression grade (TRG) was also assessed by MRI. Overall survival (OS) was estimated by using the Kaplan-Meier product-limit method, and Cox proportional hazards models were used to determine associations between staging of good and poor responders on MRI or pathology and survival outcomes after controlling for patient characteristics. On multivariate analysis, the MRI-assessed TRG (mrTRG) hazard ratios (HRs) were independently significant for survival (HR, 4.40; 95% CI, 1.65 to 11.7) and disease-free survival (DFS; HR, 3.28; 95% CI, 1.22 to 8.80). Five-year survival for poor mrTRG was 27% versus 72% (P = .001), and DFS for poor mrTRG was 31% versus 64% (P = .007). Preoperative MRI-predicted CRM independently predicted local recurrence (LR; HR, 4.25; 95% CI, 1.45 to 12.51). Five-year survival for poor post-treatment pathologic T stage (ypT) was 39% versus 76% (P = .001); DFS for the same was 38% versus 84% (P = .001); and LR for the same was 27% versus 6% (P = .018). The 5-year survival for involved pCRM was 30% versus 59% (P = .001); DFS, 28 versus 62% (P = .02); and LR, 56% versus 10% (P = .001). Pathology node status did not predict outcomes. MRI assessment of TRG and CRM are imaging markers that predict survival outcomes for good and poor responders and provide an opportunity for the multidisciplinary team to offer additional treatment options before planning definitive surgery. Postoperative histopathology assessment of ypT and CRM but not post-treatment N status were important postsurgical predictors of outcome.

Usefulness of Midregional Proadrenomedullin to Predict Poor Outcome in Patients with Community Acquired Pneumonia

PubMed Central

Gordo-Remartínez, Susana; Sevillano-Fernández, José A.; Álvarez-Sala, Luis A.; Andueza-Lillo, Juan A.; de Miguel-Yanes, José M.

2015-01-01

Background midregional proadrenomedullin (MR-proADM) is a prognostic biomarker in patients with community-acquired pneumonia (CAP). We sought to confirm whether MR-proADM added to Pneumonia Severity Index (PSI) improves the potential prognostic value of PSI alone, and tested to what extent this combination could be useful in predicting poor outcome of patients with CAP in an Emergency Department (ED). Methods Consecutive patients diagnosed with CAP were enrolled in this prospective, single-centre, observational study. We analyzed the ability of MR-proADM added to PSI to predict poor outcome using receiver operating characteristic (ROC) curves, logistic regression and risk reclassification and comparing it with the ability of PSI alone. The primary outcome was “poor outcome”, defined as the incidence of an adverse event (ICU admission, hospital readmission, or mortality at 30 days after CAP diagnosis). Results 226 patients were included; 33 patients (14.6%) reached primary outcome. To predict primary outcome the highest area under curve (AUC) was found for PSI (0.74 [0.64-0.85]), which was not significantly higher than for MR-proADM (AUC 0.72 [0.63-0.81, p > 0.05]). The combination of PSI and MR-proADM failed to improve the predictive potential of PSI alone (AUC 0.75 [0.65-0.85, p=0.56]). Ten patients were appropriately reclassified when the combined PSI and MR-proADM model was used as compared with the model of PSI alone. Net reclassification improvement (NRI) index was statistically significant (7.69%, p = 0.03) with an improvement percentage of 3.03% (p = 0.32) for adverse event, and 4.66% (P = 0.02) for no adverse event. Conclusion MR-proADM in combination with PSI may be helpful in individual risk stratification for short-term poor outcome of CAP patients, allowing a better reclassification of patients compared with PSI alone. PMID:26030588

Post-anoxic quantitative MRI changes may predict emergence from coma and functional outcomes at discharge.

PubMed

Reynolds, Alexandra S; Guo, Xiaotao; Matthews, Elizabeth; Brodie, Daniel; Rabbani, Leroy E; Roh, David J; Park, Soojin; Claassen, Jan; Elkind, Mitchell S V; Zhao, Binsheng; Agarwal, Sachin

2017-08-01

Traditional predictors of neurological prognosis after cardiac arrest are unreliable after targeted temperature management. Absence of pupillary reflexes remains a reliable predictor of poor outcome. Diffusion-weighted imaging has emerged as a potential predictor of recovery, and here we compare imaging characteristics to pupillary exam. We identified 69 patients who had MRIs within seven days of arrest and used a semi-automated algorithm to perform quantitative volumetric analysis of apparent diffusion coefficient (ADC) sequences at various thresholds. Area under receiver operating characteristic curves (ROC-AUC) were estimated to compare predictive values of quantitative MRI with pupillary exam at days 3, 5 and 7 post-arrest, for persistence of coma and functional outcomes at discharge. Cerebral Performance Category scores of 3-4 were considered poor outcome. Excluding patients where life support was withdrawn, ≥2.8% diffusion restriction of the entire brain at an ADC of ≤650×10 -6 m 2 /s was 100% specific and 68% sensitive for failure to wake up from coma before discharge. The ROC-AUC of ADC changes at ≤450×10 -6 mm 2 /s and ≤650×10 -6 mm 2 /s were significantly superior in predicting failure to wake up from coma compared to bilateral absence of pupillary reflexes. Among survivors, >0.01% of diffusion restriction of the entire brain at an ADC ≤450×10 -6 m 2 /s was 100% specific and 46% sensitive for poor functional outcome at discharge. The ROC curve predicting poor functional outcome at ADC ≤450×10 -6 mm 2 /s had an AUC of 0.737 (0.574-0.899, p=0.04). Post-anoxic diffusion changes using quantitative brain MRI may aid in predicting persistent coma and poor functional outcomes at hospital discharge. Copyright © 2017 Elsevier B.V. All rights reserved.

Airport Noise Prediction Model -- MOD 7

DOT National Transportation Integrated Search

1978-07-01

The MOD 7 Airport Noise Prediction Model is fully operational. The language used is Fortran, and it has been run on several different computer systems. Its capabilities include prediction of noise levels for single parameter changes, for multiple cha...

Evaluating Rapid Models for High-Throughput Exposure Forecasting (SOT)

EPA Science Inventory

High throughput exposure screening models can provide quantitative predictions for thousands of chemicals; however these predictions must be systematically evaluated for predictive ability. Without the capability to make quantitative, albeit uncertain, forecasts of exposure, the ...

In silico prediction of pharmaceutical degradation pathways: a benchmarking study.

PubMed

Kleinman, Mark H; Baertschi, Steven W; Alsante, Karen M; Reid, Darren L; Mowery, Mark D; Shimanovich, Roman; Foti, Chris; Smith, William K; Reynolds, Dan W; Nefliu, Marcela; Ott, Martin A

2014-11-03

Zeneth is a new software application capable of predicting degradation products derived from small molecule active pharmaceutical ingredients. This study was aimed at understanding the current status of Zeneth's predictive capabilities and assessing gaps in predictivity. Using data from 27 small molecule drug substances from five pharmaceutical companies, the evolution of Zeneth predictions through knowledge base development since 2009 was evaluated. The experimentally observed degradation products from forced degradation, accelerated, and long-term stability studies were compared to Zeneth predictions. Steady progress in predictive performance was observed as the knowledge bases grew and were refined. Over the course of the development covered within this evaluation, the ability of Zeneth to predict experimentally observed degradants increased from 31% to 54%. In particular, gaps in predictivity were noted in the areas of epimerizations, N-dealkylation of N-alkylheteroaromatic compounds, photochemical decarboxylations, and electrocyclic reactions. The results of this study show that knowledge base development efforts have increased the ability of Zeneth to predict relevant degradation products and aid pharmaceutical research. This study has also provided valuable information to help guide further improvements to Zeneth and its knowledge base.

Landscape capability predicts upland game bird abundance and occurrence

USGS Publications Warehouse

Loman, Zachary G.; Blomberg, Erik J.; DeLuca, William; Harrison, Daniel J.; Loftin, Cyndy; Wood, Petra B.

2017-01-01

Landscape capability (LC) models are a spatial tool with potential applications in conservation planning. We used survey data to validate LC models as predictors of occurrence and abundance at broad and fine scales for American woodcock (Scolopax minor) and ruffed grouse (Bonasa umbellus). Landscape capability models were reliable predictors of occurrence but were less indicative of relative abundance at route (11.5–14.6 km) and point scales (0.5–1 km). As predictors of occurrence, LC models had high sensitivity (0.71–0.93) and were accurate (0.71–0.88) and precise (0.88 and 0.92 for woodcock and grouse, respectively). Models did not predict point-scale abundance independent of the ability to predict occurrence of either species. The LC models are useful predictors of patterns of occurrences in the northeastern United States, but they have limited utility as predictors of fine-scale or route-specific abundances. 

Development of advanced structural analysis methodologies for predicting widespread fatigue damage in aircraft structures

NASA Technical Reports Server (NTRS)

Harris, Charles E.; Starnes, James H., Jr.; Newman, James C., Jr.

1995-01-01

NASA is developing a 'tool box' that includes a number of advanced structural analysis computer codes which, taken together, represent the comprehensive fracture mechanics capability required to predict the onset of widespread fatigue damage. These structural analysis tools have complementary and specialized capabilities ranging from a finite-element-based stress-analysis code for two- and three-dimensional built-up structures with cracks to a fatigue and fracture analysis code that uses stress-intensity factors and material-property data found in 'look-up' tables or from equations. NASA is conducting critical experiments necessary to verify the predictive capabilities of the codes, and these tests represent a first step in the technology-validation and industry-acceptance processes. NASA has established cooperative programs with aircraft manufacturers to facilitate the comprehensive transfer of this technology by making these advanced structural analysis codes available to industry.

Experimental validation of systematically designed acoustic hyperbolic meta material slab exhibiting negative refraction

NASA Astrophysics Data System (ADS)

Christiansen, Rasmus E.; Sigmund, Ole

2016-09-01

This Letter reports on the experimental validation of a two-dimensional acoustic hyperbolic metamaterial slab optimized to exhibit negative refractive behavior. The slab was designed using a topology optimization based systematic design method allowing for tailoring the refractive behavior. The experimental results confirm the predicted refractive capability as well as the predicted transmission at an interface. The study simultaneously provides an estimate of the attenuation inside the slab stemming from the boundary layer effects—insight which can be utilized in the further design of the metamaterial slabs. The capability of tailoring the refractive behavior opens possibilities for different applications. For instance, a slab exhibiting zero refraction across a wide angular range is capable of funneling acoustic energy through it, while a material exhibiting the negative refractive behavior across a wide angular range provides lensing and collimating capabilities.

The NASA Severe Thunderstorm Observations and Regional Modeling (NASA STORM) Project

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Gatlin, Patrick N.; Lang, Timothy J.; Srikishen, Jayanthi; Case, Jonathan L.; Molthan, Andrew L.; Zavodsky, Bradley T.; Bailey, Jeffrey; Blakeslee, Richard J.; Jedlovec, Gary J.

2016-01-01

The NASA Severe Storm Thunderstorm Observations and Regional Modeling(NASA STORM) project enhanced NASA’s severe weather research capabilities, building upon existing Earth Science expertise at NASA Marshall Space Flight Center (MSFC). During this project, MSFC extended NASA’s ground-based lightning detection capacity to include a readily deployable lightning mapping array (LMA). NASA STORM also enabled NASA’s Short-term Prediction and Research Transition (SPoRT) to add convection allowing ensemble modeling to its portfolio of regional numerical weather prediction (NWP) capabilities. As a part of NASA STORM, MSFC developed new open-source capabilities for analyzing and displaying weather radar observations integrated from both research and operational networks. These accomplishments enabled by NASA STORM are a step towards enhancing NASA’s capabilities for studying severe weather and positions them for any future NASA related severe storm field campaigns.

Advances in heterogeneous ice nucleation research: Theoretical modeling and measurements

NASA Astrophysics Data System (ADS)

Beydoun, Hassan

In the atmosphere, cloud droplets can remain in a supercooled liquid phase at temperatures as low as -40 °C. Above this temperature, cloud droplets freeze via heterogeneous ice nucleation whereby a rare and poorly understood subset of atmospheric particles catalyze the ice phase transition. As the phase state of clouds is critical in determining their radiative properties and lifetime, deficiencies in our understanding of heterogeneous ice nucleation poses a large uncertainty on our efforts to predict human induced global climate change. Experimental challenges in properly simulating particle-induced freezing processes under atmospherically relevant conditions have largely contributed to the absence of a well-established model and parameterizations that accurately predict heterogeneous ice nucleation. Conversely, the sparsity of reliable measurement techniques available struggle to be interpreted by a single consistent theoretical or empirical framework, which results in layers of uncertainty when attempting to extrapolate useful information regarding ice nucleation for use in atmospheric cloud models. In this dissertation a new framework for describing heterogeneous ice nucleation is developed. Starting from classical nucleation theory, the surface of an ice nucleating particle is treated as a continuum of heterogeneous ice nucleating activity and a particle specific distribution of this activity g is derived. It is hypothesized that an individual particle species exhibits a critical surface area. Above this critical area the ice nucleating activity of a particle species can be described by one g distribution, g, while below it g expresses itself expresses externally resulting in particle to particle variability in ice nucleating activity. The framework is supported by cold plate droplet freezing measurements for dust and biological particles in which the total surface area of particle material available is varied. Freezing spectra above a certain surface area are shown to be successfully fitted with g while a process of random sampling from g can predict the freezing behavior below the identified critical surface area threshold. The framework is then extended to account for droplets composed of multiple particle species and successfully applied to predict the freezing spectra of a mixed proxy for an atmospheric dust-biological particle system. The contact freezing mode of ice nucleation, whereby a particle induces freezing upon collision with a droplet, is thought to be more efficient than particle initiated immersion freezing from within the droplet bulk. However, it has been a decades' long challenge to accurately measure this ice nucleation mode, since it necessitates reliably measuring the rate at which particles hit a droplet surface combined with direct determination of freezing onset. In an effort to remedy this longstanding deficiency a temperature controlled chilled aerosol optical tweezers capable of stably isolating water droplets in air at subzero temperatures has been designed and implemented. The new temperature controlled system retains the powerful capabilities of traditional aerosol optical tweezers: retrieval of a cavity enhanced Raman spectrum which could be used to accurately determine the size and refractive index of a trapped droplet. With these capabilities, it is estimated that the design can achieve ice supersaturation conditions at the droplet surface. It was also found that a KCl aqueous droplet simultaneously cooling and evaporating exhibited a significantly higher measured refractive index at its surface than when it was held at a steady state temperature. This implies the potential of a "salting out" process. Sensitivity of the cavity enhanced Raman spectrum as well as the visual image of a trapped droplet to dust particle collisions is shown, an important step in measuring collision frequencies of dust particles with a trapped droplet. These results may pave the way for future experiments of the exceptionally poorly understood contact freezing mode of ice nucleation.

Prediction of Outcome From Adult Bacterial Meningitis in a High-HIV-Seroprevalence, Resource-Poor Setting Using the Malawi Adult Meningitis Score (MAMS).

PubMed

Wall, Emma C; Mukaka, Mavuto; Scarborough, Matthew; Ajdukiewicz, Katherine M A; Cartwright, Katharine E; Nyirenda, Mulinda; Denis, Brigitte; Allain, Theresa J; Faragher, Brian; Lalloo, David G; Heyderman, Robert S

2017-02-15

Acute bacterial meningitis (ABM) in adults residing in resource-poor countries is associated with mortality rates >50%. To improve outcome, interventional trials and standardized clinical algorithms are urgently required. To optimize these processes, we developed and validated an outcome prediction tool to identify ABM patients at greatest risk of death. We derived a nomogram using mortality predictors derived from a logistic regression model of a discovery database of adult Malawian patients with ABM (n = 523 [65%] cerebrospinal fluid [CSF] culture positive). We validated the nomogram internally using a bootstrap procedure and subsequently used the nomogram scores to further interpret the effects of adjunctive dexamethasone and glycerol using clinical trial data from Malawi. ABM mortality at 6-week follow-up was 54%. Five of 15 variables tested were strongly associated with poor outcome (CSF culture positivity, CSF white blood cell count, hemoglobin, Glasgow Coma Scale, and pulse rate), and were used in the derivation of the Malawi Adult Meningitis Score (MAMS) nomogram. The C-index (area under the curve) was 0.76 (95% confidence interval, .71-.80) and calibration was good (Hosmer-Lemeshow C-statistic = 5.48, df = 8, P = .705). Harmful effects of adjunctive glycerol were observed in groups with relatively low predicted risk of poor outcome (25%-50% risk): Case Fatality Rate of 21% in the placebo group and 52% in the glycerol group (P < .001). This effect was not seen with adjunctive dexamethasone. MAMS provides a novel tool for predicting prognosis and improving interpretation of ABM clinical trials by risk stratification in resource-poor settings. Whether MAMS can be applied to non-HIV-endemic countries requires further evaluation. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America.

Cross-sectional analysis of food choice frequency, sleep confounding beverages, and psychological distress predictors of sleep quality.

PubMed

Knowlden, Adam P; Burns, Maranda; Harcrow, Andy; Shewmake, Meghan E

2016-03-16

Poor sleep quality is a significant public health problem. The role of nutrition in predicting sleep quality is a relatively unexplored area of inquiry. The purpose of this study was to evaluate the capacity of 10 food choice categories, sleep confounding beverages, and psychological distress to predict the sleep quality of college students. A logistic regression model comprising 10 food choice variables (healthy proteins, unhealthy proteins, healthy dairy, unhealthy dairy, healthy grains, unhealthy grains, healthy fruits and vegetables, unhealthy empty calories, healthy beverages, unhealthy beverages), sleep confounding beverages (caffeinated/alcoholic beverages), as well as psychological distress (low, moderate, serious distress) was computed to determine the capacity of the variables to predict sleep quality (good/poor). The odds of poor sleep quality were 32.4% lower for each unit of increased frequency of healthy proteins consumed (p<0.001; OR=0.676), 14.1% lower for each unit of increased frequency of healthy dairy food choices consumed (p=0.024; OR=0.859), 13.1% higher for each unit of increased frequency of empty calorie food choices consumed (p=0.003; OR=1.131), and 107.3% higher for those classified in the moderate psychological distress (p=0.016; OR=2.073). Collectively, healthy proteins, healthy dairy, unhealthy empty calories, and moderate psychological distress were moderately predictive of sleep quality in the sample (Nagelkerke R2=23.8%). Results of the study suggested higher frequency of consumption of healthy protein and healthy dairy food choices reduced the odds of poor sleep quality, while higher consumption of empty calories and moderate psychological distress increased the odds of poor sleep quality.

Child maltreatment, parent alcohol and drug-related problems, polydrug problems, and parenting practices: a test of gender differences and four theoretical perspectives.

PubMed

Locke, Thomas F; Newcomb, Michael

2004-03-01

The authors tested how adverse childhood experiences (child maltreatment and parent alcohol- and drug-related problems) and adult polydrug use (as a mediator) predict poor parenting in a community sample (237 mothers and 81 fathers). These relationships were framed within several theoretical perspectives, including observational learning, impaired functioning, self-medication, and parentification-pseudomaturity. Structural models revealed that child maltreatment predicted poor parenting practices among mothers. Parent alcohol- and drug-related problems had an indirect detrimental influence on mothers' parenting and practices through self-drug problems. Among fathers, emotional neglect experienced as a child predicted lack of parental warmth more parental neglect, and sexual abuse experienced as a child predicted a rejecting style of parenting.

Prediction of High-Lift Flows using Turbulent Closure Models

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Gatski, Thomas B.; Ying, Susan X.; Bertelrud, Arild

1997-01-01

The flow over two different multi-element airfoil configurations is computed using linear eddy viscosity turbulence models and a nonlinear explicit algebraic stress model. A subset of recently-measured transition locations using hot film on a McDonnell Douglas configuration is presented, and the effect of transition location on the computed solutions is explored. Deficiencies in wake profile computations are found to be attributable in large part to poor boundary layer prediction on the generating element, and not necessarily inadequate turbulence modeling in the wake. Using measured transition locations for the main element improves the prediction of its boundary layer thickness, skin friction, and wake profile shape. However, using measured transition locations on the slat still yields poor slat wake predictions. The computation of the slat flow field represents a key roadblock to successful predictions of multi-element flows. In general, the nonlinear explicit algebraic stress turbulence model gives very similar results to the linear eddy viscosity models.

PGT: A Statistical Approach to Prediction and Mechanism Design

NASA Astrophysics Data System (ADS)

Wolpert, David H.; Bono, James W.

One of the biggest challenges facing behavioral economics is the lack of a single theoretical framework that is capable of directly utilizing all types of behavioral data. One of the biggest challenges of game theory is the lack of a framework for making predictions and designing markets in a manner that is consistent with the axioms of decision theory. An approach in which solution concepts are distribution-valued rather than set-valued (i.e. equilibrium theory) has both capabilities. We call this approach Predictive Game Theory (or PGT). This paper outlines a general Bayesian approach to PGT. It also presents one simple example to illustrate the way in which this approach differs from equilibrium approaches in both prediction and mechanism design settings.

Predictors of maternal health services utilization by poor, rural women: a comparative study in Indian States of Gujarat and Tamil Nadu.

PubMed

Vora, Kranti Suresh; Koblinsky, Sally A; Koblinsky, Marge A

2015-07-31

India leads all nations in numbers of maternal deaths, with poor, rural women contributing disproportionately to the high maternal mortality ratio. In 2005, India launched the world's largest conditional cash transfer scheme, Janani Suraksha Yojana (JSY), to increase poor women's access to institutional delivery, anticipating that facility-based birthing would decrease deaths. Indian states have taken different approaches to implementing JSY. Tamil Nadu adopted JSY with a reorganization of its public health system, and Gujarat augmented JSY with the state-funded Chiranjeevi Yojana (CY) scheme, contracting with private physicians for delivery services. Given scarce evidence of the outcomes of these approaches, especially in states with more optimal health indicators, this cross-sectional study examined the role of JSY/CY and other healthcare system and social factors in predicting poor, rural women's use of maternal health services in Gujarat and Tamil Nadu. Using the District Level Household Survey (DLHS)-3, the sample included 1584 Gujarati and 601 Tamil rural women in the lowest two wealth quintiles. Multivariate logistic regression analyses examined associations between JSY/CY and other salient health system, socio-demographic, and obstetric factors with three outcomes: adequate antenatal care, institutional delivery, and Cesarean-section. Tamil women reported greater use of maternal healthcare services than Gujarati women. JSY/CY participation predicted institutional delivery in Gujarat (AOR = 3.9), but JSY assistance failed to predict institutional delivery in Tamil Nadu, where mothers received some cash for home births under another scheme. JSY/CY assistance failed to predict adequate antenatal care, which was not incentivized. All-weather road access predicted institutional delivery in both Tamil Nadu (AOR = 3.4) and Gujarat (AOR = 1.4). Women's education predicted institutional delivery and Cesarean-section in Tamil Nadu, while husbands' education predicted institutional delivery in Gujarat. Overall, assistance from health financing schemes, good road access to health facilities, and socio-demographic and obstetric factors were associated with differential use of maternity health services by poor, rural women in the two states. Policymakers and practitioners should promote financing schemes to increase access, including consideration of incentives for antenatal care, and address health system and social factors in designing state-level interventions to promote safe motherhood.

Helicopter Rotor Noise Prediction: Background, Current Status, and Future Direction

NASA Technical Reports Server (NTRS)

Brentner, Kenneth S.

1997-01-01

Helicopter noise prediction is increasingly important. The purpose of this viewgraph presentation is to: 1) Put into perspective the recent progress; 2) Outline current prediction capabilities; 3) Forecast direction of future prediction research; 4) Identify rotorcraft noise prediction needs. The presentation includes an historical perspective, a description of governing equations, and the current status of source noise prediction.

Development of Modeling Capabilities for Launch Pad Acoustics and Ignition Transient Environment Prediction

NASA Technical Reports Server (NTRS)

West, Jeff; Strutzenberg, Louise L.; Putnam, Gabriel C.; Liever, Peter A.; Williams, Brandon R.

2012-01-01

This paper presents development efforts to establish modeling capabilities for launch vehicle liftoff acoustics and ignition transient environment predictions. Peak acoustic loads experienced by the launch vehicle occur during liftoff with strong interaction between the vehicle and the launch facility. Acoustic prediction engineering tools based on empirical models are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. Modeling approaches are needed that capture the important details of the plume flow environment including the ignition transient, identify the noise generation sources, and allow assessment of the effects of launch pad geometric details and acoustic mitigation measures such as water injection. This paper presents a status of the CFD tools developed by the MSFC Fluid Dynamics Branch featuring advanced multi-physics modeling capabilities developed towards this goal. Validation and application examples are presented along with an overview of application in the prediction of liftoff environments and the design of targeted mitigation measures such as launch pad configuration and sound suppression water placement.

JPL's Role in Advancing Earth System Science to Meet the Challenges of Climate and Environmental Change

NASA Technical Reports Server (NTRS)

Evans, Diane

2012-01-01

Objective 2.1.1: Improve understanding of and improve the predictive capability for changes in the ozone layer, climate forcing, and air quality associated with changes in atmospheric composition. Objective 2.1.2: Enable improved predictive capability for weather and extreme weather events. Objective 2.1.3: Quantify, understand, and predict changes in Earth s ecosystems and biogeochemical cycles, including the global carbon cycle, land cover, and biodiversity. Objective 2.1.4: Quantify the key reservoirs and fluxes in the global water cycle and assess water cycle change and water quality. Objective 2.1.5: Improve understanding of the roles of the ocean, atmosphere, land and ice in the climate system and improve predictive capability for its future evolution. Objective 2.1.6: Characterize the dynamics of Earth s surface and interior and form the scientific basis for the assessment and mitigation of natural hazards and response to rare and extreme events. Objective 2.1.7: Enable the broad use of Earth system science observations and results in decision-making activities for societal benefits.

Traditional systolic blood pressure targets underestimate hypotension-induced secondary brain injury.

PubMed

Brenner, Megan; Stein, Deborah M; Hu, Peter F; Aarabi, Bizhan; Sheth, Kevin; Scalea, Thomas M

2012-05-01

Vital signs, particularly blood pressure, are often manipulated to maximize perfusion and optimize recovery from severe traumatic brain injury (sTBI). We investigated the utility of automated continuously recorded vital signs to predict outcomes after sTBI. Sixty patients with head Abbreviated Injury Scale score ≥ 3, age >14 years, "isolated" TBI, and need for intracranial pressure monitoring were prospectively enrolled at a single, large urban tertiary care facility. Outcome was measured by mortality and extended Glasgow Outcome Scale (GOSE) at 12 months. Continuous, automated, digital data were collected every 6 seconds for 72 hours after admission, and 5-minute means of systolic blood pressure (SBP) were recorded. We calculated SBP as pressure × time dose (PTD) to describe the cumulative amplitude and duration of episodes above and below clinical thresholds. The extent and duration of the insults were calculated as percent time (%time), PTD, and PTD per day (PTD/D) of defined thresholds (SBP: <90 mm Hg, <100 mm Hg, <110 mm Hg, and <120 mm Hg; mean arterial pressure: <60 mm Hg and <70 mm Hg; heart rate: >100 bpm and >120 bpm; and SpO(2): <88% and <92%) for the first 12 hours, 24 hours, and 48 hours of intensive care unit admission. We analyzed their ability to predict mortality and GOSE by receiver operator characteristics. Mean age was 33.9 (range, 16-83) years, mean admission Glasgow Coma Scale score 6.4 ± 3, and mean head Abbreviated Injury Scale score 4.2 ± 0.72. The 30-day mortality rate was 13.3%. Of the 45 patients in whom GOSE at 12 months was available, 28 (62%) had good neurologic outcomes (GOSE score >4). Traditional markers of poor outcome (admission SBP, admission Glasgow Coma Scale, and Marshall score) were not different between groups with good or poor outcome. PTD, PTD/D, and %time SBP <110 mm Hg and SBP <120 mm Hg predicted mortality at 12 hours, 24 hours, and 48 hours (p < 0.04). Percent time SBP <110 mm Hg in the first 24 hours was predictive of 12-month GOSE (p = 0.02). PTD/D SBP <120 mm Hg in the first 24 hours and PTD and PTD/D in the first 48 hours were also predictive of 12-month GOSE (p < 0.05). Within the first 48 hours of intensive care unit admission, hypotension was found to be predictive of mortality and functional outcomes at higher thresholds than traditionally defined. Systemic blood pressure targets closer to 120 mm Hg may be more efficacious in minimizing secondary insults and particularly useful in settings without invasive intracranial monitoring capabilities. III, prognostic study.

Updraft Fixed Bed Gasification Aspen Plus Model

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

2007-09-27

The updraft fixed bed gasification model provides predictive modeling capabilities for updraft fixed bed gasifiers, when devolatilization data is available. The fixed bed model is constructed using Aspen Plus, process modeling software, coupled with a FORTRAN user kinetic subroutine. Current updraft gasification models created in Aspen Plus have limited predictive capabilities and must be "tuned" to reflect a generalized gas composition as specified in literature or by the gasifier manufacturer. This limits the applicability of the process model.

Contact and Impact Dynamic Modeling Capabilities of LS-DYNA for Fluid-Structure Interaction Problems

DTIC Science & Technology

2010-12-02

rigid sphere in a vertical water entry,” Applied Ocean Research, 13(1), pp. 43-48. Monaghan, J.J., 1994. “ Simulating free surface flows with SPH ...The kinematic free surface condition was used to determine the intersection between the free surface and the body in the outer flow domain...and the results were compared with analytical and numerical predictions. The predictive capability of ALE and SPH features of LS-DYNA for simulation

Real-time scene and signature generation for ladar and imaging sensors

NASA Astrophysics Data System (ADS)

Swierkowski, Leszek; Christie, Chad L.; Antanovskii, Leonid; Gouthas, Efthimios

2014-05-01

This paper describes development of two key functionalities within the VIRSuite scene simulation program, broadening its scene generation capabilities and increasing accuracy of thermal signatures. Firstly, a new LADAR scene generation module has been designed. It is capable of simulating range imagery for Geiger mode LADAR, in addition to the already existing functionality for linear mode systems. Furthermore, a new 3D heat diffusion solver has been developed within the VIRSuite signature prediction module. It is capable of calculating the temperature distribution in complex three-dimensional objects for enhanced dynamic prediction of thermal signatures. With these enhancements, VIRSuite is now a robust tool for conducting dynamic simulation for missiles with multi-mode seekers.

Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples.

PubMed

Fekete, Tibor; Rásó, Erzsébet; Pete, Imre; Tegze, Bálint; Liko, István; Munkácsy, Gyöngyi; Sipos, Norbert; Rigó, János; Györffy, Balázs

2012-07-01

Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort. Copyright © 2011 UICC.

Lack of Early Improvement Predicts Poor Outcome Following Acute Intracerebral Hemorrhage.

PubMed

Yogendrakumar, Vignan; Smith, Eric E; Demchuk, Andrew M; Aviv, Richard I; Rodriguez-Luna, David; Molina, Carlos A; Silva Blas, Yolanda; Dzialowski, Imanuel; Kobayashi, Adam; Boulanger, Jean-Martin; Lum, Cheemun; Gubitz, Gord; Padma, Vasantha; Roy, Jayanta; Kase, Carlos S; Bhatia, Rohit; Ali, Myzoon; Lyden, Patrick; Hill, Michael D; Dowlatshahi, Dar

2018-04-01

There are limited data as to what degree of early neurologic change best relates to outcome in acute intracerebral hemorrhage. We aimed to derive and validate a threshold for early postintracerebral hemorrhage change that best predicts 90-day outcomes. Derivation: retrospective analysis of collated clinical stroke trial data (Virtual International Stroke Trials Archive). retrospective analysis of a prospective multicenter cohort study (Prediction of haematoma growth and outcome in patients with intracerebral haemorrhage using the CT-angiography spot sign [PREDICT]). Neurocritical and ICUs. Patients with acute intracerebral hemorrhage presenting less than 6 hours. Derivation: 552 patients; validation: 275 patients. None. We generated a receiver operating characteristic curve for the association between 24-hour National Institutes of Health Stroke Scale change and clinical outcome. The primary outcome was a modified Rankin Scale score of 4-6 at 90 days; secondary outcomes were other modified Rankin Scale score ranges (modified Rankin Scale, 2-6, 3-6, 5-6, 6). We employed Youden's J Index to select optimal cut points and calculated sensitivity, specificity, and predictive values. We determined independent predictors via multivariable logistic regression. The derived definitions were validated in the PREDICT cohort. Twenty-four-hour National Institutes of Health Stroke Scale change was strongly associated with 90-day outcome with an area under the receiver operating characteristic curve of 0.75. Youden's method showed an optimum cut point at -0.5, corresponding to National Institutes of Health Stroke Scale change of greater than or equal to 0 (a lack of clinical improvement), which was seen in 46%. Early neurologic change accurately predicted poor outcome when defined as greater than or equal to 0 (sensitivity, 65%; specificity, 73%; positive predictive value, 70%; adjusted odds ratio, 5.05 [CI, 3.25-7.85]) or greater than or equal to 4 (sensitivity, 19%; specificity, 98%; positive predictive value, 91%; adjusted odds ratio, 12.24 [CI, 4.08-36.66]). All definitions reproduced well in the validation cohort. Lack of clinical improvement at 24 hours robustly predicted poor outcome and showed good discrimination for individual patients who would do poorly. These findings are useful for prognostication and may also present as a potential early surrogate outcome for future intracerebral hemorrhage treatment trials.

Li-Ion Cell Development for Low Temperature Applications

NASA Technical Reports Server (NTRS)

Huang, C.-K.; Sakamoto, J. S.; Surampudi, S.; Wolfenstine, J.

2000-01-01

JPL is involved in the development of rechargeable Li-ion cells for future Mars Exploration Missions. The specific objectives are to improve the Li-ion cell cycle life performance and rate capability at low temperature (<<-20 C) in order to enhance survivability of the Mars lander and rover batteries. Poor Li-ion rate capability at low temperature has been attributed to: (1) the electrolytes becoming viscous or freezing and/or (2) reduced electrode capacity that results from decreased Li diffusivity. Our efforts focus on increasing the rate capability at low temperature for Li-ion cells. In order to improve the rate capability we evaluated the following: (1) cathode performance at low temperatures, (2) electrode active material particle size on low temperature performance and (3) Li diffusivity at room temperature and low temperatures. In this paper, we will discuss the results of our study.

ROTONET Primer

NASA Technical Reports Server (NTRS)

Prichard, Devon S.

1996-01-01

This document provides a brief overview of use of the ROTONET rotorcraft system noise prediction capability within the Aircraft Noise Program (ANOPP). Reviews are given on rotorcraft noise, the state-of-the-art of system noise prediction, and methods for using the various ROTONET prediction modules.

Comparison of Fire Model Predictions with Experiments Conducted in a Hangar With a 15 Meter Ceiling

NASA Technical Reports Server (NTRS)

Davis, W. D.; Notarianni, K. A.; McGrattan, K. B.

1996-01-01

The purpose of this study is to examine the predictive capabilities of fire models using the results of a series of fire experiments conducted in an aircraft hangar with a ceiling height of about 15 m. This study is designed to investigate model applicability at a ceiling height where only a limited amount of experimental data is available. This analysis deals primarily with temperature comparisons as a function of distance from the fire center and depth beneath the ceiling. Only limited velocity measurements in the ceiling jet were available but these are also compared with those models with a velocity predictive capability.

Observational breakthroughs lead the way to improved hydrological predictions

NASA Astrophysics Data System (ADS)

Lettenmaier, Dennis P.

2017-04-01

New data sources are revolutionizing the hydrological sciences. The capabilities of hydrological models have advanced greatly over the last several decades, but until recently model capabilities have outstripped the spatial resolution and accuracy of model forcings (atmospheric variables at the land surface) and the hydrologic state variables (e.g., soil moisture; snow water equivalent) that the models predict. This has begun to change, as shown in two examples here: soil moisture and drought evolution over Africa as predicted by a hydrology model forced with satellite-derived precipitation, and observations of snow water equivalent at very high resolution over a river basin in California's Sierra Nevada.

Interoception in anxiety and depression

PubMed Central

Stein, Murray B.

2010-01-01

We review the literature on interoception as it relates to depression and anxiety, with a focus on belief, and alliesthesia. The connection between increased but noisy afferent interoceptive input, self-referential and belief-based states, and top-down modulation of poorly predictive signals is integrated into a neuroanatomical and processing model for depression and anxiety. The advantage of this conceptualization is the ability to specifically examine the interface between basic interoception, self-referential belief-based states, and enhanced top-down modulation to attenuate poor predictability. We conclude that depression and anxiety are not simply interoceptive disorders but are altered interoceptive states as a consequence of noisily amplified self-referential interoceptive predictive belief states. PMID:20490545

Poor Self-Control and Harsh Punishment in Childhood Prospectively Predict Borderline Personality Symptoms in Adolescent Girls

PubMed Central

Hallquist, Michael N.; Hipwell, Alison E.; Stepp, Stephanie D.

2015-01-01

Developmental theories of borderline personality disorder (BPD) propose that harsh, invalidating parenting of a child with poor self-control and heightened negative emotionality often leads to a coercive cycle of parent-child transactions that increase risk for BPD symptoms such as emotion dysregulation. Although parenting practices and child temperament have previously been linked with BPD, less is known about the prospective influences of caregiver and child characteristics. Using annual longitudinal data from the Pittsburgh Girls Study (n = 2450), our study examined how reciprocal influences among harsh parenting, self-control, and negative emotionality between ages 5 and 14 predicted the development of BPD symptoms in adolescent girls ages 14 to 17. Consistent with developmental theories, we found that harsh punishment, poor self-control, and negative emotionality predicted BPD symptom severity at age 14. Only worsening self-control between ages 12 and 14, however, predicted growth in BPD symptoms from 14 to 17. Furthermore, the effects of harsh punishment and poor self-control on age 14 BPD symptoms were partially mediated by their earlier reciprocal effects on each other between ages 5 and 14. Our findings underscore the need to address both child and parental contributions to dysfunctional transactions in order to stem the development of BPD symptoms. Moreover, problems with self-regulation in early adolescence may indicate heightened risk for subsequent BPD. Altogether, these results increase our understanding of developmental trajectories associated with BPD symptoms in adolescent girls. PMID:25961815

Poor self-control and harsh punishment in childhood prospectively predict borderline personality symptoms in adolescent girls.

PubMed

Hallquist, Michael N; Hipwell, Alison E; Stepp, Stephanie D

2015-08-01

Developmental theories of borderline personality disorder (BPD) propose that harsh, invalidating parenting of a child with poor self-control and heightened negative emotionality often leads to a coercive cycle of parent-child transactions that increase risk for BPD symptoms such as emotion dysregulation. Although parenting practices and child temperament have previously been linked with BPD, less is known about the prospective influences of caregiver and child characteristics. Using annual longitudinal data from the Pittsburgh Girls Study (n = 2,450), our study examined how reciprocal influences among harsh parenting, self-control, and negative emotionality between ages 5 and 14 predicted the development of BPD symptoms in adolescent girls ages 14 to 17. Consistent with developmental theories, we found that harsh punishment, poor self-control, and negative emotionality predicted BPD symptom severity at age 14. Only worsening self-control between ages 12 and 14, however, predicted growth in BPD symptoms from 14 to 17. Furthermore, the effects of harsh punishment and poor self-control on age 14 BPD symptoms were partially mediated by their earlier reciprocal effects on each other between ages 5 and 14. Our findings underscore the need to address both child and parental contributions to dysfunctional transactions in order to stem the development of BPD symptoms. Moreover, problems with self-regulation in early adolescence may indicate heightened risk for subsequent BPD. Altogether, these results increase our understanding of developmental trajectories associated with BPD symptoms in adolescent girls. (c) 2015 APA, all rights reserved).

A Valuable Tool in Predicting Poor Outcome due to Sepsis in Pediatric Intensive Care Unit: Tp-e/QT Ratio.

PubMed

Ozdemir, Rahmi; Isguder, Rana; Kucuk, Mehmet; Karadeniz, Cem; Ceylan, Gokhan; Katipoglu, Nagehan; Yilmazer, Murat Muhtar; Yozgat, Yilmaz; Mese, Timur; Agin, Hasan

2016-10-01

To assess the feasibility of 12-lead electrocardiographic (ECG) measures such as P wave dispersion (PWd), QT interval, QT dispersion (QTd), Tp-e interval, Tp-e/QT and Tp-e/QTc ratio in predicting poor outcome in patients diagnosed with sepsis in pediatric intensive care unit (PICU). Ninety-three patients diagnosed with sepsis, severe sepsis or septic shock and 103 age- and sex-matched healthy children were enrolled into the study. PWd, QT interval, QTd, Tp-e interval and Tp-e/QT, Tp-e/QTc ratios were obtained from a 12-lead electrocardiogram. PWd, QTd, Tp-e interval and Tp-e/QT, Tp-e/QTc ratios were significantly higher in septic patients compared with the controls. During the study period, 41 patients had died. In multivariate logistic regression analyses, only Tp-e/QT ratio was found to be an independent predictor of mortality. The ECG measurements can predict the poor outcome in patients with sepsis. The Tp-e/QT ratio may be a valuable tool in predicting mortality for patients with sepsis in the PICU. © The Author [2016]. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

Autonomic dysfunction predicts poor physical improvement after cardiac rehabilitation in patients with heart failure.

PubMed

Compostella, Leonida; Nicola, Russo; Tiziana, Setzu; Caterina, Compostella; Fabio, Bellotto

2014-11-01

Cardiac autonomic dysfunction, clinically expressed by reduced heart rate variability (HRV), is present in patients with congestive heart failure (CHF) and is related to the degree of left ventricular dysfunction. In athletes, HRV is an indicator of ability to improve performance. No similar data are available for CHF. The aim of this study was to assess whether HRV could predict the capability of CHF patients to improve physical fitness after a short period of exercise-based cardiac rehabilitation (CR). This was an observational, non-randomized study, conducted on 57 patients with advanced CHF, admitted to a residential cardiac rehabilitation unit 32 ± 22 days after an episode of acute heart failure. Inclusion criteria were sinus rhythm, stable clinical conditions, no diabetes and ejection fraction ≤ 35%. HRV (time-domain) and mean and minimum heart rate (HR) were evaluated using 24-h Holter at admission. Patients' physical fitness was evaluated at admission by 6-minute walking test (6MWT) and reassessed after two weeks of intensive exercise-based CR. Exercise capacity was evaluated by a symptom-limited cardiopulmonary exercise test (CPET). Patients with very depressed HRV (SDNN 55.8 ± 10.0 ms) had no improvement in their walking capacity after short CR, walked shorter absolute distances at final 6MWT (348 ± 118 vs. 470 ± 109 m; P = 0.027) and developed a peak-VO2 at CPET significantly lower than patients with greater HRV parameters (11.4 ± 3.7 vs. an average > 16 ± 4 mL/kg/min). Minimum HR, but not mean HR, showed a negative correlation (ρ = -0.319) with CPET performance. In patients with advanced CHF, depressed HRV and higher minimum HR were predictors of poor working capacity after a short period of exercise-based CR. An individualized and intensive rehabilitative intervention should be considered for these patients.

Early predicted time to normalization of tumor markers predicts outcome in poor-prognosis nonseminomatous germ cell tumors.

PubMed

Fizazi, Karim; Culine, Stéphane; Kramar, Andrew; Amato, Robert J; Bouzy, Jeannine; Chen, Isan; Droz, Jean-Pierre; Logothetis, Christopher J

2004-10-01

The prognostic relevance of the rate of decline of serum alpha-fetoprotein (AFP) and human chorionic gonadotropin (HCG) during the first 3 weeks of chemotherapy for nonseminomatous germ cell tumors (NSGCT) was studied in the context of the International Germ Cell Cancer Collaborative Group (IGCCCG) classification. Data from 653 patients prospectively recruited in clinical trials were studied. Tumor markers were obtained before chemotherapy and 3 weeks later. Decline rates were calculated using a logarithmic formula and expressed as a predicted time to normalization (TTN). A favorable TTN was defined when both AFP and HCG had a favorable decline rate, including cases with normal values. The median follow-up was 50 months (range, 2 to 151 months). Tumor decline rate expressed as a predicted TTN was associated with both progression-free survival (PFS; P <.0001) and overall survival (OS; P <.0001). The 4-year PFS rates were 64% and 38% in patients from the poor-prognosis group who had a favorable and an unfavorable TTN, respectively. The 4-year OS rates were 83% and 58%, respectively. This effect was independent from the initial tumor marker values, the primary tumor site, and the presence of nonpulmonary visceral metastases: tumor marker decline rate remained a strong predictor for both PFS (hazard ratio = 2.5; P =.01) and OS (hazard ratio = 4.6; P =.002) in patients from the IGCCCG poor-prognosis group in multivariate analysis. Early predicted time to tumor marker normalization is an independent prognostic factor in patients with poor-prognosis NSGCT and may be a useful tool in the therapeutic management of these patients.

Black Hole Sign Predicts Poor Outcome in Patients with Intracerebral Hemorrhage.

PubMed

Li, Qi; Yang, Wen-Song; Chen, Sheng-Li; Lv, Fu-Rong; Lv, Fa-Jin; Hu, Xi; Zhu, Dan; Cao, Du; Wang, Xing-Chen; Li, Rui; Yuan, Liang; Qin, Xin-Yue; Xie, Peng

2018-01-01

In spontaneous intracerebral hemorrhage (ICH), black hole sign has been proposed as a promising imaging marker that predicts hematoma expansion in patients with ICH. The aim of our study was to investigate whether admission CT black hole sign predicts hematoma growth in patients with ICH. From July 2011 till February 2016, patients with spontaneous ICH who underwent baseline CT scan within 6 h of symptoms onset and follow-up CT scan were recruited into the study. The presence of black hole sign on admission non-enhanced CT was independently assessed by 2 readers. The functional outcome was assessed using the modified Rankin Scale (mRS) at 90 days. Univariate and multivariable logistic regression analyses were performed to assess the association between the presence of the black hole sign and functional outcome. A total of 225 patients (67.6% male, mean age 60.3 years) were included in our study. Black hole sign was identified in 32 of 225 (14.2%) patients on admission CT scan. The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, baseline ICH volume, admission Glasgow Coma Scale score, and presence of black hole sign on baseline CT independently predict poor functional outcome at 90 days. There are significantly more patients with a poor functional outcome (defined as mRS ≥4) among patients with black hole sign than those without (84.4 vs. 32.1%, p < 0.001; OR 8.19, p = 0.001). The CT black hole sign independently predicts poor outcome in patients with ICH. Early identification of black hole sign is useful in prognostic stratification and may serve as a potential therapeutic target for anti-expansion clinical trials. © 2018 S. Karger AG, Basel.

Prediction of Agglomeration, Fouling, and Corrosion Tendency of Fuels in CFB Co-Combustion

NASA Astrophysics Data System (ADS)

Barišć, Vesna; Zabetta, Edgardo Coda; Sarkki, Juha

Prediction of agglomeration, fouling, and corrosion tendency of fuels is essential to the design of any CFB boiler. During the years, tools have been successfully developed at Foster Wheeler to help with such predictions for the most commercial fuels. However, changes in fuel market and the ever-growing demand for co-combustion capabilities pose a continuous need for development. This paper presents results from recently upgraded models used at Foster Wheeler to predict agglomeration, fouling, and corrosion tendency of a variety of fuels and mixtures. The models, subject of this paper, are semi-empirical computer tools that combine the theoretical basics of agglomeration/fouling/corrosion phenomena with empirical correlations. Correlations are derived from Foster Wheeler's experience in fluidized beds, including nearly 10,000 fuel samples and over 1,000 tests in about 150 CFB units. In these models, fuels are evaluated based on their classification, their chemical and physical properties by standard analyses (proximate, ultimate, fuel ash composition, etc.;.) alongside with Foster Wheeler own characterization methods. Mixtures are then evaluated taking into account the component fuels. This paper presents the predictive capabilities of the agglomeration/fouling/corrosion probability models for selected fuels and mixtures fired in full-scale. The selected fuels include coals and different types of biomass. The models are capable to predict the behavior of most fuels and mixtures, but also offer possibilities for further improvements.

High-fidelity modeling and impact footprint prediction for vehicle breakup analysis

NASA Astrophysics Data System (ADS)

Ling, Lisa

For decades, vehicle breakup analysis had been performed for space missions that used nuclear heater or power units in order to assess aerospace nuclear safety for potential launch failures leading to inadvertent atmospheric reentry. Such pre-launch risk analysis is imperative to assess possible environmental impacts, obtain launch approval, and for launch contingency planning. In order to accurately perform a vehicle breakup analysis, the analysis tool should include a trajectory propagation algorithm coupled with thermal and structural analyses and influences. Since such a software tool was not available commercially or in the public domain, a basic analysis tool was developed by Dr. Angus McRonald prior to this study. This legacy software consisted of low-fidelity modeling and had the capability to predict vehicle breakup, but did not predict the surface impact point of the nuclear component. Thus the main thrust of this study was to develop and verify the additional dynamics modeling and capabilities for the analysis tool with the objectives to (1) have the capability to predict impact point and footprint, (2) increase the fidelity in the prediction of vehicle breakup, and (3) reduce the effort and time required to complete an analysis. The new functions developed for predicting the impact point and footprint included 3-degrees-of-freedom trajectory propagation, the generation of non-arbitrary entry conditions, sensitivity analysis, and the calculation of impact footprint. The functions to increase the fidelity in the prediction of vehicle breakup included a panel code to calculate the hypersonic aerodynamic coefficients for an arbitrary-shaped body and the modeling of local winds. The function to reduce the effort and time required to complete an analysis included the calculation of node failure criteria. The derivation and development of these new functions are presented in this dissertation, and examples are given to demonstrate the new capabilities and the improvements made, with comparisons between the results obtained from the upgraded analysis tool and the legacy software wherever applicable.

Improving GEFS Weather Forecasts for Indian Monsoon with Statistical Downscaling

NASA Astrophysics Data System (ADS)

Agrawal, Ankita; Salvi, Kaustubh; Ghosh, Subimal

2014-05-01

Weather forecast has always been a challenging research problem, yet of a paramount importance as it serves the role of 'key input' in formulating modus operandi for immediate future. Short range rainfall forecasts influence a wide range of entities, right from agricultural industry to a common man. Accurate forecasts actually help in minimizing the possible damage by implementing pre-decided plan of action and hence it is necessary to gauge the quality of forecasts which might vary with the complexity of weather state and regional parameters. Indian Summer Monsoon Rainfall (ISMR) is one such perfect arena to check the quality of weather forecast not only because of the level of intricacy in spatial and temporal patterns associated with it, but also the amount of damage it can cause (because of poor forecasts) to the Indian economy by affecting agriculture Industry. The present study is undertaken with the rationales of assessing, the ability of Global Ensemble Forecast System (GEFS) in predicting ISMR over central India and the skill of statistical downscaling technique in adding value to the predictions by taking them closer to evidentiary target dataset. GEFS is a global numerical weather prediction system providing the forecast results of different climate variables at a fine resolution (0.5 degree and 1 degree). GEFS shows good skills in predicting different climatic variables but fails miserably over rainfall predictions for Indian summer monsoon rainfall, which is evident from a very low to negative correlation values between predicted and observed rainfall. Towards the fulfilment of second rationale, the statistical relationship is established between the reasonably well predicted climate variables (GEFS) and observed rainfall. The GEFS predictors are treated with multicollinearity and dimensionality reduction techniques, such as principal component analysis (PCA) and least absolute shrinkage and selection operator (LASSO). Statistical relationship is established between the principal components and observed rainfall over training period and predictions are obtained for testing period. The validations show high improvements in correlation coefficient between observed and predicted data (0.25 to 0.55). The results speak in favour of statistical downscaling methodology which shows the capability to reduce the gap between observed data and predictions. A detailed study is required to be carried out by applying different downscaling techniques to quantify the improvements in predictions.

Micromechanics and Piezo Enhancements of HyperSizer

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Bednarcyk, Brett A.; Yarrington, Phillip; Collier, Craig S.

2006-01-01

The commercial HyperSizer aerospace-composite-material-structure-sizing software has been enhanced by incorporating capabilities for representing coupled thermal, piezoelectric, and piezomagnetic effects on the levels of plies, laminates, and stiffened panels. This enhancement is based on a formulation similar to that of the pre-existing HyperSizer capability for representing thermal effects. As a result of this enhancement, the electric and/or magnetic response of a material or structure to a mechanical or thermal load, or its mechanical response to an applied electric or magnetic field can be predicted. In another major enhancement, a capability for representing micromechanical effects has been added by establishment of a linkage between HyperSizer and Glenn Research Center s Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC) computer program, which was described in several prior NASA Tech Briefs articles. The linkage enables Hyper- Sizer to localize to the fiber and matrix level rather than only to the ply level, making it possible to predict local failures and to predict properties of plies from those of the component fiber and matrix materials. Advanced graphical user interfaces and database structures have been developed to support the new HyperSizer micromechanics capabilities.

Multi-timescale power and energy assessment of lithium-ion battery and supercapacitor hybrid system using extended Kalman filter

NASA Astrophysics Data System (ADS)

Wang, Yujie; Zhang, Xu; Liu, Chang; Pan, Rui; Chen, Zonghai

2018-06-01

The power capability and maximum charge and discharge energy are key indicators for energy management systems, which can help the energy storage devices work in a suitable area and prevent them from over-charging and over-discharging. In this work, a model based power and energy assessment approach is proposed for the lithium-ion battery and supercapacitor hybrid system. The model framework of the lithium-ion battery and supercapacitor hybrid system is developed based on the equivalent circuit model, and the model parameters are identified by regression method. Explicit analyses of the power capability and maximum charge and discharge energy prediction with multiple constraints are elaborated. Subsequently, the extended Kalman filter is employed for on-board power capability and maximum charge and discharge energy prediction to overcome estimation error caused by system disturbance and sensor noise. The charge and discharge power capability, and the maximum charge and discharge energy are quantitatively assessed under both the dynamic stress test and the urban dynamometer driving schedule. The maximum charge and discharge energy prediction of the lithium-ion battery and supercapacitor hybrid system with different time scales are explored and discussed.

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.

Quality of life before hyperhidrosis treatment as a predictive factor for oxybutynin treatment outcomes in palmar and axillary hyperhidrosis.

PubMed

Wolosker, Nelson; Krutman, Mariana; Teivelis, Marcelo P; Campbell, Taiz P D A; Kauffman, Paulo; de Campos, José Ribas M; Puech-Leão, Pedro

2014-05-01

Studies have suggested that quality of life (QOL) evaluation before video-assisted thoracoscopic sympathectomy for patients with hyperhidrosis may serve as a predictive factor for positive postoperative outcomes. Our study aims to analyze if this tendency is also observed in patients treated with oxybutynin for palmar and axillary hyperhidrosis. Five hundred sixty-five patients who submitted to a protocol treatment with oxybutynin were retrospectively analyzed between January 2007 and January 2012 and were divided into 2 groups according to QOL assessment before treatment. The groups consisted of 176 patients with "poor" and 389 patients with "very poor" QOL evaluation before oxybutynin treatment. Outcomes involving improvements in QOL and clinical progression of hyperhidrosis were evaluated using a validated clinical questionnaire that was specifically designed to assess satisfaction in patients with excessive sweating. Improvements in hyperhidrosis after oxybutynin were observed in 65.5% of patients with very poor pretreatment QOL scores and in 75% of patients with poor pretreatment QOL scores, and the only adverse event associated with oxybutynin treatment was dry mouth, which was observed with greater intensity in patients with very poor initial QOL evaluation. Improvements in hyperhidrosis after oxybutynin treatment were similar in both groups, suggesting that QOL before treatment is not a predictive factor for clinical outcomes, contrasting with surgical results that disclose significantly better results in patients with initially poorer QOL analysis. Copyright © 2014 Elsevier Inc. All rights reserved.

Efffect of Aeroallergen Sensitization on Asthma Control in African-American Teens with Persistent Asthma

EPA Science Inventory

In African-American adolescents with persistent asthma, allergic profile predicted the likelihood of having poorly controlled asthma despite guidelines-directed therapies. Our results suggest that tree and weed pollen sensitization are independent risk factors for poorly controll...

THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY: AN EXPANDED VIEW OF CHEMICAL TOXICITY

EPA Science Inventory

A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. T...

Prediction of Recovery from Coma After CPR

MedlinePlus

... to pain. There is good evidence* that myoclonus status epilepticus within the first day after CPR accurately predicts poor recovery from coma. Myoclonus status epilepticus is a constant twitching of muscles, including the ...

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.

Proton MRS in acute traumatic brain injury: role for glutamate/glutamine and choline for outcome prediction.

PubMed

Shutter, Lori; Tong, Karen A; Holshouser, Barbara A

2004-12-01

Proton magnetic resonance spectroscopy (MRS) is being used to evaluate individuals with acute traumatic brain injury and several studies have shown that changes in certain brain metabolites (N-acetylaspartate, choline) are associated with poor neurologic outcomes. The majority of previous MRS studies have been obtained relatively late after injury and none have examined the role of glutamate/ glutamine (Glx). We conducted a prospective MRS study of 42 severely injured adults to measure quantitative metabolite changes early (7 days) after injury in normal appearing brain. We used these findings to predict long-term neurologic outcome and to determine if MRS data alone or in combination with clinical outcome variables provided better prediction of long-term outcomes. We found that glutamate/glutamine (Glx) and choline (Cho) were significantly elevated in occipital gray and parietal white matter early after injury in patients with poor long-term (6-12-month) outcomes. Glx and Cho ratios predicted long-term outcome with 94% accuracy and when combined with the motor Glasgow Coma Scale score provided the highest predictive accuracy (97%). Somatosensory evoked potentials were not as accurate as MRS data in predicting outcome. Elevated Glx and Cho are more sensitive indicators of injury and predictors of poor outcome when spectroscopy is done early after injury. This may be a reflection of early excitotoxic injury (i.e., elevated Glx) and of injury associated with membrane disruption (i.e., increased Cho) secondary to diffuse axonal injury.

EEG, evoked potentials and pulsed Doppler in asphyxiated term infants.

PubMed

Julkunen, Mia K; Himanen, Sari-Leena; Eriksson, Kai; Janas, Martti; Luukkaala, Tiina; Tammela, Outi

2014-09-01

To evaluate electroencephalograms (EEG), evoked potentials (EPs) and Doppler findings in the cerebral arteries as predictors of a 1-year outcome in asphyxiated newborn infants. EEG and EPs (brain stem auditory (BAEP), somatosensory (SEP), visual (VEP) evoked potentials) were assessed in 30 asphyxiated and 30 healthy term infants during the first days (range 1-8). Cerebral blood flow velocities (CBFV) were measured from the cerebral arteries using pulsed Doppler at ∼24h of age. EEG, EPs, Doppler findings, symptoms of hypoxic ischemic encephalopathy (HIE) and their combination were evaluated in predicting a 1-year outcome. An abnormal EEG background predicted poor outcome in the asphyxia group with a sensitivity of 67% and 81% specificity, and an abnormal SEP with 75% and 79%, respectively. Combining increased systolic CBFV (mean+3SD) with abnormal EEG or SEP improved the specificity, but not the sensitivity. The predictive values of abnormal BAEP and VEP were poor. Normal EEG and SEP predicted good outcome in the asphyxia group with sensitivities from 79% to 81%. The combination of normal EEG, normal SEP and systolic CBFV<3SD predicted good outcome with a sensitivity of 74% and 100% specificity. Combining abnormal EEG or EPs findings with increased systolic CBFV did not improve prediction of a poor 1-year outcome of asphyxiated infants. Normal EEG and normal SEP combined with systolic CBFV<3SD at about 24 h can be valuable in the prediction of normal 1-year outcome. Combining systolic CBFV at 24 h with EEG and SEP examinations can be of use in the prediction of normal 1-year outcome among asphyxiated infants. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Projected Applications of a "Weather in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Molthan, Andrew; Zavodsky, Bradley T.; Case, Jonathan L.; LaFontaine, Frank J.; Srikishen, Jayanthi

2010-01-01

The NASA Short-term Prediction Research and Transition Center (SPoRT)'s new "Weather in a Box" resources will provide weather research and forecast modeling capabilities for real-time application. Model output will provide additional forecast guidance and research into the impacts of new NASA satellite data sets and software capabilities. By combining several research tools and satellite products, SPoRT can generate model guidance that is strongly influenced by unique NASA contributions.

