Molecular phylogeny, species limits, and biogeography of the Brazilian endemic lizard genus Enyalius (Squamata: Leiosauridae): an example of the historical relationship between Atlantic Forests and Amazonia.

Science.gov (United States)

Rodrigues, Miguel Trefaut; Bertolotto, Carolina Elena Viña; Amaro, Renata Cecília; Yonenaga-Yassuda, Yatiyo; Freire, Eliza Maria Xavier; Pellegrino, Katia Cristina Machado

2014-12-01

The endemic Brazilian Enyalius encompasses a diverse group of forest lizards with most species restricted to the Atlantic Forest (AF). Their taxonomy is problematic due to extensive variation in color pattern and external morphology. We present the first phylogenetic hypothesis for the genus based on 2102 bp of the mtDNA (cyt-b, ND4, and 16S) and nuclear (c-mos) regions, uncovering all previously admitted taxa (9 spp). Different methods of tree reconstruction were explored with Urostrophus vautieri, Anisolepis grilli and A. longicauda as outgroups. The monophyly of Enyalius and its split into two deeply divergent clades (late Oligocene and early Miocene) is strongly supported. Clade A assembles most lineages restricted to south and southeastern Brazil, and within it Enyalius brasiliensis is polyphyletic; herein full species status of E. brasiliensis and E. boulengeri is resurrected. Clade B unites the Amazonian E. leechii as sister-group to a major clade containing E. bilineatus as sister-group to all remaining species from northeastern Brazil. We detected unrecognized diversity in several populations suggesting putative species. Biogeographical analyses indicate that Enyalius keeps fidelity to shadowed forests, with few cases of dispersal into open regions. Ancient dispersal into the Amazon from an AF ancestor may have occurred through northeastern Brazil. Copyright © 2014 Elsevier Inc. All rights reserved.

Monitoring and predicting crop growth and analysing agricultural ecosystems by remote sensing

Directory of Open Access Journals (Sweden)

Tsuyoshi Akiyama

1996-05-01

Full Text Available LANDSAT/TM data, which are characterized by high spectral/spatial resolutions, are able to contribute to practical agricultural management. In the first part of the paper, the authors review some recent applications of satellite remote sensing in agriculture. Techniques for crop discrimination and mapping have made such rapid progress that we can classify crop types with more than 80% accuracy. The estimation of crop biomass using satellite data, including leaf area, dry and fresh weights, and the prediction of grain yield, has been attempted using various spectral vegetation indices. Plant stresses caused by nutrient deficiency and water deficit have also been analysed successfully. Such information may be useful for farm management. In the latter half of the paper, we introduce the Arctic Science Project, which was carried out under the Science and Technology Agency of Japan collaborating with Finnish scientists. In this project, monitoring of the boreal forest was carried out using LANDSAT data. Changes in the phenology of subarctic ground vegetation, based on spectral properties, were measured by a boom-mounted, four-band spectroradiometer. The turning point dates of the seasonal near-infrared (NIR and red (R reflectance factors might indicate the end of growth and the beginning of autumnal tints, respectively.

A reassessment of the taxonomic position of mesosaurs, and a surprising phylogeny of early amniotes

Science.gov (United States)

Laurin, Michel; Piñeiro, Graciela H.

2017-11-01

We reassess the phylogenetic position of mesosaurs by using a data matrix that is updated and slightly expanded from a matrix that the first author published in 1995 with his former thesis advisor. The revised matrix, which incorporates anatomical information published in the last twenty years and observations on several mesosaur specimens (mostly from Uruguay) includes seventeen terminal taxa and 129 characters (four more taxa and five more characters than the original matrix from 1995). The new matrix also differs by incorporating more ordered characters (all morphoclines were ordered). Parsimony analyses in PAUP 4 using the branch and bound algorithm show that the new matrix supports a position of mesosaurs at the very base of Sauropsida, as suggested by the first author in 1995. The exclusion of mesosaurs from a less inclusive clade of sauropsids is supported by a Bremer (Decay) index of 4 and a bootstrap frequency of 66%, both of which suggest that this result is moderately robust. The most parsimonious trees include some unexpected results, such as placing the anapsid reptile Paleothyris near the base of diapsids, and all of parareptiles as the sister-group of younginiforms (the most crownward diapsids included in the analyses). Turtles are placed among parareptiles, as the sister-group of pareiasaurs (and in diapsids, given that parareptiles are nested within diapsids). This unexpected result offers a potential solution to the long-lasting controversy about the position of turtles because previous studies viewed a position among diapsids and among parareptiles as mutually exclusive alternatives.

A Reassessment of the Taxonomic Position of Mesosaurs, and a Surprising Phylogeny of Early Amniotes

Directory of Open Access Journals (Sweden)

Michel Laurin

2017-11-01

Full Text Available We reassess the phylogenetic position of mesosaurs by using a data matrix that is updated and slightly expanded from a matrix that the first author published in 1995 with his former thesis advisor. The revised matrix, which incorporates anatomical information published in the last 20 years and observations on several mesosaur specimens (mostly from Uruguay includes 17 terminal taxa and 129 characters (four more taxa and five more characters than the original matrix from 1995. The new matrix also differs by incorporating more ordered characters (all morphoclines were ordered. Parsimony analyses in PAUP 4 using the branch and bound algorithm show that the new matrix supports a position of mesosaurs at the very base of Sauropsida, as suggested by the first author in 1995. The exclusion of mesosaurs from a less inclusive clade of sauropsids is supported by a Bremer (Decay index of 4 and a bootstrap frequency of 66%, both of which suggest that this result is moderately robust. The most parsimonious trees include some unexpected results, such as placing the anapsid reptile Paleothyris near the base of diapsids, and all of parareptiles as the sister-group of younginiforms (the most crownward diapsids included in the analyses. Turtles are placed among parareptiles, as the sister-group of pareiasaurs (and in diapsids, given that parareptiles are nested within diapsids. This unexpected result offers a potential solution to the long-lasting controversy about the position of turtles because previous studies viewed a position among diapsids and among parareptiles as mutually exclusive alternatives.

Analysing Twitter and web queries for flu trend prediction.

Science.gov (United States)

Santos, José Carlos; Matos, Sérgio

2014-05-07

Social media platforms encourage people to share diverse aspects of their daily life. Among these, shared health related information might be used to infer health status and incidence rates for specific conditions or symptoms. In this work, we present an infodemiology study that evaluates the use of Twitter messages and search engine query logs to estimate and predict the incidence rate of influenza like illness in Portugal. Based on a manually classified dataset of 2704 tweets from Portugal, we selected a set of 650 textual features to train a Naïve Bayes classifier to identify tweets mentioning flu or flu-like illness or symptoms. We obtained a precision of 0.78 and an F-measure of 0.83, based on cross validation over the complete annotated set. Furthermore, we trained a multiple linear regression model to estimate the health-monitoring data from the Influenzanet project, using as predictors the relative frequencies obtained from the tweet classification results and from query logs, and achieved a correlation ratio of 0.89 (puser-generated content have mostly focused on the english language. Our results further validate those studies and show that by changing the initial steps of data preprocessing and feature extraction and selection, the proposed approaches can be adapted to other languages. Additionally, we investigated whether the predictive model created can be applied to data from the subsequent flu season. In this case, although the prediction result was good, an initial phase to adapt the regression model could be necessary to achieve more robust results.

Thermal analyses. Information on the expected baking process; Thermische analyses. Informatie over een te verwachten bakgedrag

Energy Technology Data Exchange (ETDEWEB)

Van Wijck, H. [Stichting Technisch Centrum voor de Keramische Industrie TCKI, Velp (Netherlands)

2009-09-01

The design process and the drying process for architectural ceramics and pottery partly determine the characteristics of the final product, but the largest changes occur during the baking process. An overview is provided of the different thermal analyses and how the information from these analyses can predict the process in practice. (mk) [Dutch] Het vormgevingsproces en het droogproces voor bouwkeramische producten en aardewerk bepalen voor een deel de eigenschappen van de eindproducten, maar de grootste veranderingen treden op bij het bakproces. Een overzicht wordt gegeven van de verschillende thermische analyses en hoe de informatie uit deze analyses het in de praktijk te verwachten gedrag kan voorspellen.

Prediction of Seismic Slope Displacements by Dynamic Stick-Slip Analyses

International Nuclear Information System (INIS)

Ausilio, Ernesto; Costanzo, Antonio; Silvestri, Francesco; Tropeano, Giuseppe

2008-01-01

A good-working balance between simplicity and reliability in assessing seismic slope stability is represented by displacement-based methods, in which the effects of deformability and ductility can be either decoupled or coupled in the dynamic analyses. In this paper, a 1D lumped mass ''stick-slip'' model is developed, accounting for soil heterogeneity and non-linear behaviour, with a base sliding mechanism at a potential rupture surface. The results of the preliminary calibration show a good agreement with frequency-domain site response analysis in no-slip conditions. The comparison with rigid sliding block analyses and with the decoupled approach proves that the stick-slip procedure can result increasingly unconservative for soft soils and deep sliding depths

Semen analysis and prediction of natural conception

NARCIS (Netherlands)

Leushuis, Esther; van der Steeg, Jan Willem; Steures, Pieternel; Repping, Sjoerd; Bossuyt, Patrick M. M.; Mol, Ben Willem J.; Hompes, Peter G. A.; van der Veen, Fulco

2014-01-01

Do two semen analyses predict natural conception better than a single semen analysis and will adding the results of repeated semen analyses to a prediction model for natural pregnancy improve predictions? A second semen analysis does not add helpful information for predicting natural conception

Taxometric analyses and predictive accuracy of callous-unemotional traits regarding quality of life and behavior problems in non-conduct disorder diagnoses.

Science.gov (United States)

Herpers, Pierre C M; Klip, Helen; Rommelse, Nanda N J; Taylor, Mark J; Greven, Corina U; Buitelaar, Jan K

2017-07-01

Callous-unemotional (CU) traits have mainly been studied in relation to conduct disorder (CD), but can also occur in other disorder groups. However, it is unclear whether there is a clinically relevant cut-off value of levels of CU traits in predicting reduced quality of life (QoL) and clinical symptoms, and whether CU traits better fit a categorical (taxonic) or dimensional model. Parents of 979 youths referred to a child and adolescent psychiatric clinic rated their child's CU traits on the Inventory of Callous-Unemotional traits (ICU), QoL on the Kidscreen-27, and clinical symptoms on the Child Behavior Checklist. Experienced clinicians conferred DSM-IV-TR diagnoses of ADHD, ASD, anxiety/mood disorders and DBD-NOS/ODD. The ICU was also used to score the DSM-5 specifier 'with limited prosocial emotions' (LPE) of Conduct Disorder. Receiver operating characteristic (ROC) analyses revealed that the predictive accuracy of the ICU and LPE regarding QoL and clinical symptoms was poor to fair, and similar across diagnoses. A clinical cut-off point could not be defined. Taxometric analyses suggested that callous-unemotional traits on the ICU best reflect a dimension rather than taxon. More research is needed on the impact of CU traits on the functional adaptation, course, and response to treatment of non-CD conditions. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Occurrence of Can-SINEs and intron sequence evolution supports robust phylogeny of pinniped carnivores and their terrestrial relatives.

Science.gov (United States)

Schröder, Christiane; Bleidorn, Christoph; Hartmann, Stefanie; Tiedemann, Ralph

2009-12-15

Investigating the dog genome we found 178965 introns with a moderate length of 200-1000 bp. A screening of these sequences against 23 different repeat libraries to find insertions of short interspersed elements (SINEs) detected 45276 SINEs. Virtually all of these SINEs (98%) belong to the tRNA-derived Can-SINE family. Can-SINEs arose about 55 million years ago before Carnivora split into two basal groups, the Caniformia (dog-like carnivores) and the Feliformia (cat-like carnivores). Genome comparisons of dog and cat recovered 506 putatively informative SINE loci for caniformian phylogeny. In this study we show how to use such genome information of model organisms to research the phylogeny of related non-model species of interest. Investigating a dataset including representatives of all major caniformian lineages, we analysed 24 randomly chosen loci for 22 taxa. All loci were amplifiable and revealed 17 parsimony-informative SINE insertions. The screening for informative SINE insertions yields a large amount of sequence information, in particular of introns, which contain reliable phylogenetic information as well. A phylogenetic analysis of intron- and SINE sequence data provided a statistically robust phylogeny which is congruent with the absence/presence pattern of our SINE markers. This phylogeny strongly supports a sistergroup relationship of Musteloidea and Pinnipedia. Within Pinnipedia, we see strong support from bootstrapping and the presence of a SINE insertion for a sistergroup relationship of the walrus with the Otariidae.

Comparative and Predictive Multimedia Assessments Using Monte Carlo Uncertainty Analyses

Science.gov (United States)

Whelan, G.

2002-05-01

Multiple-pathway frameworks (sometimes referred to as multimedia models) provide a platform for combining medium-specific environmental models and databases, such that they can be utilized in a more holistic assessment of contaminant fate and transport in the environment. These frameworks provide a relatively seamless transfer of information from one model to the next and from databases to models. Within these frameworks, multiple models are linked, resulting in models that consume information from upstream models and produce information to be consumed by downstream models. The Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) is an example, which allows users to link their models to other models and databases. FRAMES is an icon-driven, site-layout platform that is an open-architecture, object-oriented system that interacts with environmental databases; helps the user construct a Conceptual Site Model that is real-world based; allows the user to choose the most appropriate models to solve simulation requirements; solves the standard risk paradigm of release transport and fate; and exposure/risk assessments to people and ecology; and presents graphical packages for analyzing results. FRAMES is specifically designed allow users to link their own models into a system, which contains models developed by others. This paper will present the use of FRAMES to evaluate potential human health exposures using real site data and realistic assumptions from sources, through the vadose and saturated zones, to exposure and risk assessment at three real-world sites, using the Multimedia Environmental Pollutant Assessment System (MEPAS), which is a multimedia model contained within FRAMES. These real-world examples use predictive and comparative approaches coupled with a Monte Carlo analysis. A predictive analysis is where models are calibrated to monitored site data, prior to the assessment, and a comparative analysis is where models are not calibrated but

Sequence analyses and 3D structure prediction of two Type III ...

African Journals Online (AJOL)

Internet

2012-04-17

Apr 17, 2012 ... analyses were performed using the sequence data of growth hormone gene (gh) ... used as a phylogenetic marker for different taxonomic ..... structural changes have been observed in some parts of ..... of spatial restraints.

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

Science.gov (United States)

Duda, David P.; Minnis, Patrick

2009-01-01

Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

The groningen longitudinal glaucoma study III. The predictive value of frequency-doubling perimetry and GDx nerve fibre analyser test results for the development of glaucomatous visual field loss

NARCIS (Netherlands)

Heeg, G. P.; Jansonius, N. M.

Purpose To investigate whether frequency-doubling perimetry (FDT) and nerve fibre analyser (GDx) test results are able to predict glaucomatous visual field loss in glaucoma suspect patients. Methods A large cohort of glaucoma suspect patients (patients with ocular hypertension or a positive family

ICE CRAWLERS (GRYLLOBLATTODEA – THE HISTORY OF THE INVESTIGATION OF A HIGHLY UNUSUAL GROUP OF INSECTS

Directory of Open Access Journals (Sweden)

Benjamin Wipfler

2014-04-01

Full Text Available Grylloblattodea are one of the most unusual groups of insects and the second smallest order. All known extant species are wingless and exhibit a remarkable preference for cold temperatures. Although their morphology was intensively investigated shortly after their discovery, the systematic position has been disputed for a long time. The placement of Grylloblattodea as sister-group to the recently described Mantophasamtodea is supported by morphological and molecular evidence. However, the relationships of this clade, Xenonomia, among the polyneopteran lineages is not clear. Transcriptome analyses, in addition to the study of winged grylloblattodean fossils, may help to clarify the position of Xenonomia and aid in the reconstruction of the “phylogenetic backbone” of Polyneoptera.

Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses

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Arthur C. Oliveira

2017-05-01

Full Text Available Target prediction is generally the first step toward recognition of bona fide microRNA (miRNA-target interactions in living cells. Several target prediction tools are now available, which use distinct criteria and stringency to provide the best set of candidate targets for a single miRNA or a subset of miRNAs. However, there are many false-negative predictions, and consensus about the optimum strategy to select and use the output information provided by the target prediction tools is lacking. We compared the performance of four tools cited in literature—TargetScan (TS, miRanda-mirSVR (MR, Pita, and RNA22 (R22, and we determined the most effective approach for analyzing target prediction data (individual, union, or intersection. For this purpose, we calculated the sensitivity, specificity, precision, and correlation of these approaches using 10 miRNAs (miR-1-3p, miR-17-5p, miR-21-5p, miR-24-3p, miR-29a-3p, miR-34a-5p, miR-124-3p, miR-125b-5p, miR-145-5p, and miR-155-5p and 1,400 genes (700 validated and 700 non-validated as targets of these miRNAs. The four tools provided a subset of high-quality predictions and returned few false-positive predictions; however, they could not identify several known true targets. We demonstrate that union of TS/MR and TS/MR/R22 enhanced the quality of in silico prediction analysis of miRNA targets. We conclude that the union rather than the intersection of the aforementioned tools is the best strategy for maximizing performance while minimizing the loss of time and resources in subsequent in vivo and in vitro experiments for functional validation of miRNA-target interactions.

Simulation, prediction, and genetic analyses of daily methane emissions in dairy cattle.

Science.gov (United States)

Yin, T; Pinent, T; Brügemann, K; Simianer, H; König, S

2015-08-01

This study presents an approach combining phenotypes from novel traits, deterministic equations from cattle nutrition, and stochastic simulation techniques from animal breeding to generate test-day methane emissions (MEm) of dairy cows. Data included test-day production traits (milk yield, fat percentage, protein percentage, milk urea nitrogen), conformation traits (wither height, hip width, body condition score), female fertility traits (days open, calving interval, stillbirth), and health traits (clinical mastitis) from 961 first lactation Brown Swiss cows kept on 41 low-input farms in Switzerland. Test-day MEm were predicted based on the traits from the current data set and 2 deterministic prediction equations, resulting in the traits labeled MEm1 and MEm2. Stochastic simulations were used to assign individual concentrate intake in dependency of farm-type specifications (requirement when calculating MEm2). Genetic parameters for MEm1 and MEm2 were estimated using random regression models. Predicted MEm had moderate heritabilities over lactation and ranged from 0.15 to 0.37, with highest heritabilities around DIM 100. Genetic correlations between MEm1 and MEm2 ranged between 0.91 and 0.94. Antagonistic genetic correlations in the range from 0.70 to 0.92 were found for the associations between MEm2 and milk yield. Genetic correlations between MEm with days open and with calving interval increased from 0.10 at the beginning to 0.90 at the end of lactation. Genetic relationships between MEm2 and stillbirth were negative (0 to -0.24) from the beginning to the peak phase of lactation. Positive genetic relationships in the range from 0.02 to 0.49 were found between MEm2 with clinical mastitis. Interpretation of genetic (co)variance components should also consider the limitations when using data generated by prediction equations. Prediction functions only describe that part of MEm which is dependent on the factors and effects included in the function. With high

Analyses and predictions of the thermodynamic properties and phase diagrams of silicate systems

Energy Technology Data Exchange (ETDEWEB)

Blander, M. (Argonne National Lab., IL (United States)); Pelton, A.; Eriksson, G. (Ecole Polytechnique, Montreal, PQ (Canada). Dept. of Metallurgy and Materials Engineering)

1992-01-01

Molten silicates are ordered solutions which can not be well represented by the usual polynomial representation of deviations from ideal solution behavior (i.e. excess free energies of mixing). An adaptation of quasichemical theory which is capable of describing the properties of ordered solutions represents the measured properties of binary silicates over broad ranges of composition and temperature. For simple silicates such as the MgO-FeO-SiO{sub 2} ternary system, in which silica is the only acid component, a combining rule generally leads to good predictions of ternary solutions from those of the binaries. In basic solutions, these predictions are consistent with those of the conformal ionic solution theory. Our results indicate that our approach could provide a potentially powerful tool for representing and predicting the properties of multicomponent molten silicates.

Analyses and predictions of the thermodynamic properties and phase diagrams of silicate systems

Energy Technology Data Exchange (ETDEWEB)

Blander, M. [Argonne National Lab., IL (United States); Pelton, A.; Eriksson, G. [Ecole Polytechnique, Montreal, PQ (Canada). Dept. of Metallurgy and Materials Engineering

1992-07-01

Molten silicates are ordered solutions which can not be well represented by the usual polynomial representation of deviations from ideal solution behavior (i.e. excess free energies of mixing). An adaptation of quasichemical theory which is capable of describing the properties of ordered solutions represents the measured properties of binary silicates over broad ranges of composition and temperature. For simple silicates such as the MgO-FeO-SiO{sub 2} ternary system, in which silica is the only acid component, a combining rule generally leads to good predictions of ternary solutions from those of the binaries. In basic solutions, these predictions are consistent with those of the conformal ionic solution theory. Our results indicate that our approach could provide a potentially powerful tool for representing and predicting the properties of multicomponent molten silicates.

Phylogenetic divergences of the true bugs (Insecta: Hemiptera: Heteroptera), with emphasis on the aquatic lineages

DEFF Research Database (Denmark)

Wang, Yan-hui; Cui, Ying; Rédei, Dávid

2016-01-01

Heteroptera are among the most diverse hemimetabolous insects. Seven infraorders have been recognized within this suborder of Hemiptera. Apart from the well-established sister-group relationship between Cimicomorpha and Pentatomomorpha (= Terheteroptera), the two terminal lineages, the relationsh...

Evaluating the Predictive Value of Growth Prediction Models

Science.gov (United States)

Murphy, Daniel L.; Gaertner, Matthew N.

2014-01-01

This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

Computational fluid dynamics analyses of lateral heat conduction, coolant azimuthal mixing and heat transfer predictions in a BR2 fuel assembly geometry

International Nuclear Information System (INIS)

Tzanos, C.P.; Dionne, B.

2011-01-01

To support the analyses related to the conversion of the BR2 core from highly-enriched (HEU) to low-enriched (LEU) fuel, the thermal-hydraulics codes PLTEMP and RELAP-3D are used to evaluate the safety margins during steady-state operation (PLTEMP), as well as after a loss-of-flow, loss-of-pressure, or a loss of coolant event (RELAP). In the 1-D PLTEMP and RELAP simulations, conduction in the azimuthal and axial directions is not accounted. The very good thermal conductivity of the cladding and the fuel meat and significant temperature gradients in the lateral directions (axial and azimuthal directions) could lead to a heat flux distribution that is significantly different than the power distribution. To evaluate the significance of the lateral heat conduction, 3-D computational fluid dynamics (CFD) simulations, using the CFD code STAR-CD, were performed. Safety margin calculations are typically performed for a hot stripe, i.e., an azimuthal region of the fuel plates/coolant channel containing the power peak. In a RELAP model, for example, a channel between two plates could be divided into a number of RELAP channels (stripes) in the azimuthal direction. In a PLTEMP model, the effect of azimuthal power peaking could be taken into account by using engineering factors. However, if the thermal mixing in the azimuthal direction of a coolant channel is significant, a stripping approach could be overly conservative by not taking into account this mixing. STAR-CD simulations were also performed to study the thermal mixing in the coolant. Section II of this document presents the results of the analyses of the lateral heat conduction and azimuthal thermal mixing in a coolant channel. Finally, PLTEMP and RELAP simulations rely on the use of correlations to determine heat transfer coefficients. Previous analyses showed that the Dittus-Boelter correlation gives significantly more conservative (lower) predictions than the correlations of Sieder-Tate and Petukhov. STAR-CD 3-D

Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses.

Science.gov (United States)

Serbus, Laura R; Rodriguez, Brian Garcia; Sharmin, Zinat; Momtaz, A J M Zehadee; Christensen, Steen

2017-06-07

The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale. Copyright © 2017 Serbus et al.

Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses

Directory of Open Access Journals (Sweden)

Laura R. Serbus

2017-06-01

Full Text Available The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale.

Intrinsic disorder in Viral Proteins Genome-Linked: experimental and predictive analyses

Directory of Open Access Journals (Sweden)

Van Dorsselaer Alain

2009-02-01

Full Text Available Abstract Background VPgs are viral proteins linked to the 5' end of some viral genomes. Interactions between several VPgs and eukaryotic translation initiation factors eIF4Es are critical for plant infection. However, VPgs are not restricted to phytoviruses, being also involved in genome replication and protein translation of several animal viruses. To date, structural data are still limited to small picornaviral VPgs. Recently three phytoviral VPgs were shown to be natively unfolded proteins. Results In this paper, we report the bacterial expression, purification and biochemical characterization of two phytoviral VPgs, namely the VPgs of Rice yellow mottle virus (RYMV, genus Sobemovirus and Lettuce mosaic virus (LMV, genus Potyvirus. Using far-UV circular dichroism and size exclusion chromatography, we show that RYMV and LMV VPgs are predominantly or partly unstructured in solution, respectively. Using several disorder predictors, we show that both proteins are predicted to possess disordered regions. We next extend theses results to 14 VPgs representative of the viral diversity. Disordered regions were predicted in all VPg sequences whatever the genus and the family. Conclusion Based on these results, we propose that intrinsic disorder is a common feature of VPgs. The functional role of intrinsic disorder is discussed in light of the biological roles of VPgs.

Predicting behavior change from persuasive messages using neural representational similarity and social network analyses.

Science.gov (United States)

Pegors, Teresa K; Tompson, Steven; O'Donnell, Matthew Brook; Falk, Emily B

2017-08-15

Neural activity in medial prefrontal cortex (MPFC), identified as engaging in self-related processing, predicts later health behavior change. However, it is unknown to what extent individual differences in neural representation of content and lived experience influence this brain-behavior relationship. We examined whether the strength of content-specific representations during persuasive messaging relates to later behavior change, and whether these relationships change as a function of individuals' social network composition. In our study, smokers viewed anti-smoking messages while undergoing fMRI and we measured changes in their smoking behavior one month later. Using representational similarity analyses, we found that the degree to which message content (i.e. health, social, or valence information) was represented in a self-related processing MPFC region was associated with later smoking behavior, with increased representations of negatively valenced (risk) information corresponding to greater message-consistent behavior change. Furthermore, the relationship between representations and behavior change depended on social network composition: smokers who had proportionally fewer smokers in their network showed increases in smoking behavior when social or health content was strongly represented in MPFC, whereas message-consistent behavior (i.e., less smoking) was more likely for those with proportionally more smokers in their social network who represented social or health consequences more strongly. These results highlight the dynamic relationship between representations in MPFC and key outcomes such as health behavior change; a complete understanding of the role of MPFC in motivation and action should take into account individual differences in neural representation of stimulus attributes and social context variables such as social network composition. Copyright © 2017 Elsevier Inc. All rights reserved.

Factors predicting the development of pressure ulcers in an at-risk population who receive standardized preventive care: secondary analyses of a multicentre randomised controlled trial.

Science.gov (United States)

Demarre, Liesbet; Verhaeghe, Sofie; Van Hecke, Ann; Clays, Els; Grypdonck, Maria; Beeckman, Dimitri

2015-02-01

To identify predictive factors associated with the development of pressure ulcers in patients at risk who receive standardized preventive care. Numerous studies have examined factors that predict risk for pressure ulcer development. Only a few studies identified risk factors associated with pressure ulcer development in hospitalized patients receiving standardized preventive care. Secondary analyses of data collected in a multicentre randomized controlled trial. The sample consisted of 610 consecutive patients at risk for pressure ulcer development (Braden Score Pressure ulcers in category II-IV were significantly associated with non-blanchable erythema, urogenital disorders and higher body temperature. Predictive factors significantly associated with superficial pressure ulcers were admission to an internal medicine ward, incontinence-associated dermatitis, non-blanchable erythema and a lower Braden score. Superficial sacral pressure ulcers were significantly associated with incontinence-associated dermatitis. Despite the standardized preventive measures they received, hospitalized patients with non-blanchable erythema, urogenital disorders and a higher body temperature were at increased risk for developing pressure ulcers. Improved identification of at-risk patients can be achieved by taking into account specific predictive factors. Even if preventive measures are in place, continuous assessment and tailoring of interventions is necessary in all patients at risk. Daily skin observation can be used to continuously monitor the effectiveness of the intervention. © 2014 John Wiley & Sons Ltd.

Prediction, Regression and Critical Realism

DEFF Research Database (Denmark)

Næss, Petter

2004-01-01

This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

Science.gov (United States)

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

DMINDA: an integrated web server for DNA motif identification and analyses.

Science.gov (United States)

Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

2014-07-01

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Severe accident recriticality analyses (SARA)

DEFF Research Database (Denmark)

Frid, W.; Højerup, C.F.; Lindholm, I.

2001-01-01

with all three codes. The core initial and boundary conditions prior to recriticality have been studied with the severe accident codes SCDAP/RELAP5, MELCOR and MAAP4. The results of the analyses show that all three codes predict recriticality-both super-prompt power bursts and quasi steady-state power......Recriticality in a BWR during reflooding of an overheated partly degraded core, i.e. with relocated control rods, has been studied for a total loss of electric power accident scenario. In order to assess the impact of recriticality on reactor safety, including accident management strategies......, which results in large energy deposition in the fuel during power burst in some accident scenarios. The highest value, 418 cal g(-1), was obtained with SIMULATE-3K for an Oskarshamn 3 case with reflooding rate of 2000 kg s(-1). In most cases, however, the predicted energy deposition was smaller, below...

Genomic organization and phylogenetic utility of deer mouse (Peromyscus maniculatus lymphotoxin-alpha and lymphotoxin-beta

Directory of Open Access Journals (Sweden)

Prescott Joseph

2008-10-01

Full Text Available Abstract Background Deer mice (Peromyscus maniculatus are among the most common mammals in North America and are important reservoirs of several human pathogens, including Sin Nombre hantavirus (SNV. SNV can establish a life-long apathogenic infection in deer mice, which can shed virus in excrement for transmission to humans. Patients that die from hantavirus cardiopulmonary syndrome (HCPS have been found to express several proinflammatory cytokines, including lymphotoxin (LT, in the lungs. It is thought that these cytokines contribute to the pathogenesis of HCPS. LT is not expressed by virus-specific CD4+ T cells from infected deer mice, suggesting a limited role for this pathway in reservoir responses to hantaviruses. Results We have cloned the genes encoding deer mouse LTα and LTβ and have found them to be highly similar to orthologous rodent sequences but with some differences in promoters elements. The phylogenetic analyses performed on the LTα, LTβ, and combined data sets yielded a strongly-supported sister-group relationship between the two murines (the house mouse and the rat. The deer mouse, a sigmodontine, appeared as the sister group to the murine clade in all of the analyses. High bootstrap values characterized the grouping of murids. Conclusion No conspicuous differences compared to other species are present in the predicted amino acid sequences of LTα or LTβ; however, some promoter differences were noted in LTβ. Although more extensive taxonomic sampling is required to confirm the results of our analyses, the preliminary findings indicate that both genes (analyzed both separately and in combination hold potential for resolving relationships among rodents and other mammals at the subfamily level.

Prothrombin time is predictive of low plasma prothrombin concentration and clinical outcome in patients with trauma hemorrhage: analyses of prospective observational cohort studies.

Science.gov (United States)

Balendran, Clare A; Lövgren, Ann; Hansson, Kenny M; Nelander, Karin; Olsson, Marita; Johansson, Karin J; Brohi, Karim; Fries, Dietmar; Berggren, Anders

2017-03-14

Fibrinogen and prothrombin have been suggested to become rate limiting in trauma associated coagulopathy. Administration of fibrinogen is now recommended, however, the importance of prothrombin to patient outcome is unknown. We have utilized two trauma patient databases (database 1 n = 358 and database 2 n = 331) to investigate the relationship of plasma prothrombin concentration on clinical outcome and coagulation status. Database 1 has been used to assess the relationship of plasma prothrombin to administered packed red blood cells (PRBC), clinical outcome and coagulation biomarkers (Prothrombin Time (PT), ROTEM EXTEM Coagulation Time (CT) and Maximum Clot Firmness (MCF)). ROC analyses have been performed to investigate the ability of admission coagulation biomarkers to predict low prothrombin concentration (database 1), massive transfusion and 24 h mortality (database 1 and 2). The importance of prothrombin was further investigated in vitro by PT and ROTEM assays in the presence of a prothrombin neutralizing monoclonal antibody and following step-wise dilution. Patients who survived the first 24 h had higher admission prothrombin levels compared to those who died (94 vs.67 IU/dL). Patients with lower transfusion requirements within the first 24 h (≤10 units of PRBCs) also had higher admission prothrombin levels compared to patients with massive transfusion demands (>10 units of PRBCs) (95 vs.62 IU/dL). Admission PT, in comparison to admission ROTEM EXTEM CT and MCF, was found to be a better predictor of prothrombin concentration <60 IU/dL (AUC 0.94 in database 1), of massive transfusion (AUC 0.92 and 0.81 in database 1 and 2 respectively) and 24 h mortality (AUC 0.90 and 0.78 in database 1 and 2, respectively). In vitro experiments supported a critical role for prothrombin in coagulation and demonstrated that PT and ROTEM EXTEM CT are sensitive methods to measure low prothrombin concentration. Our analyses suggest that prothrombin concentration

Analyses and characterization of double shell tank

Energy Technology Data Exchange (ETDEWEB)

1994-10-04

Evaporator candidate feed from tank 241-AP-108 (108-AP) was sampled under prescribed protocol. Physical, inorganic, and radiochemical analyses were performed on tank 108-AP. Characterization of evaporator feed tank waste is needed primarily for an evaluation of its suitability to be safely processed through the evaporator. Such analyses should provide sufficient information regarding the waste composition to confidently determine whether constituent concentrations are within not only safe operating limits, but should also be relevant to functional limits for operation of the evaporator. Characterization of tank constituent concentrations should provide data which enable a prediction of where the types and amounts of environmentally hazardous waste are likely to occur in the evaporator product streams.

Analyses and characterization of double shell tank

International Nuclear Information System (INIS)

1994-01-01

Evaporator candidate feed from tank 241-AP-108 (108-AP) was sampled under prescribed protocol. Physical, inorganic, and radiochemical analyses were performed on tank 108-AP. Characterization of evaporator feed tank waste is needed primarily for an evaluation of its suitability to be safely processed through the evaporator. Such analyses should provide sufficient information regarding the waste composition to confidently determine whether constituent concentrations are within not only safe operating limits, but should also be relevant to functional limits for operation of the evaporator. Characterization of tank constituent concentrations should provide data which enable a prediction of where the types and amounts of environmentally hazardous waste are likely to occur in the evaporator product streams

Influence of the Human Skin Tumor Type in Photodynamic Therapy Analysed by a Predictive Model

Directory of Open Access Journals (Sweden)

I. Salas-García

2012-01-01

Full Text Available Photodynamic Therapy (PDT modeling allows the prediction of the treatment results depending on the lesion properties, the photosensitizer distribution, or the optical source characteristics. We employ a predictive PDT model and apply it to different skin tumors. It takes into account optical radiation distribution, a nonhomogeneous topical photosensitizer spatial temporal distribution, and the time-dependent photochemical interaction. The predicted singlet oxygen molecular concentrations with varying optical irradiance are compared and could be directly related with the necrosis area. The results show a strong dependence on the particular lesion. This suggests the need to design optimal PDT treatment protocols adapted to the specific patient and lesion.

Castor-1C spent fuel storage cask decay heat, heat transfer, and shielding analyses

International Nuclear Information System (INIS)

Rector, D.R.; McCann, R.A.; Jenquin, U.P.; Heeb, C.M.; Creer, J.M.; Wheeler, C.L.

1986-12-01

This report documents the decay heat, heat transfer, and shielding analyses of the Gesellschaft fuer Nuklear Services (GNS) CASTOR-1C cask used in a spent fuel storage demonstration performed at Preussen Elektra's Wurgassen nuclear power plant. The demonstration was performed between March 1982 and January 1984, and resulted in cask and fuel temperature data and cask exterior surface gamma-ray and neutron radiation dose rate measurements. The purpose of the analyses reported here was to evaluate decay heat, heat transfer, and shielding computer codes. The analyses consisted of (1) performing pre-look predictions (predictions performed before the analysts were provided the test data), (2) comparing ORIGEN2 (decay heat), COBRA-SFS and HYDRA (heat transfer), and QAD and DOT (shielding) results to data, and (3) performing post-test analyses if appropriate. Even though two heat transfer codes were used to predict CASTOR-1C cask test data, no attempt was made to compare the two codes. The codes are being evaluated with other test data (single-assembly data and other cask data), and to compare the codes based on one set of data may be premature and lead to erroneous conclusions

Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent.

Directory of Open Access Journals (Sweden)

Yan Guo

2016-08-01

Full Text Available Observational epidemiological studies have shown that high body mass index (BMI is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors.We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC (cases  =  46,325, controls  =  42,482. We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively.In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]  =  0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 × 10-10. The associations were similar for both premenopausal (OR   =   0.44, 95% CI:0.31-0.62, p  =  9.91 × 10-8 and postmenopausal breast cancer (OR  =  0.57, 95% CI: 0.46-0.71, p  =  1.88 × 10-8. This association was replicated in the data from the DRIVE consortium (OR  =  0.72, 95% CI: 0.60-0.84, p   =   1.64 × 10-7. Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs in association with breast cancer risk at p < 0.05; for 16 of them, the

Uncertainty and Sensitivity Analyses Plan

International Nuclear Information System (INIS)

Simpson, J.C.; Ramsdell, J.V. Jr.

1993-04-01

Hanford Environmental Dose Reconstruction (HEDR) Project staff are developing mathematical models to be used to estimate the radiation dose that individuals may have received as a result of emissions since 1944 from the US Department of Energy's (DOE) Hanford Site near Richland, Washington. An uncertainty and sensitivity analyses plan is essential to understand and interpret the predictions from these mathematical models. This is especially true in the case of the HEDR models where the values of many parameters are unknown. This plan gives a thorough documentation of the uncertainty and hierarchical sensitivity analysis methods recommended for use on all HEDR mathematical models. The documentation includes both technical definitions and examples. In addition, an extensive demonstration of the uncertainty and sensitivity analysis process is provided using actual results from the Hanford Environmental Dose Reconstruction Integrated Codes (HEDRIC). This demonstration shows how the approaches used in the recommended plan can be adapted for all dose predictions in the HEDR Project

The mitochondrial genome of Paraspadella gotoi is highly reduced and reveals that chaetognaths are a sister-group to protostomes

Energy Technology Data Exchange (ETDEWEB)

Helfenbein, Kevin G.; Fourcade, H. Matthew; Vanjani, Rohit G.; Boore, Jeffrey L.

2004-05-01

We report the first complete mitochondrial (mt) DNA sequence from a member of the phylum Chaetognatha (arrow worms). The Paraspadella gotoi mtDNA is highly unusual, missing 23 of the genes commonly found in animal mtDNAs, including atp6, which has otherwise been found universally to be present. Its 14 genes are unusually arranged into two groups, one on each strand. One group is punctuated by numerous non-coding intergenic nucleotides, while the other group is tightly packed, having no non-coding nucleotides, leading to speculation that there are two transcription units with differing modes of expression. The phylogenetic position of the Chaetognatha within the Metazoa has long been uncertain, with conflicting or equivocal results from various morphological analyses and rRNA sequence comparisons. Comparisons here of amino acid sequences from mitochondrially encoded proteins gives a single most parsimonious tree that supports a position of Chaetognatha as sister to the protostomes studied here. From this, one can more clearly interpret the patterns of evolution of various developmental features, especially regarding the embryological fate of the blastopore.

Identifying null meta-analyses that are ripe for updating

Directory of Open Access Journals (Sweden)

Fang Manchun

2003-07-01

Full Text Available Abstract Background As an increasingly large number of meta-analyses are published, quantitative methods are needed to help clinicians and systematic review teams determine when meta-analyses are not up to date. Methods We propose new methods for determining when non-significant meta-analytic results might be overturned, based on a prediction of the number of participants required in new studies. To guide decision making, we introduce the "new participant ratio", the ratio of the actual number of participants in new studies to the predicted number required to obtain statistical significance. A simulation study was conducted to study the performance of our methods and a real meta-analysis provides further evidence. Results In our three simulation configurations, our diagnostic test for determining whether a meta-analysis is out of date had sensitivity of 55%, 62%, and 49% with corresponding specificity of 85%, 80%, and 90% respectively. Conclusions Simulations suggest that our methods are able to detect out-of-date meta-analyses. These quick and approximate methods show promise for use by systematic review teams to help decide whether to commit the considerable resources required to update a meta-analysis. Further investigation and evaluation of the methods is required before they can be recommended for general use.

Analyses of cavitation instabilities in ductile metals

DEFF Research Database (Denmark)

Tvergaard, Viggo

2007-01-01

Cavitation instabilities have been predicted for a single void in a ductile metal stressed under high triaxiality conditions. In experiments for a ceramic reinforced by metal particles a single dominant void has been observed on the fracture surface of some of the metal particles bridging a crack......, and also tests for a thin ductile metal layer bonding two ceramic blocks have indicated rapid void growth. Analyses for these material configurations are discussed here. When the void radius is very small, a nonlocal plasticity model is needed to account for observed size-effects, and recent analyses......, while the surrounding voids are represented by a porous ductile material model in terms of a field quantity that specifies the variation of the void volume fraction in the surrounding metal....

Analyses of bundle experiment data using MATRA-h

Energy Technology Data Exchange (ETDEWEB)

Lim, In Cheol; Chea, Hee Taek [Korea Atomic Energy Research Institute, Taejon (Korea)

1998-06-01

When the construction and operation license for HANARO was renewed in 1995, 25% of CHF penalty was imposed. The reason for this was that the validation work related to the CHF design calculation was not enough for the assurance of CHF margin. As a part of the works to recover this CHF penalty, MATRA-h was developed by implementing the new correlations for the heat transfer, CHF prediction, subcooled void to the MATRA-a, which is the modified version of COBRA-IV-I done by KAERI. Using MATRA-h, the subchannel analyses for the bundle experiment data were performed. The comparison of the code predictions with the experimental results, it was found that the code would give the conservative predictions as far as the CHF in the bundle geometry is concerned. (author). 12 refs., 25 figs., 16 tabs.

Safety analyses of the nuclear-powered ship Mutsu with RETRAN

International Nuclear Information System (INIS)

Naruko, Y.; Ishida, T.; Tanaka, Y.; Futamura, Y.

1982-01-01

To provide a quantitative basis for the safety evaluation of the N.S. Mutsu, a number of safety analyses were performed in the course of reexamination. With respect to operational transient analyses, the RETRAN computer code was used to predict plant performances on the basis of postulated transient scenarios. The COBRA-IV computer code was also used to obtain a value of the minimum DNBR for each transient, which is necessary to predict detailed thermal-hydraulic performances in the core region of the reactor. In the present paper, the following three operational transients, which were calculated as a part of the safety analyses, are being dealt with: a complete loss of load without reactor scram; an excessive load increase incident, which is followed by a 30 percent stepwise load increase in the steam dump flow; and an accidental depressurization of the primary system, which is followed by a sudden full opening of the pressurizer spray valve. A Mutsu two-loop RETRAN model and simulation results were described. The results being compared with those of land-based PWRs, the characteristic features of the Mutsu reactor were presented and the safety of the plant under the operational transient conditions was confirmed

Analysing power for neutron-proton scattering at 14.1 MeV

International Nuclear Information System (INIS)

Brock, J.E.; Chisholm, A.; Duder, J.C.; Garrett, R.; Poletti, J.L.

1981-01-01

The analysing power Asub(y)(theta) for neutron-proton scattering has been measured at 14.1 MeV for c.m. angles between 50 0 and 157 0 . A polarized neutron beam was produced by the reaction 3 H(d,n) 4 He at 110 keV, using polarized deuterons from an atomic beam polarized ion source. Liquid and plastic scintillators were used for proton targets and the scattered particles were detected in an array of platic scintillators. Use of the associated alpha technique, multi-parameter recording of events and off-line computer treatment led to very low backgrounds. The results differ significantly from the predictions of the phase-shift analyses of Yale IV, Livermore X and Arndt et al. We find, however, excellent agreement with the predictions of the Paris potential of Lacombe et al. Existing n-p analysing power results up to 30 MeV are surveyed and found to be consistent. An attempt was made to look for an isospin splitting of the triplet P-wave phase shifts. (orig.)

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

Science.gov (United States)

Duda, David P.; Minnis, Patrick

2009-01-01

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Diagnostic Comparison of Meteorological Analyses during the 2002 Antarctic Winter

Science.gov (United States)

Manney, Gloria L.; Allen, Douglas R.; Kruger, Kirstin; Naujokat, Barbara; Santee, Michelle L.; Sabutis, Joseph L.; Pawson, Steven; Swinbank, Richard; Randall, Cora E.; Simmons, Adrian J.;

Analysing the Relevance of Experience Partitions to the Prediction of Players’ Self-Reports of Affect

DEFF Research Database (Denmark)

Martínez, Héctor Pérez; Yannakakis, Georgios N.

2011-01-01

A common practice in modeling affect from physiological signals consists of reducing the signals to a set of statistical features that feed predictors of self-reported emotions. This paper analyses the impact of various time-windows, used for the extraction of physiological features, to the accur......A common practice in modeling affect from physiological signals consists of reducing the signals to a set of statistical features that feed predictors of self-reported emotions. This paper analyses the impact of various time-windows, used for the extraction of physiological features...

Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models.

Science.gov (United States)

Alden, Kieran; Timmis, Jon; Andrews, Paul S; Veiga-Fernandes, Henrique; Coles, Mark

2017-01-01

Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here, we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behavior exhibited by a computational model at various simulated time-points, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve- hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.

Tooth width predictions in a sample of Black South Africans.

Science.gov (United States)

Khan, M I; Seedat, A K; Hlongwa, P

2007-07-01

Space analysis during the mixed dentition requires prediction of the mesiodistal widths of the unerupted permanent canines and premolars and prediction tables and equations may be used for this purpose. The Tanaka and Johnston prediction equations, which were derived from a North American White sample, is one example which is widely used. This prediction equation may be inapplicable to other race groups due to racial tooth size variability. Therefore the purpose of this study was to derive prediction equations that would be applicable to Black South African subjects. One hundred and ten pre-treatment study casts of Black South African subjects were analysed from the Department of Orthodontics' records at the University of Limpopo. The sample was equally divided by gender with all subjects having Class I molar relationship and relatively well aligned teeth. The mesiodistal widths of the maxillary and mandibular canines and premolars were measured with a digital vernier calliper and compared with the measurements predicted with the Tanaka and Johnston equations. The relationship between the measured and predicted values were analysed by correlation and regression analyses. The results indicated that the Tanaka and Johnston prediction equations were not fully applicable to the Black South African sample. The equations tended to underpredict the male sample, while slight overprediction was observed in the female sample. Therefore, new equations were formulated and proposed that would be accurate for Black subjects.

The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

Science.gov (United States)

Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

2015-05-01

A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

Comparative transcriptome analyses of three medicinal Forsythia species and prediction of candidate genes involved in secondary metabolisms.

Science.gov (United States)

Sun, Luchao; Rai, Amit; Rai, Megha; Nakamura, Michimi; Kawano, Noriaki; Yoshimatsu, Kayo; Suzuki, Hideyuki; Kawahara, Nobuo; Saito, Kazuki; Yamazaki, Mami

2018-05-07

The three Forsythia species, F. suspensa, F. viridissima and F. koreana, have been used as herbal medicines in China, Japan and Korea for centuries and they are known to be rich sources of numerous pharmaceutical metabolites, forsythin, forsythoside A, arctigenin, rutin and other phenolic compounds. In this study, de novo transcriptome sequencing and assembly was performed on these species. Using leaf and flower tissues of F. suspensa, F. viridissima and F. koreana, 1.28-2.45-Gbp sequences of Illumina based pair-end reads were obtained and assembled into 81,913, 88,491 and 69,458 unigenes, respectively. Classification of the annotated unigenes in gene ontology terms and KEGG pathways was used to compare the transcriptome of three Forsythia species. The expression analysis of orthologous genes across all three species showed the expression in leaf tissues being highly correlated. The candidate genes presumably involved in the biosynthetic pathway of lignans and phenylethanoid glycosides were screened as co-expressed genes. They express highly in the leaves of F. viridissima and F. koreana. Furthermore, the three unigenes annotated as acyltransferase were predicted to be associated with the biosynthesis of acteoside and forsythoside A from the expression pattern and phylogenetic analysis. This study is the first report on comparative transcriptome analyses of medicinally important Forsythia genus and will serve as an important resource to facilitate further studies on biosynthesis and regulation of therapeutic compounds in Forsythia species.

Is the extremely rare Iberian endemic plant species Castrilanthemum debeauxii (Compositae, Anthemideae) a 'living fossil'? Evidence from a multi-locus species tree reconstruction.

Science.gov (United States)

Tomasello, Salvatore; Álvarez, Inés; Vargas, Pablo; Oberprieler, Christoph

2015-01-01

The present study provides results of multi-species coalescent species tree analyses of DNA sequences sampled from multiple nuclear and plastid regions to infer the phylogenetic relationships among the members of the subtribe Leucanthemopsidinae (Compositae, Anthemideae), to which besides the annual Castrilanthemum debeauxii (Degen, Hervier & É.Rev.) Vogt & Oberp., one of the rarest flowering plant species of the Iberian Peninsula, two other unispecific genera (Hymenostemma, Prolongoa), and the polyploidy complex of the genus Leucanthemopsis belong. Based on sequence information from two single- to low-copy nuclear regions (C16, D35, characterised by Chapman et al. (2007)), the multi-copy region of the nrDNA internal transcribed spacer regions ITS1 and ITS2, and two intergenic spacer regions of the cpDNA gene trees were reconstructed using Bayesian inference methods. For the reconstruction of a multi-locus species tree we applied three different methods: (a) analysis of concatenated sequences using Bayesian inference (MrBayes), (b) a tree reconciliation approach by minimizing the number of deep coalescences (PhyloNet), and (c) a coalescent-based species-tree method in a Bayesian framework ((∗)BEAST). All three species tree reconstruction methods unequivocally support the close relationship of the subtribe with the hitherto unclassified genus Phalacrocarpum, the sister-group relationship of Castrilanthemum with the three remaining genera of the subtribe, and the further sister-group relationship of the clade of Hymenostemma+Prolongoa with a monophyletic genus Leucanthemopsis. Dating of the (∗)BEAST phylogeny supports the long-lasting (Early Miocene, 15-22Ma) taxonomical independence and the switch from the plesiomorphic perennial to the apomorphic annual life-form assumed for the Castrilanthemum lineage that may have occurred not earlier than in the Pliocene (3Ma) when the establishment of a Mediterranean climate with summer droughts triggered evolution towards

An Extremely Peramorphic Newt (Urodela: Salamandridae: Pleurodelini) from the Latest Oligocene of Germany, and a New Phylogenetic Analysis of Extant and Extinct Salamandrids.

Science.gov (United States)

Marjanović, David; Witzmann, Florian

2015-01-01

We describe an Oligocene newt specimen from western Germany that has gone practically unnoticed in the literature despite having been housed in the Museum für Naturkunde (Berlin) for a century. It is referable to the coeval Chelotriton, but is unusually peramorphic; for many characters it is more peramorphic than all other caudates or even all other lissamphibians. Most noticeable are the position of the jaw joints far caudal to the occiput, the honeycombed sculpture on the maxilla, and the possible presence of a septomaxilla (which would be unique among salamandrids). Referral to a species would require a revision of the genus, but the specimen likely does not belong to the type species. A phylogenetic analysis of nonmolecular characters of Salamandridae, far larger than all predecessors, confirms the referral to Chelotriton. It further loosely associates the Oligocene Archaeotriton and the Miocene Carpathotriton with the extant Lissotriton, though the former may alternatively lie outside Pleurodelinae altogether. The Miocene? I. randeckensis may not belong to the extant Ichthyosaura. The Miocene "Triturus" roehrsi is found neither with the extant Ommatotriton nor with Lissotriton, but inside an Asian/aquatic clade or, when geographic distribution is included as a character, as the sister-group to all other European molgins. The main cause for discrepancies between the results and the molecular consensus is not heterochrony, but adaptations to a life in mountain streams; this is the most likely reason why the Paleocene Koalliella from western Europe forms the sister-group to some or all of the most aquatic extant newts in different analyses. We would like to urge neontologists working on salamandrids to pay renewed attention to the skeleton, not limited to the skull, as a source of diagnostic and phylogenetically informative characters.

An Extremely Peramorphic Newt (Urodela: Salamandridae: Pleurodelini from the Latest Oligocene of Germany, and a New Phylogenetic Analysis of Extant and Extinct Salamandrids.

Directory of Open Access Journals (Sweden)

David Marjanović

Full Text Available We describe an Oligocene newt specimen from western Germany that has gone practically unnoticed in the literature despite having been housed in the Museum für Naturkunde (Berlin for a century. It is referable to the coeval Chelotriton, but is unusually peramorphic; for many characters it is more peramorphic than all other caudates or even all other lissamphibians. Most noticeable are the position of the jaw joints far caudal to the occiput, the honeycombed sculpture on the maxilla, and the possible presence of a septomaxilla (which would be unique among salamandrids. Referral to a species would require a revision of the genus, but the specimen likely does not belong to the type species. A phylogenetic analysis of nonmolecular characters of Salamandridae, far larger than all predecessors, confirms the referral to Chelotriton. It further loosely associates the Oligocene Archaeotriton and the Miocene Carpathotriton with the extant Lissotriton, though the former may alternatively lie outside Pleurodelinae altogether. The Miocene? I. randeckensis may not belong to the extant Ichthyosaura. The Miocene "Triturus" roehrsi is found neither with the extant Ommatotriton nor with Lissotriton, but inside an Asian/aquatic clade or, when geographic distribution is included as a character, as the sister-group to all other European molgins. The main cause for discrepancies between the results and the molecular consensus is not heterochrony, but adaptations to a life in mountain streams; this is the most likely reason why the Paleocene Koalliella from western Europe forms the sister-group to some or all of the most aquatic extant newts in different analyses. We would like to urge neontologists working on salamandrids to pay renewed attention to the skeleton, not limited to the skull, as a source of diagnostic and phylogenetically informative characters.

Improved phylogenomic taxon sampling noticeably affects nonbilaterian relationships.

Science.gov (United States)

Pick, K S; Philippe, H; Schreiber, F; Erpenbeck, D; Jackson, D J; Wrede, P; Wiens, M; Alié, A; Morgenstern, B; Manuel, M; Wörheide, G

2010-09-01

Despite expanding data sets and advances in phylogenomic methods, deep-level metazoan relationships remain highly controversial. Recent phylogenomic analyses depart from classical concepts in recovering ctenophores as the earliest branching metazoan taxon and propose a sister-group relationship between sponges and cnidarians (e.g., Dunn CW, Hejnol A, Matus DQ, et al. (18 co-authors). 2008. Broad phylogenomic sampling improves resolution of the animal tree of life. Nature 452:745-749). Here, we argue that these results are artifacts stemming from insufficient taxon sampling and long-branch attraction (LBA). By increasing taxon sampling from previously unsampled nonbilaterians and using an identical gene set to that reported by Dunn et al., we recover monophyletic Porifera as the sister group to all other Metazoa. This suggests that the basal position of the fast-evolving Ctenophora proposed by Dunn et al. was due to LBA and that broad taxon sampling is of fundamental importance to metazoan phylogenomic analyses. Additionally, saturation in the Dunn et al. character set is comparatively high, possibly contributing to the poor support for some nonbilaterian nodes.

Prediction methods environmental-effect reporting

International Nuclear Information System (INIS)

Jonker, R.J.; Koester, H.W.

1987-12-01

This report provides a survey of prediction methods which can be applied to the calculation of emissions in cuclear-reactor accidents, in the framework of environment-effect reports (dutch m.e.r.) or risk analyses. Also emissions during normal operation are important for m.e.r.. These can be derived from measured emissions of power plants being in operation. Data concerning the latter are reported. The report consists of an introduction into reactor technology, among which a description of some reactor types, the corresponding fuel cycle and dismantling scenarios - a discussion of risk-analyses for nuclear power plants and the physical processes which can play a role during accidents - a discussion of prediction methods to be employed and the expected developments in this area - some background information. (aughor). 145 refs.; 21 figs.; 20 tabs

[Methods, challenges and opportunities for big data analyses of microbiome].