Competitive assessment of aerospace systems using system dynamics

NASA Astrophysics Data System (ADS)

Pfaender, Jens Holger

Aircraft design has recently experienced a trend away from performance centric design towards a more balanced approach with increased emphasis on engineering an economically successful system. This approach focuses on bringing forward a comprehensive economic and life-cycle cost analysis. Since the success of any system also depends on many external factors outside of the control of the designer, this traditionally has been modeled as noise affecting the uncertainty of the design. However, this approach is currently lacking a strategic treatment of necessary early decisions affecting the probability of success of a given concept in a dynamic environment. This suggests that the introduction of a dynamic method into a life-cycle cost analysis should allow the analysis of the future attractiveness of such a concept in the presence of uncertainty. One way of addressing this is through the use of a competitive market model. However, existing market models do not focus on the dynamics of the market. Instead, they focus on modeling and predicting market share through logit regression models. The resulting models exhibit relatively poor predictive capabilities. The method proposed here focuses on a top-down approach that integrates a competitive model based on work in the field of system dynamics into the aircraft design process. Demonstrating such integration is one of the primary contributions of this work, which previously has not been demonstrated. This integration is achieved through the use of surrogate models, in this case neural networks. This enabled not only the practical integration of analysis techniques, but also reduced the computational requirements so that interactive exploration as envisioned was actually possible. The example demonstration of this integration is built on the competition in the 250 seat large commercial aircraft market exemplified by the Boeing 767-400ER and the Airbus A330-200. Both aircraft models were calibrated to existing performance and certification data and then integrated into the system dynamics market model. The market model was then calibrated with historical market data. This calibration showed a much improved predictive capability as compared to the conventional logit regression models. An additional advantage of this dynamic model is that to realize this improved capability, no additional explanatory variables were required. Furthermore, the resulting market model was then integrated into a prediction profiler environment with a time variant Monte-Carlo analysis resulting in a unique trade-off environment. This environment was shown to allow interactive trade-off between aircraft design decisions and economic considerations while allowing the exploration potential market success in the light of varying external market conditions and scenarios. The resulting method is capable of reduced decision support uncertainty and identification of robust design decisions in future scenarios with a high likelihood of occurrence with special focus on the path dependent nature of future implications of decisions. Furthermore, it was possible to demonstrate the increased importance of design and technology choices on the competitiveness in scenarios with drastic increases in commodity prices during the time period modeled. Another use of the existing outputs of the Monte-Carlo analysis was then realized by showing them on a multivariate scatter plot. This plot was then shown to enable by appropriate grouping of variables to enable the top down definition of an aircraft design, also known as inverse design. In other words this enables the designer to define strategic market and return on investment goals for a number of scenarios, for example the development of fuel prices, and then directly see which specific aircraft designs meet these goals.

Impairments of Motor Function While Multitasking in HIV

PubMed Central

Kronemer, Sharif I.; Mandel, Jordan A.; Sacktor, Ned C.; Marvel, Cherie L.

2017-01-01

Human immunodeficiency virus (HIV) became a treatable illness with the introduction of combination antiretroviral therapy (CART). As a result, patients with regular access to CART are expected to live decades with HIV. Long-term HIV infection presents unique challenges, including neurocognitive impairments defined by three major stages of HIV-associated neurocognitive disorders (HAND). The current investigation aimed to study cognitive and motor impairments in HIV using a novel multitasking paradigm. Unlike current standard measures of cognitive and motor performance in HIV, multitasking increases real-world validity by mimicking the dual motor and cognitive demands that are part of daily professional and personal settings (e.g., driving, typing and writing). Moreover, multitask assessments can unmask compensatory mechanisms, normally used under single task conditions, to maintain performance. This investigation revealed that HIV+ participants were impaired on the motor component of the multitask, while cognitive performance was spared. A patient-specific positive interaction between motor performance and working memory recall was driven by poor HIV+ multitaskers. Surprisingly, HAND stage did not correspond with multitask performance and a variety of commonly used assessments indicated normal motor function among HIV+ participants with poor motor performance during the experimental task. These results support the use of multitasks to reveal otherwise hidden impairment in chronic HIV by expanding the sensitivity of clinical assessments used to determine HAND stage. Future studies should examine the capability of multitasks to predict performance in personal, professional and health-related behaviors and prognosis of patients living with chronic HIV. PMID:28503143

International MODIS and AIRS Processing Package (IMAPP) Implementation of Infusion of Satellite Data into Environmental Applications-International (IDEA-I) for Air Quality Forecasts using Suomi-NPP, Terra and Aqua Aerosol Retrievals

NASA Astrophysics Data System (ADS)

Davies, J. E.; Strabala, K.; Pierce, R. B.; Huang, A.

2016-12-01

Fine mode aerosols play a significant role in public health through their impact on respiratory and cardiovascular disease. IDEA-I (Infusion of Satellite Data into Environmental Applications-International) is a real-time system for trajectory-based forecasts of aerosol dispersion that can assist in the prediction of poor air quality events. We released a direct broadcast version of IDEA-I for aerosol trajectory forecasts in June 2012 under the International MODIS and AIRS Processing Package (IMAPP). In January 2014 we updated this application with website software to display multi-satellite products. Now we have added VIIRS aerosols from Suomi National Polar-orbiting Partnership (S-NPP). IMAPP is a NASA-funded and freely-distributed software package developed at Space Science and Engineering Center of University of Wisconsin-Madison that has over 2,300 registered users worldwide. With IMAPP, any ground station capable of receiving direct broadcast from Terra or Aqua can produce calibrated and geolocated radiances and a suite of environmental products. These products include MODIS AOD required for IDEA-I. VIIRS AOD for IDEA-I can be generated by Community Satellite Processing Package (CSPP) VIIRS EDR Version 2.0 Software for Suomi NPP. CSPP is also developed and distributed by Space Science & Engineering Center. This presentation describes our updated IMAPP implementation of IDEA-I through an example of its operation in a region known for episodic poor air quality events.

Impairments of Motor Function While Multitasking in HIV.

PubMed

Kronemer, Sharif I; Mandel, Jordan A; Sacktor, Ned C; Marvel, Cherie L

2017-01-01

Human immunodeficiency virus (HIV) became a treatable illness with the introduction of combination antiretroviral therapy (CART). As a result, patients with regular access to CART are expected to live decades with HIV. Long-term HIV infection presents unique challenges, including neurocognitive impairments defined by three major stages of HIV-associated neurocognitive disorders (HAND). The current investigation aimed to study cognitive and motor impairments in HIV using a novel multitasking paradigm. Unlike current standard measures of cognitive and motor performance in HIV, multitasking increases real-world validity by mimicking the dual motor and cognitive demands that are part of daily professional and personal settings (e.g., driving, typing and writing). Moreover, multitask assessments can unmask compensatory mechanisms, normally used under single task conditions, to maintain performance. This investigation revealed that HIV+ participants were impaired on the motor component of the multitask, while cognitive performance was spared. A patient-specific positive interaction between motor performance and working memory recall was driven by poor HIV+ multitaskers. Surprisingly, HAND stage did not correspond with multitask performance and a variety of commonly used assessments indicated normal motor function among HIV+ participants with poor motor performance during the experimental task. These results support the use of multitasks to reveal otherwise hidden impairment in chronic HIV by expanding the sensitivity of clinical assessments used to determine HAND stage. Future studies should examine the capability of multitasks to predict performance in personal, professional and health-related behaviors and prognosis of patients living with chronic HIV.

Automated assessment of early hypoxic brain edema in non-enhanced CT predicts outcome in patients after cardiac arrest.

PubMed

Hanning, Uta; Sporns, Peter Bernhard; Lebiedz, Pia; Niederstadt, Thomas; Zoubi, Tarek; Schmidt, Rene; Knecht, Stefan; Heindel, Walter; Kemmling, André

2016-07-01

Early prediction of potential neurological recovery in patients after cardiac arrest is challenging. Recent studies suggest that the densitrometic gray-white matter ratio (GWR) determined from cranial computed tomography (CT) scans may be a reliable predictor of poor outcome. We evaluated an automated, rater independent method to determine GWR in CT as an early objective imaging predictor of clinical outcome. We analyzed imaging data of 84 patients after cardiac arrest that underwent noncontrast CT within 24h after arrest. To determine GWR in CT we applied two methods using a recently published automated probabilistic gray-white matter segmentation algorithm (GWR_aut) and conventional manual measurements within gray-white regions of interest (GWR_man). Neurological outcome was graded by the cerebral performance category (CPC). As part of standard routine CPC was assessed by the treating physician in the intensive care unit at admission and at discharge to normal ward. The performance of GWR measures (automated and manual) to predict the binary clinical endpoints of poor (CPC3-5) and good outcome (CPC1-2) was assessed by ROC analysis with increasing discrimination thresholds. Results of GWR_aut were compared to GWR_man of two raters. Of 84 patients, 55 (65%) showed a poor outcome. ROC curve analysis revealed reliable outcome prediction of GWR_aut (AUC 0.860) and GWR_man (AUC 0.707 and 0.699, respectively). Predictive power of GWR_aut was higher than GWR_man by each rater (p=0.019 and p=0.021, respectively) at an optimal cut-off of 1.084 to predict poor outcome (optimal criterion with 92.7% sensitivity, 72.4% specificity). Interrater reliability of GWR_man by intra-class correlation coefficient (ICC) was moderate (0.551). Automated quantification of GWR in CT may be used as an objective observer-independent imaging marker for outcome in patients after cardiac arrest. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of a handheld NIR spectrometer in prediction of drug content in inkjet printed orodispersible formulations containing prednisolone and levothyroxine.

PubMed

Vakili, Hossein; Wickström, Henrika; Desai, Diti; Preis, Maren; Sandler, Niklas

2017-05-30

Quality control tools to assess the quality of printable orodispersible formulations are yet to be defined. Four different orodispersible dosage forms containing two poorly soluble drugs, levothyroxine and prednisolone, were produced on two different edible substrates by piezoelectric inkjet printing. Square shaped units of 4cm 2 were printed in different resolutions to achieve an escalating drug dose by highly accurate and uniform displacement of droplets in picoliter range from the printhead onto the substrates. In addition, the stability of drug inks in a course of 24h as well as the mechanical properties and disintegration behavior of the printed units were examined. A compact handheld near-infrared (NIR) spectral device in the range of 1550-1950nm was used for quantitative estimation of the drug amount in printed formulations. The spectral data was treated with mean centering, Savitzky-Golay filtering and a third derivative approach. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) regression were applied to build predictive models for quality control of the printed dosage forms. The accurate tuning of the dose in each formulation was confirmed by UV spectrophotometry for prednisolone (0.43-1.95mg with R 2 =0.999) and high performance liquid chromatography for levothyroxine (0.15-0.86mg with R 2 =0.997). It was verified that the models were capable of clustering and predicting the drug dose in the formulations with both Q 2 and R 2 Y values between 0.94-0.99. Copyright © 2017 Elsevier B.V. All rights reserved.

The prognostic value of a seven-microRNA classifier as a novel biomarker for the prediction and detection of recurrence in glioma patients.

PubMed

Chen, Wanghao; Yu, Qiang; Chen, Bo; Lu, Xingyu; Li, Qiaoyu

2016-08-16

Glioma is often diagnosed at a later stage, and the high risk of recurrence remains a major challenge. We hypothesized that the microRNA expression profile may serve as a biomarker for the prognosis and prediction of glioblastoma recurrence. We defined microRNAs that were associated with good and poor prognosis in 300 specimens of glioblastoma from the Cancer Genome Atlas. By analyzing microarray gene expression data and clinical information from three random groups, we identified 7 microRNAs that have prognostic and prognostic accuracy: microRNA-124a, microRNA-129, microRNA-139, microRNA-15b, microRNA-21, microRNA-218 and microRNA-7. The differential expression of these miRNAs was verified using an independent set of glioma samples from the Affiliated People's Hospital of Jiangsu University. We used the log-rank test and the Kaplan-Meier method to estimate correlations between the miRNA signature and disease-free survival/overall survival. Using the LASSO model, we observed a uniform significant difference in disease-free survival and overall survival between patients with high-risk and low-risk miRNA signature scores. Furthermore, the prognostic capability of the seven-miRNA signature was demonstrated by receiver operator characteristic curve analysis. A Circos plot was generated to examine the network of genes and pathways predicted to be targeted by the seven-miRNA signature. The seven-miRNA-based classifier should be useful in the stratification and individualized management of patients with glioma.

“We Routinely Borrow to Survive”: Exploring the Financial Capability of Income-Poor People in India.

PubMed

Banerjee, Mahasweta M

2016-10-01

A lack of financial capability—financial opportunities and abilities—and poverty are highly interlinked. Over 65 percent of people in India are excluded from any financial services. This article explores income-poor Indians’ experiences with financial capability through a qualitative study. Purposive sampling was used to collect data from 658 individuals, through focus groups (n = 566) and face-to-face interviews (n = 92). Findings show that 97 percent of respondents had the opportunity to earn an income, and 55 percent earned through financial inclusion programs, but 87 percent of respondents earned less than U.S. $2 a day. Although almost all saved and needed to borrow, 46 percent were eligible for formal savings and only 23 percent for formal loans. Financial abilities or knowledge and skills related to income, savings, and loans were higher among the few who had a stable income or had medium and high income in relation to those who had unstable and low income. Respondents experienced many challenges with their financial capabilities, including borrowing to save, fearing formal loans, and lacking clarity about loan and interest rate; banks miscalculating interest rates; and political parties influencing access to loans. Implications for social policy and social work practice are discussed.

Assessing dementia in resource-poor regions.

PubMed

Maestre, Gladys E

2012-10-01

The numbers and proportions of elderly are increasing rapidly in developing countries, where prevalence of dementia is often high. Providing cost-effective services for dementia sufferers and their caregivers in these resource-poor regions poses numerous challenges; developing resources for diagnosis must be the first step. Capacity building for diagnosis involves training and education of healthcare providers, as well as the general public, development of infrastructure, and resolution of economic and ethical issues. Recent progress in some low-to-middle-income countries (LMICs) provides evidence that partnerships between wealthy and resource-poor countries, and between developing countries, can improve diagnostic capabilities. Without the involvement of the mental health community of developed countries in such capacity-building programs, dementia in the developing world is a disaster waiting to happen.

Respiratory Sinus Arrhythmia: A Transdiagnostic Biomarker of Emotion Dysregulation and Psychopathology

PubMed Central

Beauchaine, Theodore P.

2015-01-01

In the past two decades, respiratory sinus arrhythmia (RSA)—an index of parasympathetic nervous system (PNS)-mediated cardiac control—has emerged as a reliable peripheral biomarker of emotion regulation (ER). Reduced RSA and excessive RSA reactivity (i.e., withdrawal) to emotional challenge are observed consistently among individuals with poor ER capabilities, including those with various forms of internalizing and externalizing psychopathology, and those with specific psychopathological syndromes, including anxiety, phobias, attention problems, autism, callousness, conduct disorder, depression, non-suicidal self-injury, panic disorder, and trait hostility. Emerging evidence suggests that low RSA and excessive RSA reactivity index poor ER because they are downstream peripheral markers of prefrontal cortex (PFC) dysfunction. Poorly modulated inhibitory efferent pathways from the medial PFC to the PNS result in reduced RSA and excessive RSA reactivity. According to this perspective, RSA is a non-invasive proxy for poor executive control over behavior, which characterizes most forms of psychopathology. PMID:25866835

Assessment of Process Capability: the case of Soft Drinks Processing Unit

NASA Astrophysics Data System (ADS)

Sri Yogi, Kottala

2018-03-01

The process capability studies have significant impact in investigating process variation which is important in achieving product quality characteristics. Its indices are to measure the inherent variability of a process and thus to improve the process performance radically. The main objective of this paper is to understand capability of the process being produced within specification of the soft drinks processing unit, a premier brands being marketed in India. A few selected critical parameters in soft drinks processing: concentration of gas volume, concentration of brix, torque of crock has been considered for this study. Assessed some relevant statistical parameters: short term capability, long term capability as a process capability indices perspective. For assessment we have used real time data of soft drinks bottling company which is located in state of Chhattisgarh, India. As our research output suggested reasons for variations in the process which is validated using ANOVA and also predicted Taguchi cost function, assessed also predicted waste monetarily this shall be used by organization for improving process parameters. This research work has substantially benefitted the organization in understanding the various variations of selected critical parameters for achieving zero rejection.

High resolution imaging and wavefront aberration correction in plenoptic systems.

PubMed

Trujillo-Sevilla, J M; Rodríguez-Ramos, L F; Montilla, I; Rodríguez-Ramos, J M

2014-09-01

Plenoptic imaging systems are becoming more common since they provide capabilities unattainable in conventional imaging systems, but one of their main limitations is the poor bidimensional resolution. Combining the wavefront phase measurement and the plenoptic image deconvolution, we propose a system capable of improving the resolution when a wavefront aberration is present and the image is blurred. In this work, a plenoptic system is simulated using Fourier optics, and the results show that an improved resolution is achieved, even in the presence of strong wavefront aberrations.

Implementation of Premixed Equilibrium Chemistry Capability in OVERFLOW

NASA Technical Reports Server (NTRS)

Olsen, M. E.; Liu, Y.; Vinokur, M.; Olsen, T.

2003-01-01

An implementation of premixed equilibrium chemistry has been completed for the OVERFLOW code, a chimera capable, complex geometry flow code widely used to predict transonic flowfields. The implementation builds on the computational efficiency and geometric generality of the solver.

Implementation of Premixed Equilibrium Chemistry Capability in OVERFLOW

NASA Technical Reports Server (NTRS)

Olsen, Mike E.; Liu, Yen; Vinokur, M.; Olsen, Tom

2004-01-01

An implementation of premixed equilibrium chemistry has been completed for the OVERFLOW code, a chimera capable, complex geometry flow code widely used to predict transonic flowfields. The implementation builds on the computational efficiency and geometric generality of the solver.

[Identification of capacities in environmental health from environmental authorities in Colombia].

PubMed

Agudelo-Calderón, Carlos A; García-Ubaque, Juan C; Robledo-Martínez, Rocío; García-Ubaque, Cesar A; Vaca-Bohórquez, Martha L

2016-08-01

Objectives To diagnose the capabilities that environmental authorities and the Ministry of Environment and Sustainable Development have to assume their role in environmental health, based on the capacity model of the United Nations Program for Development UNDP. Method Document review, interviews on key issues and a commented survey were conducted. 84 entities were selected for a tailored survey; complete information was obtained from 76 institutions. Results The valuation of environment favorability was within the acceptable and unfavorable categories; knowledge management capabilities were found to be precarious and assessment of functional capabilities ranged between appropriate and acceptable. The assessment of specific capabilities had a rating of poor or barely acceptable. Conclusions Two major problems were found: a. The environmental authorities do not conceive or implement these capabilities based on the UNDP model but on the conventional model of the Ministry of Environment, Housing and Territorial Development; b. Environmental authorities show an incipient level of incorporation of environmental health policies in their field of action.

Integrating Local Public Health Agencies into the Homeland Security Community

DTIC Science & Technology

2007-03-01

public health needs that require attention (such as poor prenatal health, teen pregnancy , and sexually transmitted diseases) it is not difficult to...11 2. Education ... relationships and improved planning and response capabilities. Public health agencies are diverse organizations administrating multiple health programs

Special Operations Forces--Responsive, Capable, and Ready

DTIC Science & Technology

1990-05-01

communication Planning Criticisms of poor communications that hammeted mission success rangea from radio inoperability amorng raid force elements to strict...ons, an armory. and a means of rapid escape are also face the Unenviable choice of rushing light and inad- normally part of the complex. equate

Hope as a Predictor of Interpersonal Suicide Risk

ERIC Educational Resources Information Center

Davidson, Collin L.; Wingate, LaRicka R.; Rasmussen, Kathy A.; Slish, Meredith L.

2009-01-01

The current study hypothesized that (1) hope would negatively predict burdensomeness, thwarted belongingness, and acquired capability to enact lethal injury; (2) hope would negatively predict suicidal ideation; and (3) the interpersonal suicide risk factors would predict suicidal ideation. Results indicated that hope negatively predicted…

Emotional Disturbance and Chronic Low Back Pain.

ERIC Educational Resources Information Center

McCreary, Charles P.; And Others

1980-01-01

Patients high in alientation and distrust may be poor compliers. Because only the somatic concern dimension predicted outcome, a single scale that measures this characteristic may be sufficient for effective identification of the potential good v poor responders to conservative treatment of low back pain. (Author)

Fan Noise Prediction with Applications to Aircraft System Noise Assessment

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Envia, Edmane; Burley, Casey L.

2009-01-01

This paper describes an assessment of current fan noise prediction tools by comparing measured and predicted sideline acoustic levels from a benchmark fan noise wind tunnel test. Specifically, an empirical method and newly developed coupled computational approach are utilized to predict aft fan noise for a benchmark test configuration. Comparisons with sideline noise measurements are performed to assess the relative merits of the two approaches. The study identifies issues entailed in coupling the source and propagation codes, as well as provides insight into the capabilities of the tools in predicting the fan noise source and subsequent propagation and radiation. In contrast to the empirical method, the new coupled computational approach provides the ability to investigate acoustic near-field effects. The potential benefits/costs of these new methods are also compared with the existing capabilities in a current aircraft noise system prediction tool. The knowledge gained in this work provides a basis for improved fan source specification in overall aircraft system noise studies.

Surface Modified Pinecone Shaped Hierarchical Structure Fluorinated Mesocarbon Microbeads for Ultrafast Discharge and Improved Electrochemical Performances

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

Dai, Yang; Fang, Yuan; Cai, Sendan

2016-12-01

Among all primary lithium batteries, Li/CF x primary battery possesses the highest energy density of 2180 Wh kg -1. However, a key limitation is its poor rate capability because the cathode material CF x is intrinsically a poor electronic conductor. Here, we developed a so-called “doing subtraction” method to modify the pinecone shaped fluorinated mesocarbon microbead (F-MCMB). The modified fluorinated mesocarbon microbead (MF-MCMB), manifests the advantage of open-framed structure, possesses good electronic conductivity and removes transport barrier for lithium ions. Thus, high capacity performance and excellent rate capability without compromising capacity can be obtained. A capacity of 343 mAhg -1more » and a maximum power density of 54600 W kg -1 are realized at an ultrafast rate of 40 C (28A g -1). Additionally, the MF-MCMB cathode does not show any voltage delay even at 5C during the discharge, which is a remarkable improvement over the state-of-the-art CF xmaterials.« less

Human-system interfaces for space cognitive awareness

NASA Astrophysics Data System (ADS)

Ianni, J.

Space situational awareness is a human activity. We have advanced sensors and automation capabilities but these continue to be tools for humans to use. The reality is, however, that humans cannot take full advantage of the power of these tools due to time constraints, cognitive limitations, poor tool integration, poor human-system interfaces, and other reasons. Some excellent tools may never be used in operations and, even if they were, they may not be well suited to provide a cohesive and comprehensive picture. Recognizing this, the Air Force Research Laboratory (AFRL) is applying cognitive science principles to increase the knowledge derived from existing tools and creating new capabilities to help space analysts and decision makers. At the center of this research is Sensemaking Support Environment technology. The concept is to create cognitive-friendly computer environments that connect critical and creative thinking for holistic decision making. AFRL is also investigating new visualization technologies for multi-sensor exploitation and space weather, human-to-human collaboration technologies, and other technology that will be discussed in this paper.

Molecular paleontology and complexity in the last eukaryotic common ancestor

PubMed Central

Koumandou, V. Lila; Wickstead, Bill; Ginger, Michael L.; van der Giezen, Mark; Dacks, Joel B.

2013-01-01

Eukaryogenesis, the origin of the eukaryotic cell, represents one of the fundamental evolutionary transitions in the history of life on earth. This event, which is estimated to have occurred over one billion years ago, remains rather poorly understood. While some well-validated examples of fossil microbial eukaryotes for this time frame have been described, these can provide only basic morphology and the molecular machinery present in these organisms has remained unknown. Complete and partial genomic information has begun to fill this gap, and is being used to trace proteins and cellular traits to their roots and to provide unprecedented levels of resolution of structures, metabolic pathways and capabilities of organisms at these earliest points within the eukaryotic lineage. This is essentially allowing a molecular paleontology. What has emerged from these studies is spectacular cellular complexity prior to expansion of the eukaryotic lineages. Multiple reconstructed cellular systems indicate a very sophisticated biology, which by implication arose following the initial eukaryogenesis event but prior to eukaryotic radiation and provides a challenge in terms of explaining how these early eukaryotes arose and in understanding how they lived. Here, we provide brief overviews of several cellular systems and the major emerging conclusions, together with predictions for subsequent directions in evolution leading to extant taxa. We also consider what these reconstructions suggest about the life styles and capabilities of these earliest eukaryotes and the period of evolution between the radiation of eukaryotes and the eukaryogenesis event itself. PMID:23895660

Longitudinal Monitoring of Patients With Chronic Low Back Pain During Physical Therapy Treatment Using the STarT Back Screening Tool.

PubMed

Medeiros, Flávia Cordeiro; Costa, Leonardo Oliveira Pena; Added, Marco Aurélio Nemitalla; Salomão, Evelyn Cassia; Costa, Lucíola da Cunha Menezes

2017-05-01

Study Design Preplanned secondary analysis of a randomized clinical trial. Background The STarT Back Screening Tool (SBST) was developed to screen and to classify patients with low back pain into subgroups for the risk of having a poor prognosis. However, this classification at baseline does not take into account variables that can influence the prognosis during treatment or over time. Objectives (1) To investigate the changes in risk subgroup measured by the SBST over a period of 6 months, and (2) to assess the long-term predictive ability of the SBST when administered at different time points. Methods Patients with chronic nonspecific low back pain (n = 148) receiving physical therapy care as part of a randomized trial were analyzed. Pain intensity, disability, global perceived effect, and the SBST were collected at baseline, 5 weeks, 3 months, and 6 months. Changes in SBST risk classification were calculated. Hierarchical linear regression models adjusted for potential confounders were built to analyze the predictive capabilities of the SBST when administered at different time points. Results A large proportion of patients (60.8%) changed their risk subgroup after receiving physical therapy care. The SBST improved the prediction for all 6-month outcomes when using the 5-week risk subgroup and the difference between baseline and 5-week subgroup, after controlling for potential confounders. The SBST at baseline did not improve the predictive ability of the models after adjusting for confounders. Conclusion This study shows that many patients change SBST risk subgroup after receiving physical therapy care, and that the predictive ability of the SBST in patients with chronic low back pain increases when administered at different time points. Level of Evidence Prognosis, 2b. J Orthop Sports Phys Ther 2017;47(5):314-323. Epub 29 Mar 2017. doi:10.2519/jospt.2017.7199.

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

CLAES Product Improvement by use of GSFC Data Assimilation System

NASA Technical Reports Server (NTRS)

Kumer, J. B.; Douglass, Anne (Technical Monitor)

2001-01-01

Recent development in chemistry transport models (CTM) and in data assimilation systems (DAS) indicate impressive predictive capability for the movement of airparcels and the chemistry that goes on within these. This project was aimed at exploring the use of this capability to achieve improved retrieval of geophysical parameters from remote sensing data. The specific goal was to improve retrieval of the CLAES CH4 data obtained during the active north high latitude dynamics event of 18 to 25 February 1992. The model capabilities would be used: (1) rather than climatology to improve on the first guess and the a-priori fields, and (2) to provide horizontal gradients to include in the retrieval forward model. The retrieval would be implemented with the first forward DAS prediction. The results would feed back to the DAS and a second DAS prediction for first guess, a-priori and gradients would feed to the retrieval. The process would repeat to convergence and then proceed to the next day.

An evaluation of the genetic-matched pair study design using genome-wide SNP data from the European population.

PubMed

Lu, Timothy Tehua; Lao, Oscar; Nothnagel, Michael; Junge, Olaf; Freitag-Wolf, Sandra; Caliebe, Amke; Balascakova, Miroslava; Bertranpetit, Jaume; Bindoff, Laurence Albert; Comas, David; Holmlund, Gunilla; Kouvatsi, Anastasia; Macek, Milan; Mollet, Isabelle; Nielsen, Finn; Parson, Walther; Palo, Jukka; Ploski, Rafal; Sajantila, Antti; Tagliabracci, Adriano; Gether, Ulrik; Werge, Thomas; Rivadeneira, Fernando; Hofman, Albert; Uitterlinden, André Gerardus; Gieger, Christian; Wichmann, Heinz-Erich; Ruether, Andreas; Schreiber, Stefan; Becker, Christian; Nürnberg, Peter; Nelson, Matthew Roberts; Kayser, Manfred; Krawczak, Michael

2009-07-01

Genetic matching potentially provides a means to alleviate the effects of incomplete Mendelian randomization in population-based gene-disease association studies. We therefore evaluated the genetic-matched pair study design on the basis of genome-wide SNP data (309,790 markers; Affymetrix GeneChip Human Mapping 500K Array) from 2457 individuals, sampled at 23 different recruitment sites across Europe. Using pair-wise identity-by-state (IBS) as a matching criterion, we tried to derive a subset of markers that would allow identification of the best overall matching (BOM) partner for a given individual, based on the IBS status for the subset alone. However, our results suggest that, by following this approach, the prediction accuracy is only notably improved by the first 20 markers selected, and increases proportionally to the marker number thereafter. Furthermore, in a considerable proportion of cases (76.0%), the BOM of a given individual, based on the complete marker set, came from a different recruitment site than the individual itself. A second marker set, specifically selected for ancestry sensitivity using singular value decomposition, performed even more poorly and was no more capable of predicting the BOM than randomly chosen subsets. This leads us to conclude that, at least in Europe, the utility of the genetic-matched pair study design depends critically on the availability of comprehensive genotype information for both cases and controls.

Predicting the Necessity for Extracorporeal Circulation During Lung Transplantation: A Feasibility Study.