Science.gov (United States)

Sheng, Hua-Fang; Zhou, Hong-Wei

2015-07-01

Microbiome is a novel research field related with a variety of chronic inflamatory diseases. Technically, there are two major approaches to analysis of microbiome: metataxonome by sequencing the 16S rRNA variable tags, and metagenome by shot-gun sequencing of the total microbial (mainly bacterial) genome mixture. The 16S rRNA sequencing analyses pipeline includes sequence quality control, diversity analyses, taxonomy and statistics; metagenome analyses further includes gene annotation and functional analyses. With the development of the sequencing techniques, the cost of sequencing will decrease, and big data analyses will become the central task. Data standardization, accumulation, modeling and disease prediction are crucial for future exploit of these data. Meanwhile, the information property in these data, and the functional verification with culture-dependent and culture-independent experiments remain the focus in future research. Studies of human microbiome will bring a better understanding of the relations between the human body and the microbiome, especially in the context of disease diagnosis and therapy, which promise rich research opportunities.

Analyses of hypothetical FCI's in a fast reactor

International Nuclear Information System (INIS)

Padilla, A. Jr.; Martin, F.J.; Niccoli, L.G.

1981-01-01

Parametric analyses using the SIMMER code were performed to evaluate the potential for a severe recriticality from a pressure-driven recompaction caused by an energetic FCI during the transition phase of a hypothetical accident in a fast reactor. For realistic and reasonable estimates for the assumed accident conditions, a severe recriticality was not predicted. The conditions under which a severe recriticality would be obtained or averted were identified. 10 figures, 2 tables

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability: SSD Plot Diagrams

Science.gov (United States)

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

Summary of dynamic analyses of the advanced neutron source reactor inner control rods

International Nuclear Information System (INIS)

Hendrich, W.R.

1995-08-01

A summary of the structural dynamic analyses that were instrumental in providing design guidance to the Advanced Neutron source (ANS) inner control element system is presented in this report. The structural analyses and the functional constraints that required certain performance parameters were combined to shape and guide the design effort toward a prediction of successful and reliable control and scram operation to be provided by these inner control rods

MCNP benchmark analyses of critical experiments for space nuclear thermal propulsion

International Nuclear Information System (INIS)

Selcow, E.C.; Cerbone, R.J.; Ludewig, H.

1993-01-01

The particle-bed reactor (PBR) system is being developed for use in the Space Nuclear Thermal Propulsion (SNTP) Program. This reactor system is characterized by a highly heterogeneous, compact configuration with many streaming pathways. The neutronics analyses performed for this system must be able to accurately predict reactor criticality, kinetics parameters, material worths at various temperatures, feedback coefficients, and detailed fission power and heating distributions. The latter includes coupled axial, radial, and azimuthal profiles. These responses constitute critical inputs and interfaces with the thermal-hydraulics design and safety analyses of the system

Refining Prediction in Treatment-Resistant Depression: Results of Machine Learning Analyses in the TRD III Sample.

Science.gov (United States)

Kautzky, Alexander; Dold, Markus; Bartova, Lucie; Spies, Marie; Vanicek, Thomas; Souery, Daniel; Montgomery, Stuart; Mendlewicz, Julien; Zohar, Joseph; Fabbri, Chiara; Serretti, Alessandro; Lanzenberger, Rupert; Kasper, Siegfried

The study objective was to generate a prediction model for treatment-resistant depression (TRD) using machine learning featuring a large set of 47 clinical and sociodemographic predictors of treatment outcome. 552 Patients diagnosed with major depressive disorder (MDD) according to DSM-IV criteria were enrolled between 2011 and 2016. TRD was defined as failure to reach response to antidepressant treatment, characterized by a Montgomery-Asberg Depression Rating Scale (MADRS) score below 22 after at least 2 antidepressant trials of adequate length and dosage were administered. RandomForest (RF) was used for predicting treatment outcome phenotypes in a 10-fold cross-validation. The full model with 47 predictors yielded an accuracy of 75.0%. When the number of predictors was reduced to 15, accuracies between 67.6% and 71.0% were attained for different test sets. The most informative predictors of treatment outcome were baseline MADRS score for the current episode; impairment of family, social, and work life; the timespan between first and last depressive episode; severity; suicidal risk; age; body mass index; and the number of lifetime depressive episodes as well as lifetime duration of hospitalization. With the application of the machine learning algorithm RF, an efficient prediction model with an accuracy of 75.0% for forecasting treatment outcome could be generated, thus surpassing the predictive capabilities of clinical evaluation. We also supply a simplified algorithm of 15 easily collected clinical and sociodemographic predictors that can be obtained within approximately 10 minutes, which reached an accuracy of 70.6%. Thus, we are confident that our model will be validated within other samples to advance an accurate prediction model fit for clinical usage in TRD. © Copyright 2017 Physicians Postgraduate Press, Inc.

MCNP benchmark analyses of critical experiments for the Space Nuclear Thermal Propulsion program

International Nuclear Information System (INIS)

Selcow, E.C.; Cerbone, R.J.; Ludewig, H.; Mughabghab, S.F.; Schmidt, E.; Todosow, M.; Parma, E.J.; Ball, R.M.; Hoovler, G.S.

1993-01-01

Benchmark analyses have been performed of Particle Bed Reactor (PBR) critical experiments (CX) using the MCNP radiation transport code. The experiments have been conducted at the Sandia National Laboratory reactor facility in support of the Space Nuclear Thermal Propulsion (SNTP) program. The test reactor is a nineteen element water moderated and reflected thermal system. A series of integral experiments have been carried out to test the capabilities of the radiation transport codes to predict the performance of PBR systems. MCNP was selected as the preferred radiation analysis tool for the benchmark experiments. Comparison between experimental and calculational results indicate close agreement. This paper describes the analyses of benchmark experiments designed to quantify the accuracy of the MCNP radiation transport code for predicting the performance characteristics of PBR reactors

MCNP benchmark analyses of critical experiments for the Space Nuclear Thermal Propulsion program

Science.gov (United States)

Selcow, Elizabeth C.; Cerbone, Ralph J.; Ludewig, Hans; Mughabghab, Said F.; Schmidt, Eldon; Todosow, Michael; Parma, Edward J.; Ball, Russell M.; Hoovler, Gary S.

1993-01-01

Benchmark analyses have been performed of Particle Bed Reactor (PBR) critical experiments (CX) using the MCNP radiation transport code. The experiments have been conducted at the Sandia National Laboratory reactor facility in support of the Space Nuclear Thermal Propulsion (SNTP) program. The test reactor is a nineteen element water moderated and reflected thermal system. A series of integral experiments have been carried out to test the capabilities of the radiation transport codes to predict the performance of PBR systems. MCNP was selected as the preferred radiation analysis tool for the benchmark experiments. Comparison between experimental and calculational results indicate close agreement. This paper describes the analyses of benchmark experiments designed to quantify the accuracy of the MCNP radiation transport code for predicting the performance characteristics of PBR reactors.

Analysing earthquake slip models with the spatial prediction comparison test

KAUST Repository

Zhang, L.; Mai, Paul Martin; Thingbaijam, Kiran Kumar; Razafindrakoto, H. N. T.; Genton, Marc G.

2014-01-01

Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.

Analysing earthquake slip models with the spatial prediction comparison test

KAUST Repository

Zhang, L.

2014-11-10

Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.

Thermal and hydraulic analyses of the System 81 cold traps

Energy Technology Data Exchange (ETDEWEB)

Kim, K.

1977-06-15

Thermal and hydraulic analyses of the System 81 Type I and II cold traps were completed except for thermal transients analysis. Results are evaluated, discussed, and reported. Analytical models were developed to determine the physical dimensions of the cold traps and to predict the performance. The FFTF cold trap crystallizer performances were simulated using the thermal model. This simulation shows that the analytical model developed predicts reasonably conservative temperatures. Pressure drop and sodium residence time calculations indicate that the present design will meet the requirements specified in the E-Specification. Steady state temperature data for the critical regions were generated to assess the magnitude of the thermal stress.

Analyses of containment structures with corrosion damage

International Nuclear Information System (INIS)

Cherry, J.L.

1997-01-01

Corrosion damage that has been found in a number of nuclear power plant containment structures can degrade the pressure capacity of the vessel. This has prompted concerns regarding the capacity of corroded containments to withstand accident loadings. To address these concerns, finite element analyses have been performed for a typical PWR Ice Condenser containment structure. Using ABAQUS, the pressure capacity was calculated for a typical vessel with no corrosion damage. Multiple analyses were then performed with the location of the corrosion and the amount of corrosion varied in each analysis. Using a strain-based failure criterion, a open-quotes lower boundclose quotes, open-quotes best estimateclose quotes, and open-quotes upper boundclose quotes failure level was predicted for each case. These limits were established by: determining the amount of variability that exists in material properties of typical containments, estimating the amount of uncertainty associated with the level of modeling detail and modeling assumptions, and estimating the effect of corrosion on the material properties

Model-Based Recursive Partitioning for Subgroup Analyses.

Science.gov (United States)

Seibold, Heidi; Zeileis, Achim; Hothorn, Torsten

2016-05-01

The identification of patient subgroups with differential treatment effects is the first step towards individualised treatments. A current draft guideline by the EMA discusses potentials and problems in subgroup analyses and formulated challenges to the development of appropriate statistical procedures for the data-driven identification of patient subgroups. We introduce model-based recursive partitioning as a procedure for the automated detection of patient subgroups that are identifiable by predictive factors. The method starts with a model for the overall treatment effect as defined for the primary analysis in the study protocol and uses measures for detecting parameter instabilities in this treatment effect. The procedure produces a segmented model with differential treatment parameters corresponding to each patient subgroup. The subgroups are linked to predictive factors by means of a decision tree. The method is applied to the search for subgroups of patients suffering from amyotrophic lateral sclerosis that differ with respect to their Riluzole treatment effect, the only currently approved drug for this disease.

Connecting clinical and actuarial prediction with rule-based methods

NARCIS (Netherlands)

Fokkema, M.; Smits, N.; Kelderman, H.; Penninx, B.W.J.H.

2015-01-01

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction

Prediction of cereal feed value using spectroscopy and chemometrics

DEFF Research Database (Denmark)

Jørgensen, Johannes Ravn; Gislum, René

2009-01-01

of EDOM, EDOMi, FEso and FEsv. The outcome of a successful NIRS calibration will be a relatively cheap tool to monitor, diversify and evaluate the quality of cereals for animal feed, a possible tool to assess the feed value of new varieties in the variety testing and a useful, cheap and rapid tool...... for cereal breeders. A collection of 1213 grain samples of wheat, triticale, barley and rye, and related chemical reference analyses to describe the feed value have been established. The samples originate from available field trials over a three-year period. The chemical reference analyses are dry matter...... value, the prediction error has to be compared with the error in the chemical analysis. Prediction error by NIRS prediction of feed value is above the error of the chemical measurement. The conclusion is that it is possible to predict the feed value in cereals with NIRS quickly and cheaply...

Sea surface temperature predictions using a multi-ocean analysis ensemble scheme

Science.gov (United States)

Zhang, Ying; Zhu, Jieshun; Li, Zhongxian; Chen, Haishan; Zeng, Gang

2017-08-01

This study examined the global sea surface temperature (SST) predictions by a so-called multiple-ocean analysis ensemble (MAE) initialization method which was applied in the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2). Different from most operational climate prediction practices which are initialized by a specific ocean analysis system, the MAE method is based on multiple ocean analyses. In the paper, the MAE method was first justified by analyzing the ocean temperature variability in four ocean analyses which all are/were applied for operational climate predictions either at the European Centre for Medium-range Weather Forecasts or at NCEP. It was found that these systems exhibit substantial uncertainties in estimating the ocean states, especially at the deep layers. Further, a set of MAE hindcasts was conducted based on the four ocean analyses with CFSv2, starting from each April during 1982-2007. The MAE hindcasts were verified against a subset of hindcasts from the NCEP CFS Reanalysis and Reforecast (CFSRR) Project. Comparisons suggested that MAE shows better SST predictions than CFSRR over most regions where ocean dynamics plays a vital role in SST evolutions, such as the El Niño and Atlantic Niño regions. Furthermore, significant improvements were also found in summer precipitation predictions over the equatorial eastern Pacific and Atlantic oceans, for which the local SST prediction improvements should be responsible. The prediction improvements by MAE imply a problem for most current climate predictions which are based on a specific ocean analysis system. That is, their predictions would drift towards states biased by errors inherent in their ocean initialization system, and thus have large prediction errors. In contrast, MAE arguably has an advantage by sampling such structural uncertainties, and could efficiently cancel these errors out in their predictions.

TRAC analyses for CCTF and SCTF tests and UPTF design/operation

International Nuclear Information System (INIS)

Williams, K.A.

1983-01-01

The 2D/3D Program is a multinational (Germany, Japan, and the United States) experimental and analytical nuclear reactor safety research program. The Los Alamos analysis effort is functioning as a vital part of the 2D/3D program. The CCTF and SCTF analyses have demonstrated that TRAC-PF1 can correctly predict multidimensional, nonequilibrium behavior in large-scale facilities prototypical of actual PWR's. Through these and future TRAC analyses the experimental findings can be related from facility to facility, and the results of this research program can be directly related to licensing concerns affecting actual PWR's

Prediction of pork quality parameters by applying fractals and data mining on MRI

DEFF Research Database (Denmark)

Caballero, Daniel; Pérez-Palacios, Trinidad; Caro, Andrés

2017-01-01

This work firstly investigates the use of MRI, fractal algorithms and data mining techniques to determine pork quality parameters non-destructively. The main objective was to evaluate the capability of fractal algorithms (Classical Fractal algorithm, CFA; Fractal Texture Algorithm, FTA and One...... Point Fractal Texture Algorithm, OPFTA) to analyse MRI in order to predict quality parameters of loin. In addition, the effect of the sequence acquisition of MRI (Gradient echo, GE; Spin echo, SE and Turbo 3D, T3D) and the predictive technique of data mining (Isotonic regression, IR and Multiple linear...... regression, MLR) were analysed. Both fractal algorithm, FTA and OPFTA are appropriate to analyse MRI of loins. The sequence acquisition, the fractal algorithm and the data mining technique seems to influence on the prediction results. For most physico-chemical parameters, prediction equations with moderate...

Prediction model to predict critical weight loss in patients with head and neck cancer during (chemo)radiotherapy.

Science.gov (United States)

Langius, Jacqueline A E; Twisk, Jos; Kampman, Martine; Doornaert, Patricia; Kramer, Mark H H; Weijs, Peter J M; Leemans, C René

2016-01-01

Patients with head and neck cancer (HNC) frequently encounter weight loss with multiple negative outcomes as a consequence. Adequate treatment is best achieved by early identification of patients at risk for critical weight loss. The objective of this study was to detect predictive factors for critical weight loss in patients with HNC receiving (chemo)radiotherapy ((C)RT). In this cohort study, 910 patients with HNC were included receiving RT (±surgery/concurrent chemotherapy) with curative intent. Body weight was measured at the start and end of (C)RT. Logistic regression and classification and regression tree (CART) analyses were used to analyse predictive factors for critical weight loss (defined as >5%) during (C)RT. Possible predictors included gender, age, WHO performance status, tumour location, TNM classification, treatment modality, RT technique (three-dimensional conformal RT (3D-RT) vs intensity-modulated RT (IMRT)), total dose on the primary tumour and RT on the elective or macroscopic lymph nodes. At the end of (C)RT, mean weight loss was 5.1±4.9%. Fifty percent of patients had critical weight loss during (C)RT. The main predictors for critical weight loss during (C)RT by both logistic and CART analyses were RT on the lymph nodes, higher RT dose on the primary tumour, receiving 3D-RT instead of IMRT, and younger age. Critical weight loss during (C)RT was prevalent in half of HNC patients. To predict critical weight loss, a practical prediction tree for adequate nutritional advice was developed, including the risk factors RT to the neck, higher RT dose, 3D-RT, and younger age. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of neural networks and its prospect. 4. Prediction of major disruptions in tokamak plasmas, analyses of time series data

International Nuclear Information System (INIS)

Yoshino, Ryuji

2006-01-01

Disruption prediction of tokamak plasma has been studied by neural network. The disruption prediction performances by neural network are estimated by the prediction success rate, false alarm rate, and time prior to disruption. The current driving type disruption is predicted by time series data, and plasma lifetime, risk of disruption and plasma stability. Some disruptions generated by density limit, impurity mixture, error magnetic field can be predicted 100 % of prediction success rate by the premonitory symptoms. The pressure driving type disruption phenomena generate some hundred micro seconds before, so that the operation limits such as β N limit of DIII-D and density limit of ADITYA were investigated. The false alarm rate was decreased by β N limit training under stable discharge. The pressure driving disruption generated with increasing plasma pressure can be predicted about 90 % by evaluating plasma stability. (S.Y.)

Statistical and extra-statistical considerations in differential item functioning analyses

Directory of Open Access Journals (Sweden)

G. K. Huysamen

2004-10-01

Full Text Available This article briefly describes the main procedures for performing differential item functioning (DIF analyses and points out some of the statistical and extra-statistical implications of these methods. Research findings on the sources of DIF, including those associated with translated tests, are reviewed. As DIF analyses are oblivious of correlations between a test and relevant criteria, the elimination of differentially functioning items does not necessarily improve predictive validity or reduce any predictive bias. The implications of the results of past DIF research for test development in the multilingual and multi-cultural South African society are considered. Opsomming Hierdie artikel beskryf kortliks die hoofprosedures vir die ontleding van differensiële itemfunksionering (DIF en verwys na sommige van die statistiese en buite-statistiese implikasies van hierdie metodes. ’n Oorsig word verskaf van navorsingsbevindings oor die bronne van DIF, insluitend dié by vertaalde toetse. Omdat DIF-ontledings nie die korrelasies tussen ’n toets en relevante kriteria in ag neem nie, sal die verwydering van differensieel-funksionerende items nie noodwendig voorspellingsgeldigheid verbeter of voorspellingsydigheid verminder nie. Die implikasies van vorige DIF-navorsingsbevindings vir toetsontwikkeling in die veeltalige en multikulturele Suid-Afrikaanse gemeenskap word oorweeg.

Prediction of cereal feed value by near infrared spectroscopy

DEFF Research Database (Denmark)

Jørgensen, Johannes Ravn

. NIRS is therefore appropriate as a quick method for the determination of FEsv and FEso, since it is rapid (approximately 1 minute per measurement of a ground test) and cheap. The aim is to develop a rapid method to analyse grain feed value. This will contribute to highlight the opportunities...... feed, a possible tool to assess the feed value of new varieties in the variety testing and a useful, cheap and rapid tool for cereal breeders. A bank of 1213 grain samples of wheat, triticale, barley and rye, and related chemical reference analyses to describe the feed value have been established...... with the error in the chemical analysis. Prediction error by NIRS prediction of feed value has been shown to be above the error of the chemical measurement. The conclusion is that it has proved possible to predict the feed value in cereals with NIRS quickly and cheaply, but prediction error with this method...

Assessment of protein disorder region predictions in CASP10

KAUST Repository

Monastyrskyy, Bohdan; Kryshtafovych, Andriy; Moult, John; Tramontano, Anna; Fidelis, Krzysztof

2013-01-01

The article presents the assessment of disorder region predictions submitted to CASP10. The evaluation is based on the three measures tested in previous CASPs: (i) balanced accuracy, (ii) the Matthews correlation coefficient for the binary predictions, and (iii) the area under the curve in the receiver operating characteristic (ROC) analysis of predictions using probability annotation. We also performed new analyses such as comparison of the submitted predictions with those obtained with a Naïve disorder prediction method and with predictions from the disorder prediction databases D2P2 and MobiDB. On average, the methods participating in CASP10 demonstrated slightly better performance than those in CASP9.

Assessment of protein disorder region predictions in CASP10

KAUST Repository

Monastyrskyy, Bohdan

2013-11-22

The article presents the assessment of disorder region predictions submitted to CASP10. The evaluation is based on the three measures tested in previous CASPs: (i) balanced accuracy, (ii) the Matthews correlation coefficient for the binary predictions, and (iii) the area under the curve in the receiver operating characteristic (ROC) analysis of predictions using probability annotation. We also performed new analyses such as comparison of the submitted predictions with those obtained with a Naïve disorder prediction method and with predictions from the disorder prediction databases D2P2 and MobiDB. On average, the methods participating in CASP10 demonstrated slightly better performance than those in CASP9.

Asian Summer Monsoon Rainfall associated with ENSO and its Predictability

Science.gov (United States)

Shin, C. S.; Huang, B.; Zhu, J.; Marx, L.; Kinter, J. L.; Shukla, J.

2015-12-01

The leading modes of the Asian summer monsoon (ASM) rainfall variability and their seasonal predictability are investigated using the CFSv2 hindcasts initialized from multiple ocean analyses over the period of 1979-2008 and observation-based analyses. It is shown that the two leading empirical orthogonal function (EOF) modes of the observed ASM rainfall anomalies, which together account for about 34% of total variance, largely correspond to the ASM responses to the ENSO influences during the summers of the developing and decaying years of a Pacific anomalous event, respectively. These two ASM modes are then designated as the contemporary and delayed ENSO responses, respectively. It is demonstrated that the CFSv2 is capable of predicting these two dominant ASM modes up to the lead of 5 months. More importantly, the predictability of the ASM rainfall are much higher with respect to the delayed ENSO mode than the contemporary one, with the predicted principal component time series of the former maintaining high correlation skill and small ensemble spread with all lead months whereas the latter shows significant degradation in both measures with lead-time. A composite analysis for the ASM rainfall anomalies of all warm ENSO events in this period substantiates the finding that the ASM is more predictable following an ENSO event. The enhanced predictability mainly comes from the evolution of the warm SST anomalies over the Indian Ocean in the spring of the ENSO maturing phases and the persistence of the anomalous high sea surface pressure over the western Pacific in the subsequent summer, which the hindcasts are able to capture reasonably well. The results also show that the ensemble initialization with multiple ocean analyses improves the CFSv2's prediction skill of both ENSO and ASM rainfall. In fact, the skills of the ensemble mean hindcasts initialized from the four different ocean analyses are always equivalent to the best ones initialized from any individual ocean

A systematic review of the quality and impact of anxiety disorder meta-analyses.

Science.gov (United States)

Ipser, Jonathan C; Stein, Dan J

2009-08-01

Meta-analyses are seen as representing the pinnacle of a hierarchy of evidence used to inform clinical practice. Therefore, the potential importance of differences in the rigor with which they are conducted and reported warrants consideration. In this review, we use standardized instruments to describe the scientific and reporting quality of meta-analyses of randomized controlled trials of the treatment of anxiety disorders. We also use traditional and novel metrics of article impact to assess the influence of meta-analyses across a range of research fields in the anxiety disorders. Overall, although the meta-analyses that we examined had some flaws, their quality of reporting was generally acceptable. Neither the scientific nor reporting quality of the meta-analyses was predicted by any of the impact metrics. The finding that treatment meta-analyses were cited less frequently than quantitative reviews of studies in current "hot spots" of research (ie, genetics, imaging) points to the multifactorial nature of citation patterns. A list of the meta-analyses included in this review is available on an evidence-based website of anxiety and trauma-related disorders.

Ultimate compression after impact load prediction in graphite/epoxy coupons using neural network and multivariate statistical analyses

Science.gov (United States)

Gregoire, Alexandre David

2011-07-01

The goal of this research was to accurately predict the ultimate compressive load of impact damaged graphite/epoxy coupons using a Kohonen self-organizing map (SOM) neural network and multivariate statistical regression analysis (MSRA). An optimized use of these data treatment tools allowed the generation of a simple, physically understandable equation that predicts the ultimate failure load of an impacted damaged coupon based uniquely on the acoustic emissions it emits at low proof loads. Acoustic emission (AE) data were collected using two 150 kHz resonant transducers which detected and recorded the AE activity given off during compression to failure of thirty-four impacted 24-ply bidirectional woven cloth laminate graphite/epoxy coupons. The AE quantification parameters duration, energy and amplitude for each AE hit were input to the Kohonen self-organizing map (SOM) neural network to accurately classify the material failure mechanisms present in the low proof load data. The number of failure mechanisms from the first 30% of the loading for twenty-four coupons were used to generate a linear prediction equation which yielded a worst case ultimate load prediction error of 16.17%, just outside of the +/-15% B-basis allowables, which was the goal for this research. Particular emphasis was placed upon the noise removal process which was largely responsible for the accuracy of the results.

Do Work Characteristics Predict Health Deterioration Among Employees with Chronic Diseases?

Science.gov (United States)

de Wind, Astrid; Boot, Cécile R L; Sewdas, Ranu; Scharn, Micky; van den Heuvel, Swenne G; van der Beek, Allard J

2017-06-29

Purpose In our ageing workforce, the increasing numbers of employees with chronic diseases are encouraged to prolong their working lives. It is important to prevent health deterioration in this vulnerable group. This study aims to investigate whether work characteristics predict health deterioration over a 3-year period among employees with (1) chronic diseases, and, more specifically, (2) musculoskeletal and psychological disorders. Methods The study population consisted of 5600 employees aged 45-64 years with a chronic disease, who participated in the Dutch Study on Transitions in Employment, Ability and Motivation (STREAM). Information on work characteristics was derived from the baseline questionnaire. Health deterioration was defined as a decrease in general health (SF-12) between baseline and follow-up (1-3 years). Crude and adjusted logistic regression analyses were performed to investigate prediction of health deterioration by work characteristics. Subgroup analyses were performed for employees with musculoskeletal and psychological disorders. Results At follow-up, 19.2% of the employees reported health deterioration (N = 1075). Higher social support of colleagues or supervisor predicted health deterioration in the crude analyses in the total group, and the groups with either musculoskeletal or psychological disorders (ORs 1.11-1.42). This effect was not found anymore in the adjusted analyses. The other work characteristics did not predict health deterioration in any group. Conclusions This study did not support our hypothesis that work characteristics predict health deterioration among employees with chronic diseases. As our study population succeeded continuing employment to 45 years and beyond, it was probably a relatively healthy selection of employees.

Predicting child maltreatment: A meta-analysis of the predictive validity of risk assessment instruments.

Science.gov (United States)

van der Put, Claudia E; Assink, Mark; Boekhout van Solinge, Noëlle F

2017-11-01

Risk assessment is crucial in preventing child maltreatment since it can identify high-risk cases in need of child protection intervention. Despite widespread use of risk assessment instruments in child welfare, it is unknown how well these instruments predict maltreatment and what instrument characteristics are associated with higher levels of predictive validity. Therefore, a multilevel meta-analysis was conducted to examine the predictive accuracy of (characteristics of) risk assessment instruments. A literature search yielded 30 independent studies (N=87,329) examining the predictive validity of 27 different risk assessment instruments. From these studies, 67 effect sizes could be extracted. Overall, a medium significant effect was found (AUC=0.681), indicating a moderate predictive accuracy. Moderator analyses revealed that onset of maltreatment can be better predicted than recurrence of maltreatment, which is a promising finding for early detection and prevention of child maltreatment. In addition, actuarial instruments were found to outperform clinical instruments. To bring risk and needs assessment in child welfare to a higher level, actuarial instruments should be further developed and strengthened by distinguishing risk assessment from needs assessment and by integrating risk assessment with case management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

Science.gov (United States)

Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

2018-02-01

1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses.

Science.gov (United States)

Leng, Xiang'zi; Wang, Jinhua; Ji, Haibo; Wang, Qin'geng; Li, Huiming; Qian, Xin; Li, Fengying; Yang, Meng

2017-08-01

Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM 2.5 concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75 μg/m 3 . Nearly all elements had higher concentrations in industrial areas, and in winter among the four seasons. Anthropogenic elements such as Pb, Zn, Cd and Cu showed larger percentages in the fine fraction (ø≤2.5 μm), whereas the crustal elements including Al, Ba, Fe, Ni, Sr and Ti showed larger percentages in the coarse fraction (ø > 2.5 μm). SVM showed a higher training correlation coefficient (R), and lower mean absolute error (MAE) as well as lower root mean square error (RMSE), than MLR and BP-ANN for most metals. All the three methods showed better prediction results for Ni, Al, V, Cd and As, whereas relatively poor for Cr and Fe. The daily airborne metal concentrations in 2015 were then predicted by the fully trained SVM models and the results showed the heaviest pollution of airborne heavy metals occurred in December and January, whereas the lightest pollution occurred in June and July. Copyright © 2017 Elsevier Ltd. All rights reserved.

ATOP - The Advanced Taiwan Ocean Prediction System Based on the mpiPOM. Part 1: Model Descriptions, Analyses and Results

Directory of Open Access Journals (Sweden)

Leo Oey

2013-01-01

Full Text Available A data-assimilated Taiwan Ocean Prediction (ATOP system is being developed at the National Central University, Taiwan. The model simulates sea-surface height, three-dimensional currents, temperature and salinity and turbulent mixing. The model has options for tracer and particle-tracking algorithms, as well as for wave-induced Stokes drift and wave-enhanced mixing and bottom drag. Two different forecast domains have been tested: a large-grid domain that encompasses the entire North Pacific Ocean at 0.1° × 0.1° horizontal resolution and 41 vertical sigma levels, and a smaller western North Pacific domain which at present also has the same horizontal resolution. In both domains, 25-year spin-up runs from 1988 - 2011 were first conducted, forced by six-hourly Cross-Calibrated Multi-Platform (CCMP and NCEP reanalysis Global Forecast System (GSF winds. The results are then used as initial conditions to conduct ocean analyses from January 2012 through February 2012, when updated hindcasts and real-time forecasts begin using the GFS winds. This paper describes the ATOP system and compares the forecast results against satellite altimetry data for assessing model skills. The model results are also shown to compare well with observations of (i the Kuroshio intrusion in the northern South China Sea, and (ii subtropical counter current. Review and comparison with other models in the literature of ¡§(i¡¨ are also given.

ATWS analyses for Krsko Full Scope Simulator verification

Energy Technology Data Exchange (ETDEWEB)

Cerne, G; Tiselj, I; Parzer, I [Reactor Engineering Div., Inst. Jozef Stefan, Ljubljana (Slovenia)

2000-07-01

The purpose of this analysis was to simulate Anticipated Transient without Scram transient for Krsko NPP. The results of these calculations were used for verification of reactor coolant system thermal-hydraulic response predicted by Krsko Full Scope Simulator. For the thermal-hydraulic analyses the RELAP5/MOD2 code and the input card deck for NPP Krsko was used. The analyses for ATWS were performed to assess the influence and benefit of ATWS Mitigation System Actuation Circuitry (AMSAC). In the presented paper the most severe ATWS scenarios have been analyzed, starting with the loss of Main Feedwater at both steam generators. Thus, gradual loss of secondary heat sink occurred. On top of that, control rods were not supposed to scram, leaving the chain reaction to be controlled only by inherent physical properties of the fuel and moderator and eventual actions of the BOP system. The primary system response has been studied regarding the AMSAC availability. (author)

Prediction of resource volumes at untested locations using simple local prediction models

Science.gov (United States)

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Severe accident recriticality analyses (SARA)

Energy Technology Data Exchange (ETDEWEB)

Frid, W. E-mail: wiktor.frid@ski.se; Hoejerup, F.; Lindholm, I.; Miettinen, J.; Nilsson, L.; Puska, E.K.; Sjoevall, H

2001-11-01

Recriticality in a BWR during reflooding of an overheated partly degraded core, i.e. with relocated control rods, has been studied for a total loss of electric power accident scenario. In order to assess the impact of recriticality on reactor safety, including accident management strategies, the following issues have been investigated in the SARA project: (1) the energy deposition in the fuel during super-prompt power burst; (2) the quasi steady-state reactor power following the initial power burst; and (3) containment response to elevated quasi steady-state reactor power. The approach was to use three computer codes and to further develop and adapt them for the task. The codes were SIMULATE-3K, APROS and RECRIT. Recriticality analyses were carried out for a number of selected reflooding transients for the Oskarshamn 3 plant in Sweden with SIMULATE-3K and for the Olkiluoto 1 plant in Finland with all three codes. The core initial and boundary conditions prior to recriticality have been studied with the severe accident codes SCDAP/RELAP5, MELCOR and MAAP4. The results of the analyses show that all three codes predict recriticality--both super-prompt power bursts and quasi steady-state power generation--for the range of parameters studied, i.e. with core uncovering and heat-up to maximum core temperatures of approximately 1800 K, and water flow rates of 45-2000 kg s{sup -1} injected into the downcomer. Since recriticality takes place in a small fraction of the core, the power densities are high, which results in large energy deposition in the fuel during power burst in some accident scenarios. The highest value, 418 cal g{sup -1}, was obtained with SIMULATE-3K for an Oskarshamn 3 case with reflooding rate of 2000 kg s{sup -1}. In most cases, however, the predicted energy deposition was smaller, below the regulatory limits for fuel failure, but close to or above recently observed thresholds for fragmentation and dispersion of high burn-up fuel. The highest calculated

Severe accident recriticality analyses (SARA)

International Nuclear Information System (INIS)

Frid, W.; Hoejerup, F.; Lindholm, I.; Miettinen, J.; Nilsson, L.; Puska, E.K.; Sjoevall, H.

2001-01-01

Recriticality in a BWR during reflooding of an overheated partly degraded core, i.e. with relocated control rods, has been studied for a total loss of electric power accident scenario. In order to assess the impact of recriticality on reactor safety, including accident management strategies, the following issues have been investigated in the SARA project: (1) the energy deposition in the fuel during super-prompt power burst; (2) the quasi steady-state reactor power following the initial power burst; and (3) containment response to elevated quasi steady-state reactor power. The approach was to use three computer codes and to further develop and adapt them for the task. The codes were SIMULATE-3K, APROS and RECRIT. Recriticality analyses were carried out for a number of selected reflooding transients for the Oskarshamn 3 plant in Sweden with SIMULATE-3K and for the Olkiluoto 1 plant in Finland with all three codes. The core initial and boundary conditions prior to recriticality have been studied with the severe accident codes SCDAP/RELAP5, MELCOR and MAAP4. The results of the analyses show that all three codes predict recriticality--both super-prompt power bursts and quasi steady-state power generation--for the range of parameters studied, i.e. with core uncovering and heat-up to maximum core temperatures of approximately 1800 K, and water flow rates of 45-2000 kg s -1 injected into the downcomer. Since recriticality takes place in a small fraction of the core, the power densities are high, which results in large energy deposition in the fuel during power burst in some accident scenarios. The highest value, 418 cal g -1 , was obtained with SIMULATE-3K for an Oskarshamn 3 case with reflooding rate of 2000 kg s -1 . In most cases, however, the predicted energy deposition was smaller, below the regulatory limits for fuel failure, but close to or above recently observed thresholds for fragmentation and dispersion of high burn-up fuel. The highest calculated quasi steady

Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

Science.gov (United States)

Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

2015-01-01

We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

Nurses' intention to leave: critically analyse the theory of reasoned action and organizational commitment model.

Science.gov (United States)

Liou, Shwu-Ru

2009-01-01

To systematically analyse the Organizational Commitment model and Theory of Reasoned Action and determine concepts that can better explain nurses' intention to leave their job. The Organizational Commitment model and Theory of Reasoned Action have been proposed and applied to understand intention to leave and turnover behaviour, which are major contributors to nursing shortage. However, the appropriateness of applying these two models in nursing was not analysed. Three main criteria of a useful model were used for the analysis: consistency in the use of concepts, testability and predictability. Both theories use concepts consistently. Concepts in the Theory of Reasoned Action are defined broadly whereas they are operationally defined in the Organizational Commitment model. Predictability of the Theory of Reasoned Action is questionable whereas the Organizational Commitment model can be applied to predict intention to leave. A model was proposed based on this analysis. Organizational commitment, intention to leave, work experiences, job characteristics and personal characteristics can be concepts for predicting nurses' intention to leave. Nursing managers may consider nurses' personal characteristics and experiences to increase their organizational commitment and enhance their intention to stay. Empirical studies are needed to test and cross-validate the re-synthesized model for nurses' intention to leave their job.

All 37 Mitochondrial Genes of Aphid Aphis craccivora Obtained from Transcriptome Sequencing: Implications for the Evolution of Aphids.

Directory of Open Access Journals (Sweden)

Nan Song

Full Text Available The availability of mitochondrial genome data for Aphididae, one of the economically important insect pest families, in public databases is limited. The advent of next generation sequencing technology provides the potential to generate mitochondrial genome data for many species timely and cost-effectively. In this report, we used transcriptome sequencing technology to determine all the 37 mitochondrial genes of the cowpea aphid, Aphis craccivora. This method avoids the necessity of finding suitable primers for long PCRs or primer-walking amplicons, and is proved to be effective in obtaining the whole set of mitochondrial gene data for insects with difficulty in sequencing mitochondrial genome by PCR-based strategies. Phylogenetic analyses of aphid mitochondrial genome data show clustering based on tribe level, and strongly support the monophyly of the family Aphididae. Within the monophyletic Aphidini, three samples from Aphis grouped together. In another major clade of Aphididae, Pterocomma pilosum was recovered as a potential sister-group of Cavariella salicicola, as part of Macrosiphini.

Opsins in onychophora (velvet worms) suggest a single origin and subsequent diversification of visual pigments in arthropods.

Science.gov (United States)

Hering, Lars; Henze, Miriam J; Kohler, Martin; Kelber, Almut; Bleidorn, Christoph; Leschke, Maren; Nickel, Birgit; Meyer, Matthias; Kircher, Martin; Sunnucks, Paul; Mayer, Georg

2012-11-01

Multiple visual pigments, prerequisites for color vision, are found in arthropods, but the evolutionary origin of their diversity remains obscure. In this study, we explore the opsin genes in five distantly related species of Onychophora, using deep transcriptome sequencing and screening approaches. Surprisingly, our data reveal the presence of only one opsin gene (onychopsin) in each onychophoran species, and our behavioral experiments indicate a maximum sensitivity of onychopsin to blue-green light. In our phylogenetic analyses, the onychopsins represent the sister group to the monophyletic clade of visual r-opsins of arthropods. These results concur with phylogenomic support for the sister-group status of the Onychophora and Arthropoda and provide evidence for monochromatic vision in velvet worms and in the last common ancestor of Onychophora and Arthropoda. We conclude that the diversification of visual pigments and color vision evolved in arthropods, along with the evolution of compound eyes-one of the most sophisticated visual systems known.

Presence of a mitochondrial-type 70-kDa heat shock protein in Trichomonas vaginalis suggests a very early mitochondrial endosymbiosis in eukaryotes.

Science.gov (United States)

Germot, A; Philippe, H; Le Guyader, H

1996-12-10

Molecular phylogenetic analyses, based mainly on ribosomal RNA, show that three amitochondriate protist lineages, diplomonads, microsporidia, and trichomonads, emerge consistently at the base of the eukaryotic tree before groups having mitochondria. This suggests that these groups could have diverged before the mitochondrial endosymbiosis. Nevertheless, since all these organisms live in anaerobic environments, the absence of mitochondria might be due to secondary loss, as demonstrated for the later emerging eukaryote Entamoeba histolytica. We have now isolated from Trichomonas vaginalis a gene encoding a chaperone protein (HSP70) that in other lineages is addressed to the mitochondrial compartment. The phylogenetic reconstruction unambiguously located this HSP70 within a large set of mitochondrial sequences, itself a sister-group of alpha-purple bacteria. In addition, the T. vaginalis protein exhibits the GDAWV sequence signature, so far exclusively found in mitochondrial HSP70 and in proteobacterial dnaK. Thus mitochondrial endosymbiosis could have occurred earlier than previously assumed. The trichomonad double membrane-bounded organelles, the hydrogenosomes, could have evolved from mitochondria.

Climate Prediction Center - Expert Assessments Index

Science.gov (United States)

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Global Climate Data & Maps > ; Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are

Analysis of the uranium price predicted to 24 months, implementing neural networks and the Monte Carlo method like predictive tools

International Nuclear Information System (INIS)

Esquivel E, J.; Ramirez S, J. R.; Palacios H, J. C.

2011-11-01

The present work shows predicted prices of the uranium, using a neural network. The importance of predicting financial indexes of an energy resource, in this case, allows establishing budgetary measures, as well as the costs of the resource to medium period. The uranium is part of the main energy generating fuels and as such, its price rebounds in the financial analyses, due to this is appealed to predictive methods to obtain an outline referent to the financial behaviour that will have in a certain time. In this study, two methodologies are used for the prediction of the uranium price: the Monte Carlo method and the neural networks. These methods allow predicting the indexes of monthly costs, for a two years period, starting from the second bimonthly of 2011. For the prediction the uranium costs are used, registered from the year 2005. (Author)

Predictive modelling of noise level generated during sawing of rocks

Indian Academy of Sciences (India)

This paper presents an experimental and statistical study on noise level generated during of rock sawing by circular diamond sawblades. Influence of the operating variables and rock properties on the noise level are investigated and analysed. Statistical analyses are then employed and models are built for the prediction of ...

Can adverse maternal and perinatal outcomes be predicted when blood pressure becomes elevated? Secondary analyses from the CHIPS (Control of Hypertension In Pregnancy Study) randomized controlled trial.

Science.gov (United States)

Magee, Laura A; von Dadelszen, Peter; Singer, Joel; Lee, Terry; Rey, Evelyne; Ross, Susan; Asztalos, Elizabeth; Murphy, Kellie E; Menzies, Jennifer; Sanchez, Johanna; Gafni, Amiram; Gruslin, Andrée; Helewa, Michael; Hutton, Eileen; Lee, Shoo K; Logan, Alexander G; Ganzevoort, Wessel; Welch, Ross; Thornton, Jim G; Moutquin, Jean Marie

2016-07-01

For women with chronic or gestational hypertension in CHIPS (Control of Hypertension In Pregnancy Study, NCT01192412), we aimed to examine whether clinical predictors collected at randomization could predict adverse outcomes. This was a planned, secondary analysis of data from the 987 women in the CHIPS Trial. Logistic regression was used to examine the impact of 19 candidate predictors on the probability of adverse perinatal (pregnancy loss or high level neonatal care for >48 h, or birthweight hypertension, preeclampsia, or delivery at blood pressure within 1 week before randomization. Continuous variables were represented continuously or dichotomized based on the smaller p-value in univariate analyses. An area-under-the-receiver-operating-curve (AUC ROC) of ≥0.70 was taken to reflect a potentially useful model. Point estimates for AUC ROC were hypertension (0.70, 95% CI 0.67-0.74) and delivery at hypertension develop an elevated blood pressure in pregnancy, or formerly normotensive women develop new gestational hypertension, maternal and current pregnancy clinical characteristics cannot predict adverse outcomes in the index pregnancy. © 2016 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

Multivariate differential analyses of adolescents' experiences of aggression in families

Directory of Open Access Journals (Sweden)

Chris Myburgh

2011-01-01

Full Text Available Aggression is part of South African society and has implications for the mental health of persons living in South Africa. If parents are aggressive adolescents are also likely to be aggressive and that will impact negatively on their mental health. In this article the nature and extent of adolescents' experiences of aggression and aggressive behaviour in the family are investigated. A deductive explorative quantitative approach was followed. Aggression is reasoned to be dependent on aspects such as self-concept, moral reasoning, communication, frustration tolerance and family relationships. To analyse the data from questionnaires of 101 families (95 adolescents, 95 mothers and 91 fathers Cronbach Alpha, various consecutive first and second order factor analyses, correlations, multiple regression, MANOVA, ANOVA and Scheffè/ Dunnett tests were used. It was found that aggression correlated negatively with the independent variables; and the correlations between adolescents and their parents were significant. Regression analyses indicated that different predictors predicted aggression. Furthermore, differences between adolescents and their parents indicated that the experienced levels of aggression between adolescents and their parents were small. Implications for education are given.

Link Prediction Methods and Their Accuracy for Different Social Networks and Network Metrics

Directory of Open Access Journals (Sweden)

Fei Gao

2015-01-01

Full Text Available Currently, we are experiencing a rapid growth of the number of social-based online systems. The availability of the vast amounts of data gathered in those systems brings new challenges that we face when trying to analyse it. One of the intensively researched topics is the prediction of social connections between users. Although a lot of effort has been made to develop new prediction approaches, the existing methods are not comprehensively analysed. In this paper we investigate the correlation between network metrics and accuracy of different prediction methods. We selected six time-stamped real-world social networks and ten most widely used link prediction methods. The results of the experiments show that the performance of some methods has a strong correlation with certain network metrics. We managed to distinguish “prediction friendly” networks, for which most of the prediction methods give good performance, as well as “prediction unfriendly” networks, for which most of the methods result in high prediction error. Correlation analysis between network metrics and prediction accuracy of prediction methods may form the basis of a metalearning system where based on network characteristics it will be able to recommend the right prediction method for a given network.

Proposed Testing to Assess the Accuracy of Glass-To-Metal Seal Stress Analyses.

Energy Technology Data Exchange (ETDEWEB)

Chambers, Robert S.; Emery, John M; Tandon, Rajan; Antoun, Bonnie R.; Stavig, Mark E.; Newton, Clay S.; Gibson, Cory S; Bencoe, Denise N.

2014-09-01

The material characterization tests conducted on 304L VAR stainless steel and Schott 8061 glass have provided higher fidelity data for calibration of material models used in Glass - T o - Metal (GTM) seal analyses. Specifically, a Thermo - Multi - Linear Elastic Plastic ( thermo - MLEP) material model has be en defined for S S304L and the Simplified Potential Energy Clock nonlinear visc oelastic model has been calibrated for the S8061 glass. To assess the accuracy of finite element stress analyses of GTM seals, a suite of tests are proposed to provide data for comparison to mo del predictions.

Severe Accident Recriticality Analyses (SARA)

Energy Technology Data Exchange (ETDEWEB)

Frid, W. [Swedish Nuclear Power Inspectorate, Stockholm (Sweden); Hoejerup, F. [Risoe National Lab. (Denmark); Lindholm, I.; Miettinen, J.; Puska, E.K. [VTT Energy, Helsinki (Finland); Nilsson, Lars [Studsvik Eco and Safety AB, Nykoeping (Sweden); Sjoevall, H. [Teoliisuuden Voima Oy (Finland)

1999-11-01

Recriticality in a BWR has been studied for a total loss of electric power accident scenario. In a BWR, the B{sub 4}C control rods would melt and relocate from the core before the fuel during core uncovery and heat-up. If electric power returns during this time-window unborated water from ECCS systems will start to reflood the partly control rod free core. Recriticality might take place for which the only mitigating mechanisms are the Doppler effect and void formation. In order to assess the impact of recriticality on reactor safety, including accident management measures, the following issues have been investigated in the SARA project: 1. the energy deposition in the fuel during super-prompt power burst, 2. the quasi steady-state reactor power following the initial power burst and 3. containment response to elevated quasi steady-state reactor power. The approach was to use three computer codes and to further develop and adapt them for the task. The codes were SIMULATE-3K, APROS and RECRIT. Recriticality analyses were carried out for a number of selected reflooding transients for the Oskarshamn 3 plant in Sweden with SIMULATE-3K and for the Olkiluoto 1 plant in Finland with all three codes. The core state initial and boundary conditions prior to recriticality have been studied with the severe accident codes SCDAP/RELAP5, MELCOR and MAAP4. The results of the analyses show that all three codes predict recriticality - both superprompt power bursts and quasi steady-state power generation - for the studied range of parameters, i. e. with core uncovery and heat-up to maximum core temperatures around 1800 K and water flow rates of 45 kg/s to 2000 kg/s injected into the downcomer. Since the recriticality takes place in a small fraction of the core the power densities are high which results in large energy deposition in the fuel during power burst in some accident scenarios. The highest value, 418 cal/g, was obtained with SIMULATE-3K for an Oskarshamn 3 case with reflooding

Severe Accident Recriticality Analyses (SARA)

International Nuclear Information System (INIS)

Frid, W.; Hoejerup, F.; Lindholm, I.; Miettinen, J.; Puska, E.K.; Nilsson, Lars; Sjoevall, H.

1999-11-01

Recriticality in a BWR has been studied for a total loss of electric power accident scenario. In a BWR, the B 4 C control rods would melt and relocate from the core before the fuel during core uncovery and heat-up. If electric power returns during this time-window unborated water from ECCS systems will start to reflood the partly control rod free core. Recriticality might take place for which the only mitigating mechanisms are the Doppler effect and void formation. In order to assess the impact of recriticality on reactor safety, including accident management measures, the following issues have been investigated in the SARA project: 1. the energy deposition in the fuel during super-prompt power burst, 2. the quasi steady-state reactor power following the initial power burst and 3. containment response to elevated quasi steady-state reactor power. The approach was to use three computer codes and to further develop and adapt them for the task. The codes were SIMULATE-3K, APROS and RECRIT. Recriticality analyses were carried out for a number of selected reflooding transients for the Oskarshamn 3 plant in Sweden with SIMULATE-3K and for the Olkiluoto 1 plant in Finland with all three codes. The core state initial and boundary conditions prior to recriticality have been studied with the severe accident codes SCDAP/RELAP5, MELCOR and MAAP4. The results of the analyses show that all three codes predict recriticality - both superprompt power bursts and quasi steady-state power generation - for the studied range of parameters, i. e. with core uncovery and heat-up to maximum core temperatures around 1800 K and water flow rates of 45 kg/s to 2000 kg/s injected into the downcomer. Since the recriticality takes place in a small fraction of the core the power densities are high which results in large energy deposition in the fuel during power burst in some accident scenarios. The highest value, 418 cal/g, was obtained with SIMULATE-3K for an Oskarshamn 3 case with reflooding

Indian Point 2 steam generator tube rupture analyses

International Nuclear Information System (INIS)

Dayan, A.

1985-01-01

Analyses were conducted with RETRAN-02 to study consequences of steam generator tube rupture (SGTR) events. The Indian Point, Unit 2, power plant (IP2, PWR) was modeled as a two asymmetric loops, consisting of 27 volumes and 37 junctions. The break section was modeled once, conservatively, as a 150% flow area opening at the wall of the steam generator cold leg plenum, and once as a 200% double-ended tube break. Results revealed 60% overprediction of breakflow rates by the traditional conservative model. Two SGTR transients were studied, one with low-pressure reactor trip and one with an earlier reactor trip via over temperature ΔT. The former is more typical to a plant with low reactor average temperature such as IP2. Transient analyses for a single tube break event over 500 seconds indicated continued primary subcooling and no need for steam line pressure relief. In addition, SGTR transients with reactor trip while the pressurizer still contains water were found to favorably reduce depressurization rates. Comparison of the conservative results with independent LOFTRAN predictions showed good agreement

Practices for predicting and preventing preterm birth in Ireland: a national survey.

LENUS (Irish Health Repository)

Smith, V

2011-03-01

Preterm birth can result in adverse outcomes for the neonate and\\/or his\\/her family. The accurate prediction and prevention of preterm birth is paramount. This study describes and critically analyses practices for predicting and preventing preterm birth in Ireland.

Contribution of thermo-fluid analyses to the LHC experiments

CERN Document Server

Gasser, G

2003-01-01

The big amount of electrical and electronic equipment that will be installed in the four LHC experiments will cause important heat dissipation into the detectors’ volumes. This is a major issue for the experimental groups, as temperature stability is often a fundamental requirement for the different sub-detectors to be able to provide a good measurement quality. The thermofluid analyses that are carried out in the ST/CV group are a very efficient tool to understand and predict the thermal behaviour of the detectors. These studies are undertaken according to the needs of the experimental groups; they aim at evaluate the thermal stability for a proposed design, or to compare different technical solutions in order to choose the best one for the final design. The usual approach to carry out these studies is first presented and then, some practical examples of thermo-fluid analyses are presented focusing on the main results in order to illustrate their contribution.

On the applicability of probabilistic analyses to assess the structural reliability of materials and components for solid-oxide fuel cells

Energy Technology Data Exchange (ETDEWEB)

Lara-Curzio, Edgar [ORNL; Radovic, Miladin [Texas A& M University; Luttrell, Claire R [ORNL

2016-01-01

The applicability of probabilistic analyses to assess the structural reliability of materials and components for solid-oxide fuel cells (SOFC) is investigated by measuring the failure rate of Ni-YSZ when subjected to a temperature gradient and comparing it with that predicted using the Ceramics Analysis and Reliability Evaluation of Structures (CARES) code. The use of a temperature gradient to induce stresses was chosen because temperature gradients resulting from gas flow patterns generate stresses during SOFC operation that are the likely to control the structural reliability of cell components The magnitude of the predicted failure rate was found to be comparable to that determined experimentally, which suggests that such probabilistic analyses are appropriate for predicting the structural reliability of materials and components for SOFCs. Considerations for performing more comprehensive studies are discussed.

Network class superposition analyses.

Directory of Open Access Journals (Sweden)

Carl A B Pearson

Full Text Available Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., ≈ 10(30 for the yeast cell cycle process, considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses.

Secondary structural analyses of ITS1 in Paramecium.

Science.gov (United States)

Hoshina, Ryo

2010-01-01

The nuclear ribosomal RNA gene operon is interrupted by internal transcribed spacer (ITS) 1 and ITS2. Although the secondary structure of ITS2 has been widely investigated, less is known about ITS1 and its structure. In this study, the secondary structure of ITS1 sequences for Paramecium and other ciliates was predicted. Each Paramecium ITS1 forms an open loop with three helices, A through C. Helix B was highly conserved among Paramecium, and similar helices were found in other ciliates. A phylogenetic analysis using the ITS1 sequences showed high-resolution, implying that ITS1 is a good tool for species-level analyses.

Comparison of elastic and inelastic analyses

International Nuclear Information System (INIS)

Ammerman, D.J.; Heinstein, M.W.; Wellman, G.W.

1992-01-01

The use of inelastic analysis methods instead of the traditional elastic analysis methods in the design of radioactive material (RAM) transport packagings leads to a better understanding of the response of the package to mechanical loadings. Thus, better assessment of the containment, thermal protection, and shielding integrity of the package after a structure accident event can be made. A more accurate prediction of the package response can lead to enhanced safety and also allow for a more efficient use of materials, possibly leading to a package with higher capacity or lower weight. This paper discusses the advantages and disadvantages of using inelastic analysis in the design of RAM shipping packages. The use of inelastic analysis presents several problems to the package designer. When using inelastic analysis the entire nonlinear response of the material must be known, including the effects of temperature changes and strain rate. Another problem is that there currently is not an acceptance criteria for this type of analysis that is approved by regulatory agencies. Inelastic analysis acceptance criteria based on failure stress, failure strain , or plastic energy density could be developed. For both elastic and inelastic analyses it is also important to include other sources of stress in the analyses, such as fabrication stresses, thermal stresses, stresses from bolt preloading, and contact stresses at material interfaces. Offsetting these added difficulties is the improved knowledge of the package behavior. This allows for incorporation of a more uniform margin of safety, which can result in weight savings and a higher level of confidence in the post-accident configuration of the package. In this paper, comparisons between elastic and inelastic analyses are made for a simple ring structure and for a package to transport a large quantity of RAM by rail (rail cask) with lead gamma shielding to illustrate the differences in the two analysis techniques

Competition and stability analyses among emissions, energy, and economy: Application for Mexico

International Nuclear Information System (INIS)

Pao, Hsiao-Tien; Fu, Hsin-Chia

2015-01-01

In view of limited natural resources on Earth, linkage among environment, energy, and economy (3Es) becomes important perspectives for sustainable development. This paper proposes to use Lotka–Volterra model for SUstainable Development (LV-SUD) to analyse the interspecific interactions, equilibria and their stabilities among emissions, different types of energy consumption (renewable, nuclear, and fossil fuel), and real GDP, the main factors of 3Es issues. Modelling these interactions provides a useful multivariate framework for prediction outcomes. Interaction between 3Es, namely competition, symbiosis, or predation, plays an important role in policy development to achieve a balanced use of energy resources and to strengthen the green economy. Applying LV-SUD in Mexico, an emerging markets country, analysing results show that there is a mutualism between fossil fuel consumption and GDP; prey-predator relationships that fossil fuel and GDP enhance the growth of emissions, but emissions inhibit the growth of the others; and commensalisms that GDP benefits from nuclear power, and renewable power benefits from fossil fuel. It is suggested that national energy policies should remain committed to decoupling the relevance between non-clean energy and GDP, to actively developing clean energy and thereby to properly reducing fossil fuel consumption and emissions without harming economic growth. - Highlights: • LV-SUD is used to analyse the competition between environment-energy-economy (3Es). • The competitions between renewable, nuclear, and fossil energy are analysed. • Competition between 3Es plays an important role in policy development. • LV-SUD provides a useful multivariate framework for prediction outcomes. • An application for emerging markets countries such as Mexico is presented

Nonlinear piping damping and response predictions

International Nuclear Information System (INIS)

Severud, L.K.; Weiner, E.O.; Lindquist, M.R.; Anderson, M.J.; Wagner, S.E.