PubMed

Hinske, Ludwig Christian; Hoechter, Dominik Johannes; Schröeer, Eva; Kneidinger, Nikolaus; Schramm, René; Preissler, Gerhard; Tomasi, Roland; Sisic, Alma; Frey, Lorenz; von Dossow, Vera; Scheiermann, Patrick

2017-06-01

The factors leading to the implementation of unplanned extracorporeal circulation during lung transplantation are poorly defined. Consequently, the authors aimed to identify patients at risk for unplanned extracorporeal circulation during lung transplantation. Retrospective data analysis. Single-center university hospital. A development data set of 170 consecutive patients and an independent validation cohort of 52 patients undergoing lung transplantation. The authors investigated a cohort of 170 consecutive patients undergoing single or sequential bilateral lung transplantation without a priori indication for extracorporeal circulation and evaluated the predictive capability of distinct preoperative and intraoperative variables by using automated model building techniques at three clinically relevant time points (preoperatively, after endotracheal intubation, and after establishing single-lung ventilation). Preoperative mean pulmonary arterial pressure was the strongest predictor for unplanned extracorporeal circulation. A logistic regression model based on preoperative mean pulmonary arterial pressure and lung allocation score achieved an area under the receiver operating characteristic curve of 0.85. Consequently, the authors developed a novel 3-point scoring system based on preoperative mean pulmonary arterial pressure and lung allocation score, which identified patients at risk for unplanned extracorporeal circulation and validated this score in an independent cohort of 52 patients undergoing lung transplantation. The authors showed that patients at risk for unplanned extracorporeal circulation during lung transplantation could be identified by their novel 3-point score. Copyright © 2017 Elsevier Inc. All rights reserved.

PRESS-based EFOR algorithm for the dynamic parametrical modeling of nonlinear MDOF systems

NASA Astrophysics Data System (ADS)

Liu, Haopeng; Zhu, Yunpeng; Luo, Zhong; Han, Qingkai

2017-09-01

In response to the identification problem concerning multi-degree of freedom (MDOF) nonlinear systems, this study presents the extended forward orthogonal regression (EFOR) based on predicted residual sums of squares (PRESS) to construct a nonlinear dynamic parametrical model. The proposed parametrical model is based on the non-linear autoregressive with exogenous inputs (NARX) model and aims to explicitly reveal the physical design parameters of the system. The PRESS-based EFOR algorithm is proposed to identify such a model for MDOF systems. By using the algorithm, we built a common-structured model based on the fundamental concept of evaluating its generalization capability through cross-validation. The resulting model aims to prevent over-fitting with poor generalization performance caused by the average error reduction ratio (AERR)-based EFOR algorithm. Then, a functional relationship is established between the coefficients of the terms and the design parameters of the unified model. Moreover, a 5-DOF nonlinear system is taken as a case to illustrate the modeling of the proposed algorithm. Finally, a dynamic parametrical model of a cantilever beam is constructed from experimental data. Results indicate that the dynamic parametrical model of nonlinear systems, which depends on the PRESS-based EFOR, can accurately predict the output response, thus providing a theoretical basis for the optimal design of modeling methods for MDOF nonlinear systems.

The impact of competition on elephant musth strategies: A game-theoretic model.

PubMed

Wyse, J Max; Hardy, Ian C W; Yon, Lisa; Mesterton-Gibbons, Mike

2017-03-21

Mature male African Savannah elephants are known to periodically enter a temporary state of heightened aggression called "musth", often linked with increased androgens, particularly testosterone. Sexually mature males are capable of entering musth at any time of year, and will often travel long distances to find estrous females. When two musth bulls or two non-musth bulls encounter one another, the agonistic interaction is usually won by the larger male. However, when a smaller musth bull encounters a larger non-musth bull, the smaller musth male can win. The relative mating success of musth males is due partly to this fighting advantage, and partly to estrous females' general preference for musth males. Though musth behavior has long been observed and documented, the evolutionary advantages of musth remain poorly understood. Here we develop a game-theoretic model of male musth behavior which assumes musth duration as a parameter, and distributions of small, medium and large musth males are predicted in both time and space. The predicted results are similar to the musth timing behavior observed in the Amboseli National Park elephant population, and further results are generated with relevance to Samburu National Park. We discuss small male musth behavior, the effects of estrous female spatial heterogeneity on musth timing, conservation applications, and the assumptions underpinning the model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of Thermal Cycling on Thermal Expansion and Mechanical Properties of Sic Fiber-reinforced Reaction-bonded Si3n4 Composites

NASA Technical Reports Server (NTRS)

Bhatt, R. T.; Palczer, A. R.

1994-01-01

Thermal expansion curves for SiC fiber-reinforced reaction-bonded Si3N4 matrix composites (SiC/RBSN) and unreinforced RBSN were measured from 25 to 1400 C in nitrogen and in oxygen. The effects of fiber/matrix bonding and cycling on the thermal expansion curves and room-temperature tensile properties of unidirectional composites were determined. The measured thermal expansion curves were compared with those predicted from composite theory. Predicted thermal expansion curves parallel to the fiber direction for both bonding cases were similar to that of the weakly bonded composites, but those normal to the fiber direction for both bonding cases resulted in no net dimensional changes at room temperature, and no loss in tensile properties from the as-fabricated condition. In contrast, thermal cycling in oxygen for both composites caused volume expansion primarily due to internal oxidation of RBSN. Cyclic oxidation affected the mechanical properties of the weakly bonded SiC/RBSN composites the most, resulting in loss of strain capability beyond matrix fracture and catastrophic, brittle fracture. Increased bonding between the SiC fiber and RBSN matrix due to oxidation of the carbon-rich fiber surface coating and an altered residual stress pattern in the composite due to internal oxidation of the matrix are the main reasons for the poor mechanical performance of these composites.

NetMHCIIpan-2.0 - Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure.

PubMed

Nielsen, Morten; Justesen, Sune; Lund, Ole; Lundegaard, Claus; Buus, Søren

2010-11-13

Binding of peptides to Major Histocompatibility class II (MHC-II) molecules play a central role in governing responses of the adaptive immune system. MHC-II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Predicting which peptides bind to an MHC-II molecule is therefore of pivotal importance for understanding the immune response and its effect on host-pathogen interactions. The experimental cost associated with characterizing the binding motif of an MHC-II molecule is significant and large efforts have therefore been placed in developing accurate computer methods capable of predicting this binding event. Prediction of peptide binding to MHC-II is complicated by the open binding cleft of the MHC-II molecule, allowing binding of peptides extending out of the binding groove. Moreover, the genes encoding the MHC molecules are immensely diverse leading to a large set of different MHC molecules each potentially binding a unique set of peptides. Characterizing each MHC-II molecule using peptide-screening binding assays is hence not a viable option. Here, we present an MHC-II binding prediction algorithm aiming at dealing with these challenges. The method is a pan-specific version of the earlier published allele-specific NN-align algorithm and does not require any pre-alignment of the input data. This allows the method to benefit also from information from alleles covered by limited binding data. The method is evaluated on a large and diverse set of benchmark data, and is shown to significantly out-perform state-of-the-art MHC-II prediction methods. In particular, the method is found to boost the performance for alleles characterized by limited binding data where conventional allele-specific methods tend to achieve poor prediction accuracy. The method thus shows great potential for efficient boosting the accuracy of MHC-II binding prediction, as accurate predictions can be obtained for novel alleles at highly reduced experimental costs. Pan-specific binding predictions can be obtained for all alleles with know protein sequence and the method can benefit by including data in the training from alleles even where only few binders are known. The method and benchmark data are available at http://www.cbs.dtu.dk/services/NetMHCIIpan-2.0.

Development of a coupled hydrological - hydrodynamic model for probabilistic catchment flood inundation modelling

NASA Astrophysics Data System (ADS)

Quinn, Niall; Freer, Jim; Coxon, Gemma; Dunne, Toby; Neal, Jeff; Bates, Paul; Sampson, Chris; Smith, Andy; Parkin, Geoff

2017-04-01

Computationally efficient flood inundation modelling systems capable of representing important hydrological and hydrodynamic flood generating processes over relatively large regions are vital for those interested in flood preparation, response, and real time forecasting. However, such systems are currently not readily available. This can be particularly important where flood predictions from intense rainfall are considered as the processes leading to flooding often involve localised, non-linear spatially connected hillslope-catchment responses. Therefore, this research introduces a novel hydrological-hydraulic modelling framework for the provision of probabilistic flood inundation predictions across catchment to regional scales that explicitly account for spatial variability in rainfall-runoff and routing processes. Approaches have been developed to automate the provision of required input datasets and estimate essential catchment characteristics from freely available, national datasets. This is an essential component of the framework as when making predictions over multiple catchments or at relatively large scales, and where data is often scarce, obtaining local information and manually incorporating it into the model quickly becomes infeasible. An extreme flooding event in the town of Morpeth, NE England, in 2008 was used as a first case study evaluation of the modelling framework introduced. The results demonstrated a high degree of prediction accuracy when comparing modelled and reconstructed event characteristics for the event, while the efficiency of the modelling approach used enabled the generation of relatively large ensembles of realisations from which uncertainty within the prediction may be represented. This research supports previous literature highlighting the importance of probabilistic forecasting, particularly during extreme events, which can be often be poorly characterised or even missed by deterministic predictions due to the inherent uncertainty in any model application. Future research will aim to further evaluate the robustness of the approaches introduced by applying the modelling framework to a variety of historical flood events across UK catchments. Furthermore, the flexibility and efficiency of the framework is ideally suited to the examination of the propagation of errors through the model which will help gain a better understanding of the dominant sources of uncertainty currently impacting flood inundation predictions.

Predictive Measures of Locomotor Performance on an Unstable Walking Surface

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Caldwell, E. E.; Batson, C. D.; De Dios, Y. E.; Gadd, N. E.; Goel, R.; Wood, S. J.; Cohen, H. S.;

Center-TRACON Automation System (CTAS) En Route Trajectory Predictor Requirements and Capabilities

NASA Technical Reports Server (NTRS)

Vivona, Robert; Cate, Karen Tung

2013-01-01

This requirements framework document is designed to support the capture of requirements and capabilities for state-of-the-art trajectory predictors (TPs). This framework has been developed to assist TP experts in capturing a clear, consistent, and cross-comparable set of requirements and capabilities. The goal is to capture capabilities (types of trajectories that can be built), functional requirements (including inputs and outputs), non-functional requirements (including prediction accuracy and computational performance), approaches for constraint relaxation, and input uncertainties. The sections of this framework are based on the Common Trajectory Predictor structure developed by the FAA/Eurocontrol Cooperative R&D Action Plan 16 Committee on Common Trajectory Prediction. It is assumed that the reader is familiar with the Common TP Structure.1 This initial draft is intended as a first cut capture of the En Route TS Capabilities and Requirements. As such, it contains many annotations indicating possible logic errors in the CTAS code or in the description provided. It is intended to work out the details of the annotations with NASA and to update this document at a later time.

NASA's Evolutionary Xenon Thruster (NEXT) Project Qualification Propellant Throughput Milestone: Performance, Erosion, and Thruster Service Life Prediction After 450 kg

NASA Technical Reports Server (NTRS)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 28,500 hr of operation and processed 466 kg of xenon throughput--more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Verification of the predictive capabilities of the 4C code cryogenic circuit model

NASA Astrophysics Data System (ADS)

Zanino, R.; Bonifetto, R.; Hoa, C.; Richard, L. Savoldi

2014-01-01

The 4C code was developed to model thermal-hydraulics in superconducting magnet systems and related cryogenic circuits. It consists of three coupled modules: a quasi-3D thermal-hydraulic model of the winding; a quasi-3D model of heat conduction in the magnet structures; an object-oriented a-causal model of the cryogenic circuit. In the last couple of years the code and its different modules have undergone a series of validation exercises against experimental data, including also data coming from the supercritical He loop HELIOS at CEA Grenoble. However, all this analysis work was done each time after the experiments had been performed. In this paper a first demonstration is given of the predictive capabilities of the 4C code cryogenic circuit module. To do that, a set of ad-hoc experimental scenarios have been designed, including different heating and control strategies. Simulations with the cryogenic circuit module of 4C have then been performed before the experiment. The comparison presented here between the code predictions and the results of the HELIOS measurements gives the first proof of the excellent predictive capability of the 4C code cryogenic circuit module.

Advanced Ground Systems Maintenance Prognostics Project

NASA Technical Reports Server (NTRS)

Harp, Janicce Leshay

2014-01-01

The project implements prognostics capabilities to predict when a component, system or subsystem will no longer meet desired functional or performance criteria, called the "end of life." The capability also provides an assessment of the "remaining useful life" of a hardware component.

Predictive Capability Maturity Model for computational modeling and simulation.

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

Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

2007-10-01

The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronauticsmore » and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.« less

In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer.

PubMed

Abu-Jamous, Basel; Buffa, Francesca M; Harris, Adrian L; Nandi, Asoke K

2017-06-15

Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified. However, it was observed that cell line data do not always concur with clinical data, and therefore conclusions from cell line analysis should be considered with caution. As many transcriptomic cell-line datasets from hypoxia related contexts are available, integrative approaches which investigate these datasets collectively, while not ignoring clinical data, are required. We analyse sixteen heterogeneous breast cancer cell-line transcriptomic datasets in hypoxia-related conditions collectively by employing the unique capabilities of the method, UNCLES, which integrates clustering results from multiple datasets and can address questions that cannot be answered by existing methods. This has been demonstrated by comparison with the state-of-the-art iCluster method. From this collection of genome-wide datasets include 15,588 genes, UNCLES identified a relatively high number of genes (>1000 overall) which are consistently co-regulated over all of the datasets, and some of which are still poorly understood and represent new potential HIF targets, such as RSBN1 and KIAA0195. Two main, anti-correlated, clusters were identified; the first is enriched with MYC targets participating in growth and proliferation, while the other is enriched with HIF targets directly participating in the hypoxia response. Surprisingly, in six clinical datasets, some sub-clusters of growth genes are found consistently positively correlated with hypoxia response genes, unlike the observation in cell lines. Moreover, the ability to predict bad prognosis by a combined signature of one sub-cluster of growth genes and one sub-cluster of hypoxia-induced genes appears to be comparable and perhaps greater than that of known hypoxia signatures. We present a clustering approach suitable to integrate data from diverse experimental set-ups. Its application to breast cancer cell line datasets reveals new hypoxia-regulated signatures of genes which behave differently when in vitro (cell-line) data is compared with in vivo (clinical) data, and are of a prognostic value comparable or exceeding the state-of-the-art hypoxia signatures.

Development of a computer model for prediction of collision response of a railroad passenger car

DOT National Transportation Integrated Search

2002-04-23

The paper describes the development of a detailed finite element model that is capable of predicting the response of a rail passenger car to collision conditions. This model was developed to predict the car crush, the three-dimensional gross motions ...

75 FR 33629 - Agency Information Collection Activities: Submission for Review; Information Collection Request...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-14

... Infrastructure against Cyber Threats (PREDICT) Program AGENCY: Science and Technology Directorate, DHS. ACTION... Infrastructure Against Cyber Threats (PREDICT) initiative. PREDICT is an initiative to facilitate the... effective threat assessment and increase cyber security capabilities. (4) An estimate of the total number of...

Uncertainty quantification's role in modeling and simulation planning, and credibility assessment through the predictive capability maturity model

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

Rider, William J.; Witkowski, Walter R.; Mousseau, Vincent Andrew

2016-04-13

The importance of credible, trustworthy numerical simulations is obvious especially when using the results for making high-consequence decisions. Determining the credibility of such numerical predictions is much more difficult and requires a systematic approach to assessing predictive capability, associated uncertainties and overall confidence in the computational simulation process for the intended use of the model. This process begins with an evaluation of the computational modeling of the identified, important physics of the simulation for its intended use. This is commonly done through a Phenomena Identification Ranking Table (PIRT). Then an assessment of the evidence basis supporting the ability to computationallymore » simulate these physics can be performed using various frameworks such as the Predictive Capability Maturity Model (PCMM). There were several critical activities that follow in the areas of code and solution verification, validation and uncertainty quantification, which will be described in detail in the following sections. Here, we introduce the subject matter for general applications but specifics are given for the failure prediction project. In addition, the first task that must be completed in the verification & validation procedure is to perform a credibility assessment to fully understand the requirements and limitations of the current computational simulation capability for the specific application intended use. The PIRT and PCMM are tools used at Sandia National Laboratories (SNL) to provide a consistent manner to perform such an assessment. Ideally, all stakeholders should be represented and contribute to perform an accurate credibility assessment. PIRTs and PCMMs are both described in brief detail below and the resulting assessments for an example project are given.« less

Psychosocial mechanisms linking the social environment to mental health in African Americans

USDA-ARS?s Scientific Manuscript database

Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African Amer...

Initial Integration of Noise Prediction Tools for Acoustic Scattering Effects

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Burley, Casey L.; Tinetti, Ana; Rawls, John W.

2008-01-01

This effort provides an initial glimpse at NASA capabilities available in predicting the scattering of fan noise from a non-conventional aircraft configuration. The Aircraft NOise Prediction Program, Fast Scattering Code, and the Rotorcraft Noise Model were coupled to provide increased fidelity models of scattering effects on engine fan noise sources. The integration of these codes led to the identification of several keys issues entailed in applying such multi-fidelity approaches. In particular, for prediction at noise certification points, the inclusion of distributed sources leads to complications with the source semi-sphere approach. Computational resource requirements limit the use of the higher fidelity scattering code to predict radiated sound pressure levels for full scale configurations at relevant frequencies. And, the ability to more accurately represent complex shielding surfaces in current lower fidelity models is necessary for general application to scattering predictions. This initial step in determining the potential benefits/costs of these new methods over the existing capabilities illustrates a number of the issues that must be addressed in the development of next generation aircraft system noise prediction tools.

Space Environmental Effects (SEE) Testing Capability: NASA/Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

DeWittBurns, H.; Crave, Paul; Finckenor, Miria; Finchum, Charles; Nehls, Mary; Schneider, Todd; Vaughn, Jason

2012-01-01

Understanding the effects of the space environment on materials and systems is fundamental and essential for mission success. If not properly understood and designed for, the space environment can lead to materials degradation, reduction of functional lifetime, and system failure. Ground based testing is critical in predicting performance NASA/MSFC's expertise and capabilities make up the most complete SEE testing capability available.

Esophageal Dysmotility in Patients following Total Laryngectomy.

PubMed

Zhang, Teng; Maclean, Julia; Szczesniak, Michal; Bertrand, Paul P; Quon, Harry; Tsang, Raymond K; Wu, Peter I; Graham, Peter; Cook, Ian J

2018-02-01

Objectives Dysphagia is common in total laryngectomees, with some symptoms suggesting esophageal dysmotility. Tracheoesophageal (TE) phonation requires effective esophagopharyngeal air passage. Hence, esophageal dysmotility may affect deglutition or TE phonation. This study aimed to determine (1) the characteristics of esophageal dysmotility in laryngectomees, (2) whether clinical history is sensitive in detecting esophageal dysmotility, and (3) the relationship between esophageal dysmotility and TE prosthesis dysfunction. Study Design Multidisciplinary cross-sectional study. Setting Tertiary academic hospital. Subjects and Methods For 31 participants undergone total laryngectomy 1 to 12 years prior, clinical histories were taken by a gastroenterologist and a speech pathologist experienced in managing dysphagia. Esophageal high-resolution manometry was performed and analyzed using Chicago Classification v3.0. Results Interpretable manometric studies were obtained in 23 (1 normal manometry). Esophageal dysmotility patterns included achalasia, esophagogastric junction outflow obstruction, diffuse esophageal spasm, and other major (30%) and minor (50%) peristaltic disorders. The sensitivity of predicting any esophageal dysmotility was 28%, but it is noteworthy that patients with achalasia and diffuse esophageal spasm (DES) were predicted. Two of 4 participants with TE puncture leakage had poor esophageal clearance. Of 20 TE speakers, 12 had voice problems, no correlation between poor voice, and any dysmotility pattern. Conclusions Peristaltic and lower esophageal sphincter dysfunction are common in laryngectomees. Clinical history, while not predictive of minor motor abnormalities, predicted correctly cases with treatable spastic motor disorders. Dysmotility was not associated with poor phonation, although TE puncture leakage might be linked to poor esophageal clearance. Esophageal dysmotility should be considered in the laryngectomees with persisting dysphagia or leaking TE puncture.

Predictive Models of Liver Cancer

EPA Science Inventory

Predictive models of chemical-induced liver cancer face the challenge of bridging causative molecular mechanisms to adverse clinical outcomes. The latent sequence of intervening events from chemical insult to toxicity are poorly understood because they span multiple levels of bio...

Preventive Maintenance Process

NASA Technical Reports Server (NTRS)

Ciaruffoli, Veronica; Bramley, Craig; Matteson, Mike

2001-01-01

The Preventive Maintenance (PM) program at Stennis Space Center (SSC) evolved from an ineffective and poorly organized state to a highly organized state in which it became capable of tracking equipment, planning jobs with man hour estimates, and supporting outsourcing. This viewgraph presentation traces the steps the program took to improve itself.

Poor sleep in relation to natural menopause: a population-based 14-year follow-up of midlife women.

PubMed

Freeman, Ellen W; Sammel, Mary D; Gross, Stephanie A; Pien, Grace W

2015-07-01

This study aims to estimate the prevalence and predictors of moderate/severe poor sleep in relation to the final menstrual period (FMP) in midlife women. Annual assessments were conducted in a population-based cohort of 255 women. All were premenopausal at cohort enrollment and reached natural menopause during the 16-year follow-up. The outcome measure was severity of poor sleep, as reported by participants in annual interviews for 16 years and as evaluated in relation to the FMP. The annual prevalence of moderate/severe poor sleep largely ranged from about 28% to 35%, with no significant differences in any year relative to the FMP for the sample overall. When sleep status was stratified at premenopausal baseline, premenopausal sleep status strongly predicted poor sleep around the FMP. Women with moderate/severe poor sleep in premenopause were approximately 3.5 times more likely to have moderate/severe poor sleep around menopause than those with no poor sleep at baseline in adjusted analysis (odds ratio, 3.58; 95% CI, 2.50-5.11; P < 0.0001), whereas mild poor sleepers in premenopause were approximately 1.5 times more likely to have moderate/severe poor sleep around menopause (odds ratio, 1.57; 95% CI, 0.99-2.47; P = 0.053). There was no significant association between poor sleep and time relative to the FMP among women who had no poor sleep at premenopausal baseline. Hot flashes were significantly associated with poor sleep (odds ratio, 1.79; 95% CI, 1.44-2.21; P < 0.0001 in adjusted analysis) but had no interaction with baseline sleep severity (interaction P = 0.25), indicating that hot flashes contributed to poor sleep regardless of baseline sleep status. Findings show a high prevalence of moderate/severe poor sleep in midlife women, with only a small "at-risk" subgroup having a significant increase in poor sleep in relation to the FMP. Sleep status at premenopausal baseline and concurrent hot flashes strongly and consistently predict poor sleep in the menopausal transition. Overall, poor sleep does not increase around the FMP and frequently occurs in the absence of hot flashes, indicating that sleep difficulties in the menopausal transition in generally healthy women are not simply associated with ovarian decline.

Poor Sleep in Relation to Natural Menopause: A Population-Based 14-Year Follow-up of Mid-Life Women

PubMed Central

Freeman, Ellen W.; Sammel, Mary D.; Gross, Stephanie A.; Pien, Grace W.

2014-01-01

Objective To estimate the prevalence and predictors of moderate/severe poor sleep in relation to the final menstrual period (FMP) of mid-life women. Methods Annual assessments were conducted in a population-based cohort of 255 women. All were premenopausal at cohort enrollment and reached natural menopause during the 16-year follow-up. The outcome measure was the severity of poor sleep, as reported by the participants in annual interviews for 16 years and evaluated in relation to the FMP. Results The annual prevalence of moderate/severe poor sleep largely ranged from about 28% to 35%, with no significant differences in any year relative to the FMP for the sample overall. When sleep status was stratified at the premenopausal baseline, the premenopausal sleep status strongly predicted poor sleep around the FMP. Women with moderate/severe poor sleep when premenopausal were approximately 3 ½ times more likely to have moderate/severe poor sleep around menopause compared to those with no poor sleep at baseline in adjusted analysis (OR 3.58, 95% CI: 2.50-5.11, P<0.0001), while mild poor sleepers premenopause were approximately 1 ½ times more likely to have moderate/severe poor sleep around menopause (OR 1.57, 95% CI: 0.99-2.47, P=0.053). There was no significant association between poor sleep and time relative to the FMP among women who had no poor sleep at the premenopausal baseline. Hot flashes were significantly associated with poor sleep (OR 1.79, 95% CI: 1.44-2.21, P<0.0001 in adjusted analysis), but had no interaction with baseline sleep severity (interaction P=0.25), indicating that hot flashes contributed to poor sleep regardless of baseline sleep status. Conclusion The findings showed a high prevalence of moderate/severe poor sleep in mid-life women, with only a small “at risk” subgroup having a significant increase in poor sleep in relation to the FMP. Sleep status at the premenopausal baseline and concurrent hot flashes strongly and consistently predicted poor sleep in the menopause transition. Overall, poor sleep did not increase around the FMP and frequently occurred in the absence of hot flashes, indicating that sleep difficulties in the menopause transition in generally healthy women were not simply associated with ovarian decline. PMID:25549066

Predicting Handwriting Difficulties through Spelling Processes

ERIC Educational Resources Information Center

Rodríguez, Cristina; Villarroel, Rebeca

2017-01-01

This study examined whether spelling tasks contribute to the prediction of the handwriting status of children with poor and good handwriting skills in a cross-sectional study with 276 Spanish children from Grades 1 and 3. The main hypothesis was that the spelling tasks would predict the handwriting status of the children, although this influence…

Chronic and Acute Stress, Gender, and Serotonin Transporter Gene-Environment Interactions Predicting Depression Symptoms in Youth

ERIC Educational Resources Information Center

Hammen, Constance; Brennan, Patricia A.; Keenan-Miller, Danielle; Hazel, Nicholas A.; Najman, Jake M.

2010-01-01

Background: Many recent studies of serotonin transporter gene by environment effects predicting depression have used stress assessments with undefined or poor psychometric methods, possibly contributing to wide variation in findings. The present study attempted to distinguish between effects of acute and chronic stress to predict depressive…

Clinical Value of Dorsal Medulla Oblongata Involvement Detected with Conventional MRI for Prediction of Outcome in Children with Enterovirus 71-related Brainstem Encephalitis.

PubMed

Liu, Kun; Zhou, Yongjin; Cui, Shihan; Song, Jiawen; Ye, Peipei; Xiang, Wei; Huang, Xiaoyan; Chen, Yiping; Yan, Zhihan; Ye, Xinjian

2018-04-05

Brainstem encephalitis is the most common neurologic complication after enterovirus 71 infection. The involvement of brainstem, especially the dorsal medulla oblongata, can cause severe sequelae or death in children with enterovirus 71 infection. We aimed to determine the prevalence of dorsal medulla oblongata involvement in children with enterovirus 71-related brainstem encephalitis (EBE) by using conventional MRI and to evaluate the value of dorsal medulla oblongata involvement in outcome prediction. 46 children with EBE were enrolled in the study. All subjects underwent a 1.5 Tesla MR examination of the brain. The disease distribution and clinical data were collected. Dichotomized outcomes (good versus poor) at longer than 6 months were available for 28 patients. Logistic regression was used to determine whether the MRI-confirmed dorsal medulla oblongata involvement resulted in improved clinical outcome prediction when compared with other location involvement. Of the 46 patients, 35 had MRI evidence of dorsal medulla oblongata involvement, 32 had pons involvement, 10 had midbrain involvement, and 7 had dentate nuclei involvement. Patients with dorsal medulla oblongata involvement or multiple area involvement were significantly more often in the poor outcome group than in the good outcome group. Logistic regression analysis showed that dorsal medulla oblongata involvement was the most significant single variable in outcome prediction (predictive accuracy, 90.5%), followed by multiple area involvement, age, and initial glasgow coma scale score. Dorsal medulla oblongata involvement on conventional MRI correlated significantly with poor outcomes in EBE children, improved outcome prediction when compared with other clinical and disease location variables, and was most predictive when combined with multiple area involvement, glasgow coma scale score and age.

Psychosocial work characteristics and social support as predictors of SF-36 health functioning: the Whitehall II study.

PubMed

Stansfeld, S A; Bosma, H; Hemingway, H; Marmot, M G

1998-01-01

To assess whether work characteristics and social support are predictors of physical, psychological, and social functioning. Work characteristics (Karasek and Siegrist models) and social support at baseline were used to predict health functioning measured by the SF-36 General Health Survey 5 years later in a prospective cohort study of 10,308 British male and female civil servants. Effort-reward imbalance and negative aspects of close relationships predicted poor physical, psychological, and social functioning after adjustment for the potential confounding effects of age, employment grade, baseline ill health, and negative affectivity. These psychosocial characteristics seem to act in a similar way in the healthy and those with existing illness. Psychological demands at work in women, and low confiding/emotional support in men, also predicted poor functioning. Etiologically. these effects are not mediated through health-related behaviors. Negative aspects of work (high demands and effort-reward imbalance) and negative aspects of close relationships are independent powerful predictors of poor health functioning. They may have an etiological role, which is independent of baseline illness.

Applying a multi-replication framework to support dynamic situation assessment and predictive capabilities

NASA Astrophysics Data System (ADS)

Lammers, Craig; McGraw, Robert M.; Steinman, Jeffrey S.

2005-05-01

Technological advances and emerging threats reduce the time between target detection and action to an order of a few minutes. To effectively assist with the decision-making process, C4I decision support tools must quickly and dynamically predict and assess alternative Courses Of Action (COAs) to assist Commanders in anticipating potential outcomes. These capabilities can be provided through the faster-than-real-time predictive simulation of plans that are continuously re-calibrating with the real-time picture. This capability allows decision-makers to assess the effects of re-tasking opportunities, providing the decision-maker with tremendous freedom to make time-critical, mid-course decisions. This paper presents an overview and demonstrates the use of a software infrastructure that supports DSAP capabilities. These DSAP capabilities are demonstrated through the use of a Multi-Replication Framework that supports (1) predictivie simulations using JSAF (Joint Semi-Automated Forces); (2) real-time simulation, also using JSAF, as a state estimation mechanism; and, (3) real-time C4I data updates through TBMCS (Theater Battle Management Core Systems). This infrastructure allows multiple replications of a simulation to be executed simultaneously over a grid faster-than-real-time, calibrated with live data feeds. A cost evaluator mechanism analyzes potential outcomes and prunes simulations that diverge from the real-time picture. In particular, this paper primarily serves to walk a user through the process for using the Multi-Replication Framework providing an enhanced decision aid.