1986-10-01

The high level dynamic testing of four prototypic piping systems, used to provide benchmarks for analytical prediction comparisons, is overviewed. The size of pipe tested ranged from one-inch to six-inches in diameter and consisted of carbon steel or stainless steel material. Failure of the tested systems included progressive gross deformation or some combination of ratchetting-fatigue. Pretest failure predictions and post test comparisons using simplified elastic and elasto-plastic methods are presented. Detailed non-linear inelastic analyses are also shown, along with a typical ratchet-fatigue failure calculation. A simplified method for calculating modal equivalent viscous damping for snubbers and plastic hinges is also described. Conclusions are made regarding the applicability of the various analytical failure predictive methods and recommendations are made for future analytic and test efforts

Phylogenetic Relationships of Five Asian Schilbid Genera Including Clupisoma (Siluriformes: Schilbeidae.

Directory of Open Access Journals (Sweden)

Jing Wang

Full Text Available The phylogenetic relationships of Asian schilbid catfishes of the genera Clupisoma, Ailia, Horabagrus, Laides and Pseudeutropius are poorly understood, especially those of Clupisoma. Herein, we reconstruct the phylogeny of 38 species of catfishes belonging to 28 genera and 14 families using the concatenated mitochondrial genes COI, cytb, and 16S rRNA, as well as the nuclear genes RAG1 and RAG2. The resulting phylogenetic trees consistently place Clupisoma as the sister taxon of Laides, and the five representative Asian schilbid genera form two monophyletic groups with the relationships (Ailia (Laides, Clupisoma and (Horabagrus, Pseudeutropius. The so-called "Big Asia" lineage relates distantly to African schilbids. Independent analyses of the mitochondrial and nuclear DNA data yield differing trees for the two Asian schilbid groups. Analyses of the mitochondrial gene data support a sister-group relationship for (Ailia (Laides, Clupisoma and the Sisoroidea and a sister-taxon association of (Horabagrus, Pseudeutropius and the Bagridae. In contrast, analyses of the combined nuclear data indicate (Ailia (Laides, Clupisoma to be the sister group to (Horabagrus, Pseudeutropius. Our results indicate that the Horabagridae, recognized by some authors as consisting of Horabagrus, Pseudeutropius and Clupisoma does not include the latter genus. We formally erect a new family, Ailiidae fam. nov. for a monophyletic Asian group comprised of the genera Ailia, Laides and Clupisoma.

Can the theory of planned behaviour predict the physical activity behaviour of individuals?

Science.gov (United States)

Hobbs, Nicola; Dixon, Diane; Johnston, Marie; Howie, Kate

2013-01-01

The theory of planned behaviour (TPB) can identify cognitions that predict differences in behaviour between individuals. However, it is not clear whether the TPB can predict the behaviour of an individual person. This study employs a series of n-of-1 studies and time series analyses to examine the ability of the TPB to predict physical activity (PA) behaviours of six individuals. Six n-of-1 studies were conducted, in which TPB cognitions and up to three PA behaviours (walking, gym workout and a personally defined PA) were measured twice daily for six weeks. Walking was measured by pedometer step count, gym attendance by self-report with objective validation of gym entry and the personally defined PA behaviour by self-report. Intra-individual variability in TPB cognitions and PA behaviour was observed in all participants. The TPB showed variable predictive utility within individuals and across behaviours. The TPB predicted at least one PA behaviour for five participants but had no predictive utility for one participant. Thus, n-of-1 designs and time series analyses can be used to test theory in an individual.

Predictable return distributions

DEFF Research Database (Denmark)

Pedersen, Thomas Quistgaard

trace out the entire distribution. A univariate quantile regression model is used to examine stock and bond return distributions individually, while a multivariate model is used to capture their joint distribution. An empirical analysis on US data shows that certain parts of the return distributions......-of-sample analyses show that the relative accuracy of the state variables in predicting future returns varies across the distribution. A portfolio study shows that an investor with power utility can obtain economic gains by applying the empirical return distribution in portfolio decisions instead of imposing...

Application of pathways analyses for site performance prediction for the Gas Centrifuge Enrichment Plant and Oak Ridge Central Waste Disposal Facility

International Nuclear Information System (INIS)

Pin, F.G.; Oblow, E.M.

1984-01-01

The suitability of the Gas Centrifuge Enrichment Plant and the Oak Ridge Central Waste Disposal Facility for shallow-land burial of low-level radioactive waste is evaluated using pathways analyses. The analyses rely on conservative scenarios to describe the generation and migration of contamination and the potential human exposure to the waste. Conceptual and numerical models are developed using data from comprehensive laboratory and field investigations and are used to simulate the long-term transport of contamination to man. Conservatism is built into the analyses when assumptions concerning future events have to be made or when uncertainties concerning site or waste characteristics exist. Maximum potential doses to man are calculated and compared to the appropriate standards. The sites are found to provide adequate buffer to persons outside the DOE reservations. Conclusions concerning site capacity and site acceptability are drawn. In reaching these conclusions, some consideration is given to the uncertainties and conservatisms involved in the analyses. Analytical methods to quantitatively assess the probability of future events to occur and the sensitivity of the results to data uncertainty may prove useful in relaxing some of the conservatism built into the analyses. The applicability of such methods to pathways analyses is briefly discussed. 18 refs., 9 figs

Consumer factors predicting level of treatment response to illness management and recovery.

Science.gov (United States)

White, Dominique A; McGuire, Alan B; Luther, Lauren; Anderson, Adrienne I; Phalen, Peter; McGrew, John H

2017-12-01

This study aims to identify consumer-level predictors of level of treatment response to illness management and recovery (IMR) to target the appropriate consumers and aid psychiatric rehabilitation settings in developing intervention adaptations. Secondary analyses from a multisite study of IMR were conducted. Self-report data from consumer participants of the parent study (n = 236) were analyzed for the current study. Consumers completed prepost surveys assessing illness management, coping, goal-related hope, social support, medication adherence, and working alliance. Correlations and multiple regression analyses were run to identify self-report variables that predicted level of treatment response to IMR. Analyses revealed that goal-related hope significantly predicted level of improved illness self-management, F(1, 164) = 10.93, p consumer-level predictors of level of treatment response have not been explored for IMR. Although 2 significant predictors were identified, study findings suggest more work is needed. Future research is needed to identify additional consumer-level factors predictive of IMR treatment response in order to identify who would benefit most from this treatment program. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Machine learning applied to the prediction of citrus production

OpenAIRE

Díaz Rodríguez, Susana Irene; Mazza, Silvia M.; Fernández-Combarro Álvarez, Elías; Giménez, Laura I.; Gaiad, José E.

2017-01-01

An in-depth knowledge about variables affecting production is required in order to predict global production and take decisions in agriculture. Machine learning is a technique used in agricultural planning and precision agriculture. This work (i) studies the effectiveness of machine learning techniques for predicting orchards production; and (ii) variables affecting this production were also identified. Data from 964 orchards of lemon, mandarin, and orange in Corrientes, Argentina are analyse...

Monitoring and prediction of natural disasters

International Nuclear Information System (INIS)

Kondratyev, K. Ya; Krapivin, V. F.

2004-01-01

The problems of natural disaster predicting and accomplishing a synthesis of environmental monitoring systems to collect, store, and process relevant information for their solution are analysed. A three-level methodology is proposed for making decisions concerning the natural disaster dynamics. The methodology is based on the assessment of environmental indicators and the use of numerical models of the environment

Assessment of Predictive Markers of Response to Neoadjuvant Chemotherapy in Breast Cancer

Directory of Open Access Journals (Sweden)

Mallika Tewari

2010-10-01

Conclusion: Of all parameters examined, only the apoptosis-related genes (Bcl-2 and BAX seemed to exert some influence on the response to NACT, and neither by itself was sufficient to predict pCR; however, 50 patients is not sufficient to simultaneously analyse several predictive markers.

Single- and multi-frequency bioelectrical impedance analyses to analyse body composition in maintenance haemodialysis patients: comparison with dual-energy x-ray absorptiometry

International Nuclear Information System (INIS)

Donadio, C; Halim, A Ben; Caprio, F; Grassi, G; Khedr, B; Mazzantini, M

2008-01-01

The aim of this study was to evaluate the adequacy of single-frequency (sf-BIA) and multi-frequency bioelectrical impedance analyses (mf-BIA), in comparison with dual-energy x-ray absorptiometry (DXA), to evaluate body composition in maintenance haemodialysis (MHD) patients. Body composition of 27 adult MHD patients (9 f, 18 m), BMI 17.5–34.4 kg m −2 , was examined with DXA and BIA, with two different sf-BIA and 1 mf-BIA analysers. Biochemical markers of nutritional status and adequacy of dialytic treatment were also determined. Fat mass (FM) estimated by the different BIA analysers was found to be slightly but significantly higher than FM measured by DXA. In contrast, fat-free mass (FFM) obtained with BIA was found to be slightly but significantly lower than FFM DXA. No significant differences were found between LBM-DXA (that is FFM-DXA minus bone mass) and the different FFM BIA. The lowest mean prediction error versus DXA values was found with sf1BIA. In any case, a close correlation was found between all BIA values and DXA values, particularly for FFM. Furthermore, FFM and LBM results were significantly correlated with serum creatinine, which in MHD patients is an indicator of muscle mass. These results indicate that BIA can be used to evaluate body composition in MHD patients

K-West and K-East basin thermal analyses for dry conditions

International Nuclear Information System (INIS)

Beaver, T.R.; Cramer, E.R.; Hinman, C.A.

1994-01-01

Detailed 3 dimensional thermal analyses of the 100K East and 100 K West basins were conducted to determine the peak fuel temperature for intact fuel in the event of a complete loss of water from the basins. Thermal models for the building, an array of fuel encapsulation canisters on the basin floor, and the fuel within a single canister are described along with conservative predictions for the maximum expected temperatures for the loss of water event

SN transport analyses of critical reactor experiments for the SNTP program

International Nuclear Information System (INIS)

Mays, C.W.

1993-01-01

The capability of S N methodology to accurately predict the neutronics behavior of a compact, light water-moderated reactor is examined. This includes examining the effects of cross-section modeling and the choice of spatial and angular representation. The isothermal temperature coefficient in the range of 293 K to 355 K is analyzed, as well as the radial fission density profile across the central fuel element. Measured data from a series of critical experiments are used for these analyses

Seismic criteria studies and analyses. Quarterly progress report No. 3. [LMFBR

Energy Technology Data Exchange (ETDEWEB)

1975-01-03

Information is presented concerning the extent to which vibratory motions at the subsurface foundation level might differ from motions at the ground surface and the effects of the various subsurface materials on the overall Clinch River Breeder Reactor site response; seismic analyses of LMFBR type reactors to establish analytical procedures for predicting structure stresses and deformations; and aspects of the current technology regarding the representation of energy losses in nuclear power plants as equivalent viscous damping.

On-line prediction of BWR transients in support of plant operation and safety analyses

International Nuclear Information System (INIS)

Wulff, W.; Cheng, H.S.; Lekach, S.V.; Mallen, A.N.

1983-01-01

A combination of advanced modeling techniques and modern, special-purpose peripheral minicomputer technology is presented which affords realistic predictions of plant transient and severe off-normal events in LWR power plants through on-line simulations at a speed ten times greater than actual process speeds. Results are shown for a BWR plant simulation. The mathematical models account for nonequilibrium, nonhomogeneous two-phase flow effects in the coolant, for acoustical effects in the steam line and for the dynamics of the recirculation loop and feed-water train. Point kinetics incorporate reactivity feedback for void fraction, for fuel temperature, and for coolant temperature. Control systems and trip logic are simulated for the nuclear steam supply system

Fluid-structure-interaction analyses of reactor vessel using improved hybrid Lagrangian Eulerian code ALICE-II

Energy Technology Data Exchange (ETDEWEB)

Wang, C.Y.

1993-06-01

This paper describes fluid-structure-interaction and structure response analyses of a reactor vessel subjected to loadings associated with postulated accidents, using the hybrid Lagrangian-Eulerian code ALICE-II. This code has been improved recently to accommodate many features associated with innovative designs of reactor vessels. Calculational capabilities have been developed to treat water in the reactor cavity outside the vessel, internal shield structures and internal thin shells. The objective of the present analyses is to study the cover response and potential for missile generation in response to a fuel-coolant interaction in the core region. Three calculations were performed using the cover weight as a parameter. To study the effect of the cavity water, vessel response calculations for both wet- and dry-cavity designs are compared. Results indicate that for all cases studied and for the design parameters assumed, the calculated cover displacements are all smaller than the bolts` ultimate displacement and no missile generation of the closure head is predicted. Also, solutions reveal that the cavity water of the wet-cavity design plays an important role of restraining the downward displacement of the bottom head. Based on these studies, the analyses predict that the structure integrity is maintained throughout the postulated accident for the wet-cavity design.

Fluid-structure-interaction analyses of reactor vessel using improved hybrid Lagrangian Eulerian code ALICE-II

Energy Technology Data Exchange (ETDEWEB)

Wang, C.Y.

1993-01-01

This paper describes fluid-structure-interaction and structure response analyses of a reactor vessel subjected to loadings associated with postulated accidents, using the hybrid Lagrangian-Eulerian code ALICE-II. This code has been improved recently to accommodate many features associated with innovative designs of reactor vessels. Calculational capabilities have been developed to treat water in the reactor cavity outside the vessel, internal shield structures and internal thin shells. The objective of the present analyses is to study the cover response and potential for missile generation in response to a fuel-coolant interaction in the core region. Three calculations were performed using the cover weight as a parameter. To study the effect of the cavity water, vessel response calculations for both wet- and dry-cavity designs are compared. Results indicate that for all cases studied and for the design parameters assumed, the calculated cover displacements are all smaller than the bolts' ultimate displacement and no missile generation of the closure head is predicted. Also, solutions reveal that the cavity water of the wet-cavity design plays an important role of restraining the downward displacement of the bottom head. Based on these studies, the analyses predict that the structure integrity is maintained throughout the postulated accident for the wet-cavity design.

Response surface use in safety analyses

International Nuclear Information System (INIS)

Prosek, A.

1999-01-01

When thousands of complex computer code runs related to nuclear safety are needed for statistical analysis, the response surface is used to replace the computer code. The main purpose of the study was to develop and demonstrate a tool called optimal statistical estimator (OSE) intended for response surface generation of complex and non-linear phenomena. The performance of optimal statistical estimator was tested by the results of 59 different RELAP5/MOD3.2 code calculations of the small-break loss-of-coolant accident in a two loop pressurized water reactor. The results showed that OSE adequately predicted the response surface for the peak cladding temperature. Some good characteristic of the OSE like monotonic function between two neighbor points and independence on the number of output parameters suggest that OSE can be used for response surface generation of any safety or system parameter in the thermal-hydraulic safety analyses.(author)

Bond return predictability in expansions and recessions

DEFF Research Database (Denmark)

Engsted, Tom; Møller, Stig Vinther; Jensen, Magnus David Sander

We document that over the period 1953-2011 US bond returns are predictable in expansionary periods but unpredictable during recessions. This result holds in both in-sample and out-of-sample analyses and using both univariate regressions and combination forecasting techniques. A simulation study...... but negative in recessions. The results are also consistent with tests showing that the expectations hypothesis of the term structure holds in recessions but not in expansions. However, the results for bonds are in sharp contrast to results for stocks showing that stock returns are predictable in recessions...... but not in expansions. Thus, our results indicate that there is not a common predictive pattern of stock and bond returns associated with the state of the economy....

Predictive control and identification: Applications to steering dynamics

DEFF Research Database (Denmark)

Hansen, Anca Daniela

1996-01-01

and of the loss function, which defines the optimality of the control. Some guidelines on how to choose the design parameters, depending on the type of process to be controlled and on the required control performance, are presented. A predictive track keeping system for a Mariner Class Vessel is formulated based...... the under- standing of the connection between identification and control, analysed in Chapter 7. Chapter 7 focuses on how to make the on-line identification for predictive control more robust towards unmodelled dynamics. The theory is verified via simulation studies on a Mariner Class Vessel. The effects...... and the need of a prefilter in the estimation are analysed and illustrated. Based on the idea that the control criterion must be dual to the estimation criterion, an iterative optimal prefilter is designed. This seems to be an appealing way to tune the model towards the objective for which the model...

Association between Adult Height and Risk of Colorectal, Lung, and Prostate Cancer: Results from Meta-analyses of Prospective Studies and Mendelian Randomization Analyses

Science.gov (United States)

Khankari, Nikhil K.; Shu, Xiao-Ou; Wen, Wanqing; Kraft, Peter; Lindström, Sara; Peters, Ulrike; Schildkraut, Joellen; Schumacher, Fredrick; Bofetta, Paolo; Risch, Angela; Bickeböller, Heike; Amos, Christopher I.; Easton, Douglas; Gruber, Stephen B.; Haiman, Christopher A.; Hunter, David J.; Chanock, Stephen J.; Pierce, Brandon L.; Zheng, Wei

2016-01-01

Background Observational studies examining associations between adult height and risk of colorectal, prostate, and lung cancers have generated mixed results. We conducted meta-analyses using data from prospective cohort studies and further carried out Mendelian randomization analyses, using height-associated genetic variants identified in a genome-wide association study (GWAS), to evaluate the association of adult height with these cancers. Methods and Findings A systematic review of prospective studies was conducted using the PubMed, Embase, and Web of Science databases. Using meta-analyses, results obtained from 62 studies were summarized for the association of a 10-cm increase in height with cancer risk. Mendelian randomization analyses were conducted using summary statistics obtained for 423 genetic variants identified from a recent GWAS of adult height and from a cancer genetics consortium study of multiple cancers that included 47,800 cases and 81,353 controls. For a 10-cm increase in height, the summary relative risks derived from the meta-analyses of prospective studies were 1.12 (95% CI 1.10, 1.15), 1.07 (95% CI 1.05, 1.10), and 1.06 (95% CI 1.02, 1.11) for colorectal, prostate, and lung cancers, respectively. Mendelian randomization analyses showed increased risks of colorectal (odds ratio [OR] = 1.58, 95% CI 1.14, 2.18) and lung cancer (OR = 1.10, 95% CI 1.00, 1.22) associated with each 10-cm increase in genetically predicted height. No association was observed for prostate cancer (OR = 1.03, 95% CI 0.92, 1.15). Our meta-analysis was limited to published studies. The sample size for the Mendelian randomization analysis of colorectal cancer was relatively small, thus affecting the precision of the point estimate. Conclusions Our study provides evidence for a potential causal association of adult height with the risk of colorectal and lung cancers and suggests that certain genetic factors and biological pathways affecting adult height may also affect the

Autonomous and controlled motivational regulations for multiple health-related behaviors: between- and within-participants analyses

Science.gov (United States)

Hagger, M.S.; Hardcastle, S.J.; Chater, A.; Mallett, C.; Pal, S.; Chatzisarantis, N.L.D.

2014-01-01

Self-determination theory has been applied to the prediction of a number of health-related behaviors with self-determined or autonomous forms of motivation generally more effective in predicting health behavior than non-self-determined or controlled forms. Research has been confined to examining the motivational predictors in single health behaviors rather than comparing effects across multiple behaviors. The present study addressed this gap in the literature by testing the relative contribution of autonomous and controlling motivation to the prediction of a large number of health-related behaviors, and examining individual differences in self-determined motivation as a moderator of the effects of autonomous and controlling motivation on health behavior. Participants were undergraduate students (N = 140) who completed measures of autonomous and controlled motivational regulations and behavioral intention for 20 health-related behaviors at an initial occasion with follow-up behavioral measures taken four weeks later. Path analysis was used to test a process model for each behavior in which motivational regulations predicted behavior mediated by intentions. Some minor idiosyncratic findings aside, between-participants analyses revealed significant effects for autonomous motivational regulations on intentions and behavior across the 20 behaviors. Effects for controlled motivation on intentions and behavior were relatively modest by comparison. Intentions mediated the effect of autonomous motivation on behavior. Within-participants analyses were used to segregate the sample into individuals who based their intentions on autonomous motivation (autonomy-oriented) and controlled motivation (control-oriented). Replicating the between-participants path analyses for the process model in the autonomy- and control-oriented samples did not alter the relative effects of the motivational orientations on intention and behavior. Results provide evidence for consistent effects

Fracture Mechanics Prediction of Fatigue Life of Aluminum Highway Bridges

DEFF Research Database (Denmark)

Rom, Søren; Agerskov, Henning

2015-01-01

Fracture mechanics prediction of the fatigue life of aluminum highway bridges under random loading is studied. The fatigue life of welded joints has been determined from fracture mechanics analyses and the results obtained have been compared with results from experimental investigations. The fati......Fracture mechanics prediction of the fatigue life of aluminum highway bridges under random loading is studied. The fatigue life of welded joints has been determined from fracture mechanics analyses and the results obtained have been compared with results from experimental investigations...... against fatigue in aluminum bridges, may give results which are unconservative. Furthermore, it was in both investigations found that the validity of the results obtained from Miner's rule will depend on the distribution of the load history in tension and compression....

Sensitivity analyses of biodiesel thermo-physical properties under diesel engine conditions

DEFF Research Database (Denmark)

Cheng, Xinwei; Ng, Hoon Kiat; Gan, Suyin

2016-01-01

This reported work investigates the sensitivities of spray and soot developments to the change of thermo-physical properties for coconut and soybean methyl esters, using two-dimensional computational fluid dynamics fuel spray modelling. The choice of test fuels made was due to their contrasting...... saturation-unsaturation compositions. The sensitivity analyses for non-reacting and reacting sprays were carried out against a total of 12 thermo-physical properties, at an ambient temperature of 900 K and density of 22.8 kg/m3. For the sensitivity analyses, all the thermo-physical properties were set...... as the baseline case and each property was individually replaced by that of diesel. The significance of individual thermo-physical property was determined based on the deviations found in predictions such as liquid penetration, ignition delay period and peak soot concentration when compared to those of baseline...

A novel health indicator for on-line lithium-ion batteries remaining useful life prediction

Science.gov (United States)

Zhou, Yapeng; Huang, Miaohua; Chen, Yupu; Tao, Ye

2016-07-01

Prediction of lithium-ion batteries remaining useful life (RUL) plays an important role in an intelligent battery management system. The capacity and internal resistance are often used as the batteries health indicator (HI) for quantifying degradation and predicting RUL. However, on-line measurement of capacity and internal resistance are hardly realizable due to the not fully charged and discharged condition and the extremely expensive cost, respectively. Therefore, there is a great need to find an optional way to deal with this plight. In this work, a novel HI is extracted from the operating parameters of lithium-ion batteries for degradation modeling and RUL prediction. Moreover, Box-Cox transformation is employed to improve HI performance. Then Pearson and Spearman correlation analyses are utilized to evaluate the similarity between real capacity and the estimated capacity derived from the HI. Next, both simple statistical regression technique and optimized relevance vector machine are employed to predict the RUL based on the presented HI. The correlation analyses and prediction results show the efficiency and effectiveness of the proposed HI for battery degradation modeling and RUL prediction.

MDOT Pavement Management System : Prediction Models and Feedback System

Science.gov (United States)

2000-10-01

As a primary component of a Pavement Management System (PMS), prediction models are crucial for one or more of the following analyses: : maintenance planning, budgeting, life-cycle analysis, multi-year optimization of maintenance works program, and a...

Comparing direct image and wavelet transform-based approaches to analysing remote sensing imagery for predicting wildlife distribution

NARCIS (Netherlands)

Murwira, A.; Skidmore, A.K.

2010-01-01

In this study we tested the ability to predict the probability of elephant (Loxodonta africana) presence in an agricultural landscape of Zimbabwe based on three methods of measuring the spatial heterogeneity in vegetation cover, where vegetation cover was measured using the Landsat Thematic Mapper

Assessing deep-seated landslide susceptibility using 3-D groundwater and slope-stability analyses, southwestern Seattle, Washington

Science.gov (United States)

Brien, Dianne L.; Reid, Mark E.

2008-01-01

In Seattle, Washington, deep-seated landslides on bluffs along Puget Sound have historically caused extensive damage to land and structures. These large failures are controlled by three-dimensional (3-D) variations in strength and pore-water pressures. We assess the slope stability of part of southwestern Seattle using a 3-D limit-equilibrium analysis coupled with a 3-D groundwater flow model. Our analyses use a high-resolution digital elevation model (DEM) combined with assignment of strength and hydraulic properties based on geologic units. The hydrogeology of the Seattle area consists of a layer of permeable glacial outwash sand that overlies less permeable glacial lacustrine silty clay. Using a 3-D groundwater model, MODFLOW-2000, we simulate a water table above the less permeable units and calibrate the model to observed conditions. The simulated pore-pressure distribution is then used in a 3-D slope-stability analysis, SCOOPS, to quantify the stability of the coastal bluffs. For wet winter conditions, our analyses predict that the least stable areas are steep hillslopes above Puget Sound, where pore pressures are elevated in the outwash sand. Groundwater flow converges in coastal reentrants, resulting in elevated pore pressures and destabilization of slopes. Regions predicted to be least stable include the areas in or adjacent to three mapped historically active deep-seated landslides. The results of our 3-D analyses differ significantly from a slope map or results from one-dimensional (1-D) analyses.

Does life satisfaction predict five-year mortality in community-living older adults?

Science.gov (United States)

St John, Philip D; Mackenzie, Corey; Menec, Verena

2015-01-01

Depression and depressive symptoms predict death, but it is less clear if more general measures of life satisfaction (LS) predict death. Our objectives were to determine: (1) if LS predicts mortality over a five-year period in community-living older adults; and (2) which aspects of LS predict death. 1751 adults over the age of 65 who were living in the community were sampled from a representative population sampling frame in 1991/1992 and followed five years later. Age, gender, and education were self-reported. An index of multimorbidity and the Older American Resource Survey measured health and functional status, and the Terrible-Delightful Scale assessed overall LS as well as satisfaction with: health, finances, family, friends, housing, recreation, self-esteem, religion, and transportation. Cox proportional hazards models examined the influence of LS on time to death. 417 participants died during the five-year study period. Overall LS and all aspects of LS except finances, religion, and self-esteem predicted death in unadjusted analyses. In fully adjusted analyses, LS with health, housing, and recreation predicted death. Other aspects of LS did not predict death after accounting for functional status and multimorbidity. LS predicted death, but certain aspects of LS are more strongly associated with death. The effect of LS is complex and may be mediated or confounded by health and functional status. It is important to consider different domains of LS when considering the impact of this important emotional indicator on mortality among older adults.

Stigma in science: the case of earthquake prediction.

Science.gov (United States)

Joffe, Helene; Rossetto, Tiziana; Bradley, Caroline; O'Connor, Cliodhna

2018-01-01

This paper explores how earthquake scientists conceptualise earthquake prediction, particularly given the conviction of six earthquake scientists for manslaughter (subsequently overturned) on 22 October 2012 for having given inappropriate advice to the public prior to the L'Aquila earthquake of 6 April 2009. In the first study of its kind, semi-structured interviews were conducted with 17 earthquake scientists and the transcribed interviews were analysed thematically. The scientists primarily denigrated earthquake prediction, showing strong emotive responses and distancing themselves from earthquake 'prediction' in favour of 'forecasting'. Earthquake prediction was regarded as impossible and harmful. The stigmatisation of the subject is discussed in the light of research on boundary work and stigma in science. The evaluation reveals how mitigation becomes the more favoured endeavour, creating a normative environment that disadvantages those who continue to pursue earthquake prediction research. Recommendations are made for communication with the public on earthquake risk, with a focus on how scientists portray uncertainty. © 2018 The Author(s). Disasters © Overseas Development Institute, 2018.

Modelling bankruptcy prediction models in Slovak companies

Directory of Open Access Journals (Sweden)

Kovacova Maria

2017-01-01

Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

Accurate predictions for the LHC made easy

CERN Multimedia

CERN. Geneva

2014-01-01

The data recorded by the LHC experiments is of a very high quality. To get the most out of the data, precise theory predictions, including uncertainty estimates, are needed to reduce as much as possible theoretical bias in the experimental analyses. Recently, significant progress has been made in computing Next-to-Leading Order (NLO) computations, including matching to the parton shower, that allow for these accurate, hadron-level predictions. I shall discuss one of these efforts, the MadGraph5_aMC@NLO program, that aims at the complete automation of predictions at the NLO accuracy within the SM as well as New Physics theories. I’ll illustrate some of the theoretical ideas behind this program, show some selected applications to LHC physics, as well as describe the future plans.

Modeling a Predictive Energy Equation Specific for Maintenance Hemodialysis.

Science.gov (United States)

Byham-Gray, Laura D; Parrott, J Scott; Peters, Emily N; Fogerite, Susan Gould; Hand, Rosa K; Ahrens, Sean; Marcus, Andrea Fleisch; Fiutem, Justin J

2017-03-01

Hypermetabolism is theorized in patients diagnosed with chronic kidney disease who are receiving maintenance hemodialysis (MHD). We aimed to distinguish key disease-specific determinants of resting energy expenditure to create a predictive energy equation that more precisely establishes energy needs with the intent of preventing protein-energy wasting. For this 3-year multisite cross-sectional study (N = 116), eligible participants were diagnosed with chronic kidney disease and were receiving MHD for at least 3 months. Predictors for the model included weight, sex, age, C-reactive protein (CRP), glycosylated hemoglobin, and serum creatinine. The outcome variable was measured resting energy expenditure (mREE). Regression modeling was used to generate predictive formulas and Bland-Altman analyses to evaluate accuracy. The majority were male (60.3%), black (81.0%), and non-Hispanic (76.7%), and 23% were ≥65 years old. After screening for multicollinearity, the best predictive model of mREE ( R 2 = 0.67) included weight, age, sex, and CRP. Two alternative models with acceptable predictability ( R 2 = 0.66) were derived with glycosylated hemoglobin or serum creatinine. Based on Bland-Altman analyses, the maintenance hemodialysis equation that included CRP had the best precision, with the highest proportion of participants' predicted energy expenditure classified as accurate (61.2%) and with the lowest number of individuals with underestimation or overestimation. This study confirms disease-specific factors as key determinants of mREE in patients on MHD and provides a preliminary predictive energy equation. Further prospective research is necessary to test the reliability and validity of this equation across diverse populations of patients who are receiving MHD.

Analyses of HANARO bundle experiment data using MATRA-h: revision

Energy Technology Data Exchange (ETDEWEB)

Lim, In Cheol; Park, Cheol; Chae, Hee Taek; Lee, Choong Sung

1999-08-01

When the construction and operation license for HANARO was renewed in 1995, imposed was a condition that the safety limit CHFR should have the margin of 25 percent. The reason for this were that the number of bundle CHF experiment data was not enough for the validation of the prediction of CHF in bundle geometry and that the ability of COBRA/KMRR to prediction the local coolant condition was not fully validated. For the resolution of this imposition, more bundle CHF data were gathered and the subchannel exit temperature distribution was obtained during the in-core irradiation test of instrumented bundle (Type-B bundle). also, for these experimental data, subchannel analyses were performed by using MATRA-h code which is the modified version of MATRA-a which is a modified version of KAERI's MATRA-a for the application to HANARO. By comparing the analysis results with the experimental results, it was found that the HANARO subchannel analysis method would give the conservative or best-estimated predictions for the CHF in bundle geometry. This report is the revision of KAERI/TR-1090/98 on the analysis of bundle experiment data using MATRA-h. (Author). 16 refs., 16 tabs., 25 figs.

Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

Science.gov (United States)

Li, Jin; Tran, Maggie; Siwabessy, Justy

2016-01-01

Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

Seasonal predictability of Kiremt rainfall in coupled general circulation models

Science.gov (United States)

Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

2017-11-01

The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

Kaolin Quality Prediction from Samples: A Bayesian Network Approach

International Nuclear Information System (INIS)

Rivas, T.; Taboada, J.; Ordonez, C.; Matias, J. M.

2009-01-01

We describe the results of an expert system applied to the evaluation of samples of kaolin for industrial use in paper or ceramic manufacture. Different machine learning techniques - classification trees, support vector machines and Bayesian networks - were applied with the aim of evaluating and comparing their interpretability and prediction capacities. The predictive capacity of these models for the samples analyzed was highly satisfactory, both for ceramic quality and paper quality. However, Bayesian networks generally proved to be the most useful technique for our study, as this approach combines good predictive capacity with excellent interpretability of the kaolin quality structure, as it graphically represents relationships between variables and facilitates what-if analyses.

Effect of bubble interface parameters on predicted of bubble departure diameter in a narrow channel

International Nuclear Information System (INIS)

Xu Jianjun; Xie Tianzhou; Zhou Wenbin; Chen Bingde; Huang Yanping

2014-01-01

The predicted model on the bubble departure diameter in a narrow channel is built by analysis of forces acting on the bubble, and effects of bubble interface parameters such as the bubble inclination angle, upstream contact angle, downstream contact angle and bubble contact diameter on predicted bubble departure diameters in a narrow channel are analysed by comparing with the visual experimental data. Based on the above results, the bubble interface parameters as the input parameters used to obtain the bubble departure diameter in a narrow channel are assured, and the bubble departure diameters in a narrow channel are predicted by solving the force equation. The predicted bubble departure diameters are verified by the 58 bubble departure diameters obtained from the vertical and inclined visual experiment, and the predicted results agree with the experimental results. The different forces acting on the bubble are obtained and the effect of thermal parameters in this experiment on bubble departure diameters is analysed. (authors)

The role of mentor type and timing in predicting educational attainment.

Science.gov (United States)

Fruiht, Veronica M; Wray-Lake, Laura

2013-09-01

Having an adult mentor during adolescence has been found to predict academic success. Building on previous work, the present study examined interactions between the type of mentor (i.e., kin, teacher, friend, or community), the time that mentor became important (i.e., before, during, or after high school), and the ethnicity of the protégé in predicting educational attainment in young adulthood. Analyses used Waves III and IV of the National Longitudinal Study of Adolescent Health (N = 2,409). Participants' ages ranged from 18 to 27 (M = 21.75, SD = 1.79). The sample was 56.7 % female and nationally representative of ethnic diversity. Analyses showed that having a teacher-mentor was more predictive of educational attainment than having other types of mentors and that overall, having a mentor after high school predicts the most educational attainment. Kin- and community-mentors appeared to be more important to educational attainment during and before high school, respectively. Findings were consistent across ethnic groups. Overall, results highlight the value of teacher-mentors throughout childhood, adolescence, and early adulthood and our study further suggests that different types of mentors may be particularly useful at specific points in development.

Predicting Word Reading Ability: A Quantile Regression Study

Science.gov (United States)

McIlraith, Autumn L.

2018-01-01

Predictors of early word reading are well established. However, it is unclear if these predictors hold for readers across a range of word reading abilities. This study used quantile regression to investigate predictive relationships at different points in the distribution of word reading. Quantile regression analyses used preschool and…

Predicting travel time variability for cost-benefit analysis

NARCIS (Netherlands)

Peer, S.; Koopmans, C.; Verhoef, E.T.

2010-01-01

Unreliable travel times cause substantial costs to travelers. Nevertheless, they are not taken into account in many cost-benefit-analyses (CBA), or only in very rough ways. This paper aims at providing simple rules on how variability can be predicted, based on travel time data from Dutch highways.

Analysis methods for predicting the behaviour of isolators and formulation of simplified models for use in predicting response of structures to earthquake type input

International Nuclear Information System (INIS)

2002-01-01

This report describes the simplified models for predicting the response of high-damping natural rubber bearings (HDNRB) to earthquake ground motions and benchmark problems for assessing the accuracy of finite element analyses in designing base-isolators. (author)

Presence of a mitochondrial-type 70-kDa heat shock protein in Trichomonas vaginalis suggests a very early mitochondrial endosymbiosis in eukaryotes

Science.gov (United States)

Germot, Agnès; Philippe, Hervé; Le Guyader, Hervé

1996-01-01

Molecular phylogenetic analyses, based mainly on ribosomal RNA, show that three amitochondriate protist lineages, diplomonads, microsporidia, and trichomonads, emerge consistently at the base of the eukaryotic tree before groups having mitochondria. This suggests that these groups could have diverged before the mitochondrial endosymbiosis. Nevertheless, since all these organisms live in anaerobic environments, the absence of mitochondria might be due to secondary loss, as demonstrated for the later emerging eukaryote Entamoeba histolytica. We have now isolated from Trichomonas vaginalis a gene encoding a chaperone protein (HSP70) that in other lineages is addressed to the mitochondrial compartment. The phylogenetic reconstruction unambiguously located this HSP70 within a large set of mitochondrial sequences, itself a sister-group of α-purple bacteria. In addition, the T. vaginalis protein exhibits the GDAWV sequence signature, so far exclusively found in mitochondrial HSP70 and in proteobacterial dnaK. Thus mitochondrial endosymbiosis could have occurred earlier than previously assumed. The trichomonad double membrane-bounded organelles, the hydrogenosomes, could have evolved from mitochondria. PMID:8962101

Frequency, probability, and prediction: easy solutions to cognitive illusions?

Science.gov (United States)

Griffin, D; Buehler, R

1999-02-01

Many errors in probabilistic judgment have been attributed to people's inability to think in statistical terms when faced with information about a single case. Prior theoretical analyses and empirical results imply that the errors associated with case-specific reasoning may be reduced when people make frequentistic predictions about a set of cases. In studies of three previously identified cognitive biases, we find that frequency-based predictions are different from-but no better than-case-specific judgments of probability. First, in studies of the "planning fallacy, " we compare the accuracy of aggregate frequency and case-specific probability judgments in predictions of students' real-life projects. When aggregate and single-case predictions are collected from different respondents, there is little difference between the two: Both are overly optimistic and show little predictive validity. However, in within-subject comparisons, the aggregate judgments are significantly more conservative than the single-case predictions, though still optimistically biased. Results from studies of overconfidence in general knowledge and base rate neglect in categorical prediction underline a general conclusion. Frequentistic predictions made for sets of events are no more statistically sophisticated, nor more accurate, than predictions made for individual events using subjective probability. Copyright 1999 Academic Press.

Cancer predictive value of cytogenetic markers used in occupational health surveillance programs

DEFF Research Database (Denmark)

Hagmar, L; Bonassi, S; Strömberg, U

1998-01-01

It has not previously been clear whether cytogenetic biomarkers in healthy subjects will predict cancer. Earlier analyses of a Nordic and an Italian cohort indicated predictivity for chromosomal aberrations (CAS) but not for sister chromatid exchanges (SCES). A pooled analysis of the updated......, occupational exposures and smoking, will be assessed in a case-referent study within the study base....

Invited review: A commentary on predictive cheese yield formulas.

Science.gov (United States)

Emmons, D B; Modler, H W

2010-12-01

Predictive cheese yield formulas have evolved from one based only on casein and fat in 1895. Refinements have included moisture and salt in cheese and whey solids as separate factors, paracasein instead of casein, and exclusion of whey solids from moisture associated with cheese protein. The General, Barbano, and Van Slyke formulas were tested critically using yield and composition of milk, whey, and cheese from 22 vats of Cheddar cheese. The General formula is based on the sum of cheese components: fat, protein, moisture, salt, whey solids free of fat and protein, as well as milk salts associated with paracasein. The testing yielded unexpected revelations. It was startling that the sum of components in cheese was SofC) in cheese. The apparent low estimation of SofC led to the idea of adjusting upwards, for each vat, the 5 measured components in the formula by the observed SofC, as a fraction. The mean of the adjusted predicted yields as percentages of actual yields was 99.99%. The adjusted forms of the General, Barbano, and Van Slyke formulas gave predicted yields equal to the actual yields. It was apparent that unadjusted yield formulas did not accurately predict yield; however, unadjusted PY%AY can be useful as a control tool for analyses of cheese and milk. It was unexpected that total milk protein in the adjusted General formula gave the same predicted yields as casein and paracasein, indicating that casein or paracasein may not always be necessary for successful yield prediction. The use of constants for recovery of fat and protein in the adjusted General formula gave adjusted predicted yields equal to actual yields, indicating that analyses of cheese for protein and fat may not always be necessary for yield prediction. Composition of cheese was estimated using a predictive formula; actual yield was needed for estimation of composition. Adjusted formulas are recommended for estimating target yields and cheese yield efficiency. Constants for solute exclusion

Refining intra-protein contact prediction by graph analysis

Directory of Open Access Journals (Sweden)

Eyal Eran

2007-05-01

Full Text Available Abstract Background Accurate prediction of intra-protein residue contacts from sequence information will allow the prediction of protein structures. Basic predictions of such specific contacts can be further refined by jointly analyzing predicted contacts, and by adding information on the relative positions of contacts in the protein primary sequence. Results We introduce a method for graph analysis refinement of intra-protein contacts, termed GARP. Our previously presented intra-contact prediction method by means of pair-to-pair substitution matrix (P2PConPred was used to test the GARP method. In our approach, the top contact predictions obtained by a basic prediction method were used as edges to create a weighted graph. The edges were scored by a mutual clustering coefficient that identifies highly connected graph regions, and by the density of edges between the sequence regions of the edge nodes. A test set of 57 proteins with known structures was used to determine contacts. GARP improves the accuracy of the P2PConPred basic prediction method in whole proteins from 12% to 18%. Conclusion Using a simple approach we increased the contact prediction accuracy of a basic method by 1.5 times. Our graph approach is simple to implement, can be used with various basic prediction methods, and can provide input for further downstream analyses.

Application of support vector regression (SVR) for stream flow prediction on the Amazon basin

CSIR Research Space (South Africa)

Du Toit, Melise

2016-10-01

Full Text Available regression technique is used in this study to analyse historical stream flow occurrences and predict stream flow values for the Amazon basin. Up to twelve month predictions are made and the coefficient of determination and root-mean-square error are used...

BN-600 hybrid core benchmark analyses

International Nuclear Information System (INIS)

Kim, Y.I.; Stanculescu, A.; Finck, P.; Hill, R.N.; Grimm, K.N.

2003-01-01

Benchmark analyses for the hybrid BN-600 reactor that contains three uranium enrichment zones and one plutonium zone in the core, have been performed within the frame of an IAEA sponsored Coordinated Research Project. The results for several relevant reactivity parameters obtained by the participants with their own state-of-the-art basic data and codes, were compared in terms of calculational uncertainty, and their effects on the ULOF transient behavior of the hybrid BN-600 core were evaluated. The comparison of the diffusion and transport results obtained for the homogeneous representation generally shows good agreement for most parameters between the RZ and HEX-Z models. The burnup effect and the heterogeneity effect on most reactivity parameters also show good agreement for the HEX-Z diffusion and transport theory results. A large difference noticed for the sodium and steel density coefficients is mainly due to differences in the spatial coefficient predictions for non fuelled regions. The burnup reactivity loss was evaluated to be 0.025 (4.3 $) within ∼ 5.0% standard deviation. The heterogeneity effect on most reactivity coefficients was estimated to be small. The heterogeneity treatment reduced the control rod worth by 2.3%. The heterogeneity effect on the k-eff and control rod worth appeared to differ strongly depending on the heterogeneity treatment method. A substantial spread noticed for several reactivity coefficients did not give a significant impact on the transient behavior prediction. This result is attributable to compensating effects between several reactivity effects and the specific design of the partially MOX fuelled hybrid core. (author)

Prediction of the semiscale blowdown heat transfer test S-02-8 (NRC Standard Problem Five)

International Nuclear Information System (INIS)

Fujita, N.; Irani, A.A.; Mecham, D.C.; Sawtelle, G.R.; Moore, K.V.

1976-10-01

Standard Problem Five was the prediction of test S-02-8 in the Semiscale Mod-1 experimental program. The Semiscale System is an electrically heated experiment designed to produce data on system performance typical of PWR thermal-hydraulic behavior. The RELAP4 program used for these analyses is a digital computer program developed to predict the thermal-hydraulic behavior of experimental systems and water-cooled nuclear reactors subjected to postulated transients. The RELAP4 predictions of Standard Problem 5 were in good overall agreement with the measured hydraulic data. Fortunately, sufficient experience has been gained with the semiscale break configuration and the critical flow models in RELAP4 to accurately predict the break flow and, hence the overall system depressurization. Generally, the hydraulic predictions are quite good in regions where homogeneity existed. Where separation effects occurred, predictions are not as good, and the data oscillations and error bands are larger. A large discrepancy existed among the measured heater rod temperature data as well as between these data and predicted values. Several potential causes for these differences were considered, and several post test analyses were performed in order to evaluate the discrepancies

Decisions among the undecided: implicit attitudes predict future voting behavior of undecided voters.

Directory of Open Access Journals (Sweden)

Kristjen B Lundberg

Full Text Available Implicit attitudes have been suggested as a key to unlock the hidden preferences of undecided voters. Past research, however, offered mixed support for this hypothesis. The present research used a large nationally representative sample and a longitudinal design to examine the predictive utility of implicit and explicit attitude measures in the 2008 U.S. presidential election. In our analyses, explicit attitudes toward candidates predicted voting better for decided than undecided voters, but implicit candidate attitudes were predictive of voting for both decided and undecided voters. Extending our examination to implicit and explicit racial attitudes, we found the same pattern. Taken together, these results provide convergent evidence that implicit attitudes predict voting about as well for undecided as for decided voters. We also assessed a novel explanation for these effects by evaluating whether implicit attitudes may predict the choices of undecided voters, in part, because they are neglected when people introspect about their confidence. Consistent with this idea, we found that the extremity of explicit but not implicit attitudes was associated with greater confidence. These analyses shed new light on the utility of implicit measures in predicting future behavior among individuals who feel undecided. Considering the prior studies together with this new evidence, the data seem to be consistent that implicit attitudes may be successful in predicting the behavior of undecided voters.

Adolescent conscientiousness predicts lower lifetime unemployment.

Science.gov (United States)

Egan, Mark; Daly, Michael; Delaney, Liam; Boyce, Christopher J; Wood, Alex M

2017-04-01

Existing research on Big Five personality and unemployment has relied on personality measures elicited after the respondents had already spent years in the labor market, an experience that could change personality. We clarify the direction of influence by using the British Cohort Study (N = 4,206) to examine whether conscientiousness and other Big Five personality traits at age 16-17 predict unemployment over age 16-42. Our hypothesis that higher conscientiousness in adolescence would predict lower unemployment was supported. In analyses controlling for intelligence, gender, and parental socioeconomic status, the less conscientious (-1 SD) had a predicted probability of unemployment twice as high (3.4% vs. 1.7%) as the highly conscientious (+1 SD), an effect size comparable to intelligence. Mediation analysis revealed that academic motivation and educational attainment explained only 8.9% of this association. Fostering conscientiousness in early life may be an effective way to reduce unemployment throughout adulthood. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Parsimony in personality: predicting sexual prejudice.

Science.gov (United States)

Miller, Audrey K; Wagner, Maverick M; Hunt, Amy N

2012-01-01

Extant research has established numerous demographic, personal-history, attitudinal, and ideological correlates of sexual prejudice, also known as homophobia. The present study investigated whether Five-Factor Model (FFM) personality domains, particularly Openness, and FFM facets, particularly Openness to Values, contribute independent and incremental variance to the prediction of sexual prejudice beyond these established correlates. Participants were 117 college students who completed a comprehensive FFM measure, measures of sexual prejudice, and a demographics, personal-history, and attitudes-and-ideologies questionnaire. Results of stepwise multiple regression analyses demonstrated that, whereas Openness domain score predicted only marginal incremental variance in sexual prejudice, Openness facet scores (particularly Openness to Values) predicted independent and substantial incremental variance beyond numerous other zero-order correlates of sexual prejudice. The importance of integrating FFM personality variables, especially facet-level variables, into conceptualizations of sexual prejudice is highlighted. Study strengths and weaknesses are discussed as are potential implications for prejudice-reduction interventions.

Comparative values of medical school assessments in the prediction of internship performance.

Science.gov (United States)

Lee, Ming; Vermillion, Michelle

2018-02-01

Multiple undergraduate achievements have been used for graduate admission consideration. Their relative values in the prediction of residency performance are not clear. This study compared the contributions of major undergraduate assessments to the prediction of internship performance. Internship performance ratings of the graduates of a medical school were collected from 2012 to 2015. Hierarchical multiple regression analyses were used to examine the predictive values of undergraduate measures assessing basic and clinical sciences knowledge and clinical performances, after controlling for differences in the Medical College Admission Test (MCAT). Four hundred eighty (75%) graduates' archived data were used in the study. Analyses revealed that clinical competencies, assessed by the USMLE Step 2 CK, NBME medicine exam, and an eight-station objective structured clinical examination (OSCE), were strong predictors of internship performance. Neither the USMLE Step 1 nor the inpatient internal medicine clerkship evaluation predicted internship performance. The undergraduate assessments as a whole showed a significant collective relationship with internship performance (ΔR 2  = 0.12, p < 0.001). The study supports the use of clinical competency assessments, instead of pre-clinical measures, in graduate admission consideration. It also provides validity evidence for OSCE scores in the prediction of workplace performance.

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

Science.gov (United States)

Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

2015-09-01

Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Prediction of chemical composition of South African Medicago sativa ...

African Journals Online (AJOL)

The near infrared reflectance spectroscopy (NIRS) to predict chemical and digestibility parameters was investigated. Samples (n = 168) representing the spectral characteristics of the South African. Medicago sativa L. hay population were chemically analysed for the development of calibration equations. Values for r² and ...

HostPhinder: A Phage Host Prediction Tool

Directory of Open Access Journals (Sweden)

Julia Villarroel

2016-05-01

Full Text Available The current dramatic increase of antibiotic resistant bacteria has revitalised the interest in bacteriophages as alternative antibacterial treatment. Meanwhile, the development of bioinformatics methods for analysing genomic data places high-throughput approaches for phage characterization within reach. Here, we present HostPhinder, a tool aimed at predicting the bacterial host of phages by examining the phage genome sequence. Using a reference database of 2196 phages with known hosts, HostPhinder predicts the host species of a query phage as the host of the most genomically similar reference phages. As a measure of genomic similarity the number of co-occurring k-mers (DNA sequences of length k is used. Using an independent evaluation set, HostPhinder was able to correctly predict host genus and species for 81% and 74% of the phages respectively, giving predictions for more phages than BLAST and significantly outperforming BLAST on phages for which both had predictions. HostPhinder predictions on phage draft genomes from the INTESTI phage cocktail corresponded well with the advertised targets of the cocktail. Our study indicates that for most phages genomic similarity correlates well with related bacterial hosts. HostPhinder is available as an interactive web service [1] and as a stand alone download from the Docker registry [2].

Prediction of the thermohydraulic performance of porous-media reservoirs for compressed-air energy storage

Energy Technology Data Exchange (ETDEWEB)

Wiles, L.E.; McCann, R.A.

1981-09-01

The numerical modeling capability that has been developed at the Pacific Northwest Laboratory (PNL) for the prediction of the thermohydraulic performance of porous media reservoirs for compressed air energy storage (CAES) is described. The capability of the numerical models was demonstrated by application to a variety of parametric analyses and the support analyses for the CAES porous media field demonstration program. The demonstration site analyses include calculations for the displacement of aquifer water to develop the air storage zone, the potential for water coning, thermal development in the reservoir, and the dehydration of the near-wellbore region. Unique features of the demonstration site reservoir that affect the thermohydraulic performance are identified and contrasted against the predicted performance for conditions that would be considered more typical of a commercial CAES site.

Predictive Monte Carlo tools for LHC physics (1/3)

CERN Multimedia

CERN. Geneva

2012-01-01

Simulations of events taking place at the LHC play key role in all experimental analyses. Starting from the basics concepts of QCD, we first review how accurate predictions can be obtained via fixed-order calculations at higher orders. Parton showers and event generation are then introduced as a means to achieve fully exclusive predictions. Finally the recent merging and matching techniques between fixed-order and fully exclusive simulations are presented, as well as their implementations via the MLM/CKKW and MC@NLO/POWHEG methods.

Predictive Monte Carlo tools for LHC physics (3/3)

CERN Multimedia

CERN. Geneva

2012-01-01

Simulations of events taking place at the LHC play key role in all experimental analyses. Starting from the basics concepts of QCD, we first review how accurate predictions can be obtained via fixed-order calculations at higher orders. Parton showers and event generation are then introduced as a means to achieve fully exclusive predictions. Finally the recent merging and matching techniques between fixed-order and fully exclusive simulations are presented, as well as their implementations via the MLM/CKKW and MC@NLO/POWHEG methods.

Predictive Monte Carlo tools for LHC physics (2/3)

CERN Multimedia

CERN. Geneva

2012-01-01

Simulations of events taking place at the LHC play key role in all experimental analyses. Starting from the basics concepts of QCD, we first review how accurate predictions can be obtained via fixed-order calculations at higher orders. Parton showers and event generation are then introduced as a means to achieve fully exclusive predictions. Finally the recent merging and matching techniques between fixed-order and fully exclusive simulations are presented, as well as their implementations via the MLM/CKKW and MC@NLO/POWHEG methods.

Prediction of seismic motion from contained and excavation nuclear detonations

Energy Technology Data Exchange (ETDEWEB)

Mueller, R A [Environmental Research Corp., Alexandria, VA (United States)

1970-05-15

Capability to predict ground motions from nuclear events is developed on empirical and theoretical bases. Analyses of the experimental data provide basic predictions of peak particle motions and spectra which follow a (yield){sup m} times (distance){sup -n} relationship. The exponents on yield and distance are frequency dependent and derived from experiment and theory. Theory provides a physical understanding of the phenomena which allows extrapolation to off-NTS and atypical events. For example, yield scaling theory predicts significantly higher frequency motions and consequently larger ground accelerations for overburied events such as Gasbuggy, Rulison, Wasp and Wagon Wheel. These conclusions are observed from Gasbuggy (26 kt) which generated ground accelerations comparable to a normal buried event of 200 kt. This result is important in avoiding personal injury and assessing the probability of property damage. Conversely, theory predicts lower ground accelerations and seismic efficiencies for excavation events; these effects are observed from the Cabriolet and Schooner events and consequently predicted for the Sturtevant and Yawl events. With regard to the distance exponent, scattering theory determines a distance exponent which predicts greater attenuation effects on higher frequency motions. This trend is verified experimentally by regression analyses on a large number of data points which determine the distance exponent to range from -1.1 at low frequencies to -1.6 at high frequencies. Results indicate that cube root similarity scaling is not appropriate in the far field except possibly for peak particle displacements at the low frequency end of the spectrum. In addition to the source and transmission factors, current ground motion prediction techniques, on and off-NTS, take into account local site characteristics. Experimental evidence and theoretical models--layered media elastic theory, finite element modeling, and building response modeling

Low Social Status Markers: Do They Predict Depressive Symptoms in Adolescence?

Science.gov (United States)

Jackson, Benita; Goodman, Elizabeth

2011-07-01

Some markers of social disadvantage are associated robustly with depressive symptoms among adolescents: female gender and lower socioeconomic status (SES), respectively. Others are associated equivocally, notably Black v. White race/ethnicity. Few studies examine whether markers of social disadvantage by gender, SES, and race/ethnicity jointly predict self-reported depressive symptoms during adolescence; this was our goal. Secondary analyses were conducted on data from a socioeconomically diverse community-based cohort study of non-Hispanic Black and White adolescents (N = 1,263, 50.4% female). Multivariable general linear models tested if female gender, Black race/ethnicity, and lower SES (assessed by parent education and household income), and their interactions predicted greater depressive symptoms reported on the Center for Epidemiological Studies-Depression scale. Models adjusted for age and pubertal status. Univariate analyses revealed more depressive symptoms in females, Blacks, and participants with lower SES. Multivariable models showed females across both racial/ethnic groups reported greater depressive symptoms; Blacks demonstrated more depressive symptoms than did Whites but when SES was included this association disappeared. Exploratory analyses suggested Blacks gained less mental health benefit from increased SES. However there were no statistically significant interactions among gender, race/ethnicity, or SES. Taken together, we conclude that complex patterning among low social status domains within gender, race/ethnicity, and SES predicts depressive symptoms among adolescents.

Nuclear power plant analysers: their approach to analysis and design

International Nuclear Information System (INIS)

Ancarani, A.; Zanobetti, D.