High serum uric acid concentration predicts poor survival in patients with breast cancer.

PubMed

Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

2017-10-01

Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Impaired Patient-Reported Outcomes Predict Poor School Functioning and Daytime Sleepiness: The PROMIS Pediatric Asthma Study.

PubMed

Jones, Conor M; DeWalt, Darren A; Huang, I-Chan

Poor asthma control in children is related to impaired patient-reported outcomes (PROs; eg, fatigue, depressive symptoms, anxiety), but less well studied is the effect of PROs on children's school performance and sleep outcomes. In this study we investigated whether the consistency status of PROs over time affected school functioning and daytime sleepiness in children with asthma. Of the 238 children with asthma enrolled in the Patient-Reported Outcomes Measurement Information System (PROMIS) Pediatric Asthma Study, 169 children who provided survey data for all 4 time points were used in the analysis. The child's PROs, school functioning, and daytime sleepiness were measured 4 times within a 15-month period. PRO domains included asthma impact, pain interference, fatigue, depressive symptoms, anxiety, and mobility. Each child was classified as having poor/fair versus good PROs per meaningful cut points. The consistency status of each domain was classified as consistently poor/fair if poor/fair status was present for at least 3 time points; otherwise, the status was classified as consistently good. Seemingly unrelated regression was performed to test if consistently poor/fair PROs predicted impaired school functioning and daytime sleepiness at the fourth time point. Consistently poor/fair in all PRO domains was significantly associated with impaired school functioning and excessive daytime sleepiness (Ps < .01) after controlling for the influence of the child's age, sex, and race/ethnicity. Children with asthma with consistently poor/fair PROs are at risk of poor school functioning and daytime sleepiness. Developing child-friendly PRO assessment systems to track PROs can inform potential problems in the school setting. Copyright © 2017 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Implementation of Finite Rate Chemistry Capability in OVERFLOW

NASA Technical Reports Server (NTRS)

Olsen, M. E.; Venkateswaran, S.; Prabhu, D. K.

2004-01-01

An implementation of both finite rate and equilibrium chemistry have been completed for the OVERFLOW code, a chimera capable, complex geometry flow code widely used to predict transonic flow fields. The implementation builds on the computational efficiency and geometric generality of the solver.

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.

FACTORS INFLUENCING PREDICTION OF BROMODICHLOROMETHANE (BDCM) IN EXHALED BREATH: FURTHER EVALUATION OF A HUMAN BDCM PBPK MODEL

EPA Science Inventory

Confidence in the predictive capability of a PBPK model is increased when the model is demonstrated to predict multiple pharmacokinetic outcomes from diverse studies under different exposure conditions. We previously showed that our multi-route human BDCM PBPK model adequately (w...

A theoretical investigation of ground effects on USB configurations

NASA Technical Reports Server (NTRS)

Lan, C. E.

1979-01-01

A formulation predicts the variation of circulation forces and jet reaction forces in ground proximity as a function of ground height. The predicted results agree well with available experimental data. It is shown that the wing-alone theory is not capable of predicting the ground effect for USB configurations.

How well does a single question about health predict the financial health of Medicare managed care plans?

PubMed

Bierman, A S; Bubolz, T A; Fisher, E S; Wasson, J H

1999-01-01

Responses to simple questions that predict subsequent health care utilization are of interest to both capitated health plans and the payer. To determine how responses to a single question about general health status predict subsequent health care expenditures. Participants in the 1992 Medicare Current Beneficiary Survey were asked the following question: "In general, compared to other people your age, would you say your health is: excellent, very good, good, fair or poor?" To obtain each participant's total Medicare expenditures and number of hospitalizations in the ensuing year, we linked the responses to this question with data from the 1993 Medicare Continuous History Survey. Nationally representative sample of 8775 noninstitutionalized Medicare beneficiaries 65 years of age and older. Annual age- and sex-adjusted Medicare expenditures and hospitalization rates. Eighteen percent of the beneficiaries rated their health as excellent, 56% rated it as very good or good, 17% rated it as fair, and 7% rated it as poor. Medicare expenditures had a marked inverse relation to self-assessed health ratings. In the year after assessment, age- and sex-adjusted annual expenditures varied fivefold, from $8743 for beneficiaries rating their health as poor to $1656 for beneficiaries rating their health as excellent. Hospitalization rates followed the same pattern: Respondents who rated their health as poor had 675 hospitalizations per 1000 beneficiaries per year compared with 136 per 1000 for those rating their health as excellent. The response to a single question about general health status strongly predicts subsequent health care utilization. Self-reports of fair or poor health identify a group of high-risk patients who may benefit from targeted interventions. Because the current Medicare capitation formula does not account for health status, health plans can maximize profits by disproportionately enrolling beneficiaries who judge their health to be good. However, they are at a competitive disadvantage if they enroll beneficiaries who view themselves as sick.

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…

Capability for suicide interacts with states of heightened arousal to predict death by suicide beyond the effects of depression and hopelessness

PubMed Central

Ribeiro, Jessica D.; Yen, Shirley; Joiner, Thomas; Siegler, Ilene C.

2016-01-01

Background States of heightened arousal (e.g., agitation, sleep disturbance) have been repeatedly linked to suicidal thoughts and behaviors, including attempts and death. Studies have further indicated that these states may be particularly pernicious among individuals who evidence high suicidal capability. The objective of this study was to examine the interactive effects of heightened arousal and the capability for suicide in the prospective prediction of death by suicide. We examine this relation beyond the effects of robust predictors of suicide, namely depression and hopelessness. Methods Participants were drawn from a larger study of undergraduates who completed baseline assessments during their freshman year and were then followed to time of death. The sample in this study only included individuals who had died by suicide (n=96) or other causes (n=542). Proxy measures to assess predictor variables were constructed using items from the MMPI, which was administered at baseline. An independent sample of clinical outpatients (n=was used to evaluate the construct validity of the proxy measures). Results Results were in line with expectation: heightened arousal interacted with capability for suicide to prospectively predict death by suicide, such that, as severity of heightened arousal symptoms increased, the likelihood of death by suicide increased among individuals high but not low on capability for suicide. Limitations Limitations include the use of proxy measures, the extended length of follow-up, and the homogeneity of the sample (i.e., primarily White males). Conclusion These findings add to an emerging literature that supports the moderating influence of capability for suicide on the relationship between states of heightened arousal on the likelihood of death by suicide. PMID:26342889

Prevalence and Predictive Factors of Chronic Postsurgical Pain and Poor Global Recovery 1 Year After Outpatient Surgery.

PubMed

Hoofwijk, Daisy M N; Fiddelers, Audrey A A; Peters, Madelon L; Stessel, Björn; Kessels, Alfons G H; Joosten, Elbert A; Gramke, Hans-Fritz; Marcus, Marco A E

2015-12-01

To prospectively describe the prevalence and predictive factors of chronic postsurgical pain (CPSP) and poor global recovery in a large outpatient population at a university hospital, 1 year after outpatient surgery. A prospective longitudinal cohort study was performed. During 18 months, patients presenting for preoperative assessment were invited to participate. Outcome parameters were measured by using questionnaires at 3 timepoints: 1 week preoperatively, 4 days postoperatively, and 1 year postoperatively. A value of >3 on an 11-point numeric rating scale was considered to indicate moderate to severe pain. A score of ≤80% on the Global Surgical Recovery Index was defined as poor global recovery. A total of 908 patients were included. The prevalence of moderate to severe preoperative pain was 37.7%, acute postsurgical pain 26.7%, and CPSP 15.3%. Risk factors for the development of CPSP were surgical specialty, preoperative pain, preoperative analgesic use, acute postoperative pain, surgical fear, lack of optimism, and poor preoperative quality of life. The prevalence of poor global recovery was 22.3%. Risk factors for poor global recovery were recurrent surgery because of the same pathology, preoperative pain, preoperative analgesic use, surgical fear, lack of optimism, poor preoperative and acute postoperative quality of life, and follow-up surgery during the first postoperative year. Moderate to severe CPSP after outpatient surgery is common, and should not be underestimated. Patients at risk for developing CPSP can be identified during the preoperative phase.

The self-serving function of hypochondriacal complaints: physical symptoms as self-handicapping strategies.

PubMed

Smith, T W; Snyder, C R; Perkins, S C

1983-04-01

The present experiment tested the hypothesis that hypochondriacal individuals commonly use reports of physical illness and symptoms as a strategy to control attributions made about their performances in evaluative settings (i.e., self-handicapping strategies). Specifically, it was predicted that hypochondriacal individuals would report more recent physical illness and complaints and more current physical symptoms in an evaluative setting in which poor health could serve as an alternative explanation for poor performance than would either individuals in an evaluative setting in which poor health was precluded as an excuse or individuals in a nonevaluative setting. As predicted, results supported this self-protective pattern of complaints in a hypochondriacal sample but not in a nonhypochondriacal group. The self-protective role of hypochondriacal behavior is discussed in relation to other theory and research on the nature and treatment of hypochondriasis.

Gastric biomarkers: a global review.

PubMed

Baniak, Nick; Senger, Jenna-Lynn; Ahmed, Shahid; Kanthan, S C; Kanthan, Rani

2016-08-11

Gastric cancer is an aggressive disease with a poor 5-year survival and large global burden of disease. The disease is biologically and genetically heterogeneous with a poorly understood carcinogenesis at the molecular level. Despite the many prognostic, predictive, and therapeutic biomarkers investigated to date, gastric cancer continues to be detected at an advanced stage with resultant poor clinical outcomes. This is a global review of gastric biomarkers with an emphasis on HER2, E-cadherin, fibroblast growth factor receptor, mammalian target of rapamycin, and hepatocyte growth factor receptor as well as sections on microRNAs, long noncoding RNAs, matrix metalloproteinases, PD-L1, TP53, and microsatellite instability. A deeper understanding of the pathogenesis and biological features of gastric cancer, including the identification and characterization of diagnostic, prognostic, predictive, and therapeutic biomarkers, hopefully will provide improved clinical outcomes.

Virtual scanning tunneling microscopy: A local spectroscopic probe of two-dimensional electron systems

NASA Astrophysics Data System (ADS)

Sciambi, A.; Pelliccione, M.; Bank, S. R.; Gossard, A. C.; Goldhaber-Gordon, D.

2010-09-01

We propose a probe technique capable of performing local low-temperature spectroscopy on a two-dimensional electron system (2DES) in a semiconductor heterostructure. Motivated by predicted spatially-structured electron phases, the probe uses a charged metal tip to induce electrons to tunnel locally, directly below the tip, from a "probe" 2DES to a "subject" 2DES of interest. We test this concept with large-area (nonscanning) tunneling measurements, and predict a high spatial resolution and spectroscopic capability, with minimal influence on the physics in the subject 2DES.

Intelligent aircraft/airspace systems

NASA Technical Reports Server (NTRS)

Wangermann, John P.

1995-01-01

Projections of future air traffic predict at least a doubling of the number of revenue passenger miles flown by the year 2025. To meet this demand, an Intelligent Aircraft/Airspace System (IAAS) has been proposed. The IAAS operates on the basis of principled negotiation between intelligent agents. The aircraft/airspace system today consists of many agents, such as airlines, control facilities, and aircraft. All the agents are becoming increasingly capable as technology develops. These capabilities should be exploited to create an Intelligent Aircraft/Airspace System (IAAS) that would meet the predicted traffic levels of 2005.

Application of thrusting ejectors to tactical aircraft having vertical lift and short-field capability

NASA Technical Reports Server (NTRS)

Koenig, D. G.; Stoll, F.; Aoyagi, K.

1981-01-01

The status of ejector development in terms of application to V/STOL aircraft is reported in three categories: aircraft systems and ejector concepts; ejector performance including prediction techniques and experimental data base available; and, integration of the ejector with complete aircraft configurations. Available prediction techniques are reviewed and performance of three ejector designs with vertical lift capability is summarized. Applications of the 'fuselage' and 'short diffuser' ejectors to fighter aircraft are related to current and planned research programs. Recommendations are listed for effort needed to evaluate installed performance.

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface.

PubMed

Lajoie, Guillaume; Krouchev, Nedialko I; Kalaska, John F; Fairhall, Adrienne L; Fetz, Eberhard E

2017-02-01

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity.

Multiple Syntrophic Interactions in a Terephthalate-Degrading Methanogenic Consortium

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

Lykidis, Athanasios; Chen, Chia-Lung; Tringe, Susannah G.

2010-08-05

Terephthalate (TA) is one of the top 50 chemicals produced worldwide. Its production results in a TA-containing wastewater that is treated by anaerobic processes through a poorly understood methanogenic syntrophy. Using metagenomics, we characterized the methanogenic consortium tinside a hyper-mesophilic (i.e., between mesophilic and thermophilic), TA-degrading bioreactor. We identified genes belonging to dominant Pelotomaculum species presumably involved in TA degradation through decarboxylation, dearomatization, and modified ?-oxidation to H{sub 2}/CO{sub 2} and acetate. These intermediates are converted to CH{sub 4}/CO{sub 2} by three novel hyper-mesophilic methanogens. Additional secondary syntrophic interactions were predicted in Thermotogae, Syntrophus and candidate phyla OP5 and WWE1more » populations. The OP5 encodes genes capable of anaerobic autotrophic butyrate production and Thermotogae, Syntrophus and WWE1 have the genetic potential to oxidize butyrate to COsub 2}/H{sub 2} and acetate. These observations suggest that the TA-degrading consortium consists of additional syntrophic interactions beyond the standard H{sub 2}-producing syntroph ? methanogen partnership that may serve to improve community stability.« less

Ejecta- and Size-Scaling Considerations from Impacts of Glass Projectiles into Sand

NASA Technical Reports Server (NTRS)

Anderson J. L. B.; Cintala, M. J.; Siebenaler, S. A.; Barnouin-Jha, O. S.

2007-01-01

One of the most promising means of learning how initial impact conditions are related to the processes leading to the formation of a planetary-scale crater is through scaling relationships.1,2,3 The first phase of deriving such relationships has led to great insight into the cratering process and has yielded predictive capabilities that are mathematically rigorous and internally consistent. Such derivations typically have treated targets as continuous media; in many, cases, however, planetary materials represent irregular and discontinuous targets, the effects of which on the scaling relationships are still poorly understood.4,5 We continue to examine the effects of varying impact conditions on the excavation and final dimensions of craters formed in sand. Along with the more commonly treated variables such as impact speed, projectile size and material, and impact angle,6 such experiments also permit the study of changing granularity and friction angle of the target materials. This contribution presents some of the data collected during and after the impact of glass spheres into a medium-grained sand.

Technical Advances in the Measurement of Residual Disease in Acute Myeloid Leukemia

PubMed Central

Roloff, Gregory W.; Lai, Catherine; Dillon, Laura W.

2017-01-01

Outcomes for those diagnosed with acute myeloid leukemia (AML) remain poor. It has been widely established that persistent residual leukemic burden, often referred to as measurable or minimal residual disease (MRD), after induction therapy or at the time of hematopoietic stem cell transplant (HSCT) is highly predictive for adverse clinical outcomes and can be used to identify patients likely to experience clinically evident relapse. As a result of inherent genetic and molecular heterogeneity in AML, there is no uniform method or protocol for MRD measurement to encompass all cases. Several techniques focusing on identifying recurrent molecular and cytogenetic aberrations or leukemia-associated immunophenotypes have been described, each with their own strengths and weaknesses. Modern technologies enabling the digital quantification and tracking of individual DNA or RNA molecules, next-generation sequencing (NGS) platforms, and high-resolution imaging capabilities are among several new avenues under development to supplement or replace the current standard of flow cytometry. In this review, we outline emerging modalities positioned to enhance MRD detection and discuss factors surrounding their integration into clinical practice. PMID:28925935

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface

PubMed Central

Lajoie, Guillaume; Kalaska, John F.; Fairhall, Adrienne L.; Fetz, Eberhard E.

2017-01-01

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity. PMID:28151957

Relationship Between Dental Students' Pre-Admission Record and Performance on the Comprehensive Basic Science Examination.

PubMed

Lee, Kevin C; Lee, Victor Y; Zubiaurre, Laureen A; Grbic, John T; Eisig, Sidney B

2018-04-01

The Comprehensive Basic Science Examination (CBSE) is the entrance examination for oral and maxillofacial surgery, but its implementation among dental students is a relatively recent and unintended use. The aim of this study was to examine the relationship between pre-admission data and performance on the CBSE for dental students at the Columbia University College of Dental Medicine (CDM). This study followed a retrospective cohort, examining data for the CDM Classes of 2014-19. Data collected were Dental Admission Test (DAT) and CBSE scores and undergraduate GPAs for 49 CDM students who took the CBSE from September 2013 to July 2016. The results showed that the full regression model did not demonstrate significant predictive capability (F[8,40]=1.70, p=0.13). Following stepwise regression, only the DAT Perceptual Ability score remained in the final model (F[1,47]=7.97, p<0.01). Variations in DAT Perceptual Ability scores explained 15% of the variability in CBSE scores (R 2 =0.15). This study found that, among these students, pre-admission data were poor predictors of CBSE performance.

Gas distribution and clumpiness in the galaxy group NGC 2563

NASA Astrophysics Data System (ADS)

Morandi, Andrea; Sun, Ming; Mulchaey, John; Nagai, Daisuke; Bonamente, Massimiliano

2017-08-01

We present a Chandra study of the hot intragroup medium of the galaxy group NCG 2563. The Chandra mosaic observations, with a total exposure time of ˜430 ks, allow the gas density to be detected beyond R200 and the gas temperature out to 0.75 R200. This represents the first observational measurement of the physical properties of a poor groups beyond R500. By capitalizing on the exquisite spatial resolution of Chandra that is capable to remove unrelated emission from point sources and substructures, we are able to radially constrain the inhomogeneities of gas ('clumpiness'), gas fraction, temperature and entropy distribution. Although there is some uncertainty in the measurements, we find evidences of gas clumping in the virialization region, with clumping factor of about 2-3 at R200. The gas clumping-corrected gas fraction is significantly lower than the cosmological baryon budget. These results may indicate a larger impact of the gas inhomogeneities with respect to the prediction from hydrodynamic numerical simulations, and we discuss possible explanations for our findings.

Cloud Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

2001-01-01

Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

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

Improving promoter prediction for the NNPP2.2 algorithm: a case study using Escherichia coli DNA sequences.

PubMed

Burden, S; Lin, Y-X; Zhang, R

2005-03-01

Although a great deal of research has been undertaken in the area of promoter prediction, prediction techniques are still not fully developed. Many algorithms tend to exhibit poor specificity, generating many false positives, or poor sensitivity. The neural network prediction program NNPP2.2 is one such example. To improve the NNPP2.2 prediction technique, the distance between the transcription start site (TSS) associated with the promoter and the translation start site (TLS) of the subsequent gene coding region has been studied for Escherichia coli K12 bacteria. An empirical probability distribution that is consistent for all E.coli promoters has been established. This information is combined with the results from NNPP2.2 to create a new technique called TLS-NNPP, which improves the specificity of promoter prediction. The technique is shown to be effective using E.coli DNA sequences, however, it is applicable to any organism for which a set of promoters has been experimentally defined. The data used in this project and the prediction results for the tested sequences can be obtained from http://www.uow.edu.au/~yanxia/E_Coli_paper/SBurden_Results.xls alh98@uow.edu.au.

Predicting local field potentials with recurrent neural networks.

PubMed

Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

2016-08-01

We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

NEW PUBLIC DATA AND INTERNET RESOURCES IMPACTING PREDICTIVE TOXICOLOGY.

EPA Science Inventory

High-throughput screening (HTS) technologies, along with efforts to improve public access to chemical toxicity information resources and to systematize older toxicity studies, have the potential to significantly improve predictive capabilities in toxicology.

A CCIR-based prediction model for Earth-Space propagation

NASA Technical Reports Server (NTRS)

Zhang, Zengjun; Smith, Ernest K.

1991-01-01

At present there is no single 'best way' to predict propagation impairments to an Earth-Space path. However, there is an internationally accepted way, namely that given in the most recent version of CCIR Report 564 of Study Group 5. This paper treats a computer code conforming as far as possible to Report 564. It was prepared for an IBM PS/2 using a 386 chip and for Macintosh SE or Mach II. It is designed to be easy to write and read, easy to modify, fast, have strong graphic capability, contain adequate functions, have dialog capability and windows capability. Computer languages considered included the following: (1) Turbo BASIC, (2) Turbo PASCAL, (3) FORTRAN, (4) SMALL TALK, (5) C++, (6) MS SPREADSHEET, (7) MS Excel-Macro, (8) SIMSCRIPT II.5, and (9) WINGZ.

A small cysteine-rich protein from the Asian soybean rust fungus, Phakopsora pachyrhizi, suppresses plant immunity

USDA-ARS?s Scientific Manuscript database

The Asian soybean rust fungus, Phakopsora pachyrhizi, is an obligate pathogen capable of causing explosive disease epidemics that drastically reduce the yield of soybean (Glycine max). Currently, the molecular mechanisms by which P. pachyrhizi and other rust fungi cause disease are poorly understood...

Governance and Free Education: Directions, Mechanisms and Policy Tensions

ERIC Educational Resources Information Center

Bray, Mark

2007-01-01

In 2006, the Department for International Development (DfID) of the United Kingdom Government issued a White Paper entitled "Eliminating World Poverty: Making Governance Work for Poor People." The DfID document observed that good governance requires attention to State capability, described at "the extent to which leaders and…

Assessment and Develop the Saudi's Contractors Classification System

ERIC Educational Resources Information Center

Almutairi, Saud

2017-01-01

Research has shown that construction projects in Saudi Arabia have had a perceived poor performance for the past three decades, from 1970-2016. The Saudi construction industry relies on a Contractor Classification System (CCS) to determine contractors' capabilities, and prevent underperformance. Through this study, a survey was conducted among…

The People Capability Maturity Model

ERIC Educational Resources Information Center

Wademan, Mark R.; Spuches, Charles M.; Doughty, Philip L.

2007-01-01

The People Capability Maturity Model[R] (People CMM[R]) advocates a staged approach to organizational change. Developed by the Carnegie Mellon University Software Engineering Institute, this model seeks to bring discipline to the people side of management by promoting a structured, repeatable, and predictable approach for improving an…

Conventional MRI features for predicting the clinical outcome of patients with invasive placenta

PubMed Central

Chen, Ting; Xu, Xiao-Quan; Shi, Hai-Bin; Yang, Zheng-Qiang; Zhou, Xin; Pan, Yi

2017-01-01

PURPOSE We aimed to evaluate whether morphologic magnetic resonance imaging (MRI) features could help to predict the maternal outcome after uterine artery embolization (UAE)-assisted cesarean section (CS) in patients with invasive placenta previa. METHODS We retrospectively reviewed the MRI data of 40 pregnant women who have undergone UAE-assisted cesarean section due to suspected high risk of massive hemorrhage caused by invasive placenta previa. Patients were divided into two groups based on the maternal outcome (good-outcome group: minor hemorrhage and uterus preserved; poor-outcome group: significant hemorrhage or emergency hysterectomy). Morphologic MRI features were compared between the two groups. Multivariate logistic regression analysis was used to identify the most valuable variables, and predictive value of the identified risk factor was determined. RESULTS Low signal intensity bands on T2-weighted imaging (P < 0.001), placenta percreta (P = 0.011), and placental cervical protrusion sign (P = 0.002) were more frequently observed in patients with poor outcome. Low signal intensity bands on T2-weighted imaging was the only significant predictor of poor maternal outcome in multivariate analysis (P = 0.020; odds ratio, 14.79), with 81.3% sensitivity and 84.3% specificity. CONCLUSION Low signal intensity bands on T2-weighted imaging might be a predictor of poor maternal outcome after UAE-assisted cesarean section in patients with invasive placenta previa. PMID:28345524

Managing Computer Systems Development: Understanding the Human and Technological Imperatives.

DTIC Science & Technology

1985-06-01

for their organization’s use? How can they predict tle impact of future systems ca their management control capabilities ? Cf equal importance is the...commercial organizations discovered that there was only a limited capability of interaction between various types of computers. These organizations were...Viewed together, these three interrelated subsystems, EDP, MIS, and DSS, establish the framework of an overall systems capability known as a Computer

Integration of Satellite, Modeled, and Ground Based Aerosol Data for use in Air Quality and Public Health Applications

NASA Astrophysics Data System (ADS)

Garcia, V.; Kondragunta, S.; Holland, D.; Dimmick, F.; Boothe, V.; Szykman, J.; Chu, A.; Kittaka, C.; Al-Saadi, J.; Engel-Cox, J.; Hoff, R.; Wayland, R.; Rao, S.; Remer, L.

2006-05-01

Advancements in remote sensing over the past decade have been recognized by governments around the world and led to the development of the international Global Earth Observation System of Systems 10-Year Implementation Plan. The plan for the U.S. contribution to GEOSS has been put forth in The Strategic Plan for the U.S. Integrated Earth Observation System (IEOS) developed under IWGEO-CENR. The approach for the development of the U.S. IEOS is to focus on specific societal benefits that can be achieved by integrating the nation's Earth observation capabilities. One such challenge is our ability to understand the impact of poor air quality on human health and well being. Historically, the air monitoring networks put in place for the Nations air quality programs provided the only aerosol air quality data on an ongoing and systematic basis at national levels. However, scientific advances in the remote sensing of aerosols from space have improved dramatically. The MODIS sensor and GOES Imager aboard NASA and NOAA satellites, respectively, provide synoptic-scale measurements of aerosol optical depth (AOD) which have been demonstrated to correlate with high levels of PM10 and PM2.5 at the surface. The MODIS sensor has been shown to be capable of a 1 km x 1 km (at nadir) AOD product, while the GOES Imager can provide AOD at 4 km x 4 km every 30 minutes. Within the next several years NOAA and EPA will begin to issue PM2.5 air quality forecasts over the entire domain of the eastern United States, eventually extending to national coverage. These forecasts will provide continuous estimated values of PM2.5 on a daily basis. A multi-agency collaborative project among government and academia is underway to improve the spatial prediction of fine particulate matter through the integration of multi-sensor and multi-platform aerosol observations (MODIS and GOES), numerical model output, and air monitoring data. By giving more weight to monitoring data in monitored areas and relying on adjusted model output and satellite data in non-monitored areas, a Bayesian hierarchical space-time model will be used to improve the accuracy of prediction and associated prediction errors. The improved spatial predictions will be tested as estimates of exposure for input to modeling relationships between air quality and asthma/other respiratory diseases through CDC under the Environmental Public Health Tracking Network. We will also focus on the use of the predictive spatial maps within the EPA AIRNow program which provides near real-time spatial maps of daily average PM2.5 concentrations across the US. We will present the overall project plan and preliminary results with emphasis on how GEOSS framework is facilitating this effort.

Status epilepticus severity score (STESS): A useful tool to predict outcome of status epilepticus.

PubMed

Goyal, Manoj Kumar; Chakravarthi, Sudheer; Modi, Manish; Bhalla, Ashish; Lal, Vivek

2015-12-01

The treatment protocols for status epilepticus (SE) range from small doses of intravenous benzodiazepines to induction of coma. The pros and cons of more aggressive treatment regimen remain debatable. The importance of an index need not be overemphasized which can predict outcome of SE and guide the intensity of treatment. We tried to evaluate utility of one such index Status epilepticus severity score (STESS). 44 consecutive patients of SE were enrolled in the study. STESS results were compared with various outcome measures: (a) mortality, (b) final neurological outcome at discharge as defined by functional independence measure (FIM) (good outcome: FIM score 5-7; bad outcome: FIM score 1-4), (c) control of SE within 1h of start of treatment and (d) need for coma induction. A higher STESS score correlated significantly with poor neurological outcome at discharge (p=0.0001), need for coma induction (p=0.0001) and lack of response to treatment within 1h (p=0.001). A STESS of <3 was found to have a negative predictive value of 96.9% for mortality, 96.7% for poor neurological outcome at discharge and 96.7% for need of coma induction, while a STESS of <2 had negative predictive value of 100% for mortality, coma induction and poor neurological outcome at discharge. STESS can reliably predict the outcome of status epilepticus. Further studies on STESS based treatment approach may help in designing better therapeutic regimens for SE. Copyright © 2015 Elsevier B.V. All rights reserved.

Validating Inertial Confinement Fusion (ICF) predictive capability using perturbed capsules

NASA Astrophysics Data System (ADS)

Schmitt, Mark; Magelssen, Glenn; Tregillis, Ian; Hsu, Scott; Bradley, Paul; Dodd, Evan; Cobble, James; Flippo, Kirk; Offerman, Dustin; Obrey, Kimberly; Wang, Yi-Ming; Watt, Robert; Wilke, Mark; Wysocki, Frederick; Batha, Steven

2009-11-01

Achieving ignition on NIF is a monumental step on the path toward utilizing fusion as a controlled energy source. Obtaining robust ignition requires accurate ICF models to predict the degradation of ignition caused by heterogeneities in capsule construction and irradiation. LANL has embarked on a project to induce controlled defects in capsules to validate our ability to predict their effects on fusion burn. These efforts include the validation of feature-driven hydrodynamics and mix in a convergent geometry. This capability is needed to determine the performance of capsules imploded under less-than-optimum conditions on future IFE facilities. LANL's recently initiated Defect Implosion Experiments (DIME) conducted at Rochester's Omega facility are providing input for these efforts. Recent simulation and experimental results will be shown.

Simulation for Prediction of Entry Article Demise (SPEAD): An Analysis Tool for Spacecraft Safety Analysis and Ascent/Reentry Risk Assessment

NASA Technical Reports Server (NTRS)

Ling, Lisa

2014-01-01

For the purpose of performing safety analysis and risk assessment for a potential off-nominal atmospheric reentry resulting in vehicle breakup, a synthesis of trajectory propagation coupled with thermal analysis and the evaluation of node failure is required to predict the sequence of events, the timeline, and the progressive demise of spacecraft components. To provide this capability, the Simulation for Prediction of Entry Article Demise (SPEAD) analysis tool was developed. The software and methodology have been validated against actual flights, telemetry data, and validated software, and safety/risk analyses were performed for various programs using SPEAD. This report discusses the capabilities, modeling, validation, and application of the SPEAD analysis tool.

Buckling Testing and Analysis of Space Shuttle Solid Rocket Motor Cylinders

NASA Technical Reports Server (NTRS)

Weidner, Thomas J.; Larsen, David V.; McCool, Alex (Technical Monitor)

2002-01-01

A series of full-scale buckling tests were performed on the space shuttle Reusable Solid Rocket Motor (RSRM) cylinders. The tests were performed to determine the buckling capability of the cylinders and to provide data for analytical comparison. A nonlinear ANSYS Finite Element Analysis (FEA) model was used to represent and evaluate the testing. Analytical results demonstrated excellent correlation to test results, predicting the failure load within 5%. The analytical value was on the conservative side, predicting a lower failure load than was applied to the test. The resulting study and analysis indicated the important parameters for FEA to accurately predict buckling failure. The resulting method was subsequently used to establish the pre-launch buckling capability of the space shuttle system.

Comparison of ISS Power System Telemetry with Analytically Derived Data for Shadowed Cases

NASA Technical Reports Server (NTRS)

Fincannon, H. James

2002-01-01

Accurate International Space Station (ISS) power prediction requires the quantification of solar array shadowing. Prior papers have discussed the NASA Glenn Research Center (GRC) ISS power system tool SPACE (System Power Analysis for Capability Evaluation) and its integrated shadowing algorithms. On-orbit telemetry has become available that permits the correlation of theoretical shadowing predictions with actual data. This paper documents the comparison of a shadowing metric (total solar array current) as derived from SPACE predictions and on-orbit flight telemetry data for representative significant shadowing cases. Images from flight video recordings and the SPACE computer program graphical output are used to illustrate the comparison. The accuracy of the SPACE shadowing capability is demonstrated for the cases examined.

Social Ecology of Child Soldiers: Child, Family, and Community Determinants of Mental Health, Psychosocial Wellbeing, and Reintegration in Nepal

PubMed Central

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

2013-01-01

This study employs social ecology to evaluate psychosocial wellbeing in a cross-sectional sample of 142 former child soldiers in Nepal. Outcome measures included the Depression Self Rating Scale (DSRS), Child Posttraumatic Stress Scale (CPSS), and locally developed measures of function impairment and reintegration. At the child level, traumatic exposures, especially torture, predicted poor outcomes, while education improved outcomes. At the family level, conflict-related death of a relative, physical abuse in the household, and loss of wealth during the conflict predicted poor outcomes. At the community level, living in high caste Hindu communities predicted fewer reintegration supports. Ultimately, social ecology is well-suited to identify intervention foci across ecological levels, based on community differences in vulnerability and protective factors. PMID:21088102

Medicaid eligibility policy in the 1980s: medical utilitarianism and the "deserving" poor.

PubMed

Tanenbaum, S J

1995-01-01

Between 1981 and the early 1990s, the Medicaid program grew substantially, in part because, for the first time in the program's history, eligibility for medical assistance was severed from eligibility for income-maintenance payments. Program participation had always been reserved for the "deserving poor," and these were originally defined as persons excluded from market relationships through no fault of their own. The Medicaid expansion of the 1980s, however, created a new constituency of poor, and not-so-poor, persons whose actual or predictable medical problems promised a calculable return on program funds.

Components of Young Children's Trait Understanding: Behavior-to-Trait Inferences and Trait-to-Behavior Predictions

ERIC Educational Resources Information Center

Liu, David; Gelman, Susan A.; Wellman, Henry M.

2007-01-01

Trait attribution is central to people's naive theories of people and their actions. Previous developmental research indicates that young children are poor at predicting behaviors from past trait-relevant behaviors. We propose that the cognitive process of behavior-to-behavior predictions consists of two component processes: (1) behavior-to-trait…

High capacity reversible watermarking for audio by histogram shifting and predicted error expansion.

PubMed

Wang, Fei; Xie, Zhaoxin; Chen, Zuo

2014-01-01

Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution algorithm to optimize prediction coefficients and then apply prediction error expansion to output stego data. Second, in order to reduce location map bits length, we introduced histogram shifting scheme. Meanwhile, the prediction error modification threshold according to a given embedding capacity can be computed by our proposed scheme. Experiments show that this algorithm improves the SNR of embedded audio signals and embedding capacity, drastically reduces location map bits length, and enhances capacity control capability.

State-of-the-art of high-speed propeller noise prediction - A multidisciplinary approach and comparison with measured data

NASA Technical Reports Server (NTRS)

Dunn, Mark H.; Farassat, F.

1990-01-01

The results of NASA's Propeller Test Assessment program involving extensive flight tests of a large-scale advanced propeller are presented. This has provided the opportunity to evaluate the current capability of advanced propeller noise prediction utilizing principally the exterior acoustic measurements for the prediction of exterior noise. The principal object of this study was to evaluate the state-of-the-art of noise prediction for advanced propellers utilizing the best available codes of the disciplines involved. The effects of blade deformation on the aerodynamics and noise of advanced propellers were also studied. It is concluded that blade deformation can appreciably influence propeller noise and aerodynamics, and that, in general, centrifugal and blade forces must both be included in the calculation of blade forces. It is noted that the present capability for free-field noise prediction of the first three harmonics for advanced propellers is fairly good. Detailed data and diagrams of the test results are presented.

Airspace Technology Demonstration 2 (ATD-2) Phase 1 Concept of Use (ConUse)

NASA Technical Reports Server (NTRS)

Jung, Yoon; Engelland, Shawn; Capps, Richard; Coppenbarger, Rich; Hooey, Becky; Sharma, Shivanjli; Stevens, Lindsay; Verma, Savita; Lohr, Gary; Chevalley, Eric;

Predictive Models of Nanotoxicity: Relationship of Physicochemical Properties to Particle Movement Through Biological Barriers

EPA Science Inventory

Understanding the linkage between the physicochemical (PC) properties of nanoparticles (NP) and their activation of biological systems is poorly understood, yet fundamental to predicting nanotoxicity, idenitifying mode of actions and developing appropriate and effective regul...

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.

Instruments for Deep Space Weather Prediction and Science

NASA Astrophysics Data System (ADS)

DeForest, C. E.; Laurent, G.

2018-02-01

We discuss remote space weather monitoring system concepts that could mount on the Deep Space Gateway and provide predictive capability for space weather events including SEP events and CME crossings, and advance heliophysics of the solar wind.

Evaluation of the synoptic and mesoscale predictive capabilities of a mesoscale atmospheric simulation system

NASA Technical Reports Server (NTRS)

Koch, S. E.; Skillman, W. C.; Kocin, P. J.; Wetzel, P. J.; Brill, K.; Keyser, D. A.; Mccumber, M. C.

1983-01-01

The overall performance characteristics of a limited area, hydrostatic, fine (52 km) mesh, primitive equation, numerical weather prediction model are determined in anticipation of satellite data assimilations with the model. The synoptic and mesoscale predictive capabilities of version 2.0 of this model, the Mesoscale Atmospheric Simulation System (MASS 2.0), were evaluated. The two part study is based on a sample of approximately thirty 12h and 24h forecasts of atmospheric flow patterns during spring and early summer. The synoptic scale evaluation results benchmark the performance of MASS 2.0 against that of an operational, synoptic scale weather prediction model, the Limited area Fine Mesh (LFM). The large sample allows for the calculation of statistically significant measures of forecast accuracy and the determination of systematic model errors. The synoptic scale benchmark is required before unsmoothed mesoscale forecast fields can be seriously considered.

Test-Analysis Correlation for Space Shuttle External Tank Foam Impacting RCC Wing Leading Edge Component Panels

NASA Technical Reports Server (NTRS)

Lyle, Karen H.

2008-01-01

The Space Shuttle Columbia Accident Investigation Board recommended that NASA develop, validate, and maintain a modeling tool capable of predicting the damage threshold for debris impacts on the Space Shuttle Reinforced Carbon-Carbon (RCC) wing leading edge and nosecap assembly. The results presented in this paper are one part of a multi-level approach that supported the development of the predictive tool used to recertify the shuttle for flight following the Columbia Accident. The assessment of predictive capability was largely based on test analysis comparisons for simpler component structures. This paper provides comparisons of finite element simulations with test data for external tank foam debris impacts onto 6-in. square RCC flat panels. Both quantitative displacement and qualitative damage assessment correlations are provided. The comparisons show good agreement and provided the Space Shuttle Program with confidence in the predictive tool.

Recent developments in analysis of crack propagation and fracture of practical materials. [stress analysis in aircraft structures

NASA Technical Reports Server (NTRS)

Hardrath, H. F.; Newman, J. C., Jr.; Elber, W.; Poe, C. C., Jr.

1978-01-01

The limitations of linear elastic fracture mechanics in aircraft design and in the study of fatigue crack propagation in aircraft structures are discussed. NASA-Langley research to extend the capabilities of fracture mechanics to predict the maximum load that can be carried by a cracked part and to deal with aircraft design problems are reported. Achievements include: (1) improved stress intensity solutions for laboratory specimens; (2) fracture criterion for practical materials; (3) crack propagation predictions that account for mean stress and high maximum stress effects; (4) crack propagation predictions for variable amplitude loading; and (5) the prediction of crack growth and residual stress in built-up structural assemblies. These capabilities are incorporated into a first generation computerized analysis that allows for damage tolerance and tradeoffs with other disciplines to produce efficient designs that meet current airworthiness requirements.

Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid

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

Etingov, Pavel; Makarov, PNNL Yuri; Subbarao, PNNL Kris

RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variablemore » resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.« less

Modeling sand wave characteristics on the Belgian Continental Shelf and in the Calais-Dover Strait

NASA Astrophysics Data System (ADS)

Cherlet, J.; Besio, G.; Blondeaux, P.; van Lancker, V.; Verfaillie, E.; Vittori, G.

2007-06-01

The capability of the model of Besio et al. (2006) to predict the main geometrical characteristics (crest orientation, wavelength,…) of tidal sand waves is tested by comparing the theoretical predictions with field data. In particular the field observations carried out by Mouchet (1990) and Van Lancker et al. (2005) along the continental shelf of Belgium are used. Additional comparisons are carried out against the field measurements described by Le Bot (2001) and Le Bot and Trenteseaux (2004) which were carried out in an adjacent region. Attention is focused on the prediction of the wavelength of the bottom forms. Indeed, the capability of a linear stability analysis to predict the occurrence of sand waves has been already tested by Hulscher and van den Brink (2001) and more recently by van der Veen et al. (2006). The obtained results show that the theoretical predictions fairly agree with field observations even though some of the comparisons suggest that the accuracy of the predictions depends on the accurate evaluation of the local current and sediment characteristics.

Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance

USGS Publications Warehouse

Loman, Zachary G.; DeLuca, William; Harrison, Daniel J.; Loftin, Cynthia S.; Rolek, Brian W.; Wood, Petra B.

2018-01-01

ContextSpecies-specific models of landscape capability (LC) can inform landscape conservation design. Landscape capability is “the ability of the landscape to provide the environment […] and the local resources […] needed for survival and reproduction […] in sufficient quantity, quality and accessibility to meet the life history requirements of individuals and local populations.” Landscape capability incorporates species’ life histories, ecologies, and distributions to model habitat for current and future landscapes and climates as a proactive strategy for conservation planning.ObjectivesWe tested the ability of a set of LC models to explain variation in point occupancy and abundance for seven bird species representative of spruce-fir, mixed conifer-hardwood, and riparian and wooded wetland macrohabitats.MethodsWe compiled point count data sets used for biological inventory, species monitoring, and field studies across the northeastern United States to create an independent validation data set. Our validation explicitly accounted for underestimation in validation data using joint distance and time removal sampling.ResultsBlackpoll warbler (Setophaga striata), wood thrush (Hylocichla mustelina), and Louisiana (Parkesia motacilla) and northern waterthrush (P. noveboracensis) models were validated as predicting variation in abundance, although this varied from not biologically meaningful (1%) to strongly meaningful (59%). We verified all seven species models [including ovenbird (Seiurus aurocapilla), blackburnian (Setophaga fusca) and cerulean warbler (Setophaga cerulea)], as all were positively related to occupancy data.ConclusionsLC models represent a useful tool for conservation planning owing to their predictive ability over a regional extent. As improved remote-sensed data become available, LC layers are updated, which will improve predictions.

A dual coaxial nanocable sulfur composite for high-rate lithium-sulfur batteries.

PubMed

Li, Zhen; Yuan, Lixia; Yi, Ziqi; Liu, Yang; Xin, Ying; Zhang, Zhaoliang; Huang, Yunhui

2014-01-01

Lithium-sulfur batteries have great potential for some high energy applications such as in electric vehicles and smart grids due to their high capacity, natural abundance, low cost and environmental friendliness. But they suffer from rapid capacity decay and poor rate capability. The problems are mainly related to the dissolution of the intermediate polysulfides in the electrolyte, and to the poor conductivity of sulfur and the discharge products. In this work, we propose a novel dual coaxial nanocable sulfur composite fabricated with multi-walled nanotubes (MWCNT), nitrogen-doped porous carbon (NPC) and polyethylene glycol (PEG), i.e. MWCNTs@S/NPC@PEG nanocable, as a cathode material for Li-S batteries. In such a coaxial structure, the middle N-doped carbon with hierarchical porous structure provides a nanosized capsule to contain and hold the sulfur particles; the inner MWCNTs and the outer PEG layer can further ensure the fast electronic transport and prevent the dissolution of the polysulfides into the electrolyte, respectively. The as-designed MWCNT@S/NPC@PEG composite shows good cycling stability and excellent rate capability. The capacity is retained at 527 mA h g(-1) at 1 C after 100 cycles, and 791 mA h g(-1) at 0.5 C and 551 mA h g(-1) at 2 C after 50 cycles. Especially, the high-rate capability is outstanding with 400 mA h g(-1) at 5 C.

Magnetic Resonance Imaging-DRAGON score: 3-month outcome prediction after intravenous thrombolysis for anterior circulation stroke.

PubMed

Turc, Guillaume; Apoil, Marion; Naggara, Olivier; Calvet, David; Lamy, Catherine; Tataru, Alina M; Méder, Jean-François; Mas, Jean-Louis; Baron, Jean-Claude; Oppenheim, Catherine; Touzé, Emmanuel

2013-05-01

The DRAGON score, which includes clinical and computed tomographic scan parameters, showed a high specificity to predict 3-month outcome in patients with acute ischemic stroke treated by intravenous tissue plasminogen activator. We adapted the score for patients undergoing MRI as the first-line diagnostic tool. We reviewed patients with consecutive anterior circulation ischemic stroke treated ≤ 4.5 hour by intravenous tissue plasminogen activator between 2003 and 2012 in our center, where MRI is systematically implemented as first-line diagnostic work-up. We derived the MRI-DRAGON score keeping all clinical parameters of computed tomography-DRAGON (age, initial National Institutes of Health Stroke Scale and glucose level, prestroke handicap, onset to treatment time), and considering the following radiological variables: proximal middle cerebral artery occlusion on MR angiography instead of hyperdense middle cerebral artery sign, and diffusion-weighted imaging Alberta Stroke Program Early Computed Tomography Score (DWI ASPECTS) ≤ 5 instead of early infarct signs on computed tomography. Poor 3-month outcome was defined as modified Rankin scale >2. We calculated c-statistics as a measure of predictive ability and performed an internal cross-validation. Two hundred twenty-eight patients were included. Poor outcome was observed in 98 (43%) patients and was significantly associated with all parameters of the MRI-DRAGON score in multivariate analysis, except for onset to treatment time (nonsignificant trend). The c-statistic was 0.83 (95% confidence interval, 0.78-0.88) for poor outcome prediction. All patients with a MRI-DRAGON score ≤ 2 (n=22) had a good outcome, whereas all patients with a score ≥ 8 (n=11) had a poor outcome. The MRI-DRAGON score is a simple tool to predict 3-month outcome in acute stroke patients screened by MRI then treated by intravenous tissue plasminogen activator and may help for therapeutic decision.

Preoperative serum C-reactive protein levels and post-operative lymph node ratio are important predictors of survival after pancreaticoduodenectomy for pancreatic ductal adenocarcinoma.

PubMed

Sanjay, Pandanaboyana; de Figueiredo, Rodrigo S; Leaver, Heather; Ogston, Simon; Kulli, Christoph; Polignano, Francesco M; Tait, Iain S

2012-03-10

There is paucity of data on the prognostic value of pre-operative inflammatory response and post-operative lymph node ratio on patient survival after pancreatic-head resection for pancreatic ductal adenocarcinoma. To evaluate the role of the preoperative inflammatory response and postoperative pathology criteria to identify predictive and/or prognostic variables for pancreatic ductal adenocarcinoma. All patients who underwent pancreaticoduodenectomy for pancreatic ductal adenocarcinoma between 2002 and 2008 were reviewed retrospectively. The following impacts on patient survival were assessed: i) preoperative serum CRP levels, white cell count, neutrophil count, neutrophil/lymphocyte ratio, lymphocyte count, platelet/lymphocyte ratio; and ii) post-operative pathology criteria including lymph node status and lymph node ratio. Fifty-one patients underwent potentially curative resection for pancreatic ductal adenocarcinoma during the study period. An elevated preoperative CRP level (greater than 3 mg/L) was found to be a significant adverse prognostic factor (P=0.015) predicting a poor survival, whereas white cell count (P=0.278), neutrophil count (P=0.850), neutrophil/lymphocyte ratio (P=0.272), platelet/lymphocyte ratio (P=0.532) and lymphocyte count (P=0.721) were not significant prognosticators at univariate analysis. Presence of metastatic lymph nodes did not adversely affect survival (P=0.050), however a raised lymph node ratio predicted poor survival at univariate analysis (P<0.001). The preoperative serum CRP level retained significance at multivariate analysis (P=0.011), together with lymph node ratio (P<0.001) and tumour size (greater than 2 cm; P=0.008). A pre-operative elevated serum CRP level and raised post-operative lymph node ratio represent significant independent prognostic factors that predict poor prognosis in patients undergoing curative resection for pancreatic ductal adenocarcinoma. There is potential for future neo-adjuvant and adjuvant treatment strategies in pancreatic cancer to be tailored based on preoperative and postoperative factors that predict a poor survival.

Intelligent Prediction of Fan Rotation Stall in Power Plants Based on Pressure Sensor Data Measured In-Situ

PubMed Central

Xu, Xiaogang; Wang, Songling; Liu, Jinlian; Liu, Xinyu

2014-01-01

Blower and exhaust fans consume over 30% of electricity in a thermal power plant, and faults of these fans due to rotation stalls are one of the most frequent reasons for power plant outage failures. To accurately predict the occurrence of fan rotation stalls, we propose a support vector regression machine (SVRM) model that predicts the fan internal pressures during operation, leaving ample time for rotation stall detection. We train the SVRM model using experimental data samples, and perform pressure data prediction using the trained SVRM model. To prove the feasibility of using the SVRM model for rotation stall prediction, we further process the predicted pressure data via wavelet-transform-based stall detection. By comparison of the detection results from the predicted and measured pressure data, we demonstrate that the SVRM model can accurately predict the fan pressure and guarantee reliable stall detection with a time advance of up to 0.0625 s. This superior pressure data prediction capability leaves significant time for effective control and prevention of fan rotation stall faults. This model has great potential for use in intelligent fan systems with stall prevention capability, which will ensure safe operation and improve the energy efficiency of power plants. PMID:24854057

Children's Negative Emotionality Combined with Poor Self-Regulation Affects Allostatic Load in Adolescence

ERIC Educational Resources Information Center

Dich, Nadya; Doan, Stacey; Evans, Gary

2015-01-01

The present study examined the concurrent and prospective, longitudinal effects of childhood negative emotionality and self-regulation on allostatic load (AL), a physiological indicator of chronic stress. We hypothesized that negative emotionality in combination with poor self-regulation would predict elevated AL. Mothers reported on children's…

Social Skills, Competence, and Drug Refusal Efficacy as Predictors of Adolescent Alcohol Use.

ERIC Educational Resources Information Center

Scheier, Lawrence M.; Botvin, Gilbert J.; Diaz, Tracy; Griffin, Kenneth W.

1999-01-01

Examines the extent to which assertiveness and related social skills, personal competence, and refusal efficacy predict alcohol involvement in adolescents. Males were at higher risk for poor refusal skills and reported higher alcohol involvement. Youth characterized by poor social skill development reported lower refusal efficacy, lower grades,…

Proteomic analysis of human follicular fluid in poor ovarian responders during in vitro fertilization.

PubMed

Oh, Jae Won; Kim, Seul Ki; Cho, Kyung-Cho; Kim, Min-Sik; Suh, Chang Suk; Lee, Jung Ryeol; Kim, Kwang Pyo

2017-03-01

Poor ovarian response (POR) in controlled ovarian stimulation is often observed during in vitro fertilization and embryo transfer cycles and it is a major problem. A POR has been found to be related to several factors, including advanced age, high body mass index, and history of ovarian or pelvic surgery. However, it is difficult to predict POR, as there are no specific biomarkers known. In this study, we used quantitative proteomic analyses to investigate potential biomarkers that can predict poor response during in vitro fertilization based on follicular fluid samples. A total of 1079 proteins were identified using a high-resolution orbitrap mass spectrometer coupled online to a nanoflow-LC system. It is notable that 65 upregulated and 66 downregulated proteins were found to be functionally enriched in poor responders. We also validated these differentially expressed proteins using a triple-quadrupole mass spectrometer for quantification of targeted proteins. Of the differentially expressed proteins, three proteins (pregnancy zone protein, renin, and sushi repeat-containing protein SRPX) were regarded as statistically significant (p < 0.05). © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improved Outcome Prediction Using CT Angiography in Addition to Standard Ischemic Stroke Assessment: Results from the STOPStroke Study

PubMed Central

González, R. Gilberto; Lev, Michael H.; Goldmacher, Gregory V.; Smith, Wade S.; Payabvash, Seyedmehdi; Harris, Gordon J.; Halpern, Elkan F.; Koroshetz, Walter J.; Camargo, Erica C. S.; Dillon, William P.; Furie, Karen L.

2012-01-01

Purpose To improve ischemic stroke outcome prediction using imaging information from a prospective cohort who received admission CT angiography (CTA). Methods In a prospectively designed study, 649 stroke patients diagnosed with acute ischemic stroke had admission NIH stroke scale scores, noncontrast CT (NCCT), CTA, and 6-month outcome assessed using the modified Rankin scale (mRS) scores. Poor outcome was defined as mRS>2. Strokes were classified as “major” by the (1) Alberta Stroke Program Early CT Score (ASPECTS+) if NCCT ASPECTS was≤7; (2) Boston Acute Stroke Imaging Scale (BASIS+) if they were ASPECTS+ or CTA showed occlusion of the distal internal carotid, proximal middle cerebral, or basilar arteries; and (3) NIHSS for scores>10. Results Of 649 patients, 253 (39.0%) had poor outcomes. NIHSS, BASIS, and age, but not ASPECTS, were independent predictors of outcome. BASIS and NIHSS had similar sensitivities, both superior to ASPECTS (p<0.0001). Combining NIHSS with BASIS was highly predictive: 77.6% (114/147) classified as NIHSS>10/BASIS+ had poor outcomes, versus 21.5% (77/358) with NIHSS≤10/BASIS− (p<0.0001), regardless of treatment. The odds ratios for poor outcome is 12.6 (95% CI: 7.9 to 20.0) in patients who are NIHSS>10/BASIS+ compared to patients who are NIHSS≤10/BASIS−; the odds ratio is 5.4 (95% CI: 3.5 to 8.5) when compared to patients who are only NIHSS>10 or BASIS+. Conclusions BASIS and NIHSS are independent outcome predictors. Their combination is stronger than either instrument alone in predicting outcomes. The findings suggest that CTA is a significant clinical tool in routine acute stroke assessment. PMID:22276182

Hyperfibrinogenemia is a poor prognostic factor in diffuse large B cell lymphoma.

PubMed

Niu, Jun-Ying; Tian, Tian; Zhu, Hua-Yuan; Liang, Jin-Hua; Wu, Wei; Cao, Lei; Lu, Rui-Nan; Wang, Li; Li, Jian-Yong; Xu, Wei

2018-06-02

Diffuse large B cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphomas worldwide. Previous studies indicated that hyperfibrinogenemia was a poor predictor in various tumors. The purpose of our study was to evaluate the prognostic effect of hyperfibrinogenemia in DLBCL. Data of 228 patients, who were diagnosed with DLBCL in our hospital between May 2009 and February 2016, were analyzed retrospectively. The Kaplan-Meier method and Cox regression were performed to find prognostic factors associated with progression-free survival (PFS) and overall survival (OS). Receiver operator characteristic (ROC) curve and the areas under the curve were used to evaluate the predictive accuracy of predictors. Comparison of characters between groups indicated that patients with high National Comprehensive Cancer Network-International Prognostic Index (NCCN-IPI) score (4-8) and advanced stage (III-IV) were more likely to suffer from hyperfibrinogenemia. The Kaplan-Meier method revealed that patients with hyperfibrinogenemia showed inferior PFS (P < 0.001) and OS (P < 0.001) than those without hyperfibrinogenemia. Multivariate analysis showed that hyperfibrinogenemia was an independent prognostic factor associated with poor outcomes (HR = 1.90, 95% CI: 1.15-3.16 for PFS, P = 0.013; HR = 2.65, 95% CI: 1.46-4.79 for OS, P = 0.001). We combined hyperfibrinogenemia and NCCN-IPI to build a new prognostic index (NPI). The NPI was demonstrated to have a superior predictive effect on prognosis (P = 0.0194 for PFS, P = 0.0034 for OS). Hyperfibrinogenemia was demonstrated to be able to predict poor outcome in DLBCL, especially for patients with advanced stage and high NCCN-IPI score. Adding hyperfibrinogenemia to NCCN-IPI could significantly improve the predictive effect of NCCN-IPI.

Baseline Assessment and Prioritization Framework for IVHM Integrity Assurance Enabling Capabilities

NASA Technical Reports Server (NTRS)

Cooper, Eric G.; DiVito, Benedetto L.; Jacklin, Stephen A.; Miner, Paul S.

2009-01-01

Fundamental to vehicle health management is the deployment of systems incorporating advanced technologies for predicting and detecting anomalous conditions in highly complex and integrated environments. Integrated structural integrity health monitoring, statistical algorithms for detection, estimation, prediction, and fusion, and diagnosis supporting adaptive control are examples of advanced technologies that present considerable verification and validation challenges. These systems necessitate interactions between physical and software-based systems that are highly networked with sensing and actuation subsystems, and incorporate technologies that are, in many respects, different from those employed in civil aviation today. A formidable barrier to deploying these advanced technologies in civil aviation is the lack of enabling verification and validation tools, methods, and technologies. The development of new verification and validation capabilities will not only enable the fielding of advanced vehicle health management systems, but will also provide new assurance capabilities for verification and validation of current generation aviation software which has been implicated in anomalous in-flight behavior. This paper describes the research focused on enabling capabilities for verification and validation underway within NASA s Integrated Vehicle Health Management project, discusses the state of the art of these capabilities, and includes a framework for prioritizing activities.

Testing the Predictive Capability of the High-Fidelity Generalized Method of Cells Using an Efficient Reformulation

NASA Technical Reports Server (NTRS)

Arnold, Steven M. (Technical Monitor); Bansal, Yogesh; Pindera, Marek-Jerzy

2004-01-01

The High-Fidelity Generalized Method of Cells is a new micromechanics model for unidirectionally reinforced periodic multiphase materials that was developed to overcome the original model's shortcomings. The high-fidelity version predicts the local stress and strain fields with dramatically greater accuracy relative to the original model through the use of a better displacement field representation. Herein, we test the high-fidelity model's predictive capability in estimating the elastic moduli of periodic composites characterized by repeating unit cells obtained by rotation of an infinite square fiber array through an angle about the fiber axis. Such repeating unit cells may contain a few or many fibers, depending on the rotation angle. In order to analyze such multi-inclusion repeating unit cells efficiently, the high-fidelity micromechanics model's framework is reformulated using the local/global stiffness matrix approach. The excellent agreement with the corresponding results obtained from the standard transformation equations confirms the new model's predictive capability for periodic composites characterized by multi-inclusion repeating unit cells lacking planes of material symmetry. Comparison of the effective moduli and local stress fields with the corresponding results obtained from the original Generalized Method of Cells dramatically highlights the original model's shortcomings for certain classes of unidirectional composites.

A subjective evaluation of synthesized STOL airplane noises

NASA Technical Reports Server (NTRS)

Powell, C. A., Jr.

1973-01-01

A magnitude-estimation experiment was conducted to evaluate the subjective annoyance of the noise generated by possible future turbofan STOL aircraft as compared to that of several current CTOL aircraft. In addition, some of the units used to scale the magnitude of aircraft noise were evaluated with respect to their applicability to STOL noise. Twenty test subjects rated their annoyance to a total of 119 noises over a range of 75 PNdb to 105 PNdb. Their subjective ratings were compared with acoustical analysis of the noises in terms of 28 rating scale units. The synthesized STOL noises of this experiment were found to be slightly more annoying than the conventional CTOL noises at equal levels of PNL and EPNL. Over the range of levels investigated the scaling units, with a few exceptions, were capable of predicting the points of equal annoyance for all of the noises with plus or minus 3 dB. The inclusion of duration corrections, in general, improved the predictive capabilities of the various scaling units; however, tone corrections reduced their predictive capabilities.

Simulation for analysis and control of superplastic forming. Final report

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

Zacharia, T.; Aramayo, G.A.; Simunovic, S.