1985-01-01

''Analysers'' as used for nuclear power plant simulators are powerful tools and their purpose can be variously assigned: it may vary from the aid in the design of power plants to the assistance to operators in emergency situations. A fundamental problem arising from the analysers' concept and use is the definition of the simulation capability. This can be assessed either by comparison with previous operational data statistically significant and suitably elaborated; or by comparison with theoretical (computed) values obtained from engineering codes. In both these, to take advantage of all the possibilities offered by the ''analysers'', it is mandatory that suitable terms of reference be clearly stated and agreed upon. Particular care is devoted to accuracy in the prediction of physical values both for the steady state and the transient situations. For instance, it can be seen that such evaluations can be met by specifying the maximum error on value of parameters (ordinates), save for very fast transients; the maximum error on time (abscissae) for occurrence of extreme values; the maximum error on values of extremes (ordinates); the maximum error on derivatives (slopes) for rapidly variable transients, save near extreme values. The paper also deals with a brief account of the present projects and proposals in different countries as known from various sources, and mentions a possible co-ordination at international level. (author)

Comparative biochemical analyses of venous blood and peritoneal fluid from horses with colic using a portable analyser and an in-house analyser.

Science.gov (United States)

Saulez, M N; Cebra, C K; Dailey, M

2005-08-20

Fifty-six horses with colic were examined over a period of three months. The concentrations of glucose, lactate, sodium, potassium and chloride, and the pH of samples of blood and peritoneal fluid, were determined with a portable clinical analyser and with an in-house analyser and the results were compared. Compared with the in-house analyser, the portable analyser gave higher pH values for blood and peritoneal fluid with greater variability in the alkaline range, and lower pH values in the acidic range, lower concentrations of glucose in the range below 8.3 mmol/l, and lower concentrations of lactate in venous blood in the range below 5 mmol/l and in peritoneal fluid in the range below 2 mmol/l, with less variability. On average, the portable analyser underestimated the concentrations of lactate and glucose in peritoneal fluid in comparison with the in-house analyser. Its measurements of the concentrations of sodium and chloride in peritoneal fluid had a higher bias and were more variable than the measurements in venous blood, and its measurements of potassium in venous blood and peritoneal fluid had a smaller bias and less variability than the measurements made with the in-house analyser.

Finite element predictions of active buckling control of stiffened panels

Science.gov (United States)

Thompson, Danniella M.; Griffin, O. H., Jr.

1993-04-01

Materials systems and structures that can respond 'intelligently' to their environment are currently being proposed and investigated. A series of finite element analyses was performed to investigate the potential for active buckling control of two different stiffened panels by embedded shape memory alloy (SMA) rods. Changes in the predicted buckling load increased with the magnitude of the actuation level for a given structural concept. Increasing the number of actuators for a given concept yielded greater predicted increases in buckling load. Considerable control authority was generated with a small number of actuators, with greater authority demonstrated for those structural concepts where the activated SMA rods could develop greater forces and moments on the structure. Relatively simple and inexpensive analyses were performed with standard finite elements to determine such information, indicating the viability of these types of models for design purposes.

Probabilistic fuel rod analyses using the TRANSURANUS code

Energy Technology Data Exchange (ETDEWEB)

Lassmann, K; O` Carroll, C; Laar, J Van De [CEC Joint Research Centre, Karlsruhe (Germany)

1997-08-01

After more than 25 years of fuel rod modelling research, the basic concepts are well established and the limitations of the specific approaches are known. However, the widely used mechanistic approach leads in many cases to discrepancies between theoretical predictions and experimental evidence indicating that models are not exact and that some of the physical processes encountered are of stochastic nature. To better understand uncertainties and their consequences, the mechanistic approach must therefore be augmented by statistical analyses. In the present paper the basic probabilistic methods are briefly discussed. Two such probabilistic approaches are included in the fuel rod performance code TRANSURANUS: the Monte Carlo method and the Numerical Noise Analysis. These two techniques are compared and their capabilities are demonstrated. (author). 12 refs, 4 figs, 2 tabs.

Spent fuel shipping costs for transportation logistics analyses

International Nuclear Information System (INIS)

Cole, B.M.; Cross, R.E.; Cashwell, J.W.

1983-05-01

Logistics analyses supplied to the nuclear waste management programs of the U.S. Department of Energy through the Transportation Technology Center (TTC) at Sandia National Laboratories are used to predict nuclear waste material logistics, transportation packaging demands, shipping and receiving rates and transportation-related costs for alternative strategies. This study is an in-depth analysis of the problems and contingencies associated with the costs of shipping irradiated reactor fuel. These costs are extremely variable however, and have changed frequently (sometimes monthly) during the past few years due to changes in capital, fuel, and labor costs. All costs and charges reported in this study are based on January 1982 data using existing transport cask systems and should be used as relative indices only. Actual shipping costs would be negotiable for each origin-destination combination

Prediction of Wild-type Enzyme Characteristics

DEFF Research Database (Denmark)

Geertz-Hansen, Henrik Marcus

of biotechnology, including enzyme discovery and characterization. This work presents two articles on sequence-based discovery and functional annotation of enzymes in environmental samples, and two articles on analysis and prediction of enzyme thermostability and cofactor requirements. The first article presents...... a sequence-based approach to discovery of proteolytic enzymes in metagenomes obtained from the Polar oceans. We show that microorganisms living in these extreme environments of constant low temperature harbour genes encoding novel proteolytic enzymes with potential industrial relevance. The second article...... presents a web server for the processing and annotation of functional metagenomics sequencing data, tailored to meet the requirements of non-bioinformaticians. The third article presents analyses of the molecular determinants of enzyme thermostability, and a feature-based prediction method of the melting...

THE EFFECTS OF BANKRUPTCY ON THE PREDICTABILITY OF PRICE FORMATION PROCESSES ON WARSAW’S STOCK MARKET

Directory of Open Access Journals (Sweden)

Paweł Fiedor

2016-07-01

Full Text Available In this study we investigate how bankruptcy affects the market behaviour of prices of stocks on Warsaw’s Stock Exchange. As the behaviour of prices can be seen in a myriad of ways, we investigate a particular aspect of this behaviour, namely the predictability of these price formation processes. We approximate their predictability as the structural complexity of logarithmic returns. This method of analysing predictability of price formation processes using information theory follows closely the mathematical definition of predictability, and is equal to the degree to which redundancy is present in the time series describing stock returns. We use Shannon’s entropy rate (approximating Kolmogorov-Sinai entropy to measure this redundancy, and estimate it using the Lempel-Ziv algorithm, computing it with a running window approach over the entire price history of 50 companies listed on the Warsaw market which have gone bankrupt in the last few years. This enables us not only to compare the differences between predictability of price formation processes before and after their filing for bankruptcy, but also to compare the changes in predictability over time, as well as divided into different categories of companies and bankruptcies. There exists a large body of research analysing the efficiency of the whole market and the predictability of price changes enlarge, but only a few detailed studies analysing the influence of external stimulion the efficiency of price formation processes. This study fills this gap in the knowledge of financial markets, and their response to extreme external events.

Large-scale replication study reveals a limit on probabilistic prediction in language comprehension.

Science.gov (United States)

Nieuwland, Mante S; Politzer-Ahles, Stephen; Heyselaar, Evelien; Segaert, Katrien; Darley, Emily; Kazanina, Nina; Von Grebmer Zu Wolfsthurn, Sarah; Bartolozzi, Federica; Kogan, Vita; Ito, Aine; Mézière, Diane; Barr, Dale J; Rousselet, Guillaume A; Ferguson, Heather J; Busch-Moreno, Simon; Fu, Xiao; Tuomainen, Jyrki; Kulakova, Eugenia; Husband, E Matthew; Donaldson, David I; Kohút, Zdenko; Rueschemeyer, Shirley-Ann; Huettig, Falk

2018-04-03

Do people routinely pre-activate the meaning and even the phonological form of upcoming words? The most acclaimed evidence for phonological prediction comes from a 2005 Nature Neuroscience publication by DeLong, Urbach and Kutas, who observed a graded modulation of electrical brain potentials (N400) to nouns and preceding articles by the probability that people use a word to continue the sentence fragment ('cloze'). In our direct replication study spanning 9 laboratories ( N =334), pre-registered replication-analyses and exploratory Bayes factor analyses successfully replicated the noun-results but, crucially, not the article-results. Pre-registered single-trial analyses also yielded a statistically significant effect for the nouns but not the articles. Exploratory Bayesian single-trial analyses showed that the article-effect may be non-zero but is likely far smaller than originally reported and too small to observe without very large sample sizes. Our results do not support the view that readers routinely pre-activate the phonological form of predictable words. © 2018, Nieuwland et al.

Prediction of material damage in orthotropic metals for virtual structural testing

OpenAIRE

Ravindran, S.

2010-01-01

Models based on the Continuum Damage Mechanics principle are increasingly used for predicting the initiation and growth of damage in materials. The growing reliance on 3-D finite element (FE) virtual structural testing demands implementation and validation of robust material models that can predict the material behaviour accurately. The use of these models within numerical analyses requires suitable material data. EU aerospace companies along with Cranfield University and other similar resear...

Analyses of Potential Predictive Markers and Response to Targeted Therapy in Patients with Advanced Clear-cell Renal Cell Carcinoma

Directory of Open Access Journals (Sweden)

Yan Song

2015-01-01

Full Text Available Background: Vascular endothelial growth factor-targeted agents are standard treatments in advanced clear-cell renal cell carcinoma (ccRCC, but biomarkers of activity are lacking. The aim of this study was to investigate the association of Von Hippel-Lindau (VHL gene status, vascular endothelial growth factor receptor (VEGFR or stem cell factor receptor (KIT expression, and their relationships with characteristics and clinical outcome of advanced ccRCC. Methods: A total of 59 patients who received targeted treatment with sunitinib or pazopanib were evaluated for determination at Cancer Hospital and Institute, Chinese Academy of Medical Sciences between January 2010 and November 2012. Paraffin-embedded tumor samples were collected and status of the VHL gene and expression of VEGFR and KIT were determined by VHL sequence analysis and immunohistochemistry. Clinical-pathological features were collected and efficacy such as response rate and Median progression-free survival (PFS and overall survival (OS were calculated and then compared based on expression status. The Chi-square test, the Kaplan-Meier method, and the Lon-rank test were used for statistical analyses. Results: Of 59 patients, objective responses were observed in 28 patients (47.5%. The median PFS was 13.8 months and median OS was 39.9 months. There was an improved PFS in patients with the following clinical features: Male gender, number of metastatic sites 2 or less, VEGFR-2 positive or KIT positive. Eleven patients (18.6% had evidence of VHL mutation, with an objective response rate of 45.5%, which showed no difference with patients with no VHL mutation (47.9%. VHL mutation status did not correlate with either overall response rate (P = 0.938 or PFS (P = 0.277. The PFS was 17.6 months and 22.2 months in VEGFR-2 positive patients and KIT positive patients, respectively, which was significantly longer than that of VEGFR-2 or KIT negative patients (P = 0.026 and P = 0.043. Conclusion

Lacunarity, predictability and predictive instability of the daily pluviometric regime in the Iberian Peninsula

Directory of Open Access Journals (Sweden)

M. D. Martínez

2007-01-01

Full Text Available The complexity of the daily pluviometric regime of the Iberian Peninsula is analysed from the point of view of its lacunarity, predictability and predictive instability. The database consists of daily pluviometric records obtained from 43 rain gauges in Spain and Portugal for the period 1950–1990. Five different series are generated for every rain gauge. The first series is constituted by the consecutive daily amounts. The other four consist of dry spell lengths with respect to daily amount thresholds of 0.1, 1.0, 5.0 and 10.0 mm/day. A dry spell length is defined as the number of consecutive days with rainfall amounts below one of these thresholds. The empirical lacunarity for every rain gauge is well reproduced by two power laws, the exponents varying notably from one gauge to another. The spatial distribution of the lacunarity is characterised by a north to south or southeast gradient, thus suggesting that this parameter can be a useful tool to distinguish between different pluviometric regimes. The predictability of the five series is quantified by means of the rescaled analysis and the interpretation of the Hurst exponent. Its patterns reveal that most part of the Iberian Peninsula shows signs of persistence for the daily rainfall and the dry spell series, although persistence is only clearly manifested in some small domains. The instability of possible predictive algorithms is analysed through the Lyapunov exponents. They are only computed for the series of daily amounts and for dry lengths respect to the threshold level of 0.1 mm/day due to the short number of dry spells for larger threshold levels. The series of daily amounts depict the highest instability along the Mediterranean coast. The series of dry spells show an increasing instability from NE to SW Spain, with a relevant nucleus of high Lyapunov values in the south-western Atlantic coast. As a summary, lacunarity and Hurst and Lyapunov exponents depict a relevant spatial

Sensitivity Analyses for Cross-Coupled Parameters in Automotive Powertrain Optimization

Directory of Open Access Journals (Sweden)

Pongpun Othaganont

2014-06-01

Full Text Available When vehicle manufacturers are developing new hybrid and electric vehicles, modeling and simulation are frequently used to predict the performance of the new vehicles from an early stage in the product lifecycle. Typically, models are used to predict the range, performance and energy consumption of their future planned production vehicle; they also allow the designer to optimize a vehicle’s configuration. Another use for the models is in performing sensitivity analysis, which helps us understand which parameters have the most influence on model predictions and real-world behaviors. There are various techniques for sensitivity analysis, some are numerical, but the greatest insights are obtained analytically with sensitivity defined in terms of partial derivatives. Existing methods in the literature give us a useful, quantified measure of parameter sensitivity, a first-order effect, but they do not consider second-order effects. Second-order effects could give us additional insights: for example, a first order analysis might tell us that a limiting factor is the efficiency of the vehicle’s prime-mover; our new second order analysis will tell us how quickly the efficiency of the powertrain will become of greater significance. In this paper, we develop a method based on formal optimization mathematics for rapid second-order sensitivity analyses and illustrate these through a case study on a C-segment electric vehicle.

Thermodynamical analyses of molecular simulations of dislocation-defect interactions: simulations at 0 K

International Nuclear Information System (INIS)

Monnet, G.

2008-01-01

Full text of publication follows. Static molecular (SM) simulations of dislocation-defect interaction are analysed through a framework of different interaction regimes, in which the applied work has different roles. In most regimes, the applied work is transformed into elastic energy, a dissipative energy resulting from the lattice friction and a large quantity of energy needed to enable the dislocation to bow out when it is pinned by the defect. While the dissipative work is entirely evacuated in SM simulations, the elastic and curvature energies contribute to a large increase of the internal energy of the system. A method is presented in this work to evaluate the curvature energy and the result is compared to prediction of the line tension model. These analyses allow the determination of the dislocation-defect interaction energy. (author)

Evaluation of fracture mechanics analyses used in RPV integrity assessment regarding brittle fracture

International Nuclear Information System (INIS)

Moinereau, D.; Faidy, C.; Valeta, M.P.; Bhandari, S.; Guichard, D.

1997-01-01

Electricite de France has conducted during these last years some experimental and numerical research programmes in order to evaluate fracture mechanics analyses used in nuclear reactor pressure vessels structural integrity assessment, regarding the risk of brittle fracture. These programmes included cleavage fracture tests on large scale cladded specimens containing subclad flaws with their interpretations by 2D and 3D numerical computations, and validation of finite element codes for pressurized thermal shocks analyses. Four cladded specimens made of ferritic steel A508 C13 with stainless steel cladding, and containing shallow subclad flaws, have been tested in four point bending at very low temperature in order to obtain cleavage failure. The specimen failure was obtained in each case in base metal by cleavage fracture. These tests have been interpreted by two-dimensional and three-dimensional finite element computations using different fracture mechanics approaches (elastic analysis with specific plasticity corrections, elastic-plastic analysis, local approach to cleavage fracture). The failure of specimens are conservatively predicted by different analyses. The comparison between the elastic analyses and elastic-plastic analyses shows the conservatism of specific plasticity corrections used in French RPV elastic analyses. Numerous finite element calculations have also been performed between EDF, CEA and Framatome in order to compare and validate several fracture mechanics post processors implemented in finite element programmes used in pressurized thermal shock analyses. This work includes two-dimensional numerical computations on specimens with different geometries and loadings. The comparisons show a rather good agreement on main results, allowing to validate the finite element codes and their post-processors. (author). 11 refs, 24 figs, 3 tabs

Evaluation of fracture mechanics analyses used in RPV integrity assessment regarding brittle fracture

Energy Technology Data Exchange (ETDEWEB)

Moinereau, D [Electricite de France, Dept. MTC, Moret-sur-Loing (France); Faidy, C [Electricite de France, SEPTEN, Villeurbanne (France); Valeta, M P [Commisariat a l` Energie Atomique, Dept. DMT, Gif-sur-Yvette (France); Bhandari, S; Guichard, D [Societe Franco-Americaine de Constructions Atomiques (FRAMATOME), 92 - Paris-La-Defense (France)

1997-09-01

Electricite de France has conducted during these last years some experimental and numerical research programmes in order to evaluate fracture mechanics analyses used in nuclear reactor pressure vessels structural integrity assessment, regarding the risk of brittle fracture. These programmes included cleavage fracture tests on large scale cladded specimens containing subclad flaws with their interpretations by 2D and 3D numerical computations, and validation of finite element codes for pressurized thermal shocks analyses. Four cladded specimens made of ferritic steel A508 C13 with stainless steel cladding, and containing shallow subclad flaws, have been tested in four point bending at very low temperature in order to obtain cleavage failure. The specimen failure was obtained in each case in base metal by cleavage fracture. These tests have been interpreted by two-dimensional and three-dimensional finite element computations using different fracture mechanics approaches (elastic analysis with specific plasticity corrections, elastic-plastic analysis, local approach to cleavage fracture). The failure of specimens are conservatively predicted by different analyses. The comparison between the elastic analyses and elastic-plastic analyses shows the conservatism of specific plasticity corrections used in French RPV elastic analyses. Numerous finite element calculations have also been performed between EDF, CEA and Framatome in order to compare and validate several fracture mechanics post processors implemented in finite element programmes used in pressurized thermal shock analyses. This work includes two-dimensional numerical computations on specimens with different geometries and loadings. The comparisons show a rather good agreement on main results, allowing to validate the finite element codes and their post-processors. (author). 11 refs, 24 figs, 3 tabs.

The Predictive Utility of Narcissism among Children and Adolescents: Evidence for a Distinction between Adaptive and Maladaptive Narcissism

Science.gov (United States)

Barry, Christopher T.; Frick, Paul J.; Adler, Kristy K.; Grafeman, Sarah J.

2007-01-01

We examined the predictive utility of narcissism among a community sample of children and adolescents (N=98) longitudinally. Analyses focused on the differential utility between maladaptive and adaptive narcissism for predicting later delinquency. Maladaptive narcissism significantly predicted self-reported delinquency at one-, two-, and…

Potential predictability of a Colombian river flow

Science.gov (United States)

Córdoba-Machado, Samir; Palomino-Lemus, Reiner; Quishpe-Vásquez, César; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In this study the predictability of an important Colombian river (Cauca) has been analysed based on the use of climatic variables as potential predictors. Cauca River is considered one of the most important rivers of Colombia because its basin supports important productive activities related with the agriculture, such as the production of coffee or sugar. Potential relationships between the Cauca River seasonal streamflow anomalies and different climatic variables such as sea surface temperature (SST), precipitation (Pt), temperature over land (Tm) and soil water (Sw) have been analysed for the period 1949-2009. For this end, moving correlation analysis of 30 years have been carried out for lags from one to four seasons for the global SST, and from one to two seasons for South America Pt, Tm and Sw. Also, the stability of the significant correlations have been also studied, identifying the regions used as potential predictors of streamflow. Finally, in order to establish a prediction scheme based on the previous stable correlations, a Principal Component Analysis (PCA) applied on the potential predictor regions has been carried out in order to obtain a representative time series for each predictor field. Significant and stable correlations between the seasonal streamflow and the tropical Pacific SST (El Niño region) are found for lags from one to four (one-year) season. Additionally, some regions in the Indian and Atlantic Oceans also show significant and stable correlations at different lags, highlighting the importance that exerts the Atlantic SST on the hydrology of Colombia. Also significant and stable correlations are found with the Pt, Tm and Sw for some regions over South America, at lags of one and two seasons. The prediction of Cauca seasonal streamflow based on this scheme shows an acceptable skill and represents a relative improvement compared with the predictability obtained using the teleconnection indices associated with El Niño. Keywords

Aggression in Primary Schools: The Predictive Power of the School and Home Environment

Science.gov (United States)

Kozina, Ana

2015-01-01

In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…

Chaotic time series. Part II. System Identification and Prediction

Directory of Open Access Journals (Sweden)

Bjørn Lillekjendlie

1994-10-01

Full Text Available This paper is the second in a series of two, and describes the current state of the art in modeling and prediction of chaotic time series. Sample data from deterministic non-linear systems may look stochastic when analysed with linear methods. However, the deterministic structure may be uncovered and non-linear models constructed that allow improved prediction. We give the background for such methods from a geometrical point of view, and briefly describe the following types of methods: global polynomials, local polynomials, multilayer perceptrons and semi-local methods including radial basis functions. Some illustrative examples from known chaotic systems are presented, emphasising the increase in prediction error with time. We compare some of the algorithms with respect to prediction accuracy and storage requirements, and list applications of these methods to real data from widely different areas.

Prediction of IRI in short and long terms for flexible pavements: ANN and GMDH methods

NARCIS (Netherlands)

Ziari, H.; Sobhani, J.; Ayoubinejad, J.; Hartmann, Timo

2015-01-01

Prediction of pavement condition is one of the most important issues in pavement management systems. In this paper, capabilities of artificial neural networks (ANNs) and group method of data handling (GMDH) methods in predicting flexible pavement conditions were analysed in three levels: in 1 year,

The Diagnostic Apathia Scale predicts the ability to return to work following depression or anxiety

DEFF Research Database (Denmark)

Hellström, Lc; Eplov, Lf; Nordentoft, M

2014-01-01

, tiredness/fatigue, insomnia, and reduced ability to work and engage in personal interests. The scale was analysed for psychometric validity (scalability) and for its ability to predict RTW. Finally, the predictive validity of the Diagnostic Apathia Scale regarding RTW was compared with scales measuring...

Prediction of Advisability of Returning Home Using the Home Care Score

Directory of Open Access Journals (Sweden)

Akiyoshi Matsugi

2015-01-01

Full Text Available Purpose. The aim of this study was to assess whether the home care score (HCS, which was developed by the Ministry of Health and Welfare in Japan in 1992, is useful for the prediction of advisability of home care. Methods. Subjects living at home and in assisted-living facilities were analyzed. Binominal logistic regression analyses, using age, sex, the functional independence measure score, and the HCS, along with receiver operating characteristic curve analyses, were conducted. Findings/Conclusions. Only HCS was selected for the regression equation. Receiver operating characteristic curve analysis revealed that the area under the curve (0.9, sensitivity (0.82, specificity (0.83, and positive predictive value (0.84 for HCS were higher than those for the functional independence measure, indicating that the HCS is a powerful predictor for advisability of home care. Clinical Relevance. Comprehensive measurements of the condition of provided care and the activities of daily living of the subjects, which are included in the HCS, are required for the prediction of advisability of home care.

Prediction of Advisability of Returning Home Using the Home Care Score

Science.gov (United States)

Matsugi, Akiyoshi; Tani, Keisuke; Tamaru, Yoshiki; Yoshioka, Nami; Yamashita, Akira; Mori, Nobuhiko; Oku, Kosuke; Ikeda, Masashi; Nagano, Kiyoshi

2015-01-01

Purpose. The aim of this study was to assess whether the home care score (HCS), which was developed by the Ministry of Health and Welfare in Japan in 1992, is useful for the prediction of advisability of home care. Methods. Subjects living at home and in assisted-living facilities were analyzed. Binominal logistic regression analyses, using age, sex, the functional independence measure score, and the HCS, along with receiver operating characteristic curve analyses, were conducted. Findings/Conclusions. Only HCS was selected for the regression equation. Receiver operating characteristic curve analysis revealed that the area under the curve (0.9), sensitivity (0.82), specificity (0.83), and positive predictive value (0.84) for HCS were higher than those for the functional independence measure, indicating that the HCS is a powerful predictor for advisability of home care. Clinical Relevance. Comprehensive measurements of the condition of provided care and the activities of daily living of the subjects, which are included in the HCS, are required for the prediction of advisability of home care. PMID:26491568

The Efficacy of Violence Prediction: A Meta-Analytic Comparison of Nine Risk Assessment Tools

Science.gov (United States)

Yang, Min; Wong, Stephen C. P.; Coid, Jeremy

2010-01-01

Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their…

Experimental and Computational Modal Analyses for Launch Vehicle Models considering Liquid Propellant and Flange Joints

Directory of Open Access Journals (Sweden)

Chang-Hoon Sim

2018-01-01

Full Text Available In this research, modal tests and analyses are performed for a simplified and scaled first-stage model of a space launch vehicle using liquid propellant. This study aims to establish finite element modeling techniques for computational modal analyses by considering the liquid propellant and flange joints of launch vehicles. The modal tests measure the natural frequencies and mode shapes in the first and second lateral bending modes. As the liquid filling ratio increases, the measured frequencies decrease. In addition, as the number of flange joints increases, the measured natural frequencies increase. Computational modal analyses using the finite element method are conducted. The liquid is modeled by the virtual mass method, and the flange joints are modeled using one-dimensional spring elements along with the node-to-node connection. Comparison of the modal test results and predicted natural frequencies shows good or moderate agreement. The correlation between the modal tests and analyses establishes finite element modeling techniques for modeling the liquid propellant and flange joints of space launch vehicles.

Issues Related to the Frequency of Exploratory Analyses by Evidence Review Groups in the NICE Single Technology Appraisal Process.

Science.gov (United States)

Kaltenthaler, Eva; Carroll, Christopher; Hill-McManus, Daniel; Scope, Alison; Holmes, Michael; Rice, Stephen; Rose, Micah; Tappenden, Paul; Woolacott, Nerys

2017-06-01

Evidence Review Groups (ERGs) critically appraise company submissions as part of the National Institute for Health and Care Excellence (NICE) Single Technology Appraisal (STA) process. As part of their critique of the evidence submitted by companies, the ERGs undertake exploratory analyses to explore uncertainties in the company's model. The aim of this study was to explore pre-defined factors that might influence or predict the extent of ERG exploratory analyses. The aim of this study was to explore predefined factors that might influence or predict the extent of ERG exploratory analyses. We undertook content analysis of over 400 documents, including ERG reports and related documentation for the 100 most recent STAs (2009-2014) for which guidance has been published. Relevant data were extracted from the documents and narrative synthesis was used to summarise the extracted data. All data were extracted and checked by two researchers. Forty different companies submitted documents as part of the NICE STA process. The most common disease area covered by the STAs was cancer (44%), and most ERG reports (n = 93) contained at least one exploratory analysis. The incidence and frequency of ERG exploratory analyses does not appear to be related to any developments in the appraisal process, the disease area covered by the STA, or the company's base-case incremental cost-effectiveness ratio (ICER). However, there does appear to be a pattern in the mean number of analyses conducted by particular ERGs, but the reasons for this are unclear and potentially complex. No clear patterns were identified regarding the presence or frequency of exploratory analyses, apart from the mean number conducted by individual ERGs. More research is needed to understand this relationship.

Botanical discrimination of Greek unifloral honeys with physico-chemical and chemometric analyses.

Science.gov (United States)

Karabagias, Ioannis K; Badeka, Anastasia V; Kontakos, Stavros; Karabournioti, Sofia; Kontominas, Michael G

2014-12-15

The aim of the present study was to investigate the possibility of characterisation and classification of Greek unifloral honeys (pine, thyme, fir and orange blossom) according to botanical origin using volatile compounds, conventional physico-chemical parameters and chemometric analyses (MANOVA and Linear Discriminant Analysis). For this purpose, 119 honey samples were collected during the harvesting period 2011 from 14 different regions in Greece known to produce unifloral honey of good quality. Physico-chemical analysis included the identification and semi quantification of fifty five volatile compounds performed by Headspace Solid Phase Microextraction coupled to gas chromatography/mass spectroscopy and the determination of conventional quality parameters such as pH, free, lactonic, total acidity, electrical conductivity, moisture, ash, lactonic/free acidity ratio and colour parameters L, a, b. Results showed that using 40 diverse variables (30 volatile compounds of different classes and 10 physico-chemical parameters) the honey samples were satisfactorily classified according to botanical origin using volatile compounds (84.0% correct prediction), physicochemical parameters (97.5% correct prediction), and the combination of both (95.8% correct prediction) indicating that multi element analysis comprises a powerful tool for honey discrimination purposes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Redesign of the Analysing Magnet in the ISIS H- Penning Ion Source

International Nuclear Information System (INIS)

Lawrie, S. R.; Faircloth, D. C.; Letchford, A. P.; Westall, M.; Whitehead, M. O.; Wood, T.; Pozimski, J.

2009-01-01

A full 3D electromagnetic finite element analysis and particle tracking study is undertaken of the ISIS Penning surface plasma H - ion source. The extraction electrode, 90 deg. analysing magnet, post-extraction acceleration gap and 700 mm of drift space have been modelled in CST Particle Studio 2008 to study the beam acceleration and transport at all points in the system. The analyzing magnet is found to have a sub-optimal field index, causing beam divergence and contributing the beam loss. Different magnet pole piece geometries are modelled and the effects of space charge investigated. The best design for the analysing magnet involves a shallower intersection angle and larger separation of the pole faces. This provides radial focusing to the beam, leading to less collimation. Three new sets of magnet poles are manufactured and tested on the Ion Source Development Rig to compare with predictions.

Prediction of infarction development after endovascular stroke therapy with dual-energy computed tomography

International Nuclear Information System (INIS)

Djurdjevic, Tanja; Gizewski, Elke Ruth; Grams, Astrid Ellen; Rehwald, Rafael; Glodny, Bernhard; Knoflach, Michael; Matosevic, Benjamin; Kiechl, Stefan

2017-01-01

After intraarterial recanalisation (IAR), the haemorrhage and the blood-brain barrier (BBB) disruption can be distinguished using dual-energy computed tomography (DECT). The aim of the present study was to investigate whether future infarction development can be predicted from DECT. DECT scans of 20 patients showing 45 BBB disrupted areas after IAR were assessed and compared with follow-up examinations. Receiver operator characteristic (ROC) analyses using densities from the iodine map (IM) and virtual non-contrast (VNC) were performed. Future infarction areas are denser than future non-infarction areas on IM series (23.44 ± 24.86 vs. 5.77 ± 2.77; p < 0.0001) and more hypodense on VNC series (29.71 ± 3.33 vs. 35.33 ± 3.50; p < 0.0001). ROC analyses for the IM series showed an area under the curve (AUC) of 0.99 (cut-off: <9.97 HU; p < 0.05; sensitivity 91.18 %; specificity 100.00 %; accuracy 0.93) for the prediction of future infarctions. The AUC for the prediction of haemorrhagic infarctions was 0.78 (cut-off >17.13 HU; p < 0.05; sensitivity 90.00 %; specificity 62.86 %; accuracy 0.69). The VNC series allowed prediction of infarction volume. Future infarction development after IAR can be reliably predicted with the IM series. The prediction of haemorrhages and of infarction size is less reliable. (orig.)

Prediction of infarction development after endovascular stroke therapy with dual-energy computed tomography

Energy Technology Data Exchange (ETDEWEB)

Djurdjevic, Tanja; Gizewski, Elke Ruth; Grams, Astrid Ellen [Medical University of Innsbruck, Department of Neuroradiology, Innsbruck (Austria); Rehwald, Rafael; Glodny, Bernhard [Medical University of Innsbruck, Department of Radiology, Innsbruck (Austria); Knoflach, Michael; Matosevic, Benjamin; Kiechl, Stefan [Medical University of Innsbruck, Department of Neurology, Innsbruck (Austria)

2017-03-15

After intraarterial recanalisation (IAR), the haemorrhage and the blood-brain barrier (BBB) disruption can be distinguished using dual-energy computed tomography (DECT). The aim of the present study was to investigate whether future infarction development can be predicted from DECT. DECT scans of 20 patients showing 45 BBB disrupted areas after IAR were assessed and compared with follow-up examinations. Receiver operator characteristic (ROC) analyses using densities from the iodine map (IM) and virtual non-contrast (VNC) were performed. Future infarction areas are denser than future non-infarction areas on IM series (23.44 ± 24.86 vs. 5.77 ± 2.77; p < 0.0001) and more hypodense on VNC series (29.71 ± 3.33 vs. 35.33 ± 3.50; p < 0.0001). ROC analyses for the IM series showed an area under the curve (AUC) of 0.99 (cut-off: <9.97 HU; p < 0.05; sensitivity 91.18 %; specificity 100.00 %; accuracy 0.93) for the prediction of future infarctions. The AUC for the prediction of haemorrhagic infarctions was 0.78 (cut-off >17.13 HU; p < 0.05; sensitivity 90.00 %; specificity 62.86 %; accuracy 0.69). The VNC series allowed prediction of infarction volume. Future infarction development after IAR can be reliably predicted with the IM series. The prediction of haemorrhages and of infarction size is less reliable. (orig.)

Hebbian learning and predictive mirror neurons for actions, sensations and emotions

OpenAIRE

Keysers, C.; Gazzola, Valeria

2014-01-01

Spike-timing-dependent plasticity is considered the neurophysiological basis of Hebbian learning and has been shown to be sensitive to both contingency and contiguity between pre- and postsynaptic activity. Here, we will examine how applying this Hebbian learning rule to a system of interconnected neurons in the presence of direct or indirect re-afference (e.g. seeing/hearing one's own actions) predicts the emergence of mirror neurons with predictive properties. In this framework, we analyse ...

Integral analyses of fission product retention at mitigated thermally-induced SGTR using ARTIST experimental data

International Nuclear Information System (INIS)

Rýdl, Adolf; Lind, Terttaliisa; Birchley, Jonathan

2016-01-01

Highlights: • Source term analyses in a PWR of mitigated thermally-induced SGTR scenario performed. • Experimental ARTIST program results on aerosol scrubbing efficiency used in analyses. • Results demonstrate enhanced aerosol retention in a flooded steam generator. • High aerosol retention cannot be predicted by current theoretical scrubbing models. - Abstract: Integral source-term analyses are performed using MELCOR for a PWR Station Blackout (SBO) sequence leading to induced steam generator tube rupture (SGTR). In the absence of any mitigation measures, such a sequence can result in a containment bypass where the radioactive materials can be released directly to the environment. In some SGTR scenarios flooding of the faulted SG secondary side with water can mitigate the accident escalation and also the release of aerosol-borne and volatile radioactive materials. Data on the efficiency of aerosol scrubbing in an SG tube bundle were obtained in the international ARTIST project. In this paper ARTIST data are used directly with parametric MELCOR analyses of a mitigated SGTR sequence to provide more realistic estimates of the releases to environment in such a type of scenario or similar. Comparison is made with predictions using the default scrubbing model in MELCOR, as a representative of the aerosol scrubbing models in current integral codes. Specifically, simulations are performed for an unmitigated sequence and 2 cases where the SG secondary was refilled at different times after the tube rupture. The results, reflecting the experimental observations from ARTIST, demonstrate enhanced aerosol retention in the highly turbulent two-phase flow conditions caused by the complex geometry of the SG secondary side. This effect is not captured by any of the models currently available. The underlying physics remains only partly understood, indicating need for further studies to support a more mechanistic treatment of the retention process.

Machine learning algorithms for datasets popularity prediction

CERN Document Server

Kancys, Kipras

2016-01-01

This report represents continued study where ML algorithms were used to predict databases popularity. Three topics were covered. First of all, there was a discrepancy between old and new meta-data collection procedures, so a reason for that had to be found. Secondly, different parameters were analysed and dropped to make algorithms perform better. And third, it was decided to move modelling part on Spark.

Comparison of Prediction Model for Cardiovascular Autonomic Dysfunction Using Artificial Neural Network and Logistic Regression Analysis

Science.gov (United States)

Zeng, Fangfang; Li, Zhongtao; Yu, Xiaoling; Zhou, Linuo

2013-01-01

Background This study aimed to develop the artificial neural network (ANN) and multivariable logistic regression (LR) analyses for prediction modeling of cardiovascular autonomic (CA) dysfunction in the general population, and compare the prediction models using the two approaches. Methods and Materials We analyzed a previous dataset based on a Chinese population sample consisting of 2,092 individuals aged 30–80 years. The prediction models were derived from an exploratory set using ANN and LR analysis, and were tested in the validation set. Performances of these prediction models were then compared. Results Univariate analysis indicated that 14 risk factors showed statistically significant association with the prevalence of CA dysfunction (P<0.05). The mean area under the receiver-operating curve was 0.758 (95% CI 0.724–0.793) for LR and 0.762 (95% CI 0.732–0.793) for ANN analysis, but noninferiority result was found (P<0.001). The similar results were found in comparisons of sensitivity, specificity, and predictive values in the prediction models between the LR and ANN analyses. Conclusion The prediction models for CA dysfunction were developed using ANN and LR. ANN and LR are two effective tools for developing prediction models based on our dataset. PMID:23940593

Predicting thermally stressful events in rivers with a strategy to evaluate management alternatives

Science.gov (United States)

Maloney, K.O.; Cole, J.C.; Schmid, M.

2016-01-01

Water temperature is an important factor in river ecology. Numerous models have been developed to predict river temperature. However, many were not designed to predict thermally stressful periods. Because such events are rare, traditionally applied analyses are inappropriate. Here, we developed two logistic regression models to predict thermally stressful events in the Delaware River at the US Geological Survey gage near Lordville, New York. One model predicted the probability of an event >20.0 °C, and a second predicted an event >22.2 °C. Both models were strong (independent test data sensitivity 0.94 and 1.00, specificity 0.96 and 0.96) predicting 63 of 67 events in the >20.0 °C model and all 15 events in the >22.2 °C model. Both showed negative relationships with released volume from the upstream Cannonsville Reservoir and positive relationships with difference between air temperature and previous day's water temperature at Lordville. We further predicted how increasing release volumes from Cannonsville Reservoir affected the probabilities of correctly predicted events. For the >20.0 °C model, an increase of 0.5 to a proportionally adjusted release (that accounts for other sources) resulted in 35.9% of events in the training data falling below cutoffs; increasing this adjustment by 1.0 resulted in 81.7% falling below cutoffs. For the >22.2 °C these adjustments resulted in 71.1% and 100.0% of events falling below cutoffs. Results from these analyses can help managers make informed decisions on alternative release scenarios.

Ideal Teacher Behaviors: Student Motivation and Self-Efficacy Predict Preferences

Science.gov (United States)

Komarraju, Meera

2013-01-01

Differences in students' academic self-efficacy and motivation were examined in predicting preferred teacher traits. Undergraduates (261) completed the Teaching Behavior Checklist, Academic Self-Concept scale, and Academic Motivation scale. Hierarchical regression analyses indicated that academic self-efficacy and extrinsic motivation explained…

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels

Directory of Open Access Journals (Sweden)

Chika Sumiyoshi

2015-09-01

Full Text Available Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1 to identify which outcome factors predict occupational functioning, quantified as work hours, and 2 to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB, the UCSD Performance-based Skills Assessment-Brief (UPSA-B, and the Social Functioning Scale Individuals’ version modified for the MATRICS-PASS (Modified SFS for PASS, respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly and a multiple logistic regression analyses (predicting dichotomized work status based on work hours. ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60–70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

How coping styles, cognitive distortions, and attachment predict problem gambling among adolescents and young adults.

Science.gov (United States)

Calado, Filipa; Alexandre, Joana; Griffiths, Mark D

2017-12-01

Background and aims Recent research suggests that youth problem gambling is associated with several factors, but little is known how these factors might influence or interact each other in predicting this behavior. Consequently, this is the first study to examine the mediation effect of coping styles in the relationship between attachment to parental figures and problem gambling. Methods A total of 988 adolescents and emerging adults were recruited to participate. The first set of analyses tested the adequacy of a model comprising biological, cognitive, and family variables in predicting youth problem gambling. The second set of analyses explored the relationship between family and individual variables in problem gambling behavior. Results The results of the first set of analyses demonstrated that the individual factors of gender, cognitive distortions, and coping styles showed a significant predictive effect on youth problematic gambling, and the family factors of attachment and family structure did not reveal a significant influence on this behavior. The results of the second set of analyses demonstrated that the attachment dimension of angry distress exerted a more indirect influence on problematic gambling, through emotion-focused coping style. Discussion This study revealed that some family variables can have a more indirect effect on youth gambling behavior and provided some insights in how some factors interact in predicting problem gambling. Conclusion These findings suggest that youth gambling is a multifaceted phenomenon, and that the indirect effects of family variables are important in estimating the complex social forces that might influence adolescent decisions to gamble.

MAAP - modular program for analyses of severe accidents

International Nuclear Information System (INIS)

Henry, R.E.; Lutz, R.J.

1990-01-01

The MAAP computer code was developed by Westinghouse as a fast, user-friendly, integrated analytical tool for evaluations of the sequences and consequences of severe accidents. The code allows a fully integrated treatment of thermohydraulic behavior and of the fission products in the primary system, the containment, and the ancillary buildings. This ensures interactive inclusion of all thermohydraulic events and of fission product behavior. All important phenomena which may occur in a major accident are contained in the modular code. In addition, many of the important parameters affecting the multitude of different phenomena can be defined by the user. In this way, it is possible to study the accuracy of the predicted course and of the consequences of a series of major accident phenomena. The MAAP code was subjected to extensive benchmarking with respect to the results of the experimental and theoretical programs, the findings obtained in other safety analyses using computers and data from accidents and transients in plants actually in operation. With the expected connection of the validation and test programs, the computer code attains a quality standard meeting the most stringent requirements in safety analyses. The code will be enlarged further in order to expand the number of benchmarks and the resolution of individual comparisons, and to ensure that future MAAP models will be in better agreement with the experiments and experiences of industry. (orig.) [de

Comprehensive immunoproteogenomic analyses of malignant pleural mesothelioma.

Science.gov (United States)

Lee, Hyun-Sung; Jang, Hee-Jin; Choi, Jong Min; Zhang, Jun; de Rosen, Veronica Lenge; Wheeler, Thomas M; Lee, Ju-Seog; Tu, Thuydung; Jindra, Peter T; Kerman, Ronald H; Jung, Sung Yun; Kheradmand, Farrah; Sugarbaker, David J; Burt, Bryan M

2018-04-05

We generated a comprehensive atlas of the immunologic cellular networks within human malignant pleural mesothelioma (MPM) using mass cytometry. Data-driven analyses of these high-resolution single-cell data identified 2 distinct immunologic subtypes of MPM with vastly different cellular composition, activation states, and immunologic function; mass spectrometry demonstrated differential abundance of MHC-I and -II neopeptides directly identified between these subtypes. The clinical relevance of this immunologic subtyping was investigated with a discriminatory molecular signature derived through comparison of the proteomes and transcriptomes of these 2 immunologic MPM subtypes. This molecular signature, representative of a favorable intratumoral cell network, was independently associated with improved survival in MPM and predicted response to immune checkpoint inhibitors in patients with MPM and melanoma. These data additionally suggest a potentially novel mechanism of response to checkpoint blockade: requirement for high measured abundance of neopeptides in the presence of high expression of MHC proteins specific for these neopeptides.

Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments.

Science.gov (United States)

Gorter, Florien A; Aarts, Mark G M; Zwaan, Bas J; de Visser, J Arjan G M

2018-01-01

The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change. Copyright © 2018 by the Genetics Society of America.

Standardizing the performance evaluation of short-term wind prediction models

DEFF Research Database (Denmark)

Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

2005-01-01

Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

Centrality of positive and negative deployment memories predicts posttraumatic growth in danish veterans

DEFF Research Database (Denmark)

Staugaard, Søren Risløv; Johannessen, Kim Berg; Thomsen, Yvonne Duval

2015-01-01

OBJECTIVE: The purpose of the present study was to examine theoretically motivated predictors for the development of positive changes following potentially traumatic experiences (i.e., posttraumatic growth). Specifically, we wanted to examine the prediction that memories of highly negative......-sectional analyses of the data. RESULTS: The main findings were that the centrality of highly emotional memories from deployment predicted growth alongside openness to experience, combat exposure, and social support. Importantly, the centrality of both positive and negative memories predicted growth equally well...

Magnitude of bacteraemia predicts one-year mortality

DEFF Research Database (Denmark)

Gradel, Kim Oren; Schønheyder, Henrik Carl; Søgaard, Mette

Objectives: All hospitals in our region use the BacT/Alert® blood culture (BC) system with a 3-bottle BC set for adults. We hypothesized that the magnitude of bacteremia (i.e., number of positive bottles in the initial BC set) predicted one-year mortality. Methods In a population-based study we...... with a BC index of 1 (i.e., one positive bottle) were chosen as the reference group. We computed Kaplan-Meier curves and performed Cox regression analyses to estimate mortality rate ratios (MRRs) with 95 % confidence intervals [CIs] 30 and 365 days after the initial BC sampling date, first in crude analyses...... mortality....

ALBEDO PATTERN RECOGNITION AND TIME-SERIES ANALYSES IN MALAYSIA

Directory of Open Access Journals (Sweden)

S. A. Salleh

2012-07-01

Full Text Available Pattern recognition and time-series analyses will enable one to evaluate and generate predictions of specific phenomena. The albedo pattern and time-series analyses are very much useful especially in relation to climate condition monitoring. This study is conducted to seek for Malaysia albedo pattern changes. The pattern recognition and changes will be useful for variety of environmental and climate monitoring researches such as carbon budgeting and aerosol mapping. The 10 years (2000–2009 MODIS satellite images were used for the analyses and interpretation. These images were being processed using ERDAS Imagine remote sensing software, ArcGIS 9.3, the 6S code for atmospherical calibration and several MODIS tools (MRT, HDF2GIS, Albedo tools. There are several methods for time-series analyses were explored, this paper demonstrates trends and seasonal time-series analyses using converted HDF format MODIS MCD43A3 albedo land product. The results revealed significance changes of albedo percentages over the past 10 years and the pattern with regards to Malaysia's nebulosity index (NI and aerosol optical depth (AOD. There is noticeable trend can be identified with regards to its maximum and minimum value of the albedo. The rise and fall of the line graph show a similar trend with regards to its daily observation. The different can be identified in term of the value or percentage of rises and falls of albedo. Thus, it can be concludes that the temporal behavior of land surface albedo in Malaysia have a uniform behaviours and effects with regards to the local monsoons. However, although the average albedo shows linear trend with nebulosity index, the pattern changes of albedo with respects to the nebulosity index indicates that there are external factors that implicates the albedo values, as the sky conditions and its diffusion plotted does not have uniform trend over the years, especially when the trend of 5 years interval is examined, 2000 shows high

Complex behaviour and predictability of the European dry spell regimes

Directory of Open Access Journals (Sweden)

X. Lana

2010-09-01

Full Text Available The complex spatial and temporal characteristics of European dry spell lengths, DSL, (sequences of consecutive days with rainfall amount below a certain threshold and their randomness and predictive instability are analysed from daily pluviometric series recorded at 267 rain gauges along the second half of the 20th century. DSL are obtained by considering four thresholds, R₀, of 0.1, 1.0, 5.0 and 10.0 mm/day. A proper quantification of the complexity, randomness and predictive instability of the different DSL regimes in Europe is achieved on the basis of fractal analyses and dynamic system theory, including the reconstruction theorem. First, the concept of lacunarity is applied to the series of daily rainfall, and the lacunarity curves are well fitted to Cantor and random Cantor sets. Second, the rescaled analysis reveals that randomness, persistence and anti-persistence are present on the European DSL series. Third, the complexity of the physical process governing the DSL series is quantified by the minimum number of nonlinear equations determined by the correlation dimension. And fourth, the loss of memory of the physical process, which is one of the reasons for the complex predictability, is characterized by the values of the Kolmogorov entropy, and the predictive instability is directly associated with positive Lyapunov exponents. In this way, new bases for a better prediction of DSLs in Europe, sometimes leading to drought episodes, are established. Concretely, three predictive strategies are proposed in Sect. 5. It is worth mentioning that the spatial distribution of all fractal parameters does not solely depend on latitude and longitude but also reflects the effects of orography, continental climate or vicinity to the Atlantic and Arctic Oceans and Mediterranean Sea.

Determinants of work ability and its predictive value for disability

NARCIS (Netherlands)

Alavinia, S. M.; de Boer, A. G. E. M.; Van Duivenbooden, J. C.; Frings-Dresen, M. H. W.; Burdorf, A.

2009-01-01

Background Maintaining the ability of workers to cope with physical and psychosocial demands at work becomes increasingly important in prolonging working life. Aims To analyse the effects of work-related factors and individual characteristics on work ability and to determine the predictive value of

Predicting Alcohol, Cigarette, and Marijuana Use from Preferential Music Consumption

Science.gov (United States)

Oberle, Crystal D.; Garcia, Javier A.

2015-01-01

This study investigated whether use of alcohol, cigarettes, and marijuana may be predicted from preferential consumption of particular music genres. Undergraduates (257 women and 78 men) completed a questionnaire assessing these variables. Partial correlation analyses, controlling for sensation-seeking tendencies and behaviors, revealed that…

ConKit: a python interface to contact predictions.

Science.gov (United States)

Simkovic, Felix; Thomas, Jens M H; Rigden, Daniel J

2017-07-15

Recent advances in protein residue contact prediction algorithms have led to the emergence of many new methods and a variety of file formats. We present ConKit , an open source, modular and extensible Python interface which allows facile conversion between formats and provides an interface to analyses of sequence alignments and sets of contact predictions. ConKit is available via the Python Package Index. The documentation can be found at http://www.conkit.org . ConKit is licensed under the BSD 3-Clause. hlfsimko@liverpool.ac.uk or drigden@liverpool.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Artificial Neural Network for the Prediction of Chromosomal Abnormalities in Azoospermic Males.

Science.gov (United States)

Akinsal, Emre Can; Haznedar, Bulent; Baydilli, Numan; Kalinli, Adem; Ozturk, Ahmet; Ekmekçioğlu, Oğuz

2018-02-04

To evaluate whether an artifical neural network helps to diagnose any chromosomal abnormalities in azoospermic males. The data of azoospermic males attending to a tertiary academic referral center were evaluated retrospectively. Height, total testicular volume, follicle stimulating hormone, luteinising hormone, total testosterone and ejaculate volume of the patients were used for the analyses. In artificial neural network, the data of 310 azoospermics were used as the education and 115 as the test set. Logistic regression analyses and discriminant analyses were performed for statistical analyses. The tests were re-analysed with a neural network. Both logistic regression analyses and artificial neural network predicted the presence or absence of chromosomal abnormalities with more than 95% accuracy. The use of artificial neural network model has yielded satisfactory results in terms of distinguishing patients whether they have any chromosomal abnormality or not.

A survey on computational intelligence approaches for predictive modeling in prostate cancer

OpenAIRE

Cosma, G; Brown, D; Archer, M; Khan, M; Pockley, AG

2017-01-01

Predictive modeling in medicine involves the development of computational models which are capable of analysing large amounts of data in order to predict healthcare outcomes for individual patients. Computational intelligence approaches are suitable when the data to be modelled are too complex forconventional statistical techniques to process quickly and eciently. These advanced approaches are based on mathematical models that have been especially developed for dealing with the uncertainty an...

Methodology development for statistical evaluation of reactor safety analyses

International Nuclear Information System (INIS)

Mazumdar, M.; Marshall, J.A.; Chay, S.C.; Gay, R.

1976-07-01

In February 1975, Westinghouse Electric Corporation, under contract to Electric Power Research Institute, started a one-year program to develop methodology for statistical evaluation of nuclear-safety-related engineering analyses. The objectives of the program were to develop an understanding of the relative efficiencies of various computational methods which can be used to compute probability distributions of output variables due to input parameter uncertainties in analyses of design basis events for nuclear reactors and to develop methods for obtaining reasonably accurate estimates of these probability distributions at an economically feasible level. A series of tasks was set up to accomplish these objectives. Two of the tasks were to investigate the relative efficiencies and accuracies of various Monte Carlo and analytical techniques for obtaining such estimates for a simple thermal-hydraulic problem whose output variable of interest is given in a closed-form relationship of the input variables and to repeat the above study on a thermal-hydraulic problem in which the relationship between the predicted variable and the inputs is described by a short-running computer program. The purpose of the report presented is to document the results of the investigations completed under these tasks, giving the rationale for choices of techniques and problems, and to present interim conclusions

Predicting Community Evolution in Social Networks

Directory of Open Access Journals (Sweden)

Stanisław Saganowski

2015-05-01

Full Text Available Nowadays, sustained development of different social media can be observed worldwide. One of the relevant research domains intensively explored recently is analysis of social communities existing in social media as well as prediction of their future evolution taking into account collected historical evolution chains. These evolution chains proposed in the paper contain group states in the previous time frames and its historical transitions that were identified using one out of two methods: Stable Group Changes Identification (SGCI and Group Evolution Discovery (GED. Based on the observed evolution chains of various length, structural network features are extracted, validated and selected as well as used to learn classification models. The experimental studies were performed on three real datasets with different profile: DBLP, Facebook and Polish blogosphere. The process of group prediction was analysed with respect to different classifiers as well as various descriptive feature sets extracted from evolution chains of different length. The results revealed that, in general, the longer evolution chains the better predictive abilities of the classification models. However, chains of length 3 to 7 enabled the GED-based method to almost reach its maximum possible prediction quality. For SGCI, this value was at the level of 3–5 last periods.

Attributing Predictable Signals at Subseasonal Timescales

Science.gov (United States)

Shelly, A.; Norton, W.; Rowlands, D.; Beech-Brandt, J.

2016-12-01

Subseasonal forecasts offer significant economic value in the management of energy infrastructure and through the associated financial markets. Models are now accurate enough to provide, for some occasions, good forecasts in the subseasonal range. However, it is often not clear what the drivers of these subseasonal signals are and if the forecasts could be more accurate with better representation of physical processes. Also what are the limits of predictability in the subseasonal range? To address these questions, we have run the ECMWF monthly forecast system over the 2015/16 winter with a set of 6 week ensemble integrations initialised every week over the period. In these experiments, we have relaxed the band 15N to 15S to reanalysis fields. Hence, we have a set of forecasts where the tropics is constrained to actual events and we can analyse the changes in predictability in middle latitudes - in particular in regions of high energy consumption like North America and Europe. Not surprisingly, the forecast of some periods are significantly improved while others show no improvement. We discuss events/patterns that have extended range predictability and also the tropical forecast errors which prevent the potential predictability in middle latitudes from being realised.

Comparison of the Nosocomial Pneumonia Mortality Prediction (NPMP) model with standard mortality prediction tools.

Science.gov (United States)

Srinivasan, M; Shetty, N; Gadekari, S; Thunga, G; Rao, K; Kunhikatta, V

2017-07-01

Severity or mortality prediction of nosocomial pneumonia could aid in the effective triage of patients and assisting physicians. To compare various severity assessment scoring systems for predicting intensive care unit (ICU) mortality in nosocomial pneumonia patients. A prospective cohort study was conducted in a tertiary care university-affiliated hospital in Manipal, India. One hundred patients with nosocomial pneumonia, admitted in the ICUs who developed pneumonia after >48h of admission, were included. The Nosocomial Pneumonia Mortality Prediction (NPMP) model, developed in our hospital, was compared with Acute Physiology and Chronic Health Evaluation II (APACHE II), Mortality Probability Model II (MPM 72  II), Simplified Acute Physiology Score II (SAPS II), Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), Clinical Pulmonary Infection Score (CPIS), Ventilator-Associated Pneumonia Predisposition, Insult, Response, Organ dysfunction (VAP-PIRO). Data and clinical variables were collected on the day of pneumonia diagnosis. The outcome for the study was ICU mortality. The sensitivity and specificity of the various scoring systems was analysed by plotting receiver operating characteristic (ROC) curves and computing the area under the curve for each of the mortality predicting tools. NPMP, APACHE II, SAPS II, MPM 72  II, SOFA, and VAP-PIRO were found to have similar and acceptable discrimination power as assessed by the area under the ROC curve. The AUC values for the above scores ranged from 0.735 to 0.762. CPIS and MODS showed least discrimination. NPMP is a specific tool to predict mortality in nosocomial pneumonia and is comparable to other standard scores. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Predicting Geomorphic and Hydrologic Risks after Wildfire Using Harmonic and Stochastic Analyses

Science.gov (United States)

Mikesell, J.; Kinoshita, A. M.; Florsheim, J. L.; Chin, A.; Nourbakhshbeidokhti, S.

2017-12-01

Wildfire is a landscape-scale disturbance that often alters hydrological processes and sediment flux during subsequent storms. Vegetation loss from wildfires induce changes to sediment supply such as channel erosion and sedimentation and streamflow magnitude or flooding. These changes enhance downstream hazards, threatening human populations and physical aquatic habitat over various time scales. Using Williams Canyon, a basin burned by the Waldo Canyon Fire (2012) as a case study, we utilize deterministic and statistical modeling methods (Fourier series and first order Markov chain) to assess pre- and post-fire geomorphic and hydrologic characteristics, including of precipitation, enhanced vegetation index (EVI, a satellite-based proxy of vegetation biomass), streamflow, and sediment flux. Local precipitation, terrestrial Light Detection and Ranging (LiDAR) scanning, and satellite-based products are used for these time series analyses. We present a framework to assess variability of periodic and nonperiodic climatic and multivariate trends to inform development of a post-wildfire risk assessment methodology. To establish the extent to which a wildfire affects hydrologic and geomorphic patterns, a Fourier series was used to fit pre- and post-fire geomorphic and hydrologic characteristics to yearly temporal cycles and subcycles of 6, 4, 3, and 2.4 months. These cycles were analyzed using least-squares estimates of the harmonic coefficients or amplitudes of each sub-cycle's contribution to fit the overall behavior of a Fourier series. The stochastic variances of these characteristics were analyzed by composing first-order Markov models and probabilistic analysis through direct likelihood estimates. Preliminary results highlight an increased dependence of monthly post-fire hydrologic characteristics on 12 and 6-month temporal cycles. This statistical and probabilistic analysis provides a basis to determine the impact of wildfires on the temporal dependence of

In silico and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

Science.gov (United States)

Schmidt, Julien; Guillaume, Philippe; Dojcinovic, Danijel; Karbach, Julia; Coukos, George; Luescher, Immanuel

2017-07-14

Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer immunotherapy. Of particular interest are mutated tumor antigen T-cell epitopes, because neoepitope-specific T cells often are tumoricidal. However, identifying tumor-specific T-cell epitopes is a major challenge. A widely used strategy relies on initial prediction of human leukocyte antigen-binding peptides by in silico algorithms, but the predictive power of this approach is unclear. Here, we used the human tumor antigen NY-ESO-1 (ESO) and the human leukocyte antigen variant HLA-A*0201 (A2) as a model and predicted in silico the 41 highest-affinity, A2-binding 8-11-mer peptides and assessed their binding, kinetic complex stability, and immunogenicity in A2-transgenic mice and on peripheral blood mononuclear cells from ESO-vaccinated melanoma patients. We found that 19 of the peptides strongly bound to A2, 10 of which formed stable A2-peptide complexes and induced CD8 + T cells in A2-transgenic mice. However, only 5 of the peptides induced cognate T cells in humans; these peptides exhibited strong binding and complex stability and contained multiple large hydrophobic and aromatic amino acids. These results were not predicted by in silico algorithms and provide new clues to improving T-cell epitope identification. In conclusion, our findings indicate that only a small fraction of in silico -predicted A2-binding ESO peptides are immunogenic in humans, namely those that have high peptide-binding strength and complex stability. This observation highlights the need for improving in silico predictions of peptide immunogenicity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

A Trillion-Dollar Question: What Predicts Student Loan Delinquencies?

Science.gov (United States)

Mezza, Alvaro; Sommer, Kamila

2016-01-01

The recent significant increase in student loan delinquencies has generated interest in understanding the key factors predicting the non-performance of these loans. However, despite the large size of the student loan market, existing analyses have been limited by lack of data. This paper studies predictors of student loan delinquencies using a…

Progress Report on Computational Analyses of Water-Based NSTF

Energy Technology Data Exchange (ETDEWEB)

Lv, Q. [Argonne National Lab. (ANL), Argonne, IL (United States); Kraus, A. [Argonne National Lab. (ANL), Argonne, IL (United States); Hu, R. [Argonne National Lab. (ANL), Argonne, IL (United States); Bucknor, M. [Argonne National Lab. (ANL), Argonne, IL (United States); Lisowski, D. [Argonne National Lab. (ANL), Argonne, IL (United States); Nunez, D. [Argonne National Lab. (ANL), Argonne, IL (United States)

2017-08-01

CFD analysis has been focused on important component-level phenomena using STARCCM+ to supplement the system analysis of integral system behavior. A notable area of interest was the cavity region. This area is of particular interest for CFD analysis due to the multi-dimensional flow and complex heat transfer (thermal radiation heat transfer and natural convection), which are not simulated directly by RELAP5. CFD simulations allow for the estimation of the boundary heat flux distribution along the riser tubes, which is needed in the RELAP5 simulations. The CFD results can also provide additional data to help establish what level of modeling detail is necessary in RELAP5. It was found that the flow profiles in the cavity region are simpler for the water-based concept than for the air-cooled concept. The local heat flux noticeably increases axially, and is higher in the fins than in the riser tubes. These results were utilized in RELAP5 simulations as boundary conditions, to provide better temperature predictions in the system level analyses. It was also determined that temperatures were higher in the fins than the riser tubes, but within design limits for thermal stresses. Higher temperature predictions were identified in the edge fins, in part due to additional thermal radiation from the side cavity walls.

Robust artificial neural network for reliability and sensitivity analyses of complex non-linear systems.

Science.gov (United States)

Oparaji, Uchenna; Sheu, Rong-Jiun; Bankhead, Mark; Austin, Jonathan; Patelli, Edoardo

2017-12-01

Artificial Neural Networks (ANNs) are commonly used in place of expensive models to reduce the computational burden required for uncertainty quantification, reliability and sensitivity analyses. ANN with selected architecture is trained with the back-propagation algorithm from few data representatives of the input/output relationship of the underlying model of interest. However, different performing ANNs might be obtained with the same training data as a result of the random initialization of the weight parameters in each of the network, leading to an uncertainty in selecting the best performing ANN. On the other hand, using cross-validation to select the best performing ANN based on the ANN with the highest R 2 value can lead to biassing in the prediction. This is as a result of the fact that the use of R 2 cannot determine if the prediction made by ANN is biased. Additionally, R 2 does not indicate if a model is adequate, as it is possible to have a low R 2 for a good model and a high R 2 for a bad model. Hence, in this paper, we propose an approach to improve the robustness of a prediction made by ANN. The approach is based on a systematic combination of identical trained ANNs, by coupling the Bayesian framework and model averaging. Additionally, the uncertainties of the robust prediction derived from the approach are quantified in terms of confidence intervals. To demonstrate the applicability of the proposed approach, two synthetic numerical examples are presented. Finally, the proposed approach is used to perform a reliability and sensitivity analyses on a process simulation model of a UK nuclear effluent treatment plant developed by National Nuclear Laboratory (NNL) and treated in this study as a black-box employing a set of training data as a test case. This model has been extensively validated against plant and experimental data and used to support the UK effluent discharge strategy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impulsivity facets’ predictive relations with DSM-5 PTSD symptom clusters

Science.gov (United States)

Roley, Michelle E.; Contractor, Ateka A.; Weiss, Nicole H.; Armour, Cherie; Elhai, Jon D.

2017-01-01

Objective Posttraumatic Stress Disorder (PTSD) has a well-established theoretical and empirical relation with impulsivity. Prior research has not used a multidimensional approach for measuring both PTSD and impulsivity constructs when assessing their relationship. Method The current study assessed the unique relationship of impulsivity facets on PTSD symptom clusters among a non-clinical sample of 412 trauma-exposed adults. Results Linear regression analyses revealed that impulsivity facets best accounted for PTSD’s arousal symptoms. The negative urgency facet of impulsivity was most predictive, as it was associated with all of PTSD’s symptom clusters. Sensation seeking did not predict PTSD’s intrusion symptoms, but did predict the other symptom clusters of PTSD. Lack of perseverance only predicted intrusion symptoms, while lack of premeditation only predicted PTSD’s mood/cognition symptoms. Conclusions Results extend theoretical and empirical research on the impulsivity-PTSD relationship, suggesting that impulsivity facets may serve as both risk and protective factors for PTSD symptoms. PMID:27243571

Prediction of crack coalescence of steam generator tubes in nuclear power plants

International Nuclear Information System (INIS)

Abou-Hanna, Jeries; McGreevy, Timothy E.; Majumdar, Saurin

2004-01-01

Prediction of failure pressures of cracked steam generator tubes of nuclear power plants is an important ingredient in scheduling inspection and repair of tubes. Prediction is usually based on nondestructive evaluation (NDE) of cracks. NDE often reveals two neighboring cracks. If the cracks interact, the tube pressure under which the ligament between the two cracks fails could be much lower than the critical burst pressure of an individual equivalent crack. The ability to accurately predict the ligament failure pressure, called ''coalescence pressure,'' is important. The failure criterion was established by nonlinear finite element model (FEM) analyses of coalescence of two 100% through-wall collinear cracks. The ligament failure is precipitated by local instability of the ligament under plane strain conditions. As a result of this local instability, the ligament thickness in the radial direction decreases abruptly with pressure. Good correlation of FEM analysis results with experimental data obtained at Argonne National Laboratory's Energy Technology Division demonstrated that nonlinear FEM analyses are capable of predicting the coalescence pressure accurately for 100% through-wall cracks. This failure criterion and FEA work have been extended to axial cracks of varying ligament width, crack length, and cases where cracks are offset by axial or circumferential ligaments

Impacts of Process and Prediction Uncertainties on Projected Hanford Waste Glass Amount

Energy Technology Data Exchange (ETDEWEB)

Gervasio, Vivianaluxa [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Vienna, John D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kim, Dong-Sang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kruger, Albert A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2018-02-19

Analyses were performed to evaluate the impacts of using the advanced glass models, constraints (Vienna et al. 2016), and uncertainty descriptions on projected Hanford glass mass. The maximum allowable WOL was estimated for waste compositions while simultaneously satisfying all applicable glass property and composition constraints with sufficient confidence. Different components of prediction and composition/process uncertainties were systematically included in the calculations to evaluate their impacts on glass mass. The analyses estimated the production of 23,360 MT of IHLW glass when no uncertainties were taken into accound. Accounting for prediction and composition/process uncertainties resulted in 5.01 relative percent increase in estimated glass mass 24,531 MT. Roughly equal impacts were found for prediction uncertainties (2.58 RPD) and composition/process uncertainties (2.43 RPD). ILAW mass was predicted to be 282,350 MT without uncertainty and with weaste loading “line” rules in place. Accounting for prediction and composition/process uncertainties resulted in only 0.08 relative percent increase in estimated glass mass of 282,562 MTG. Without application of line rules the glass mass decreases by 10.6 relative percent (252,490 MT) for the case with no uncertainties. Addition of prediction uncertainties increases glass mass by 1.32 relative percent and the addition of composition/process uncertainties increase glass mass by an additional 7.73 relative percent (9.06 relative percent increase combined). The glass mass estimate without line rules (275,359 MT) was 2.55 relative percent lower than that with the line rules (282,562 MT), after accounting for all applicable uncertainties.

Dietary acculturation and body composition predict American Hmong children's blood pressure.

Science.gov (United States)

Smith, Chery; Franzen-Castle, Lisa

2012-01-01

Determine how dietary acculturation, anthropometric measures (height, weight, circumferences, and skinfolds), body mass index (BMI), and waist hip ratios (WHRs) are associated with blood pressure (BP) measures in Hmong children living in Minnesota. Acculturation was measured using responses to questions regarding language usage, social connections, and diet. Dietary assessment was completed using the multiple-pass 24-h dietary recall method on two different days. Anthropometric and BP measurement were taken using standard procedures, and BMI and WHR were calculated. Data analyses included descriptive statistics, ANOVA, and stepwise regression analyses. Using stepwise regression analysis, hip circumference (HC) predicted boys' systolic (S)BP (R(2) = 0.55). For girls' SBP, mid-upper arm circumference, WHR, low calcium consumption, and height percentile jointly explained 41% of the total variation. Mid upper arm circumference (MAC) and carbohydrate consumption predicted 35% of the variance for boys' diastolic (D)BP, and HC, dairy consumption, and calcium intake predicted 31% of the total variance for girls' DBP. Responses to dietary acculturation questions revealed between group differences for breakfast with half of the younger Born-Thailand/Laos (Born-T/L) consuming mostly Hmong food, while at dinner Born-US consumed a mixed diet and Born-T/L were more likely to consume Hmong food. Dietary acculturation and body composition predict Hmong children's BP. Copyright © 2012 Wiley Periodicals, Inc.

Predictive Utility of Brief AUDIT for HIV Antiretroviral Medication Nonadherence

Science.gov (United States)

Broyles, Lauren Matukaitis; Gordon, Adam J.; Sereika, Susan M.; Ryan, Christopher M.; Erlen, Judith A.

2012-01-01

Alcohol use negatively affects adherence to antiretroviral therapy (ART), thus HIV/AIDS providers need accurate, efficient assessments of alcohol use. Using existing data from an efficacy trial of two cognitive-behavioral ART adherence interventions, we sought to determine if results on two common alcohol screening tests (Alcohol Use Disorders Identification Test—Consumption (AUDIT-C) and its binge-related question (AUDIT-3)) predict ART nonadherence. Twenty seven percent of the sample (n=308) were positive on the AUDIT-C and 34% were positive on the AUDIT-3. In multivariate analyses, AUDIT-C positive status predicted ART nonadherence after controlling for race, age, conscientiousness, and self-efficacy (p=.036). While AUDIT-3 positive status was associated with ART nonadherence in unadjusted analyses, this relationship was not maintained in the final multivariate model. The AUDIT-C shows potential as an indirect screening tool for both at-risk drinking and ART nonadherence, underscoring the relationship between alcohol and chronic disease management. PMID:22014256

Collapse mechanisms and strength prediction of reinforced concrete pile caps

DEFF Research Database (Denmark)

Jensen, Uffe G.; Hoang, Linh Cao

2012-01-01

. Calculations have been compared with nearly 200 test results found in the literature. Satisfactory agreement has been found. The analyses are conducted on concentrically loaded caps supported by four piles. The paper briefly outlines how the approach may be extended to more complicated loadings and geometries......This paper describes an upper bound plasticity approach for strength prediction of reinforced concrete pile caps. A number of collapse mechanisms are identified and analysed. The procedure leads to an estimate of the load-carrying capacity and an identification of the critical collapse mechanism...

BRCA1/2 missense mutations and the value of in-silico analyses.

Science.gov (United States)

Sadowski, Carolin E; Kohlstedt, Daniela; Meisel, Cornelia; Keller, Katja; Becker, Kerstin; Mackenroth, Luisa; Rump, Andreas; Schröck, Evelin; Wimberger, Pauline; Kast, Karin

2017-11-01

The clinical implications of genetic variants in BRCA1/2 in healthy and affected individuals are considerable. Variant interpretation, however, is especially challenging for missense variants. The majority of them are classified as variants of unknown clinical significance (VUS). Computational (in-silico) predictive programs are easy to access, but represent only one tool out of a wide range of complemental approaches to classify VUS. With this single-center study, we aimed to evaluate the impact of in-silico analyses in a spectrum of different BRCA1/2 missense variants. We conducted mutation analysis of BRCA1/2 in 523 index patients with suspected hereditary breast and ovarian cancer (HBOC). Classification of the genetic variants was performed according to the German Consortium (GC)-HBOC database. Additionally, all missense variants were classified by the following three in-silico prediction tools: SIFT, Mutation Taster (MT2) and PolyPhen2 (PPH2). Overall 201 different variants, 68 of which constituted missense variants were ranked as pathogenic, neutral, or unknown. The classification of missense variants by in-silico tools resulted in a higher amount of pathogenic mutations (25% vs. 13.2%) compared to the GC-HBOC-classification. Altogether, more than fifty percent (38/68, 55.9%) of missense variants were ranked differently. Sensitivity of in-silico-tools for mutation prediction was 88.9% (PPH2), 100% (SIFT) and 100% (MT2). We found a relevant discrepancy in variant classification by using in-silico prediction tools, resulting in potential overestimation and/or underestimation of cancer risk. More reliable, notably gene-specific, prediction tools and functional tests are needed to improve clinical counseling. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Using meta-analytic path analysis to test theoretical predictions in health behavior: An illustration based on meta-analyses of the theory of planned behavior.

Science.gov (United States)

Hagger, Martin S; Chan, Derwin K C; Protogerou, Cleo; Chatzisarantis, Nikos L D

2016-08-01

Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs from social cognitive theories is important to test nomological validity, account for mediation effects, and evaluate unique effects of theory constructs independent of past behavior. We illustrate our points by conducting new analyses of two meta-analyses of a popular theory applied to health behaviors, the theory of planned behavior. We conducted meta-analytic path analyses of the theory in two behavioral contexts (alcohol and dietary behaviors) using data from the primary studies included in the original meta-analyses augmented to include intercorrelations among constructs and relations with past behavior missing from the original analysis. Findings supported the nomological validity of the theory and its hypotheses for both behaviors, confirmed important model processes through mediation analysis, demonstrated the attenuating effect of past behavior on theory relations, and provided estimates of the unique effects of theory constructs independent of past behavior. Our analysis illustrates the importance of conducting a simultaneous test of theory-stipulated effects in meta-analyses of social cognitive theories applied to health behavior. We recommend researchers adopt this analytic procedure when synthesizing evidence across primary tests of social cognitive theories in health. Copyright © 2016 Elsevier Inc. All rights reserved.

Conceptual design and neutronics analyses of a fusion reactor blanket simulation facility

International Nuclear Information System (INIS)

Beller, D.E.

1986-01-01

A new conceptual design of a fusion reactor blanket simulation facility was developed. This design follows the principles that have been successfully employed in the Purdue Fast Breeder Blanket Facility (FBBR), because experiments conducted in it have resulted in the discovery of deficiencies in neutronics prediction methods. With this design, discrepancies between calculation and experimental data can be fully attributed to calculation methods because design deficiencies that could affect results are insignificant. Inelastic scattering cross sections are identified as a major source of these discrepancies. The conceptual design of this FBBR analog, the fusion reactor blanket facility (FRBF), is presented. Essential features are a cylindrical geometry and a distributed, cosine-shaped line source of 14-MeV neutrons. This source can be created by sweeping a deuteron beam over an elongated titanium-tritide target. To demonstrate that the design of the FRBF will not contribute significant deviations in experimental results, neutronics analyses were performed: results of comparisons of 2-dimensional to 1-dimensional predictions are reported for two blanket compositions. Expected deviations from 1-D predictions which are due to source anisotropy and blanket asymmetry are minimal. Thus, design of the FRBF allows simple and straightforward interpretation of the experimental results, without a need for coarse 3-D calculations

Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery.

Science.gov (United States)

Stenberg, Erik; Cao, Yang; Szabo, Eva; Näslund, Erik; Näslund, Ingmar; Ottosson, Johan

2018-01-12

Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently. This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these. Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015. Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p prediction model. Despite high specificity, the sensitivity of the model was low. Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.

Prediction of the radionuclide migration in the rocky environment. Part 1

International Nuclear Information System (INIS)

Ventura, M.A.

1987-01-01

A model for the prediction of the migration of radionuclides in a granitic rock was developed. Different numerial techniques associated with the resolution of the differential equations representing the problem were analysed. Verification results of the developed methodologies are presented. (author) [es

Parent Ratings of Impulsivity and Inhibition Predict State Testing Scores

Directory of Open Access Journals (Sweden)

Rebecca A. Lundwall

2018-03-01

Full Text Available One principle of cognitive development is that earlier intervention for educational difficulties tends to improve outcomes such as future educational and career success. One possible way to help students who struggle is to determine if they process information differently. Such determination might lead to clues for interventions. For example, early information processing requires attention before the information can be identified, encoded, and stored. The aim of the present study was to investigate whether parent ratings of inattention, inhibition, and impulsivity, and whether error rate on a reflexive attention task could be used to predict child scores on state standardized tests. Finding such an association could provide assistance to educators in identifying academically struggling children who might require targeted educational interventions. Children (N = 203 were invited to complete a peripheral cueing task (which measures the automatic reorienting of the brain’s attentional resources from one location to another. While the children completed the task, their parents completed a questionnaire. The questionnaire gathered information on broad indicators of child functioning, including observable behaviors of impulsivity, inattention, and inhibition, as well as state academic scores (which the parent retrieved online from their school. We used sequential regression to analyze contributions of error rate and parent-rated behaviors in predicting six academic scores. In one of the six analyses (for science, we found that the improvement was significant from the simplified model (with only family income, child age, and sex as predictors to the full model (adding error rate and three parent-rated behaviors. Two additional analyses (reading and social studies showed near significant improvement from simplified to full models. Parent-rated behaviors were significant predictors in all three of these analyses. In the reading score analysis

Analyses of systems availability and operator actions to support the development of severe accident procedures

International Nuclear Information System (INIS)

Lutz, R.J. Jr.; Scobel, J.H.

1989-01-01

This paper reports on traditional analyses of severe accidents, such as those presented in Probabilistic Risk Assessment (PRA) studies of nuclear power stations, that have generally been performed on the assumption that all means of cooling the reactor core are lost and that no operator actions to mitigate the consequences or progression of the severe accident are performed. The assumption to neglect the availability of safety systems and operator actions which do not prevent core melting can lead to erroneous conclusions regarding the plant severer accident profile. Recent work in severe accident management has identified the need to perform analyses which consider all systems availabilities and operator actions, irrespective of their contribution to the prevention of core melting. These new analyses indicate that the traditional analyses result in overfly pessimistic predictions of the time of core melting and the subsequent potential for recovery of core cooling prior to core melting. Additionally, since the traditional analyses do not model all of the operator actions which are prescribed, the impact of additional severe accident operator actions on the progression and consequences of the accident cannot be reliably identified. Further, the more detailed analysis can change the focus of the importance of various system to the prevention of core damage and the mitigation of severe accident consequences. Finally, the simplicity of the traditional analyses can have a considerable impact on severe accident decision making, particularly in the evaluation of alternate plant design features and the priorities for research studies

Engineering design and exergy analyses for combustion gas turbine based power generation system

International Nuclear Information System (INIS)

Sue, D.-C.; Chuang, C.-C.

2004-01-01

This paper presents the engineering design and theoretical exergetic analyses of the plant for combustion gas turbine based power generation systems. Exergy analysis is performed based on the first and second laws of thermodynamics for power generation systems. The results show the exergy analyses for a steam cycle system predict the plant efficiency more precisely. The plant efficiency for partial load operation is lower than full load operation. Increasing the pinch points will decrease the combined cycle plant efficiency. The engineering design is based on inlet air-cooling and natural gas preheating for increasing the net power output and efficiency. To evaluate the energy utilization, one combined cycle unit and one cogeneration system, consisting of gas turbine generators, heat recovery steam generators, one steam turbine generator with steam extracted for process have been analyzed. The analytical results are used for engineering design and component selection

Fully plastic crack opening analyses of complex-cracked pipes for Ramberg-Osgood materials

International Nuclear Information System (INIS)

Jeong, Jae Uk; Choi, Jae Boong; Huh, Nam Su; Kim, Yun Jae

2016-01-01

The plastic influence functions for calculating fully plastic Crack opening displacement (COD) of complex-cracked pipes were newly proposed based on systematic 3-dimensional (3-D) elastic-plastic Finite element (FE) analyses using Ramberg-Osgood (R-O) relation, where global bending moment, axial tension and internal pressure are considered separately as a loading condition. Then, crack opening analyses were performed based on GE/EPRI concept by using the new plastic influence functions for complex-cracked pipes made of SA376 TP304 stainless steel, and the predicted CODs were compared with FE results based on deformation plasticity theory of tensile material behavior. From the comparison, the confidence of the proposed fully plastic crack opening solutions for complex-cracked pipes was gained. Therefore, the proposed engineering scheme for COD estimation using the new plastic influence functions can be utilized to estimate leak rate of a complex-cracked pipe for R-O material.

Amikacin Concentrations Predictive of Ototoxicity in Multidrug-Resistant Tuberculosis Patients.

Science.gov (United States)

Modongo, Chawangwa; Pasipanodya, Jotam G; Zetola, Nicola M; Williams, Scott M; Sirugo, Giorgio; Gumbo, Tawanda

2015-10-01

Aminoglycosides, such as amikacin, are used to treat multidrug-resistant tuberculosis. However, ototoxicity is a common problem and is monitored using peak and trough amikacin concentrations based on World Health Organization recommendations. Our objective was to identify clinical factors predictive of ototoxicity using an agnostic machine learning method. We used classification and regression tree (CART) analyses to identify clinical factors, including amikacin concentration thresholds that predicted audiometry-confirmed ototoxicity among 28 multidrug-resistant pulmonary tuberculosis patients in Botswana. Amikacin concentrations were measured for all patients. The quantitative relationship between predictive factors and the probability of ototoxicity were then identified using probit analyses. The primary predictors of ototoxicity on CART analyses were cumulative days of therapy, followed by cumulative area under the concentration-time curve (AUC), which improved on the primary predictor by 87%. The area under the receiver operating curve was 0.97 on the test set. Peak and trough were not predictors in any tree. When algorithms were forced to pick peak and trough as primary predictors, the area under the receiver operating curve fell to 0.46. Probit analysis revealed that the probability of ototoxicity increased sharply starting after 6 months of therapy to near maximum at 9 months. A 10% probability of ototoxicity occurred with a threshold cumulative AUC of 87,232 days · mg · h/liter, while that of 20% occurred at 120,000 days · mg · h/liter. Thus, cumulative amikacin AUC and duration of therapy, and not peak and trough concentrations, should be used as the primary decision-making parameters to minimize the likelihood of ototoxicity in multidrug-resistant tuberculosis. Copyright © 2015, Modongo et al.

What predicts performance during clinical psychology training?

OpenAIRE

Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

2013-01-01

Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a r...

Prediction of postoperative pain by preoperative pain response to heat stimulation in total knee arthroplasty

DEFF Research Database (Denmark)

Lunn, Troels H; Gaarn-Larsen, Lissi; Kehlet, Henrik

2013-01-01

It has been estimated that up to 54% of the variance in postoperative pain experience may be predicted with preoperative pain responses to experimental stimuli, with suprathreshold heat pain as the most consistent test modality. We aimed to explore if 2 heat test paradigms could predict postopera......It has been estimated that up to 54% of the variance in postoperative pain experience may be predicted with preoperative pain responses to experimental stimuli, with suprathreshold heat pain as the most consistent test modality. We aimed to explore if 2 heat test paradigms could predict...... and logistic regressions analyses were carried out including 8 potential preoperative explanatory variables (among these anxiety, depression, preoperative pain and pain catastrophizing) to assess pain response to preoperative heat pain stimulation as independent predictor for postoperative pain. 100 patients...... by the linear and logistic regression analyses, where only anxiety, preoperative pain and pain catastrophizing were significant explanatory variables (but with low R-Squares;0.05-0.08). Pain responses to 2 types of preoperative heat stimuli were not independent clinical relevant predictors for postoperative...

Predicting future forestland area: a comparison of econometric approaches.

Science.gov (United States)

SoEun Ahn; Andrew J. Plantinga; Ralph J. Alig

2000-01-01

Predictions of future forestland area are an important component of forest policy analyses. In this article, we test the ability of econometric land use models to accurately forecast forest area. We construct a panel data set for Alabama consisting of county and time-series observation for the period 1964 to 1992. We estimate models using restricted data sets-namely,...

Spent-fuel composition: a comparison of predicted and measured data

International Nuclear Information System (INIS)

Thomas, C.C. Jr.; Cobb, D.D.; Ostenak, C.A.

1981-03-01

The uncertainty in predictions of the nuclear materials content of spent light-water reactor fuel was investigated to obtain guidelines for nondestructive spent-fuel verification and assay. Values predicted by the reactor operator were compared with measured values from fuel reprocessors for six reactors (three PWR and three BWR). The study indicates that total uranium, total plutonium, fissile uranium, fissile plutonium, and total fissile content can be predicted with biases ranging from 1 to 6% and variabilities (1-sigma) ranging from 2 to 7%. The higher values generally are associated with BWRs. Based on the results of this study, nondestructive assay measurements that are accurate and precise to 5 to 10% (1sigma) or better should be useful for quantitative analyses of typical spent fuel

Predictability of the evolution of hydrogeological and hydrogeochemical systems; geological disposal of nuclear waste in crystalline rocks

International Nuclear Information System (INIS)

Murphy, W.M.; Diodato, D.M.

2009-01-01

Confidence in long-term geologic isolation of high-level nuclear waste and spent nuclear fuel requires confidence in predictions of the evolution of hydrogeological and hydrogeochemical systems. Prediction of the evolution of hydrogeological and hydrogeochemical systems is based on scientific understanding of those systems in the present - an understanding that can be tested with data from the past. Crystalline rock settings that have been geologically stable for millions of years and longer offer the potential of predictable, long-term waste isolation. Confidence in predictions of geologic isolation of radioactive waste can measured by evaluating the extent to which those predictions and their underlying analyses are consistent with multiple independent lines of evidence identified in the geologic system being analysed, as well as with evidence identified in analogs to that geologic system. The proposed nuclear waste repository at Yucca Mountain, Nevada, United States, differs in significant ways from potential repository sites being considered by other nations. Nonetheless, observations of hydrogeological and hydrogeochemical systems of Yucca Mountain and Yucca Mountain analogs present multiple independent lines of evidence that can be used in evaluating long-term predictions of the evolution of hydrogeological and hydrogeochemical systems at Yucca Mountain. (authors)

Genomic Prediction of Gene Bank Wheat Landraces

Directory of Open Access Journals (Sweden)

José Crossa

2016-07-01

Full Text Available This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H for the highly heritable traits, days to heading (DTH, and days to maturity (DTM. Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E. Two alternative prediction strategies were studied: (1 random cross-validation of the data in 20% training (TRN and 80% testing (TST (TRN20-TST80 sets, and (2 two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm

Pegasys: software for executing and integrating analyses of biological sequences

Directory of Open Access Journals (Sweden)

Lett Drew

2004-04-01

Full Text Available Abstract Background We present Pegasys – a flexible, modular and customizable software system that facilitates the execution and data integration from heterogeneous biological sequence analysis tools. Results The Pegasys system includes numerous tools for pair-wise and multiple sequence alignment, ab initio gene prediction, RNA gene detection, masking repetitive sequences in genomic DNA as well as filters for database formatting and processing raw output from various analysis tools. We introduce a novel data structure for creating workflows of sequence analyses and a unified data model to store its results. The software allows users to dynamically create analysis workflows at run-time by manipulating a graphical user interface. All non-serial dependent analyses are executed in parallel on a compute cluster for efficiency of data generation. The uniform data model and backend relational database management system of Pegasys allow for results of heterogeneous programs included in the workflow to be integrated and exported into General Feature Format for further analyses in GFF-dependent tools, or GAME XML for import into the Apollo genome editor. The modularity of the design allows for new tools to be added to the system with little programmer overhead. The database application programming interface allows programmatic access to the data stored in the backend through SQL queries. Conclusions The Pegasys system enables biologists and bioinformaticians to create and manage sequence analysis workflows. The software is released under the Open Source GNU General Public License. All source code and documentation is available for download at http://bioinformatics.ubc.ca/pegasys/.

A systematic review of the quality of conduct and reporting of systematic reviews and meta-analyses in paediatric surgery.

Directory of Open Access Journals (Sweden)

Paul Stephen Cullis

Full Text Available Our objective was to evaluate quality of conduct and reporting of published systematic reviews and meta-analyses in paediatric surgery. We also aimed to identify characteristics predictive of review quality.Systematic reviews summarise evidence by combining sources, but are potentially prone to bias. To counter this, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA was published to aid in reporting. Similarly, the Assessing the Methodological Quality of Systematic Reviews (AMSTAR measurement tool was designed to appraise methodology. The paediatric surgical literature has seen an increasing number of reviews over the past decade, but quality has not been evaluated.Adhering to PRISMA guidelines, we performed a systematic review with a priori design to identify systematic reviews and meta-analyses of interventions in paediatric surgery. From 01/2010 to 06/2016, we searched: MEDLINE, EMBASE, Cochrane, Centre for Reviews and Dissemination, Web of Science, Google Scholar, reference lists and journals. Two reviewers independently selected studies and extracted data. We assessed conduct and reporting using AMSTAR and PRISMA. Scores were calculated as the sum of reported items. We also extracted author, journal and article characteristics, and used them in exploratory analysis to determine which variables predict quality.112 articles fulfilled eligibility criteria (53 systematic reviews; 59 meta-analyses. Overall, 68% AMSTAR and 56.8% PRISMA items were reported adequately. Poorest scores were identified with regards a priori design, inclusion of structured summaries, including the grey literature, citing excluded articles and evaluating bias. 13 reviews were pre-registered and 6 in PRISMA-endorsing journals. The following predicted quality in univariate analysis:, word count, Cochrane review, journal h-index, impact factor, journal endorses PRISMA, PRISMA adherence suggested in author guidance, article mentions PRISMA

PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA.

Science.gov (United States)

Schwartz, H Andrew; Sap, Maarten; Kern, Margaret L; Eichstaedt, Johannes C; Kapelner, Adam; Agrawal, Megha; Blanco, Eduardo; Dziurzynski, Lukasz; Park, Gregory; Stillwell, David; Kosinski, Michal; Seligman, Martin E P; Ungar, Lyle H

2016-01-01

We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being, which encompasses much more than emotion and mood, is linked with good mental and physical health. The ability to quickly and accurately assess it can supplement multi-million dollar national surveys as well as promote whole body health. Through crowd-sourced ratings of tweets and Facebook status updates, we create message-level predictive models for multiple components of well-being. However, well-being is ultimately attributed to people, so we perform an additional evaluation at the user-level, finding that a multi-level cascaded model, using both message-level predictions and userlevel features, performs best and outperforms popular lexicon-based happiness models. Finally, we suggest that analyses of language go beyond prediction by identifying the language that characterizes well-being.

DATA MINING WORKSPACE AS AN OPTIMIZATION PREDICTION TECHNIQUE FOR SOLVING TRANSPORT PROBLEMS

Directory of Open Access Journals (Sweden)

Anastasiia KUPTCOVA

2016-09-01

Full Text Available This article addresses the study related to forecasting with an actual high-speed decision making under careful modelling of time series data. The study uses data-mining modelling for algorithmic optimization of transport goals. Our finding brings to the future adequate techniques for the fitting of a prediction model. This model is going to be used for analyses of the future transaction costs in the frontiers of the Czech Republic. Time series prediction methods for the performance of prediction models in the package of Statistics are Exponential, ARIMA and Neural Network approaches. The primary target for a predictive scenario in the data mining workspace is to provide modelling data faster and with more versatility than the other management techniques.

Post-Irradiation Non-Destructive Analyses of the AFIP-7 Experiment

Science.gov (United States)

Williams, W. J.; Robinson, A. B.; Rabin, B. H.

2017-12-01

This article reports the results and interpretation of post-irradiation non-destructive examinations performed on four curved full-size fuel plates that comprise the AFIP-7 experiment. These fuel plates, having a U-10 wt.%Mo monolithic design, were irradiated under moderate operating conditions in the Advanced Test Reactor to assess fuel performance for geometries that are prototypic of research reactor fuel assemblies. Non-destructive examinations include visual examination, neutron radiography, profilometry, and precision gamma scanning. This article evaluates the qualitative and quantitative data taken for each plate, compares corresponding data sets, and presents the results of swelling analyses. These characterization results demonstrate that the fuel meets established irradiation performance requirements for mechanical integrity, geometric stability, and stable and predictable behavior.

SHERPA: A systematic human error reduction and prediction approach

International Nuclear Information System (INIS)

Embrey, D.E.

1986-01-01

This paper describes a Systematic Human Error Reduction and Prediction Approach (SHERPA) which is intended to provide guidelines for human error reduction and quantification in a wide range of human-machine systems. The approach utilizes as its basic current cognitive models of human performance. The first module in SHERPA performs task and human error analyses, which identify likely error modes, together with guidelines for the reduction of these errors by training, procedures and equipment redesign. The second module uses a SARAH approach to quantify the probability of occurrence of the errors identified earlier, and provides cost benefit analyses to assist in choosing the appropriate error reduction approaches in the third module

Incorporating Variational Local Analysis and Prediction System (vLAPS) Analyses with Nudging Data Assimilation: Methodology and Initial Results

Science.gov (United States)

2017-09-01

in the hybrid scheme. They conclude that in the Lorenz model they investigated, the hybrid scheme cannot result in errors that are simultaneously ...centered on the analysis time. Note that the spatial and temporal refinement of the analyses are taking place simultaneously (i.e., the first analysis...of a strong capping inversion and then a deep elevated mixed layer. At 1800 UTC (Fig. 5b), daytime heating along with the formation of a convective

Degradation mode analysis: An approach to establish effective predictive maintenance tasks

International Nuclear Information System (INIS)

Sonnett, D.E.; Douglass, P.T.; Barnard, D.D.

1991-01-01

A significant number of nuclear generating stations have been employing Reliability Centered Maintenance methodology to arrive at applicable and effective maintenance tasks for their plant equipment. The resultant endpoint of most programs has been an increased emphasis on predictive maintenance as the task of choice for monitoring and trending plant equipment condition to address failure mechanisms of the analyses. Many of these plants have spent several years conducting reliability centered analysis before they seriously begin implementing predictive program improvements. In this paper we present another methodology, entitled Degradation Mode Analysis, which provides a more direct method to quickly and economically achieve the major benefit of reliability centered analysis, namely predictive maintenance. (author)

Multi-model analysis in hydrological prediction

Science.gov (United States)

Lanthier, M.; Arsenault, R.; Brissette, F.

2017-12-01

Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

Analysis of syntax and word use to predict successful participation in guided self-help for anxiety and depression

DEFF Research Database (Denmark)

Zinken, Jörg; Zinken, Katarzyna; Wilson, J. Clare

2010-01-01

This study investigated whether an analysis of narrative style (word use and cross-clausal syntax) of patients with symptoms of generalised anxiety and depression disorders can help predict the likelihood of successful participation in guided self-help. Texts by 97 people who had made contact...... with a primary care mental health service were analysed. Outcome measures were completion of the guided self-help programme, and change in symptoms assessed by a standardised scale (CORE-OM). Regression analyses indicated that some aspects of participants' syntax helped to predict completion of the programme...

Impacts of Process and Prediction Uncertainties on Projected Hanford Waste Glass Amount

Energy Technology Data Exchange (ETDEWEB)

Gervasio, V.; Kim, D. S.; Vienna, J. D.; Kruger, A. A.

2018-03-08

Analyses were performed to evaluate the impacts of using the advanced glass models, constraints (Vienna et al. 2016), and uncertainty descriptions on projected Hanford glass mass. The maximum allowable waste oxide loading (WOL) was estimated for waste compositions while simultaneously satisfying all applicable glass property and composition constraints with sufficient confidence. Different components of prediction and composition/process uncertainties were systematically included in the calculations to evaluate their impacts on glass mass. The analyses estimated the production of 23,360 MT of immobilized high-level waste (IHLW) glass when no uncertainties were taken into account. Accounting for prediction and composition/process uncertainties resulted in 5.01 relative percent increase in estimated glass mass of 24,531 MT. Roughly equal impacts were found for prediction uncertainties (2.58 RPD) and composition/process uncertainties (2.43 RPD). The immobilized low-activity waste (ILAW) mass was predicted to be 282,350 MT without uncertainty and with waste loading “line” rules in place. Accounting for prediction and composition/process uncertainties resulted in only 0.08 relative percent increase in estimated glass mass of 282,562 MT. Without application of line rules the glass mass decreases by 10.6 relative percent (252,490 MT) for the case with no uncertainties. Addition of prediction uncertainties increases glass mass by 1.32 relative percent and the addition of composition/process uncertainties increase glass mass by an additional 7.73 relative percent (9.06 relative percent increase combined). The glass mass estimate without line rules (275,359 MT) was 2.55 relative percent lower than that with the line rules (282,562 MT), after accounting for all applicable uncertainties.

FDG-PET Response Prediction in Pediatric Hodgkin’s Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value

Energy Technology Data Exchange (ETDEWEB)

Hussien, Amr Elsayed M. [Department of Nuclear Medicine (KME), Forschungszentrum Jülich, Medical Faculty, Heinrich-Heine-University Düsseldorf, Jülich, 52426 (Germany); Department of Nuclear Medicine, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, 40225 (Germany); Furth, Christian [Department of Radiology and Nuclear Medicine, Medical School, Otto-von-Guericke University Magdeburg, Magdeburg, 39120 (Germany); Schönberger, Stefan [Department of Pediatric Oncology, Hematology and Clinical Immunology, University Children’s Hospital, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, 40225 (Germany); Hundsdoerfer, Patrick [Department of Pediatric Oncology and Hematology, Charité Campus Virchow, Humboldt-University Berlin, Berlin, 13353 (Germany); Steffen, Ingo G.; Amthauer, Holger [Department of Radiology and Nuclear Medicine, Medical School, Otto-von-Guericke University Magdeburg, Magdeburg, 39120 (Germany); Müller, Hans-Wilhelm; Hautzel, Hubertus, E-mail: h.hautzel@fz-juelich.de [Department of Nuclear Medicine (KME), Forschungszentrum Jülich, Medical Faculty, Heinrich-Heine-University Düsseldorf, Jülich, 52426 (Germany); Department of Nuclear Medicine, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, 40225 (Germany)

2015-01-28

Background: In pediatric Hodgkin’s lymphoma (pHL) early response-to-therapy prediction is metabolically assessed by (18)F-FDG PET carrying an excellent negative predictive value (NPV) but an impaired positive predictive value (PPV). Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV), PET-derived metabolic tumor volume (MTV) and the product of both parameters, termed total lesion glycolysis (TLG); Methods: One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54) of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in %) were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC)-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; Results: All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0%) but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Conclusions: Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV.

FDG-PET Response Prediction in Pediatric Hodgkin’s Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value

International Nuclear Information System (INIS)

Hussien, Amr Elsayed M.; Furth, Christian; Schönberger, Stefan; Hundsdoerfer, Patrick; Steffen, Ingo G.; Amthauer, Holger; Müller, Hans-Wilhelm; Hautzel, Hubertus

2015-01-01

Background: In pediatric Hodgkin’s lymphoma (pHL) early response-to-therapy prediction is metabolically assessed by (18)F-FDG PET carrying an excellent negative predictive value (NPV) but an impaired positive predictive value (PPV). Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV), PET-derived metabolic tumor volume (MTV) and the product of both parameters, termed total lesion glycolysis (TLG); Methods: One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54) of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in %) were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC)-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; Results: All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0%) but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Conclusions: Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV

Habitat features and predictive habitat modeling for the Colorado chipmunk in southern New Mexico

Science.gov (United States)

Rivieccio, M.; Thompson, B.C.; Gould, W.R.; Boykin, K.G.

2003-01-01

Two subspecies of Colorado chipmunk (state threatened and federal species of concern) occur in southern New Mexico: Tamias quadrivittatus australis in the Organ Mountains and T. q. oscuraensis in the Oscura Mountains. We developed a GIS model of potentially suitable habitat based on vegetation and elevation features, evaluated site classifications of the GIS model, and determined vegetation and terrain features associated with chipmunk occurrence. We compared GIS model classifications with actual vegetation and elevation features measured at 37 sites. At 60 sites we measured 18 habitat variables regarding slope, aspect, tree species, shrub species, and ground cover. We used logistic regression to analyze habitat variables associated with chipmunk presence/absence. All (100%) 37 sample sites (28 predicted suitable, 9 predicted unsuitable) were classified correctly by the GIS model regarding elevation and vegetation. For 28 sites predicted suitable by the GIS model, 18 sites (64%) appeared visually suitable based on habitat variables selected from logistic regression analyses, of which 10 sites (36%) were specifically predicted as suitable habitat via logistic regression. We detected chipmunks at 70% of sites deemed suitable via the logistic regression models. Shrub cover, tree density, plant proximity, presence of logs, and presence of rock outcrop were retained in the logistic model for the Oscura Mountains; litter, shrub cover, and grass cover were retained in the logistic model for the Organ Mountains. Evaluation of predictive models illustrates the need for multi-stage analyses to best judge performance. Microhabitat analyses indicate prospective needs for different management strategies between the subspecies. Sensitivities of each population of the Colorado chipmunk to natural and prescribed fire suggest that partial burnings of areas inhabited by Colorado chipmunks in southern New Mexico may be beneficial. These partial burnings may later help avoid a fire

Multiscale Analysis of the Predictability of Stock Returns

Directory of Open Access Journals (Sweden)

Paweł Fiedor

2015-06-01

Full Text Available Due to the strong complexity of financial markets, economics does not have a unified theory of price formation in financial markets. The most common assumption is the Efficient-Market Hypothesis, which has been attacked by a number of researchers, using different tools. There were varying degrees to which these tools complied with the formal definitions of efficiency and predictability. In our earlier work, we analysed the predictability of stock returns at two time scales using the entropy rate, which can be directly linked to the mathematical definition of predictability. Nonetheless, none of the above-mentioned studies allow any general understanding of how the financial markets work, beyond disproving the Efficient-Market Hypothesis. In our previous study, we proposed the Maximum Entropy Production Principle, which uses the entropy rate to create a general principle underlying the price formation processes. Both of these studies show that the predictability of price changes is higher at the transaction level intraday scale than the scale of daily returns, but ignore all scales in between. In this study we extend these ideas using the multiscale entropy analysis framework to enhance our understanding of the predictability of price formation processes at various time scales.

iPat: intelligent prediction and association tool for genomic research.

Science.gov (United States)

Chen, Chunpeng James; Zhang, Zhiwu

2018-06-01

The ultimate goal of genomic research is to effectively predict phenotypes from genotypes so that medical management can improve human health and molecular breeding can increase agricultural production. Genomic prediction or selection (GS) plays a complementary role to genome-wide association studies (GWAS), which is the primary method to identify genes underlying phenotypes. Unfortunately, most computing tools cannot perform data analyses for both GWAS and GS. Furthermore, the majority of these tools are executed through a command-line interface (CLI), which requires programming skills. Non-programmers struggle to use them efficiently because of the steep learning curves and zero tolerance for data formats and mistakes when inputting keywords and parameters. To address these problems, this study developed a software package, named the Intelligent Prediction and Association Tool (iPat), with a user-friendly graphical user interface. With iPat, GWAS or GS can be performed using a pointing device to simply drag and/or click on graphical elements to specify input data files, choose input parameters and select analytical models. Models available to users include those implemented in third party CLI packages such as GAPIT, PLINK, FarmCPU, BLINK, rrBLUP and BGLR. Users can choose any data format and conduct analyses with any of these packages. File conversions are automatically conducted for specified input data and selected packages. A GWAS-assisted genomic prediction method was implemented to perform genomic prediction using any GWAS method such as FarmCPU. iPat was written in Java for adaptation to multiple operating systems including Windows, Mac and Linux. The iPat executable file, user manual, tutorials and example datasets are freely available at http://zzlab.net/iPat. zhiwu.zhang@wsu.edu.

Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers.

Science.gov (United States)

Klimov, Sergey; Rida, Padmashree Cg; Aleskandarany, Mohammed A; Green, Andrew R; Ellis, Ian O; Janssen, Emiel Am; Rakha, Emad A; Aneja, Ritu

2017-09-05

Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC. A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses. Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status. Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.

Prediction of suicidality and violence in hospitalized adolescents: comparisons by sex.

Science.gov (United States)

Becker, Daniel F; Grilo, Carlos M

2007-09-01

To examine psychological correlates of suicidality and violent behaviour in hospitalized adolescents and the extent to which these associations may be affected by their sex. A sample of 487 psychiatric inpatients (207 male, 280 female), aged 12 to 19 years, completed a battery of psychometrically sound self-report measures of psychological functioning, substance abuse, suicidality, and violent behaviour. We conducted multiple regression analyses to determine the joint and independent predictors of suicide risk and violence risk. In subsequent analyses, we examined these associations separately by sex. Multiple regression analysis revealed that 9 variables (sex, age, hopelessness, self-esteem, depression, impulsivity, alcohol abuse, drug abuse, and violence risk) jointly predicted suicide risk and that an analogous model predicted violence risk. However, we found several differences with respect to which variables made significant independent contributions to these 2 predictive models. Female sex, low self-esteem, depression, drug abuse, and violence risk made independent contributions to suicide risk. Male sex, younger age, hopelessness, impulsivity, drug abuse, and suicide risk made independent contributions to violence risk. We observed a few additional differences when we considered male and female subjects separately. We found overlapping but distinctive patterns of prediction for suicide risk and violence risk, as well as some differences between male and female subjects. These results may reflect distinct psychological and behavioural pathways for suicidality and violence in adolescent psychiatric patients and differing risk factors for each sex. Such differences have potential implications for prevention and treatment programs.

Analysing the length of care episode after hip fracture: a nonparametric and a parametric Bayesian approach.

Science.gov (United States)

Riihimäki, Jaakko; Sund, Reijo; Vehtari, Aki

2010-06-01

Effective utilisation of limited resources is a challenge for health care providers. Accurate and relevant information extracted from the length of stay distributions is useful for management purposes. Patient care episodes can be reconstructed from the comprehensive health registers, and in this paper we develop a Bayesian approach to analyse the length of care episode after a fractured hip. We model the large scale data with a flexible nonparametric multilayer perceptron network and with a parametric Weibull mixture model. To assess the performances of the models, we estimate expected utilities using predictive density as a utility measure. Since the model parameters cannot be directly compared, we focus on observables, and estimate the relevances of patient explanatory variables in predicting the length of stay. To demonstrate how the use of the nonparametric flexible model is advantageous for this complex health care data, we also study joint effects of variables in predictions, and visualise nonlinearities and interactions found in the data.

Mood and the market: can press reports of investors' mood predict stock prices?

Science.gov (United States)

Cohen-Charash, Yochi; Scherbaum, Charles A; Kammeyer-Mueller, John D; Staw, Barry M

2013-01-01

We examined whether press reports on the collective mood of investors can predict changes in stock prices. We collected data on the use of emotion words in newspaper reports on traders' affect, coded these emotion words according to their location on an affective circumplex in terms of pleasantness and activation level, and created indices of collective mood for each trading day. Then, by using time series analyses, we examined whether these mood indices, depicting investors' emotion on a given trading day, could predict the next day's opening price of the stock market. The strongest findings showed that activated pleasant mood predicted increases in NASDAQ prices, while activated unpleasant mood predicted decreases in NASDAQ prices. We conclude that both valence and activation levels of collective mood are important in predicting trend continuation in stock prices.

A Prediction Model for ROS1-Rearranged Lung Adenocarcinomas based on Histologic Features

OpenAIRE

Zhou, Jianya; Zhao, Jing; Zheng, Jing; Kong, Mei; Sun, Ke; Wang, Bo; Chen, Xi; Ding, Wei; Zhou, Jianying

2016-01-01

Aims To identify the clinical and histological characteristics of ROS1-rearranged non-small-cell lung carcinomas (NSCLCs) and build a prediction model to prescreen suitable patients for molecular testing. Methods and Results We identified 27 cases of ROS1-rearranged lung adenocarcinomas in 1165 patients with NSCLCs confirmed by real-time PCR and FISH and performed univariate and multivariate analyses to identify predictive factors associated with ROS1 rearrangement and finally developed predi...

Inclusion of chloroplast genes that have undergone expansion misleads phylogenetic reconstruction in the Chlorophyta.

Science.gov (United States)

Novis, Phil M; Smissen, Rob; Buckley, Thomas R; Gopalakrishnan, Kishore; Visnovsky, Gabriel

2013-11-01

Chlorophytes comprise a substantial proportion of green plant diversity. However, sister-group relationships and circumscription of the classes Chlorophyceae, Trebouxiophyceae, and Ulvophyceae have been problematic to resolve. Some analyses support a sister relationship between the trebouxiophycean Leptosira and chlorophyceans, potentially altering the circumscription of two classes, also supported by a shared fragmentation in the chloroplast gene rpoB. We sought to determine whether the latter is a synapomorphy or whether the supporting analyses are vulnerable to systematic bias. We sequenced a portion of rpoB spanning the fragmented region in strains for which it had not previously been sampled: four Chlorophyceae, six counterclockwise (CCW) group (ulvophyceans and trebouxiophyceans) and one streptophyte. We then explored the effect of subsampling proteins and taxa on phylogenetic reconstruction from a data set of 41 chloroplast proteins. None of the CCW or streptophyte strains possessed the split in rpoB, including inferred near relatives of Leptosira, but it was found in all chlorophycean strains. We reconstructed alternative phylogenies (Leptosira + Chlorophyceae and Leptosira + Chlorellales) using two different protein groups (Rpo and Rps), both subject to coding-region expansion. A conserved region of RpoB remained suitable for analysis of more recent divergences. The Rps sequences can explain earlier findings linking Leptosira with the Chlorophyceae and should be excluded from phylogenetic analyses attempting to resolve deep nodes because their expansion violates the assumptions of substitution models. We reaffirm that Leptosira is a trebouxiophycean and that fragmentation of rpoB has occurred at least twice in chlorophyte evolution.

Predicting genome-wide redundancy using machine learning

Directory of Open Access Journals (Sweden)

Shasha Dennis E

2010-11-01

Full Text Available Abstract Background Gene duplication can lead to genetic redundancy, which masks the function of mutated genes in genetic analyses. Methods to increase sensitivity in identifying genetic redundancy can improve the efficiency of reverse genetics and lend insights into the evolutionary outcomes of gene duplication. Machine learning techniques are well suited to classifying gene family members into redundant and non-redundant gene pairs in model species where sufficient genetic and genomic data is available, such as Arabidopsis thaliana, the test case used here. Results Machine learning techniques that combine multiple attributes led to a dramatic improvement in predicting genetic redundancy over single trait classifiers alone, such as BLAST E-values or expression correlation. In withholding analysis, one of the methods used here, Support Vector Machines, was two-fold more precise than single attribute classifiers, reaching a level where the majority of redundant calls were correctly labeled. Using this higher confidence in identifying redundancy, machine learning predicts that about half of all genes in Arabidopsis showed the signature of predicted redundancy with at least one but typically less than three other family members. Interestingly, a large proportion of predicted redundant gene pairs were relatively old duplications (e.g., Ks > 1, suggesting that redundancy is stable over long evolutionary periods. Conclusions Machine learning predicts that most genes will have a functionally redundant paralog but will exhibit redundancy with relatively few genes within a family. The predictions and gene pair attributes for Arabidopsis provide a new resource for research in genetics and genome evolution. These techniques can now be applied to other organisms.

Development of a risk index for the prediction of chronic post-surgical pain.

Science.gov (United States)

Althaus, A; Hinrichs-Rocker, A; Chapman, R; Arránz Becker, O; Lefering, R; Simanski, C; Weber, F; Moser, K-H; Joppich, R; Trojan, S; Gutzeit, N; Neugebauer, E

2012-07-01

The incidence of chronic post-surgical pain (CPSP) after various common operations is 10% to 50%. Identification of patients at risk of developing chronic pain, and the management and prevention of CPSP remains inadequate. The aim of this study was to develop an easily applicable risk index for the detection of high-risk patients that takes into account the multifactorial aetiology of CPSP. A comprehensive item pool was derived from a systematic literature search. Items that turned out significant in bivariate analyses were then analysed multivariately, using logistic regression analyses. The items that yielded significant predictors in the multivariate analyses were compiled into an index. The cut-off score for a high risk of developing CPSP with an optimal trade-off between sensitivity and specificity was identified. The data of 150 patients who underwent different types of surgery were included in the analyses. Six months after surgery, 43.3% of the patients reported CPSP. Five predictors multivariately contributed to the prediction of CPSP: capacity overload, preoperative pain in the operating field, other chronic preoperative pain, post-surgical acute pain and co-morbid stress symptoms. These results suggest that several easily assessable preoperative and perioperative patient characteristics can predict a patient's risk of developing CPSP. The risk index may help caregivers to tailor individual pain management and to assist high-risk patients with pain coping. © 2011 European Federation of International Association for the Study of Pain Chapters.