1996-08-01

A joint study was conducted by Oak Ridge National Laboratory (ORNL) and the Pacific Northwest Laboratory (PNL) for the U.S. Department of Energy-Lightweight Materials (DOE-LWM) Program. the purpose of the study was to assess and benchmark the current modeling capabilities with respect to accuracy of predictions and simulation time. Two modeling capabilities with respect to accuracy of predictions and simulation time. Two simulation platforms were considered in this study, which included the LS-DYNA3D code installed on ORNL`s high- performance computers and the finite element code MARC used at PNL. both ORNL and PNL performed superplastic forming (SPF) analysis on amore » standard butter-tray geometry, which was defined by PNL, to better understand the capabilities of the respective models. The specific geometry was selected and formed at PNL, and the experimental results, such as forming time and thickness at specific locations, were provided for comparisons with numerical predictions. Furthermore, comparisons between the ORNL simulation results, using elasto-plastic analysis, and PNL`s results, using rigid-plastic flow analysis, were performed.« less

Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

PubMed

Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

2016-03-01

The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

A comparison of the diagnostic power of the Full Outline of Unresponsiveness scale and the Glasgow coma scale in the discharge outcome prediction of patients with traumatic brain injury admitted to the intensive care unit

PubMed Central

Gorji, Mohammad Ali Heidari; Hoseini, Seyed Hosein; Gholipur, Afshin; Mohammadpur, Reza Ali

2014-01-01

Background and Aim: This study aimed to determine whether the Full Outline of Unresponsiveness (FOUR) score is an accurate predictorof discharge outcome in traumatic brain injury (TBI) patients and to compare its performanceto Glasgow coma scale (GCS). Materials and Methods: Thisis diagnostic study conducted prospectively on 53 TBI patients admitted to ICU of education hospitals of Medical Science University of Mazandaran during February 2013 to June 2013. Data collection was done with a checklist including biographic, clinical information and outcome. The FOUR score and GCS were determined by the researcher in the first 24 hours. Outcomes considered as in-hospital mortality and poor neurologic outcome (Glasgow Outcome Scale (GOS) 1-3) in discharge time from the hospital. Results: In terms of predictive power for in-hospital mortality, the area under the receiver operating characteristic (ROC) curve was 0/92 (95% CI. 0/81-0/97) for FOUR score and 0/96 (95% CI. 0/87-0/99) for GCS. In terms of predictive power of poor neurologic outcome, the area under the ROC curve was 0/95 (95% CI. 0/86-0/99) for FOUR score and 0/90 (95% CI.0/79-0/96) for GCS as evidenced by GOS 1-3. The cut-off of 6 showed sensitivity and specificity of total four score predicting poor outcome at 0/86 and 0/87 while the cut-off of 4 showed the value of in hospital mortality at 0/90 and 0/90. The total GCS score showed sensitivity and specificity 0/100 and 0/61 at cut-off 7 in predicting poor outcome while in predicting mortality at cut-off of 4 this range was 0/100 and 0/92. Conclusion: The FOUR score is an accurate predictor of discharge outcome in TBI patients. Thus, researchers recommend for therapeutic Schematizationto use in neurosurgical patients at admission day. PMID:24843331

Blood urea nitrogen to serum creatinine ratio is an accurate predictor of outcome in diarrhea-associated hemolytic uremic syndrome, a preliminary study.

PubMed

Keenswijk, Werner; Vanmassenhove, Jill; Raes, Ann; Dhont, Evelyn; Vande Walle, Johan

2017-03-01

Diarrhea-associated hemolytic uremic syndrome (D+HUS) is a common thrombotic microangiopathy during childhood and early identification of parameters predicting poor outcome could enable timely intervention. This study aims to establish the accuracy of BUN-to-serum creatinine ratio at admission, in addition to other parameters in predicting the clinical course and outcome. Records were searched for children between 1 January 2008 and 1 January 2015 admitted with D+HUS. A complicated course was defined as developing one or more of the following: neurological dysfunction, pancreatitis, cardiac or pulmonary involvement, hemodynamic instability, and hematologic complications while poor outcome was defined by death or development of chronic kidney disease. Thirty-four children were included from which 11 with a complicated disease course/poor outcome. Risk of a complicated course/poor outcome was strongly associated with oliguria (p = 0.000006) and hypertension (p = 0.00003) at presentation. In addition, higher serum creatinine (p = 0.000006) and sLDH (p = 0.02) with lower BUN-to-serum creatinine ratio (p = 0.000007) were significantly associated with development of complications. A BUN-to-sCreatinine ratio ≤40 at admission was a sensitive and highly specific predictor of a complicated disease course/poor outcome. A BUN-to-serum Creatinine ratio can accurately identify children with D+HUS at risk for a complicated course and poor outcome. What is Known: • Oliguria is a predictor of poor long-term outcome in D+HUS What is New: • BUN-to-serum Creatinine ratio at admission is an entirely novel and accurate predictor of poor outcome and complicated clinical outcome in D+HUS • Early detection of the high risk group in D+HUS enabling early treatment and adequate monitoring.

Preschool Executive Functioning Abilities Predict Early Mathematics Achievement

ERIC Educational Resources Information Center

Clark, Caron A. C.; Pritchard, Verena E.; Woodward, Lianne J.

2010-01-01

Impairments in executive function have been documented in school-age children with mathematical learning difficulties. However, the utility and specificity of preschool executive function abilities in predicting later mathematical achievement are poorly understood. This study examined linkages between children's developing executive function…

A prospective study of personality as a predictor of quality of life after pelvic pouch surgery.

PubMed

Weinryb, R M; Gustavsson, J P; Liljeqvist, L; Poppen, B; Rössel, R J

1997-02-01

Surgeons often "know" preoperatively which patients will achieve good postoperative quality of life (QOL). This intuition is probably based on impressions of the patient's personality. The present aim was to examine whether preoperative personality traits predict postoperative QOL. In 53 patients undergoing pelvic pouch surgery for ulcerative colitis the relationship between preoperative personality traits, and surgical functional outcome and QOL was examined at a median of 17 months postoperatively. Personality assessment instruments (KAPP and KSP), and specific measures of alexithymia were used. Postoperatively, the Psychosocial Adjustment to Illness Scale (PAIS), and surgical functional outcome scales were used. Using multiple correlation/regression, analysis lack of alexithymia, poor frustration tolerance, anxiety proneness, and poor socialization (resentment over childhood and present life situation) were found to predict poor postoperative QOL. The findings suggest personality traits, in addition to surgical functional outcome, to be important for the patient's postoperative QOL.

"Wealth Makes Many Friends": Children Expect More Giving From Resource-Rich Than Resource-Poor Individuals.

PubMed

Ahl, Richard E; Dunham, Yarrow

2017-08-21

Young children show social preferences for resource-rich individuals, although few studies have explored the causes underlying such preferences. We evaluate the viability of one candidate cause: Children believe that resource wealth relates to behavior, such that they expect the resource rich to be more likely to materially benefit others (including themselves) than the resource poor. In Studies 1 and 2 (ages 4-10), American children from predominantly middle-income families (n = 94) and Indian children from lower income families (n = 30) predicted that the resource rich would be likelier to share with others than the resource poor. In Study 3, American children (n = 66) made similar predictions in an incentivized decision-making task. The possibility that children's expectations regarding giving contribute to prowealth preferences is discussed. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Altering cortical connectivity: Remediation-induced changes in the white matter of poor readers

PubMed Central

Keller, Timothy A.; Just, Marcel Adam

2009-01-01

SUMMARY Neuroimaging studies using diffusion tensor imaging (DTI) have revealed regions of cerebral white matter with decreased microstructural organization (lower fractional anisotropy or FA) among poor readers. We examined whether 100 hours of intensive remedial instruction affected the white matter of 8–10-year-old poor readers. Prior to instruction, poor readers had significantly lower FA than good readers in a region of the left anterior centrum semiovale. The instruction resulted in a change in white matter (significantly increased FA), and in the very same region. The FA increase was correlated with a decrease in radial diffusivity (but not with a change in axial diffusivity), suggesting that myelination had increased. Furthermore, the FA increase was correlated with improvement in phonological decoding ability, clarifying the cognitive locus of the effect. The results demonstrate for the first time the capability of a behavioral intervention to bring about a positive change in cortico-cortical white matter tracts. PMID:20005820

What impact do anxiety, depression, perceived control and technology capability have on whether patients with chronic heart failure take-up or continue to use home tele-monitoring services? Study design of ADaPT-HF.

PubMed

Crundall-Goode, Amanda; Goode, Kevin M; Clark, Andrew L

2017-04-01

Home tele-monitoring (HTM) is used to monitor the clinical signs and symptoms of patients with chronic heart failure (CHF) in order to reduce unplanned hospital admissions. However, not all patients who are referred will agree to use HTM, and some patients choose to withdraw early from its use. ADaPT-HF will investigate whether depression, anxiety, low perceived control, reduced technology capability, level of education, age or the severity or complexity of a patient's illness can predict refusal of, or early withdrawal from, HTM in patients with CHF. The study will recruit 288 patients who have been recently admitted to hospital with heart failure who have been referred for HTM. At the time of referral, patients will complete depression (nine-item Patient Health Questionnaire), anxiety (seven-item Generalised Anxiety Disorder questionnaire), perceived control (eight-item revised Controlled Attitudes Scale) and technology capability (ten-item Technology Readiness Index 2.0) screening questionnaires. In addition, data on demographics, diagnosis, clinical examination, socio-economic status, history of comorbidities, medication, biochemistry and haematology will be recorded. The primary outcome will be a composite of refusal of or early withdrawal from HTM. The principle analysis will be made using logistic regression. By establishing which factors influence a patient's decision to refuse or withdraw early from HTM, it may be possible to redesign HTM referral processes. It may be that patients with CHF who also have depression, anxiety, low control and poor technology skills should not be referred until they receive appropriate support or that they should be managed differently when they do receive HTM. The results of ADAPT-HF may provide a way of making more efficient and cost-effective use of HTM services.

A Search for Nitrogen-enhanced Metal-poor Stars

NASA Astrophysics Data System (ADS)

Johnson, Jennifer A.; Herwig, Falk; Beers, Timothy C.; Christlieb, Norbert

2007-04-01

Theoretical models of very metal-poor intermediate-mass asymptotic giant branch (AGB) stars predict a large overabundance of primary nitrogen. The very metal-poor, carbon-enhanced, s-process-rich stars, which are thought to be the polluted companions of now extinct AGB stars, provide direct tests of the predictions of these models. Recent studies of the carbon and nitrogen abundances in metal-poor stars have focused on the most carbon-rich stars, leading to a potential selection bias against stars that have been polluted by AGB stars that produced large amounts of nitrogen and hence have small [C/N] ratios. We call these stars nitrogen-enhanced metal-poor (NEMP) stars and define them as having [N/Fe]>+0.5 and [C/N]<-0.5. In this paper we report on the [C/N] abundances of a sample of 21 carbon-enhanced stars, all but three of which have [C/Fe]<+2.0. If NEMP stars were made as easily as carbon-enhanced metal-poor (CEMP) stars, then we expected to find between two and seven NEMP stars. Instead, we found no NEMP stars in our sample. Therefore, this observational bias is not an important contributor to the apparent dearth of N-rich stars. Our [C/N] values are in the same range as values reported previously in the literature (-0.5 to +2.0), and all stars are in disagreement with the predicted [C/N] ratios for both low- and high-mass AGB stars. We suggest that the decrease in [C/N] from the low-mass AGB models is due to enhanced extramixing, while the lack of NEMP stars may be caused by unfavorable mass ratios in binaries or the difficulty of mass transfer in binary systems with large mass ratios. Based on observations obtained at Cerro Tololo Inter-American Observatory and Kitt Peak National Observatory, a division of the National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under cooperative agreement with the National Science Foundation.

Monitoring interannual variation in global crop yield using long-term AVHRR and MODIS observations

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Zhang, Qingyuan

2016-04-01

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05° (∼5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

Chondritic models of 4 Vesta: Implications for geochemical and geophysical properties

NASA Astrophysics Data System (ADS)

Toplis, M. J.; Mizzon, H.; Monnereau, M.; Forni, O.; McSween, H. Y.; Mittlefehldt, D. W.; McCoy, T. J.; Prettyman, T. H.; De Sanctis, M. C.; Raymond, C. A.; Russell, C. T.

2013-11-01

Simple mass-balance and thermodynamic constraints are used to illustrate the potential geochemical and geophysical diversity of a fully differentiated Vesta-sized parent body with a eucrite crust (e.g., core size and density, crustal thickness). The results of this analysis are then combined with data from the howardite-eucrite-diogenite (HED) meteorites and the Dawn mission to constrain Vesta's bulk composition. Twelve chondritic compositions are considered, comprising seven carbonaceous, three ordinary, and two enstatite chondrite groups. Our analysis excludes CI and LL compositions as plausible Vesta analogs, as these are predicted to have a negative metal fraction. Second, the MELTS thermodynamic calculator is used to show that the enstatite chondrites, the CV, CK and L-groups cannot produce Juvinas-like liquids, and that even for the other groups, depletion in sodium is necessary to produce liquids of appropriate silica content. This conclusion is consistent with the documented volatile-poor nature of eucrites. Furthermore, carbonaceous chondrites are predicted to have a mantle too rich in olivine to produce typical howardites and to have Fe/Mn ratios generally well in excess of those of the HEDs. On the other hand, an Na-depleted H-chondrite bulk composition is capable of producing Juvinas-like liquids, has a mantle rich enough in pyroxene to produce abundant howardite/diogenite, and has a Fe/Mn ratio compatible with eucrites. In addition, its predicted bulk-silicate density is within 100 kg m-3 of solutions constrained by data of the Dawn mission. However, oxidation state and oxygen isotopes are not perfectly reproduced and it is deduced that bulk Vesta may contain approximately 25% of a CM-like component. Values for the bulk-silicate composition of Vesta and a preliminary phase diagram are proposed.

Evaluating Fire Risk in the Northeastern United States in the Past, Present, and Future

NASA Astrophysics Data System (ADS)

Miller, D.; Bradley, R. S.

2017-12-01

One poorly understood consequence of climate change is its effects on extreme events such as wildfires. Robust associations between wildfire frequency and climatic variability have been shown to exist, indicating that future climate change may continue to have a significant effect on wildfire activity. The Northeastern United States (NEUS) has seen some of the most infamous and largest historic fires in North America, such as the Miramichi Fire of 1825 and the fires of 1947. Although return intervals for large fires in the NEUS are long (hundreds of years), wildfires have played a critical role in ecosystem development and forest structure in the region. Understanding and predicting fire occurrence and vulnerability in the NEUS, especially in a changing climate, is economically and culturally important yet remains difficult due to human impacts (i.e. fire suppression activities and human disturbance). Thus, an alternative method for investigating fire risk in the NEUS is needed. Here, we present a compilation of meteorological data collected from Automated Surface Observing Systems (ASOS) from the NEUS throughout the 20th century through present day. We use these data to compute fifteen common "fire danger indices" employed in the USA and Canada to investigate changes in the region's fire risk over time, as well as the skill of each of these indices at predicting wildfire activity relative to the historical record of fires in the NEUS. We use dynamically-downscaled regional climate model output for the 21st century to project future wildfire activity based on the fire danger indices capable of capturing historical fire activity in the NEUS. These projections will aid in predicting how fire risk in the NEUS will evolve with anticipated climate change.

Toxico-Cheminformatics: A New Frontier for Predictive Toxicology

EPA Science Inventory

The DSSTox database network and efforts to improve public access to chemical toxicity information resources, coupled with high-throughput screening (HTS) data and efforts to systematize legacy toxicity studies, have the potential to significantly improve predictive capabilities i...

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

The long-term effects of maternal depression: early childhood physical health as a pathway to offspring depression.

PubMed

Raposa, Elizabeth; Hammen, Constance; Brennan, Patricia; Najman, Jake

2014-01-01

Cross-sectional and retrospective studies have highlighted the long-term negative effects of maternal depression on offspring physical, social, and emotional development, but longitudinal research is needed to clarify the pathways by which maternal depression during pregnancy and early childhood affects offspring outcomes. The current study tested one developmental pathway by which maternal depression during pregnancy might negatively impact offspring mental health in young adulthood, via poor physical health in early childhood. The sample consisted of 815 Australian youth and their mothers who were followed for 20 years. Mothers reported on their own depressive symptoms during pregnancy and offspring early childhood. Youth completed interviews about health-related stress and social functioning at age 20 years, and completed a questionnaire about their own depressive symptoms 2 to 5 years later. Path analysis indicated that prenatal maternal depressive symptoms predicted worse physical health during early childhood for offspring, and this effect was partially explained by ongoing maternal depression in early childhood. Offspring poor physical health during childhood predicted increased health-related stress and poor social functioning at age 20. Finally, increased health-related stress and poor social functioning predicted increased levels of depressive symptoms later in young adulthood. Maternal depression had a significant total indirect effect on youth depression via early childhood health and its psychosocial consequences. Poor physical health in early childhood and its effects on young adults' social functioning and levels of health related stress is one important pathway by which maternal depression has long-term consequences for offspring mental health. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Development of a fourth generation predictive capability maturity model.

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

Hills, Richard Guy; Witkowski, Walter R.; Urbina, Angel

2013-09-01

The Predictive Capability Maturity Model (PCMM) is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated for an intended application. The primary application of this tool at Sandia National Laboratories (SNL) has been for physics-based computational simulations in support of nuclear weapons applications. The two main goals of a PCMM evaluation are 1) the communication of computational simulation capability, accurately and transparently, and 2) the development of input for effective planning. As a result of the increasing importance of computational simulation to SNLs mission, themore » PCMM has evolved through multiple generations with the goal to provide more clarity, rigor, and completeness in its application. This report describes the approach used to develop the fourth generation of the PCMM.« less

Is the AIMS65 score useful in predicting outcomes in peptic ulcer bleeding?

PubMed

Jung, Sung Hoon; Oh, Jung Hwan; Lee, Hye Yeon; Jeong, Joon Won; Go, Se Eun; You, Chan Ran; Jeon, Eun Jung; Choi, Sang Wook

2014-02-21

To evaluate the applicability of AIMS65 scores in predicting outcomes of peptic ulcer bleeding. This was a retrospective study in a single center between January 2006 and December 2011. We enrolled 522 patients with upper gastrointestinal haemorrhage who visited the emergency room. High-risk patients were regarded as those who had re-bleeding within 30 d from the first endoscopy as well as those who died within 30 d of visiting the Emergency room. A total of 149 patients with peptic ulcer bleeding were analysed, and the AIMS65 score was used to retrospectively predict the high-risk patients. A total of 149 patients with peptic ulcer bleeding were analysed. The poor outcome group comprised 28 patients [male: 23 (82.1%) vs female: 5 (10.7%)] while the good outcome group included 121 patients [male: 93 (76.9%) vs female: 28 (23.1%)]. The mean age in each group was not significantly different. The mean serum albumin levels in the poor outcome group were slightly lower than those in the good outcome group (P = 0.072). For the prediction of poor outcome, the AIMS65 score had a sensitivity of 35.5% (95%CI: 27.0-44.8) and a specificity of 82.1% (95%CI: 63.1-93.9) at a score of 0. The AIMS65 score was insufficient for predicting outcomes in peptic ulcer bleeding (area under curve = 0.571; 95%CI: 0.49-0.65). The AIMS65 score may therefore not be suitable for predicting clinical outcomes in peptic ulcer bleeding. Low albumin levels may be a risk factor associated with high mortality in peptic ulcer bleeding.

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.

Retrospective study of long-term outcome after brain arteriovenous malformation rupture: the RAP score.

PubMed

Shotar, Eimad; Debarre, Matthieu; Sourour, Nader-Antoine; Di Maria, Federico; Gabrieli, Joseph; Nouet, Aurélien; Chiras, Jacques; Degos, Vincent; Clarençon, Frédéric

2018-01-01

OBJECTIVE The authors aimed to design a score for stratifying patients with brain arteriovenous malformation (BAVM) rupture, based on the likelihood of a poor long-term neurological outcome. METHODS The records of consecutive patients with BAVM hemorrhagic events who had been admitted over a period of 11 years were retrospectively reviewed. Independent predictors of a poor long-term outcome (modified Rankin Scale score ≥ 3) beyond 1 year after admission were identified. A risk stratification scale was developed and compared with the intracranial hemorrhage (ICH) score to predict poor outcome and inpatient mortality. RESULTS One hundred thirty-five patients with 139 independent hemorrhagic events related to BAVM rupture were included in this analysis. Multivariate logistic regression followed by stepwise analysis showed that consciousness level according to the Glasgow Coma Scale (OR 6.5, 95% CI 3.1-13.7, p < 10 -3 ), hematoma volume (OR 1.8, 95% CI 1.2-2.8, p = 0.005), and intraventricular hemorrhage (OR 7.5, 95% CI 2.66-21, p < 10 -3 ) were independently associated with a poor outcome. A 12-point scale for ruptured BAVM prognostication was constructed combining these 3 factors. The score obtained using this new scale, the ruptured AVM prognostic (RAP) score, was a stronger predictor of a poor long-term outcome (area under the receiver operating characteristic curve [AUC] 0.87, 95% CI 0.8-0.92, p = 0.009) and inpatient mortality (AUC 0.91, 95% CI 0.85-0.95, p = 0.006) than the ICH score. For a RAP score ≥ 6, sensitivity and specificity for predicting poor outcome were 76.8% (95% CI 63.6-87) and 90.8% (95% CI 81.9-96.2), respectively. CONCLUSIONS The authors propose a new admission score, the RAP score, dedicated to stratifying the risk of poor long-term outcome after BAVM rupture. This easy-to-use scoring system may help to improve communication between health care providers and consistency in clinical research. Only external prospective cohorts and population-based studies will ensure full validation of the RAP scores' capacity to predict outcome after BAVM rupture.

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.

A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric cancer agents

PubMed Central

Sánchez-Rodríguez, Aminael; Tejera, Eduardo; Cruz-Monteagudo, Maykel; Borges, Fernanda; Cordeiro, M. Natália D. S.; Le-Thi-Thu, Huong; Pham-The, Hai

2018-01-01

Gastric cancer is the third leading cause of cancer-related mortality worldwide and despite advances in prevention, diagnosis and therapy, it is still regarded as a global health concern. The efficacy of the therapies for gastric cancer is limited by a poor response to currently available therapeutic regimens. One of the reasons that may explain these poor clinical outcomes is the highly heterogeneous nature of this disease. In this sense, it is essential to discover new molecular agents capable of targeting various gastric cancer subtypes simultaneously. Here, we present a multi-objective approach for the ligand-based virtual screening discovery of chemical compounds simultaneously active against the gastric cancer cell lines AGS, NCI-N87 and SNU-1. The proposed approach relays in a novel methodology based on the development of ensemble models for the bioactivity prediction against each individual gastric cancer cell line. The methodology includes the aggregation of one ensemble per cell line using a desirability-based algorithm into virtual screening protocols. Our research leads to the proposal of a multi-targeted virtual screening protocol able to achieve high enrichment of known chemicals with anti-gastric cancer activity. Specifically, our results indicate that, using the proposed protocol, it is possible to retrieve almost 20 more times multi-targeted compounds in the first 1% of the ranked list than what is expected from a uniform distribution of the active ones in the virtual screening database. More importantly, the proposed protocol attains an outstanding initial enrichment of known multi-targeted anti-gastric cancer agents. PMID:29420638

Watershed Models for Predicting Nitrogen Loads from Artificially Drained Lands

Treesearch

R. Wayne Skaggs; George M. Chescheir; Glenn Fernandez; Devendra M. Amatya

2003-01-01

Non-point sources of pollutants originate at the field scale but water quality problems usually occur at the watershed or basin scale. This paper describes a series of models developed for poorly drained watersheds. The models use DRAINMOD to predict hydrology at the field scale and a range of methods to predict channel hydraulics and nitrogen transport. In-stream...

Using Growth Rate of Reading Fluency to Predict Performance on Statewide Achievement Tests

ERIC Educational Resources Information Center

Hinkle, Rachelle Whittaker

2011-01-01

Federal legislation has prescribed the increased use of statewide achievement tests as the culmination of a student's knowledge and ability at the end of a grade level; however, schools need to be able to predict those who are at-risk of performing poorly on these high-stakes tests. Three studies served to identify a means of predicting statewide…

Inclusive Education and Intellectual Disability: A Sociological Engagement with Martha Nussbaum

ERIC Educational Resources Information Center

Rogers, Chrissie

2013-01-01

As a result of exclusionary tactics, social, cultural or economic disadvantage or disability, vast numbers of pupils have poor educational experiences and are either marginalised or demonised due to "difficult differences". In the context of Martha Nussbaum's capabilities approach, where she suggests that we ought to be who we want to…

Bleu Ribbon Chocolates: How Can Small Businesses Adapt to a Changing Environment?

ERIC Educational Resources Information Center

Deeter-Schmelz, Dawn R.; Ramsey, Rosemary P.; Gassenheimer, Jule B.

2011-01-01

Bleu Ribbon Chocolates is a small regional manufacturer of high-quality chocolate that sells its products via trade accounts, corporate-owned stores, and online/mail. Historically, the company has not engaged in strategic planning, as demand was greater than manufacturing capabilities. The trend toward healthier foods and the poor economy,…

Poverty in People with Disabilities: Indicators from the Capability Approach

ERIC Educational Resources Information Center

Rosano, Aldo; Mancini, Federica; Solipaca, Alessandro

2009-01-01

People with disability are particularly exposed to poor living conditions: on one hand they have more difficulties in getting an income cause to their inabilities, on the other hand conditions of poverty increase the risk of disability. However, little rigorous quantitative research has been undertaken to measure the real impact of disability on…

Indigenous Child Care--Leading the Way

ERIC Educational Resources Information Center

Sims, Margaret; Saggers, Sherry; Hutchins, Teresa; Guilfoyle, Andrew; Targowska, Anna; Jackiewicz, Stephanie

2008-01-01

We believe that the Australian early childhood sector is not performing well. The incidence of poor outcomes for children is increasing, and we believe that current service delivery is not capable of addressing this. We argue that, as a sector, there is an abundance of evidence of the kinds of programs and initiatives that could address our…

A Review on Dalith Women Empowerment in India

ERIC Educational Resources Information Center

Ramaiah, Kollapudi; Nagamani, K.; Latchaiah, P.; Kishore, Mendam

2015-01-01

Empowerment is the expansion of asserts and capabilities of poor people to participate in negotiate with influence, control and hold accountable institutions that affect their lives. Education is one of the important sources of empowering women with the knowledge, skill and self confidence necessary to participate fully in the development process.…

Pre-treatment neutrophil to lymphocyte ratio as a predictive marker for pathological response to preoperative chemoradiotherapy in pancreatic cancer

PubMed Central

HASEGAWA, SHINICHIRO; EGUCHI, HIDETOSHI; TOMOKUNI, AKIRA; TOMIMARU, YOSHITO; ASAOKA, TADAFUMI; WADA, HIROSHI; HAMA, NAOKI; KAWAMOTO, KOICHI; KOBAYASHI, SHOGO; MARUBASHI, SHIGERU; KONNNO, MASAMITSU; ISHII, HIDESHI; MORI, MASAKI; DOKI, YUICHIRO; NAGANO, HIROAKI

2016-01-01

An elevated neutrophil to lymphocyte ratio (NLR) has been reported to be associated with the pathological response to neoadjuvant therapies in numerous types of cancer. The aim of the current study was to clarify the association between pre-treatment NLR and the pathological response to preoperative chemoradiotherapy in pancreatic cancer patients. This retrospective analysis included data from 56 consecutive patients whose tumors were completely surgically resected. All patients received preoperative therapy, consisting of gemcitabine-based chemotherapy (alone or in combination with S-1) combined with 40 or 50.4 Gy irradiation, prior to surgery. Predictive factors, including NLR, platelet to lymphocyte ratio (PLR), modified Glasgow prognostic score and prognostic nutrition index, were measured prior to treatment. A comparison was made between those who responded well pathologically (good response group, Evans classification IIb/III) and those with a poor response (Evans I/IIa). NLR was determined to be significantly higher in the poor response group. Multivariate analysis identified an elevated NLR as an independent risk factor for the poor pathological response [odds ratio (OR), 5.35; P=0.0257]. The pre-treatment NLR (≥2.2/<2.2) was found to be a statistically significant predictive indicator of pathological response (P=0.00699). The results demonstrate that pre-treatment NLR may be a useful predictive marker for the pathological response to preoperative therapy in pancreatic cancer patients. PMID:26893780

Subtypes of developmental dyslexia: testing the predictions of the dual-route and connectionist frameworks.

PubMed

Peterson, Robin L; Pennington, Bruce F; Olson, Richard K

2013-01-01

We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the Dual-Route Cascaded Model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg's connectionist model (HS model; Harm & Seidenberg, 1999). The regression-outlier procedure was applied to a large sample to identify children with disproportionately poor phonological coding skills (phonological dyslexia) or disproportionately poor orthographic coding skills (surface dyslexia). Consistent with the predictions of the HS model, children with "pure" phonological dyslexia, who did not have orthographic deficits, had milder phonological impairments than children with "relative" phonological dyslexia, who did have secondary orthographic deficits. In addition, pure cases of dyslexia were more common among older children. Consistent with the predictions of the DRC model, surface dyslexia was not well conceptualized as a reading delay; both phonological and surface dyslexia were associated with patterns of developmental deviance. In addition, some results were problematic for both models. We identified a small number of individuals with severe phonological dyslexia, relatively intact orthographic coding skills, and very poor real word reading. Further, a subset of controls could read normally despite impaired orthographic coding. The findings are discussed in terms of improvements to both models that might help better account for all cases of developmental dyslexia. Copyright © 2012 Elsevier B.V. All rights reserved.

Subtypes of developmental dyslexia: Testing the predictions of the dual-route and connectionist frameworks

PubMed Central

Peterson, Robin L.; Pennington, Bruce F.; Olson, Richard K.