Evaluation of residue-residue contact prediction in CASP10

KAUST Repository

Monastyrskyy, Bohdan

2013-08-31

We present the results of the assessment of the intramolecular residue-residue contact predictions from 26 prediction groups participating in the 10th round of the CASP experiment. The most recently developed direct coupling analysis methods did not take part in the experiment likely because they require a very deep sequence alignment not available for any of the 114 CASP10 targets. The performance of contact prediction methods was evaluated with the measures used in previous CASPs (i.e., prediction accuracy and the difference between the distribution of the predicted contacts and that of all pairs of residues in the target protein), as well as new measures, such as the Matthews correlation coefficient, the area under the precision-recall curve and the ranks of the first correctly and incorrectly predicted contact. We also evaluated the ability to detect interdomain contacts and tested whether the difficulty of predicting contacts depends upon the protein length and the depth of the family sequence alignment. The analyses were carried out on the target domains for which structural homologs did not exist or were difficult to identify. The evaluation was performed for all types of contacts (short, medium, and long-range), with emphasis placed on long-range contacts, i.e. those involving residues separated by at least 24 residues along the sequence. The assessment suggests that the best CASP10 contact prediction methods perform at approximately the same level, and comparably to those participating in CASP9.

Do fly parasites of bats and their hosts coevolve?speciation in Trichobius phyllostomae group (Diptera, Streblidae and their hosts (Chiroptera, Phyllostomidae suggests that they do not

Directory of Open Access Journals (Sweden)

Gustavo Graciolli

2012-12-01

Full Text Available We examined whether, like many parasite-host systems of coevolution, a group of obligate parasitic bat flies (Trichobius phyllostomae Kessel and related species cospeciate with their hosts. We first did a cladistic analysis of the T. phyllostomae group and combined that analysis with a phylogenetic hypothesis from the literature for the Stenodermatinae bats. The cladistic analysis included, as outgroups, one species from each morphological group and complex of Trichobius Gervais, and one species from the following genera: Paratrichobius Miranda-Ribeiro, Megistopoda Macquart, Megistapophysys Dick & Wenzel, Neotrichobius Wenzel & Aitken, Speiseria Kessel and Strebla Wiedemann. The cladogram was rooted with a species of Strebla in the subfamily Streblinae. One cladogram was obtained and which found Trichobius to be polyphyletic. The phylogenetic hypothesis as follows: (Paratrichobius, (Neotrichobius, (Megistopoda, Megistapophysis is the sister-group of the phyllostomae group and the following relationships within the ingroup, (((T. vampyropis Wenzel, Trichobius sp. 2 ((T. hispidus Wenzel, T. petersoni Wenzel ((Trichobius sp. 1 (T. phyllostomae, T. brennani Wenzel. When we compared phylogenies through historical association analyses, cospeciation was uncommon, while host-switching was more common and better explained the association between the phyllostomae group and their bat hosts.

Effect of relative humidity and temperature control on in-cabin thermal comfort state: Thermodynamic and psychometric analyses

International Nuclear Information System (INIS)

Alahmer, A.; Omar, M.A.; Mayyas, A.; Dongri, Shan

2011-01-01

This manuscript discusses the effect of manipulating the Relative Humidity RH of in-cabin environment on the thermal comfort and human occupants' thermal sensation. The study uses thermodynamic and psychometric analyses, to incorporate the effect of changing RH along with the dry bulb temperature on human comfort. Specifically, the study computes the effect of changing the relative humidity on the amount of heat rejected from the passenger compartment and the effect of relative humidity on occupants comfort zone. A practical system implementation is also discussed in terms of an evaporative cooler design. The results show that changing the RH along with dry bulb temperature inside vehicular cabins can improve the air conditioning efficiency by reducing the heat removed while improving the Human comfort sensations as measured by the Predicted Mean Value PMV and the Predicted Percentage Dissatisfied PPD indices. - Highlights: → Investigates the effect of controlling the RH and dry bulb temperature on in-cabin thermal comfort and sensation. → Conducts the thermodynamic and psychometric analyses for changing the RH and temperature for in-cabin air conditioning. → Discusses a possible system implementation through an evaporative cooler design.

1D/2D analyses of the lower head vessel in contact with high temperature melt

International Nuclear Information System (INIS)

Chang, Jong Eun; Cho, Jae Seon; Suh, Kune Y.; Chung, Chang H.

1998-01-01

One- and two-dimensional analyses were performed for the ceramic/metal melt and the vessel to interpret the temperature history of the outer surface of the vessel wall measured from typical Al 2 O 3 /Fe thermite melt tests LAVA (Lower-plenum Arrested Vessel Attack) spanning heatup and cooldown periods. The LAVA tests were conducted at the Korea Atomic Energy Research Institute (KAERI) during the process of high temperature molten material relocation from the delivery duct down into the water in the test vessel pressurized to 2.0 MPa. Both analyses demonstrated reasonable predictions of the temperature history of the LHV (Lower Head Vessel). The comparison sheds light on the thermal hydraulic and material behavior of the high temperature melt within the hemispherical vessel

Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach

Directory of Open Access Journals (Sweden)

Rui Xue

2015-01-01

Full Text Available Although bus passenger demand prediction has attracted increased attention during recent years, limited research has been conducted in the context of short-term passenger demand forecasting. This paper proposes an interactive multiple model (IMM filter algorithm-based model to predict short-term passenger demand. After aggregated in 15 min interval, passenger demand data collected from a busy bus route over four months were used to generate time series. Considering that passenger demand exhibits various characteristics in different time scales, three time series were developed, named weekly, daily, and 15 min time series. After the correlation, periodicity, and stationarity analyses, time series models were constructed. Particularly, the heteroscedasticity of time series was explored to achieve better prediction performance. Finally, IMM filter algorithm was applied to combine individual forecasting models with dynamically predicted passenger demand for next interval. Different error indices were adopted for the analyses of individual and hybrid models. The performance comparison indicates that hybrid model forecasts are superior to individual ones in accuracy. Findings of this study are of theoretical and practical significance in bus scheduling.

Statistical prediction of biomethane potentials based on the composition of lignocellulosic biomass

DEFF Research Database (Denmark)

Thomsen, Sune Tjalfe; Spliid, Henrik; Østergård, Hanne

2014-01-01

Mixture models are introduced as a new and stronger methodology for statistical prediction of biomethane potentials (BPM) from lignocellulosic biomass compared to the linear regression models previously used. A large dataset from literature combined with our own data were analysed using canonical...

Analyses and computer code developments for accident-induced thermohydraulic transients in water-cooled nuclear reactor systems

International Nuclear Information System (INIS)

Wulff, W.

1977-01-01

A review is presented on the development of analyses and computer codes for the prediction of thermohydraulic transients in nuclear reactor systems. Models for the dynamics of two-phase mixtures are summarized. Principles of process, reactor component and reactor system modeling are presented, as well as the verification of these models by comparing predicted results with experimental data. Codes of major importance are described, which have recently been developed or are presently under development. The characteristics of these codes are presented in terms of governing equations, solution techniques and code structure. Current efforts and problems of code verification are discussed. A summary is presented of advances which are necessary for reducing the conservatism currently implied in reactor hydraulics codes for safety assessment

The Predictive Value of Selection Criteria in an Urban Magnet School

Science.gov (United States)

Lohmeier, Jill Hendrickson; Raad, Jennifer

2012-01-01

The predictive value of selection criteria on outcome data from two cohorts of students (Total N = 525) accepted to an urban magnet high school were evaluated. Regression analyses of typical screening variables (suspensions, absences, metropolitan achievement tests, middle school grade point averages [GPAs], Matrix Analogies test scores, and…

Predicting the mental health of college students with psychological capital.

Science.gov (United States)

Selvaraj, Priscilla Rose; Bhat, Christine Suniti

2018-06-01

Behavioral health treatment is grounded in the medical model with language of deficits and problems, rather than resources and strengths. With developments in the field of positive psychology, re-focusing on well-being rather than illness is possible. The primary purpose of this study was to examine relationships and predictions that exist between levels of mental health in college students, i.e., flourishing, moderate mental health, and languishing, and psychological capital (PsyCap). For this cross-sectional, exploratory study survey method was used for data collection and for analyses of results a series of descriptive, correlation, ANOVA, and multiple regression analyses were done. Results indicated that developing positive psychological strengths such as hope, efficacy, resilience, and optimism (acronym HERO) within college students significantly increased their positive mental health. Based on the predictive nature of PsyCap, mental health professionals may engage more in creating programs incorporating PsyCap development intervention for college students. Implications for counseling and programmatic services for college students are presented along with suggestions for future research.

SitesIdentify: a protein functional site prediction tool

Directory of Open Access Journals (Sweden)

Doig Andrew J

2009-11-01

Full Text Available Abstract Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify, based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/

Risk analyses in nuclear engineerig, their value in terms of information, and their limits in terms of applicability

International Nuclear Information System (INIS)

Heuser, F.W.

1983-01-01

This contribution first briefly explains the main pillars of the deterministic safety concept as developed in nuclear engineering, and some basic ideas on risk analyses in general. This is followed by an outline of the methodology and main purposes of risk analyses. The German Risk Study is taken as an example to discuss selected aspects with regard to information value and limits of risk analyses. The main conclusions state that risk analyses are a valuable instrument for quantitative safety evaluation, leading to a better understanding of safety problems and their prevention, and allowing a comparative assessment of various safety measures. They furthermore allow a refined evaluation of a variety of accident parameters and other impacts determining the risk emanating from accidents. The current state of the art in this sector still leaves numerous uncertainties so that risk analyses yield information for assessments rather than for definite predictions. However, the urge for quantifying the lack of knowledge leads to a better and more precise determination of the gaps still to be filled up by researchers and engineers. Thus risk analyses are a useful help in defining suitable approaches and setting up standards, showing the tasks to be fulfilled in safety research in general. (orig./HSCH) [de

Error analysis in predictive modelling demonstrated on mould data.

Science.gov (United States)

Baranyi, József; Csernus, Olívia; Beczner, Judit

2014-01-17

The purpose of this paper was to develop a predictive model for the effect of temperature and water activity on the growth rate of Aspergillus niger and to determine the sources of the error when the model is used for prediction. Parallel mould growth curves, derived from the same spore batch, were generated and fitted to determine their growth rate. The variances of replicate ln(growth-rate) estimates were used to quantify the experimental variability, inherent to the method of determining the growth rate. The environmental variability was quantified by the variance of the respective means of replicates. The idea is analogous to the "within group" and "between groups" variability concepts of ANOVA procedures. A (secondary) model, with temperature and water activity as explanatory variables, was fitted to the natural logarithm of the growth rates determined by the primary model. The model error and the experimental and environmental errors were ranked according to their contribution to the total error of prediction. Our method can readily be applied to analysing the error structure of predictive models of bacterial growth models, too. © 2013.

Beyond discrimination: A comparison of calibration methods and clinical usefulness of predictive models of readmission risk.

Science.gov (United States)

Walsh, Colin G; Sharman, Kavya; Hripcsak, George

2017-12-01

Prior to implementing predictive models in novel settings, analyses of calibration and clinical usefulness remain as important as discrimination, but they are not frequently discussed. Calibration is a model's reflection of actual outcome prevalence in its predictions. Clinical usefulness refers to the utilities, costs, and harms of using a predictive model in practice. A decision analytic approach to calibrating and selecting an optimal intervention threshold may help maximize the impact of readmission risk and other preventive interventions. To select a pragmatic means of calibrating predictive models that requires a minimum amount of validation data and that performs well in practice. To evaluate the impact of miscalibration on utility and cost via clinical usefulness analyses. Observational, retrospective cohort study with electronic health record data from 120,000 inpatient admissions at an urban, academic center in Manhattan. The primary outcome was thirty-day readmission for three causes: all-cause, congestive heart failure, and chronic coronary atherosclerotic disease. Predictive modeling was performed via L1-regularized logistic regression. Calibration methods were compared including Platt Scaling, Logistic Calibration, and Prevalence Adjustment. Performance of predictive modeling and calibration was assessed via discrimination (c-statistic), calibration (Spiegelhalter Z-statistic, Root Mean Square Error [RMSE] of binned predictions, Sanders and Murphy Resolutions of the Brier Score, Calibration Slope and Intercept), and clinical usefulness (utility terms represented as costs). The amount of validation data necessary to apply each calibration algorithm was also assessed. C-statistics by diagnosis ranged from 0.7 for all-cause readmission to 0.86 (0.78-0.93) for congestive heart failure. Logistic Calibration and Platt Scaling performed best and this difference required analyzing multiple metrics of calibration simultaneously, in particular Calibration

Species classifier choice is a key consideration when analysing low-complexity food microbiome data.

Science.gov (United States)

Walsh, Aaron M; Crispie, Fiona; O'Sullivan, Orla; Finnegan, Laura; Claesson, Marcus J; Cotter, Paul D

2018-03-20

The use of shotgun metagenomics to analyse low-complexity microbial communities in foods has the potential to be of considerable fundamental and applied value. However, there is currently no consensus with respect to choice of species classification tool, platform, or sequencing depth. Here, we benchmarked the performances of three high-throughput short-read sequencing platforms, the Illumina MiSeq, NextSeq 500, and Ion Proton, for shotgun metagenomics of food microbiota. Briefly, we sequenced six kefir DNA samples and a mock community DNA sample, the latter constructed by evenly mixing genomic DNA from 13 food-related bacterial species. A variety of bioinformatic tools were used to analyse the data generated, and the effects of sequencing depth on these analyses were tested by randomly subsampling reads. Compositional analysis results were consistent between the platforms at divergent sequencing depths. However, we observed pronounced differences in the predictions from species classification tools. Indeed, PERMANOVA indicated that there was no significant differences between the compositional results generated by the different sequencers (p = 0.693, R 2  = 0.011), but there was a significant difference between the results predicted by the species classifiers (p = 0.01, R 2  = 0.127). The relative abundances predicted by the classifiers, apart from MetaPhlAn2, were apparently biased by reference genome sizes. Additionally, we observed varying false-positive rates among the classifiers. MetaPhlAn2 had the lowest false-positive rate, whereas SLIMM had the greatest false-positive rate. Strain-level analysis results were also similar across platforms. Each platform correctly identified the strains present in the mock community, but accuracy was improved slightly with greater sequencing depth. Notably, PanPhlAn detected the dominant strains in each kefir sample above 500,000 reads per sample. Again, the outputs from functional profiling analysis using

Physiological Informatics: Collection and Analyses of Data from Wearable Sensors and Smartphone for Healthcare.

Science.gov (United States)

Bai, Jinwei; Shen, Li; Sun, Huimin; Shen, Bairong

2017-01-01

Physiological data from wearable sensors and smartphone are accumulating rapidly, and this provides us the chance to collect dynamic and personalized information as phenotype to be integrated to genotype for the holistic understanding of complex diseases. This integration can be applied to early prediction and prevention of disease, therefore promoting the shifting of disease care tradition to the healthcare paradigm. In this chapter, we summarize the physiological signals which can be detected by wearable sensors, the sharing of the physiological big data, and the mining methods for the discovery of disease-associated patterns for personalized diagnosis and treatment. We discuss the challenges of physiological informatics about the storage, the standardization, the analyses, and the applications of the physiological data from the wearable sensors and smartphone. At last, we present our perspectives on the models for disentangling the complex relationship between early disease prediction and the mining of physiological phenotype data.

Comparison of LOFT zero power physics testing measurement results with predicted values

International Nuclear Information System (INIS)

Rushton, B.L.; Howe, T.M.

1978-01-01

The results of zero power physics testing measurements in LOFT have been evaluated to assess the adequacy of the physics data used in the safety analyses performed for the LOFT FSAR and Technical Specifications. Comparisons of measured data with computed data were made for control rod worths, temperature coefficients, boron worths, and pressure coefficients. Measured boron concentrations at exact critical points were compared with predicted concentrations. Based on these comparisons, the reactivity parameter values used in the LOFT safety analyses were assessed for conservatism

Development of time-trend model for analysing and predicting case pattern of dog bite injury induced rabies-like-illness in Liberia, 2014-2017.

Science.gov (United States)

Jomah, N D; Ojo, J F; Odigie, E A; Olugasa, B O

2014-12-01

The post-civil war records of dog bite injuries (DBI) and rabies-like-illness (RLI) among humans in Liberia is a vital epidemiological resource for developing a predictive model to guide the allocation of resources towards human rabies control. Whereas DBI and RLI are high, they are largely under-reported. The objective of this study was to develop a time model of the case-pattern and apply it to derive predictors of time-trend point distribution of DBI-RLI cases. A retrospective 6 years data of DBI distribution among humans countrywide were converted to quarterly series using a transformation technique of Minimizing Squared First Difference statistic. The generated dataset was used to train a time-trend model of the DBI-RLI syndrome in Liberia. An additive detenninistic time-trend model was selected due to its performance compared to multiplication model of trend and seasonal movement. Parameter predictors were run on least square method to predict DBI cases for a prospective 4 years period, covering 2014-2017. The two-stage predictive model of DBI case-pattern between 2014 and 2017 was characterised by a uniform upward trend within Liberia's coastal and hinterland Counties over the forecast period. This paper describes a translational application of the time-trend distribution pattern of DBI epidemics, 2008-2013 reported in Liberia, on which a predictive model was developed. A computationally feasible two-stage time-trend permutation approach is proposed to estimate the time-trend parameters and conduct predictive inference on DBI-RLI in Liberia.

Microscopic model analyses of proton elastic scattering from diverse targets in the energy range 65 to 400 MeV

International Nuclear Information System (INIS)

Dortmans, P.J.; Amos, K.

1997-01-01

Two nucleon (NN) effective interactions based upon two-nucleon g matrices have been used in fully microscopic calculations of nonlocal proton-nucleus optical potentials for protons with energies between 65 and 400 MeV. Excellent predictions of the differential cross sections, analysing powers and spin rotations for scattering angles to 60 deg result. (authors)

Can Preoperative Psychological Assessment Predict Outcomes After Temporomandibular Joint Arthroscopy?

Science.gov (United States)

Bouloux, Gary F; Zerweck, Ashley G; Celano, Marianne; Dai, Tian; Easley, Kirk A

2015-11-01

Psychological assessment has been used successfully to predict patient outcomes after cardiothoracic and bariatric surgery. The purpose of this study was to determine whether preoperative psychological assessment could be used to predict patient outcomes after temporomandibular joint arthroscopy. Consecutive patients with temporomandibular dysfunction (TMD) who could benefit from arthroscopy were enrolled in a prospective cohort study. All patients completed the Millon Behavior Medicine Diagnostic survey before surgery. The primary predictor variable was the preoperative psychological scores. The primary outcome variable was the difference in pain between the pre- and postoperative periods. The Spearman rank correlation coefficient and the Pearson product-moment correlation were used to determine the association between psychological factors and change in pain. Univariable and multivariable analyses were performed using a mixed-effects linear model and multiple linear regression. A P value of .05 was considered significant. Eighty-six patients were enrolled in the study. Seventy-five patients completed the study and were included in the final analyses. The mean change in visual analog scale (VAS) pain score 1 month after arthroscopy was -15.4 points (95% confidence interval, -6.0 to -24.7; P psychological factors was identified with univariable correlation analyses. Multivariable analyses identified that a greater pain decrease was associated with a longer duration of preoperative symptoms (P = .054) and lower chronic anxiety (P = .064). This study has identified a weak association between chronic anxiety and the magnitude of pain decrease after arthroscopy for TMD. Further studies are needed to clarify the role of chronic anxiety in the outcome after surgical procedures for the treatment of TMD. Copyright © 2015. Published by Elsevier Inc.

Mood and the Market: Can Press Reports of Investors' Mood Predict Stock Prices?

Science.gov (United States)

Scherbaum, Charles A.; Kammeyer-Mueller, John D.

2013-01-01

We examined whether press reports on the collective mood of investors can predict changes in stock prices. We collected data on the use of emotion words in newspaper reports on traders' affect, coded these emotion words according to their location on an affective circumplex in terms of pleasantness and activation level, and created indices of collective mood for each trading day. Then, by using time series analyses, we examined whether these mood indices, depicting investors' emotion on a given trading day, could predict the next day's opening price of the stock market. The strongest findings showed that activated pleasant mood predicted increases in NASDAQ prices, while activated unpleasant mood predicted decreases in NASDAQ prices. We conclude that both valence and activation levels of collective mood are important in predicting trend continuation in stock prices. PMID:24015202

Analysis of MRI by fractals for prediction of sensory attributes: A case study in loin

DEFF Research Database (Denmark)

Caballero, Daniel; Antequera, Teresa; Caro, Andrés

2018-01-01

This study investigates the use of fractal algorithms to analyse MRI of meat products, specifically loin, in order to determine sensory parameters of loin. For that, the capability of different fractal algorithms was evaluated (Classical Fractal Algorithm, CFA; Fractal Texture Algorithm, FTA...... was analysed. Results on this study firstly demonstrate the capability of fractal algorithms to analyse MRI from meat product. Different combinations of the analysed techniques can be applied for predicting most sensory attributes of loins adequately (R > 0.5). However, the combination of SE, OPFTA and MLR...... offered the most appropriate results. Thus, it could be proposed as an alternative to the traditional food technology methods....

Process of Integrating Screening and Detailed Risk-based Modeling Analyses to Ensure Consistent and Scientifically Defensible Results

International Nuclear Information System (INIS)

Buck, John W.; McDonald, John P.; Taira, Randal Y.

2002-01-01

To support cleanup and closure of these tanks, modeling is performed to understand and predict potential impacts to human health and the environment. Pacific Northwest National Laboratory developed a screening tool for the United States Department of Energy, Office of River Protection that estimates the long-term human health risk, from a strategic planning perspective, posed by potential tank releases to the environment. This tool is being conditioned to more detailed model analyses to ensure consistency between studies and to provide scientific defensibility. Once the conditioning is complete, the system will be used to screen alternative cleanup and closure strategies. The integration of screening and detailed models provides consistent analyses, efficiencies in resources, and positive feedback between the various modeling groups. This approach of conditioning a screening methodology to more detailed analyses provides decision-makers with timely and defensible information and increases confidence in the results on the part of clients, regulators, and stakeholders

Laser Beam Focus Analyser

DEFF Research Database (Denmark)

Nielsen, Peter Carøe; Hansen, Hans Nørgaard; Olsen, Flemming Ove

2007-01-01

the obtainable features in direct laser machining as well as heat affected zones in welding processes. This paper describes the development of a measuring unit capable of analysing beam shape and diameter of lasers to be used in manufacturing processes. The analyser is based on the principle of a rotating......The quantitative and qualitative description of laser beam characteristics is important for process implementation and optimisation. In particular, a need for quantitative characterisation of beam diameter was identified when using fibre lasers for micro manufacturing. Here the beam diameter limits...... mechanical wire being swept through the laser beam at varying Z-heights. The reflected signal is analysed and the resulting beam profile determined. The development comprised the design of a flexible fixture capable of providing both rotation and Z-axis movement, control software including data capture...

Nuclear criticality predictability

International Nuclear Information System (INIS)

Briggs, J.B.

1999-01-01

As a result of lots of efforts, a large portion of the tedious and redundant research and processing of critical experiment data has been eliminated. The necessary step in criticality safety analyses of validating computer codes with benchmark critical data is greatly streamlined, and valuable criticality safety experimental data is preserved. Criticality safety personnel in 31 different countries are now using the 'International Handbook of Evaluated Criticality Safety Benchmark Experiments'. Much has been accomplished by the work of the ICSBEP. However, evaluation and documentation represents only one element of a successful Nuclear Criticality Safety Predictability Program and this element only exists as a separate entity, because this work was not completed in conjunction with the experimentation process. I believe; however, that the work of the ICSBEP has also served to unify the other elements of nuclear criticality predictability. All elements are interrelated, but for a time it seemed that communications between these elements was not adequate. The ICSBEP has highlighted gaps in data, has retrieved lost data, has helped to identify errors in cross section processing codes, and has helped bring the international criticality safety community together in a common cause as true friends and colleagues. It has been a privilege to associate with those who work so diligently to make the project a success. (J.P.N.)

Detailed comparison of next-to-leading order predictions for jet photoproduction at HERA.

Energy Technology Data Exchange (ETDEWEB)

Harris, B. W.; Klassen, M.; Vossebeld, J.

1999-06-02

The precision of new HERA data on jet photoproduction opens up the possibility to discriminate between different models of the photon structure. This requires equally precise theoretical predictions from perturbative QCD calculations. In the past years, next-to-leading order calculations for the photoproduction of jets at HERA have become available. Using the kinematic cuts of recent ZEUS analyses, we compare the predictions of three calculations for different dijet and three-jet distributions. We find that in general all three calculations agree within the statistical accuracy of the Monte Carlo integration yielding reliable theoretical predictions. In certain restricted regions of phase space, the calculations differ by up to 5%.

Predictive value of specific radiographic findings of disability in patients with rheumatoid arthritis

International Nuclear Information System (INIS)

Kaye, J.J.; Nance, E.P. Jr.; Callahan, L.F.; Pincus, T.

1986-01-01

This study was carried out to determine whether and to what extend radiographic erosion, joint space narrowing, and malalignment are predictive of clinical disability in patients with rheumatoid arthristis (RA). Radiographs of the hands and wrists of 224 patients with RA were scored for these radiographic parameters. To determine which of these findings best explained variation in clinical measures of disability, a series of regression analyses was performed. Malalignment scores were the best predictor of joint deformity and limitation of motion. Erosion scores were most predictive of variation in functional tests. The author concludes that specific radiographic findings of malalignment and erosion are significantly predictive of disability in patients with RA

Probabilistic approach in treatment of deterministic analyses results of severe accidents

International Nuclear Information System (INIS)

Krajnc, B.; Mavko, B.

1996-01-01

Severe accidents sequences resulting in loss of the core geometric integrity have been found to have small probability of the occurrence. Because of their potential consequences to public health and safety, an evaluation of the core degradation progression and the resulting effects on the containment is necessary to determine the probability of a significant release of radioactive materials. This requires assessment of many interrelated phenomena including: steel and zircaloy oxidation, steam spikes, in-vessel debris cooling, potential vessel failure mechanisms, release of core material to the containment, containment pressurization from steam generation, or generation of non-condensable gases or hydrogen burn, and ultimately coolability of degraded core material. To asses the answer from the containment event trees in the sense of weather certain phenomenological event would happen or not the plant specific deterministic analyses should be performed. Due to the fact that there is a large uncertainty in the prediction of severe accidents phenomena in Level 2 analyses (containment event trees) the combination of probabilistic and deterministic approach should be used. In fact the result of the deterministic analyses of severe accidents are treated in probabilistic manner due to large uncertainty of results as a consequence of a lack of detailed knowledge. This paper discusses approach used in many IPEs, and which assures that the assigned probability for certain question in the event tree represent the probability that the event will or will not happen and that this probability also includes its uncertainty, which is mainly result of lack of knowledge. (author)

Impact of implementation choices on quantitative predictions of cell-based computational models

Science.gov (United States)

Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

2017-09-01

'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

A new approach to analyse longitudinal epidemiological data with an excess of zeros.

Science.gov (United States)

Spriensma, Alette S; Hajos, Tibor R S; de Boer, Michiel R; Heymans, Martijn W; Twisk, Jos W R

2013-02-20

Within longitudinal epidemiological research, 'count' outcome variables with an excess of zeros frequently occur. Although these outcomes are frequently analysed with a linear mixed model, or a Poisson mixed model, a two-part mixed model would be better in analysing outcome variables with an excess of zeros. Therefore, objective of this paper was to introduce the relatively 'new' method of two-part joint regression modelling in longitudinal data analysis for outcome variables with an excess of zeros, and to compare the performance of this method to current approaches. Within an observational longitudinal dataset, we compared three techniques; two 'standard' approaches (a linear mixed model, and a Poisson mixed model), and a two-part joint mixed model (a binomial/Poisson mixed distribution model), including random intercepts and random slopes. Model fit indicators, and differences between predicted and observed values were used for comparisons. The analyses were performed with STATA using the GLLAMM procedure. Regarding the random intercept models, the two-part joint mixed model (binomial/Poisson) performed best. Adding random slopes for time to the models changed the sign of the regression coefficient for both the Poisson mixed model and the two-part joint mixed model (binomial/Poisson) and resulted into a much better fit. This paper showed that a two-part joint mixed model is a more appropriate method to analyse longitudinal data with an excess of zeros compared to a linear mixed model and a Poisson mixed model. However, in a model with random slopes for time a Poisson mixed model also performed remarkably well.

Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

Science.gov (United States)

Lee, Diane Sookyoung; Padilla, Amado M.

2016-01-01

This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

Evaluation of multivariate statistical analyses for monitoring and prediction of processes in an seawater reverse osmosis desalination plant

Energy Technology Data Exchange (ETDEWEB)

Kolluri, Srinivas Sahan; Esfahani, Iman Janghorban; Garikiparthy, Prithvi Sai Nadh; Yoo, Chang Kyoo [Kyung Hee University, Yongin (Korea, Republic of)

2015-08-15

Our aim was to analyze, monitor, and predict the outcomes of processes in a full-scale seawater reverse osmosis (SWRO) desalination plant using multivariate statistical techniques. Multivariate analysis of variance (MANOVA) was used to investigate the performance and efficiencies of two SWRO processes, namely, pore controllable fiber filterreverse osmosis (PCF-SWRO) and sand filtration-ultra filtration-reverse osmosis (SF-UF-SWRO). Principal component analysis (PCA) was applied to monitor the two SWRO processes. PCA monitoring revealed that the SF-UF-SWRO process could be analyzed reliably with a low number of outliers and disturbances. Partial least squares (PLS) analysis was then conducted to predict which of the seven input parameters of feed flow rate, PCF/SF-UF filtrate flow rate, temperature of feed water, turbidity feed, pH, reverse osmosis (RO)flow rate, and pressure had a significant effect on the outcome variables of permeate flow rate and concentration. Root mean squared errors (RMSEs) of the PLS models for permeate flow rates were 31.5 and 28.6 for the PCF-SWRO process and SF-UF-SWRO process, respectively, while RMSEs of permeate concentrations were 350.44 and 289.4, respectively. These results indicate that the SF-UF-SWRO process can be modeled more accurately than the PCF-SWRO process, because the RMSE values of permeate flowrate and concentration obtained using a PLS regression model of the SF-UF-SWRO process were lower than those obtained for the PCF-SWRO process.

Evaluation of multivariate statistical analyses for monitoring and prediction of processes in an seawater reverse osmosis desalination plant

International Nuclear Information System (INIS)

Kolluri, Srinivas Sahan; Esfahani, Iman Janghorban; Garikiparthy, Prithvi Sai Nadh; Yoo, Chang Kyoo

2015-01-01

Our aim was to analyze, monitor, and predict the outcomes of processes in a full-scale seawater reverse osmosis (SWRO) desalination plant using multivariate statistical techniques. Multivariate analysis of variance (MANOVA) was used to investigate the performance and efficiencies of two SWRO processes, namely, pore controllable fiber filterreverse osmosis (PCF-SWRO) and sand filtration-ultra filtration-reverse osmosis (SF-UF-SWRO). Principal component analysis (PCA) was applied to monitor the two SWRO processes. PCA monitoring revealed that the SF-UF-SWRO process could be analyzed reliably with a low number of outliers and disturbances. Partial least squares (PLS) analysis was then conducted to predict which of the seven input parameters of feed flow rate, PCF/SF-UF filtrate flow rate, temperature of feed water, turbidity feed, pH, reverse osmosis (RO)flow rate, and pressure had a significant effect on the outcome variables of permeate flow rate and concentration. Root mean squared errors (RMSEs) of the PLS models for permeate flow rates were 31.5 and 28.6 for the PCF-SWRO process and SF-UF-SWRO process, respectively, while RMSEs of permeate concentrations were 350.44 and 289.4, respectively. These results indicate that the SF-UF-SWRO process can be modeled more accurately than the PCF-SWRO process, because the RMSE values of permeate flowrate and concentration obtained using a PLS regression model of the SF-UF-SWRO process were lower than those obtained for the PCF-SWRO process.

Predictive role of the nighttime blood pressure

DEFF Research Database (Denmark)

Hansen, Tine W; Li, Yan; Boggia, José

2011-01-01

Numerous studies addressed the predictive value of the nighttime blood pressure (BP) as captured by ambulatory monitoring. However, arbitrary cutoff limits in dichotomized analyses of continuous variables, data dredging across selected subgroups, extrapolation of cross-sectional studies...... of conclusive evidence proving that nondipping is a reversible risk factor, the option whether or not to restore the diurnal blood pressure profile to a normal pattern should be left to the clinical judgment of doctors and should be individualized for each patient. Current guidelines on the interpretation...

An approach to model validation and model-based prediction -- polyurethane foam case study.

Energy Technology Data Exchange (ETDEWEB)

Dowding, Kevin J.; Rutherford, Brian Milne

2003-07-01

Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical

Distance saturation product predicts health-related quality of life among sarcoidosis patients.

Science.gov (United States)

Bourbonnais, Julie M; Malaisamy, Subramanian; Dalal, Bhavinkumar D; Samarakoon, Priyan C; Parikh, Swapna R; Samavati, Lobelia

2012-06-13

Sarcoidosis is a chronic disease with different phenotypic manifestations. Health-related quality of life is an important aspect in sarcoidosis, yet difficult to measure. The objective of this study was to identify clinical markers predictive of poor quality of life in sarcoidosis patients that can be followed over time and targeted for intervention. We assessed the quality of life of 162 patients with confirmed sarcoidosis in a prospective, cross-sectional study using the Sarcoidosis Health Questionnaire (SHQ) and Short Form-36 Health Survey (SF-36). We evaluated the validity of these questionnaires and sought to identify variables that would best explain the performance scores of the patients. On multivariate regression analyses, the very best composite model to predict total scores from both surveys was a model containing the distance-saturation product and Borg Dyspnea Scale score at the end of a 6-min walk test. This model could better predict SF-36 scores (R² = 0.33) than SHQ scores (R² = 0.24). Substitution of distanced walked in 6 min for the distance-saturation product in this model resulted in a lesser ability to predict both scores (R² = 0.26 for SF-36; R² = 0.22 for SHQ). Both the SHQ and SF-36 surveys are valuable tools in the assessment of health-related quality of life in sarcoidosis patients. The best model to predict quality of life among these patients, as determined by regression analyses, included the distance-saturation product and Borg score after the 6-min walk test. Both variables represent easily obtainable clinical parameters that can be followed over time and targeted for intervention.

Microscopic model analyses of the elastic scattering of 25, 30, and 40 MeV protons from targets of diverse mass

International Nuclear Information System (INIS)

Deb, P.K.; Amos, K.; Karataglidis, S.

2000-01-01

An extensive survey and analysis of cross section and analysing power data from proton elastic scattering at energies 25 to 40 MeV is presented. The data are compared with predictions obtained from a full folding specification of the proton-nucleus optical potentials. Isotope and energy variation of the data is explained

Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: pattern-recognition analyses for screening quality control purposes.

Science.gov (United States)

Flumignan, Danilo Luiz; Boralle, Nivaldo; Oliveira, José Eduardo de

2010-06-30

In this work, the combination of carbon nuclear magnetic resonance ((13)C NMR) fingerprinting with pattern-recognition analyses provides an original and alternative approach to screening commercial gasoline quality. Soft Independent Modelling of Class Analogy (SIMCA) was performed on spectroscopic fingerprints to classify representative commercial gasoline samples, which were selected by Hierarchical Cluster Analyses (HCA) over several months in retails services of gas stations, into previously quality-defined classes. Following optimized (13)C NMR-SIMCA algorithm, sensitivity values were obtained in the training set (99.0%), with leave-one-out cross-validation, and external prediction set (92.0%). Governmental laboratories could employ this method as a rapid screening analysis to discourage adulteration practices. Copyright 2010 Elsevier B.V. All rights reserved.

Defining the predicted protein secretome of the fungal wheat leaf pathogen Mycosphaerella graminicola.

Directory of Open Access Journals (Sweden)

Alexandre Morais do Amaral

Full Text Available The Dothideomycete fungus Mycosphaerella graminicola is the causal agent of Septoria tritici blotch, a devastating disease of wheat leaves that causes dramatic decreases in yield. Infection involves an initial extended period of symptomless intercellular colonisation prior to the development of visible necrotic disease lesions. Previous functional genomics and gene expression profiling studies have implicated the production of secreted virulence effector proteins as key facilitators of the initial symptomless growth phase. In order to identify additional candidate virulence effectors, we re-analysed and catalogued the predicted protein secretome of M. graminicola isolate IPO323, which is currently regarded as the reference strain for this species. We combined several bioinformatic approaches in order to increase the probability of identifying truly secreted proteins with either a predicted enzymatic function or an as yet unknown function. An initial secretome of 970 proteins was predicted, whilst further stringent selection criteria predicted 492 proteins. Of these, 321 possess some functional annotation, the composition of which may reflect the strictly intercellular growth habit of this pathogen, leaving 171 with no functional annotation. This analysis identified a protein family encoding secreted peroxidases/chloroperoxidases (PF01328 which is expanded within all members of the family Mycosphaerellaceae. Further analyses were done on the non-annotated proteins for size and cysteine content (effector protein hallmarks, and then by studying the distribution of homologues in 17 other sequenced Dothideomycete fungi within an overall total of 91 predicted proteomes from fungal, oomycete and nematode species. This detailed M. graminicola secretome analysis provides the basis for further functional and comparative genomics studies.

Drug target prediction and prioritization: using orthology to predict essentiality in parasite genomes

Directory of Open Access Journals (Sweden)

Hall Ross S

2010-04-01

Full Text Available Abstract Background New drug targets are urgently needed for parasites of socio-economic importance. Genes that are essential for parasite survival are highly desirable targets, but information on these genes is lacking, as gene knockouts or knockdowns are difficult to perform in many species of parasites. We examined the applicability of large-scale essentiality information from four model eukaryotes, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus and Saccharomyces cerevisiae, to discover essential genes in each of their genomes. Parasite genes that lack orthologues in their host are desirable as selective targets, so we also examined prediction of essential genes within this subset. Results Cross-species analyses showed that the evolutionary conservation of genes and the presence of essential orthologues are each strong predictors of essentiality in eukaryotes. Absence of paralogues was also found to be a general predictor of increased relative essentiality. By combining several orthology and essentiality criteria one can select gene sets with up to a five-fold enrichment in essential genes compared with a random selection. We show how quantitative application of such criteria can be used to predict a ranked list of potential drug targets from Ancylostoma caninum and Haemonchus contortus - two blood-feeding strongylid nematodes, for which there are presently limited sequence data but no functional genomic tools. Conclusions The present study demonstrates the utility of using orthology information from multiple, diverse eukaryotes to predict essential genes. The data also emphasize the challenge of identifying essential genes among those in a parasite that are absent from its host.

Prediction of the residual strength of clay using functional networks

Directory of Open Access Journals (Sweden)

S.Z. Khan

2016-01-01

Full Text Available Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of stability of slopes or landslides. This effect is more pronounced in sensitive clays which show large changes in shear strength from peak to residual states. This study analyses the prediction of the residual strength of clay based on a new prediction model, functional networks (FN using data available in the literature. The performance of FN was compared with support vector machine (SVM and artificial neural network (ANN based on statistical parameters like correlation coefficient (R, Nash--Sutcliff coefficient of efficiency (E, absolute average error (AAE, maximum average error (MAE and root mean square error (RMSE. Based on R and E parameters, FN is found to be a better prediction tool than ANN for the given data. However, the R and E values for FN are less than SVM. A prediction equation is presented that can be used by practicing geotechnical engineers. A sensitivity analysis is carried out to ascertain the importance of various inputs in the prediction of the output.

[Predictive value of Hodgkin's lymphoma tumor burden in present].

Science.gov (United States)

Kulyova, S A; Karitsky, A P

2014-01-01

Today approximately 70% of patients with Hodgkin lymphoma can be cured with the combined-modality therapy. Tumor burden, the importance of which was demonstrated 15 years ago for the first time, is a powerful prognostic factor. Data of literature of representations on predictive value of Hodgkin's lymphoma tumor burden are shown in the article. The difficult immunological relations between tumor cells and reactive ones lead to development of the main symptoms. Nevertheless, the collective sign of tumor burden shows the greatest influence on survival and on probability of resistance, which relative risk can be predicted on this variable and treatment program. Patients with bulky disease need escalated therapy with high-dose chemotherapy. Integration into predictive models of the variable will change an expected contribution of clinical and laboratory parameters in the regression analyses constructed on patients with Hodgkin's lymphoma. Today the role of diagnostic functional methods, in particular a positron emission tomography, for metabolic active measurement is conducted which allows excluding a reactive component.

Analyses of non-fatal accidents in an opencast mine by logistic regression model - a case study.

Science.gov (United States)

Onder, Seyhan; Mutlu, Mert

2017-09-01

Accidents cause major damage for both workers and enterprises in the mining industry. To reduce the number of occupational accidents, these incidents should be properly registered and carefully analysed. This study efficiently examines the Aegean Lignite Enterprise (ELI) of Turkish Coal Enterprises (TKI) in Soma between 2006 and 2011, and opencast coal mine occupational accident records were used for statistical analyses. A total of 231 occupational accidents were analysed for this study. The accident records were categorized into seven groups: area, reason, occupation, part of body, age, shift hour and lost days. The SPSS package program was used in this study for logistic regression analyses, which predicted the probability of accidents resulting in greater or less than 3 lost workdays for non-fatal injuries. Social facilities-area of surface installations, workshops and opencast mining areas are the areas with the highest probability for accidents with greater than 3 lost workdays for non-fatal injuries, while the reasons with the highest probability for these types of accidents are transporting and manual handling. Additionally, the model was tested for such reported accidents that occurred in 2012 for the ELI in Soma and estimated the probability of exposure to accidents with lost workdays correctly by 70%.

Prediction of LOFT L1-4 experiment

International Nuclear Information System (INIS)

Soda, Kunihisa; Sasaki, Shinobu; Akimoto, Masayuki; Koizumi, Yasuo; Araya, Fumimasa

1977-10-01

LOFT L1-4 experimental results were predicted by LOFT Analysis Group and Code Development Group using RELAP-4J and ALARM-P1 respectively. The input data prepared by the former group were used in both the analyses. Thus any differences in the results should stem from the differences in code performance characteristics of the two codes. (1) The coolant behaviors predicted by RELAP-4J and ALARM-P1 are in good agreement although some differences do exist between these two calculation models. (2) Large difference is seen in coolant flow rate across the pump. The coast down and the flow rate by ALARM-P1 are larger and smaller respectively than by RELAP-4J. (3) An explicit method of the ALARM-P1 leads to unstable calculation at a T shaped junction when one of the two volumes connected by the junction is filled with subcooled water. (4) Coolant flow in the downcomer, heat transfer to and from the steam generator secondary and suppression tank behavior must be modified to better predict the experimental results. (5) Additional instrumentation in reflood assist and ECC injection lines are necessary to better nderstand the coolant behavior. (auth.)

Predicting, monitoring and controlling geomechanical effects of CO2 injection

International Nuclear Information System (INIS)

Streit, J.E.; Siggins, A.F.

2005-01-01

A key objective of geological carbon dioxide (CO 2 ) storage in porous rock is long-term subsurface containment of CO 2 . Fault stability and maximum sustainable pore-fluid pressures should be estimated in geomechanical studies in order to avoid damage to reservoir seals and fault seals of storage sites during CO 2 injection. Such analyses rely on predicting the evolution of effective stresses in rocks and faults during CO 2 injection. However, geomechanical analyses frequently do not incorporate poroelastic behaviour of reservoir rock, as relevant poroelastic properties are rarely known. The knowledge of rock poroelastic properties would allow the use of seismic methods for the accurate measurement of the effective stress evolution during CO 2 injection. This paper discussed key geomechanical effects of CO 2 injection into porous rock, and in particular, focused on the effects that the poroelasticity of reservoir rocks and pore pressure/stress coupling have on effective stresses. Relevant geophysical monitoring techniques were also suggested. The paper also outlined how these techniques could be applied to measure stress changes related to poroelastic rock behaviour during CO 2 injection and to test the predictions of sustainable changes in effective stress in CO 2 storage sites. It was concluded that a combination of predictive geomechanical techniques and application of geophysical monitoring techniques is a valid new concept for controlling and monitoring the geomechanical effects of CO 2 storage. 36 refs., 5 figs

Work characteristics predict the development of multi-site musculoskeletal pain.

Science.gov (United States)

Oakman, Jodi; de Wind, Astrid; van den Heuvel, Swenne G; van der Beek, Allard J

2017-10-01

Musculoskeletal pain in more than one body region is common and a barrier to sustaining employment. We aimed to examine whether work characteristics predict the development of multi-site pain (MSP), and to determine differences in work-related predictors between age groups. This study is based on 5136 employees from the Study on Transitions in Employment, Ability and Motivation (STREAM) who reported no MSP at baseline. Measures included physical, emotional, mental, and psychological job demands, social support and autonomy. Predictors of MSP were studied by logistic regression analyses. Univariate and multivariate analyses with age stratification (45-49, 50-54, 55-59, and 60-64 years) were done to explore differences between age groups. All work characteristics with the exception of autonomy were predictive of the development of MSP, with odds ratios varying from 1.21 (95% CI 1.04-1.40) for mental job demands to 1.63 (95% CI 1.43-1.86) for physical job demands. No clear pattern of age-related differences in the predictors of MSP emerged, with the exception of social support, which was predictive of MSP developing in all age groups except for the age group 60-64 years. Adverse physical and psychosocial work characteristics are associated with MSP. Organisations need to comprehensively assess work environments to ensure that all relevant workplace hazards, physical and psychosocial, are identified and then controlled for across all age groups.

Analyzing power in pp scattering at low energies: the Paris potential predictions

International Nuclear Information System (INIS)

Cote, J.; Pires, P.; Tourreil, R. de; Lacombe, M.; Loiseau, B.; Vinh Mau, R.

1979-12-01

Predictions of the Paris potential for the analyzing power in pp scattering at low energies are compared with recent high precision measurements at 6.14MeV and earlier measurements at 10 and 16MeV. Phase shift values are also presented and discussed in view of previous analyses

Consumer brand choice: individual and group analyses of demand elasticity.

Science.gov (United States)

Oliveira-Castro, Jorge M; Foxall, Gordon R; Schrezenmaier, Teresa C

2006-03-01

Following the behavior-analytic tradition of analyzing individual behavior, the present research investigated demand elasticity of individual consumers purchasing supermarket products, and compared individual and group analyses of elasticity. Panel data from 80 UK consumers purchasing 9 product categories (i.e., baked beans, biscuits, breakfast cereals, butter, cheese, fruit juice, instant coffee, margarine and tea) during a 16-week period were used. Elasticity coefficients were calculated for individual consumers with data from all or only 1 product category (intra-consumer elasticities), and for each product category using all data points from all consumers (overall product elasticity) or 1 average data point per consumer (interconsumer elasticity). In addition to this, split-sample elasticity coefficients were obtained for each individual with data from all product categories purchased during weeks 1 to 8 and 9 to 16. The results suggest that: 1) demand elasticity coefficients calculated for individual consumers purchasing supermarket food products are compatible with predictions from economic theory and behavioral economics; 2) overall product elasticities, typically employed in marketing and econometric research, include effects of interconsumer and intraconsumer elasticities; 3) when comparing demand elasticities of different product categories, group and individual analyses yield similar trends; and 4) individual differences in demand elasticity are relatively consistent across time, but do not seem to be consistent across products. These results demonstrate the theoretical, methodological, and managerial relevance of investigating the behavior of individual consumers.

Contesting Citizenship: Comparative Analyses

DEFF Research Database (Denmark)

Siim, Birte; Squires, Judith

2007-01-01

importance of particularized experiences and multiple ineequality agendas). These developments shape the way citizenship is both practiced and analysed. Mapping neat citizenship modles onto distinct nation-states and evaluating these in relation to formal equality is no longer an adequate approach....... Comparative citizenship analyses need to be considered in relation to multipleinequalities and their intersections and to multiple governance and trans-national organisinf. This, in turn, suggests that comparative citizenship analysis needs to consider new spaces in which struggles for equal citizenship occur...

Making detailed predictions makes (some) predictions worse

Science.gov (United States)

Kelly, Theresa F.

In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

E-waste Management and Refurbishment Prediction (EMARP) Model for Refurbishment Industries.

Science.gov (United States)

Resmi, N G; Fasila, K A

2017-10-01

This paper proposes a novel algorithm for establishing a standard methodology to manage and refurbish e-waste called E-waste Management And Refurbishment Prediction (EMARP), which can be adapted by refurbishing industries in order to improve their performance. Waste management, particularly, e-waste management is a serious issue nowadays. Computerization has been into waste management in different ways. Much of the computerization has happened in planning the waste collection, recycling and disposal process and also managing documents and reports related to waste management. This paper proposes a computerized model to make predictions for e-waste refurbishment. All possibilities for reusing the common components among the collected e-waste samples are predicted, thus minimizing the wastage. Simulation of the model has been done to analyse the accuracy in the predictions made by the system. The model can be scaled to accommodate the real-world scenario. Copyright © 2017 Elsevier Ltd. All rights reserved.

Incremental validity of positive and negative valence in predicting personality disorder.

Science.gov (United States)

Simms, Leonard J; Yufik, Tom; Gros, Daniel F

2010-04-01

The Big Seven model of personality includes five dimensions similar to the Big Five model as well as two evaluative dimensions—Positive Valence (PV) and Negative Valence (NV)—which reflect extremely positive and negative person descriptors, respectively. Recent theory and research have suggested that PV and NV predict significant variance in personality disorder (PD) above that predicted by the Big Five, but firm conclusions have not been possible because previous studies have been limited to only single measures of PV, NV, and the Big Five traits. In the present study, we replicated and extended previous findings using three markers of all key constructs—including PV, NV, and the Big Five—in a diverse sample of 338 undergraduates. Results of hierarchical multiple regression analyses revealed that PV incrementally predicted Narcissistic and Histrionic PDs above the Big Five and that NV nonspecifically incremented the prediction of most PDs. Implications for dimensional models of personality pathology are discussed. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: a case study in endemic districts of Bhutan.

Science.gov (United States)

Wangdi, Kinley; Singhasivanon, Pratap; Silawan, Tassanee; Lawpoolsri, Saranath; White, Nicholas J; Kaewkungwal, Jaranit

2010-09-03

Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009

Non-Statistical Methods of Analysing of Bankruptcy Risk

Directory of Open Access Journals (Sweden)

Pisula Tomasz

2015-06-01

Full Text Available The article focuses on assessing the effectiveness of a non-statistical approach to bankruptcy modelling in enterprises operating in the logistics sector. In order to describe the issue more comprehensively, the aforementioned prediction of the possible negative results of business operations was carried out for companies functioning in the Polish region of Podkarpacie, and in Slovakia. The bankruptcy predictors selected for the assessment of companies operating in the logistics sector included 28 financial indicators characterizing these enterprises in terms of their financial standing and management effectiveness. The purpose of the study was to identify factors (models describing the bankruptcy risk in enterprises in the context of their forecasting effectiveness in a one-year and two-year time horizon. In order to assess their practical applicability the models were carefully analysed and validated. The usefulness of the models was assessed in terms of their classification properties, and the capacity to accurately identify enterprises at risk of bankruptcy and healthy companies as well as proper calibration of the models to the data from training sample sets.

Numerical Analyses of Earthquake Induced Liquefaction and Deformation Behaviour of an Upstream Tailings Dam

Directory of Open Access Journals (Sweden)

Muhammad Auchar Zardari

2017-01-01

Full Text Available Much of the seismic activity of northern Sweden consists of micro-earthquakes occurring near postglacial faults. However, larger magnitude earthquakes do occur in Sweden, and earthquake statistics indicate that a magnitude 5 event is likely to occur once every century. This paper presents dynamic analyses of the effects of larger earthquakes on an upstream tailings dam at the Aitik copper mine in northern Sweden. The analyses were performed to evaluate the potential for liquefaction and to assess stability of the dam under two specific earthquakes: a commonly occurring magnitude 3.6 event and a more extreme earthquake of magnitude 5.8. The dynamic analyses were carried out with the finite element program PLAXIS using a recently implemented constitutive model called UBCSAND. The results indicate that the magnitude 5.8 earthquake would likely induce liquefaction in a limited zone located below the ground surface near the embankment dikes. It is interpreted that stability of the dam may not be affected due to the limited extent of the liquefied zone. Both types of earthquakes are predicted to induce tolerable magnitudes of displacements. The results of the postseismic slope stability analysis, performed for a state after a seismic event, suggest that the dam is stable during both the earthquakes.

A simple technique investigating baseline heterogeneity helped to eliminate potential bias in meta-analyses.

Science.gov (United States)

Hicks, Amy; Fairhurst, Caroline; Torgerson, David J

2018-03-01

To perform a worked example of an approach that can be used to identify and remove potentially biased trials from meta-analyses via the analysis of baseline variables. True randomisation produces treatment groups that differ only by chance; therefore, a meta-analysis of a baseline measurement should produce no overall difference and zero heterogeneity. A meta-analysis from the British Medical Journal, known to contain significant heterogeneity and imbalance in baseline age, was chosen. Meta-analyses of baseline variables were performed and trials systematically removed, starting with those with the largest t-statistic, until the I 2 measure of heterogeneity became 0%, then the outcome meta-analysis repeated with only the remaining trials as a sensitivity check. We argue that heterogeneity in a meta-analysis of baseline variables should not exist, and therefore removing trials which contribute to heterogeneity from a meta-analysis will produce a more valid result. In our example none of the overall outcomes changed when studies contributing to heterogeneity were removed. We recommend routine use of this technique, using age and a second baseline variable predictive of outcome for the particular study chosen, to help eliminate potential bias in meta-analyses. Copyright © 2017 Elsevier Inc. All rights reserved.

Fukushima, one year after. First analyses of the accident and of its consequences

International Nuclear Information System (INIS)

2012-01-01

This report proposes assessments and discussions of knowledge gathered by the IRSN during the first twelve months following the Fukushima accident to understand the status of the installations, to assess the releases, and to analyse and assess the consequences of the accident on workers and the impact on the population and environment. After a description of a boiling water reactor (general description, confinement barriers, safeguard systems), and of the earthquake, the authors describe and comment the consequences for several reactors (Fukushima-Dai-ini, Onagawa, Tokai, Higashidoru and Hamaoka). Then, they more precisely describe the Fukushima-Dai-ichi accident by distinguishing different periods (first two weeks, next three weeks, after the 17 of April). They analyse and comment the environmental impact in Japan (atmospheric dispersion of radioactive releases, ground contamination, impact of radioactive fallouts, contamination of the marine environment, and predictable impact on marine and ground ecosystems). They describe the actions undertaken to protect the population and in terms of post-accidental management, comment assessments of the dosimetric and health impact (workers and population exposure). They finally discuss the long range impact

Experimental and numerical analyses of magnesium alloy hot workability

Directory of Open Access Journals (Sweden)

F. Abbassi

2016-12-01

Full Text Available Due to their hexagonal crystal structure, magnesium alloys have relatively low workability at room temperature. In this study, the hot workability behavior of cast-extruded AZ31B magnesium alloy is studied through hot compression testing, numerical modeling and microstructural analyses. Hot deformation tests are performed at temperatures of 250 °C to 400 °C under strain rates of 0.01 to 1.0 s−1. Transmission electron microscopy is used to reveal the presence of dynamic recrystallization (DRX, dynamic recovery (DRY, cracks and shear bands. To predict plastic instabilities during hot compression tests of AZ31B magnesium alloy, the authors use Johnson–Cook damage model in a 3D finite element simulation. The optimal hot workability of magnesium alloy is found at a temperature (T of 400 °C and strain rate (ε˙ of 0.01 s−1. Stability is found at a lower strain rate, and instability is found at a higher strain rate.

Seizure Prediction: Science Fiction or Soon to Become Reality?

Science.gov (United States)

Freestone, Dean R; Karoly, Philippa J; Peterson, Andre D H; Kuhlmann, Levin; Lai, Alan; Goodarzy, Farhad; Cook, Mark J

2015-11-01

This review highlights recent developments in the field of epileptic seizure prediction. We argue that seizure prediction is possible; however, most previous attempts have used data with an insufficient amount of information to solve the problem. The review discusses four methods for gaining more information above standard clinical electrophysiological recordings. We first discuss developments in obtaining long-term data that enables better characterisation of signal features and trends. Then, we discuss the usage of electrical stimulation to probe neural circuits to obtain robust information regarding excitability. Following this, we present a review of developments in high-resolution micro-electrode technologies that enable neuroimaging across spatial scales. Finally, we present recent results from data-driven model-based analyses, which enable imaging of seizure generating mechanisms from clinical electrophysiological measurements. It is foreseeable that the field of seizure prediction will shift focus to a more probabilistic forecasting approach leading to improvements in the quality of life for the millions of people who suffer uncontrolled seizures. However, a missing piece of the puzzle is devices to acquire long-term high-quality data. When this void is filled, seizure prediction will become a reality.

Machine Learning Techniques for Prediction of Early Childhood Obesity.

Science.gov (United States)

Dugan, T M; Mukhopadhyay, S; Carroll, A; Downs, S

2015-01-01

This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA. Analyses of six different machine learning methods: RandomTree, RandomForest, J48, ID3, Naïve Bayes, and Bayes trained on CHICA data show that an accurate, sensitive model can be created. Of the methods analyzed, the ID3 model trained on the CHICA dataset proved the best overall performance with accuracy of 85% and sensitivity of 89%. Additionally, the ID3 model had a positive predictive value of 84% and a negative predictive value of 88%. The structure of the tree also gives insight into the strongest predictors of future obesity in children. Many of the strongest predictors seen in the ID3 modeling of the CHICA dataset have been independently validated in the literature as correlated with obesity, thereby supporting the validity of the model. This study demonstrated that data from a production clinical decision support system can be used to build an accurate machine learning model to predict obesity in children after age two.

Development of a predictive system for SLM product quality

Science.gov (United States)

Park, H. S.; Tran, N. H.; Nguyen, D. S.

2017-08-01

Recently, layer by layer manufacturing or additive manufacturing (AM) has been used in many application fields. Selective laser melting (SLM) is the most attractive method for building layer by layer from metallic powders. However, applications of AM in general and SLM in particular to industry have some barriers due to the quality of the manufactured parts which are affected by the high residual stresses and large deformation. SLM process is characterized by high heat source and fast solidification which lead to large thermal stress. The aim of this research is to develop a system for predicting the printed part quality during SLM process by simulation in consideration of the temperature distribution on the workpiece. For carrying out the system, model for predicting the temperature distribution was established. From this model, influences of process parameters to temperature distribution were analysed. The thermal model in consideration of relationship among printing parameters with temperature distribution is used for optimizing printing process parameters. Then, these results are used for calculating residual stress and predicting the workpiece deformation. The functionality of the proposed predictive system is proven through a case study on aluminium material manufactured on a MetalSys150 - SLM machine.

Preliminary analyses on hydrogen diffusion through small break of thermo-chemical IS process hydrogen plant

International Nuclear Information System (INIS)

Somolova, Marketa; Terada, Atsuhiko; Takegami, Hiroaki; Iwatsuki, Jin

2008-12-01

Japan Atomic Energy Agency has been conducting a conceptual design study of nuclear hydrogen demonstration plant, that is, a thermal-chemical IS process hydrogen plant coupled with the High temperature Engineering Test Reactor (HTTR-IS), which will be planed to produce a large amount of hydrogen up to 1000m 3 /h. As part of the conceptual design work of the HTTR-IS system, preliminary analyses on small break of a hydrogen pipeline in the IS process hydrogen plant was carried out as a first step of the safety analyses. This report presents analytical results of hydrogen diffusion behaviors predicted with a CFD code, in which a diffusion model focused on the turbulent Schmidt number was incorporated. By modifying diffusion model, especially a constant accompanying the turbulent Schmidt number in the diffusion term, analytical results was made agreed well with the experimental results. (author)

Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression.

Science.gov (United States)

Guilloux, Jean-Philippe; Bassi, Sabrina; Ding, Ying; Walsh, Chris; Turecki, Gustavo; Tseng, George; Cyranowski, Jill M; Sibille, Etienne

2015-02-01

Major depressive disorder (MDD) in general, and anxious-depression in particular, are characterized by poor rates of remission with first-line treatments, contributing to the chronic illness burden suffered by many patients. Prospective research is needed to identify the biomarkers predicting nonremission prior to treatment initiation. We collected blood samples from a discovery cohort of 34 adult MDD patients with co-occurring anxiety and 33 matched, nondepressed controls at baseline and after 12 weeks (of citalopram plus psychotherapy treatment for the depressed cohort). Samples were processed on gene arrays and group differences in gene expression were investigated. Exploratory analyses suggest that at pretreatment baseline, nonremitting patients differ from controls with gene function and transcription factor analyses potentially related to elevated inflammation and immune activation. In a second phase, we applied an unbiased machine learning prediction model and corrected for model-selection bias. Results show that baseline gene expression predicted nonremission with 79.4% corrected accuracy with a 13-gene model. The same gene-only model predicted nonremission after 8 weeks of citalopram treatment with 76% corrected accuracy in an independent validation cohort of 63 MDD patients treated with citalopram at another institution. Together, these results demonstrate the potential, but also the limitations, of baseline peripheral blood-based gene expression to predict nonremission after citalopram treatment. These results not only support their use in future prediction tools but also suggest that increased accuracy may be obtained with the inclusion of additional predictors (eg, genetics and clinical scales).

Prediction of main factors’ values of air transportation system safety based on system dynamics

Science.gov (United States)

Spiridonov, A. Yu; Rezchikov, A. F.; Kushnikov, V. A.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikova, E. V.; Shulga, T. E.; Tverdokhlebov, V. A.; Kushnikov, O. V.; Fominykh, D. S.

2018-05-01

On the basis of the system-dynamic approach [1-8], a set of models has been developed that makes it possible to analyse and predict the values of the main safety indicators for the operation of aviation transport systems.

Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa

CSIR Research Space (South Africa)

Wessels, Konrad J

2011-02-01

Full Text Available the distribution of the recently redefined biomes be predicted based on remotely sensed, phenology and productivity metrics? Ten-day, 1 km, NDVI AVHRR were analysed for the period 1985 to 2000. Phenological metrics such as start, end and length of the growing...

[Evaluation of thermal comfort in a student population: predictive value of an integrated index (Fanger's predicted mean value].

Science.gov (United States)

Catenacci, G; Terzi, R; Marcaletti, G; Tringali, S

1989-01-01

Practical applications and predictive values of a thermal comfort index (Fanger's PRV) were verified on a sample school population (1236 subjects) by studying the relationships between thermal sensations (subjective analysis), determined by means of an individual questionnaire, and the values of thermal comfort index (objective analysis) obtained by calculating the PMV index individually in the subjects under study. In homogeneous conditions of metabolic expenditure rate and thermal impedence from clothing, significant differences were found between the two kinds of analyses. At 22 degrees C mean radiant and operative temperature, the PMV values averaged 0 and the percentage of subjects who experienced thermal comfort did not exceed 60%. The high level of subjects who were dissatisfied with their environmental thermal conditions confirms the doubts regarding the use of the PMV index as a predictive indicator of thermal comfort, especially considering that the negative answers were not homogeneous nor attributable to the small thermal fluctuations (less than 0.5 degree C) measured in the classrooms.

"Meta-analyses and P-curves support robust cycle shifts in women's mate preferences: Reply to Wood and Carden (2014) and Harris, Pashler, and Mickes (2014)": Correction to Gildersleeve, Haselton, and Fales (2014).

Science.gov (United States)

2017-11-01

Reports an error in "Meta-analyses and p -curves support robust cycle shifts in women's mate preferences: Reply to Wood and Carden (2014) and Harris, Pashler, and Mickes (2014)" by Kelly Gildersleeve, Martie G. Haselton and Melissa R. Fales ( Psychological Bulletin , 2014[Sep], Vol 140[5], 1272-1280). In the article, all p -curve analyses examining the Context Moderation Hypothesis Prediction mistakenly included the p-value from Little, Jones, Burt, & Perrett (2007) Study 2 for the simple effect of fertility on attraction to facial symmetry in a short-term relationship context ( p < .001). The analyses should have instead included the p -value for the fertility X relationship context interaction ( p = .011). In addition, the p -curve analyses examining exact two-tailed p -values for the Cycle Shift Prediction should have included an additional p -value from Provost et al. (2008) Study 1 for the main effect of fertility on attraction to gait masculinity. The reported p -value for this effect was .05, making it ineligible for inclusion in p -curves of reported p-values. However, the exact recalculated two-tailed p -value was .049, making it eligible for inclusion in p -curves of exact p -values. The corrected p -curve of exact two-tailed p -values evaluating the Cycle Shift Prediction and Context Moderation Prediction (displayed in Figure 2) now includes a total of 15 p -values ( N = 1442) is no longer significantly right skewed χ²(30) = 41.25, p = .08. The corrected p -curve of exact two-tailed p -values evaluating the Cycle Shift Prediction, Context Moderation Prediction, and Partner Qualities Moderation Prediction (displayed in Figure 3) now includes a total of 21 p -values ( N = 1707) and continues to be significantly right skewed Χ²(42) = 69.83, p = .004. As part of this correction, the online supplemental materials have been updated. (The following abstract of the original article appeared in record 2014-35938-003.) Two meta-analyses evaluated shifts across

Gray model prediction of the sea wall profile survey in the first process of Qinshan Nuclear Power Plant

International Nuclear Information System (INIS)

Zang Deyan

1998-01-01

Based on gray system theory, the information about deformation observation of the first stage Qinshan nuclear power plant is analysed and predicted as well. The gray system theory is applied to engineering prediction and a large-scale building deformation observation. It is convenient to apply the model and it a has high degree of accuracy

Using meta-analytic path analysis to test theoretical predictions in health behavior: An illustration based on meta-analyses of the theory of planned behavior

OpenAIRE

Hagger, Martin; Chan, Dervin K. C.; Protogerou, Cleo; Chatzisarantis, Nikos L. D.

2016-01-01

Objective Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs fr...

The Role of Goal Importance in Predicting University Students' High Academic Performance

Science.gov (United States)

Kyle, Vanessa A.; White, Katherine M.; Hyde, Melissa K.; Occhipinti, Stefano

2014-01-01

We examined goal importance, focusing on high, but not exclusive priority goals, in the theory of planned behaviour (TPB) to predict students' academic performance. At the beginning of semester, students in a psychology subject (N = 197) completed TPB and goal importance items for achieving a high grade. Regression analyses revealed partial…

Methodological issues in radiation dose-volume outcome analyses: Summary of a joint AAPM/NIH workshop

International Nuclear Information System (INIS)

Deasy, Joseph O.; Niemierko, Andrzej; Herbert, Donald; Yan, Di; Jackson, Andrew; Ten Haken, Randall K.; Langer, Mark; Sapareto, Steve

2002-01-01

This report represents a summary of presentations at a joint workshop of the National Institutes of Health and the American Association of Physicists in Medicine (AAPM). Current methodological issues in dose-volume modeling are addressed here from several different perspectives. Areas of emphasis include (a) basic modeling issues including the equivalent uniform dose framework and the bootstrap method, (b) issues in the valid use of statistics, including the need for meta-analysis, (c) issues in dealing with organ deformation and its effects on treatment response, (d) evidence for volume effects for rectal complications, (e) the use of volume effect data in liver and lung as a basis for dose escalation studies, and (f) implications of uncertainties in volume effect knowledge on optimized treatment planning. Taken together, these approaches to studying volume effects describe many implications for the development and use of this information in radiation oncology practice. Areas of significant interest for further research include the meta-analysis of clinical data; interinstitutional pooled data analyses of volume effects; analyses of the uncertainties in outcome prediction models, minimal parameter number outcome models for ranking treatment plans (e.g., equivalent uniform dose); incorporation of the effect of motion in the outcome prediction; dose-escalation/isorisk protocols based on outcome models; the use of functional imaging to study radio-response; and the need for further small animal tumor control probability/normal tissue complication probability studies

Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

Science.gov (United States)

Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

2014-02-01

The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

Effects prediction guidelines for structures subjected to ground motion

International Nuclear Information System (INIS)

1975-07-01

Part of the planning for an underground nuclear explosion (UNE) is determining the effects of expected ground motion on exposed structures. Because of the many types of structures and the wide variation in ground motion intensity typically encountered, no single prediction method is both adequate and feasible for a complete evaluation. Furthermore, the nature and variability of ground motion and structure damage prescribe effects predictions that are made probabilistically. Initially, prediction for a UNE involves a preliminary assessment of damage to establish overall project feasibility. Subsequent efforts require more detailed damage evaluations, based on structure inventories and analyses of specific structures, so that safety problems can be identified and safety and remedial measures can be recommended. To cover this broad range of effects prediction needs for a typical UNE project, three distinct but interrelated methods have been developed and are described. First, the fundamental practical and theoretical aspects of predicting the effects of dynamic ground motion on structures are summarized. Next, experimentally derived and theoretically determined observations of the behavior of typical structures subjected to ground motion are presented. Then, based on these fundamental considerations and on the observed behavior of structures, the formulation of the three effects prediction procedures is described, along with guidelines regarding their applicability. Example damage predictions for hypothetical UNEs demonstrate these procedures. To aid in identifying the vibration properties of complex structures, one chapter discusses alternatives in vibration testing, instrumentation, and data analysis. Finally, operational guidelines regarding data acquisition procedures, safety criteria, and remedial measures involved in conducting structure effects evaluations are discussed. (U.S.)

Micromechanical Failure Analyses for Finite Element Polymer Modeling

Energy Technology Data Exchange (ETDEWEB)

CHAMBERS,ROBERT S.; REEDY JR.,EARL DAVID; LO,CHI S.; ADOLF,DOUGLAS B.; GUESS,TOMMY R.

2000-11-01

Polymer stresses around sharp corners and in constrained geometries of encapsulated components can generate cracks leading to system failures. Often, analysts use maximum stresses as a qualitative indicator for evaluating the strength of encapsulated component designs. Although this approach has been useful for making relative comparisons screening prospective design changes, it has not been tied quantitatively to failure. Accurate failure models are needed for analyses to predict whether encapsulated components meet life cycle requirements. With Sandia's recently developed nonlinear viscoelastic polymer models, it has been possible to examine more accurately the local stress-strain distributions in zones of likely failure initiation looking for physically based failure mechanisms and continuum metrics that correlate with the cohesive failure event. This study has identified significant differences between rubbery and glassy failure mechanisms that suggest reasonable alternatives for cohesive failure criteria and metrics. Rubbery failure seems best characterized by the mechanisms of finite extensibility and appears to correlate with maximum strain predictions. Glassy failure, however, seems driven by cavitation and correlates with the maximum hydrostatic tension. Using these metrics, two three-point bending geometries were tested and analyzed under variable loading rates, different temperatures and comparable mesh resolution (i.e., accuracy) to make quantitative failure predictions. The resulting predictions and observations agreed well suggesting the need for additional research. In a separate, additional study, the asymptotically singular stress state found at the tip of a rigid, square inclusion embedded within a thin, linear elastic disk was determined for uniform cooling. The singular stress field is characterized by a single stress intensity factor K{sub a} and the applicable K{sub a} calibration relationship has been determined for both fully bonded and

Siemens experience on linear and nonlinear analyses of out-of-phase BWR instabilities

International Nuclear Information System (INIS)

Kreuter, D.; Wehle, F.

1995-01-01

The Siemens design code STAIF has been applied extensively for linear analysis of BWR instabilities. The comparison between measurements and STAIF calculations for different plants under various conditions has shown good agreement for core-wide and regional instabilities. Based on the high quality of STAIF, the North German TUeV has decided to replace the licensing requirement of extensive stability measurements by predictive analyses with the code STAIF. Nonlinear stability analysis for beyond design boundary conditions with RAMONA has shown dryout during temporarily reversed flow at core inlet in case of core-wide oscillations. For large out-of-phase oscillations, dryout occurs already for small, still positive channel inlet flow. (orig.)

Predicting genotypes environmental range from genome-environment associations.

Science.gov (United States)

Manel, Stéphanie; Andrello, Marco; Henry, Karine; Verdelet, Daphné; Darracq, Aude; Guerin, Pierre-Edouard; Desprez, Bruno; Devaux, Pierre

2018-05-17

Genome-environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single-locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random Single Nucleotide Polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity-associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress-aridity conditions and could be used to improve the resistance of cultivated varieties to aridity. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A rapid method of predicting radiocaesium concentrations in sheep from activity levels in faeces

International Nuclear Information System (INIS)

McGee, E.J.; Synnott, H.J.; Colgan, P.A.; Keatinge, M.J.

1994-01-01

The use of faecal samples taken from sheep flocks as a means of predicting radiocaesium concentrations in live animals was studied. Radiocaesium levels in 1726 sheep from 29 flocks were measured using in vivo techniques and a single faecal sample taken from each flock was also analysed. A highly significant relationship was found to exist between mean flock activity and activity in the corresponding faecal samples. Least-square regression yielded a simple model for predicting mean flock radiocaesium concentrations based on activity levels in faecal samples. A similar analysis of flock maxima and activity levels in faeces provides an alternative model for predicting the expected within-flock maximum radiocaesium concentration. (Author)

Risk Factor Analyses for the Return of Spontaneous Circulation in the Asphyxiation Cardiac Arrest Porcine Model

Directory of Open Access Journals (Sweden)

Cai-Jun Wu

2015-01-01

Full Text Available Background: Animal models of asphyxiation cardiac arrest (ACA are frequently used in basic research to mirror the clinical course of cardiac arrest (CA. The rates of the return of spontaneous circulation (ROSC in ACA animal models are lower than those from studies that have utilized ventricular fibrillation (VF animal models. The purpose of this study was to characterize the factors associated with the ROSC in the ACA porcine model. Methods: Forty-eight healthy miniature pigs underwent endotracheal tube clamping to induce CA. Once induced, CA was maintained untreated for a period of 8 min. Two minutes following the initiation of cardiopulmonary resuscitation (CPR, defibrillation was attempted until ROSC was achieved or the animal died. To assess the factors associated with ROSC in this CA model, logistic regression analyses were performed to analyze gender, the time of preparation, the amplitude spectrum area (AMSA from the beginning of CPR and the pH at the beginning of CPR. A receiver-operating characteristic (ROC curve was used to evaluate the predictive value of AMSA for ROSC. Results: ROSC was only 52.1% successful in this ACA porcine model. The multivariate logistic regression analyses revealed that ROSC significantly depended on the time of preparation, AMSA at the beginning of CPR and pH at the beginning of CPR. The area under the ROC curve in for AMSA at the beginning of CPR was 0.878 successful in predicting ROSC (95% confidence intervals: 0.773∼0.983, and the optimum cut-off value was 15.62 (specificity 95.7% and sensitivity 80.0%. Conclusions: The time of preparation, AMSA and the pH at the beginning of CPR were associated with ROSC in this ACA porcine model. AMSA also predicted the likelihood of ROSC in this ACA animal model.

Neurological abnormalities predict disability

DEFF Research Database (Denmark)

Poggesi, Anna; Gouw, Alida; van der Flier, Wiesje

2014-01-01

To investigate the role of neurological abnormalities and magnetic resonance imaging (MRI) lesions in predicting global functional decline in a cohort of initially independent-living elderly subjects. The Leukoaraiosis And DISability (LADIS) Study, involving 11 European centres, was primarily aimed...... at evaluating age-related white matter changes (ARWMC) as an independent predictor of the transition to disability (according to Instrumental Activities of Daily Living scale) or death in independent elderly subjects that were followed up for 3 years. At baseline, a standardized neurological examination.......0 years, 45 % males), 327 (51.7 %) presented at the initial visit with ≥1 neurological abnormality and 242 (38 %) reached the main study outcome. Cox regression analyses, adjusting for MRI features and other determinants of functional decline, showed that the baseline presence of any neurological...

Quasi-laminar stability and sensitivity analyses for turbulent flows: Prediction of low-frequency unsteadiness and passive control

Science.gov (United States)

Mettot, Clément; Sipp, Denis; Bézard, Hervé

2014-04-01

This article presents a quasi-laminar stability approach to identify in high-Reynolds number flows the dominant low-frequencies and to design passive control means to shift these frequencies. The approach is based on a global linear stability analysis of mean-flows, which correspond to the time-average of the unsteady flows. Contrary to the previous work by Meliga et al. ["Sensitivity of 2-D turbulent flow past a D-shaped cylinder using global stability," Phys. Fluids 24, 061701 (2012)], we use the linearized Navier-Stokes equations based solely on the molecular viscosity (leaving aside any turbulence model and any eddy viscosity) to extract the least stable direct and adjoint global modes of the flow. Then, we compute the frequency sensitivity maps of these modes, so as to predict before hand where a small control cylinder optimally shifts the frequency of the flow. In the case of the D-shaped cylinder studied by Parezanović and Cadot [J. Fluid Mech. 693, 115 (2012)], we show that the present approach well captures the frequency of the flow and recovers accurately the frequency control maps obtained experimentally. The results are close to those already obtained by Meliga et al., who used a more complex approach in which turbulence models played a central role. The present approach is simpler and may be applied to a broader range of flows since it is tractable as soon as mean-flows — which can be obtained either numerically from simulations (Direct Numerical Simulation (DNS), Large Eddy Simulation (LES), unsteady Reynolds-Averaged-Navier-Stokes (RANS), steady RANS) or from experimental measurements (Particle Image Velocimetry - PIV) — are available. We also discuss how the influence of the control cylinder on the mean-flow may be more accurately predicted by determining an eddy-viscosity from numerical simulations or experimental measurements. From a technical point of view, we finally show how an existing compressible numerical simulation code may be used in

Assessment applicability of selected models of multiple discriminant analyses to forecast financial situation of Polish wood sector enterprises

Directory of Open Access Journals (Sweden)

Adamowicz Krzysztof

2017-03-01

Full Text Available In the last three decades forecasting bankruptcy of enterprises has been an important and difficult problem, used as an impulse for many research projects (Ribeiro et al. 2012. At present many methods of bankruptcy prediction are available. In view of the specific character of economic activity in individual sectors, specialised methods adapted to a given branch of industry are being used increasingly often. For this reason an important scientific problem is related with the indication of an appropriate model or group of models to prepare forecasts for a given branch of industry. Thus research has been conducted to select an appropriate model of Multiple Discriminant Analysis (MDA, best adapted to forecasting changes in the wood industry. This study analyses 10 prediction models popular in Poland. Effectiveness of the model proposed by Jagiełło, developed for all industrial enterprises, may be labelled accidental. That model is not adapted to predict financial changes in wood sector companies in Poland.

Rainfall and Extratropical Transition of Tropical Cyclones: Simulation, Prediction, and Projection

Science.gov (United States)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET

Predictive assessment of models for dynamic functional connectivity

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Schmidt, Mikkel Nørgaard; Madsen, Kristoffer Hougaard

2018-01-01

represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state......In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature...... dynamics. To address these issues, we consider a predictive likelihood approach to model assessment, where models are evaluated based on their predictive performance on held-out test data. Examining several prominent models of dFC (in their probabilistic formulations) we demonstrate our framework...

Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs

Science.gov (United States)

Lim, Chun Shen; Brown, Chris M.

2018-01-01

Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community. PMID:29354101

Freshman year alcohol and marijuana use prospectively predict time to college graduation and subsequent adult roles and independence.

Science.gov (United States)

Wilhite, Emily R; Ashenhurst, James R; Marino, Elise N; Fromme, Kim

2017-06-15

This study examined how freshman year substance use prospectively predicted time to college graduation, and whether delayed graduation predicted postponed adoption of adult roles and future substance use. Participants were part of a longitudinal study that began in 2004. The first analyses focused on freshman year (N = 2,050). The second analyses corresponded to a subset of participants at age 27 (N = 575). Measures included self-reported substance use, adult role adoption, and university reported graduation dates. Results indicated that frequent binge drinking and marijuana use during freshman year predicted delayed college graduation. Those who took longer to graduate were more likely to have lower incomes and were less likely to obtain a graduate degree. Taking 5-6 years to graduate was associated with greater likelihood of alcohol-related problems. Findings support the importance of interventions during freshman year of college to decrease substance use and promote timely graduation.

Analysing and Comparing Encodability Criteria

Directory of Open Access Journals (Sweden)

Kirstin Peters

2015-08-01

Full Text Available Encodings or the proof of their absence are the main way to compare process calculi. To analyse the quality of encodings and to rule out trivial or meaningless encodings, they are augmented with quality criteria. There exists a bunch of different criteria and different variants of criteria in order to reason in different settings. This leads to incomparable results. Moreover it is not always clear whether the criteria used to obtain a result in a particular setting do indeed fit to this setting. We show how to formally reason about and compare encodability criteria by mapping them on requirements on a relation between source and target terms that is induced by the encoding function. In particular we analyse the common criteria full abstraction, operational correspondence, divergence reflection, success sensitiveness, and respect of barbs; e.g. we analyse the exact nature of the simulation relation (coupled simulation versus bisimulation that is induced by different variants of operational correspondence. This way we reduce the problem of analysing or comparing encodability criteria to the better understood problem of comparing relations on processes.

ATHENA/INTRA analyses for ITER, NSSR-2

International Nuclear Information System (INIS)

Shen, Kecheng; Eriksson, John; Sjoeberg, A.

1999-02-01

The present report is a summary report including thermal-hydraulic analyses made at Studsvik Eco and Safety AB for the ITER NSSR-2 safety documentation. The objective of the analyses was to reveal the safety characteristics of various heat transfer systems at specified operating conditions and to indicate the conditions for which there were obvious risks of jeopardising the structural integrity of the coolant systems. In the latter case also some analyses were made to indicate conceivable mitigating measures for maintaining the integrity.The analyses were primarily concerned with the First Wall and Divertor heat transfer systems. Several enveloping transients were analysed with associated specific flow and heat load boundary conditions. The analyses were performed with the ATHENA and INTRA codes

ATHENA/INTRA analyses for ITER, NSSR-2

Energy Technology Data Exchange (ETDEWEB)

Shen, Kecheng; Eriksson, John; Sjoeberg, A

1999-02-01

The present report is a summary report including thermal-hydraulic analyses made at Studsvik Eco and Safety AB for the ITER NSSR-2 safety documentation. The objective of the analyses was to reveal the safety characteristics of various heat transfer systems at specified operating conditions and to indicate the conditions for which there were obvious risks of jeopardising the structural integrity of the coolant systems. In the latter case also some analyses were made to indicate conceivable mitigating measures for maintaining the integrity.The analyses were primarily concerned with the First Wall and Divertor heat transfer systems. Several enveloping transients were analysed with associated specific flow and heat load boundary conditions. The analyses were performed with the ATHENA and INTRA codes 8 refs, 14 figs, 15 tabs

Is the AIMS65 score useful in predicting outcomes in peptic ulcer bleeding?

Science.gov (United States)

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.

Prediction of fish biomass, harvest and prey--predator relations in reservoirs

International Nuclear Information System (INIS)

Jenkins, R.M.

1977-01-01

Regression analyses of the effect of total dissolved solids on fish standing crops in 166 reservoirs produced formulas with coefficients of determination of 0.63 to 0.81. These formulas provide indexes to average biotic conditions and help to identify stressed aquatic environments. Simple predictive formulas are also presented for clupeid crops in various reservoir types, as clupeids are the fishes most frequently impinged or entrained at southern power plants. A method of calculating the adequacy of the available prey crop in relation to the predator crop is advanced to further aid in identification of perturbed prey populations. Assessment of stress as reflected by changes in sport fishing success can also be approached by comparison of the predicted harvest potential with actual fish harvest data. Use of these predictive indexes is recommended until more elaborate models are developed to identify power plant effects

Can Childhood Factors Predict Workplace Deviance?

Science.gov (United States)

Piquero, Nicole Leeper; Moffitt, Terrie E

2014-07-01

Compared to the more common focus on street crime, empirical research on workplace deviance has been hampered by highly select samples, cross-sectional research designs, and limited inclusion of relevant predictor variables that bear on important theoretical debates. A key debate concerns the extent to which childhood conduct-problem trajectories influence crime over the life-course, including adults' workplace crime, whether childhood low self-control is a more important determinant than trajectories, and/or whether each or both of these childhood factors relate to later criminal activity. This paper provides evidence on this debate by examining two types of workplace deviance: production and property deviance separately for males and females. We use data from the Dunedin Multidisciplinary Health and Development Study, a birth cohort followed into adulthood, to examine how childhood factors (conduct-problem trajectories and low self-control) and then adult job characteristics predict workplace deviance at age 32. Analyses revealed that none of the childhood factors matter for predicting female deviance in the workplace but that conduct-problem trajectories did account for male workplace deviance.

Bootstrap prediction and Bayesian prediction under misspecified models

OpenAIRE

Fushiki, Tadayoshi

2005-01-01

We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

Quantifying data worth toward reducing predictive uncertainty

Science.gov (United States)

Dausman, A.M.; Doherty, J.; Langevin, C.D.; Sukop, M.C.

2010-01-01

The present study demonstrates a methodology for optimization of environmental data acquisition. Based on the premise that the worth of data increases in proportion to its ability to reduce the uncertainty of key model predictions, the methodology can be used to compare the worth of different data types, gathered at different locations within study areas of arbitrary complexity. The method is applied to a hypothetical nonlinear, variable density numerical model of salt and heat transport. The relative utilities of temperature and concentration measurements at different locations within the model domain are assessed in terms of their ability to reduce the uncertainty associated with predictions of movement of the salt water interface in response to a decrease in fresh water recharge. In order to test the sensitivity of the method to nonlinear model behavior, analyses were repeated for multiple realizations of system properties. Rankings of observation worth were similar for all realizations, indicating robust performance of the methodology when employed in conjunction with a highly nonlinear model. The analysis showed that while concentration and temperature measurements can both aid in the prediction of interface movement, concentration measurements, especially when taken in proximity to the interface at locations where the interface is expected to move, are of greater worth than temperature measurements. Nevertheless, it was also demonstrated that pairs of temperature measurements, taken in strategic locations with respect to the interface, can also lead to more precise predictions of interface movement. Journal compilation ?? 2010 National Ground Water Association.

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

Science.gov (United States)

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.

Predictive Validity of the Columbia-Suicide Severity Rating Scale for Short-Term Suicidal Behavior

DEFF Research Database (Denmark)

Conway, Paul Maurice; Erlangsen, Annette; Teasdale, Thomas William

2017-01-01

adolescents (90.6% females) who participated at follow-up (85.9%) out of the 99 (49.7%) baseline respondents. All adolescents were recruited from a specialized suicide-prevention clinic in Denmark. Through multivariate logistic regression analyses, we examined whether baseline suicidal behavior predicted......Using the Columbia-Suicide Severity Rating Scale (C-SSRS), we examined the predictive and incremental predictive validity of past-month suicidal behavior and ideation for short-term suicidal behavior among adolescents at high risk of suicide. The study was conducted in 2014 on a sample of 85...... subsequent suicidal behavior (actual attempts and suicidal behavior of any type, including preparatory acts, aborted, interrupted and actual attempts; mean follow-up of 80.8 days, SD = 52.4). Furthermore, we examined whether suicidal ideation severity and intensity incrementally predicted suicidal behavior...

Optimizing the photon selection of the CMS Single-Photon search for Supersymmetry using multivariate analyses

CERN Document Server

Lange, Johannes

2014-01-01

The purpose of this thesis is to improve the photon selection of the CMS SinglePhoton search for Supersymmetry by using multivariate analyses.The Single-Photon search aims to find Supersymmetry (SUSY) in data taken by theCompact Muon Solenoid (CMS) detector at the Large Hadron Collider located atthe research center CERN. SUSY is an extension of the standard model of particlephysics. The search is designed for a general gauge mediation scenario, which describes the gauge mediated SUSY breaking. The analysis uses final states with jets,at least one photon and missing transverse energy. A data-driven prediction of themultijet background is performed for the analysis. For this purpose, photon candidates have to be classified into two selections.In this thesis the usage of multivariate analyses for the photon candidate classification is studied. The methods used are Fisher Discriminant, Boosted Decision Treesand Artificial Neural Networks. Their performance is evaluated with respect to different aspects impor...

Biomass feedstock analyses

Energy Technology Data Exchange (ETDEWEB)

Wilen, C.; Moilanen, A.; Kurkela, E. [VTT Energy, Espoo (Finland). Energy Production Technologies

1996-12-31

The overall objectives of the project `Feasibility of electricity production from biomass by pressurized gasification systems` within the EC Research Programme JOULE II were to evaluate the potential of advanced power production systems based on biomass gasification and to study the technical and economic feasibility of these new processes with different type of biomass feed stocks. This report was prepared as part of this R and D project. The objectives of this task were to perform fuel analyses of potential woody and herbaceous biomasses with specific regard to the gasification properties of the selected feed stocks. The analyses of 15 Scandinavian and European biomass feed stock included density, proximate and ultimate analyses, trace compounds, ash composition and fusion behaviour in oxidizing and reducing atmospheres. The wood-derived fuels, such as whole-tree chips, forest residues, bark and to some extent willow, can be expected to have good gasification properties. Difficulties caused by ash fusion and sintering in straw combustion and gasification are generally known. The ash and alkali metal contents of the European biomasses harvested in Italy resembled those of the Nordic straws, and it is expected that they behave to a great extent as straw in gasification. Any direct relation between the ash fusion behavior (determined according to the standard method) and, for instance, the alkali metal content was not found in the laboratory determinations. A more profound characterisation of the fuels would require gasification experiments in a thermobalance and a PDU (Process development Unit) rig. (orig.) (10 refs.)

Predicting precompetitive state anxiety: using the 2 x 2 achievement goal framework.

Science.gov (United States)

Li, Chiung-Huang

2013-10-01

The goal was to examine the predictiveness of achievement goals for self-confidence, cognitive anxiety, and somatic anxiety using a prospective design. 160 high school athletes completed the 2 x 2 Achievement Goals Questionnaire for Sport after daily practice and the Revised Competitive State Anxiety Inventory-2 before an official competition. Using hierarchical regression analyses, mastery-approach goals were found as positive predictors of self-confidence and negative predictors of cognitive and somatic anxiety. In contrast, performance- and mastery-avoidance goals positively predicted cognitive and somatic anxiety. Also, performance-avoidance goals negatively predicted self-confidence. Generally, athletes who pursued task mastery and improvement of competence were less physically and cognitively anxious and more self-confident. However, athletes felt tense, worried, and had lower confidence when they endorsed avoidance forms of achievement goals.

Testing Predictive Models of Technology Integration in Mexico and the United States

Science.gov (United States)

Velazquez, Cesareo Morales

2008-01-01

Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…

Prediction of permeability changes in an excavation response zone

International Nuclear Information System (INIS)

Kinoshita, Naoto; Ishii, Takashi; Kuroda, Hidetaka; Tada, Hiroyuki

1992-01-01

In geologic disposal of radioactive wastes, stress changes due to cavern excavation may expand the existing fractures and create possible bypasses for groundwater. This paper proposes a simple method for predicting permeability changes in the excavation response zones. Numerical analyses using this method predict that the response zones created by cavern excavation would differ greatly in thickness and permeability depending on the depth of the cavern site and the initial in-situ stress, that when the cavern site is deeper, response zones would expand more and permeability would increases more, and that if the ratio of horizontal to vertical in-situ stress is small, extensive permeable zones at the crown and the bottom would occur, whereas if the ratio is large, extensive permeable zones would occur in the side walls. (orig.)

Polygenic risk predicts obesity in both white and black young adults.

Directory of Open Access Journals (Sweden)

Benjamin W Domingue

Full Text Available To test transethnic replication of a genetic risk score for obesity in white and black young adults using a national sample with longitudinal data.A prospective longitudinal study using the National Longitudinal Study of Adolescent Health Sibling Pairs (n = 1,303. Obesity phenotypes were measured from anthropometric assessments when study members were aged 18-26 and again when they were 24-32. Genetic risk scores were computed based on published genome-wide association study discoveries for obesity. Analyses tested genetic associations with body-mass index (BMI, waist-height ratio, obesity, and change in BMI over time.White and black young adults with higher genetic risk scores had higher BMI and waist-height ratio and were more likely to be obese compared to lower genetic risk age-peers. Sibling analyses revealed that the genetic risk score was predictive of BMI net of risk factors shared by siblings. In white young adults only, higher genetic risk predicted increased risk of becoming obese during the study period. In black young adults, genetic risk scores constructed using loci identified in European and African American samples had similar predictive power.Cumulative information across the human genome can be used to characterize individual level risk for obesity. Measured genetic risk accounts for only a small amount of total variation in BMI among white and black young adults. Future research is needed to identify modifiable environmental exposures that amplify or mitigate genetic risk for elevated BMI.

Polygenic risk predicts obesity in both white and black young adults.

Science.gov (United States)

Domingue, Benjamin W; Belsky, Daniel W; Harris, Kathleen Mullan; Smolen, Andrew; McQueen, Matthew B; Boardman, Jason D

2014-01-01

To test transethnic replication of a genetic risk score for obesity in white and black young adults using a national sample with longitudinal data. A prospective longitudinal study using the National Longitudinal Study of Adolescent Health Sibling Pairs (n = 1,303). Obesity phenotypes were measured from anthropometric assessments when study members were aged 18-26 and again when they were 24-32. Genetic risk scores were computed based on published genome-wide association study discoveries for obesity. Analyses tested genetic associations with body-mass index (BMI), waist-height ratio, obesity, and change in BMI over time. White and black young adults with higher genetic risk scores had higher BMI and waist-height ratio and were more likely to be obese compared to lower genetic risk age-peers. Sibling analyses revealed that the genetic risk score was predictive of BMI net of risk factors shared by siblings. In white young adults only, higher genetic risk predicted increased risk of becoming obese during the study period. In black young adults, genetic risk scores constructed using loci identified in European and African American samples had similar predictive power. Cumulative information across the human genome can be used to characterize individual level risk for obesity. Measured genetic risk accounts for only a small amount of total variation in BMI among white and black young adults. Future research is needed to identify modifiable environmental exposures that amplify or mitigate genetic risk for elevated BMI.

Predicting story goodness performance from cognitive measures following traumatic brain injury.

Science.gov (United States)

Lê, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

2012-05-01

This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Lê, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. One hundred sixty-seven individuals with TBI participated in the study. Story retellings were analyzed using the SGI protocol. Three cognitive measures--Delis-Kaplan Executive Function System (D-KEFS; Delis, Kaplan, & Kramer, 2001) Sorting Test, Wechsler Memory Scale--Third Edition (WMS-III; Wechsler, 1997) Working Memory Primary Index (WMI), and WMS-III Immediate Memory Primary Index (IMI)--were entered into a multiple linear regression model for each discourse measure. Two sets of regression analyses were performed, the first with the Sorting Test as the first predictor and the second with it as the last. The first set of regression analyses identified the Sorting Test and IMI as the only significant predictors of performance on measures of the SGI. The second set identified all measures as significant predictors when evaluating each step of the regression function. The cognitive variables predicted performance on the SGI measures, although there were differences in the amount of explained variance. The results (a) suggest that storytelling ability draws on a number of underlying skills and (b) underscore the importance of using discrete cognitive tasks rather than broad cognitive indices to investigate the cognitive substrates of discourse.

Fukushima Daiichi Unit 1 Ex-Vessel Prediction: Core Concrete Interaction

International Nuclear Information System (INIS)

Robb, Kevin R; Farmer, Mitchell; Francis, Matthew W

2015-01-01

Lower head failure and corium concrete interaction were predicted to occur at Fukushima Daiichi Unit 1 (1F1) by several different system-level code analyses, including MELCOR v2.1 and MAAP5. Although these codes capture a wide range of accident phenomena, they do not contain detailed models for ex-vessel core melt behavior. However, specialized codes exist for analysis of ex-vessel melt spreading (e.g., MELTSPREAD) and long-term debris coolability (e.g., CORQUENCH). On this basis, an analysis was carried out to further evaluate ex-vessel behavior for 1F1 using MELTSPREAD and CORQUENCH. Best-estimate melt pour conditions predicted by MELCOR v2.1 and MAAP5 were used as input. MELTSPREAD was then used to predict the spatially dependent melt conditions and extent of spreading during relocation from the vessel. The results of the MELTSPREAD analysis are reported in a companion paper. This information was used as input for the long-term debris coolability analysis with CORQUENCH.

Risico-analyse brandstofpontons

NARCIS (Netherlands)

Uijt de Haag P; Post J; LSO

2001-01-01

Voor het bepalen van de risico's van brandstofpontons in een jachthaven is een generieke risico-analyse uitgevoerd. Er is een referentiesysteem gedefinieerd, bestaande uit een betonnen brandstofponton met een relatief grote inhoud en doorzet. Aangenomen is dat de ponton gelegen is in een

Guidelineness of the parameters using integrated test in down syndrome risk prediction

International Nuclear Information System (INIS)

Lee, Jin Won; Go, Sung Jin; Kang, Se Sik; Kim, Chang Soo

2016-01-01

This study was an evaluation of the significance of each parameter through aimed at pregnant women subjected to screening test(integrated test) in predicting risk of Down syndrome. We retrospectively analysed the correlation of risk of Down's syndrome with Nuchal Translucency(NT) images measured by ultrasound, Pregnancy Associated Plasma Protein A(PAPP-A), alpha-fetoprotein(AFP), unconjugated estriol(uE3), human chorionic gonadotrophin(hCG) and Inhibin A by maternal serum. As a result, a significant correlation with NT, uE3, hCG, Inhibin A is revealed with Down's syndrome risk(P<.001). In ROC analysis, AUC of Inhibin A is analysed as the biggest predictor of Down's syndrome(0.859). And the criterion for cut-off was inhibin A 1.4 MoM(sensitivity 81.8%, specificity 75.9%). In conclusion, Inhibin A was the most useful in parameters to predict Down's syndrome in the integrated test. If we make up for the weakness based on the cut-off value of parameters they will be able to be used as an independent indicator in the risk of Down's syndrome screening

Discrimination ability of comorbidity, frailty, and subjective health to predict mortality in community-dwelling older people

DEFF Research Database (Denmark)

Kusumastuti, Sasmita; Gerds, Thomas Alexander; Lund, Rikke

2017-01-01

OBJECTIVE: To investigate the added value of comorbidity, frailty, and subjective health to mortality predictions in community-dwelling older people and whether it changes with increasing age. PARTICIPANTS: 36,751 community-dwelling subjects aged 50-100 from the longitudinal Survey of Health......, Ageing, and Retirement in Europe. METHODS: Mortality risk associated with Comorbidity Index, Frailty Index, Frailty Phenotype, and subjective health was analysed using Cox regression. The extent to which health indicators modified individual mortality risk predictions was examined and the added ability......, and household income. CONCLUSION: Calendar age encompasses most of the discrimination ability to predict mortality. The added value of comorbidity, frailty, and subjective health to mortality predictions decreases with increasing age....

Evaluation of burst pressure prediction models for line pipes

Energy Technology Data Exchange (ETDEWEB)

Zhu, Xian-Kui, E-mail: zhux@battelle.org [Battelle Memorial Institute, 505 King Avenue, Columbus, OH 43201 (United States); Leis, Brian N. [Battelle Memorial Institute, 505 King Avenue, Columbus, OH 43201 (United States)

2012-01-15

Accurate prediction of burst pressure plays a central role in engineering design and integrity assessment of oil and gas pipelines. Theoretical and empirical solutions for such prediction are evaluated in this paper relative to a burst pressure database comprising more than 100 tests covering a variety of pipeline steel grades and pipe sizes. Solutions considered include three based on plasticity theory for the end-capped, thin-walled, defect-free line pipe subjected to internal pressure in terms of the Tresca, von Mises, and ZL (or Zhu-Leis) criteria, one based on a cylindrical instability stress (CIS) concept, and a large group of analytical and empirical models previously evaluated by Law and Bowie (International Journal of Pressure Vessels and Piping, 84, 2007: 487-492). It is found that these models can be categorized into either a Tresca-family or a von Mises-family of solutions, except for those due to Margetson and Zhu-Leis models. The viability of predictions is measured via statistical analyses in terms of a mean error and its standard deviation. Consistent with an independent parallel evaluation using another large database, the Zhu-Leis solution is found best for predicting burst pressure, including consideration of strain hardening effects, while the Tresca strength solutions including Barlow, Maximum shear stress, Turner, and the ASME boiler code provide reasonably good predictions for the class of line-pipe steels with intermediate strain hardening response. - Highlights: Black-Right-Pointing-Pointer This paper evaluates different burst pressure prediction models for line pipes. Black-Right-Pointing-Pointer The existing models are categorized into two major groups of Tresca and von Mises solutions. Black-Right-Pointing-Pointer Prediction quality of each model is assessed statistically using a large full-scale burst test database. Black-Right-Pointing-Pointer The Zhu-Leis solution is identified as the best predictive model.

Evaluation of burst pressure prediction models for line pipes

International Nuclear Information System (INIS)

Zhu, Xian-Kui; Leis, Brian N.

2012-01-01

Accurate prediction of burst pressure plays a central role in engineering design and integrity assessment of oil and gas pipelines. Theoretical and empirical solutions for such prediction are evaluated in this paper relative to a burst pressure database comprising more than 100 tests covering a variety of pipeline steel grades and pipe sizes. Solutions considered include three based on plasticity theory for the end-capped, thin-walled, defect-free line pipe subjected to internal pressure in terms of the Tresca, von Mises, and ZL (or Zhu-Leis) criteria, one based on a cylindrical instability stress (CIS) concept, and a large group of analytical and empirical models previously evaluated by Law and Bowie (International Journal of Pressure Vessels and Piping, 84, 2007: 487–492). It is found that these models can be categorized into either a Tresca-family or a von Mises-family of solutions, except for those due to Margetson and Zhu-Leis models. The viability of predictions is measured via statistical analyses in terms of a mean error and its standard deviation. Consistent with an independent parallel evaluation using another large database, the Zhu-Leis solution is found best for predicting burst pressure, including consideration of strain hardening effects, while the Tresca strength solutions including Barlow, Maximum shear stress, Turner, and the ASME boiler code provide reasonably good predictions for the class of line-pipe steels with intermediate strain hardening response. - Highlights: ► This paper evaluates different burst pressure prediction models for line pipes. ► The existing models are categorized into two major groups of Tresca and von Mises solutions. ► Prediction quality of each model is assessed statistically using a large full-scale burst test database. ► The Zhu-Leis solution is identified as the best predictive model.

Recent and Past Musical Activity Predicts Cognitive Aging Variability: Direct Comparison with Leisure Activities

Directory of Open Access Journals (Sweden)

Brenda eHanna-Pladdy

2012-07-01

Full Text Available Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years on preserved cognitive functioning in advanced age . These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to nonmusical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study examined the type of leisure activity (musical versus other as well as the timing of engagement (age of acquisition, past versus recent in predictive models of successful cognitive aging. Seventy age and education matched older musicians (> 10 years and nonmusicians (ages 59-80 were evaluated on neuropsychological tests and life-style activities (AAP. Partition analyses were conducted on significant cognitive measures to explain performance variance in musicians. Musicians scored higher on tests of phonemic fluency, verbal immediate recall, judgment of line orientation (JLO, and Letter Number Sequencing (LNS, but not the AAP. The first partition analysis revealed education best predicted JLO in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (< 9 years predicted enhanced LNS in musicians, while analyses for AAP, verbal recall and fluency were not predictive. Recent and past musical activity, but not leisure activity, predicted variability across verbal and visuospatial domains in aging. Early musical acquisition predicted auditory

BWR spent fuel storage cask performance test. Volume 2. Pre- and post-test decay heat, heat transfer, and shielding analyses

International Nuclear Information System (INIS)

Wiles, L.E.; Lombardo, N.J.; Heeb, C.M.; Jenquin, U.P.; Michener, T.E.; Wheeler, C.L.; Creer, J.M.; McCann, R.A.

1986-06-01

This report describes the decay heat, heat transfer, and shielding analyses conducted in support of performance testing of a Ridhihalgh, Eggers and Associates REA 2033 boiling water reactor (BWR) spent fuel storage cask. The cask testing program was conducted for the US Department of Energy (DOE) Commercial Spent Fuel Management Program by the Pacific Northwest Laboratory (PNL) and by General Electric at the latters' Morris Operation (GE-MO) as reported in Volume I. The analyses effort consisted of performing pretest calculations to (1) select spent fuel for the test; (2) symmetrically load the spent fuel assemblies in the cask to ensure lateral symmetry of decay heat generation rates; (3) optimally locate temperature and dose rate instrumentation in the cask and spent fuel assemblies; and (4) evaluate the ORIGEN2 (decay heat), HYDRA and COBRA-SFS (heat transfer), and QAD and DOT (shielding) computer codes. The emphasis of this second volume is on the comparison of code predictions to experimental test data in support of the code evaluation process. Code evaluations were accomplished by comparing pretest (actually pre-look, since some predictions were not completed until testing was in progress) predictions with experimental cask testing data reported in Volume I. No attempt was made in this study to compare the two heat transfer codes because results of other evaluations have not been completed, and a comparison based on one data set may lead to erroneous conclusions

Grey literature in meta-analyses.

Science.gov (United States)

Conn, Vicki S; Valentine, Jeffrey C; Cooper, Harris M; Rantz, Marilyn J

2003-01-01

In meta-analysis, researchers combine the results of individual studies to arrive at cumulative conclusions. Meta-analysts sometimes include "grey literature" in their evidential base, which includes unpublished studies and studies published outside widely available journals. Because grey literature is a source of data that might not employ peer review, critics have questioned the validity of its data and the results of meta-analyses that include it. To examine evidence regarding whether grey literature should be included in meta-analyses and strategies to manage grey literature in quantitative synthesis. This article reviews evidence on whether the results of studies published in peer-reviewed journals are representative of results from broader samplings of research on a topic as a rationale for inclusion of grey literature. Strategies to enhance access to grey literature are addressed. The most consistent and robust difference between published and grey literature is that published research is more likely to contain results that are statistically significant. Effect size estimates of published research are about one-third larger than those of unpublished studies. Unfunded and small sample studies are less likely to be published. Yet, importantly, methodological rigor does not differ between published and grey literature. Meta-analyses that exclude grey literature likely (a) over-represent studies with statistically significant findings, (b) inflate effect size estimates, and (c) provide less precise effect size estimates than meta-analyses including grey literature. Meta-analyses should include grey literature to fully reflect the existing evidential base and should assess the impact of methodological variations through moderator analysis.

Prediction of Starch, Soluble Sugars and Amino Acids in Potatoes (Solanum tuberosum L.) Using Hyperspectral Imaging, Dielectric and LF-NMR Methodologies

DEFF Research Database (Denmark)

Kjær, Anders; Nielsen, Glenn; Stærke, Søren

2016-01-01

Handling and processing of potatoes is performed in increasingly large and more automated facilities, and the industry calls for more automated machinery for quality assessment and sorting by concentration of starch, soluble sugars, protein, amino acids etc. of the potato tubers. The present study...... cultivars were simultaneously sampled for analyses of content and scanned by the five different scanning methods. The resulting multivariate dataset was used to estimate the prediction ability of the individual scanning methods on starch-related parameters, selected simple sugars, selected amino acids......, conductivity of pressed cell sap and cell sizes. Results showed that most types of spectral analyses had relatively high potential for predicting the starch-related parameters and medium potential for predicting the concentration of the reducing sugars fructose and glucose. Most methods showed medium potential...

Refinement and evaluation of crack-opening-area analyses for circumferential through-wall cracks in pipes

International Nuclear Information System (INIS)

Rahman, S.; Brust, F.; Ghadiali, N.; Krishnaswamy, P.; Wilkowski, G.; Choi, Y.H.; Moberg, F.; Brickstad, B.

1995-04-01

Leak-before-break (LBB) analyses for circumferentially cracked pipes are currently being conducted in the nuclear industry to justify elimination of pipe whip restraints and jet impingement shields which are present because of the expected dynamic effects from pipe rupture. The application of the LBB methodology frequently requires calculation of leak rates. These leak rates depend on the crack-opening area of a through-wall crack in the pipe. In addition to LBB analyses, which assume a hypothetical flaw size, there is also interest in the integrity of actual leaking cracks corresponding to current leakage detection requirements in NRC Regulatory Guide 1.45, or for assessing temporary repair of Class 2 and 3 pipes that have leaks as are being evaluated in ASME Section 11. This study was requested by the NRC to review, evaluate, and refine current analytical models for crack-opening-area analyses of pipes with circumferential through-wall cracks. Twenty-five pipe experiments were analyzed to determine the accuracy of the predictive models. Several practical aspects of crack-opening such as; crack-face pressure, off-center cracks, restraint of pressure-induced bending, cracks in thickness transition regions, weld residual stresses, crack-morphology models, and thermal-hydraulic analysis, were also investigated. 140 refs., 105 figs., 41 tabs

Cost-Benefit Analyses of Transportation Investments

DEFF Research Database (Denmark)

Næss, Petter

2006-01-01

This paper discusses the practice of cost-benefit analyses of transportation infrastructure investment projects from the meta-theoretical perspective of critical realism. Such analyses are based on a number of untenable ontological assumptions about social value, human nature and the natural......-to-pay investigations. Accepting the ontological and epistemological assumptions of cost-benefit analysis involves an implicit acceptance of the ethical and political values favoured by these assumptions. Cost-benefit analyses of transportation investment projects tend to neglect long-term environmental consequences...

Prediction of Outcome in Acute Lower Gastrointestinal Bleeding Using Gradient Boosting.

Directory of Open Access Journals (Sweden)

Lakshmana Ayaru

Full Text Available There are no widely used models in clinical care to predict outcome in acute lower gastro-intestinal bleeding (ALGIB. If available these could help triage patients at presentation to appropriate levels of care/intervention and improve medical resource utilisation. We aimed to apply a state-of-the-art machine learning classifier, gradient boosting (GB, to predict outcome in ALGIB using non-endoscopic measurements as predictors.Non-endoscopic variables from patients with ALGIB attending the emergency departments of two teaching hospitals were analysed retrospectively for training/internal validation (n=170 and external validation (n=130 of the GB model. The performance of the GB algorithm in predicting recurrent bleeding, clinical intervention and severe bleeding was compared to a multiple logic regression (MLR model and two published MLR-based prediction algorithms (BLEED and Strate prediction rule.The GB algorithm had the best negative predictive values for the chosen outcomes (>88%. On internal validation the accuracy of the GB algorithm for predicting recurrent bleeding, therapeutic intervention and severe bleeding were (88%, 88% and 78% respectively and superior to the BLEED classification (64%, 68% and 63%, Strate prediction rule (78%, 78%, 67% and conventional MLR (74%, 74% 62%. On external validation the accuracy was similar to conventional MLR for recurrent bleeding (88% vs. 83% and therapeutic intervention (91% vs. 87% but superior for severe bleeding (83% vs. 71%.The gradient boosting algorithm accurately predicts outcome in patients with acute lower gastrointestinal bleeding and outperforms multiple logistic regression based models. These may be useful for risk stratification of patients on presentation to the emergency department.

Automatic incrementalization of Prolog based static analyses

DEFF Research Database (Denmark)

Eichberg, Michael; Kahl, Matthias; Saha, Diptikalyan

2007-01-01

Modem development environments integrate various static analyses into the build process. Analyses that analyze the whole project whenever the project changes are impractical in this context. We present an approach to automatic incrementalization of analyses that are specified as tabled logic prog...

Do needs for security and certainty predict cultural and economic conservatism? A cross-national analysis

NARCIS (Netherlands)

Malka, A.; Soto, C.J.; Inzlicht, M.; Lelkes, Y.

2014-01-01

We examine whether individual differences in needs for security and certainty predict conservative (vs. liberal) position on both cultural and economic political issues and whether these effects are conditional on nation-level characteristics and individual-level political engagement. Analyses with

Sample preparation in foodomic analyses.

Science.gov (United States)

Martinović, Tamara; Šrajer Gajdošik, Martina; Josić, Djuro

2018-04-16

Representative sampling and adequate sample preparation are key factors for successful performance of further steps in foodomic analyses, as well as for correct data interpretation. Incorrect sampling and improper sample preparation can be sources of severe bias in foodomic analyses. It is well known that both wrong sampling and sample treatment cannot be corrected anymore. These, in the past frequently neglected facts, are now taken into consideration, and the progress in sampling and sample preparation in foodomics is reviewed here. We report the use of highly sophisticated instruments for both high-performance and high-throughput analyses, as well as miniaturization and the use of laboratory robotics in metabolomics, proteomics, peptidomics and genomics. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Comparative analyses of genetic risk prediction methods reveal ...

Indian Academy of Sciences (India)

2015-03-12

Mar 12, 2015 ... 1National Institute of Biomedical Genomics, Netaji Subhas Sanatorium (T. B. ... 2Institute of Post Graduate Medical Education and Research, J. C. Bose Road, ...... Torres D. M. and Harrison S. A 2008 Diagnosis and therapy of.

Comparative analyses of genetic risk prediction methods reveal ...

Indian Academy of Sciences (India)

0.85. 0.8. 0.95. 0.93. 0.81 rs1227756. 0.5. 0.56. 0.75. 0.55. 0.7. 0.71. 0.58. 0.81. 0.25. 0.5. 0.53. 0.48. 0.64. 0.58. 0.58. 0.8. 0.68. 0.78. 0.48. 0.65. NA. NA. NA. NA rs1501299. 0.64. 0.78. 0.75. 0.83. 0.83. 0.89. 0.83. 0.72. 0.63. 0.73. 0.78. 0.75. 0.84. 0.79. 0.61. 0.78. 0.78. 0.7. 0.73. 0.73. NA. NA. NA. NA rs16944. 0.64. 0.72. 0.68.