2012-01-01

We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the dual-route cascaded model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg’s connectionist model (HS model; Harm & Seidenberg, 1999). The regression-outlier procedure was applied to a large sample to identify children with disproportionately poor phonological coding skills (phonological dyslexia) or disproportionately poor orthographic coding skills (surface dyslexia). Consistent with the predictions of the HS model, children with “pure” phonological dyslexia, who did not have orthographic deficits, had milder phonological impairments than children with “relative” phonological dyslexia, who did have secondary orthographic deficits. In addition, pure cases of dyslexia were more common among older children. Consistent with the predictions of the DRC model, surface dyslexia was not well conceptualized as a reading delay; both phonological and surface dyslexia were associated with patterns of developmental deviance. In addition, some results were problematic for both models. We identified a small number of individuals with severe phonological dyslexia, relatively intact orthographic coding skills, and very poor real word reading. Further, a subset of controls could read normally despite impaired orthographic coding. The findings are discussed in terms of improvements to both models that might help better account for all cases of developmental dyslexia. PMID:23010562

Functional outcomes of child and adolescent ODD symptoms in young adult men

PubMed Central

Burke, Jeffrey D.; Rowe, Richard; Boylan, Khrista

2013-01-01

Background ODD is considered to be a disorder of childhood, yet evidence suggests that prevalence rates of the disorder are stable into late adolescence and trajectories of symptoms persist into young adulthood. Functional outcomes associated with ODD through childhood and adolescence include conflict within families, poor peer relationships, peer rejection and academic difficulties. Little examination of functional outcomes in adulthood associated with ODD has been undertaken. Method Data for the present analyses come from a clinic referred sample of 177 boys aged 7 to 12 followed up annually to age 18 and again at age 24. Annual parental report of psychopathology through adolescence was used to predict self-reported functional outcomes at 24. Results Controlling for parent reported symptoms of ADHD, CD, depression and anxiety, ODD symptoms from childhood through adolescence predicted poorer age 24 functioning with peers, poorer romantic relationships, a poorer paternal relationship, and having nobody who would provide a recommendation for a job. CD symptoms predicted workplace problems, poor maternal relationship, lower academic attainment and violent injuries. Only parent reported ODD symptoms and child reported CD symptoms predicted a composite of poor adult outcomes. Conclusion ODD is a disorder that significantly interferes with functioning, particularly in social or interpersonal relationships. The persistence of impairment associated with ODD into young adulthood calls for a reconsideration of ODD as a disorder limited to childhood. PMID:24117754

Implications of the formation of small polarons in Li2O2 for Li-air batteries

NASA Astrophysics Data System (ADS)

Kang, Joongoo; Jung, Yoon Seok; Wei, Su-Huai; Dillon, Anne C.

2012-01-01

Lithium-air batteries (LABs) are an intriguing next-generation technology due to their high theoretical energy density of ˜11 kWh/kg. However, LABs are hindered by both poor rate capability and significant polarization in cell voltage, primarily due to the formation of Li2O2 in the air cathode. Here, by employing hybrid density functional theory, we show that the formation of small polarons in Li2O2 limits electron transport. Consequently, the low electron mobility μ = 10-10-10-9 cm2/V s contributes to both the poor rate capability and the polarization that limit the LAB power and energy densities. The self-trapping of electrons in the small polarons arises from the molecular nature of the conduction band states of Li2O2 and the strong spin polarization of the O 2p state. Our understanding of the polaronic electron transport in Li2O2 suggests that designing alternative carrier conduction paths for the cathode reaction could significantly improve the performance of LABs at high current densities.

Surface modified CF x cathode material for ultrafast discharge and high energy density

DOE PAGES

Dai, Yang; Zhu, Yimei; Cai, Sendan; ...

2014-11-10

Li/CF x primary possesses the highest energy density of 2180 W h kg⁻¹ among all primary lithium batteries. However, a key limitation for the utility of this type of battery is in its poor rate capability because the cathode material, CF x, is an intrinsically poor electronic conductor. Here, we report on our development of a controlled process of surface de-fluorination under mild hydrothermal conditions to modify the highly fluorinated CF x. The modified CF x, consisting of an in situ generated shell component of F-graphene layers, possesses good electronic conductivity and removes the transporting barrier for lithium ions, yieldingmore » a high-capacity performance and an excellent rate-capability. Indeed, a capacity of 500 mA h g⁻¹ and a maximum power density of 44 800 W kg⁻¹ can be realized at the ultrafast rate of 30 C (24 A g⁻¹), which is over one order of magnitude higher than that of the state-of-the-art primary lithium-ion batteries.« less

Application of pattern recognition techniques to crime analysis

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

Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

1976-08-15

The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

Assessment of CTAS ETA prediction capabilities

NASA Astrophysics Data System (ADS)

Bolender, Michael A.

1994-11-01

This report summarizes the work done to date in assessing the trajectory fidelity and estimated time of arrival (ETA) prediction capability of the NASA Ames Center TRACON Automation System (CTAS) software. The CTAS software suite is a series of computer programs designed to aid air traffic controllers in their tasks of safely scheduling the landing sequence of approaching aircraft. in particular, this report concerns the accuracy of the available measurements (e.g., position, altitude, etc.) that are input to the software, as well as the accuracy of the final data that is made available to the air traffic controllers.

Setting priorities for research on pollution reduction functions of agricultural buffers.

PubMed

Dosskey, Michael G

2002-11-01

The success of buffer installation initiatives and programs to reduce nonpoint source pollution of streams on agricultural lands will depend the ability of local planners to locate and design buffers for specific circumstances with substantial and predictable results. Current predictive capabilities are inadequate, and major sources of uncertainty remain. An assessment of these uncertainties cautions that there is greater risk of overestimating buffer impact than underestimating it. Priorities for future research are proposed that will lead more quickly to major advances in predictive capabilities. Highest priority is given for work on the surface runoff filtration function, which is almost universally important to the amount of pollution reduction expected from buffer installation and for which there remain major sources of uncertainty for predicting level of impact. Foremost uncertainties surround the extent and consequences of runoff flow concentration and pollutant accumulation. Other buffer functions, including filtration of groundwater nitrate and stabilization of channel erosion sources of sediments, may be important in some regions. However, uncertainty surrounds our ability to identify and quantify the extent of site conditions where buffer installation can substantially reduce stream pollution in these ways. Deficiencies in predictive models reflect gaps in experimental information as well as technology to account for spatial heterogeneity of pollutant sources, pathways, and buffer capabilities across watersheds. Since completion of a comprehensive watershed-scale buffer model is probably far off, immediate needs call for simpler techniques to gage the probable impacts of buffer installation at local scales.

Simulating urban-scale air pollutants and their predicting capabilities over the Seoul metropolitan area.

PubMed

Park, Il-Soo; Lee, Suk-Jo; Kim, Cheol-Hee; Yoo, Chul; Lee, Yong-Hee

2004-06-01

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter > or = 10 microm, and ozone (O3) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km x 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of approximately 0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.

Scaling approach in predicting the seatbelt loading and kinematics of vulnerable occupants: How far can we go?

PubMed

Nie, Bingbing; Forman, Jason L; Joodaki, Hamed; Wu, Taotao; Kent, Richard W

2016-09-01

Occupants with extreme body size and shape, such as the small female or the obese, were reported to sustain high risk of injury in motor vehicle crashes (MVCs). Dimensional scaling approaches are widely used in injury biomechanics research based on the assumption of geometrical similarity. However, its application scope has not been quantified ever since. The objective of this study is to demonstrate the valid range of scaling approaches in predicting the impact response of the occupants with focus on the vulnerable populations. The present analysis was based on a data set consisting of 60 previously reported frontal crash tests in the same sled buck representing a typical mid-size passenger car. The tests included two categories of human surrogates: 9 postmortem human surrogates (PMHS) of different anthropometries (stature range: 147-189 cm; weight range: 27-151 kg) and 5 anthropomorphic test devices (ATDs). The impact response was considered including the restraint loads and the kinematics of multiple body segments. For each category of the human surrogates, a mid-size occupant was selected as a baseline and the impact response was scaled specifically to another subject based on either the body mass (body shape) or stature (the overall body size). To identify the valid range of the scaling approach, the scaled response was compared to the experimental results using assessment scores on the peak value, peak timing (the time when the peak value occurred), and the overall curve shape ranging from 0 (extremely poor) to 1 (perfect match). Scores of 0.7 to 0.8 and 0.8 to 1.0 indicate fair and acceptable prediction. For both ATDs and PMHS, the scaling factor derived from body mass proved an overall good predictor of the peak timing for the shoulder belt (0.868, 0.829) and the lap belt (0.858, 0.774) and for the peak value of the lap belt force (0.796, 0.869). Scaled kinematics based on body stature provided fair or acceptable prediction on the overall head/shoulder kinematics (0.741, 0.822 for the head; 0.817, 0.728 for the shoulder) regardless of the anthropometry. The scaling approach exhibited poor prediction capability on the curve shape for the restraint force (0.494 and 0.546 for the shoulder belt; 0.585 and 0.530 for the lap belt). It also cannot well predict the excursion of the pelvis and the knee. The results revealed that for the peak lap belt force and the forward motion of the head and shoulder, the underlying linear relationship with body size and shape is valid over a wide anthropometric range. The chaotic nature of the dynamic response cannot be fully recovered by the assumption of the whole-body geometrical similarity, especially for the curve shape. The valid range of the scaling approach established in this study can be reasonably referenced in predicting the impact response of a given specific population with expected deviation. Application of this knowledge also includes proposing strategies for restraint configuration and providing reference for ATD and/or human body model (HBM) development for vulnerable occupants.

One-month validation of the Space Weather Modeling Framework geospace model

NASA Astrophysics Data System (ADS)

Haiducek, J. D.; Welling, D. T.; Ganushkina, N. Y.; Morley, S.; Ozturk, D. S.

2017-12-01

The Space Weather Modeling Framework (SWMF) geospace model consists of a magnetohydrodynamic (MHD) simulation coupled to an inner magnetosphere model and an ionosphere model. This provides a predictive capability for magnetopsheric dynamics, including ground-based and space-based magnetic fields, geomagnetic indices, currents and densities throughout the magnetosphere, cross-polar cap potential, and magnetopause and bow shock locations. The only inputs are solar wind parameters and F10.7 radio flux. We have conducted a rigorous validation effort consisting of a continuous simulation covering the month of January, 2005 using three different model configurations. This provides a relatively large dataset for assessment of the model's predictive capabilities. We find that the model does an excellent job of predicting the Sym-H index, and performs well at predicting Kp and CPCP during active times. Dayside magnetopause and bow shock positions are also well predicted. The model tends to over-predict Kp and CPCP during quiet times and under-predicts the magnitude of AL during disturbances. The model under-predicts the magnitude of night-side geosynchronous Bz, and over-predicts the radial distance to the flank magnetopause and bow shock. This suggests that the model over-predicts stretching of the magnetotail and the overall size of the magnetotail. With the exception of the AL index and the nightside geosynchronous magnetic field, we find the results to be insensitive to grid resolution.

BEHAVE: fire behavior prediction and fuel modeling system - BURN subsystem, Part 2

Treesearch

Patricia L. Andrews; Carolyn H. Chase

1989-01-01

This is the third publication describing the BEHAVE system of computer programs for predicting behavior of wildland fires. This publication adds the following predictive capabilities: distance firebrands are lofted ahead of a wind-driven surface fire, probabilities of firebrands igniting spot fires, scorch height of trees, and percentage of tree mortality. The system...

A mathematical model of a large open fire

NASA Technical Reports Server (NTRS)

Harsha, P. T.; Bragg, W. N.; Edelman, R. B.

1981-01-01

A mathematical model capable of predicting the detailed characteristics of large, liquid fuel, axisymmetric, pool fires is described. The predicted characteristics include spatial distributions of flame gas velocity, soot concentration and chemical specie concentrations including carbon monoxide, carbon dioxide, water, unreacted oxygen, unreacted fuel and nitrogen. Comparisons of the predictions with experimental values are also given.

Predictability of gypsy moth defoliation in central hardwoods: a validation study

Treesearch

David E. Fosbroke; Ray R., Jr. Hicks

1993-01-01

A model for predicting gypsy moth defoliation in central hardwood forests based on stand characteristics was evaluated following a 5-year outbreak in Pennsylvania and Maryland. Study area stand characteristics were similar to those of the areas used to develop the model. Comparisons are made between model predictive capability in two physiographic provinces. The tested...

Life prediction systems for critical rotating components

NASA Technical Reports Server (NTRS)

Cunningham, Susan E.

1993-01-01

With the advent of advanced materials in rotating gas turbine engine components, the methodologies for life prediction of these parts must also increase in sophistication and capability. Pratt & Whitney's view of generic requirements for composite component life prediction systems are presented, efforts underway to develop these systems are discussed, and industry participation in key areas requiring development is solicited.

Prognostic value of blood interleukin-6 in the prediction of functional outcome after stroke: a systematic review and meta-analysis.

PubMed

Bustamante, Alejandro; Sobrino, Tomás; Giralt, Dolors; García-Berrocoso, Teresa; Llombart, Victor; Ugarriza, Iratxe; Espadaler, Marc; Rodríguez, Noelia; Sudlow, Cathie; Castellanos, Mar; Smith, Craig J; Rodríguez-Yánez, Manuel; Waje-Andreassen, Ulrike; Tanne, David; Oto, Jun; Barber, Mark; Worthmann, Hans; Wartenberg, Katja E; Becker, Kyra J; Chakraborty, Baidarbhi; Oh, Seung-Hun; Whiteley, William N; Castillo, José; Montaner, Joan

2014-09-15

We aimed to quantify the association of blood interleukin-6 (IL-6) concentrations with poor outcome after stroke and its added predictive value over clinical information. Meta-analysis of 24 studies confirmed this association with a weighted mean difference of 3.443 (1.592-5.294) pg/mL, despite high heterogeneity and publication bias. Individual participant data including 4112 stroke patients showed standardized IL-6 levels in the 4th quartile were independently associated with poor outcome (OR=2.346 (1.814-3.033), p<0.0001). However, the additional predictive value of IL-6 was moderate (IDI=1.5%, NRI=5.35%). Overall these results indicate an unlikely translation of IL-6 into clinical practice for this purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

Cortical Responses to Chinese Phonemes in Preschoolers Predict Their Literacy Skills at School Age.

PubMed

Hong, Tian; Shuai, Lan; Frost, Stephen J; Landi, Nicole; Pugh, Kenneth R; Shu, Hua

2018-01-01

We investigated whether preschoolers with poor phonological awareness (PA) skills had impaired cortical basis for detecting speech feature, and whether speech perception influences future literacy outcomes in preschoolers. We recorded ERP responses to speech in 52 Chinese preschoolers. The results showed that the poor PA group processed speech changes differentially compared to control group in mismatch negativity (MMN) and late discriminative negativity (LDN). Furthermore, speech perception in kindergarten could predict literacy outcomes after literacy acquisition. These suggest that impairment in detecting speech features occurs before formal reading instruction, and that speech perception plays an important role in reading development.

Aeromechanics and Aeroacoustics Predictions of the Boeing-SMART Rotor Using Coupled-CFD/CSD Analyses

NASA Technical Reports Server (NTRS)

Bain, Jeremy; Sim, Ben W.; Sankar, Lakshmi; Brentner, Ken

2010-01-01

This paper will highlight helicopter aeromechanics and aeroacoustics prediction capabilities developed by Georgia Institute of Technology, the Pennsylvania State University, and Northern Arizona University under the Helicopter Quieting Program (HQP) sponsored by the Tactical Technology Office of the Defense Advanced Research Projects Agency (DARPA). First initiated in 2004, the goal of the HQP was to develop high fidelity, state-of-the-art computational tools for designing advanced helicopter rotors with reduced acoustic perceptibility and enhanced performance. A critical step towards achieving this objective is the development of rotorcraft prediction codes capable of assessing a wide range of helicopter configurations and operations for future rotorcraft designs. This includes novel next-generation rotor systems that incorporate innovative passive and/or active elements to meet future challenging military performance and survivability goals.

Dynamic Smagorinsky model on anisotropic grids

NASA Technical Reports Server (NTRS)

Scotti, A.; Meneveau, C.; Fatica, M.

1996-01-01

Large Eddy Simulation (LES) of complex-geometry flows often involves highly anisotropic meshes. To examine the performance of the dynamic Smagorinsky model in a controlled fashion on such grids, simulations of forced isotropic turbulence are performed using highly anisotropic discretizations. The resulting model coefficients are compared with a theoretical prediction (Scotti et al., 1993). Two extreme cases are considered: pancake-like grids, for which two directions are poorly resolved compared to the third, and pencil-like grids, where one direction is poorly resolved when compared to the other two. For pancake-like grids the dynamic model yields the results expected from the theory (increasing coefficient with increasing aspect ratio), whereas for pencil-like grids the dynamic model does not agree with the theoretical prediction (with detrimental effects only on smallest resolved scales). A possible explanation of the departure is attempted, and it is shown that the problem may be circumvented by using an isotropic test-filter at larger scales. Overall, all models considered give good large-scale results, confirming the general robustness of the dynamic and eddy-viscosity models. But in all cases, the predictions were poor for scales smaller than that of the worst resolved direction.

Disorganized attachment and inhibitory capacity: predicting externalizing problem behaviors.

PubMed

Bohlin, Gunilla; Eninger, Lilianne; Brocki, Karin Cecilia; Thorell, Lisa B

2012-04-01

The aim of the present study was to investigate whether attachment insecurity, focusing on disorganized attachment, and the executive function (EF) component of inhibition, assessed at age 5, were longitudinally related to general externalizing problem behaviors as well as to specific symptoms of ADHD and Autism spectrum disorder (ASD), and callous-unemotional (CU) traits. General externalizing problem behaviors were also measured at age 5 to allow for a developmental analysis. Outcome variables were rated by parents and teachers. The sample consisted of 65 children with an oversampling of children with high levels of externalizing behaviors. Attachment was evaluated using a story stem attachment doll play procedure. Inhibition was measured using four different tasks. The results showed that both disorganized attachment and poor inhibition were longitudinally related to all outcome variables. Controlling for initial level of externalizing problem behavior, poor inhibition predicted ADHD symptoms and externalizing problem behaviors, independent of disorganized attachment, whereas for ASD symptoms no predictive relations remained. Disorganized attachment independently predicted CU traits.

Adolescents’ Pregnancy Intentions, Wantedness, and Regret: Cross-Lagged Relations With Mental Health and Harsh Parenting

PubMed Central

East, Patricia L.; Chien, Nina C.; Barber, Jennifer S.

2011-01-01

The authors used cross-lagged analyses to examine the across-time influences on and consequences of adolescents’ pregnancy intentions, wantedness, and regret. One hundred pregnant Latina adolescents were studied during pregnancy and at 6 and 12 months postpartum. The results revealed 4 main findings: (a) similar to what has been found in adult women, adolescents’ lower prenatal pregnancy intendedness and wantedness predicted initial difficulties in parenting; (b) frequent depression symptoms predicted subsequent lower pregnancy intendedness and wantedness; (c) adolescents’ poor mental health and harsh parenting of their child predicted subsequent higher childbearing regret, and (d) high childbearing regret and parenting stress were reciprocally related across time. In addition, adolescents’ wantedness of their pregnancy declined prenatally to postbirth, and strong pregnancy intendedness and wantedness were not concurrently related to adolescents’ poor prenatal mental health. The findings reveal how adolescents’ thoughts and feelings about their pregnancies are influenced by and predictive of their mental health and parenting experiences. PMID:22544975

Mothers' depressive symptoms and children's cognitive and social agency: Predicting first-grade cognitive functioning.

PubMed

Yan, Ni; Dix, Theodore

2016-08-01

Using data from the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development (N = 1,364), the present study supports an agentic perspective; it demonstrates that mothers' depressive symptoms in infancy predict children's poor first-grade cognitive functioning because depressive symptoms predict children's low social and cognitive agency-low motivation to initiate social interaction and actively engage in activities. When mothers' depressive symptoms were high in infancy, children displayed poor first-grade cognitive functioning due to (a) tendencies to become socially withdrawn by 36 months and low in mastery motivation by 54 months and (b) tendencies for children's low agency to predict declines in mothers' sensitivity and cognitive stimulation. Findings suggest that mothers' depressive symptoms undermine cognitive development through bidirectional processes centered on children's low motivation to engage in social interaction and initiate and persist at everyday tasks. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Extending the time window for endovascular procedures according to collateral pial circulation.

PubMed

Ribo, Marc; Flores, Alan; Rubiera, Marta; Pagola, Jorge; Sargento-Freitas, Joao; Rodriguez-Luna, David; Coscojuela, Pilar; Maisterra, Olga; Piñeiro, Socorro; Romero, Francisco J; Alvarez-Sabin, Jose; Molina, Carlos A

2011-12-01

Good collateral pial circulation (CPC) predicts a favorable outcome in patients undergoing intra-arterial procedures. We aimed to determine if CPC status may be used to decide about pursuing recanalization efforts. Pial collateral score (0-5) was determined on initial angiogram. We considered good CPC when pial collateral score<3, defined total time of ischemia (TTI) as onset-to-recanalization time, and clinical improvement>4-point decline in admission-discharge National Institutes of Health Stroke Scale. We studied CPC in 61 patients (31 middle cerebral artery, 30 internal carotid artery). Good CPC patients (n=21 [34%]) had lower discharge National Institutes of Health Stroke Scale score (7 versus 21; P=0.02) and smaller infarcts (56 mL versus 238 mL; P<0.001). In poor CPC patients, a receiver operating characteristic curve defined a TTI cutoff point<300 minutes (sensitivity 67%, specificity 75%) that better predicted clinical improvement (TTI<300: 66.7% versus TTI>300: 25%; P=0.05). For good CPC patients, no temporal cutoff point could be defined. Although clinical improvement was similar for patients recanalizing within 300 minutes (poor CPC: 60% versus good CPC: 85.7%; P=0.35), the likelihood of clinical improvement was 3-fold higher after 300 minutes only in good CPC patients (23.1% versus 90.1%; P=0.01). Similarly, infarct volume was reduced 7-fold in good as compared with poor CPC patients only when TTI>300 minutes (TTI<300: poor CPC: 145 mL versus good CPC: 93 mL; P=0.56 and TTI>300: poor CPC: 217 mL versus good CPC: 33 mL; P<0.01). After adjusting for age and baseline National Institutes of Health Stroke Scale score, TTI<300 emerged as an independent predictor of clinical improvement in poor CPC patients (OR, 6.6; 95% CI, 1.01-44.3; P=0.05) but not in good CPC patients. In a logistic regression, good CPC independently predicted clinical improvement after adjusting for TTI, admission National Institutes of Health Stroke Scale score, and age (OR, 12.5; 95% CI, 1.6-74.8; P=0.016). Good CPC predicts better clinical response to intra-arterial treatment beyond 5 hours from onset. In patients with stroke receiving endovascular treatment, identification of good CPC may help physicians when considering pursuing recanalization efforts in late time windows.

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

PubMed

Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

2018-04-01

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

Frequency of RNA–RNA interaction in a model of the RNA World

PubMed Central

STRIGGLES, JOHN C.; MARTIN, MATTHEW B.; SCHMIDT, FRANCIS J.

2006-01-01

The RNA World model for prebiotic evolution posits the selection of catalytic/template RNAs from random populations. The mechanisms by which these random populations could be generated de novo are unclear. Non-enzymatic and RNA-catalyzed nucleic acid polymerizations are poorly processive, which means that the resulting short-chain RNA population could contain only limited diversity. Nonreciprocal recombination of smaller RNAs provides an alternative mechanism for the assembly of larger species with concomitantly greater structural diversity; however, the frequency of any specific recombination event in a random RNA population is limited by the low probability of an encounter between any two given molecules. This low probability could be overcome if the molecules capable of productive recombination were redundant, with many nonhomologous but functionally equivalent RNAs being present in a random population. Here we report fluctuation experiments to estimate the redundancy of the set of RNAs in a population of random sequences that are capable of non-Watson-Crick interaction with another RNA. Parallel SELEX experiments showed that at least one in 106 random 20-mers binds to the P5.1 stem–loop of Bacillus subtilis RNase P RNA with affinities equal to that of its naturally occurring partner. This high frequency predicts that a single RNA in an RNA World would encounter multiple interacting RNAs within its lifetime, supporting recombination as a plausible mechanism for prebiotic RNA evolution. The large number of equivalent species implies that the selection of any single interacting species in the RNA World would be a contingent event, i.e., one resulting from historical accident. PMID:16495233

High throughput research and evaporation rate modeling for solvent screening for ethylcellulose barrier membranes in pharmaceutical applications.

PubMed

Schoener, Cody A; Curtis-Fisk, Jaime L; Rogers, True L; Tate, Michael P

2016-10-01

Ethylcellulose is commonly dissolved in a solvent or formed into an aqueous dispersion and sprayed onto various dosage forms to form a barrier membrane to provide controlled release in pharmaceutical formulations. Due to the variety of solvents utilized in the pharmaceutical industry and the importance solvent can play on film formation and film strength it is critical to understand how solvent can influence these parameters. To systematically study a variety of solvent blends and how these solvent blends influence ethylcellulose film formation, physical and mechanical film properties and solution properties such as clarity and viscosity. Using high throughput capabilities and evaporation rate modeling, thirty-one different solvent blends composed of ethanol, isopropanol, acetone, methanol, and/or water were formulated, analyzed for viscosity and clarity, and narrowed down to four solvent blends. Brookfield viscosity, film casting, mechanical film testing and water permeation were also completed. High throughput analysis identified isopropanol/water, ethanol, ethanol/water and methanol/acetone/water as solvent blends with unique clarity and viscosity values. Evaporation rate modeling further rank ordered these candidates from excellent to poor interaction with ethylcellulose. Isopropanol/water was identified as the most suitable solvent blend for ethylcellulose due to azeotrope formation during evaporation, which resulted in a solvent-rich phase allowing the ethylcellulose polymer chains to remain maximally extended during film formation. Consequently, the highest clarity and most ductile films were formed. Employing high throughput capabilities paired with evaporation rate modeling allowed strong predictions between solvent interaction with ethylcellulose and mechanical film properties.

Elder Fraud and Financial Exploitation: Application of Routine Activity Theory.

PubMed

DeLiema, Marguerite

2017-03-10

Elder financial exploitation, committed by individuals in positions of trust, and elder fraud, committed by predatory strangers, are two forms of financial victimization that target vulnerable older adults. This study analyzes differences between fraud and financial exploitation victims and tests routine activity theory as a contextual model for victimization. Routine activity theory predicts that criminal opportunities arise when a motivated offender and suitable target meet in the absence of capable guardians. Fifty-three financial exploitation and fraud cases were sampled from an elder abuse forensic center. Data include law enforcement and caseworker investigation reports, victim medical records, perpetrator demographic information, and forensic assessments of victim health and cognitive functioning. Fraud and financial exploitation victims performed poorly on tests of cognitive functioning and financial decision making administered by a forensic neuropsychologist following the allegations. Based on retrospective record review, there were few significant differences in physical health and cognitive functioning at the time victims' assets were taken, although their social contexts were different. Significantly more fraud victims were childless compared with financial exploitation victims. Fraud perpetrators took advantage of elders when they had no trustworthy friends or relatives to safeguard their assets. Findings support an adapted routine activity theory as a contextual model for financial victimization. Fraud most often occurred when a vulnerable elder was solicited by a financial predator in the absence of capable guardians. Prevention efforts should focus on reducing social isolation to enhance protection. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Advances and Computational Tools towards Predictable Design in Biological Engineering

PubMed Central

2014-01-01

The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated. PMID:25161694

A critical evaluation of bridge scour for Michigan specific conditions

DOT National Transportation Integrated Search

2011-02-01

The overall goal of this research was to improve MDOTs bridge scour prediction capability. In : an effort to achieve this goal, the research team evaluated scour prediction methods utilized by : state DOTs, conducted a field data collection project, ...

Recent Developments in Toxico-Cheminformatics: A New Frontier for Predictive Toxicology

EPA Science Inventory

Efforts to improve public access to chemical toxicity information resources, coupled with new high-throughput screening (HTS) data and efforts to systematize legacy toxicity studies, have the potential to significantly improve predictive capabilities in toxicology. Important rec...

NASA progress in aircraft noise prediction

NASA Technical Reports Server (NTRS)

Raney, J. P.; Padula, S. L.; Zorumski, W. E.

1981-01-01

Some of the essential features of aircraft noise prediction are described and the basis for evaluating its capability and future potential is discussed. A takeoff noise optimizing procedure is described which calculates a minimum noise takeoff procedure subject to multiple site noise constraints.

Computational simulations of vocal fold vibration: Bernoulli versus Navier-Stokes.

PubMed

Decker, Gifford Z; Thomson, Scott L

2007-05-01

The use of the mechanical energy (ME) equation for fluid flow, an extension of the Bernoulli equation, to predict the aerodynamic loading on a two-dimensional finite element vocal fold model is examined. Three steady, one-dimensional ME flow models, incorporating different methods of flow separation point prediction, were compared. For two models, determination of the flow separation point was based on fixed ratios of the glottal area at separation to the minimum glottal area; for the third model, the separation point determination was based on fluid mechanics boundary layer theory. Results of flow rate, separation point, and intraglottal pressure distribution were compared with those of an unsteady, two-dimensional, finite element Navier-Stokes model. Cases were considered with a rigid glottal profile as well as with a vibrating vocal fold. For small glottal widths, the three ME flow models yielded good predictions of flow rate and intraglottal pressure distribution, but poor predictions of separation location. For larger orifice widths, the ME models were poor predictors of flow rate and intraglottal pressure, but they satisfactorily predicted separation location. For the vibrating vocal fold case, all models resulted in similar predictions of mean intraglottal pressure, maximum orifice area, and vibration frequency, but vastly different predictions of separation location and maximum flow rate.

Measurement error and timing of predictor values for multivariable risk prediction models are poorly reported.

PubMed

Whittle, Rebecca; Peat, George; Belcher, John; Collins, Gary S; Riley, Richard D

2018-05-18

Measurement error in predictor variables may threaten the validity of clinical prediction models. We sought to evaluate the possible extent of the problem. A secondary objective was to examine whether predictors are measured at the intended moment of model use. A systematic search of Medline was used to identify a sample of articles reporting the development of a clinical prediction model published in 2015. After screening according to a predefined inclusion criteria, information on predictors, strategies to control for measurement error and intended moment of model use were extracted. Susceptibility to measurement error for each predictor was classified into low and high risk. Thirty-three studies were reviewed, including 151 different predictors in the final prediction models. Fifty-one (33.7%) predictors were categorised as high risk of error, however this was not accounted for in the model development. Only 8 (24.2%) studies explicitly stated the intended moment of model use and when the predictors were measured. Reporting of measurement error and intended moment of model use is poor in prediction model studies. There is a need to identify circumstances where ignoring measurement error in prediction models is consequential and whether accounting for the error will improve the predictions. Copyright © 2018. Published by Elsevier Inc.