Safety culture and learning from incidents: the role of incident reporting and causal analyses

International Nuclear Information System (INIS)

Wilpert, B.

1994-01-01

Nuclear industry more than any other industrial branch has developed and used predictive risk analysis as a method of feedforward control of safety and reliability. Systematic evaluation of operating experience, statistical documentation of component failures, systematic documentation and analysis of incidents are important complementary elements of feedback control: we are dealing here with adjustment and learning from experience, in particular from past incidents. Using preliminary findings from ongoing research at the Research Center Systems Safety at the Berlin University of Technology the contribution discusses preconditions for an effective use of lessons to be learnt from closely matched incident reporting and in depth analyses of causal chains leading to incidents. Such conditions are especially standardized documentation, reporting and analyzing methods of incidents; structured information flows and feedback loops; abstaining from culpability search; mutual trust of employees and management; willingness of all concerned to continually evaluate and optimize the established learning system. Thus, incident related reporting and causal analyses contribute to safety culture, which is seen to emerge from tightly coupled organizational measures and respective change in attitudes and behaviour. (author) 2 figs., 7 refs

Fatigue-creep life prediction for a notched specimen of 2[1]/[4]Cr-1Mo steel at 600 C

International Nuclear Information System (INIS)

Inoue, Tatsuo; Sakane, Masao; Fukuda, Yoshio; Igari, Toshihide; Miyahara, Mitsuo; Okazaki, Masakazu

1994-01-01

This paper presents the life prediction of 2[1]/[4]Cr-1Mo notched specimens subjected to fast-fast, slow-slow and hold-time loadings at 600 C. The crack initiation lives of notched specimens were estimated based on the local stress-strain calculated by inelastic finite element analyses. For the life prediction, combinations of seven different constitutive models and five fatigue-creep damage laws were used. The applicability of the constitutive model and damage law is discussed. The constitutive models predict similar stress-strain relations at the notch root, leading to similar predicted lives. The damage model, however, has a much larger influence on the life prediction. ((orig.))

Machine learning applied to the prediction of citrus production

International Nuclear Information System (INIS)

Díaz, I.; Mazza, S.M.; Combarro, E.F.; Giménez, L.I.; Gaiad, J.E.

2017-01-01

An in-depth knowledge about variables affecting production is required in order to predict global production and take decisions in agriculture. Machine learning is a technique used in agricultural planning and precision agriculture. This work (i) studies the effectiveness of machine learning techniques for predicting orchards production; and (ii) variables affecting this production were also identified. Data from 964 orchards of lemon, mandarin, and orange in Corrientes, Argentina are analysed. Graphic and analytical descriptive statistics, correlation coefficients, principal component analysis and Biplot were performed. Production was predicted via M5-Prime, a model regression tree constructor which produces a classification based on piecewise linear functions. For all the species studied, the most informative variable was the trees' age; in mandarin and orange orchards, age was followed by between and within row distances; irrigation also affected mandarin production. Also, the performance of M5-Prime in the prediction of production is adequate, as shown when measured with correlation coefficients (~0.8) and relative mean absolute error (~0.1). These results show that M5-Prime is an appropriate method to classify citrus orchards according to production and, in addition, it allows for identifying the most informative variables affecting production by tree.

Machine learning applied to the prediction of citrus production

Directory of Open Access Journals (Sweden)

Irene Díaz

2017-07-01

Full Text Available An in-depth knowledge about variables affecting production is required in order to predict global production and take decisions in agriculture. Machine learning is a technique used in agricultural planning and precision agriculture. This work (i studies the effectiveness of machine learning techniques for predicting orchards production; and (ii variables affecting this production were also identified. Data from 964 orchards of lemon, mandarin, and orange in Corrientes, Argentina are analysed. Graphic and analytical descriptive statistics, correlation coefficients, principal component analysis and Biplot were performed. Production was predicted via M5-Prime, a model regression tree constructor which produces a classification based on piecewise linear functions. For all the species studied, the most informative variable was the trees’ age; in mandarin and orange orchards, age was followed by between and within row distances; irrigation also affected mandarin production. Also, the performance of M5-Prime in the prediction of production is adequate, as shown when measured with correlation coefficients (~0.8 and relative mean absolute error (~0.1. These results show that M5-Prime is an appropriate method to classify citrus orchards according to production and, in addition, it allows for identifying the most informative variables affecting production by tree.

Machine learning applied to the prediction of citrus production

Energy Technology Data Exchange (ETDEWEB)

Díaz, I.; Mazza, S.M.; Combarro, E.F.; Giménez, L.I.; Gaiad, J.E.

2017-07-01

An in-depth knowledge about variables affecting production is required in order to predict global production and take decisions in agriculture. Machine learning is a technique used in agricultural planning and precision agriculture. This work (i) studies the effectiveness of machine learning techniques for predicting orchards production; and (ii) variables affecting this production were also identified. Data from 964 orchards of lemon, mandarin, and orange in Corrientes, Argentina are analysed. Graphic and analytical descriptive statistics, correlation coefficients, principal component analysis and Biplot were performed. Production was predicted via M5-Prime, a model regression tree constructor which produces a classification based on piecewise linear functions. For all the species studied, the most informative variable was the trees' age; in mandarin and orange orchards, age was followed by between and within row distances; irrigation also affected mandarin production. Also, the performance of M5-Prime in the prediction of production is adequate, as shown when measured with correlation coefficients (~0.8) and relative mean absolute error (~0.1). These results show that M5-Prime is an appropriate method to classify citrus orchards according to production and, in addition, it allows for identifying the most informative variables affecting production by tree.

Non-linear finite element analyses of wide plate fracture mechanics experiments

International Nuclear Information System (INIS)

Harrop, L.P.; Gibson, S.

1988-06-01

A series of centre-cracked, wide plate fracture mechanics tests is being conducted with plates made from 0.36% carbon steel. This report gives an account of post-test finite element analyses performed to compare with the results of one of these tests (designated CSTP4) and a pre-test analysis of the next test which has a slightly different geometry (CSTP5). The plates are relatively thick (75mm) and have a width of 1.62m. The finite element analyses use a two-dimensional plane stress mesh. The work shows good agreement between the post-test analysis results and the overall experimental results for CSTP4. It is not expected that the analysis results will be accurate within the dimensions of the process zone ahead of the crack tip; the mesh is not sufficient for this. A vital ingredient in attaining the good overall agreement is the representation of the actual stress-strain curve of the material. The predicted response of test CSTP5 is markedly different from that of CSTP4 even though the only change is the increase in the height of the plate. In particular the shape and size of the plastic zone ahead of the crack tip is quite different in the two tests at the same nominal remote applied load. (author)

Comparative brain transcriptomic analyses of scouting across distinct behavioural and ecological contexts in honeybees

Science.gov (United States)

Liang, Zhengzheng S.; Mattila, Heather R.; Rodriguez-Zas, Sandra L.; Southey, Bruce R.; Seeley, Thomas D.; Robinson, Gene E.

2014-01-01

Individual differences in behaviour are often consistent across time and contexts, but it is not clear whether such consistency is reflected at the molecular level. We explored this issue by studying scouting in honeybees in two different behavioural and ecological contexts: finding new sources of floral food resources and finding a new nest site. Brain gene expression profiles in food-source and nest-site scouts showed a significant overlap, despite large expression differences associated with the two different contexts. Class prediction and ‘leave-one-out’ cross-validation analyses revealed that a bee's role as a scout in either context could be predicted with 92.5% success using 89 genes at minimum. We also found that genes related to four neurotransmitter systems were part of a shared brain molecular signature in both types of scouts, and the two types of scouts were more similar for genes related to glutamate and GABA than catecholamine or acetylcholine signalling. These results indicate that consistent behavioural tendencies across different ecological contexts involve a mixture of similarities and differences in brain gene expression. PMID:25355476

Comparative Analysis of Upper Ocean Heat Content Variability from Ensemble Operational Ocean Analyses

Science.gov (United States)

Xue, Yan; Balmaseda, Magdalena A.; Boyer, Tim; Ferry, Nicolas; Good, Simon; Ishikawa, Ichiro; Rienecker, Michele; Rosati, Tony; Yin, Yonghong; Kumar, Arun

2012-01-01

Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have

Taxometric analyses and predictive accuracy of callous-unemotional traits regarding quality of life and behavior problems in non-conduct disorder diagnoses

NARCIS (Netherlands)

Herpers, P.C.M.; Klip, H.; Rommelse, N.N.J.; Taylor, M.J.; Greven, C.U.; Buitelaar, J.K.

2017-01-01

Callous-unemotional (CU) traits have mainly been studied in relation to conduct disorder (CD), but can also occur in other disorder groups. However, it is unclear whether there is a clinically relevant cut-off value of levels of CU traits in predicting reduced quality of life (QoL) and clinical

Hebbian learning and predictive mirror neurons for actions, sensations and emotions.

Science.gov (United States)

Keysers, Christian; Gazzola, Valeria

2014-01-01

Spike-timing-dependent plasticity is considered the neurophysiological basis of Hebbian learning and has been shown to be sensitive to both contingency and contiguity between pre- and postsynaptic activity. Here, we will examine how applying this Hebbian learning rule to a system of interconnected neurons in the presence of direct or indirect re-afference (e.g. seeing/hearing one's own actions) predicts the emergence of mirror neurons with predictive properties. In this framework, we analyse how mirror neurons become a dynamic system that performs active inferences about the actions of others and allows joint actions despite sensorimotor delays. We explore how this system performs a projection of the self onto others, with egocentric biases to contribute to mind-reading. Finally, we argue that Hebbian learning predicts mirror-like neurons for sensations and emotions and review evidence for the presence of such vicarious activations outside the motor system.

Incremental value of the CT coronary calcium score for the prediction of coronary artery disease

Energy Technology Data Exchange (ETDEWEB)

Genders, Tessa S.S. [Erasmus University Medical Center, Department of Epidemiology, P.O. Box 2040, CA, Rotterdam (Netherlands); Erasmus University Medical Center, Department of Radiology, P.O. Box 2040, CA, Rotterdam (Netherlands); Pugliese, Francesca; Mollet, Nico R.; Meijboom, W. Bob; Weustink, Annick C.; Mieghem, Carlos A.G. van; Feyter, Pim J. de [Erasmus University Medical Center, Department of Radiology, P.O. Box 2040, CA, Rotterdam (Netherlands); Erasmus University Medical Center, Department of Cardiology, P.O. Box 2040, CA, Rotterdam (Netherlands); Hunink, M.G.M. [Erasmus University Medical Center, Department of Epidemiology, P.O. Box 2040, CA, Rotterdam (Netherlands); Erasmus University Medical Center, Department of Radiology, P.O. Box 2040, CA, Rotterdam (Netherlands); Harvard University, Department of Health Policy and Management, Harvard School of Public Health, Boston (United States)

2010-10-15

To validate published prediction models for the presence of obstructive coronary artery disease (CAD) in patients with new onset stable typical or atypical angina pectoris and to assess the incremental value of the CT coronary calcium score (CTCS). We searched the literature for clinical prediction rules for the diagnosis of obstructive CAD, defined as {>=}50% stenosis in at least one vessel on conventional coronary angiography. Significant variables were re-analysed in our dataset of 254 patients with logistic regression. CTCS was subsequently included in the models. The area under the receiver operating characteristic curve (AUC) was calculated to assess diagnostic performance. Re-analysing the variables used by Diamond and Forrester yielded an AUC of 0.798, which increased to 0.890 by adding CTCS. For Pryor, Morise 1994, Morise 1997 and Shaw the AUC increased from 0.838 to 0.901, 0.831 to 0.899, 0.840 to 0.898 and 0.833 to 0.899. CTCS significantly improved model performance in each model. Validation demonstrated good diagnostic performance across all models. CTCS improves the prediction of the presence of obstructive CAD, independent of clinical predictors, and should be considered in its diagnostic work-up. (orig.)

Incremental value of the CT coronary calcium score for the prediction of coronary artery disease

International Nuclear Information System (INIS)

Genders, Tessa S.S.; Pugliese, Francesca; Mollet, Nico R.; Meijboom, W. Bob; Weustink, Annick C.; Mieghem, Carlos A.G. van; Feyter, Pim J. de; Hunink, M.G.M.

2010-01-01

To validate published prediction models for the presence of obstructive coronary artery disease (CAD) in patients with new onset stable typical or atypical angina pectoris and to assess the incremental value of the CT coronary calcium score (CTCS). We searched the literature for clinical prediction rules for the diagnosis of obstructive CAD, defined as ≥50% stenosis in at least one vessel on conventional coronary angiography. Significant variables were re-analysed in our dataset of 254 patients with logistic regression. CTCS was subsequently included in the models. The area under the receiver operating characteristic curve (AUC) was calculated to assess diagnostic performance. Re-analysing the variables used by Diamond and Forrester yielded an AUC of 0.798, which increased to 0.890 by adding CTCS. For Pryor, Morise 1994, Morise 1997 and Shaw the AUC increased from 0.838 to 0.901, 0.831 to 0.899, 0.840 to 0.898 and 0.833 to 0.899. CTCS significantly improved model performance in each model. Validation demonstrated good diagnostic performance across all models. CTCS improves the prediction of the presence of obstructive CAD, independent of clinical predictors, and should be considered in its diagnostic work-up. (orig.)

A novel MADS-box gene subfamily with a sister-group relationship to class B floral homeotic genes.

Science.gov (United States)

Becker, A; Kaufmann, K; Freialdenhoven, A; Vincent, C; Li, M-A; Saedler, H; Theissen, G

2002-02-01

Class B floral homeotic genes specify the identity of petals and stamens during the development of angiosperm flowers. Recently, putative orthologs of these genes have been identified in different gymnosperms. Together, these genes constitute a clade, termed B genes. Here we report that diverse seed plants also contain members of a hitherto unknown sister clade of the B genes, termed B(sister) (B(s)) genes. We have isolated members of the B(s) clade from the gymnosperm Gnetum gnemon, the monocotyledonous angiosperm Zea mays and the eudicots Arabidopsis thaliana and Antirrhinum majus. In addition, MADS-box genes from the basal angiosperm Asarum europaeum and the eudicot Petunia hybrida were identified as B(s) genes. Comprehensive expression studies revealed that B(s) genes are mainly transcribed in female reproductive organs (ovules and carpel walls). This is in clear contrast to the B genes, which are predominantly expressed in male reproductive organs (and in angiosperm petals). Our data suggest that the B(s) genes played an important role during the evolution of the reproductive structures in seed plants. The establishment of distinct B and B(s) gene lineages after duplication of an ancestral gene may have accompanied the evolution of male microsporophylls and female megasporophylls 400-300 million years ago. During flower evolution, expression of B(s) genes diversified, but the focus of expression remained in female reproductive organs. Our findings imply that a clade of highly conserved close relatives of class B floral homeotic genes has been completely overlooked until recently and awaits further evaluation of its developmental and evolutionary importance. Electronic supplementary material to this paper can be obtained by using the Springer Link server located at http://dx.doi.org/10.1007/s00438-001-0615-8.

Expansion analyses of strategic petroleum reserve in Bayou Choctaw : revised locations.

Energy Technology Data Exchange (ETDEWEB)

Ehgartner, Brian L.; Park, Byoung Yoon

2010-11-01

This report summarizes a series of three-dimensional simulations for the Bayou Choctaw Strategic Petroleum Reserve. The U.S. Department of Energy plans to leach two new caverns and convert one of the existing caverns within the Bayou Choctaw salt dome to expand its petroleum reserve storage capacity. An existing finite element mesh from previous analyses is modified by changing the locations of two caverns. The structural integrity of the three expansion caverns and the interaction between all the caverns in the dome are investigated. The impacts of the expansion on underground creep closure, surface subsidence, infrastructure, and well integrity are quantified. Two scenarios were used for the duration and timing of workover conditions where wellhead pressures are temporarily reduced to atmospheric pressure. The three expansion caverns are predicted to be structurally stable against tensile failure for both scenarios. Dilatant failure is not expected within the vicinity of the expansion caverns. Damage to surface structures is not predicted and there is not a marked increase in surface strains due to the presence of the three expansion caverns. The wells into the caverns should not undergo yield. The results show that from a structural viewpoint, the locations of the two newly proposed expansion caverns are acceptable, and all three expansion caverns can be safely constructed and operated.

Weld investigations by 3D analyses of Charpy V-notch specimens

DEFF Research Database (Denmark)

Tvergaard, Viggo; Needleman, Allan

2005-01-01

The Charpy impact test is a standard procedure for determining the ductile-brittle transition in welds. The predictions of such tests have been investigated by full three dimensional transient analyses of Charpy V-notch specimens. The material response is characterised by an elastic...... parameters in the weld material differ from those in the base material, and the heat a®ected zone (HAZ) tends to be more brittle than the other material regions. The effect of weld strength undermatch or overmatch is an important issue. Some specimens, for which the notched surface is rotated relative...... to the surface of the test piece, have so complex geometry that only a full 3D analysis is able to account for the interaction of failure in the three different material regions, whereas ther specimens can be approximated in terms of a planar analysis....

Clinical Perspectives of Genetic Analyses on Dyslipidemia and Coronary Artery Disease

Science.gov (United States)

Kawashiri, Masa-aki; Yamagishi, Masakazu

2017-01-01

We have learned that low-density lipoprotein (LDL) cholesterol is the cause of atherosclerosis from various aspects, including a single case with familial hypercholesterolemia, other cases with different types of Mendelian dyslipidemias, large-scale randomized controlled trials using LDL cholesterol lowering therapies, and Mendelian randomization studies using common as well as rare variants associated with LDL cholesterol levels. There is no doubt that determinations of genotypes in lipid-associated genes have contributed not only to the genetic diagnosis for Mendelian dyslipidemias but also to the discoveries of novel therapeutic targets. Furthermore, recent studies have shown that such genetic information could provide useful clues for the risk prediction as well as risk stratification in general and in particular population. We provide the current understanding of genetic analyses relating to plasma lipids and coronary artery disease. PMID:28250266

Behavior of underclad cracks in reactor pressure vessels - evaluation of mechanical analyses with tests on cladded mock-ups

International Nuclear Information System (INIS)

Moinereau, D.; Rousselier, G.; Bethmont, M.

1993-01-01

Innocuity of underclad flaws in the reactor pressure vessels must be demonstrated in the French safety analyses, particularly in the case of a severe transient at the end of the pressure vessel lifetime, because of the radiation embrittlement of the vessel material. Safety analyses are usually performed with elastic and elasto-plastic analyses taking into account the effect of the stainless steel cladding. EDF has started a program including experiments on large size cladded specimens and their interpretations. The purpose of this program is to evaluate the different methods of fracture analysis used in safety studies. Several specimens made of ferritic steel A508 C1 3 with stainless steel cladding, containing small artificial defects, are loaded in four-point bending. Experiments are performed at very low temperature to simulate radiation embrittlement and to obtain crack instability by cleavage fracture. Three tests have been performed on mock-ups containing a small underclad crack (with depth about 5 mn) and a fourth test has been performed on one mock-up with a larger crack (depth about 13 mn). In each case, crack instability occurred by cleavage fracture in the base metal, without crack arrest, at a temperature of about - 170 deg C. Each test is interpreted using linear elastic analysis and elastic-plastic analysis by two-dimensional finite element computations. The fracture are conservatively predicted: the stress intensity factors deduced from the computations (K cp or K j ) are always greater than the base metal toughness. The comparison between the elastic analyses (including two plasticity corrections) and the elastic-plastic analyses shows that the elastic analyses are often conservative. The beneficial effect of the cladding in the analyses is also shown : the analyses are too conservative if the cladding effects is not taken into account. (authors). 9 figs., 6 tabs., 10 refs

Protein docking prediction using predicted protein-protein interface

Directory of Open Access Journals (Sweden)

Li Bin

2012-01-01

Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Protein docking prediction using predicted protein-protein interface.

Science.gov (United States)

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Social Media Analyses for Social Measurement

Science.gov (United States)

Schober, Michael F.; Pasek, Josh; Guggenheim, Lauren; Lampe, Cliff; Conrad, Frederick G.

2016-01-01

Demonstrations that analyses of social media content can align with measurement from sample surveys have raised the question of whether survey research can be supplemented or even replaced with less costly and burdensome data mining of already-existing or “found” social media content. But just how trustworthy such measurement can be—say, to replace official statistics—is unknown. Survey researchers and data scientists approach key questions from starting assumptions and analytic traditions that differ on, for example, the need for representative samples drawn from frames that fully cover the population. New conversations between these scholarly communities are needed to understand the potential points of alignment and non-alignment. Across these approaches, there are major differences in (a) how participants (survey respondents and social media posters) understand the activity they are engaged in; (b) the nature of the data produced by survey responses and social media posts, and the inferences that are legitimate given the data; and (c) practical and ethical considerations surrounding the use of the data. Estimates are likely to align to differing degrees depending on the research topic and the populations under consideration, the particular features of the surveys and social media sites involved, and the analytic techniques for extracting opinions and experiences from social media. Traditional population coverage may not be required for social media content to effectively predict social phenomena to the extent that social media content distills or summarizes broader conversations that are also measured by surveys. PMID:27257310

Social Media Analyses for Social Measurement.

Science.gov (United States)

Schober, Michael F; Pasek, Josh; Guggenheim, Lauren; Lampe, Cliff; Conrad, Frederick G

2016-01-01

Demonstrations that analyses of social media content can align with measurement from sample surveys have raised the question of whether survey research can be supplemented or even replaced with less costly and burdensome data mining of already-existing or "found" social media content. But just how trustworthy such measurement can be-say, to replace official statistics-is unknown. Survey researchers and data scientists approach key questions from starting assumptions and analytic traditions that differ on, for example, the need for representative samples drawn from frames that fully cover the population. New conversations between these scholarly communities are needed to understand the potential points of alignment and non-alignment. Across these approaches, there are major differences in (a) how participants (survey respondents and social media posters) understand the activity they are engaged in; (b) the nature of the data produced by survey responses and social media posts, and the inferences that are legitimate given the data; and (c) practical and ethical considerations surrounding the use of the data. Estimates are likely to align to differing degrees depending on the research topic and the populations under consideration, the particular features of the surveys and social media sites involved, and the analytic techniques for extracting opinions and experiences from social media. Traditional population coverage may not be required for social media content to effectively predict social phenomena to the extent that social media content distills or summarizes broader conversations that are also measured by surveys.

Burnout does not help predict depression among French school teachers.

Science.gov (United States)

Bianchi, Renzo; Schonfeld, Irvin Sam; Laurent, Eric

2015-11-01

Burnout has been viewed as a phase in the development of depression. However, supportive research is scarce. We examined whether burnout predicted depression among French school teachers. We conducted a 2-wave, 21-month study involving 627 teachers (73% female) working in French primary and secondary schools. Burnout was assessed with the Maslach Burnout Inventory and depression with the 9-item depression module of the Patient Health Questionnaire (PHQ-9). The PHQ-9 grades depressive symptom severity and provides a provisional diagnosis of major depression. Depression was treated both as a continuous and categorical variable using linear and logistic regression analyses. We controlled for gender, age, and length of employment. Controlling for baseline depressive symptoms, linear regression analysis showed that burnout symptoms at time 1 (T1) did not predict depressive symptoms at time 2 (T2). Baseline depressive symptoms accounted for about 88% of the association between T1 burnout and T2 depressive symptoms. Only baseline depressive symptoms predicted depressive symptoms at follow-up. Similarly, logistic regression analysis revealed that burnout symptoms at T1 did not predict incident cases of major depression at T2 when depressive symptoms at T1 were included in the predictive model. Only baseline depressive symptoms predicted cases of major depression at follow-up. This study does not support the view that burnout is a phase in the development of depression. Assessing burnout symptoms in addition to "classical" depressive symptoms may not always improve our ability to predict future depression.

Predictive value of the DASH tool for predicting return to work of injured workers with musculoskeletal disorders of the upper extremity.

Science.gov (United States)

Armijo-Olivo, Susan; Woodhouse, Linda J; Steenstra, Ivan A; Gross, Douglas P

2016-12-01

To determine whether the Disabilities of the Arm, Shoulder, and Hand (DASH) tool added to the predictive ability of established prognostic factors, including patient demographic and clinical outcomes, to predict return to work (RTW) in injured workers with musculoskeletal (MSK) disorders of the upper extremity. A retrospective cohort study using a population-based database from the Workers' Compensation Board of Alberta (WCB-Alberta) that focused on claimants with upper extremity injuries was used. Besides the DASH, potential predictors included demographic, occupational, clinical and health usage variables. Outcome was receipt of compensation benefits after 3 months. To identify RTW predictors, a purposeful logistic modelling strategy was used. A series of receiver operating curve analyses were performed to determine which model provided the best discriminative ability. The sample included 3036 claimants with upper extremity injuries. The final model for predicting RTW included the total DASH score in addition to other established predictors. The area under the curve for this model was 0.77, which is interpreted as fair discrimination. This model was statistically significantly different than the model of established predictors alone (pmodels (p=0.34). The DASH tool together with other established predictors significantly helped predict RTW after 3 months in participants with upper extremity MSK disorders. An appealing result for clinicians and busy researchers is that DASH item 23 has equal predictive ability to the total DASH score. 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/.

Toxicological relationships between proteins obtained from protein target predictions of large toxicity databases

International Nuclear Information System (INIS)

Nigsch, Florian; Mitchell, John B.O.

2008-01-01

The combination of models for protein target prediction with large databases containing toxicological information for individual molecules allows the derivation of 'toxiclogical' profiles, i.e., to what extent are molecules of known toxicity predicted to interact with a set of protein targets. To predict protein targets of drug-like and toxic molecules, we built a computational multiclass model using the Winnow algorithm based on a dataset of protein targets derived from the MDL Drug Data Report. A 15-fold Monte Carlo cross-validation using 50% of each class for training, and the remaining 50% for testing, provided an assessment of the accuracy of that model. We retained the 3 top-ranking predictions and found that in 82% of all cases the correct target was predicted within these three predictions. The first prediction was the correct one in almost 70% of cases. A model built on the whole protein target dataset was then used to predict the protein targets for 150 000 molecules from the MDL Toxicity Database. We analysed the frequency of the predictions across the panel of protein targets for experimentally determined toxicity classes of all molecules. This allowed us to identify clusters of proteins related by their toxicological profiles, as well as toxicities that are related. Literature-based evidence is provided for some specific clusters to show the relevance of the relationships identified

Performance Optimization of Unglazed Nanofluid Photovoltaic/Thermal System: Energy and Exergy Analyses

Directory of Open Access Journals (Sweden)

M. Imtiaz Hussain

2018-01-01

Full Text Available The focus of this paper is to predict the transient response of a nanoengineered photovoltaic thermal (PV/T system in view of energy and exergy analyses. Instead of a circular-shaped receiver, a trapezoidal-shaped receiver is employed to increase heat transfer surface area with photovoltaic (PV cells for improvement of heat extraction and thus achievement of a higher PV/T system efficiency. The dynamic mathematical model is developed using MATLAB® software by considering real-time heat transfer coefficients. The proposed model is validated with experimental data from a previous study. Negligible discrepancies were found between measured and predicted data. The validated model was further investigated in detail using different nanofluids by dispersing copper oxide (CuO and aluminum oxide (Al2O3 in pure water. The overall performance of the nanoengineered PV/T system was compared to that of a PV/T system using water only, and optimal operating conditions were determined for maximum useful energy and exergy rates. The results indicated that the CuO/water nanofluid has a notable impact on the energy and exergy efficiencies of the PV/T system compared to that of Al2O3/water nanofluid and water only cases.

Trial sequential analyses of meta-analyses of complications in laparoscopic vs. small-incision cholecystectomy: more randomized patients are needed

DEFF Research Database (Denmark)

Keus, Frederik; Wetterslev, Jørn; Gluud, Christian

2010-01-01

Conclusions based on meta-analyses of randomized trials carry a status of "truth." Methodological components may identify trials with systematic errors ("bias"). Trial sequential analysis (TSA) evaluates random errors in meta-analysis. We analyzed meta-analyses on laparoscopic vs. small-incision ......Conclusions based on meta-analyses of randomized trials carry a status of "truth." Methodological components may identify trials with systematic errors ("bias"). Trial sequential analysis (TSA) evaluates random errors in meta-analysis. We analyzed meta-analyses on laparoscopic vs. small...

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

International Nuclear Information System (INIS)

Fukunaga, Satoki; Kakehashi, Anna; Sumida, Kayo; Kushida, Masahiko; Asano, Hiroyuki; Gi, Min; Wanibuchi, Hideki

2015-01-01

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective of initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

Energy Technology Data Exchange (ETDEWEB)

Fukunaga, Satoki [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558 (Japan); Kakehashi, Anna [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Sumida, Kayo; Kushida, Masahiko; Asano, Hiroyuki [Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558 (Japan); Gi, Min [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Wanibuchi, Hideki, E-mail: wani@med.osaka-cu.ac.jp [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan)

2015-08-01

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective of initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis.

The Validity of Conscientiousness Is Overestimated in the Prediction of Job Performance.

Science.gov (United States)

Kepes, Sven; McDaniel, Michael A

2015-01-01

Sensitivity analyses refer to investigations of the degree to which the results of a meta-analysis remain stable when conditions of the data or the analysis change. To the extent that results remain stable, one can refer to them as robust. Sensitivity analyses are rarely conducted in the organizational science literature. Despite conscientiousness being a valued predictor in employment selection, sensitivity analyses have not been conducted with respect to meta-analytic estimates of the correlation (i.e., validity) between conscientiousness and job performance. To address this deficiency, we reanalyzed the largest collection of conscientiousness validity data in the personnel selection literature and conducted a variety of sensitivity analyses. Publication bias analyses demonstrated that the validity of conscientiousness is moderately overestimated (by around 30%; a correlation difference of about .06). The misestimation of the validity appears to be due primarily to suppression of small effects sizes in the journal literature. These inflated validity estimates result in an overestimate of the dollar utility of personnel selection by millions of dollars and should be of considerable concern for organizations. The fields of management and applied psychology seldom conduct sensitivity analyses. Through the use of sensitivity analyses, this paper documents that the existing literature overestimates the validity of conscientiousness in the prediction of job performance. Our data show that effect sizes from journal articles are largely responsible for this overestimation.

Does the emergency surgery score accurately predict outcomes in emergent laparotomies?

Science.gov (United States)

Peponis, Thomas; Bohnen, Jordan D; Sangji, Naveen F; Nandan, Anirudh R; Han, Kelsey; Lee, Jarone; Yeh, D Dante; de Moya, Marc A; Velmahos, George C; Chang, David C; Kaafarani, Haytham M A

2017-08-01

The emergency surgery score is a mortality-risk calculator for emergency general operation patients. We sought to examine whether the emergency surgery score predicts 30-day morbidity and mortality in a high-risk group of patients undergoing emergent laparotomy. Using the 2011-2012 American College of Surgeons National Surgical Quality Improvement Program database, we identified all patients who underwent emergent laparotomy using (1) the American College of Surgeons National Surgical Quality Improvement Program definition of "emergent," and (2) all Current Procedural Terminology codes denoting a laparotomy, excluding aortic aneurysm rupture. Multivariable logistic regression analyses were performed to measure the correlation (c-statistic) between the emergency surgery score and (1) 30-day mortality, and (2) 30-day morbidity after emergent laparotomy. As sensitivity analyses, the correlation between the emergency surgery score and 30-day mortality was also evaluated in prespecified subgroups based on Current Procedural Terminology codes. A total of 26,410 emergent laparotomy patients were included. Thirty-day mortality and morbidity were 10.2% and 43.8%, respectively. The emergency surgery score correlated well with mortality (c-statistic = 0.84); scores of 1, 11, and 22 correlated with mortalities of 0.4%, 39%, and 100%, respectively. Similarly, the emergency surgery score correlated well with morbidity (c-statistic = 0.74); scores of 0, 7, and 11 correlated with complication rates of 13%, 58%, and 79%, respectively. The morbidity rates plateaued for scores higher than 11. Sensitivity analyses demonstrated that the emergency surgery score effectively predicts mortality in patients undergoing emergent (1) splenic, (2) gastroduodenal, (3) intestinal, (4) hepatobiliary, or (5) incarcerated ventral hernia operation. The emergency surgery score accurately predicts outcomes in all types of emergent laparotomy patients and may prove valuable as a bedside decision

Steady State Thermal Analyses of SCEPTOR X-57 Wingtip Propulsion

Science.gov (United States)

Schnulo, Sydney L.; Chin, Jeffrey C.; Smith, Andrew D.; Dubois, Arthur

2017-01-01

Electric aircraft concepts enable advanced propulsion airframe integration approaches that promise increased efficiency as well as reduced emissions and noise. NASA's fully electric Maxwell X-57, developed under the SCEPTOR program, features distributed propulsion across a high aspect ratio wing. There are 14 propulsors in all: 12 high lift motor that are only active during take off and climb, and 2 larger motors positioned on the wingtips that operate over the entire mission. The power electronics involved in the wingtip propulsion are temperature sensitive and therefore require thermal management. This work focuses on the high and low fidelity heat transfer analysis methods performed to ensure that the wingtip motor inverters do not reach their temperature limits. It also explores different geometry configurations involved in the X-57 development and any thermal concerns. All analyses presented are performed at steady state under stressful operating conditions, therefore predicting temperatures which are considered the worst-case scenario to remain conservative.

Field-scale predictions of soil contaminant sorption using visible–near infrared spectroscopy

DEFF Research Database (Denmark)

Paradelo Pérez, Marcos; Hermansen, Cecilie; Knadel, Maria

2016-01-01

. By means of the vis–NIR spectra we were able to predict phenanthrene (R2 = 0.95, RMSECV = 31 L kg−1) and glyphosate (R2 = 0.79, RMSECV = 45 L kg−1) sorption capacities. A model using vis–NIR spectra plus pH values improved the prediction of glyphosate sorption capacity (R2 = 0.88, RMSECV = 34 L kg−1......) and glyphosate (sorbed on mineral fractions). Forty-five bulk soil samples were collected from an agricultural field in Estrup, Denmark, in a 15 m × 15 m grid. Samples were air-dried, sieved to 2 mm and analysed for selected soil properties. Sorption coefficients were obtained from a batch equilibration...

Stigma Predicts Treatment Preferences and Care Engagement among Veterans Affairs Primary Care Patients with Depression

Science.gov (United States)

Campbell, Duncan G.; Bonner, Laura M.; Bolkan, Cory R.; Lanto, Andrew B.; Zivin, Kara; Waltz, Thomas J.; Klap, Ruth; Rubenstein, Lisa V.; Chaney, Edmund F.

2016-01-01

Background Whereas stigma regarding mental health concerns exists, the evidence for stigma as a depression treatment barrier among patients in Veterans Affairs (VA) primary care (PC) is mixed. Purpose To test whether stigma, defined as depression label avoidance, predicted patients' preferences for depression treatment providers, patients' prospective engagement in depression care, and care quality. Methods We conducted cross-sectional and prospective analyses of existing data from 761 VA PC patients with probable major depression. Results Relative to low stigma patients, those with high stigma were less likely to prefer treatment from mental health specialists. In prospective controlled analyses, high stigma predicted lower likelihood of the following: taking medications for mood, treatment by mental health specialists, treatment for emotional concerns in PC, and appropriate depression care. Conclusions High stigma is associated with lower preferences for care from mental health specialists and confers risk for minimal depression treatment engagement. PMID:26935310

Residual Strength Pressure Tests and Nonlinear Analyses of Stringer- and Frame-Stiffened Aluminum Fuselage Panels with Longitudinal Cracks

Science.gov (United States)

Young, Richard D.; Rouse, Marshall; Ambur, Damodar R.; Starnes, James H., Jr.

1999-01-01

The results of residual strength pressure tests and nonlinear analyses of stringer- and frame-stiffened aluminum fuselage panels with longitudinal cracks are presented. Two types of damage are considered: a longitudinal crack located midway between stringers, and a longitudinal crack adjacent to a stringer and along a row of fasteners in a lap joint that has multiple-site damage (MSD). In both cases, the longitudinal crack is centered on a severed frame. The panels are subjected to internal pressure plus axial tension loads. The axial tension loads are equivalent to a bulkhead pressure load. Nonlinear elastic-plastic residual strength analyses of the fuselage panels are conducted using a finite element program and the crack-tip-opening-angle (CTOA) fracture criterion. Predicted crack growth and residual strength results from nonlinear analyses of the stiffened fuselage panels are compared with experimental measurements and observations. Both the test and analysis results indicate that the presence of MSD affects crack growth stability and reduces the residual strength of stiffened fuselage shells with long cracks.

Predictive value of sperm morphology and progressively motile sperm count for pregnancy outcomes in intrauterine insemination

NARCIS (Netherlands)

Lemmens, L.; Kos, S.; Beijer, C.; Brinkman, J.W.; Horst, F.A. van der; Hoven, L. van den; Kieslinger, D.C.; Trooyen-van Vrouwerff, N.J.; Wolthuis, A.; Hendriks, J.C.M.; Wetzels, A.M.M.

2016-01-01

OBJECTIVE: To investigate the value of sperm parameters to predict an ongoing pregnancy outcome in couples treated with intrauterine insemination (IUI), during a methodologically stable period of time. DESIGN: Retrospective, observational study with logistic regression analyses. SETTING: University

Decline Curve Based Models for Predicting Natural Gas Well Performance

OpenAIRE

Kamari, Arash; Mohammadi, Amir H.; Lee, Moonyong; Mahmood, Tariq; Bahadori, Alireza

2016-01-01

The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN) modelling strategy, least square support vector machine (LSSVM) approach, adaptive neuro-fuzzy ...

Methods and techniques for prediction of environmental impact

International Nuclear Information System (INIS)

1992-04-01

Environmental impact assessment (EIA) is the procedure that helps decision makers understand the environmental implications of their decisions. The prediction of environmental effects or impact is an extremely important part of the EIA procedure and improvements in existing capabilities are needed. Considerable attention is paid within environmental impact assessment and in handbooks on EIA to methods for identifying and evaluating environmental impacts. However, little attention is given to the issue distribution of information on impact prediction methods. The quantitative or qualitative methods for the prediction of environmental impacts appear to be the two basic approaches for incorporating environmental concerns into the decision-making process. Depending on the nature of the proposed activity and the environment likely to be affected, a combination of both quantitative and qualitative methods is used. Within environmental impact assessment, the accuracy of methods for the prediction of environmental impacts is of major importance while it provides for sound and well-balanced decision making. Pertinent and effective action to deal with the problems of environmental protection and the rational use of natural resources and sustainable development is only possible given objective methods and techniques for the prediction of environmental impact. Therefore, the Senior Advisers to ECE Governments on Environmental and Water Problems, decided to set up a task force, with the USSR as lead country, on methods and techniques for the prediction of environmental impacts in order to undertake a study to review and analyse existing methodological approaches and to elaborate recommendations to ECE Governments. The work of the task force was completed in 1990 and the resulting report, with all relevant background material, was approved by the Senior Advisers to ECE Governments on Environmental and Water Problems in 1991. The present report reflects the situation, state of

Prediction of future labour market outcome in a cohort of long-term sick-listed Danes

DEFF Research Database (Denmark)

Pedersen, Jacob; Gerds, Thomas Alexander; Bjørner, Jakob

2014-01-01

BACKGROUND: Targeted interventions for the long-term sick-listed may prevent permanent exclusion from the labour force. We aimed to develop a prediction method for identifying high risk groups for continued or recurrent long-term sickness absence, unemployment, or disability among persons on long...... data set, statistical prediction methods were built using logistic regression and a discrete event simulation approach for a one year prediction horizon. Personalized risk profiles were obtained for five outcomes: employment, unemployment, recurrent sickness absence, continuous long-term sickness...... of recession (2008-2010). The accuracy of the prediction models was assessed with analyses of Receiver Operating Characteristic (ROC) curves and the Brier score in an independent validation data set. RESULTS: In comparison with a null model which ignored the predictor variables, logistic regression achieved...

Early post-stroke cognition in stroke rehabilitation patients predicts functional outcome at 13 months.

Science.gov (United States)

Wagle, Jørgen; Farner, Lasse; Flekkøy, Kjell; Bruun Wyller, Torgeir; Sandvik, Leiv; Fure, Brynjar; Stensrød, Brynhild; Engedal, Knut

2011-01-01

To identify prognostic factors associated with functional outcome at 13 months in a sample of stroke rehabilitation patients. Specifically, we hypothesized that cognitive functioning early after stroke would predict long-term functional outcome independently of other factors. 163 stroke rehabilitation patients underwent a structured neuropsychological examination 2-3 weeks after hospital admittance, and their functional status was subsequently evaluated 13 months later with the modified Rankin Scale (mRS) as outcome measure. Three predictive models were built using linear regression analyses: a biological model (sociodemographics, apolipoprotein E genotype, prestroke vascular factors, lesion characteristics and neurological stroke-related impairment); a functional model (pre- and early post-stroke cognitive functioning, personal and instrumental activities of daily living, ADL, and depressive symptoms), and a combined model (including significant variables, with p value Stroke Scale; β = 0.402, p stroke cognitive functioning (Repeatable Battery of Neuropsychological Status, RBANS; β = -0.248, p = 0.001) and prestroke personal ADL (Barthel Index; β = -0.217, p = 0.002). Further linear regression analyses of which RBANS indexes and subtests best predicted long-term functional outcome showed that Coding (β = -0.484, p stroke cognitive functioning as measured by the RBANS is a significant and independent predictor of long-term functional post-stroke outcome. Copyright © 2011 S. Karger AG, Basel.

WALS Prediction

NARCIS (Netherlands)

Magnus, J.R.; Wang, W.; Zhang, Xinyu

2012-01-01

Abstract: Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty

Impact of modellers' decisions on hydrological a priori predictions

Science.gov (United States)

Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

2014-06-01

In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

An introduction to loricifera, cycliophora, and micrognathozoa.

Science.gov (United States)

Kristensen, Reinhardt Møbjerg

2002-07-01

Loriciferans, cycliophorans and micrognathozoans are amongst the latest groups of animals to be discovered. Other than all being microscopic, they have very different body plans and are not closely related. Loriciferans were originally assigned to the Aschelminthes. However, both new molecular and ultrastructural researches have shown that Aschelminthes consist of two unrelated groups, Cycloneuralia and Gnathifera. Cycloneuralia may be included in the Ecdysozoa, including all molting invertebrates, and Gnathifera are more closely related to Platyhelminthes. The phylum Loricifera shares many apomorphic characters (e.g., scalids on the introvert) with both Priapulida and Kinorhyncha, and can be included in the taxon Scalidophora, a subgroup of Cycloneuralia. Cycliophora was originally allied to the Entoprocta and Ectoprocta (Bryozoa) based on ultrastructual research. Subsequent molecular data show they may be related to Rotifera and Acanthocephala, within the taxon Gnathifera. The phylogenetic position of Cycliophora is therefore not settled, and more ultrastructural and molecular data are needed. Micrognathozoa is the most recent major group of animals to be described. They show strong affinities with both Rotifera and Gnathostomulida (within the taxon Gnathifera), especially in the fine structure of the pharyngeal apparatus, where the jaw elements have cuticular rods with osmiophilic cores. Furthermore the micrognathozoans have two rows of multiciliated cells that form a locomotory organ, similar to that seen in some gastrotrichs and interstitial annelids. This character is never seen in Rotifera or in the monociliated Gnathostomulida. Rotifera and Acanthocephala always have a syncytial epidermis (Syndermata). Micrognathozoa lack this characteristic feature. Therefore, they are postulated to be placed basally in the Gnathifera, either as a sister-group to Gnathostomulida or as a sister-group to Rotifera + Acanthocephala.

Comparison of tree types of models for the prediction of final academic achievement

Directory of Open Access Journals (Sweden)

Silvana Gasar

2002-12-01

Full Text Available For efficient prevention of inappropriate secondary school choices and by that academic failure, school counselors need a tool for the prediction of individual pupil's final academic achievements. Using data mining techniques on pupils' data base and expert modeling, we developed several models for the prediction of final academic achievement in an individual high school educational program. For data mining, we used statistical analyses, clustering and two machine learning methods: developing classification decision trees and hierarchical decision models. Using an expert system shell DEX, an expert system, based on a hierarchical multi-attribute decision model, was developed manually. All the models were validated and evaluated from the viewpoint of their applicability. The predictive accuracy of DEX models and decision trees was equal and very satisfying, as it reached the predictive accuracy of an experienced counselor. With respect on the efficiency and difficulties in developing models, and relatively rapid changing of our education system, we propose that decision trees are used in further development of predictive models.

Looking Māori predicts decreased rates of home ownership: institutional racism in housing based on perceived appearance.

Science.gov (United States)

Houkamau, Carla A; Sibley, Chris G

2015-01-01

This study examined differences in rates of home ownership among Māori (the indigenous peoples of New Zealand). We identified systematic factors that predicted why some Māori were more likely to own their own home (partially or fully) relative to other Māori. Data were drawn from a large national postal sample of 561 self-identified Māori collected as part of the New Zealand Attitudes and Values Study. As predicted, our analyses indicated that self-reported appearance as Māori, or the extent to which people thought they personally displayed features which visibly identified them as Māori to others, significantly predicted decreased rates of home ownership. This association held when adjusting for numerous demographic covariates, such as education, level of deprivation of the immediate area, household income, age, relationship status, region of residence, and so forth. Our analyses suggest there is, or at least has been in the recent past, institutional racism against Māori in New Zealand's home lending industry based on merely appearing more Māori.

Prediction of infarction development after endovascular stroke therapy with dual-energy computed tomography.

Science.gov (United States)

Djurdjevic, Tanja; Rehwald, Rafael; Knoflach, Michael; Matosevic, Benjamin; Kiechl, Stefan; Gizewski, Elke Ruth; Glodny, Bernhard; Grams, Astrid Ellen

2017-03-01

After intraarterial recanalisation (IAR), the haemorrhage and the blood-brain barrier (BBB) disruption can be distinguished using dual-energy computed tomography (DECT). The aim of the present study was to investigate whether future infarction development can be predicted from DECT. DECT scans of 20 patients showing 45 BBB disrupted areas after IAR were assessed and compared with follow-up examinations. Receiver operator characteristic (ROC) analyses using densities from the iodine map (IM) and virtual non-contrast (VNC) were performed. Future infarction areas are denser than future non-infarction areas on IM series (23.44 ± 24.86 vs. 5.77 ± 2.77; p VNC series (29.71 ± 3.33 vs. 35.33 ± 3.50; p 17.13 HU; p VNC series allowed prediction of infarction volume. Future infarction development after IAR can be reliably predicted with the IM series. The prediction of haemorrhages and of infarction size is less reliable. • The IM series (DECT) can predict future infarction development after IAR. • Later haemorrhages can be predicted using the IM and the BW series. • The volume of definable hypodense areas in VNC correlates with infarction volume.

Predictive value of cognition for different domains of outcome in recent-onset schizophrenia.

Science.gov (United States)

Holthausen, Esther A E; Wiersma, Durk; Cahn, Wiepke; Kahn, René S; Dingemans, Peter M; Schene, Aart H; van den Bosch, Robert J

2007-01-15

The aim of this study was to see whether and how cognition predicts outcome in recent-onset schizophrenia in a large range of domains such as course of illness, self-care, interpersonal functioning, vocational functioning and need for care. At inclusion, 115 recent-onset patients were tested on a cognitive battery and 103 patients participated in the follow-up 2 years after inclusion. Differences in outcome between cognitively normal and cognitively impaired patients were also analysed. Cognitive measures at inclusion did not predict number of relapses, activities of daily living and interpersonal functioning. Time in psychosis or in full remission, as well as need for care, were partly predicted by specific cognitive measures. Although statistically significant, the predictive value of cognition with regard to clinical outcome was limited. There was a significant difference between patients with and without cognitive deficits in competitive employment status and vocational functioning. The predictive value of cognition for different social outcome domains varies. It seems that cognition most strongly predicts work performance, where having a cognitive deficit, regardless of the nature of the deficit, acts as a rate-limiting factor.

Great Expectations: Is there Evidence for Predictive Coding in Auditory Cortex?

Science.gov (United States)

Heilbron, Micha; Chait, Maria

2017-08-04

Predictive coding is possibly one of the most influential, comprehensive, and controversial theories of neural function. While proponents praise its explanatory potential, critics object that key tenets of the theory are untested or even untestable. The present article critically examines existing evidence for predictive coding in the auditory modality. Specifically, we identify five key assumptions of the theory and evaluate each in the light of animal, human and modeling studies of auditory pattern processing. For the first two assumptions - that neural responses are shaped by expectations and that these expectations are hierarchically organized - animal and human studies provide compelling evidence. The anticipatory, predictive nature of these expectations also enjoys empirical support, especially from studies on unexpected stimulus omission. However, for the existence of separate error and prediction neurons, a key assumption of the theory, evidence is lacking. More work exists on the proposed oscillatory signatures of predictive coding, and on the relation between attention and precision. However, results on these latter two assumptions are mixed or contradictory. Looking to the future, more collaboration between human and animal studies, aided by model-based analyses will be needed to test specific assumptions and implementations of predictive coding - and, as such, help determine whether this popular grand theory can fulfill its expectations. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

How distributed processing produces false negatives in voxel-based lesion-deficit analyses.

Science.gov (United States)

Gajardo-Vidal, Andrea; Lorca-Puls, Diego L; Crinion, Jennifer T; White, Jitrachote; Seghier, Mohamed L; Leff, Alex P; Hope, Thomas M H; Ludersdorfer, Philipp; Green, David W; Bowman, Howard; Price, Cathy J

2018-07-01

In this study, we hypothesized that if the same deficit can be caused by damage to one or another part of a distributed neural system, then voxel-based analyses might miss critical lesion sites because preservation of each site will not be consistently associated with preserved function. The first part of our investigation used voxel-based multiple regression analyses of data from 359 right-handed stroke survivors to identify brain regions where lesion load is associated with picture naming abilities after factoring out variance related to object recognition, semantics and speech articulation so as to focus on deficits arising at the word retrieval level. A highly significant lesion-deficit relationship was identified in left temporal and frontal/premotor regions. Post-hoc analyses showed that damage to either of these sites caused the deficit of interest in less than half the affected patients (76/162 = 47%). After excluding all patients with damage to one or both of the identified regions, our second analysis revealed a new region, in the anterior part of the left putamen, which had not been previously detected because many patients had the deficit of interest after temporal or frontal damage that preserved the left putamen. The results illustrate how (i) false negative results arise when the same deficit can be caused by different lesion sites; (ii) some of the missed effects can be unveiled by adopting an iterative approach that systematically excludes patients with lesions to the areas identified in previous analyses, (iii) statistically significant voxel-based lesion-deficit mappings can be driven by a subset of patients; (iv) focal lesions to the identified regions are needed to determine whether the deficit of interest is the consequence of focal damage or much more extensive damage that includes the identified region; and, finally, (v) univariate voxel-based lesion-deficit mappings cannot, in isolation, be used to predict outcome in other patients

Analyse of Maintenance Cost in ST

CERN Document Server

Jenssen, B W

2001-01-01

An analyse has been carried out in ST concerning the total costs for the division. Even though the target was the maintenance costs in ST, the global budget over has been analysed. This has been done since there is close relation between investments & consolidation and the required level for maintenance. The purpose of the analyse was to focus on maintenance cost in ST as a ratio of total maintenance costs over the replacement value of the equipment, and to make some comparisons with other industries and laboratories. Families of equipment have been defined and their corresponding ratios calculated. This first approach gives us some "quantitative" measurements. This analyse should be combined with performance indicators (more "qualitative" measurements) that are telling us how well we are performing. This will help us in defending our budget, make better priorities, and we will satisfy the requirements from our external auditors.

Suitability of cuticular pores and sensilla for harpacticoid copepod species delineation and phylogenetic reconstruction.

Science.gov (United States)

Karanovic, Tomislav; Kim, Kichoon

2014-11-01

Cuticular organs have not been described systematically in harpacticoids until recently, and they haven ever been used as characters for reconstructing phylogenetic relationships in any crustacean group. We survey cuticular pores and sensilla on somites in ten Miraciidae species, belonging to six genera, from Korea, Australia, and Russia. Nine species belong to the subfamily Stenheliinae, while the outgroup belongs to the subfamily Diosaccinae. We aim to compare phylogenetic trees reconstructed for these harpactioids based on: 1) cuticular organs (with 76 characters scored, 71% of them phylogenetically informative); 2) traditionally used macro-morphological characters (66 scored, 77% of them informative);and 3) mtCOI DNA data. All analyses suggest that cuticular organs are useful characters for harpacticoid species delineation, although not as sensitive as some fast-evolving molecular markers. Reconstructed cladograms based on all three datasets show very high bootstrap values for clades representing distinct genera, suggesting that cuticular organs are suitable characters for studying phylogenetic relationships. Bootstrap values for the more basal nodes differ among the different cladograms,as do the sister-group relationships they suggest, indicating that cuticular organs probably have different evolutionary constraints from macro-morphological characters. Cuticular organs could be quite useful in the study of old museum specimens and fossil crustaceans.

Genomic prediction of reproduction traits for Merino sheep.

Science.gov (United States)

Bolormaa, S; Brown, D J; Swan, A A; van der Werf, J H J; Hayes, B J; Daetwyler, H D

2017-06-01

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy

Predicting complex acute wound healing in patients from a wound expertise centre registry: a prognostic study

OpenAIRE

Ubbink, Dirk T; Lindeboom, Robert; Eskes, Anne M; Brull, Huub; Legemate, Dink A; Vermeulen, Hester

2015-01-01

It is important for caregivers and patients to know which wounds are at risk of prolonged wound healing to enable timely communication and treatment. Available prognostic models predict wound healing in chronic ulcers, but not in acute wounds, that is, originating after trauma or surgery. We developed a model to detect which factors can predict (prolonged) healing of complex acute wounds in patients treated in a large wound expertise centre (WEC). Using Cox and linear regression analyses, we ...

A Simple, Reliable Precision Time Analyser

Energy Technology Data Exchange (ETDEWEB)

Joshi, B. V.; Nargundkar, V. R.; Subbarao, K.; Kamath, M. S.; Eligar, S. K. [Atomic Energy Establishment Trombay, Bombay (India)

1966-06-15

A 30-channel time analyser is described. The time analyser was designed and built for pulsed neutron research but can be applied to other uses. Most of the logic is performed by means of ferrite memory core and transistor switching circuits. This leads to great versatility, low power consumption, extreme reliability and low cost. The analyser described provides channel Widths from 10 {mu}s to 10 ms; arbitrarily wider channels are easily obtainable. It can handle counting rates up to 2000 counts/min in each channel with less than 1% dead time loss. There is a provision for an initial delay equal to 100 channel widths. An input pulse de-randomizer unit using tunnel diodes ensures exactly equal channel widths. A brief description of the principles involved in core switching circuitry is given. The core-transistor transfer loop is compared with the usual core-diode loops and is shown to be more versatile and better adapted to the making of a time analyser. The circuits derived from the basic loop are described. These include the scale of ten, the frequency dividers and the delay generator. The current drivers developed for driving the cores are described. The crystal-controlled clock which controls the width of the time channels and synchronizes the operation of the various circuits is described. The detector pulse derandomizer unit using tunnel diodes is described. The scheme of the time analyser is then described showing how the various circuits can be integrated together to form a versatile time analyser. (author)

Random error in cardiovascular meta-analyses

DEFF Research Database (Denmark)

Albalawi, Zaina; McAlister, Finlay A; Thorlund, Kristian

2013-01-01

BACKGROUND: Cochrane reviews are viewed as the gold standard in meta-analyses given their efforts to identify and limit systematic error which could cause spurious conclusions. The potential for random error to cause spurious conclusions in meta-analyses is less well appreciated. METHODS: We exam...

Diversity of primary care systems analysed.

NARCIS (Netherlands)

Kringos, D.; Boerma, W.; Bourgueil, Y.; Cartier, T.; Dedeu, T.; Hasvold, T.; Hutchinson, A.; Lember, M.; Oleszczyk, M.; Pavlick, D.R.

2015-01-01

This chapter analyses differences between countries and explains why countries differ regarding the structure and process of primary care. The components of primary care strength that are used in the analyses are health policy-making, workforce development and in the care process itself (see Fig.